DRAFT—DO NOT CITE OR QUOTE EPA/635/R-10/001 

 www.epa.gov/iris 

TOXICOLOGICAL REVIEW 

OF 

INORGANIC ARSENIC

(CAS No. 7440-38-2) 

In Support of Summary Information on the 

Integrated Risk Information System (IRIS)

February 2010 

NOTICE 

This document is a final draft. This information is distributed solely for the purpose of 

pre-dissemination peer review under applicable information quality guidelines. It has not 

been formally disseminated by EPA. It does not represent and should not be construed to 

represent any Agency determination or policy. It is being circulated for review of its 

technical accuracy and science policy implications. 

. 

U.S. Environmental Protection Agency 

Washington, DC 
DISCLAIMER 

This document is a final draft for review purposes only. This information is distributed 

solely for the purpose of pre-dissemination peer review under applicable information quality 

guidelines. It has not been formally disseminated by EPA. It does not represent and should not 

be construed to represent any Agency determination or policy. Mention of trade names or 

commercial products does not constitute endorsement or recommendation for use. 

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TABLE OF CONTENTS—TOXICOLOGICAL REVIEW of INORGANIC ARSENIC 

(CAS No. 7440-38-2) 

LIST OF TABLES ......................................................................................................................VI

LIST OF FIGURES .................................................................................................................. VII

LIST OF ABBREVIATIONS .................................................................................................VIII

FOREWORD............................................................................................................................XIII

AUTHORS, CONTRIBUTORS, AND REVIEWERS ......................................................... XIV

1. INTRODUCTION..................................................................................................................... 1

2. CHEMICAL AND PHYSICAL INFORMATION RELEVANT TO ASSESSMENTS 3

2.1. PROPERTIES.............................................................................................................. 3 

2.2. USES............................................................................................................................ 3 

2.3. OCCURRENCE........................................................................................................... 4 

2.4. ENVIRONMENTAL FATE........................................................................................ 5 

3. TOXICOKINETICS................................................................................................................. 6

3.1. ABSORPTION ............................................................................................................ 7 

3.2. DISTRIBUTION.......................................................................................................... 9 

3.2.1. Transport in Blood............................................................................................. 9 

3.2.2. Tissue Distribution .......................................................................................... 10 

3.2.3. Cellular Uptake, Distribution, and Transport.................................................. 14 

3.3. METABOLISM ......................................................................................................... 15 

3.3.1. Reduction......................................................................................................... 19 

3.3.2. Arsenic Methylation........................................................................................ 20 

3.3.3. Species Differences in the Methylation of Arsenic......................................... 23 

3.3.4. Thioarsenical Metabolites ............................................................................... 24 

3.4. ELIMINATION ......................................................................................................... 26 

3.5. PHYSIOLOGICALLY BASED TOXICOKINETIC MODELS............................... 27 

4. HAZARD IDENTIFICATION .............................................................................................. 31

4.1. STUDIES IN HUMANS............................................................................................ 31 

4.1.1. Taiwan ............................................................................................................. 32 

4.1.2. Japan................................................................................................................ 46 

4.1.3. South America................................................................................................. 47 

4.1.4. North America (United States and Mexico).................................................... 52 

4.1.5. China................................................................................................................ 58 

4.1.6. Finland............................................................................................................. 59 

4.1.7. Denmark .......................................................................................................... 61 

4.1.8. Australia .......................................................................................................... 61 

4.2. PRECHRONIC AND CHRONIC STUDIES AND CANCER BIOASSAYS IN 

ANIMALS—ORAL.................................................................................................. 62 

4.2.1. Prechronic and Chronic Studies ...................................................................... 62 

4.2.2. Cancer Bioassays............................................................................................. 62 

4.2.2.1. Mice—Transplacental ...................................................................... 62 

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4.2.2.2. Rat—Oral.......................................................................................... 65 

4.2.2.3. Other ................................................................................................. 66 

4.3. REPRODUCTIVE/DEVELOPMENTAL STUDIES—ORAL................................. 67 

4.4. OTHER STUDIES..................................................................................................... 67 

4.4.1. Possible Modes of Action and Key Events of Possible Importance ............... 67 

4.4.1.1. In Vivo Human Studies .................................................................... 71 

4.4.1.2. In Vivo Experiments Using Laboratory Animals............................. 75 

4.4.1.3. In Vitro Experiments ........................................................................ 81 

4.5. SYNTHESIS AND EVALUATION OF MAJOR NONCANCER EFFECTS ......... 93 

4.6. WEIGHT-OF-EVIDENCE EVALUATION AND CANCER 

CHARACTERIZATION........................................................................................... 94 

4.6.1. Summary of Overall Weight-of-Evidence....................................................... 94 

4.6.2. Synthesis of Human, Animal, and Other Supporting Evidence ...................... 94 

4.6.2.1. Skin Cancer....................................................................................... 96 

4.6.2.2. Lung Cancer...................................................................................... 96 

4.6.2.3. Kidney, Bladder, and Liver Cancer .................................................. 97 

4.6.2.4. In Utero Exposure............................................................................. 98 

4.6.3. Mode of Action Information ........................................................................... 98 

4.6.3.1. General Comments on MOAs .......................................................... 98 

4.6.3.2. Low-Dose Extrapolation................................................................. 102 

4.7. SUSCEPTIBLE POPULATIONS AND LIFE STAGES ........................................ 102 

4.7.1. Possible Childhood Susceptibility................................................................. 102 

4.7.2. Possible Gender Differences ......................................................................... 105 

4.7.3. Other.............................................................................................................. 106 

4.7.3.1. Genetic Polymorphism ................................................................... 106 

4.7.3.2. Nutritional Status............................................................................ 109 

4.7.3.3. Cigarette Smokers........................................................................... 111 

5. DOSE-RESPONSE ASSESSMENTS.................................................................................. 112

5.1. ORAL REFERENCE DOSE (RfD)......................................................................... 112 

5.2. INHALATION REFERENCE CONCENTRATION (RfC).................................... 112 

5.3. CANCER ASSESSMENT (ORAL EXPOSURE)................................................... 112 

5.3.1. Background: History of Cancer Risk Assessments for Arsenic.................... 112 

5.3.2. Choice of Study/Data, Estimation Approach, and Input Assumptions ......... 119 

5.3.3. Dose-Response Model Selection for Cancer Mortality in Taiwan................ 120 

5.3.4. Selection of Cancer Endpoints and Estimation of Risks for U.S. Populations

................................................................................................................................. 121 

5.3.5. Nonwater Arsenic Intake and Drinking Water Consumption ....................... 123 

5.3.6. Dose-Response Data...................................................................................... 125 

5.3.7. Risk Assessment Methodology ..................................................................... 126 

5.3.7.1. Dose-Response Estimation Based on Taiwan Cancer Mortality Data

......................................................................................................... 127 

5.3.7.2. Estimation of Confidence Limits on Cancer Slope Parameters...... 128 

5.3.7.3. Estimation of LED01 Values Using Relative Risk Models............... 129 

5.3.7.4. Estimation of Unit Risks................................................................. 129 

5.3.8. Results ........................................................................................................... 130 

5.3.8.1. Ingestion Pathway Oral CSFs and Unit Risks ................................ 130 

5.3.8.2. Comparison to Previous Cancer Risk Estimates ............................ 132 

5.3.8.3. ED01 and LED01 Estimates From Chen et al. (1988a, 1992), Ferreccio 

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et al. (2000), and Chiou et al. (2001)............................................... 133 

5.3.8.4. Estimated Risk Associated With 10 μg/L Drinking Water Arsenic 

From NRC (2001) and U.S. EPA (2005c)....................................... 135 

5.3.8.5. Sensitivity Analyses of Cancer Risk Estimates to Changes in 

Parameter Values............................................................................. 137 

5.3.8.6. Sensitivity Analyses of Cancer Risk Estimates to Dose-Response 

Model Form ..................................................................................... 142 

5.3.8.7. Significance of Cancer Risks at Low Arsenic Exposures .............. 143 

5.4. CANCER ASSESSMENT (INHALATION EXPOSURE)..................................... 145 

6. MAJOR CONCLUSIONS IN THE CHARACTERIZATION OF HAZARD AND DOSERESPONSE ............................................................................................................................... 146

6.1. HUMAN HAZARD POTENTIAL.......................................................................... 146 

6.2. DOSE-RESPONSE.................................................................................................. 148 

6.2.1. Choice of Models .......................................................................................... 150 

6.2.2. Dose Metric ................................................................................................... 151 

6.2.3. Human Population Variability....................................................................... 151 

7. REFERENCES...................................................................................................................... 153

APPENDIX A. SUMMARY OF EXTERNAL PEER REVIEW AND PUBLIC 

COMMENTS AND DISPOSITION........................................................................................ A-1

APPENDIX B. TABULAR DATA ON CANCER EPIDEMIOLOGY STUDIES.............. B-1

APPENDIX C. TABLES FOR STUDIES ON POSSIBLE MODE OF ACTION FOR 

INORGANIC ARSENIC.......................................................................................................... C-1

APPENDIX D. IMMUNOTOXICITY.................................................................................... D-1

APPENDIX E. QUANTITATIVE ISSUES IN THE CANCER RISK ASSESSMENT FOR 

INORGANIC ARSENIC.......................................................................................................... E-1

APPENDIX F. RISK ASSESSMENT FOR TOWNSHIPS AND LOW-EXPOSURE 

TAIWANESE POPULATIONS ...............................................................................................F-1

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LIST OF TABLES 

Table 2-1. Chemical and Physical Properties of Arsenic and Selected Inorganic Arsenic 

Compounds (ATSDR, 2000; Merck Index, 1989)....................................................... 4 

Table 4-1. Summary of Number of Rows Derived From Peer-Reviewed Publications for 

Different Hypothesized Key Eventsa

......................................................................... 71 

Table 5-1. Historical Summary of Arsenic Risk Assessment Efforts........................................ 114 

Table 5-2. Cancer Mortality Data Used in the Arsenic Risk Assessment ................................. 126 

Table 5-3. Cancer Incidence Risk Estimates for Lung and Bladder Cancers in Males and 

Femalesa

................................................................................................................... 131 

Table 5-4. Combined Lung and Bladder Cancer Incidence Risk Estimate for the U.S. Population 

(Males and Females)................................................................................................ 132 

Table 5-5. Comparison of ED01 and LED01

a

 Estimates From Past Studiesb With Those From the 

Current Analysis ...................................................................................................... 134 

Table 5-6. Comparison of cancer risk assessment results with estimates from NRC (2001) and 

U.S. EPA (2005c) .................................................................................................... 135 

Table 5-7. Drinking water intake and body weight assumptions in females in recent arsenic risk 

assessments.............................................................................................................. 136 

Table 5-8. Theoretical maximum likelihood estimates of excess lifetime risk (incidence per 

10,000 people) of lung cancer and bladder cancer for US populations................... 137 

Table 5-9. Arsenic oral CSFs (per mg/kg-d) for lung cancer and bladder cancer in US 

populations............................................................................................................... 137 

Table 5-10. Sensitivity analysis of estimated cancer incidence risks associated with 10 μg/L to 

changes in modeling assumptions and inputs.......................................................... 139 

Table 5-11. Proportional Changes in Cancer Risks at 10 μg/L Associated With Changes in 

Modeling Inputs and Assumptions .......................................................................... 140 

Table B-1. Taiwan Cancer Studies ............................................................................................ B-4 

Table B-2. Japan Cancer Studies ............................................................................................. B-22 

Table B-3. South America Cancer Studies .............................................................................. B-23 

Table B-4. North America cancer studies................................................................................ B-30 

Table B-5. China cancer studies .............................................................................................. B-38 

Table B-6. Finland cancer studies............................................................................................ B-39 

Table B-7. Denmark cancer studies......................................................................................... B-41

Table B-8. Australia Cancer Studies........................................................................................ B-42 

Table C-1. In vivo human studies related to possible modes of action of arsenic in the 

development of cancer........................................................................................... C-19 

Table C-2. In vivo experiments on laboratory animals related to possible modes of action of 

arsenic in the development of cancer—only oral exposures ................................. C-30 

Table C-3. In vitro studies related to possible MOA of arsenic in the development of cancerC-57 

Table D-1. Lymphocyte counts and labeling, mitotic, and replication indexes (mean ± se) in the 

peripheral blood lymphocytes in populations exposed to low (control) and high 

(exposed) levels of arsenic (Gonsebatt et al., 1994)................................................ D-2 

Table F-1. Coefficients from linear regressions of age-adjusted cancer risk versus arsenic doses 

for townships identified by Lamm et al. (2006) .......................................................F-5 

Table F-2. Arsenic dose coefficients for study populations with median well water arsenic 

concentrations less than 127 ppb..............................................................................F-6 

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LIST OF FIGURES 

Figure 3-1. Traditional metabolic pathway for inorganic arsenic in humans.............................. 16 

Figure 3-2. Alternative metabolic pathway for inorganic arsenic in humans proposed by 

Hayakawa et al. (2005).............................................................................................. 17 

Figure 3-3. Thioarsenical structures. ........................................................................................... 25 

Figure 4-1. Level of significant exposure of adult mice to sodium arsenite in drinking water in 

ppm As....................................................................................................................... 76 

Figure 5-1. Estimated oral CSFs for individual and combined cancer endpoints. .................... 132 

Figure 5-2. Change in arsenic-related unit risk estimates associated with variations in input 

assumptions.............................................................................................................. 140 

Figure F-1. Lifetime crude total cancer risk (male + female) for the low- and high-exposure 

villages......................................................................................................................F-4 

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LIST OF ABBREVIATIONS 

∼ approximately (if before a listing of concentrations, 

it applies to all) 

293 cells a cell line derived from adenovirus-transformed 

human embryonic kidney epithelial cells 

2-AAAF 2-acetoxyacetylaminofluorene 

8-OHdG 8-hydroxydeoxyguanosine 

AG06 cells SV40-transformed human keratinocytes 

AGT average generation time 

AIC Akaike information criterion 

AMI acute myocardial infraction 

AP activator protein or activating protein 

APE apurinic/apyrimidinic endonuclease 

As arsenic 

AsIII arsenite 

AsV arsenate 

AS3MT arsenic(+3 oxidation state) methyltransferase 

AQP aquaglycoporins 

ATG arsenic triglutathione 

ATO arsenic trioxide 

ATSDR Agency for Toxic Substances and Disease Registry 

B[a]P benzo[a]pyrene 

BBDR biologically based quantitative dose-response 

BCC basal cell carcinoma 

BER base excision repair 

BFD blackfoot disease 

BMI body mass index 

BPDE benzo[a]pyrene diol epoxide, an active metabolite 

of B[a]P 

BrdU bromodeoxyuridine 

BSO L-buthionine-S,R-sulphoximine (depletes GSH, γGCS inhibitor) 

BW or bw body weight 

CA chromosome aberrations 

Caco-2 a human intestinal cell line 

CAE cumulative arsenic exposure 

CASRN Chemical Abstracts Service Registry Number 

CAT catalase (decomposes H2O2) 

CCA chromate copper arsenate 

CCRIS Chemical Carcinogenesis Research Information 

System 

cDNA complementary DNA 

cen+ centromere positive 

cen- centromere negative 

Chang cells a human cell line thought to be derived from HeLa 

cells 

CHO Chinese hamster ovary 

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CI confidence interval 

c-Jun or c-jun an AP-1 protein 

CL3 cells human lung adenocarcinoma cells (established from 

a non-small-cell lung carcinoma) 

COPD chronic obstructive pulmonary disease 

CSF cancer CSF 

DEB diepoxybutane (DNA crosslinking agent) 

DES diethylstilbestrol 

dhfr gene dihydrofolate reductase gene 

DHLP dihydrolipoic acid 

DI-I or II or III iodothyronine deiodinase-I or II or III (are 3 forms of 

this selenoenzyme) 

dL deciliter 

DMA dimethyl arsenic (used when the oxidative state is 

unknown or not specified) 

DMAIII dimethylarsenous acid 

DMAV dimethylarsinic acid 

DMAG dimethylarsinic glutathione 

DMMTAIII dimethylmonothioarsinic acid 

DMMTAV dimethylmonothioarsonic acid 

DMPS 2,3-dimercaptopropane-1-sulfonic acid 

DMSA dimercaptosuccinic acid or meso 2,3-

dimercaptosuccinic acid 

DNA deoxyribonucleic acid 

DNMT DNA methyltransferase 

DTT dithiothreitol 

DW drinking water 

E. coli Escherichia coli 

ED effective dose 

EGFR-ECD extracellular domain of the epidermal growth factor 

receptor 

EPA Environmental Protection Agency 

ER-α estrogen receptor-alpha 

ERCC1 excision repair cross-complement 1 component 

ERCC2 excision repair cross-complementing rodent repair 

deficiency, complementation group 2 (also known 

as xeroderma pigmentosum group D or XPD) 

ERK extracellular signal-regulated kinase 

FAK focal adhesion kinase 

FPG formamidopyrimidine-DNA glycosylase (digestion 

of DNA) 

G6PDH glucose-6-phosphate dehydrogenase 

GAPDH glyceraldehyde-3-phosphate dehydrogenase 

GI gastrointestinal 

GLM generalized linear model 

GM04312C cells a SV-40 transformed XPA human fibroblast NERdeficient cell line 

GM-CSF granulocyte-macrophage colony-stimulating factor 

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GPx glutathione peroxidase 

GSH glutathione 

GST glutathione-S-transferase 

GSTO1 glutathione-S-transferase omega 1 

GSTP1-1 glutathione-S-transferase P1-1 

H69AR a multi-drug resistant human cancer cell line 

H9c2 cells immortalized myoblast cell line derived from fetal 

rat hearts 

HAC highest arsenic concentration 

HCC hepatocellular carcinoma 

HEALS Health Effects of Arsenic Longitudinal Study 

HELF cells human embryo lung fibroblast cell line 

HepG2 cells human hepatocellular liver carcinoma cell line 

(Caucasian) 

HGPRT hypoxanthine-guanine phosphoribosyltransferase 

hGST-O1 human glutathione-S-transferase omega 1 

HMOX-1 heme oxygenase 1 

hOGG1 human 8-oxoguanine DNA glycosylase 

HPBM human peripheral blood monocytes 

HSDB Hazardous Substances Data Bank 

HXT hexose permease transporters 

IC50 concentration that is needed to cause 50% inhibition 

IFN-γ interferon-gamma 

IL interleukin 

ILK integrin-linked kinase 

IRIS Integrated Risk Information System 

IRR incidence rate ratio 

iv intravenous 

JAK Janus kinase 

LED lowest effective dose 

LI labeling index 

LOEC lowest observed effect concentration 

LOEL lowest observed effect level 

MADG monomethylarsonic diglutathione 

MAP mitogen-activated protein 

MCF-7 cells human breast carcinoma cell line 

M-CSF macrophage colony-stimulating factor 

MDA malondialdehyde 

mdm2 murine double minute 2 proto-oncogene 

MEK MAP/ERK kinase 

MI mitotic index 

MLE maximum likelihood 

MMA monomethyl arsenic (used when oxidative state is 

unknown or not specified) 

MMAIII monomethylarsonous acid 

MMAV monomethyl arsonic acid 

MMS methyl methanesulfonate 

MN micronuclei 

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MNU N-methyl-N-nitrosourea 

MOA mode of action 

MPR2/cMOAT multi-drug resistance associated protein 2 

transporter 

mRNA messenger ribonucleic acid 

MRP multidrug resistance protein 

MTHFR methylene trihydrofolate reductase 

NAC n-acetyl-cysteine 

NAD nicotinamide adenine dinucleotide 

NADPH nicotinamide adenine dinucleotide phosphateoxidase 

NCHS National Center for Health Statistics 

NCI National Cancer Institute 

NER nucleotide excision repair 

NHEK cells primary normal human epidermal keratinocytes 

NK natural killer 

NO nitric oxide 

NRC National Research Council 

OATP-C organic anion transporting polypeptide-C 

ODC ornithine decarboxylase 

OGG1 8-oxoguanine DNA glycosylase 

OPP Office of Pesticide Programs 

OR odds ratio 

PARP poly(adenosine diphosphate–ribose) polymerase 

PBPK model physiologically based pharmacokinetic model 

PBMC peripheral blood mononuclear cells 

PCNA proliferating cell nuclear antigen 

PCR polymerase chain reaction 

PGK phosphoglyerate kinase 

PHA phytohemagglutinin 

PMI primary methylation indices 

PNP purine nucleoside phosphorylase 

POD point of departure 

ppb parts per billion 

ppm parts per million 

PTEN phosphatase and tensin homolog 

PYR person-years at risk 

R15 arsenic-resistent cells 

RAGE receptor for advanced glycation end products 

RBCs red blood cells 

RED Reregistration Eligibility Decision 

RfC inhalation reference concentration 

RfD oral reference dose 

RI replication index 

RNS reactive nitrogen species 

ROS reactive oxygen species 

RR relative risk 

RT real time 

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SAB Science Advisory Board 

SAM S-adenosylmethionine 

SBET simplified bioaccessibility extraction test 

SCC squamous cell carcinoma 

SCE sister chromatid exchange 

SCGE single cell gel electrophoresis 

Se selenium 

SEER surveillance epidemiology and end result 

SHE cells Syrian hamster ovary cells 

SIR standardized incidence ratio 

SMI secondary methylation indices 

SMR standard mortality ratio 

SOD superoxide radical dismutase 

STAT signal transducer and activator of transcription 

SV-HUC-1 cells SV40 large T-transformed human urothelial cell line 

T3 thyroid hormone triiodothyronine 

T4 thyroid hormone thyroxine 

TAT tyrosine aminotransferase 

TCEP tris(2-carboxylethyl)phospine 

Tg.AC a strain of transgenic mice that contains the fetal 

beta-globin promoter fused to the v-Ha-ras 

structural gene (with mutations at codons 12 and 59) 

and linked to a simian virus 40 

polyadenylation/splice sequence 

TGF-α transforming growth factor alpha 

TMAIII trimethyl arsine 

TMAV trimethylarsinic acid 

TMAO trimethylarsine oxide 

TNF-α tumor necrosis factor alpha 

TPA 12-O-tetradecanoyl phorbol-13-acetate 

Trx thioredoxin 

TrxR thioredoxin reductase 

TWA time-weighted average 

UCL upper confidence limits 

UROtsa a SV40-immortalized human urothelium cell line 

UV ultraviolet radiation 

V79 cells a cell line derived from lung fibroblasts of a male 

Chinese hamster 

VEGF vascular endothelial cell growth factor 

XRCC1 X-ray repair cross-complimentary group 1 

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FOREWORD 

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The purpose of this Toxicological Review is to provide scientific support and rationale 

for the hazard and dose-response assessment in IRIS pertaining to chronic exposure to inorganic 

arsenic. It is not intended to be a comprehensive treatise on the chemical or toxicological nature 

of inorganic arsenic. 

The intent of Section 6, “Major Conclusions in the Characterization of Hazard and Dose 

Response,” is to present the major conclusions reached in the derivation of the reference dose, 

reference concentration, and cancer assessment, where applicable, and to characterize the overall 

confidence in the quantitative and qualitative aspects of hazard and dose-response by addressing 

the quality of data and related uncertainties. The discussion is intended to convey the limitations 

of the assessment and to aid and guide the risk assessor in the ensuing steps of the risk 

assessment process. 

For other general information about this assessment or other questions relating to IRIS, 

the reader is referred to EPA’s IRIS Hotline at (202) 566-1676 (phone), (202) 566-1749 (fax), or 

hotline.iris@epa.gov (email address). 

xiii DRAFT—DO NOT CITE OR QUOTE 
AUTHORS, CONTRIBUTORS, AND REVIEWERS 

CHEMICAL MANAGER/AUTHOR 

Santhini Ramasamy, Ph.D., MPH, DABT 

Office of Science and Technology 

Office of Water 

U.S. Environmental Protection Agency 

Washington, DC 

OFFICE OF RESEARCH AND DEVELOPMENT CO-LEAD/AUTHOR 

Reeder Sams, Ph.D. 

National Center for Environmental Assessment 

Office of Research and Development 

U.S. Environmental Protection Agency 

Research Triangle Park, NC 

AUTHORS 

Robyn B. Blain, Ph.D. 

Gregory M. Blumenthal, Ph.D. 

William M. Mendez, Ph.D. 

Welford C. Roberts, Ph.D. 

ICF International 

Fairfax, VA 

Paul B Selby, Ph.D., DABT 

RiskMuTox 

Oak Ridge, TN 

Arthur W. Stange, Ph.D. 

Oak Ridge Associated Universities 

Arvada, CO 80005 

Susan M. Wells, M.P.H. 

Oak Ridge Associated Universities 

Oak Ridge, TN 37831-0117 

CONTRIBUTORS 

Elizabeth Doyle, Ph.D. 

Office of Science and Technology 

Office of Water 

U.S. Environmental Protection Agency 

Washington, DC 

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Jonathan Chen, Ph.D. 

Office of Pesticide Programs 

U.S. Environmental Protection Agency 

Washington, DC 

Andrew Schulman, Ph.D. 

Office of Enforcement and Compliance Assurance 

U.S. Environmental Protection Agency 

Washington, DC 

Chao Chen, Ph.D. 

National Center for Environmental Assessment 

Office of Research and Development 

U.S. Environmental Protection Agency 

Washington, DC 

Paul White, M.S. 

National Center for Environmental Assessment 

Office of Research and Development 

U.S. Environmental Protection Agency 

Washington, DC 

Irene Dooley 

Office of Water 

U.S. Environmental Protection Agency 

Washington, DC 

Brenda Foos, Ph.D. 

Office of Children’s Health Protection 

U.S. Environmental Protection Agency 

Washington, DC 

Molly Rosett 

National Center for Environmental Assessment 

Office of Research and Development 

U.S. Environmental Protection Agency 

Research Triangle Park, NC 

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REVIEWERS 

This document has been reviewed by EPA scientists, interagency reviewers from other 

federal agencies, and the public, and peer reviewed by independent scientists external to EPA. A 

summary and EPA’s disposition of the comments received from the independent external peer 

reviewers and from the public is included in Appendix A. 

INTERNAL EPA REVIEWERS

Ila Cote, Ph.D. 

National Center for Environmental Assessment 

Office of Research and Development 

U.S. Environmental Protection Agency 

Joyce Morrissey Donohue, Ph.D. 

Office of Science and Technology 

Office of Water 

U.S. Environmental Protection Agency 

Hisham El-Masri, Ph.D. 

National Health and Environmental Effects Research Laboratory 

Office of Research and Development 

U.S. Environmental Protection Agency 

Nicole Hagan 

ORISE, National Center for Environmental Assessment 

Office of Research and Development 

U.S. Environmental Protection Agency 

Elaina Kenyon, Ph.D. 

National Health and Environmental Effects Research Laboratory 

Office of Research and Development 

U.S. Environmental Protection Agency 

Kirk Kitchin, Ph.D. 

National Health and Environmental Effects Research Laboratory 

Office of Research and Development 

U.S. Environmental Protection Agency 

Andrew Kligerman, Ph.D. 

National Health and Environmental Effects Research Laboratory 

Office of Research and Development 

U.S. Environmental Protection Agency 

Danelle Lobdell, Ph.D. 

National Health and Environmental Effects Research Laboratory 

Office of Research and Development 

U.S. Environmental Protection Agency 

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Bob Hetes 

National Health and Environmental Effects Research Laboratory 

Office of Research and Development 

U.S. Environmental Protection Agency 

Stephen Nesnow, Ph.D. 

National Health and Environmental Effects Research Laboratory 

Office of Research and Development 

U.S. Environmental Protection Agency 

Julian Preston, Ph.D. 

National Health and Environmental Effects Research Laboratory 

Office of Research and Development 

U.S. Environmental Protection Agency 

David Thomas, Ph.D. 

National Health and Environmental Effects Research Laboratory 

Office of Research and Development 

U.S. Environmental Protection Agency 

John Vandenberg, Ph.D. 

National Center for Environmental Assessment 

Office of Research and Development 

U.S. Environmental Protection Agency 

Tim Wade, Ph.D. 

National Health and Environmental Effects Research Laboratory 

Office of Research and Development 

U.S. Environmental Protection Agency 

Debra Walsh 

National Center for Environmental Assessment 

Office of Research and Development 

U.S. Environmental Protection Agency 

Doug Wolf, D.V.M., Ph.D. 

National Health and Environmental Effects Research Laboratory 

Office of Research and Development 

U.S. Environmental Protection Agency 

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EXTERNAL PEER REVIEWERS

Science Advisory Board Arsenic Review Panel 

CHAIR 

Genevieve Matanoski, M.D., Ph.D. 

Johns Hopkins University 

MEMBERS 

H. Vasken Aposhian, Ph.D. 

The University of Arizona 

Aaron Barchowsky, Ph.D. 

University of Pittsburgh 

David Brusick, Ph.D. 

Retired, Convance Labs 

Kenneth P. Cantor, Ph.D. 

National Cancer Institute 

John (Jack) Colford, Ph.D. 

University of California 

Yvonne P. Dragan, Ph.D. 

National Center for Toxicological Research, 

Food and Drug Administration 

Sidney Green, Ph.D. 

Howard University 

Sioban Harlow, Ph.D. 

University of Michigan 

Steven Heeringa, Ph.D. 

University of Michigan 

Claudia Maria Hopenhayn, Ph.D. 

University of Kentucky 

James E. Klaunig, Ph.D. 

Indiana University 

X. Chris Le, Ph.D. 

University of Alberta 

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Michele Medinsky, Ph.D. 

Toxcon 

Kenneth Portier, Ph.D. 

American Cancer Society 

Atlanta, GA 

Barry Rosen, Ph.D. 

Wayne State University 

Toby Rossman, Ph.D. 

New York University 

Miroslav Styblo, Ph.D. 

University of North Carolina 

Justin Teeguarden, Ph.D. 

Pacific Northwest National Laboratory 

Michael Waalkes, Ph.D. 

National Institute of Environmental Health Science 

Janice Yager, Ph.D. 

Electric Power Research Institute 

xix DRAFT—DO NOT CITE OR QUOTE 
1. INTRODUCTION 

This document presents background information and justification for the Integrated Risk 

Information System (IRIS) Summary of the hazard and dose-response assessment of inorganic 

arsenic. The IRIS Summary may include oral reference dose (RfD) and inhalation reference 

concentration (RfC) values for chronic and other exposure durations, as well as a carcinogenicity 

assessment. 

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This document is based on EPA reviews of the reports Arsenic in Drinking Water and 

Arsenic in Drinking Water, 2001 Update published by the National Research Council (NRC) in 

1999 and 2001, respectively. In writing those reports, the NRC arsenic committee considered 

presentations at the committee’s public meetings, comments from the public, and the comments 

made by technical experts on the draft NRC arsenic reports. The conclusions, recommendations, 

and final content of the NRC (1999, 2001) reports rest entirely with the committee and the NRC. 

 This IRIS document—based on reviews of those reports—has undergone evaluation by EPA 

health scientists from several program offices and regional offices, interagency review, and 

external peer review by the Science Advisory Board (SAB). 

Compared to the draft Toxicological Review submitted to the SAB in 2005, this 

assessment is expanded: it provides a detailed review of epidemiological studies and the mode of 

action (MOA) studies, as well as revisions to the dose-response analysis to address the 

recommendations of the SAB (SAB, 2007). Specifically, it includes additional sensitivity 

analyses on the effects of modeling assumptions on estimated cancer risk. 

The RfD and RfC, if derived, provide quantitative information for use in risk assessments 

for health effects known or assumed to be produced through a non-linear (presumed threshold) 

MOA. The RfD (expressed in units of mg/kg-day) is defined as an estimate (with uncertainty 

spanning perhaps an order of magnitude) of a daily exposure to the human population (including 

sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a 

lifetime. The inhalation RfC (expressed in units of mg/m3

) is analogous to the oral RfD, but 

provides a continuous inhalation exposure estimate. The inhalation RfC considers both toxic 

effects on the respiratory system (portal of entry) and toxic effects peripheral to the respiratory 

system (extrarespiratory or systemic effects). Reference values are generally derived for chronic 

exposures (up to a lifetime), but may also be derived for acute (≤ 24 hours), short-term (>24 

hours to 30 days), and subchronic (>30 days to 10% of lifetime) exposure durations, all of which 

are derived based on an assumption of continuous exposure throughout the duration specified. 

Unless specified otherwise, the RfD and RfC are derived for chronic exposure duration. 

The carcinogenicity assessment provides information on the carcinogenic hazard 

potential of the substance in question and quantitative estimates of risk from oral and inhalation 

exposures may be derived. The information includes a weight-of-evidence judgment of the 

likelihood that the agent is a human carcinogen and the conditions under which the carcinogenic 

1
effects may be expressed. Quantitative risk estimates may be derived from the application of a 

low-dose extrapolation procedure. If derived, the oral cancer CSF (CSF) is a plausible upper 

bound on the estimate of risk per mg/kg-day of oral exposure. Similarly, an inhalation unit risk 

is a plausible upper bound on the estimate of risk per μg/m3

 air breathed. 

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Development of these hazard identification and dose-response assessments for inorganic 

arsenic has followed the general guidelines for risk assessment set forth by the National 

Research Council (NRC, 1983). EPA Guidelines and Risk Assessment Forum Technical Panel 

Reports that may have been used in the development of this assessment include the following: 

Guidelines for the Health Risk Assessment of Chemical Mixtures (U.S. EPA, 1986a), Guidelines 

for Mutagenicity Risk Assessment (U.S. EPA, 1986b), Recommendations for and Documentation 

of Biological Values for Use in Risk Assessment (U.S. EPA, 1988a), Guidelines for 

Developmental Toxicity Risk Assessment (U.S. EPA, 1991), Use of the Benchmark Dose 

Approach in Health Risk Assessment (U.S. EPA, 1995), Guidelines for Reproductive Toxicity 

Risk Assessment (U.S. EPA, 1996), Guidelines for Neurotoxicity Risk Assessment (U.S. EPA, 

1998), Science Policy Council Handbook: Peer Review (U.S. EPA, 2000a), Science Policy 

Council Handbook: Risk Characterization (U.S. EPA, 2000b), Benchmark Dose Technical 

Guidance Document (U.S. EPA, 2000c), Supplementary Guidance for Conducting Health Risk 

Assessment of Chemical Mixtures (U.S. EPA, 2000d), A Review of the Reference Dose and 

Reference Concentration Processes (U.S. EPA, 2002), Guidelines for Carcinogen Risk 

Assessment (U.S. EPA, 2005a), Supplemental Guidance for Assessing Susceptibility from EarlyLife Exposure to Carcinogens (U.S. EPA, 2005b), Science Policy Council Handbook: Peer 

Review (U.S. EPA, 2006a), and A Framework for Assessing Health Risks of Environmental 

Exposures to Children (U.S. EPA, 2006b). 

The literature search strategy employed for this compound was based on the Chemical 

Abstracts Service Registry Number (CASRN) and at least one common name. Any pertinent 

scientific information submitted by the public to the IRIS Submission Desk was also considered 

in the development of this document. The relevant literature was reviewed through December, 

2007; however, a few references from 2008 have also been included. 

2
2. CHEMICAL AND PHYSICAL INFORMATION RELEVANT TO ASSESSMENTS 

2.1. PROPERTIES 

Arsenic (As) is a metalloid that can exist in the -3, 0, +3, and +5 oxidation states.1 The 

arsenite (AsIII; +3) and arsenate (AsV ; +5) forms are the primary forms found in drinking water. 

The chemical and physical properties of arsenic are listed in Table 2-1. 

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2.2. USES 

The metalloid, arsenic, is used for hardening copper and lead alloys (HSDB, 2005). It 

also is used in glass manufacturing as a decolorizing and refining agent, as a component of 

electrical devices, in the semiconductor industry, and as a catalyst in the production of ethylene 

oxide. Arsenic compounds are used as a mordant in the textile industry, for preserving hides, as 

medicinals, pesticides, pigments, and wood preservatives. Production of chromate copper 

arsenate (CCA), a wood preservative whose production is currently being phased out, accounts 

for about 90% of the domestic consumption of arsenic (ATSDR, 2007). 

1

 Oxidation states for arsenic have been abbreviated differently by different organizations or authors. For example, 

arsenite can be abbreviated as either “As(III)” or “AsIII”; both refer to trivalent inorganic arsenic compounds. This 

document uses the superscript abbreviation. 

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Table 2-1. Chemical and Physical Properties of Arsenic and Selected Inorganic Arsenic 

Compounds (ATSDR, 2000; Merck Index, 1989) 

Arsenic As2O3 As2O5 NaAsO2 Na2HAsO4

CAS No. 7440-38-2 1327-53-3 1303-28-2 7784-46-5 7778-43-0 

Oxidation State 0 +3 +5 +3 +5 

Molecular Weight 74.9 197.8 229.8 129.9 185.9 

Synonyms metallic arsenic, 

gray arsenic 

arsenic trioxide, 

arsenolite, 

white arsenic 

(+3) 

arsenic 

pentoxide, 

arsenic acid 

anhydride (+5) 

sodium arsenite 

(+3) 

disodium 

arsenate (+5) 

Physical State 

(25°C) 

solid solid solid solid solid 

Boiling Point (°C) 613 (sublimes) 465 — — — 

Melting Point (°C) 817 @ 28 atm 312 315 

(decompose) 

— 86.3 

Density (g/cm3

) 5.7 3.7 4.3 1.8 1.8 

Vapor Pressure 

(20°C) 

— — — — — 

Taste Threshold — — — — — 

Odor Threshold — — — — — 

Conversion Factor — — — — — 

— No data available 

2.3. OCCURRENCE 

Arsenic naturally makes up about 3.4 parts per million (ppm) of the Earth’s crust, where 

it is the twentieth most abundant element (ATSDR, 2007; Merck Index, 1989). Arsenic leaches 

from natural weathering of soil and rock into water, and low concentrations of arsenic are found 

in water, food, soil, and air. However, industrial activities such as coal combustion and smelting 

operations release higher concentrations of arsenic to the environment (Adams et al., 1994). The 

highest background arsenic levels found in the environment are in soils, with concentrations 

ranging from 1 to 40 ppm (ATSDR, 2007). Food typically contains arsenic concentrations of 20 

to 140 parts per billion (ppb) (ATSDR, 2007). The majority of surface and ground waters 

contain less than 10 ppb (although levels of 1,000–3,400 ppb have been reported, especially in 

areas of the western United States). Average arsenic content in drinking water in the United 

States is 2 ppb; 12% of water supplies from surface water in the central United States and 12% 

of ground water sources in the western United States exceed 20 ppb (ATSDR, 2007). Mean 

arsenic concentrations in ambient air have generally been found to range from 1 to 2,000 ng/m3

(ATSDR, 2007). 

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2.4. ENVIRONMENTAL FATE 

Arsenic as a free element (0 oxidation state) is rarely encountered in the environment 

(HSDB, 2005). Under normal conditions in water, arsenic is present as soluble inorganic AsV

because it is more thermodynamically stable in water than AsIII. In soil there are many biotic 

and abiotic processes controlling arsenic’s overall fate and environmental impact. Arsenic in 

soil exists in various oxidation states and chemical species, depending upon soil pH and 

oxidation-reduction potential (ATSDR, 2007). Arsenic is largely immobile in agricultural soils, 

and tends to remain in upper soil layers (ATSDR, 2007). However, reducing conditions form 

soluble mobile forms of arsenic and leaching is greater in sandy soil than in clay loam (ATSDR, 

2007). The most influential parameter affecting arsenic mobility is the iron content of the soil. 

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3. TOXICOKINETICS 

This Toxicological Review discusses oral waterborne arsenic exposure. It does not 

specifically address inhalation exposures, though they are also common. Dermal exposure and 

exposure from food consumption, however, can be significant and may be confounding variables 

in epidemiological studies. Therefore, this report’s toxicokinetic information focuses on oral 

exposure from water sources, but absorption from dermal exposure and arsenic in food is also 

briefly addressed. 

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The behavior of arsenic in the body is very complex. After absorption, inorganic arsenic 

can undergo a complicated series of enzymatic and non-enzymatic oxidation, reduction, and 

conjugation reactions. Although all these reactions may occur throughout the body, the rate at 

which they occur varies greatly from organ to organ. In addition, there are important differences 

in arsenic metabolism across animal species, and these variations make it difficult to identify 

suitable animal models for predicting human metabolic patterns. 

Each metabolic transformation affects the subsequent biokinetic behavior (transport, 

persistence, elimination) and toxicokinetics of the arsenic species. Thus, absorption, transport, 

and metabolic processes are highly interdependent and cannot easily be discussed separately. 

The general pattern described in this chapter involves the gastrointestinal (GI) absorption of 

inorganic arsenic species, followed by a cascade of oxidation-reduction reactions and 

methylation steps, resulting in the partial transformation of the inorganic species into mono- or 

dimethylated species (collectively referred to as MMA and DMA, recognizing that there is often 

ambiguity in characterizing the oxidation state of the methylarsenic compounds). Conjugated 

arsenic species, either methylated or not (e.g., glutathione conjugates or other sulfur-containing 

derivatives), also may be produced. 

As discussed in Section 3.3, several metabolic schemes have been proposed that describe 

the general pathway that converts inorganic arsenic to its primary metabolites MMA and DMA. 

These pathways involve numerous enzymes and cofactors. Some of the proposed metabolic 

pathways involve the cycling of arsenic species back and forth between the +3 (trivalent) and +5 

(pentavalent) oxidation states, and there is evidence that key metabolic processes may be 

saturable, so that metabolic patterns differ with exposure levels. MMA, DMA, and inorganic 

arsenic levels in tissues, blood, and urine are the most easily and frequently measured 

metabolites; the relative levels of these compounds in blood or urine are often the primary 

evidence in support of one or another metabolic pathway. Genomic tools are being increasingly 

employed to better characterize human arsenic metabolism and to identify individuals at higher 

risk from arsenic exposures. 

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3.1. ABSORPTION 

Water-soluble forms of inorganic arsenic (both trivalent and pentavalent) are readily 

absorbed from the GI tract in experimental animal models (about 80–90% 0.62 mg/kg of sodium 

arsenate; Freeman et al., 1995) as well as humans (Pomroy et al., 1980, who recovered 62% of a 

0.06 ng dose of arsenic in seven days). Monomethyl arsonic acid (MMAV) and dimethylarsinic 

acid (DMAV) also appear to be well absorbed (75–85%) in humans and experimental animals 

(Stevens et al., 1977; Buchet et al., 1981; Yamauchi and Yamamura, 1984; Hughes et al., 2005). 

 Using an in vivo swine test, however, Juhasz et al. (2006) determined that MMA (oxidation 

state not specified) and DMA (oxidation state not specified) were poorly absorbed, with only 

16.7% and 33.3%, respectively, bioavailable. 

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Laparra et al. (2006) used a Caco-2 permeability model, which measured transport 

through a monolayer of human intestinal cells, to examine the intestinal permeability of AsIII. A 

decrease in the apical to basolateral permeability with increasing dose was found, indicating the 

presence of a saturable intestinal transport system. The data also indicated that Caco-2 cells 

have a secretory system for AsIII. In an earlier study, Laparra et al. (2005a) demonstrated that 

the retention and transport of AsIII in Caco-2 cells was more efficient than that of AsV. However, 

this could have been due to the presence of phosphate in the culture medium, which would 

compete with arsenate for transport across the membrane. 

Gastrointestinal absorption of low-solubility arsenic compounds such as arsenic 

trisulfide, lead arsenate, arsenic selenide, gallium arsenide (Mappes, 1977; Webb et al., 1984; 

Yamauchi et al., 1986), and arsenic-contaminated soil (Freeman et al., 1995) is much less 

efficient than that of soluble inorganic arsenic compounds. The degree of absorption of arsenic 

from soil was found to be dependent on the arsenic species present in the soil and on the type of 

soil. Juhasz et al. (2007) performed in vivo bioavailability studies in swine and determined that 

the bioavailability of total arsenic in soils was highly variable, with a range of 6.9% to 74.7% 

depending on the soil type. They also determined that a simplified bioaccessibility extraction 

test (SBET; a rapid in vitro chemical extraction method) had results highly correlated with the in 

vivo results. Therefore, they concluded that the less expensive in vitro test was just as effective 

for determining bioavailability. 

There is little information concerning the bioavailability of inorganic arsenic from 

various types of food (NRC, 1999, 2001). However, there have been recent studies examining 

the bioaccessibility of arsenic from rice (Laparra et al., 2005b; Juhasz et al., 2006). Laparra et 

al. (2005b) determined that while cooking rice (they tested several types, but did not specify 

them) in deionized water caused no change in arsenic content compared to the raw form, cooking 

in water contaminated with 0.5 μg/mL of AsV increased the inorganic arsenic content 5- to 17-

fold over the raw rice. Laparra et al. subjected the rice samples (10 grams) to an in vitro 

simulated digestion process. They measured levels of soluble arsenic to determine 

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bioaccessibility. The results demonstrated that large amounts of the arsenic (i.e., 63%–99%), 

mainly in the pentavalent form, were bioaccessible for intestinal absorption. Ackerman et al. 

(2005) also found 89%–105% bioaccessible arsenic in different samples of white and brown rice 

cooked in water containing AsV. 

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Juhasz et al. (2006) examined the bioavailability of arsenic from rice (mainly white rice 

samples) using an in vivo swine assay. Quest rice was grown in arsenic-contaminated water and 

cooked in arsenic-free water. This caused the rice to contain arsenic, mainly in the form of 

DMA. Administration of the cooked rice to swine demonstrated a bioavailability similar to that 

observed after a single oral administration of DMA in water (i.e., 33.3%). Basmati white rice 

cooked in water contaminated with 1,000 ppb of AsV, which contained entirely inorganic arsenic 

as a result of the arsenate in the cooking water, had a bioavailability of 89.4%. 

Although there have been no studies performed on the rate of inorganic arsenic 

absorption through intact human skin, systemic toxicity due to high dermal occupational 

exposure to aqueous inorganic arsenic solutions indicates that the skin may be a significant 

exposure route (Hostynek et al., 1993). The systemic absorption via the skin from less 

concentrated solutions, however, appears to be low (NRC, 1999). An in vivo study by Wester et 

al. (1993) demonstrated that 2% to 6% of radiolabeled arsenate (as a water solution) was 

absorbed by rhesus monkey skin over a 24-hour period. Results demonstrated that the lower 

dose (0.000024 μg/cm2) was absorbed at a greater rate (6%) than the higher arsenic exposure 

(2.1 μg/cm2; 2%), but the difference did not reach statistical significance. Wester et al. (2004) 

performed another in vivo dermal absorption study using female rhesus monkeys. Using the 

levels excreted in the urine and the applied dose, they calculated that 0.6% to 4.4% was absorbed 

in the three monkeys tested, which was similar to their previous results. In vitro results on 

human skin (from donors) demonstrated a 24-hour absorption of 1.9% (Wester et al., 1993). 

Mouse dorsal skin was demonstrated to absorb 30% to 60% of applied arsenic (Rahman et al., 

1994) using similar in vitro testing, with 60% to 90% of the absorbed arsenic being retained in 

the skin. NRC (1999) suggests this indicates that inorganic arsenic binds significantly to skin 

and hair. Lowney et al. (2007) found that dermal absorption of arsenic from soils was negligible 

in an in vivo study in rhesus monkeys. 

Harrington et al. (1978) compared arsenic metabolite levels in the urine from a group of 

people in Fairbanks, Alaska, who had arsenic-contaminated water (345 ppb) in their home, but 

drank only bottled water, with the levels measured in a group of people who drank home water 

containing less than 50 ppb. The results demonstrated that the group with high arsenic in their 

water had close to the same average concentration of total arsenic metabolites in their urine (i.e., 

43 μg/L) as the group who drank home water with less than 50 ppb arsenic (i.e., 38 μg/L in 

urine), indicating possible dermal absorption via bathing or other exposure sources. Levels of 

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arsenic in the bottled water, however, were not measured. Possible exposure through using 

contaminated water for cooking also was not examined. 

3.2. DISTRIBUTION 

The retention and distribution patterns of arsenic species are strongly dependent on their 

chemical properties. While both AsIII and AsV bind to sulfhydryl groups, AsIII has approximately 

a 5- to 10-fold greater affinity for sulfhydryl groups than AsV (Jacobson-Kram and Montalbano, 

1985). Cellular uptake rates and resulting tissue concentrations are substantially lower for the 

pentavalent than for the trivalent forms of arsenic. DMA (an important metabolite of inorganic 

arsenic) appears to be more readily excreted than MMA (NRC, 2001). Liu et al. (2002) found 

arsenite to be transported into cells by aquaglycoporins (AQP7 and AQP9), whose usual 

substrates are water and glycerol. Liu et al. (2006a) also detected transport of 

monomethylarsonous acid (MMAIII) by AQP9. MMAIII was transported at a rate nearly 3 times 

faster than AsIII. A hydrophobic residue at position 64 was required for the transport of both 

species, suggesting that both species are transported by AQP9 using the same translocation 

pathway. AsV, however, has been suggested to be transported by the phosphate transporter 

(Huang and Lee, 1996). Retention of arsenic can vary not only with its form, but also with tissue 

(Thomas et al., 2001). Other factors that affect the retention and distribution of arsenic include 

the chemical species, dose level, methylation capacity, valence state, and route of administration. 

3.2.1. Transport in Blood 

Once arsenic is absorbed, it is transported in the blood throughout the body. In the blood, 

inorganic arsenic species are generally bound to sulfhydryl groups of proteins and lowmolecular-weight compounds such as glutathione (GSH) and cysteine (NRC, 1999). Binding of 

AsIII to GSH has been demonstrated by several investigators (Anundi et al., 1982; Scott et al., 

1993; Delnomdedieu et al., 1994a,b). Because of the different binding and transport 

characteristics of various arsenic compounds, the persistence in the blood varies across species. 

Inorganic arsenic elimination in humans has been observed to be triphasic, with first-order halflives for elimination of 1 hour, 30 hours, and 200 hours (Mealey et al., 1959, used AsIII; Pomroy 

et al., 1980, used AsV). A single intravenous (iv) dose of 5.8 μg As/kg body weight (in the form 

of 73AsV) administered to two male chimpanzees had a half-life plasma elimination rate of 

1.2 hours and a half-life elimination rate from red blood cells (RBCs) of about 5 hours (Vahter et 

al., 1995a). 

Rats retain arsenic in the blood considerably longer than other species because 

dimethylarsenous acid (DMAIII) and DMAV accumulate in RBCs, apparently bound to 

hemoglobin (Odanaka et al., 1980; Lerman and Clarkson, 1983; Vahter, 1983; Vahter et al., 

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1984). Naranmandura et al. (2007) found that 75% of an oral dose of arsenite accumulated in rat 

RBCs mainly in the form of DMAIII; however, less than 0.8% of the same dose to hamsters was 

found in their RBCs. Rats maintained this level in their RBCs for at least 7 days whereas the 

treated hamsters had levels equivalent to those in controls by 3 days after the administered dose. 

 Stevens et al. (1977) calculated an elimination half-life for inorganic arsenic of 90 days in rat 

whole blood after a single oral dose of 200 mg/kg. Lanz et al. (1950) also reported a high 

retention of arsenic in the blood of cats, although less than in the rat. However, they did not 

determine if the retained arsenic was in the form of DMA. 

The relative concentration of arsenic in human plasma and RBCs apparently differs 

depending on exposure levels and the health status of the exposed individuals. Heydorn (1970) 

reported that healthy people in Denmark with low arsenic exposures had similar arsenic 

concentrations in their plasma and RBCs (2.4 μg/L and 2.7 μg/L, respectively; the RBC:plasma 

ratio was 1.1). However, normal healthy Taiwanese exposed to arsenic-contaminated water had 

plasma levels of 15.4 μg/L and RBCs levels of 32.7 μg/L (RBC:plasma ratio 2.1). Blackfoot 

disease (BFD) patients and their unaffected family members had 38.1 μg/L and 93 μg/L of 

arsenic species in their plasma and RBCs, respectively (RBC:plasma ratio 2.4). These results 

indicate a different distribution between the RBCs and the plasma depending on exposure levels. 

 However, examining the BFD patients and their families, who presumably have the same 

exposure levels, demonstrates a different distribution, possibly due to disease state. BFD 

patients had a ratio of 3.3 (106 μg/L in RBCs and 32.3 μg/L in plasma) compared to 1.8 (81 μg/L 

in RBCs and 45.2 μg/L in plasma) in family members without BFD. This indicates that 

accumulation of arsenic in the RBCs is greater as exposure increases and possibly even greater 

when health is compromised. The ratio between plasma and RBC arsenic concentrations may 

also depend on the exposure form of arsenic (NRC, 1999). 

3.2.2. Tissue Distribution 

Once arsenic compounds enter the blood, they are transported and taken up by other 

tissues and organs, with a large proportion of ingested material being subject to “first pass” 

processing through the liver. Uptake varies with arsenic species, dose, and organ. The observed 

uptake of inorganic arsenic (mainly AsIII) in the skin, hair, oral mucosa, and esophagus is most 

likely due to the binding of inorganic arsenic species with sulfhydryl groups of keratin in these 

organs. In studies using rabbits and mice, where the transfer of methyl groups from 

S-adenosylmethionine (SAM; a proposed major reaction during arsenic metabolism; see Section 

3.3) was chemically inhibited, the concentration of arsenic in most tissues (especially the skin) 

was found to be increased (Marafante and Vahter, 1984). The important role of chemical 

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binding of arsenic species also is supported by the observed tissue distribution in the marmoset 

monkey, which does not methylate inorganic arsenic (Vahter et al., 1982). 

Human subjects also have demonstrated high concentrations of arsenic in tissues 

containing a high content of cysteine-containing proteins, including the hair, nails, skin, and 

lungs. Total arsenic concentrations in these tissues of human subjects exposed to background 

levels of arsenic ranged from 0.01 to 1.0 mg/kg of dry weight (Liebscher and Smith, 1968; Cross 

et al., 1979). Benign and malignant skin lesions from 14 patients, with a minimum of 4 years of 

exposure to inorganic arsenical medication, had higher arsenic levels (0.8 to 8.9 ppm) than six 

subjects with no history of arsenic intake (0.4 to 1.0 ppm; Scott, 1958). In West Bengal, India, 

where the average arsenic concentration in the drinking water ranges from 193 to 737 ppb, 

arsenic concentrations in the skin, hair, and nails were 1.6–5.5, 3.6–9.6, and 6.1–22.9 mg/kg dry 

weight, respectively (Das et al., 1995). Mandal et al. (2004) measured different arsenic species 

in the hair and fingernails of 41 subjects in West Bengal, India, who were drinking arseniccontaminated water and in blood from 25 individuals who had stopped drinking contaminated 

water 2 years earlier. Results were: fingernail contained AsIII (62.4%), AsV (20.2%), MMAV

(5.7%), DMAIII (8.9%), and DMAV (2.8%); hair contained AsIII (58.9%), AsV (34.8%), MMAV

(2.9%), and DMAV (3.4%); RBCs contained arsenobetaine (22.5%) and DMAV (77.5%); and 

blood plasma contained arsenobetaine (16.7%), AsIII (21.1%), MMAV (27.1%), and DMAV

(35.1). However, the amount of arsenic in these tissues resulting from other exposure pathways 

(e.g., dermal exposure) was not determined. 

The longest retention of inorganic arsenic in mammalian tissues during experimental 

studies has been observed in the skin (Marafante and Vahter, 1984), hair, squamous epithelium 

of the upper GI tract (oral cavity, tongue, esophagus, and stomach wall), epididymis, thyroid, 

skeleton, and the lens of the eye (Lindgren et al., 1982). Although the study authors measured 

radioactive arsenic (74As) in the various tissues, they did not differentiate between the different 

species of arsenic and could not determine if accumulation was due to the originally 

administered compound or metabolites. Arsenic levels in all these tissues, with the exception of 

the skeleton, were greater in mice administered AsIII than in mice administered AsV. This could 

indicate that AsIII is taken up more efficiently than AsV and that less was found in the tissues of 

AsV-treated mice due to the initial reduction to AsIII. The calcified areas of the skeleton in mice 

administered AsV accumulated and retained more arsenic than mice administered AsIII, most 

likely due to the similarities between AsV and phosphate, causing a substitution of phosphate by 

AsV in the apatite crystals in bone. Marmoset monkeys were found not to accumulate arsenic in 

the ocular lens or the thyroid (Vahter et al., 1982); however, intravenous administration of 74Aslabelled DMA to mice resulted in accumulation of DMA in the ocular lens and the thyroid. 

Marmoset monkeys do not methylate arsenic and DMA was found to accumulate in the ocular 

lens and thyroid; this suggests that only the methylated species are retained in these organs. 

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Mouse tissues with the largest retention of DMA were the lens of the eyes, thyroid, lungs, and 

intestinal mucosa (Vahter et al., 1984). Methylated arsenic species (DMA), in general, have a 

shorter tissue retention time in mice than rats (i.e., more than 99% of the administered dose was 

eliminated in mice within 3 days as compared to 50% in rats due to accumulation in blood) 

(Vahter et al., 1984). 

Hughes et al. (2003) estimated that a steady-state, whole-body arsenic balance was 

established after nine repeated oral daily doses of 0.5 mg As/kg as radioactive AsV in adult 

female B6C3F1 mice. Twenty-four hours after the last dose, the whole-body burden of arsenic 

was about twice that observed after a single dose. The rate of elimination was slower following 

repeated doses. Accumulation of radioactivity was highest in the bladder, kidney, and skin, 

while the loss of radioactivity was greatest from the lungs and slowest from the skin. Atomic 

absorption spectrometry was used to characterize the organ distribution of arsenic species. 

MMA was detected in all tissues except the bladder. DMA was found at the highest levels in the 

bladder and lung after a single oral exposure, with increases after repeated exposures. Inorganic 

arsenic was predominantly found in the kidney. After a single oral exposure of AsV (0.5 mg 

As/kg), DMA was the predominant form of arsenic in the liver, but after nine repeat exposures, 

the proportion of DMA decreased while the proportion of inorganic arsenic increased (this could 

indicate metabolic saturation or GSH depletion; see Section 3.3 for more details). A 

trimethylated form of arsenic also was detected in the liver. 

Kenyon et al. (2005a) examined the time course of tissue distribution of different arsenic 

species after a single oral dose of 0, 10, or 100 μmole As/kg as sodium arsenate to adult female 

B6C3F1 mice. The concentrations of all forms of arsenic were lower in the blood than in other 

organs across all doses and time points. The concentration of inorganic arsenic measured in the 

liver was similar to that measured in the kidney at both dose levels, with peak concentrations 

observed 1 hour after dosing. For the first 1 to 2 hours, inorganic arsenic was the predominant 

form in both the liver and kidney, regardless of dose. At the later times, DMA became the 

predominant form. Kidney measurements 1 hour after dosing demonstrated that MMA levels 

were 3 to 4 times higher than in other tissues. DMA concentrations in the kidney reached their 

peak 2 hours after dosing. DMA was the predominant form measured in the lungs at all time 

points following exposure to 10 μmole As/kg as AsV. DMA concentrations in the lung were 

greater than or equal to those of the other tissues beginning at four hours. The study did not 

distinguish the different valence states of the MMA or DMA compounds. 

In a follow-up study by Kenyon et al. (2008), adult female C57Bl/6 mice were 

administered 0, 0.5, 2, 10, or 50 ppm of arsenic as sodium arsenate in the drinking water for 

12 weeks. The average daily intakes were estimated to be 0, 0.083, 0.35, 1.89, and 7.02 mg 

As/kg/day, respectively. After 12 weeks of exposure, the tissue distributions were as follows: 

kidney > lung > urinary bladder > skin > blood > liver. In the kidney, MMA was the 

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predominant form measured, while DMA was more prominent in the lungs and blood. The skin 

and urinary bladder had nearly equal levels of both inorganic arsenic and DMA and the liver had 

equal proportions of all three species. 

Naranmandura et al. (2007) characterized the tissue distribution in rats and hamsters 

administered a single oral dose of AsIII (5.0 mg As/kg body weight, or BW). In rats, the highest 

concentrations were found in RBCs. Because hamsters did not accumulate arsenic species in 

their RBCs, they exhibited a more uniform tissue distribution. While the quantity of arsenic in 

the liver and kidneys of the hamster were significantly greater than those observed in the rat, 

arsenic accumulated more and was retained longer in the kidneys than the liver in both species. 

The hamster had greater levels of MMAIII bound to protein in the kidney than rats. 

AsIII and AsV, as well as methylated metabolites, cross the placenta at all stages of 

gestation in mice, marmoset monkeys, and hamsters (Hanlon and Ferm, 1977; Lindgren et al., 

1984; Hood et al., 1987; Jin et al., 2006a), with tissue distribution of arsenic similar between the 

mother and the fetus in late gestation. Jin et al. (2006a) found increased levels of inorganic 

arsenic and DMA in the livers and brains of newborn mice from dams administered either AsIII 

or AsV in their drinking water throughout gestation and lactation. The levels of total arsenic in 

the mothers’ livers increased in a dose-dependent manner and were greater than those observed 

in the mothers’ brains or in the newborns’ brains or livers. The levels of total arsenic in the 

livers and brains of newborn mice, however, were greater than those observed in the mothers’ 

brains, suggesting easier passage through the placenta than through a mature blood-brain barrier. 

 Because the levels of inorganic arsenic in the newborn livers and brains were nearly identical, it 

appears that there was no difficulty in passing through an immature blood-brain barrier. In 

addition, the nearly 2:1 ratio of DMA in the brains compared to the livers of newborns indicates 

either a preferential distribution of DMA in the newborns’ brains or an increased distribution of 

inorganic arsenic to the brain that is subsequently metabolized. The marmoset monkey (known 

to not methylate arsenic) displayed somewhat less placental transfer after administration of AsIII

than was seen in mice (Lindgren et al., 1984). 

The arsenic concentration in the cord blood (11 μg/L) was similar to that observed in 

maternal blood (an average of 9 μg/L) in pregnant women living in a village in northwestern 

Argentina, where the arsenic concentration in the drinking water was approximately 200 ppb 

(Concha et al., 1998a). Hall et al. (2007) also found a strong association between maternal (11.9 

μg/L) and cord blood levels (15.7 μg/L) in Matlab, Bangladesh (arsenic exposure ranged from 

0.1 to 661 ppb in drinking water). They also measured arsenic metabolite levels and found that 

the association also was observed for the metabolites MMA and DMA. Elevated arsenic 

concentrations also were noted in pregnant women living in cities with low dust fall (i.e., low 

arsenic inhalation exposures), where an average of 3 μg/L was measured in the maternal blood 

and 2 μg/L in cord blood (Kagey et al., 1977). Women living near smelters also have been 

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observed to have an increased concentration of placental arsenic (Tabacova et al., 1994). 

Although the human fetus is exposed to arsenic, it may be more in the form of DMA (at least in 

late gestation) because 90% or more of the arsenic in the urine and plasma of newborns and 

mothers (at time of delivery) was DMA. 

3.2.3. Cellular Uptake, Distribution, and Transport 

Cellular uptake of inorganic arsenic compounds also depends on oxidation state, with 

AsIII generally being taken up at a much greater rate than arsenate (Cohen et al., 2006). In 

Chinese hamster ovary (CHO) cells, the rate of uptake was DMAIII > MMAIII > AsIII (Dopp et 

al., 2004), with the pentavalent forms being taken up much more slowly than the trivalent forms. 

 Delnomdedieu et al. (1995) demonstrated that AsIII is taken up more readily than AsV, MMAV, 

or DMAV by RBCs in rabbits. Drobná et al. (2005) found that MMAIII and DMAIII were taken 

up by modified UROtsa cells expressing arsenic methyltransferase (this is a human urothelial 

cell line that normally does not methylate inorganic arsenic) at an order of magnitude faster than 

AsIII. Because arsenate uptake is inhibited in a dose-dependent manner by phosphate (Huang 

and Lee, 1996), it has been suggested that a common transport system is responsible for the 

cellular uptake for both compounds. AsIII uptake, however, is not affected by phosphate; 

therefore, Huang and Lee (1996) suggested that cellular uptake of AsIII occurs through simple 

diffusion. Liu et al. (2002, 2006a), however, suggested that transport of AsIII and MMAIII across 

the cellular membrane may be mediated by AQP7 and AQP9 with MMAIII transported at a 

higher rate. Lu et al. (2006) found that inorganic arsenic (both pentavalent and trivalent 

oxidation states) can be transported by organic anion transporting polypeptide-C (OATP-C; 

which was transfected into cells of a human embryonic kidney cell line), but not MMAV or 

DMAV. In a cell line resistant to arsenic (R15), Lee et al. (2006a) found little AQP7 or AQP9 

messenger RNA (mRNA) and only half the AQP3 mRNA expression compared to the parental 

cell line (CL3, a human lung adenocarcinoma cell line). Suppressing the AQP3 expression in 

CL3 cells caused less arsenic to accumulate in these cells. Over-expression of AQP3 in a 293 

cell line (a human embryonic kidney cell line) resulted in an increase in arsenic accumulation in 

the cells. Hexose permease transporters (HXT) also have been suggested as another influx 

pathway for AsIII (Thomas, 2007). 

Shiobara et al. (2001) demonstrated that the uptake of DMA in RBCs was dependent on 

not only the chemical form (or oxidation state), but animal species. DMAIII and DMAV were 

incubated with rat, hamster, mouse, and human RBCs. DMAV was only minimally absorbed by 

RBCs, and the cellular uptake was very slow in all animal species tested. DMAIII, on the other 

hand, was efficiently taken up by the RBCs in the following order: rats > hamsters > humans. 

Mouse RBCs were less efficient at the uptake of DMAIII than any of the other species. Rat 

RBCs retained the DMAIII throughout the 4 hours of the experiment, but hamster RBCs were 

found to excrete the arsenic absorbed as DMAIII in the form of DMAV. Human RBCs also 

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excreted DMAIII as DMAV, though the rate of uptake of DMAIII and efflux of DMAV was much 

slower than in hamster RBCs. 

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Cellular excretion of arsenic species also depends on oxidation state and the degree of 

methylation. Leslie et al. (2004), using membrane vesicles from a multi-drug resistant human 

lung cancer cell line (H69AR), found that a multi-drug resistance protein (MRP) called MRP1 

transports AsIII in the presence of GSH but did not transport AsV under any conditions. This 

suggests that AsV must be reduced to AsIII before being excreted from the cell. Further, the 

MRP1 transport was more efficient with arsenic triglutathione (ATG) as the substrate. This 

finding, along with the observation that AsIII transport is more efficient at neutral or low pH 

where ATG is more readily formed and more stable, suggests that ATG is formed prior to 

transport. Leslie et al. (2004) also suggest that the formation of the conjugate is catalyzed by the 

glutathione-S-transferase P1-1 (GSTP1-1) enzyme. MRP2 may also be involved in the efflux of 

arsenic species from cells (Thomas, 2007). MRP2 expression was found to be five times higher 

in arsenic-resistant (R15) cells compared to the parent cell line (CL3). However, expression 

levels of MRP1 and MRP3 were similar to levels in parent cells (Lee et al., 2006a). Suppressing 

the multi-drug resistant transporters reduced the efflux of arsenic from R15 cells. 

In a study of rabbits and mice exposed to radio-labeled arsenic (as AsIII), the majority of 

the arsenic was found in the nuclear and soluble fractions of liver, kidney, and lung cells 

(Marafante et al., 1981; Marafante and Vahter, 1984). The marmoset monkey had a different 

intracellular distribution, with approximately 50% of the arsenic dose found in the microsomal 

fraction in the liver (Vahter et al., 1982; Vahter and Marafante, 1985). Chemical inhibition of 

arsenic methylation in rabbits did not alter the intracellular distribution of arsenic (Marafante and 

Vahter, 1984; Marafante et al., 1985). 

Increases in tissue arsenic concentration (especially in the liver) have been found to be 

associated with increased arsenic concentrations in the microsomal fraction of the liver in rabbits 

fed diets containing low concentrations of methionine, choline, or proteins, which leads to 

decreased arsenic methylation (Vahter and Marafante, 1987). The levels of arsenic in the 

microsomal fraction of the liver in these rabbits were similar to those observed in the marmoset 

monkey (Vahter et al., 1982), indicating that nutritional factors may play a role in determining 

the subcellular distribution of arsenic. 

3.3. METABOLISM 

After entering the body, AsV can be reduced to AsIII, which can then proceed through a 

series of methylation and conjugation reactions, some of which involve re-oxidation of arsenic to 

AsV. The traditional metabolic pathways proposed for arsenic are shown in Figure 3-1. In this 

metabolic scheme, less toxic species (i.e., AsV, MMAV, and DMAV) can be converted to more 

toxic species (i.e., AsIII, MMAIII, and DMAIII). The trivalent species have been found to be more 

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cytotoxic, genotoxic, and more potent inhibitors of enzyme activity (Thomas et al., 2001). While 

the final metabolite in humans is predominantly DMAV, as this is the form most highly excreted, 

some animal species further metabolize DMAV through DMAIII to trimethylarsine oxide 

(TMAO). 

?

Glutathione S transferase-ω

ArseniteIII

ArsenateV

Monomethylarsonic acid (MMAV)

Monomethylarsonous acid (MMAIII)

Dimethylarsinic acid (DMAV)

Dimethylarsenous acid (DMAIII)

Trimethyl arsine oxide (TMAOV)

Arsenate reductase, Glutathione S-transferase-ω, 

Glyceraldehyde phosphate dehydrogenase 

(GAPDH)?; Nonenzymatic pathway

Arsenite (III) 

Methyltransferase (AS3MT)

Trimethyl arsine (TMAIII)

SAM

SAH

SAM

SAH

SAM

SAH

Source: Sams et al. (2007). 

Figure 3-1. Traditional metabolic pathway for inorganic arsenic in 

humans. 

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Hayakawa et al. (2005) suggested a possible alternate metabolic pathway for inorganic 

arsenic (Figure 3-2). As in the previously described model, the first step involves reduction of 

AsV to AsIII. A major difference, however, is that Hayakawa et al. (2005) suggest that arsenicglutathione complexes are important intermediates in the metabolism of arsenic and are the 

primary substrates for arsenic methyltransferases. The proposed model was based on the 

observation that more DMAV is produced from AsIII than from MMAV. This should not be the 

case if the reactions depicted in Figure 3-1 are the primary arsenic metabolic pathways. Their 

data suggest that arsenite, in the presence of GSH, non-enzymatically reacts to form ATG. In 

support of this mechanism, they observed a dose-dependent increase in concentration of ATG 

with increasing doses of GSH, up to 4 mM. Monomethyl and dimethyl arsenic species were 

generated by the transfer of a methyl group from SAM in the presence of human recombinant 

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arsenic (+3 oxidation state) methyltransferase (AS3MT), and only occurred when ATG or 

monomethylarsonic diglutathione (MADG) was present. At concentrations of glutathione of 

2.0 mM or greater, there was a dose-dependent increase in DMAV levels, accompanied by a 

dose-dependent decrease in AsV. 

O

II

OH ─ AsV ─ OH

I

OH

Arsenate

OH ─ AsIII ─ OH

I

OH

Arsenite

O

II

OH ─ AsV ─ CH3

I

CH3

DMA(V)

GS ─ AsIII ─ SG

I

SG

O

II

OH ─ AsV ─ OH

I

CH3

MMA(V)

ATG

(Arsenic triglutathione)

Arsenic 3 methyl transferase (As3MT); SAM -S-adenosyl methionine; GSH -Glutathione

As3MT

SAM

GS ─ AsIII ─ SG

I

CH3

GS ─ AsIII ─ CH3

I

CH3

DMAG

(Dimethylarsinic 

Glutathione)

MADG

(Monomethylarsinic 

diglutathione)

OH ─ AsIII ─ OH

I

CH3

MMA(III)

GSH

DMA(III)

OH ─ AsIII ─ CH3

I

CH3

GSH

GSH

Hayakawa et al. 2005

As3MT

SAM

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Source: Hayakawa et al. (2005). 

Figure 3-2. Alternative metabolic pathway for inorganic arsenic in 

humans proposed by Hayakawa et al. (2005). 

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In summary, the proposed metabolic model of Hayakawa et al. (2005) suggests that AsV

is first reduced to AsIII, which then reacts (non-enzymatically) with GSH (producing ATG). In 

the presence of AS3MT (specified as cyt19 in the Hayakawa article),

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 ATG is methylated to 

MADG if the GSH concentration is sufficient, which then comes to equilibrium with MMAIII

(GSH concentrations lower than 1 mM caused MADG to be unstable in solution and was readily 

hydrolyzed and oxidized to MMAV). While some of the MMAIII is oxidized to MMAV, some of 

the MADG is methylated by AS3MT to dimethylarsinic glutathione (DMAG), which, like 

MADG, is in equilibrium with its trivalent form and can be oxidized to its pentavalent form. 

This more recently proposed pathway leads to higher proportions of less toxic final species than 

the original proposed metabolic pathway (Figure 3-1). 

Results reported by Hughes et al. (2005) may provide support for the Hayakawa et al. 

(2005) revised pathway. B6C3F1 mice administered MMAV per os demonstrated its rapid 

absorption, distribution, and excretion, with 80% of the dose eliminated within 8 hours. Very 

little of the absorbed dose, however, was methylated to DMA and/or TMAO. Less than 10% of 

the dose excreted in urine and 25% or less of the dose measured in the tissues were in the form 

of DMA. In contrast, in MMAIII-treated mice, more than 90% of the excreted dose and more 

than 75% of the arsenic measured in the tissues was identified as DMA. This discrepancy 

between the two forms of MMA is not expected if the generally accepted metabolic pathway 

(Figure 3-1) is followed. However, if MMAIII is the form methylated to DMA while MMAV is 

an end product, as is suggested by Hayakawa et al. (2005), then it would be expected that a 

greater proportion of MMAIII would be methylated to DMA than MMAV. There are, however, 

factors that may limit the in vivo methylation of MMAV that are unrelated to the metabolic 

pathway proposed by Hayakawa et al. (2005). First, MMAV does not appear to be taken up well 

by the liver (Hughes et al., 2005), a major site of inorganic arsenic metabolism (Thomas et al., 

2001). In fact, pentavalent species of arsenic are not taken up by cells as readily as trivalent 

arsenicals (Dopp et al., 2004). In addition, in the generally accepted metabolic pathway (Figure 

3-1), MMAV needs to be reduced to MMAIII in order to be methylated. Therefore, if very little is 

taken up into cells, very little can be methylated. 

 Aposhian and Aposhian (2006) suggest that it is too early to accept AS3MT as the 

primary methyltransferase responsible for arsenic methylation in humans because it has only 

been observed in experiments involving deoxyribonucleic acid (DNA) recombinant technology 

and because there is no indication that the enzyme is expressed in human liver. Although 

AS3MT has been detected in human liver cell lines (Zakharyan et al., 1999), it has not been 

2 Arsenic (+3 oxidative state) methyltransferase (AS3MT) has been referred to by many investigators as cyt19 in 

their references. According to Thomas et al. (2007), the Human Genome Nomenclature Committee 

(http://www.gene.ucl.ac.uk/cgi-bin/nomenclature/searchgenes.pl) recommends that this protein be systematically 

named AS3MT. In this document, references to cyt19 it has been changed to AS3MT to avoid confusion and for 

uniform consistency. 

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isolated from surgically removed liver tissue. Thomas et al. (2007) also states the evidence 

supports the conclusion that arsenic methylation catalyzed by AS3MT is not strictly dependent 

on the presence of GSH, which would suggest that other pathways may be involved in addition 

to those included in Hayakawa et al.’s (2005) model. GSH depletion would likely occur at high 

arsenic exposures under Hayakawa et al.’s proposed pathway. Therefore, it is possible that both 

pathways work in conjunction, or one is predominant over the other depending on the 

concentration of arsenic. Hayakawa et al. (2005) found that levels of MMAV were not 

dependent on GSH level (from 2 to 5 mM), suggesting that this indicated possible further 

methylation to DMAV. Since this is not part of the proposed Hayakawa et al. (2005) pathway, at 

least some of the MMAV may be methylated through the classic pathway. 

3.3.1. Reduction 

A substantial fraction of absorbed AsV is rapidly reduced to AsIII in most species studied; 

in mice, rabbits, and marmoset monkeys, the reduction apparently occurs mainly in the blood 

(Vahter and Envall, 1983; Vahter and Marafante, 1985; Marafante et al., 1985). Reduction also 

may occur in the stomach or intestines prior to absorption, but quantitative experimental data are 

not available to determine the importance of this GI reduction. In addition to the reduction of 

inorganic AsV, as shown in Figure 3-1, methylated AsV species also may be reduced, apparently 

by different enzymes. 

GSH may play a role in the reduction of AsV, but apparently is not the only cofactor, as 

cysteine and dithiothreitol (DTT) also have been found to reduce AsV to AsIII in vitro (Zakharyan 

et al., 1995; NRC, 1999; Németi and Gregus, 2002). Inorganic phosphate inhibits the formation 

of AsIII from AsV in intact RBCs (Németi and Gregus, 2004), probably by competing with the 

phosphate transporter for the uptake into cells. 

Arsenate reductase enzymes have been detected in the human liver (Radabaugh and 

Aposhian, 2000). At least one of these enzymes has been characterized as a purine nucleoside 

phosphorylase (PNP) (Gregus and Németi, 2002; Radabaugh et al., 2002). This enzyme requires 

a thiol and a heat-stable cofactor for activation. According to Radabaugh et al. (2002), 

dihydrolipoic acid (DHLP) is the most active naturally occurring thiol in mammalian systems 

and appears to be required for the enzymatic reduction of AsV to AsIII. PNP, however, did not 

catalyze the reduction of MMAV to MMAIII. An MMAV reductase has been detected in rabbit 

liver (Zakharyan and Aposhian, 1999), hamster tissues (Sampayo-Reyes et al., 2000), and human 

liver (Zakharyan et al., 2001). In humans, this reductase is human glutathione-S-transferase ω

(hGST-O1), which is a member of the glutathione-S-transferase (GST) superfamily (Aposhian 

and Aposhian, 2006). 

Although PNP has been determined to reduce AsV to AsIII, Németi et al. (2003) observed 

this reduction only in vitro. PNP did not appear to be a major player in the reduction of AsV to 

AsIII in either human erythrocytes or in rats in vivo. Németi and Gregus (2004, 2005) further 

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demonstrated that human erythrocytes exhibit a PNP-independent AsV-reducing pathway that 

requires GSH, nicotinamide adenine dinucleotide (NAD), and a substrate for either one or both 

of the following enzymes: glyceraldehyde-3-phosphate dehydrogenase (GAPDH) or 

phosphoglycerate kinase (PGK). This mechanism of reduction also was demonstrated in rat liver 

cytosol (Németi and Gregus, 2005). In addition, another unidentified enzyme in the liver cytosol 

had the capacity to reduce AsV. A further study (Gregus and Németi, 2005) demonstrated that 

GAPDH exhibited AsV reductase activity, but that PGK served as an auxiliary enzyme when 

3-phosphoglycerate was the glycolic substrate. 

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The reduction of pentavalent arsenicals also has been observed to be catalyzed by 

AS3MT (Waters et al., 2004a). According to Waters et al. (2004b), AS3MT may possess both 

AsIII methyltransferase and AsV reductase activities. In the presence of an exogenous or 

physiological reductant, AS3MT was found to catalyze the entire sequence converting arsenite to 

all of its methylated metabolites through both methylation and reduction steps (Figure 3-1). 

Thomas et al. (2007) also suggest that thioredoxin (Trx, isolated from E. coli) is necessary, 

possibly reducing some critical cysteine residue in AS3MT as a step in the methyltransferase 

reaction. Cohen et al. (2006) suggest that Trx, thioredoxin reductase (TrxR), and nicotinamide 

adenine dinucleotide phosphate-oxidase (NADPH) are the primary reducing agents involved in 

the conversion of MMAV to DMAV, but they are orders of magnitude less effective than the 

arsenic methyltransferase isolated from rabbit liver (i.e., AS3MT). Zakharyan and Aposhian 

(1999) found that MMAV-reductase was the rate-limiting enzyme in arsenic biotransformation in 

rabbit livers. Jin et al. (2006a) also suggest that AsV reduction is possibly a rate-limiting step in 

arsenic metabolism at low concentrations. At higher concentrations, saturation or methylation 

inhibition may cause other reactions to become rate-limiting. 

3.3.2. Arsenic Methylation 

Methylation is an important factor affecting arsenic tissue distribution and excretion. 

Humans and most experimental animal models methylate inorganic arsenic to MMA and DMA, 

with the amounts differing across species, as determined by analysis of urinary metabolites. The 

methylated metabolites in and of themselves have historically been considered less acutely toxic, 

less reactive with tissue constituents, less cytotoxic, and more readily excreted in the urine than 

inorganic arsenic (Vahter and Marafante, 1983; Vahter et al., 1984; Yamauchi and Yamamura, 

1984; Marafante et al., 1987; Moore et al., 1997a; Rasmussen and Menzel, 1997; Hughes and 

Kenyon, 1998; Sakurai et al., 1998). The trivalent species MMAIII and DMAIII, however, have 

been demonstrated to be more cytotoxic in a human liver cell line called Chang cells (Petrick et 

al., 2000, 2001), CHO (Dopp et al., 2004), and cultured primary rat hepatocytes (Styblo et al., 

1999a, 2000) than AsIII, AsV, MMAV, or DMAV. 

Although the kinetics of arsenic methylation in vivo are not fully understood, it is 

believed the liver may be the primary site of arsenic methylation. However, the testes, kidney, 

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and lung also have been observed to have a high methylating capacity (Cohen et al., 2006). 

Marafante et al. (1985) found that DMA appeared in the liver prior to any other tissue in rabbits 

exposed to inorganic As. It also has been demonstrated oral administration of inorganic arsenic 

favors methylation more than either subcutaneous or intravenous administration (Charbonneau et 

al., 1979; Vahter, 1981; Buchet et al., 1984), presumably because the arsenic will pass through 

the liver first after oral administration. However, liver disease (i.e., alcoholic, post-necrotic or 

biliary cirrhosis, chronic hepatitis, hemochromatosis, and steatosis) can be associated with 

increased ratios of DMA to MMA in the urine following a single injection of sodium arsenite 

(Buchet et al., 1984; Geubel et al., 1988). This appears to indicate that efficient methylation of 

arsenic continues in the presence of liver damage, possibly indicating that a different organ is 

responsible for methylation under these circumstances. In addition, the site of methylation may 

depend on the rate of reduction of AsV to AsIII. Isolated rat hepatocytes readily absorbed and 

methylated AsIII, but not AsV (Lerman et al., 1983). Kidney slices, on the other hand, produced 

five times more DMA from AsV than AsIII (Lerman and Clarkson, 1983). Therefore, it is likely 

that any AsV not initially reduced can be efficiently methylated in the kidney for subsequent 

urinary excretion. 

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Identifying the main organs responsible for methylation of arsenic in vivo has not been 

straightforward because in vitro results do not necessarily reflect in vivo methylation patterns 

(NRC, 1999). Buchet and Lauwerys (1985) identified the rat liver as the main organ for 

methylation, with the methylating capacities in the RBCs, brain, lung, intestine, and kidneys 

being insignificant in comparison. Assays of arsenite methyltransferases from mouse tissues 

demonstrated the testes had the highest methylating activity, followed by the kidney, lung, and 

liver (Healy et al., 1998). Aposhian (1997) determined that the amount of methyltransferases 

vary in the liver of different animal species. Arsenite bound to components of tissue can be 

methylated and released (Marafante et al., 1981; Vahter and Marafante, 1983). This may explain 

the initial rapid phase (immediate methylation and excretion) followed by a slow elimination 

phase (continuous release of bound arsenite through methylation) (NRC, 1999), as described in 

Section 3.4. 

It has been demonstrated that inhibition of arsenic methylation results in increased tissue 

concentrations of arsenic (Marafante and Vahter, 1984; Marafante et al., 1985). Loffredo et al. 

(2003) suggest that the second methylation step is inducible and that the inducibility is possibly 

polymorphic (i.e., more than one enzyme or enzyme form may be involved, depending on the 

individual). This suggestion is based on observations that human urinary DMA concentrations 

in high-exposure groups were higher and more variable than urinary MMA levels, and because 

urinary DMA levels appeared to have a bimodal distribution in a population from Mexico, 

regardless of exposure status. Others have suggested that the second methylation step may be 

saturable, which would be consistent with the decreasing excretion of DMA with increasing 

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arsenic exposures (Ahsan et al., 2007). Cysteine, GSH, and DTT have been shown to increase 

the activity of arsenite methyltransferase and MMA methyltransferase (both later identified as 

AS3MT; Lin et al., 2002) in purified rabbit liver enzyme preparations (Zakharyan et al., 1995). 

Dithiols (e.g., reduced lipoic acid) have also been found to enhance arsenite methylation by 

MMAIII methyltransferase (Zakharyan et al., 1999). Glutathione-S-transferase omega 1 

(GSTO1) has also been associated with arsenic biotransformation (Meza et al., 2007). Although 

humans have been observed to methylate arsenic, no arsenic methyltransferase has yet been 

isolated from human tissues (Aposhian and Aposhian, 2006). 

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In vitro studies using rat liver preparations indicate that the methylating activity is 

localized in the cytosol, with SAM being the main methyl donor for AsIII methylation (Marafante 

and Vahter, 1984; Buchet and Lauwerys, 1985; Marafante et al., 1985; Styblo et al., 1995, 1996; 

Zakharyan et al., 1995). AS3MT catalyzes the transfer of the methyl group from SAM to the 

arsenic substrates (Lin et al., 2002; Thomas, 2007). Expressing AS3MT in UROtsa (human 

urothelial cells that do not normally methylate inorganic arsenic) caused the cells to effectively 

methylate arsenite (Drobná et al., 2005). High concentrations of AsIII or MMAIII in the culture 

caused an inhibition in the formation of DMA, but had little effect on the formation of MMA. 

The inhibition of DMA production resulted in MMA accumulation in cells. Drobná et al. (2006) 

demonstrated that AS3MT was the major enzyme for arsenic methylation in human 

hepatocellular carcinoma (HepG2) cells, but reducing it by 88% (protein levels) only accounted 

for a 70% reduction in methylation capacity, suggesting that there is another methylation process 

that is independent of AS3MT. 

The addition of GSH has been found to increase the yield of mono- and dimethylated 

arsenicals but suppressed the production of TMAO in the presence of rat AS3MT (Waters et al., 

2004a), indicating that GSH suppresses the third methylation reaction but not the first two 

(Thomas et al., 2007). Thomas et al. (2004) discovered a similar arsenic methyltransferase in the 

rat liver, which they designated cyt19 because an orthologous cyt19 gene encodes an arsenic 

methyltransferase in the mouse and human genome. It has subsequently been concluded that this 

methyltransferase was the same as AS3MT. 

GSH alone does not support recombinant rat AS3MT catalytic function, but when added 

to a reaction mixture containing other reductants, the rate of arsenic methylation increases 

(Waters et al., 2004b). GSH alone (5mM) does not support the catalytic activity of AS3MT, but 

stimulates the methylation rate in the presence of the reductant tris(2-carboxylethyl)phosphine 

(TCEP; 1 mM) (Thomas et al., 2007). GSH (5 mM) did not have any effect on DTT (1 mM)-

induced arsenic methylation. Drobná et al. (2004) linked the genetic polymorphism of AS3MT 

with other cellular factors and to the inter-individual variability in the capacity of primary human 

hepatocytes to retain and metabolize AsIII (see Section 4.7). 

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The main products of arsenic methylation in humans are MMAV and DMAV, which are 

readily excreted in the urine (Marcus and Rispin, 1988). MMAIII and DMAIII have recently been 

detected in human urine (NRC, 2001); however, most studies do not differentiate the valence 

state of mono- or dimethylated arsenic species detected in urine or tissue samples. Le et al. 

(2000a,b) and Del Razo et al. (2001) noted that the concentration of trivalent metabolites in the 

urine may be underestimated because they are easily oxidized after collection. Le et al. (2000b) 

found 43 to 227 μg/L of MMAIII in the urine of populations from Inner Mongolia, China, who 

were exposed to 510–660 ppb (0.46 μM) of arsenic via the drinking water. 

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A small percent of DMAIII may further be methylated to TMAO in mice and hamsters 

(see Kenyon and Hughes, 2001, for a review). A single human volunteer ingesting DMA 

excreted 3.5% of the dose as TMAO (Kenyon and Hughes, 2001). TMAO can be detected in 

urine following DMA exposure, but has not been detected in the blood or tissues of mice 

exposed intravenously to DMA (Hughes et al., 2000) or in the urine of mammals orally exposed 

to inorganic As. This may be due to rapid clearance of DMA and MMA from cells (Styblo et al., 

1999b); however, most analytical methods are not optimized for the detection of TMAO that 

could have been present but not detected. 

3.3.3. Species Differences in the Methylation of Arsenic 

There is considerable variation in the patterns of inorganic arsenic methylation among 

mammalian species (NRC, 1999). Humans, rats, mice, dogs, rabbits, and hamsters have been 

shown to efficiently methylate inorganic arsenic to MMA and/or DMA. Rats and hamsters 

appear to methylate administered DMA into TMAO more efficiently than other species (NRC, 

1999; Yamauchi and Yamamura, 1984). About 40% of urinary arsenic was present as TMAO 1 

week after exposure to DMA in the drinking water, while 24% was present as TMAO after 7 

months of exposure (100 mg/L) in male rats (Yoshida et al., 1998). 

Humans (mainly exposed to background levels or exposed at work) have been estimated 

through a number of studies to excrete 10% to 30% of the arsenic in its inorganic form, 10% to 

20% as MMA, and 55% to 75% as DMA (see Vahter, 1999a, for a review). In contrast, a study 

of urinary arsenic metabolites in a population from northern Argentina exposed to arsenic via 

drinking water demonstrated an average of only 2% MMA in the urine (Vahter et al., 1995b; 

Concha et al., 1998b). This may indicate variations in methylation activity depending on the 

route of exposure, level of exposure, and possible nutritional or genetic factors. Although 

humans are considered efficient at arsenic methylation, they are less efficient than many animal 

models, as indicated by the larger proportion of MMAV excreted in the urine (Vahter, 1999a). 

This is important because it may explain why humans are more susceptible to cancer from 

arsenic exposures, and why no adult animal model for inorganic-arsenic-induced cancers has yet 

been identified (Tseng et al., 2005). 

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The rabbit (Marafante et al., 1981; Vahter and Marafante, 1983; Maiorino and Aposhian, 

1985) and hamster (Charbonneau et al., 1980; Yamauchi and Yamamura, 1984; Marafante and 

Vahter, 1987) appear to be more comparable to humans with respect to arsenic methylation than 

other experimental animals (NRC, 1999). However, rabbits and hamsters, in general, excrete 

more DMA and less MMA than humans. In contrast, Flemish giant rabbits (De Kimpe et al., 

1996) excrete MMA in amounts similar to humans. Mice and dogs, efficient methylators of 

arsenic, excrete more than 80% of a single arsenic dose administered as DMA within a few days 

(Charbonneau et al., 1979; Vahter, 1981). Guinea pigs (Healy et al., 1997), marmoset monkeys 

(Vahter et al., 1982; Vahter and Marafante, 1985), and chimpanzees (Vahter et al., 1995a), on 

the other hand, do not appear to appreciably methylate inorganic arsenic. In addition, no 

methyltransferase activity was detected in these species (Zakharyan et al., 1995, 1996; Healy et 

al., 1997; Vahter, 1999a). Li et al. (2005) identified a frameshift mutation in the chimpanzee 

AS3MT gene that resulted in the production of an inactive truncated protein, possibly explaining 

the lack of methylation activity in that species. 

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AS3MT homolog proteins with five fully conserved cysteine residues have been 

observed in the genome of numerous species (Thomas et al., 2007). Chimpanzees were found to 

differ from other species studied in that their AS3MT protein was shorter and lacked the 5th 

cysteine (Thomas et al., 2007). Healy et al. (1999) identified marked variations in the activity of 

methyltransferases, while Vahter (1999b) characterized differences in methylation efficiency 

among different human populations. The observed variations in methyltransferase activity and 

methylation efficiency are probably the underlying reason for the cross-species variability in 

methylation ability, as all the species had ample arsenate reductase activity (Vahter, 1999a; 

NRC, 2001). 

Although arsenic methylation is generally believed to take place in order to enhance 

excretion, there are several species (guinea pigs, marmoset monkeys, and chimpanzees) that do 

not methylate arsenic, but still efficiently excrete it. In fact, these animals do not retain arsenic 

any longer than species that methylate arsenic (Cohen et al., 2006), indicating that factors other 

than methylation also affect arsenic excretion rates. Supporting this is the fact that inorganic 

arsenic is found in the urine of even the most efficient methylators (Vahter, 1994). 

3.3.4. Thioarsenical Metabolites 

In 2004, Hansen et al. reported the detection of unusual arsenic-containing metabolites in 

the urine of sheep exposed to arsenic-contaminated vegetation. The metabolite was tentatively 

identified as dimethylmonothioarsinic acid (DMMTAIII), a sulfur-containing derivative of 

DMAIII as shown in Figure 3-3. Because the exposed sheep consumed algae known to contain 

arsenosugars, some of which contain sulfur, the relevance of this finding to human exposures 

was not initially clear. Subsequently, Raml et al. (2006) detected the presence of DMMTAIII in 

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the urine of Japanese men, but again, consumption of arsenosugars was suspected as a source of 

the observed arsenic containing species. 

DMMTAIII

SH ─ AsIII ─ CH3

I 

CH3 

S

II 

 OH ─ AsV ─ CH3 

I 

CH3 

DMMTAV

Source: Hansen et al. (2004). 

Figure 3-3. Thioarsenical structures. 

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In experiments addressing this issue, Adair et al. (2007) and Naramandura et al. (2007) 

found substantial concentrations of thioarsenical metabolites in arsenic-exposed experimental 

animals. Adair et al. (2007) administered drinking water containing 100 ppm AsV or up to 200 

ppm DMAIII to female Fisher 344 rats for 14 days. During analysis of the urine (collected during 

the last 24 hours of exposure) for metabolites, they found high levels of DMMTAIII and 

trimethylarsine sulfide (another sulfur-containing metabolite) in the urine of rats treated with 

DMAIII. Lower levels of the sulfur-containing metabolites were detected in the urine of 

arsenate-treated animals. They proposed a mechanism whereby the reaction of DMAIII and 

DMAV with hydrogen sulfide resulted in the observed metabolites. 

Naranmandura et al. (2007) administered single doses of 5.0 mg/kg AsIII to Syrian 

hamsters and Wistar rats by gavage and measured the levels of sulfur-containing arsenic 

metabolites in urine. Both DMMTAIII and dimethylmonothioarsonic acid (DMMTAV) were 

found at appreciable levels in urine from hamsters, but only the latter metabolite was found in rat 

urine. A previously uncharacterized metabolite, monomethylmonothioarsonic acid, was also 

found in urine from both species. 

These studies suggest that the generation of sulfur-containing arsenic metabolites does 

not depend on exposures to arsenosugars, at least in rodents, but can occur during the 

metabolism of inorganic arsenic compounds. In 2007, Raml et al. presented evidence that this 

pathway was also significant in humans. DMMTAIII was detected in the urine of 44% (33 of 75) 

women exposed to inorganic arsenic-contaminated drinking water in Bangladesh. The 

metabolite was present in urine samples at concentrations between “trace” amounts and 24 μg/L, 

with total arsenic concentrations ranging from 8 to 1034 μg/L. It was suggested that 

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thioarsenical metabolites may have been present in urine from other epidemiological studies of 

arsenic-exposed populations, but may have not been detected due to analytical difficulties. 

3.4. ELIMINATION 

The major route of excretion for most arsenic compounds by humans is via the urine 

(Yamauchi and Yamamura 1979; Tam et al., 1979; Pomroy et al., 1980; Buchet et al., 1981). Six 

human subjects who ingested 0.01 μg of radio-labeled 74AsV excreted an average of 38% of the 

administered dose in the urine within 48 hours and 58% within 5 days (Tam et al., 1979). 

Inorganic arsenic elimination in humans has been observed to be triphasic, with first-order halflives for elimination of 1 hour, 30 hours, and 200 hours (Mealey et al., 1959 used AsIII; Pomroy 

et al., 1980 used AsV). 

As mentioned in the preceding section, MMA and DMA are important metabolites 

generated after exposure to inorganic As. These methylated metabolites are excreted in the 

urine faster than the inorganic As. In humans orally exposed to MMA or DMA in aqueous 

solution, about 78% of MMA and 75% of DMA were excreted in the urine within 4 days of 

ingestion (Buchet et al., 1981). In mice, the half-time of MMA and DMA excretion was found 

to be about 2 hours following iv administration (Hughes and Kenyon, 1998). 

Kenyon et al. (2008) administered 0, 0.5, 2, 10, or 50 ppm of arsenic as sodium arsenate 

to adult C57Bl/6 female mice in the drinking water for 12 weeks. The average daily intakes 

were estimated to be 0, 0.083, 0.35, 1.89, and 7.02 mg As/kg/day, respectively. Levels of 

MMAIII, DMAIII, DMAV, and TMAO in the urine collected at the end of treatment increased in a 

linear manner with dose, but AsV and MMAV did not. 

Rats excrete DMA slowly compared to other species (Vahter et al., 1984), even though 

they are efficient at methylating inorganic arsenic to DMA. The slow excretion is believed to be 

associated with retention of a significant portion of the DMA in erythrocytes (Odanaka et al., 

1980; Lerman and Clarkson, 1983; Vahter, 1983; Vahter et al., 1984). The biliary excretion of 

inorganic arsenic by rats is about 800 times greater than observed in dogs and 37 times that of 

rabbits, as proportion of administered dose. Hughes et al. (2005) found that in mice the level of 

MMAV excreted in the urine compared to the bile was related to dose, with fecal excretion 

increasing at higher doses. Cui et al. (2004a) also found that rat biliary excretion rates varied 

with dose, but found it was also related to route of administration and chemical form. After oral 

administration of inorganic arsenic (either form) to male Sprague-Dawley rats, MADG and 

DMAV (likely present due to dissociation of DMAG) were the predominant forms in the bile. 

MADG was found at a higher level after a higher (i.e., 100 ppm) dose, while DMAV was more 

prevalent at the lower dose (i.e., 10 ppm). Kala et al. (2000) found that the secretion of arsenic 

into the bile of rats was dependent on the multi-drug resistance-associated protein 2 transporter 

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(MPR2/cMOAT) and that GSH is necessary for the transport, as arsenic-glutathione complexes 

accounted for the majority of arsenic found in the bile. 

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Although absorbed arsenic is removed from the body mainly via the urine, small amounts 

of arsenic are excreted through other routes (e.g., skin, sweat, hair, breast milk). While arsenic 

has been detected at low levels in the breast milk of women in northwestern Argentina (i.e., 2 

μg/kg), breastfeeding was associated with lower concentrations of arsenic in the urine of 

newborn children (Concha et al., 1998c) than formula feeding, owing to the use of arsenic 

contaminated water in formula preparation. Parr et al. (1991) measured arsenic (as well as other 

elements) in the breast milk from three groups of mothers from four countries (Guatemala, 

Hungary, Nigeria, and the Philippines), and one to two groups from Sweden and Zaire. The 

breast milk was collected 3 months after birth. Levels of arsenic in the breast milk from women 

in the Philippines were higher than other regions with levels about 19 μg/kg. Women from 

Nigeria had levels similar to those observed by Concha et al. (1998c). Women from all the other 

areas measured had levels of 0.24 to 0.55 μg/kg. 

The average concentration of arsenic in sweat induced in a hot and humid environment 

was 1.5 μg/L, with an hourly loss rate of 2.1 μg (Vellar, 1969). Based on an average arsenic 

concentration in the skin of 0.18 mg/kg, Molin and Wester (1976) estimated that the daily loss of 

arsenic through desquamation was 0.1 to 0.2 μg in males with no known exposure to arsenic. 

3.5. PHYSIOLOGICALLY BASED TOXICOKINETIC MODELS 

Physiologically based pharmacokinetic (PBPK) models for inorganic arsenic are 

important for developing a biologically based dose-response (BBDR) model. The development 

of useful BBDR models has proved to be challenging because inorganic arsenic appears to 

mediate its toxicity through a range of metabolites, and their roles with regard to specific adverse 

effects are not clear (Clewell et al., 2007). 

A PBPK model for exposure to inorganic arsenic (orally, intravenously, and 

intratracheally) was developed in hamsters and rabbits by Mann et al. (1996a). The model 

includes tissue compartments for lung (nasopharynx, tracheobronchial, pulmonary), plasma, 

RBCs, liver, GI tract, skin, kidney, keratin, and combined other tissues. Oral absorption of AsIII, 

AsV, and DMA (pooled III and V oxidation states) was modeled as a first-order transport process 

directly from the GI contents into the liver. Distribution to tissues was diffusion-limited, with 

transfer rates estimated based upon literature values for capillary thickness and pore sizes for 

each tissue. Reductive metabolism of AsV to AsIII was modeled as a first-order process occurring 

in the plasma. Oxidative metabolism of AsIII to AsV was modeled as first-order processes in the 

plasma and kidneys. Methylation of inorganic arsenic species to MMA (pooled III and V 

oxidation states) and then to DMA were modeled as saturable Michaelis-Menten processes 

taking place in the liver. Urinary, biliary, and fecal excretion of AsIII, AsV, MMA, and DMA 

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also are modeled as first-order processes. Parameters for absorption, tissue partition, 

metabolism, and biliary excretion were estimated by fitting the model to literature data on the 

urinary and fecal excretion of total arsenic from rabbits and hamsters administered various 

arsenic compounds by iv, oral gavage, or intratracheal instillation (Charbonneau et al., 1980; 

Yamauchi and Yamamura, 1984; Marafante et al., 1985, 1987). The model was found to 

accurately simulate the excretion of arsenic metabolites in the urine of rabbits and hamsters and 

to produce reasonable fits to liver, kidney, and skin concentrations in rabbits and hamsters 

(Yamauchi and Yamamura, 1984; Marafante et al., 1985; Marafante and Vahter, 1987). 

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Mann et al. (1996b) extended their PBPK model for use in humans by adjusting 

physiological parameters (organ weights, blood flows) and re-estimating absorption and 

metabolic rate constants. The model was fit to literature data on the urinary excretion of total 

arsenic following a single oral dose of AsIII or AsV in human volunteers (Tam et al., 1979; 

Buchet et al., 1981). The extended human model was further tested against empirical data on the 

urinary excretion of the different metabolites of inorganic arsenic following oral intake of AsIII, 

intake of inorganic arsenic via drinking water, and occupational exposure to arsenic trioxide 

(ATO) (Harrington et al., 1978; Valentine et al., 1979; Buchet et al., 1981; Vahter et al., 1986). 

The model predicted a slight decrease (about 10%) in the percentage of DMA in urine with 

increasing single-dose exposure (highest dose of arsenic at 15 μg/kg of body weight), especially 

following exposure to AsIII, and an almost corresponding increase in the percentage of MMA. 

The model predicted that adults’ drinking water containing 50 ppb would excrete more arsenic in 

urine than an occupational inhalation exposure of 10 μg/m3 (Mann et al., 1996b). 

Yu (1999a,b) also developed a PBPK model for arsenic in humans that includes tissue 

compartments for lung, skin, fat, muscle, combined kidney and richly perfused tissues, liver, 

intestine, GI and stomach contents, and bile. Oral absorption of AsIII, AsV, and DMA (pooled III

and V oxidation states) was modeled as first-order transport from the GI contents into the 

intestinal tissue. Distribution to tissues was modeled as perfusion-limited. Reductive 

metabolism of AsV to AsIII was modeled as a first-order, GSH-dependent process taking place in 

the intestinal tissue, skin, liver, and kidney/rich tissues. Oxidative metabolism of AsIII to AsV

was not modeled. Methylation of inorganic arsenic species to MMA (pooled III and V oxidation 

states) and then to DMA was modeled as saturable Michaelis-Menten processes occurring in the 

liver and kidney. Urinary, biliary, and fecal excretion of AsIII, AsV, MMA, and DMA were 

modeled as first-order processes. Parameters for absorption, tissue partition, metabolism, and 

biliary excretion were estimated by fitting the model to literature data on tissue concentrations of 

total arsenic from a fatal human poisoning (Saady et al., 1989), and blood, urine, and fecal 

elimination of total arsenic following oral administration (Odanaka et al., 1980; Pomroy et al., 

1980). The model was not tested further against external data, and fits to the data sets used for 

parameter estimation were not provided. 

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Gentry et al. (2004) adapted the model proposed by Mann et al. (1996a) to different 

mouse strains by adjusting physiological parameters (organ weights and perfusion rates). The 

absorption, partition, and metabolic rate constants were re-estimated by fitting the model to 

literature data on urinary excretion of various arsenic species following iv administration of 

MMA to B6C3F1 mice (Hughes and Kenyon, 1998) or single oral administration of AsIII or AsV

to mice (Kenyon et al., 1997; Hughes et al., 1999). Additionally, the description of methylation 

in the model was refined to include the uncompetitive inhibition of the conversion of MMA to 

DMA by AsIII. The PBPK model was then validated using data from a single oral administration 

of AsV (Hughes et al., 1999) and a 26-week drinking water exposure of AsIII to C57Black mice 

(Moser et al., 2000). These data were found to adequately fit the model without further 

parameter adjustment. Ng et al. (1999) had found arsenic-induced tumors in C57Bl/6J mice, 

while numerous other mouse strains (Swiss CR:NIH[S], C57Bl/6p53[+/-], C57Bl/6p53[+/+], and 

Swiss CD-1) had not experienced a significant increase in arsenic-induced tumors. The Gentry 

et al. (2004) model was unable to explain the different outcomes in the mouse bioassay on the 

basis of predicted target organ doses. 

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The Mann et al. (1996a,b) and Gentry et al. (2004) models are well documented, were 

validated against external data, and appear to capture the salient features of arsenic 

toxicokinetics in rodents and humans. The information provided by these models may help 

explain the MOAs involved in carcinogenesis along with possible reasons that humans are 

apparently more susceptible to the carcinogenic effects of arsenic. 

Clewell et al. (2007) noted that the then-available PBPK models did not incorporate the 

most recent available information on arsenic methylation kinetics and suggested several steps for 

improving the PBPK models. El-Masri and Kenyon (2008) have developed a PBPK model 

incorporating some of the improvements suggested by Clewell et al. (2007) (although not the 

simulation of changes in gene expression). The model predicts the levels of inorganic arsenic 

and its metabolites in human tissues and urine following oral exposure of AsV, AsIII, and for oral 

exposure to organoarsenical pesticides. The model consists of interconnecting submodels for 

inorganic arsenic (AsIII and AsV), MMAV, and DMAV. Reduction of MMAV and DMAV to their 

trivalent forms is also modeled. The submodels include the GI tract (lumen and tissue), lung, 

liver, kidney, muscle, skin, heart, and brain, with reduction of MMAV and DMAV to their 

trivalent forms modeled as occurring in the lung, liver, and kidney. The model also incorporates 

the inhibitory effects of AsIII on the methylation of MMAIII to DMA and MMAIII on the 

methylation of AsIII to MMA into consideration, modeled as noncompetitive inhibition. This 

model differs from the other models described above because it provides an updated description 

of metabolism using recent biochemical data on the mechanism of arsenic methylation. In 

addition, it uses in vitro studies to estimate most of the model parameters (statistically 

optimizing those that are sensitive to urinary excretion levels to avoid problems with parameter 

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identifiability), and can predict the formation and excretion of trivalent methylated arsenicals. 

The partition coefficients estimated in the model are comparable to those developed by Yu 

(1999a). The performance of the model was tested against limited human data on urinary 

excretion; the model needs to be evaluated for its ability to predict the tissue and urinary 

concentrations of arsenicals in large numbers of subjects. This model is an improvement over 

previous models because it can quantitatively assess impacts of parameter variability arising 

from genetic polymorphism. 

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4. HAZARD IDENTIFICATION 

4.1. STUDIES IN HUMANS 

Numerous epidemiologic investigations have examined the association between 

waterborne arsenic exposure and cancer outcome. These epidemiologic investigations used 

many different study designs, each with their inherent limitations. Regardless of the study type, 

the majority of these investigations found some level of association between arsenic exposure 

and cancer outcome. This association is not new, since arsenic exposure has been linked with 

cancer as far back as 1887 when Hutchinson reported an unusual number of skin tumors in 

patients treated with arsenicals. Since 1887, the association between skin cancer and arsenic has 

been reported in a number of studies (Tseng et al., 1968; Tseng, 1977; Chen et al., 1985, 

1988a,b; Wu et al., 1989; Hinwood et al., 1999; NRC, 1999; Tsai et al., 1999; Karagas et al., 

2001; Knobeloch et al., 2006; Lamm et al., 2007). 

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The SAB Arsenic Review Panel provided comments on key scientific issues associated 

with arsenicals on cancer risk estimation in July 2007 (SAB, 2007). It was concluded that the 

Taiwanese database is still the most appropriate source for estimating bladder and lung cancer 

risk among humans (specifics provided in Section 5) because of: (1) the size and statistical 

stability of the database relative to other studies; (2) the reliability of the population and 

mortality counts; (3) the stability of residential patterns; and (4) the inclusion of long-term 

exposures. However, SAB also noted considerable limitations within this data set (EPA-SAB07-008, http://www.epa.gov/sab). The Panel suggested that one way to mitigate the limitations 

of the Taiwanese database would be to include other relevant epidemiological studies from 

various countries. For example, SAB referenced other databases that contained studies of 

populations also exposed to high levels of arsenic (e.g., Argentina and Chile), and recommended 

that these alternate sources of data be used to compare the unit risks at the higher exposure levels 

that have emerged from the Taiwan data. SAB also suggested that, along with the Taiwan data, 

published epidemiology studies from the United States and other countries where the population 

is chronically exposed to low levels of arsenic in drinking water (0.5 to 160 ppb) be critically 

evaluated, using a uniform set of criteria presented in a narrative and tabular format. The 

relative strengths and weaknesses of each study should be described in relation to each criterion. 

 The caveats and assumptions used should be presented so that they are apparent to anyone who 

uses these data. The risk assessment background document should be a complete and transparent 

treatment of variability within and among studies and how it affects risk estimates. Additionally, 

SAB (2007) recommended considering the following issues when reviewing “low-level” and 

“high-level” studies: (1) estimates of the level of exposure misclassification; (2) temporal 

variability in assigning past arsenic levels from recent measurements; (3) the extent of reliance 

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waterborne arsenic; (5) study response/participation rates; (6) estimates of exposure variability; 

(7) control selection methods in case-control studies; and (8) the resulting influence of these 

factors on the magnitude and statistical stability of cancer risk estimates. 

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In order to address these issues, this Toxicological Review provides a comprehensive 

review of the significant epidemiologic investigations in the literature from 1968 to 2007 with 

the focus on the more recent publications. The report includes data from all populations that 

have been examined in regards to cancer from arsenic exposure via drinking water. Earlier 

publications were reviewed and are included as needed to facilitate the understanding of results 

from certain study populations. As recommended by SAB, studies were presented in both a 

narrative (below) and tabular (Appendix B) format. Each publication was evaluated using a 

uniform set of criteria, including the study type, the size of the study population and control 

population, and the relative strengths and weaknesses of the study. While the information in the 

tables mirrors the information in the narrative, the narrative may provide additional important 

information concerning the investigation. The studies are presented by country of origin, then in 

chronological order by publication year. In order to facilitate comparisons across the 

epidemiological studies, the arsenic concentrations pertaining to water exposure levels have been 

converted from milligrams (mg) per liter (or ppm) to parts per billion (ppb). This was not 

applied when discussing animal or in vitro MOA studies because a wide range of concentrations 

was employed; converting the arsenic levels or doses into ppb would not be reader-friendly. 

4.1.1. Taiwan 

More than 80 years ago (between 1910 and 1920), parts of southwestern Taiwan began 

using artesian (ground water) wells to increase water supplies and decrease the salt content of 

their drinking water. Some of these artesian wells were discovered to be contaminated with 

naturally occurring arsenic, thus resulting in widespread arsenic exposure. As a result, the 

Taiwanese population has been extensively studied. Due to the high arsenic content in the 

artesian wells, water was piped into certain areas in Taiwan from the reservoir of the Chia-Nan 

irrigation system in 1956. This water was reported to contain 10 ppb of arsenic (Tseng, 1977). 

Almost 75% of the residences had tap water by the 1970s; however, a survey in 1988 noted that 

artesian well water was still used for drinking, aquaculture, and agriculture in 1988, especially 

during the dry season (Wu et al., 1989). 

 Tseng et al. (1968) conducted a general survey using an ecological study design of 

40,421 inhabitants (21,152 females, 19,269 males) from the southwest coast of Taiwan in order 

to determine the potential relationship between skin cancer and chronic arsenicism. The arsenic 

content was measured in 142 samples from 114 wells (110 deep artesian and 4 shallow) and 

ranged from 10 to 1,820 ppb. The authors noted, however, that the arsenic content varied 

considerably over a 2-year period when measurements were taken. For example, in one well 

measurements were 528 ppb in July, 1962; 530 ppb in June, 1963; and 1190 ppb in February, 

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1964. These variations made dose-response relationships difficult to determine. Study subjects 

were categorized by arsenic exposure into three groups (low: 0–290 ppb, medium: 300–590 ppb, 

and high: 600 ppb or greater). The overall prevalence rate for skin cancer was 10.6 per 1,000. 

The male-to-female ratio was 2.9:1 for skin cancer. The prevalence rate increased steadily with 

age (recorded in 10-year increments), except for declining cancer prevalence rates for females 

older than 69 years. Age-specific (plotted in 20-year intervals) and sex-specific prevalence rates 

for skin cancer increased with arsenic concentration. The most common type of lesion was intraepidermal carcinoma (51.7%), and the body areas most frequently involved were unexposed 

surfaces (74.5%). In addition, an extremely high percentage of cases with multiple skin cancer 

(99.5%) was observed. The association between BFD and skin cancer was significantly higher 

than expected. Strengths of the Tseng et al. (1968) study include the large number of 

participants and the inclusion of dose-response information. Weaknesses include the lack of 

individual exposure data (ecological study design) and the potential for recall bias among study 

participants in determining the age of cancer onset and the length of residence in the area. In 

addition, changes in water supply over time were not noted, information on smoking history was 

not obtained, and the arsenic concentration from individual wells varied over time. 

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Tseng (1977) also used the general ecologic survey design discussed in Tseng et al. 

(1968) to report skin cancer incidence among the 40,421 individuals and to follow up on 1,108 

patients with BFD (identified between 1958 and 1975). By the end of the follow-up period, 528 

of the BFD patients had died. Tseng (1977) identified 428 cases (prevalence of 10.6/1,000) of 

skin cancer and 370 cases (prevalence of 9.0/1,000) of BFD, and analyzed the relationship 

between the two. Skin cancer and BFD occurred in 61 cases (1.51/1,000), but only 4 cases 

(0.09/1,000) were expected. The observed:expected ratio was 16.77. Tseng (1977) determined 

that the patients with BFD consumed artesian water before the onset of the disease, and none of 

the residents who had consumed only surface water or water from shallow wells developed BFD. 

 This finding illustrates that no cases were found among the inhabitants who were born after the 

tap water supply was introduced, and supports the close association between the consumption of 

arsenic contaminated water and the development of BFD. In addition, the study found that 

patients with skin cancer or BFD had a greater incidence of death due to cancers of various sites 

(28% and 19%, respectively) when compared to the general population of the endemic area 

(13%) or to the entire population of Taiwan (8%). 

Using similar arsenic exposure categories (low <300 ppb, medium 300–600 ppb, and 

high >600 ppb) from the Tseng et al. (1968) investigation, the skin cancer and the BFD 

prevalence rates showed an ascending gradient from low to high arsenic exposure for both sexes 

(Tseng, 1977). Skin cancer prevalence rates by age and arsenic exposure group were as follows: 

20–39 years (high exposure: 11.5; medium exposure 2.2; low exposure: 1.3); 40–59 years (high: 

72.0; medium: 32.6; low: 4.9); and 60+ years (high: 192.0; medium: 106.2; low: 27.1). BFD 

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prevalence rates by age and arsenic exposure group were as follows: 20–39 years (high: 14.2; 

medium: 13.2; low: 4.5); 40–59 years (high: 46.9; medium: 32.0; low: 10.5); 60+ years (high: 

61.4; medium: 32.2; low: 20.3). The common cause of death in the patients with skin cancer and 

BFD was carcinoma of various sites, including lung, bladder, liver, and kidney. The Tseng 

(1977) investigation observed that the prevalence of skin cancer increased steadily with age. It 

was difficult to obtain the age at onset of cancer from patient interviews, as most of the patients 

were unable to name a date. Strengths and weaknesses of this study are the same as Tseng et al. 

(1968); however, this study also included adjusted analysis for age and gender. 

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The objective of the Chen et al. (1985) ecological study was to evaluate the possible 

association between exposure to elevated levels of arsenic from artesian well water and cancer in 

the BFD-endemic area of southwestern Taiwan (i.e., Peimen, Hsuechia, Putai, and Ichu 

townships). The population of the BFD-endemic area in 1982 was 120,607 and consisted 

primarily of individuals engaged in farming, fishing, and salt production operations. The 

educational and socioeconomic status of the BFD-endemic area was below average for Taiwan. 

Chen et al. (1985) cited arsenic measurements from 83,565 wells across Taiwan taken by Lo et 

al. (1977), which showed that 29.1% of the wells in the study area had concentrations greater 

than 50 ppb (with the highest concentration measuring 2500 ppb), while only 5.7% of wells in 

other areas of Taiwan exceeded 50 ppb. A previous study by Chen et al. (1962) demonstrated a 

range of 350 to 1,140 ppb, with a median of 780 ppb arsenic content in Taiwanese artesian wells 

in BFD-endemic areas. As compared with the general population in Taiwan, both the 

standardized mortality ratio (SMR) and cumulative mortality rate were significantly higher in 

BFD-endemic areas. SMRs for males were significant for bladder (11.00, 95% confidence 

interval [CI]: 9.33–12.87), kidney (7.72, 95% CI: 5.37–10.07), skin (5.34, 95% CI: 3.79–8.89), 

lung (3.20, 95% CI: 2.86–3.54), liver (1.70, 95% CI: 1.51–1.89), and colon (1.80, 95% CI: 1.17–

2.03) cancers. SMRs for females also were significantly increased for bladder (20.09, 95% CI: 

17.02–23.16), kidney (11.19, 95% CI: 8.38–14.00), skin (6.52, 95% CI: 4.69–8.35), lung (4.13, 

3.60–4.66), liver (2.29, 95% CI: 1.92–2.66), and colon (1.68, 95% 1.26–2.10) cancers. Cancer 

SMRs were greater in villages that used only artesian wells as the drinking water source, as 

compared to villages that used both artesian and shallow wells. Villages and townships using 

only shallow wells generally had the lowest SMRs. Strengths of the investigation include the 

use of general population of Taiwan and world population for determining SMRs and potential 

confounders of age and gender were controlled for in the analysis. Weaknesses were that arsenic 

measurements were not linked to cancer mortality, death certificates list the main cause of death 

(Yang et al., 2005) rather than all causes, and SMRs were only presented by township and by 

well type. 

To evaluate the association between high arsenic exposure from artesian well water and 

cancer mortality in the BFD-endemic area of the southwest coast of Taiwan (i.e., the Peimen, 

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Hsuechia, Putai, and Ichu townships), Chen et al. (1986) used a case-control study design to 

evaluate 69 bladder cancer, 76 lung cancer, and 65 liver cancer deceased cases and 368 alive 

community controls matched on age and gender. The study area was the same one Chen et al. 

had used in 1985. Cases were selected from the Republic of China’s National Health 

Department between January 1980 and December 1982. The age distribution for cases was 

significantly lower than the controls. Similar gender distributions were observed for bladder and 

lung cancer cases and controls, though there was a slightly higher proportion of males in liver 

cancer cases than in controls. Other sociodemographic factors (marital status, education, 

occupation, and resident years) were comparable between cases and controls. Age and gender 

differences were adjusted for in the analysis. The artesian well water arsenic content from the 

BFD-endemic area ranged from 350 to 1,140 ppb (median 780 ppb), and the shallow well water 

arsenic concentration ranged from below detection limits to 300 ppb (median 40 ppb). A 

positive dose-response relationship was observed between the exposure to artesian well water 

and cancers of bladder, lung, and liver. The age-gender-adjusted odds ratios (ORs) of bladder, 

lung, and liver cancers for those who had used artesian well water for 40 or more years were 

3.90, 3.39, and 2.67, respectively, when compared with those who never used artesian well 

water. Regression analyses examined the associations between exposure to artesian well water 

and bladder, lung, and liver cancers after adjusting for other variables including age, gender, and 

cigarette smoking. Results showed a statistically significant association between exposure to 

artesian well water and bladder and lung cancers (p < 0.01) when other variables were 

controlled, but the association between the exposure to artesian well water and liver cancer was 

not statistically significant (p < 0.05). (The text of the article specifies that liver cancers are not 

significantly associated with arsenic, but the table that the text refers to illustrates a significant 

association.) Strengths of the Chen et al. (1986) study include that most cases were confirmed 

using histology or cytology findings, cancer cases and controls were from the same BFD 

community, and potential confounders were adjusted for in the analysis (i.e., age, gender, 

smoking, tea consumption, vegetable consumption, and fermented bean consumption). 

Weaknesses include selection bias (control selection) and not controlling recall bias for the 

following confounders: lifestyle, diet, daily water consumption, and source of water. 

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In a cohort study conducted by Chen et al. (1988a), cancer mortality associated with BFD 

was analyzed in area residents (i.e., Peimen, Hsuechia, Putai, and Ichu townships, Taiwan) from 

1973 to 1986. Arsenic levels in drinking water were measured between 1962 and 1964; these 

levels were used to divide the study population into three groups: <300 ppb; 300–599 ppb; and 

>600 ppb. Sociodemographic characteristics including lifestyle, diet, and living conditions were 

comparable among study participants. Between 1974 and 1976, water from more than 83,000 

wells in 313 villages throughout Taiwan was reanalyzed for arsenic content. The levels of 

arsenic in the drinking water were consistent between the two measurement periods. Death 

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certificates (n = 1031) were obtained from Taiwanese health care registration offices. Ageadjusted cancer mortality rates were calculated using the 1976 world population as the standard. 

Significantly elevated dose-response cancer mortality was observed among residents of the BFD 

area (<300 ppb, SMR female=118.8, male=154.0; 300–599 ppb SMR female=182.6, 

male=258.9; >600 ppb SMR female=369.1, male=434.7) as compared to the general population 

of Taiwan (SMR female=85.5, male=128.1). For both genders, significantly elevated doseresponse mortality also was observed for cancers of the liver, lung, skin, bladder, and kidney in 

comparison to the general population of Taiwan. A strength of the study is that data from 

arsenic monitoring conducted in 1962–64 and 1974–76 revealed similar results. A weakness of 

the study is that arsenic exposure levels are not individualized. 

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The objective of the Chen et al. (1988b) cohort (nested case-control) study was to 

examine multiple risk factors and their correlation to malignant neoplasms related to BFD. A 

total of 241 BFD cases, including 169 with spontaneous or surgical amputations of affected 

extremities and 759 age-sex-residence-matched healthy community controls, were identified and 

studied in the Peimen, Hsuechia, Putai, and Ichu townships of southwest Taiwan. Multiple 

logistic regression analysis showed that artesian well water consumption, arsenic poisoning, 

familial history of BFD, and undernourishment were significantly associated with the 

development of BFD. In a nonconcurrent cohort, cancer mortality of 789 BFD patients followed 

for 15 years also was examined using a life table. Results showed a significantly higher 

mortality from cancers of the bladder (SMR=38.80, p < 0.001), skin (SMR=28.46, p < 0.01), 

lung (SMR=10.49, p < 0.001), liver (SMR=4.66, p < 0.001), and colon (SMR=3.81, p < 0.05) as 

compared with the general population in Taiwan. When non-BFD residents in the BFD-endemic 

area were used as controls, significant differences in mortality rates were found for cancers of 

the bladder (SMR=2.55, p < 0.01), skin (SMR=4.51, p < 0.05), lung (SMR=2.84, p < 0.01), and 

liver (SMR=2.48, p < 0.01). The results strongly suggest carcinogenic effects from the artesian 

well water in the BFD-endemic area. Study strengths include minimizing recall bias through 

interview techniques, which identified the education, hours of occupational sunshine exposure, 

artesian well use, family medical history, history of smoking and alcohol use, and frequency of 

categories of food consumption. SMRs were calculated using both the national Taiwanese 

population and the local endemic area population, and BFD cases were matched to healthy 

community controls for age, sex, and residence. A weakness of the study was not providing the 

individual arsenic dose levels. 

Chiang et al. (1988) conducted a case-control prevalence study of bladder cancer in the 

BFD-endemic and surrounding areas of the southwestern coast of Taiwan. Four groups (cases: 

246 BFD patients; controls: 444 residents of the BFD-endemic area, 286 residents of the region 

neighboring the endemic area, and 731 residents of the non-endemic area) were screened using a 

detailed questionnaire and urinalysis. Three hundred and four subjects received urinary cytology 

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examinations. The study revealed no difference in the prevalence of bladder cancer between the 

BFD patients and non-BFD controls in the BFD-endemic area, indicating that individuals in the 

BFD-endemic area were equally affected by a high prevalence of bladder cancer. A high 

prevalence of bladder cancer in the BFD-endemic area was noted when compared with the 

neighboring region and residents of the non-endemic area. However, sporadic cases of bladder 

cancer were noted in the region neighboring the endemic area. This study also found that the 

non-BFD-endemic areas, which had a high arsenic content in the well water, did not have a high 

prevalence of bladder cancer, indicating other possible environmental factors. The histological 

confirmation of bladder cancer diagnoses is a strength of the study; however, the lack of 

individual arsenic exposure data is a limitation. 

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Wu et al. (1989) analyzed age-adjusted mortality rates using an ecological study design 

to determine whether a dose-response relationship exists between ingested arsenic levels and the 

risk of cancer among residents in the BFD endemic area. The study population consisted of a 

cohort of individuals from the southwestern coast of Taiwan (27 villages from the townships of 

Peimen, Hsuechia, Putai, and Ichu and 15 villages from the townships of Yensui and Hsiaying). 

The arsenic levels in well water for the 42 villages were determined from 1964 to 1966, while 

mortality and population data were obtained for the years of 1973 to 1986 from the local 

registration offices and from the Taiwan Provincial Department of Health. Age-adjusted 

mortality rates from various cancers by gender were calculated using the 1976 world population 

as the standard population. A significant dose-response relationship was observed between 

arsenic levels in well water and bladder, kidney, skin, and lung cancers in both males and 

females. A similar relationship was observed for prostate and liver cancers in males. There was 

no association for leukemia or cancers of the nasopharynx, esophagus, stomach, colon, and 

uterine cervix. Strengths of the study include the fact that adjustments were made for age and 

gender, and that lifestyle, access to medical care, and socioeconomic status were similar among 

the study groups. The use of mortality data can be considered a weakness of the study, since 

death certificates may not list all cancers. Additionally, associations observed at the local level 

may not be accurate at the individual level. 

The Chen and Wang (1990) ecological study was carried out to examine correlations 

between the arsenic level in well water and mortality from various malignant neoplasms in 314 

precincts and townships of Taiwan. The arsenic content of water from 83,656 wells was 

available from measurements taken in 1974 through 1976. Mortality rates from 1972 to 1983 

were derived from residents in study precincts and townships who displayed one or more of the 

21 examined malignant neoplasms. Arsenic content in the water was available at the precinct or 

township level. A statistically significant association with the arsenic level in well water was 

observed for cancers of the liver, nasal cavity, lung, skin, bladder, and kidney in both males and 

females, as well as for prostate cancer in males. These associations remained significant after 

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adjusting for indices of urbanization and industrialization through multiple regression analyses. 

No significant association was identified for the other 14 cancers examined. The multivariateadjusted regression coefficient showed an increase in age-adjusted mortality for cancers in males 

and females for every 100 ppb increase in arsenic level in well water. Coefficients for males and 

females, respectively, were as follows: 6.8 and 2.0 (liver), 0.7 and 0.4 (nasal cavity), 5.3 and 5.3 

(lung), 0.9 and 1.0 (skin), 3.9 and 4.2 (bladder), and 1.1 and 1.7 (kidney). Results were 

unchanged when 170 southwestern townships were included. Strengths of the study were that 

potential confounders (including socioeconomic differences, i.e., urbanization and 

industrialization) were controlled for, the study reported ecological correlations between arsenic 

content in well water and mortality from various cancers, and cancer rates in endemic BFD 

townships were compared with cancer rates in non-endemic townships of Taiwan. Potential 

confounders not controlled for were gender, other potential well water exposure contaminants, 

and individual arsenic exposures that were not available. 

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Using an ecologic investigation, Chen et al. (1992) showed a comparable excess risk of 

cancer of liver, lung, bladder, and kidney cancers induced by arsenic in drinking water. The 

study area and population were previously described by Wu et al. (1989). In order to compare 

the risk of developing various cancers as the result of ingesting inorganic arsenic and to assess 

the differences in risk between males and females, cancer potency indices were calculated with 

the Armitage-Doll multistage model using mortality rates among residents of 42 villages in six 

townships (Peimen, Hsuechia, Putai, Ichu, Yensui, and Hsiaying) located on the southwest coast 

of Taiwan. Locations selected were considered to be chronic arsenicism endemic areas. Arsenic 

exposure levels from drinking water in these villages were categorized into four groups: <100 

ppb (13 villages), 100–299 ppb (8 villages), 300–599 ppb (15 villages), and 600 ppb or greater 

(6 villages). Based on a total of 898,806 person-years during the study period from 1973 

through 1986, a significant dose-response relationship was observed between the arsenic level in 

drinking water and cancer mortality of the liver, lung, bladder, and kidney. The lifetime risk 

(determined using the Armitage-Doll model) of developing cancer due to an intake of 10 μg/kgday of arsenic was estimated to be 4.3 × 10-3 (liver), 1.2 × 10-2 (lung), 1.2 × 10-2 (bladder), and 

4.2 × 10-3 (kidney) for males and 3.6 × 10-3 (liver), 1.3 × 10-2 (lung), 1.7 × 10-2 (bladder), and 

4.8 × 10-3 (kidney) for females. Strengths include that potential confounders including age, 

gender, access to medical care, socioeconomic status, and lifestyle were all controlled for during 

the analysis, and that villages shared similar socioeconomic status, living environments, 

lifestyles, dietary patterns, and medical facilities. A weakness of the study is the assumption that 

an individual’s arsenic intake remained constant from birth to the end of the follow-up period; 

this flaw possibly led to the underestimation of risk. Additional weaknesses include that the 

Armitage-Doll model constrains risk estimates to be monotonically increasing function of age, 

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that dietary sources of arsenic were not quantified, and that age stratification was for under 30, 

over 70, and 20-year strata. 

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arsenic and cancer, Chiou et al. (1995) used a cohort study with a total of 263 BFD patients and 

2293 healthy residents in the arseniasis-endemic area of southwestern coast of Taiwan (Peimen, 

Hsuechia, Putai, and Ichu townships). Participants were followed for an average of 4.97 years 

(range: 0.05–7.69 years). Data concerning the consumption of artesian well water containing 

high levels of arsenic, sociodemographic characteristics, lifestyle and dietary habits, and cancer 

histories were obtained through a standardized interview. Internal cancers were determined via 

health examinations, personal interviews, household registration data checks, and Taiwan’s 

national death certification and cancer registry databases. Concentrations used in the assessment 

were ≤ 50 ppb, 50–70 ppb, 71+ ppb, and unknown. Disregarding the unknown category, a doseresponse relationship was observed between the long-term arsenic exposure from drinking 

artesian well water and the incidence of lung cancer, bladder cancer, and cancers of all sites 

combined after adjusting for age, sex, and cigarette smoking through a Cox’s proportional 

hazards regression analysis. BFD patients had a significantly increased incidence of bladder 

cancer and for all sites combined after adjusting for age, gender, smoking history, and 

cumulative arsenic exposure (CAE). Strengths include that the analysis adjusted for BFD status, 

age, gender, and smoking; incidence data were reported; and the results of the study showed a 

significant dose-response relationship. A weakness of the study is that well water artesian 

arsenic concentrations were unknown for some study subjects; consequently, this was a 

significant confounder. 

To further evaluate the association between arsenic exposure in drinking water and 

urinary cancers of various cell types, Guo et al. (1997) conducted an ecological study 

encompassing 243 townships using Taiwanese National Cancer Registry data of patients 

diagnosed with cancer between 1980 and 1987. Wells with known arsenic concentrations in 

each township were used to separate people into the following exposures: <50 ppb, 50–80 ppb, 

90–160 ppb, 170–320 ppb, 330–640 ppb, and >640 ppb. The effects of urbanization and 

smoking were evaluated by an urbanization index based on 19 socioeconomic factors shown to 

be good indicators of urbanization and the number of cigarettes sold per capita. For both 

genders, Guo et al. observed associations between high arsenic levels in drinking water and 

transitional cell carcinomas (bladder, kidney, ureter, and all urethral cancers combined). 

Positive associations between the proportion of wells with arsenic levels above 640 ppb and the 

incidence of transitional cell carcinomas of the bladder, kidney, ureter, and all urethral cancers 

combined in both genders were identified after the model was adjusted for urbanization and age. 

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squamous cell carcinomas of the bladder or renal cell carcinomas or nephroblastomas of the 

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kidney. Males also exhibited a positive association between the urbanization index and 

transitional cell carcinomas of the ureter. The results support the case that the carcinogenicity of 

arsenic may be cell-type specific. Analyses were adjusted for age, gender, urbanization, and 

smoking; however, the ecologic study design was a limitation. 

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Tsai et al. (1999) conducted a cross-sectional study in BFD-endemic areas in the 

southwest coastal region of Taiwan (Peimen, Hsuechia, Putai, and Ichu townships) to analyze 

mortality from neglected cancers related to artesian well water containing high levels of arsenic. 

 The median artesian well water arsenic content was 780 ppb (range: 250–1,140 ppb). Local 

endemic area residents’ daily ingestion of arsenic was estimated to be ≤ 1 mg. SMRs were 

calculated for cancer diseases, by gender, during the period from 1971 to 1994. These SMRs 

were compared to the local reference group (Chiayi–Tainan County population) and a national 

reference group (Taiwanese population). The comparisons revealed significant differences 

between SMRs of the three groups. Mortality increases (p < 0.05) were found in males and 

females, respectively, for all cancers (SMR=2.19, 95% CI: 2.11–2.28; SMR=2.40, 95% CI: 

2.30–2.51) when compared to the local reference population. Additionally, the following other 

cancers showed mortality increases in males and females, respectively, when compared to the 

local reference population: bladder (SMR=8.92, 95% CI: 7.96–9.96; SMR=14.07, 95% CI: 

12.51–15.78); kidney (SMR=6.76, 95% CI: 5.46–8.27; SMR=8.89, 95% CI: 7.42–10.57); skin, 

lung, nasal-cavity, bone, and liver (SMR=1.83, 95% CI: 1.69–1.98; SMR=1.88, 95% CI: 1.64–

2.14); and larynx, stomach, colon, intestine, rectum, lymphoma, and prostate cancer in males 

only (SMR=2.52, 95% CI: 1.86–3.34). When compared to the national reference population, 

significantly increased (p < 0.05) mortality was found in males and females, respectively, for all 

cancers (SMR=1.94, 95% CI: 1.87–2.01; SMR=2.05, 95% CI: 1.96–2.14) and for the other 

following cancers: bladder (SMR=10.50, 95% CI: 9.37–11.73; SMR=17.65, 95% CI: 5.70–

19.79) and lung (SMR=2.64, 95% CI: 2.45–2.84; SMR=3.50, 95% CI: 3.19–3.84). The results 

of the Tsai et al. (1999) investigation indicate that the hazardous effect of arsenic may be 

systemic. Key strengths of the study are that the exposed group and local reference group had 

similar lifestyle factors; all cancers were pathologically confirmed; and the analysis controlled 

for gender. Weaknesses of the study are that death certificates indicated only one underlying 

cause of death (not multiple causes), resulting in possible distortion of association between 

exposure and disease; individual exposure data were not provided; and certain potential 

confounders were not controlled for (age, smoking history, alcohol consumption, and 

occupational exposures). 

The Morales et al. (2000) ecological investigation re-analyzed data originally reported by 

Chen et al. (1988a, 1992) and Wu et al. (1989) from 42 villages in the arseniasis-endemic region 

of southwestern Taiwan by considering the number of liver, lung, and bladder cancer deaths. 

Morales et al. (2000) used a generalized linear model (i.e., Poisson distribution) and the 

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multistage-Weibull models to determine lifetime cancer risk estimates. Liver, lung, and bladder 

cancer mortality data were collected from death certificates of residents in 42 villages during 

1973 through 1986. Drinking water samples had been collected from wells in the 42 villages 

between 1964 and 1966. SMRs were used to summarize the observed patterns of mortality in the 

collected data. Morales et al. (2000) selected two comparison populations (the Taiwanese 

population as a whole and a population from a southwestern region of Taiwan) to account for 

urban versus non-urban populations differences. Although a non-significant trend was observed 

in the combined cancer analyses with respect to age, there was no observed tendency in liver, 

lung, or bladder SMRs with respect to age. This suggests that there is no age dependency on the 

risk ratio. Liver cancer mortality was higher than expected, although there was no strong 

exposure-response relationship found. The Morales et al. (2000) investigation results showed 

that exposure-response assessments were highly dependent on the choice of the analysis model 

and whether or not a comparison population is used in the analysis. One possible explanation for 

this observation is the inherent uncertainty associated with the limitations of an ecological study 

design. Depending on the model used and the comparison population used in the analysis, the 

effective dose at the 1% level (ED01) estimates ranged from 21 to 633 ppb for male bladder 

cancer, and from 17 to 365 ppb for female bladder cancer. The lung cancer risk for males was 

found to be slightly higher than the bladder cancer risk, with ED01 estimates ranging from 10 to 

364 ppb. The risk for female cancer tended to be higher than that of males for each cancer type. 

For lung cancer, female ED01 estimates ranged from 8 to 396 ppb. 

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In summary, the Morales et al. (2000) analysis of the Taiwan data suggests that excessive 

cancer mortality may occur in many populations where the drinking water standard for arsenic is 

set at 50 ppb, the drinking water standard for arsenic in the United States at the time of 

publication. A strength of the study was that person-years at risk (PYR) were stratified by 5-

year age groups, gender, and median arsenic level for each village. Weaknesses include the 

ecological study design (i.e., there were no individual monitoring data and individual exposures 

were not available) and the fact that potential confounders such as smoking, dietary arsenic, and 

the use of bottled water (U.S. population) were not controlled for in the analysis. 

Between 1991 and 1994, Chiou et al. (2001) recruited a cohort of 8,102 residents aged 40 

years or older from four townships (18 villages) in northeastern Taiwan (4 villages in Chiaohsi, 7 

in Chuangwei, 3 in Wuchih, and 4 in Tungshan) and followed it until the end of 1996. The study 

examined the risk of transitional cell carcinoma in relation to ingested arsenic. The Chiou et al. 

(2001) findings were consistent with previously reported findings from the arsenic-endemic area 

of southwestern Taiwan. Based on the arsenic concentration in well water, each study subject’s 

individual exposure to inorganic arsenic was estimated. Information concerning the duration of 

consumption of the well water was obtained through standardized questionnaire interviews. 

Urinary tract cancers were identified by follow-up interviews, community hospital records, the 

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Taiwanese national death certification profile, and the cancer registry profile. A significantly 

increased incidence of urinary tract cancers for the study cohort was observed (standardized 

incidence ratio [SIR]=2.05; 95% CI: 1.22–3.24) when compared to the general population in 

Taiwan. In addition, a dose-response relationship was observed between the risk of cancers of 

the urinary organs, especially transitional cell carcinoma, and indices of arsenic exposure after 

adjusting for age, sex, and cigarette smoking. The relative risks (RR) of developing transitional 

cell carcinoma were 1.9, 8.2, and 15.3 for arsenic concentrations of 10.1–50.0 ppb, 50.1–

100.0 ppb, and >100.0 ppb, respectively, compared with the referent level of ≤ 10.0 ppb. No 

association was observed for the duration of well water drinking (<40 years compared to 

≥ 40 years). The findings of this study suggest that arsenic ingestion may increase the risk of 

urinary tract cancer at levels around 50 ppb. Strengths include adjustments for potential 

confounders (age, gender, smoking history), individual arsenic exposure estimates, and a doseresponse relationship even with the low levels of arsenic. Weaknesses include possible 

diagnostic bias as the result of medical data collection from various community hospitals and 

recall bias from self-reported information. The short duration of follow-up also is a limitation 

because it impacted: (1) the number of person-years of observation; and (2) only a few cases 

were recorded. This study also has an apparent supralinear curve, which is likely due to dose 

misclassification in the low-dose individuals. If food arsenic concentrations (estimated in NRC, 

2001, to be approximately 50 μg/day) were included, the curve might not be supralinear. 

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Guo et al. (2001) conducted an ecological investigation of the 243 townships from their 

1997 publication; however, this investigation focused on arsenic exposure through drinking 

water and the potential association with skin cancers. Data regarding arsenic levels in drinking 

water were available from the previous investigation, and cases of skin cancer were identified 

using the Taiwanese National Cancer Registry. Data were analyzed with regression models 

using multiple variables to describe exposures, including arsenic. To adjust for potential 

confounding variables, an urbanization index based on 19 socioeconomic factors shown to be 

good indicators of urbanization was developed. A total of 2,369 individuals with skin cancer 

(954 females and 1,415 males) were registered with the Cancer Registry between January 1980 

and December 1989. After age and urbanization adjustment, arsenic levels above 640 ppb 

showed a statistically significant (p < 0.01) association with the incidence of basal cell 

carcinoma (BCC) in males. Exposed females also exhibited an increased incidence in skin 

cancer rates; however, this increase did not reach statistical significance (p = 0.20). For 

squamous cell carcinomas (SCC), a significant (p < 0.01), positive association was found for 

males exposed to 170–320 ppb and >640 ppb. However, a statistically significant (p < 0.01) 

negative association was found for males exposed to 330–640 ppb. For females, a similar 

statistically significant (p < 0.01) positive association was observed at >640 ppb, while a 

statistically significant (p < 0.05) negative association was observed in 330–640 ppb females. 

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For melanomas, no significant associations were identified in females or males at any exposure. 

The results of the investigation suggest that skin cancers are cell-type-specific, as previously was 

demonstrated for urinary tract cancers (Guo et al., 1997). Strengths of the study include that 

cases were identified from a government operated National Cancer Registration Program, 

pathological classifications were determined by board-certified pathologists, and potential 

confounders (gender and age) were adjusted in the analysis. A limitation of the study is the 

ecological study design. 

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Studies on cancers of the urinary system and skin showed that arsenic’s carcinogenic 

effect was cell-type-specific (Guo et al., 1997, 2001). Guo (2003) conducted an ecological 

investigation in 243 townships in Taiwan, previously used in the Guo et al. (1997, 2001) 

investigations for urinary and skin cancers, to determine if a similar relationship could be 

identified for liver cancer. Many previous epidemiologic studies did not provide data on 

pathological diagnoses; therefore, there was no information to support the hypothesis that 

hepatocellular carcinoma (HCC) or cholangiocarcinoma of the liver were not associated with 

arsenic ingestion. Liver cancers were identified through the Taiwanese National Cancer 

Registry. The distribution of cancer cell-types between an arseniasis-endemic area and a 

township outside the arseniasis area were compared. Between January 1980 and December 

1999, 32,034 men and 8,798 women living in the study townships were diagnosed with liver 

cancer. The distribution of two cancer cell-types (HCC and cholangiocarcinoma) did not appear 

to be different between the arseniasis-endemic and non-arseniasis-endemic areas, and an 

association between HCC and arsenic ingestion was not observed. The remainder of the celltypes did not have enough cases to provide stable estimates. Identified strengths of the study 

include the following: cases were identified from the government-operated National Cancer 

Registration Program; pathological classifications were determined by board-certified 

pathologists; and analyses were adjusted for gender and age. Weaknesses include the limitations 

of ecological study design (no monitoring data were presented). 

A cohort investigation of residents from two arsenic endemic areas were followed for 8 

years by Chen et al. (2004a) to investigate the dose-response relationship between arsenic 

exposure and lung cancer, as well as how cigarette smoking influenced the relationship between 

arsenic and lung cancer. Arsenic-endemic areas included the southwestern coast (Peimen, 

Hsuechia, Putai, and Ichu; n = 2,503) and the northeastern coast (Tungshan, Chuangwei, 

Chiaohsi, and Wuchieh; n = 8,088) of Taiwan. The amount of arsenic in well water from these 

areas ranged from less than 0.15 ppb to more than 3,000 ppb. The Taiwanese National Cancer 

Registry was used to identify new cases of lung cancer diagnosed between January 1, 1985, and 

December 31, 2000. For each participant, follow-up person-years were calculated using the time 

from the initial interview date to the date of diagnosis, death, or December 31, 2000, whichever 

came first. Arsenic concentration was arbitrarily divided into five categories: <10 ppb (referent), 

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10–99.9 ppb, 100–299.9 ppb, 300–699.9 ppb, and ≥700 ppb. Smoking histories were obtained 

from interviews. Cox proportional hazards regression models were used to estimate RR and 

95% CI. The final model was adjusted for age, gender, years of schooling, study cohort (BFD 

cases and matched controls of the southwestern coast, residents along the arseniasishyperendemic southwestern coast villages, and residents living in the northeastern coastal 

Lanyang Basin), smoking status, and alcohol consumption. During the study follow-up period, 

there were 139 lung cancers diagnosed, resulting in an incidence rate of 165.9 per 100,000 

person-years. When the highest level of arsenic exposure was compared to the lowest, the RR 

was 3.29 (95% CI: 1.60–6.78). The risk of lung cancer was four times higher for past and 

current smokers compared to non-smokers. A synergistic effect of ingested arsenic and cigarette 

smoking on lung cancer was noted, with synergy indices ranging from 1.62 to 2.52. Strengths of 

the study include controlling for confounders (age, gender, education, smoking history, and 

alcohol consumption), having a long follow-up period, using a national computerized cancer 

case registry, and pathologically confirming all lung cancer cases. Weaknesses include the lack 

of historical monitoring data and possible misclassification bias (exposure measurements were 

based on one survey). 

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Chiu et al. (2004), using a cohort study design, examined whether liver cancer mortality 

rates were altered after the consumption of high-arsenic artesian well water ceased. SMRs for 

liver cancer were calculated for the BFD-endemic area of the southwest coast of Taiwan (i.e., 

Peimen, Hsuechia, Putai, and Ichu townships) for the years 1971 through 2000. Median well 

water arsenic concentrations in the early 1960s were 780 ppb. Temporal changes in the SMRs 

were monitored using cumulative-sum techniques and were reported for 3-year intervals between 

1971 and 2000. Study results showed that female mortality from liver cancer started declining 9 

years after consumption of high-arsenic artesian well water stopped. The SMR for liver cancer 

in females was 2.041 during the 1983–1985 period (peak) and was 1.137 during 1998 through 

2000. Data in males, however, showed fluctuations in liver cancer mortality rates. The SMR for 

liver cancer in males from 1989 to 1991 was 1.868 and 1.242 during 1998 to 2000. Based on 

analyses by Chiu et al. (2004), it was determined that the relationship between arsenic exposure 

and liver cancer mortality was possibly causal in females, but not in males. Strengths of the 

study are: (1) residents in the study area were similar in terms of socioeconomic status, living 

environments, lifestyles, dietary patterns, and availability of health service facilities; and (2) the 

study used an accurate death registration system. Weaknesses include the limitations of the 

mortality data. 

To obtain data on the potential dose-response relationship between lung cancer and the 

level of arsenic in drinking water, Guo (2004) conducted an ecological investigation in 10 

townships (138 villages) in Taiwan. Measurements of arsenic levels in drinking water were 

available for the 138 villages from a census survey conducted by the Taiwanese government. 

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Death certificates dated between January 1, 1971, and December 31, 1990, were reviewed, and 

673 males and 405 females were identified as dying from lung cancer. Multivariate regression 

models were applied to assess the relationship between arsenic levels in drinking water and lung 

cancer mortality. After adjusting for age, arsenic levels above 640 ppb were associated with a 

significant increase in lung cancer mortality for both genders; however, no significant effect was 

observed at lower arsenic exposure levels. Regression analyses and stratified analyses 

confirmed a dose-response relationship at >640 ppb. Guo (2004) noted that the results of this 

investigation show a carcinogenic effect of high arsenic levels in drinking water on the lung. 

Guo (2004), however, recommended that further studies with exposure data on individuals were 

warranted to confirm these findings. As a result of the study’s ecologic design, the association 

observed on an aggregate level may not necessarily represent the association that exists at an 

individual level. In addition, the study design may have contributed to biases introduced by the 

effects of population mobility. Strengths of the study include that analyses adjusted for gender 

and age, and cases were ascertained using information from household registry offices in each 

township. Weaknesses of the investigation include the inherent limitations of ecological studies 

and the fact that smoking was not controlled for in the analysis. 

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In a cross-sectional study, Yang et al. (2004) examined whether kidney cancer mortality 

decreased in the southwest coast of Taiwan (Peimen, Hsuechia, Puta, and Ichu townships) after 

the elimination of arsenic exposure in the 1970s. SMRs for kidney cancer were calculated for 

the BFD-endemic area for the years 1971 through 2000. There were 308 kidney cancer deaths 

(135 men and 173 women) in the BFD-endemic area between 1971 and 2000. The means of the 

3-year SMRs for female and male kidney cancer were significantly higher than for Taiwan as a 

whole. Time series plots for male SMRs showed decreasing mortality rates. The estimated 

slope for male SMRs (rate of decrease per year) in the linear time trend analysis was -15.13 

(p < 0.01). The time series plot for female SMRs also showed decreasing mortality rates. 

Kidney cancer mortality rates among residents in the BFD-endemic area decreased after removal 

of the arsenic source through tap water implementation. SMRs decreased each year, on average, 

from 1971 to 2000 (p < 0.01). Study strengths include the adjustment of potential confounders 

(gender and age); mandatory registering of all births, deaths, marriages, divorces, and migration 

issues with the Household Registration Office in Taiwan, making it an accurate data source; and 

a comparable study population (i.e., residents likely had similar socioeconomic status, living 

environments, lifestyles, dietary patterns; they worked in farming, fisheries, or salt production) 

that had comparable access to medical care (i.e., all kidney cancer cases likely had similar access 

to medical care). Weaknesses of the study include cross-sectional mortality limitations and not 

adequately controlling for smoking histories. 

Tsai et al. (2005) used a cross-sectional study to compare primary urethral carcinomas 

from the BFD-endemic area of Taiwan with those in the United States and explore the potential 

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influence of chronic arsenic exposure. Cases were identified by the only medical center near the 

BFD area. There were 21 pathologically proven primary urethral carcinomas diagnosed (7 

females and 14 males) between 1988 and 2001. Seven of 14 male patients had reported an 

average of 23 years of chronic arsenic exposure from drinking water. Tsai et al. (2005) 

compared these cases to cases identified in three U.S. cancer centers (MD Anderson, Memorial 

Sloan-Kettering, and Barbara Ann Karmanos; n = 79 females, n = 80 males), and analyzed for a 

relationship with chronic arsenic exposure. In comparison to the three U.S. cancer centers, there 

was a higher frequency of bulbomembranous adenocarcinoma (43% vs. 18%, 2%, and 0%, 

respectively, p < 0.0001). In those with chronic arsenic exposure, there was an even greater 

association with bulbomembranous adenocarcinoma compared to those without chronic arsenic 

exposure (73% vs. 14%, p=0.031). Based on these results, Tsai et al. (2005) concluded that the 

BFD-endemic area in Taiwan had a high frequency of bulbomembranous urethral 

adenocarcinoma, which may be associated with chronic arsenic exposure. A strength of the 

study is that cases were pathologically confirmed. The small number of cases and the lack of 

arsenic exposure information are study weaknesses. 

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The objective of the Yang et al. (2005) cross-sectional study was to determine whether 

bladder cancer mortality decreased after the implementation of the tap water system and the 

subsequent elimination of arsenic exposure. SMRs for bladder cancer were calculated for the 

BFD-endemic area for the years 1971–2000. The study showed that bladder cancer mortality 

decreased gradually after the instillation of the tap water system, thereby eliminating exposure to 

arsenic through artesian well water, (1971, male SMR=10.25, female SMR=14.89; 2000, male 

SMR=2.15, female SMR=7.63). Strengths include similar access to medical care for bladder 

cancer, the adjustment for age and gender, and the mandatory registering of all births, deaths, 

marriages, divorces, and migration issues to the Household Registration Office in Taiwan, 

making it an accurate data source. Limitations of the study include the cross-sectional mortality 

study design and smoking history confounding. 

4.1.2. Japan 

Tsuda et al. (1995) used a cohort study to investigate the long-term effect of ingesting 

arsenic in drinking water for an estimated exposure period of 5 years (1955–1959). Four 

hundred and fifty-four residents identified in 1959 as living in an arsenic-polluted area of Niigata 

Prefecture, Japan, were followed until 1992. The mortality of these residents between October 1, 

1959, and February 29, 1992, was examined using death certificates. These individuals used 

arsenic-contaminated well water, and none worked at a nearby factory that was the source of the 

water contamination. Death certificates for the people who died between 1959 and 1992 were 

examined and a total of 113 of the 454 residents were estimated to have consumed well water 

containing a high concentration of arsenic (≥1,000 ppb). The SMRs of these 113 residents were 

15.69 for lung cancer (95% CI: 7.38–31.02) and 31.18 for urinary tract cancer (95% CI: 8.62–

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91.75). Cox’s proportional hazard analyses demonstrated that the hazard ratios of the highest 

exposure level group (≥1,000 ppb) versus the background exposure level group (1.0 ppb) were 

1.74 (95% CI: 1.10–2.74) for all deaths, 1972.16 (95% CI: 4.34–895,385.11) for lung cancer, 

and 4.82 (95% CI: 2.09–11.14) for all cancers. The study also analyzed skin signs of chronic 

arsenicism, and results indicated that they were useful risk indicators for subsequent cancer 

development. These results indicate a relationship between well water arsenic exposure and lung 

and urinary tract cancers. The study also showed that arsenic-induced cancer could develop 

years following the end of arsenic exposure. For lung cancer, there was evidence of synergistic 

effects between arsenic exposure and smoking history. Strengths of this study include data on 

smoking history, age, and gender, and an examination of the cohort by three arsenic exposure 

categories. Weaknesses, however, include the lack of detailed arsenic intake information, a 

small study population, as well as possible misclassification and recall bias pertaining to 

smoking history. 

4.1.3. South America 

Hopenhayn-Rich et al. (1996a) used an ecological study design to investigate bladder 

cancer mortality for the years 1986 through 1991 in the province of Cordoba, Argentina, using 

rates for all of Argentina as the standard for comparison. The study compiled arsenic 

measurements from a major water survey performed more than 50 years earlier. Using these 

earlier arsenic data, a crude estimate of exposure was made. The data were matched to the 

population listings from the national census bureau. This study grouped counties into three 

defined arsenic exposure categories: low, medium, and high (groups were defined based on the 

location of counties and the concentrations were only provided for the high group, which had a 

mean arsenic level of 178 ppb). In the absence of smoking data for each county, mortality from 

chronic obstructive pulmonary disease (COPD) was used as a surrogate. SMRs for bladder 

cancer were higher in counties with known elevated levels of arsenic exposure through drinking 

water. The SMRs (95% CI) for corresponding arsenic exposure categories were 0.80 (0.66–

0.96), 1.42 (1.14–1.74), and 2.14 (1.78–2.53) for males, and 1.21 (0.85–1.64), 1.58 (1.01–2.35), 

and l.82 (1.19–2.64) for females, respectively. Significant trends were noted in both males and 

females. 

Results of this study showed a dose-response relationship between arsenic exposure from 

drinking water and bladder cancer in spite of the limitations inherent from the ecologic design. 

Argentina has one of the world’s highest rates of per capita beef consumption. The high-arsenic 

region of Cordoba is an important agricultural and beef-producing area, and animal protein is 

considered to be one of the basic foods of the population. This is important because protein 

deficiency in the Taiwanese population has been suggested to diminish their capacity to detoxify 

arsenic. The similar findings between the two populations, regardless of genetic and dietary 

differences, strengthens the link between arsenic exposure and bladder cancer. Strengths of the 

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study include the adjustment for age and gender, the use of stomach cancer as a non-arsenicinduced comparison, and that the analysis was restricted to rural counties to limit confounders. 

The lack of individual smoking history (mortality from COPD was used as a surrogate for 

smoking), the lack of arsenic measurements in low and medium groups, and the lack of 

individual arsenic exposure data (ecological study) are important potential weaknesses of this 

study. 

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To investigate dose-response relationships between arsenic exposure from drinking water 

and cancer mortality, Hopenhayn-Rich et al. (1998) conducted an ecological study in Cordoba, 

Argentina. Cancer mortality from the lung, kidney, liver, and skin during the 1986–1991 period 

in 26 counties of Cordoba were studied. This investigation expanded the analysis of the authors’ 

previous study (Hopenhayn-Rich et al., 1996a), which only examined bladder cancer in Cordoba. 

 Counties were grouped into low, medium, and high arsenic exposure categories based on arsenic 

exposure data taken from Hopenhayn-Rich et al. (1996a). In the absence of smoking data for 

each county, mortality from COPD was used as a surrogate. SMRs were calculated using all of 

Argentina as the reference population. Hopenhayn-Rich et al. (1998) found increasing trends for 

kidney and lung cancer mortality with increasing arsenic exposure (i.e., low, medium, high) as 

follows: male kidney cancer SMRs=0.87 (95% CI: 0.66–1.10), 1.33 (95% CI: 1.02–1.68), and 

1.57 (95% CI:1.17–2.04); female kidney cancer SMRs=1.00 (95% CI: 0.71–1.37), 1.36 (95% CI: 

0.94–1.89), and 1.81 (95% CI: 1.19–2.64); male lung cancer SMRs=0.92 (95% CI: 0.85–0.98), 

1.54 (95% CI: 1.44–1.64), and 1.77 (95% CI: 1.63–1.90); and female lung cancer SMRs=1.24 

(95% CI: 1.06–1.42), 1.34 (95% CI: 1.12–1.58), and 2.16 (95% CI: 1.83–2.52), respectively 

(p < 0.001 in trend test). These findings were similar to the previously reported bladder cancer 

results. Additionally, the Hopenhayn-Rich et al. (1998) study showed a weakly positive trend 

for liver cancer, with SMRs being significantly increased even in the lowest exposure category. 

Skin cancer mortality was elevated only for females in the highest arsenic exposure group, while 

males showed an increase in mortality only in the lowest exposure group. The results add to the 

evidence that arsenic ingestion through drinking water increases the risk of lung and kidney 

cancers. The association between arsenic and mortality from liver and skin cancers was not as 

clear. Risk analyses were restricted to rural Cordoba counties to limit confounders and to 

account for cancer diagnosis and detection bias. Strengths and weaknesses are the same as those 

observed for Hopenhayn-Rich et al. (1996a). 

Smith et al. (1998), using an ecological design, studied cancer mortality in a population 

of approximately 400,000 people exposed to high arsenic levels in drinking water in past years in 

Region II of northern Chile. Arsenic concentrations in drinking water from 1950 to 1996 were 

available. The population-weighted average arsenic levels reached 570 ppb between 1955 and 

1969, but decreased to less than 100 ppb by 1980. SMRs were calculated for the years 1989 to 

1993, and increased SMRs were identified for bladder, kidney, lung, and skin cancers. Bladder 

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cancer mortality was the most elevated (female SMR=8.2, 95% CI: 6.3–10.5; male SMR=6.0, 

95% CI: 4.8–7.4). Lung cancer mortality was likewise significantly elevated (female SMR=3.1, 

95% CI: 2.7–3.7; male SMR=3.8, 95% CI: 3.5–4.1). Smoking survey data and mortality rates 

from COPD provided evidence that smoking did not contribute to the increased mortality from 

these cancers. These results provide additional evidence that ingestion of inorganic arsenic in 

drinking water can lead to increases in cancers of the bladder and lung. Smith et al. (1998) 

estimated that approximately 7% of all deaths in individuals more than 30 years old might be 

attributable to arsenic exposure. Strengths of the study are the large size of the study population, 

the adjustment of SMRs by age and gender, and the use of Chilean national data for comparison. 

 Weaknesses include that arsenic levels were not available at the individual source level, doseresponse information was not provided, and only limited individual smoking history information 

was available (i.e., participants were asked if they had smoked cigarettes over a 1-month period 

in 1990). 

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In a case-control study, Ferreccio et al. (2000) investigated the association between lung 

cancer and arsenic in drinking water by comparing patients diagnosed with lung cancer (1994–

1996; 152 cases) with frequency-matched hospital controls (419 controls). Using a full-logistic 

regression model, a clear trend in lung cancer ORs was observed with increasing concentration 

of arsenic in drinking water: 10–29 ppb arsenic, OR: 1.6 (95% CI: 0.5–5.3), 30–49 ppb arsenic, 

OR: 3.9 (95% CI:1.2–12.3), 50–199 ppb arsenic, OR: 5.2 (95% CI: 2.3–11.7), and 200–400 ppb, 

OR: 8.9 (95% CI: 4.0–19.6). Evidence of synergistic effects between arsenic in drinking water 

and cigarette smoking history was much greater than expected, as the OR for lung cancer was 

32.0 (95% CI: 7.2–198.0) among smokers exposed to more than 200 ppb. In comparison, an OR 

of 8.0 was observed for those who never smoked but were in the highest arsenic category, and an 

OR of 6.1 was observed for smokers in the lowest arsenic category. Based on these results, the 

effect was considered synergistic because an OR of 13.1 was expected if the effect was additive. 

 This study provided strong evidence that ingestion of inorganic arsenic through drinking water 

is associated with lung cancer. ORs for the full-analysis model were adjusted for age, gender, 

cumulative lifetime cigarette smoking, working in copper smelting, and socioeconomic status; 

this is considered a study strength. The fact that more controls were obtained from Antofagasta 

than from the lower-exposure cities of Arica and Iquique, which could lead to an improper 

(lower) estimation of risk, is considered a study limitation. 

Bates et al. (2004) recognized that epidemiologic studies had found an association 

between increased bladder cancer risk and high levels of arsenic in drinking water; however, 

little information was found concerning cancer risks at lower concentrations. It also was 

recognized that ecologic studies in Argentina had found increased bladder cancer mortality in 

Cordoba Province, where some wells were contaminated with moderate arsenic concentrations. 

Therefore, Bates et al. (2004) decided to use a population-based bladder cancer case-control 

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study during 1996–2000 in two Cordoba counties and recruited 114 case-control pairs, matched 

by age, sex, and county of residence over the past 40 years. Three arsenic exposure metrics 

based on questionnaire and water sampling data were used: average arsenic concentration in 

domestic water, arsenic concentration adjusted to fluid intake, and reported years of well water 

consumption. Statistical analyses showed no evidence of an association of bladder cancer with 

arsenic exposure estimates based on arsenic concentrations in drinking water. Additional timetrend analyses, however, did suggest that the use of arsenic-contaminated well water at least 50 

years prior to the study was associated with increased bladder cancer risk. This positive 

association was limited to people who had ever smoked (OR=2.5, 95% CI: 1.1–5.5 for the time 

period 51–70 years before the study interview). Bates et al. (2004) suggested that it could not be 

excluded that these associations were based on chance. 

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The results of this study suggest a decreased bladder cancer risk for arsenic exposure than 

had been predicted from other studies. The results of the Bates et al. (2004) study did add to the 

evidence that the latency for arsenic-induced bladder cancers may be longer than previously 

thought and that increased lengths of follow-up for studies may be required to accurately 

measure the induced risk. Strengths include that potential confounders (age, gender, smoking 

history, and residence county) were controlled for in the analysis. However, weaknesses related 

to the lack of a cancer registry, arsenic exposure misclassification, and recall and selection bias 

exist. Selection bias may have occurred, as the controls had a significantly lower rate of 

participation than cases. Additional selection bias may have occurred with the selection of cases 

from the tumor registry. An additional weakness is that other harmful exposures (including 

arsenic exposure through food) were not measured. 

Using a cohort study design, Smith et al. (2006) investigated lung cancer, bronchiectasis, 

and COPD mortality rates in Antofagasta, Chile, from 1989 through 2000 and compared these 

rates to the rest of Chile. Study subjects (30–49 years old at time of death) were selected 

primarily from those born during or just prior to the peak in the arsenic exposure period. Results 

show a lung cancer SMR of 7.0 (95% CI: 5.4–8.9, p < 0.001) for the cohort born just before the 

peak exposure period (i.e., from 1950 through 1957), and, therefore, were exposed to arsenic 

during their childhood. For those cases born between 1958 and 1971 (i.e., the high-exposure 

period), a lung cancer SMR of 6.1 (95% CI: 3.5–9.9, p < 0.001) was estimated; this group was 

probable exposed to arsenic in utero and early childhood. These findings suggest that exposure 

to arsenic in drinking water during early childhood or in utero has pronounced pulmonary effects 

greatly increasing subsequent mortality in young adults from malignant lung disease. The study 

concluded that the observed effects are most probably due to arsenic in water, even though 

possible effect-dilution occurred as the result of in-migration of those from other regions of 

Chile. A strength of the study was the extensive documentation of drinking water arsenic levels 

in the Antofagasta water system. Weaknesses include that place of residence was determined 

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from the death certificates, which relates to residence at the time of death, and the reliance on 

death certificates (potential diagnostic bias). Smoking, although considered unlikely by Smith et 

al. (2006), is a potential confounder for this study. 

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Marshall et al. (2007) conducted an ecological study to investigate lung and bladder 

cancer mortality from 1950 to 2000 in a region of Chile where drinking water was contaminated 

with arsenic (Region II), and in another region of Chile where arsenic was not an issue (Region 

V). Elevated arsenic exposure through drinking water began in Region II in 1958 and continued 

into the early 1970s. Mortality data tapes and mortality data from death certificates for the two 

regions for 1950 to 1970 identified 307,541 deaths from the two regions for 1971 to 2000. 

Poisson regression models were used to compare Region II with Region V by identifying time 

trends in rate ratios of mortality from lung and bladder cancers. Lung and bladder cancer 

mortality rate ratios for Region II compared with Region V began to increase approximately 10 

years after high arsenic exposures commenced and continued to rise, peaking between 1986 and 

1997. The peak lung cancer mortality rate ratios for women and men were 3.26 (95% CI: 2.50–

4.23) and 3.61 (95% CI: 3.13–4.16), respectively. The peak bladder cancer rate ratios for 

women and men were 13.8 (95% CI: 7.74–24.5) and 6.10 (95% CI: 3.97–9.39), respectively. 

Together, lung and bladder cancer mortality rates in Region II were highest from 1992 to 1994, 

with mortality rates of 50/100,000 for women and 153/100,000 for men compared with 

19/100,000 and 54/100,000, respectively, in Region V. The long latency for lung and bladder 

cancer mortality continued to have a residual effect through the late 1990s, even though there 

was a significant decrease in arsenic exposure through drinking water more than 25 years earlier. 

 Strengths of the investigation include the large study population, the availability of past 

exposure data, and that potential confounders of age, gender, and smoking history were 

controlled for in the analysis. However, weaknesses include the inability to account for 

migration, the ecologic design (i.e., lack of individual exposure data) and lack of information 

concerning occupation. 

Yuan et al. (2007) investigated mortality from 1950 to 2000 using an ecological study 

design in the arsenic-exposed Region II of Chile and the unexposed population from Region V. 

Before 1958, the drinking water in Region II contained approximately 90 ppb of arsenic. In 

1958, it became necessary to supplement the Region II water supply using rivers that had an 

average arsenic concentration of 870 ppb. After the installation of an improved water treatment 

operation in the early 1970s, the arsenic concentrations in the Region II water supply dropped 

sharply (<10 ppb). While acute myocardial infarction (AMI) mortality was the predominant 

cause of excess deaths during and immediately after the high-exposure period, due to the longer 

latency of cancer, excess deaths from lung and bladder cancer became predominated years later. 

Yuan et al. (2007) concluded that after a 15- to 20-year lag period following initial exposure to 

significantly elevated levels of arsenic from drinking water (1958–1970), mortality from bladder 

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and lung cancer surpassed other causes of mortality. Strengths of the study included known 

arsenic concentrations and the large study population. In addition, to ensure appropriate 

selection of a control population, preliminary investigations were conducted to compare regional 

income, smoking history, and availability and quality of death certificate information. The major 

weakness of the study was its ecological study design (i.e., lack of individual arsenic exposure). 

In addition, potential confounders (i.e., smoking histories, diet, and exercise) were not examined 

on an individual basis, but were compared on a regional basis. 

4.1.4. North America (United States and Mexico) 

Bates et al. (1995), in a case-control study, used data obtained from Utah respondents for 

the 1978 National Bladder Cancer Study to examine the potential relationship between bladder 

cancer in a U.S. population exposed to measurable levels of arsenic in drinking water. Arsenic 

levels in drinking water were lower than those in Asian and South American studies. A total of 

117 cases and 266 controls were selected as participants for this study. Restricting subjects to 

those who had lived in study areas for at least half of their lives, the number of subjects still 

eligible was 71 cases and 160 controls. Arsenic exposures ranged from 0.5 to 160 ppb (mean, 

5.0 ppb). Two measurements of arsenic exposure were used. One measure used was the total 

CAE and the other was the arsenic concentration ingested adjusted for individual water 

consumption. Bates et al. (1995) found no association between bladder cancer and either arsenic 

exposure measure. However, among smokers, positive trends in cancer risk were found for 

arsenic exposures between 30 to 39 years prior to cancer diagnosis. The risk estimates were 

stronger for the drinking water measure that estimated the ingested arsenic concentration than 

the CAE. The risk estimates obtained, however, were higher than predicted based on the results 

of the Taiwanese studies, which raised concerns by Bates et al. (1995) regarding confounders, 

bias, and chance. 

The data from this study raised the potential that smoking contributes to the increased 

effect of arsenic on the risk of bladder cancer. Potential confounders included in the logistic 

models were gender, age, smoking status, years of exposure to chlorinated water, history of 

bladder infection, and the highest educational level attained. Strengths of the Bates et al. (1995) 

investigation are that these confounders were controlled for; occupation, population size of 

geographic area, and urbanization were addressed in the analysis; and cases were histologically 

confirmed. Potential weaknesses of the study are the small size of the study population, the fact 

that the subjects were mostly male and the data on females were inadequate, and that arsenic 

exposure levels were based on measurements close to the time that cases were diagnosed. Due 

to the low concentration in the water, the lack of measurement of arsenic in the food was a 

limitation of this study. Although the purpose of the Bates et al. (1995) study was to compare 

low-level arsenic exposure and bladder cancer with the results from the Taiwanese population, 

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the results cannot be interpreted without consideration of potential confounders and bias 

resulting from the retrospective study design. 

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Employing a retrospective cohort mortality investigation of residents from Millard 

County, Utah, Lewis et al. (1999) examined the relationship between arsenic exposure from 

drinking water and mortality outcome. Median drinking water arsenic concentrations for 

selected study areas ranged from 14 to 166 ppb. Drinking water samples were obtained from 

public and private sources and were collected and analyzed under supervision of the State of 

Utah Department of Environmental Quality, Division of Drinking Water. Cohort members were 

assembled using historical documents made available by the Church of Jesus Christ of LatterDay Saints. Residential histories and median drinking water arsenic concentration were used to 

construct a matrix for CAE. Previous drinking water arsenic concentrations (from 1964 forward) 

were obtained from historical records of arsenic measurements maintained by the state of Utah. 

Without regard to specific exposure levels, statistically significant increases in mortality from 

prostate cancer (SMR=1.45, 95% CI: 1.07–1.91) among cohort males was observed. Nonsignificant increases in mortality for males were observed in cancer of the kidney (SMR=1.75, 

95% CI: 0.80–3.32). There was no increased risk for cancer of the bladder and other urinary 

organs (SMR=0.42, 95% CI: 0.08–1.22) in males. Among cohort females, no statistically 

significant increase in mortality was observed. Females did, however, exhibit non-significant 

increases in mortality from kidney cancer (SMR=1.60, 95% CI: 0.44–4.11) and melanoma of the 

skin (SMR=1.82, 95% CI: 0.50–4.66). Female cancer of the bladder and other urinary organs 

(SMR=0.81, 95% CI: 0.10–2.93) was not increased. Risk analysis using low-, medium-, and 

high-arsenic exposure groups did not provide any clear indication of a dose-response for prostate 

cancer. Confounding was not considered to be a significant concern by Lewis et al. (1999). 

Exposure to other arsenic sources (food- or airborne), however, may have contributed to the total 

exposure potential of this population. Strengths of the study included the cohort study design. 

In this design type, the exposure precedes the effect being measured so a variety of effects from 

a single type of exposure can be considered. The study population was mostly rural and 

Mormon (low tobacco and alcohol use). In addition, NRC (2001) and EPA (U.S. EPA, 2001) 

identified that the Lewis et al. (1999) study was not powerful enough to estimate risk. 

To address the association between skin cancer and arsenic exposure in drinking water, 

Karagas et al. (2001) used data collected on 587 basal cell and 284 squamous cell skin cancer 

cases and 524 controls. Cases and controls were interviewed as part of a case-control study 

conducted in New Hampshire (and bordering regions) between 1993 and 1996. Arsenic 

exposure levels were determined using toenail clippings. The ORs for SCC (range 0.93–1.10) 

and BCC (range 0.72–1.06) were not significant and near unity (1.0) in all but the highest 

category (0.345–0.81 μg/g). For cases with significantly elevated toenail arsenic concentrations, 

the adjusted ORs were 2.07 (95% CI 0.92–4.66) for SCC and 1.44 (95% CI: 0.74–2.81) for BCC, 

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compared with those with concentrations at or below the median. Since the risks of SCC and/or 

BCC were not elevated in the range of toenail arsenic concentrations detected in most study 

subjects, the authors did not exclude the possibility of a dose-related increase at the highest 

levels of exposure. Strengths include evaluating the effects of potential confounders such as age, 

gender, race, educational attainment, smoking status, skin reaction to first exposure to the sun, 

and history of radiotherapy. Toenail arsenic concentrations can be considered a strength and a 

weakness. They are a strength because they individualize the dose and could account for arsenic 

exposure from other sources (e.g., food), but they also could be considered a weakness because 

toenail arsenic is a biomarker of recent past exposure (covering a period of about one year 

according to Cantor and Lubin, 2007). Some confounding variables were not controlled for and 

may have influenced the results. The latency of arsenic-induced skin cancer is unknown and, as 

a result, the follow-up period for this study may have been inadequate. 

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The identification of a potential leukemia cluster in Churchill County, Nevada, where 

arsenic levels in water supplies are relatively high, prompted a study by Moore et al. (2002). 

Using an ecological study design, Moore et al. examined the incidence of childhood cancer 

between 1979 and 1999 in all 17 Nevada counties. For analysis, arsenic exposures were grouped 

into low (<10 ppb), medium (10–25 ppb), and high (35–90 ppb) population-weighted arsenic 

levels based on the levels obtained from public drinking water. SIRs for all childhood cancers 

combined were 1.00 (95% CI: 0.94–1.06) for low-exposure, 0.72 (95% CI: 0.43–1.12) for 

medium, and 1.25 (95% CI: 0.91–1.69) for high-exposure counties. Moore et al. (2002) found 

no apparent relationship between the three arsenic levels and childhood leukemia with SIRs of 

1.02 (95% CI: 0.90–1.15), 0.61 (95% CI: 0.12–1.79), and 0.86 (95% CI: 0.37–1.70) in the low, 

medium, and high exposure categories, respectively. No association was found for all childhood 

cancers, excluding leukemia, with SIRs of 0.99 (95% CI: 0.92–1.07), 0.82 (95% CI: 0.47–1.33), 

and 1.37 (95% CI: 0.96–1.91), respectively. There was, however, an excess for bone cancers in 

5- to 9-year-olds and 10- to 14-year-olds and an excess in cancer (primarily lymphomas) in 15- 

to 19-year-old young adults in the high-exposure group. The findings in this study showed no 

increase in leukemia risk at the concentrations of arsenic identified and categorized in the water. 

 Although the results did not eliminate the possibility for increased risks for non-leukemia 

childhood cancers, there is no reason to suspect that the exposures to low levels of arsenic in the 

small study group are responsible. Strengths of the study are that the analysis of the data was 

stratified by age, the study was a low-level arsenic exposure study, and the findings were 

reported at different arsenic concentrations. Weaknesses of the study include the small study 

size, the potential for exposure misclassification, and the limitations of the ecological study 

design. 

Steinmaus et al. (2003) used a case-control study to evaluate the effects of arsenic 

ingestion on bladder cancer risk in seven counties in the western United States. These counties 

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contain the largest populations historically exposed to arsenic via drinking water at levels of 

approximately 100 ppb. These populations gave Steinmaus et al. the opportunity to critically 

evaluate the effects of relatively low-level arsenic exposure on bladder cancer incidence. 

Incident bladder cancer cases diagnosed between 1994 and 2000 were recruited based on 

information obtained from the Nevada Cancer Registry and the Cancer Registry of Central 

California. Arsenic measurements for community-supplied drinking water within the study were 

provided by the Nevada State Health Division and the California Department of Health Services. 

 Over 7000 arsenic measurements were obtained. Individuals’ data on water sources, water 

consumption patterns, smoking history, and other sociodemographic factors were obtained for 

181 bladder cancer cases and 328 matched controls. There was no observed increased risk for 

bladder cancer associated with intakes greater than 80 μg/day (OR=0.94, 95% CI: 0.56–1.57; 

linear trend, p=0.48). This observed OR was below the risk predicted based on higher arsenic 

concentrations in drinking water studies from Taiwan. However, when the analysis focused 

solely on previous smokers who had arsenic exposures greater than 80 μg/day (median 177 

μg/day) for more than 40 years, the risk was significantly increased (OR=3.67, 95% CI: 1.43–

9.42; linear trend, p< 0.01). These data provide evidence that smoking and ingesting arsenic at 

elevated concentrations (i.e., greater than 100 μg/day) may result in an increased risk of bladder 

cancer. A strength of the Steinmaus et al. (2003) study is the use of individual exposure level 

data to examine low-dose drinking water arsenic exposure; however, the lack of arsenic exposure 

from food is a study weakness due to the low levels of exposure through drinking water. In 

addition, the use of cancer registries allowed for improved case identification. Potential 

confounders adjusted for in the analysis included gender, age, smoking history, education, 

occupation associated with elevated rates of bladder cancer, and income. However, bias as the 

result of next-of-kin interviews may have influenced the exposure assessment. Arsenic 

exposures from outside the study area also may have influenced the exposure assessment. In the 

arsenic-exposed areas, the percentage of non-participants was 5% higher among cases than 

controls. This difference probably means that more exposed cases were missed in analyses of 

recent exposure, biasing the OR toward the null. 

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There has been little research investigating the link between arsenic and cutaneous 

melanoma, although arsenic has been associated with increased risk of non-melanoma skin 

cancer. Beane-Freeman et al. (2004) performed a case-control study to examine the potential 

relationship between melanoma and environmental arsenic exposure in a cohort from Iowa. 

Study participants included 368 cutaneous melanoma cases (selected from 645 eligible cases) 

and 373 colorectal cancer controls (selected from 732 eligible controls) diagnosed in 1999 or 

2000, frequency-matched on gender and age. Participants completed a mailed survey and 

submitted toenail clippings (obtained from 355 cases and 353 controls) for analysis of arsenic 

content. The authors identified an increased risk of melanoma in study cases with elevated 

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toenail arsenic concentrations (OR=2.1, 95% CI: 1.4–3.3; p-trend=0.001) and an increased risk 

of melanoma with previous diagnosis of skin cancer and elevated toenail arsenic concentrations 

(OR=6.6, 95% CI: 2.0–21.9). There was a greater association between the toenail arsenic and 

melanoma when subjects reported a previous diagnosis of melanoma. Strengths of this 

investigation include the fact that the potential confounders (age, gender, skin color/skin type, 

prior history of sunburn, education, and occupational exposure) were controlled for in the 

analysis. Ascertainment of cases and controls was accomplished by using the Iowa Cancer 

Registry, a Surveillance, Epidemiology, and End Results Program registry. This allowed newly 

diagnosed melanoma cases to be identified for a specific period and assured a greater degree of 

certainty regarding the accuracy of diagnosis. Another strength is that toenail arsenic 

concentrations individualize the exposure and account for arsenic exposure from other sources. 

A limitation of this study was that toenail samples were collected 2 to 3 years after diagnosis and 

therefore do not measure arsenic concentrations prior to diagnosis, resulting in possible exposure 

misclassification. 

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Karagas et al. (2004) used a case-control study design to examine the effects of low-level 

arsenic exposure on the incidence of bladder cancer in New Hampshire (and bordering regions), 

where levels above 10 ppb are commonly found in private wells. The authors studied 383 cases 

of transitional cell carcinoma of the bladder, diagnosed between July 1, 1994, and June 30, 1998, 

and 641 general population controls. Individual exposure to arsenic was determined through the 

use of toenail clippings. Karagas et al. (2004) found arsenic concentrations ranged from 0.014 to 

2.484 μg/g among bladder cancer cases and 0.009 to 1.077 μg/g among controls. When stratified 

by smoking history, toenail arsenic concentrations were not associated with the risk of bladder 

cancer. However, among smokers in the uppermost category of arsenic exposure, an elevated 

OR for bladder cancer was observed (OR: 2.17, 95% CI: 0.92–5.11 for >0.330 μg/g compared to 

<0.06 μg/g). When Karagas et al. (2004) stratified their analysis by duration of current water 

system usage (<15 years and ≥15 years), an increased bladder cancer OR for people who ever 

smoked with the highest category of arsenic exposure with less than 15 years of use was 

identified (<15 years, OR=3.09, 95% CI: 0.80–11.96; ≥15 years, OR=1.86, 95% CI: 0.57–6.03). 

 These data suggest that ingestion of low to moderate arsenic levels may affect bladder cancer 

incidence and that cigarette smoking may act as a co-carcinogen. Strengths of the study include 

its use of a stratified analysis to evaluate the potential that an extended latency period was 

required for bladder cancer development and its minimizing of misclassification by using 

biomarkers. The following potential confounders were adjusted for: age, gender, race, 

educational attainment, smoking status, family history of bladder cancer, study period, and 

average number of glasses of tap water consumed per day. Toenail clippings were used in an 

attempt to minimize misclassification. This, however, is a limitation because it only measures 

recent past exposures. Limitations of the study were that misclassification at the lower 

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exposures was possible and that lifetime exposure could not be calculated since data from 

previous residences could not be determined. In addition, there was limited data at extreme ends 

of exposure. 

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The Lamm et al. (2004) ecological study investigated the association between arsenic 

exposure from drinking water and bladder cancer mortality in 133 counties in the United States. 

Caucasian male county-specific bladder cancer mortality data between 1950 and 1979 and 

county-specific ground water arsenic concentration data were obtained for counties solely 

dependent on ground water for their public drinking water supply. Arsenic exposure was based 

on measurements for at least 5 wells for each county. No arsenic-related increase in bladder 

cancer mortality (SMR=0.94, 95% CI: 0.90–0.98) was identified (arsenic exposure range: 3–60 

ppb) using stratified analysis and regression analyses. These findings are consistent with other 

previously published U.S. studies. Strengths of the study include the large nationwide study 

population, which included more than 75 million person-years of observation. Weaknesses, 

however, are the lack of available individual exposure data, the assumption that study 

participants consumed only local drinking water, the assumption that available data were 

representative of actual arsenic content in the water, that arsenic contribution from food sources 

were not analyzed, and that the analysis did not directly adjust for smoking, urbanization, or 

industrialization. 

The Wisconsin Division of Public Health, in July 2000 through January 2002, conducted 

a cross-sectional study in 19 rural Wisconsin townships concerning private drinking-water wells 

and arsenic exposure (Knobeloch et al., 2006). Residents in these townships were asked to 

collect well-water samples and complete a questionnaire regarding residential history, 

consumption of drinking water, and family health. In Wisconsin, skin cancer is not reportable; 

therefore, no skin cancer registry data were available. During the study, 2,233 private wells 

were tested, and 6,669 residents provided information on water consumption and health. Water 

arsenic levels ranged from less than 1.0 to 3,100 ppb. The median arsenic level was 2.0 ppb. 

Eighty percent of the wells had arsenic levels below 10 ppb, but 11% had an arsenic level of 

above 20 ppb. Age-, gender-, and smoking-adjusted ORs of residents 35 years of age and older 

who had consumed water with arsenic levels greater than 1.0 ppb for at least 10 years showed a 

significant increase in individuals who reported skin cancer compared to those whose water 

arsenic levels were less than 1.0 ppb (arsenic 1.0–9.9 ppb OR=1.81, 95% CI: 1.10–3.14). 

Similarly, adults whose well-water reportedly contained arsenic concentrations greater than 10 

ppb were significantly more likely to report skin cancer than those whose water arsenic levels 

were less than 1.0 ppb (OR=1.92, 95% CI: 1.01–3.68). Tobacco use also was associated with 

higher rates of skin cancer and may—synergistically with arsenic exposure—affect the 

development of skin cancer. Strengths of the study include: the large sample size, a history of 

individual tobacco use, arsenic well water analysis for each household, an exposure duration of 

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at least 10 years in participants who consumed water from the tested wells, and the fact that the 

analysis controlled for age, gender, and tobacco use. Weaknesses include the following: skin 

cancers were self-reported and not confirmed by a medical records review, few people could 

provide information about specific types of cancer, potential bias could have resulted from the 

participating families being concerned about arsenic exposure, sun exposure and occupation 

were not controlled for in the analysis, and food sources of arsenic were not considered. 

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Meliker et al. (2007) performed an ecological study in a contiguous six-county study area 

of southeastern Michigan to investigate the relationship between moderate arsenic levels (10–

100 ppb) and selected disease outcomes. This region of southeastern Michigan was chosen 

because it had moderately high arsenic concentrations in the ground water and low rates of 

migration. The six counties had a population-weighted mean arsenic concentration of 11.00 ppb 

and a population-weighted median of 7.58 ppb. In comparison, the remainder of Michigan has a 

population-weighted mean of 2.98 ppb with a median of 1.27 ppb. SMRs for cancers were not 

significantly different from the age- and race-adjusted expected values for males or females for 

the state of Michigan (SMR skin melanoma female=0.97, 95% CI: 0.73–1.27, melanoma 

male=0.99, 95% CI: 0.79–1.22; SMR bladder female=0.98, 95% CI: 0.80–1.19, bladder 

male=0.94, 0.82–1.08; SMR kidney female=1.00, 95% CI: 0.80–1.20, kidney male=1.06, 95% 

CI: 0.91–1.22; SMR trachea, lung, bronchus female=1.02, 95% CI: 0.96–1.07, trachea, lung, 

bronchus male=1.02, 95% CI: 0.98–1.06). The only exception was cancer of the female 

reproductive organs (SMR=1.11, 95% CI: 1.03–1.19). The potential explanations for the lack of 

significant cancer findings were the relatively low level of arsenic in the ground water of 

southeastern Michigan, which may be below the threshold for cancer induction and other 

moderating factors that were not considered by this study (i.e., food as a source of arsenic 

exposure). Strengths include that mortality rates, which were gathered from Michigan Resident 

Death Files for a 20-year period, were stratified by gender, age, and race. Weaknesses include 

the following: the ecological study design did not provide individual arsenic exposure data and 

may not permit the detection of significant risk, there may have been differences in reporting and 

classification of underlying causes of death, case migration occurred, preferential sampling was 

conducted based on home owners’ request, arsenic contribution from food was not measured, 

and there was a lack of information concerning smoking history and obesity. 

4.1.5. China 

Using an ecological study design, Lamm et al. (2007) conducted dermatological 

examinations for 3,179 of the 3,228 (98.5%) residents of three villages (Zhi Ji Liang, Tie Men 

Geng, and Hei He) in Huhhot, Inner Mongolia, with well water arsenic levels that ranged from 

undetectable (<10 ppb) to 2,000 ppb. Individual water consumption histories were obtained for 

this population, and arsenic levels were measured for 184 wells. Arsenic exposures were 

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summarized as the highest arsenic concentration (HAC) and CAE. Thirty-five percent of the 

study population had HAC of less than 50 ppb, 86% had HAC less than 150 ppb, and only 1% of 

the participants had HAC greater than 500 ppb. The proportion of females to males was similar 

in each of the three villages (female range 49%–50% and male range 50%–51%), and almost all 

study subjects identified themselves as being of Chinese (99.8%) rather than Mongolian (0.2%) 

origin. The median age for all participants was 29 years; however, participants from Hei He 

tended to be older than those from the other two villages (55.0% older than 30 in Hei He, 42.4% 

in Zhi Ji Liang and Tie Men Geng). Participants (female or male) who reported occupations 

listed “student” or “farmer.” None of the examinations revealed any evidence of BFD. Analyses 

included frequency-weighted, simple linear regression, and most likely estimate models. Eight 

people were found to have skin cancer. In addition to skin cancer, these eight cases also had 

both hyperkeratoses and dyspigmentation. Skin cancer cases were only identified in those 

participants with HAC exposures >150 ppb or whose CAE was less than 1,000 ppb-years. The 

models showed a threshold of 122–150 ppb. Lamm et al. (2007) identified a general exposureprevalence pattern (higher prevalence for HAC exposure group) for skin disorders 

(hyperkeratosis, dyspigmentation, and skin cancers). Duration of water usage (arsenic 

exposure), age, latency, and misclassification did not appear to markedly affect the analysis. 

Strengths of the study include the large study population, the fact that HAC and CAE were used 

in the analyses, and the fact that arsenic concentrations were measured in 184 wells. 

Confounders that were controlled for included age, differences in cumulative arsenic dose, and 

duration of exposure. A confounder not adjusted for in the analysis was sun exposure. 

Additional weaknesses are the ecological study design and the potential for recall or 

misclassification bias resulting from the collection of arsenic exposure histories through 

interviews. 

4.1.6. Finland 

In a case-cohort study, Kurttio et al. (1999) examined the levels of arsenic in Finnish 

water wells and their relationship to the risk of bladder and kidney cancers. The study 

population consisted of 61 bladder cancer cases and 49 kidney cancer cases diagnosed between 

1981 and 1995, and a randomly selected age- and gender-adjusted reference cohort of 275 

subjects. Arsenic exposure was estimated for cancer cases and for the reference cohort for two 

periods. The first period was from the third to ninth calendar years (the shorter latency period) 

prior to either the cancer diagnosis or the respective year for referent cohort, while the other was 

from the tenth or earlier calendar years (the longer latency period). Water specimens were 

obtained from the wells used by the study cohort from 1967 to 1980. The arsenic concentrations 

in the wells of the control population were low, with approximately 1% exceeding 10 ppb. 

Bladder cancer was associated with arsenic concentration and daily dose during the third to ninth 

calendar years prior to the cancer diagnosis. The risk ratios for arsenic exposure concentration 

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categories 0.1–0.5 and >0.5 ppb relative to the category with <0.1 ppb were 1.53 (95% CI: 0.75–

3.09) and 2.44 (95% CI: 1.11–5.37), respectively. In spite of low levels of arsenic exposure, 

Kurttio et al. (1999) found evidence of a relationship between exposure to arsenic at the higher 

exposure level and bladder cancer risk. No association, however, was observed between arsenic 

exposure level and kidney cancer risk. Strengths include the following: Finnish Cancer Registry 

records were accessible; Statistics Finland’s 1985 Population Census file was used to identify 

areas in which less than 10% of the population used the municipal water supply; and age, gender, 

and smoking histories were accounted for in the risk ratio calculations. Possible weaknesses 

include misclassification and recall bias resulting from the study choosing to use water 

consumption from the 1970s. In addition, because of the low arsenic concentrations, arsenic 

exposure from other sources (e.g., food) could bias the results. 

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Michaud et al. (2004) used a cohort (nested case-control) study design to investigate the 

relationship between arsenic levels in toenail and bladder cancer risk among Finnish male 

smokers aged 50–69 years who were participating in the Alpha-Tocopherol, Beta-Carotene 

Cancer Prevention Study. Data for 280 incident bladder cancer cases, identified between 1985 

and 1988 as well as April 1999, were available for analysis. Controls (n = 293) were matched to 

each case on the basis of age, toenail collection date, intervention group, and duration of 

smoking. Logistic regression analyses were performed to estimate ORs. Arsenic toenail 

concentrations in this Finnish study (cases and controls) ranged between 0.01 and 2.11 μg/g, 

with one control outlier at 17.5 μg/g. Arsenic toenail concentrations were similar to those 

reported in the United States (range: 0.02–17.7 μg/g). Men were categorized into quartiles based 

on the distribution of arsenic among the controls (<0.050, 0.050–0.105, 0.106–0.161, and 

>0.161). The study observed no significant relationship between arsenic concentration and 

bladder cancer risk (OR=1.13, 95% CI: 0.70–1.81 for the highest vs. lowest quartile). Strengths 

of the Michaud et al. (2004) study were that the authors excluded toenail samples with nondetectable arsenic levels greater than 0.09 μg/g, in an attempt to avoid potential misclassification 

of samples with high detection limits, and that they controlled for potential confounders in the 

analysis (i.e., smoking history, beverage intake, place of residence, toenail weight, smoking 

cessation, smoking inhalation, educational level, beverage intake, and place of residence). Cases 

and controls were matched according to age, toenail collection date, intervention group (alpha 

tocopherol and beta carotene), and smoking duration. Toenail arsenic concentrations are a 

strength because they individualize the dose and could account for arsenic exposure from other 

sources, but they also could be considered a weakness because toenail arsenic is a biomarker of 

recent past exposure (covering about 1 year according to Cantor and Lubin, 2007). Another 

weakness of the study was that water consumption was not included in the total beverage intake 

variable. 

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4.1.7. Denmark 

The Baastrup et al. (2008) cohort study was designed to determine whether exposure to 

low levels of arsenic in drinking-water in Denmark is associated with an increased risk for 

cancer. The study population was selected from participants in the prospective Danish cohort 

Diet, Cancer, and Health. A cohort of 56,378 people (39,378 from Copenhagen and 17,000 from 

Aarhus) accepted an invitation to participate in the study. Cancer cases were identified in the 

Danish Cancer Registry, and the Danish civil registration system was used to trace residential 

addresses of the cohort members. The study used a geographic information system to link 

residential addresses with water supply areas and using this information estimated arsenic 

exposure by addresses. The average arsenic exposure for the cohort ranged between 0.05 and 

25.3 ppb (mean = 1.2 ppb) and was based on 4,954 measurements reported between 1987 and 

2004 (the majority between 2002 and 2004). The exposure was generally higher among Aarhus 

participants than those enrolled in the Copenhagen area (Aarhus mean = 2.3 ppb, min = 0.09 ppb 

and max=25.3 ppb; Copenhagen mean = 0.7 ppb, min = 0.05 ppb, and max=15.8 ppb). 

Regression models were used to analyze possible relationships between arsenic and cancer. The 

study found no significant association between arsenic exposure and risk for cancers of the lung, 

bladder, liver, kidney, prostate, colon, or melanoma skin cancer. The incidence rate ratio (IRR) 

for non-melanoma skin cancer (0.88, 95% CI: 0.84–0.94) decreased with per ppb increases in the 

time-weighted average exposure to arsenic. The study did identify a significant increased risk 

for breast cancer in association with time-weighted average exposure to arsenic (IRR=1.05, 95% 

CI: 1.01–1.10). Strengths of the study include the large study population, the 

socioeconomic/demographic similarities of the cohort, and the adjustment for potential 

confounders (smoking, alcohol consumption, education, body mass index [BMI], daily intake of 

fruits/vegetables, red meat, fat and dietary fiber, skin reaction to the sun, hormone replacement 

therapy use, reproduction, occupation, and enrollment area). Weaknesses of the study include 

the low arsenic levels in Danish drinking water, the lack of information on other sources of 

arsenic exposure, and the inability to assess arsenic exposures before 1970, all resulting in 

possible misclassification bias. 

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4.1.8. Australia 

Hinwood et al. (1999) conducted an ecological study that investigated areas of Victoria, 

Australia, with elevated environmental arsenic concentrations, areas with arsenic concentrations 

in the soil of more than 100 mg/kg and/or drinking water arsenic concentrations greater than 10 

ppb, and the relationship with cancer incidence. SIRs for cancer were generated for 22 areas 

between 1982 and 1991 using cancer registry data. In addition, SIRs for combined areas 

according to environmental exposure (high soil and/or high water arsenic concentrations, etc.) 

were generated. The SIRs (females and males together) for the combined 22 areas were 

significantly elevated for all cancers (1.06, 95% CI: 1.03–1.09), melanoma (1.36, 95% CI: 1.24–

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1.48), chronic myeloid leukemia (1.54, 95% CI 1.13–2.10), breast cancer in females (1.10, 95% 

CI: 1.03–1.18), and prostate cancer in males (1.14, 95% CI: 1.05–1.23). The SIR for kidney 

cancer (females and males combined) was 1.16 (95% CI: 0.98–1.37), and although elevated was 

not statistically significant. When stratified by exposure category, the SIR for prostate cancer 

was significant at 1.20 (95% CI: 1.06–1.36) for the high soil/high water category only. This 

result was likely confounded by misclassification (level of population exposure) and limited by 

low statistical power. There was no significant dose-response relationship observed between 

drinking water and any individual cancer. Strengths of the study include that water and soil 

arsenic levels were provided and a large area was examined. Hinwood et al. (1999) recognized 

that the results of this study were potentially confounded by a number of factors, including the 

ecological study design, socioeconomic status, race, occupation, and urban versus rural status. 

Due to the low concentrations in the drinking water, the lack of arsenic exposure from food 

could cause exposure misclassification. 

4.2. PRECHRONIC AND CHRONIC STUDIES AND CANCER BIOASSAYS IN 

ANIMALS—ORAL 

4.2.1. Prechronic and Chronic Studies 

Wei et al. (1999, 2002) demonstrated that 10-week-old male F344/DuCrj rats (36/group) 

administered 12.5, 50, or 200 ppm DMAV (a major metabolite of inorganic arsenic) in their 

drinking water for 104 weeks had no effect on the morbidity, mortality, body weights, 

hematology, or serum biochemistry. Reductions in electrolyte concentrations in the urine were 

related to an increase in urinary volume resulting from increased water consumption in the 50- 

and 200-ppm groups. There was no difference in the urinary pH between control and treated 

rats. 

4.2.2. Cancer Bioassays 

Cancer bioassays with inorganic arsenic have generally obtained negative results with 

mice, rats, hamsters, rabbits, beagles, and cynomologus monkeys (for review see Kitchin, 2001; 

NRC, 1999). However, the following studies have observed increases in tumors in animals 

exposed to arsenic species. 

4.2.2.1. Mice—Transplacental 

Timed pregnant female C3H mice (10/group) were administered 0 (control), 42.5, or 85 

ppm AsIII in their drinking water ad libitum from day 8 to day 18 of gestation (Waalkes et al., 

2003). Strain and doses used in the experiment were determined through preliminary short-term 

testing that determined C3H mice to be the most sensitive to arsenic toxicity of the three strains 

tested (i.e., C3H, C57BL/6NCr, and B6C3F1/NCr), and the preliminary test indicated that a dose 

of 100 ppm was unpalatable and resulted in approximately 10% reduced growth in the offspring. 

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 The doses used in this study did not affect maternal water consumption or body weight in the 

dams. It was estimated that the pregnant females consumed 9.55 to 19.13 mg arsenic/kg-day, for 

a total dose of 95.6 to 191.3 mg arsenic/kg. 

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Offspring were weaned at 4 weeks and received no additional exposure to arsenic. Male 

and female offspring (25/sex/group) were observed for the next 74 or 90 weeks, respectively. 

Males were sacrificed at 74 weeks due to high mortality in the high-dose group beginning at 52 

weeks. Both the 42.5- and 85-ppm males had a significant increase in the incidence of HCC 

(12.5% in the control group versus 38.1% in the 42.5-ppm group and 60.9% in the 85-ppm 

group) and adrenal cortical tumors (37.5% in the control group versus 66.6% in the 42.5-ppm 

group and 91.3% in the 85-ppm group), which followed a significant (p≤0.001), dose-related 

trend. In addition, the 85-ppm group had a significant increase in the multiplicity (tumor/mouse) 

for both HCC (0.13, 0.42, and 1.30, respectively) and adrenal tumors (0.71, 1.10, and 1.57, 

respectively), which also had a significant (p≤0.02), dose-related trend. Although there were no 

differences in the incidence of hepatocellular adenomas in males, the multiplicity of 

hepatocellular adenomas (0.71, 1.43, and 3.61, respectively) followed a significant (p < 0.0001), 

dose-related trend. 

Males and females had an increase in lung tumors (8.0%, 13.0%, and 25.0%, 

respectively, in females; 0%, 0%, and 13.0%, respectively, in males), which followed a 

significant (p≤0.03), dose-response trend. In addition, females had increases in the incidence of 

benign ovarian tumors, which reached statistical significance in the 85-ppm group. Although a 

significant increase was not observed in malignant ovarian tumors, the total incidence (benign 

plus malignant) of ovarian tumors was significant in the 85-ppm group and followed a 

significant (p=0.015), dose-related trend (8% in the control group versus 26% in the 42.5-ppm 

group and 37.5% in the 85-ppm group). There was an increase in uterine tumors that was not 

significant and did not follow a dose-response trend, but was accompanied by a significant 

(p=0.0019), dose-related increase in hyperplasia occurring at both doses. Females also had a 

dose-related increase in hyperplasia of the oviduct. The number of both tumor-bearing and 

malignant tumor-bearing males was significantly increased in both dose groups and followed a 

significant (p=0.0006 and 0.0001, respectively), dose-related trend. Female animals had a slight 

increase in the number of tumors, which did not reach statistical significance and did not appear 

to be dose-related. The number of females bearing malignant tumors was significantly increased 

for both dose groups, but not in a dose-dependent manner. 

Waalkes et al. (2004a) followed the same procedure (except that offspring were observed 

for 104 weeks), but exposed 25 male and 25 female offspring from each exposure group (0, 42.5, 

or 85 ppm in the drinking water from gestational days 8 to 18 with no additional exposure after 

birth) to acetone or 12-O-tetradecanoyl phorbol-13-acetate (TPA; 2 μg/0.1 mL in acetone) twice 

a week—via a shaved area of dorsal skin—for 21 weeks after weaning in an attempt to promote 

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skin tumors. However, very few skin lesions occurred and were not associated with arsenic 

exposure either in the absence or presence of TPA. As was noted in Waalkes et al. (2003), there 

was a dose-dependent increase in the incidence and/or multiplicity of hepatocellular adenomas 

and carcinomas in treated males, both in the absence and presence of TPA. In the absence of 

TPA, the incidence of adenomas was 41.7%, 52.2%, and 90.5% for the 0-, 42.5-, and 85-ppm 

exposure groups, respectively; the incidence of carcinomas was 12.5%, 34.8%, and 47.6%, 

respectively; total incidence was 50%, 60.9%, and 90.5%, respectively; and multiplicity was 

0.75, 1.87, and 2.14, respectively. In the presence of TPA, the incidence of adenomas was 

34.8%, 52.2%, and 76.2% for the 0-, 42.5-, and 85-ppm exposure groups, respectively; the 

incidence of carcinomas was 8.7%, 26.0%, and 33.3%, respectively; total incidence was 39.1%, 

65.2%, and 85.7%, respectively; and multiplicity was 0.61, 1.44, and 2.14, respectively. A 

statistically significant increase was noted at 85 ppm. Arsenic only caused a dose-dependent 

increase in hepatocellular adenomas and carcinomas in the presence of TPA in females 

(adenomas: 8.3%, 18.2%, and 28.6% for the 0-, 42.5-, and 85-ppm exposure groups with TPA 

exposure, respectively; carcinomas: 4.2%, 9.1%, and 19.0%, respectively; total incidence: 12.5, 

27.3, and 38.1%, respectively; multiplicity: 0.13, 0.32, and 0.71, respectively), with a 

statistically significant increase in total incidence and multiplicity for the 85-ppm group. 

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There also was an increase in ovarian adenomas in treated female offspring regardless of 

whether they were treated with TPA (0%, 22.7%, 19.0%, respectively) or acetone (0%, 17.4%, 

and 19.0%, respectively). There was no effect on the incidence of ovarian carcinomas. This was 

accompanied by increases in the incidence of uterine epithelial hyperplasia (cystic) and total 

uterine proliferative lesions, which increased in severity with dose. There also was a dosedependent increase in oviduct hyperplasia. Male offspring exposed to arsenic had an increase in 

the incidence and multiplicity of cortical adenomas of the adrenal glands. The increases were 

statistically significant for both arsenic exposure groups, but were only related to dose in the 

absence of TPA (p=0.020). Incidences were as follows: 37.5%, 65.2%, and 71.4% for the 0-, 

42.5-, and 85-ppm dose groups, respectively, in the absence of TPA and 30.4%, 65.2%, and 

57.1%, respectively, with TPA treatment. Multiplicities also were statistically significantly 

increased in arsenic-exposed male offspring with a significant dose-dependent trend both in the 

absence (0.58, 2.13, and 2.19, respectively; p=0.0014) or presence (0.54, 1.65, and 1.62, 

respectively; p=0.016) of TPA. 

Lung adenomas were increased in a dose-dependent manner in females exposed to TPA 

(4.2%, 9.1%, and 28.%, respectively; p=0.018), but not in the absence of TPA (4.2%, 8.7%, and 

9.5%, respectively; not significant). Males only had a statistically significant increase (5-fold 

increase) in lung adenomas in the 42.5-ppm group exposed to TPA. 

A statistically significant increase in the multiplicity of all tumors in males (with or 

without TPA) was observed after arsenic exposure, but was not dependent on dose. Although 

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females also had an increase in the multiplicity of all tumors, the only statistically significant 

increase occurred in the 85-ppm group exposed to TPA. The increase in females exposed to 

TPA also appeared to be dose-dependent. The statistically significant increase observed in the 

multiplicity of malignant tumors in males was greater in the absence of TPA, but was dosedependent in the presence of TPA. In females, there was also an increase in the multiplicity of 

malignant tumors in arsenic treated mice (regardless of TPA exposure), but the results did not 

reach statistical significance, nor were they dose-dependent. 

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tumors. Thirty-five percent (12/34) of female offspring receiving 85 ppm of AsIII via the dams’ 

drinking water on gestational days 8 to 18 developed urogenital tumors, with 9% being 

malignant compared to 0% in the controls. 

4.2.2.2. Rat—Oral 

Soffritti et al. (2006) administered male and female Sprague-Dawley rats 0, 50, 100, or 

200 mg/L (i.e., ppm) of sodium arsenite via the drinking water for 104 weeks. There was a 

consistent dose-dependent decrease in water and food consumption accompanied by a doserelated decrease in body weight (there was no difference in body weight in females administered 

50 mg/L). There was only a slight decrease in survival in male rats administered 100 or 200 

mg/L beginning at 40 weeks of age. Females only had a decrease in survival rate after 104 

weeks of age. Males and females administered 100 mg/L had an increase in the number of 

tumor-bearing animals and in the number of tumors. Although there is no dose-related trends in 

tumors, there were sporadic benign and malignant tumors of the lung, kidney, and bladder 

observed in treated rats that are extremely rare in the authors’ extensive historical controls. 

These tumors consisted of adenomas and carcinomas of the lung, adenomas and carcinomas of 

the kidney, papillomas and one carcinoma of the renal pelvis transitional cell epithelium, and one 

carcinoma of the bladder transitional cell epithelium. 

Wei et al. (1999 and 2002) demonstrated that 10-week-old male F344/DuCrj rats 

(36/group) administered 50 or 200 ppm DMAV in their drinking water for 104 weeks developed 

bladder tumors (mainly carcinomas) and papillary or nodular hyperplasia in a dose-dependent 

manner. Controls and rats administered 12.5 ppm did not develop any bladder tumors or 

hyperplasia. There was a significant (p < 0.05) increase in bromodeoxyuridine (BrdU) labeling 

of morphologically normal epithelium of the bladder in the 50- and 200-ppm groups (Wei et al., 

2002). There was no significant increase in any other tumor type related to DMAV treatment. 

There appeared to be a dose-related increase in subcutis fibromas (i.e., 4% in controls, 12% in 

the 12.5-ppm group, and 16% in both the 50- and 200-ppm groups). Data indicate that multiple 

genes are involved in the stages of DMAV-induced urinary bladder tumors. Wei et al. (2002) 

further indicate that reactive oxygen species (ROS) may play an important role during the early 

stages of DMA carcinogenesis. 

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Shen et al. (2003) administered TMAO, an organic metabolite of inorganic As, to male 

F344 rats for 2 years via their drinking water at concentrations of 0, 50, or 200 ppm. Total 

intakes were estimated to be 0, 638, and 2475 mg/kg, respectively. From 87 weeks of treatment 

on, there was an increase in the incidence and multiplicity of hepatocellular adenomas in rats 

sacrificed or dead. Incidences of 14.3%, 23.8%, and 35.6%, respectively, were reported. The 

respective multiplicities were 0.21, 0.33, and 0.53. The results were statistically significant in 

the 200-ppm dose group. 

4.2.2.3. Other 

Transgenic models also have been developed to examine arsenic carcinogenesis. Arsenic 

exposure (200 ppm sodium arsenite in drinking water for 4 weeks) in Tg.AC transgenic mice 

containing activated H-ras did not induce skin tumors alone; however, the group of mice that 

were administered arsenic and a subsequent skin painting with TPA showed an increase in the 

number of papillomas compared to mice treated with TPA alone. Thus, it was suggested that 

arsenite may be a “tumor enhancer” in skin carcinogenesis (Germolec et al., 1997; Luster et al., 

1995). 

Ten ppm of either sodium arsenite or DMAV (cacodylic acid) administered for 5 months 

in the drinking water of K6/ODC transgenic mice induced a small number of skin papillomas 

(Chen et al., 2000a). K6/ODC transgenic mice have hair follicle keratinocytes (likely targets for 

skin carcinogens), which over express ornithine decarboxylase (ODC). ODC is involved in 

polyamine synthesis, which is needed in S phase. Over expression of ODC is sufficient to 

promote papilloma formation without administration of TPA, which has been demonstrated to 

induce ODC (O’Brien et al., 1997). 

Rossman et al. (2001) administered sodium arsenite (10 ppm) in the drinking water of 

hairless Skh 1 mice for 26 weeks. Mice were also administered 1.7 kJ/m2 solar ultraviolet 

radiation (UV), which is considered a low, nonerythemic dose, 3 times weekly, either with or 

without sodium arsenite exposure. Results demonstrated a 2.4-fold increase in the yield of skin 

tumors for mice exposed to both sodium arsenite and UV than in mice administered UV alone. 

A second experiment by the same group (Burns et al., 2004), demonstrated a 5-fold increase in 

skin tumors using 5 mg/L AsIII with 1 kJ/m2 solar UV, but also observed a significant increase 

with 1.25 mg/L AsIII with 1 kJ/m2 solar UV. The skin tumors (mainly SCCs) occurred earlier, 

were larger, and were more invasive in mice administered AsIII. Arsenite alone did not induce 

skin tumors. Rossman (2003) concluded that this demonstrates that arsenite enhances the onset 

and growth of malignant skin tumors induced by a genotoxic carcinogen in mice. Rossman 

(2003) also suggested that the increased tumor incidence observed by Waalkes et al. (2003) may 

be due to the same enhancement as C3H mice have a high background of spontaneous tumors 

and suggests the need for examining the transgenic effects in another strain of mice with a lower 

background tumorgenicity. 

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discussed in this report. 

4.3. REPRODUCTIVE/DEVELOPMENTAL STUDIES—ORAL 

Not addressed in this document.

4.4. OTHER STUDIES 

4.4.1. Possible Modes of Action and Key Events of Possible Importance 

As discussed in Section 3.3, the metabolism of inorganic arsenic in humans occurs 

through alternating steps of reduction and oxidative methylation mostly to DMAV. Many of the 

metabolites have been subjected to a variety of toxicological tests in vivo and in vitro, and they 

often differ considerably in their toxicological responses. The relative contributions of the many 

different forms of arsenic to the toxicity and carcinogenicity of inorganic arsenic are uncertain. 

Each of the arsenical metabolites exhibits its own pattern of toxicity, possibly via similar and/or 

separate MOAs that together are responsible for inorganic arsenic toxicity and tumor formation 

(Kitchin, 2001). 

The biotransformation and pharmacodynamics of inorganic arsenic are complex in 

mammals, with inorganic arsenic being biotransformed through a complex cycle of reduction, 

oxidation, and methylation steps to form the trimethylated TMAO metabolite, and possibly its 

reduced form, trimethylarsine, which may not be of consequence in humans. Arsenical forms of 

greater instability (i.e., trivalent forms) are produced within each step, and those forms have 

greater reactivity toward biological and biochemical intermediates and biological 

macromolecules. The trivalent species MMAIII and DMAIII have been identified as the most 

toxic and genotoxic forms in several assay systems (Thomas et al., 2001). Each intermediate 

arsenical form, however, has the potential to induce cancer or to affect the promotion and 

progression of cancer, such as by disrupting signal transduction pathways and gene expression. 

Many of these forms have been detected in the urine of humans exposed to inorganic arsenic and 

in rodents exposed to inorganic and organoarsenicals. Through the process of metabolizing 

arsenic, cells and organs are exposed to mixtures of these intermediates, which bring to the 

forefront potential synergistic interactions between them that could enhance the tumorigenesis 

process. 

Inorganic arsenic has been demonstrated to cause tumors in humans at multiple sites 

(bladder, lung, skin, liver, and possibly kidney). Rodents are generally much less sensitive to the 

tumorigenic effects of inorganic arsenic, except for a few recent transplacental mouse studies in 

which AsIII caused liver, lung, ovarian, and/or adrenal cortical tumors (Waalkes et al., 2003, 

2004a, and 2006a). Currently, there is insufficient information to fully explain the differences 

between human and rodent sensitivity to arsenic carcinogenicity. 

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Based on its extensive review of health consequences of inorganic arsenic in drinking 

water, NRC (1999) concluded that 

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4 • “The mode of action for arsenic carcinogenicity has not been established. Inorganic 

arsenic and its metabolites have been shown to induce deletion mutations and 

chromosomal alterations (aberrations, aneuploidy, and SCE [sister chromatid exchange]), 

but not point mutations. Other genotoxic responses that can be pertinent to the mode of 

action for arsenic carcinogenicity are co-mutagenicity, DNA methylation, oxidative 

stress, and cell proliferation; however, data on those genotoxic responses are insufficient 

to draw firm conclusions. The most plausible and generalized mode of action for arsenic 

carcinogenicity is that it induces structural and numerical chromosomal abnormalities 

without acting directly with DNA.” 

• “For arsenic carcinogenicity, the mode of action has not been established, but the several 

modes of action that are considered most plausible (namely, indirect mechanisms of 

mutagenicity) lead to a sublinear dose-response at some point below the level at which a 

significant increase in tumors is observed. However, because a specific mode (or modes) 

of action has not been identified at this time, it is prudent not to rule out the possibility of 

a linear response.” 

Several of the report’s other concluding statements drew attention to the possible 

importance of ROS to several health effects caused by arsenic and suggested that “intracellular 

production of ROS might play an initiating role in the carcinogenic process by producing DNA 

damage” (NRC, 1999). At the time of the NRC report, the prevailing view was that metabolism 

of inorganic arsenic through several methylated forms represented a detoxification pathway. 

One of the fundamental changes in thinking about the effects of inorganic arsenic since the NRC 

report has been the growing awareness that some of those metabolites (specifically, MMAIII and 

DMAIII) can have especially high levels of toxicity. Thus, metabolism also represents a 

toxification pathway. Regardless, when there is a steady influx of inorganic arsenic into the 

body as through continual exposure from drinking water, metabolism is essential to eliminate 

that arsenic, including the highly reactive AsIII, from the body. 

In 2001, NRC produced an update to its major review on inorganic arsenic in drinking 

water. It summarized, in tabular format, the mechanistic studies completed since 1998 and 

included a discussion of them. It focused on experiments that appeared to induce biochemical 

effects at moderate to relatively low concentrations of arsenic in vitro (e.g., less than 10 μM); 

however, some studies that used higher concentrations were included for comparative purposes. 

The focus was on moderate- to relatively low-dose studies because it was felt that studies that 

required arsenic concentrations greater than 10 μM to produce a biological response in vitro 

would be less likely to be relevant to the health effects related to chronic ingestion of arsenic in 

drinking water. NRC (2001) concluded that “The mechanistic studies reviewed herein and those 

reviewed previously in the 1999 NRC report suggest that trivalent arsenic species (primarily 

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AsIII, MMAIII, and, possibly, DMAIII) are the forms of arsenic of greatest toxicological concern.” 

They estimated concentrations of arsenic that could be expected in human urine from the known 

human experience and concluded that “Arsenite concentrations in excess of 10 μM generally 

exceed concentrations that can occur in the urine of individuals chronically exposed to arsenic in 

drinking water and have less direct relevance to understanding the modes of action responsible 

for human cancer induced by this route of exposure.” They also stated that: 

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8 • “Experiments in animals and in vitro have demonstrated that arsenic has many 

biochemical and cytotoxic effects at low doses and concentrations that are potentially 

attainable in human tissues following ingestion of arsenic in drinking water. Those 

effects include induction of oxidative damage to DNA; altered DNA methylation and 

gene expression; changes in intracellular levels of murine double minute 2 protooncogene (mdm2) protein and p53 protein; inhibition of thioredoxin reductase (TrxR; 

MMAIII but not AsIII); inhibition of pyruvate dehydrogenase; altered colony-forming 

efficiency; induction of protein-DNA cross-links; induction of apoptosis; altered 

regulation of DNA-repair genes, thioredoxin, glutathione reductase, and other stressresponse pathways; stimulation or inhibition of normal human keratinocyte cell 

proliferation, depending on the concentration; and altered function of the glucocorticoid 

receptor.” 

 

Despite the extensive research on MOA up to that time, NRC stated that “the 

experimental evidence does not allow confidence in distinguishing between various shapes 

(sublinear, linear, or supralinear) of the dose-response curve for tumorigenesis at low doses.” 

The present review uses the terms “mode of action” and “key event” as they are 

described in the Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a). According to 

EPA, “‘mode of action’ is defined as a sequence of key events and processes, starting with 

interaction of an agent with a cell, proceeding through operational and anatomical changes, and 

resulting in cancer formation. A ‘key event’ is an empirically observable precursor step that is 

itself a necessary element of the mode of action or is a biologically based marker for such an 

element. Mode of action is contrasted with ‘mechanism of action’, which implies a more 

detailed understanding and description of events, often at the molecular level, than is meant by 

mode of action. The toxicokinetic processes that lead to formation or distribution of the active 

agent to the target tissue are considered in estimating dose, but are not part of the mode of action 

as the term is used here. There are many examples of hypothesized modes of carcinogenic 

action, such as mutagenicity, mitogenesis, inhibition of cell death, cytotoxicity with reparative 

cell proliferation, and immune suppression.” 

In this review, tables have been compiled in order to make a large amount of information 

on the biological effects of inorganic arsenic readily available. Appendix C contains tables that 

deal with in vivo human studies (Table C-1), in vivo experiments on laboratory animals (Table 

C-2), and in vitro studies (Table C-3). These tables include as many experiments published from 

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2005 through August 2007 as possible. Numerous earlier experiments have been included as 

well, based on various selection criteria: being mentioned in the SAB Arsenic Review Panel 

comments of July 2007 (SAB, 2007) or in NRC’s update (NRC, 2001), or inclusion in an earlier 

draft that lacked tables (U.S. EPA, 2005c). The tables provide information on: (1) the arsenic 

species tested; (2) the cell types, tissues, or species tested; (3) all concentrations or doses tested; 

(4) all durations of exposure; (5) estimates of the LOEC or LOEL (i.e., lowest observed effect 

concentration or level); (6) a summary of the most important results of each study; and (7) the 

citations. The 22 categories into which the hypothesized key events are grouped in those tables 

are listed in column 1 of Table 4-1, and the number of data rows under each category provide an 

estimate of the amount of available data pertaining to each category topic. Data from a single 

publication are sometimes entered under multiple event categories. For example, the results in 

Wang et al. (1996) are summarized in rows under Apoptosis, Cytotoxicity, and Effects Related 

to Oxidative Stress (ROS). 

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When judging the possible relevance of in vitro experiments or in vivo laboratory animal 

experiments on human health, it is useful to keep in mind that the total concentration of AsIII and 

AsV in drinking water pumped from tube wells in Bangladesh (as an example of one country 

with high exposures to inorganic arsenic in drinking water) ranges from 20 to over 2,000 ppb 

arsenic (i.e., 0.3 to 27 μM). In people exposed at those high levels, total blood arsenic levels 

range from 0.5 to 1.2 μM (Snow et al., 2005), and total arsenic concentrations in urine would 

probably not exceed 10 μM (NRC, 2001). 

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Table 4-1. Summary of Number of Rows Derived From Peer-Reviewed Publications for 

Different Hypothesized Key Eventsa

Number of Rows in Tables 

Hypothesized Key Events In Vivo Human 

Studies 

(Table C-1) 

In Vivo

Experiments 

Using 

Laboratory 

Animals 

(Table C-2)

In Vitro

Experiments 

(Table C-3)

Aberrant Gene or Protein Expressionb 6 32 124 

Apoptosis 1 6 78 

Cancer Promotion 0 3 3 

Cell Cycle Arrest or Reduced Proliferation 0 1 29 

Cell Proliferation Stimulation 0 18 21 

Chromosomal Aberrations and/or Genetic Instability 13 3 83 

Co-carcinogenesis 0 2 3 

Co-mutagenesis 0 1 21 

Cytotoxicity 0 2 118 

DNA Damage 5 6 35 

DNA Repair Inhibition or Stimulation 2 0 11 

Effects Related to Oxidative Stress (ROS) 2 30 69 

Enzyme Activity Inhibition 0 0 5 

Gene Amplification 0 0 5 

Gene Mutations 1 2 7 

Hypermethylation of DNA 2 1 2 

Hypomethylation of DNA 1 2 7 

Immune System Response 1 0 46 

Inhibition of Differentiation 0 0 13 

Interference With Hormone Function 0 1 7 

Malignant Rransformation or Morphological 

Transformation 0 0 13 

Signal Transduction 1 2 51 

a

 Details of the studies are presented in Appendix C. 

b Some hypothesized key events are shown in boldface to emphasize that in at least one of the tables they contain 

much more data than the other categories. 

4.4.1.1. In Vivo Human Studies 

Table C-1 summarizes in vivo human studies. Here and elsewhere in the consideration of 

human studies there was particular interest in the subset of people who develop skin lesions 

(usually keratoses, which are often considered premalignant, or hyperpigmentation) following 

long-term exposure to inorganic arsenic in drinking water. Indeed, four of the six studies related 

to Aberrant Gene or Protein Expression compared groups of people with and without arsenicrelated skin lesions following similar exposures to high levels of inorganic arsenic in drinking 

water, and in three cases, they also compared them to groups of people with much lower 

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inorganic arsenic exposure levels. The genomics study by Argos et al. (2006) showed that 312 

more genes were down-regulated in the group with skin lesions than in the inorganic arsenicexposed group without such lesions. No genes were shown to be up-regulated. Other studies 

showed increased levels of the EGFR-ECD protein (i.e., extracellular domain of the epidermal 

growth factor receptor) in serum (Li et al., 2007), increased levels of transforming growth factor 

alpha (TGF-α) protein in bladder urothelial cells (Valenzuela et al., 2007), and decreased levels 

of three integrins in and around skin lesions following exposures to inorganic arsenic in drinking 

water (Lee et al., 2006b). Integrins are important in the control of differentiation and 

proliferation of the epidermis. Many skin diseases, including arsenical keratosis, show altered 

patterns of integrin distribution and expression. In the first two instances, there were bigger 

increases in the group with skin lesions. The study on integrins only made comparisons to a 

control group. One of the other studies showed a decrease in the concentration of the receptor 

for advanced glycation end products (RAGE) protein in sputum when there was a higher 

concentration of inorganic arsenic in the urine (Lantz et al., 2007). Changes in that biomarker 

are related to several chronic inflammatory diseases in the lung, including lung cancer. The 

remaining study showed that two oncogenes were up-regulated in tumor tissues in patients with 

arsenic-related urothelial cancer, but not in those from patients with non-arsenic-related 

urothelial cancer (Hour et al., 2006). 

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The Chromosomal Aberrations and/or Genetic Instability category has the most entries in 

the table on human studies. Although some of the studies found no effects (usually on SCE 

induction) in people exposed to inorganic As, most of the studies included in the table showed 

clear increases of chromosomal aberrations (CA) in lymphocytes, micronuclei (MN; in various 

cell types), or both CA and MN in people who had been exposed to high levels of inorganic 

arsenic in drinking water or to Fowler’s solution (i.e., a solution containing 1% arsenic that was 

commonly used as a medicine in the 1800s and early 1900s). Arsenic was shown to increase the 

incidence of MN specifically in bladder cells (Warner et al., 1994; Moore et al., 1996, 1997b). 

There also was suggestive evidence that some arsenic-induced MN (a minority of them) result 

from aneuploidy (Moore et al., 1996). There was some evidence for induction of SCE. Three of 

the papers showed that those persons with arsenic-induced skin lesions had higher frequencies of 

induced chromosomal damage seen either as CA or MN than those without lesions (Gonsebatt et 

al., 1997; Ghosh et al., 2006; Banerjee et al., 2007). It is intriguing that one of the studies 

demonstrated an apparent predisposition to both skin lesions and CA that was correlated with 

(and was thus perhaps caused by) a single polymorphism of the ERCC2 (excision repair crosscomplementing rodent repair deficiency gene, complementation group 2) gene, which plays a 

key role in the nucleotide excision repair (NER) pathway. The polymorphism resulted from an 

A→C mutation at codon 751 that caused a change from lysine to glutamine, and the allele 

conferring the higher predisposition in homozygotes had the remarkably high gene frequency of 

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0.40 in that population (Banerjee et al., 2007). Although only some of the homozygotes heavily 

exposed to inorganic arsenic in drinking water developed skin lesions or had chromosomal 

aberrations, those that were affected had both endpoints. 

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Table C-1 also provides data showing that oral inorganic arsenic exposure increases 

DNA damage. Two papers reported oxidative damage to DNA revealed by increases in the 

concentration of 8-hydroxydeoxyguanosine (8-OHdG) in the urine. Both studies were in Japan, 

with the first showing a positive correlation between urinary concentrations of arsenic and 8-

OHdG after analyzing samples from 248 people in the general population (Kimura et al., 2006). 

The other study (Yamauchi et al., 2004) involved clinical examination of 52 patients following 

an incident in which 63 people (four of whom died within about 12 hours of being poisoned) 

were poisoned by eating food contaminated with ATO. Those 52 patients were followed up for 

various effects including levels of 8-OHdG in urine. Maximal levels of ~150% compared to 

normal Japanese levels were reached 30 days after the exposure, and by 180 days the levels had 

returned to normal. The same paper reported that people in Inner Mongolia, China, who drank 

water contaminated with about 130 ppb arsenic had a significant increase in urinary 8-OHdG, 

which returned to normal after they drank “low-arsenic” water for one year. 

Table C-1 includes data that demonstrate DNA damage (i.e., single-strand breaks) 

detected by the single cell gel electrophoresis (SCGE) comet assay. One of those studies, in 

which the high-exposure group drank water containing about 247 ppb As, also included a comet 

assay combined with formamidopyrimidine-DNA glycosylase (FPG) digestion and thereby 

showed that arsenic also induced oxidative base damage. (Digestion with the FPG enzyme 

breaks the DNA at the sites of oxidative damage so that those sites are seen in this modified 

comet assay.) Besides looking at baseline DNA damage, the other comet study investigated the 

capacity of the lymphocytes of subjects who used drinking water containing 13–93 ppb arsenic 

to repair damage induced by an in vitro challenge with the mutagen 2-

acetoxyacetylaminofluorene (2-AAAF). Adducts formed following treatment with 2-AAAF are 

primarily repaired through the NER pathway and lymphocytes from arsenic-exposed individuals 

had more adducts. The lymphocytes from the people with high-arsenic exposure had reduced 

NER ability (Basu et al., 2005). The remaining DNA damage study (Mo et al., 2006) used 8-

oxoguanine DNA glycosylase (OGG1) expression as an indicator of oxidative-induced DNA 

damage. The OGG1 gene codes for an enzyme involved in base excision repair (BER) of 

residues that result from oxidative damage to DNA. OGG1 expression was found to be closely 

linked to the levels of arsenic in drinking water and in toenails, thereby indicating a link between 

ROS damage to DNA and inorganic arsenic exposure. An inverse relationship between OGG1 

expression and selenium (Se) levels in toenails was found, which suggests a possible protective 

effect of Se against arsenic-induced oxidative stress. As was often the case when populating the 

MOA tables in Appendix C, some studies could equally well be placed into one or another 

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hypothesized key event category, and clearly some studies listed under DNA Damage also relate 

to the hypothesized key events of DNA Repair Inhibition or Stimulation and Effects Related to 

Oxidative Stress (ROS). 

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In another polymorphism study, homozygotes for two different alleles of the p53 gene 

were shown to be at higher risk (than those carrying other alleles) of developing arsenic-induced 

keratosis among individuals who used drinking water that contained roughly 180 ppb arsenic 

(De Chaudhuri et al., 2006). Because that gene is so important in controlling apoptosis, that 

study was listed under Apoptosis. It is unclear, however, why mutations at that gene would 

predispose those who consume high levels of arsenic to develop skin lesions. Two studies 

described under DNA Repair Inhibition or Stimulation demonstrated reduced expression of three 

nucleotide excision repair (NER) genes in a population that used drinking water that contained 

10–75 ppb arsenic (Andrew et al., 2003, 2006). Still more evidence that arsenic causes Effects 

Related to Oxidative Stress (ROS) comes from school children in Taiwan who showed a positive 

correlation between urinary concentrations of arsenic and 8-OHdG; no information was provided 

regarding the level of arsenic in their drinking water (Wong et al., 2005). Subjects with arsenicrelated skin lesions from a population in Inner Mongolia, China, that used drinking water with a 

mean of 158 ppb arsenic showed a statistically significant positive correlation between 8-OHdG 

adducts in their urine and individual urinary concentrations of inorganic As, MMA, and DMA. 

In contrast, those without skin lesions showed no correlation (Fujino et al., 2005). 

Evidence is presented under Hypermethylation of DNA that arsenic exposure causes 

hypermethylation of the promoter sequence in the DNA for four tumor suppressor genes. For 

two of the genes, p53 and p16, there was a positive dose-response between arsenic 

contamination of drinking water and the level of effect; however, this was only seen in 

individuals with skin lesions (Chanda et al., 2006). For the other two genes, RASSF1A and 

PRSS3, the association was demonstrated with regard to the level of arsenic consumption 

estimated from toenail clippings (Marsit et al., 2006). Because the Marsit et al. (2006) study was 

done on bladder cancer patients, it provides a potential link between arsenic exposure and 

epigenetic alterations in patients with bladder cancer. The Chanda et al. (2006) study also 

demonstrated hypomethylation in a few individuals, but it was found only in persons having 

prolonged arsenic exposure at high doses. 

Regarding the hypothesized key event category Immune System Response, there was 

suggestive evidence of an association between changes in sensitive markers of lung 

inflammation (i.e., metalloproteinase concentrations in induced sputum) and levels of only about 

20 ppb of arsenic in drinking water. The initial comparison between the high- and low-level 

exposure towns showed no difference with regard to these biomarkers, but a significant 

association appeared when the analysis was adjusted for possible confounding factors (Josyula et 

al., 2006). Islam et al. (2007) found that IgG and IgE levels were significantly elevated in 

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arsenic-exposed individual with skin lesions. More details about that experiment, including 

clinical findings possibly related to inflammatory reactions, are found in Appendix D. Appendix 

D discusses several other studies (including in vitro experiments and experiments on laboratory 

animals) related to immunotoxicity, including some that are not included in any of the tables in 

Appendix C. 

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The only study listed under Gene Mutations gave no more than a hint of an effect 

(Ostrosky-Wegman et al., 1991). Regarding Signal Transduction, a study in Taiwan showed that 

both the levels of plasma TGF-α and the proportion of individuals with TGF-α over-expression 

were significantly higher in the high CAE group than in the control group (Hsu et al., 2006). 

Only limited information from the cited experiments has been included in this discussion. 

 Much more detail on these studies can be found in Table C-1 of Appendix C as well as in Table 

C-2 for in vivo experiments using laboratory animals and Table C-3 for in vitro experiments. 

Brief discussions of the information in Table C-2 and C-3 are found in Sections 4.4.1.2 and 

4.4.1.3, respectively. 

4.4.1.2. In Vivo Experiments Using Laboratory Animals 

Table C-2 summarizes in vivo experiments using laboratory animals. All doses given in 

this section are stated in terms of the amount of arsenic in the dose. Twenty-four of the 112 rows 

in Table C-2 involve studies of nine key event categories in mice that drank water containing 

arsenic for several to many weeks. Results are of particular interest because they involved most 

of the lowest dose levels tested, and AsIII is the most toxic oxidation state of inorganic As. 

Figure 4-1 summarizes the results according to key events by showing, for each endpoint, the 

concentration of arsenic in the water that was the LOEL, the period of treatment, and the organ 

or tissue in which the effect was seen. Because the result for gene mutations was a negative 

finding, it is not shown in the figure. Sometimes more than one entry in Table C-2 corresponds 

to a single item in the figure, and sometimes a single entry in the table deals with separate groups 

of animals. Consequently, there may be multiple LOELs shown in the figure. It should also be 

kept in mind that sometimes only one dose was tested in an experiment, and, of course, if an 

effect was found, that dose became the LOEL (even though a much lower dose might have been 

effective). One benefit of the detailed descriptions found in Table C-2 is that all doses tested are 

listed. As Figure 4-1 shows, roughly half the dose levels used exceed 2,000 ppb and are thus 

much higher than levels ever found in drinking water used for human consumption. While all of 

the experiments summarized in Table C-2 are useful in terms of showing their effects in mice, 

this discussion gives more attention to doses that overlap higher levels of exposure to humans 

from drinking water. A better understanding of the pharmacokinetic characteristics in different 

species may aid in determining the relevance of the high-dose animal studies to human subjects 

exposed to arsenic in drinking water at lower concentrations for a longer period. 

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The Aberrant Gene or Protein Expression effects seen at those lower levels included 

increases in levels of several proteins and in mRNA levels of a few genes that are important in 

angiogenesis and remodeling. For example, vascular endothelial cell growth factor [VEGF] and 

its receptors VEGFR1 and VEGFR2 were measured in hearts, and increases were sometimes 

restricted to areas around blood vessels (Kamat et al., 2005; Soucy et al., 2005). However, 

increases in dose (up to 0.5 ppm in drinking water) and duration (up to 20 weeks) actually 

caused decreases in the protein and mRNA levels for VEGFR1 and VEGFR2, suggesting that 

chronic exposure at these higher levels was toxic to the cardiac vasculature in mice. Consistent 

with the decreased mRNA levels seen for VEGFR1 and VEGFR2 following 20-week chronic 

exposures to 0.5 ppm, the same treatment regimen produced evidence of reduced cell 

proliferation, which was represented as a decrease in the density of microvessels of less than 12 

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μm in the heart (Soucy et al., 2005). These data thus provide an interesting example of the 

concentration and time-dependent effects of arsenic exposure that might be important in the 

etiology of some of the diseases that it causes. In contrast, stimulation of cell proliferation at 

low-dose levels involved increases in (1) blood vessel number in Matrigel implants (Soucy et al., 

2005), (2) tumor growth rates after implantation of tumor cells (Kamat et al., 2005), and (3) 

number of metastases to the lungs after implantation of those tumor cells (Kamat et al., 2005). 

Proteomic analysis of bronchoalveolar lavage fluid from lungs of mice that drank 0.05 

ppm (i.e., 50 ppb) arsenic in water for 4 weeks showed an increase in peroxiredoxin-6 and 

enolase 1 levels and a decrease in GSTO1, RAGE, contraspin, and apolipoproteins A-I and A-IV 

(Lantz et al., 2007). That same paper had demonstrated a decrease in the level of RAGE protein 

in human sputum that was associated with arsenic exposure. Two microarray experiments at 

much higher dose levels of 28.8 and 45 ppm showed changes in expression of dozens of genes 

(Chen et al., 2004b; Lantz and Hays, 2006). In each experiment, the LOEL was the only dose 

tested, which leaves open the possibility that such high doses might not have been necessary to 

obtain these changes. 

Mice that were exposed for 23 weeks to 0.7–5.8 ppm arsenic in drinking water developed 

no skin tumors; however, when they were also exposed to UV thrice weekly for most of that 

time, they showed a strong dose-related increase up through 2.9 ppm As, thus providing strong 

evidence of co-carcinogenesis (Burns et al., 2004). Another part of the same study (reported in 

Uddin et al., 2005) demonstrated that at 2.9 ppm there was oxidative DNA damage caused by the 

co-treatment. Effects Related to Oxidative Stress (ROS) following 26 weeks of exposure at 1.8 

ppm included decreases in GSH content, and in the activities of glucose-6-phosphate 

dehydrogenase (G6PDH), glutathione peroxidase (GPx), and plasma membrane Na+/K+ 

ATPase. Additional changes suggestive of such damage, such as an increase in the 

concentration of malondialdehyde (MDA), were apparent after 9, 12, or 15 months at the same 

dose level (Mazumder, 2005). 

Eighteen of the 112 rows in Table C-2 involved rats that drank water containing sodium 

arsenite for several to many weeks, but those studies are distributed among only two key event 

categories and do not extend down to nearly as many effects at low exposure levels. Most 

experiments cited in the 18 rows involved drinking water containing 57.7 ppm arsenic for 

several to many weeks and showed findings of numerous changes indicative of oxidative damage 

in several organs. A few experiments show differing levels of oxidative damage in different 

regions of the brain (Samuel et al., 2005; Shila et al., 2005a,b). By far the lowest dose tested 

among these experiments was 0.03 ppm As, and it was found to be effective in decreasing the 

GSH level and superoxide radical dismutase (SOD) activity in the liver. The other two dose 

levels tested, 1.4 and 2.9 ppm, caused bigger changes in these two variables, as well as 

additional changes indicative of oxidative stress. It is of interest that the changes per unit dose 

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were much higher for GSH and SOD at 0.03 ppb than they were at the two much higher doses 

tested (Bashir et al., 2006a). In experiments using 5.8 ppm As, which rats drank for 4, 8, or 12 

weeks, activities of catalase (CAT) and SOD in kidney, liver, and RBCs were found to be 

elevated at 4 weeks, but they decreased to baseline levels or lower by 12 weeks; MDA levels 

were always elevated (Nandi et al., 2006). Consumption of water containing 1.4 ppm arsenic for 

60 days led to a demonstrable increase in apoptosis in liver cells (Bashir et al., 2006a). 

Twenty-six of the 112 rows in Table C-2 involve rats or mice that consumed pentavalent 

arsenicals (AsV, MMAV, DMAV, or TMAV) for several to many weeks, and in all but three rows 

they were delivered in drinking water instead of food. As would be expected for these less 

potent forms of arsenic, LOELs were typically high and usually above 50 ppm. Only a few 

results occurred at much lower concentrations, and are mentioned in this discussion. After rats 

were exposed for 28 days to 0.35 ppm arsenic in drinking water in the form of DMAV, 

microarray analysis demonstrated significant effects on the expression of 503 genes (i.e., 11% of 

the genes tested with that microarray) in urothelial cells. Even more genes were affected at the 

three higher doses tested (i.e., 1.4, 14, and 35 ppm As). Most of the effected genes related to the 

functional categories of apoptosis, cell cycle regulation, adhesion, signal transduction, stress 

response, or growth factor and hormone receptors. There was a change in the types of genes 

affected at the different doses, particularly when comparing the higher two doses (both 

cytotoxic) with the two non-cytotoxic doses (Sen et al., 2005). When rats were exposed to 0.24 

ppm AsV for 1 or 4 months in drinking water, changes in signal transduction were increased 

expression of integrin-linked kinase (ILK) and decreased expression of phosphatase and tensin 

homolog (PTEN) in the liver. At higher doses, the expression of these genes and additional 

cancer-related genes was affected (Cui et al., 2004b). 

DNA damage (both fragmentation and oxidative) was demonstrated in peripheral blood 

leukocytes of mice using the comet assay following exposure of 50, 200, or 500 ppb arsenic in 

drinking water in the form of AsV for 3 months with and without a low-Se diet. Arsenic caused 

increased DNA fragmentation only in mice consuming the low-Se diet, and induced oxidative 

damage only in mice consuming the normal-Se diet. Neither case showed a positive doseresponse (Palus et al., 2006). In lung adenocarcinomas from mice exposed for 18 months to 

0.24, 2.4, or 24 ppm AsV in drinking water, there was an increase in the extent of 

hypermethylation of promoter regions of tumor suppressor genes p16INK4a and RASSF1A 

(genes frequently found inactivated in many types of cancer including lung cancer), based on 

methylation-specific polymerase chain reaction (PCR). All doses had an effect, and there was a 

positive dose-response. Reduced expression or lack of expression of these two genes was 

correlated with the extent of hypermethylation. Mice without tumors, whether control or 

arsenic-treated, had normal (i.e., not reduced or eliminated) expression of these genes in their 

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lungs. The authors concluded that epigenetic changes of tumor suppressor genes are involved in 

inorganic arsenic-induced lung carcinogenesis (Cui et al., 2006). 

Of the experiments described in Table C-2 in which arsenic exposure occurred through 

consumption of arsenic in drinking water or food, the only group not yet discussed consists of 

the series of experiments in which pregnant female mice drank water containing 42.5 or 85 ppm 

arsenic in the form of sodium arsenite for 10 days on gestation days 8 to 18. These studies 

follow up on the interesting observation that arsenic seems to be a complete carcinogen in mice 

following such a treatment. The offspring were observed for effects (sometimes only after they 

had grown to be adults), and results are categorized in Table C-2 under Aberrant Gene or Protein 

Expression, Cell Proliferation or Stimulation, Hypomethylation of DNA, and Signal 

Transduction. Some of the more noteworthy findings were as follows. Numerous microchip 

analyses were conducted, often with some of the findings confirmed by real-time (RT) PCR. 

Microarrays containing from 588 to 22,000 genes were used. It was not unusual to find changes 

in the expression of scores of genes (sometimes even of thousands) in the different studies. 

Changes (often many-fold) included both increases and decreases of expression, occurring at 

both dose levels. Some of the many types of genes often altered included oncogenes, HCC 

biomarkers, cell proliferation-related genes, stress proteins, insulin-like growth factors, estrogenlinked genes, and genes involved in cell-cell communication. Tissues in which gene expression 

changes were found in offspring that had been exposed to arsenic in utero included: (1) arsenicinduced HCC tumors that developed in adult males, (2) normal-appearing cells in livers of adult 

males, (3) fetal livers of males right at the end of treatment, (4) livers of newborn males, (5) fetal 

lungs of females right at the end of treatment, and (6) arsenic-induced adenomas and 

adenocarcinomas that developed in lungs of adult females. 

The expression of three estrogen-related genes was shown to increase synergistically in 

the uteri of females (at 11 days of age) that had been exposed in utero to arsenic and also 

subcutaneously injected with diethylstilbestrol (DES) on the first 5 days after birth. These and 

other results showed that inorganic arsenic acts with estrogens to enhance production of 

urogenital cancers in female mice (Waalkes et al., 2006a). Females that had been exposed to 

arsenic in utero and then received a 21-week post-weaning treatment with TPA showed changes 

in gene expression that were similar to those seen in liver samples from males that had received 

only the arsenic treatment in utero. This is interesting because it parallels another situation in 

which TPA-treated females showed a response similar to males without TPA treatment. 

Specifically, female mice exposed in utero to arsenic develop HCC only after TPA treatment 

(Liu et al., 2006b); however, male mice exposed in utero to arsenic develop those tumors without 

receiving any TPA treatment. Observed changes in estrogen-related genes sometimes seemed 

especially important in the interpretation of results, and fetal lungs of females exposed to arsenic 

in utero showed a large increase in estrogen receptor-alpha (ER-α), as well as several other 

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estrogen-related genes and numerous other genes, including some associated with lung cancer. 

There also was a large increase in nuclear ER-α in adenomas and adenocarcinomas that 

developed in the lungs of adult females that had been exposed to arsenic in utero (Shen et al., 

2007). 

Stimulation of cell proliferation during treatment of males while in utero at 85 ppm 

induced kidney cystic tubular hyperplasia in 23% of the animals, and although males did not 

develop bladder hyperplasia from the arsenic treatment alone, they often did if treated in 

conjunction with DES or tamoxifen on the first 5 days after birth because of a synergistic 

interaction that occurred with those chemicals. Although females exposed while in utero showed 

bladder hyperplasia similar to the males, arsenic exposure in utero alone caused no hyperplasia 

in their kidneys (Waalkes et al., 2006a,b). Global hypomethylation of GC-rich regions was 

demonstrated in livers of newborn males that received 85 ppm in utero (Xie et al., 2007). 

Almost all remaining experiments summarized in Table C-2 involved treatments of mice 

or rats by gavage, and those results are summarized under Aberrant Gene or Protein Expression, 

Apoptosis, Chromosomal Aberrations and/or Genetic Instability, Effects Related to Oxidative 

Stress (ROS), and Interference With Hormone Function. In all rows where AsIII

 was 

administered, it was usually as sodium arsenite, but sometimes as arsenic trioxide (ATO). One 

study also included treatment with pentavalent arsenicals. By using gavage, the amount of the 

arsenical administered to each animal was controlled precisely, and it was given as a certain 

weight of arsenic per animal, often with adjustment to the individual weight of each animal (i.e., 

μg/animal or mg/kg bw, respectively). Most treatments were administered repeatedly, with 

treatment regimens in one case lasting an entire year. As in all other studies on experimental 

animals, there was an attempt here to state all doses in terms of the amount of arsenic. Because 

it was unclear from the reporting of a few experiments whether doses were expressed as arsenic 

compound or as As, Table C-2 always makes it clear whether or not such a correction was made. 

 In a gavage study with one of the smallest amounts of arsenic per dose (equivalent to 36 

μg/mouse if a mouse weighed 25 g), Patra et al. (2005) found induction of chromosomal 

aberrations in mice that received 1.44 mg As/kg bw given as sodium arsenite by gavage onceper-week for 4 weeks. Induction of chromosomal aberrations also was seen after 5 and 6 

treatments; however, 7 and 8 treatments were lethal to the mice. A 25 g mouse in that study 

would have received the same amount of arsenic in that one day if it had drunk water that 

contained 6 ppm arsenic (assuming that it drank 6 mL of water, which would be a reasonable 

amount for a mouse). 

In the only gavage study with in utero treatments, 9 daily treatments of 4.35 mg As/kg 

bw was shown to increase the activity of the selenoprotein iodothyronine deiodinase-II (DI-II) in 

fetal brains and to decrease the activity of the selenoprotein TrxR in fetal livers. In both cases, 

these results were observed only if the mice were on a Se-deficient diet (Miyazaki et al., 2005). 

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In a gavage study lasting a full year (Das et al., 2005), mice were administered 50, 100, or 150 

μg/mouse, 6 days a week for 3, 6, 9, or 12 months; it took 9 months before substantial increases 

were seen in the activities of tumor necrosis factor alpha (TNF-α) and interleukin (IL)-6 at any 

dose, but by then all doses had an effect and there was a positive dose-response. Three months 

later, both effects had increased substantially at all doses, still with a positive dose-response. A 

similar response was seen for the concentration of total collagen, although increases were not as 

large in comparison to the control group. That same study examined six components of the 

antioxidant defense system and found numerous interesting changes over time. While all of the 

affected components had a LOEL of 50 μg at the 3-, 9-, and 12-month test periods, all five 

affected components had a LOEL of 100 μg at 6 months. GSH levels and activities of GPx and 

CAT increased by 3 months, but decreased by 9 and 12 months. In another experiment with 

single, large doses of AsIII or AsV given to mice by gavage, there were large increases in heme 

oxygenase 1 (HMOX-1) activity within 6 hours in liver and kidney but not in the brain. The 

effect was somewhat higher with AsIII, but DMAV had no effect. This study also tested some 

much smaller doses, and a dose as high as 2.25 mg/kg bw had no effect on this endpoint in 

kidneys (Kenyon et al., 2005b). 

Various biochemical indicators of apoptosis were seen in brain and liver 24 hours after 

giving rats a single high dose of sodium arsenite by gavage (Bashir et al., 2006b). The same 

paper showed that single, large doses of sodium arsenite given to rats by gavage affected many 

biochemical indicators of oxidative stress in liver and brain 24 hours after treatment. Some 

studies on Effects Related to Oxidative Stress (ROS) included co-treatments with antioxidants 

that were shown to reduce the level of effects seen (Modi et al., 2006; Sohini and Rana, 2007). 

With regard to Interference With Hormone Function, rats given 30.3 mg AsIII/kg bw as ATO by 

gavage every other day for 30 days were shown to have a large increase in the levels of thyroid 

hormones triiodothyronine (T3) and thyroxine (T4) in their blood serum (Rana and Allen, 2006). 

4.4.1.3. In Vitro Experiments 

Table C-3 summarizes a large number of in vitro experiments; and some highlights are 

discussed below. The potencies of many arsenicals, including both trivalent and pentavalent 

forms, have been compared in several series of experiments, with the obvious conclusion that the 

pentavalent forms almost always have much higher LOECs (e.g., Moore et al., 1997a; Sakurai et 

al., 1998; Petrick et al., 2000; Drobná et al., 2002; Kligerman et al., 2003). Consequently, the 

discussion below does not focus on the studies that analyzed pentavalent arsenicals. 

Three chemical properties of arsenic likely to account for its biological activity are: 

(1) the soft acid/soft base principle (which is related to trivalent arsenicals and sulfhydryl 

binding); (2) the nucleophilicity of trivalent arsenicals; and (3) the formation of free radicals, 

ROS, or both by arsenicals (Kitchin et al., 2003). As noted by Kitchin et al. (2003): 

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of action of arsenic carcinogenesis may include altered DNA repair, altered growth 

factors, cell proliferation, altered DNA methylation patterns and promotion of 

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Arsenic is readily absorbed from the GI tract in humans and is primarily transported in 

the blood bound to sulfhydryl groups in proteins and low-molecular-weight compounds, such as 

amino acids and peptides (NRC, 1999). At any given time, about 99% of absorbed AsIII is bound 

to tissue sulfhydryls, mostly to monothiol sites (Kitchin and Wallace, 2006). Based on the 

results of their peptide binding studies, Kitchin and Wallace (2006) suggested that dithiol- and 

trithiol-binding sites would be “the most likely causal triggers of biological effects because of 

their stronger affinity and because the bi- and tri-dentate complexes last so much longer than the 

rapidly dissociating and reforming binding of arsenite to monothiol sites.” While the AsIII

attachment to the monothiol-binding sites are short-lived, a substantial part of the total AsIII

attaches to those sites because of their great abundance in mammals. Because the functional 

group of the amino acid cysteine in a protein or peptide is a thiol group, any proteins that contain 

cysteine are of importance for interactions with AsIII. Although Table C-3 includes large 

amounts of data under Effects Related to Oxidative Stress (ROS), arsenic’s action as a soft acid 

and its nucleophilicity are not included as key events. It is obvious, nonetheless, that those 

chemical properties play important roles in the interactions of inorganic arsenic with organisms 

at early stages in multiple key event(s) leading to tumor development. 

Table C-3 summarizes a great deal of data under Aberrant Gene or Protein Expression. 

Abundant evidence is presented showing that changes can easily occur at concentrations of AsIII

(as either sodium arsenite or arsenic trioxide) of less than 10 μM and often with durations of 

exposure of 24 hours or less. Results from 10 microarray analyses are found in this category, 

and they all demonstrated changes in expression of large numbers of genes, often numbering in 

the hundreds. Two studies with longer exposures to especially low concentrations are of special 

interest. In one study, NB4 cells were exposed to 0.5 μM ATO for periods up to 72 hours for 

transcriptome analysis and up to 48 hours for proteomic analysis. The regulation of 487 genes 

was affected at the transcriptome level; however, at the proteome level, 982 protein spots were 

affected. The finding of more significant changes at the proteomic level, in comparison with the 

relatively minor changes found at many of the corresponding genes at the transcriptome level, 

suggests that ATO particularly enhances mechanisms of post-transcriptional/translational 

modification (Zheng et al., 2005). In the second experiment, which was a cDNA 

(complementary DNA) microarray analysis of about 2,000 genes, the LOECs for SV40 large Ttransformed human urothelial cells (SV-HUC-1) exposed to AsIII, MMAIII, or DMAIII for 25 

passages (with subculturing twice weekly) were found to be 0.5, 0.05, and 0.2 μM, respectively. 

DMAIII was shown to have a substantially different gene profile from the other two arsenicals. 

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Most genes were down-regulated by these arsenicals, and evidence suggested that the 

suppression of two of these genes resulted from epigenetic hypermethylation (Su et al., 2006). 

Since each finding is presented only one time in Table C-3, subjectivity was often involved in 

the placement of data into the different key event categories. As a result, the densities of data in 

the different categories presented in Table 4-1 are only approximate estimates. This situation 

was especially common for several key event categories that have large densities of data: 

Aberrant Gene or Protein Expression, Signal Transduction, and Effects Related to Oxidative 

Stress (ROS). 

Table C-3 also presents details on the genes and proteins affected and changes related to 

dose and time. It also provides the possible significance of such changes, when available. A few 

examples follow. When primary normal human epidermal keratinocytes (NHEK) cells were 

exposed to 1 μM sodium arsenite for 24, 48, and 72 hours, there was an increase in focal 

adhesion kinase (FAK) protein at 24 hours followed by a decrease to below the background level 

at later times, with almost none being present at 72 hours (Lee et al., 2006b). The concentration 

of some enzymes increased after exposures to 0.5 μM for 24 hours, but the concentrations 

decreased at higher levels of exposure up to 25 μM (Snow et al., 2001). DuMond and Singh 

(2007) demonstrated the same relationship for proliferating cell nuclear antigen (PCNA) with 

exposures to sodium arsenite lasting 70 days. The expression of PCNA increased at 0.008 μM, 

but decreased at 0.77 and 7.7 μM. Similar results have been observed for telomerase activity 

(Zhang et al., 2003). Numerous studies investigated effects of various modulators or inhibitors 

or of different genetic conditions (e.g., knockout mutations or transfections). Cell type can have 

a major influence on the effect of arsenic on protein expression, as was shown for p53 

expression, with some cells having no response to 50 μM sodium arsenite for 24 hours while 

other cells showed an increase after exposure to only 1 μM sodium arsenite (Salazar et al., 1997). 

 Clearly, small levels of arsenic exposure can have large effects on many genes and proteins, and 

the relationships involving time and dose can be complicated and subject to many influences. 

Results found in the Apoptosis category show that ATO and sodium arsenite can often 

induce apoptosis in cells with exposures to less than 10 μM (often much less) for a few days or 

less. Zhang et al. (2003) demonstrated a large difference in the sensitivity of cell lines to 

arsenic-induced apoptosis. The authors found a positive association between telomerase activity 

in cell lines and their susceptibility to induction of apoptosis by exposure to sodium arsenite. 

Exposure to extremely low concentrations of sodium arsenite (i.e., 0.1–1 μM in HaCaT cells and 

0.1–0.5 μM in HL-60 cells) for 5 days increased telomerase activity, maintained or elongated 

telomere length, and promoted cell proliferation. At higher concentrations, exposure of these 

cell lines to sodium arsenite for 5 days decreased telomerase activity, decreased telomere length, 

and induced apoptosis. The positive association noted earlier means that cell lines that innately 

have more telomerase activity are more likely to be affected by sodium arsenite in inducing 

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apoptosis. Many experiments tested effects of modulators on the arsenic-induced apoptosis. For 

example, Chen et al. (2006) demonstrated that co-treatment with L-buthionine-S,R-sulphoximine 

(BSO) markedly increased induction of apoptosis, presumably because of its effect in decreasing 

GSH levels. Other experiments looked at the effects of inhibitors of various proteins involved in 

signal transduction pathways. For example, Lunghi et al. (2005) showed that use of MAP/ERK 

kinase (MEK) 1 inhibitors greatly increased ATO-induced apoptosis. Other studies showed that 

different genetic conditions established using knockout mutations or transfections could 

markedly affect the extent of arsenic-induced apoptosis (e.g., Bustamante et al., 2005; Poonepalli 

et al., 2005; Ouyang et al., 2007). Many of the experiments related to apoptosis were motivated 

by the desire to improve methods for using ATO in cancer therapy, but in the process they have 

provided much additional information about the complex pathways by which arsenic can affect 

apoptosis. 

In the hypothesized key event category Cancer Promotion, Tsuchiya et al. (2005) tested 

sodium arsenite and three pentavalent arsenicals in a two-stage transformation assay in BALB/c 

3T3 A31-1-1 cells. Sodium arsenite caused cancer promotion at a LOEC of 0.5 μM when the 

initiating treatment was exposure to 0.2 μg/mL 20-methylcholanthrene for 3 days before the 18-

day post-treatment with sodium arsenite. Sodium arsenite caused promotion at a LOEC of 1 μM 

when the initiating treatment was exposure to 10 μM sodium arsenite for 3 days before the 18-

day post treatment with sodium arsenite. When AsV was tested in the same way with the same 

initiating treatments, it was somewhat less potent, with LOECs of 1 and 5 μM respectively. The 

two methylated arsenicals had little or no effect. Paralleling their cancer promotion effects, the 

same study demonstrated LOECs for AsIII and AsV of 0.7 and 5 μM, respectively, for inhibition 

of gap-junctional intercellular communication, which is a mechanism linked to many tumor 

promoters. 

The Cell Cycle Arrest or Reduced Proliferation category includes many experiments that 

showed that levels of exposure to ATO and sodium arsenite of less than 10 μM (often much less) 

for a few days or less can often increase the numbers of cells in mitosis and otherwise disrupt 

mitosis, so as to reduce cell proliferation. In the Drobná et al. (2002) experiment, the LOECs for 

reduced cell proliferation were 1, 1, and 5 μM for 24-hour exposures to AsIII, MMAIII, and 

DMAIII, respectively; no effects were seen following exposures to the pentavalent forms of these 

arsenicals at 200 μM. By testing cells enriched in different phases of the cell cycle using 

centrifugal elutriation, McCollum et al. (2005) showed that AsIII slowed cell growth in every 

phase of the cell cycle. Cell passage from any cell cycle phase to the next was inhibited by 5 μM 

sodium arsenite. By looking at caspase activity, they showed that AsIII-induced apoptosis 

specifically in cell populations delayed in the G2/M phase. Tests with knockout mutations 

showed that poly(adenosine diphosphate–ribose) polymerase-1 (PARP-1) (Poonepalli et al., 

2005) and securin (Chao et al., 2006a) protect against arsenic-induced cell cycle disruption. Yih 

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et al. (2005) provided evidence that 1 μM sodium arsenite appears to inhibit activation of the G2 

DNA damage checkpoint and thereby allows cells with damaged DNA to proceed from G2 into 

mitosis. 

Extremely small concentrations of AsIII can stimulate cell proliferation. For example, 

0.005 μM sodium arsenite exposure for 24 hours stimulated cell proliferation in NHEK; 

however, concentrations of 0.05 μM or higher inhibited it (Vega et al., 2001). In other studies, 

stimulation occurred at much higher concentrations. Mudipalli et al. (2005) exposed NHEK 

cells to many exposure levels of AsIII, MMAIII, and DMAIII for 24 hours. The LOECs were 2, 

0.5, and 0.6 μM, respectively. There was increased stimulation of cell proliferation up to doses 

of 6, 0.8, and 0.6 μM, respectively, and in all cases significant cytotoxicity was observed at 

higher doses. Proliferation was often stimulated to a considerable extent. Yang et al. (2007) 

showed that human embryo lung fibroblast (HELF) cells exposed to 0.5 μM sodium arsenite for 

24 hours had 175% of the cell proliferation efficiency of control cells. When the concentration 

of AsIII was increased to 5 μM, however, the cell proliferation efficiency decreased to 60% that 

of the control. The increased proliferation rates can extend over long periods, as shown by 

Bredfeldt et al. (2006), who exposed UROtsa cells to 0.05 μM MMAIII for 12, 24, or 52 weeks. 

Cell population doubling times were 27, 25, and 21 hours, respectively, in comparison to the 42 

hours observed in the control. 

Mutations can play an important part in initiating carcinogenesis or in the development of 

cancers, and they range from gene mutations that involve a single base-pair change to 

chromosomal aberrations (CAs). Much evidence is presented in Table C-3 under Chromosomal 

Aberrations and/or Genetic Instability to show that inorganic arsenic can induce CAs, SCEs, 

MN, multilocus deletions, and several other endpoints such as changes in the length of 

telomeres. Arsenic appears to be ineffective in inducing gene (point) mutations, but mutations at 

some genes tend to be deletions that are so large that they extend over several genes (termed 

multilocus deletions). These multilocus deletions have been grouped with CA in Table C-3. 

CD59 mutations (Liu et al., 2005) and gpt mutations (Klein et al., 2007) provide examples of 

such mutations. Numerous experiments are summarized in Table C-3 that show that CAs can be 

induced by exposure to 10 μM or less of sodium arsenite for periods of 24 hours or less. 

Following exposures of human primary peripheral blood lymphocytes for 24 hours, LOECs for 

AsIII, MMAIII, and DMAIII were 2.5, 0.6, and 1.35 μM, respectively (Kligerman et al., 2003). 

Examination of data shown in the table for the few other experiments on MMAIII and DMAIII are 

consistent with this experiment in suggesting that both of those methylated arsenicals tend to be 

more effective in inducing CAs than AsIII. The table includes estimates of about 15 LOECs for 

induction of SCEs and about 20 LOECs for induction of MN following exposure to AsIII, and it 

appears that CAs, SCEs, and MN are all induced to roughly the same extent by AsIII. Some 

experiments fail to show a dose-response, which makes them difficult to interpret. 

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Several of the experiments on CAs provided evidence of arsenic-induced changes in 

chromosome number (e.g., Barrett et al., 1989; Ochi et al., 2004). In the Ochi et al. (2004) 

experiment, DMAIII was much more potent than AsIII, and it induced mitotic spindle, 

centrosome, and microtubule elongation abnormalities. Experiments on induction of MN were 

conducted in such a way as to distinguish between MN caused by aneuploidy and those caused 

by chromosomal breakage; these experiments provided evidence that both mechanisms may be 

important (e.g., Colognato et al., 2007; Ramírez et al., 2007). Chou et al. (2001) showed that 

exposure to 0.25 μM ATO for 4 weeks caused a decrease in telomere length. Mouse embryo 

fibroblasts that are homozygous for the PARP knockout mutation were shown to be much more 

sensitive to both arsenite-induced telomere attrition and induction of MN by AsIII (Poonepalli et 

al., 2005). Many experiments investigated the effects of various modulators on induction of 

arsenic-induced chromosomal damage. For example, Jan et al. (2006) found that co-treatment 

with low concentrations of dimercaptosuccinic acid, meso 2,3-dimercaptosuccinic acid (DMSA), 

or 2,3-dimercaptopropane-1-sulfonic acid (DMPS) markedly increased the induction of MN by 

sodium arsenite, ATO, MMAIII, and DMAIII, while co-treatment with high concentrations of the 

same chemicals decreased the ability of arsenic to induce MN. Although the authors stated that 

the reasons are obscure why these dithiol compounds effectively enhanced the toxic effects of 

arsenic when they were at micromolar concentrations, they speculated that the observed results 

might be related to the influence of dithiols on retention of arsenite in cells, with low 

concentrations of dithiols increasing arsenite levels and high concentrations of dithiol decreasing 

them. Ramírez et al. (2007) also showed that co-treatment with SAM blocked AsIII induction of 

centromere positive (cen+) MN without having any effect on its induction of centromere 

negative (cen-) MN. The authors suggested that the reason for this might be that SAM in some 

way influences some components (probably microtubules) of the mitotic spindle. As the main 

methyl group donor, SAM plays a major role in chromatin methylation and condensation, and it 

might stop the lagging of chromosomes by in some way correcting the cell's methylation status. 

Alternatively, they suggested that SAM might interfere with the effects of ROS in causing 

aneuploidy. Whatever SAM does to block induction of cen+ MN, it does not appear to affect 

induction of double strand DNA breaks that would lead to cen- MN. 

The results from the Co-Carcinogenesis category all relate to promotion of 

benzo[a]pyrene (B[a]P)-mediated carcinogenesis via exposure to 1.5 μM sodium arsenite for 12 

weeks. Transformation (i.e., anchorage-independent growth in soft agar) of a rat lung epithelial 

cell line occurred because of the arsenite treatment alone, and the transformed cells were shown 

by proteomic analysis to have changes in the amounts present of many proteins. When the 

arsenite treatment was preceded by exposure to 100 nM B[a]P for 24 hours, there was a 

synergistic interaction. Results indicate that the transformation rate increased more than 500 and 

200 times when compared to arsenite and B[a]P treatments alone, respectively. The findings in 

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the proteomic analysis also showed synergistic interactions (Lau and Chiu, 2006). BPDE 

(benzo[a]pyrene diol epoxide) is an active metabolite of B[a]P. Shen et al. (2006) showed that a 

24-hour pretreatment of GM04312C cells, a SV-40 transformed XPA human fibroblast NERdeficient cell line, with 10 or 50 μM AsIII markedly increased the cellular uptake of BPDE in a 

dose-dependent manner. 

The results found under Co-Mutagenesis showed that AsIII affected the induction of 

mutations (using different assays) when there was also a treatment with UV, diepoxybutane 

(DEB), methyl methanesulfonate (MMS), X-radiation, gamma-radiation, or N-methyl-Nnitrosourea (MNU). Many of the types of mutations affected were gene mutations (i.e., point 

mutations and numerous other changes in the DNA of single genes, such as small deficiencies), 

which are not normally induced by arsenic alone. Arsenic treatment also caused co-mutagenesis 

regarding CAs and MN. Sometimes the timing of the AsIII treatment relative to the treatment 

with the other agent was of importance to the result observed. For example, a 24-hour 

pretreatment with 10 μM sodium arsenite reduced the frequency of induction of hypoxanthineguanine phosphoribosyltransferase (HGPRT) mutations by MMS, but a 24-hour post-treatment 

with the same concentration of sodium arsenite caused a synergistic interaction with MMS in 

induction of HGPRT gene mutations (Lee et al., 1986). 

The data found in Table C-3 under Cytotoxicity are sometimes important to help 

determine the possible relevance to human health of findings related to other key events. For 

example, a large arsenic-induced increase in the expression of some protein that is important in 

signal transduction is much more likely to have such relevance if it occurs at concentrations 

having little or no cytotoxicity than if it occurs only when most cells are dying. Table C-3 shows 

that large differences in LOECs for cytotoxicity can result from a change in any of the following 

variables: species of arsenic, duration of treatment, cell line, and particular assay used. As 

another example, LOECs of AsIII were 0.1 and 50 μM after 24-hour exposures in Jurkat cells and 

HeLa cells, respectively (Salazar et al., 1997). Petrick et al. (2000) showed that three different 

cytotoxicity assays yielded substantially different 24-hour LC50s for each of five different 

arsenic species. Sometimes the different assays yield more similar results when treatments last 

at least 48 hours (Komissarova et al., 2005). Overall it appears that in comparison to AsIII, 

MMAIII has substantially higher cytotoxicity, DMAIII has higher cytotoxicity, and AsV has 

substantially lower cytotoxicity. 

Effects of modulators on arsenic-induced cytotoxicity were tested in many experiments. 

Snow et al. (1999) showed that pretreatment with BSO, to decrease GSH levels, markedly 

increased cytotoxicity of sodium arsenite following a 48-hour exposure. Jan et al. (2006) found 

that co-treatment with low concentrations of DMSA or DMPS (dithiols that are currently used to 

treat arsenic poisoning) markedly increased the cytotoxicity of ATO, while co-treatment with 

high concentrations of DMSA or DMPS had the opposite effect. Probably the most important 

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observation related to cytotoxicity from perusal of Table C-3 is that exposure of a large number 

of different cell lines to trivalent arsenicals results in significant cytotoxicity at molarities 

smaller than what would be found in urine, or even in the blood streams, of individuals exposed 

to high levels of inorganic arsenic in drinking water in places like Bangladesh. In some cell 

lines, even the pentavalent arsenicals destroyed more than 50% of the cells following a 7-day 

exposure with concentrations such as those observed in Bangladesh; AsIII and MMAIII would do 

the same at concentrations far below such levels (Wang et al., 2007). Also, from the numerous 

dose-response curves published in those papers, it is apparent that cytotoxicity generally has a 

threshold below which there is no apparent effect. 

DNA Damage is another key event category for which many experimental data are 

summarized in Table C-3. Evidence showed induction of oxidative DNA damage, DNA singlestrand breaks, and DNA-protein crosslinks by exposures at 10 μM (and often much less) of AsIII

for periods of often much less than one day. MMAIII is especially effective in inducing damage 

detected by the comet assay (Gómez et al., 2005). Much more DNA damage was detected in the 

comet assay by using enzyme treatments to reveal oxidative DNA adducts and DNA protein 

crosslinks, and DNA damage was induced at levels of sodium arsenite that caused no 

cytotoxicity in two different cell types (Wang et al., 2001). In a third cell type, no DNA damage 

was observed up to the maximum concentration tested (2 μM), even though in each of the other 

two cell types the LOEC was 0.25 μM. Jan et al. (2006) found that co-treatment with low 

concentrations of DMSA or DMPS markedly increased the DNA damage detected by the comet 

assay following treatment with ATO, while co-treatment with high concentrations of DMSA or 

DMPS had the opposite effect. Several experiments looked at induction of 8-OHdG formation 

as a measure of oxidative DNA damage. In one such experiment, sodium arsenite was shown to 

be effective. However, MMAIII was shown to be about 200 times more effective than AsIII (with 

an LOEC of 0.05 μM) following a 1-hour treatment (Eblin et al., 2006). Pre-incubation with 

SOD or catalase to reduce effects of ROS almost completely blocked induction of 8-OHdG 

formation by a 24-hour treatment with sodium arsenite (Ding et al., 2005). Tests with a cell line 

containing a knockout mutation of the PARP-1 gene showed that the PARP-1 protein protects 

against arsenic-induced DNA damage detected by the comet assay at pH >13 in the version of 

the assay that does not include further digestion to detect additional types of DNA damage 

(Poonepalli et al., 2005). 

The DNA Repair Inhibition or Stimulation category includes rather few experiments in 

Table C-3. A microarray experiment that showed decreased expression of DNA repair genes 

involved exposure to only 0.77 μM of sodium arsenite for 70 days (DuMond and Singh, 2007). 

Arsenic does not always have the effect of decreasing repair. Snow et al. (2005) found that 

W138 cells exposed to 0.1 μM sodium arsenite for 24 hours showed increased DNA ligase 

activity. Increasing the AsIII concentration to 1 μM further increased the activity, but 5 μM 

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decreased DNA ligase activity to below normal levels. The same paper demonstrated a rather 

similar reversal-of-direction effect for DNA polymerase β. In another experiment, when CHO 

K1 cells were treated with MMS followed by 5 μM sodium arsenite for 6 hours, there was a 

decrease in repair of MMS-induced single-strand breaks in DNA (Lee-Chen et al., 1993). 

Andrew et al. (2006) demonstrated that in Jurkat cells the LOEC for sodium arsenite was 0.01 

μM for reduction of expression of NER gene ERCC1 (excision repair cross-complement 1 

component). The decrease in expression was 45% at that concentration and 60% at 

concentrations of 0.1 and 1 μM. The functional effect of this decrease in expression was shown 

by reduced repair following a challenge with the mutagen 2-AAAF immediately after the sodium 

arsenite treatment. Clearly, exposure to inorganic arsenic at low concentrations can modify the 

level of DNA repair. 

The Effects Related to Oxidative Stress (ROS) category in Table C-3 includes many 

experiments in which antioxidants or radical scavengers were used as modulators. When a 

reduction in the effects was seen, it was taken as evidence that oxidative stress was the cause of 

the original effects observed, as, for example, in the study by Sasaki et al. (2007). Results from a 

series of experiments by Lynn et al. (2000) led to the conclusion that AsIII activates NADH 

oxidase to produce superoxide, which then causes oxidative damage to DNA. Experiments by 

Liu et al. (2005) dealt with the effects of various modulators on induction of CD59- mutations 

and lead to the conclusion that peroxynitrites, which are formed as a result of ROS and reactive 

nitrogen species, have an important role in the induction by AsIII of such mutations. Wang et al. 

(2007) measured formation of oxidative damage to lipids, proteins, and DNA (comet assay) by 

three trivalent arsenicals and three pentavalent arsenicals in two different cell lines. For AsIII, 

AsV, MMAIII, and DMAIII, the LOECs were all 0.2 μM for a 24-hour exposure for all three types 

of damage. The order of effectiveness of the different arsenicals differed in the two cell lines 

used and for the different types of damage. Consistent with these effects, increased levels of 

nitric oxide, superoxide ions, hydrogen peroxide, and the cellular free iron pool were 

consistently detected in both cell lines after treatments by all three trivalent arsenicals. A 

microarray analysis in which genes were identified for which the response to ATO and hydrogen 

peroxide was reversed by n-acetyl-cysteine (NAC) suggested that 26% of the genes significantly 

responsive to ATO were directly altered by ROS (Chou et al., 2005). Further evidence that ROS 

is likely involved in arsenite-induced DNA damage comes from comet assays done on splenic 

lymphocytes from SOD knockout mice (Kligerman and Tennant, 2007). Results showed 

homozygotes exhibiting a large decrease in splenic SOD levels and a large increase in arseniteinduced DNA damage, while heterozygotes had intermediate changes in SOD levels and DNA 

damage. 

Table C-3 includes little information on Enzyme Activity Inhibition. Hu et al. (1998) and 

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in vitro, including enzymes required for DNA repair and some related to GSH metabolism. The 

purpose of the study was to examine whether AsIII binding to sulfhydryls caused protein 

denaturation and inhibited enzyme activity. In almost all cases, the purified enzymes were not 

inhibited by physiologically relevant concentration of AsIII. The concentrations that are needed 

to cause 50% inhibition (IC50s) for the rate of the reaction (over 6 minutes for many of those 

enzymes) ranged from 6.3 to 381 mM. The one exception was purified pyruvate dehydrogenase 

for which the IC50 was 5.6 μM. Table C-3 also lists IC50s for GSH peroxidase and ligase when 

tested in extracts of AG06 (SV40-transformed human keratinocyte) cells that were pretreated for 

24 hours with an unspecified concentration of sodium arsenite; these IC50s were both low, i.e., 

2.0 and 14.5 μM, respectively. 

Table C-3, under Gene Amplification, shows that AsIII caused amplification of 

dihydrofolate reductase (dhfr) genes in three different experiments with LOECs ranging from 

0.0125 to 6 μM (Barrett et al., 1989; Rossman and Wolosin, 1992; Mure et al., 2003). Takahashi 

et al. (2002) showed that several neoplastic transformed cell lines produced by 48-hour 

treatments with either ≤ 8 μM AsIII

 or ≤ 150 μM AsV contained gene amplification of either the 

c-Ha-ras or the c-myc oncogene. Almost all of the data in Table C-3 for Gene Mutations show 

no induction of mutations by arsenic. 

Hypermethylation of DNA was demonstrated in a number of specific DNA sequences in 

two human kidney carcinoma cell lines and in one human lung carcinoma cell line. In the lung 

cell line, the LOEC for AsIII was 0.08 μM for a 7-day exposure, and there was a positive doseresponse extending over the two higher doses tested (0.4 and 2.0 μM). Hypermethylation in this 

cell line was demonstrated within a 341-base-pair fragment of the promoter region of p53 (Mass 

and Wang, 1997; Zhong and Mass, 2001). 

Hypomethylation of DNA has been demonstrated globally and for a number of specific 

DNA sequences. In one instance, exposure of HaCaT cells to 0.2 μM sodium arsenite for 10 

serial passages in folic-acid depleted media caused genomic hypomethylation. Sodium arsenite 

repressed the expression of the DNA methyltransferase (DNMT) genes DNMT1 and DNMT3A 

and caused depletion of SAM, the main cellular methyl donor. It is thought that long-term 

exposure to sodium arsenite may have resulted in DNA hypomethylation as a consequence of 

those two complementary mechanisms (Reichard et al., 2007). Singh and DuMond (2007) 

demonstrated methylation changes in DNA at 18 genetic loci in TM3 cells, with some showing 

hypomethylation and others hypermethylation, following sodium arsenite exposures ranging 

from 0.008–7.7 μM that lasted for either 25 or 75 days. The LOEC was the lowest dose. Some 

loci were affected only after 25 days of exposure, while others were affected after 75 days of 

exposure. In one of several other demonstrations of hypomethylation, a 19-week exposure of 

TRL 1215 cells to 0.125 μM sodium arsenite was sufficient to cause global hypomethylation 

(Zhao et al., 1997). 

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Under Immune System Response, Table C-3 describes a wide-range of effects on the 

immune system. This discussion provides highlights from that table and Appendix D, which is 

devoted entirely to the immunotoxicity of inorganic arsenic. Appendix D discusses some aspects 

of the immunotoxicity of inorganic arsenic in much more detail, including more emphasis on 

human studies and in vivo experiments on laboratory animals, as well as on some older in vitro 

studies. It overlaps very little with data found in Table C-3. Effects thought to be related to 

Immune System Response were grouped under that heading in Table C-3 even if they dealt 

mainly with other key events. For example, several findings related to Apoptosis, Cytotoxicity, 

or Signal Transduction are included in this section of Table C-3. 

Exposures to low concentrations of AsIII over 1–2 weeks inhibited maturation of human 

peripheral blood monocytes (HPBMs) into the following types of cells: M-type and GM-type 

macrophages, immature dendritic cells, and multinucleated giant cells (Sakurai et al., 2006). The 

IC50s for this inhibition ranged from 0.06 to 0.70 μM. Lemarie et al. (2006a) showed that ATO 

inhibited macrophage differentiation of peripheral blood mononuclear cells (PBMCs) and that 

concentrations as low as 0.125 μM over 6 days induced apoptosis and necrosis in PBMCs cotreated with granulocyte-macrophage colony-stimulating factor (GM-CSF) or macrophage 

colony-stimulating factor (M-CSF). Differentiated macrophages developed from PBMCs treated 

with GM-CSF for 6 days were exposed to 0.25 μM ATO for 6 days. The ATO treatment caused 

major alterations in morphology, adhesion, and actin organization, giving the impression that the 

ATO “de-differentiated” the macrophages back into monocytic cells (Lemarie et al., 2006b). 

The same series of experiments showed that macrophages exposed to 1 μM ATO for 6 days also 

caused a reduction in several surface markers, markedly decreased endocytosis and 

phagocytosis, and increased the secretion of inflammatory cytokines in response to a cotreatment with lipopolysaccharide. 

Exposure of PBMCs that had been stimulated with phytohemagglutinin (PHA) after 

exposure to 1–5 μM sodium arsenite for 120 hours caused a marked dose-related decrease in 

both cell proliferation and the percentage of divided cells (Tenorio and Saavedra, 2005). Even at 

the higher doses, most of the cells were viable but unable to divide. The treatments also 

modified the expression of CD4 and CD8 molecules. Judging from evaluation of blast 

transformation, CD4+

 and CD8+ T cells appear to have different sensitivities to AsIII. As the 

concentration of the sodium arsenite increased from 1 to 5 μM in the 120-hour treatment, there 

was an accumulation of resting CD8+ cells with a positive dose-response, but there was not an 

accumulation of CD4+

 cells. The Janus kinase (JAK)–signal transducer and activator of 

transcription (STAT) pathway is an essential cascade for mediating normal functions of different 

cytokines in the development of the hematopoietic and immune systems. Huang et al. (2007a) 

showed that exposure of SV-HUC-1 cells to sodium arsenite for 48 hours caused changes in 

levels of proteins that are part of that cascade, and the LOEC was 2 μM. Sometimes there was a 

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dose-response, and sometimes the direction of the change reversed. Cheng et al. (2004) showed 

that a 48-hour pretreatment of HepG2 cells with 4 μM sodium arsenite was sufficient to block 

induction of STAT3 activity by an IL-6 treatment. Other experiments showed that AsIII acted 

directly on the JAK1 protein to cause JAK-STAT inactivation. Di Gioacchino et al. (2007) 

studied the effects of several arsenicals on PBMC proliferation and cytokine release. At a 

concentration of 100 μM, sodium arsenite was effective in decreasing PHA-induced cell 

proliferation and in reducing interferon-gamma (IFN-γ) and TNF-α release. However, at a 

concentration of 0.1 μM, AsIII significantly increased cell proliferation. More details about that 

experiment are found in Appendix D. 

Regarding Inhibition of Differentiation, in experiments done on spontaneously 

immortalized human keratinocytes and on normal human epidermal cells derived from foreskin, 

sodium arsenite was shown to delay differentiation and preserve the proliferative potential of 

keratinocytes (Patterson et al., 2005; Patterson and Rice, 2007). A concentration of sodium 

arsenite as low as 0.1 μM over 4 days had a noticeable effect, but most experiments were done 

using 2 μM sodium arsenite over 4-14 days, which yielded a much larger effect. Treatment of 

C3H 10T1/2 cells with 6 μM sodium arsenite for 8 weeks completely inhibited their 

differentiation into adipocytes following dexamethasone/insulin treatment, and treatment with 

3 μM sodium arsenite for only 48 hours was the LOEC for that effect (Trouba et al., 2000). 

Interference With Hormone Function was demonstrated in experiments by Bodwell et al. 

(2004, 2006). Some effects were observed at approximately 0.09 μM of sodium arsenite; 

however, the increases found in glucocorticoid-receptor-mediated gene transcription of reporter 

genes that contained tyrosine aminotransferase (TAT) response elements were highly dependent 

on, and inversely related to, the amount of activated steroid receptor within cells. More detailed 

information on interference with hormone function can be found in Table C-3. 

Under Malignant Transformation or Morphological Transformation, Table C-3 shows 

that concentrations of less than 1 μM of AsIII, MMAIII, or DMAIII are capable of causing 

transformation. HaCaT cells exposed to 0.5 μM AsIII for 20 passages caused the cells to become 

tumorigenic, as shown by production of tumors 2 months after injection into Balb/c nude mice 

(Chien et al., 2004). Zhao et al. (1997) found similar results with another cell line after 18 weeks 

of exposure to 0.25 μM AsIII. UROtsa cells exposed to 0.05 μM MMAIII for 52 weeks caused 

anchorage-independent growth as detected by colony formation in soft agar, and cells from those 

colonies showed enhanced tumorigenicity in SCID mouse xenographs (Bredfeldt et al., 2006). 

After 26 weeks, this experiment showed much anchorage-independent growth but not yet 

enhanced tumorigenicity. Syrian hamster ovary (SHE) cells exposed to DMAIII for 48 hours 

showed morphological transformation at a concentration of only 0.1 μM, and at the highest dose 

tested of 1.0 μM, 3.35% of the surviving colonies had become transformed (Ochi et al., 2004). 

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In contrast, at a dose of 10 μM after the same exposure duration of 48 hours, AsIII had only 

transformed 0.48% of the surviving cells. 

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Table C-3 summarizes many findings related to the Signal Transduction category, even 

though considerable data found under Aberrant Gene or Protein Expression could have been 

placed into this category. Most of the data in this category are for sodium arsenite or ATO. In 

addition, there are numerous LOECs smaller than 10 μM (often much less), and they are often 

for treatments that lasted much less than one day. Drobná et al. (2002) evaluated 

phosphorylation of extracellular signal-regulated kinase (ERK)-2, activator protein (AP)-1 

binding activity, and phosphorylation of c-Jun (an AP-1 protein) by six arsenicals in treatments 

lasting up to 2 hours. AsV, MMAV, and DMAV were all tested at concentrations up to 100 μM 

and had no effect. AsIII, MMAIII, and DMAIII each had an LOEC of 0.1 for at least one endpoint. 

 Details presented in Table C-3 show that the responses of those three arsenicals were different 

and that, in some cases, the direction of the response reversed as the concentration increased. In 

some cases a reduction from an increase was observed, which is interesting because various 

responses for some endpoints described above showed a reversal in which the lowest doses 

caused a bigger effect. Another experiment showing a reversal in response (from a decrease to 

an increase) was for phosphorylation of Akt Thr308 in JB6 C141 cells (P+ mouse epidermal cell 

line) (Ouyang et al., 2006). Following 1-hour exposures to sodium arsenite, there was slight 

decrease at 0.1 μM, a larger decrease at 0.5 μM, increases above the control level at 1 and 5 μM, 

and a much larger increase at 10 μM. Additionally, several experiments in this category related 

to different ways in which arsenic affects signal transduction to either increase or decrease 

apoptosis. For example, MCF-7 cells exposed to 2 μM ATO for 1 hour activated the prosurvival MEK/ERK pathway (Ye et al., 2005). By decreasing apoptosis, such an effect might 

permit the survival of cells containing damage that could eventually lead to a cancer. Yancy et 

al. (2005) did a series of experiments on H9c2 cells (an immortalized myoblast cell line derived 

from fetal rat hearts) and concluded that sodium arsenite exposure decreases cell migration 

through an effect on focal adhesions and by disrupting cell interactions with the extra-cellular 

matrix. Focal adhesions are involved in integrin signaling. Florea et al. (2007) showed that 

ATO triggered three different kinds of Ca2+ signals (i.e., steady state increases, transient 

elevations, and calcium spikes). The Ca2+ concentration in cells was substantially increased (and 

by rather similar amounts) by exposure to either 0.1 or 1 μM ATO for about 1 hour in two 

different cell lines (i.e., the human neuroblastoma cell line SY-5Y and the human embryonic 

kidney cell line HEK 293). 

4.5. SYNTHESIS AND EVALUATION OF MAJOR NONCANCER EFFECTS 

Not addressed in this document. 

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4.6. WEIGHT-OF-EVIDENCE EVALUATION AND CANCER CHARACTERIZATION 

4.6.1. Summary of Overall Weight-of-Evidence 

Based upon the EPA Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a) 

inorganic arsenic is categorized as “carcinogenic to humans” due to convincing epidemiological 

evidence of a causal relationship between oral exposure of humans to inorganic arsenic and 

cancer. Arsenic is a multisite carcinogen, with numerous studies finding an association between 

arsenic and increased incidences of a number of different types of cancers. The carcinogenic 

effect of arsenic has been reported for populations in many different countries. While the studies 

detailed in this document provide evidence for cancer after oral exposure to arsenic, arsenic also 

has been associated with cancer after inhalation exposure (U.S. EPA, 1994). 

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4.6.2. Synthesis of Human, Animal, and Other Supporting Evidence 

Numerous epidemiologic investigations, each conducted differently and containing its 

own biases (e.g., lack of confounding variables, possible recall bias), provide support for an 

association between oral exposure to inorganic arsenic and cancer including skin, bladder, 

kidney, lung, liver, and prostate. The most extensively studied population is from southwest 

Taiwan. This is because between 1910 and 1920, water supplies were changed from shallow 

surface water wells to artesian wells, which were subsequently found to contain high levels of 

arsenic in various regions. Studies in these arsenic-endemic regions of Taiwan have found 

increases in all of the aforementioned cancer types. The link between these cancers and arsenic 

exposure in drinking water also have been observed in other parts of the world, including Japan, 

Chile, and Argentina. Therefore, it is unlikely that any single environmental factor (e.g., 

nutritional habits) associated with a single population is entirely responsible for the increased 

cancer rates. Although many studies did not account for confounding variables (e.g., cigarette 

smoking in association with lung cancer), the positive associations between arsenic intake and 

cancer risk were still observed in studies that did account for confounding variables (e.g., 

lifestyle habits, age, and socioeconomic status). 

Most of the epidemiology studies examining the relationship between arsenic exposure 

from drinking water and cancers are ecological in nature and are therefore subject to the 

limitations inherent in such studies (e.g., lack of measured individual exposure). For a number 

of reasons, the southwest Taiwanese database remains the most appropriate source for estimating 

bladder and lung cancer risk among humans (NRC, 1999, 2001; SAB, 2000, 2007), despite 

lacking individual water consumption and nonwater arsenic intake. Strengths of the data include 

the size of the population, the reliability of the population and mortality counts, the stability of 

residential patterns, the homogenous lifestyle as confirmed by surveys, the long-term exposures, 

the extensive follow-up (almost 900,000 person-years), the large number of exposed villages 

(42), and the large number of cancer deaths (1152 recorded from 1973 to 1986). Population 

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records in Taiwan have been well kept since 1905, and death certificates include all primary 

cancers. In addition, cancer cases were pathologically confirmed in some of the Taiwanese 

studies. 

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Although dose-response relationships have been observed for the majority of cancers 

noted in areas with high levels of arsenic in their drinking water, results for low-level arsenic 

epidemiologic investigations (primarily from the United States and Europe) have been equivocal 

with regard to the relationship between these cancers and arsenic exposure. This could be due to 

the fact that none of the studies accounted for arsenic exposure through food sources. Kile et al. 

(2007) found that as the level of arsenic in the water decreased for women in Bangladesh, the 

contribution of arsenic from dietary sources became of greater importance. Uchino et al. (2006) 

found that with concentrations of 50 ppb or less of arsenic in the drinking water in a population 

in West Bengal, India, the contribution of arsenic from food was the main source of arsenic 

exposure (i.e., contribution from water with less than 50 ppb was less than 27% of the total 

arsenic consumed). Therefore, as the exposure of arsenic from drinking water decreases and the 

relative contribution from food increases, misclassification of exposure groups can become 

significant. The average estimate of inorganic arsenic consumption in food ranges from 1.34 

μg/day in infants to 18 μg/day in adults, for a total arsenic average of 62 μg/day for people in the 

United States (NRC, 1999). At the lower concentrations, dietary intake could easily create total 

arsenic intake levels to be similar between the referent group and what is considered the 

exposure group. 

Cantor and Lubin (2007) also conclude that misclassification occurs because exposure is 

not necessarily assessed during disease-relevant exposure periods. In regards to cancer, there is 

a long latency period, which appears to vary depending on the type of cancer and exposure. This 

means that exposure to arsenic sources during the decades prior to cancer outcome is necessary. 

Therefore, studies with low levels of exposure that are ecological in nature (no individual 

exposure) are more prone to misclassification, which means they are biased toward the null 

hypothesis. In addition, studies that attempted to individualize exposure by examining toenail 

arsenic levels are looking at only the prior year of exposure (Cantor and Lubin, 2007) and may 

miss the important exposure period. Despite all these numerous limitations in low-level 

exposure studies, significant associations have been observed for cancers of the prostate 

(Hinwood et al., 1999; Lewis et al., 1999), skin (Hinwood et al., 1999; Karagas et al., 2001; 

Beane-Freeman et al., 2004; Knobeloch et al., 2006), and bladder (Kurttio et al., 1999; 

Steinmaus et al., 2003; Karagas et al., 2004). In most cases, however, there is no dose-response 

with increases observed at the highest concentrations only and in many cases significant results 

occurred in smokers only. 

There are very few animal data demonstrating the carcinogenic potential of arsenic. This 

is likely due to the fact that rodents, which are the most likely animal model, are better 

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methylators of arsenic than humans (Vahter, 1999a). Since it has been noted that humans who 

are better methylators are at lower risk (Yu et al., 2000; Chen et al., 2005a; Steinmaus et al., 

2005; Valenzuela et al., 2005; Ahsan et al., 2007; Huang et al., 2007b; McCarthy et al., 2007a), 

it is not surprising that animals that are better methylators are at even lower risk. As stated 

before, arsenic has been associated with cancers of the skin, lung, kidney, bladder, and liver. 

Below is a summary these different types of cancers and their association with arsenic exposure 

in drinking water. 

4.6.2.1. Skin Cancer 

Epidemiologic investigations of populations in the arseniasis-endemic areas of Taiwan 

have shown that exposure to arsenic from drinking water is associated with skin cancer (Tseng et 

al., 1968; Tseng, 1977; Chen et al., 1985, 1988a,b; Wu et al., 1989; Chen and Wang, 1990; Tsai 

et al., 1999). The prevalence rate for skin cancer showed an increasing gradient according to the 

arsenic content of the well water. Guo et al. (2001) found significant increases in SCCs at the 

highest dose only (>640 ppb) with results at lower doses variable, suggesting that skin cancers 

may be cell-type specific. Contrastingly, Karagas et al. (2001) found increases in both SCC and 

BCC in the highest toenail arsenic concentration in a population in the United States. BeaneFreeman et al. (2004) also found an increase in the risk of melanoma with elevated toenail 

arsenic concentrations. Therefore, these results demonstrate that skin cancers may not be celltype-specific. Although Taiwan has been the area most associated with skin cancers in relation 

to arsenic exposure, the association has been made in other populations as well. Arsenic has also 

been associated with skin cancers in Argentina, where signs of arsenicism also have been 

observed (Smith et al., 1998). Hopenhayn-Rich et al. (1998), however, found a significant 

association in women in the highest category and surprisingly in males in the lowest category 

only. Skin cancer has also been found in China with drinking water concentrations of 150 ppb or 

greater (Lamm et al., 2007). Skin cancer was not found associated with arsenic in Denmark 

(Baastrup et al., 2008) or in the United States (Meliker et al., 2007), but these studies were at 

lower concentrations of arsenic. 

Skin tumors have only been induced in transgenic mice or with subsequent TPA or UV 

exposure (indicating co-carcinogenesis) in mice. Because co-carcinogenesis has been 

demonstrated in animal models, it is possible that the same occurs in humans. Sun exposure 

would likely be high and the use of sunblock is less likely in the areas where skin cancer has 

been noted (i.e., Taiwan and Argentina). Therefore, a possible co-carcinogenic effect also may 

be contributing to the association. 

4.6.2.2. Lung Cancer 

Lung cancer has been associated with arsenic in populations that were exposed to 

exceedingly high arsenic levels in Taiwan, Chile, and Argentina. Studies of populations with 

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lower arsenic exposure, especially <50 ppb, have not conclusively found an association between 

arsenic and lung cancer. Lung cancer was not associated with arsenic exposure in the United 

States (Lewis et al., 1999 and Meliker et al., 2007), Denmark (Baastrup et al., 2008), or Australia 

(Hinwood et al., 1999). Yang et al. (2004) found that lung cancer incidence in endemic areas of 

Taiwan remained elevated even after the use of the arsenic-containing well water ceased. Yuan 

et al. (2007) also found that mortality from lung cancers exceeded that observed in regions with 

consistently low arsenic exposure even after a 10- to 20-year lag period after removal of the 

arsenic source. These were likely due to the long latency for cancer. Many of the studies have 

not controlled for smoking history, which is a potential confounder for lung cancer. 

4.6.2.3. Kidney, Bladder, and Liver Cancer 

Significant increases in mortality rates for cancers of the kidney, bladder, and liver have 

been identified in populations from Taiwan, Argentina, and Chile. These three regions all have 

elevated levels of arsenic exposure through drinking water. Yang et al. (2004) found that arsenic 

was associated with kidney cancers in Taiwan. Unlike lung cancer, the mortality associated with 

kidney cancer decreased after reducing arsenic exposure. Yang et al. (2005) also found a 

reduction in bladder cancer after removal of arsenic exposure (through tap water instillation), but 

the decline was gradual. In Chile, supplementation of drinking water with water from rivers 

caused exposure to high levels of arsenic, but after the installation of improved water treatment 

in the early 1970s, arsenic exposure dropped dramatically. Yuan et al. (2007), however, found 

that even after a 10- to 20-year lag period after removal of the arsenic source, mortality from 

bladder cancers still exceeded that observed in regions with consistently low arsenic exposure. 

While high levels of arsenic have been found to be related to bladder, kidney, and liver 

cancers, low-dose exposures from the United States, Europe, and Australia have been less clear. 

Lewis et al. (1999) observed increased SMRs in kidney cancer for both males (SMR=1.75) and 

females (SMR=1.60), but the results were not significant. Because the highest concentration in 

this population was 166 ppb, the results are still noteworthy. Kurttio et al. (1999) found that 

despite the low levels of arsenic (median = 0.1 ppb; max=64 ppb) there was evidence of a 

relationship between exposure to arsenic at levels above 0.5 ppb and bladder cancer risk. No 

association was observed for kidney cancer risk. Hinwood et al. (1999), Meliker et al. (2007), 

and Baastrup et al. (2008) did not find associations between these cancers and the low levels of 

exposure in Australia, the United States, and Denmark. 

Although inorganic arsenic exposure in rodents has not been observed to cause increases 

in cancer, long-term (104 weeks) exposure to DMAV in rats has been found to increase bladder 

tumors with doses of 50 ppm or greater. These concentrations are quite high in comparison to 

the amount of inorganic arsenic exposure in humans. 

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4.6.2.4. In Utero Exposure 

There is no adult animal model available to study the relationship between arsenic 

exposure via drinking water and cancer outcome; however, lung and liver tumors have been 

induced by inorganic arsenic in mice when exposed during gestation. Pregnant dams were 

exposed for 10 days during gestation only; this increases the evidence that lung and liver cancers 

are associated with oral exposure to inorganic arsenic. Reproductive and adrenal tumors also 

have been observed with transplacental exposure in mice. 

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There is very little epidemiology information specifically linking in utero arsenic 

exposure to cancer outcome. Although the available epidemiological studies conducted in 

Taiwan and other countries included women of reproductive age, the cancer outcomes from adult 

exposures were not differentiated from in utero exposures. Recently, Smith et al. (2006) 

examined lung cancer rates (and other respiratory diseases) in cohorts born just before the peak 

exposure period in Antofagasta, Chile (meaning that they were not exposed in utero to high 

levels of arsenic, but were exposed during childhood) and cohorts born during the high-exposure 

period (indicating likely in utero exposure). Results demonstrated that exposure during either 

period of development caused increased risk of lung cancer; however, the results from early 

childhood exposures and/or in utero exposures were not compared to exposures during adulthood 

to determine the possible cancer sensitivity effects in humans. 

Because both in utero studies in mice and a study in humans by Smith et al. (2006) 

indicate that lung cancer development may be associated with transplacental arsenic exposure, 

there is an opportunity to examine the similarities in mechanistic effects mediating lung cancers 

between the two species. Several PBPK models exist for humans (Yu, 1999a,b; El-Masri and 

Kenyon, 2008) and mice (Gentry et al., 2004). However, these studies are inadequate in 

interpreting the findings from the in utero studies in mice and relating them to human exposure 

concentrations. 

4.6.3. Mode of Action Information 

4.6.3.1. General Comments on MOAs 

The carcinogenic MOA for inorganic arsenic is unknown. Multiple MOAs for inorganic 

As seem likely in view of the numerous ways in which arsenic acts upon living organisms and 

the several metabolites produced before it is excreted from the body. While this review focuses 

on inorganic As, the methylated species produced during its metabolism, especially the highly 

reactive MMAIII and DMAIII, probably play an important role in the carcinogenesis of inorganic 

arsenic consumed in drinking water. Each successive product in the metabolic pathway has its 

own toxicity and carcinogenic potential, with possible differential transport into and out of 

different organs. In comparison to laboratory animals, humans excrete more MMA in urine and 

are more prone to arsenic-induced carcinogenesis. These findings suggest that MMA (probably 

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in the trivalent form) may be of special importance to arsenic-induced carcinogenesis in humans. 

 The finding of numerous different tumor types associated with arsenic exposure both in humans 

and transplacental animal models also supports the view that multiple MOAs are likely. Due to 

the complexities of the available data related to MOA, including the range of possible toxicities 

of the different arsenic species, the different levels of each arsenic compound in target tissues, 

multiple hypothesized key events, and multiple tissue tumor effects in humans, there is a need 

for improved PBPK models to assist in understanding the MOA. Although there are several 

PBPK models available (see Section 3.5), none have sufficiently addressed the complex nature 

of the kinetics associated with arsenic carcinogenesis; therefore, this is an ongoing effort along 

with BBDR modeling. 

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It seems useful to describe a few MOAs for cancer to use as a frame of reference when 

considering arsenic specifically. Although inorganic arsenic and its metabolites have not been 

found to induce gene (point) mutations, the key events involved in mutagenesis—i.e., (1) 

exposure of target or stem cells; (2) reaction with DNA to produce DNA damage; (3) 

misreplication of a damaged DNA template or misrepair of DNA damage leading to a mutation 

in a critical gene in the replicating target cell; (4) replication forming a clone of mutated cells; 

(5) DNA replication, possibly leading to additional mutations in critical genes; (6) unbalanced 

and uncontrolled clonal growth of mutant cells, possibly leading to pre-neoplastic lesions; (7) 

progression of pre-neoplastic cells in those lesions, resulting in emergence of overt neoplasms, 

solid tumors (which require neoangiogenesis), or leukemia; (8) additional mutations in critical 

genes occurring as a result of uncontrolled cell division; and (9) cancer occurring due to 

malignant behavior (adapted from Preston and Williams, 2005)—may contribute to one or more 

arsenic-mediated MOA(s) for carcinogenesis. A mutagen with the above MOA would likely be 

thought to have a linear dose-response. It is unclear what the shape of the dose-response curve is 

for any specific key event that might be involved in the MOA for arsenic and its metabolites. 

Therefore, a linear dose-response is the prudent choice unless the dose-response of the identified 

key events mediating the carcinogenesis is fully understood. 

A second example of a MOA is the one hypothesized for arsenical-induced urinary 

bladder carcinogenesis as follows: after the requisite arsenical ingestion, absorption, and 

metabolism, (1) DMAIII is excreted into urine above a critical concentration, (2) it reacts with 

urothelial critical sulfhydryl groups, (3) urothelial cytotoxicity and necrosis results, (4) urothelial 

regenerative cell proliferation (hyperplasia) results, and (5) urothelial cancer develops; oxidative 

damage might possibly stimulate both steps 3 and 4 (adapted from Cohen et al., 2007). 

Obviously this MOA directly relates to the topic of this review, and any combination of factors 

in which consumption of inorganic arsenic would lead to more than the critical (threshold) 

concentration of DMAIII for a particular individual for a sufficient time could result in bladder 

cancer. 

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Section 4.4.1 provided abundant evidence that many potential key events can occur at 

levels of exposure that would be encountered in populations exposed to high levels of inorganic 

arsenic in drinking water. It seems possible that those key events could fit together in many 

ways to result in a MOA for carcinogenesis. For example, some known mutagen and/or 

carcinogen commonly encountered in the environment might cause the initiation step, and then 

various arsenic-induced key events would provide the later steps necessary to result in a cancer. 

Alternatively, oxidative damage to DNA (or other types of DNA damage caused by arsenic) 

would make the DNA more prone to be acted upon by some other agent to produce a mutation 

that fulfills the initiation step. Although arsenic exposure does not induce gene mutations, 

evidence from all three tables in Appendix C shows that chromosomal aberrations can be 

induced, and if a chromosome happened to break, for example in a tumor suppressor gene, that 

mutation might provide an important step in a MOA. After the steps in a MOA resulted in cell 

proliferation and genomic instability, cancer would result when changes occurred that provided 

evasion of apoptosis, self-sufficiency of growth signals and insensitivity to anti-growth signals, 

and limitless replicative potential (Hanahan and Weinberg, 2000). Vascularization would also 

be needed to help the tumors grow larger. 

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Many detailed reviews in the past decade have discussed possible MOAs for arsenic 

carcinogenesis. Numerous ideas expressed in these reviews agree that exposure to inorganic 

arsenic may be able to cause cancer by many alternative MOAs. For example, Kitchin (2001) 

discussed nine possible MOAs for arsenic carcinogenesis, suggesting that the three with the most 

positive evidence in both animals and human cells are chromosomal abnormalities, oxidative 

stress, and a continuum of altered growth factors leading to increased cell proliferation and then 

the promotion of carcinogenesis. Florea et al. (2005) suggested that genomic damage, apoptosis, 

and changes in gene expression associated with arsenic exposure are related to arsenic-induced 

intracellular calcium disruption. Rossman (2003), Huang et al. (2004), and Simeonova and 

Luster (2000) also provided noteworthy reviews related to MOAs of arsenic carcinogenesis. 

Snow et al. (2005) reviewed effects of arsenic at low concentrations and suggested that hormesis 

(i.e., a biphasic response) occurs in regard to cell proliferation and/or viability, base excision 

DNA repair, and telomerase activity. While some low-dose effects (e.g., increased DNA repair) 

may be protective of carcinogenesis, other effects (e.g., cell proliferation or telomerase 

activation) may be protective and thus permit mutant cells to survive by preventing cellular 

senescence and death and may thereby be involved in arsenic’s cancer-promoting capacity. 

Kitchin and Ahmad (2003) provided an in-depth review on oxidative stress. They did not 

reach a definitive conclusion on the role of oxidative stress in arsenic carcinogenesis, but rather 

stated, 

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1 • “ ...it may eventually be found that many arsenic species act through several modes of 

carcinogenic action at many stages of multistage carcinogenesis and that the concept of a 

single cause of arsenic carcinogenesis simply does not fit the existing facts.” 

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Oxidative stress seems particularly attractive as an important early step for some of the 

following reasons. Some ROS can interconvert between themselves or react with nitric oxide 

(NO) to become reactive nitrogen species (RNS). RNS have their own spectra of biological 

reactivity. High-energy ROS can convert to lower-energy forms and in the process can damage 

biological molecules. ROS and related species can be inactivated by cellular defenses. 

Extended, high-level exposure to reactive arsenic species might result in the depletion of 

generalized cellular defense mechanisms against oxidative damage. ROS have been postulated 

to be involved in both the initiation and promotional stages of carcinogenesis (Zhong et al., 

1997; Bolton et al., 1998, 2000; Shackelford et al., 2000; Chen et al., 2000b). Low levels of 

ROS can modulate gene expression by acting as a secondary messenger, while high doses of 

ROS can cause oxidative injury leading to cell death (Perkins et al., 2000). It has also been 

demonstrated or suggested that ROS can (or does) damage cells by the following mechanisms: 

lipid peroxidation; DNA and protein-modification; structural alterations in DNA including basepair mutations, rearrangements, deletions, insertions, and sequence amplifications (but not point 

mutations); involvement in the signaling of the cell transformation response; affecting 

cytoplasmic and nuclear signal transduction pathways that regulate gene expression; and 

increasing the expression of certain genes (e.g., MDM2 protein, a key regulator of the tumor 

suppression gene p53) (Li et al., 1998; Sen and Parker, 1996; Lander, 1997). Activation of 

signal transduction pathways that enhance cell proliferation, reduce antiproliferative signaling, 

and override checkpoints controlling cell division after genotoxic insult also have been 

considered as possible mechanisms of arsenic’s co-carcinogenic properties (Rossman, 2003). 

Luster and Simeonova (2004) cited the results of in vitro studies suggesting that arsenic 

stimulates cell proliferation through specific signal transduction pathways that are similar to 

other classic tumor promotors. There has been much research in the last few years on the 

effectiveness of AsIII, especially ATO, on apoptosis, with much of it aimed at improving cancer 

therapy. Those results reveal the extreme complexity of the signal transduction cascades 

involved in controlling apoptosis. Regarding causation of cancer, any effects that inorganic 

arsenic ingestion might have on signal transduction pathways that inhibit apoptosis could result 

in proliferation of damaged cells and thereby lead to cancer. 

 The few animal studies (Waalkes et al., 2006a, 2006b, 2004a, 2004b, 2003a, 2003b) that 

suggest inorganic arsenic is a complete carcinogen are those of Waalkes and his group that 

involved treatments in utero. Doses received by the pregnant dams were large compared to 

human exposures, but tissue levels in the fetuses were reported as being comparable to levels 

sometimes seen in humans. Almost all of the categories of key events discussed in this 

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document can be caused by inorganic arsenic at exposure levels comparable to, or lower than, 

those that would be present in large population groups presently. The experiments also indicate 

that typically when a treatment is extended over a longer period of time, the concentration of 

inorganic arsenic necessary to cause an effect decreases. This indicates that the impact in 

humans suggested by the in vitro findings might be substantially greater than might be expected 

by just comparing the concentrations found in humans and in those used in experiments. Due to 

the complexities of the possible MOAs of inorganic-arsenic-mediated carcinogenesis, various 

scientific tools (e.g., genomic tools, human pharmacokinetic and biologically based doseresponse models) may be needed in order to interpret the data for the hypothesized key events 

qualitatively and quantitatively in a meaningful way. 

4.6.3.2. Low-Dose Extrapolation 

According to the 2005 Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a), a 

linear extrapolation to low doses is to be used either when there are MOA data to indicate that 

the dose-response curve is expected to have a linear component below the point of departure 

(e.g., DNA-reactivity or direct mutagenic activity) or when the available data are insufficient to 

establish the MOA for a tumor site. Since the MOA of inorganic arsenic is unknown, a linear 

low-dose extrapolation was applied as a default option. 

4.7. SUSCEPTIBLE POPULATIONS AND LIFE STAGES 

Several studies (Yu et al., 2000; Chen et al., 2005a; Steinmaus et al., 2005; Valenzuela et 

al., 2005; Ahsan et al., 2007; Huang et al., 2007b; McCarthy et al., 2007a) have observed a 

correlation between increased disease risk and low urinary DMA and/or high urinary MMA, 

indicating a slower secondary methylation. Valenzuela et al. (2005) measured the levels of 

MMAIII in the urine of the residents of the Zimapan region of central Mexico. They found that 

individuals exposed chronically to arsenic who also had arsenic-related skin lesions had 

significantly greater concentrations and proportions of MMAIII in their urine than exposed 

individuals without skin lesions. These findings support the hypothesis that any factor (e.g., 

genetic variability in metabolic enzymes) associated with reduced secondary methylation (i.e., 

the conversion of MMA to DMA) may also be correlated with increase susceptibility to arsenicinduced disease. In the following sections, factors affecting DMA and/or MMA ratios and level 

in the urine or secondary methylation will be evaluated with regard to how they may affect 

individual susceptibility. 

4.7.1. Possible Childhood Susceptibility 

Although children are exposed to arsenic through generally the same sources as adults 

(i.e., air, water, food, and soil), their behaviors and physiology may result in them receiving 

higher absorbed doses in relation to their body weight than adults for a given set of exposure 

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conditions. Because children tend to eat less varied foods than adults, exposure to contaminated 

food, juice, or infant formula prepared with contaminated water may result in higher doses than 

adults. In addition, children are more likely to ingest arsenic-contaminated soil, either 

intentionally or by putting dirty hands in their mouths. 

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There are few data on the relative efficiency of absorption of arsenic from the 

gastrointestinal tract of children compared to adults, but measurement of urinary arsenic levels in 

children indicate that absorption does occur. ATSDR (2007) suggests that there is some 

evidence that children may be less efficient at methylating arsenic. A decreased methylation 

capacity could lead to different tissue distribution and longer retention times that might possibly 

increase their susceptibility relative to adults. Adults have been demonstrated to excrete 40% to 

60% of the arsenic as DMA, 20% to 25% as inorganic As, and 15% to 25% as MMA. Concha et 

al. (1998b), however, determined that children ingesting 200 ppb (μg/L) arsenic in their drinking 

water excreted about 49% as inorganic arsenic and 47% as DMA. Women in the same study 

were found to excrete 66% of the arsenic as DMA and 32% as inorganic arsenic. In contrast, 

others (Chowdhury et al., 2003; Meza et al., 2005, 2007; Sun et al., 2007) have found that 

children have a higher urinary DMA:MMA ratio than adults, suggesting increased capacity for 

secondary methylation. Lindberg et al. (2008) also concluded that children and adolescents (i.e., 

<20 years of age) are more efficient methylators than adults (i.e., >20 years of age). Studying a 

population in Bangladesh exposed to high levels of arsenic in drinking water, Sun et al. (2007) 

found increased secondary methylation indices (SMI) in children exposed to 90 or 160 ppb of 

arsenic in drinking water, but not in controls. Chowdhury et al. (2003) also found that the 

increased methylation in children was only observed in exposed individuals (average 

concentration in drinking water 382 ppb) and not in the controls (<3 ppb in drinking water). 

This could indicate a lower saturation point for secondary methylation in adults than in children. 

 Primary methylation indices (PMI) were not age-dependent in any case. 

Epidemiological studies provide only limited data on whether childhood exposures to 

arsenic may result in increased cancer risk later in life. Because a significant dose-response 

relationship has been found between cancer mortality and increased years of exposure to the 

high-arsenic artesian well water of southwestern Taiwan (Chen et al., 1986), it is important to 

consider the extent to which childhood exposures contributed to lifetime arsenic intake. The 

analysis of cancer risks in the same population (Chen et al., 1992) included “only residents who 

had lived in the study area after birth,” and assumed that the arsenic intake of each person 

continued from birth to the end of the follow-up period (1973 to 1986)3. No information was 

provided on the exposure of pregnant women in this population to the artesian well water. 

3 The artesian wells were introduced in 1910 to 1920; prior sources of fresh water included ponds, streams, and 

rainwater (Tseng, 1968). 

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Arsenic has been found to pass through the placenta (Hanlon and Ferm, 1977; Lindgren et al., 

1984; Hood et al., 1987; Concha et al., 1998a; Jin et al., 2006a). 

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Chen et al. (1992) stated that their cancer study results may somewhat underestimate 

arsenic-related risks in this population because tap water with lower arsenic concentrations was 

introduced into the study area in 1956 and was available to almost 75% of the residents in the 

1970s. Thus, the actual lifetime arsenic ingestion may be lower than estimated as residents 

switched from the high-arsenic artesian wells to alternate water sources. Also, because this 

study is based on mortality records (1973 to 1986) from the study region, it would not capture 

cancer incidence among individuals exposed during childhood and early adulthood who then 

migrated from the region. Chen et al. (1986) reported that the 1982 migration rate for this area 

was 27%, with primarily the youths and young adults leaving the area to move to cities and those 

45+ years old emigrating at a rate less than 6%. There is limited migration into this region, and 

it has been reported that more than 90% of the local residents lived in the study area all their 

lives (Wu et al., 1989). 

There is very little epidemiology information specifically linking in utero arsenic 

exposure to cancer outcome. Although the available epidemiological studies conducted in 

Taiwan and other countries included women of reproductive age, the cancer outcomes from adult 

exposures were not differentiated from in utero exposures. Recently, Smith et al. (2006), 

examined lung cancer rates (and other respiratory diseases) in cohorts born just before the peak 

exposure period in Antofagasta, Chile (meaning that they were not exposed in utero to high 

levels of arsenic, but were exposed during childhood) and cohorts born during the high-exposure 

period (indicating likely in utero exposure). Results demonstrated that exposure during either 

period of development caused increased risk of lung cancer; however, the results from early 

childhood exposures and/or in utero exposures were not compared to exposures during 

adulthood to determine the possible cancer sensitivity effects in humans. 

Although there is no adult animal model available for arsenic carcinogenesis, 

administering inorganic arsenic to mice for 10 days during gestation has been found to increase 

the incidence of lung, liver, reproductive, and adrenal tumors (Waalkes et al., 2003, 2004a, 

2006a). This demonstrates that, at least in animals, embryos are more sensitive to the 

carcinogenic effects of arsenic. 

The Supplemental Guidance for Assessing Susceptibility from Early-Life Exposure to 

Carcinogens (U.S. EPA, 2005b) indicates that age-dependent adjustment factors should be 

applied to the CSF and combined with early-life exposure estimates when estimating cancer 

risks from exposures to carcinogens with a mutagenic MOA. A mutagenic MOA for inorganic 

arsenic has not been determined; therefore, the application of age-dependent adjustment factors 

is not recommended. 

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4.7.2. Possible Gender Differences 

Differences in methylation patterns have been noted between men and women in a 

number of studies. Higher MMA:DMA ratios have been observed in men than in women in a 

variety of populations tested, including in the United States (Hopenhayn-Rich et al., 1996b; 

Steinmaus et al., 2005, 2006, 2007), Taiwan (Tseng et al., 2005), and Bangladesh (Ahsan et al., 

2007). In contrast, Loffredo et al. (2003) found that gender differences in arsenic methylation 

varied across populations studied in Mexico, China, and Chile, sometimes by exposure level. 

Based on mean urinary metabolite levels, they found no difference in the MMA:DMA ratio 

between males and females in China in the group with the highest arsenic levels in their drinking 

water (i.e., 405 ppb). Low-exposure Chinese males (i.e., those exposed to 18 ppb in drinking 

water) had MMA:DMA ratios similar to both the high-dose males and females (0.31 to 0.32), but 

low-dose females had a much lower (i.e., 0.22) MMA:DMA ratio. In Mexico, there was a 

difference between the sexes at high concentrations (408 ppb in the drinking water) of arsenic 

(i.e., the MMA:DMA ratio was 0.23 in males vs. 0.18 in females), but there was no differences 

in the MMA:DMA ratio (0.11) at low concentrations (i.e., 30 ppb in the drinking water). In 

Chile, a completely different pattern was observed, with females exposed to high concentrations 

(600 ppb in the drinking water) demonstrating a higher MMA:DMA ratio (0.27) than males 

(0.20), while the opposite pattern was seen at low concentrations (30 ppb in the drinking water; 

0.18 in males vs. 0.13 in females). Studying a population in Bangladesh exposed to high levels 

of arsenic in drinking water, Heck et al. (2007) found a higher percentage of urinary MMA in 

men and a higher proportion of urinary DMA in women. 

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Age and reproductive status also may affect the male-female differences in arsenic 

methylation patterns. Concha et al. (1998a) demonstrated that pregnant women in their third 

trimester excrete approximately 90% of arsenic as DMA. Engström et al. (2007) also found 

pregnant women to have an increased proportion of DMA in their urine compared to nonpregnant women in the same population, with increases occurring with gestational age. This 

indicates possible hormonal effects on arsenic methylation. Lindberg et al. (2007) also found 

possible hormonal effect on arsenic methylation, noting that females younger than 60 (i.e., likely 

pre-menopausal) generally had a more efficient methylation than men of the same age, while the 

difference narrowed considerably in males and females over 60. Lindberg et al. (2008) found 

that although females of all ages generally were better at methylating arsenic than males, the 

greatest disparity between the sexes occurred between the ages of 20 and 55 (childbearing age in 

women). Lindberg et al. (2007) also found that selenium, BMI, and AS3MT polymorphism 

affected the observed proportions of methylated urinary arsenic metabolites in males only. The 

pattern of arsenic methylation was also altered in males with mutations in one allele of the 

methylenetetrahydrofolate reductase (MTHFR) gene, but in females variants in both alleles were 

required. 

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Brenton et al. (2006) used a case-control study with 900 case-control pairs to examine the 

effect of hemoglobin levels on skin lesion prevalence in Pabna, Bangladesh. A 1.0 g/dL increase 

in hemoglobin was found to be associated with a 21% decrease in the odds for having skin 

lesions even after adjusting for toenail arsenic levels, BMI, education, biri or cigarette smoking, 

chewing tobacco, and betel nut chewing. However, when the data was examined further, it was 

discovered that the hemoglobin levels were correlated with decreased skin lesion prevalence 

only in males (40% reduction), but not in females. Females, however, were more likely to have 

anemia than males (18.2% vs. 8.2%; p < 0.0001). A subsequent cohort study (Brenton et al., 

2006) found that hemoglobin levels were not associated with changes in urinary arsenic levels or 

MMA/DMA ratios. 

4.7.3. Other 

4.7.3.1. Genetic Polymorphism 

Despite the observed differences in methylation related to age and sex, data from 

Bangladesh analyzed by Lindberg et al. (2008) suggest that genetic polymorphism is the most 

important factor affecting the methylation of inorganic arsenic, with only 30% of variation in 

methylation patterns attributable to level of arsenic exposure, gender, and age. Most humans 

excrete 10% to 30% of absorbed inorganic arsenic as unchanged in urine, 10% to 20% as MMA, 

and 60% to 80% as DMA. Excretion patterns vary across populations, however. A study of 

urinary arsenic in a population in northern Argentina exposed to arsenic via drinking water 

demonstrated an average of only 2% MMA in the urine (Vahter et al., 1995b; Concha et al., 

1998b). Studies on populations in San Pedro and Toconao in northern Chile demonstrated 

differences in the ratio of MMA:DMA excretion between the two populations (Hopenhayn-Rich 

et al., 1996b). Chiou et al. (1997) found that in a population in northeastern Taiwan, 27% of the 

arsenic consumed was excreted as MMA. Although these variations have not been 

unequivocally linked with genetic factors, as opposed to environmental or nutritional factors, 

human genetic polymorphism has been reported for methyltransferases believed to be involved 

in arsenic metabolism (e.g., thiopurine S-methyltransferase; Yates et al., 1997). 

Chung et al. (2002) studied the association of familial relationships with urinary arsenic 

methylation patterns in 11 families (father, mother, and two children studied from each family) 

from Chile where drinking water concentrations were 735–762 ppb. Their results indicate that 

13–52% of the variation in methylation patterns could be explained by being a member of a 

specific family. There was a high and significant correlation in the methylation patterns between 

siblings and a much lower correlation between parent and child, which could be attributed to 

inherent differences in methylation patterns between children and adults. Adjusting for 

nutritional factors (blood levels of methionine, homocysteine, folate, vitamin B6, selenium, and 

vitamin B12) did not notably alter the correlation. As might be expected, the correlation between 

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father and mother was relatively low, even when adjusted for age and gender. However, the 

correlation became stronger when adjusting for homocysteine levels as well. 

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Meza et al. (2005) found a strong association between the variations in the DNA 

sequence of AS3MT and urinary DMA:MMA ratios in native populations in Yaqui Valley in 

Sonora, Mexico. Three polymorphic sites were found to be associated with increased 

DMA:MMA levels in the study population, but site 30585 was most strongly associated with 

urinary arsenic metabolite patterns. Using a stepwise linear regression model with DMA:MMA 

as the dependent variable and 30585 genotype, age, sex, and log-converted daily arsenic dose as 

independent variables, only the 30585 genotype and age were found to have a highly significant 

association with DMA:MMA levels. Further investigation determined that there was no 

significant genetic association observed in adults, but there was a highly significant effect in 

children aged 7 to 11 years. There was no difference in the allele frequencies at the 23 sites 

examined between the adults and children. 

Engström et al. (2007) also found a strong association between the presence of three 

intronic single nucleotide polymorphisms in AS3MT (i.e., G12390C, C14215T, and A35991G) 

and increased DMA levels. The study population consisted of adult women living in San 

Antonio de los Cobres (a village in the northern Argentinean Andes) who were exposed to 

approximately 200 ppb of arsenic in their drinking water. This group provided a rather uniform 

genetic background against which to examine the impact of polymorphism alone as a variant. 

Subjects who were homozygous for one or more of the variant alleles had lower MMA and 

higher DMA levels than heterozygotes, who in turn had lower MMA:DMA ratios than 

individuals lacking the alleles. Because the proportion of ingested inorganic arsenic that was 

excreted was relatively constant across the groups, the effects of the variants were attributed 

primarily to increased secondary methylation. Individuals homogenous for all three variant 

alleles were found to have the lowest proportions of urinary MMA and the highest proportions of 

DMA among all the groups studied. 

A case-referent study in Bangladesh evaluated arsenic metabolite patterns in 594 

individuals with arsenic-related skin lesions compared to 1,041 controls (Ahsan et al., 2007). A 

correlation was found between increased arsenic concentrations in the drinking water, increased 

proportions of MMA in the urine, and the risk of skin lesions, suggesting that variations in 

secondary methylation could increase the risk of developing such lesions. Individuals with 

variants in MTHFR (677TT/1298AA and 677CT/1298AA diplotypes) also had slightly increased 

skin lesion risk (OR 1.66 and 1.77, respectively). However, the risk for developing skin lesions 

in relation to all at-risk alleles for the GSTO1 diplotype was 3.91. Additivity of effect was 

observed when the genotypes were analyzed jointly with water arsenic concentrations and 

proportion of urinary MMA. 

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Steinmaus et al. (2007) examined the association between genetic polymorphisms in 

MTHFR and GST and urinary arsenic metabolites in 170 subjects from Argentina. Subjects with 

the TT/AA variant of MTHFR 677/1298 were found to have higher urinary proportions of 

inorganic arsenic and MMA (not statistically significant) and lower levels of DMA, with the 

results being more pronounced in males. A null genotype of GSTM1 in women was 

significantly associated with lower proportions of urinary MMA and higher proportions of 

urinary DMA compared to women with the active genotype. While the same trend was observed 

in males, it was weaker and did not achieve statistical significance. Polymorphism in the GSTT1 

gene was not associated with differences in arsenic methylation. Lindberg et al. (2007) also 

found that carriers of the variant allele of the M287T (C→T) polymorphism of the AS3MT gene 

or the A222V (C→T) polymorphism in the MTHFR gene had higher proportions of urinary 

MMA. 

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McCarthy et al. (2007a,b) examined the effect of GST polymorphisms on skin lesion risk 

in a case-control (600 pairs) study in Pabna, Bangladesh. In one study (2007a), they found that a 

10-fold increase in MMA/inorganic arsenic ratio was associated with a 1.5-fold increase in risk 

of skin lesions. There was a significant interactive effect between GSTT1 wild-type and 

secondary methylation on skin lesions, but no interactive effects with the GSTM1 or GSTP1 

genotypes or any of the genotypes with primary methylation. In their second study (2007b), 

however, they found a greater risk for skin lesions in GSTT1 wild-type (OR=1.56, 95% CI 1.10–

2.19) compared to GSTT1 null status (referent group). The presence of the GSTP1 GG genotype 

was associated with a 1.86-fold increase (95% CI: 1.15–3.00) in risk of skin lesions over the AA 

genotype. However, none of the polymorphisms examined (i.e., GSTT1, GSTM1, and GSTP1) 

were found to modify the association between arsenic exposure and skin lesion risk. 

Banerjee et al. (2007) also found a significant correlation between genetic polymorphism 

and skin lesions in a population in West Bengal, India. This population was selected because 

even though over 6 million people are exposed to high arsenic levels, only 15% to 20% 

developed skin lesions. Polymorphisms in ERCC2, which is a NER pathway gene, was 

examined. Specifically, the relationship between the ERCC2 codon 751 A→C polymorphism 

(lysine to glutamine) and skin lesion risk. Subjects exposed to arsenic-contaminated drinking 

water with hyperkeratosis (n = 165) were compared to those without skin lesions (n = 153). 

Occurrence of hyperkeratosis was strongly associated with the Lys/Lys genotype in the ERCC2 

codon 751, with an OR of 4.77 (95% CI: 2.75–8.23). A significant increase in chromosomal 

aberrations in individuals with the AA genotype compared to either the AC or CC genotypes 

combined was also observed. 

Brenton et al. (2007a) observed a positive association between total urinary arsenic and 

oxidative stress (as measured by 8-OHdG) in healthy women (only females were studied) from 

Pabna, Bangladesh, with the GSTM1 null genotype. No such association was found in GSTM1 

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positive women. APE1 (apurinic/apyrimidinic endonuclease) was found to be a predictor of 8-

OHdG levels with the variant allele associated with a decrease in 8-OHdG. Other factors that 

also were predictive of 8-OHdG levels included creatinine, betel nut chewing, presence of 

environmental tobacco smoke in the home (even though none of the women reportedly smoked 

themselves), and education. 

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In a case-control study with 792 pairs with and without skin lesions in Pabna, 

Bangladesh, Brenton et al. (2007b) studied the association between genetic polymorphisms in 

the base excision DNA repair pathway and arsenic-induced skin lesions. Four common base 

excision repair (BER) genetic polymorphisms (X-ray repair cross-complimentary group 1 

[XRCC1] Arg399Gln, XRCC1 Arg194Trp, human 8-oxoguanine DNA glycosylase [hOGG1] 

Ser326Cys, and APE1 Asp148Glu) were examined. APE1 148 Glu/Glu individuals were twice 

as likely to have skin lesions as APE1 148 Asp/Asp individuals, even after adjusting for toenail 

arsenic concentration, BMI, education, smoking, and betel nut use. Presence of the Glu/Glu 

variant of APE1 Asp148 Glu was associated with a 2- to 2.5-fold increased OR for skin lesions 

compared to the Asp/Asp variant, in the low and middle tertiles, but no increase was observed in 

risk at the highest tertile of exposure. XRCC1 Arg194 Trp genotypes, however, were not 

associated with skin lesion risk in the low and middle tertiles, but were associated with a 3-fold 

difference in the highest exposure tertile (i.e., OR of 2.9 for Trp/Trp compared to 8.4 for 

Arg/Arg where Arg/Arg at the lowest tertile is the referent group). No association was observed 

between skin lesions and genetic polymorphisms in XRCC1 Arg399Gln or hOGG1 Ser326Cys 

alleles. 

4.7.3.2. Nutritional Status 

In many of the epidemiological studies discussed above (e.g., southwestern Taiwan and 

Bangladesh), the study subjects were relatively poor and had poor nutritional status. Mazumder 

et al. (1998) demonstrated that people in and around West Bengal who had body weights below 

80% for their age and sex had an increased RR (2.1 for females and 1.5 for males) in the 

prevalence of arsenic-associated keratosis. Lindberg et al. (2008), however, found that women 

in Bangladesh were better at methylating arsenic than men even though they were less likely to 

eat nutritious food (e.g., meat and fresh vegetables) than men, indicating that gender was a better 

predictor of methylation capacity than nutritional status in this group. 

Selenium has been demonstrated to reduce the teratogenic, clastogenic, and cytogenic 

effects of arsenic (ATSDR, 1993). Chen et al. (2007) found that individuals in the Health 

Effects of Arsenic Longitudinal Study (HEALS; population from Araihazar, Bangladesh) with 

low selenium intake were at a greater risk for developing pre-malignant skin lesions than those 

with adequate intake. In 93 pregnant women from Antofagasta, Christian et al. (2006) found that 

increases in urinary selenium levels were associated with increased urinary arsenic excretion, 

and with a greater percent excreted as DMA and less excreted as inorganic arsenic. The 

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proportion of urinary MMA was fairly consistent in the study population. Using four quartiles of 

increasing urinary selenium levels, results showed that the total arsenic excretion increased 

steadily across quartiles of selenium intake. The proportion of DMA excreted increased, and the 

proportion of inorganic arsenic excreted decreased with increasing selenium intake, but only in 

the first two quartiles. Although different gestational stages of pregnancy have been associated 

with differences in urinary arsenic excretion patterns, this was controlled for in the analysis. 

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Gamble et al. (2005) suggest that adequate folate is necessary for both primary and 

secondary arsenic methylation and that adequate folate intake is associated with increased 

urinary DMA. Gamble et al. (2006) found that providing folate supplements to individuals from 

Araihazar, Bangladesh, with a diet low in folate significantly increased the proportion of arsenic 

excreted as DMA in the urine. Heck et al. (2007), however, found that levels of folate 

consumption (measured by levels in the food) were directly related to percentages of urinary 

MMA, but not to changes in urinary DMA in a population from Bangladesh (participants of the 

HEALS study) exposed to arsenic in drinking water. Heck et al. found no correlation between 

intake of folate-related nutrients and urinary DMA levels, but found that increases in methionine, 

vitamin B12, calcium, protein, and riboflavin were associated with decreases in the proportion of 

urinary inorganic arsenic and increases in the percent of urinary MMA. Niacin and choline were 

found to be the better predictors of secondary methylation (as measured by DMA/MMA). 

Although high levels of plasma homocysteine were not associated with urinary MMA levels, 

they were associated with a decrease in DMA levels (Gamble et al., 2005). 

Mitra et al. (2004) studied whether nutritional deficiencies increased the susceptibility of 

individuals to arsenic-related health effects as measured by skin lesions. In West Bengal, India, 

where exposures were <500 ppb, nutritional assessments were based on a 24-hour recall for 

major dietary constituents and a 1-week recall for less common constituents. Increases in risk 

were associated with low intake of animal protein (OR=1.94, 95% CI: 1.05–3.59), calcium 

(OR=1.89, 95% CI: 1.04–3.43), fiber (OR=2.20, 95% CI: 1.15–4.21), and folate (OR=1.67, 95% 

CI: 0.87–3.2). Nutrient intake was not related to arsenic exposure. The authors concluded that 

the potential protective effects of these nutrients were small in comparison to eliminating the 

exposure to arsenic. 

Steinmaus et al. (2005) found an association between low dietary protein, iron, zinc, and 

niacin, and decreased production of urinary DMA accompanied by increased levels of urinary 

MMA in arsenic-exposed individuals from a U.S. population. An associations between arsenic 

methylation patterns and dietary intake of thiamine, vitamin B6, lutein, and α-carotene were 

found, but the links were not as clear when adjusted for confounding variables (i.e., age, sex, 

smoking, and total urinary arsenic levels). The authors suggest, however, that the effect of 

specific nutrient intake levels on methylation patterns was small in comparison with the known 

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magnitude of inter-individual variability associated with genetic polymorphisms. Kreppel et al. 

(1994) found that dietary zinc protects mice against acute arsenic toxicity. 

4.7.3.3. Cigarette Smokers 

Cigarette smokers (current or former) were found to have a decreased secondary 

methylation capacity, resulting in increased urinary MMA and decreased DMA concentrations 

(Huang et al., 2007b). Tseng et al. (2005) reported a decrease in secondary metabolism in 

cigarette smokers exposed to arsenic-contaminated drinking water, resulting in a significant 

increase in the secreted MMA as a fraction of total metabolites. Steinmaus et al. (2005) found 

that current smokers in a U.S. population had lower proportion of arsenic excreted as DMA than 

either former or never-smokers (although the difference was not statistically significant). 

Steinmaus et al. (2006) found that in a population in Argentina the proportion of excreted MMA 

was associated with bladder cancer risk in former smokers, but not in individuals who had never 

smoked. Subjects who had ever smoked and had proportions of MMA in the upper tertile had a 

2-fold elevated risk of bladder cancer compared to subjects with proportions of MMA in the 

lower two tertiles. Therefore, it was concluded that individuals who smoke had an increased 

susceptibility to arsenic toxicity. Steinmaus et al. (2006) also studied a population in the United 

States. Although the results indicated increased MMA was associated with increased cancer 

risk, the number of cases was too small to estimate separate ORs for never-smokers and eversmokers. 

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5. DOSE-RESPONSE ASSESSMENTS 

5.1. ORAL REFERENCE DOSE (RfD) 

 An RfD was developed for inorganic arsenic and posted on the IRIS database in 

1991. An oral noncancer dose-response estimation is not addressed in this document. However, 

the Agency is currently reviewing the literature and will develop an updated RfD at a later date. 

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5.2. INHALATION REFERENCE CONCENTRATION (RfC) 

An inhalation noncancer dose-response estimation is not addressed in this document. An 

RfC is not developed for inorganic arsenic, nor does a current value exist on the IRIS database. 

5.3. CANCER ASSESSMENT (ORAL EXPOSURE) 

5.3.1. Background: History of Cancer Risk Assessments for Arsenic 

This assessment is unusual in that it builds on a long history of previous efforts by EPA 

and others to evaluate potential risks from oral exposure to arsenic via drinking water. Table 5-1 

summarizes previous assessments and expert reviews of arsenic carcinogenicity. 

 The table starts (chronologically) with EPA’s 1988 risk assessment for skin cancer (U.S. 

EPA, 1988b). The scope of the 1988 assessment was to review the applicability of EPA’s 1984 

assessment (U.S. EPA, 1984) on skin cancer risk from the Taiwanese population to the U.S. 

population. The skin cancer risk from oral exposure was estimated based on two studies (Tseng 

et al., 1968; Tseng, 1977) of age-specific prevalence rates for skin cancer in a large cohort of 

Taiwanese (40,241 subjects in 37 villages) in an “arseniasis-endemic” area, where arsenic 

concentrations in water supply wells ranged from less than 10 μg/L (ppb) to 1,820 μg/L. The 

occurrence of skin cancer was estimated in a survey lasting approximately 2 years (U.S. EPA, 

1988b). Preliminary data from the same cohort suggested that risks of internal cancers (lung, 

liver, and bladder) were also elevated, but U.S. EPA (1988b) concluded that insufficient data 

were available to support a dose-response assessment for these effects. 

The second entry in the table is the National Research Council’s 1999 review (NRC, 

1999) of EPA’s 1988 risk assessment. EPA commissioned NRC to review the U.S. EPA (1988b) 

assessment and also the qualitative and quantitative evidence on arsenic and health effects for 

reassessment of human health risks from arsenic in drinking water. One of the major 

recommendations of NRC’s 1999 review was that studies from the arsenic-endemic area of 

Taiwan (Wu et al., 1989; Chen et al., 1988a, 1992) provide the best available empirical human 

data for assessing the risks of arsenic-induced cancer. The report explored quantitative modeling 

approaches for the male bladder cancer data, but did not provide a formal risk assessment; 

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additional modeling analyses were recommended. NRC 1999 applied absolute Taiwan risks to 

the U.S. populations. 

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NRC (1999) published the arsenic concentration in village wells, person-years of males 

and females by village and the village-specific lung, bladder, and liver deaths for the Wu et al. 

(1989) and Chen et al. (1992) studies. Additional raw data were obtained from study authors by 

Morales and Ryan during reanalysis and these data were subsequently provided to EPA 

(personal communications). All of the succeeding assessments summarized in Table 5-1 derive 

dose-response estimates based on the internal cancer data. 

In the first of these efforts, Morales et al. (2000) gathered data on lung, bladder, and liver 

cancer, as well as detailed exposure data (well arsenic concentrations) from the three 

epidemiological studies (Wu 1989; Chen et al., 1988a, 1992), and evaluated a range of statistical 

models for estimating potential arsenic-related cancer risks in the Taiwanese population and for 

extrapolating these risks to the U.S. population. In promulgating the Primary Drinking Water 

Standard for Arsenic, U.S. EPA (2001) adopted one of Morales et al.’s models, with adjustments 

of some exposure assumptions, for estimating the health benefits of regulatory alternatives. The 

Office of Pesticide Programs (OPP) also recently applied oral CSFs based on the U.S. EPA 

(2001) assessment in their Reregistration Eligibility Decision (RED) Documents for organic 

arsenic pesticides (U.S. EPA, 2006c) and for Inorganic Arsenicals and/or Chromium Based 

Wood Preservatives (U.S. EPA, 2008). 

In response to continued public concern over arsenic-related cancer risks, EPA asked 

NRC to update its 1999 recommendations in light of new scientific evidence, and to review the 

risk assessment in support of the 2001 drinking water standard. NRC (2001) reviewed the 

methodology used in EPA’s arsenic risk assessment (U.S. EPA, 2001) and provided a systematic 

analysis of and recommendations for applying the Taiwanese epidemiological data for assessing 

cancer risks from arsenic exposure in U.S. populations. Recommendations included the 

inclusion of a reference population in the dose-response assessment, the form of the doseresponse model, exposure assumptions, and approaches for extrapolating risks to the U.S. 

population. As the committee noted, the cancer risk estimates that it developed were higher than 

those reported by U.S. EPA (2001), and reasons for those differences were reviewed. EPA 

examined and applied the NRC (2001) statistical methodology and submitted its revised analysis 

(U.S. EPA, 2005c) to SAB for review and comment. SAB (2007) provided additional discussion 

related to the treatment of arsenic exposure, and recommended expanded sensitivity analyses of 

other exposure-related assumptions. EPA adopted these recommendations, along with responses 

to comments from interagency reviewers, into the current assessment. The current quantitative 

risk assessment can thus be described as EPA’s reimplementation of the technical cancer risk 

modeling recommendations in NRC (2001), with additional examination of arsenic exposure 

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assumptions and taking into account SAB’s (2007) advice for the expansion of sensitivity 

analyses of modeling methods and choices. 

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Table 5-1. Historical Summary of Arsenic Risk Assessment Efforts 

Assumption/ 

Method 

U.S. EPA 

(1988b) NRC (1999) Morales et 

al. (2000) 

U.S. EPA 

(2001) NRC (2001) U.S. EPA 

(2005c) 

Goals/Scope of 

Assessment 

Revise EPA’s 

1984 risk 

assessment 

for skin 

cancer, 

evaluate 

evidence of 

arsenic 

essentiality 

Review EPA’s 

1988b risk 

assessment, 

suggest 

alternative 

approaches; 

was “not a 

risk 

assessment” 

Test doseresponse 

models, 

modeling 

assumptions 

Estimate U.S. 

cancer risks in 

support of 

drinking water 

standard 

Review 

EPA’s 2001 

methods and 

results 

Incorporate 

NRC (2001) 

recommendations for SAB 

Review 

Critical Study Taiwan skin 

cancer 

prevalence 

studies 

(Tseng et al., 

1968; Tseng, 

1977) 

Taiwan 

epidemiologic

al studies (Wu 

et al., 1989; 

Chen et al., 

1988a, 1992) 

Taiwan epidemiological studies (Wu et al., 1989; Chen et al., 1988a, 

1992) 

Critical Study 

Endpoint(s) 

Skin cancer 

incidence 

Bladder 

cancer 

mortality 

Bladder, lung, 

liver cancer 

mortality 

Bladder, lung cancer mortality 

Dose-Response 

Model 

Linear 

multistage 

Weibull, 

Poisson 

regression 

Nine Poisson 

forms with 

varying age, 

dose 

representation

s; one 

multistage 

Weibull 

Morales et al. 

“Model 1” 

(multiplicative 

linear dose, 

quadratic age) 

Additive 

Poisson, 

linear dose, 

quadratic age 

Additive 

Poisson, linear 

dose, quadratic 

age; UCLs on 

dose coefficients 

estimated by 

Bayesian 

simulation 

Reference 

Population 

Taiwanese 

outside 

arseniasisendemic area 

With and 

without allTaiwan 

None, 

southwest 

Taiwan, allTaiwan 

None All-Taiwan, 

southwest 

Taiwan 

Southwest 

Taiwan 

Arsenic 

Concentration 

Stratified: 0–

300, 300–

600, 600–900 

μg/L in well 

water, 

unknown 

exposure 

Median well 

arsenic 

concentrations 

Median well 

arsenic 

concentration

s 

Median well 

arsenic 

concentrations 

Median; 

sensitivity 

analysis of 

other values 

Median well 

arsenic 

concentrations 

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Assumption/ 

Method 

U.S. EPA 

(1988b) NRC (1999) Morales et 

al. (2000) 

U.S. EPA 

(2001) NRC (2001) U.S. EPA 

(2005c) 

Taiwanese 

Water Intake 

3.5 L/day 

(M), 

2.0 L/day (F) 

3.5 L/day (M), 

2.0 L/day (F) 

Water intakes 

not specified 

3.5 L/day (M), 

2.0 L/day (F) + 

1.0 L/day 

cooking 

Recommenda

tions based 

on approx. 2 

L/day; 

sensitivity 

analysis of 

U.S./Taiwan 

intake ratios 

is presented 

2.0 L/day 

Taiwanese 

Body Weight 

55 kg (M), 50 

kg (F) 

55 kg (M), 50 

kg (F) 

Body weights 

not specified 

55 kg (M), 

50 kg (F) 

55 kg (M), 

50 kg (F) 

50 kg (M and F) 

Nonwater 

arsenic Intake 

None (0 

μg/day) 

Not explored None (0 

μg/day) 

50 μg/day 

(exposed 

population) 

None (0 

μg/day) 

in baseline 

assessment; 

sensitivity 

analysis 

showed little 

effect of 

adding 30 or 

50 μg/day to 

study village

exposure 

estimates 

30 μg/day 

exposed 

population only, 

sensitivity 

analyses of 

0–50 μg/day 

Risk Model 

for U.S. 

Population 

Simple life 

table 

Simple life 

table 

Life table, 5-

year age strata 

Life table, 

5-year age 

strata 

BEIR IV survival model (relative 

risk) 

U.S. Incidence, 

Mortality Data 

Not specified NCHS 1994 

mortality data 

NCHS 1996 mortality 

U.S. Water 

Intake 

2.0 L/day 

(approximate 

90th 

percentile 

value) 

2.0 L/day 

(approximate 

90th percentile 

value) 

Average U.S. 

water intake 

1.0–1.2 L/day 

used as central 

tendency 

values; 

2.1–2.3 L for 

90th percentile 

risk in Monte 

Carlo model 

1.0 L/day 

with 

sensitivity 

analyses 

1.0 L/day 

U.S. Body 

Weight 

70 kg (M and 

F) 

70 kg (M and 

F) 

Average U.S. 

body weights 

70 kg (M and F) 

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Assumption/ 

Method 

U.S. EPA 

(1988b) NRC (1999) Morales et 

al. (2000) 

U.S. EPA 

(2001) NRC (2001) U.S. EPA 

(2005c) 

Endpoints 

Calculated 

Unit risk = 

3×10-5 per 

μg/L 

(females), 

7×10-5 per 

μg/L (males); 

CSFs = 1 to 2 

per mg/kgday 

(incidence) 

Lifetime 

bladder cancer 

risk at 10 μg/L 

= 3×10-3

(males), 

9×10-3

(females); 

ED01 = 404–

443 μg/L, 

LED01 = 

323–407 μg/L 

“Model 1,” no 

reference pop. 

Males (μg/L)

 ED01 

LED01

Lung 364 

 294 

Bladder 395 

 326 

Females 

(μg/L)

 ED01 

 LED01

Lung 258 

 213 

Bladder 252 

 211 

Many other 

results 

presented 

CSFs derived 

from Morales 

et al. (2000) 

ED01, 

LED 01 values 

Unit risk, per 

μg/L: 

 

Male bladder= 

2.5×10-5

(MLE), 

3.1×10-5 (UCL) 

Male lung = 

2.8×10-5

(MLE), 

3.4×10-5

(UCL) 

Female bladder 

= 4.0×10-5

(MLE), 

4.7×10-5

(UCL) 

Female lung= 

3.9×10-5, 

(MLE), 

4.7×10-5

(UCL) 

Lifetime 

cancer risk 

incidence 

from 

10 μg/L: 

Male 

lung = 

1.8×10-3

bladder = 

2.3×10-3 

Female 

lung = 

1.4×10-3

bladder = 

1.2×10-3

Female lung + 

bladder 

incidence: 

unit risk = 

1.6×10-4 per 

μg/L 

Incidence at 10 

μg/L in drinking 

water = 1.6×10-3

Drinking water 

concentration 

for 10-4

incidence risk = 

0.63 μg/L 

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The techniques and assumptions used in arsenic risk assessment have evolved and 

changed over time, and it is not possible to do justice to all of the changes and innovations in 

each assessment in this chapter. Table 5-1 provides a general summary of the important data 

sources, techniques, and assumptions employed in each assessment. Where cells in the table are 

merged across the columns, it indicates that the same assumptions were used in more than one 

assessment, implying a solidification of a technical consensus. The major issues addressed in 

each study include: 

9 • Scope and goals. Some of the efforts in Table 5-1 (the NRC studies most importantly) 

were not intended to be comprehensive risk assessment, but to provide recommendations 

for EPA and other agencies. Some were pure modeling studies (Morales et al., 2000), 

and some were employed to derive quantitative risk estimates for regulatory support 

purposes (U.S. EPA, 2001) or for health criteria development (U.S. EPA, 2005c). 

• Selection of critical studies for use in the risk assessment. As noted above, the U.S. 

EPA (1988b) assessment was based on skin cancer prevalence data (Tseng et al., 1968; 

Tseng, 1977). All of the subsequent assessments in the table use data from later 

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epidemiological studies (Wu et al., 1989; Chen et al., 1988a, 1992), which provide 

information on PYR and cancer mortality in narrowly defined age strata, and exposure 

concentrations from individual water supply wells. 

5 • Critical study endpoints. Over time, assessments have moved from evaluating skin 

cancer (U.S. EPA, 1984, 1988b) to internal cancers (lung and bladder). As discussed 

below, the change in endpoint is the major reason that the cancer potency estimated in the 

current assessment is so different from that derived in 1988. Wu et al. (1989) and Chen 

et al. (1988a, 1992) also reported data on liver cancer, but in response to concerns related 

to a high incidence of viral hepatitis in Taiwan (U.S. EPA, 2001), liver cancer has not 

been included as an endpoint in recent assessments. 

• Dose-response models. The form of the dose-response models used to assess risks in the 

Taiwanese population has evolved over time as different investigators explored the 

performance of various models under a wide range of exposure assumptions. In the early 

models, linear regression and multistage models were used for dose-response assessment 

in the Taiwanese population. In the more recent analyses, Poisson regression with linear 

dose terms and quadratic age terms have been employed, as recommended by NRC 

(2001), to derive primary risk estimates. In addition, sensitivity analyses of other Poisson 

models (different transformations of dose) have been conducted, as recommended by 

SAB (2007). Changes in the modeling approaches, like changes in the endpoints 

modeled, have resulted in changes in estimated cancer potency. 

• Inclusion/exclusion of a reference population. EPA’s 2001 risk assessment was based 

on a dose-response model for the Taiwanese population that did not include a reference 

population (i.e., a group with similar characteristics not exposed to arsenic in drinking 

water). In keeping with NRC (2001) and SAB (2007) comments, the primary estimates 

in this chapter are derived based on the inclusion of a reference population from 

southwest Taiwan; sensitivity analyses are provided for risk estimates with the reference 

population excluded and with a reference population from all regions of Taiwan (i.e., 

“all-Taiwan”). 

• Arsenic concentration used in the dose-response model. The available exposure data 

(Wu et al., 1989; Chen et al., 1992) consist of measurements from 155 village drinking 

water wells taken between 1964 and 1966 for 42 exposed villages. Most of the 

assessments in Table 5-1 employed the median exposure concentrations for each group. 

That approach also is followed in this assessment; however, following SAB (2007) 

recommendations, a sensitivity analyses on the impacts of using minimum and maximum 

village arsenic concentrations in the risk assessment has been conducted. 

• Water intake and body weight of the exposed population. As discussed in Section 

5.3.5, there are few precise data available concerning the distribution of daily drinking 

water intake volumes in the exposed populations. As shown in Table 5-1, past 

assessments have employed a range of assumptions; the basic consensus is that 

Taiwanese men appear to consume more water than men in the U.S. owing to the hotter 

climate, and because a large proportion of them engage in vigorous outdoor activity as 

part of their livelihood. Consistent with the limited information, the current analysis has 

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followed this consensus. Following other analyses, this assessment assumes an average 

body weight of 50 kg for both Taiwanese men and women. 

4 • Nonwater arsenic intake. Because the risk modeling for the Taiwanese population is 

based on estimated daily arsenic dosage, it is important to include reasonable 

assumptions about the amount of arsenic intake coming from non-drinking water sources. 

 This is an area where there is relatively little data, and considerable confusion about, for 

example, whether and how to include a contribution from cooking water, reasonable 

estimates of arsenic concentrations in food, and whether the arsenic-exposed and 

reference populations should be assumed to receive the same nonwater arsenic intake. 

The various assumptions used in previous analyses are summarized in Table 5-1, and the 

basis for nonwater arsenic intake estimates used in this assessment is discussed in Section 

5.3.5. As is the case for many other assumptions, the approach to dealing with 

uncertainty in nonwater arsenic intake is to conduct sensitivity analyses based on a 

reasonable range of values. 

• Risk model for the U.S. population. The outputs of the dose-response modeling for the 

Taiwanese population were arsenic dose-response coefficients that described the 

relationship between estimated arsenic intake in the Taiwanese population and 

proportional increases in age-specific lung and bladder cancer mortality risk. Consistent 

with NRC (2001) recommendations, lifetime cancer incidence in U.S. populations was 

then estimated by using a modified version of the “BEIR IV” relative risk model, as 

described in Appendix E. A key assumption underlying this model is that the risk of 

arsenic-related cancer mortality or incidence for the U.S. population is a constant 

multiplicative function of the current “background” age profile of cancer risks in the 

same U.S. population. 

• U.S. mortality and cancer incidence data. Models for extrapolating cancer risks for the 

U.S population require data on overall mortality, and the BEIR IV model requires nonarsenic related cancer incidence data for the U.S. population. One source of variation in 

the cancer risk estimates over time has been the use of more recent mortality and cancer 

incidence data in the most recent assessments. 

• U.S. water intake and body weight. Estimates of the drinking water intake and typical 

body weight of the exposed population are also needed to predict cancer risks in the U.S. 

population. All of the recent assessments assume body weight of 70 kg for males and 

females. For the primary risk estimates, the current assessment assumes a water intake of 

2.0 L/day, as discussed in Section 5.3.5, with sensitivity analyses of other values. Adult 

water intake of 2.0 L/day is used as a standard factor in EPA IRIS assessments, and 

represents approximately the 90th percentile of intake of community water in the U.S. 

population. Other intake assumptions (e.g., mean versus upper percentile) can be used in 

risk assessments, depending on target population characteristics and assessment needs. 

• Endpoints calculated. As can be seen in Table 5-1, different assessments have 

calculated a range of risk endpoints, including ED01s, LED01s, lifetime cancer risks, CSFs, 

and drinking water concentrations corresponding to various cancer risk levels. As 

discussed in Section 5.3.8.2, this can create some difficulty in comparing the results 

across assessments, since converting from one measure to another can require 

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assumptions related to exposure that may not have been clearly specified. Where they 

have been calculated, the most commonly used and easily comparable endpoints are 

provided, including drinking water unit risks (lifetime cancer incidence associated with 

1 μg/L exposure), estimated cancer risk at 10 μg/L in drinking water, and the drinking 

water concentration associated with a lifetime cancer risk of 10-4. 

Given the many features of the risk assessment for arsenic that have changed over time, it 

is not surprising that the magnitude of the risk estimates has also varied from assessment to 

assessment. As discussed above, the CSF from U.S. EPA’s (1988b) assessment, which is 

derived based on skin cancer prevalence, is not directly comparable to CSFs derived from 

internal cancer data in the later assessments. Section 5.3.8.2 discusses modeling methods and 

assumptions used in the current assessment, describing precisely how they differ from previous 

analyses. 

5.3.2. Choice of Study/Data, Estimation Approach, and Input Assumptions 

As discussed in Section 4.2, the few animal carcinogenicity bioassays that have been 

conducted on inorganic arsenic compounds do not provide data of high enough quality to use in 

human dose-response modeling (NRC, 2001; SAB, 2000, 2007). There are, however, several 

epidemiologic studies that relate human exposures to arsenic in drinking water to cancer risk. 

NRC (2001) and SAB (2007) concluded that the epidemiological studies by Chen et al. (1988a, 

1992) and Wu et al. (1989) that use the southwestern Taiwanese population provide the best 

available data for conducting a quantitative risk assessment for exposure to arsenic in drinking 

water. SAB (2007) cited the important strengths of the data, including the large population, 

extensive follow-up (almost 900,000 person-years), large number of exposed villages (42), large 

number of lung and bladder cancer deaths (441), reliability of the population and mortality 

counts, and stability of residential patterns, stating that: 

• “...in view of the size and statistical stability of the database relative to other studies, the 

reliability of the population and mortality counts, the stability of residential patterns, and 

the inclusion of long-term exposures, it is the Panel’s view that this [the Taiwanese] 

database remains, at this time, the most appropriate choice for estimating cancer risk 

among humans. Supporting this view is the fact that the datasets from Taiwan have been 

subjected to many years of peer review as part of published studies.” 

In keeping with SAB’s recommendations, epidemiological studies by Smith et al. (1998) 

and Ferreccio et al. (2000) on arsenic-related lung cancer in Chile, as well as studies by Chiou et 

al. (2001) and Chen et al. (2004a), were evaluated (see Section 4.1 and Appendix B); however, 

these studies were not considered to be of comparable quality to the Taiwanese data set for use 

in the quantitative assessment. The dose-response estimation discussed below, like previous 

analyses, is based on the southwest Taiwanese data and incorporates the NRC and SAB 

recommendations for modeling approaches and sensitivity analyses. 

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5.3.3. Dose-Response Model Selection for Cancer Mortality in Taiwan 

Despite the high quality of the data set, estimation of dose-response relationships based 

on the Taiwanese data is challenging for a number of reasons. First, owing to the “ecological” 

nature of the study, drinking water exposure information is not available for individual study 

subjects. Instead, drinking water arsenic exposure must be estimated based on measured arsenic 

concentrations in wells serving the 42 population groups (“villages”) that constitute the study 

population. For 20 of the 42 villages, water was supplied by a single well at the time of 

sampling. For another 10 villages, water was supplied by two wells; the remaining villages used 

more than two wells. Data provided are related to all the arsenic measurements for each well in 

each village, but no information is available concerning the time variability of arsenic levels in 

individual wells. 

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In addition to villages where drinking water arsenic concentrations were measured, the 

epidemiological data used in this assessment include information on the cancer mortality in two 

reference populations (southwest Taiwan and all of Taiwan) for the same period covered by the 

Chen et al. (1988a, 1992) studies. Drinking water concentrations for the reference populations 

were not measured, but are assumed to be lower than those seen in the 42 arsenic-exposed 

villages (zero drinking water arsenic intake was assumed for the reference populations). As 

discussed below, the data on the nonwater arsenic intakes available for both the exposed and 

reference populations are very limited (Schoof et al., 1998), so the impacts of different 

assumptions are explored through a sensitivity analysis. 

It is clear that cancer mortality in the reference population and in the arsenic-exposed 

villages is strongly age-dependent, with the older study subjects generally exhibiting higher 

mortality. The age-dependence does not appear to be monotonic, however, but rather peaks 

around age 60 and declines thereafter. This non-linear age-dependence complicates the 

estimation of dose-response relationships because it requires the estimation of models using nonstandard methods. 

Chen et al. (1992) used an Armitage-Doll time-to-tumor model to estimate cancer risks as 

a function of dose in this population for 20-year age strata, but the model they used assumed 

monotonically increasing cancer risk with age. As discussed below, using narrower age strata (5 

years), the non-monotonic dependence of cancer risk on age becomes more apparent. Morales et 

al. (2000) used a variety of non-linear models to fit dose-response functions to data derived from 

the Chen et al. (1988a, 1992) and Wu et al. (1989) studies. They derived cancer slope estimates 

for arsenic-associated cancers of the bladder, liver, and lung by using Poisson regression with a 

number of different methods for expressing the dependence of risks on age and arsenic intake. 

When no reference population was included in the data, the best-fitting model included a 

quadratic function of age and a linear exponential term for dose. When the southwest Taiwan 

reference population was included in the risk modeling, the best-fitting model again included a 

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quadratic age model, but an exponential function of log-transformed dose. A number of other 

models with different age and dose terms were found to fit nearly as well as judged by the 

Akaike Information criterion (AIC). Many of the models also were very sensitive to changes in 

input assumptions. 

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NRC (2001) reviewed the U.S. EPA (2001) cancer assessment including application of 

the model from the Morales et al. (2000) study and conducted independent analyses of the data 

in order to systematically evaluate the effects of different modeling approaches, assumptions 

related to background cancer rates, and individual variability in exposures. As noted above, they 

recommended two specific changes to EPA’s modeling approach; the inclusion of a reference 

population, and the use of an additive (rather than multiplicative) linear dose term in the Poisson 

regression. SAB (2007) also reviewed EPA’s modeling procedures. Given the NRC 

recommendations and results of the SAB review, the current model (see Section 5.3.7) employs 

the following approaches: 

• Poisson regression (of cancer mortality against age and dose) fit by maximum likelihood 

estimation (MLE). 

• A quadratic age model. 

• Additive linear dose term. 

• Confidence limits on the dose terms estimated by profile likelihood. 

• Primary risk estimates derived for the data set that includes the southwest Taiwan 

reference population. 

As recommended by SAB, sensitivity analyses were conducted to evaluate the impacts of 

different modeling assumptions (nonwater arsenic intake, daily water intake, and reference 

population) on risk estimates. Several different model forms (quadratic, exponential linear, and 

exponential quadratic dose transformations) also were evaluated (see Section 5.3.8.4 for further 

detail). 

5.3.4. Selection of Cancer Endpoints and Estimation of Risks for U.S. Populations 

Lung and bladder cancer mortality in the Taiwanese population have been chosen as 

endpoints in the dose-response modeling because they are the internal cancers most consistently 

observed and best characterized in epidemiological studies of arsenic exposure (U.S. EPA, 2001; 

NRC, 2001). Oral CSFs and other risk metrics were calculated separately for each endpoint and 

gender. 

Although liver cancer risks also were examined by Morales et al. (2000), they were not 

included in the quantitative risk assessment because the observed liver cancer mortality in the 

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southwest Taiwanese population was thought to be affected by a high incidence of viral 

hepatitis, which made attribution of risks to arsenic problematic. As noted in Section 4.1, 

arsenic-related skin cancer also has been noted in the Taiwanese population (and in other 

arsenic-exposed groups), but this endpoint was not included in the cancer risk assessment for 

several reasons. The high mortality rates for internal cancers, compared to skin cancers which 

are rarely fatal, makes the internal cancers an appropriate critical health endpoints for the cancer 

risk assessment. In addition, the internal cancers were identified as the critical endpoints 

because the estimated cancer potency of arsenic for lung and bladder cancers was much greater 

than the potency estimated for skin cancers (see Section 5.3.8.1). The development of precancerous skin lesions (as reported by Ahsan et al., 2006) is being addressed separately in EPA’s 

noncancer risk assessment. 

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The current risk model includes multiplicative terms for age and dose. Therefore, the 

risk calculated for a target population (e.g., a U.S. population exposed to arsenic in drinking 

water) depends on the “background” cancer risk, i.e., the expected age-specific cancer risk in the 

U.S. population in the absence of arsenic exposure. Morales et al. (2000) calculated lifetime 

arsenic-related mortality risks for the U.S. population exposed to different drinking water 

concentrations by applying age-specific hazard functions (derived from the dose-response 

models estimated for the Taiwanese population) to a “life table” of age-specific probabilities of 

death for the U.S. population. These calculations were based on data from 1996. 

In response to comments from NRC and SAB, a slightly different approach to estimate 

cancer risks for U.S. populations is being used. In the following analysis, arsenic concentrations 

corresponding to an additional 1% lifetime cancer incidence (effective dose; ED01 values) above 

“background” are derived for each endpoint. Also derived are lowest effective dose (LED01) 

values, which represent the lower confidence limits on the dose corresponding to a one percent 

lifetime incidence risk in the U.S. population. Consistent with EPA’s Guidelines for Carcinogen 

Risk Assessment (U.S. EPA, 2005a) and the NRC (2001) cancer assessment, risk estimates are 

derived based on a linear extrapolation from the points of departure (LED01s for lung, bladder, 

and combined cancers) because the MOA for inorganic arsenic is unknown. 

The ED01 and LED01 values are estimated using a variation on the “BEIR IV” model 

derived for use in estimating population cancer risks for radionuclide exposures (NRC, 2001). 

This method, which is described further in Section 5.3.7.3 and Appendix E.2, includes the 

application of relative cancer risk estimate derived from the Taiwanese dose-response 

assessment multiplicatively to age-specific cancer risks for the United States. In this model, the 

background hazard consists of age-specific cancer incidence data for bladder and lung cancer 

from the United States for the years 2000 to 2003 (NCI, 2006). The ratios of cancer mortality to 

incidence for arsenic-related cancers are assumed to be the same in the U.S. and Taiwanese 

populations. 

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5.3.5. Nonwater Arsenic Intake and Drinking Water Consumption 

It is important to clarify that the nonwater arsenic intake value corresponds to the arsenic 

amount from dietary sources (rice and yams, the dietary staples for the Taiwanese population in 

the endemic area) only. It does not include the arsenic intake value from water used for cooking 

rice or produce, which was addressed separately via sensitivity analysis modeling with higher 

water intake values. 

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For the baseline risk calculations, the nonwater arsenic intake was assumed to be 10 

μg/day for the reference and exposed populations. Although the data supporting this value are 

scarce, it appears to be a reasonable intake estimate for the reference populations based on the 

available information. U.S. EPA (1989) estimated the arsenic intake based on soil arsenic level 

and rice consumption in Taiwan to be between 2 and 16 μg/day. The higher value was presumed 

to result from possible soil contamination by organic arsenical herbicides applications. U.S. 

EPA (1989) found no reliable data to estimate arsenic intake from sweet potato (yam) 

consumption by the southwest Taiwanese population. In a separate study, Schoof et al. (1998) 

estimated that the total inorganic arsenic intake from food sources in the endemic area in Taiwan 

ranged between 15 and 211 μg/day, with the average intake value as 50 μg/day. This arsenic 

intake value is based on analysis of limited rice and yam samples collected in the endemic area 

of Taiwan during 1993 and 1995 (Schoof et al., 1998). It is likely that the arsenic intake in the 

non-endemic area (background arsenic intake value for reference population) is lower than that 

reported in the endemic area. 

EPA also examined the arsenic intake value from food sources in countries where the 

arsenic exposures are much lower than in Taiwan. The average nonwater inorganic arsenic 

intake from food consumption is reported to range from 8.3 to 14 μg/day in the United States and 

from 4.8 to 12.7 μg/day in Canada, with variation across age groups (Yost et al., 1998). Based 

on the available information, EPA selected 10 μg/day as the best estimate for nonwater arsenic 

intake (food sources) in baseline calculations. Alternate values of nonwater arsenic intake were 

also explored in the sensitivity analysis (Section 5.3.8.3). 

NRC (1999) reported the background arsenic intake of 50 μg/day in endemic areas based 

on the Schoof et al. (1998) findings. It is not clear if this value was ever used for dose-response 

modeling in estimating bladder cancer risk. However, NRC (2001) included the background 

intake of 30 μg/day in the dose-response modeling; the basis for the latter value is not clear. 

NRC (2001) also reported that there was no difference in the lung and bladder cancer risk 

estimates when 30 or 50 μg/day were used as the nonwater intake values in the exposed 

populations. It is not clear if NRC (2001) assumed any nonwater arsenic intake value for the 

reference populations. In the draft Toxicological Review submitted to SAB in 2005 (U.S. EPA, 

2005c), nonwater arsenic intake values of 0, 30, and 50 μg/day were assumed for the exposed 

populations only, and the background inorganic arsenic intake was assumed to be zero for the 

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reference populations. SAB (2007) recommended that the background arsenic intake for 

reference (control) populations should not be assumed to be zero. However, SAB did not specify 

a nonwater inorganic arsenic intake value for the reference population. 

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Given the state of the available data and the recommendations from SAB, EPA has 

assumed 10 μg/day nonwater arsenic intake for the current assessment for both reference and 

exposed populations in the baseline risk calculations. EPA also evaluated 0, 30, and 50 μg/day 

for dietary arsenic intake assumption for reference populations, and up to 200 μg/day for 

exposed populations. The high-end background arsenic intake value was recommended by SAB 

in 2007 (i.e., the background arsenic intake value in the exposed populations as high as 200 

μg/day should be included to assess the impact in lung and bladder cancer risk estimates) 

(Section 5.3.8.3). 

In the current assessment, the drinking water consumptions for Taiwanese males and 

females are assumed to be 3.5 L/day and 2.0 L/day, respectively, in the baseline risk 

calculations. These values are consistent with the assumptions applied by U.S. EPA (1988b), 

Chen et al. (1992), and NRC (1999 and 2001) for cancer risk estimations. There is conflicting 

information concerning the extent to which these values include both direct drinking water 

consumption and water used for cooking. To examine the impact of additional water 

consumption in cancer risk estimations, NRC (2001) also examined different ratios of water 

intake-rates between Taiwanese and U.S. populations (up to ratio of 3.0). 

In the U.S. EPA (1989) report, the arsenic workgroup estimated that the total water 

consumption for the Taiwanese men, including the water used for cooking rice and yams (the 

dietary staples in the southwest Taiwanese population), was 4.5 L/day since Taiwanese workers 

could drink 3.0 to 4.0 L/day of water and the 3.5 L/day seemed to be a reasonable estimate for 

direct water consumption. Indirect water consumption from cooking rice and yams was 

estimated to be 1.0 L/day. The basis for the derivation of the drinking water values in the U.S. 

EPA (1989) report is approximate and gathered from very limited populations (three or four 

residents were surveyed). In the Arsenic Rule (U.S. EPA, 2001), the total water Taiwanese 

consumption rates (including water used for cooking) were assumed to be 4.5 L/day for males 

and 3.5 L/day for females. 

SAB (2007) did not recommend specific water intake values to be used for cancer risk 

modeling in the Taiwanese populations. Therefore, in the current assessment, the baseline water 

intake values modeled are 3.5 L/day for males and 2.0 L/day for females, to be consistent with 

NRC (1999) recommendations. In addition, a range of water consumption values (up to 5.1 

L/day in males and 4.1 L/day in females) were evaluated in the sensitivity analysis to study the 

impact of alternate water consumption in the cancer risk estimates. The water consumption 

values modeled in the baseline calculations for Taiwanese populations are also close to the 

average estimates provided for populations in West Bengal, India (Chowdhury et al., 2001), 

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where the climate is close to Taiwan. The average drinking water intake values for children, 

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The drinking water consumption for the U.S. reference population is estimated to be 2.0 

L/day for both men and women. This is approximately equal to the 90th percentile estimate 

(2.014 L/day) from the 1994–1996 and 1998 data gathered as part of the Continuing Survey of 

Food Intake by Individuals (U.S. EPA, 2004), and is consistent with upper percentile estimates 

from previous surveys. Alternative assumptions about U.S. drinking water consumption result in 

simple reciprocal adjustments to CSF estimates (discussed further in Section 5.3.8.3). Within 

the range analyzed, changes in the assumptions about Taiwanese drinking water consumption 

also result in nearly linear effects on estimated dose-response slope estimates. 

5.3.6. Dose-Response Data 

Table 5-2 summarizes the cancer mortality data from the Morales et al. (2000) study. For 

this assessment, the original data set containing age-specific PYR, mortality statistics, and 

village water concentration data was obtained from Dr. Morales (Morales et al., 2000). 

Water arsenic concentration data were provided for each village. Single concentration 

measurements were provided for each well. For 20 of the 42 villages only data for one well was 

reported. However, for the remaining 22 villages, multiple well concentrations were available 

(range between 2 and 47 measurements) (NRC, 1999). For dose-response estimation, models 

were fit to the median well concentration for each village. As part of the sensitivity analysis, the 

reported maximum or minimum well arsenic concentrations were also applied to the models. 

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Table 5-2. Cancer Mortality Data Used in the Arsenic Risk Assessment 

Gender 

Village Water 

Concentration, 

μg/L 

Age 20–30 30–49 50–69 >70 Total 

PYRa 35,818 34,196 21,040 4,401 95,455 <100 

Deathsb (0, 0, 0) (1, 10, 2) (6, 17, 12) (10, 4, 14) (17, 31, 28) 

PYR 18,578 16,301 10,223 2,166 47,268 100–299 

Deaths (0, 0, 0) (0, 4, 3) (7, 15, 14) (2, 4, 13) (9, 23, 30) 

PYR 27,556 25,544 15,747 3,221 72,068 300–599 

Deaths (0, 3, 0) (5, 7, 9) (15, 23, 30) (12, 6, 14) (32, 39, 53) 

PYR 16,609 15,773 8,573 1,224 42,179 >600 

Deaths (0, 0, 1) (4, 12, 3) (15, 15, 23) (8, 2, 6) (27, 29, 33) 

PYR 98,561 91,814 55,583 11,012 256,970 

Male 

Total 

Deaths (0, 3, 1) (10, 33, 17) (43, 70, 79) (32, 16, 47) (85, 122, 144)

PYR 27,901 32,471 21,556 5,047 86,975 <100 

Deaths (0, 0, 0) (3, 1, 5) (9, 6, 18) (9, 5, 5) (21, 12, 29) 

PYR 13,381 15,514 11,357 2,960 43,212 100–299 

Deaths (0, 0, 0) (0, 3, 4) (9, 6, 10) (2, 5, 5) (11, 14, 19) 

PYR 19,831 24,343 16,881 3,848 64,903 300–599 

Deaths (0, 0, 0) (0, 5, 6) (19, 6, 20) (11, 2, 10) (30, 13, 36) 

PYR 12,988 15,540 9,084 1,257 38,869 >600 

Deaths (0, 0, 0) (0, 4, 6) (21, 7, 28) (7, 1, 4) (28, 12, 38) 

PYR 74,101 87,868 58,878 13,112 233,959 

Female 

Total 

Deaths (0, 0, 1) (3, 13, 21) (58, 25, 76) (29, 13, 24) (90, 51, 122) 

a PYR = person-years at risk 

b

 Numbers in parentheses = number of cancer deaths due to bladder, liver, and lung cancer, respectively. 

5.3.7. Risk Assessment Methodology 

The cancer risk assessment for U.S. population exposure to arsenic in drinking water was 

conducted in four steps: 

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4 • Models were fit to the data using mg/kg-day intake metrics calculated from the estimated 

water consumption values for the Taiwanese population and village water arsenic 

concentrations, assuming a 10 μg/day nonwater dietary intake in the baseline analysis. 

Dose-response models were fit to the Morales et al. (2000) data for bladder and lung 

cancer in both genders using maximum likelihood methods (see Section 5.3.7.1). 

• Upper confidence limits (UCLs) on the dose coefficients from the fitted models were 

estimated using the profile likelihood method (see Section 5.3.7.2). 

• LED01 values for U.S. populations were calculated for each endpoint and gender based on 

the dose coefficient UCLs calculated for the Taiwanese populations in the previous step. 

Using the “BEIR IV” methodology, U.S. bladder and lung cancer incidence data for the 

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years 2000 to 2003 (NCI, 2006) were used as the reference values for calculating U.S. 

lifetime cancer risks. Thus, the LED01 values are expressed in terms of lifetime cancer 

incidence for the U.S. population (see Section 5.3.7.3). 

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The LED01 values were used to calculate ingestion drinking water unit risks for lung and 

bladder cancer for arsenic-exposed men and women in the United States. This step involved 

linear extrapolation from the LED01 values to zero dose and risk, yielding estimates of low-dose 

CSFs. Unit risk and CSF calculations were adjusted for differences between body weights and 

drinking water ingestion rates in Taiwan and the United States. Other risk metrics (estimated 

lifetime incidence risk per mg/kg-day arsenic intake and corresponding to specific drinking 

water concentrations) were calculated for each endpoint from the LED01 values (see Section 

5.3.7.4). 

5.3.7.1. Dose-Response Estimation Based on Taiwan Cancer Mortality Data 

A “Poisson model” was used to fit the cancer mortality data for the Taiwanese 

population. The general form of the Poisson model is: 

h(x,t) = h0(t) × g(x) (Equation 5-1) 

where: h(x,t) = cancer mortality risk at dose “x” and age “t” 

 h0(t) = cancer mortality risk in the reference population at age “t” 

 g(x) = risk attributable to arsenic exposure at dose “x” (mg/kg-day) 

Taiwanese cancer mortality and PYR data were available for 5-year ranges for ages 20 to 

84. Cancer mortality data for the southwest Taiwan reference groups also were included in the 

preferred version of the model; estimates were derived without the reference population and with 

cancer mortality statistics from all regions of Taiwan. In the Poisson model, which is widely 

applied in the analysis of epidemiology data, cancer deaths are assumed to be “rare” events and 

Poisson-distributed within each age-dose group. When h0(t) and/or g(x) are non-linear 

functions, as is the case for arsenic, the model cannot be fit using conventional least-squares 

regression methods or general linear models (GLM). Based on recommendations from NRC 

(2001) and after testing a number of different models, the following model form was selected for 

primary risk estimates based on goodness-of-fit and parsimony criteria:4 

h(x,t) = exp(a1 + a2 × age + a3 × age2) × (1 + b × dose) (Equation 5-2) 

where: a1, a2, a3 = age coefficients; b = dose coefficient 

4

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Specifically, the model parameters in h(x,t) in Equation 5-2 were obtained by assuming 

that the number of cases in each exposure-age category has a Poisson distribution with parameter 

λ(x,t), Cases ~ Poisson (Py × λ(x,t)), where Py is person-years, and λ is the intensity of Poisson 

parameter at the exposure-age,(x,t), category. Because data are given in 5-year age intervals, the 

parameter λ is related to hazard rate h which is equal to λ/5. 

In this model, the exponential term represents “h0(t)”in Equation 5-1, the age-dependent 

risk of cancer at the “background” doses of arsenic (zero from drinking water and 10 μg/day 

from diet in the preferred model). The last term in the equation captures the dependency of risk 

on the daily ingestion dose of arsenic. 

Cancer mortality data were stratified across 13 5-year age groups and 43 villages (42 

exposed villages plus the reference population). This stratification yielded 559 data points per 

cancer endpoint for model fitting. Mid-range values for the age ranges were standardized to 

their mean values and treated as nuisance parameters. 

The unit of dose used in the modeling was mg/kg-day. In the primary (baseline) risk 

model, the estimated nonwater arsenic intake was 10 μg/day for both the exposed and reference 

populations. The total arsenic dose received by the population of any village was estimated as 

the sum of the nonwater dietary intake plus the median arsenic well water concentration for the 

village (baseline model), multiplied by the estimated water Taiwanese consumption rates (3.5 

L/day for men, 2.0 L/day for women) and divided by estimated average body weights for 

Taiwanese men and women (50 kg for both genders; Chen et al., 1992). The southwest 

Taiwanese population outside of the arseniasis-endemic area (Morales et al., 2000) served as the 

reference population in the baseline model. 

Values for the coefficients a1, a2, a3, and b were fit using MLE methods. Likelihood 

maximization was performed using the Solver add-in of Excel®. The MLE fits for the baseline 

model were replicated using the Non-Linear Estimation module of Statistica®. Replicated 

results (estimated age and dose coefficients) were identical to Solver estimates to the third 

decimal place for all endpoints. 

5.3.7.2. Estimation of Confidence Limits on Cancer Slope Parameters 

The LED01 values were derived based on estimated upper confidence limits on the 

estimated dose coefficients (“b”) for each endpoint and gender. The confidence limits were 

calculated using the likelihood profile method (Venson and Moolgavkar, 1988). In this 

approach, the value of the dose parameter, b, was varied from its estimated mean value. The 

ratio of the log likelihood for the best-fit model to the log likelihood for other values of “b” is 

known to follow an approximate chi-squared distribution with one degree of freedom. Thus, the 

5th and 95th confidence limits on the dose coefficient “b” correspond to the values where the 

likelihood ratio is equal to 1.92. Upper and lower confidence limits were calculated using 

Solver®. The fact that the profile likelihood method ignores the likelihood impact of the age 

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“nuisance parameters” implies that the calculated confidence limits are only approximate. 

Confidence limit calculations using other methods (empirical Bayesian simulation

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5 and 

“bootstrap-t”) gave comparable results (within a few percent of the values estimated by profile 

likelihood). 

5.3.7.3. Estimation of LED01 Values Using Relative Risk Models 

Once the dose coefficients were calculated, they were used to estimate arsenic-associated 

lifetime risks in the U.S. population. In this analysis, LED01 values for the U.S. population were 

calculated using a variant of the “BEIR IV” relative risk model recommended by NRC (2001). 

The method applied the relative risk estimated as (1 + bUCL × dose) to the age profile of cancer 

incidence for the reference (U.S. male or female) population, where bUCL is the 95% upper 

confidence limit on “b” (the arsenic coefficient from the dose-response model for the Taiwanese 

population, estimated as explained in Section 5.3.7.2). The BEIR IV model also takes into 

account the effect of noncancer mortality, cancer mortality, and previous cancer incidence on the 

number of individuals in the exposed population who survive to the start of each 5-year age 

stratum. To estimate cancer risks in the U.S. population, incidence risks are calculated for each 

5-year age stratum and summed to give an estimate of lifetime incidence. The dose is then 

adjusted until the estimated extra incidence risk from arsenic-associated cancer risk equals 0.01 

(1%) for the U.S. reference population. The dose (in mg/kg-day) that fulfills this condition is the 

LED01, which becomes the point of departure (POD) for estimating the CSF. 

The BEIR IV model takes as its input age-specific mortality data and lung and bladder 

cancer incidence for the U.S. reference population.6 U.S. cancer incidence was estimated in this 

analysis based on mortality data for the year 2000 (NCHS, 2000). Lung and bladder incidence 

data for the years 2000 to 2003 were obtained from the National Cancer Institute’s SEER 

(surveillance epidemiology and end result) program (NCI, 2006). Arsenic intakes resulting in 

10-4 lifetime risks were estimated using Solver®. Details of the relative risk methodology are 

provided in Appendix E.2. 

5.3.7.4. Estimation of Unit Risks 

For each endpoint and gender, the slope of a line from the LED01 dose through the 

intercept (water-related arsenic dose = 0, water-related arsenic risk = 0) was calculated. The 

slopes of these lines represent the oral CSF for the endpoint: 

5 The empirical Bayes modeling involved taking random samples within the neighborhoods of the MLE coefficient 

values, calculating the log likelihood, and after many iterations, building up an estimate of the posterior distribution 

of the “b” coefficient (mean and standard error). Confidence limits were then estimated assuming the posterior 

probability of b was normally distributed. 

6 Note that the age dependence estimated for the Taiwanese population—represented by the parameters a1, a2, and 

a3—is specific to that population, and is not carried over to the United States. 

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oral CSF (per mg/kg-day) = 0.01/LED01 (Equation 5-3) 

Linear low-dose extrapolation was employed consistent with EPA’s finding that 

insufficient mode of action data are available to justify the use of non-linear, low-dose models 

(Section 4.6.3.2). Unit risks (cancer risk per μg/L arsenic in drinking water) also were 

estimated: 

unit risk (per μg/L) = CSF (per mg/kg-day) × 0.001 × DW/BW (Equation 5-4) 

where: 0.001 = conversion from milligrams to micrograms 

 BW = body weight for exposed population in kilograms (U.S. male and female) 

 DW = daily drinking water consumption for exposed population in liters (U.S. male 

and female) 

As discussed previously, the estimated drinking water consumption for the U.S. adult 

population is 2.0 L/day for both males and females. U.S. male and female body weights are 

estimated to be 70 kg. The 2.0 L/day is a standard factor used in EPA IRIS assessments, and 

represents approximately the 90th percentile of intake of community water in the U.S. 

population. Other intake assumptions (e.g., mean versus upper percentile) can be used in risk 

assessments, depending on target population characteristics and assessment needs. 

5.3.8. Results 

5.3.8.1. Ingestion Pathway Oral CSFs and Unit Risks 

Table 5-3 presents the estimated risk metrics for lung and bladder cancers in males and 

females under baseline assumptions (see Footnote “a” to the table for baseline modeling 

assumptions). 

The estimated oral CSF for female lung cancer (16.6 per mg/kg-day) is higher than that 

for males (6.7 per mg/kg-day), but the bladder cancer oral CSFs for males and females are 

comparable (11.2 and 10.5 per mg/kg-day, respectively). Drinking water unit risks for lung 

cancer are 1.9 × 10-4 and 4.8 × 10-4 per μg/L, respectively, for males and females while the 

drinking water unit risks for bladder cancer are 3.2 × 10-4 and 3.0 × 10-4 per μg/L, respectively. 

Estimated lifetime incidence risks corresponding to 10 μg/L arsenic in drinking water follow 

similar patterns for the various endpoints. Estimated drinking water concentrations associated 

with 10-4 lifetime incidence range from 0.21 μg/L (female lung cancer) to 0.52 μg/L (male lung 

cancer). 

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Table 5-3. Cancer Incidence Risk Estimates for Lung and Bladder Cancers in Males and 

Femalesa

Metric Lung Cancer Bladder Cancer 

Males 

ED01, mg/kg-day 1.9E-03 1.1E-03

LED01, mg/kg-day 1.5E-03 8.9E-04

Oral CSF, per mg/kg-day 6.7 11.2

Unit risk, per μg/L drinking water 1.9E-04 3.2E-04

Lifetime incidence risk at 10 μg/L in drinking water 1.9E-03 3.2E-03

Water concentration for 10-4 risk, μg/L 0.52 0.31

Females 

ED01, mg/kg-day 7.5E-04 1.2E-03

LED01, mg/kg-day 6.0E-04 9.5E-04

Oral CSF, per mg/kg-day 16.6 10.5

Unit risk, per μg/L drinking water 4.8E-04 3.0E-04

Lifetime incidence risk at 10 μg/L in drinking water 4.8E-03 3.0E-03

Water concentration for 10-4 risk, μg/L 0.21 0.33

a Baseline assumptions: reference population = southwest Taiwan; Taiwanese male and female body weight = 50 

kg, Taiwanese male water intake = 3.5 L/day, Taiwanese female water intake = 2.0 L/day; reference and exposed 

population nonwater arsenic intake = 10 μg/day. Male and female U.S. body weights are assumed to be 70 kg, 

and U.S. water intake for both males and females is assumed to be 2.0 L/day. 

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Arsenic-related cancer risks also are calculated for the population as a whole, that is, for 

combined bladder and lung cancer incidence in a population composed of both men and women. 

 In this analysis, total cancer risk (lung plus bladder) for males and females is calculated by 

combining the risk for the individual tumor types. Upper confidence limits on the combined 

cancer risks can be calculated based in the assumption that the uncertainties in the two CSFs are 

both normally distributed. If this is the case, the 95% upper bound, U, for the combined cancer 

potency can be calculated as: 

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21 11 −+−++= mumummU )()()( 9 (Equation 5-5) 

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where mi and ui, i = 1,2, are respectively mean and 95% upper bound cancer potency for the two 

tumor types. The results of these calculations are summarized in Table 5-4. Using this 

approach, the combined cancer potency factor estimate for males is 16.9 per mg/kg-day for 

males and 25.7 per mg/kg-day for females. The estimated drinking water unit risk for combined 

male lung and bladder cancer is 4.8 × 10-4 per μg/L; for females, the estimated value is 7.3 × 10-4

per μg/L. The drinking water concentrations corresponding to 10-4 combined cancer risks for 

males and females are 0.21 and 0.14 μg/L, respectively. 

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Table 5-4. Combined Lung and Bladder Cancer Incidence Risk Estimate for the U.S. 

Population (Males and Females) 

Metric Male Combined 

Lung+Bladder 

Female Combined 

Lung+Bladder 

Oral CSF, per mg/kg-day 16.9 25.7 

Unit risk, per μg/L drinking water 4.8E-04 7.3E-04 

Lifetime incidence risk at 10 μg/L 

in drinking water 4.8E-03 7.3E-03 

Water concentration for 10-4 risk, 

μg/L 0.21 0.14 

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Figure 5-1 shows the estimated oral CSFs for each of the endpoints separately, along 

with oral CSF estimates for the combined cancers in males and females. In keeping with EPA 

policy, the combined oral CSF for women (25.7 per mg/kg-day) is appropriate for use in 

establishing health criteria, since, based on the available data, women appear to be the 

more sensitive group. 

0

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25

30

Male Lung Male

Bladder

Male

Combined 

Female

Lung 

Female

Bladder

Female

Combined

Cancer Slope Factor, per mg/kg-day

Figure 5-1. Estimated oral CSFs for individual and combined cancer 

endpoints. 

5.3.8.2. Comparison to Previous Cancer Risk Estimates 

As discussed in Section 5.3.1, a number of risk assessments have been conducted by EPA 

and others. Results of the present dose-response assessment were compared to cancer risk 

estimates derived from the same and other data sets in previous studies (NRC, 2001; U.S. EPA, 

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2005c). Note that the results of the U.S. EPA (1988b) analysis, which estimated a CSF of 1.0–

2.0 per mg/kg-day, are not comparable to the results of the current assessment (CSF 25.7 per 

mg/kg-day), because the former was based on skin cancer, while all of the more recent analyses 

estimate risks of internal (lung and bladder) cancers. Thus, the detailed comparisons in this 

section are limited to assessments that also address lung and bladder cancer. The drinking water 

standard (U.S. EPA, 2001) also provides numerical risk estimates for exposures to arsenic in 

drinking water. However, Tables III.D-2(a) and (b) of the rule (U.S. EPA, 2001) display ranges 

of cancer risks for populations exposed to distributions of arsenic concentrations in drinking 

water at and above the proposed MCL options. Thus, the numerical risk results of that analysis 

are also not directly comparable to the NRC (2001), U.S. EPA (2005c), and current assessments, 

which apply to populations exposed to single concentrations. In the analyses that follow, some 

of the risk comparisons are based on mortality estimates that have been converted to incidence 

using recent U.S. incidence-mortality ratios. This conversion introduces additional uncertainty 

into the comparisons; different results would have been obtained had the incidence been 

modeled directly rather than estimated after the fact. 

5.3.8.3. ED01 and LED01 Estimates From Chen et al. (1988a, 1992), Ferreccio et al. (2000), 

and Chiou et al. (2001) 

Consistent with SAB (2007) recommendations, Table 5-5 presents risk estimates from 

previous studies and compares them to estimates derived in this analysis. The estimates in Table 

5-5 come from Table 5-3 of NRC (2001), and include ED01 and LED01 estimates (expressed as 

μg/L arsenic in drinking water) from a number of studies of arsenic-related cancer risks in Chile 

(Ferreccio et al., 2000) and Taiwan (Chiou et al., 2001; Chen et al., 1988a, 1992). 

NRC calculated ED01 and LED01 values for lung and bladder cancer mortality from the 

same Taiwanese cohort used in the current assessment, based on the results presented in Chen et 

al. (1988a, 1992), but without a reference population. In addition, these values do not account 

for differences in drinking water consumption between the U.S. and Taiwanese populations, and 

did not apply life-table adjustments. 

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Table 5-5. Comparison of ED01 and LED01

a

 Estimates From Past Studiesb With Those From 

the Current Analysis 

Male Lung Female Lung Male Bladder Female Bladder Study ED01 LED01 ED01 LED01 ED01 LED01 ED01 LED01

Chen et al. (1988a, 

1992), Taiwan 38–84 37–72 33–

94 31–84 102–317 94–286 138–443 125–406 

Ferreccio et al. 

(2000), Chile 5–17 3–14 7–27 5–21 — — — — 

Chiou et al. (2001), 

Taiwan — — — — 129–500+ 42–

500+ 231–500+ 88–500+ 

Current analysis 66 52 26 21 40 31 41 33 

a

 Units = μg/L arsenic in drinking water 

b

 Source of estimates: NRC (2001) 

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NRC also estimated ED01 and LED01 values based on data from the Ferreccio et al. (2000) 

case-control study of male and female lung cancer data from a Chilean population that included 

151 lung cancer cases and 419 controls. The ED01 and LED01 derived by NRC were obtained by 

linear regression of mortality odds ratio estimates on exposures, with the intercept forced to a 

value of 1.0 at zero exposure. These estimates are shown in the second row of Table 5-5. 

Multiplicative linear dose and log dose models were used to derive ED01 and LED01 estimates 

from the study by Chiou et al. (2001) of urinary tract cancer incidence over a 4-year period in 

8,000 Taiwanese exposed to arsenic in drinking water. These results are presented in the third 

row of Table 5-5. Where ranges are given in the table, the minimum and maximum values 

represent the lowest and highest ED01 or LED01 estimates that were derived when different 

models were used. 

The bottom row of the table shows the ED01 and LED01 values for cancer incidence 

derived in this analysis using the Poisson regression and BEIR IV models. The ED01 and LED01

values for lung cancer derived in the current assessment fall within, or are close to, the ranges 

estimated from the Chen et al. (1988a, 1992) data. This finding is not surprising because the 

results are estimated for the same cohort in both cases, and because the case mortality for lung 

cancer is so high (nearly 100%). The ED01 and LED01 values derived in the current assessment 

are, however, higher than those estimated by Ferreccio et al. (2000). One possible explanation 

involves differences in modeling methods; to estimate ED01 and LED01 values from the Ferreccio 

study, NRC applied linear regression to the odds ratio estimates, forcing the intercept through 

1.0 at zero dose. Thus, these values must be considered highly uncertain. The differences also 

may be due to differences in exposure conditions (e.g., NRC did not account for differences in 

drinking water intake between the Chilean and U.S. populations) or other covariates (e.g., 

smoking) between the two studies. 

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For bladder cancer, the ED01 and LED01 values estimated in this analysis are lower (2.5- 

to 10-fold) than those derived from the Chen et al. studies (1988a, 1992). In addition to the 

differences in modeling approaches outlined above, another possible reason for this difference is 

that the Chen et al. (1988a, 1992) studies are based on bladder cancer mortality, while the ED01 

and LED01 values in this analysis are for bladder cancer incidence. Adjustment for bladder cancer 

case mortality (in the order of 16–20%) would make EPA’s current results much more similar to 

those of Chen et al. (1988a, 1992). 

Finally, the ED01 and LED01 values from the current analysis are below the lower end of 

the ranges estimated by Chiou et al. (2001). Reasons for this finding are not entirely clear. The 

sensitivity of the Chiou et al. study may have been limited by the short follow-up period (NRC, 

2001), and only 18 total urinary tract cancers were identified in the study. Only four exposure 

categories were analyzed (less than 10 μg/L, 10–50, 50-100, and more than 100 μg/L in water; 

nonwater exposures were not evaluated). The low sensitivity could have caused the ED01 and 

LED01 estimates derived by Chiou et al. (2001) to be biased upward from what would have been 

seen with a more extended follow-up period. 

5.3.8.4. Estimated Risk Associated With 10 μg/L Drinking Water Arsenic From NRC 

(2001) 

Table 5-6 provides an additional set of comparisons between the current risk estimates 

and the results from a previous analysis by NRC (2001). Lifetime incidence risks are presented 

for a hypothetical U.S. population exposed to 10 μg/L arsenic in drinking water. NRC (2001) 

estimated arsenic-associated risks using an “additive Poisson model with dose entered as a linear 

term and using the BEIR IV formula” (p. 201). 

Table 5-6. Comparison of cancer risk assessment results with estimates from NRC (2001) 

Estimated Cancer Incidence at 10 μg/L Arsenic in 

Drinking Water (per 10,000 Exposed Population) 

Bladder Lung 

Source of Estimate 

Male Female Male Female 

NRC (2001), Taiwan 23 12 14 18 

Current analysis 32 30 19 48 

a The original mortality risk estimates from U.S. EPA (2005c) were multiplied by incidencemortality ratios for the various endpoints to obtain incidence estimates. For the Taiwanese 

populations, case mortality for lung cancer was assumed to be 100% and mortality for bladder 

cancer was assumed to be 80% (NRC, 2001). 

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The incidence risks derived in the current analysis, however, are reasonably close, but not 

identical, to the NRC (2001) estimates. Differences in the calculated cancer potency relate to 

several factors. Changes in the assumed drinking water intake in females in the current 

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assessment compared to the NRC (2001) and U.S. EPA (2005c) analyses are summarized in 

Table 5-7. In particular, the change in the assumed ratios of Taiwanese/U.S. female water intake 

from 2.8 in the earlier assessments to 1.4 in the current analysis are relevant to the differences in 

risk shown in Table 5-6. The lower ratio in the current analysis translates into a slightly greater 

than 2-fold greater estimated risk for females in the current assessment than in the NRC (2001) 

and current analyses. 

Table 5-7. Drinking water intake and body weight assumptions in females in recent arsenic 

risk assessments 

Body Weight, kg Water Intake, L/day Assessment 

Taiwan U.S. Taiwan U.S. 

Ratio of Taiwan/U.S. 

Drinking Water Intake 

NRC (2001) 50 70 2 1 2.8 

U.S. EPA (2005c) 50 70 2 1 2.8 

Current analysis 50 70 2 2 1.4

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In addition, the NRC (2001) risk estimates are based on maximum likelihood estimates 

(MLE) of the arsenic slope parameters in the Poisson regression, while U.S. EPA (2005c) and 

the current assessment derive risks based on the statistical upper confidence bounds on these 

parameters. As shown in Table 5-3, the difference between the MLE estimates (ED01 values) 

compared to the upper confidence limit (LED01) is on the order of 20%. This would translate into 

approximately 20% greater risks calculated based on the upper confidence limit values compared 

to the MLE estimates. 

 The use of more recent cancer incidence and mortality data in the BEIR IV model than 

in the previous risk assessments also probably contributes to the differences in risks in Table 5-6. 

 Also, the current assessment includes a modification to the BEIR IV model suggested by Gail et 

al. (1999) for obtaining more accurate estimates of incidence within multi-year age strata. The 

modifications to the model are described in detail in Appendix E.2. 

Changes in the assumptions related to nonwater arsenic intake also would be expected to 

have small to moderate effects on the results within the range in question. In this assessment, 

both the reference and exposed populations are assumed to receive 10 μg/day nonwater arsenic 

intake (see Section 5.3.5). Section 5.3.8.3 presents the results of uncertainty analyses that 

explore the effects of changes in selected modeling assumptions, including nonwater arsenic 

intake, on the risk estimates. 

The cancer risk estimates presented in Table 5-8 for consumption of drinking water with 

specified arsenic concentrations provide information that is scientifically equivalent to estimates 

of CSFs. The NRC’s (2001)recommended risk models provide estimates that consumption of 

drinking water containing 10 μg/L arsenic is associated with the site specific cancer risks below. 

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2 

 Note that the same CSF values, other than small differences due to rounding error, would be 

obtained starting with any of the water concentrations presented in the NRC (2001) Table S-1. 

Table 5-8. Theoretical maximum likelihood estimates of excess lifetime risk (incidence per 

10,000 people) of lung cancer and bladder cancer for US populations 

Arsenic Bladder Lung 

concentration 

(μg /L ) 

Male Female Male Female 

10 23 12 14 18 

3 The equivalent CSFs can be calculated as follows: 

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• Using the exposure factors for US populations applied in NRC (2001), consumption of 

10 μg/L arsenic in drinking water results in a daily exposure of (10 μg/L) × (1 L/d) × 

(1 mg/1,000 μg) × (1/70 kg) = 0.000143 mg/kg-d of inorganic arsenic. As the NRC risk 

estimates are linear (proportional to dose) for these exposures, equivalent CSF values 

come from the equation: 

• Risk = CSF (per mg/kg-d) × dose (mg/kg-d) 

• As an example, applying this equation to bladder cancers in females: 

• 12 × 10-4 = CSF × 0.000143 mg/kg-d, or CSF = 8.4 per mg/kg-d 

Thus the CSF estimates resulting from Table 5-8 are shown below in Table 5-9. 

Table 5-9. Arsenic oral CSFs (per mg/kg-d) for lung cancer and bladder cancer in US 

populations 

Bladder Lung 

Male Female Male Female 

16 8 10 13 

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21 

As these are maximum likelihood estimates, it is appropriate to add risks across the two 

sites resulting in combined CSFs for lung and bladder cancer of 21 and 26 per mg/kg-d in 

females and males respectively. 

5.3.8.5. Sensitivity Analyses of Cancer Risk Estimates to Changes in Parameter Values 

NRC (2001) and SAB (2007) recommended that the impacts of different modeling 

assumptions and input parameter values be investigated in the risk assessment for arsenic in 

drinking water. EPA, therefore, examined several aspects of the cancer risk modeling through 

single-value sensitivity analysis. The Agency felt that the currently available data were 

insufficient to support detailed probabilistic uncertainty and variability estimation. In response 

to SAB comments, EPA evaluated the impacts of: 

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1 • Varying the assumed daily nonwater arsenic intake of the exposed and reference 

populations. Sensitivity cases were run in which the nonwater arsenic intake in the 

exposed populations was varied from its default value of 10 μg/day to 0, 100, and 200 

μg/day. An additional case was run in which both the exposed and reference populations 

were assumed to receive 0, 30, and 50 μg/day nonwater arsenic exposure. Because the 

Poisson risk model for female bladder cancer is particularly sensitive to changes in 

assumptions related to nonwater arsenic intakes (see below), nonwater arsenic intake was 

limited to below 50 μg/day in reference populations. 

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• Varying assumptions related to drinking water intake by the exposed Taiwanese 

population. Cases were run in which the male drinking water consumption was varied 

from its baseline value of 3.5 L/day to 5.1 L/day, 3.0 L/day, and 2.75 L/day. Female 

drinking water intake in the Taiwanese population was varied from its baseline value of 

2.0 L/day to 2.75 and 4.1 L/day. 

• Varying the arsenic well concentrations used to fit the dose-response model for the 

Taiwanese population. The baseline risk model used the median village arsenic 

concentrations as the exposure metric. In the sensitivity analysis, cases also were run 

using the minimum and maximum well concentrations in each village. 

• Including different Taiwanese reference populations in the dose-response assessment. 

The baseline (southwest Taiwan) reference population was replaced by data from all 

Taiwan. The model also was run without any distinct reference population. 

Tables 5-10 and 5-11 summarize the results of the sensitivity analysis runs. Table 5-10 

shows the estimated (incidence) risks associated with a drinking water concentration of 10 μg/L 

for the U.S. population estimated when calculated using the assumptions specified in the lefthand column of the table. Table 5-11 shows the proportional changes in estimated risks in 

relations to the baseline estimate. Figure 5-2 summarizes the impact of alternative modeling 

assumptions, showing the ratios of estimated cancer risks to the base case estimates for changes 

in input variables having a substantial (>20%) effect on the risk estimates. 

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Table 5-10. Sensitivity analysis of estimated cancer incidence risks associated with 10 μg/L 

to changes in modeling assumptions and inputs 

Estimated Cancer Risk at 10 μg/L Male 

Lung 

Female 

Lung 

Male 

Bladder 

Female 

Bladder 

Baseline (all default values)a 1.9E-03 4.8E-03 3.2E-03 3.0E-03 

Nonwater arsenic intake = 0 μg/day (reference and 

exposed populations) 1.9E-03 4.6E-03 3.0E-03 2.6E-03 

Nonwater arsenic intake = 30 μg/day (reference and 

exposed populations) 2.0E-03 5.1E-03 3.5E-03 4.5E-03 

Nonwater arsenic intake = 50 μg/day (reference and 

exposed populations) 2.0E-03 5.5E-03 3.9E-03 1.1E-02 

Nonwater arsenic intake (exposed population) = 0 

μg/day 1.9E-03 4.8E-03 3.2E-03 3.0E-03 

Nonwater arsenic intake (exposed population) = 100 

μg/day 1.8E-03 4.4E-03 3.0E-03 2.8E-03 

Nonwater arsenic intake (exposed population) = 200 

μg/day 1.7E-03 3.9E-03 2.8E-03 2.4E-03 

Taiwan water consumption = 3.0 L/day (M), 2.0 L/day 

(F) 2.3E-03 4.8E-03 3.8E-03 3.0E-03 

Taiwan water consumption = 5.1 L/day (M), 4.1 L/day 

(F) 1.3E-03 2.3E-03 2.2E-03 1.4E-03 

Taiwan water consumption = 2.75 L/day (M, F) 2.5E-03 3.4E-03 4.1E-03 2.1E-03 

Village water arsenic concentrations = minimum values 2.5E-03 5.7E-03 4.0E-03 4.0E-03 

Village water arsenic concentrations = maximum values 1.4E-03 3.5E-03 2.3E-03 2.1E-03 

Reference population = none 1.2E-03 1.5E-03 8.3E-04 3.5E-04 

Reference population = all Taiwan 2.4E-03 3.9E-03 4.8E-03 6.2E-03 

a

Baseline inputs: reference population = southwest Taiwan; male and female body weight = 50 kg, male water 

intake = 3.5 L/day, female water intake = 2.0 L/day, reference and exposed population nonwater arsenic intake 

= 10 μg/day. U.S. population male and female body weights = 70 kg, male and female water consumption = 

2.0 L/day. 

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Table 5-11. Proportional Changes in Cancer Risks at 10 μg/L Associated With Changes in 

Modeling Inputs and Assumptions 

Modeling Assumptions/Input Values Male Lung Female 

Lung 

Male 

Bladder 

Female 

Bladder 

Baseline (all default values)a 0% 0% 0% 0% 

Nonwater arsenic intake = 0 μg/day (reference and exposed 

populations) 0% -4% -6% -13% 

Nonwater arsenic intake = 30 μg/day (reference and exposed 

populations) 5% 6% 9% 50% 

Nonwater arsenic intake = 50 μg/day (reference and exposed 

populations) 5% 15% 22% 267% 

Nonwater arsenic intake (exposed population) = 0 μg/day 0% 0% 0% 0% 

Nonwater arsenic intake (exposed population) = 100 μg/day -5% -8% -6% -7% 

Nonwater arsenic intake (exposed population) = 200 μg/day -11% -19% -13% -20% 

Taiwan water consumption = 3.0 L/day (M), 2.0 L/day (F) 21% 0% 19% 0% 

Taiwan water consumption = 5.1 L/day (M), 4.1 L/day (F) -32% -52% -31% -53% 

Taiwan water consumption = 2.75 L/day (M, F) 32% -29% 28% -30% 

Village water arsenic concentrations = minimum values 32% 19% 25% 33% 

Village water arsenic concentrations = maximum values -26% -27% -28% -30% 

Reference population = none -37% -69% -74% -88% 

Reference population = all Taiwan 26% -19% 50% 107% a

 Baseline inputs as described in footnote to Table 5-8. 

0.0

1.0

2.0

3.0

4.0

Non-water As

intake = 30 

Non-water As

intake = 50 

Taiwan H20 =

3.0 L/day (M),

2.0 L/day (F)

Taiwan H20 =

5.1 L/day (M),

4.1 L/day (F)

Taiwan H20 =

2.75 L/day (M,

F)

Village H20 As

= minimum

values

Village H20 As

= maximum

values

Reference

Pop. = none

Reference

Pop. = all

Risk Relative to Baselin

Taiwan

e

Male Lung

Female Lung

Male Bladder

Female Bladder

Figure 5-2. Change in arsenic-related unit risk estimates associated 

with variations in input assumptions. 

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These results indicate that varying most of the risk modeling inputs within the tested 

ranges have a small or moderate effect on risk estimates for most endpoints. For all of the 

endpoints except female bladder cancer, changing assumptions related to nonwater arsenic intake 

for the reference and/or exposed populations results in small changes (<25%) in the estimated 

oral CSF and cancer risks at 10 μg/L in drinking water. Risk estimates for female bladder 

cancer, in contrast, are quite sensitive to changes in nonwater arsenic intake in the range from 0 

to 50 μg/day. When nonwater arsenic intake is assumed to be 30 μg/day (rather than 10 μg/day 

in the baseline estimate), estimated female bladder cancer risks are approximately 50% higher 

than under baseline assumptions. When nonwater arsenic intake increases to 50 μg/day, female 

bladder cancer risk increases by 267% compared to baseline. The sensitivity of the risk 

estimates is greater for changes in reference population arsenic intake; when nonwater intake 

increases to 100 and 200 μg/day for the exposed populations alone, the impacts on female 

bladder cancer risks are much less (7% and 20%, respectively). 

As expected, the risk estimates obtained when making different assumptions concerning 

Taiwanese drinking water consumption are very nearly inversely proportional to the assumed 

water intake. For example, when male drinking water consumption is assumed to be 5.1 L/day, 

rather than 3.5 L/day in the baseline case, estimated cancer risks for male lung and bladder 

cancer are both approximately 0.69 ( = 3.5/5.1) times the values derived using baseline 

assumptions. Similar results are seen for the other endpoints. 

Using different exposure concentration metrics also shows relatively limited impacts on 

the estimated cancer risks. When the village minimum water concentrations are used as inputs to 

the Poisson risk model, the estimated cancer risks increase slightly (32%, 19%, 25%, and 33% 

over baseline) for male and female lung and male and female bladder cancer, respectively. 

When village maximum water concentrations are used as model inputs, the estimated cancer 

incidence risks decrease between 26 and 30% relative to baseline. These changes are roughly 

reciprocal to the changes in average exposure concentrations, as expected. 

The final two rows of Tables 5-8 and 5-9 illustrate the impact of alternative assumptions 

about which reference populations are included in the Taiwanese risk assessment model. When 

no reference population is included (the Poisson model is fit only to the data from the 42 

exposed villages), the estimated risks for all four endpoints are considerably lower than under 

the baseline case, which included the southwest Taiwan population. This finding is not 

unexpected, because the addition of the relatively large reference population serves to “anchor” 

the low-exposure end of the model and decrease the impact of the high variability (“noise”) in 

the exposed population data. When the reference population is excluded from the assessment, 

estimated cancer risks are reduced between 37% (male lung) and 88% (female bladder cancer) 

compared to the baseline model that included the southwest Taiwan reference populations. All 

of the exposure-response “b” parameters retain statistical significance, however, even when the 

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reference population is excluded. Finally, including the “all Taiwan” reference population, 

rather than southwest Taiwan, has smaller and variable effects on the risk estimates. Predicted 

risks for male lung and bladder cancer are increased (decreased) by approximately 26% and 

19%, respectively, while risks for female lung and bladder cancer are increased by 50% and 

107%, respectively, compared to baseline. 

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Based on these outcomes, it appears that the risk model results are relatively stable and 

react predictably to reasonable changes in exposure assumptions. The exception is female 

bladder cancer, for which the dose-response parameter estimated in the Poisson model is very 

sensitive to the assumed nonwater arsenic intake by the reference population in the range 

between 0 and 50 μg/day. In addition, risk estimates for all endpoints are strongly affected by 

the inclusion or exclusion of a low-dose reference population in the Poisson risk model. 

5.3.8.6. Sensitivity Analyses of Cancer Risk Estimates to Dose-Response Model Form 

In the course of this analysis, EPA has investigated the impact of alternative model forms 

on the cancer risks estimated for the Taiwanese and U.S. populations for individual endpoints 

(lung and bladder cancer). Based on the past experience of Morales et al. (2000) and modeling 

results presented by NRC (2001), this effort was limited to exploring alternative forms for the 

dose dependence of risks. Equation 5-5 shows EPA’s baseline model, which is “linear Poisson” 

with the form: 

h(x,t) = exp(a1 + a2 × age + a3 × age2) × (1 + b × dose) (Equation 5-5) 

In addition to the linear model, three other models were evaluated. First, the quadratic form of 

dose dependence: 

 

 h(x,t) = exp(a1 + a2 × age + a3 × age2

) × (1 + b1 × dose +b2 × dose2) (Equation 5-6) 

Next, two models in which the dose dependence was exponential, one linear and one quadratic: 

h(x,t) = exp(a1 + a2 × age + a3 × age2

) × Exp(b0 + b1 × dose) (Equation 5-7) 

 

 h(x,t) = exp(a1 + a2 × age + a3 × age2

) × Exp(b0 + b1 × dose + b2 × dose2) (Equation 5-8) 

The last model (Equation 5-8) was specifically recommended by SAB (2007) for 

evaluation. In the discussion that follows, these four models are referred to, respectively, as the 

“linear” (baseline) model (Equation 5-5), quadratic model (Equation 5-6), linear exponential 

model (Equation 5-7), and quadratic exponential model (Equation 5-8).7

 

7 “Absolute risk” models (models in which arsenic exposure was assumed to result in additive, rather than 

multiplicative, increments in risks) were found to fit the data much less well than the multiplicative forms shown in 

Equations 5-6 to 5-8 and are not discussed further. 

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All four models were fit to lung cancer data from the Taiwanese population, using the 

baseline exposure parameter values and including the southwest Taiwanese reference population. 

 Models were fit using the Non-Linear Estimation module of Statistica®. For males, the 

quadratic and quadratic exponential models curve sharply downward at high doses, whereas the 

linear exponential model curves sharply upward. Over the dose range from 0 to 0.05 mg/kg-day 

in males, which corresponds to an arsenic drinking water concentration range of 0 to 710 μg/L 

(which covers approximately 95% of the exposed population years at risk), predictions from the 

non-linear models are never more than 22% higher or 24% lower than the predictions from the 

linear (baseline) model. As noted previously, these differences are relatively small compared to 

the degree of statistical uncertainty in the estimates of the dose-response coefficients. 

For females, two of the models (quadratic and quadratic exponential) predict lung cancer 

risks for 60- to 65-year-olds that are very close to those predicted by the linear model. The 

linear exponential model, however, curves strongly upward at high doses. Over the dose range 

from 0 to 0.03 mg/kg-day in females (corresponding to 0 to 750 μg/L arsenic in drinking water, 

about 95% of the exposed population years at risk), the cancer risks predicted by the non-linear 

models are never more than 9% above or 37% below the risks predicted by the linear (baseline) 

model. 

These analyses indicate that, within the range of exposures covered by the 

epidemiological data, the alternative model forms predict very similar risks (i.e., variations in 

risk estimates across models are well within the estimated statistical uncertainty of the models). 

The behavior to the various models at the extremes of the data (high and low exposures) depends 

to a large extent on the model specification; models with non-linear dose specifications will 

predict risks that increase more or less rapidly in the extremes than the linear additive Poisson 

regression, depending on the form of the dose term. As discussed in Section 4.6.3, given the 

limitations in data related to mode of action, there is no compelling reason to prefer non-linear 

models, and the additive Poisson model is the simplest, best-fitting, and most parsimonious 

model currently available for establishing a point of departure for establishing health criteria. 

5.3.8.7. Significance of Cancer Risks at Low Arsenic Exposures 

Several recently published studies have called into question the strength and significance 

of the exposure-response relationship for arsenic in the Taiwanese population studied by Chen et 

al. (1988a, 1992) and Wu et al. (1989) that have been used by EPA for estimating cancer risk. 

Based on “graphical and regression analysis,” Lamm et al. (2003) found no significant doseresponse relationship for arsenic-related bladder cancer in the subset of the Taiwanese 

population with median drinking water well concentrations less than 400 μg/L. Kayajanian 

(2003) found that combined male and female lung, bladder, and liver cancers were relatively 

elevated at low arsenic exposures, then decreased to minimums for villages with water arsenic 

concentrations in the range between 42 and 60 μg/L, and then again increased with increasing 

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arsenic exposure. In a more recent analysis, Lamm et al. (2006) found that (1) dummy variables 

related to “township” location were significant (along with arsenic well concentration) when all 

the townships were included in the analysis and (2) the dose-response parameter for arsenic 

exposure became insignificant for arsenic well concentrations less than 151 μg/L when only a 

subset of the data was included in the regression. 

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The studies by Lamm et al. (2003, 2006) and Kayajanian (2003) have severe limitations. 

In evaluating the findings of these studies, it is important to recognize the complexity and 

limitations of the Taiwanese data set. Cancer mortality and person-years at risk observations are 

provided for a large number (n = 559) of relatively small age- and village-stratified populations 

(median person-years at risk ~ 340 for both males and females). Most population groups have 

zero cancer deaths, and the data are very “noisy.” Cancer mortality is strongly age-dependent, 

and simultaneously evaluating the age- and dose-dependence of cancer mortality based on a data 

set in which cancer deaths are “rare events” requires appropriately structured models. All of 

these features of the data drove the selection of the Poisson regression methods described in 

Section 5, and the use of simpler models (linear regression, for example) can (and did) produce 

misleading results. 

With regard to the Lamm et al. (2003) paper, it is likely that the use of linear regression 

and the failure to correctly account for the age-dependency of bladder cancer risks combined to 

make it impossible to detect a significant exposure-response relationship in villages with water 

arsenic levels less than 400 μg/L. U.S. EPA (2005d) evaluated this study and noted the 

following weaknesses: 

• Classification of wells as artesian or shallow was based solely on arsenic concentration. 

• Age was not included as a variable in the regression analysis, despite the clear strong 

dependence of cancer risks on age. 

• Previous studies have found little evidence for the presence of other potential carcinogens 

in the sampled wells. 

The major limitation of Kayanjaian’s (2003) analysis of the Taiwanese data is that it 

breaks the data into strata that are too small to be used to calculate reliable mortality risks, and 

that it is very sensitive to the specific way that the data are stratified. The observed trend in 

cancer mortality versus arsenic dose would be very different if only few cancer deaths were 

misclassified, or if the pattern of cancer deaths had been slightly different by chance. Lamm et 

al.’s (2006) failure to find a significant exposure-response relationship in villages with arsenic 

water concentrations below 151 μg/L can also be explained by (1) the use of linear regression 

without age-adjustment; and (2) the omission of data from three of the six townships from the 

regression. 

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Appendix F provides additional analyses supporting the significance and robustness of 

the dose-response relationship for arsenic at low doses and in the defined subsets of the 

population studied by Lamm et al. (2006). 

5.4. CANCER ASSESSMENT (INHALATION EXPOSURE) 

An inhalation unit risk was developed for inorganic arsenic and posted on the IRIS 

database in 1988. This document does not present a re-assessment of the cancer dose-response 

estimation for inhalation exposure to inorganic arsenic. 

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6. MAJOR CONCLUSIONS IN THE CHARACTERIZATION OF HAZARD AND DOSERESPONSE 

6.1. HUMAN HAZARD POTENTIAL 

Arsenic is readily absorbed from the GI tract, either from drinking water or food sources. 

 Although dermal absorption is not significant compared to absorption from oral exposure, it 

may have contributed to the total arsenic exposures and health effects reported in many 

epidemiological studies in the literature. There appears, however, to be little if any dermal 

absorption (NRC, 1999) except at high occupational exposures (Hostynek et al., 1993). 

Inhalation is not being addressed in this document. 

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After absorption, inorganic arsenic can undergo a complicated series of enzymatic and 

non-enzymatic reduction, enzymatic oxidative methylation, and conjugation reactions. Although 

these reactions occur throughout the body, the rate at which they occur varies greatly from organ 

to organ, with major metabolism occurring in the liver. While there are two proposed pathways 

(Figures 3-1 and 3-2) for arsenic metabolism—with each pathway likely to occur depending on 

exposure level and/or individual—the main urinary excretion products in humans are MMA and 

DMA and the parent compound. Arsenic metabolism (mainly methylation) varies greatly across 

different species (Vahter, 1994, 1999a), which may explain why there has been no adult animal 

model for the carcinogenic potential of arsenic. Although a few animal bioassays have been 

conducted, they have all been negative. Arsenic-induced cancers have been observed with 

transplacental exposure in mice. Transplacental exposure to arsenic in mice has found increases 

in the development of lung, liver, reproductive, and adrenal tumors. Skin tumors in animals have 

only been induced in transgenic models or in co-carcinogenesis studies. 

Despite the lack of a good animal model for arsenic carcinogenesis, numerous 

epidemiological studies have examined the carcinogenic potential of inorganic arsenic via oral 

exposure. Although each of the investigations has its own inherent strengths and weaknesses, 

the combination of all the study results supports an association between oral exposure to 

inorganic arsenic and cancer including bladder, kidney, skin, lung, liver, and prostate. Because 

the association between arsenic and these cancers has been found in different populations, it is 

unlikely that any single attribute (e.g., nutritional habits) associated with a single population is 

responsible for the increased cancer rates. However, genetic polymorphisms have been found to 

be an important factor in the methylation of arsenic. Evidence suggests that people who have a 

greater capacity to methylate arsenic completely to DMA are at a lower risk for developing 

arsenic-related cancers. Nutritional and personal habits including smoking also affect the 

methylation rate. Therefore, genetic, nutritional, and lifestyle factors contribute to the interindividual variations. 

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Although dose-response relationships have been observed for the majority of cancers 

noted in areas with high levels of arsenic in their drinking water, results for low-level arsenic 

epidemiologic investigations (primarily from the United States and Europe) have been equivocal 

in the relationship between these cancers and arsenic exposure. This could be due to the fact that 

none of the studies accounted for arsenic exposure through food sources, which would be a 

significant source as the levels in the drinking water decreased (Uchino et al., 2006; Kile et al., 

2007). Because cancer has a long latency period, misclassification also occurs due to lack of 

data on disease-relevant exposures (Cantor and Lubin, 2007), which would be more significant 

in studies examining lower exposures. Therefore, studies with low levels of exposure that are 

ecological in nature (no individual exposure) are more prone to exposure misclassification, 

which means they are biased toward the null hypothesis. Despite all these numerous limitations 

in low-level exposure studies, positive associations have been observed for cancers of the 

prostate (Hinwood et al., 1999; Lewis et al., 1999), skin (Hinwood et al., 1999; Karagas et al., 

2001; Beane-Freeman et al., 2004; Knobeloch et al., 2006), and bladder (Kurttio et al., 1999; 

Steinmaus et al., 2003; Karagas et al., 2004). In most cases, however, there is no dose-response 

with increases observed at the highest concentrations only and in many cases significant results 

occurred in smokers only. 

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Based upon current EPA Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a), 

inorganic arsenic is determined to be “carcinogenic to humans” due to convincing 

epidemiological evidence of a causal relationship between oral exposure of humans to inorganic 

arsenic and cancer. 

The available evidence is inadequate to establish a MOA by which arsenic induces 

tumors. The genotoxicity data for arsenic are equivocal. Chromosomal aberrations have been 

observed in humans and animals exposed to arsenic, but arsenic has been generally negative in 

bacterial mutagenicity tests and has only been observed to be a weak mutagen at the hprt locus in 

Chinese hamster V79 cells at toxic concentrations (Li and Rossman, 1989a). In addition, even 

though it appears genotoxic in animal models, it does not generally induce tumors in animal 

models. Arsenic does not appear to cause point mutations in standard assays, but instead causes 

large deletion mutations (Rossman, 1998). These large deletions can cause lethality when 

closely linked to essential genes. Therefore, the mutations are not easily observed in standard 

bacterial and mammalian cell mutation assays. However, even in transgenic cell lines, which 

were tolerant of large deletions, arsenic was still only weakly mutagenic at doses causing overt 

cytotoxicity (Rossman, 2003). It has been suggested that arsenic acts as an aneugen (affects the 

number of chromosomes) at low doses, but as a clastogen (causes chromosomal breaks) at high 

doses (Rossman, 2003). However, arsenic has also been demonstrated to affect other processes 

possibly involved with carcinogenesis, including aberrant gene/protein expression, ROS, DNA 

repair inhibition, signal transduction, and cancer promotion. Therefore, it is likely that arsenic 

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acts via multiple MOAs, which would explain the number of different internal cancers associated 

with arsenic. 

6.2. DOSE-RESPONSE 

Only the oral cancer assessment is addressed in this document. Lung and bladder cancer 

mortality in the Taiwanese population were selected as endpoints in the dose-response modeling 

because they are the internal cancers with the most consistent results and are best characterized 

in epidemiology studies of arsenic exposure (NRC, 1999, 2001; SAB 2000, 2007). Doseresponse models were estimated for the Taiwanese population using additive Poisson regression 

with linear dose terms and quadratic age terms. 

ED01 values were derived from the MLE dose-response parameter estimates. LED01

estimates were derived from the 95% upper confidence limits on the dose-response parameters, 

as described in Appendix E. The analysis was done in two phases. The first phase consisted of 

the derivation and fitting of dose-response models using the Taiwanese epidemiology data from 

Chen et al. (1988a, 1992) and Wu et al. (1989). The outputs of this phase of the analysis were 

arsenic dose-response coefficients that described the relationship between estimated arsenic 

intake in the Taiwanese population and proportional increases in age-specific lung and bladder 

cancer mortality risk. Lifetime cancer incidence in U.S. populations was then estimated by using 

a modified version of the “BEIR IV” relative risk model. A key assumption underlying this 

model is that the risk of arsenic-related cancer is a constant multiplicative function of the 

“background” age profile of cancer risks in the target U.S. population. Estimates of arsenicrelated cancer risks in a (hypothetical) U.S. population exposed to arsenic at varying levels in 

drinking water were then derived. 

The oral CSFs for lung and bladder cancers in U.S. males and females were derived using 

the following assumptions: nonwater arsenic intake for the reference and exposed populations 

was 10 μg/day; drinking water consumption was 3.5 and 2.0 L/day in Taiwanese men and 

women, respectively; 50 kg was the average Taiwanese body weight; and a 70 kg individual in 

the United States consumes 2.0 L/day of water (Section 5.3.5). The oral CSF is dependent on 

assumptions related to the volume of contaminated water consumed over the course of a day and 

the amount of arsenic consumed through the diet. Changes in these assumptions would result in 

different cancer potency estimates (as discussed in Section 5.3.8.3), and corresponding changes 

in the other risk criteria (drinking water unit risk, drinking water concentration associated with 

10LED01 lifetime cancer risk, etc.). Sensitivity analyses were performed to test the effects of 

differences in drinking water intake assumptions, nonwater arsenic intake assumptions, using 

median well water values compared to minimum and maximum values, and including different 

Taiwanese reference populations on the estimates (Section 5.3.8.3). Based on the results of the 

sensitivity analyses, the risk model results, with the exception of female bladder cancer, appear 

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to be relatively stable and react predictably to reasonable changes in exposure assumptions. 

Female bladder cancer estimates were particularly sensitive to variations in nonwater arsenic 

intake. 

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Estimated cancer potency factors for lifetime U.S. male lung and bladder cancer 

incidence were 6.7 and 11.2 per mg/kg-day, respectively. The corresponding values for females 

were 16.6 and 10.5 per mg/kg-day (Table 5-3). Cancer potency for combined lung and bladder 

cancer risks were estimated for males and females, as described in Section 5.3.8.1. The 

estimated cancer potency factors for combined (lung plus bladder) cancer incidence were 16.9 

and 25.7 per mg/kg-day, respectively. The potency factor estimate for women (25.7 per 

mg/kg-day) was identified as the recommended point of departure for derivation of health 

criteria, with women being the more sensitive population.

The cancer potency estimates derived in this analysis are not directly comparable to those 

estimated in EPA’s 1988 assessment (U.S. EPA, 1988b). That analysis derived a much lower 

potency factor estimate (1.0–2.0 per mg/kg-day) based on an analysis of skin cancer incidence in 

the Taiwanese population studied by Tseng et al. (1968; Tseng, 1977). Since the exposureresponse data on internal cancers has become available, all the subsequent assessments 

(including this one) have been based on internal (bladder and/or lung) cancer (see Section 5.3.1). 

 The difference in endpoints (skin versus internal cancers) is the main reason for the relatively 

large difference in estimated cancer potency in the more recent assessment compared to the 1988 

assessment. 

As discussed in Section 5.3.8.2, the lifetime risk estimates for male and female lung and 

bladder cancer calculated in this assessment are generally consistent with the risk estimates from 

previous analyses that used the internal cancers (NRC, 2001). The bulk of the difference 

between the cancer potency estimates in this assessment and those from previous analyses can be 

explained by differences in dose-response models, changes in the assumptions related to the 

relative drinking water consumption by women in Taiwan and the United States, and the use of 

more recent data on U.S. population mortality and cancer incidence in the BEIR IV relative risk 

model. 

The Supplemental Guidance for Assessing Susceptibility From Early-Life Exposure to 

Carcinogens (U.S. EPA, 2005b) indicates that age-dependent adjustment factors should be 

applied to the CSF and combined with early-life exposure estimates when estimating cancer 

risks from exposures to carcinogens with a mutagenic MOA. As discussed in Section 4.6.3, 

insufficient data are available to adequately demonstrate a mutagenic mode of action for 

inorganic arsenic. Therefore, the application of age-dependent adjustment factors is not 

recommended. 

The overall level of confidence in the data is high. The data used in the dose-response 

assessment come from human epidemiology rather than animal bioassays. The Taiwanese 

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studies characterize the cancer risks of an extremely large, well-characterized population with a 

wide range of exposure concentrations. Reliability and accuracy of mortality records, 

verification of endpoints with histological examinations, several decades of exposure to arsenic 

in drinking water to detect internal cancer outcomes, apparent similarities in lifestyle habits 

(similar urbanization in the endemic area versus the rest of southwestern Taiwan) between 

exposed and reference populations, and the residential stability of the population (i.e., little 

migration or emigration) are high. The data demonstrate a statistically significant dose-related 

effect in humans, across the entire range of exposures (i.e., 10–934 ppb median levels) evaluated. 

 The currently used BEIR IV model is an improvement over previous models because it contains 

a quadratic age model, an additive linear dose term, and a reference population, and adjusts for 

differences between the exposed and target (i.e., U.S.) populations. 

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Despite all their strengths, the Chen et al. (1988a, 1992) and Wu et al. (1989) studies are 

“ecological”; data on individual exposure (which are a function of both water consumption rates 

and concentrations) are not available. In addition, smoking information was not provided in the 

critical studies (however, it appears comparable—40% vs. 32% in endemic area vs. the rest of 

Taiwan according to Chen et al., 1985). Lacking this information introduces an unquantifiable 

degree of uncertainty into the risk estimates. In EPA’s judgment, these factors are equally likely 

to have resulted in overestimates or underestimates of risks. 

6.2.1. Choice of Models 

As discussed in Section 5.3.1, the Taiwanese data have been used as the basis for 

quantitative risk assessment by a number of investigators. In this current analysis, EPA is 

building on the experience of previous efforts by itself and others, and has incorporated 

comments and recommendations by NRC (2001) and SAB (SAB, 2007) in the selection of 

statistical methods for use in the risk assessment. As discussed in Section 5.3.7.1, the current 

assessment employs a Poisson regression model with additive linear dose terms and quadratic 

age terms for dose-response model fitting in the Taiwanese population. This model was found to 

be the simplest, best-fitting model among a number of alternatives tested. Sensitivity analyses of 

other models (quadratic, exponential linear, and exponential quadratic dose transformation) were 

also conducted (see Section 5.3.8.4 for further details). 

To extrapolate arsenic-related cancer risks to the U.S. population, the current assessment 

employs a variant of the “BEIR IV” relative risk model (Section 5.3.7.3). This model takes as its 

inputs the dose-response coefficients from the Poisson regressions and “background” cancer 

incidence and population mortality data from the target (U.S.) population. Population mortality 

data for the year 2000 (NCHS, 2000) and background lung and bladder cancer incidence for 

2000–2003 (NCI, 2006) were used as inputs to the BEIR IV model. 

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6.2.2. Dose Metric 

Inorganic arsenic is metabolized in vivo, with some of the known metabolites being more 

toxic than the parent compound. However, it is not known whether it is a metabolite, the parent 

compound, or a combination of the two that is responsible for the observed carcinogenic 

potential. An increase in MMA or decreased DMA in the urine has been associated with an 

increase in disease risk (Yu et al., 2000; Chen et al., 2005a; Steinmaus et al., 2005; Valenzuela et 

al., 2005; Ahsan et al., 2007; Huang et al., 2007b; McCarthy et al., 2007a); therefore, the actual 

carcinogenic moiety may not be proportional to administered exposure and use of administered 

exposure may produce a bias in the model. However, the exposure assessment for the model is 

ecological in nature and produces its own inherent bias. Detailed arsenic speciation data are not 

available for the Taiwanese population used in the risk assessment. Therefore, estimated total 

daily arsenic dose (water + other dietary) has been used as the dose metric in the risk assessment. 

 Arsenic dose is estimated based on well water concentration data, and it is assumed that the 

arsenic concentrations have been constant over the period of exposure. Since there are no data 

related to the temporal variability in the well water concentrations, this introduces uncertainty 

into the dose estimates for the 43 villages. Sensitivity analyses were conducted to investigate the 

impact of using alternative exposure indices, as discussed in Section 5.3.8.3. 

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6.2.3. Human Population Variability 

Although the extent of inter-individual variability in arsenic metabolism has not been 

adequately characterized, genetic polymorphism, nutritional status, and personal habits (e.g., 

smoking) have all been associated with differences in arsenic methylation. Data exploring 

whether there is a differential sensitivity to arsenic carcinogenicity across life stages is limited. 

Data by Waalkes et al. (2003, 2004a) indicate that transplacental exposure in mice is a sensitive 

stage for carcinogenic potential. These are the only studies in which inorganic arsenic exposure 

has been associated with cancer in rodents. Lung, liver, reproductive, and adrenal tumors were 

associated with arsenic administration during gestation (10 days only). A single epidemiological 

study by Smith et al. (2006) examined lung cancer rates (and other respiratory diseases) in 

cohorts exposed during childhood and cohorts likely exposed in utero to arsenic concentrations 

of 860 ppb that subsequently dropped to 100 ppb. Results demonstrated that exposure during 

either period of development caused increased risk of lung cancer in females aged 40 to 49 born 

between 1950 and 1957 and in males aged 30 to 49 born between 1950 and 1970. However, the 

risks associated with early childhood exposures and/or in utero exposures were not compared to 

risks from exposures during adulthood. Thus, the available data do not allow for a quantitative 

assessment of the relative sensitivity to arsenic exposures between the Taiwanese population 

used in the dose-response assessment and U.S. populations exposed to arsenic in drinking water. 

 SAB (2007) acknowledged “the possible issue of compromised nutrition among 

segments of the exposed population” in the Taiwanese study population, along with the lack of 

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data related to smoking history. However, data are not available that would allow quantitative 

evaluation of these factors. Therefore, this risk assessment assumes that the observed 

carcinogenic potency in the Taiwanese population, with suitable corrections for differences in 

drinking water intake and background cancer incidence, is an appropriate predictor of the 

potential for human cancer risk in the U.S. population. 

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APPENDIX A. SUMMARY OF EXTERNAL PEER REVIEW AND PUBLIC 

COMMENTS AND DISPOSITION 

The Toxicological Review of Inorganic Arsenic has been formally reviewed by scientists 

outside EPA—i.e., the SAB Arsenic Review Panel—in accordance with EPA guidance on peer 

review (U.S. EPA, 2000a). The reviewers on the Panel were tasked with providing written 

answers to general questions on the overall assessment and on chemical-specific charge 

questions, addressing key scientific issues of the assessment. While the Panel was supplied with 

questions regarding both DMAV and inorganic arsenic, this appendix addresses only questions 

and responses pertaining to inorganic arsenic. Charge question B3 asked SAB to comment on 

EPA’s hypothesis that inorganic arsenic acts via different modes of action for carcinogenicity. 

SAB agreed with EPA’s conclusion, but during a discussion on the mode of action of DMAV, a 

member of the Panel stated that the description for inorganic arsenic’s mode of action could be 

strengthened. In addition to strengthening the mode of action discussion, studies on the mode of 

action for inorganic arsenic have been placed in a table in Appendix C. Section 4.4.1 provides a 

summary of the specifics in the tables instead of detailed write-ups for all the studies. A 

summary of significant comments made by the external reviewers and EPA’s responses to these 

comments arranged by charge question follow. Public comments were submitted to SAB and 

were taken into consideration by the Panel during their review. The summary of significant 

comments and responses below is inclusive of the major issues raised by public commenters 

which specifically focused on the choice of study for cancer quantitation and the nature of the 

dose-response. Editorial comments were considered and incorporated into the document as 

appropriate and are not discussed further. 

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Charge Question B3

EPA concluded that inorganic arsenic mostly likely causes human cancer by many 

different modes of action. This is based on the observed findings that inorganic arsenic 

undergoes successive methylation steps in humans and results in the production of a number of 

intermediate metabolic products and that each has its own toxicity. EPA asked SAB to comment 

on the soundness of its conclusion. 

SAB Comments

The Panel concluded that: 

1) Multiple modes of action may operate in carcinogenesis induced by inorganic 

arsenic because there is simultaneous exposure to multiple metabolic products 

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as well as multiple target organs and the composition of metabolites can differ 

in different organs. 

2) Each arsenic metabolite has its own cytotoxic and genotoxic capability. 

3) Inorganic arsenic (iAsIII) and its metabolites are not direct genotoxicants because 

these compounds do not directly react with DNA. However, iAsIIIand some of its 

metabolites can exhibit indirect genotoxicity, induce aneuploidy, cause changes in 

DNA methylation, and alter signaling and hormone action. In addition, inorganic 

arsenic can act as a transplacental carcinogen and a cocarcinogen. 

4) Studies of indirect genotoxicity strongly suggest the possibility of a threshold for 

arsenic carcinogenicity. However, the studies discussed herein do not show 

where such a threshold might be, nor do they show the shape of the dose-response 

curve at these low levels. In addition, a threshold has not been confirmed by 

epidemiological studies. This issue is an extremely important area for research 

attention, and it is an issue that should be evaluated in EPA’s continuing risk 

assessment for inorganic arsenic. 

5) Arsenic essentiality and the possibility of hormetic effects are in need of 

additional research to determine how they would influence the determination of 

a threshold for specific arsenic-associated health endpoints. 

EPA Response 

EPA agrees that the available data potentially support multiple modes of action for 

inorganic arsenic. The Agency believes that, at this point, the data concerning mode of action 

are not well-enough understood to support their use in quantitative risk assessment. 

Charge Question C2

EPA reviewed the available epidemiologic studies, including those published since the 

NRC 2001 review, for U.S. populations exposed to inorganic arsenic via drinking water. EPA 

concluded that the Taiwanese data set remains the most appropriate choice for estimating cancer 

risk in humans. SAB was asked to comment on the soundness of this conclusion and also on 

whether these data provide adequate characterization of the impact of childhood exposure to 

inorganic arsenic. 

SAB Comments

The Panel concluded that: 

1) Because of various factors (e.g., the size and statistical stability of the 

Taiwanese database relative to other studies, the reliability of the population 

and mortality counts, the stability of residential patterns, and the inclusion of 

long-term exposures), this database remains, at this time, the most appropriate 

choice for estimating bladder cancer risk among humans, though the data have 

considerable limitations that should be described qualitatively or quantitatively 

to help inform risk managers about the strength of the conclusions. 

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2) There are other epidemiologic databases from studies of populations also 

exposed at high levels of arsenic, and the panel recommends that these be used 

to compare the unit risks at the higher exposure levels that have emerged from 

the Taiwan data. 

3) The panel also suggests that published epidemiology studies of U.S. and other 

populations chronically exposed from 0.5 to 160 μg/L inorganic arsenic in 

drinking water be critically evaluated, using a uniform set of criteria, and that the 

results from these evaluations be transparently documented in EPA’s assessment 

documents. If, after this evaluation, one or more of these studies are shown to be 

of potential utility, the low-level studies and Taiwan data may be compared for 

concordance. Comparative analyses could lead to further insights into the 

possible influence of these differences on population responses to arsenic in 

drinking water. 

4) Regarding childhood exposure to inorganic arsenic, it was the Panel’s view that, 

based on available data, it is not clear whether children differ from adults with 

regard to their sensitivity to the carcinogenic effects of arsenic in drinking water. 

 However, the possibility of a different response in degree or kind should not be 

ignored and needs to be investigated. 

EPA Response

After considering additional studies, EPA agreed with SAB that the Taiwanese data were 

the best available for quantitative analysis. Studies assessed, but not used in the analysis, are 

summarized in Section 4.1 of the document. The studies were systematically evaluated for their 

suitability in risk assessment based on a uniform set of criteria including the study type, the size 

of the study population and control population, and the relative strengths and weaknesses of the 

study based on SAB-recommended criteria (i.e., estimates of the level of exposure 

misclassification; temporal variability in assigning past arsenic levels from recent measurements; 

the extent of reliance on imputed exposure levels; the number of persons exposed at various 

estimated levels of waterborne arsenic; study response/participation rates; estimates of exposure 

variability; control selection methods in case-control studies; and the resulting influence of these 

factors on the magnitude and statistical stability of cancer risk estimates). Study summaries are 

also provided in tabular form in Appendix B for ease of comparison. Studies are arranged 

geographically and include other areas of high arsenic exposure (e.g., South America) as well as 

areas of low exposure (e.g., U.S. and Europe). Studies examining children were evaluated and 

are discussed in Section 4.7.1 of the document, but EPA believes that the available data do not 

yet allow a definitive conclusion on children’s differential susceptibility to arsenic exposure. 

EPA notes that recent animal studies demonstrating the potential for cancer after in utero arsenic 

exposures give rise to additional concerns regarding exposures early in development. 

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EPA determined that the most prudent approach for modeling cancer risk from inorganic 

arsenic is to use a linear model because of the remaining uncertainties regarding the ultimate 

carcinogenic metabolites and whether mixtures of toxic metabolites interact at the site(s) of 

action. EPA asked SAB if it concurred with the selection of a linear model following the 

recommendations of the NRC (2001) to estimate cancer risk in light of the multiple modes of 

carcinogenic action for inorganic arsenic. 

SAB Comments

The Panel concluded that: 

1) Inorganic arsenic has the potential for a highly complex mode of action. 

2) Until more is learned about the complex PK and PD properties of inorganic 

arsenic and its metabolites, there is not sufficient justification for the choice of a 

specific nonlinear form of the dose-response relationship. 

3) The NRC (2001) recommendation to base risk assessments on a linear doseresponse model that includes the southwestern Taiwan population as a 

comparison group seems the most appropriate approach. 

4) The Panel also recommends that EPA perform a sensitivity analysis of the 

Taiwanese data with different exposure metrics, with the subgroup of villages 

with more than one well measurement, and using a multiplicative model that 

includes a quadratic term for dose. 

EPA Response 

As discussed in Section 5.3, EPA investigated a range of model forms for use in the risk 

assessment, building on previous efforts, including U.S. EPA (2001) and Morales et al. (2000). 

The model used in the derivation of the preferred risk assessments (see Section 5.3.3) employs: 

• Poisson regression (of cancer mortality against age and dose) fit by maximum likelihood 

estimation (MLE). 

• A quadratic age model. 

• A linear multiplicative dose term. 

• Confidence limits on the dose term estimated by profile likelihood. 

• Estimates derived for the data set that includes the southwest Taiwan reference 

population. 

A range of alternative model forms were investigated, as discussed in Section 5.3.8.4, 

and the impacts of alternative assumptions about nonwater arsenic intake, drinking water 

consumption, and other exposure factors were investigated through sensitivity analyses, as 

described in Section 5.3.8.3. EPA also investigated the properties of the dose-response 

relationship in the low-dose range of the Taiwanese data, and found that arsenic slope 

coefficients were positive and statistically significant even when high-exposure groups were 

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excluded from the analysis. EPA’s dose-response modeling found no indication of the existence 

of a threshold arsenic exposure below which cancer risks are not elevated. As discussed in 

Section 4.6.3, EPA believes that the available mode of action data do not justify the use of nonlinear low-dose extrapolation from the point of departure (POD). 

Charge Question D3

EPA re-implemented the model presented in the NRC (2001) in the language R as well as 

in an Excel spreadsheet format. In addition, extensive testing of the resulting code was 

conducted. Please comment upon precision and accuracy of the re-implementation of the model. 

SAB Comments

The Panel concluded: 

1) That the EPA program conformed to the NRC (2001) recommendation for 

modeling cancer hazard as a function of age and the average daily dose of 

exposure to arsenic through drinking water sources. 

2) The Panel did, however, identify and report to the EPA on two potential 

discrepancies in the data inputs and one computational error in the portion of the 

program that employs the BEIR-IV formula to evaluate excess lifetime cancer 

risk from arsenic exposure. 

3) The Panel made several suggestions for improvements in the model’s 

programming and documentation conventions, as well as recommendations for 

specific sensitivity analyses designed to test the robustness of the model to 

alternative formulations of the hazard function and aggregate population data 

inputs. 

EPA Response 

EPA made a number of changes to the model implementation in response to the SAB 

comments. As in the previous analyses, the linear Poisson dose-response models were estimated 

using maximum likelihood methods; models were implemented in Excel® and replicated using 

Statistica®. In the latest analyses, confidence limits on the arsenic dose-response coefficients 

were estimated using profile likelihood, rather than Bayesian simulation. The confidence limit 

estimates derived using profile likelihood were very similar to those obtained using Bayesian 

simulation and estimates derived by “bootstrap” methods. 

In this latest analysis, the BEIR IV formula for estimating lifetime cancer incidence risks 

was modified in response to SAB and internal EPA comments. The revised model estimates 

lifetime cancer incidence data based on “background” cancer incidence and mortality data from 

the NCI SEER program (see Section 5.3.7.3). The revised approach is discussed in detail in 

Appendix E.2. 

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As discussed in the previous response, EPA conducted sensitivity analyses on a number 

of model parameters. These analyses are described in Section 5.3.8.3. 

Charge Question D4

In calculating estimated cancer risk to the U.S. general population from drinking water 

exposure to inorganic arsenic, the EPA used epidemiologic data from Taiwan. EPA followed the 

NRC (2001) recommendations to account for the differences in the drinking water consumption 

rates for the Taiwanese population and U.S. populations. On the basis of more recent data 

(noted in U.S. EPA, 2005b), EPA used water intake adjustments for 2 to 3.5 liters/day. EPA 

asked SAB to recommend a drinking water value. 

SAB Comments

The Panel agreed that water consumption (via drinking as water, in beverages, or in 

cooking water) assumptions have a substantial impact on the assessment of arsenic’s risk. 

However, the Panel did not recommend specific values for EPA to use in evaluating doseresponse in the Taiwanese study nor for levels of exposure in the U.S. population risk estimates. 

 It did recommend that uncertainty in this parameter be evaluated for both the Taiwanese study 

population and the U.S. populations at risk. The Panel recommended that EPA should: 

1) Evaluate the impact of drinking water consumption rates associated with more 

highly exposed population groups with differing exposures and susceptibilities 

(e.g., children, pregnant women). 

2) Incorporate variability parameters for individual water consumption into their 

analysis for dose-response in the Taiwanese population, as they have done for 

the U.S. population. 

3) Conduct sensitivity analyses of the impact of using a range of 

consumption values for the Taiwanese population. 

4) Provide a better justification for assuming different consumption levels by gender 

or, in the absence of such a justification, conduct additional sensitivity analyses to 

examine the impact of equalizing the gender-specific consumption level. 

5) More fully articulate and document how different sources of water intake, as 

well as variability, are incorporated into the risk model (e.g., data for intake from 

beverages and cooking water). 

EPA Response 

Data are not available regarding individual water consumption rates and background 

(nonwater) arsenic intake in the Taiwanese study populations. EPA, therefore, conducted a 

series of sensitivity analyses involving ranges of drinking water consumption and “background” 

(nonwater) arsenic consumption that the Agency believes spans a reasonable range of values for 

these parameters. Arsenic dose-response models were fit assuming nonwater arsenic intakes of 

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0, 10, 30, 50, 100, and 200 μg/day in the exposed populations, nonwater arsenic intake of 0, 30, 

and 50 μg/day in the reference population, and daily water consumption ranging from 2.75 to 5.1 

L/day for (Taiwanese) males and water consumption ranging from 2.0 to 4.1 L/day for females. 

Risk models also were fit using three different sets of village arsenic drinking water 

concentrations (median, minimum, and maximum), and three sets of assumptions related to 

reference (unexposed) populations (southwest Taiwan, all Taiwan, and none). The results of 

these analyses are summarized in Tables 5-8 and 5-9. Overall, EPA found that cancer slope 

estimates for male and female lung cancer and male bladder cancer were relatively insensitive to 

assumptions related to nonwater arsenic intake and varied more or less inversely with the 

assumed daily water consumption, and with drinking water arsenic concentration estimates. 

When alternative reference populations were assumed (all Taiwan or none), cancer slope 

coefficients were lower than when the southwest Taiwan comparison group was included in the 

analysis. The cancer slope estimates for female bladder cancer were generally more sensitive to 

changes in exposure assumptions than the other endpoints. 

Charge Question D5 

As recommended by NRC (2001), EPA considered the background dietary intake of 

inorganic arsenic and incorporated adjustment values of 0, 10, 30, and 50 μg per day into the 

cancer modeling based on available new data. SAB was asked to recommend a value for the 

background dietary intake of inorganic arsenic for both the control population and study 

population of southwestern Taiwan. 

SAB Comments

The Panel agreed that arsenic levels in food are important considerations for EPA’s 

assessment of lung and bladder cancer risk associated with exposures to arsenic in drinking 

water. However, the Panel did not recommend a specific value for EPA to use in its base risk 

assessment. It did recommend a range of values for consideration by EPA in its sensitivity 

analysis and the Panel offered suggestions to EPA for additional analytical steps to clarify the 

impact of food levels of arsenic on dose-response and exposure as it revises its risk estimates. 

These Panel recommendations include that EPA should: 

1) Conduct sensitivity analyses using a range of total arsenic food intake values 

from at least 50 to 100 μg /day to perhaps as high as 200 μg/day to assess the 

impact of this range of dietary intakes on risk of lung and bladder cancer from 

exposure via drinking water in the Taiwan cohort. 

2) Not assume that the control population has an intake value of zero arsenic from 

food. 

3) Apply greater rigor in their discussions of data used in these assessments (e.g., 

sources, methodological and analytical issues, bioavailability). 

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4) Give immediate research attention to the issue of arsenic bioavailability. 

EPA Response 

 As discussed in the previous response, EPA conducted sensitivity analyses that 

assumed nonwater arsenic intakes (doses) for the exposed populations ranging from 0 to 200 

μg/day and ranging from 0 to 50 μg/day in the reference population. EPA did not specifically 

conduct sensitivity analyses related to arsenic bioavailability. The Agency notes, however, that 

the range of absorbed dose that was evaluated implicitly addresses potential bioavailability 

differences. For example, assuming 50 μg arsenic intake absorbed dose is equivalent to 

assuming 50% of absorption of a 100 μg/day dose, etc. The Agency believes that the range of 

arsenic intake that was considered covers the plausible ranges of nonwater dietary arsenic and 

bioavailability thereof. 

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APPENDIX B. TABULAR DATA ON CANCER EPIDEMIOLOGY STUDIES 

The SAB Arsenic Review Panel provided comments on key scientific issues associated 

with arsenicals on cancer risk estimation in July 2007 (SAB, 2007). It was concluded that the 

Taiwanese database is still the most appropriate source for estimating bladder and lung cancer 

risk among humans (specifics provided in Section 5) because of: (1) the size and statistical 

stability of the database relative to other studies; (2) the reliability of the population and 

mortality counts; (3) the stability of residential patterns; and (4) the inclusion of long-term 

exposures. However, SAB also noted considerable limitations within this data set (SAB, 2007). 

The Panel suggested that one way to mitigate the limitations of the Taiwanese database would be 

to include other relevant epidemiological studies from various countries. For example, SAB 

referenced other databases that contained studies of populations also exposed to high levels of 

arsenic (e.g., Argentina and Chile), and recommended that these alternate sources of data be used 

to compare the unit risks at the higher exposure levels that have emerged from the Taiwan data. 

SAB also suggested that, along with the Taiwan data, published epidemiology studies from the 

United States and other countries where the population is chronically exposed to low levels of 

arsenic in drinking water (0.5 to 160 ppb) be critically evaluated, using a uniform set of criteria 

presented in a narrative and tabular format. The relative strengths and weaknesses of each study 

should be described in relation to each criterion. Additionally, SAB (2007) recommended 

considering the following issues when reviewing “low-level” and “high-level” studies: (1) 

estimates of the level of exposure misclassification, (2) temporal variability in assigning past 

arsenic levels from recent measurements, (3) the extent of reliance on imputed exposure levels, 

(4) the number of persons exposed at various estimated levels of waterborne arsenic, (5) study 

response/participation rates, (6) estimates of exposure variability, (7) control selection methods 

in case-control studies, and (8) the resulting influence of these factors on the magnitude and 

statistical stability of cancer risk estimates. 

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In light of the SAB recommendations, epidemiological studies in the literature from 1968 

to 2007 have been reviewed. The report includes data from all populations that have been 

examined in regard to cancer from arsenic exposure via drinking water. Earlier publications 

were reviewed and are included as needed to facilitate the understanding of results from certain 

study populations. As recommended by SAB, studies were presented in both a narrative 

(Section 4.1) and tabular (below) format. Each publication was evaluated using a uniform set of 

criteria, including the study type, the size of the study population and control population, and the 

relative strengths and weaknesses of the study, focusing on the major strengths and weaknesses. 

While the information in the tables mirrors the information in the narrative, the narrative may 

provide additional important information concerning the investigation. The studies are presented 

B-1 DRAFT—DO NOT CITE OR QUOTE 
by country of origin, then in chronological order by publication year. Below also are definitions 

of terms that are used in the tables (and the narratives in Section 4.1). 

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37 

Cross-sectional studies have inherent limitations including: (1) difficulty in making 

causal inference; (2) the fact that data are collected for only one point in time, so that different 

results may be found if another time-frame had been chosen; and (3) prevalence-incidence bias 

(also called Neyman bias), which is especially prevalent for longer-lasting diseases, where any 

risk factor that results in death will be under-represented among those with the disease. 

Ecological studies provide low cost, convenience, simplicity of analysis, and ease of 

exposure measurement at population or group level rather than at the individual level; therefore, 

a wider range of exposures can often be obtained. Concerns about the methodological weakness 

of ecological studies arise from three facts: estimates of effect do not equate to estimates of 

biological effect obtained from individual level analysis, exposure data from this design cannot 

be used to obtain direct estimates of the rate of injury in exposed and unexposed populations, 

existing data sources are often flawed, and it is difficult to control confounding. 

Cohort studies are research studies in which the medical records of groups of individuals, 

who are alike in many ways, but differ by a certain characteristic (for example, individuals who 

smoke and those who do not smoke) are compared for a particular outcome (such as lung 

cancer). Cohort studies are generally used to follow large groups over a long period to study rare 

or long-latency diseases. 

A case-control study is a retrospective study that compares two groups of people: those 

with the disease or condition under study (cases) and a very similar group of people (matched 

controls) who do not have the disease or condition. Researchers study the medical and lifestyle 

histories of the people in each group to determine which factors may be associated with the 

disease or condition under investigation. An example is where one group may have been 

exposed to a particular substance that the other was not. 

In a nested case-control study, cases of a disease that occur in a defined cohort are 

identified and, for each, a specified number of matched controls is selected from among those in 

the cohort who have not developed the disease by the time of disease occurrence in the case. 

The nested case-control design can potentially offer a lower cost and effort for data collection 

and analysis compared with the full cohort approach, with relatively minor loss in statistical 

efficiency. The nested case-control design is particularly advantageous for studies of biologic 

precursors of disease. 

Recall bias is a type of systematic bias that occurs when the way a survey respondent 

answers a question is affected not just by the correct answer, but also by the respondent’s 

memory. 

Selection bias is the error of distorting a statistical analysis due to the methodology of 

how the samples were collected. As an example, sample selection may involve pre- or postB-2 DRAFT—DO NOT CITE OR QUOTE 
selecting the samples that may preferentially include or exclude certain kinds of results. 

Selection bias is possible whenever the group of people being studied has any form of control 

over whether to participate making the participants a non-representative sample. Selection bias 

may also occur when investigators preferentially select individuals to be included as cases or 

controls based on prior knowledge of study hypotheses or outcomes. Selection bias in 

epidemiology is a distortion of data that arises from the way that the data have been collected. If 

the selection bias is not taken into account, conclusions drawn from the results obtained may be 

wrong. Self-selection bias is when individuals who make up the study population have any 

control over whether or not they are allowed to participate. An individual’s decision to 

participate in a study may be associated with other factors that affect the study, which results in 

the participants being a non-representative sample. 

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The standardized mortality ratio (SMR) in epidemiology is the ratio of observed deaths 

to expected deaths in a population for a specific health outcome. The SMR also serves as an 

indirect means for adjusting a rate. The number of observed deaths is obtained for a particular 

sample of a population that is under investigation, and the number of expected deaths reflects the 

number of deaths for a larger population from which the study sample has been taken. The 

calculation used to determine the SMR is simply the number of observed deaths divided by the 

number of expected deaths. The SMR may be displayed as either a ratio or sometimes as a 

percentage. If the SMR is shown as a ratio and is equal to 1.0, this means the number of 

observed deaths equals that of expected cases. If the SMR is greater than 1.0 there is a higher 

number of deaths than expected, and if the SMR is less than 1.0 there is a lower number of 

observed than expected deaths. 

The standardized incidence ratio (SIR) is a common tool for monitoring disease rates. 

Incidence is the number of newly diagnosed cases in a given location during a given time period. 

 An SIR compares the actual number of cases for a given place and time to the number that 

would be expected based on disease rates in some comparison area. 

In statistics and epidemiology, relative risk (RR) is the risk of an event (or of developing 

a disease) relative to exposure. Relative risk is a ratio of the probability of the event occurring in 

the exposed group versus the control (non-exposed) group. 

Time-weighted average (TWA) is the average exposure to a contaminant or condition 

(such as noise) to which workers are exposed over a period, such as in an 8-hour work day. 

B-3 DRAFT—DO NOT CITE OR QUOTE 
Table B-1. Taiwan Cancer Studies 

Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

Not 

indicated 

19,269 males 

21,152 females 

(40,421 total) 

Arsenic 

concentration 

in well water 

(ppb): 

low (L) = 0–

290 

mid (M) = 

300–590 

high (H) = 

≥600 

undetermined 

(U) 

Age-/gender-specific 

skin cancer prevalence 

rate (1/1000) by arsenic 

concentration (L, M, H, 

U): 

Males, 20–39 yrs.— 

L = 1.5, M = 4.3, H = 

22.4, U = 1.7 

Males, 40–59 yrs.— 

L = 6.5, M = 47.7, H = 

98.3, U = 51.7 

Males, 60 yrs. and 

over— 

L = 48.1, M = 163.4, H 

= 255.3, U = 148.2 

Total all males 

combined— 

L = 4.0, M = 14.4, H = 

31.0, U = 16.5 

Females, 20–39 yrs.— 

L = 0.1, M = 0.7, H = 

3.5, U = 0.9 

Females, 40–59 yrs.— 

L = 3.6, M = 19.7, H = 

48.0, U = 9.2 

Females, 60 yrs. and 

over— 

L = 9.1, M = 62.0, H = 

110.1, U = 62.9 

Total all females 

combined— 

L = 1.3, M = 6.3, H = 

12.1, U = 4.7 

Both genders, 20–39 

yrs.— 

L = 1.3, M = 2.2, H = 

11.5, U = 1.2 

Both genders, 40–59 

yrs.— 

L = 4.9, M = 32.6, H = 

72.0, U = 28.3 

Both genders, 60 yrs. 

and over— 

L = 27.1, M = 106.2, H 

= 192.0, 

U = 107.9 

Total both genders 

combined— 

L = 2.6, M = 10.1, H = 

21.4, U = 10.4 

Observed rate/1000: 

hyperpigmentation = 

Strengths: 

-Large number of 

participants. 

-Dose-response 

information provided. 

Weaknesses: 

-No individual 

exposure data. 

-Possible recall bias 

among study 

participants in 

determining the age 

of cancer onset and 

length of residence in 

the study area. 

-Water supply 

changes over time 

were not collected, 

nor was information 

on smoking histories; 

the arsenic 

concentration from 

individual wells 

varied over time. 

Tseng et al., 

1968 

Ecological 

B-4 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

183.52 

keratosis = 70.95 

skin cancer = 10.59 

blackfoot disease = 

8.91 

1958–

1975 

40,421 

individuals 

Arsenic 

concentration 

in well water 

(ppb): 

<300 = low 

(L) 

300–600 = 

mid (M) 

>600 = high 

(H) 

Age-specific prevalence 

(per 1000): 

Skin cancer 

20–39 years— 

L = 1.3, M = 2.2, H = 

11.5 

40–59 years— 

L = 4.9, M = 32.6, H = 

72.0 

60+ years— 

L = 27.1, M = 106.2, H 

= 192.0 

Blackfoot disease 

20–39 years— 

L = 4.5, M = 13.2, H = 

14.2 

40–59 years— 

L = 10.5, M = 32.0, H = 

46.9 

60+ years— 

L = 20.3, M = 32.2, H = 

61.4 

Skin cancer and BFD 

combined: 

observed—61 cases, 

1.51/1000 

expected—4 cases, 

0.09/1000 

observed to expected 

ratio = 16.77 

Strengths: 

-Large study 

population. 

-Adjusted for age and 

gender. 

Weaknesses: 

-No individual 

monitoring data. 

-Possible recall bias 

among study 

participants 

(interviews and 

mailed surveys) in 

determining the age 

of cancer onset and 

the length of 

residence in the area. 

Tseng, 1977 

Ecological 

B-5 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1968–

1982 

Subjects from 

BFD-endemic 

area 

Median 

arsenic 

concentration 

(ppb): 

artesian well 

water—780 

(range: 350–

1140) 

shallow well 

water—40 

(range: 0–300) 

Cancer SMRs 

(95% CI, p value 

<0.05): 

Males— 

bladder = 11.00 (9.33–

12.67) 

kidney = 7.72 (5.37–

10.07) 

skin = 5.34 (3.79–8.89) 

lung = 3.20 (2.86–3.54) 

liver = 1.70 (1.51–1.89) 

colon = 1.60 (1.17–

2.03) 

Females— 

bladder = 20.09 (17.02–

23.16) 

kidney = 11.19 (8.38–

14.00) 

skin = 6.52 (4.69–8.35) 

lung = 4.13 (3.60–4.66) 

liver =2.29 (1.92–2.66) 

colon = 1.68 (1.26–

2.10) 

Strengths: 

-The SMRs for the 

study cohort taken 

from BFD endemic 

area in Taiwan were 

determined using the 

general population of 

Taiwan and world 

population. 

-Controlled for the 

potential confounders 

age and gender. 

Weakness: 

-Arsenic 

measurements not 

linked to cancer 

mortality. 

- Death certificates 

list the main cause of 

death rather than all 

causes 

- SMRs were only 

presented by 

township and 

villages. 

Chen et al., 

1985 

ecological 

B-6 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

January 

1980–

December 

1982 

Deceased 

cancer cases: 

69 bladder 

76 lung 

59 liver 

Controls: 368 

(community 

matched) 

Median 

arsenic 

concentration: 

artesian well 

water—780 

ppb (range: 

350–1140) 

shallow well 

water—40 ppb 

(range: 0–300) 

Age-/sex-adjusted odds 

ratios, well water use 

≥40 years: 

bladder cancer = 3.90 

lung cancer = 3.39 

liver cancer = 2.67 

Mantel-Haenszel x2: 

bladder cancer = 13.74* 

lung cancer = 8.49* 

liver cancer = 9.01* 

*p < 0.01 

Multivariate logistic 

regression: 

improvement x2 

value— 

bladder cancer = 11.45* 

lung cancer = 9.04* 

liver cancer = 6.34* 

*p < 0.01 

Strengths: 

-Cases confirmed 

using histology or 

cytology findings. 

-Cancer cases and 

controls were from 

the same BFD 

community. 

-Potential 

confounders adjusted 

for in the analysis 

included age, gender, 

smoking, tea 

drinking, vegetable 

consumption, and 

fermented bean 

consumption. 

Weaknesses: 

-Confounders not 

controlled for 

included recall bias 

from case and control 

interviews regarding 

lifestyle, diet, and 

daily water 

consumption and 

source of water. 

-Selection bias 

(control selection). 

Chen et al., 

1986 

Casecontrol 

B-7 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1973–

1986 

Blackfootendemic area 

residents 

Population of 

Taiwan as 

reference 

population 

World 

population as 

reference 

population 

Three 

exposure 

categories 

(ppb): 

<300 

300–590 

≥600 

Age-standardized 

mortality per 100,000 

for various cancers: 

World population: 

<300 ppb 

Males—all sites = 

154.0, liver = 32.6, lung 

= 35.1, skin = 1.6, 

prostate = 0.5, bladder 

= 15.7, kidney = 5.4 

Females—all sites = 

118.8, liver = 14.2, lung 

= 26.5, skin = 1.6, 

bladder = 16.7, kidney 

= 3.6 

300–590 ppb 

Males—all sites = 

258.9, liver =42.7, lung 

= 64.7, skin = 10.7, 

prostate = 5.8, bladder 

= 37.8, kidney = 13.1 

Females—all sites = 

182.6, liver= 18.8, lung 

= 40.9, skin = 10.0, 

bladder = 35.1, 

kidney = 12.5 

≥600 ppb 

Males—all sites = 

434.7, liver = 68.8, lung 

= 87.9, skin = 28.0, 

prostate = 8.4, bladder 

= 89.1, kidney = 21.6 

Females—all sites = 

369.4, liver = 31.8, lung 

= 83.8, skin = 15.1, 

bladder = 91.5, 

kidney = 35.3 

Taiwan: 

Males—all sites = 

128.1, liver = 28.0, lung 

= 19.4, skin = 0.8, 

prostate = 1.5, bladder 

= 3.1, kidney = 1.1 

Females—all sites = 

85.5, liver = 8.9, 

lung = 9.5, skin = 0.8, 

bladder = 1.4, kidney = 

0.9 

Strengths: 

-Data from arsenic 

monitoring conducted 

in 1962–64 and 

1974–76 found 

similar results. 

Weaknesses: 

-Individual arsenic 

exposure levels were 

not presented. 

Chen et al., 

1988a 

Cohort 

B-8 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

January 

1968–

December 

1983 

241 cases 

759 controls 

General 

population of 

Taiwan 

Local endemic 

area population 

Arsenic 

concentration 

(ppb): artesian 

well water— 

median = 780 

range = 350–

1140 shallow 

well water— 

median = 40 

range = 0–300 

Significant SMRs (p 

values) (compared to 

population of Taiwan): 

Cancers— 

bladder = 38.80 

(<0.001) 

skin = 28.46 (<0.01) 

lung = 10.49 (<0.001) 

liver = 4.66 (<0.001) 

colon = 3.81 (<0.05) 

Significant SMRs (p 

values) (compared to 

population of BFDendemic area): 

Cancers— 

bladder = 2.55 (<0.01) 

skin = 4.51 (<0.05) 

lung = 2.84 (<0.01) 

liver = 2.48 (<0.01) 

Strengths: 

-Cases consisted of 

blackfoot disease 

cases, matched to 

healthy community 

controls for age, sex, 

and residence. 

-Recall bias was 

minimized through 

interview techniques. 

-SMRs were 

determined using both 

the national 

Taiwanese population 

and the local endemic 

area population. 

Weakness: 

-Arsenic dose levels 

were not provided. 

Chen et al., 

1988b 

Cohort/ 

nested casecontrol 

August 

1983–

February 

1987 

246 BFD 

bladder cancer 

cases 

444 BFDendemic area 

residents 

286 residents 

neighboring the 

endemic area 

731 nonendemic 

area residents 

Percent of area 

well water 

with arsenic 

content of 

≥50 ppb: 

Pei-men = 81 

Hsueh-Chia = 

27 

Pu-Tai = 58 

Jinag-Jium = 

24 

Tai-Pao = 45 

Pao-Chung = 

54 

≥350 ppb: 

Pei-men = 62 

Hsueh-Chia = 

7 

Pu-Tai = 8 

Jinag-Jium = 0 

Tai-Pao = 6 

Pao-Chung = 0 

Positive cytology 

(bladder cancer/atypia) 

prevalence rate (%): 

BFD cases = 4.5 

endemic area = 2.5 

neighboring area = 0.7 

non-endemic area = 

0.13 

Strengths: 

-Histological 

confirmation of 

bladder cancer 

diagnoses. 

Weaknesses: 

-Lack of individual 

exposure data. 

Chiang et 

al., 1988 

Casecontrol 

B-9 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1973–

1986 

Residents of 42 

villages 

1976 world 

population used 

as comparison 

Three 

exposure 

categories 

(ppb): 

<300 

300–590 

 >600 

Trend test of the 

extension of the 

Mantel-Haenszel Chi 

square test: 

Cancers— 

Both genders: 

bladder, skin, lung—

p < 0.001 

Males only: 

kidney, liver, 

prostate—p < 0.05 

Females only: 

kidney—p < 0.001 

Strengths: 

-Adjustments made 

for age and gender. 

-Lifestyle, access to 

medical care, and 

socioeconomic status 

were similar among 

the study groups. 

Weaknesses: 

-Limitations of 

mortality data. 

-Associations 

observed at the local 

level may not be 

accurate at the 

individual level 

(ecological fallacy). 

Wu et al., 

1989 

Ecological 

1972–

1983 

Arsenicexposed 

subjects from 

314 townships 

and precincts 

Total wells 

tested = 

83,656, 

≥50 ppb in 

15,649 wells 

(18.7%), 

≥ 350 ppb in 

2,224 wells 

(2.7%) 

Concentrations 

in the 

remainder of 

the wells were 

not given 

Multivariate adjusted 

regression coefficient 

for cancers (SE): 

Males— 

liver = 6.8 (1.3), nasal 

cavity = 0.7(0.2), lung 

= 5.3 (0.9), skin = 0.9 

(0.2), bladder = 3.9 

(0.5), kidney = 1.1 

(0.2), prostate = 0.5 

(0.2) 

Females— 

liver = 2.0 (0.5), nasal 

cavity = 0.4 (0.1), lung 

= 5.3 (0.7), skin = 1.0 

(0.2), bladder = 4.2 

(0.5), kidney = 1.7 (0.2) 

No p values indicated. 

Strengths: 

-Potential 

confounders 

controlled for 

included 

socioeconomic 

differences, i.e., 

urbanization and 

industrialization. 

-Cancer rates in 

endemic BFD 

townships were 

compared with cancer 

rates in non-endemic 

townships of Taiwan. 

-Ecological 

correlations reported 

between arsenic 

content in well water 

and mortality from 

various cancers. 

Weaknesses: 

-Potential 

confounders not 

controlled for were 

gender and other 

potential well water 

contaminants. 

-No individual arsenic 

exposures. 

Chen and 

Wang, 

1990 

Ecological 

B-10 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1973–

1986 

Arsenicexposed 

subjects from 

42 villages 

Well water 

arsenic 

exposure 

categories 

(ppb): 

<100 

100–290 

300–590 

≥600 

Overall range: 

10–1,752 

Cancer development 

potency index (daily 

arsenic intake of 10 

μg/kg): 

Males— 

liver = 4.3 × 10-3 

lung = 1.2 × 10-2 

bladder = 1.2 × 10-2

kidney = 4.2 × 10-3 

Females— 

liver = 3.6 × 10-3

lung = 1.3 × 10-2

bladder = 1.7 × 10-2

kidney = 4.8 × 10-3

Strengths: 

-Potential 

confounders included 

age, gender, access to 

medical care, 

socioeconomic status, 

and lifestyle and were 

all controlled for in 

the analysis. 

-Villages share 

similar 

socioeconomic status, 

living environments, 

lifestyles, dietary 

patterns, and even 

medical facilities. 

Weaknesses: 

-Armitage-Doll model 

constrains risk 

estimates to be 

monotonically 

increasing function of 

age. 

-Age stratification 

only available for 20-

year strata. 

-Possible 

underestimation of 

risk because it was 

assumed that an 

individual’s arsenic 

intake remained 

constant from birth to 

the end of the followup period. 

-Assumption that an 

individual’s arsenic 

intake remained 

constant from birth to 

the end of the followup period and the 

possible 

underestimation of 

risk because other 

sources of arsenic 

exposure were not 

considered. 

Chen et al., 

1992 

Ecological 

Followed 

up for 

0.05–7.69 

years 

(4.97 

±1.72 

[SD] 

263 BFD cases 

2,293 healthy 

residents 

Artesian well 

water median 

arsenic level = 

780 ppb 

Shallow well 

water median 

Multivariate adjusted 

RR (95% CI), cancer: 

All sites— 

Age: every-l-yr 

increment = 1.05 

(1.03–1.06)* 

Sex: men = 1.00, 

Strengths: 

-Showed a significant 

dose-response 

relationship with 

increasing 

concentrations of 

arsenic. 

Chiou et al., 

1995 

Cohort 

B-11 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

years) 

until 

January 

1993 

arsenic level = 

40 ppb 

women = 0.72 

(0.43–1.18)* 

Cigarette smoking: 

no = 1.00, yes = 1.52 

(1.00–2.48)* 

Status of blackfoot 

disease: 

no = 1.00, yes = 2.69 

(l.80–4.01)* 

Cumulative arsenic 

exposure (mg/liter × 

yr): 

0 = 1.00 

0.1–19.9 = 1.39 (0.82–

2.37) 

20+ = 1.76 (1.01–

3.06)* 

unknown = 0.72 (0.42–

1.22) 

Lung— 

Age: every-l-yr 

increment = 1.06 (1.02–

1.10)* 

Sex: men = 1.00, 

women = 1.79 (0.44–

7.32)* 

Cigarette smoking: 

no = 1.00, yes = 4.31 

(1.08–17.20)* 

Status of blackfoot 

disease: 

no = 1.00, yes = 2.45 

(1.07–0.57)* 

Cumulative arsenic 

exposure (mg/liter × 

yr): 

0 = 1.00 

0.1–9.9 = 2.74 (0.69–

11.0) 

20+ = 4.01 (1.00–

16.12)* 

unknown = 2.01 (0.55–

7.36) 

Bladder— 

Age: every l-yr 

increment = 1.04 (1.05–

1.08)* 

Sex: men = 1.00, 

women = 0.45 (0.18–

1.16) 

Cigarette smoking: 

no = 1.00, yes = 1.00 

(0.37–2.31) 

Status of blackfoot 

disease: 

-Analysis adjusted for 

BFD status, age, sex, 

and smoking. 

-Reported incidence 

data. 

Weaknesses: 

-Artesian well water 

arsenic concentration 

was unknown for 

some study subjects. 

B-12 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

no = 1.00, yes = 4.41 

(2.06–9.45)* 

Cumulative arsenic 

exposure (mg/liter × 

yr): 

0 = 1.00 

0.1–19.9 = 1.57 (0.44–

5.55) 

20+ = 3.58 (1.05–

12.l9)* 

unknown = 1.25 (0.38–

4.12) 

*p < 0.05 

January 

1980–

December 

1987 

2,915 urinary 

cancer cases 

6 categories of 

arsenic 

exposure 

(ppb): 

<50 

50–80 

90–160 

170–320 

330–640 

>640 

Rate differences (SE)* 

with positive 

associations: 

Males— 

Bladder cancer: 

transitional cell 

>640 ppb = 0.57(0.07), 

adenocarinoma 

>640 ppb = 

0.027(0.008) 

Kidney cancer: 

transitional cell 

330–640 ppb = 

0.05(0.02) 

Females— 

Urethral cancer, all cell 

types combined 

>640 ppb = 

0.027(0.007) 

*Estimates for 1 unit 

increase (1%) in 

predictor (exposure 

category) 

Strengths: 

-Adjusted for age, 

gender, urbanization, 

and smoking. 

Weaknesses: 

- Limitations of 

ecological study 

design. 

Guo et al., 

1997 

Ecological 

B-13 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1971–

1994 

11,193 

mortalities 

from all causes 

of disease 

Local reference 

population 

National 

reference 

population 

Median 

artesian wells 

water arsenic 

content: 780 

ppb 

(range = 250–

1140 ppb) 

Individual 

exposure data 

not available 

Males— 

BFD area compared to 

local reference— SMR 

(95% CI): 

all cancers = 2.19 

(2.11–2.28) 

BFD area compared to 

national reference— 

SMR (95% CI): 

all cancers = 1.94 

(1.87–2.01) 

Females— 

BFD area compared to 

local reference—SMR 

(95% CI): 

all cancers = 2.40 

(2.30–2.51) 

BFD area compared to 

national reference— 

SMR (95% CI): 

all cancers = 2.05 

(1.96–2.14) 

p < 0.05 

Strengths: 

-Exposed group and 

local reference group 

had similar lifestyle 

factors. 

-All cancers were 

pathologically 

confirmed. 

-Controlled for 

gender, a potential 

confounder. 

Weaknesses: 

–Only one underlying 

cause of death (not 

multiple causes) was 

indicated on death 

certificate, resulting 

in possible distortion 

of association 

between exposure and 

disease. 

-Lack of individual 

exposure data. 

-Potential 

confounders not 

controlled for were 

age, smoking, alcohol 

consumption, and 

occupational 

exposures. 

Tsai et al., 

1999 

Crosssectional 

B-14 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1973–

1986 

42 arseniasisendemic 

villages 

Population of 

Taiwan 

Arsenic 

exposure 

categories 

(ppb) = 

0–50 

50–100 

100–200 

200–300 

300–400 

400–500 

500–600 

600+ 

SMRs (male and female 

combined.) 

Bladder cancer SMRs:* 

0–50 ppb = 10.02 

50–100 ppb = 4.15 

100–200 ppb = 10.47 

200–300 ppb = 7.66 

300–400 ppb = 7.44 

400–500 ppb = 29.68 

500–600 ppb = 14.90 

600+ ppb = 32.71 

Lung cancer SMRs:* 

0–50 ppb = 1.56 

50–100 ppb = 1.43 

100–200 ppb = 2.43 

200–300 ppb = 3.08 

300–400 ppb = 1.97 

400–500 ppb = 3.65 

500–600 ppb = 3.32 

600+ ppb = 5.14 

Liver cancer SMRs:* 

0–50 ppb = 1.18 

50–100 ppb = 0.65 

100–200 ppb = 1.74 

200–300 ppb = 1.44 

300–400 ppb = 0.77 

400–500 ppb = 1.60 

500–600 ppb = 1.59 

600+ ppb = 2.17 

Bladder, lung, and liver 

combined cancer 

SMRs:* 

0–50 ppb = 1.83 

50–100 ppb = 1.16 

100–200 ppb = 2.51 

200–300 ppb = 2.47 

300–400 ppb = 1.63 

400–500 ppb = 3.93 

500–600 ppb = 3.06 

600+ ppb = 4.86 

 

*No significance levels 

presented. 

Strengths: 

-Person-years at risk 

stratified by age, 

gender, and arsenic 

level. 

-Individual well 

concentrations were 

available for each 

village. 

Weaknesses: 

-Ecological study 

design (no individual 

monitoring data, 

individual exposures 

not available). 

-Potential 

confounding by 

smoking, use of 

bottled water, and 

dietary intake, since 

this information was 

not available. 

Morales et 

al., 2000 

Ecological 

B-15 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

October 

1991– 

September 

1994 with 

follow-up 

through 

the end of 

1996 

8,102 residents 

(4,056 men and 

4,046 women) 

General 

population of 

Taiwan used as 

comparison 

Exposure 

categories 

(ppb) : 

≤10.00 

10.1–50.0 

50.1–100.0 

≥100.0 

Standardized incidence 

ratio (95% CI): 

urinary cancer = 2.05 

(1.22, 3.24) 

bladder = 1.96 (0.94–

3.61) 

kidney = 2.82 (1.29–

5.36) 

p < 0.05 

Multivariate adjusted 

RR (95% CI): 

Well water arsenic 

concentration (ppb): 

Urinary organs— 

10.1–50.0 = 1.5 (0.3–

8.0) 

50.1–100.0 = 2.2 (0.4–

13.7) 

>100.0 = 4.8 (1.2–19.4) 

TCC 

10.1–50.0 = 1.9 (0.1–

32.5) 

50.1–100.0 = 8.2 (0.7–

99.1) 

>100.0 = 15.3 (1.7–

139.9) 

Strengths: 

- Showed a 

significant doseresponse relationship 

with increasing 

concentrations of 

arsenic. 

-Potential 

confounders adjusted 

for included age, 

gender, and smoking. 

-Individual exposure 

estimates were 

available. 

Weaknesses: 

-Possible diagnosis 

bias, since data were 

collected from 

various community 

hospitals. 

-Possible recall bias 

resulting from selfreported information. 

- Short duration of 

follow-up, which 

limited the number of 

person-years of 

observation. 

-Possible 

misclassification, 

especially in the lowdose region due to 

lack of arsenic 

exposure information 

in the food. 

Chiou et al., 

2001 

Cohort 

B-16 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

January 

1980–

December 

1989 

2,369 skin 

cancer cases 

(1,415 men and 

954 women) 

6 categories of 

arsenic 

exposure 

(ppb): 

<50, 

50–80, 

90–160, 

170–320, 

330–640, 

>640 

Statistically significant 

rate differences per 

100,000 person-years 

(SE):* 

Males— 

Basal cell carcinoma 

>640 ppb = 

0.128(0.025)** 

Squamous cell 

carcinoma 

170–320 ppb = 

0.073(0.024)** 

330–640 ppb= -

0.10(0.031)** 

>640 ppb = 

0.155(0.028)** 

Females— 

Squamous cell 

carcinoma 

330–640 ppb = -

0.064(0.027)* 

>640 ppb = 

0.212(0.024)** 

*p < 0.05 

**p < 0.01 

Strengths: 

-Cases were identified 

from government 

operated National 

Cancer Registration 

Program. 

-Pathological 

classifications 

determined by boardcertified pathologists. 

-Potential 

confounders adjusted 

for in the analysis 

included gender and 

age. 

Weaknesses: 

-Limitations of 

ecological study 

design. (No 

monitoring data were 

presented.) 

Guo et al., 

2001 

Ecological 

January 

1980–

December 

1999 

40,832 liver 

cancer patients 

(32,034 men 

and 8,798 

women) 

BFD area 

average 

arsenic 

concentration 

= 220 ppb 

Non-BFD area 

average 

arsenic 

concentration 

= 20 ppb 

No statistically 

significant (P > 0.05) 

differences were noted 

for cell types of liver 

cancer between the 

BFD area and the other 

areas. 

Strengths: 

-Cases identified from 

government operated 

National Cancer 

Registration Program. 

-Pathological 

classifications were 

determined by boardcertified pathologists. 

-Potential 

confounders adjusted 

for included gender 

and age. 

Weaknesses: 

-Limitations of 

ecological study 

design. (No 

monitoring data were 

presented). 

Guo, 2003 

Ecological 

B-17 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

January 

1985–

December 

2000; 

average 

follow-up 

of 8 years 

2,503 residents 

in southwestern 

area 

8,088 residents 

in northeastern 

area 

Southwestern 

area average 

arsenic 

exposure 

categories 

(ppb): 

<10 

10–99.9 

100–299.9 

300–699.9 

≥700 

Unknown 

Multivariate-adjusted 

RR of lung cancer for 

average arsenic level in 

well water (ppb): 

<10 = 1.00 (referent) 

10–99.9 = 1.09(0.63–

1.91) 

100–299.9 =2.28 (1.22–

4.27) 

300–699.9 = 3.03 

(1.62–5.69) 

≥700 = 3.29 (1.60–

6.78) 

Unknown = 1.10 (0.60–

2.03) 

Strengths: 

-Confounders 

controlled for were 

age, gender, 

education, and 

alcohol consumption. 

-Long follow-up 

period and the use of 

a national 

computerized cancer 

case registry. 

-All lung cancer cases 

were pathologically 

confirmed. 

Weaknesses: 

-Historical monitoring 

data not available. 

-Possible 

misclassification bias 

because exposure 

measurements were 

based on one survey. 

Chen et al., 

2004a 

Cohort 

1971–

2000 

Residents of 4 

BFD-endemic 

townships 

Median well 

water arsenic 

level, early 

1960s = 780 

ppb 

SMR liver cancer: 

Males— 

1989–1991 = 1.868 

1998–2000 = 1.242 

Females— 

1983–1985 = 2.041 

1998–2000 = 1.137 

Strengths: 

-Residents in the 

study area were 

similar in terms of 

socioeconomic status, 

living environments, 

lifestyles, dietary 

patterns, and health 

service facilities. 

-Accurate death 

registration system. 

Weaknesses: 

-Limitations of 

mortality data. 

Chiu et al., 

2004 

Cohort 

B-18 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

January 

1971–

December 

1990 

1,078 lung 

cancer 

mortality cases 

Arsenic 

exposure 

levels (ppb): 

<050 

50–80 

90–160 

170–320 

330–640 

>640 

Lung cancer mortality 

increase with 1,000 ppb 

increase in mean 

arsenic level (p=0.01): 

Men— 

27.45/100,000 personyears 

Women— 

18.93/100,00 personyears 

Strengths: 

-Adjusted for gender 

and age. 

-Cases were 

ascertained using 

information from 

household registry 

offices in each 

township. Taiwanese 

law requires timely 

reporting of deaths to 

these offices. 

Weaknesses: 

-Limitations of 

ecological studies. 

-Smoking was not 

controlled for in the 

analysis. 

Guo, 2004 

Ecological 

B-19 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1971–

2000 

Residents of 4 

BFD-endemic 

townships 

Median 

arsenic level 

(ppb), early 

1960s = 780 

(range: 350–

1140) 

Kidney cancer SMR 

(observed vs. 

expected): 

1971— 

Men = 19.04 (4 vs. 

0.21) 

Women = 23.52 (8 vs. 

0.34) 

2000— 

Men = 4.46 (8 vs. 1.79) 

Women = 6.52 (9 vs. 

1.38) 

Strengths: 

-Adjusted for gender 

and age. 

-Mandatory 

registering of all 

births, deaths, 

marriages, divorces, 

and migration to the 

Household 

Registration Office in 

Taiwan, making it an 

accurate data source. 

-Most residents had 

similar 

socioeconomic status, 

living environments, 

lifestyles, dietary 

patterns, and health 

service facilities and 

worked in farming, 

fisheries, or salt 

production. 

-All kidney cancer 

cases in the area 

probably had similar 

access to medical 

care. 

Weaknesses: 

-Mortality data 

limitations. 

-Cross-sectional study 

limitations. 

-Smoking may 

possibly have been a 

confounder not 

adequately controlled 

for. 

Yang et al., 

2004 

Crosssectional 

1988–

2001 

7 females 

14 males 

No exposure 

data 

Chi square (Taiwan 

case series compared to 

3 U.S. case series 

studies): 

Males— 

urethral 

adenocarcinoma: 

p < 0.0001 

Strengths: 

-Cases were 

pathologically 

confirmed. 

Weaknesses: 

-Limited number of 

cases. 

-No exposure 

information. 

Tsai et al., 

2005 

Crosssectional 

B-20 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1971–

2000 

Residents in 4 

BFD-endemic 

area townships 

Median 

arsenic level, 

early 1960s = 

780 ppb 

Bladder cancer SMRs 

(observed vs. 

expected): 

1971— 

Males = 10.25 (8 vs. 

0.78) 

Females = 14.89 (7 vs. 

0.47) 

2000— 

Males = 2.15 (5 vs. 

2.32) 

Females = 7.63 (10 vs. 

1.31) 

Strengths: 

-All bladder cancer 

cases in the area 

probably had similar 

access to medical 

care. 

-Adjusted for age and 

gender. 

-Mandatory 

registering of all 

births, deaths, 

marriages, divorces, 

and migration to the 

Household 

Registration Office in 

Taiwan, making it an 

accurate data source. 

Weaknesses: 

-Limitations of a 

cross-sectional 

mortality study. 

-Smoking may 

possibly have been a 

confounder. 

Yang et al., 

2005 

Crosssectional 

B-21 DRAFT—DO NOT CITE OR QUOTE 
Table B-2. Japan Cancer Studies 

Study Subjects/ 

Controls 

Exposure 

Period Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1959–

1992 

454 

residents 

Well arsenic 

concentration 

(ppb): 

<50 

50–990 

≥ 1000 

≥1000 ppb 

SMRs (95% CI): 

Males— 

all deaths = 1.88 

(1.17–2.96) 

all cancers = 4.19 

(2.20–7.56) 

lung cancer = 19.08 

(8.88–38.76) 

urinary cancer = 33.16 

(5.92–121.58) 

all cancers except lung 

= 

2.22 (0.87–5.22) 

Females— 

all deaths = 1.31 

(0.76–2.18) 

all cancers = 3.00 

(1.40–6.13) 

lung cancer = 7.15 

(0.36–41.11) 

urinary cancer = 27.85 

(1.42–159.89) 

all cancers except lung 

= 

2.73 (1.19–6.04) 

Cox’s proportional 

hazard analysis (95% 

CI), highest group vs. 

background: 

concentration 

categories (ppb) 

≥1 000 vs. 1 

all deaths = 1.74 

(1.10–2.74) 

all cancers = 4.82 

(2.09–11.14) 

lung cancer = 

1,972.16 (4.34–

895,385.11) 

Strengths: 

-Cohort examined by 3 

exposure categories. 

-Included information on 

smoking, age and gender. 

Weaknesses: 

-Lacking detailed arsenic 

intake information. 

-Small study population. 

-Possible misclassification 

bias. 

-Recall bias (smoking 

history)..

Tsuda et al., 

1995 

Cohort 

1 

B-22 DRAFT—DO NOT CITE OR QUOTE 
Table B-3. South America Cancer Studies 

Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1986–

1991 

Bladder 

cancer 

deaths in 

26 

Cordoba 

counties 

Population 

of 

Argentina 

Exposure 

categories: 

low 

medium 

high 

(crude average 

estimate of 178 

ppb) 

Two counties in 

high-exposure 

group 

Bladder cancer SMR 

(95% CI) by exposure 

category: 

Men— 

low = 0.80 (0.66–

0.96) 

medium = 1.42 (1.14–

1.74) 

high = 2.14 (1.78–

2.53) 

test for trend: 

p=0.001 

Women— 

low = 1.21 (0.85–

1.64) 

medium = 1.58 (1.01–

2.35) 

high = 1.82 (1.19–

2.64) 

test for trend: p=0.04 

Strengths:

-Adjusted for age and 

gender. 

-Analysis restricted to 

rural counties to limit 

confounders. 

-To account for cancer 

diagnosis and detection 

bias, stomach cancer, 

which is known not to be 

related to arsenic 

exposure, was used as a 

comparison cancer. 

Weaknesses: 

-Limitations of ecological 

studies.

-Lack of comprehensive, 

systematic monitoring 

data. 

-No arsenic exposure 

levels in low and medium 

groups reported. 

-Lack of individual 

smoking history. 

HopenhaynRich et al., 

1996a 

Ecological 

B-23 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1986–

1991 

Population 

from 26 

counties in 

Cordoba 

Population 

of 

Argentina 

Exposure 

categories: 

low 

medium 

high 

(crude average 

estimate of 178 

ppb) 

SMRs (95% CI) by 

exposure categories: 

Kidney cancer— 

Men 

low = 0.87 (0.66–

1.10) 

medium = 1.33 (1.02–

1.68) 

high = 1.57 (1.17–

2.05) 

Women 

low = 1.00 (0.71–

1.37) 

medium = 1.36 (0.94–

1.89) 

high = 1.81 (1.19–

2.64) 

Lung cancer 

Men 

low = 0.92 (0.85–

0.98) 

medium = 1.54 (1.44–

1.64) 

high = 1.77 (1.63–

1.90) 

Women 

low = 1.24 (1.06–

1.42) 

medium = 1.34 (1.12–

1.58) 

high = 2.16 (1.83–

2.52) 

p < 0.001 in trend test 

Strengths:

-Adjusted for age and 

gender. 

-Analysis restricted to 

rural counties to limit 

confounders. 

-To account for cancer 

diagnosis and detection 

bias, stomach cancer, that 

is known not to be related 

to arsenic exposure, as a 

comparison cancer. 

Weaknesses: 

-Limitations of ecological 

studies.

-Lack of comprehensive, 

systematic monitoring 

data. 

-No arsenic exposure 

levels in low and medium 

groups reported. 

-Lack of individual 

smoking history.

HopenhaynRich et al., 

1998 

Ecological 

B-24 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1989–

1993 

390,340 

residents 

national 

mortality 

data from 

1991 

Population 

of Chile 

used as 

reference 

group 

Region II average 

water arsenic level 

(ppb): 

1950–1954 = 123 

1955–1959 = 569 

1960–1964 = 568 

1965–1969 = 568 

1970–1974 = 272 

1975–1979 = 176 

1980–1984 = 94 

1985–1989 = 71 

1990–1994 = 43 

SMRs (95% CI, p 

value) 

≥30 years old: 

Men— 

bladder = 6.0 (4.8–

7.4, <0.001) 

kidney = 1.6 (1.1–2.1, 

0.012) 

liver = 1.1 (0.8–1.5, 

0.392) 

lung = 3.8 (3.5–4.1, 

<0.001) 

skin = 7.7 (4.7–11.9, 

<0.001) 

Women— 

bladder = 8.2 (6.3–

10.5, <0.001) 

kidney = 2.7 (1.9–3.8, 

<0.001) 

liver = 1.1 (0.8–1.5, 

0.377) 

lung = 3.1 (2.7–3.7, 

<0.001) 

skin = 3.2 (1.3–6.6, 

0.016) 

Strengths:

-Large study size. 

-Used national data for 

comparison. No other 

major populations in Chile 

were exposed to arsenic in 

drinking water. 

-SMRs adjusted for age 

and gender. 

Weaknesses: 

-Arsenic levels in drinking 

water available only by 

city or town. 

-Deaths were not linked to 

town so individual 

exposure is not known. 

-Limited smoking data. 

-No dose-response 

information provided. 

Smith et al., 

1998 

Ecological

B-25 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1994–

1996 

152 lung 

cancer 

cases 

419 

controls 

Average water 

arsenic 

concentration (ppb) 

during peak 

exposure years: 

0–10 

10–29 

30–59 

60–89 

90–199 

200–399 

400–699 

700–999 

Lung cancer odds 

ratio (95% CI): 

Age/gender 

adjusted— 

0–10 ppb = 1 

(referent) 

10–29 ppb = 0.4 (0.1–

0.5) 

30–59 ppb = 0.0 (0.6–

7.2) 

60–89 ppb = 0.1 (1.8–

9.2) 

90–199 ppb = 0.8 

(1.1–7.0) 

200–399 ppb = 0.4 

(2.0–10.0) 

400–699 ppb = 0.9 

(2.4–19.8) 

700–999 ppb = 0.3 

(3.1–12.8) 

Male vs. female = 0.7 

(1.1–2.7) 

Full model (95% CI) 

(included smoking 

and copper smelting): 

0–10 ppb = 1 

(referent) 

10–29 ppb = 0.3 (0.1–

1.2) 

30–59 ppb = 1.8 (0.5–

6.9) 

60–89 ppb = 4.1 (1.8–

9.6) 

90–199 ppb = 2.7 

(1.0–7.1) 

200–399 ppb = 4.7 

(2.0–11.0) 

400–699 ppb = 5.7 

(1.9–16.9) 

700–999 ppb = 7.1 

(3.4–14.8) 

Male vs. female = 1.1 

(0.6–1.8) 

Ever vs. never 

smoked = 

4.3 (2.6–7.3) 

SES medium vs. low 

= 1.3 (0.7–2.5) 

SES high vs. low = 

2.3 (0.5–12.1) 

Copper smelting 

(ever/never) = 1.7 

(0.7–4.4) 

Strengths: 

-Odds ratios adjusted for 

age, gender, cumulative 

lifetime cigarette smoking, 

working in copper 

smelting, and 

socioeconomic status. 

-Because the control 

group selection was 

complex, several validity 

checks were completed. 

Weaknesses: 

-Relatively more controls 

were chosen from the 

highly exposed city of 

Antofagasta than from the 

lower exposure cities of 

Arica and Iquique 

resulting in possible 

underestimation of risk. 

Ferreccio et 

al., 2000 

Casecontrol 

B-26 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1996–

2000 

114 

bladder 

cancer 

cases 

114 

individuals 

without 

bladder 

cancer 

Average arsenic 

concentration (ppb) 

of 5 years of 

highest exposure 

during the period 

of 6–40 years prior 

to interview: 

0–50 

51–100 

101–200 

>200 

(mean: 164 ppb) 

Bladder cancer 

Odds ratio (95% 

CI)—ever smokers by 

time before interview: 

51–60 years earlier = 

2.65 (1.2–5.8) 

61–70 years earlier = 

2.54 (1.0–6.4) 

periods combined = 

2.5 (1.1–5.5) 

Strength: 

-Potential confounders 

controlled included age, 

gender, smoking, and 

county of residence. 

Weaknesses: 

-Lack of a cancer registry, 

arsenic exposure 

misclassification (use of 

current water source 

arsenic measurements 

possibly causing 

underestimation of 

exposure), and recall bias. 

-Possible selection bias 

since controls had a 

significantly reduced rate 

of participation than cases 

and cases were selected 

from the tumor registry. 

-Other harmful exposures 

not measured. 

Bates et al., 

2004 

Casecontrol 

1989–

2000 

~200,000 

residents 

Water arsenic 

levels: 

prior to 1958, ~90 

ppb; in the late 

1950s, water 

supplementation 

from a nearby river 

where arsenic 

levels approached 

1000 ppb was 

added to the 

existing city water 

supply 

SMRs (95% CI): 

1950–1957 birth 

cohort (early 

childhood exposure): 

lung cancer = 7.0 

(5.4–8.9, p < 0.001) 

High exposure period 

(1958–1971) with 

probable exposure in 

utero and early 

childhood: 

lung cancer = 6.1 

(3.5–9.9, p < 0.001) 

Strengths: 

-Extensive documentation 

of arsenic in drinking 

water in the Antofagasta 

water system. 

Weaknesses: 

-Residence was 

determined from death 

certificates and relates to 

residence at the time at 

death. 

-Reliance on death 

certificates resulting in 

potential diagnostic bias. 

-Information bias 

(smoking history).

Smith et al., 

2006 

Cohort 

B-27 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1950–

2000 

Region II 

residents 

Region V 

residents as 

comparison 

group 

Population 

of Chile 

Average arsenic 

concentration 

(ppb): 

Region II 

1950–1954 = 123 

1955–1959 = 569 

1960–1964 = 568 

1965–1969 = 568 

1970–1974 = 272 

1975–1979 = 176 

1980–1984 = 94 

1985–1989 = 71 

1990–1994 = 43 

Region V 

unexposed 

Peak rate ratios (95% 

CI) compared to 

Region V and Chile: 

Lung Cancer 

1992–1994 

Men 

3.61 (3.13–4.16) 

(Region V) 

4.20 (3.76–4.70) 

(Chile) 

1989–1991 

Women 

3.26 (2.50–4.23) 

(Region V) 

3.41 (2.76–4.22) 

(Chile) 

Bladder Cancer

1986–1988 

Men 

6.10 (3.97–9.39) 

(Region V) 

5.99 (4.41–8.14) 

(Chile) 

1992–1994 

Women 

13.8 (7.74–24.5) 

(Region V) 

9.32 (6.67–13.0) 

(Chile) 

Strengths: 

-Large population size. 

-Accurate past exposure 

data. 

-Known exposure pattern. 

-Controlled for potential 

confounding by age, 

gender, and smoking. 

Weaknesses: 

-Could not account for 

migration. 

-No individual exposure 

data or data on other risk 

factors (smoking and 

occupation).

Marshall et 

al., 2007 

Ecological 

B-28 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1950–

2000 

314,807 

exposed 

1,230,498 

unexposed 

Average water 

concentration (ppb) 

in Region II: 

Before arsenic 

removal plant— 

1950–1957 = 90 

1958–1970 = 870 

After arsenic 

removal plant— 

1971–1985 = 110 

1986–2000 = 40 

Present = 10 

Excess deaths as 

percentage of total 

deaths (%) due to 

acute myocardial 

infarction, lung 

cancer, and bladder 

cancer combined: 

Males— 

1950–1957 = 1.00 

1958–1964 = 4.19 

1965–1970 = 6.03 

1971–1979* = 6.48 

1980–1985 = 8.94 

1986–1990 = 10.07 

1991–1995 = 10.87 

1996–2000 = 7.92 

Total = 6.93 

Females— 

1950–1957 = 0.48 

1958–1964 = 1.59 

1965–1970 = 3.11 

1971–1979* = 3.78 

1980–1985 = 2.75 

1986–1990 = 3.85 

1991–1995 = 4.00 

1996–2000 = 3.36 

Total = 2.94 

*No data available for 

1976 

Strengths:

-Almost all drinking water 

came from a few 

municipal water sources, 

which had known arsenic 

concentrations. 

-The study involved a 

large population that 

experienced a rapid 

increase in arsenic 

exposure followed by a 

rapid decrease in arsenic 

exposure. 

-To ensure that an 

appropriate comparison 

population was chosen, 

preliminary investigations 

were conducted to 

compare income, 

smoking, and quality of 

death certificate 

information. 

Weaknesses: 

-Possible biases resulting 

from a lack of individual 

exposure data and 

confounders. 

Yuan et al., 

2007 

Ecological 

B-29 DRAFT—DO NOT CITE OR QUOTE 
Table B-4. North America cancer studies 

Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

39 years 

(endpoint–

1978 

diagnosis) 

71 

National 

Bladder 

Cancer 

Study 

participants 

160 

National 

Bladder 

Cancer 

Study 

participants 

without 

bladder 

cancer 

Mean arsenic 

level (ppb) = 5.0 

(range = 0.5–160 ) 

Exposure indices: 

Index 1—

cumulative dose 

(<19, 19 to <33, 

33 to <53, ≥53 

mg) 

Index 2—intake 

concentration 

adjusted to fluid 

intake (<33, 33 to 

<53, 53 to <74, 

≥74 mg- years) 

Odds ratio for 

bladder cancer and 

arsenic exposure: no 

association of 

bladder cancer with 

Index 1 or Index 2. 

Among smokers, 

positive trend in 10 

year intervals. 

Strengths: 

-Age, gender, smoking 

status, years of 

chlorinated surface water 

exposure, history of 

bladder infection, 

education, occupation, 

population size of 

geographic area, and 

urbanization were 

addressed. 

-Cases were 

histologically confirmed. 

Weaknesses: 

-Small size of study 

population. 

-Absence of historical 

monitoring data and data 

on arsenic levels in 

public water supplies 

were collected in 1978–

1979. 

-The subjects were 

mostly males and the 

data on females were 

inadequate. 

-Arsenic exposure levels 

were based on 

measurements close to 

the time that cases were 

diagnosed. 

-Arsenic from food was 

not considered. 

Bates et al., 

1995 

Casecontrol 

B-30 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1996 2,203 

deceased 

individuals 

from 

Millard 

County 

General 

Utah 

population 

used as 

comparison 

Arsenic exposure 

index (ppb-years): 

low = <1000 

medium = 1000–

4999 

high = >5000 

Cancer SMRs (95% 

CI): 

kidney— 

males = 1.75 (0.80–

3.32) 

females = 1.60 

(0.44–4.11) 

bladder and other 

urinary organs— 

males = 0.42 (0.08–

1.22) 

females = 0.81 

(0.10–2.93) 

melanoma of the 

skin— 

females = 1.82 

(0.50–4.66) 

prostate = 1.45* 

(1.07–1.91) 

*p≤0.05 

Strengths:

-A major strength of the 

study is that it measured 

the effects of chronic 

arsenic exposure in U.S. 

population. 

-Advantages of cohort 

design include the fact 

that the exposure 

precedes the effect being 

measured and that the 

cohort design has the 

ability to measure a 

variety of effects from a 

single type of exposure. 

Weaknesses: 

-Exposure assessment.

-Study power. 

-Exposure to atmospheric 

arsenic and arsenic from 

food were potential 

confounder. 

Lewis et al., 

1999 

Cohort 

1993–

1996 

587 BCC 

cases 

284 SCC 

cases 

524 

controls 

Toenail arsenic 

level (μg/g): 

BCC cases = 

0.01–2.03 

SCC cases = 

0.01–2.57 

controls = 0.01–

0.81 

OR (95% CI), 

toenail arsenic 

concentrations above 

the 97th percentile: 

SCC = 2.07 (0.92–

4.66) 

BCC = 1.44 (0.74–

2.81) 

Strengths: 

-Evaluated the effects of 

age, gender, race, 

educational attainment, 

smoking status, skin 

reaction to first exposure 

to the sun, history of 

radiotherapy (potential 

confounders). 

-Toenail concentrations 

individualize exposure 

and account for arsenic 

from other sources.

Weaknesses:

-Latency of arsenicinduced skin cancer 

unknown, follow-up 

period may have been 

inadequate. 

-Toenail arsenic 

measurements only 

account for recent past 

exposure. 

Karagas et 

al., 2001 

Casecontrol

B-31 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1979–

1999 

Not 

applicable 

Arsenic exposure 

categories (ppb): 

low = <10 

medium = 10–25 

high = 35–90 

SIR (95% CI), 

childhood leukemia 

and all childhood 

cancers excluding 

leukemia: 

Low-exposure 

group— 

leukemia = 1.02 

(0.90–1.15) 

all cancers = 0.99 

(0.92–1.07) 

Medium-exposure 

group: 

leukemia = 0.61 

(0.12–1.79) 

all cancers = 0.82 

(0.47–1.33) 

High-exposure 

group: 

leukemia = 0.86 

(0.37–1.70) 

all cancers = 1.37 

(0.96–1.91) 

Strengths:

-The analysis was 

stratified by age. 

-Low arsenic exposure 

study. 

-Findings were reported 

for different 

concentration ranges. 

Weaknesses: 

-Small study size. 

-Limitations of 

ecological study design. 

-Arsenic from food was 

not measured, leading to 

possible exposure 

misclassification. 

Moore et 

al., 2002 

Ecological

1994–

2000 

181 cases 

328 

controls 

Exposure 

categories (ppb): 

0–19 

20–79 

80–120 

>120 

Arsenic exposure 

indices: 

(1) highest 

average daily 

arsenic intake for 

any one year, (2) 

highest average 

daily arsenic 

intake averaged 

over any 

contiguous 5 

years, (3) highest 

average daily 

arsenic intake 

averaged over any 

contiguous 20 

years, and (4) total 

lifetime 

cumulative 

exposure 

Bladder cancer OR 

(95% CI): 

>80 μg/day = 0.94 

(0.56–1.57) 

linear trend, p = 0.48 

>80 μg/day, ≥40 

years ago—smokers 

= 3.67 (1.43–9.42) 

linear trend, p < 0.01 

Strengths: 

-Potential confounders 

adjusted included gender, 

age, smoking history, 

education, occupation 

associated with elevated 

rates of bladder cancer, 

and income. 

-Use of cancer registry. 

-Individual exposure 

levels. 

Weaknesses: 

-Information bias (nextof-kin interviews). 

-Arsenic exposures 

outside the study area 

were not incorporated. 

-In the arsenic-exposed 

areas, the percentage of 

nonparticipants was 5% 

higher among cases than 

controls. This difference 

would probably mean 

that more exposed cases 

were missed in analyses 

of recent exposure, 

biasing the odds ratio 

toward the null. 

-Arsenic exposure from 

food was not considered. 

Steinmaus 

et al., 2003 

Casecontrol

B-32 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1999–

2000 

368 

cutaneous 

melanoma 

cases 

373 

colorectal 

cancer 

controls 

Median toenail 

arsenic 

concentration: 

cases = 0.06 μg/g, 

controls = 0.04 

μg/g 

OR = 2.1 (95% CI = 

1.4–3.3, 

p-trend = 0.001) for 

increased risk of 

melanoma with 

elevated toenail 

arsenic 

concentrations 

OR = 6.6 (CI = 2.0–

21.9) for increased 

risk of melanoma 

with previous 

diagnosis of skin 

cancer and elevated 

toenail arsenic 

concentrations 

Strengths: 

-Potential confounders 

controlled for were age, 

gender, skin color/skin 

type, prior history of 

sunburn, education, and 

occupational exposure(s).

-Ascertainment of cases 

and controls was 

accomplished by using 

the Iowa Cancer 

Registry, a Surveillance, 

Epidemiology, and End 

Results Program registry. 

 This allowed newly 

diagnosed melanoma 

cases to be identified for 

a specific period and 

ensured a greater degree 

of certainty regarding the 

accuracy of diagnosis. 

-Toenail arsenic 

measurements 

individualize exposure 

and account for arsenic 

exposure from other 

sources. 

Weaknesses:

-A limitation was that 

toenail samples were 

collected 2–3 years after 

diagnosis, resulting in 

possible exposure 

misclassification. 

BeaneFreeman et 

al., 2004 

Casecontrol

B-33 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

July 1, 

1994 and 

June 30, 

1998 

383 

transitional 

cell 

bladder 

cancer 

cases 

641 

controls 

Toenail arsenic 

level (μg/g): 

cases = 0.014–

2.484 

controls = 0.009–

1.077 

Odds ratio (95% 

CI)— 

bladder cancer 

among smokers: 

>0.330 μg/g = 2.17 

(0.92–5.11) 

Strengths:

-Evaluated the following 

potential confounders: 

age, gender, race, 

educational attainment, 

smoking status, family 

history of bladder cancer, 

study period and average 

number of glasses of tap 

water consumed per day. 

-Conducted stratified 

analyses according to 

how long subjects used 

their current water 

system (<15 years, ≥15 

years) to evaluate the 

possibility that an 

extended latency period 

is required for bladder 

cancer development. 

-Attempted to minimize 

misclassification by 

using biomarker 

(toenails). 

Weaknesses:

-Possible 

misclassification at lower 

end of exposure range. 

-Limited data at extreme 

ends of exposure. 

-Lifetime exposure could 

not be calculated since 

data from previous 

residences could not be 

determined. 

Karagas et 

al., 2004 

Casecontrol

B-34 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1950–

1979 

2,498,185 

white 

males 

1970 U.S. 

standard 

population 

Median water 

arsenic 

concentration 

(ppb): 

3.0–3.9 

4.0–4.9 

5.0–7.4 

7.5–9.9 

10.0–19.9 

20.0–49.9 

50.0–59.9 

Bladder cancer 

SMRs (95% CI), 

white males by 

median arsenic 

concentration in 

ground water (ppb): 

3.0–3.9 = 0.95 

(0.89–1.01) 

4.0–4.9 = 0.95 ( 

0.88–1.02) 

5.0–7.4 = 0.97 

(0.85–1.12) 

7.5–9.9 = 0.89 

(0.75–1.06) 

10.0–19.9 = 0.90 

(0.78–1.04) 

20.0–49.9 = 0.80 

(0.54–1.17) 

50.0–59.9 = 0.73 ( 

0.41–1.27) 

All levels combined 

= 

0.94 (0.90–0.98) 

Strengths: 

-Large study population. 

-Study was nationwide. 

-Included over 75 million 

person-years of 

observation. 

Weaknesses: 

-No individual exposure 

data. 

-Assumed that study 

participants consumed 

local drinking water. 

-Available data assumed 

to represent actual 

arsenic content of water. 

-Analysis did not directly 

adjust for smoking, 

urbanization, and 

industrialization. 

-Arsenic contribution 

from food was not 

measured. 

Lamm et 

al., 2004 

Ecological

B-35 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

July 

2000–

January 

2002 

6,669 

residents 

Three arsenic 

exposure 

categories (ppb): 

<1.0 

1.0–9.0 

≥10 

Skin cancer 

adjusted odds ratio 

(95% CI): 

Arsenic level 

(ppb)— 

<1.0 = referent 

1–9.9 = 1.81 (1.10–

3.41) 

≥ 10 = 1.92 (1.10–

3.68) 

Age (years)— 

35–64 = referent 

≥ 65 = 4.53 (2.79–

7.38) 

Gender— 

female = referent 

males = 2.25 (1.33–

3.79) 

Cigarette use— 

no = referent 

yes = 1.37 (0.84–

2.24) 

Strengths: 

-Large sample size. 

-History of individual 

tobacco use. 

-Arsenic well water 

analysis for each 

household. 

-Participants consumed 

water from the tested 

wells for at least 10 

years. 

-Analysis controlled for 

age, gender, and tobacco 

use. 

Weaknesses:

-Skin cancers were selfreported and not 

confirmed by a medical 

records review. 

-Few people could 

provide information 

about specific types of 

cancer. 

-Families that 

participated may have 

been especially 

concerned about arsenic 

exposure or family 

members may have had 

existing health 

conditions. 

-Not controlled for sun 

exposure or occupation. 

-Arsenic contribution 

from food was not 

measured. 

Knobeloch 

et al., 2006 

Crosssectional

B-36 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1979–

1997 

Residents 

of six 

Michigan 

counties 

Remainder 

of 

Michigan 

population 

as 

comparison 

Populationweighted mean 

arsenic 

concentration 

(ppb): 

exposed counties 

= 11.00 

remainder of 

Michigan = 2.98 

Elevated cancer 

SMRs (95% CI): 

Males— 

liver/biliary = 0.85 

(0.72–1.00) 

trachea, bronchus, 

lung = 1.02 

(0.98–1.06) 

melanoma = 0.99 

(0.79–1.22) 

other skin cancer = 

1.24 (0.86–1.72) 

bladder = 0.94 

(0.82–1.08) 

kidney/urinary = 

1.06 (0.91–1.22) 

Females— 

liver/biliary = 1.04 

(0.89–1.20) 

trachea, bronchus, 

lung = 

1.02 (0.96–1.07) 

melanoma = 0.97 

(0.73–1.27) 

other skin cancer = 

1.06 (0.60–1.72) 

female reproductive 

organs = 1.11* 

(1.03–1.19) 

bladder = 0.98 

(0.80–1.19) 

kidney/urinary 

organs = 

1.00 (0.82–1.20) 

*p < 0.01 

Strengths:

-Mortality data gathered 

from Michigan Resident 

Death Files for 20-year 

period. 

-Mortality rates stratified 

by gender, age, and race. 

Weaknesses: 

-Possible differences in 

reporting and 

classification of 

underlying causes of 

death. 

-No assessment of 

individual exposures and 

case migration. 

-Smoking and obesity, 

possible confounders, 

were not included in the 

analysis. 

-Preferential sampling 

based on home owners’ 

request. 

-Arsenic contribution 

from food was not 

measured. 

Meliker et 

al., 2007 

Ecological 

B-37 DRAFT—DO NOT CITE OR QUOTE 
Table B-5. China cancer studies 

Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1990 3,179 

residents 

HAC (ppb): 

<10 

10– 

30– 

50– 

60– 

100– 

150– 

500+

CAE (ppb-year): 

<10 

10– 

32– 

100– 

316– 

1000– 

3162– 

10000+ 

Crude and (ageadjusted) skin cancer 

prevalence rates by 

HAC: 

<10 = 0.0 (0.0) 

10– = 0.0 (0.0) 

50– = 0.0 (0.0) 

150– = 1.2 (1.0) 

500+ = 7.1 (5.9) 

Crude and (ageadjusted) skin cancer 

rates by CAE: 

<10 = 0.0 (0.0) 

10– = 0.0 (0.0) 

32– = 0.0 (0.0) 

100– = 0.0 (0.0) 

316– = 0.0 (0.0) 

1000– = 0.4 (0.3) 

3162– = 0.8 (0.2) 

10000+ = 2.7 (2.0) 

Strengths: 

-Large study population. 

-Used both HAC and CAE 

in the analyses. 

-Arsenic concentrations 

measured in 184 wells. 

-Controlled for age and 

differences in cumulative 

arsenic exposure dose and 

duration of exposure. 

Weaknesses: 

-Possible recall and 

misclassification bias 

resulting from the 

collection of exposure 

histories through 

interviews. 

-Inherent limitations of 

ecological study design. 

-Did not control for sun 

exposure.

Lamm et 

al., 2007 

Ecological 

B-38 DRAFT—DO NOT CITE OR QUOTE 
Table B-6. Finland cancer studies 

Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/ 

Type of 

Study 

1981–

1995 

61 

bladder 

cancer 

cases and 

49 

kidney 

cancer 

cases 

 

275 

referents 

Water arsenic 

concentration 

(ppb): 

<0.1 

0.1–0.5 

≥0.5 

Arsenic daily dose 

(μg/day): 

<0.2 

0.2–1.0 

≥1.0 

Cumulative dose 

(μg): 

<500 

500–2000 

≥2000 

Bladder cancer risk 

ratios (95% CI): 

Shorter latency— 

Water arsenic 

concentration (ppb): 

0.1–0.5 = 1.53 (0.75–

3.09) 

≥0.5 = 2.44 (1.11–

5.37) 

Daily arsenic dose 

(μg/day): 

0.2–1.0 = 1.34 (0.66–

2.69) 

≥1.0 = 1.84 (0.84–

4.03) 

Cumulative dose (μg): 

500–2000 = 1.61 

(0.74–3.54) 

≥2000 = 1.50 (0.71–

3.15) 

Longer latency— 

Water arsenic 

concentration (ppb): 

0.1–0.5 = 0.81 (0.41–

1.63) 

≥0.5 = 1.51 (0.67–

3.38) 

Daily arsenic dose 

(μg/day): 

0.2–1.0 = 0.76 (0.38–

1.52) 

≥1.0 = 1.07 (0.48–

2.38) 

Cumulative dose (μg): 

500–2000 = 0.81 

(0.39–1.69) 

≥2000 = 0.53 (0.25–

1.10) 

Strengths:

-Cases were identified 

through the Finnish Cancer 

Registry. 

-The 1985 Population 

Census file of Statistics 

Finland was used to 

identify areas in which less 

than 10% of the population 

used the municipal water 

supply. 

-Risk ratios adjusted for 

age, gender, and smoking. 

Weaknesses:

-Possible misclassification 

and possible recall bias 

resulting from the study 

choosing to use water 

consumption from the 

1970. 

-Lacks other sources of 

arsenic exposure.

Kurttio et al., 

1999 

Case-cohort 

B-39 DRAFT—DO NOT CITE OR QUOTE 
Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/ 

Type of 

Study 

1985–

1988 

and 

April 

1999 

280 

incident 

bladder 

cancer 

cases 

293 

controls 

Arsenic exposure 

quartiles (μg/g)— 

1: <0.050 

2: 0.050–0.105 

3: 0.106–0.161 

4: >0.161 

Bladder cancer odds 

ratio (95% CI): 

highest vs. lowest 

quartile of toenail 

arsenic = 1.13, (0.70, 

1.81) 

p trend = 0.65 for the 

highest vs. lowest 

quartile) 

Strengths: 

-Study used toenail arsenic 

as biomarkers of exposure. 

-Cases and controls 

matched according to age, 

toenail collection date, 

intervention group (alpha 

tocopherol and beta 

carotene), and smoking 

duration. 

-Study adjusted for 

matching factors, smoking, 

educational level, beverage 

intake, and place of 

residence. 

-Cut point of >0.09 μg/g 

used to avoid sample 

misclassification. 

-Potential confounders, 

including smoking 

cessation, smoking 

inhalation, educational 

level, beverage intake, and 

place of residence, were 

controlled for in the study 

analysis. 

Weaknesses: 

-Water intake was not 

included in the total 

beverage variable. 

-Toenail arsenic measures 

recent past exposures. 

Michaud et 

al., 2004 

Cohort/nested 

case-control 

B-40 DRAFT—DO NOT CITE OR QUOTE 
Table B-7. Denmark cancer studies 

Study 

Period 

Subjects/ 

Controls 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1970–

2003 

39,378 

Copenhagen 

residents 

17,000 

Aarhus 

residents 

TWA arsenic 

exposure (ppb) 

from 41 years old 

to date of 

enrollment: 

Copenhagen: 

min = 0.05 

max = 15.8 

Aarhus: 

min = 0.09 

max = 25.3 

Entire cohort: 

min = 0.05 

max = 25.3 

Cancer incidence 

rate ratios 

(95% CI): 

Time-weighted 

average exposure: 

Copenhagen— 

melanoma = 0.73 

(0.46–1.14) 

non-melanoma = 

1.09 (0.95–1.24) 

breast = 1.04 (0.88–

1.22) 

Aarhus— 

melanoma = 0.85 

(0.61–1.20) 

non-melanoma = 

0.97 (0.90–1.05) 

breast = 1.06 (1.01–

1.11) 

Cumulative 

exposure: 

Copenhagen— 

melanoma = 0.94 

(0.81–1.08) 

non-melanoma = 

1.01 (0.97–1.06) 

breast =1.01 (0.95–

1.06) 

Aarhus— 

melanoma = 0.97 

(0.90–1.05) 

non-melanoma = 

0.98 (0.95–1.01) 

breast = 1.01 (0.99–

1.03) 

Strengths:

-Large study population. 

-

Socioeconomic/demographic 

similarities of the cohorts. 

-Potential confounders 

adjusted were smoking, 

alcohol consumption, 

education, body mass index, 

daily intake of 

fruits/vegetables, red meat, 

fat and dietary fiber, skin 

reaction to the sun, hormone 

replacement therapy use, 

reproduction, occupation, 

and enrollment area. 

Weaknesses: 

-Possible misclassification 

bias. 

-Overall low arsenic 

concentration in drinking 

water in Denmark. 

-Lack of data regarding 

other sources of arsenic. 

Baastrup et 

al., 2008 

Cohort 

B-41 DRAFT—DO NOT CITE OR QUOTE 
Table B-8. Australia Cancer Studies 

Study 

Period Subjects/Control 

Exposure 

Assessment Study Outcome 

Strengths/ 

Weaknesses 

Reference/

Type of 

Study 

1982–

1991 

Victoria Cancer 

Registry cancer 

data 

Australian Bureau 

of Statistics 

denominator data 

Water/soil 

exposure 

groups: 

High 

water/high 

soil— 

>10 ppb / >100 

mg/kg 

High water/low 

soil— 

>10 ppb / <100 

mg/kg 

High soil/low 

water— 

<10 ppb / >100 

mg/kg 

Cancer SIRs (95% 

CI): 

Males and 

females— 

all cancers = 1.06 

(1.03–1.09) 

prostate = 1.14 

(1.05–1.23) 

kidney = 1.16 

(0.98–1.37) 

melanoma = 1.36 

(1.24–1.48) 

chronic myeloid 

leukemia = 1.54 

(1.13–2.10) 

Females— 

breast = 1.10 

(1.03–1.18) 

Strengths: 

-Study included both 

water and soil in 

exposure categories. 

-Twenty-two areas 

included in the study. 

Weaknesses: 

-Socioeconomic status, 

race, occupation 

and living in a rural area 

were possible 

confounders. 

-Possible exposure 

misclassification. 

-Ecological study 

limitations.

Hinwood et 

al., 1999 

Ecological 

B-42 DRAFT—DO NOT CITE OR QUOTE 
APPENDIX C. TABLES FOR STUDIES ON POSSIBLE MODE OF ACTION FOR 

INORGANIC ARSENIC 

This appendix contains three tables that deal with possible MOAs of arsenic in the 

development of cancer based on in vivo human studies (Table C-1), in vivo experiments on 

laboratory animals (Table C-2), and in vitro studies (Table C-3). They describe numerous 

experiments published from 2005 through August 2007, as well as earlier experiments that were 

mentioned in the Science Advisory Board Arsenic Review Panel comments of July 2007 (SAB, 

2007), 2001 NRC document on arsenic (NRC, 2001), or a detailed early draft of this document 

that lacked MOA tables. The data from these studies are distributed among 22 key-event 

categories, with the data from different experiments from a single publication often being 

summarized under different key-event categories. For example, the results in Wang et al. (1996) 

are summarized by rows under Apoptosis, Cytotoxicity, and Effects Related to Oxidative Stress 

(ROS). The advantage of distributing the data in this way is that it helped to focus on a 

particular key event for each set of data. The disadvantage of using this approach is that it 

spatially separated the different parts of each experiment. An exception to this procedure is the 

category Immune System Response, in which results from different parts of each experiment are 

presented in successive rows. 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

23 

24 

25 

26 

27 

28 

29 

30 

31 

32 

33 

34 

A brief discussion of the approaches and conventions used in preparing the tables is 

included here. Abbreviations are used liberally in an attempt to reduce the size of the table. An 

attempt was made to provide a summary of the main findings of each experiment, with the 

expectation that any reader wanting more detail would read the publication. A search for any 

specific citation should make it easy to pull together the information from the numerous parts of 

some studies that related to different categories. Although, for example, cytotoxicity data are 

generally summarized in the Cytotoxicity category, exceptions sometimes were made in an 

attempt to decrease the size of the table. For example, if data presented on apoptosis contained 

only slight, but interesting, data on cytotoxicity, a brief summary of those cytotoxicity findings 

was sometimes added at the end of the results column in the row that described the results on 

apoptosis. When an experiment that tested only one concentration yielded interesting results, the 

results column is sometimes merged with one or more columns to its left in that same row so the 

long description of results did not drastically increase the height of the table. In such a case, the 

only dose tested was obviously the LOEC or LOEL. 

In vivo experiments on laboratory animals were almost always restricted to experiments 

in which the route of exposure was oral. In most cases this meant that the arsenical was 

administered in drinking water or was given by gavage. A few experiments had the arsenical in 

the feed. Two experiments on chicken embryos had a solution (with concentration in μM) put 

onto the embryo, and one genetic assay done on Drosophila melanogaster had the concentration 

C-1 DRAFT—DO NOT CITE OR QUOTE
(given in mM) reported for the media. All other in vivo experiments were done on mice or rats. 

Numerous studies were excluded on other non-mammalian species, including, for example, fish, 

nematodes, and algae. 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

23 

24 

25 

26 

27 

28 

29 

30 

31 

32 

33 

34 

35 

36 

37 

Tables C-2 and C-3 list all doses or concentrations tested as well as the duration of 

testing. It was often necessary to estimate the concentrations or doses tested from figures. For 

brevity, the control dose of 0 is not listed as a concentration tested. In the rare instances in 

which there was no zero-dose control group, this omission is mentioned in the results section. In 

many cases the papers themselves did not specify the LOECs or LOELs, and those values were 

estimated from tables or figures. Because of the large variation in the way that papers presented 

data and variability in their findings, and because of the rather common failure to clearly define 

the error bars around data points in figures, there was often subjectivity involved in selecting the 

LOEC or LOEL. There was no strict requirement that the LOEC or LOEL declared for each 

experiment had to be shown to be statistically significantly higher than the control, although it 

was not uncommon for that to be the case. The wording in the results column often helps to 

clarify this situation. If six concentrations were tested, for example, and if the second from the 

lowest concentration had error bars that did not overlap those of the control, and if the third from 

the lowest concentration was identified as being statistically significantly higher then the control, 

then the second from the lowest concentration tested would have been declared the LOEC. The 

LOEC, for example, should be viewed as the lowest concentration that was “quite likely” to have 

caused an effect—without any specific statistical interpretation being attached to it. As long as 

this was made clear, it was felt that this approach would be most useful to readers who want to 

know the lowest concentration level at which a particular effect would probably occur. 

Arrows are used to indicate changes that were increases or decreases from the control. If 

the change was relative to some other group, it was clearly indicated as such. In most cases, the 

changes in magnitude of effects relative to the control were described as, for example, “2.34x” or 

“0.46x”—2.34 times higher than the control or only 46% as high as the control. When those 

ratios were based on estimates made from a graph, they are generally preceded by a “∼” mark; if 

they were calculated from tabulated values, they are generally presented without that mark. 

In Table C-2 the doses are presented in terms of the amount of arsenic. When doses were 

reported in mg arsenic/L or in ppm As, it was assumed that the doses included adjustment to 

determine the amount of arsenic administered. In a few publications it was unclear if the 

reported doses were for the compound or for the amount of arsenic administered. Partly because 

of this uncertainty, all doses shown in the table that were corrected to the amount of arsenic from 

values that were clearly reported as concentrations of some arsenical compound (or for which 

that was assumed to be the case) are preceded by an asterisk. Species of arsenic are shown in 

Tables C-2 and C-3, and AsV is almost always sodium arsenate. 

C-2 DRAFT—DO NOT CITE OR QUOTE
Abbreviations for Tables in Appendix C 

⇑ increase 

⇓ decrease 

∼ approximately (if before a listing of concentrations, 

it applies to all) 

≈ approximately equal 

1RB3AN27 cells an immortalized dopamine-producing rat 

mesencephalic cell line 

1T1 cells a human epithelial cell line 

293 cells a cell line derived from adenovirus-transformed 

human embryonic kidney epithelial cells 

2-AAAF 2-acetoxyacetylaminofluorene 

2BS cells human fetal lung fibroblasts 

3-NT 3-nitrotyrosine 

4HNE 4-hydroxy-2-nonenal 

4NQO 4-nitroquinoline 1-oxide 

5-aza-dC 5-aza-deoxycytidine, a demethylating agent 

6-4 PPs 6-4 photoproducts (UV-induced DNA photoproduct) 

7-AAD 7-aminoactinomycin D 

8-OHdG 8-hydroxy-2’-deoxyguanosine or 8-

hydroxydeoxyguanosine (synonym) 

8-oxoG 7,8-dihydro-8-oxoguanine 

A2780 cells human ovarian carcinoma cell line 

A431 cells human epidermoid carcinoma cell line 

A5/SG assays A5 (Annexin V-Alexa568) and SG (a green 

fluorescent DNA dye) staining assays; A5+/SG- cells 

are apoptotic 

A549 cells human non-small cell lung cancer (NSCLC) cell line 

(alveolar basal epithelial cell line) 

AA ascorbic acid (vitamin C) 

AB assay AlamarBlue assay 

ABTS 2,2′-azinobis(3-ethylbenzothiazoline)-6-sulfonic acid 

AC arsenic chloride 

ADM adriamycin 

ADSB apparent DNA strand break 

AFP α-fetoprotein 

AG06 cells SV40-transformed human keratinocytes 

AGT average generation time 

Ahr+/+ MEFs mouse embryo fibroblasts of genotype Ahr+/+ from 

C57BL/6J mice, which are cells known to respond to 

a B(α)P or TCCD challenge by activation of the AhR 

Akt1 V-akt murine thymoma viral oncogene homolog 1 (a 

human gene) 

ALAD δ-aminolevulinic acid dehydratase 

ALAS δ-aminolevulinic acid synthetase 

C-3 DRAFT—DO NOT CITE OR QUOTE
AL hybrid cells a cell line that contains structural set of CHO-K1 

chromosomes and one copy of human chromosome 

11 

AMs alveolar macrophages 

AML acute myelogenous leukemia 

AMPK adenosine monophosphate-activated protein kinase 

AO acridine orange 

APE/Ref-1 apurinic/apyrimidinic endonuclease (hAPE1) 

AP-PCR arbitrarily primed polymerase chain reaction 

Aprt adenosine phosphoribosyl transferase 

AP sites sites of base loss (apurinic/apyrimidinic [AP] sites) 

AR230 cells a CML cell line that expresses large amounts of BcrAbl 

AR230-r cells AR230 cells that are resistant to the Bcr-Abl 

inhibitor imatinib mesylate 

AR230-s cells AR230 cells that are sensitive to the Bcr-Abl 

inhibitor imatinib mesylate 

ARE antioxidant response element 

AS52 cells a pSV2 gpt-transformed Chinese hamster ovary cell 

line; cells in this line carry a single copy of a 

transfected E. coli gpt gene 

As arsenic 

AsIII arsenite 

AsV arsenate 

ASK1 apoptosis signal-regulating kinase 1 

ATO arsenic trioxide 

B0653 2,3-dihydro-5-hydroxy-2,2-dipentyl-4,6-di-tertbutylbenzofuran 

B16-F10 cells mouse melanoma cells 

BAEC bovine aortic endothelial cells 

BALF bronchoalveolar lavage fluid 

B[a]P benzo[a]pyrene 

BCS bathocuproinedisulphonic acid 

BEAS-2B cells human bronchial (pulmonary) epithelial cell line 

BER base excision repair 

BFTC905 cells a human urothelial carcinoma cell line 

BFU burst-forming units 

BHMT betaine-homocysteine methyltransferase 

BHT butylated hydroxytoluene 

Bid a BH3 domain-containing proapoptotic Bcl2 family 

member that is a specific proximal substrate of 

Casp8 in the Fas apoptotic signaling pathway 

BPDE benzo[a]pyrene diol epoxide 

BrdU bromodeoxyuridine 

BSO L-buthionine-S,R- sulphoximine (depletes GSH, γGCS inhibitor) 

BUC bladder urothelial cells 

C-4 DRAFT—DO NOT CITE OR QUOTE
C-33A cells a transformed human non-differentiated carcinoma 

cell line 

CAM cell adhesion molecule 

CAM assay chorioallantoic membrane assay of angiogenesis 

CAs chromosome aberrations 

CAT catalase (decomposes H2O2) 

Cdc cell division cycle 

Cdc42 a small GTPase in the Rho/Rac subfamily of Raslike GTPases 

cen+ centromere positive (micronuclei) 

cen- centromere negative (micronuclei) 

CFE colony-forming efficiency 

c-Fos an AP-1 protein 

CFSE 5,6-carboxyfluorescein diacetate succinimidyl ester 

CFU colony-forming units 

CGL-2 cells a cell line derived from a hybrid (ESH5) of the HeLa 

variant, D98/AH2, and a normal human fibroblast 

strain, GM77 

cGpx cellular glutathione peroxidase 

Chang cells a human cell line thought to be derived from HeLa 

cells 

ChAT choline acetyltransferase 

CHO Chinese hamster ovary 

CI confidence interval 

c-Jun or c-jun an AP-1 protein 

CK8 cytokeratin 8 

CL3 cells human lung adenocarcinoma cells (established from 

a non-small-cell lung carcinoma) 

CL3R15 cells cell line derived from CL3 cells that were maintained 

in 4 μM arsenic SA 

c-met the oncogene that encodes HGF (hepatocyte growth 

factor) receptor 

c-Mos proto-oncogene 

CM-H2DCFDA 5-(and-6)-carboxy-2′,7′-dichlorofluorescein diacetate 

CML chronic myeloid leukemia 

Conc concentration 

Contraspin a serine—or cysteine—proteinase inhibitor isoform 

COS-7 cells African green monkey kidney fibroblast cell line 

containing 10,000 glucocorticoid receptors per cell 

that are transcriptionally inactive 

CoTr co-treatment 

COX cytochrome c oxidase; its activity is a measure of 

mitochondrial function 

COX-2 cyclooxygenase-2 

CPDs cyclobutane pyrimidine dimers (UV-induced DNA 

photoproduct) 

Cpp32 caspase-3 

CREBP cAMP response element binding protein 

C-5 DRAFT—DO NOT CITE OR QUOTE
CRL1675 cells a human melanocyte cell line 

CRL-1609 cells chimpanzee transformed skin fibroblast cells 

cRNA RNA derived from complimentary DNA through 

standard RNA synthesis 

CSTP clonal survival treat and plate 

Cul3 Cullin 3, an Nrf2-finding protein 

CV assay crystal violet assay; it measures cellular protein, 

which is related to cell number 

CYP1A1 cytochrome P450 1A1 

CYP7B1 cytochrome P450 family 7, subfamily b polypeptide 

1 

DA disodium arsenate 

DAP 2,6-diaminopurine 

DCF assay dichlorofluorescein assay 

DCFH-DA 2′,7′-dichlorofluorescein diacetate 

DCHA docosahexaenoic acid, a ω-3 polyunsaturated fatty 

acid vital for the developing nervous system 

DEB diepoxybutane (DNA crosslinking agent) 

DENA diethylnitrosamine 

DES diethylstilbestrol 

Dex dexamethasone (synthetic glucocorticoid) 

DHA dehydroascorbic acid 

dhfr gene dihydrofolate reductase gene 

DHR123 dihydrorhodamine 123 

DIC dicumarol, and Nqo1 inhibitor 

DI-I or II or III iodothyronine deiodinase-I or II or III (are 3 forms of 

this selenoenzyme) 

DKO double knock out 

dL deciliter 

DMAIII dimethylarsenous acid 

DMAV dimethylarsinic acid 

DMA dimethyl arsenic (used when the oxidative state is 

unknown or not specified) 

DMAIIII dimethylarsinous iodide 

DMBA dimethylbenzanthracene 

DMN dimethylnitrosamine 

DMNQ 2,3-dimethoxy-1,4-naphthoquinone 

DMPO 5,5′-dimethyl-1-pyrroline N-oxide (a spin-trap agent) 

DMPS 2,3-dimercaptopropane-1-sulfonic acid 

DMSA dimercaptosuccinic acid or meso 2,3- 

dimercaptosuccinic acid 

DMSO dimethyl sulfoxide 

DNA deoxyribonucleic acid 

DNA-PK DNA-dependent protein kinase, which has 3 

subunits, of which the Ku70 protein is one 

D-NMMA NG-methyl-D-arginine, the inactive enantiomer of a 

nitric oxide synthase inhibitor 

DNMT DNA methyltransferase 

C-6 DRAFT—DO NOT CITE OR QUOTE
DPC DNA protein crosslinks 

DPI diphenyleneiodonium 

DPIC diphenylene iodonium chloride, an NADPH-oxidase 

inhibitor

DR death receptor 

DRE-CALUX dioxin-responsive element (DRE)–mediated 

Chemical Activated LUciferase eXpression 

DSB double strand break (in DNA) 

DTNB 5,5 ́-dithiobis(2-nitrobenzoic acid) 

DTT dithiothreitol 

DU145 cells a human prostate carcinoma cell line 

DW drinking water 

E2N ubiquitin-conjugating enzyme 

E7 cells an immortalized human bladder cell line 

EA ethacrynic acid (a GST inhibitor) 

EB ethidium bromide 

E. coli Escherichia coli 

EDR3 cells a rat hepatoma cell line (glucocorticoid receptor 

negative, with neither protein nor mRNA detectable) 

EGCG ( -)-epigallocatechin gallate 

EGF epidermal growth factor 

EGFR epidermal growth factor receptor 

EGFR ECD extracellular domain of the epidermal growth factor 

receptor 

EGR early growth response 

eIF eukaryotic initiation factor 

eIF4E eukaryotic translation initiation factor 4E, which is 

the mRNA cap binding and rate-limiting factor 

required for translation 

ELISA enzyme-linked immunosorbent assay 

Emodin (l,3,8-trihydroxy-6-methylanthraquinone) 

EMSA electrophoretic mobility shift assays 

EnIII endonuclease III

eNOS endothelial nitric acid synthase 

ER-α estrogen receptor-α

ERCC1 excision repair cross-complement 1 component 

ERCC2 excision repair cross-complementing rodent repair 

deficiency, complementation group 2 (also known as 

xeroderma pigmentosum group D or XPD) 

Erk or ERK extracellular signal-regulated kinase 

EROD ethoxyresorufin-O-deethylase 

ESR electron spin resonance 

ETU S-ethylisothiourea, a NOS inhibitor 

FACS fluorescence-activated cell sorting 

FADD Fas-associated death domain protein 

FAK focal adhesion kinase 

FBS fetal bovine serum 

C-7 DRAFT—DO NOT CITE OR QUOTE
FeTMPyP 5,10,15,20-tetrakis (N-methyl-4’-pyridyl) porphinato 

iron(III) chloride (ONOO–

 decomposition catalyst) 

FGC4 cells rat hepatoma cells 

FGF-2 fibroblast growth factor -2 

FGFR1 fibroblast growth factor receptor 1 

FISH fluorescent in situ hybridization 

FITC fluorescein isothiocyanate 

FLIP FLICE-inhibitory protein, an antiapoptotic protein 

controlled by NF-κB 

FLIPL long-splice variant of FLIP 

Fox O3a an oxidative stress inducible forkhead transcription 

factor 

FPG formamidopyrimidine-DNA glycosylase (digestion 

of DNA) 

G12 cells a pSV2gpt-transformed Chinese hamster V79 (hprt–) 

cell line 

G6PDH glucose-6-phosphate dehydrogenase 

G-6-P glucose-6-phosphatase; the paper that presented data 

on this chemical called it G-6-PD in the discussion 

GADD growth arrest and DNA damage-inducible 

GCLM glutamate cysteine ligase modifier, GCLM knockout 

mice (-/-) have only 9%–16% of GSH level of wt 

littermates 

GCR glucocorticoid receptor 

GFP green fluorescent protein (GFP expressing tumor 

cells) 

GLN glutamine 

GlycoA glycophorin A 

GM04312C 

cells 

a SV-40 transformed XPA human fibroblast NERdeficient cell line 

GM847 cells a SV-40-transformed human lung fibroblast cell line 

GM-CSF granulocyte-macrophage colony-stimulating factor 

GM-Mp GM-type macrophage 

gpt guanine phosphoribosyltransferase 

GPx glutathione peroxidase 

GR glutathione reductase 

GRE glucocorticoid response elements 

GSH glutathione 

GSSG glutathione disulfide 

GST glutathione-S-transferase 

GTP guanosine-5'-triphosphate 

Gy gray (unit of ionizing radiation) 

H1355 cells a human lung adenocarcinoma cell line 

H2O2 hydrogen peroxide 

H22 cells a hepatocellular carcinoma cell line 

H411E cells a rat hepatoma cell line 

H460 cells a human non-small-cell lung cancer cell line (also 

called human lung large cell carcinoma cells) 

C-8 DRAFT—DO NOT CITE OR QUOTE
H9c2 cells an immortalized myoblast cell line derived from fetal 

rat hearts 

HaCaT cells a human epidermal keratinocyte cell line 

Hb hemoglobin 

HCC hepatocellular carcinoma 

HCT116 cells a human colorectal cancer cell line (available in 

securin-wild-type and securin-null forms) 

HCT15 cells a human colon adenocarcinoma cell line 

HEC hamster embryo cells 

HEK 293 cells an adenovirus-transformed human embryonic kidney 

epithelial cell line (non-tumor cells), also called 

HEK293 cells 

HEK293T cells human embryonic kidney cells 

Hepa-1c1c7 

cells 

a mouse hepatoma cell line known to respond to a 

B[α]P or TCCD challenge by activation of the AhR 

HepG2 cells a human hepatocellular liver carcinoma cell line 

(Caucasian) 

HeLa cells a human cervical adenocarcinoma cell line 

HeLa S3 cells a human cervical carcinoma cell line, derived from 

the parent HeLa cell line; adapted to grow in 

suspension (spinner) culture and has the same virus 

susceptibility as the parent line 

HELF cells a human embryo lung fibroblast cell line 

HEL cells an AML cell line that is a cytokine-independent 

human erythroleukemia cell line that has constitutive 

STAT3 activity 

hEp cells normal human epidermal cells derived from foreskin 

HFF cells a human foreskin fibroblasts cell line 

HFW cells a diploid human fibroblast cell line 

HGF hepatocyte growth factor 

HGPRT hypoxanthine-guanine phosphoribosyltransferase 

HIF hypoxia inducible factor 

HK-2 cells a human proximal tubular cell line 

HL-60 cells human promyelocytic leukemia cells 

HLA human leukocyte antigen 

HLA-DR human leukocyte antigen DR, which is a major 

histocompatibility complex class-II antigen 

HLF cells human embryo lung fibroblasts 

HLFC cells an HLF subline that is not Ku70 deficient; it has the 

null pEGFP-C1 vector transferred into it 

HLFK cells an HLF subline that is Ku70 deficient; it has a 

recombinant plasmid of Ku70 gene antisense RNA 

transferred into it; it had 38% as much Ku70 protein 

content as the HLFC cell line 

HMEC-1 cells human microvascular endothelial cells 

HMOX-1 heme oxygenase 1 

HO· hydroxyl radicals 

HOS cells a human osteogenic sarcoma cell line 

C-9 DRAFT—DO NOT CITE OR QUOTE
HpaII or HPAII Haemophilus parainfluenzae (restriction 

endonucleases) 

HPBM human peripheral blood monocytes 

HPLC high-performance liquid chromatography 

HPRT hypoxanthine phosphoribosyl transferase 

HRE hypoxia response element, the DNA binding element 

of HIF-mediated transactivation 

Hr hour(s) 

HSF1 heat shock transcription factor 1 

HSP heat shock protein 

HT1080 cells a human sarcoma cell line 

hTER RNA component of telomerase 

hTERT human telomerase reverse transcriptase 

HT1197 cells a human (Caucasian) epithelial bladder cancer cell 

line 

HU hydroxyurea 

Huh7 cells a human hepatoma cell line 

HuR RNA binding protein 

HUVEC cells a human umbilical vein endothelial cell line (or 

HUVECs) 

IAP inhibitor of apoptosis protein family 

iAs inorganic arsenic 

icAA intracellular ascorbic acid, which is accumulated at 

up to high concentrations by culturing cells in DHA 

ICAM-1 inter-cellular adhesion molecule-1 

ICE interleukin-1β-converting enzyme 

IC50 concentration that causes 50% inhibition of activity 

ID1 inhibitor of DNA binding-1 

IEC cells a primary culture of rat intestinal epithelial cells 

IEC-6 cells a rat intestinal epithelial cell line 

IGF insulin growth factor (system) 

IGFBP-1 insulin-like growth factor binding protein 1 

IKKβ inhibitor of kappa light polypeptide gene enhancer in 

B-cells, kinase beta; also called IkappaB kinase beta 

subunit 

IL interleukin 

ILK integrin-linked kinase 

Imatinib imatinib mesylate 

IM9 cells a human multiple myeloma cell line 

IRE iron responsive element 

IRP-1 iron regulatory protein 1 

J82 cells human bladder tumor cells 

JAK Janus kinase 

JAR cells a human placental choriocarcinoma cell line 

JB6 C141 cells a P+

 mouse epidermal cell line (sometimes called 

JB6 C1 41 cells) 

JB6 C141 PG13 

cells 

stable p53 luciferase reporter plasmid transfectant of 

cell line JB6 C141 

C-10 DRAFT—DO NOT CITE OR QUOTE
JB6 C141 P+

1-1 

cells 

stable activator protein-1 (AP-1) transfectant of cell 

line JB6 C141 

JC-1 voltage-sensitive lipophilic cationic fluorescence 

probe 5,5′,6,6′-tetrachloro-1,1′,3,3′-

tetraethylbenzimidazolcarbocyanine iodide 

JNK c-Jun N-terminal kinase 

Jurkat cells a transformed human T-lymphocyte cell line (also 

called lymphoblast cells) 

K1735-SW1 

cells 

a mouse melanoma cell line 

K562 cells a human immortalized myelogenous leukemia cell 

line that is a bcr:abl positive erythroleukemia line 

derived from a 53-year-old female CML patient in 

blast crisis

KCL22 cells a Bcr-Abl positive CML cell line 

KCL22-r cells KCL22 cells that are resistant to the Bcr-Abl 

inhibitor imatinib mesylate 

KCL22-s cells KCL22 cells that are sensitive to the Bcr-Abl 

inhibitor imatinib mesylate 

kDa kilodalton, a unit of mass 

Keap1 the cytoplasmic Nrf2-binding protein 

KMS12BM 

cells 

a human multiple myeloma cell line 

Ku70 one of the three subunits of DNA-dependent protein 

kinase 

L-132 cells human alveolar type II cells 

LAK cells lymphokine activated killers (effector cells) 

LCL-EBV cells mononuclear cells obtained from healthy donors and 

transformed by Epstein–Barr virus 

LC50 50% lethal concentration 

LDH lactate dehydrogenase 

LD50 50% lethal dose 

LI labeling index 

LOEC lowest observed effect concentration 

LOEL lowest observed effect level 

LOH loss of heterozygosity 

LPO lipid peroxidation 

Luc the PEPCK-luciferase construct 

LU1205 cells a human melanoma cell line 

L-NAME Nω-nitro-L-arginine methyl ester (an inhibitor of 

NOS) 

L-NMMA NG-methyl-L-arginine, the active enantiomer of a 

nitric oxide synthase inhibitor 

LPS lipopolysaccharide 

LTE4 leukotriene, a proinflammatory mediator 

Lys lysine 

Maf musculoaponeurotic fibrosarcoma (transcription 

factor) 

C-11 DRAFT—DO NOT CITE OR QUOTE
MAP mitogen-activated protein 

MAPK mitogen-activated protein kinase 

MCA 20-methylcholanthrene 

MC/CAR cells a human multiple myeloma cell line 

MCF-7 cells human breast carcinoma cell line 

MCR mineralocorticoid receptor 

M-CSF macrophage colony-stimulating factor 

MDA malondialdehyde (the thiobarbituric acid-reactive 

substance in the brain that reflects extensive lipid 

peroxidation) 

MDAH 2774 

cells 

human ovarian carcinoma cells 

MDA-MB-231 

cells 

a human breast cancer cell line (an invasive estrogen 

unresponsive cell line) 

MDA-MB-435 a human metastatic breast cancer cell line 

mdm2 murine double minute 2 proto-oncogene 

MDR multidrug resistance gene 

MED minimal erythemic dose 

MEF mouse embryo fibroblasts 

MEF cells a mouse embryonic fibroblast cell line 

MEK MAP/ERK kinase (also, a family of related serinethreonine protein kinases that regulate mitogenactivated protein kinase) 

MGC-803 cells a human gastric cancer cell line 

MI mitotic index 

MiADMSA monoisoamyl meso 2,3- dimercaptosuccinic acid 

min minutes(s) 

MK-571 MRP antagonist 

MKP-1 MAP kinase phosphatase 1 

MMA monomethyl arsenic (used when oxidative state is 

unknown or not specified) 

MMAIII monomethylarsonous acid 

MMAIIIO methylarsine oxide 

MMAV monomethyl arsonic acid 

MMC mitomycin C 

MMP mitochondrial membrane potential 

MMP-2 matrix metalloproteinase-2 

MMP-9 matrix metalloproteinase-9 

MMP-13 matrix metalloproteinase-13 

MMS methyl methanesulfonate 

MN micronuclei 

MNNG 1-methyl-3-nitro-1-nitrosoguanidine 

MnTMPyP Mn(III)tetrakis(1-methyl-4-pyridyl) porphyrin 

pentachloride (a cell permeable SOD mimic) 

MNU N-methyl-N-nitrosourea 

MRC-5 cells a human lung fibroblast cell line 

mRNA messenger ribonucleic acid 

MRP multidrug resistance-associated protein 

C-12 DRAFT—DO NOT CITE OR QUOTE
Mrps efflux transporters encoded by MRP genes 

MS mass spectrometer or mass spectrometry 

MT metallothionein 

mtDNA mitochondrial DNA 

MTOC microtubule-organizing center 

MTS assay 3-(4,5-dimethylthiazol-2-yl)-5-(3-

carboxymethoxyphenyl)-2-(4-sulfophenyl)-2Htetrazolium, inner salt assay; in Yi et al. (2004) study 

this was referred to as the CellTiter 96 AQueous 

Non-Radioactive Cell Proliferation Assay (MTS) Kit 

(Promega, Madison, WI) 

MTT 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium 

bromide 

MTX methotrexate 

MT-1 metallothionein-1 

MT2A gene symbol for metallothionein 2A 

MW molecular weight 

MYH MutY homolog, an endonuclease 

MYP3 cells rat epithelial cells line (urinary bladder cells) 

N-18 cells a mouse neuroblastoma cell line

NAC n-acetyl-cysteine (precursor of GSH; it elevates 

cellular GSH levels, also an antioxidant), also Nacetyl-L-cysteine 

NADH reduced form of nicotinamide adenine dinucleotide 

NADPH nicotinamide adenine dinucleotide phosphateoxidase 

Namalwa cells a human Burkitt’s lymphoma cell line 

NB4 cells a human acute promyelocytic leukemia cell line 

NB4-AsR an arsenic-resistant subline of NB4 that was made by 

culturing and maintaining cells in 1μM As2O3

NB4-M-AsR2 

cells 

an arsenic-resistant human acute promyelocytic 

leukemia cell line, which is routinely grown in RPMI 

1640 media containing 2 μM As2O3

NCE normochromatic erythrocytes 

NCI cells a human myeloma cell line 

NE nuclear extract 

NER nucleotide excision repair (pathway) 

NF-κB nuclear factor-kappa B 

NHEK cells primary normal human epidermal keratinocytes 

NIH 3T3 cells a mouse fibroblast cell line 

NO• nitric oxide 

NOS nitric oxide synthase 

Nqo1 nicotinamide adenine dinucleotide phosphatequinone oxidoreductase (or NAD(P)H-quinone 

oxidoreductase) 

NR neutral red 

Nrf2 cap ’n’ collar basic leucine zipper transcription 

factor (nuclear factor erythroid 2-related factor 2) 

C-13 DRAFT—DO NOT CITE OR QUOTE
NSAID non-steroidal anti-inflammatory drug 

NSE no significant effect (often not based on a statistical 

test but on whether an effect appears likely to be real 

based on examination of graphs) 

NTUB1 cells a human urothelial carcinoma cell line 

NuF nuclear fragmentation 

OATP-C organic anion transporting polypeptide-C 

ODA oxidative DNA adducts 

OGG1 8-oxoguanine DNA glycosylase 

OM431 cells a human melanoma cell line 

ONOO– peroxynitrite 

OR odds ratio 

p21 a cyclin-dependent kinase inhibitor 

PAEC cells porcine aortic endothelial cells 

PAI-1 plasminogen activator inhibitor-1 

PARP poly(adenosine diphosphate–ribose) polymerase 

PBMC peripheral blood mononuclear cell (human) 

PC protein carbonyl (form of protein oxidation) 

PC12 cells a rat sympathetic (neuronal) pheochromocytoma cell 

line 

PCE polychromatic erythrocyte 

PCI-1 cells a human head and neck squamous cell carcinoma 

cell line 

PCNA proliferating cell nuclear antigen 

PCR polymerase chain reaction 

PDH pyruvate dehydrogenase 

PDT population doubling time 

PD98059 inhibitor of MEK1/2, which are ERK upstream 

kinases (structurally unrelated to U0126) 

PEG monomethoxypolyethylene glycol (covalent 

attachment of PEG to CAT or SOD extends their 

plasma half-lives) 

PEPCK phosphoenolpyruvate carboxykinase gene (a 

hormone-inducible gene) 

pEpREβgeo β-galactosidase-neomycin-resistance reporter 

plasmid 

PGE2 prostaglandin E2 

P-gp P-glycoprotein, the efflux transporter encoded by 

MDR 

PHA phytohemagglutinin

PHEN o-phenanthroline (an iron chelator) 

PI propidium iodide 

PI3K phosphatidylinositol 3-kinase 

PK proteinase K 

PLAP placental alkaline phosphatase 

PLC/PR/5 cells a human hepatocellular carcinoma cell line 

PMA phorbol 12-myristate 13-acetate 

PMN polymorphonuclear neutrophils (or PMNs) 

C-14 DRAFT—DO NOT CITE OR QUOTE
PMs peritoneal macrophages 

PNA peptide nucleic acid 

ppb parts per billion 

P-PKB phosphorylated protein kinase B 

ppm parts per million 

PQ paraquat (a generator of O2

–

) 

PR progesterone receptor 

PRCC primary renal cortical cell 

PSH protein thiol 

p-STAT3 phosphorylated-STAT3 

pt pretreatment 

PTEN phosphatase and tensin homolog (mutated in 

multiple advanced cancers 1) 

p-XSC 1,4-phenylenebis(methylene)selenocyanate 

R-3T3 cells Ras-transformed NIH 3T3 cells, a mouse fibroblast 

cell line 

Rac a subfamily of the Rho family of GTPases, which are 

small (~21 kDa) signaling G proteins (more 

specifically GTPases). 

RACs rapidly adhering cells; epidermal cells with the 

highest proliferative potential and with properties of 

stem cells 

Raf a proto-oncogene 

RAGE receptor for advanced glycation end products 

RANKL receptor activator of NFκB ligand 

RAPD-PCR random(ly) amplified polymorphic DNA polymerase 

chain reaction 

Ras a name of a proto-oncogene 

RAW264.7 

cells 

a mouse macrophage cell line (another source 

described it as mouse macrophage-like cells) 

RBC red blood cell, erythrocyte 

RFU relative fluorescence units (units of ROS) 

RHMVE cells rat heart microvessel endothelial cells 

RI replicative index 

RKO cells a human colorectal carcinoma cell line that expresses 

wild-type p53 proteins 

ROCK Rho/kinase, and effector molecule of RhoA 

RNA ribonucleic acid 

RNS reactive nitrogen species 

ROS reactive oxygen species 

RPMI-8226 

cells 

a human myeloma cell line 

RT-PCR reverse transcription-polymerase chain reaction 

RWPE-1 cells human prostate epithelial cell line 

SA sodium arsenite 

SACs slowly adhering cells; epidermal cell fraction that 

contains cells undergoing terminal differentiation, 

with little ability to form colonies 

C-15 DRAFT—DO NOT CITE OR QUOTE
SAH S-adenosylhomocysteine 

SAM S-adenosylmethionine 

SCC squamous cell carcinoma 

SCE sister chromatid exchange 

SCGE single cell gel electrophoresis (assay) 

Se selenium 

SE standard error of the mean 

SEM scanning electron microscopy 

Se-Met selenomethionine 

Ser serine, an amino acid 

SF sodium formate, an •OH radical scavenger 

SFN sulforaphanem, an activator of transcription factor 

Nrf2, which plays a critical role in metabolism and 

excretion of xenobiotics 

SHE cells Syrian hamster ovary cells 

SIK cells spontaneously immortalized human keratinocytes (or 

epidermal cells) 

siRNA small interfering RNA (ribonucleic acid) 

SLC30A1 gene symbol for the zinc transporter, solute carrier 

family 30, member 1 

SMART somatic mutation and recombination test 

SMC cells human bladder smooth muscle cells 

SOCS suppressors of cytokine signaling 

SOD superoxide dismutase (an antioxidant to O2•

–

) 

SP shock protein 

SRB assay sulforhodamine B colorimetric assay 

Src first oncogene discovered, the transforming protein 

of the chicken retrovirus, Rous sarcoma virus 

SSB single strand break (in DNA) 

STAT signal transducer and activator of transcription 

StRE site stress response element recognition site 

SU5416 inhibitor of VEGF receptor-2 kinase 

SVEC4-10 cells a C3H/HeN mouse vascular endothelium cell line 

(also called immortalized mouse endothelial cell 

line) 

SV-HUC-1 cells an SV40 large T-transformed human urothelial cell 

line (non-tumor cells, derived from urethra, 

immortalized) 

SV-40 simian virus 40 

SW13 cells a human adrenal carcinoma cell line 

SW480 cells a colorectal adenocarcinoma cell line derived from a 

Caucasian male that has two base-pair substitution 

mutations in the p53 gene 

SY-5Y cells a human neuroblastoma cell line 

T3 thyroid hormone triiodothyronine 

T4 thyroid hormone thyroxine 

T47D cells a human mammary adenocarcinoma cell line 

TAM tamoxifen 

C-16 DRAFT—DO NOT CITE OR QUOTE
TAT tyrosine aminotransferase 

TBARS thiobarbituric acid reactive substances (a measure of 

tissue lipid peroxidation) 

tBHQ t-butylhydroquinone 

TCDD 2,3,7,8-tetrachlorodibenzo-p-dioxin 

TF theaflavin 

Tg.AC strain of transgenic mice that contains the fetal betaglobin promoter fused to the v-Ha-ras structural gene 

(with mutations at codons 12 and 59) and linked to a 

simian virus 40 polyadenylation/splice sequence 

TGF transforming growth factor 

THP-1 + 

A23187 cells 

a human dendritic cell line; THP-1 cells acquire the 

characteristics of dendritic cells in the presence of 

the calcium ionophore A23187 

TIG-112 cells human normal skin diploid cells 

TIMP-1 tissue inhibitor of metalloproteinase-1 

Tiron 4,5-dihydroxy-m-benzenedisulfonic acid, disodium 

salt 

TK6 cells human lymphoblastoid cells 

TM tail moment 

TMAVO trimethylarsine oxide 

TM3 cells immortalized Leydig cells derived from normal 

mouse testis 

TNF-α tumor necrosis factor α (an inflammatory cytokine) 

TPA 12-O-tetradecanoylphorbol-13-acetate 

TR9-7 cells a spontaneously immortalized human fibroblast cell 

line, derived from a Li-Fraumeni patient, and 

subsequently stably transfected with a tetracyclineregulated p53 expression vector 

TRAIL TNF-related apoptosis-inducing ligand 

TRAIL-R TRAIL receptor 

TRAP tartrate resistant acid phosphatase (RAW264.7 cells 

can undergo osteoclast differentiation, which is 

accompanied by an increase in the number of 

multinucleate cells expressing TRAP) 

TRF terminal restriction fragment 

TRL 1215 cells nontumorigenic adhesive rat epithelial liver cells 

originally derived from the liver of 10-day-old Fisher 

F344 rats 

Trolox® 6-hydroxy-2,5,7,8- tetramethylchroman-2-carboxylic 

acid 

Trx thioredoxin 

TrxR thioredoxin reductase 

TrxR1 cytosolic thioredoxin reductase 

Trx1 cytoplasmic thioredoxin-1 

Trx2 mitochondrial thioredoxin-2 

TUNEL assay terminal deoxynucleotidyl transferase-mediated 

deoxyuridine nick-end labeling assay 

C-17 DRAFT—DO NOT CITE OR QUOTE
U0126 inhibitor of MEK1/2, which are ERK upstream 

kinases (structurally unrelated to PD98059) 

U118MG cells a human glioblastoma cell line, also called U118MG 

(ATCC HTB-15) cells 

U266 cells a human multiple myeloma cell line 

U937 cells a human leukemic monocyte lymphoma cell line 

(also described as a human promonocytic cell line or 

as a human myeloid leukemia cell line) 

U-937 cells human diffuse histiocytic lymphoma cells, perhaps 

the same as U937 cells 

U-2OS cells a human osteogenic sarcoma cell line 

Ub ubiquitin 

UROtsa cells an SV40-immortalized human urothelium cell line 

UV ultraviolet radiation 

UVA ultraviolet radiation A 

UVB ultraviolet radiation B 

UVC ultraviolet radiation C 

V79 cells a cell line derived from lung fibroblasts of a male 

Chinese hamster 

VEGF vascular endothelial growth factor or vascular 

endothelial cell growth factor 

VEGFR1 a vascular endothelial cell growth factor receptor 

(flt-1) 

VEGFR2 a vascular endothelial cell growth factor receptor 

(Flk-1, KDR) 

V-FITC V-fluorescein isothiocyanate 

VH16 human primary fibroblasts 

vs. versus 

VSMC vascular smooth muscle cells 

W138 a human diploid lung fibroblast cell line 

wk week(s) 

wt wild-type 

WM9 cells a human melanoma cell line 

WRL-68 a human hepatic cell line 

WT-1 Wilm’s tumor protein-1 

XIAP X-linked inhibitor of apoptosis protein, an 

antiapoptotic protein controlled by NF-κB 

XPA (B or F) xeroderma pigmentosum, complementation group A 

(B or F) 

XRS X-ray sensitive 

XTT 2,3-bis[2-methyloxy-4-nitro-5-sulfophenyl]-2Htetrazolium-5-carboxanilide 

YC-1 a small molecule inhibitor of HIF signaling 

ypt locus xanthine-guanine phosphoribosyltransferase locus 

Z-DEVD-FMK benzyloxycarbonyl-L-Asp-Glu-Val-Aspfluoromethyl ketone, a caspase 3 inhibitor 

ZPP zinc protoporphyrin 

C-18 DRAFT—DO NOT CITE OR QUOTE
Z-VAD-FMK Z-Val-Ala-DL-Asp-fluoromethylketone, a general 

caspase inhibitor 

α7-nAChR α7-nicotinic acetylcholine receptor 

α-Toc α-tocopherol, an antioxidant 

γGCS γ-glutamylcysteine synthetase 

γH2A.X phosphorylated histone variant H2A.X that is 

indicative of DNA double strand breaks 

ρ0 cells AL hybrid cells made highly deficient in 

mitochondrial DNA by long-term treatment with 

ditercalinium 

Table C-1. In vivo human studies related to possible modes of action of arsenic in the 

development of cancer 

Topic(s) 

Population 

Sampled 

Information on Exposure 

Levels and Durations and 

on Biomarkers Results Reference

Aberrant Gene or Protein Expression 

Effect of 

inorganic arsenic 

exposure from 

DW on 

concentration of 

RAGE protein in 

sputum 

People in Ajo 

(high dose) 

and Tucson 

(low dose), 

Arizona, 

USA 

Compared subjects from 

Ajo (∼20 ppb of arsenic in 

DW) with subjects from 

Tucson (∼5 ppb of arsenic 

in DW). They also 

determined total inorganic 

arsenic concentrations in 

urine in individuals. 

No difference was seen in concentration of RAGE 

protein in sputum between cities. Since there was 

much overlap of total inorganic arsenic 

concentrations in urine in individuals in those cities, 

a comparison was also made using inorganic arsenic

levels in urine. The regression analysis yielded a 

significant negative association between urinary 

total inorganic arsenic concentrations and RAGE 

concentrations in sputum. Thus inorganic arsenic 

exposure caused ⇓ in RAGE level as was seen in 

mice. 

Lantz et al., 

2007 

Effect of 

inorganic arsenic 

exposure from 

DW on serum 

levels of 

extracellular 

domain of EGFR 

(i.e., EGFR 

ECD) 

Araihazar 

area of 

Bangladesh 

Estimates of inorganic 

arsenic exposure level were 

based on well water arsenic 

(ranged from 0.1 to 768 

ppb), urinary arsenic, and 

cumulative arsenic index. 

Such estimates and EGFR 

ECD protein levels were 

compared in 574 people. 

Found significant positive correlation between 

EGFR ECD protein levels in serum and all of these 

measures of inorganic arsenic exposure, with the 

association being strongest among individuals with 

As-induced skin lesions. 

Li et al., 

2007 

Effect of 

inorganic arsenic 

exposure from 

DW on levels of 

TGF-α in 

bladder 

urothelial cells 

(BUC) 

3 towns in 

central 

Mexico 

Estimates of inorganic 

arsenic exposure level were 

based on levels of different 

metabolites of arsenic in 

urine from 72 women who 

used drinking water that 

contained 2–378 ppb As. 

Found significant positive correlation between TGFα protein levels in exfoliated BUC and each of 6 

arsenic species present in urine. Women from areas 

with high arsenic exposures had significantly higher 

TGF-α protein levels in BUC than those from areas 

of low arsenic exposure. BUC cells from people 

with As-induced skin lesions contained significantly 

more TGF-α. 

Valenzuela 

et al., 2007

C-19 DRAFT—DO NOT CITE OR QUOTE
Topic(s) 

Population 

Sampled 

Information on Exposure 

Levels and Durations and 

on Biomarkers Results Reference

Microarraybased gene 

expression study 

comparing 

groups with and 

without arsenical 

skin lesions, 

both of which 

were exposed to 

inorganic arsenic 

in DW but to 

different extents 

Bangladesh Compared subjects with 

cutaneous signs of 

arsenicism (mean of 

343±258 ppb of arsenic in 

DW) with asymptomatic 

individuals (mean of 40±50 

ppb of arsenic in DW in one 

set, and 95±91 ppb in 

another). 

Looked at expression of ∼22,000 transcripts in RNA 

from peripheral blood lymphocytes. When the 

comparison was restricted to female never-smokers, 

312 differentially expressed genes were identified 

between those with and without As-induced skin 

lesions, with all of them being down-regulated in the 

skin-lesion group. Signal transduction through the 

IL-1 receptor was identified as a significant pathway 

of differentially expressed genes between the 

arsenical skin lesion (n = 11) and nonlesion (n = 2) 

groups. It discriminated between the 2 groups. 

Argos et al., 

2006 

Comparison of 

expression of 

several genes 

between patients 

with As-related 

urothelial cancer 

and non-Asrelated urothelial 

cancer 

Taiwan, 

patients with 

urothelial 

cancer 

All 33 patients with arsenicrelated urothelial cancer had 

been living in the arseniasisendemic area of southwest 

Taiwan, where people had 

drunk the As-contaminated 

artesian well water for at 

least 10 years. They were 

compared with 25 patients 

who had nonarsenic-related 

urothelial cancer. 

Comparisons were made of protein expression of 

GST-π, p53, Bcl-2, and c-Fos by Western blotting of

tumor tissues. A significantly higher proportion of 

the patients with the arsenic-induced cancer had the 

proteins present for Bcl-2 (33/33 vs. 19/25) and for 

c-Fos (30/33 vs 16/25), suggesting that upregulation of these 2 oncoproteins may play 

important roles in arsenic-mediated urothelial 

carcinogenesis. Cellular GSH content was downregulated in both types of tumors, but to a greater 

extent in the arsenic-induced ones. 

Hour et al., 

2006 

Comparison of 

expression of 

several integrins 

between people 

with arsenicrelated keratosis 

and people with 

normal skin 

Taiwan, 

patients with 

arsenical 

keratosis 

All 25 arsenical keratosis 

patients were from 

arseniasis-endemic areas of 

southwest Taiwan, where 

water is contaminated by 

high concentrations of 

inorganic arsenic. Control 

specimens were obtained 

from the non-sun-exposed 

skin of 8 age-comparable 

patients who did not live in 

the endemic areas. 

Immunohistochemical staining patterns of integrin 

β1, α2β1, and α3β1 were observed. The various 

patterns of staining among the patients in 

comparison to the controls showed decreased 

expression of all 3 integrins in both arsenical 

keratosis and in perilesional skin. None showed the 

normal expression pattern of all 3 integrins. 

However, there was no association with the 

occurrence of basal cell carcinoma or squamous cell 

carcinoma and the expression pattern of any of the 3 

integrins. 

Lee et al., 

2006b 

Apoptosis 

Possible 

association of 

specific p53 

polymorphisms 

with arsenicrelated keratosis 

in individuals 

exposed to 

arsenic in DW 

West Bengal, 

India 

Compared 177 arsenicexposed subjects with 

keratosis (mean of 177 ppb 

of arsenic in DW) with 189 

arsenic-exposed subjects 

without such skin lesions 

(mean of 180 ppb of arsenic 

in DW), and looked for 

association of keratosis with 

3 specific p53 

polymorphisms. Used 

arsenic concentration 

comparisons in DW, urine, 

nails, and hair. 

Homozygotes for alleles at 2 of the polymorphisms 

were significantly over represented in the 

individuals with keratosis. Results suggest that 

individuals carrying the arginine homozygous 

genotype at codon 72 and/or the no duplication 

homozygous genotype at intron 3 are at higher risk 

for the development of arsenic-induced keratosis. In 

both cases the OR was 2.086 and the 95% CI did not 

overlap 1. Urinary excretion of arsenic was slightly 

lower (NSE) in the group with keratosis suggesting 

higher retention of arsenic in the body, which was 

reflected in significantly higher arsenic content in 

nails and hair. 

De 

Chaudhuri 

et al., 2006

C-20 DRAFT—DO NOT CITE OR QUOTE
Topic(s) 

Population 

Sampled 

Information on Exposure 

Levels and Durations and 

on Biomarkers Results Reference

Chromosomal Aberrations and/or Genetic Instability 

Nested casecontrol study/ 

CAs and/or 

SCEs as 

biomarkers for 

the prediction of 

cancer 

development 

Blackfootendemic area 

in Taiwan 

Looked at CAs and SCEs in 

lymphocytes from venous 

blood samples 

Chromosome-type CAs, but not chromatid-type CAs 

or SCEs, were significantly higher in the cases than 

in the controls. The cancer risk OR for subjects 

with >0 chromosome-type breaks was 5.0 (95% CI = 

1.09–22.82). The OR became even higher with 

more refinements. Thus chromosome-type CAs (but 

not chromatid-type CAs or SCEs) can serve as 

useful biomarkers for prediction of cancer 

development. 

Liou et al., 

1999 

Induction of MN West Bengal, 

India 

Compared subjects with 

cutaneous signs of 

arsenicism (368 ppb of 

arsenic in DW) with 

asymptomatic individuals 

(5.5 ppb of arsenic in DW). 

 Also used arsenic 

concentration comparisons 

in urine, nails, and hair. 

In the exposed group, the frequencies of MN per 

1,000 cells were highly elevated over those of the 

control group (# per 1000 cells): 5.15 vs 0.77 in the 

oral mucosa, 5.74 vs 0.56 in urothelial cells, and 

6.39 vs. 0.53 in peripheral lymphocytes, 

respectively. 

Basu et al., 

2002 

Induction of MN 

and CAs 

(relationship to 

presence of 

arsenicism and 

GST 

polymorphisms) 

West Bengal, 

India 

Compared arsenic-exposed 

subjects with cutaneous 

signs of arsenicism (mean 

of 242 ppb of arsenic in 

DW), arsenic-exposed 

subjects without cutaneous 

signs of arsenicism (mean 

of 202 ppb of arsenic in 

DW), and arsenicunexposed subjects (mean 

of 7.2 ppb of arsenic in 

DW), and looked for 

association of effects with 

different GSTT1 and 

GSTM1 genotypes. Used 

arsenic concentration 

comparisons in DW, urine, 

nails, and hair. 

arsenic-exposed groups showed ⇑ in MN in the 

lymphocytes, oral mucosa, and urothelial cells and ⇑

in frequencies of CAs in lymphocytes. The 

symptomatic (i.e., with cutaneous signs of 

arsenicism) exposed group had more of all types of 

cytogenetic damage than the asymptomatic exposed 

group, and the asymptomatic exposed group had 

more of all types of cytogenetic damage than the 

unexposed group. Asymptomatic and symptomatic 

exposed groups demonstrated rather similar 

concentrations in the urine, nails, and hair. 

Individuals carrying at least one GSTM1-positive 

allele had a significantly higher risk of developing 

cutaneous signs of arsenicism. 

Ghosh et al., 

2006 

C-21 DRAFT—DO NOT CITE OR QUOTE
Topic(s) 

Population 

Sampled 

Information on Exposure 

Levels and Durations and 

on Biomarkers Results Reference

Association 

between a 

polymorphism in 

ERCC2 codon 

751 that 

probably 

improves NER 

and (1) the 

incidence of 

CAs and (2) the 

presence of 

inorganic 

arsenic-induced 

hyperkeratosis 

West Bengal, 

India 

Comparisons were made 

between people with 

hyperkeratosis and 

individuals with no skin 

lesions who were drinking 

similar inorganic arseniccontaminated water. 

Groups with and without 

hyperkeratosis had means of

195 and 185 ppb arsenic in 

DW, respectively, with 

large standard deviations. 

The polymorphism resulted from a base pair change 

from A to C at codon 751 that resulted in an amino 

acid substitution from lysine to glutamine. The A/A 

(i.e., Lys/Lys) genotype was compared with the A/C 

and C/C genotypes combined. In the study 

population, the allele frequencies of A and C were 

0.4 and 0.6, respectively. A/A individuals were 

shown to be at significantly higher risk of having 

hyperkeratosis and also to have a higher frequency 

of CAs in their lymphocytes, as follows: A/A 

individuals were over-represented among 

individuals with inorganic arsenic-induced 

hyperkeratosis (OR = 4.77, 95% CI = 2.75–8.23). 

There was a higher percentage of cells with CAs in 

A/A individuals than in (A/C and C/C) individuals: 

43% more in those exposed to inorganic arsenic but 

not having hyperkeratosis, 18% more in those 

exposed to inorganic arsenic and having 

hyperkeratosis, and 31% in both groups combined. 

Also, CAs were significantly more frequent in 

inorganic arsenic-exposed people with 

hyperkeratosis. 

Banerjee et 

al., 2007 

Induction of MN 

(bladder cells) 

Chile, men Compared subjects having 

high (average 600 ppb of 

arsenic in DW) and low 

(average 15 ppb of arsenic 

in DW) exposures. 

Used a fluorescent version of exfoliated bladder cell 

MN assay to identify presence or absence of whole 

chromosomes within MN. Significant ⇑ in 

induction of MN by arsenic was found, and 

chromosome breakage appeared to be its major 

cause. 4th highest quintile of exposure groups gave 

the highest response, but there was a significant ⇑ in 

each of quintiles 2–4. Highest (5th) quintile (729–

1894 ppb) returned to baseline MN level, perhaps 

because of cytostasis or cytotoxicity. 

Moore et 

al., 1997b 

Induction of 

SCEs 

(Fowler’s 

solution, 

(lymphocytes) 

6 patients 

treated with 

Fowler’s 

solution who 

developed 

arsenicism 

and biopsyproven skin 

cancers 

Nothing is known about 

doses; duration of treatment 

with inorganic arsenic 

ranged from 4 months to 27 

years, and in most cases 

treatment ceased decades 

before this cytogenetic 

analysis. 

Patients treated with Fowler’s solution had mean of 

14.0 SCE/mitotic cell, while 44 normal controls had 

mean of 5.8 SCEs/mitotic cell. They saw no 

difference in chromosome breakage between the 

groups. 

Burgdorf et 

al., 1977 

Induction of CAs 

and SCEs 

(Fowler’s 

solution, 

lymphocytes) 

8 psoriasis 

patients 

treated with 

Fowler’s 

solution were 

compared 

with 8 

psoriasis 

patients not 

treated with 

inorganic 

arsenic (7 

men in each 

group) 

The total doses of inorganic 

arsenic were from 300 to 

1200 mg for the 7 with 

known doses. Inorganic 

arsenic treatments ceased 

many years before this 

study. Comparisons were 

also made to 30 apparently 

healthy untreated males. 

 ⇑ in frequency of chromosomal breaks (i.e., 

chromatid and chromosome aberrations together) in 

psoriasis patients with inorganic arsenic treatment 

and an even bigger ⇑ in comparison to healthy 

untreated males. Inorganic arsenic treatment had 

NSE on SCE frequency. 

Nordenson 

et al., 1979

C-22 DRAFT—DO NOT CITE OR QUOTE
Topic(s) 

Population 

Sampled 

Information on Exposure 

Levels and Durations and 

on Biomarkers Results Reference

Induction of CAs 

(mostly airborne 

inorganic 

arsenic, 

lymphocytes) 

9 workers 

exposed to 

inorganic 

arsenic at 

smelter in 

northern 

Sweden 

Little information was 

presented except to say that 

there was no obvious 

relationship between 

exposure and CA 

frequencies. 

87 CAs/819 mitotic cells among smelter workers 

and 13 CAs/1012 mitotic cells in controls. Person 

with highest CA frequency had also been exposed to 

lead and selenium. 

Beckman et 

al., 1977 

Induction of CAs 

and SCEs 

(lymphocytes) 

People in 

Fallon 

(exposed) 

and Reno 

(control), 

Nevada, USA 

The exposed sample of 104 

used DW containing >50 

ppb arsenic (mostly >100 

ppb As) for at least 5 years 

and the control sample of 86 

used DW containing <50 

ppb arsenic (and often much 

less) for the same period. 

No hint of any effect of inorganic arsenic on CA or 

SCE frequencies was seen, even though there was 

an approximately 9-fold difference in the mean 

inorganic arsenic concentrations in DW between the 

2 groups. 

Vig et al., 

1984 

Induction of CAs 

and MN 

(lymphocytes for 

CAs) 

People in 

Santa Ana 

(high dose) 

and Nazareno 

(control), 

Mexico 

The high-dose group used 

DW containing a mean of 

408 ppb As, and the control 

(i.e., low dose) group used 

DW containing a mean of 

30 ppb As. They also 

considered arsenic 

concentrations in urine and 

blood and concentrations of 

arsenic metabolites. 

inorganic arsenic caused ⇑ in CA (chromatid and 

isochromatid deletions) frequency in lymphocytes 

and an ⇑ in MN frequency in exfoliated epithelial 

cells obtained from the oral mucosa and from urine 

samples. MN frequencies were higher in people 

with skin lesions, by a factor of 2.3 in oral mucosa 

and 4.3 in urothelial cells. There was also much 

more induction of MN in males than in females for 

both cell types. 

Gonsebatt et 

al., 1997 

Induction of MN People in 

Nevada, 

USA, with 

either very 

high or low 

exposure to 

inorganic 

arsenic in 

DW 

The high-dose group of 18 

used DW containing a mean 

of 1312 ppb As, and the 

individually matched 

control (i.e., low-dose) 

group used DW containing 

a mean of 16 ppb As. They 

also considered the 

concentration of inorganic 

arsenic and methylated 

metabolites in urine. 

inorganic arsenic caused ⇑ in MN frequency in 

exfoliated bladder cells to 1.8x (90% CI, 1.06x to 

2.99x). The MN frequency was positively 

correlated with the urinary concentration of 

inorganic arsenic plus methylated metabolites. In 

contrast, inorganic arsenic had no effect on the MN 

frequency in epithelial cells obtained from the 

buccal mucosa. 

Warner et 

al., 1994 

Induction of MN 

(chromosome 

breakage 

and/or 

aneuploidy) 

People in 

Nevada, 

USA, with 

either very 

high or low 

exposure to 

inorganic 

arsenic in 

DW 

The high dose group of 18 

used DW containing a mean 

of 1,312 ppb As, and the 

individually matched 

control (i.e., low-dose) 

group used DW containing 

a mean of 16 ppb As. They 

also considered the 

concentration of inorganic 

arsenic and methylated 

metabolites in urine. 

The exfoliated cell MN assay using FISH with a 

centromeric probe was applied: frequencies of MN 

containing acentric fragments (MN-) and those 

containing whole chromosomes (MN+) both showed 

⇑, to 1.65x (statistically significant) and 1.37x 

(p = 0.15), respectively, suggesting that arsenic has 

clastogenic and possibly even aneuploidogenic 

properties. Effect was stronger in males than in 

females. Thus, in males the increases were 2.06x (p

= 0.07) and 1.86x (p = 0.08), respectively. The 

frequencies of MN- and MN+ were both positively 

correlated with urinary arsenic and its metabolites.

Moore et 

al., 1996 

C-23 DRAFT—DO NOT CITE OR QUOTE
Topic(s) 

Population 

Sampled 

Information on Exposure 

Levels and Durations and 

on Biomarkers Results Reference

Induction of CAs 

and SCEs 

(lymphocytes for 

CAs) 

People in 

Santa Ana 

(high dose) 

and Nuevo 

Leon (lowexposure 

group), 

Mexico 

The high-exposure group of 

11 used DW containing a 

mean of 390 ppb arsenic 

(98% as AsV), and the lowexposure group of 13 used 

DW that ranged from 19 to 

60 ppb As. They also 

considered arsenic 

concentrations in urine. 

Examined the levels of CAs and SCEs in peripheral 

blood lymphocytes. There were no skin lesions in 

the control subjects, but 4 of the 11 exposed subjects 

had cutaneous signs of arsenicism. The percentages 

of total CAs and SCEs were similar in the two 

groups; however, the finding of a higher point 

estimate of the frequency of complex CAs (i.e., 

dicentrics, rings, and translocations) in the highexposure group was considered suggestive of a 

possible effect of inorganic arsenic. Average 

generation times (AGT) of lymphocytes were 19.02 

hr in the laboratory control, 19.90 hr in the lowexposure group, and 28.70 hr in the high-exposure 

group, with this difference being statistically 

significant. It was suggested that this effect might 

suggest an impairment of the immune response. 

OstroskyWegman et 

al., 1991 

DNA Damage 

DNA damage 

detected using 

SCGE (comet) 

assay 

(lymphocytes) 

New 

Hampshire, 

USA 

Low-exposure (control) 

group had < 0.7 ppb arsenic 

in DW and high-exposure 

group had ≥13 (nd up to 93) 

ppb arsenic in DW. 

Using the SCGE (comet) assay, baseline DNA 

damage as well as the capacity of the lymphocytes 

from these subjects to repair damage induced by an 

in vitro challenge with 2-AAAF were assessed. 2-

AAAF was used because its adducts are primarily 

repaired through the NER pathway. High-exposure 

group had ⇑ in baseline damage (i.e., damage 

resulting from inorganic arsenic exposure only) to 

∼1.8x. Two hours after identical in vitro 2-AAAF 

treatments to cells from both high- and lowinorganic arsenic-exposure groups, cells from both 

groups showed big ⇑ in DNA damage, with 

inorganic arsenic-high-exposure group showing 

∼15% more DNA damage than control (NSE). After 

4-hr repair period, significantly more DNA damage 

remained in lymphocytes from individuals in highexposure group (∼1.54x), and essentially all 2-

AAAF-induced DNA damage had been repaired in 

the control cells. 

Andrew et 

al., 2006 

C-24 DRAFT—DO NOT CITE OR QUOTE
Topic(s) 

Population 

Sampled 

Information on Exposure 

Levels and Durations and 

on Biomarkers Results Reference

Oxidative DNA 

damage 

Residents of 

Bayingnorme

n 

(Ba Men), 

Inner 

Mongolia, 

China, with 

exposures to 

a wide range 

of 

concentration

s of inorganic 

arsenic in 

DW 

Concentrations of inorganic 

arsenic in DW were 

determined for individuals; 

∼70% of subjects used DW 

containing nondetectable 

arsenic through 200 ppb As, 

with the rest using DW 

containing up to ∼830 ppb 

As, with all exposures 

lasting at least 5 years. 

They also determined 

arsenic levels in toenail 

clippings as a biomarker of 

exposure. 

OGG1 expression was used as an indicator of 

oxidative stress. OGG1 was selected because it 

codes for the enzyme 8-oxoguanine DNA 

glycosylase, which is involved in base excision 

repair of 8-oxoguanine residues that result from 

oxidative damage to DNA. The study found that 

OGG1 expression was closely linked to the levels of

arsenic in the drinking water and toenails of the 

individuals examined, indicating a link between 

ROS damage to DNA and arsenic exposure in 

humans. There were no significant differences in 

arsenic-induced expression due to gender, smoking, 

or age. OGG1 expression was also associated with 

skin hyperkeratosis in males, and there was a hint of 

the same in females. There was an inverse 

relationship between OGG1 expression and Se 

levels in toenails, indicating possible protective 

effects of Se against arsenic-induced oxidative 

stress. The maximal OGG1 response appeared to be 

at a water arsenic concentration of 149 ppb, after 

which its expression leveled off and was gradually 

down-regulated. 

Mo et al., 

2006 

Correlation of 

urinary 

8-OHdG with 

urinary metal 

elements and 

many other 

substances 

6 regions of 

Japan 

128 men and 120 women 

from Japan who did not live 

within several kilometers of 

large chemical factories or 

garbage incinerator facilities

The association was investigated between urinary 

concentrations of 8-OHdG and urinary 

concentrations of As, Al, Cr, Ni, Hg, Zn, Cu, Pb (in 

ng of element/mg creatinine) as well as with 5 

antioxidants and several other substances. 

Statistically significant positive correlations were 

found with As, Cr, and Ni and not with any other 

substances. (The correlation coefficient for arsenic 

was 0.25.) It thus appears that exposure of healthy 

people to these 3 metals under normal conditions 

may increase oxidative DNA damage. Urinary 

arsenic levels ranged from ∼0 to ∼230 ng As/mg 

creatinine. 

Kimura et 

al., 2006 

Levels of urinary 

8-OHdG 

following acute 

arsenic 

poisoning 

incident 

Wakayama, 

Japan 

63 people were poisoned by 

eating food contaminated 

with arsenic trioxide, with 4 

dying about 12 hours after 

eating. Doses in individuals 

were poorly known. 

Some interesting observations were made among the 

52 poisoned individuals who were tested for 8-

OHdG levels in urine following acute poisoning. 

After 30 days, urinary 8-OHdG levels were 

maximal, with a mean for all patients of ∼1.5x the 

normal level in Japanese people. By 180 days after 

the poisoning, levels returned to normal. About 

37% of the patients never showed any increase in 

the concentration of 8-OHdG in urine. The same 

paper documented a significant increase in urinary 

8-OHdG in people from Outer Mongolia, China, 

who drank water contaminated with about 130 ppb 

As. The increase in urinary 8-OHdG disappeared 

after they drank “low-arsenic” water for 1 year. 

Yamauchi et 

al., 2004 

C-25 DRAFT—DO NOT CITE OR QUOTE
Topic(s) 

Population 

Sampled 

Information on Exposure 

Levels and Durations and 

on Biomarkers Results Reference

DNA damage in 

peripheral blood 

lymphocytes 

detected by 

alkaline comet 

assay 

West Bengal, 

India 

Low-exposure (control) 

group had 7.7±0.5 ppb 

arsenic in DW. Highexposure group had 247±19

ppb arsenic in DW. They 

also considered arsenic 

levels in nails, hair, and 

urine. 

Used SCGE (comet) assay with DNA denaturation 

at pH >13. High-exposure group had significantly 

more DNA damage in lymphocytes. Assay was also 

combined with FPG enzyme digestion to 

demonstrate that arsenic induced oxidative base 

damage. 

Basu et al., 

2005 

DNA Repair Inhibition or Stimulation 

Decreased DNA 

repair 

(lymphocytes) 

New 

Hampshire, 

USA, and the 

towns of 

Esperanza 

and Colonia 

Allende, 

Mexico 

Subjects from New 

Hampshire were from an 

ongoing epidemiological 

study of bladder cancer. 

Low-exposure (control) 

group had 0.007–5.3 ppb 

(average of 0.7) arsenic in 

DW. High-exposure group 

had 10.4–74.7 ppb (average 

of 32) arsenic in DW. 

Subjects from Colonia 

Allende had 5.5 ± 0.20 ppb 

arsenic in DW, and those 

from Esperanza had 43.3 ± 

8.4 ppb arsenic in DW. 

Comparisons between the 

low (i.e., control) and high 

exposure groups used either 

5 (for protein analysis) or 6 

ppb (for mRNA analysis) as 

the dividing line between 

low and high. They also 

considered arsenic levels in 

urine and toenails. 

Earlier work suggested that inorganic arsenic 

exposure was correlated with decreased expression 

of the nucleotide excision repair genes ERCC1, 

XPB, and XPF. This study focused on ERCC1 and, 

besides considering gene expression, it looked at 

both the protein and DNA repair functional levels 

(for latter, see part of study described in DNA 

damage part of this table). Inorganic arsenic 

exposure was associated with ⇓ in expression of 

ERCC1 in isolated lymphocytes both at the mRNA 

and protein levels. In combined data, there was a ⇓

to ∼0.71x, with a significant effect in New 

Hampshire alone and in the total data. Estimate of 

effect in Mexico was ⇓ to ∼0.84x (NSE). ⇓ in 

ERCC1 protein level to ∼0.28x was also 

demonstrated in high-exposure group in New 

Hampshire. 

Andrew et 

al., 2006 

Decreased DNA 

repair 

(lymphocytes) 

New 

Hampshire, 

USA 

Subjects from New 

Hampshire were from an 

ongoing epidemiological 

study of bladder cancer. 

They compared levels of 

expression of 5 NER genes 

in 6 cases and 10 controls 

with the inorganic arsenic 

levels in their DW and in 

their toenails. 

Toenail and DW arsenic levels were inversely 

correlated with expression of ERCC1, XPB, and 

XPF. The arsenic levels in toenails were more 

strongly negatively correlated with the changes in 

gene expression that the arsenic concentrations in 

DW. In these comparisons, expression levels were 

compared between high and low levels of arsenic 

exposure. By definition a high level in DW was 

anything ≥2 ppb arsenic and a high level in toenails 

was anything ≥2 ppm As. 

Andrew et 

al., 2003 

Effects Related to Oxidative Stress (ROS) 

Evidence of 

oxidative 

damage to DNA 

caused by As, 

but not 

necessarily from 

inorganic arsenic 

in DW 

Taichung 

County, 

Taiwan 

School children ages 10–12, 

with attention being given 

to possibility of oxidative 

stress to DNA from 

exposure to environmental 

pollutants As, Cr, and Ni. 

No information given on 

concentrations of inorganic 

arsenic in DW. 

When oxidative damage occurs in DNA, the excised 

8-OHdG adduct is excreted into urine and is a 

biomarker of oxidative stress. In this cross-sectional 

study, subjects with higher urinary arsenic tended to 

have more (19% more, p = 0.09) urinary 8-OHdG 

than those with lower urinary As. Cr was also on 

the borderline of showing a significant ⇑; when both

arsenic and Cr were at a higher level in urine, there 

was a highly significant ⇑ of 39% in urinary 8-

OHdG. 

Wong et al., 

2005 

C-26 DRAFT—DO NOT CITE OR QUOTE
Topic(s) 

Population 

Sampled 

Information on Exposure 

Levels and Durations and 

on Biomarkers Results Reference

Evidence of 

oxidative 

damage to DNA 

caused by 

inorganic arsenic 

in DW, and the 

relationship of 

that DNA 

damage to 

arsenic-related 

skin lesions 

2 villages in 

Wuyuan 

prefecture in 

Hetao Plain, 

Inner 

Mongolia, 

China 

Adults from low-arsenicexposure village (mean of 

5.3 ppb arsenic in DW) and 

from high-arsenic-exposure 

village (mean of 158.3 ppb 

arsenic in DW). They also 

measured levels of MMA 

and DMA in the urine, and 

the levels of those 

metabolites in the urine in 

the high-arsenic-exposure 

village were at least 17x 

higher than they were in the 

low-arsenic-exposure 

village. 

When oxidative damage occurs in DNA, the excised 

8-OHdG adduct is excreted into urine and is a 

biomarker of oxidative stress. For subjects without 

arsenic-related skin lesions in the high-arsenicexposure village, there was no statistically 

significant correlation found between inorganic 

arsenic, MMA, or DMA and 8-OHdG adducts in the 

urine. However, for subjects with arsenic-related 

skin lesions in the high-arsenic-exposure village, 

there was a significant positive correlation in urine 

between levels of each those 3 types of arsenic and 

the level of 8-OHdG adducts. There was so much 

individual variability that overall there was no 

excess of 8-OHdG adducts in urine in the high-As 

village compared to the low-As village, even if 

restricted to only those with arsenic-related lesions. 

An overall comparison did, however, show an 

excess of 8-OHdG adducts in urine in the higharsenic village among those who had been drinking 

well water for more than 12 years when compared to 

those who had been drinking it for less than 12 

years, regardless of whether they had skin lesions. 

Fujino et al., 

2005 

Gene Mutations 

Induction of 

HGPRT 

mutations 

(isolated 

mononuclear 

cells) 

People in 

Santa Ana 

(high dose) 

and Nuevo 

Leon (lowexposure 

group), 

Mexico 

The high-exposure group of 

11 used DW containing a 

mean of 390 ppb arsenic 

(98% as AsV), and the lowexposure group of 13 used 

DW that ranged from 19 to 

60 ppb As. They also 

considered arsenic 

concentrations in urine. 

 The frequency of monocytes resistant to 

thioguanine (i.e., mutants) was twice as high in the 

high-exposure group, but this suggestion of an ⇑

was not statistically significant. 

OstroskyWegman et 

al., 1991 

Hypermethylation of DNA

Extent of 

methylation of 

the promoters of 

tumor suppressor 

genes p53 and 

p16 (relationship 

to arsenicosis) 

West Bengal, 

India 

Criteria for diagnosis of 

arsenicosis included a 

history of using DW 

containing > 50 ppb arsenic 

for more than 6 months and 

presence of skin lesions 

characteristic of chronic 

arsenic toxicity. 

Comparisons were made to 

individuals without skin 

lesions or those who live in 

non-arsenic affected areas.

Methylation of the p53 promoter region of DNA 

obtained from blood samples was studied using 

methyl-sensitive restriction endonuclease HPAII. 

Methylation of p16 was studied using bisulfite 

modification of the DNA followed by methyl 

sensitive PCR. Hypermethylation of the promoter 

region of both genes was observed in people with 

arsenicosis, and there was a positive dose-response 

for this hypermethylation. There was a strong 

suggestion that the promoter region of p53 is 

hypermethylated in individuals with arsenic-induced 

skin cancer in comparison to those with skin cancer 

unrelated to inorganic arsenic exposure, but this 

comparison did not reach statistical significance (p < 

0.2) 

Chanda et 

al., 2006 

C-27 DRAFT—DO NOT CITE OR QUOTE
Topic(s) 

Population 

Sampled 

Information on Exposure 

Levels and Durations and 

on Biomarkers Results Reference

Relationship 

between 

epigenetic 

silencing of 3 

tumor suppressor 

genes and 

exposure to 

arsenic in 

patients with 

bladder cancer 

New 

Hampshire 

patients with 

bladder 

cancer 

Estimated internal dose of 

arsenic exposure from 

toenail measurements. 18 

patients with bladder cancer 

had ≥0.26 ppm arsenic in 

their toenails, and 318 had 

<0.26 ppm arsenic in their 

toenails. 0.26 ppm was the 

95th percentile of arsenic 

exposure in this population.

They applied methylation-specific PCR. A 

significant relationship was identified between 

arsenic exposure and promoter methylation of 

RASSF1A and PRSS3 but not p16INK4A. The 

promoter hypermethylation was associated with 

advanced tumor state. Thus the data provide a 

potential link between arsenic exposure and 

epigenetic alterations in patients with bladder 

cancer. 

Marsit et al., 

2006 

Hypomethylation of DNA 

Extent of 

methylation of 

the promoters of 

tumor suppressor 

genes p53 and 

p16 

(relationship to 

arsenicosis) 

West Bengal, 

India 

Criteria for diagnosis of 

arsenicosis included a 

history of using DW 

containing >50 ppb arsenic 

for more than 6 months and 

presence of skin lesions 

characteristic of chronic 

arsenic toxicity. 

Comparisons were made to 

individuals without skin 

lesions or those who live in 

non-arsenic-affected areas.

Methylation of the p53 promoter region of DNA 

obtained from blood samples was studied using 

methyl-sensitive restriction endonuclease HPAII. 

Methylation of p16 was studied using bisulfite 

modification of the DNA followed by methyl 

sensitive PCR. In the study described in the row 

above, a small number of people with high arsenic 

exposure showed hypomethylation. 

Hypomethylation occurs only after prolonged 

arsenic exposure at higher doses. The authors noted 

that cases of both hyper- and hypomethylation 

leading to silencing of tumor suppressor genes and 

activation of oncogenes have been documented in 

different types of cancers. 

Chanda et 

al., 2006 

Immune System Response 

Association 

between 

biomarkers of 

lung 

inflammation 

and level of 

inorganic arsenic 

exposure from 

DW 

Ajo and 

Tucson, 

Arizona, 

USA 

40 subjects were from the 

high-arsenic-exposure town 

of Ajo (20.3 ± 3.7 ppb 

arsenic in DW), and 33 

were from the low-arsenicexposure town of Tucson 

(4.0 ± 2.3 ppb arsenic in 

DW). They also measured 

inorganic arsenic levels in 

urine, with the mean in Ajo 

being 2.6 times higher than 

that in Tucson. 

Proteolytic enzymes including MMP-2 and MMP-9 

are continually secreted in the airways, and their 

activities are regulated mainly by TIMP-1. The lognormalized concentrations of these 3 substances in 

induced sputum were not significantly different 

between these towns. However, after adjusting for 

town, asthma, diabetes, urinary MMA/inorganic 

arsenic, and smoking history, total urinary arsenic 

was negatively associated with MMP-2 and TIMP-1 

levels and positively associated with the ratio of 

MMP-2/TIMP-1 and MMP-9/TIMP-1. This 

suggests an association between changes in sensitive 

markers of lung inflammation and levels of 

inorganic arsenic of only ∼20 ppb in DW. It appears 

that inorganic arsenic levels in DW and the extent of

arsenic methylation may be important predictors of 

lung metalloproteinase concentrations. 

Josyula et 

al., 2006 

Signal Transduction 

C-28 DRAFT—DO NOT CITE OR QUOTE
Topic(s) 

Population 

Sampled 

Information on Exposure 

Levels and Durations and 

on Biomarkers Results Reference

Association 

between TGF-α

and/or EGFR 

and cumulative 

inorganic arsenic 

exposure from 

DW 

Taiwan 150 persons were selected 

from the arseniasis-endemic 

area in Ilan county in 

northeast Taiwan, with 30 

each coming from those 

having residential well 

water in the following 

ranges (all in ppb of As): 0–

50, >50–100, >100–300, 

>300–600, and >600. Of 

them, the 66 who agreed to 

participate in medical 

surveillance were compared 

to 35 healthy individuals 

with no known arsenic 

exposure. Those with 

arsenic exposure were 

further divided on the basis 

of cumulative arsenic dose 

(i.e., total DW inorganic 

arsenic levels × years of 

exposure) into the following 

2 groups: 32 with ≤6 ppmyears and 34 with >6 ppmyears. 

Blood plasma was collected and tested for TGF-α

and EGFR levels using immunoassays. No 

relationship between arsenic exposure and EGFR 

protein levels was found. However, both levels of 

plasma TGF-α and the proportion of individuals 

with TGF-α overexpression were significantly 

higher in the high cumulative arsenic exposure 

group than in the control group. After adjusting for 

age and sex, there was also a significant linear trend 

between cumulative arsenic exposure and the 

prevalence of plasma TGF-α overexpression. 

Hsu et al., 

2006 

1 

2 

C-29 DRAFT—DO NOT CITE OR QUOTE
Table C-2. In vivo experiments on laboratory animals related to possible modes of action 

of arsenic in the development of cancer—only oral exposures 

Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

Reference 

Aberrant Gene or Protein Expression 

Lung/mouse 

(C57BL/6) AsIII SA 

* 5.8, 28.8 ppm 

(DW) 

8 wk 28.8 ppm mRNA levels were determined in a 

microchip analysis and validated using 

real-time PCR: 29 genes were upregulated and 42 down-regulated. 15% 

of affected genes were associated with 

inflammation, including HSP27 and 

HSP90 (both up-regulated). Numerous 

extracellular matrix genes were affected, 

as reflected in phenotypic lung changes 

related to the organization of elastin and 

collagen. Protein levels were 

determined by a Western blot assay: ⇑

for 4 genes, ⇓ for 14. No correlation 

was found between altered genes and 

altered proteins. 

Lantz and 

Hays, 2006

Lung/mouse 

(C57B16, male, 

21 days of age at 

start of exposure) 

AsIII SA 

10, 50 ppb (DW) 

Note in ppb! 

4 wk 50 ppb Protein levels in BALF determined by 

proteomic analysis: it is unclear if 

samples from 10 ppb were examined. ⇑

after dose of 50 ppb: peroxiredoxin-6 

and enolase 1. ⇓ after dose of 50: GSTomega-1, RAGE, contraspin, and 

apolipoproteins A-I and A-IV. 

Lantz et al., 

2007 

Urothelial 

cells/rat 

(F344, female) 

DMAV

sodium 

cacodyl

atetrihydrat

e 

* 0.35, 1.4, 14, 35 

ppm (DW) 

28 days 0.35 ppm Microarray analysis using chip for 4395 

genes: gene trees generated by 

hierarchical clustering of the 510 

responsive genes showed marked 

changes at every dose in comparison to 

the dose (or dose of 0) below it. Of the 

510 genes, 38% were up-regulated and 

9% down-regulated by ≥3-fold. Most 

affected genes related to the functional 

categories of apoptosis, cell cycle 

regulation, adhesion, signal transduction, 

stress response, or growth factor and 

hormone receptors. There was a change 

in the types of genes affected at the 

different doses, particularly when 

comparing the higher 2 doses (both 

cytotoxic) with the 2 non-cytotoxic 

doses. The dose with most genes 

affected was 14 ppm. At the lowest 

dose, 503 genes (11%) were 

significantly affected, of which 41% 

were up-regulated and 6% downregulated by ≥3-fold. 

Sen et al., 

2005 

C-30 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Liver cells/mouse 

(129/SvJ) AsIII SA 

45 ppm (DW) 48 wk 45 ppm Microarray analysis, RT-PCR, and 

immunochemistry: big ⇑ in ER-α and 

cyclin D1 mRNA and protein levels. Of 

588 genes tested in microarray analysis, 

30 showed aberrant expression, 

including steroid-related genes, 

cytokines, apoptosis-related genes, cell 

cycle-related genes, and genes encoding 

for growth factors and hormone 

receptors. 

Chen et al., 

2004b 

Brain, liver, 

placenta/mouse 

(only pregnant 

ICR females 

drank the water) 

AsIII SA * 4.35 mg/kg 

(gavage) 

1 time only 

on each of 

9 days, 

gestation 

days 7 to 16

4.35 mg/kg Activities of selenoenzymes GPx, TrxR, 

DI-I, DI-II, and DI-III in maternal tissues 

when examined on gestation day 17 of 

their litter: 

liver: ⇓ of DI-I to ∼0.61x when Seadequate diet; 

liver: ⇓ of DI-I to ∼0.30x when Sedeficient diet; 

all other comparisons were either slight 

or NSE. 

Miyazaki et 

al., 2005 

Fetal brain, fetal 

liver/mouse 

(only pregnant 

ICR females 

drank the water) 

AsIII SA * 4.35 mg/kg 

(gavage) 

1 time only 

on each of 

9 days, 

gestation 

days 7 to 16

4.35 mg/kg Activities of selenoenzymes GPx, TrxR, 

DI-I, DI-II, and DI-III in fetal tissues 

when examined on gestation day 17: 

brain: ⇑ of DI-II to ∼4.1x when Sedeficient diet; 

liver: ⇓ of TrxR to ∼0.78x when Sedeficient diet; 

all other comparisons were either slight 

or NSE. 

Miyazaki et 

al., 2005 

Liver/mouse 

(BALB/c, male) 

AsIII SA 50, 100, 150 

μg/mouse/day for 

6 days/week 

(gavage) 

3, 6, 9, 12 

months 50 

at 9 and 12 

months 

only 

Levels of TNF-α and IL-6: 

NSE on either one at any dose in first 6 

months. 

At 9 months: 

TNF-α: 50, ∼1.2x; 100, ∼1.2x; 150, 

∼1.4x; 

IL-6: 50, ∼2.0x; 100, ∼2.5x; 150, ∼2.7x.

At 12 months: 

TNF-α: 50, ∼1.9x; 100, ∼2.3x; 150, 

∼3.0x; 

IL-6: 50, ∼2.8x; 100, ∼5.7x; 150, ∼9.5x.

Das et al., 

2005 

Liver/mouse 

(BALB/c, male) 

AsIII SA 50, 100, 150 

μg/mouse/day for 

6 days/week 

(gavage) 

3, 6, 9, 12 

months 50 

at 9 and 12 

months 

Concentration of total collagen: 

At 3 months: NSE at all doses, but hint 

of ⇑ at 100 (∼1.2x) and 150 (∼1.3x). 

At 6 months: NSE at all doses, but hint 

of ⇑ at 100 (∼1.3x) and 150 (∼1.4x). 

At 9 months: 50, ∼1.3x; 100, ∼1.4x; 150, 

∼1.6x. 

At 12 months: 50, ∼1.5x; 100, ∼1.9x; 

150, ∼2.1x. 

Das et al., 

2005 

C-31 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Liver, kidney, 

and lung/mouse 

(B6C3F1, 

female) 

AsIII SA 

AsV 

sodium 

arsenate 

DMAV 

In all cases, 

dissolved in water 

and administered 

once by gavage: 

* 9.58 mg/kg for 

all 

* 9.58 mg/kg for 

all 

*391 mg/kg for all 

One dose 

for all 

9.58 mg/kg

9.58 mg/kg

None 

HMOX-1 activity 6 hr after the single 

oral dose was administered by gavage: 

Liver: AsIII, ∼7.5x; AsV, ∼5.1x, DMAV, 

∼0.96x (NSE). 

Kidney: AsIII, ∼7.6x; AsV, ∼3.2x, 

DMAV, ∼1.03x (NSE). 

Lung: none of the arsenicals induced 

HMOX-1 activity. 

Kenyon et 

al., 2005b 

Liver and 

kidney/mouse 

(B6C3F1, 

female) 

AsIII SA In all cases, 

dissolved in water 

and administered 

once by gavage: 

* 0.0749, 0.749, 

2.25, 7.49 mg/kg 

for both 

One dose 2.25 mg/kg 

in liver 

7.49 mg/kg 

in kidney 

HMOX-1 activity in liver 6 hr after the 

single oral dose was administered by 

gavage: 

at 2 lower doses, NSE; 2.25, ∼2.5x; 

7.49, ∼7.5x. 

HMOX-1 activity in kidney 4 hr after 

the single oral dose was administered by 

gavage: 

at 3 lower doses, NSE; 7.49, ∼3.5x. 

Kenyon et 

al., 2005b 

HCC cells/mouse 

(only pregnant 

C3H females 

drank the water, 

male offspring) 

AsIII SA 42.5, 85 ppm 

(DW); 

report did not state 

if molecular 

analysis was done 

on one or both of 

these doses 

combined 

10 days, 

gestation 

days 

 8 to 18 

42.5 or 85 

ppm 

Comparisons of gene expression based 

on microarray analysis, with 

comparisons being made between HCC 

tumors from offspring of exposed dams 

and normal liver tissue from offspring of

unexposed dams: ⇑ of AFP to ∼18.5x; ⇓

of IGF-1 to 0.78x; 

⇑ of IGFBP-1 to ∼8.8x; ⇑ of CK8 to 

∼2.4x; 

⇑ of CK18 to ∼8.8x; ⇓ of BHMT to 

∼0.33x. 

Waalkes et 

al., 2004b 

HCC cells/mouse 

(only pregnant 

C3H females 

drank the water, 

male offspring) 

AsIII SA 42.5, 85 ppm 

(DW); 

report did not state 

if molecular 

analysis was done 

on one or both of 

these doses 

combined 

10 days, 

gestation 

days 

 8 to 18 

42.5 or 85 

ppm 

Comparisons of gene expression based 

on microarray analysis, with 

comparisons being made between HCC 

tumors of offspring of exposed dams and 

spontaneous liver tumors of offspring of 

unexposed dams: 

⇑ of AFP to ∼6.2x; NSE for IGF-1; 

⇑ of IGFBP-1 to ∼1.7x; ⇑ of CK8 to 

∼1.4x; 

⇑ of CK18 to ∼5.8x; ⇓ of BHMT to 

∼0.36x. 

Waalkes et 

al., 2004b 

HCC cells/mouse 

(only pregnant 

C3H females 

drank the water, 

male offspring) 

AsIII SA 42.5, 85 ppm 

(DW); 

report did not state 

if molecular 

analysis was done 

on one or both of 

these doses 

combined 

10 days, 

gestation 

days 

 8 to 18 

42.5 or 85 

ppm 

Comparisons of gene expression based 

on microarray analysis, with 

comparisons being made between HCC 

tumors and normal-appearing liver cells 

of offspring of exposed dams: 

⇑ of AFP to ∼7.4x; ⇓ of IGF-1 to 

∼0.68x; ⇑ of IGFBP-1 to ∼3.7x; 

⇑ of CK8 to ∼1.3x; ⇑ of CK18 to ∼7.0 x; 

⇓ of BHMT to ∼0.32x. 

Waalkes et 

al., 2004b 

C-32 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Liver cells/mouse 

(only pregnant 

C3H females 

drank the water, 

male offspring) 

AsIII SA 42.5, 85 ppm 

(DW); 

report did not state 

if molecular 

analysis was done 

on one or both of 

these doses 

combined 

10 days, 

gestation 

days 8 to 18

42.5 or 85 

ppm 

Comparisons of gene expression based 

on microarray analysis, with 

comparisons being made between 

normal-appearing liver cells in both 

offspring of exposed dams and 

unexposed dams: 

⇑ of AFP to ∼2.5x; ⇑ of IGF-1 to ∼1.1x; 

⇑ of IGFBP-1 to ∼2.4x; ⇑ of CK8 to 

∼1.8x; 

NSE for CK18 or BHMT. 

Waalkes et 

al., 2004b 

HCC cells/mouse 

(only pregnant 

C3H females 

drank the water, 

male offspring) 

AsIII SA 42.5, 85 ppm 

(DW); 

report did not state 

if molecular 

analysis was done 

on one or both of 

these doses 

combined 

10 days, 

gestation 

days 8 to 18

42.5 or 85 

ppm 

In general, the results in the 4 previous 

rows were confirmed by real-time RTPCR analysis. Aberrant gene expression 

was also noted in the microarray 

analysis for numerous other genes 

including those related to cell 

proliferation, oncogenes, stress, and 

metabolism. 

Waalkes et 

al., 2004b 

Uterus/mouse 

(only pregnant 

CD1 females 

drank the water, 

female offspring 

only) 

AsIII SA 85 ppm (DW) 10 days, 

gestation 

days 8 to 18

85 ppm if 

also treated 

with DES 

or TAM 

Expression (by real-time RT-PCR) of 

various estrogen-related genes in uteri at 

11 days of age: ⇑ in ER-α to 1.56x. 

Some female offspring were also 

exposed by subcutaneous injection to 

DES on the first 5 days after birth. DES 

alone or (inorganic arsenic + DES) did 

not significantly increase ER-α

expression. Inorganic arsenic alone did 

not ⇑ expression of pS2, CYP2A4, or 

lactoferrin. However, DES alone caused 

large ⇑ in expression of all 3 of these 

genes, and (inorganic arsenic + DES) 

caused a further ⇑ to 3.0 times, 7.8 

times, and 1.47 times that of DES alone, 

respectively. These and other results 

showed that inorganic arsenic acts with 

estrogens to enhance production of 

urogenital cancers in female mice. 

Waalkes et 

al., 2006a 

HCC cells/mouse 

(only pregnant 

C3H females 

drank the water, 

male offspring) 

AsIII SA 42.5, 85 ppm 

(DW) 

10 days, 

gestation 

days 8 to 18

42.5 ppm Comparisons of gene expression based 

on microarray analysis of RNA, with 

comparisons being made between HCC 

tumors from offspring of exposed dams 

and normal (i.e., non-tumorous) liver 

tissue from offspring of unexposed 

dams: 13.7% of 600 genes were 

significantly up-regulated or downregulated. Only 7.7% of those 600 

genes were similarly affected in 

spontaneous tumors in liver tissue from 

offspring of unexposed dams. The 600 

genes studied included oncogenes and 

genes associated with cell proliferation, 

differentiation, or otherwise related to 

cancer outcome. 

Liu et al., 

2004 

C-33 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

HCC cells/mouse 

(only pregnant 

C3H females 

drank the water, 

male offspring) 

AsIII SA 42.5, 85 ppm 

(DW) 

10 days, 

gestation 

days 

 8 to 18 

42.5 ppm Comparisons of gene expression based 

on microarray analysis of RNA (see row 

above): up-regulated genes included 

oncogene/tumor suppressor genes and 

genes related to cell proliferation, 

hormone receptors, metabolism, stress, 

apoptosis, growth arrest, and DNA 

damage. A wide array of different types 

of genes was also down-regulated. 

Real-time RT-PCR analysis largely 

confirmed the findings of microarray 

analysis. The higher dose tended to 

yield more significant differences, but a 

positive dose-response was not always 

evident. 

Liu et al., 

2004 

Liver cells/mouse 

(only pregnant 

C3H females 

drank the water, 

male offspring) 

AsIII SA 42.5, 85 ppm 

(DW) 

10 days, 

gestation 

days 

 8 to 18 

42.5 ppm Comparisons of gene expression based 

on microarray analysis of RNA, with 

comparisons being made between nontumorous liver cells in both offspring of 

exposed dams and unexposed dams: 

~10% of 600 genes were significantly 

up-regulated or down-regulated. The 

600 genes studied included oncogenes 

and genes associated with cell 

proliferation, differentiation, or 

otherwise related to cancer outcome. 

Liu et al., 

2004 

HCC cells/mouse 

(only pregnant 

C3H females 

drank the water, 

male offspring) 

AsIII SA 85 ppm (DW) 10 days, 

gestation 

days 

 8 to 18 

85 ppm Comparisons of gene expression based 

on microarray analysis of RNA, with 

comparisons being made between HCC 

tumors from offspring of exposed dams 

and normal liver tissue from offspring of

unexposed dams: statistically significant 

alterations in expression were seen for 

2,540 genes. Real-time RT-PCR and 

Western blot analyses of selected genes 

or proteins showed >90% concordance. 

Affected gene expression included 

oncogenes, HCC biomarkers, cell 

proliferation-related genes, stress 

proteins, insulin-like growth factors, 

estrogen-linked genes, and genes 

involved in cell-cell communication. 

Liu et al., 

2006c 

Liver cells/mouse 

 (only pregnant 

C3H females 

drank the water, 

male offspring) 

AsIII SA 85 ppm (DW) 10 days, 

gestation 

days 

 8 to 18 

85 ppm Comparisons of gene expression based 

on microarray analysis of RNA, with 

comparisons being made between nontumorous liver cells in both offspring of 

exposed dams and unexposed dams: 

statistically significant alterations in 

expression were seen for 2010 genes. 

See row above for results in HCC cells.

Liu et al., 

2006c 

C-34 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Fetal 

livers/mouse 

 (only pregnant 

C3H females 

drank the water, 

male offspring) 

AsIII SA 85 ppm (DW) 10 days, 

gestation 

days 

 8 to 18 

85 ppm Comparisons of gene expression based 

on microarray analysis of RNA from 

fetal livers just after treatment ended, 

with confirmation by real-time RT-PCR: 

alteration of expression of 187 genes (of 

22,000 in array) was demonstrated, with 

∼25% of them being related to either 

estrogen signaling or steroid 

metabolism—some with dramatic (here 

meaning >>100x) up-regulation. 

Expression of some genes important in 

methionine metabolism was suppressed.

Liu et al., 

2007a 

Livers of 

newborn 

males/mouse 

 (only pregnant 

C3H females 

drank the water) 

AsIII SA 85 ppm (DW) 10 days, 

gestation 

days 

 8 to 18 

85 ppm Comparisons of gene expression based 

on microarray analysis of RNA from 

livers of newborn males, with 

confirmation by real-time RT-PCR: 

among 600 genes examined, marked 

alteration of expression of 40 genes was 

demonstrated. Affected genes included 

genes related to stress (several in the 

glutathione system), metabolism (several 

cytochrome P450 genes), growth factors 

(several insulin-like growth factor 

genes), and hormone metabolism. 

Xie et al., 

2007 

Liver and liver 

tumors/mouse 

 (only pregnant 

C3H females 

drank the water) 

AsIII SA 85 ppm (DW) 10 days, 

gestation 

days 

 8 to 18 

Samples from adults of both sexes were tested. 

Some had had a post-weaning 21-wk dermal 

treatment with TPA. Comparisons with the TPAtreatment-only control were made regarding gene 

expression based on microarray analysis of RNA, 

with confirmation by real-time RT-PCR. Alteration 

of expression of ~70 genes (of 588 in array) was 

demonstrated. There were generally similar gene 

alteration patterns in both sexes both in inorganic 

arsenic/TPA exposed non-tumorous livers and in 

inorganic arsenic/TPA-induced tumors. The tumors 

themselves generally had more pronounced 

alterations in gene expression than the normal tissue 

around them. In general, the inorganic arsenic/TPAinduced gene expression alterations were similar to 

those seen in liver samples from male mice exposed 

only to inorganic arsenic in utero. It should be noted 

that while in utero inorganic arsenic-exposed males 

developed hepatocellular carcinoma without the TPA 

treatment, in utero inorganic arsenic-exposed 

females only developed those tumors after TPA 

treatment. 

Liu et al., 

2006b 

C-35 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Bladder and 

liver/rat 

(Fisher 344, 

male) 

MMAV

DMAV

TMAVO 

* 121 ppm (DW)c 

* 109 ppm (DW)c 

* 110 ppm (DW)c

20 days 

for all 

Changes in gene expression observed in cDNA 

microarray analysis: MMAV caused ⇑ for 20 genes 

and ⇓ for 1 gene in liver and ⇑ for 5 genes and ⇓ for 

5 genes in bladder. DMAV caused ⇑ for 15 genes 

and ⇓ for 2 genes in liver and ⇑ for 13 genes and ⇓

for 4 genes in bladder. TMAVO caused ⇑ for 23 

genes and ⇓ for 2 genes in liver and ⇑ for 6 genes 

and ⇓ for 7 genes in bladder. Groups of genes 

affected by all arsenicals in both tissues included 

genes related to xenobiotic metabolism, growth 

factor receptors, and energy metabolism. In the 

liver, phase I and II metabolizing enzymes were 

induced to a lesser extent by MMAV and DMAV than 

by TMAVO, and in the bladder they were induced 

only by DMAV. CYP1A1 was only overexpressed 

by TMAVO and in liver. 

Kinoshita et 

al., 2007a 

Lung/mice 

(C57BL/6J 

Ogg1+/+ wt mice 

and Ogg1-/- 

knockout mice, 

both sexes, 14 

weeks old at start 

of treatment) 

DMAV * 115.3 ppm (DW) 4 weeks Results of an Affymetrix oligonucleotide microarray 

analysis: a change in expression was found for 165 

and 182 genes in male and female knockout Ogg1-/-

mice, respectively. In DMAV-treated knockout 

Ogg1-/- mice, there was marked induction of Pola1, 

CYP7B1, Ndfua3, MMP-13 and other genes specific 

to cell proliferation, cell signaling, and xenobiotic 

metabolism. 

Kinoshita et 

al., 2007b 

Liver cells/rat 

(Sprague 

Dawley) 

AsV as 

Na2HAs

O4• 

7H2O 

* 0.24, 2.4, 24 

ppm (DW) 

1 month Various Determination of mRNA levels of 

cancer-related genes using real-time 

quantitative RT-PCR: 

⇑ cyclin D1 at 2.4 only; ⇑ p27Kip1 at 2.4 

only; 

⇑ ILK at 0.24 only; ⇓ PTEN at 0.24 

only; ⇓ β-catenin at 24 only. 

Cui et al., 

2004b 

Liver cells/rat 

(Sprague 

Dawley) 

AsV as 

Na2HAs

O4• 

7H2O 

* 0.24, 2.4, 24 

ppm (DW) 

4 months Various Determination of mRNA levels of 

cancer-related genes using real-time 

quantitative RT-PCR: ⇑ cyclin D1 at 24 

only; ⇑ ILK at 0.24 and 2.4; 

⇑ p27Kip1 at 0.24 only; ⇓ PTEN at all 

doses; 

⇓ β-catenin at all doses. Results were 

confirmed by protein levels. 

(Histograms were assumed to be correct 

for ILK and p27; the descriptions for 

them appear to have become reversed in 

the text.) 

Cui et al., 

2004b 

Skin/mouse 

(homozygous, 

strain Tg.AC, 

female) 

AsIII SA 200 ppm (DW) 4, 10 wk 200 ppm Kinetics of mRNA expression based on 

RT-PCR: 

EGFR and TNF-α: ⇑ by week 10; 

GM-CSF and TGF-α: ⇑ by week 4; big 

⇑ by week 10; c-myc: NSE. 

Germolec et 

al., 1998 

C-36 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Heart/mouse 

(C57BL/6NCr, 

male) 

AsIII SA 0.05, 0.25, 0.5 

ppm 

(DW) 

5, 10, 20 

wk 

Various mRNA levels determined by RT-PCR: 

VEGF165: ⇑ at 0.25 and 0.5 at wk 5; ⇑ at 

all doses at wk 10; NSE at wk 20; 

VEGFR1: NSE at wk 5 and 10; big ⇑ at 

0.25 and big ⇓ at 0.5 at wk 20; 

VEGFR2: ⇑ at 0.5 at wk 5; NSE at wk 

10; ⇑ at 0.05 and 0.25 and 

⇓ at 0.5 at wk 20; 

PAI-1: NSE at wk 5; ⇑ at 0.5 at wk 10; 

⇑ at 0.25 and 0.5 at wk 20; 

Endothelin-1: NSE at wk 5 and 10; ⇑ at 

0.05 and big ⇑ at 0.25 at wk 20; 

MMP-9: NSE at wk 5; ⇑ at 0.5 at wk 10; 

⇑ at all doses at wk 20. 

Soucy et al., 

2005 

Blood 

plasma/mouse 

(C57BL/6NCr, 

male) 

AsIII SA 0.5 ppm (DW) 20 wk 0.5 ppm PAI-1 protein levels determined by 

ELISA assay: 

⇑ to ∼1.33x. 

Soucy et al., 

2005 

Tumors that 

developed from 

B16-F10 (GFP) 

melanoma tumor 

cells/ mice 

(NCr nu/nu, 

male) 

AsIII SA 10, 50, 200 ppb 

(DW) 

9 wk 10 ppb Protein levels in primary melanoma 

tumors determined by 

immunohistochemical staining: 

⇑ HIF-1α at 10 and 50 only; ⇑ VEGF at 

10 and 200 only. ⇑ for both proteins 

was just locally around tumor blood 

vessels. Western blot assay of whole 

tumor lysates showed no more than 

barely detectable ⇑ of HIF-1α at any 

dose. 

Kamat et al., 

2005 

Apoptosis 

Bladder and 

liver/rat 

(Fisher 344, 

male) 

MMAV

DMAV

TMAVO 

* 121 ppm (DW)c 

* 109 ppm (DW)c 

* 110 ppm (DW)c 

5, 10, 15, 

and 20 days 

for all 

None 

Various 

Various 

Apoptosis labeling index based on an 

immunochemistry method of staining 

single-stranded DNA: 

Bladder: ⇑ on day 20 to ∼1.5x for 

DMAV only; 

Liver: ⇑ on day 20 to ∼3.3x for TMAVO 

only. 

Kinoshita et 

al., 2007a 

Liver/rat 

(Wistar, male) AsIII SA 

* 0.03, 1.4, 2.9 

ppm (DW) 

60 days 1.4 Induced apoptosis (experimental – 

control) based on TUNEL assay with PI 

staining and analysis using fluorescence 

microscopy: 

0.03, 5.0; (NSE); 1.4, 14.9; 2.9, 22.3; 

these results were consistent with DNA 

ladder formation found by agarose gel 

electrophoresis for which there was an ⇑

at 1.4; bigger ⇑ at 2.9. There was also 

microscopic evidence of cell death by 

necrosis. 

Bashir et al., 

2006a 

C-37 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Kidney, 

leukocytes and 

liver/rat 

(albino Wistar, 

male) 

AsIII SA 

* 57.7 ppm (DW) 30 days 57.7 ppm TNF-α levels: kidney, ⇑ ∼1.6x; leuko., ⇑

∼2.2x; liver, ⇑ ∼1.9x; 

caspase-3 levels: kidney, ⇑ ∼3.2x; 

leuko., ⇑ ∼2.8x; liver, ⇑ ∼3.5x; effects 

on both endpoints in all 3 tissues were 

markedly reduced by co-treatment with 

AA and/or α-Toc. 

Ramanathan 

et al., 2005 

Kidney, 

leukocytes and 

liver/rat 

(albino Wistar, 

male) 

AsIII SA 

* 57.7 ppm (DW) 30 days 57.7 ppm Induced percentage of DNA that was 

fragmented 

(experimental – control): 

kidney, ⇑ ∼17.6%; leuko., ⇑ ∼17.4%; 

liver, ⇑ ∼21.8%. 

Induced percentage of TUNEL positive 

cells (experimental – control): 

kidney, ⇑ ∼6.7%; leuko., ⇑ ∼5.1%; liver, 

⇑ ∼8.1%; effects on both endpoints in all 

3 tissues were markedly reduced by cotreatment with AA and/or α-Toc. 

Confirmation of induced apoptosis in 

leukocytes shown by finding typical 

DNA ladders after agarose gel 

electrophoresis; co-treatment with AA 

and/or α-Toc abolished that effect. 

Ramanathan 

et al., 2005 

Splenocytes and 

thymocytes/mous

e 

(C57BL/6, 

female) 

AsV as 

Na2HAs

O4• 

7H2O 

0.5, 5, 50 ppm 

(DW) 

8, 12 wk 50 at 8 wk 

for both 

cell types 

Induced apoptosis (experimental – 

control) determined by TUNEL method:

Splenocytes: 8 wk: 0.14% of cells at 

dose of 50 (or 6.6x); 12 wk: 0.22% of 

cells at dose of 50 (or 5.4x). 

Thymocytes: 8 wk: 0.40% of cells at 

dose of 50 (or 4.0x); 12 wk: 0.28% 

(NSE) of cells at dose of 50 (or 2.5x). 

For both cell types, the data suggested a 

positive dose-response across all doses; 

however, the other results showed much 

variability. 

Stepnik et al., 

2005 

Brain and 

liver/rat 

(Wistar, male) 

AsIII SA 

* 3.6, 6.1, 7.3 

mg/kg 

(gavage, with 

animals being 

killed 24 hr later 

for sample 

collection) 

One dose Various Brain: caspase-3 activity: ⇑ to ∼1.4x 

(NSE) at 3.6, 

to ∼2.0x at 6.1, and to ∼2.6x at 7.3; 

Liver: caspase-3 activity: ⇑ to ∼1.8x at 

3.6, to ∼2.5x at 6.1, and to ∼3.0x at 7.3. 

Both brain and liver: agarose gel 

electrophoresis showed DNA 

“nucleosomal ladder,” suggesting 

induction of apoptosis; results were not 

quantified. Histopathological 

examination also showed evidence of 

cellular necrosis. 

Bashir et al., 

2006b 

C-38 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Cancer Promotion 

Skin/mouse 

(homozygous, 

strain Tg.AC, 

female) 

AsIII SA 200 ppm (DW) 14 wk 200 ppm After low-dose application of TPA on 4 

occasions over 2 weeks starting after 31 

days of inorganic arsenic exposure, there

was a marked ⇑ in the number of skin 

papillomas compared to single 

treatments, whereas no papillomas 

developed in inorganic arsenic-treated 

Tg.AC mice without TPA treatment or 

in FVB/N mice with the combined 

treatment. Injection of neutralizing 

antibodies to GM-CSF after TPA 

application reduced the number of 

papillomas in Tg.AC mice. Inorganic 

arsenic acted like a co-promoter. 

Germolec et 

al., 1998 

Skin/mouse 

(hairless swissbald strain, male) 

AsV 

sodium 

arsenate 

* 11.4 ppm (DW) 25 wk None, but 

11.4 ppm if 

also treated 

with 

DMBA 

PCNA protein levels determined by 

Western blotting: no PCNA was present 

following the inorganic arsenic 

treatment alone, compared to the 

baseline of 22 units of PCNA in the 

control (set equal to x). When mice 

were given 4 DMBA treatments (as an 

initiating carcinogen) during the first 2 

weeks of the inorganic arsenic treatment, 

there was PCNA ⇑ to ∼5.3x. DMBA 

treatment alone caused ⇑ to only 2.9x. 

Mice that were untreated or treated with 

inorganic arsenic alone developed no 

papillomas or skin tumors. DMBA 

treatment alone induced development of 

squamous cell papillomas. Combined 

inorganic arsenic and DMBA treatment 

caused development of welldifferentiated squamous cell carcinomas. 

 Inorganic arsenic acted as a skin tumor 

promoter by promoting abnormal cell 

proliferation. Findings suggest that 

inorganic arsenic is toxic to normal skin 

cells and that preneoplastic cells are 

more resistant to inorganic arsenic. 

Motiwale et 

al., 2005 

Lung/mouse 

(ddY, male) 

DMAV

assumed 

to be 

dimethy

lar-sinic 

acid 

* 217 ppm (DW) 25 wk 217 ppm, 

but only 

following 

4NQO 

treatment 

Some of the mice were subcutaneously 

injected with 10 mg/kg of 4NQO just 

before the 25-wk DMA treatment began. 

 Some of the mice ate only feed 

containing 0.05% of the antioxidant 

EGCG. Number out of 10 mice in each 

group bearing tumors: control, 0; DMA 

alone, 0; 4NQO alone, 7; EGCG alone, 

0; (4NQO + DMA), 10; 

(4NQO + DMA + EGCG), 7. That last 

group had only 0.89 tumor/mouse 

compared to 3.10 tumors/mouse in 

4NQO group and 4.00 tumors/mouse in 

the (4NQO + DMA) group. 

Mizoi et al., 

2005 

C-39 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Cell Cycle Arrest or Reduced Proliferation 

Heart/mouse 

(C57BL/6NCr, 

male) 

AsIII SA 0.5 ppm (DW) 5, 10, 20 

wk 

0.5 ppm at 

20 wk 

Density of microvessels of <12 μm 

diameter using histopathology and a 

digital-imaging subroutine: 

⇓ to ∼0.82x at 20 wk; hint of a ⇓ at 10 

wk. 

Soucy et al., 

2005 

Cell Proliferation Stimulation 

Bladder/rat 

(F344, female) 

DMAV * 54.3 ppm (food) 

(assumes MW of 

chemical used was 

138.0) 

2 wk 54.3 ppm Stimulation of proliferation determined 

by BrdU labeling assay: 

⇑ to 3.9x; co-treatment with DMPS (a 

chelator of trivalent arsenicals) 

completely eliminated the effect. 

Cohen et al., 

2002 

Bladder/rat 

(F344, female) 

DMAV * 54.3 ppm (food) 

(assumes MW of 

chemical used was 

138.0) 

26 wk 54.3 ppm Stimulation of proliferation determined 

by BrdU labeling assay: 

⇑ to 1.6x; co-treatment with DMPS (a 

chelator of trivalent arsenicals) 

completely eliminated the effect. 

Histological examination showed simple 

hyperplasia in 4 of 9 rats, compared to 0 

of 10 rats in control and 1 of 10 rats with 

co-treatment with DMPS. 

Cohen et al., 

2002 

Liver/rat 

(Fischer 344, 

male) 

(they used 

normal-appearing 

tissue) 

TMAVO * 27.5, 110.2 ppm 

(DW) Estimated 

total intakes: 351 

and 1363 mg 

As/rat 

104 wk 110.2 ppm Livers were stained for the analysis of 

PCNA by an immunohistochemical 

method, with the PCNA index being the 

number of positive cells/100 cells: ⇑ in 

PCNA index to 2.0x, thereby suggesting 

that cell proliferation in the normalappearing parenchyma was elevated. 

The point estimate of the index was also 

⇑ at lower dose, but the SE for it was 

large. 

Shen et al., 

2003 

Bladder and 

liver/rat 

(Fisher 344, 

male) 

MMAV

DMAV

TMAVO 

* 121 ppm (DW)c 

* 109 ppm (DW)c 

* 110 ppm (DW)c

5, 10, 15, 

and 20 days 

for all 

None 

Various 

Various 

PCNA labeling index based on an 

immunochemistry method: 

Bladder: ⇑ on day 20 to ∼1.8x for 

DMAV only; 

Liver: ⇑ on day 20 to ∼1.8x for TMAVO 

only. 

Kinoshita et 

al., 2007a 

C-40 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Bladder/mouse 

(only pregnant 

CD1 females 

drank the water, 

male offspring 

only) 

AsIII SA 85 ppm (DW) 10 days, 

gestation 

days 

8 to 18 

85 ppm if 

also treated 

with DES 

or TAM 

Some male offspring were also exposed 

by subcutaneous injection to DES or 

TAM on the first 5 days after birth; all 

male offspring were held for 90 wk 

before examination. Induced (i.e., 

experimental – control) % of mice with 

bladder hyperplasia: inorganic arsenic 

alone, 9% (NSE); DES alone, 12% 

(NSE); TAM alone, 10% (NSE); 

(inorganic arsenic + DES), 45%; 

(inorganic arsenic + TAM), 30%. All 

induced percentages were the same for 

total proliferative lesions, except for 

(inorganic arsenic + TAM), which was 

40%. The lesions induced by inorganic 

arsenic with either DES or TAM 

overexpressed ER-α. 

Waalkes et 

al., 2006b 

Kidney/mouse 

(only pregnant 

CD1 females 

drank the water, 

male offspring 

only) 

AsIII SA 85 ppm (DW) 10 days, 

gestation 

days 

 8 to 18 

85 ppm Some male offspring were also exposed 

by subcutaneous injection to DES or 

TAM on the first 5 days after birth; all 

male offspring were held for 90 weeks 

before examination. Induced (i.e., 

experimental – control) % of mice with 

cystic tubular hyperplasia: inorganic 

arsenic alone, 23%; DES alone, 0%; 

TAM alone, 0%; (inorganic arsenic + 

DES), 24%; (inorganic arsenic + TAM), 

7%. 

Waalkes et 

al., 2006b 

Bladder/mouse 

(only pregnant 

CD1 females 

drank the water, 

female offspring 

only) 

AsIII SA 85 ppm (DW) 10 days, 

gestation 

days 

 8 to 18 

85 ppm if 

also treated 

with DES 

or TAM 

Some female offspring were also 

exposed by subcutaneous injection to 

DES or TAM on the first 5 days after 

birth; all female offspring were held for 

90 wk before examination. Induced 

(i.e., experimental – control) % of mice 

with bladder hyperplasia: inorganic 

arsenic alone, 12% (NSE); DES alone, 

0% (NSE); TAM alone, -3% (NSE); 

(inorganic arsenic + DES), 26%; 

(inorganic arsenic + TAM), 23%. All 

induced percentages were the same for 

total proliferative lesions, except for 

(inorganic arsenic + DES), which was 

35%, and (inorganic arsenic + TAM), 

which was 26%. Unlike in the male 

offspring, inorganic arsenic did not 

induce hyperplasia in kidneys. 

Waalkes et 

al., 2006a 

C-41 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Lung/mice 

(C57BL/6J 

Ogg1+/+ wt mice, 

both sexes, 14 

weeks old at start 

of treatment) 

Lung/mice 

(C57BL/6J Ogg1-

/- knockout mice, 

both sexes, 14 

weeks old at start 

of treatment) 

DMAV * 115.3 ppm (DW) 72 weeks None 

115.3 

PCNA labeling index based on an 

immunochemistry method, x = wt 

control level: 

wt with inorganic arsenic treatment: ⇑ to 

∼3x (NSE). 

Knockout Ogg1-/- without inorganic 

arsenic: ⇑ to ∼6x. 

Knockout Ogg1-/- with inorganic arsenic

treatment: ⇑ to ∼17x. 

Results were confirmed in a study with 

only a 4 week exposure. 

Kinoshita et 

al., 2007b 

Bladder/mouse 

(C57BL/6, 

female) 

AsIII SA * 57.7 ppm (DW) 4 wk 57.7 ppm All experimental mice developed mild 

hyperplasia of the urinary bladder 

epithelium, that being a 3- to 4-fold ⇑ in 

the thickness of the transitional cell 

layer. 

Simeonova et 

al., 2000 

Bladder/mouse 

(C57BL/6, 

female) 

AsIII SA * 57.7 ppm (DW) 16 wk 57.7 ppm ⇑ in PCNA-stained nuclei in the bladder 

epithelium from 2% in control to 31% in 

experimental group, an indication of big 

⇑ in cell proliferation. Similar ⇑ also 

seen at 4 weeks. 

Simeonova et 

al., 2000 

Bladder/mouse 

(C57BL/6, 

female) 

AsIII SA * 11.5, 57.7 ppm 

(DW) 

16 wk 11.5 ppm Also consistent with ⇑ in proliferation: ⇑

in DNA binding of the AP-1 

transcription factor to ∼1.9x and ∼4.7x at

the 2 doses, respectively. At one or both 

doses (not specified): 38% and 76% of 

the bladder cells stained positive for the 

c-jun and c-fos immunoreactive proteins, 

respectively, compared to only 2% in 

control mice. 

Simeonova et 

al., 2000 

Blood 

vessels/chicken 

(Leghorn, 

chorioallantoic 

membranes of 

10-day-old 

chicken embryos) 

AsIII SA 0.00033, 0.001, 

0.0033, 0.01, 

0.033, 0.1, 0.33, 

1.0, 3.3, 10 μM 

24 hr 0.033 μM CAM assay to determine vascularity 

(i.e., blood vessel density): ⇑ to ∼2.2x 

and remained at about that level to dose 

of 1; ⇓ to ∼0.28x at dose of 3.3 and 

remained at about that level to dose of 

10. 

Soucy et al., 

2003 

Matrigel 

implants/mouse 

(C57BL/6NCr, 

male) 

AsIII SA 0.001, 0.005, 0.01, 

 0.05 ppm (DW) 

5 wk 0.001 ppm Blood vessel no. determined in Matrigel 

implants surgically inserted during last 2 

wk of inorganic arsenic treatment: 

probable ⇑ to ∼1.8x at dose of 0.001; 

statistically significant ⇑ to ∼2.4x at the 

higher 3 doses. Implants were 

supplemented with recombinant FGF-2; 

inorganic arsenic-enhanced neovascularization did not occur without FGF-2. 

Data suggest that inorganic arsenic 

potentiates, but does not directly cause, 

neovascularization in Matrigel implants. 

Soucy et al., 

2005 

C-42 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Matrigel 

implants/mouse 

(C57BL/6NCr, 

male) 

AsIII SA 0.05, 0.25, 0.5 

ppm (DW) 

5, 10, 20 

wk 

0.05 ppm 

for each 

duration 

Blood vessel number determined in 

Matrigel implants surgically inserted 

during last 2 wk of inorganic arsenic 

treatment: at 5 wk: ⇑ to ∼2.6x, ∼4.4x, 

and ∼5.5x at the 3 doses in ascending 

order. For each longer duration 

treatment, there was still a strong ⇑ at 

dose of 0.05 but a somewhat diminished 

⇑ at 2 higher doses. 

Soucy et al., 

2005 

Tumors that 

developed from 

B16-F10 (GFP) 

melanoma tumor 

cells/mice 

(NCr nu/nu, 

male) 

AsIII SA 10, 50, 200 ppb 

(DW) 

Note in ppb! 

8 wk 10 ppb Tumor volume and tumor growth rate, 

after implantation of tumor cells (into 

external surface at the base of right ear) 

5 wk after inorganic arsenic treatment 

began: 

Volume: 10, ∼1.4x (NSE); 50, ∼2.2x; 

200, ∼3.0x. 

Rate: 10, ∼1.9x (NSE); 50, ∼2.2x; 200, 

∼3.2x. 

Kamat et al., 

2005 

Tumors that 

developed from 

B16-F10 (GFP) 

melanoma tumor 

cells/mice 

(NCr nu/nu, 

male) 

AsIII SA 10, 50, 200 ppb 

(DW) 

Note in ppb! 

8 wk 10 ppb Mean no. of lung metastases/lobe, after 

implantation of tumor cells (into external 

surface at the base of right ear) 5 wk 

after inorganic arsenic treatment began:

10, ∼1.6x; 50, ∼2.0x; 200, ∼2.0x 

(statistically significant at 10 and 200); 

the metastases were significantly larger 

at the 2 lower doses. 

Kamat et al., 

2005 

Blood 

vessels/chicken 

(Leghorn, 

chorioallantoic 

membranes of 

10-day-old 

chicken embryos) 

AsIII SA 0.33, 10 μM 48 hr 0.33 μM CAM assay to determine vascularity 

(i.e., blood vessel density): ⇑ to ∼1.8x at 

0.33 but big ⇓ at dose of 10. At dose of 

0.33, co-treatment with YC-1 or SU5416 

(inhibitors of HIF and VEGF receptor-2 

kinase) eliminated inorganic arsenic 

effect. 10 μM inorganic arsenic + YC-1 

caused no change from control, but 

inorganic arsenic alone, or in addition to 

SU5416, resulted in ⇓ to ∼0.28x. 

Kamat et al., 

2005 

Skin/mouse 

(homozygous, 

strain Tg.AC, 

female) 

AsIII SA 200 ppm (DW) 10 wk 200 ppm By 10 weeks the skin showed 

hyperkeratosis as well as ⇑ in numbers 

of proliferating cells. A kinetic study 

with samples at weekly intervals 

demonstrated ⇑ in number of BrdUpositive nuclei in skin after 4 weeks and 

number remained elevated through 10 

weeks. 

Germolec et 

al., 1998 

Chromosomal Aberrations and/or Genetic Instability 

Bone marrow/rat 

(Rattus 

norvegicus, 

Charles foster 

strain) 

AsV as 

disodiu

m 

hydroge

n 

arsenate 

* 4.0 mg As/kg bw 

(unspecified route 

of administration) 

15, 21 days 4.0 mg/kg Chromosomal analysis of Giemsastained cells, with few details provided: 

induction of gross CAs for both periods 

of treatment; induction of hyperploidy 

detected as aneuploids for longer 

treatment. 

Datta et al., 

1986 

C-43 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Bone 

marrow/mouse 

(albino Swiss, 

male) 

AsIII SA * 1.44 mg/kg × 4, 

5, and 6 times at 

weekly intervals, 

(gavage) 

Single dose 

each week

1.44 × 4 Significant ⇑ in CA and probably also in 

polyploidy after 4, 5, and 6 gavage 

treatments. CA frequencies were 

significantly higher than control in all 3 

comparisons at 2.5x, 2.7x, and 4.4x, 

respectively. Similar experiments with 7 

and 8 exposures killed the mice. Daily 

treatments by gavage with a black tea 

infusion for one week before every 

inorganic arsenic treatment caused a 

significant reduction in the frequency of 

CAs after 4 and 6 inorganic arsenic 

treatments. 

Patra et al., 

2005 

Bone 

marrow/mouse 

(C57BL/6J/Han, 

female) 

AsV as 

Na2HAs

O4• 

7H2O 

50, 200, 500 

ppb (DW) 

Note in ppb! 

3, 6, 12 

months 

None Half of the mice were maintained on a 

low-Se diet. Mouse erythrocyte MN 

test: inorganic arsenic caused no 

induction of MN in PCEs and no change 

in the PCE:NCE ratio at any dose at any 

interval, with or without the low-Se diet.

Palus et al., 

2006 

Co-carcinogenesis 

Skin/mouse 

(Hairless mice, 

strain Skh1) 

AsIII SA * 0.7, 1.4, 2.9, 5.8 

ppm (DW) 

161 days 

beginning 

at 21 days 

of age 

0.7 ppm Starting 21 days after the AsIII treatments 

began, mice had their dorsal skin 

exposed to 1.0 kJ/m2

 of solar spectrum 

UV (a low nonerythemic dose) 3 times 

weekly. Untreated control mice and 

inorganic arsenic-treated mice 

unexposed to UV developed no skin 

tumors. Of mice exposed to UV, skin 

tumor yields per mouse at the different 

doses of inorganic arsenic were as 

follows: 0, 2.40; 0.7, 5.40; 1.4, 7.21; 2.9, 

11.10; 5.8, 6.80. More than 95% of 

tumors were squamous cell carcinomas. 

Mice in all dose groups exposed to UV 

and inorganic arsenic showed a 2.5–3x ⇑

in epidermal hyperplasia above that 

caused by UV alone, with the highest 

point estimate at 0.7. 

Burns et al., 

2004 

Skin/mouse 

(Hairless 

CrL:SK1-hrBD, 

female, 

weanling) 

Starting 3 wk 

after inorganic 

arsenic treatment 

began; mice were 

irradiated thrice 

weekly with UV 

at a dose of 1.0 

kJ/m2

 

(i.e., ∼30% of 

MED) 

AsIII SA * 2.9 ppm (DW) 29 wk 2.9 ppm Immunohistological determination of 

oxidative DNA damage shown by 

staining of 8-oxo-dG: 

Control: no effect. 

UV alone: very slight ⇑. 

inorganic arsenic alone at 5.8 ppm 

(earlier experiment): ⇑. 

inorganic arsenic + UV (this 

experiment): huge ⇑. 

Co-treatment with vitamin E or p-XSC: 

⇑ (i.e., a significant reduction in 

inorganic arsenic + UV effect). 

Above effects roughly paralleled those 

for SCC induction, except that no tumors 

were caused by arsenic alone. 

Uddin et al., 

2005 

C-44 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Co-mutagenesis

Skin/mouse 

(F1 offspring 

from cross of 

FVB/N carrying 

G11 PLAP 

transgene x 

C57BL/6J, both 

sexes)

AsIII SA * 5.8 ppm (DW) 10 wk None, 

but 5.8 ppm 

if 

cotreatment 

with B[α]P

Frequencies of induction of PLAP+

 cells 

(result from frameshift mutations) in (A) 

untreated control, (B) group with 

inorganic arsenic treatment alone, (C) 

group with skin painting with B[α]P 5 

days/week during weeks 3–10 after start 

of experiment, and (D) group with both 

B and C: 

A = x; B, ∼1.9x, was a NSE; C, ∼3.2x, 

was a NSE; D, ∼10.7x. Also, 

significantly more of the individual 

mutations arose as clusters in group D, 

which suggests that more mutations 

arose in stem cells. This assay in 

bladder, spleen, lung, kidney, and liver 

yielded no obvious effect. Oxidation of 

guanosines in poly G tracts of G:C base 

pairs is thought to be one cause of these 

frameshift mutations. 

Fischer et al., 

2005 

Cytotoxicity 

Bladder/rat 

(F344, female) 

DMAV * 54.3 ppm (food) 

(assumes MW of 

chemical used was 

138.0) 

2 wk 54.3 ppm Evidence of cytotoxicity by SEM as 

frequency of class-5 bladders, which 

showed necrosis and piling up of 

rounded urothelial cells: 6 of 10 rats, 

compared to 0 of 10 in control. In group 

with co-treatment with DMPS (a 

chelator of trivalent arsenicals), only 1 in 

10 rats had a class-1 bladder. In another 

experiment with the same dose for 26 

weeks, none of the rats had class-5 

bladders. 

Cohen et al., 

2002 

Urothelium/rat 

(F344, female) 

DMAV

as 

sodium 

cacodyl

atetrihydrat

e 

* 0.35, 1.4, 14, 35 

ppm (DW) 

28 days 14 ppm By light and transmission electron 

microscopy, no alterations were detected 

at lower 2 doses. At higher 2 doses, 

urothelial cells showed signs of 

swelling, appearance of cytoplasmic 

vacuoles and a decreased number of 

mitochondria (all being signs of 

cytotoxicity), with a positive doseresponse. 

Sen et al., 

2005 

DNA Damage 

Liver/rat 

(Fischer 344, 

male) 

(they used 

normal-appearing 

tissue) 

TMAVO * 27.5, 110.2 ppm 

(DW) Estimated 

total intakes: 351 

and 1363 mg 

As/rat 

104 wk 

110.2 ppm 8-OHdG formation assessed by HPLC:

⇑ to ∼1.22x; point estimate was also ⇑ at 

lower dose, but the SE for it was large.

Shen et al., 

2003 

C-45 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Lung/mice 

(C57BL/6J 

Ogg1+/+ wt mice, 

both sexes, 14 

weeks old at start 

of treatment) 

Lung/mice 

(C57BL/6J Ogg1-

/- knockout mice, 

both sexes, 14 

weeks old at start 

of treatment) 

DMAV * 115.3 ppm (DW) 72 weeks None 

115.3 

8-OHdG formation assessed by HPLC, x

= level of wt control: 

wt with inorganic arsenic treatment: ⇑ to 

∼1.6x (NSE); 

knockout Ogg1-/- without inorganic 

arsenic: ⇑ to ∼7.8x; 

knockout Ogg1-/- with inorganic arsenic 

treatment: ⇑ to ∼13.1x. 

Kinoshita et 

al., 2007b 

Peripheral blood 

leukocytes/mous

e 

(C57BL/6J/Han, 

female) 

AsV as 

Na2HAs

O4• 

7H2O 

50, 200, 500 ppb 

(DW) 

Note in ppb! 

3, 6, 12 

months 

50 ppb Half of the mice were maintained on a 

low-Se diet. 

Alkaline SCGE (comet assay) was used 

to detect DNA fragmentation (SSBs) and 

alkaline labile sites as well as oxidative 

DNA base damage identified by using 

FPG and EnIII enzymes. The only 

significant inorganic arsenic effects were 

seen at 3 months, perhaps because water 

consumption (and thus inorganic arsenic

consumption) was lower at the last 2 

times sampled. An ⇑ in DNA 

fragmentation was observed only in the 

mice with the low-Se diet, but there was 

no positive dose-response. An ⇑ in 

oxidative DNA damage was observed 

only in the mice with the normal-Se diet, 

and again there was no positive doseresponse. 

Palus et al., 

2006 

Lung/mouse 

(ddY, male) 

DMAV

assumed 

to be 

dimethy

lar-sinic 

acid 

* 217 ppm (DW) 4 wk 217 ppm 8-oxo-dG levels: ⇑ to 1.42x; 

subcutaneous injection of 10 mg/kg 

4NQO just before 4-wk DMA treatment 

had no significant effect on this level; it 

was 1.38x. Use of feed containing 

0.05% of the antioxidant EGCG was 

tested. 8-oxo-dG level in the (4NQO + 

DMA + EGCG) group was only 1.09x.

Mizoi et al., 

2005 

Liver/rat 

(Fisher 344, 

male) 

MMAV

DMAV

TMAVO 

* 121 ppm (DW)c 

* 109 ppm (DW)c 

* 110 ppm (DW)c

5, 10, 15, 

and 20 days 

for all 

None 

None 

110 ppm 

8-OHdG formation assessed by HPLC:

TMAVO: ⇑ on day 15 to ∼1.5x and on 

day 20 to ∼1.82x. Kinoshita et 

al., 2007a 

Bladder/rat 

(Fisher 344, 

male) 

MMAV

DMAV

TMAVO 

* 121 ppm (DW)c 

* 109 ppm (DW)c 

* 110 ppm (DW)c

20 days 

for all 

None 

109 ppm 

None 

8-OHdG formation assessed by HPLC:

DMAV: ⇑ to ∼1.62x. 

Kinoshita et 

al., 2007a 

C-46 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Effects Related to Oxidative Stress (ROS) 

Brain, liver, 

RBCs/rat 

(Wistar, male) 

AsIII as 

SA

* 57.7 ppm (DW) 12 wk 57.7 ppm In liver and brain: ⇓ GSH levels; ⇑

GSSG levels; ⇑ MDA levels. 

In RBCs: ⇓ GSH levels; ⇓ ALAD levels; 

⇑ MDA levels. 

Some, but not all, of these effects were 

mitigated by oral post-treatment with 

NAC and/or DMSA. 

Flora, 1999 

Liver/rat 

(Fisher 344, 

male) 

MMAV

DMAV

TMAVO 

* 121 ppm (DW)c 

* 109 ppm (DW)c 

* 110 ppm (DW)c

5, 10, 15, 

and 20 days 

for all 

None 

109 ppm 

110 ppm 

Oxidative stress in microsomes shown 

by elevation of total cytochrome P450 

content and/or by ⇑ in hydroxyl radical 

levels: 

DMAV for P450: ⇑ on day 10 only to 

∼1.14x. 

DMAV for OH radicals: ⇑ on day 15 

only to ∼1.18x. 

TMAVO for P450: ⇑ on days 10-20, 

maximum ⇑ on day 15 to ∼1.25x. 

TMAVO for OH radicals: ⇑ on days 15 

and 20, maximum ⇑ on day 20 to 

∼1.33x. 

Kinoshita et 

al., 2007a 

Kidney and 

liver/rat 

(Wistar, female) 

AsIII 

ATO 

* 30.3 mg/kg, 

15 times (gavage) 

Every other 

day for 30 

days 

30.3 mg/kg

x 15 

Kidney: MDA level ⇑ to 3.8x; GSH 

level ⇓ to 0.78x; 

GSSG level ⇑ to 7.5x; GST activity ⇓ to 

0.44x. 

Liver: MDA level ⇑ to 2.0x; 

GSSG level ⇑ to 5.3x; GST activity ⇓ to 

0.52x. 

Co-treatment with L-ascorbate reduced 

the size of the inorganic arsenic-induced 

effects (either ⇑ or ⇓) on all 4 endpoints 

in kidneys and on all but GSH in livers.

Sohini and 

Rana, 2007

Kidney and 

liver/rat 

(Wistar, male) 

AsIII 

ATO 

* 30.3 mg/kg, 

15 times (gavage) 

Every other 

day for 30 

days 

30.3 mg/kg

× 15 

Kidney: MDA level ⇑ to 3.4x; GSH 

level ⇓ to 0.62x; 

GSSG level ⇑ to 8.5x; GST activity ⇓ to 

0.49x. 

Liver: MDA level ⇑ to 2.7x; GSH level 

⇓ to 0.82x; 

GSSG level ⇑ to 5.9x; GST activity ⇓ to 

0.49x. 

Co-treatment with L-ascorbate reduced 

the size of the inorganic arsenic-induced 

effects (either ⇑ or ⇓) on all 4 endpoints 

in kidneys and on all but GSH in livers.

Sohini and 

Rana, 2007

C-47 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Blood, kidney, 

liver/mouse 

(albino Swiss, 

male) 

AsIII SA * 57.7 ppm (DW) 8 wk 57.7 Blood: ALAD activity ⇓ to 0.32x; GSH 

level ⇓ to 0.78x; ROS level ⇑ to 2.82x.

Kidney: SOD activity ⇓ to 0.38x; CAT 

activity ⇓ to 0.34x; TBARS level ⇑ to 

1.17x; GSH level ⇓ to ∼0.39x; GSSG 

level ⇑ to ∼2.5x; 

GPx activity ⇓ 0.94x (NSE). 

Liver: SOD activity ⇓ to 0.33x; CAT 

activity ⇓ to 0.54x; TBARS level ⇑ to 

1.25x; GSH level ⇓ to ∼0.44x; GSSG 

level ⇑ to ∼3.1x; GPx activity ⇓ 0.76x 

(NSE); G-6-P activity ⇓ to ∼0.73x. 

Mittal and 

Flora, 2006

Liver/rat 

(Wistar, male) AsIII SA 

* 0.03, 1.4, 2.9 

ppm (DW) 

60 days Various Cytochrome P450 activity: ⇑ to 1.41x 

and 1.51x at 1.4 and 2.9, respectively. 

MDA level: ⇑ to 1.39x and 1.55x at 1.4 

and 2.9, respectively. 

GSH level: ⇓ to 0.59x, 0.47x, and 0.42x 

at 3 doses in ascending order. 

SOD activity: ⇓ to 0.76x, 0.60x, and 

0.55x at 3 doses in ascending order. 

⇓ in activities of CAT, GPx, GR, G-6-P, 

and GST, respectively, to 0.90x, 0.75x, 

0.50x, 0.76x, and 0.61x at 1.4 ppm and 

to 0.54x, 0.66x, 0.42x, 0.64x, and 0.45x 

at 2.9 ppm. 

Bashir et al., 

2006a 

Liver/mouse 

(BALB/c, male) 

AsIII SA 50, 100, 150 

μg/mouse/day for 

6 days/week 

(gavage) 

3 months 50 for ⇑

None 

None 

None 

50 for ⇑

50 for ⇑

Changes in various components of 

antioxidant defense system: 

GSH level: 50, 1.14x; 100, 1.17x; 150, 

1.25x. 

MDA level: NSE at any dose. 

PSH level: NSE at any dose. 

PC level: NSE at any dose. 

GPx activity: 50, 1.12x; 100, 1.15x; 150, 

1.24x. 

CAT activity: 50, 1.06x; 100, 1.08x; 

150, 1.10x. 

Das et al., 

2005 

Liver/mouse 

(BALB/c, male) 

AsIII SA 50, 100, 150 

μg/mouse/day for 

6 days/week 

(gavage) 

6 months None 

100 for ⇑

100 for ⇓

100 for ⇑

100 for ⇓

100 for ⇓

Changes in various components of 

antioxidant defense system: 

GSH level: NSE at any dose. 

MDA level: 50, NSE; 100, 1.39x; 150, 

1.44x. 

PSH level: 50, NSE; 100, 0.81x; 150, 

0.75x. 

PC level: 50, NSE; 100, 1.16x; 150, 

1.30x. 

GPx activity: 50, NSE; 100, 0.91x; 150, 

0.90x. 

CAT activity: 50, NSE; 100, 0.94x; 150, 

0.92x. 

Das et al., 

2005 

C-48 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Liver/mouse 

(BALB/c, male) 

AsIII SA 50, 100, 150 

μg/mouse/day for 

6 days/week 

(gavage) 

9 months 50 for ⇓

50 for ⇑

50 for ⇓

50 for ⇑

50 for ⇓

50 for ⇓

Changes in various components of 

antioxidant defense system: 

GSH level: 50, 0.80x; 100, 0.77x; 150, 

0.66x. 

MDA level: 50, 1.97x; 100, 2.06x; 150, 

2.16x. 

PSH level: 50, 0.80x; 100, 0.75x; 150, 

0.71x. 

PC level: 50, 1.64x; 100, 1.78x; 150, 

1.94x. 

GPx activity: 50, 0.95x; 100, 0.91x; 150, 

0.87x. 

CAT activity: 50, 0.95x; 100, 0.93x; 

150, 0.92x. 

Das et al., 

2005 

Liver/mouse 

(BALB/c, male) 

AsIII SA 50, 100, 150 

μg/mouse/day for 

6 days/week 

(gavage) 

12 months 50 for ⇓

50 for ⇑

50 for ⇓

50 for ⇑

50 for ⇓

50 for ⇓

Changes in various components of 

antioxidant defense system: 

GSH level: 50, 0.76x; 100, 0.72x; 150, 

0.63x. 

MDA level: 50, 2.20x; 100, 3.03x; 150, 

3.97x. 

PSH level: 50, 0.73x; 100, 0.63x; 150, 

0.56x. 

PC level: 50, 2.09x; 100, 2.91x; 150, 

3.46x. 

GPx activity: 50, 0.87x; 100, 0.84x; 150, 

0.75x. 

CAT activity: 50, 0.93x; 100, 0.92x; 

150, 0.88x. 

Das et al., 

2005 

Blood/rat 

(Wistar, male) AsIII SA 

* 57.7 ppm (DW) 6 weeks 57.7 ppm Effects on levels of biochemical 

variables indicative of disturbances in 

the heme synthesis pathway and 

oxidative stress: ALAD ⇓ to 0.12x; GSH 

⇓ to 0.73x; RBC ROS ⇑ to 1.35x; GPx 

showed NSE. 

Kalia et al., 

2007 

Liver/rat 

(Wistar, male) AsIII SA 

* 57.7 ppm (DW) 6 weeks 57.7 ppm Effects on levels of biochemical 

variables indicative of oxidative stress:

GSH ⇓ to 0.69x; GSSG ⇑ to 1.41x; 

TBARS ⇑ to 1.16x; catalase showed 

NSE. There was NSE for any of these 

parameters in the kidney. 

Kalia et al., 

2007 

Blood, kidney, 

liver/rat 

(Wistar, male) 

AsIII SA 

*1.15 mg/kg/day 

(gavage) 

3 weeks Various ALAD activity: blood, 0.45x. 

CAT activity: kidney, 1.12x (NSE); 

liver, 1.16x. 

GSH level: blood and kidney, NSE; 

liver, 0.79x. 

TBARS level: kidney, NSE; liver, 

1.28x;. 

Co-treatment with NAC (i.p. injection) 

and/or zinc sulfate (oral) reduced some 

effects, especially when used together. 

Modi et al., 

2006 

C-49 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Brain/rat 

(albino Wistar, 

male) 

AsIII SA 

* 57.7 ppm (DW) 60 days 57.7 ppm Effects on levels of chemicals indicative 

of oxidative stress in 5 regions of the 

brain (hippocampus, cortex, striatum, 

hypothalamus, and cerebellum): MDA ⇑

to from 1.64x to 2.21x; GSH ⇓ to from 

0.43x to 0.58x; GPx ⇓ to from 0.77x to 

0.81x; GR ⇓ to from 0.73x to 0.78x; 

G6PDH ⇓ to from 0.70x to 0.84x. 

Simultaneous treatment with DL-αlipoic acid markedly reduced all of these 

effects. 

Shila et al., 

2005a 

Brain/rat 

(albino Wistar, 

male) 

AsIII SA 

* 57.7 ppm (DW) 60 days 57.7 ppm Effects on levels of chemicals indicative 

of oxidative stress in 5 regions of the 

brain (hippocampus, cortex, striatum, 

hypothalamus, and cerebellum): 

ROS based on DCF assay ⇑ to from 

1.62x to 2.18x; total SOD ⇓ to from 

0.56x to 0.77x; Mn SOD ⇓ to from 

0.36x to 0.55x; Cu/Zn SOD ⇓ to from 

0.53x to 0.62x; CAT ⇓ to from 0.67x to 

0..80x. 

Simultaneous treatment with DL-αlipoic acid markedly reduced all of these 

effects. 

(This is the same experiment as in the 

previous row; findings not already listed 

in that row are listed here.) 

Shila et al., 

2005b 

Brain/rat 

(albino Wistar, 

male) 

AsIII SA 

* 57.7 ppm (DW) 60 days 57.7 ppm Measures of protein oxidation: 

⇑ in protein carbonyl level: cerebellum, 

1.23x; cortex, 1.32x; hippocampus, 

1.48x; hypothalamus, 1.25x; striatum, 

1.49x; 

⇓ in membrane protein sulfhydryl 

content: cerebellum, 0.71x; cortex, 

0.55x; hippocampus, 0.50x; 

hypothalamus, 0.79x; striatum, 0.61x; 

essentially the same regional pattern of 

inorganic arsenic-induced loss occurred 

with total protein-bound sulfhydryls. 

Co-treatment with DL-α-lipoic acid 

mostly or completely abolished all of the 

above effects. 

Samuel et al., 

2005 

Kidney, liver, 

RBCs/rat 

(albino Wistar, 

male) 

AsIII SA 

* 5.8 ppm (DW) 12 weeks 5.8 ppm, 

but for only 

some 

effects 

 MDA level: ⇑ in kidney to ∼2.1x, in 

liver to ∼1.7x, and in RBCs to ∼1.4x. 

CAT activity: ⇓ in kidney to ∼0.73x, in 

liver to ∼0.91x (NSE), and in RBCs to 

∼0.78. 

SOD activities were measured but with 

NSE. 

Co-treatment with cysteine, methionine, 

AA, or thiamine usually decreased tissue

arsenic concentrations (especially in 

kidney and liver) and blocked oxidative 

damage to variable degrees. 

Nandi et al., 

2005 

C-50 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Kidney/rat 

(albino Wistar, 

male) 

AsIII SA 

* 5.8 ppm (DW) 4, 8, 12 

weeks 

Various for 

⇑ and ⇓ 

MDA level: ⇑ at 4 wk to ∼1.27x (NSE), 

at 8 wk to ∼1.54x, and at 12 wk to 

∼2.11x. 

CAT activity: ⇑ at 4 wk to ∼1.72x, at 8 

wk to ∼1.18x (NSE) but ⇓ at 12 wk to 

∼0.75x. 

SOD activity: ⇑ at 4 wk to ∼1.84x, at 8 

wk to ∼1.23x, but ⇓ at 12 wk to 0.91x 

(NSE). 

Nandi et al., 

2006 

Liver/rat 

(albino Wistar, 

male) 

AsIII SA 

* 5.8 ppm (DW) 4, 8, 12 

weeks 

Various for 

⇑ and ⇓

 MDA level: ⇑ at 4 wk to ∼1.07x (NSE), 

at 8 wk to ∼1.46x, and at 12 wk to 

∼1.49x. 

CAT activity: ⇑ at 4 wk to ∼1.19x 

(NSE), at 8 wk to ∼1.52x but ⇓ at 12 wk 

to ∼0.91x (NSE). 

SOD activity: ⇑ at 4 wk to ∼1.52x, at 8 

wk to ∼1.16x, but NSE at 12 wk. 

Nandi et al., 

2006 

RBCs/rat 

(albino Wistar, 

male) 

AsIII SA 

* 5.8 ppm (DW) 4, 8, 12 

weeks 

Various for 

⇑ and ⇓

 MDA level: ⇑ at 4 wk to ∼1.13x (NSE), 

at 8 wk to ∼1.28x, and at 12 wk to 

∼1.41x. 

CAT activity: ⇑ at 4 wk to ∼1.36x, NSE 

at 8 wk, and ⇓ at 12 wk to ∼0.71x. 

SOD activity: ⇑ at 4 wk to ∼1.81x, at 8 

wk to ∼1.59x, but NSE at 12 wk. 

Nandi et al., 

2006 

Liver and 

kidney/rat 

(albino Wistar, 

male) 

AsIII SA 

* 57.7 ppm (DW) 30 days 57.7 ppm Level of ROS determined by DCFH 

assay: 

⇑ in liver to ∼3.6x and in kidney to 

∼3.5x. 

Level of MDA released per mg protein:

⇑ in liver to ∼1.5x and in kidney to 

∼1.6x. 

Co-treatment with both DL-α-lipoic acid 

and DMSA markedly reduced all of 

these effects. 

Kokilavani et 

al., 2005 

Liver and 

kidney/rat 

(albino Wistar, 

male) 

AsIII SA 

* 57.7 ppm (DW) 30 days 57.7 ppm Activities of antioxidant enzymes: 

⇓ of SOD in liver to ∼0.51x and in 

kidney to ∼0.55x. 

⇓ of CAT in liver to ∼0.59x and in 

kidney to ∼0.58x. 

⇓ of GPx in liver to ∼0.53x and in 

kidney to ∼0.56x. 

Levels of non-enzymatic antioxidants: 

⇓ of GSH in liver to ∼0.56x and in 

kidney to ∼0.67x. 

⇓ of AA in liver to ∼0.48x and in kidney 

to ∼0.50x. 

⇓ of α-Toc in liver to ∼0.49x and in 

kidney to ∼0.58x. 

⇓ of total sulfhydryls in liver to ∼0.53x 

and in kidney to ∼0.59x. 

Co-treatment with both DL-α-lipoic acid 

and DMSA markedly reduced all of 

these effects. 

Kokilavani et 

al., 2005 

C-51 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Blood (whole), 

brain, kidney, 

liver/mice 

(Swiss albino, 

male) 

AsIII SA 

* 14.4 ppm (DW) 3 months 14.4 ppm Whole blood: ⇓ of ALAD activity to 

0.37x; ⇓ of GSH level to 0.93x. 

Brain: ⇑ in TBARS level to ∼2.2x; ⇓ in 

GSH/GSSG ratio to ∼0.96x. 

Kidney: ⇑ in TBARS level to 1.65x. 

Liver: ⇑ in TBARS level to 1.21x; ⇓ in 

SOD activity to 0.76x; ⇓ in CAT activity 

to 0.89x; ⇓ in GSH/GSSG ratio to 0.89x.

Post-treatments with 3 different extracts 

of Hippophae rhamnoides L. (thought to 

have antioxidant properties) showed 

various levels of effectiveness in 

reducing some of the above effects in all 

but the kidney. 

Gupta and 

Flora, 2005

Blood (whole), 

brain, kidney, 

liver/rat 

(Wistar, male) 

AsIII SA 

* 11.5 ppm (DW) 4 wk 11.5 ppm Whole blood: ⇓ of ALAD activity to 

0.24x; ⇓ of GSH level to 0.86x; ⇑ of 

ZPP level to 1.30x. 

Brain: ⇑ in TBARS level to 1.89x; ⇓ in 

GSH level to 0.85x; NSE on GSSG 

level; ⇓ in SOD activity to 0.75x; ⇓ in 

CAT activity to 0.75x. 

Kidney: ⇑ in TBARS level to 1.39x; ⇓ in 

GSH level to 0.55x; ⇑ in GSSG level to 

1.59x. 

Liver: ⇑ in TBARS level to 1.96x; ⇓ in 

GSH level to 0.61x; ⇑ in GSSG level to 

2.00x; oral co-treatment with Centella 

asiatica (thought to have antioxidant 

properties) showed various levels of 

effectiveness in reducing some of the 

above effects. 

Gupta and 

Flora, 2006

Blood (whole), 

brain/rat 

(Wistar, male) 

AsIII SA 

* 57.7 ppm (DW) 10 wk 57.7 ppm Whole blood: ⇑ of ROS level to 2.63x; ⇓

of ALAD activity to 0.46x; ⇓ of GSH 

level to 0.85x; ⇓ of Hb as grams/dL to 

0.79x. 

Brain: ⇑ of ROS level to 4.03x; ⇑ in 

TBARS level to 1.50x; ⇓ in GSH level 

to 0.82x; ⇓ in SOD activity to 0.92x 

(NSE); ⇓ of ALAD activity to 0.58x; ⇑

of ALAS activity to 1.21x; ⇓ of GPx 

activity to 0.84x (NSE); ⇑ of GST 

activity to 1.08x (NSE); “considerable” 

but unquantified ⇑ in DNA 

fragmentation (single-strand breaks) was 

detected by polyacrylamide gel 

electrophoresis. 

Postreatment with the thiol chelating 

agents DMSA, DMPS, and MiADMSA 

showed various levels of effectiveness in 

reducing some of the above effects. 

Flora et al., 

2005 

C-52 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Liver/mouse 

(BALB/c, male) 

Unspeci

fied 

arsenica

l, but 

from 

discussi

on 

assumed 

to be 

AsIII SA 

* 1.8 ppm (DW) 3, 6, 9, 12, 

15 months

1.8 at ≥9 

months for 

MDA 

1.8 at ≥6 

months for 

GSH 

MDA conc: ⇑ to ∼1.7x at 9, ∼1.9x at 12, 

and ∼2.2x at 15. 

GSH content: ⇓ to ∼0.84x at 6, ∼0.78x at 

9, ∼0.67x at 12, and ∼0.58x at 15. ⇓ in 

activities were also noted for G6PDH, 

GPx, and 

plasma membrane Na+

/K+ ATPase at 6 

months, for CAT at 9 months, and for 

GST and GR at 12 and 15 months. It 

seems likely that the activities remained

lower at later times than when each ⇓

was noted, but that was not stated. 

Mazumder, 

2005 

Lung/mouse 

(ddY, male) 

DMAV * 217.2 ppm (DW) 2, 4, 8, 15,

 25 wk 

217.2 ppm 

at 8 wk or 

longer 

Immunohistochemical analysis of 4HNE 

adducts showed that lipid peroxidation 

occurred in 48.8%, 72.9%, and 77.6% of

terminal bronchiolar Clara cells by 8, 15, 

and 25 weeks, respectively. (None 

before that.) The modified proteins were 

specifically in the secretory granules of 

those cells. 8-OHdG adducts (showing 

oxidative DNA) damage were also 

demonstrated in the same cells. Clara 

cells are the major target cell for DMAinduced oxidative stress, and the authors 

suggested that lipid peroxidation via the 

formation of ROS is involved in 

promotion of lung tumor (malignant 

adenocarcinoma) formation following 

initiation by 4NQO. 

An et al., 

2005 

Liver/rat 

(Wistar, male) AsIII SA 

* 3.6, 6.1, 7.3 

mg/kg 

(gavage, with 

animals being 

killed 24 hr later 

for sample 

collection) 

One dose Various Significant dose-related ⇑ in total 

arsenic conc at all doses; conc in liver at 

highest dose was ~22 times that in brain. 

 

MDA conc: ⇑ to 1.43x at 6.1 and 1.52x 

at 7.3. 

GSH level: ⇓ to 0.57x at 3.6, to 0.41x at 

6.1, and to 0.39x at 7.3. 

Total cytochrome P450 activity: ⇑ to 

1.46x at 6.1 and 1.54x at 7.3. 

SOD level: ⇓ to 0.67x at both 6.1 and 

7.3. 

CAT activity: ⇓ to 0.54x at 6.1 and 

0.49x at 7.3. 

GPx activity ⇑ to 1.15x at 3.6, 1.21x at 

6.1, and 1.27x at 7.3. 

GST activity: ⇓ to 0.72x at 6.1 and 0.62x 

at 7.3. 

NSE on either GR or G6PD activity. 

Bashir et al., 

2006b 

C-53 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Brain/rat 

(Wistar, male) AsIII SA 

* 3.6, 6.1, 7.3 

mg/kg 

(gavage, with 

animals being 

killed 24 hr later 

for sample 

collection) 

One dose Various Significant ⇑ in total arsenic conc at 

both higher doses. 

MDA conc: ⇑ to 1.48x at 6.1 and 1.56x 

at 7.3. 

GSH level: ⇓ to 0.79x at 3.6, to 0.60x at 

6.1, and to 0.51x at 7.3. 

SOD level: ⇓ to 0.73x at 6.1 and 0.70x 

at 7.3. 

CAT activity: ⇓ to 0.58x at 6.1 and 

0.51x at 7.3. 

GPx activity ⇑ to 1.17x at 6.1, and 1.26x 

at 7.3. 

GST activity: ⇓ to 0.71x at 6.1 and 0.69x 

at 7.3. 

NSE on either GR or G6PD activity. 

Bashir et al., 

2006b 

Kidney, rat 

(Wistar, male) 

AsIII 

ATO 

* 30.3 mg/kg, 

15 times (gavage) 

Every other 

day for 30 

days 

30.3 × 15 GSH content ⇓ to ∼0.59x. 

GST activity: NSE. 

Rana and 

Allen, 2006

Gene Mutations 

Skin/mouse 

(Aprt+/- hybrid 

mice of complex 

genotype needed 

for assay: see 

paper) 

AsIII SA 

* 5.7 ppm (DW) 10 wk None Starting 2 wk after consumption of 

inorganic arsenic-contaminated water 

began, half of the mice were also 

exposed to B[α]P for 8 wk by skin 

painting. Skin was assayed for DAPresistant (DAPr

) colonies indicative of 

cells lacking Aprt activity as the result 

of loss of heterozygosity (LOH) at Aprt 

because of malsegregation or mitotic 

recombination in vivo. No significant 

differences were found because of 

inorganic arsenic and/or B[α]P exposure, 

and thus there was no evidence that 

inorganic arsenic alone, or by 

enhancement of a known mutagen (but 

not one + in this assay), caused such 

genetic changes. Curiously, the point 

estimate for most LOH was in the 

control (45%); it was 38% for B[α]P 

alone, 8% for inorganic arsenic alone, 

and 30% for them together. Because 

there was much variability, these 

seemingly large differences were not 

statistically significant. 

Fischer et al., 

2006 

C-54 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Wing/Drosophila 

melanogaster

DMAV 0.05, 0.1, 0.25, 0.5 

mM 

(in medium) 

72 hr 0.25 mM, 

regarding 

total spots

SMART (somatic mutation and 

recombination test) wing spot assay: 

positive dose-response was found, but 

nature of induced mutations was 

uncertain. Was earlier shown that 

inorganic arsenic is inactive in this 

assay. They showed no biomethylation 

occurs in larvae or in growth medium. 

Results suggest importance of 

biomethylation as a determinant of 

genotoxicity of arsenic compounds, at 

least in Drosophila. 

Rizki et al., 

2006 

Hypermethylation of DNA

Lung/mice 

(A/J, male) 

AsV as 

Na2HAs

O4• 

7H2O 

* 0.24, 2.4, 24 

ppm (DW) 

18 months The LOEL was 0.24 ppm. Extent of 

hypermethylation of promoter regions of tumor 

suppressor genes p16INK4a and RASSF1A in lung 

adenocarcinomas from inorganic arsenic exposed 

mice compared to the control, based on methylationspecific PCR: percentages of methylated promoters 

of p16INK4a in lung tumors of 0, 0.24, 2.4, and 24 

ppm dose groups were 11%, 30%, 36%, and 42%, 

respectively. Percentages of methylated promoters 

of RASSF1A in lung tumors of the same dose groups 

were 33%, 70%, 82%, and 89%, respectively. 

Reduced expression, or lack of expression, of these 2 

genes was correlated with the extent of 

hypermethylation. There was constant expression of 

these genes in lungs without tumors in both control 

and inorganic arsenic-treated mice. They concluded 

that epigenetic changes of tumor suppressor genes 

are involved in inorganic arsenic-induced lung 

carcinogenesis. 

Cui et al., 

2006 

Hypomethylation of DNA 

Liver cells/mouse 

(129/SvJ) AsIII SA 

45 ppm (DW) 48 wk 45 ppm There was global DNA 

hypomethylation, as shown by 5-

methylcytosine content of DNA and by 

using the methyl acceptance assay. In 

particular, there was a marked ⇓ in 

methylation within the ER-α gene 

promoter region, which was statistically 

significant in 8 of 13 CpG sites. Control 

had 28.3% of ER-α sites methylated, but 

experimental group had 2.9%. 

Chen et al., 

2004b 

C-55 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

 Reference 

Livers of 

newborn 

males/mouse 

 (only pregnant 

C3H females 

drank the water) 

AsIII SA 85 ppm (DW) 10 days, 

gestation 

days 

8 to 18 

85 ppm Global DNA methylation status was not 

significantly altered based on methyl 

acceptance assay, which measures 

methylation in both quiescent and active 

areas of DNA. However, another assay 

showed that GC-rich regions globally 

were less methylated if they were from 

livers of newborn males exposed in 

utero to inorganic arsenic. Band 

intensity showing the extent of 

methylation was 0.20x after RsaI + MspI 

digestion and 0.40x after RsaI + HpaII 

digestion. MspI and HpaII are 

methylation sensitive enzymes. 

Xie et al., 

2007 

Interference With Hormone Function 

Kidney, rat 

(Wistar, male) AsIII 

ATO 

* 30.3 mg/kg, 

15 times (gavage) 

Every other 

day for 30 

days 

30.3 × 15 T3 and T4 levels in serum: 

triodothyronine (T3) ⇑ to ∼4.8x; 

thyroxine (T4) ⇑ to ∼1.7x. 

Rana and 

Allen, 2006

Signal Transduction 

Fetal 

lungs/mouse 

(only pregnant 

C3H females 

drank the water, 

female offspring 

only) 

AsIII SA 85 ppm (DW) 10 days, 

gestation 

days 

8 to 18 

85 ppm ⇑ in ER-α transcript (5.3x) and protein 

levels; ⇑ in expression of the following 

estrogen-related genes: trefoil factor-3 

(9.66x), anterior gradient-2 (3.21x); ⇑ in 

expression of the following steroid 

metabolism genes: 17-β-hydroxysteroid 

dehydrogenase type 5 (3.55x) and 

aromatase (2.53x). (Expression of ER-α

and the ER-linked genes was unchanged 

in male fetal lung as compared to 

control.) The insulin growth factor 

system was also activated, with 

transcripts for 

IGF-1, IGF-2, IGF-R1, IGF-R2, IGFBP1, and IGF-BP5 all being increased to 

1.6-2.5x. Also, there was 

overexpression of the following genes 

that have been associated with lung 

cancer: AFP (6.9x), EGFR (3.2x), Lmyc (1.9x), and metallothionein-1 

(2.1x). 

Shen et al., 

2007 

Adenomas and 

adenocarcinomas from 

lungs of adults 

exposed in 

utero/mouse 

(only pregnant 

C3H females 

drank the water, 

female offspring 

only) 

AsIII SA 85 ppm (DW) 10 days, 

gestation 

days 

 8 to 18 

85 ppm Based on immunohistochemical 

analysis: 

intense and widespread ⇑ in nuclear ERα expression; in contrast, normal adult 

lung and DENA-induced lung 

adenocarcinoma showed little evidence 

of ER-α expression. 

Shen et al., 

2007 

C-56 DRAFT—DO NOT CITE OR QUOTE
Tissue or Cell 

Type/Species 

Arsenic 

Species 

Dose in 

Elemental Asa

(in Units Stated) 

Duration 

of 

Treatment

LOELb Results 

Reference 

a When doses were reported in mg arsenic/L or in ppm As, it was assumed that the doses included adjustment for the 

amount of arsenic in solution. Because it was sometimes unclear from the papers whether a correction was needed, a “*” 

was put front of the doses listed in the table if those doses were corrected to the amount of arsenic in the dose. 

b Lowest observed effect level. 

c Estimates were based on the reported concentrations of MMAV, DMAV, and TMAVO in DW of 1.62, 1.45, and 1.47 mM, 

respectively, and on their molecular weights (MWs) of 139.969, 137.997, and 136.025 g and on the atomic weight of 

arsenic of 74.926 g. The paper stated that the concentrations of all arsenicals were 0.02% (or 200 ppm). For the 

arsenicals themselves, the concentrations were actually 226, 200, and 200 ppm, respectively, if based on the MWs just 

listed. 

1 

Table C-3. In vitro studies related to possible MOA of arsenic in the development of cancer 

Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Aberrant Gene or Protein Expression 

HaCaT cells AsIII SA 0.5, 1.0 20 passages 0.5 ⇑ intracellular GSH 

quantities. 

⇓ keratins 5, 6, 7, 8, 10, 

and 17. 

Chien et 

al., 2004 

TRL 1215 

cells (normal 

rat liver) 

AsIII SA 0.125, 0.250, 

0.500 

24 wk 

0.500 for 

effects 

noted here 

Using Atlas Rat cDNA 

expression microarrays, 

~80 of the 588 genes 

assayed were aberrantly 

expressed—including 

genes related to stress 

and DNA damage, signal 

transduction modulators 

and effectors, apoptosisrelated proteins, 

cytokines and cytokinerelated components, and 

growth factors and 

hormone receptors. 

Chen et al., 

2001 

Hepa-1 cells 

(mouse 

hepatoma) 

AsIII SA 1, 3, 10, 30 

30 min before 

4 hr 

co-treatment 

with 1 nM 

TCDD 

1 

Results of Northern blot 

analysis of mRNA: ⇑

TCDD-inducible levels 

of Nqo1 mRNA; 

response was much 

higher at 3 and 10, but 

decreased markedly at 30 

to slightly more than was 

present at 1. 

Maier et 

al., 2000 

C-57 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Huh7 cells AsIII SA 0.5, 1, 3, 5, 10, 20 24 hr 3 

Following co-treatment 

with 10 nM TCDD: ⇓

TCDD-inducible level of 

CYP1A1 activation to 

∼45% of level without 

inorganic arsenic, then 

reached plateau of ∼18% 

at doses of 5-15 (based 

on EROD assay); 

inorganic arsenic did not 

affect CYP1A1 

activation by itself. 

Chao et al., 

2006b 

Huh7 cells, 

transfected for 

use in the 

DRE-CALUX 

bioassay 

AsIII SA 0.5, 1, 3, 5, 10, 20 24 hr 3 

Following co-treatment 

with 10 nM TCDD: 

⇓ TCDD-inducible 

luciferase activity in the 

DRE-CALUX bioassay 

to ∼80% of level without 

inorganic arsenic, 

followed by a doserelated ⇓ to 42% at dose 

of 20. 

Chao et al., 

2006b 

PARP-1+/+

MEF cells 

PARP-1-/-

MEF cells 

AsIII SA 

for both 

11.5 

for both 

24 hr 

for both 

In a microarray gene chip analysis that 

analyzed the expression pattern of 

more than 34,000 genes, ~311 genes 

were found to be differentially 

expressed among the different groups 

(i.e., control versus inorganic arsenic 

treatment or in comparisons between 

the 2 genotypes). Many of those 

genes belonged to the following 

groups: responders to stress and 

external stimuli, genes related to cell 

growth and maintenance, cell death, or 

DNA metabolism. While some genes 

were markedly up-regulated in both 

genotypes (sometimes to widely 

different amounts), other genes were 

up-regulated for one genotype and 

down-regulated for the other, and vice 

versa. 

Poonepalli 

et al., 2005 

C-58 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

NB4 cells AsIII ATO 0.5 

6, 12, 24, 48, 

and 72 hr for 

transcriptome 

analysis; 

12 and 48 hr 

for proteomic 

analysis 

In a microarray and 2-dimensional gel 

electrophoresis (with mass 

spectrometry) study aimed at 

understanding effects of therapies with 

ATO alone, retinoic acid alone, and 

their combined therapy, the main 

findings for ATO were as follows. At 

the transcriptome level, ATO affected 

regulation of 487 genes, many of 

which were probably related to 

essential aspects of cell-activity 

control such as induction of 

differentiation antigens, modulation of 

apoptosis regulators, and regulation of 

genes involved in cell-cycle and 

growth control. Other groups of 

affected genes included those involved 

with protein degradation, cell defense, 

stress response, protein modification 

and synthesis, and a group of 5 downregulated HLA-class I genes. At the 

proteome level, ATO affected 982 

protein spots, and there was often a 

time-dependent pattern of regulation, 

with much lower protein levels at 48 

hr than at 12 hr after treatment. A 

group of enzymes involved in 

biochemical metabolism was found to 

be significantly down-regulated, and 

there was a strong reduction of 

cytoskeleton proteins, implying a 

considerable reorganization of the cell 

nucleus and cytoplasmic structures. 

By comparison with relatively minor 

changes at many of the corresponding 

genes at the transcriptome level, the 

significant changes found at the 

proteomic level suggest that ATO 

particularly enhances mechanisms of 

post-transcriptional/translational 

modification. 

Zheng et 

al., 2005 

PRCCs 

 HEK293 

cells 

AsIII ATO 

for both 

0.1 

1 

10 min, 

1, 6, 24 hr 

for both 

0.1 at 6 hr 

1 at 6 hr 

HMOX1 gene 

expression (mRNA 

levels measured by 

quantitative PCR): 

In PRCCs: NSE at 10 

min or 1 hr; ∼2.3x at 6 

hr, ∼2.8x at 24 hr. 

HEK293: NSE at 10 min 

or 1 hr; ∼40x at 6 hr, 

∼54x at 24 hr. 

Sasaki et 

al., 2007 

C-59 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

PRCCs 

 HEK293 

cells 

AsIII ATO 

for both 

0.1, 0.5, 2 

for both 

24 hr 

for both 

0.1 

0.5 

HMOX1 gene 

expression (mRNA 

levels measured by 

quantitative PCR): 

In PRCCs: 0.1, 2.2x, 0.5, 

11.7x; 2, 33.5x. 

In HEK293: 0.1, 1.2x, 

0.5, 8.3x; 2, 224.9x. 

Western blot analysis for 

heme oxygenase 1 

protein for dose of 1 for 

24 hr: Huge ⇑ in PRCCs 

and big ⇑ in HEK293. 

Sasaki et 

al., 2007 

PRCCs 

 HEK293 

cells 

AsIII ATO 

for both 

0.1 

for both 

10 min, 

1, 6, 24 hr 

for both 

Microarray analysis identified 73 

genes whose expression changed in 

both types of cells, and for many 

expression increased in a timedependent manner. These included 

HMOX1, Bax (involved in induction 

of apoptosis), and genes involved in 

many other biological processes 

including intracellular protein 

transport, signal transduction, 

differentiation, GSH metabolism, and 

protein complex assembly among 

others. Data were presented that 

suggest that heme oxygenase 1 protein 

confers a cytoprotective effect against 

inorganic arsenic treatment. 

Sasaki et 

al., 2007 

HCT15 cells 

HeLa cells 

PLC/PR/5 

cells 

Chang cells 

AsIII SA 

for all 

278.33, the LC50

200.33, the LC50

376.66, the LC50 

328.33, the LC50

24 hr 

for all 

278.33 

200.33 

376.66 

328.33 

Western blot assay to 

determine eIF4E protein 

levels: 

for all cell lines, there 

was a reduction in the 

protein level to roughly 

50%–60% of the 

corresponding control 

level. There was also a 

statistically significant, 

but smaller, ⇓ after 16 hr 

for all lines. 

Othumpan

gat et al., 

2005 

C-60 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HCT15 cells 

HeLa cells 

PLC/PR/5 

cells 

Chang cells 

AsIII SA 

for all 

278.33, the LC50

200.33, the LC50

376.66, the LC50 

328.33, the LC50

24 hr 

for all 

278.33 

200.33 

376.66 

None 

Quantitative real-time 

PCR to determine eIF4E 

mRNA levels: there was 

a statistically significant 

⇓ only in lines HCT15 

and HeLa. Actual data 

on gene expression, in 

arbitrary units: 

HCT15: no inorganic 

arsenic, 0.099, with 

inorganic arsenic, 0.049. 

HeLa: no inorganic 

arsenic, 0.041, with 

inorganic arsenic, 0.029. 

PLC/PR/5: no inorganic 

arsenic, 0.051, with 

inorganic arsenic, 0.028. 

Chang: no inorganic 

arsenic, 0.018, with 

inorganic arsenic, 0.019. 

(Judging from their SEs, 

the result for PLC/PR/5 

must have been of 

borderline significance.) 

Othumpan

gat et al., 

2005 

HeLa cells AsIII SA 200 24 hr 200 

Western blot assay to 

determine protein levels: 

Big ⇓ in cyclin D1. 

⇑ in cellular levels of 

ubiquitin and in the 

process of ubiquitination. 

Othumpan

gat et al., 

2005 

HeLa cells, 

HCT15 cells, 

CHO-K1 cells 

AsIII SA 

for all 

Various 

Additional experiments involving a genetically modified 

cell line, an siRNA that targeted expression of eIF4E, 

and proteasome inhibitors suggested (1) that the changes 

seen in eIF4E protein levels played a role in the 

observed cytotoxicity, (2) and that the inhibition of 

cyclin D1 is mediated through the inhibition of eIF4E, 

and (3) that the inorganic arsenic stimulated 

ubiquitination and the resulting proteolysis play an 

important role in reducing eIF4E protein levels. 

Othumpan

gat et al., 

2005 

TR9-7 cells 

that were 

released from 

being mostly 

synchronized 

in G2 (using 

Hoechst 

33342) 

shortly before 

inorganic 

arsenic 

treatment 

began 

AsIII SA 5 3–24 hr 

Conclusions based on determining 

protein levels using Western blot 

assays until 24 hr of inorganic arsenic 

treatment in cells made p53(+) or p53(-)

by controlling tetracycline levels: big 

⇑ in ID1, but it occurred only when 

there was p53 protein present. arsenic 

p53 protein level decreased, ID1 

protein level decreased. The general 

finding was confirmed by microarray 

analysis. Work by others showed that 

ID1 protects against apoptosis through 

activation of the 

NF-κB signaling pathway. 

McNeely 

et al., 2006 

C-61 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

TR9-7 cells 

that were 

released from 

being mostly 

synchronized 

in G2 (using 

Hoechst 

33342) 

shortly before 

inorganic 

arsenic 

treatment 

began 

AsIII SA 5 3 hr 

Conclusions based on microarray 

analysis (done by hybridizing 

fragmented cRNAs to U95Av2 

GeneChips) in cells made p53(+) or 

p53(-) by controlling tetracycline 

levels: several genes were induced by 

inorganic arsenic independently of p53 

status, of which some of the biggest 

effects were as follows (at both p53 

conditions): HMOX1: huge ⇑ by 

>25x; MT2A: ⇑ by >3x; SLC30A1: ⇑

by >3x. MKP-1 was induced only in 

p53(+) cells, and 

ubiquitin-conjugating enzyme E2N 

was induced only in p53(-) cells. 

McNeely 

et al., 2006 

HeLa cells 

 

AsIII

ATO 2 6 and 24 hr 

 In a cDNA microarray-based global 

transcription profiling experiment that 

compared the inorganic arsenic 

treatment with a co-treatment of the 

same inorganic arsenic dose with 30 

μM emodin, the numbers of genes 

with an expression level that differed 

between the two treatments by more 

than a factor of 2 at the 2 time points 

were 793 and 480, respectively. The 

affected genes included genes 

involved in such things as cell 

signaling, organelle functions, cellcycle control, redox regulation, and 

apoptosis. The manner of data 

presentation did not permit 

identification of genes affected 

exclusively by inorganic arsenic. 

Wang et 

al., 2005 

TRL 1215 

cells 

AsIII SA 0.125, 0.250, 

0.500 

24 weeks Various 

mRNA levels determined 

by real time RT-PCR: 

effects on oncogenes

AFP: ⇑ at 0.250, big ⇑ at 

0.500; WT-1: ⇑ at 0.125, 

big ⇑ at 0.250 and 0.500. 

c-jun: ⇑ at 0.250, big ⇑

at 0.500; H-ras: ⇑ at 

0.125, big ⇑ at 0.250 and 

0.500. 

(By 24 weeks of 

exposure at the higher 2 

doses, these cells had 

undergone malignant 

transformation and were 

called CAsE cells.) 

Liu et al., 

2006d 

C-62 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

TRL 1215 

cells 

AsIII SA 0.125, 0.250, 

0.500 

24 weeks Various 

mRNA levels determined 

by real time RT-PCR: 

effects on stress-related 

genes

HMOX-1: ⇑ at 0.125 and 

0.250, big ⇑ at 0.500; 

SOD: ⇑ at 0.250, big ⇑ at 

0.500. 

MT-1: big ⇑ at 0.250, ⇑

at 0.500; GSTπ: ⇑ at 

0.125, big ⇑ at 0.250 and 

0.500. 

(By 24 weeks of 

exposure at the higher 2 

doses, these cells had 

undergone malignant 

transformation and were 

called CAsE cells.) 

Liu et al., 

2006d 

TRL 1215 

cells 

AsIII SA 0.125, 0.250, 

0.500 

24 weeks Various 

mRNA levels determined 

by real time RT-PCR: 

effects on cell cycle 

regulators

Cyclin D1: ⇑ at 0.125, 

then ⇑ with dose to 

0.500. 

PCNA: ⇑ at 0.250, big ⇑

at 0.500. 

p21: big ⇓ at 0.125, then 

⇓ with dose to 0.500. 

p16: ⇓ at 0.125, big ⇓ to 

∼0% at 0.250 and 0.500. 

(By 24 weeks of 

exposure at the higher 2 

doses, these cells had 

undergone malignant 

transformation and were 

called CAsE cells.) 

Liu et al., 

2006d 

C-63 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

TRL 1215 

cells 

AsIII SA 0.125, 0.250, 

0.500 

24 weeks Various 

mRNA levels determined 

by real time RT-PCR: 

effects on growth factor 

genes

c-met: big ⇑ at 0.125, 

then ⇑ with dose to 

0.500. 

HGF: ⇑ at 0.125, big ⇑ at 

0.250 and 0.500. 

FGFR1: huge ⇓ at 0.250, 

then ⇓ to ∼0% at 0.500. 

IGF-II: huge ⇓ to ∼0% at 

all doses. 

(By 24 weeks of 

exposure at the higher 2 

doses, these cells had 

undergone malignant 

transformation and were 

called CAsE cells.) 

Liu et al., 

2006d 

TRL 1215 

cells 

AsIII SA 0.125, 0.250, 

0.500 

24 weeks Various 

Protein levels determined 

using Western blots: 

AFP: slight ⇑ at 0.125 

through 0.500; WT-1: 

huge ⇑ at 0.125 through 

0.500. 

Cyclin D1: ⇑ at 0.125 

through 0.500; p16: huge 

⇓ at all doses. 

p21: ⇓ at 0.125, then ⇓

with dose to 0.500. 

(By 24 weeks of 

exposure at the higher 2 

doses, these cells had 

undergone malignant 

transformation and were 

called CAsE cells.) 

Liu et al., 

2006d 

C-64 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

TRL 1215 

cells 

AsIII SA 0.500 24 weeks Various 

mRNA levels determined 

by real time RT-PCR: 

effects of 72-hr posttreatment with 5 μM 5-

aza-dC

(results were compared 

to cells with inorganic 

arsenic treatment alone) 

MT-1: ⇑ 19x over 

already elevated level. 

p21: ⇑ 15x over what 

was a greatly reduced 

level, and level then far 

above that with no 

inorganic arsenic 

exposure 

p16 and IGF-II: NSE. 

(By 24 weeks of 

exposure at the higher 2 

doses, these cells had 

undergone malignant 

transformation and were 

called CAsE cells.) 

Liu et al., 

2006d 

CL3 cells AsIII SA 2 24 hr 2 

⇑ Nqo1 mRNA level to 

1.7x control; ⇑ Nqo1 

protein level to 6.4x 

control. 

Cells given this 

inorganic arsenic 

pretreatment became 

more sensitive to MMCinduced cytotoxicity and 

less sensitive to ADMinduced cytotoxicity. 

Co-treatment with MMC 

and the Nqo1 inhibitor 

DIC resulted in big ⇑ in 

cell survival (even higher 

than after MMC 

treatment without an 

inorganic arsenic 

pretreatment). CL3R15 

cells, which have much 

higher levels of Nqo1 

activity than CL3 cells, 

are also much more 

sensitive to MMCinduced cytotoxicity than 

CL3 cells. 

Lin et al., 

2006 

C-65 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

H460 cells 

CL3 cells 

AsIII SA 

for both 

2.5, 5, 10, 20 

1, 2.5, 5, 10 

72 hr 

for both 

2.5 

1 

Cell survival determined 

by SRB assay: LC50s: 

H460, 9.0; CL3, 3.7; 

H460 cell have ∼30x 

higher endogenous Nqo1 

activity than CL3 cells, 

and unlike CL3 cells 

they showed no 

statistically significant 

induction of Nqo1 after 

24-hr treatments with 

inorganic arsenic at 

doses of 2, 5, or 10. 

(Even at the highest level 

of induction in CL3 

cells, the endogenous 

level of Nqo1 activity in 

H460 cells was still ∼15x 

higher.) These findings 

raised question whether 

Nqo1 plays a role in 

inorganic arsenic 

resistance. 

Lin et al., 

2006 

CL3R15 cells 

CL3R15 cells 

co-treated 

with 200 μM 

DIC for 6 hr 

to inhibit 

>95% of the 

high 

endogenous 

level of Nqo1 

activity 

AsIII SA 

for both 

50, 100, 200 

for both 

6 hr 

for both 100 

50 

Cell survival determined 

by colony-forming assay: 

LC50s: with DIC, ~35; 

without DIC, 120. 

Lin et al., 

2006 

C-66 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

SIK cells AsIII SA 2 1, 3, 5, 7, 9 

days 

Changes in protein levels detected at 

each of the 5 times using 2-

dimensional gel electrophoresis of 

soluble proteins, with proteins 

identified by peptide mass mapping 

and other methods: ∼300 distinct 

protein spots were monitored with 

∼40% showing ≥2-fold ⇑ or ⇓ in silver 

staining intensity at every time point, 

about as many ⇑ as ⇓, with at least as 

many changes on day 1 as on other 

days. There were some changes as to 

the proteins affected over time. Of 10 

proteins identified as showing 

prominent changes within first few 

days of inorganic arsenic treatment, 

enzymes of the glycolytic pathway 

were seen to be substantially elevated. 

 This dose of inorganic arsenic 

suppressed differentiation but did not 

cause cell loss. 

Lee et al., 

2005 

C-67 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

TRL 1215 

cells 

MMAV

DMAV

TMAVO 

1300 

700 

10000 

20 weeks 

for all 

1300 

700 

10000 

⇑ GST activity to 2.6x 

control, ⇑ cellular GSH 

protein level to 2.2x 

control. 

⇑ GST activity to 1.7x 

control, ⇓ cellular GSH 

protein level to 43% of 

control. 

⇑ GST activity to 1.8x 

control, ⇑ cellular GSH 

protein level to 2.4x 

control. 

All 3 treatments 

increased GST, MRP 

and MDR at the mRNA 

level, and all 3 

treatments increased 

GST, Mrps, and P-gp at 

the protein level. GST 

and MRP have several 

forms. While not all 

forms responded in the 

same way, the overall 

responses were as noted. 

 Experiments with 

inhibitors of GSH, Mrps, 

and P-gp led to the 

conclusion that increased 

arsenic excretion caused 

the resistance to arsenicinduced cytotoxicity that 

resulted from these 

treatments. 

Kojima et 

al., 2006 

C-68 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Ahr+/+ MEFs 

 

AsIII SA 1, 2, 5 6 hr 

2 for 

Nqo1 only 

None for 

CYP1B1 

mRNA levels measured 

by real-time RT-PCR: ⇑

Nqo1 mRNA to 4x 

control; 5 μM B[α]P 

increased Nqo1 mRNA 

to 8x control; there was a 

synergistic interaction 

between them such that 

the dose of 2 of 

inorganic arsenic plus 

the dose of 5 of B[α]P 

increased Nqo1 mRNA 

to 27x control. A 

synergistic interaction to 

20x control also occurred 

with a dose of 1 of 

inorganic arsenic. At a 

dose of 5 of inorganic 

arsenic, the interaction 

became only additive. 

The interaction between 

inorganic arsenic and 

B[α]P regarding 

CYP1B1 mRNA was 

never more than additive. 

 In Ahr-/- MEFs, there 

was no interaction of 

inorganic arsenic and 

B(α)P regarding Nqo1 

mRNA; the combined 

treatment did not ⇑ Nqo1 

mRNA levels. Thus the 

synergistic interaction 

requires the wt Ahr gene. 

Kann et 

al., 2005a 

Ahr+/+ MEFs 

 

AsIII SA 

Following treatment with 2 μM inorganic arsenic, 5 μM B[α]P, or both, for an 

unspecified time, oligonucleotide microarray analysis of 13,332 sequences 

from annotated mouse genes: they identified 64 genes that were up-regulated 

or down-regulated by inorganic arsenic, B[α]P, or both; of these, 13 showed at 

least a 2x up-regulation and 12 caused at least a 2-fold down-regulation in 

gene expression because of the inorganic arsenic treatment alone. Many 

different types of genes were affected. One of the major consequences of 

exposure to these mixtures was the up-regulation of oxidative stress and 

protein chaperone responses and the down-regulation of the TGF-β pathway. 

Exposure to inorganic arsenic/B[α]P mixtures caused regulatory changes in 

the expression of detoxification genes that ultimately affect the metabolic 

activation and disposition of toxicants. 

Kann et 

al., 2005a 

AG06 cells AsIII SA 0.2, 1, 3, 10 

24 hr 

48 hr 

1 

0.2 

⇑ GSH concentration. Snow et 

al., 1999 

AG06 cells AsIII SA 3 48 hr 3 Specific activities: GSTπ

⇑ to ~1.6x and γGCS to 

~2.2x at dose of 3. 

Snow et 

al., 1999 

C-69 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

AG06 cells 

GM847 cells 

AsIII SA 0.1, 0.25, 0.5, 1.0, 

5, 10, 25 

24 hr 1.0 

0.25 

⇑ GR protein level to 

2.9x at 1. 

⇑ GR mRNA level to 

1.3x and enzyme activity 

to 2.0x at 0.25. 

Snow et 

al., 2001 

GM847 cells AsIII SA 0.5, 1.0, 10, 25 24 hr 0.5 for ⇑

0.5 for ⇓

⇑ Trx, TrxR, GR mRNA 

levels; for TrxR and GR: 

⇑ to ~2.7x by 10 and 

then ⇓ to ~1.5x by 25). 

⇓ GPx mRNA level to 

~0.5x by 1 and ~0.2x by 

25. 

Snow et 

al., 2001 

AG06 cells AsIII SA 0.2, 4, 20 

 

3 hr 

24 hr 

0.2 

0.2 

APE/Ref-1 mRNA 

levels: at 3 hr: ⇑ to ~2.7x 

at 0.2 and then only 

slight ⇑ to ~3.0x at 20. 

At 24 hr: ⇑ to ~3.0x at 

0.2 but ⇓ to ~0.9x at 20. 

 (APE/Ref-1 is required 

for BER.) 

Snow et 

al., 2001 

WI38 cells AsIII SA 0.3, 1.4, 5.7, 29 

 

Not reported 0.3 

⇑ DNA Poly β level 

(both cytoplasmic and 

nuclear) to ~2x by 1.4 

but ⇓ to ~0.8x by 29. 

(DNA Poly β is required 

for BER.) 

Snow et 

al., 2001 

HaCaT cells AsIII SA 

0.001, 0.01, 0.05, 

0.1, 0.5, 1.0 

2 days 

14 days 

0.1 

0.01 

⇓ p53 protein; ⇑ mdm2 

protein. 

⇓ p53 protein; ⇑ mdm2 

protein. 

Hamadeh 

et al., 1999 

HaCaT cells AsIII SA, 

AsV

MMAV, 

DMAV

1.0 

1.0 

2 days 

for all 

1.0 

None 

⇓ p53 protein; ⇑ mdm2 

protein; (much bigger 

effect for AsIII). 

No significant change. 

Hamadeh 

et al., 1999 

 JB6 Cl41 

cells 

AsIII SA 0.05, 0.2, 0.8, 

3.125, 12.5, 50, 

200 

15 min 0.8 ⇑ Erk activation 

resulting from Erk 

phosphorylation; another 

experiment showed that 

overexpression of 

dominant negative Erk2 

blocks arsenite-induced 

activation of Erk. 

Huang et 

al., 1999a 

K562 cells AsIII ATO 2.5 6 hr 2.5 ⇑ GlycoA, HLA-DR, 

CD33, and CD34 on the 

cell surface, indicating 

maturation of myeloid 

cells. 

Li and 

Broome, 

1999 

C-70 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

MCF-7 cells AsIII ATO 3 12 hr 3 Microtubule 

polymerization, with a 

major effect on the 

organization of the 

cellular microtubule 

network, resulting in the 

formation of long 

polymerized microtubule 

bundles; ⇑ p34cdc2/cyclin 

B complex (both 

activation and 

accumulation); ⇑ Bcl-2 

phosphorylation. 

Ling et al., 

2002 

H460 cells 

AsIII ATO 

10 24 hr 10 

The following changes 

occurred only in mitotic 

cells (definitely not in 

interphase cells): ⇑

caspase-3 activation, ⇑

caspase-7 activation, 

cleavage of PARP and βcatenin. These findings 

suggest that arsenicinduced mitotic arrest 

may be a requirement for 

the activation of 

apoptotic pathways. 

Ling et al., 

2002 

Primary 

cultures of rat 

cerebellar 

neurons 

AsIII SA 10 24 hr 10 ⇑ caspase activity 

(apoptosis is blocked in 

these cells if caspase is 

inhibited; there was a 

much bigger effect with 

a 48-hr treatment). 

Namgung 

and Xia, 

2001 

MC/CAR 

(human 

multiple 

myeloma cell 

line) 

AsIII ATO 2 72 hr 2 

⇑ caspase-3 activity, 

p21, and CDK1; upregulation of cdc2 

phosphorylation; ⇓ in 

CDK6, cdc2, cyclin A, 

and Bcl-2 levels; ⇑

binding of p21 with 

CDK6, cdc2, and cyclins 

A and E; ⇓ activity of 

CDK6-associated kinase 

and cdc2-associated 

kinase; loss of 

mitochondrial 

transmembrane potential 

(∆ψm); no change in p27, 

CDK2, CDK4, or cyclins 

B1, D1, or E levels. 

Park et al., 

2000 

C-71 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

PCI-1 (human 

head and neck 

squamous cell 

carcinoma 

cell line) 

AsIII ATO 2 3 days 2 

⇑ p21 and its binding 

with cdc2; ⇓ protein 

levels of cdc2 and cyclin 

B1; 

⇓ activity of cdc2 kinase; 

no change in CDK2, 

CDK4, CDK6 and 

cyclins A, D1, E. 

Seol et al., 

1999 

(Human 

myeloma-like 

cell lines) 

RPMI 8226 

Karpas 707 

U266 

AsIII ATO 

0.5 72 hr 0.5 ⇑ CD38 and CD54 

(molecules involved in 

cell-cell interactions). 

Deaglio et 

al., 2001 

LAK effector 

cells AsIII ATO 0.5 

72 hr 0.5 ⇑ CD11a and CD31 

(molecules involved in 

cell-cell interactions, and 

the ligands [i.e., counterreceptors] of CD54 and 

CD38, respectively). 

Deaglio et 

al., 2001 

WRL-68 

(human 

hepatic cell 

line) 

AsIII SA 

0.001, 0.01, 0.1, 

10 

16 hr 0.1 

0.001 

⇑ GSH. 

⇑ CK18. 

Ramírez et 

al., 2000 

Human aorta 

VSMCs 

(vascular 

smooth 

muscle cells) 

AsIII SA 

2.5, 5, 10 4 hr ∼5 ⇑ p22phox mRNA 

expression (p22phox is 1 

of at least 7 subunits of 

NADH oxidase.) ⇓ αactin mRNA expression. 

Lynn et al., 

2000 

Human aorta 

VSMCs 

(vascular 

smooth 

muscle cells) 

AsIII SA 2.5, 5, 10, 20 4 hr ∼5 ⇑ NADH oxidase 

activity. The effect was 

even stronger, with a 

LOEC of 1, in 

nonproliferating VSMCs. 

Lynn et al., 

2000 

WI38 cells AsIII SA 0.1 

10, 20, 50 

14 days 

18 hr 

0.1 

50 

⇑ p53 (3-fold increase). 

⇑ p53 (large increase). 

Vogt and 

Rossman, 

2001 

WI38 cells AsIII SA 

0.1 

50 

14 days 

18 hr 

0.1 

50 

⇑ cyclin D1; also 

treatment blocks ⇑ in 

p21 that occurs follow 

exposure to 6 Gy of 

ionizing radiation. 

⇓ cyclin D1; also 

treatment mostly blocks 

⇑ in p21 that occurs 

follow exposure to 6 Gy 

of ionizing radiation. 

Vogt and 

Rossman, 

2001 

C-72 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Untransforme

d and 

immortalized 

RWPE-1 cells 

(human 

prostate 

epithelial cell 

line) 

AsIII SA 5 Up to 30 wk 5 

⇑ MMP-9 activity (likely 

biomarker of when 

malignant transformation 

occurred); ⇓ in DNA 

methyltransferase 

activity but no change in 

DNA methyltransferase 

mRNA levels; ⇑ K-ras 

mRNA and protein 

levels. Time course 

study suggested overexpression of K-ras 

preceded malignant 

transformation. There 

was no indication of 

mutations being induced 

in K-ras gene and no 

indication that 

hypomethylation of Kras promoter region 

caused K-ras changes. 

The cells became 

tumorigenic after 29 

weeks of treatment and 

were then called the 

CAsE-PE cell line. 

Benbrahim

-Tallaa et 

al., 2005 

PAEC from 

freshly 

harvested 

vessels 

AsIII

probably 

ATO, but 

called 

arsenite 

5 15 min to 3 hr 

depending on 

endpoint 

5 ⇑ NF-κB dependent 

transcription, ⇑ H2O2-

dependent tyrosine 

phosphorylation (which 

was blocked by CAT), 

⇑cSrc activation. MAP 

kinases, extracellular 

signal-regulated kinase, 

and p38 were only 

activated at a dose of 

100, which causes cell 

death. 

Barchowsk

y et al., 

1999a 

C-73 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HeLa S3 cells AsIII SA 5 24 hr 5 

Changes in cells that 

were arrested in mitosis 

by AsIII: c-Mos was 

hyperphosphorylated, 

cyclin A was degraded, 

cyclin B accumulated; 

⇑⇑ p34cdc2/cyclin B 

kinase activity. These 

and numerous other 

changes in mitotic 

proteins were similar to 

changes seen in cells 

arrested in mitosis by 

nocodazole, which is a 

known microtubule 

disassembly agent. 

Huang and 

Lee, 1998 

TM3 cells AsIII SA 0.008, 0.77, 7.7 70 days Various 

Changes in expression of 

cell-cycle related genes: 

⇓ at 7.7 for Cyclin D1; 

for PCNA: ⇑ at 0.008, ⇓

at 0.77 and 7.7. 

Changes in expression of 

DNA repair genes: 

⇓ at 0.77 and higher for 

ERCC6 and OGG1; 

⇓ at 7.7 for XPC, MYH, 

and DNA polymerase-β. 

Changes in expression of 

other genes: 

⇓ at 7.7 for, MnSoD, and 

Bax; 

for DNMT1: ⇑ at 0.008, 

NSE at 0.77, ⇓ at 7.7. 

DuMond 

and Singh, 

2007 

E7 cells AsIII ATO 0.025, 0.05, 0.1, 

0.25, 0.51 

4 weeks 0.005 ⇑ Aurora-A protein 

expression level, with a 

positive dose-response, 

reaching 4.2x control at 

dose of 0.1; unreported 

data showed ⇑ Aurora-A 

mRNA. 

Tseng et 

al., 2006 

C-74 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

BEAS-2B 

cells 

AsIII AC 1.25, 2.5, 5, 10, 20 12 hr 1.25 

⇑ GADD45α protein 

expression level, with a 

positive dose-response; 

however, only a marginal 

⇑ in GADD45α

transcription; 

pretreatment with NAC 

completely blocked the ⇑

of GADD45α. After 

inorganic arsenic dose of 

20 for 4–20 hr: transitory 

activation of Akt and 

transitory ⇑

phosphorylation of 

FoxO3a. Inorganic 

arsenic induced 

accumulation of 

GADD45α mRNA and 

did not affect the 

degradation of 

GADD45α protein. 

Inorganic arsenic 

stabilized GADD45α

mRNA through 

nucleolin; it induced the 

binding of mRNA 

stabilizing proteins, 

nucleolin and less 

potently, HuR, to 

GADD45α mRNA. 

Inorganic arsenic did not 

affect the expression of 

nucleolin; inorganic 

arsenic treatment 

resulted in redistribution 

of nucleolin from 

nucleoli to nucleoplasm. 

 Silencing of nucleolin 

reversed inorganic 

arsenic-induced 

stabilization of the 

GADD45α mRNA. 

Zhang et 

al., 2006 

C-75 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Gclm+/+ MEF 

cells and 

Gclm-/- MEF 

cells, from 

GCLM 

knockout 

mice 

AsIII SA 

for all 

See rows under Apoptosis and Cytotoxicity for this citation for experimental 

conditions. Analysis of global gene expression profiles revealed up-regulation 

or down-regulation of vast numbers of genes by inorganic arsenic. Significant 

changes were largely consistent with changes in the expression of DNA 

damage and repair genes, the suppression of TGF-β signals, inhibition of 

integrin-mediated cell adhesion, induction of multiple transcription factors, 

repression of co-repressors, and the derailment of cell cycle regulatory 

functions. Inorganic arsenic exposure also caused profound changes in 

protein levels in what appear to be conflicting regulatory changes. These 

changes go hand in hand with massive up-regulation of HSPs, 

metalloproteinases, and proteasome components, and the authors suggested 

that inorganic arsenic induces critical changes in protein folding and structure 

and that the cells mount a major effort to properly refold misfolded proteins or 

to eliminate them altogether. Global gene expression profiles also indicated 

that tBHQ is significantly effective in reversing inorganic arsenic-induced 

gene deregulation in Gclm+/+ but not in Gclm-/- MEFs. These results 

suggested that regulation of GSH levels by GCLM determines the sensitivity 

to inorganic arsenic-induced apoptosis and cytotoxicity by setting the overall 

ability of the cells to mount an effective antioxidant response. 

Kann et 

al., 2005b 

NB4 cells 

NB4-M-AsR2 

cells 

AsIII ATO 

for both 

0.5, 1 

2, 4 

16 hrs 

for both 

0.5 

2 

JNK activation leading 

to phosphorylation of cjun, after treatment with 

ATO alone and cotreatment with 100 μM 

Trolox: 

At 0.5: slight ⇑ alone, ⇑

with Trolox. 

At 1: big ⇑ alone, huge ⇑

with Trolox. 

At 2: slight ⇑ alone, ⇑

with Trolox. 

At 4: big ⇑ alone, huge ⇑

with Trolox. 

Diaz et al., 

2005 

JB6 C141 

PG13 cells 

JB6 C141 

PG13 cells 

exposed to 4 

kJ/m2

 of UVB 

at end of 

inorganic 

arsenic 

treatment 

AsIII SA 

for both 

1, 5, 10, 20 

for both 

24 hrs 

for both 

5 

5 

⇓ in p53 activity with 

dose, reaching ∼30% of 

control at dose of 20. 

⇓ in p53 activity with 

dose, reaching ∼5% of 

that with the UVB 

treatment alone at dose 

of 20. The UVB 

exposure strongly 

stimulated p53 activation 

(to ~9x the control 

level), and the inorganic 

arsenic treatment 

inhibited that increase, 

reducing it to a point 

estimate less than that of 

the untreated control at 

the dose of 20. 

Tang et al., 

2006 

C-76 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

JB6 C141 

P+

1-1 cells 

JB6 C141 

P+

1-1 cells 

exposed to 4 

kJ/m2

 of UVB 

at end of 

inorganic 

arsenic 

treatment 

AsIII SA 

for both 

1, 5, 10, 20 

0.1, 1, 5, 10 

24 hrs 

for both 

5 

5 

⇑ in AP-1 activity to 2x 

control at 5 and to 5x 

control at 10, back to 

control level at 20. 

⇑ in AP-1 activity to 

1.5x and 1.7x that with 

the UVB treatment alone 

at doses of 5 and 10, 

respectively. It should 

be noted that the UVB 

exposure strongly 

stimulated AP-1 

activation (to ~6x the 

control level). 

Tang et al., 

2006 

JB6 C141 

cells exposed 

to 4 kJ/m2

 of 

UVB at end 

of inorganic 

arsenic 

treatment 

AsIII SA 

for both 

5, 10 

1, 5, 10 

24 hrs 

for both 

5 

5 

⇓ UVB-induced p53 

phosphorylation (at 

serines 15 and 392); 

bigger ⇓ at 10. 

⇓ UVB-induced p53 

DNA binding activity; 

bigger ⇓ at 10. 

Other experiments not 

involving UVB showed 

that inorganic arsenic 

inhibited casein kinase 

2α activity and decreased 

p53-regulated p21 

protein expression. 

Tang et al., 

2006 

C-77 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

SV-HUC-1 

cells 

AsIII SA 

MMAIII

DMAIII

0.5 

0.05, 0.1, 0.2 

0.2, 0.5 

Subcultured 

twice weekly 

for 25 

passages 

0.5 

0.05 

0.2 

Results of cDNA 

microarray analysis of 

∼2000 genes: 114 genes 

were differentially 

expressed among the 6 

groups; DMAIII had a 

substantially different 

gene profile from other 

2. Gene coding for IL-1 

receptor, type II, was the 

only gene with ⇑

expression by all 

arsenicals. 11 genes had 

⇓ expression by all 

arsenicals. For 2 of 

those 11, transcription 

was partially restored by 

treatment with 5-aza-dC, 

which suggests that the 

suppression resulted 

from epigenetic DNA 

hypermethylation. The 

treatments also caused 

differential 

morphological changes 

affecting cell size, extent 

of aggregation, and 

adhesion ability. 

Su et al., 

2006 

SVEC4-10 

cells 

AsIII SA 5, 10, 20 24 hr 5 

Protein levels: 

α7-nAChR: slight ⇓ at 5, 

huge ⇓ at 10 and 20, 

with only a trace present 

at 20. 

eNOS: slight ⇓ at 5, 

huge ⇓ at 10 and 20, 

with none present at 20. 

ChAT: NSE. 

Hsu et al., 

2005 

C-78 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

BEAS-2B 

cells 

AsIII ATO 10, 20, 50 12 hr 10 

HSP70 protein ⇑: fold 

increases over control by 

Western blotting after 

12-hr recovery period: 

2.6x, 2.5x, and 7.9x at 

doses of 10, 20, and 50, 

respectively; alternative 

ELISA analysis gave 

similar response but with 

much higher-fold 

increases over the 

control. Co-treatments 

with large doses of 

antioxidants CAT, SOD, 

NAC, or SF considerably 

reduced the arsenic 

effect, with the NAC 

treatment completely 

eliminating it. 

Han et al., 

2005 

BEAS-2B 

cells 

AsIII ATO 10, 20, 50 6 hr 10 for all 

mRNA levels determined 

by RT-PCR, with no 

recovery time after 

exposure, 

fold ⇑ over control: 

At 10: HSP70A, 4.4x; 

HSP70B, 4.3x; HSP70C, 

3.6x. 

After 4-, 8-, and 12-hr 

recovery periods, mRNA 

levels usually ⇓ to levels 

closer to control and 

often NSE; however, all 

increases remained 

significantly higher than 

control at dose of 50. 

Han et al., 

2005 

BEAS-2B 

cells 

AsIII ATO 10, 20, 50 6 hr 10 Intracellular GSH levels: 

⇓ to 80% of control at 

10, followed by doserelated decrease to 70% 

of control at dose of 50; 

co-treatment with NAC 

blocked this effect of 

inorganic arsenic. 

Han et al., 

2005 

HT1197 cells AsIII SA 10 8 hr 10 

p53 protein levels: slight 

⇑; at 24 hr at this dose: 

big ⇑ to 4x control. 

p21 protein levels: ⇑ to 

7.5x control; also at this 

dose: at 12-20 hr, much 

smaller increases; at 24 

hr, big ⇓; at 4 hr, 2.4x 

control. 

Hernández

-Zavala 

 et al., 

2005 

C-79 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

SVEC4-10 

cells 

AsIII SA 

4, 8, 12, 16; 

separase was 

tested only at the 

highest dose 

24 hr Various 

Effects on protein levels: 

Securin: ⇓ at 12 to 23%, 

⇓ at 16 to 5%. 

Separase: ⇑ to 1.2x 

control (of ?-able 

significance). 

Phospho-CDC2 

(threonine-161): ⇓ at 16 

to 34%. 

CDC2: ⇓ at 12 to 73%, ⇓

at 16 to 38%; cyclin B1: 

⇓ at 16 to 11%. 

p53 (DO-1): ⇑ at 4 to 2x 

control with positive 

dose-response reaching 

8x control at dose of 16. 

Chao et al., 

2006a 

RAW264.7 

cells 

AsIII SA 2.5, 5 24 hr 2.5 

TRAP histochemistry 

was done 3 days after the 

end of the inorganic 

arsenic treatment: 

huge ⇑ in TRAP activity 

at both doses; this 

increased activity 

accompanied 

multinucleated cell 

formation and the 

beginning of osteoclast 

differentiation; the level 

of effect at both doses 

was comparable to (and, 

at the dose of 2.5, 

probably higher than) 

that caused by a RANKL 

treatment; co-treatment 

with CAT blocked most 

of the inorganic arsenicinduced effect. 

Szymczyk 

et al., 2006 

C-80 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HCT116 cells 

(securin +/+) 

HCT116 cells 

(securin -/-) 

AsIII SA 

for both 

4, 8, 12, 16 

for both 

24 hr 

for both 

Various 

Various 

Effects on protein levels: 

Securin: ⇓ at 4, then ⇓

with dose to ∼30% at 16. 

Phospho-p53 (serine 15): 

⇑ to 2x control at 4 and 

then ⇑ with dose to 6x 

control at 16. 

p53 (DO-1): ⇑ to 2x 

control at 12 and ⇑ to 

3.4x control at 16. 

No securin present at any 

dose in -/- mutant. 

Phospho-p53 (serine 15): 

⇑ to 3.5x control at 4 and 

then ⇑ with dose to 7x 

control at 16. 

p53 (DO-1): ⇑ to 1.8x 

control at 4 and then ⇑

with dose to 3.2x control 

at 16. 

Chao et al., 

2006a 

RKO cells 

(p53 wt) 

SW480 cells 

(p53 mutant) 

 AsIII SA 

for both 8, 16 

for both 

24 hr 

for both 

16 

16 

Effects on protein levels 

of securin: rather similar 

⇓ in both, reaching 27% 

and 13% of control in 

RKO and SW480, 

respectively. 

Chao et al., 

2006a 

FGC4 cells AsIII SA 

50, 65 

Equivalent to ≤5% 

and 20–25% 

cytotoxicity 

24 hr Various 

Effects on protein levels 

of SPs: 

MT, HSP60 and HSP90: 

NSE at either dose. 

HSP25: big ⇑ at 50, big 

⇑ at 65. 

HSP40: big ⇑ at 50, big 

⇑ at 65. 

HSP70: big ⇑ at 50, huge 

⇑ at 65. 

Gottschalg 

et al., 2006 

HepG2 cells AsIII SA 

15, 55 

Equivalent to ≤5% 

and 20–25% 

cytotoxicity 

24 hr Various 

Effects on protein levels 

of SPs: 

MT: NSE at 15, very 

slight ⇑ at 55. 

HSP60 and HSP90: NSE 

at either dose. 

HSP27: slight ⇑ at 15, ⇑

at 55. 

HSP40: slight ⇑ at 15, 

big ⇑ at 55. 

HSP70: ⇑ at 15, big ⇑ at 

55. 

Gottschalg 

et al., 2006 

C-81 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Rat 

hepatocytes 

AsIII SA 

10, 20 

Equivalent to ≤5% 

and 20–25% 

cytotoxicity 

24 hr Various 

Effects on protein levels 

of SPs: 

MT, HSP60 and HSP90: 

NSE at either dose. 

HSP25: ⇑ at 10, ⇑ at 20. 

HSP40: NSE at 10, ⇑ at 

20. 

HSP70: NSE at 10, big ⇑

at 20. 

Gottschalg 

et al., 2006 

HELF cells AsIII SA 0.1, 0.5, 1, 5, 10 

3, 6, 12, 24, 

 or 48 hr Various 

HSP27 protein: ⇑ at 0.5 

and 1 after 12-hr 

treatment, but ⇓ at 5 and 

10 after 

48-hr treatment; HSP27 

was said to be a 

chaperone whose 

expression protects 

against oxidative stress 

and is anti-apoptotic. 

HSP70 protein: ⇓ at 1 

and 5 after 12-hr 

treatment, but ⇑ at 5 and 

10 after 24-hr treatment; 

an inducible form of 

HSP70 was said to be 

expressed at a high level 

in various malignant 

human tumors. 

Yang et 

al., 2007 

MDAH 2774 

cells 

AsIII ATO 1, 2, 5, 8 

Probably 

72 hr or 

96 hr 

1 or 2 

⇓ topoisomerase IIα to 

about half of control 

value at dose of 5 

(paralleling degree of 

cytotoxicity)—there is 

some question about this 

result because band 

densities were not 

normalized to another 

protein; decrease 

possibly resulted from ⇓

in cell number. 

Askar et 

al., 2006 

UROtsa cells AsIII SA 0.5, 5, 10, 25 24 hr 5 

⇑ accumulation of highmolecular-weight Ubconjugated proteins. 

Co-treatment with BSO: 

⇑⇑ in the same effect, 

which was then seen 

even at dose of 0.5. 

Bredfeldt 

et al., 2004 

UROtsa cells MMAIII 0.05 12 weeks 0.05 Huge ⇑ COX-2 protein, 

with an even higher level 

after 24 weeks and still 

high level after 52 

weeks. 

Eblin et 

al., 2007 

C-82 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

UROtsa cells 

AsIII SA 

MMAIII

1, 10 

0.01, 0.05, 0.1 

4 hr 

for both 

1 

0.01 

Big ⇑ COX-2 protein 

level at both doses. 

Regarding COX-2 

protein level: huge ⇑ at 

0.01, big ⇑ over control 

at 0.05, ⇑ over control at 

0.1. Various 

experiments, including 

some with 

pharmacological 

inhibitors of various 

signal transduction 

pathways, led to the 

conclusion that MMAIII

appears to stimulate 

ligand-independent 

activation of EGFR, 

subsequent ERK-1 and -

2 phosphorylation via 

MEK-1 and -2, as well 

as activation of PI3K, 

which leads to elevated 

levels of COX-2 protein. 

Eblin et 

al., 2007 

UROtsa cells 

AsIII SA 

MMAIII

1, 10 

0.05, 0.5, 5 

30 min 

for both 

1 

0.05 

⇑ HSP70 protein (similar 

response at both doses; 

with lower dose, the 

level decreases from 60 

to 240 min); ⇑ MT 

protein (much bigger ⇑

at higher dose). 

⇑ HSP70 protein (strong 

response at all doses). 

⇑ MT protein (much 

bigger ⇑ at higher 

doses). 

Eblin et 

al., 2006 

C-83 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HaCaT cells 

AsIII SA 

AsV

MMAIII

DMAIII

2, 6, 10 

1, 5, 10 

1, 2, 3 

1, 4, 7 

24 hr 

for all 

6, 2 

None 

2, 3 

4 

Extent of selenium 

incorporation into 

selenoproteins 

determined using 75Se-selenite: 

LOECs of 6 and 2 for ⇓

TrxR1 and ⇓ cGpx, 

respectively; big ⇓ at 

higher dose(s). 

NSE. 

LOECs of 2 and 3 for ⇑

TrxR1 and ⇓ cGpx, 

respectively. 

⇑ of TrxR1 and cGpx at 

dose of 4 and decrease 

for both proteins to near 

control levels at higher 

dose. 

Ganyc et 

al., 2007 

MEF cells AsIII SA 0.01, 0.1, 5, 10, 

20, 40 

5 hr 5 

⇑ eIF2α

phosphorylation; ⇑

ATF4 protein; ⇑ ATF3 

protein. At doses ≥10: ⇑

GADD45a protein and ⇑

CHOP protein. All 

effects showed 

substantial 

dose-related increases. 

Effects were mostly 

blocked by NAC 

pretreatment. (ATF3 

was not tested.) 

Jiang et al., 

2007 

MEF cells AsIII SA 20 in most assays 

GADD45a is a small protein implicated in the regulation 

of the cell cycle, DNA repair, genome stability, innate 

immunity, and apoptosis. Additional tests with 

modulators and genetic variants of MEF cells showed 

the following: ATF4 is required for an increase in 

GADD45a mRNA following inorganic arsenic exposure, 

and its induction is independent of p53. ATF4 binds to 

a GADD45a promoter element in response to inorganic 

arsenic stress. Exposure to inorganic arsenic reduces 

proteasome activity, which permits the increase in 

transcription of GADD45a to actually result in an 

increase in the protein level of GADD45a, which is 

labile. 

Jiang et al., 

2007 

C-84 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Protein 

extracts 

(membrane 

fraction) 

derived from 

BAEC cells 

MMAIII

AsIII SA, 

AsV, 

MMAV or 

DMAV

1, 2.5, 5, 7.5, 10, 

15 

10 

5 min 

for all 

1 

None 

For MMAIII only: ⇓

eNOS activity, IC50 = 2.1 

and a 5-min treatment at 

dose of 10 caused ∼90% 

⇓; co-treatment with 

DTT substantially 

blocked the MMAIII

effect, resulting in only 

∼50% ⇓. 

Sumi et al., 

2005 

N-18 cells AsIII SA 5, 10, 20, 50 6 hr 

5 for first 

effect 

noted 

⇑ synthesis of HSP 

proteins of 50, 73, 78, 

89, 98, and 104 kDa. 

Other experiments 

demonstrated: ⇑

activation of HSF1 

DNA-binding (detected 

by EMSA) by dose of 20 

(lowest dose tested) in 2 

hr; ⇑ induction of 

HSP70-luciferase 

reporter gene expression 

by dose of 20 (lowest 

dose tested) in 6 hr; an ⇑

induction of HSP70 

mRNA by dose of 50 

(lowest dose tested) in 1 

hr. 

Khalil et 

al., 2006 

N-18 cells 

AsV 

potassium 

arsenate 

20 6 hr 20 ⇑ induction of HSP70-

luciferase reporter gene 

expression (point 

estimates suggests 

weaker response from 

AsV than from same dose 

of AsIII SA). 

Khalil et 

al., 2006 

C-85 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

N-18 cells AsIII

2, 5, 10, 20, 50, 

100, 200, 500 

0.5, 1, 2, 3, 6, 

or 12 hr 

Various 

⇑ induction of HSP70-

luciferase reporter gene 

expression, with bellshaped dose-response 

curves for each duration 

of treatment; e.g. for 1-hr 

treatment, the peak 

occurred at dose of 200 

(highest peak seen); for 

6-hr treatment, the peak 

occurred at dose of 20; 

the bell-shaped curves 

shifted to the left as the 

duration increased. 

Results on HSP70-firefly 

luciferase activity were 

normalized against that 

of Renilla luciferase to 

correct for differences in 

transfection efficiency 

and/or toxic and nonspecific effects of the 

experimental treatment 

conditions. 

Khalil et 

al., 2006 

hsf+/+

immortalized 

MEF cells 

hsf-/-

immortalized 

MEF cells 

hsf-/-

immortalized 

MEF cells 

transfected 

with HSF1 

expression 

vector 

AsIII SA 

for all 

5, 10, 20, 50, 100, 

200, 500 for all 

1 hr 

for all 

50 

None 

50 

⇑ induction of HSP70-

luciferase reporter gene 

expression: 

⇑ with dose up to peak at 

200; still big ⇑ at 500. 

No effect; clearly 

inorganic arsenic 

requires a functional 

HSF1 gene to induce 

HSP70-luciferase 

reporter gene expression. 

⇑ with dose up to peak at 

200; still big ⇑ at 500. 

Generally similar results 

were also found with 

treatment durations of 

0.5 and 2 hr. 

Khalil et 

al., 2006 

C-86 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

H1355 cells 

AsIII ATO 

5, 25, 50, 100, 200 24 hr Various 

Phosphorylation of ERK 

1/2: ⇑ at 50, huge ⇑ at 

100 and 200. 

Phosphorylation of JNK: 

slight ⇑ at 50, huge ⇑ at 

100 and 200. 

Phosphorylation of p38: 

slight ⇑ at 100, big ⇑ at 

200. 

PARP cleavage: ⇑ at 100 

and 200. 

Survivin protein level: ⇓

at 100 and 200. 

Ubiquitination in total 

cell lysate: big ⇑ at 100 

(the only dose tested for 

it). 

Cheng et 

al., 2006 

H1355 cells 

AsIII ATO 

100 24 hr Various 

Effects of pretreatments 

with specific inhibitors 

of p38, JNK, MEK 1/2 

(upstream of ERK 1/2) 

or ubiquitin-proteasome 

showed that blockage of 

either p38 or JNK 

phosphorylation 

attenuated the ATOinduced down-regulation 

of survivin and increase 

of PARP cleavage; 

however, blockage of 

ERK 1/2 or ubiquitinproteasome did not 

attenuate those same 

effects. Also, only 

inhibitors of p38 and 

JNK affected ATOinduced cytotoxicity, 

which was just slightly 

reduced (i.e., there was 

∼5%–8% more cell 

survival). The specific 

inhibitors of p38, JNK, 

and MEK 1/2 did block 

the phosphorylations of 

p38, JNK, and ERK 1/2, 

respectively. 

Cheng et 

al., 2006 

C-87 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

A549 cells 

AsIII ATO 

2 48 hr 

Protein levels and mRNA levels: 

2 μM inorganic arsenic: NSE on 

survivin. 200 μM sulindac: NSE on 

survivin. 

(Sulindac is a NSAID that inhibits 

COX-2.) 

(2 μM inorganic arsenic + 200 μM 

sulindac): big ⇓ in survivin (by 72 hr 

almost no survivin was protein 

present). Protein levels only for 

combined treatment: 

 big ⇑ for p53 but NSE for XIAP, 

cIAP-1, cIAP-2, and Bcl-2. Inhibition 

of p53 ⇑ by siRNA blocked the downregulation of survivin by the (2 μM 

inorganic arsenic + 200 μM sulindac) 

treatment. (It is known that p53 binds 

to the survivin promoter and 

suppresses its transcription.) 

Transfected cells with a survivinluciferase reporter also showed the big 

⇓ in survivin for the combined 

treatment and NSE for single 

treatments. Pretreatment with NAC 

mostly (or entirely) blocked the 

synergistic effect of a ⇓ of survivin 

protein (was shown both by Western 

blot and luciferase reporter assays). 

Jin et al., 

2006b 

A549 cells AsIII ATO 2 48 hr 

More about the synergistic effect 

between 2 μM inorganic arsenic and 

200 μM sulindac: evidence that 

changes in survivin levels are related 

to synergistic big ⇑ in cytotoxicity: (1) 

if marked overexpression of survivin 

by transfection, then ⇓ in cytotoxicity 

by 1/3, (2) if inhibition of survivin 

level by siRNA, then ⇑ in cytotoxicity. 

 (Sulindac is a NSAID that inhibits 

COX-2.) 

Jin et al., 

2006b 

C-88 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

N-18 cells AsIII SA 2, 5, 10, 20, 50, 

100, 200, 500 

6 hr 10 

Induction of HSP70-

luciferase reporter gene 

expression: big ⇑ at 10, 

huge ⇑ (peak) at 20, big 

⇑ at 50, then NSE. 

Effects of pretreatment + 

co-treatment with 

modulators: 

DTT: almost entirely 

blocked inorganic 

arsenic effect; slight ⇑ at 

20 and 50, questionable 

⇑ at 10 and 100. 

NAC and GSH 

(individually): ⇑ at 10, 

big ⇑ at 20, huge ⇑

(peak) at 50, ⇑ at 100, 

then NSE. 

Khalil et 

al., 2006 

NHEK cells AsIII SA 0.1, 1, 5, 10 72 hr 

0.1 for ⇑

1 for ⇓

Level of β1-integrin 

protein: after a possible 

slight ⇑ at 0.1, there was 

a ⇓ to 

61-63% of control level 

at other 3 doses. 

Lee et al., 

2006b 

NHEK cells AsIII SA 0.1, 1, 5, 10 7 days 

0.1 for ⇑

1 for ⇓

Level of β1-integrin 

mRNA: after a possible 

slight ⇑ at 0.1, a doserelated ⇓ at other 3 doses 

reaching 47% of control 

at dose of 10. 

Lee et al., 

2006b 

NHEK cells AsIII SA 1 24, 48, 72 hr 1 

Level of FAK protein 

based on 

immunofluorescence: ⇑

at 24 hr followed by ⇓

below control level at 

later times, with almost 

none present at 72 hr. 

Lee et al., 

2006b 

C-89 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Normal 

human 

mammary 

epidermal 

keratinocytes 

AsIII SA 

for all 

0.005, 0.5, 1, 2.5 

1, 2.5, 5 

4 hr 

8 hr 

0.005 

2.5 

⇑ COX-2 mRNA (also at 

8 and 24 hr). 

⇑ COX- protein (also at 

12 hr), also under the 

same or similar 

conditions: ⇑ PGE2

secretion, 

phosphorylation of 

p42/44 MAPK, and 

DNA synthesis. Tests 

with various modulators 

showed that inorganic 

arsenicIII elevates COX-2 

at the transcriptional and 

translational levels. 

Trouba 

and 

Germolec, 

2004 

Swiss 3T3 

mouse cells 

AsIII SA 1, 2.5, 5, 10, 20, 

40 

16 hr 1 

⇑ GSH synthesis; 

starting at 2.5: cell 

retraction and loss of 

thick cables of actin 

filaments, ⇓ cytoskeletal 

protein synthesis; 

starting at 20: ⇑ in 

protein sulfhydryl 

content of both 

cytoskeletal and 

cytosolic protein 

fractions, with the time 

course showing a slight 

decrease before the 

increase. There was also 

severe loss of 

microtubules. 

Li and 

Chou, 

1992 

UROtsa cells 

AsIII SA 

MMAV

DMAV

5, 50 for all 2 hr for all 5 for all 

Increased DNA binding 

of the AP-1 transcription 

factor, which is often 

associated with the 

regulation of genes 

involved in cell 

proliferation. For all 3 

chemicals the response 

was higher at dose of 50; 

the highest amount of 

binding was with SA. 

Simeonova 

et al., 2000 

C-90 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

UROtsa cells AsIII SA 10, 50 2 hr 10 

Use of a cDNA array 

consisting of 588 human 

genes, and other 

methods: 

At 10: ⇑ activity of 7 

genes; ⇓ activity in 6 

genes. 

At 50: ⇑ activity of 15 

genes; ⇓ activity in 6 

genes. 

Specifics: 

Genes affecting cell 

growth: ⇑ for c-fos, cjun, Pig 7, EGR-1, and 

Rho 8. 

Genes affecting cell 

growth arrest: ⇑ for 

GADD45 and 

GADD153.

Simeonova 

et al., 2000 

C-33A cells 

HeLa cells 

Jurkat cells 

LCL-EBV 

cells 

AsIII SA 

for all 

1, 10, 25, 50 for 

all 

24 hr 

for all 

None 

10 

1 

1 

p53 protein expression: 

No ⇑, slight ⇓ at high 

doses, very high basal 

level. 

⇑, peak at 25, low basal 

level. 

⇑, peak at 10, moderate 

basal level. 

⇑, peak at 10, very low 

basal level. 

Decreases above peak 

may result from cell 

death. 

Salazar et 

al., 1997 

HeLa cells AsIII SA 100, 200, 400 30 min 100 

⇑ GADD153 mRNA 

expression (harvested for 

RNA isolation after 4 

hours of incubation 

following the arsenite 

treatment). This effect 

was increased by 

pretreatment with BSO, 

PHEN (slight increase), 

BCS, or mannitol (an 

HO-

 scavenger). Effect 

was completely blocked 

by pretreatment with 

NAC. 

Guyton et 

al., 1996 

C-91 DRAFT—DO NOT CITE OR QUOTE
Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

WI38 cells 

Simian virus 

40 (SV40)- 

transformed 

subline of the 

above 

parental 

W138 line 

with twice the 

GPx specific 

activity of 

parental cells 

AsIII SA 

for both 

100, 200, 400 

for both 

30 min 100 for 

both 

⇑ GADD153 mRNA 

expression (harvested for 

RNA isolation after 4 

hours of incubation 

following the arsenite 

treatment). The increase 

was cut approximately in 

half (i.e., half the slope) 

in the transformed cell 

line. Other parts of this 

study showed that AP-1 

is critical to oxidative 

regulation of GADD153. 

Guyton et 

al., 1996 

JB6 Cl41 

cells 

AsIII SA 

AsV

3.125, 12.5, 50, 

200 

3.125, 12.5, 50, 

200 

3 hr 

50 

50 

⇑ activity of JNKs: 

stronger response at 50 

for AsV (sodium 

arsenate); both forms 

shown some response by 

1 hr at dose of 200; 

arsenic did not induce 

p53-dependent 

transactivation. 

Huang et 

al., 1999b 

JB6 Cl41 

cells 

AsIII SA 

AsV

200 

200 

0 min 

60 min 

200 

200 

⇑ phosphorylation of 

JNKs: stronger response 

for AsV (sodium 

arsenate). 

Huang et 

al., 1999b 

HFW cells 

(diploid 

human 

fibroblasts) 

AsIII SA 5, 10, 20 24 hr 5 

⇑ heme oxygenase 

activity (arsenic-induced 

synthesis of this enzyme 

was blocked by cotreatment with 

antioxidants sodium 

azide or DMSO); ⇑

ferritin. 

Lee and 

Ho, 1995 

HFW cells 

(diploid 

human 

fibroblasts) 

AsIII SA 1, 2.5, 5, 10, 20 24 hr 1 ⇑ GSH (by 20 level 

drops to control level). 

Lee and 

Ho, 1995 

HFW cells 

(diploid 

human 

fibroblasts) 

AsIII SA 0.5, 2, 10 24 hr See next 

column 

⇑ SOD activities, ⇓

catalase and GPx 

activities, with LOECs 

being 0.5, 2, and 10, 

respectively. 

Lee and 

Ho, 1995 

Both 

HL-60 cells 

and 

HaCaT cells 

AsIII SA 0.5, 20 3 days 0.5 

⇑ hTERT protein 

expression; 

however ⇓ hTERT 

protein expression at 20 

(i.e., significantly 

inhibited at higher 

concentration). 

Zhang et 

al., 2003 

C-92 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HaCaT cells AsIII SA 0.5, 10, 20 3 days 0.5 ⇑ telomerase activity; 

however, telomerase 

activity was below 

control level at 10 and 

even lower at 20. 

Zhang et 

al., 2003 

HL-60 cells AsIII SA 0.1, 0.5, 1, 10, 20 3 days 0.1 ⇑ telomerase activity; 

however, telomerase 

activity was below 

control level at 10 and 

even lower at 20. 

Zhang et 

al., 2003 

NB4 cells 

AsIII ATO 

0.75 8 days 0.75 

⇓ telomerase activity; ⇓

hTERT mRNA and 

protein levels; ⇓ c-myc 

mRNA and protein 

levels; ⇑ hTER mRNA 

level; no change in p53

mRNA or protein level; 

no change in Sp1 mRNA 

or protein levels. Further 

experiments showed that 

arsenic inhibits 

transcription of hTERT 

and inhibits the function 

of Sp1 in hTERT

transcription. 

Chou et 

al., 2001 

NB4 cells AsIII ATO 0.75 2 days 0.75 ⇓ hTERT mRNA. Chou et 

al., 2001 

NB4 cells AsIII ATO 0.1, 0.25 12 days 0.1 ⇓ hTERT mRNA. Chou et 

al., 2001 

HeLa cells 

LoVo cells 

MCF7 cells 

AsIII ATO 

for all 

2 

for all 

14 days 

for all 

2 

for all 

⇓ hTERT mRNA and 

⇓ c-myc mRNA 

for all. 

Chou et 

al., 2001 

C-93 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Normal 

human 

keratinocytes 

treated with 

50 mJ/cm2

UVB before 

or after 

inorganic 

arsenic 

treatment 

AsIII SA 

for both 

1, as pretreatment 

1, as posttreatment 

begun 24 hr after 

irradiation 

24 hr for both 

1 

 

None 

 No change from control 

in procaspase-8 and 

procaspase-9 protein 

levels or in caspase-3, 

caspase-8, and caspase-9 

enzyme activities; this is 

considered an LOEC 

because the inorganic 

arsenic-pretreatment 

blocked the effects of 

UVB described below. 

⇓ procaspase-8 protein 

level, slight ⇓

procaspase-9 protein 

level; ⇑ caspase-8 

enzyme activity; ⇑

caspase-9 enzyme 

activity; ⇑ caspase-9 

enzyme activity; effects 

similar to with UVB 

alone. 

Chen et al., 

2005b 

NB4 cells 

AsIII ATO 

for both 

1 

0.5, 1.0, 1.5, 2.0 

2 days 

3 days 

1 

1.0 

As a result of 

permeability changes in 

the outer mitochondrial 

membrane: 

slight release of 

cytochrome c into 

cytoplasm; complete 

release by 3 days of 

treatment. 

⇑ Cpp32 (was activated) 

as shown by ⇓ of its 

precursor. 

Jing et al., 

1999 

SHE cells AsIII SA 

AsV

6, 8 

50, 100, 150 

48 hr 

for both 

— From among these 

treatment groups, 5 

neoplastic transformed 

cell lines were produced 

that were shown to be 

tumorigenic. Of these: 

all had ⇑ c-Ha-ras 

(oncogene) mRNA 

expression; 

4 had ⇑ c-myc 

(oncogene) mRNA 

expression; 

a few other arsenictreated cell lines also 

showed the same effects. 

Takahashi 

et al., 2002 

C-94 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Peritoneal 

macrophages 

(PMs) from 

CDF1 mice 

AsIII SA 

AsV 

MMAV

DMAV

TMAV

1.25, 2.5, 5, 10 

125, 250, 500, 

1000 

1.25, 2.5, 5, 10 

mM 

1.25, 2.5, 5, 10 

mM 

1.25, 2.5, 5, 10 

mM 

48 hr for all 

1.25 

500 

None 

2.5 mM 

5 mM 

Changes in release of 

TNF-α from 

macrophages in the 

presence of both 

lipopolysaccharide and 

recombinant murine 

interferon γ, which are 

two compounds known 

to increase secretory 

functions of PMs: 

⇓ at 1.25, no change 

from control at 5; big ⇑

at 10. 

big ⇑ at 500 and much 

bigger ⇑ at 1000. 

no effect. 

⇓ at 2.5, 5 and 10 mM. 

⇓ at 5 and 10 mM. 

Sakurai et 

al., 1998 

U118MG 

cells 

AsIII ATO 1, 5, 10, 25 24 hr 1 or 5 

Changes in protein 

expression: 

p53: ⇑ at 1, ⇓ at 5 or 

higher; Bcl-2: ⇑ at 1 or 

higher. 

Bax: ⇓ at 1 or higher; 

HSP70: ⇑ at 5 or higher. 

Co-treatment with lipoic 

acid blocked all of these 

effects at an inorganic 

arsenicIII dose of 5. 

Cheng et 

al., 2007 

HaCaT cells 

(immortalized 

nontumorigenic 

human 

keratinocyte 

cell line) 

arsenic-TL 

cells (arsenictolerant cells, 

which are 

HaCaT cells 

that were 

cultured for 

28 weeks in 

100 nM AsIII

SA) 

AsIII SA 

for both 

20 for both 6 hr for both 20 for 

both 

⇑ caspase-3 activation. 

Much smaller ⇑ in 

caspase-3 activation than 

in HaCaT cells. 

Pi et al., 

2005 

C-95 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HUVEC cells AsIII ATO 20 2 hr 20 

⇑ expression of ICAM-1; 

effect was similarly 

strong after 24-hr 

treatment but weaker 

after 4- or 8-hr treatment 

(yet still ⇑ above control 

level). Effect was 

completely blocked by a 

1-hr pretreatment with 

15 mM NAC followed 

by a 

co-treatment of NAC 

with the AsIII-treatment. 

Griffin et 

al., 2003 

Apoptosis 

K562 cells AsIII ATO 2.5 12 hr 2.5 ⇑ annexin V, an 

apoptotic marker. 

Li and 

Broome, 

1999 

NCI (human 

myeloma cell 

line) 

AsIII ATO 1 24 hr 1 

 Apoptosis was 

demonstrated by 4,6-

diamidino-2-

phenylindole staining, by 

the demonstration of 

typical DNA ladders 

corresponding to 

internucleosomal 

cleavage, and by 

annexin-V and PI 

staining. Various 

indications of induction 

of apoptosis were also 

presented (with less 

detail) for at least 1 other 

myeloma cell line and 

for fresh myeloma cells. 

In the NCI cells, 

[3H]thymidine 

incorporation was also 

used to assess 

proliferation: the 50% 

growth-inhibitory 

concentration (IC50) in 

NCI cells was found to 

be 0.3 μM, based on 

concentrations tested of 

0.05, 0.1, 0.5, 1, 5, 10 

over 72 hr. Similar 

testing of 3 other human 

myeloma cell lines 

yielded IC50s of 0.1 for 1 

line and ∼1 for 2 other 

lines, with much less 

detail presented. 

Rousselot 

et al., 1999 

C-96 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

MGC-803 

cells 

AsIII ATO

0.01–1 

24 hr 0.01 Apoptosis detected by 

flow cytometry and by 

agarose gel 

electrophoresis of 

genomic DNA showing 

typical DNA ladder; at 

various doses apoptosis 

was also induced in 5 

other human malignant 

cell lines. 

Zhang et 

al., 1999 

Primary 

cultures of rat 

cerebellar 

neurons 

AsIII SA 

DMAV

5, 10 

5 mM 

12 hr 

48 hr 

5 

5 mM 

Demonstrated by “DNA 

ladders” with agarose gel 

electrophoresis and 

microscopic examination 

(nuclear fragmentation 

and/or condensation). 

Namgung 

and Xia, 

2001 

MC/CAR 

(human 

multiple 

myeloma cell 

line) 

AsIII ATO 1, 2, 5, 10 72 hr 2 Apoptosis was 

demonstrated by an 

analysis using a FACStar 

flow cytometer and by 

detection of cell 

membrane changes by 

labeling with annexin VFITC and annexin PI. 

Park et al., 

2000 

V79-C13 

Chinese 

hamster cell 

line 

AsIII SA 10 24 hr 10 Apoptotic cells appeared 

by 6 hr after treatment 

began and included 40% 

of cells by 24 hr; 

frequency gradually 

decreased during 48 hr 

of observation after 

treatment ended. 

Sciandrello 

et al., 2002 

HL-60 cells 

HaCaT cells 

AsIII SA 

for both 

0.1, 0.5, 1, 10, 20, 

40 

for both 

5 days 

for both 

1 or 

possibly 

0.5 

10 

By use of Hoechst/PI 

staining assay: 

⇑ in apoptosis for both; 

for both cell lines, there 

was the same general 

response, but to a lesser 

extent, when same 

treatments were given 

over 1 or 3 days. 

Zhang et 

al., 2003 

C-97 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HL-60 cells 

HaCaT cells 

SW13 cells 

SW480 cells 

HT1080 cells 

AsIII SA 

for all 

1, 10, 20, 40 

for all 

5 days 

for all 

1 

10 

∼20 

∼20 

1 

By use of Hoechst/PI 

staining assay: 

⇑ in apoptosis in all. 

SW13 and SW480 are 

telomerase negative cell 

lines, and they showed 

much less apoptosis at 

all concentrations than 

the other 3 cell lines. 

HT1080 is a telomerase 

positive cell line, and it 

was intermediate in the 

amount of apoptosis at 

all concentrations to HL60 (which was higher) 

and HaCaT. Thus there 

is a strong positive 

correlation between 

telomerase activity and 

susceptibility to arsenicinduced apoptosis. 

Zhang et 

al., 2003 

TRL 1215 

cells 

TRL 1215 

cells 

pretreated 

with 50 μM 

BSO for 24 hr 

to deplete 

GSH levels 

and then cotreated with 

50 μM BSO 

MMAV 

for both 

5 mM 

for both 

24 hr 

for both 

None 

5 mM 

Apoptosis demonstrated 

by TUNEL staining: 

there was little evidence 

of induction of apoptosis 

by MMAV alone; 

however, the cells also 

treated with BSO 

showed considerable 

apoptosis. 

Sakurai et 

al., 2005a 

TRL 1215 

cells 

DMAV 5 mM 24 hr 5 mM 

Apoptosis demonstrated 

by TUNEL staining: 

huge ⇑, much more 

extensive that that of the 

considerable level of 

apoptosis reported in row 

above for MMAV + BSO. 

Sakurai et 

al., 2005a 

C-98 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

TRL 1215 

cells 

TRL 1215 

cells 

pretreated 

with 50 μM 

BSO for 24 hr 

to deplete 

GSH levels 

and then cotreated with 

50 μM BSO 

MMAV 

for both 

5 mM 

for both 

12, 24, 36, or 

48 hr for both 

5 mM 

5 mM 

Apoptosis demonstrated 

by FACS analysis after 

annexin-V and PI 

staining: 

 5 mM MMAV alone 

caused some apoptosis 

after 48 hr; however, that 

response was slight 

compared to the response 

of the MMAV + BSO 

group after only 24 hr, 

and the MMAV + BSO 

group showed huge ⇑ at 

36 hr and even bigger ⇑

at 48 hr. After 48 hr, the 

percentages of annexinpositive cells were as 

follows: control, 1.9%, 

BSO alone, 6.7%; MMAV

alone, 10.6%; MMAV + 

BSO, 64%. The PI 

staining showed that by 

48 hr there were also 

numerous induced 

necrotic cells in the 

MMAV + BSO group. 

Sakurai et 

al., 2005a 

TRL 1215 

cells 

TRL 1215 

cells 

pretreated 

with 50 μM 

BSO for 24 hr 

to deplete 

GSH levels 

and then cotreated with 

50 μM BSO 

MMAV 

for both 

5 mM 

for both 

24 hr 

for both 

None 

5 mM 

Apoptosis demonstrated 

by agarose gel 

electrophoresis showing 

induced 

internucleosomal DNA 

fragmentation: 

substantial DNA 

fragmentation in 

MMAV + BSO group; no 

effect with MMAV alone. 

Sakurai et 

al., 2005a 

C-99 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

TRL 1215 

cells 

TRL 1215 

cells 

pretreated 

with 50 μM 

BSO for 24 hr 

to deplete 

GSH levels 

and then cotreated with 

50 μM BSO 

DMAV 

for both 

5 mM 

for both 

24 hr 

for both 

5 mM 

5 mM 

Apoptosis demonstrated 

by agarose gel 

electrophoresis showing 

induced 

internucleosomal DNA 

fragmentation: massive ⇑

with DMAV alone (many 

times more than with 

MMAV + BSO in 

previous row); slight ⇑ in 

DMAV + BSO group 

(about the same as with 

MMAV + BSO in 

previous row). 

Sakurai et 

al., 2005a 

TRL 1215 

cells 

TRL 1215 

cells 

pretreated 

with 50 μM 

BSO for 24 hr 

to deplete 

GSH levels 

and then cotreated with 

50 μM BSO 

MMAV 

for both 

5 mM 

for both 

12 hr 

for both 

None 

5 mM 

Cellular caspase-3 

activation: ⇑ to ∼1.6x in 

MMAV + BSO group; no 

effect 

without BSO; other 

experiments showed that 

co-treatment with 150 

μM 

Z-DEVD-FMK (a 

caspase 3 inhibitor) 

during preincubation 

period and during a 24-hr 

MMAV treatment blocked 

almost all or all of the 

cytotoxicity detected by 

AB assay (i.e., ∼35% 

survival without 

inhibitor, ∼92% survival 

with inhibitor); with a 

48-hr MMAV + BSO 

treatment, Z-DEVDFMK caused cytotoxicity 

to be markedly reduced 

(i.e., ∼7% survival 

without inhibitor, ∼42% 

survival with inhibitor). 

Sakurai et 

al., 2005a 

Primary 

keratinocytes 

(in third 

passage) 

obtained from 

foreskins of 

adults 

AsIII SA 1, 5, 10 48 hr 1 

Apoptosis detected by 

the presence of DNA 

ladders after agarose gel 

electrophoresis: much 

bigger ⇑ at two higher 

doses, which showed a 

similar effect. 

Liao et al., 

2004 

C-100 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Primary 

keratinocytes 

(in third 

passage) 

obtained from 

foreskins of 

adults 

AsIII SA 1, 5, 10 48 hr Various 

Protein levels detected 

by Western blotting: 

FADD: ⇑ at 1, bigger ⇑

at 5 and 10. 

Caspase-8 (p18, active): 

⇑ at 1, huge ⇑ at 5 and 

10. 

Caspase-3 (p20, active): 

huge ⇑ at 5 and 10. 

Cleaved PARP (85 kD): 

⇑ at 5 and 10; additional 

experiments with and 

without modulators 

confirmed the 

involvement of the Fasassociated pathway in 

inorganic arsenicinduced apoptosis. 

Liao et al., 

2004 

HeLa cells 

AsIII ATO 

2 3 days 2 

Induced apoptosis 

(experimental – control) 

detected by Annexin 

V/PI flow cytometry: 

∼13% for inorganic 

arsenic alone; ∼3% for 

10 μM emodin alone; 

∼41% for inorganic 

arsenic plus 10 μM 

emodin; ∼14% for 

inorganic arsenic with 

both 10 μM emodin and 

1.5 mM NAC. Other 

experiments showed that 

the effect of emodin in 

enhancing inorganic 

arsenic-induced 

apoptosis involved a 

decrease of 

mitochondrial membrane 

potential. Emodin was 

used because it has a 

semiquinone structure 

that is likely to increase 

the generation of 

intracellular ROS. 

Yi et al., 

2004 

C-101 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HeLa cells AsIII ATO 2 3 days 2 

Induced apoptosis 

(experimental – control) 

detected by Annexin VFITC/PI flow cytometry: 

27.0% for inorganic 

arsenic alone; 6.9% for 

30 μM emodin alone; 

44.1% for inorganic 

arsenic plus 30 μM 

emodin; 20.4% for 

inorganic arsenic with 

both 30 μM emodin and 

1.5 mM NAC. Emodin 

and inorganic arsenic 

synergistically interacted 

to greatly ⇑ the ROS 

level and to cause 

cytotoxicity. 

Pretreatment or cotreatment with NAC 

blocked the synergism 

for both effects. A 2μM 

inorganic arsenic 

treatment of 90 min 

caused an ⇑ in ROS to 

∼2.0x (with wide 

confidence limits) and, in 

a treatment lasting 48 hr, 

about 20% cytotoxicity. 

Wang et 

al., 2005 

AR230-s 

cells, 

AR230-r 

cells, 

KCL22-s 

cells, KCL22-

r cells 

AsIII ATO 

 1 24 hr None 

Apoptosis detected by 

Annexin V-FLUOS 

staining kit and flow 

cytometry: NSE in any 

of the 4 cell lines with 

ATO or 100 μM BSO 

treatments alone. For the 

combined treatment, 

induced rates 

(experimental – control) 

were: AR230-s, ∼35%; 

AR230-r, ∼35%; 

KCL22-s, ∼10%; 

KCL22-r, ∼13%. 

Konig et 

al., 2007 

C-102 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

AR230-r 

cells, 

KCL22-r cells 

AsIII ATO 

 

1 24 hr None 

Western blot analyses: 

inorganic arsenic alone 

caused NSE on protein 

levels of tyrosine 

phosphorylated Bcr-Abl 

or total cellular Bcr-Abl 

in either cell line. In 

both cell lines, combined 

treatment of inorganic 

arsenic with 100 μM 

BSO yielded huge ⇓ in 

both proteins. In nonimatinib resistant CML 

cells, unlike in these 2 

imatinib-resistant cell 

lines, inorganic arsenic 

alone had been shown to 

suppress Bcr-Abl 

activity. 

Konig et 

al., 2007 

U-937 cells 

NB4 cells 

HL-60 cells 

AsIII ATO 

for all 

1, 2, 4, 8 

0.5, 1, 2, 4 

1, 2, 4 

24 hr 

for all 

4 

1 

2 

Induced apoptosis 

(experimental – control) 

based on chromatin 

fragmentation: 

U-937 cells: 1, NSE; 2, 

∼2%; 4, ∼14%; 8, ∼85%. 

NB4 cells: 0.5, NSE; 1, 

∼5%; 2, ∼33%; 4, ∼63%. 

HL-60 cells: 1, NSE; 2, 

∼5%; 4, ∼22%. 

Induction of apoptosis 

was potentiated by cotreatment with PI3K 

inhibitors LY294002 and 

wortmannin, and by the 

Akt inhibitor Akti5. 

Ramos et 

al., 2005 

C-103 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

U-937 cells 

AsIII ATO 

4 Various 4 

⇓ in Akt phosphorylation 

after 24 hr (not by 14 hr); 

⇑ in caspase 3 activity to 

∼3x after 24 hr; ⇑ in 

cytochrome c protein 

(released from 

mitochondria) after 14 

hr; big ⇑ in activated 

Bax after 14 hr; big ⇑ in 

HSP 27 after 14 and 24 

hr; 

big ⇑ in HSP 70 after 14 

and 24 hr. The 

potentiation of apoptosis 

by inhibitors mentioned 

in prior row involved 

more extreme changes in 

the same direction for pAkt, caspase 3, 

cytochrome c, and Bax 

activation as well as 

attenuation of HSP27 

expression. It also 

involved increased 

disruption of the 

mitochondrial 

transmembrane potential. 

Ramos et 

al., 2005 

HK-2 cells 

AsIII SA 

AsV 

0.1, 1, 10 

for both 

6, 24 hr 

0.1 at 24 

hr 

Probably 1 at 

24 hr 

To assess mitochondrial 

function, depolarization 

of mitochondrial 

membrane was detected 

using MitoTracker Red, 

a mitochondrion 

selective dye. Effect of 

dose of 1 of AsIII

appeared equivalent to 

that of dose of 10 of AsV. 

 Effect increased with 

dose and time. 

Peraza et 

al., 2006 

C-104 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HK-2 cells 

 

AsIII SA 0.1, 1, 10, 25 24 hr 0.1 

Induced apoptosis 

(experimental – control) 

detected by Annexin VFITC/PI flow cytometry: 

0.1, ∼36%; 1, ∼23%; 10, 

∼15%; 25, ∼15%. 

Induced necrotic cells 

(experimental – control) 

detected by same 

method: 0.1, ∼2.5%; 1, 

∼3%; 10, ∼6%; 25, 

∼24%. Apoptotic cells 

detected in this way were 

said to be in early 

apoptosis. Examination 

by transmission electron 

microscopy showed that 

most such cells failed to 

complete apoptosis and 

ultimately underwent 

necrosis instead. They 

suggested that inorganic 

arsenic was so toxic to 

mitochondria that they 

lost “their ability to keep 

the cell on course for 

apoptotic cell death.” 

Peraza et 

al., 2006 

APL primary 

cells 

K562 cells 

NB4 cells 

AsIII ATO 3 24 hr 3 for all 

Apoptosis rates (control 

rates were not provided), 

detected by FITCannexin V and PI 

double-staining: 

52.2% 

27.6% 

56.6% 

Sahu and 

Jena, 2005 

Thymocytes 

from adult 

male 

BALB/cByJ 

mice 

AsIII ATO 

AsV

5 

for both 

3, 10, 22 hr 

for both 

None 

None 

NSE at any time point 

for induction of 

apoptosis by any of the 

following types of 

analysis: (1) “Annexin 

V-FITC positive” 

without loss of 

membrane impermeance 

(i.e., “7-AAD negative”) 

to identify early 

apoptotic cells, (2) DNA 

loss, and (3) both 

“Annexin V-FITC 

positive” and “7-AAD 

positive” for cells in the 

final stages of cell death. 

Mondal et 

al., 2005 

C-105 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Jurkat cells 

Namalwa 

cells 

NB4 cells 

U937 cells 

AsIII ATO 

for all 

1, 2 

for all 

24 hr 

for all 

None 

2 

1 

None 

Induced apoptosis 

(experimental – control) 

detected by fluorescence 

microscope analysis after 

staining with AO and 

EB: 

Namalwa cells: 1, ∼1%; 

2, ∼16%. 

NB4 cells: 1, ∼12%; 2, 

∼26%. 

NSE at dose of 2 in 

Jurkat and U937 cells. 

Pretreatment with NAC 

or Z-VAD-FMK blocked 

induction of apoptosis in 

Namalwa and NB4 cells. 

Chen et al., 

2006 

Jurkat cells 

Namalwa 

cells 

NB4 cells 

U937 cells 

AsIII ATO 

for all 

2 

for all 

24 hr 

for all 

None 

2 

2 

None 

Western blot analysis: 

⇑ in PARP-cleavage and 

⇓ in procaspase-3 level 

in both Namalwa and 

NB4 cells but not in the 

other two cell lines; 

inorganic arsenic did not 

induce JNK 

phosphorylation. 

Chen et al., 

2006 

NB4 cells 

U937 cells 

AsIII ATO 

for both 1, 2, 4, 6 

for both 

24 hr 

for both 

1 

4 

Induced apoptosis 

(experimental – control) 

detected by fluorescence 

microscope analysis after 

staining with AO and 

EB: 

NB4 cells: 1, ∼6%; 2, 

∼30%; 4, ∼70%; 6, 85%. 

U937 cells: 1, ∼0%; 2, 

∼4%; 4, ∼15%; 6, 12%. 

NB4 cells showed more 

severe cell growth 

inhibition at doses of ≥2. 

 Also, Western blot 

analysis showed that 

inorganic arsenic 

induced PARP cleavage 

in a dose-dependent 

pattern in NB4 cells. In 

U937 cells there was 

only very slight PARP 

cleavage at the highest 

dose. JNK 

phosphorylation did not 

occur in either cell line. 

Chen et al., 

2006 

C-106 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

MEFs that are 

wt 

MEFs that are 

DKOs for 

Bax and Bak 

AsIII ATO 

both 

10 

for both 

8 hr 

for both 

10 

None 

Various indicators of 

apoptosis: 

Induced (experimental – 

control) DNA 

fragmentation: wt, ∼7%; 

DKO, NSE. 

Cytochrome c release: ⇑

in wt, NSE in DKO. 

Induced caspase-3 

activity: wt, ∼140 units; 

DKO, none. Caspase-3 

activity was only 

detected in DKO cells 

when they were 

permeabilized and 

incubated for 1 hr in the 

presence of 4 μM 

exogenous cytochrome c. 

 These and other 

experiments showed that 

mitochondrial events 

associated with apoptotic 

cell death induced at 

concentrations such as 

10 or less required Bax 

and/or Bak. 

Nutt et al., 

2005 

MEFs that are 

wt or DKOs 

for Bax and 

Bak 

AsIII ATO 10, 125, 500, 1000 

Results from several experiments suggested that 

extramitochondrial thiol oxidation leading to changes in 

intracellular Ca2+ compartmentalization plays a critical 

role in inorganic arsenic-induced cytochrome c release. 

At concentrations of 125 and higher, Bax and Bak 

became irrelevant to the mechanism of cytotoxicity and 

cell death resulted from oxidative stress that led to 

necrosis. ROS seem to be implicated in a 

concentration-dependent mechanistic switch between 

apoptosis and necrosis. 

Nutt et al., 

2005 

Namalwa 

cells 

NB4 cells 

AsIII ATO 

for both 

1 

for both 

24 hr 

for both 

1 

for both 

without 

BSO 

Induced apoptosis 

(experimental – control) 

detected by fluorescence 

microscope analysis after 

staining with AO and 

EB: 

Namalwa cells: inorganic 

arsenic, ∼6%; inorganic 

arsenic + 10 μM BSO, 

∼29%. 

NB4 cells: inorganic 

arsenic, ∼8%; inorganic 

arsenic + 10 μM BSO, 

∼47%. 

BSO treatments 

markedly reduced GSH 

levels. 

Chen et al., 

2006 

C-107 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Jurkat cells 

U937 cells 

AsIII ATO 

for both 

 

1 

for both 

48 hr 

for both 

None 

for both 

without 

BSO 

Induced apoptosis 

(experimental – control) 

detected by fluorescence 

microscope analysis after 

staining with AO and 

EB: 

Jurkat cells: inorganic 

arsenic, NSE; inorganic 

arsenic + 10 μM BSO, 

∼25%. 

U937 cells: inorganic 

arsenic, NSE; inorganic 

arsenic + 10 μM BSO, 

∼67%. 

BSO treatments 

markedly reduced GSH 

levels. 

Chen et al., 

2006 

Jurkat cells 

Namalwa 

cells 

NB4 cells 

U937 cells 

AsIII ATO 

for all 

1 

for all 

24 hr 

for Namalwa 

and NB4 cells, 

48 hr for other 

2 lines 

1 for all 

with BSO 

Results of Western blot 

analysis in all 4 cell lines 

following co-treatment 

of inorganic arsenic with 

10 μM BSO: 

Big ⇑ in PARP-cleavage; 

big ⇓ in procaspase-3 

level. 

Big ⇑ in JNK 

phosphorylation (the 

latter effect was not seen 

in absence of BSO cotreatment). 

Chen et al., 

2006 

Jurkat cells 

U937 cells 

AsIII ATO 

for both 

1 

for both 

Various, for 

6–72 hr 

Time course experiments for cotreatment with 10 μM BSO showed ⇑

in PARP-cleavage; 

⇓ in procaspase-3 level; strong ⇑ in 

JNK phosphorylation. Induced 

apoptosis increased to ∼85% and 

∼50% by 72 hr in U937 and Jurkat 

cells, respectively. 

Chen et al., 

2006 

C-108 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

U937 cells 

AsIII ATO 1 48 hr 

1, but only 

with BSO 

co-treatment 

Induced apoptosis 

(experimental – control) 

detected by fluorescence 

microscope analysis after 

staining with AO and 

EB: ~55% following the 

co-treatment with BSO; 

this ⇑ was not 

significantly decreased 

by 4-hr treatments with 

either 10 mM NAC or 

200 units of catalase 

even though those 

treatments substantially 

decreased H2O2 levels. 

Moreover, NAC and 

catalase did not block the 

JNK activation caused 

by the inorganic arsenic 

+ BSO treatment. 

Chen et al., 

2006 

U937 cells AsIII ATO 1 48 hr 1, but only 

with BSO 

co-treatment 

Results of Western blot 

analyses: huge ⇑ in DR5, 

huge ⇓ in Bid, and ⇓ in 

IκBα following cotreatment with 10 μM 

BSO; NSE on these 3 

proteins after inorganic 

arsenic or BSO alone. 

Experiments with 

inhibitors suggested that 

(1) both caspase- and 

JNK-mediated pathways 

(due to activation of NFκB) participate in the 

induction of apoptosis 

that occurs following cotreatment with inorganic 

arsenic and BSO and (2) 

that JNK increases DR5 

protein levels that in turn 

mediate that apoptosis. 

Chen et al., 

2006 

C-109 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

NB4 cells, 

NB4-AsR

, and 

APL primary 

cells 

AsIII ATO 

 A series of experiments was conducted involving 24–72 hr treatments with 

concentrations of inorganic arsenic of 0.125–10 μM. Tests of MEK1 mRNA 

knockdown using inorganic arsenic treatments and MEK1 inhibitors (namely, 

PD98059 at 40 μM and PD184352 at 1 μM) showed that MEK1 inhibitors and 

inorganic arsenic synergize to induce apoptosis. Although inorganic arsenic 

induces apoptosis, it also causes ERK1/2 activation, which tends to decrease 

the extent of apoptosis by causing phosphorylation at Ser112 of the 

proapoptotic Bad protein. Phosphorylated Bad protein does not 

heterodimerize with the Bcl proteins. The only known function of the Bad 

protein is to bind (i.e., heterodimerize) with the death antagonist Bcl-2 family 

proteins, Bcl-2 and Bcl-xL, thereby blocking their antiapoptotic action by 

preventing them from binding to Bax/Bak. Because MEK1 inhibitors block 

this ERK1/2 activation and the phosphorylation of BAD, there is more 

nonphosphorylated Bad protein to heterodimerize with the Bcl-2 proteins and 

keep them from functioning to block apoptosis. In this way, exposure to 

inorganic arsenic in the presence of MEK1 inhibitors greatly increases the 

extent of apoptosis. 

Lunghi et 

al., 2005 

Primary AML 

blasts from 25 

patients with 

non-APL 

AML 

AsIII ATO 

In experiments involving 48-hr treatments that used concentrations of 

inorganic arsenic of 0.125–10 μM in the presence or absence of 

concentrations of the MEK1 inhibitor PD184352 of 0.1–10 μM, synergistic, 

additive, or antagonistic interactions in the induction of apoptosis were found 

in primary cells from 13, 8, and 4 patients, respectively. The p53-related gene 

p73 was shown to be the molecular target of importance in this interaction, 

and the synergism had the following basis. Inorganic arsenic induced both the 

proapoptotic and antiproliferative TAp73 and the antiapoptotic and 

proproliferative ∆Np73 isoforms, with no net effect on apoptosis because the 

TAp73/∆Np73 ratio did not change. The MEK1 inhibitor reduced the level of 

∆Np73 and blunted the inorganic arsenic-induced up-regulation of ∆Np73, 

with the result that the TAp73/∆Np73 ratio increased, leading to more 

apoptosis. At 1 μM, inorganic arsenic induced only p73, but at doses ≥2 μM) 

it also promoted accumulation of p53 protein levels, which also caused 

apoptosis. 

Lunghi et 

al., 2006 

C-110 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

CHO K1 cells AsIII SA 20, 40, 80 4 hr 20 

Apoptosis detected by 

flow cytometry and by 

the presence of DNA 

ladders from 

internucleosomal DNA 

degradation—ladder 

effect did not appear 

until 24 hr after 

treatment. At dose of 40, 

it took 8 hours after 

treatment before 

apoptosis could be 

detected by flow 

cytometry. Reduced 

levels of apoptosis 

resulted from treatment 

with various modulators 

(antioxidants, a copper 

ion chelator, a protein 

kinase inhibitor, and a 

protein synthesis 

inhibitor) either 

simultaneously or, in 

some instances, 

immediately following 

the arsenic treatment. 

 

Wang et 

al., 1996 

Normal 

human 

keratinocytes 

treated with 

50 mJ/cm2

UVB before 

or after 

inorganic 

arsenic 

treatment 

AsIII SA 

for both 

1, as pretreatment 

1, as posttreatment 

begun 24 hr after 

irradiation 

24 hr for both 

1 

 

None 

Apoptosis as detected by 

PI staining and TUNEL 

assay: the inorganic 

arsenic treatment alone 

did not induce a 

significant increase in 

apoptosis or cytotoxicity; 

⇓ in the level of UVinduced apoptosis to 

control levels, with a 

corresponding ⇓ in 

cytotoxicity to control 

levels. 

A similar amount of 

apoptosis was seen as 

with UVB alone, or 

possibly apoptosis 

increased slightly; 

cytotoxicity was similar 

to that with UVB 

treatment alone or 

possibly slightly more 

extreme. 

Chen et al., 

2005b 

C-111 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

A mouse 

fibroblast cell 

line as well as 

various stable 

transfectants 

of JB6 Cl41 

cells 

AsIII SA 

AsV

Various — — Various tests indicated 

that p53 is not involved 

in arsenic-induced 

apoptosis. The pathway 

of JNKs was shown to 

play an essential role in 

arsenic-induced 

apoptosis. For example, 

such apoptosis was 

blocked by expression of 

the dominant-negative 

mutant of JNK1. 

Huang et 

al., 1999b 

NB4 cells 

U937 cells 

HL-60 cells 

AsIII ATO 

for all 2 for all 

2 days 

for all 

2 

2 

2 

Percentages of apoptosis 

determined by 

fluorescent microscopy, 

and units of basal 

activity of GSTπ, GPx, 

and CAT, respectively: 

67.5%, 94.0, 28.3, 25.8. 

5.6%, 212.1, 67.6, 170.5. 

5.8%, 138.6, 55.5, 198.3. 

These data and others 

showed that the higher 

the basal levels of these 

3 enzymes, the less the 

inorganic arsenicinduced apoptosis. 

Higher activities of these 

enzymes decrease the 

amount of H2O2 in cells. 

 Modulators that increase 

activities of these 

enzymes were shown to 

decrease apoptosis and 

vice versa. 

Jing et al., 

1999 

Mouse 

291.03C 

keratinocytes 

AsIII SA 

for both 

5 

5 

48 hr 

60 hr 

5 

5 

Apoptosis measured by 

flow cytometry: 

⇑ by 4.20% over control, 

which was 0.74%. 

⇑ by 7.31% over control. 

Wu et al., 

2005 

C-112 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Mouse 

291.03C 

keratinocytes 

irradiated 

immediately 

after the 

arsenic 

treatment with 

a single dose 

of 0.30k J/m2

UV 

AsIII SA 

for all 

None (i.e., UV 

only) 

2.5 

5.0 

— 

24 hr 

24 hr 

— 

2.5 

5.0 

Apoptosis measured by 

flow cytometry 24 hr 

after the dose of UV: 

⇑ by 26.87% over 

control, which was 

0.74%. 

⇑ by 20.62% over 

control. 

⇑ by 9.78% over control. 

Thus, both pretreatments 

with AsIII SA markedly 

reduced the amount of 

UV-induced apoptosis. 

In parallel with the 

above, UV-induced 

caspase 3/7 activity was 

also decreased by both 

treatments. 

Wu et al., 

2005 

HaCaT cells 

(immortalized

, 

nontumorigenic 

human 

keratinocyte 

cell line) 

 

arsenic-TL 

cells (arsenictolerant cells, 

which are 

HaCaT cells 

that were 

cultured for 

28 weeks in 

100 nM AsIII

SA) 

AsIII SA 

for both 

20, 40, 60, 80 for 

both 

24 hr 

for both 

20 

 

40 

Apoptosis detected using 

flow cytometry 

following staining with 

Annexin V and PI: 

⇑ in apoptosis. 

Much smaller ⇑ in 

apoptosis. There was a 

significant decrease in 

apoptosis compared to 

HaCaT cells at all 4 dose 

levels. A similar 

resistance by arsenic-TL 

cells was seen to 

apoptosis induction by 

25 J/cm2 of UVA, as 

well as by cisplatin, 

etoposide, and 

doxorubicin. ArsenicTL cells showed greatly 

increased stability of 

nuclear P-PKB, and 

pretreatment with 

chemicals that inhibit 

PKB phosphorylation 

blocked inorganic 

arsenic-induced acquired 

apoptotic resistance. 

Pi et al., 

2005 

C-113 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

MCF-7 cells AsIII ATO 3 36 hr 3 Apoptosis detected based 

on electrophoretic 

analysis of DNA 

fragmentation: 

~18% of the cells were 

apoptotic. 

Ling et al., 

2002 

U-2OS cells AsIII SA 0.1, 1, 10 24 hr 0.1 

TUNEL staining assay 

was used to detect 

apoptotic cells after 0, 

24, or 48 hr of posttreatment culturing in 

arsenic-free medium. 

At dose of 0.1, apoptotic 

cells were ~0%, ~0.3%, 

and ~3.6%, respectively. 

At dose of 1, apoptotic 

cells were ~0%, ~0.2%, 

and ~3.4%, respectively. 

At dose of 10, apoptotic 

cells were ~0%, ~0%, 

and ~0%, respectively. 

Note that a 24-hr 

treatment with SA 

affected apoptosis only if 

there was an additional 

24-hr or longer period of 

culturing in SA-free 

medium between the end 

of the SA treatment and 

when the assay was 

done. 

Komissaro

va et al., 

2005 

C-114 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

U-2OS cells AsIII SA 0.1, 1, 10 24 hr 0.1 

Assay utilizing 

activation of cellular 

caspase-3 was used to 

detect apoptotic cells 

after 0, 24, or 48 hr of 

post-treatment culturing 

in arsenic-free medium: 

At dose of 0.1, apoptotic 

cells were ~0%, ~1.3%, 

and ~6.2%, respectively. 

At dose of 1, apoptotic 

cells were ~0%, ~0.3%, 

and ~5.4%, respectively. 

At dose of 10, apoptotic 

cells were ~0%, ~0%, 

and ~0%, respectively. 

Note that a 24-hr 

treatment with SA 

affected apoptosis only if 

there was an additional 

24-hr or longer period of 

culturing in SA-free 

medium between the end 

of the SA treatment and 

when the assay was 

done. 

Komissaro

va et al., 

2005 

Undifferentiat

ed PC12 cells 

AsIII ATO 8 24 hr 8 Induction of apoptosis 

detected by annexin V 

binding and caspase 

activity: 

∼55% of cells with 

apoptotic death, rest with 

necrotic death; at 6 hrs, 

∼60% of dead cells were 

apoptotic. 

Piga et al., 

2007 

PARP-1+/+

MEF cells 

PARP-1-/-

MEF cells 

AsIII SA 

for both 

11.5, 23 

for both 

24 hr 

for both 

11.5 

11.5 

Induction of apoptosis 

detected by PI and 

RNase staining and flow 

cytometry, visualized as 

sub-G1 population and 

reported as % of 

apoptosis 

(controls were always 

0%): 

~6% at 11.5, ~9% at 23 

~11% at 11.5, ~21% at 

23. 

Poonepalli 

et al., 2005 

C-115 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

PARP-1+/+

MEF cells 

PARP-1-/-

MEF cells 

AsIII SA 

for both 

11.5, 23 

for both 

48 hr 

for both 

11.5 

11.5 

Induction of apoptosis 

detected by PI and 

RNase staining and flow 

cytometry, visualized as 

sub-G1 population and 

reported as % of 

apoptosis 

(controls were always 

0%): 

~23% at 11.5, ~32% at 

23. 

~40% at 11.5, ~62% at 

23. 

Poonepalli 

et al., 2005 

JB6 C141 

cells, 

transfected 

with IKKβKM to greatly 

reduce COX2 induction 

JB6 C141 

cells 

transfected 

with vector 

only 

AsIII SA 

for both 

20, 40 

for both 

24 hr 

for both 

20 

20 

Induction of apoptosis 

detected by PI staining 

and flow cytometry: 

⇑⇑ in apoptosis: medium 

alone, 0.83%; 20, 

12.60%, 40, 41.33%;. 

Slight ⇑ in apoptosis: 

medium alone, 1.03%; 

20, 4.58%, 40, 7.23%. 

Similar conclusion was 

reached using TUNEL 

assay and flow 

cytometry. 

Ouyang et 

al., 2007 

JB6 C141 

cells, after 

knockdown of 

endogenous 

COX-2 

expression to 

low levels by 

its specific 

siRNA 

JB6 C141 

cells 

transfected 

with mock 

vector for the 

siRNA, with 

normal COX2 expression 

AsIII SA 

for both 

10, 20 

for both 

36 hr 

for both 

10 

10 

Induction of apoptosis 

detected by PI staining 

and flow cytometry: 

⇑⇑ in apopthosis: 

medium alone, 4.14%; 

10, 28.45%, 20, 49.22%. 

Much smaller ⇑ in 

apoptosis: medium 

alone, 1.86%; 10, 

10.52%, 20, 26.60%. 

Another experiment 

showed that pretreatment 

of normal JB6 C141 cells 

with NS398, an inhibitor 

of COX-2, markedly ⇑

amount of apoptosis. 

Ouyang et 

al., 2007 

C-116 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

MEF cells 

that were 

made IKKβ-/-

so that they 

markedly 

overexpressed 

COX-2 

MEF cells 

that had the 

vector only, 

with normal 

(low) level of 

COX-2 

AsIII SA 

for both 

20 

for both 

36 hr 

for both 

20 

20 

Induction of apoptosis 

detected by PI staining 

and flow cytometry: 

Slight ⇑ in apoptosis: 

medium alone, 0.68%; 

20, 6.35%. 

Big ⇑ in apoptosis: 

medium alone, 0.87%; 

20, 49.62%. 

Thus, COX-2 protects 

cells from apoptosis. 

Ouyang et 

al., 2007 

SY-5Y cells 

HEK 293 

cells 

AsIII ATO 

for both 1 

for both 

24 hr 

48 hr 

72 hr 

1 

for all 

Induction of apoptosis 

detected by Hoechst 

staining: 

Response as % of control 

in SY-5Y and HEK 293 

cells, respectively, for 

each duration of 

treatment: 

266%, 156%. 

152%, 192%. 

214%, 200%. 

There was NSE on the 

mitotic index at any 

time. 

Florea et 

al., 2007 

C-117 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

PMs from 

CDF1 mice 

AsIII SA 

AsV 

MMAV

DMAV

TMAV

10 

1 mM 

10 mM 

10 mM 

10 mM 

48 hr 

for all 

10 

1 mM 

10 mM 

10 mM 

None 

Apoptosis detected based 

on electrophoretic 

analysis of DNA 

fragmentation and by 

TUNEL staining. The 

particular assay shown in 

this row used cellular 

morphological changes 

to assess apoptosis and 

the AlamarBlue assay to 

measure cell death. 

Approximate resulting 

percentages of cell death 

(listed first) and 

apoptotic cells (listed 

second) for the 5 

compounds follow: 

For AsIII SA: 82% and 

23%. 

For AsV: 65% and 17%. 

For MMAV: 10% and 7%. 

For DMAV: 100% and 

100%. 

For TMAV: 12% and 

none. 

Thus DMAV was unusual 

in causing almost 

entirely apoptotic cell 

death, while the 

inorganic arsenicals 

caused mainly necrotic 

cell death. 

Sakurai et 

al., 1998 

TK6 cells 

AsIII SA 

AsIII ATO 

0.1, 1 

for both 

24 hr 

for both 

1 

1 

Apoptosis identified 

using APO2.7 antibody: 

⇑ to 5.0% from 3.6% in 

control. 

⇑ to 5.5% from 3.6% in 

control. 

Hornhardt 

et al., 2006 

C-118 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

TK6 cells 

irradiated 

with 1, 2, or 4 

Gy of 69 

cGy/min 

gamma 

radiation at 

beginning of 

inorganic 

arsenic 

treatment 

AsIII SA 

AsIII ATO 

0.1, 1 

for both 

24 hr 

for both 

None 

1 

Apoptosis identified 

using APO2.7 antibody: 

At dose of 1: 1 Gy, 

9.1%; 2 Gy, 10.4%, 4 

Gy, 22.6%; SA had no 

significant effect on any 

of them. 

At dose of 1: 1 Gy, 

12.5%; 2 Gy, 21.75%, 4 

Gy, 38.6%; ATO caused 

a significant increase 

over the control (no 

inorganic arsenic + 

radiation) at all 3 

radiation doses. This 

was a synergistic 

interaction. 

Hornhardt 

et al., 2006 

HCT116 cells 

(securin +/+) 

HCT116 cells 

(securin -/-) 

AsIII SA 

for both 

16 

for both 

24 hr 

for both 

16 

16 

Induced apoptosis (i.e., 

experimental – control) 

detected using 

fluorescent microscopy 

after Hoechst staining: 

securin +/+: ∼6%; 

securin -/-: ∼10%; 

with the amount of 

apoptosis in the null 

mutant being 

significantly higher. 

Chao et al., 

2006a 

C-119 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

NB4 cells 

NB4-M-AsR2 

cells 

IM9 cells 

AsIII ATO 

for all 

0.5, 1 

for all 

48 hr 

for all 

0.5 

1 

0.5 

Induced apoptosis (i.e., 

experimental – control) 

for ATO alone and for 

ATO with 100 μM 

Trolox, detected using PI 

staining in binding 

buffer: 

At 0.5: ~6% alone, ~20% 

with Trolox; at 1: ~16% 

alone, ~55% with 

Trolox. 

At 0.5: 0% alone, ~11% 

with Trolox; at 1: ~14% 

alone, ~45% with 

Trolox. 

At 0.5: ~1.5% alone, 

~4% with Trolox; at 1: 

~6% alone, ~20% with 

Trolox. 

Additional support for 

the conclusion that 

Trolox enhanced ATOmediated apoptosis was 

provided by an annexin 

V-FITC staining assay 

and by the observation 

that Trolox significantly 

enhanced the percentage 

of cells with activated 

caspase-3 and cleaved 

PARP. 

Diaz et al., 

2005 

Gclm-/- MEF 

cells, from 

GCLM 

knockout 

mice 

AsIII SA 

for both 

durations 

25 

for both 

durations 

8 hr 

24 hr 

25 

for both 

dura-tions 

Induced apoptosis (i.e., 

experimental – control) 

detected by staining with 

FITC-labeled annexin-V 

and PI: 

At 8 hours: ∼5% early 

apoptotic, ∼38% late 

apoptotic, ∼8% necrotic. 

At 24 hours: ∼3% early 

apoptotic, ∼79% late 

apoptotic, ∼5% necrotic. 

Experiments in Gclm+/+ 

cells showed that cotreatment or pretreatment 

with tBHQ partially or 

completely blocked 

inorganic arsenicinduced apoptosis. 

Kann et 

al., 2005b 

C-120 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

MEFs 

AsIII ATO 

2, 3, 5 3 days 2 

Induced apoptosis (i.e., 

experimental – control) 

for ATO alone and for 

ATO 

co-treatment with 

Trolox, detected by PI 

staining using flow 

cytometry: 

ATO alone: 2, ∼9%; 3, 

∼22%; 5, ∼62%. 

ATO and Trolox: 2, 

∼3%; 3, ∼3%; 5, ∼20%. 

Thus, in contrast to what 

happened in malignant 

cells, Trolox blocked the 

effects of ATO. 

Diaz et al., 

2005 

MEFs that 

were wt 

MEFs that 

were Bax-/-

and Bak-/-

double 

knockout 

(DKO) cells 

AsIII ATO 

for both 

10 

for both 

12 hr 

for both 

10 

10 

Induced apoptosis (i.e., 

experimental – control) 

detected by PI staining 

and FACS: 

∼23% in wt and ∼7% in 

DKO; the results at dose 

of 500 are ignored here. 

wt: large ⇑ in release of 

cytochrome c, which was 

mostly blocked by 

pretreatment with 

BAPTA-AM; DKO: 

trace ⇑ in release of 

cytochrome c. 

Results showed that 

cytochrome c release and 

apoptosis occurred 

largely via a Bax/Bakdependent mechanism. 

Bustamant

e et al., 

2005 

C-121 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Isolated rat 

liver 

mitochondria 

loaded with 

Ca2+ 

AsIII ATO 10, 50, 100 2 min 10 

There was a dosedependent, cyclosporin 

A-sensitive release of 

cytochrome c via 

induction of 

mitochondrial 

permeability transition 

and subsequent swelling 

of mitochondria. 

Mitochondrial GSH did 

not seem to be a target 

for inorganic arsenic 

which, however, 

appeared to cause 

oxidative modification of 

thiol groups of poreforming proteins, notably 

adenine nucleotide 

translocase. 

Bustamant

e et al., 

2005 

SVEC4-10 

cells 

AsIII SA 20 24 hr 20 

Induced apoptosis (i.e., 

experimental – control), 

apoptotic cells were 

counted by 

hemocytometer in a 

fluorescence microscope: 

∼68%. 

Hsu et al., 

2005 

RAW264.7 

cells 

AsIII SA 5, 25 24 hr 5 

Apoptosis detected by 

TUNEL assay; results 

were presented as mean 

densities of TUNEL 

staining: there was a 

positive dose-response. 

Szymczyk 

et al., 2006 

RAW264.7 

cells 

AsIII SA 5, 25 24 hr 5 

Apoptosis detected by 

fluorescence staining of 

caspase-3 activation: 

there was a positive 

dose-response. A 30-

min pretreatment with 

DPIC (which inhibits 

H2O2 production) 

completely blocked 

caspase-3 activation at 

both inorganic arsenic 

doses, thus showing that 

it prevented induction of 

apoptosis by inorganic 

arsenic. 

Szymczyk 

et al., 2006 

C-122 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

NIH 3T3 cells AsIII SA 5, 10, 20, 50, 100, 

200 

6 hr 10 

Induction of caspase 3/7 

activity assayed using 

Caspase-GloTM assay (an 

indicator of apoptosis): 

units of activity at 0, 10, 

50, 100, and 200 were 

about 2.5, 4, 12, 17, and 

36, respectively. Preinduction of HSP by 

conditioning heat shock 

(2 hr at 42°C on prior 

day) or by constitutive 

expression of HSP70 

markedly reduced the 

induction, as follows: 

With heat: NSE at any 

dose. 

With constitutive 

expression: at most a hint 

of induction at highest 3 

doses. 

Khalil et 

al., 2006 

HL-60 cells 

AsIII ATO 

3 48 hr 3 

Induced apoptosis (i.e., 

experimental – control), 

based on TUNEL assay: 

15%. Effect of 

intracellular AA (icAA): 

(cells were loaded with 4 

mM icAA by incubating 

them with DHA prior to 

inorganic arsenic 

treatments, thus avoiding 

generation of 

extracellular ROS in 

tissue culture media 

caused by direct addition 

to it of AA) 

Induced apoptosis for 

inorganic arsenic + icAA 

= 1% (NSE). 

Results using annexin 

V/FITC assay gave a 

consistent but milder 

effect. 

Karasavva

s et al., 

2005 

C-123 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

H22 cells 

BAEC cells 

AsIII ATO 

for both 

0.5, 1, 2, 4 

for both 

24 hr, 48 hr 

24 hr, 48 hr 

1, 0.5 

1, 1 

Induced apoptosis index 

(i.e., experimental – 

control), based on 

TUNEL assay: 

H22, 24 hr: 0.5, NSE; 1, 

∼8%; 2, ∼22%; 4, ∼35%. 

H22, 48 hr: 0.5, ∼8%; 1, 

∼20%; 2, ∼36%; 4, 

∼45%. 

BAEC, 24 hr: 0.5, NSE; 

1, ∼6%; 2, ∼22%; 4, 

∼26%. 

BAEC, 48 hr: 0.5, NSE; 

1, ∼8%; 2, ∼28%; 4, 

∼40%. 

Liu et al., 

2006e 

NB4 cells 

AsIII ATO 3 48 hr 3 

% of cells with nuclear 

fragmentation (NuFr): 

∼80%. 

Effects of modulators at 

high doses: 

Co-treatments with 

1000–4000 μM DTT: 

dose-related marked ⇓ in 

NuFr reaching ∼20%. 

Co-treatments with 100–

400 μM DMSA: doserelated marked ⇓ in NuFr 

reaching ∼20%. 

Co-treatments with 50–

200 μM DMPS: doserelated marked ⇓ in NuFr 

reaching ∼27%. 

Jan et al., 

2006 

NB4 cells 

AsIII ATO 

1 48 hr 1 

% of cells with NuFr: 

∼20% for experiments 

with DTT and DMSA; 

about 12% in experiment 

with DMPS. 

Effects of modulators at 

low doses: 

Co-treatments with 12.5–

50 μM DTT: doserelated marked ⇑ in NuFr 

reaching ∼90%. 

Co-treatments with 10–

40 μM DMSA: doserelated marked ⇑ in NuFr 

reaching ∼75%. 

Co-treatments with 5–20 

μM DMPS: dose-related 

marked ⇑ in NuFr 

reaching ∼80%. 

Jan et al., 

2006 

C-124 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

293 cells AsIII ATO 2 48 hr 2 

% of cells with sub-G1 

DNA content: untreated 

= ∼5%; dose of 2: big ⇑

to ∼53%. 

Effects of co-treatment 

(CoTr) with modulators 

at high doses: 

CoTr 200 μM DMSA: ⇓

from inorganic arsenic 

alone to ∼26%. 

CoTr 100 μM DMPS: ⇓

from inorganic arsenic 

alone to ∼37%. 

Effects of CoTr with 

modulators at low doses: 

CoTr 20 μM DMSA: ⇑

from inorganic arsenic 

alone to ∼83%. 

CoTr 10 μM DMPS: ⇑

from inorganic arsenic 

alone to ∼88%. 

Jan et al., 

2006 

SV-HUC-1 

cells 

AsIII ATO 2 48 hr 2 

% of cells with sub-G1 

DNA content: untreated 

= ∼6%; dose of 2: big ⇑

to ∼46%. 

Effects of CoTr with 

modulators at high 

doses: 

CoTr 200 μM DMSA: ⇓

from inorganic arsenic 

alone to ∼22%. 

CoTr 100 μM DMPS: ⇓

from inorganic arsenic 

alone to ∼28%. 

Effects of CoTr with 

modulators at low doses: 

CoTr 20 μM DMSA: ⇑

from inorganic arsenic 

alone to ∼70%. 

CoTr 10 μM DMPS: ⇑

from inorganic arsenic 

alone to ∼72%. 

Jan et al., 

2006 

C-125 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

A549 cells 

AsIII ATO 

1, 2, 5, 10, 20, 50 48 hr 5 

Cell survival determined 

by MTT assay: LC50 = 

∼27. 

Cell survival determined 

by flow cytometry after 

annexin V and PI 

staining: 

inorganic arsenic at dose 

of 2: NSE. 

200 μM sulindac: NSE. 

(2 μM inorganic arsenic 

+ 200 μM sulindac): 

∼40% cytotoxicity; 

pretreatment with NAC 

almost completely 

blocked this synergistic 

interaction. 

Jin et al., 

2006b 

A549 cells 

AsIII ATO 

2 48 hr 

Regarding caspase 3/7 protein levels: 

2 μM inorganic arsenic: NSE. 

200 μM sulindac: NSE. 

(2 μM inorganic arsenic + 200 μM 

sulindac): ⇑ to ∼1.4x. 

Regarding caspase 9 protein levels: 

2 μM inorganic arsenic: ⇑ to 1.05x. 

200 μM sulindac: NSE. 

(2 μM inorganic arsenic + 200 μM 

sulindac): ⇑ to ∼1.5x. 

There was also a clear synergistic 

interaction between these treatments in 

causing big ⇓ of both procaspase-3 

and procaspase-9 protein levels. 

Pretreatment with NAC almost 

entirely blocked the caspase 3/7 and 

caspase 9 effects. 

Jin et al., 

2006b 

WM9 cells 

OM431 cells 

LU1205 cells 

AsIII SA 

for all 4 48 hr 4 

Induced apoptosis (i.e., 

experimental – control), 

based on PI staining and 

FACS analysis of hypodiploid content of DNA 

in the pre-G0/G1 region: 

WM9, ~32%; OM431, 

~17%; LU1205, ~18%. 

Treatment with soluble 

recombinant TRAIL was 

effective in inducing 

apoptosis; combined 

treatment with inorganic 

arsenic yielded no more 

than an additive effect. 

Ivanov and 

Hei, 2006 

C-126 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Cancer Promotion 

BALB/c 3T3 

A31-1-1 cells 

(derived from 

mice) 

AsIII SA 

AsV DA 

MMAV

DMAV

0.2, 0.5, 1, 2, 5 

0.5, 1, 2, 5, 10 

50, 100, 200, 500, 

1000 

10, 20, 50, 100, 

200 

18 days for all 

0.5 

1 

200 

None 

Caused promotion in a 

two-stage transformation 

assay; based on a 

significant increase in 

the number of 

transformed cells after an 

initiating treatment of 

0.2 μg/mL MCA for 3 

days followed by posttreatment with an arsenic 

compound for 18 days. 

At doses above the 

LOEC, the responses 

increased no more than 

slightly with dose. For 

AsIII SA there was a 

humped dose-response 

with a peak at the dose 

of 1. 

Tsuchiya 

et al., 2005 

BALB/c 3T3 

A31-1-1 cells 

(derived from 

mice) 

AsIII SA 

AsV DA 

MMAV

DMAV

1 

5 

500 

50 

18 days for all 

1 

5 

500 

None 

Caused promotion in a 

two-stage transformation 

assay; based on a 

significant increase in 

the number of 

transformed cells after an 

initiating treatment of 

10 μM AsIII SA for 3 

days followed by posttreatment with an arsenic 

compound for 18 days. 

Tsuchiya 

et al., 2005 

V79 cells 

AsIII SA 

AsV DA 

MMAV

DMAV

0.15, 0.3, 0.7, 1.5, 

2.5 

0.5, 1.5, 2.5, 5, 10, 

20 

0.5, 1.5, 2.5, 5, 10, 

20 mM 

0.15, 0.3, 0.6, 1.3, 

2.7, 5 mM 

72 hrs for all 

0.7 

5 

5 mM 

None 

Inhibited gap-junctional 

intercellular 

communication, which is 

a mechanism linked to 

many tumor promoters; it 

is based on the metabolic 

cooperation assay, which 

detects chemicals that 

inhibit the transfer of the 

lethal metabolite of 6-

thioguanine from HPRTproficient to HPRTdeficient cells, thereby 

allowing recovery of the 

6-thioguanine-resistant 

(HPRT-deficient) cells. 

Tsuchiya 

et al., 2005 

C-127 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Cell Cycle Arrest or Reduced Proliferation 

MGC-803 

(human 

gastric 

cancer) 

AsIII ATO 0.01–1 24 hr 0.01 Growth inhibition 

(growth measured by 

MTT assay): at various 

doses, growth inhibition 

was also induced in 5 

other human malignant 

cell lines. 

Zhang et 

al., 1999 

MC/CAR 

(human 

multiple 

myeloma cell 

line) 

AsIII ATO 1, 2, 3, 4, 5 72 hr 1 

Growth inhibition 

(growth measured by 

MTT assay): 

About 60% inhibition at 

2; cells were arrested in 

both G1 and G2-M 

phases. Growth 

inhibition was also 

induced in 7 other human 

multiple myeloma cell 

lines to various degrees. 

Park et al., 

2000 

UROtsa cells 

AsIII SA 

AsV 

MMAIIIO 

MMAV

DMAIIII 

DMAV

0.1, 0.5, 1, 5 

1, 200 

0.1, 0.5, 1, 5 

1, 200 

0.1, 0.5, 1, 5 

1, 200 

24 hr 

for all 

1 

None 

1 

None 

5 

None 

Extent of reduction of 

cell proliferation based 

on [3

H]thymidine 

incorporation: 

Cell proliferation 

reductions at dose of 5 

were approximately as 

follows: DMAIIII, 15%; 

AsIII, 30%; MMAIIIO, 

85%. 

Drobná et 

al., 2002 

V79 cells DMAV 1, 2, 5 mM 12 hr 1 mM 

Induction of mitotic 

delay and formation of 

aberrant mitotic spindles, 

including tripolar and 

quadripolar spindles: 

~18% aberrant spindles 

at 1 mM. γ-tubulin was 

co-localized with the 

aberrant spindles. The 

following things were 

noted to occur after 

exposure of V79 cells to 

DMAV: multiple MTOCs, 

multipolar spindles, 

amoeboid cells, 

multinucleated cells, and 

cell death. 

Ochi et al., 

1999a 

C-128 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HeLa S3 cells AsIII SA 1, 3, 5, 10, 20 24 hr 3 

Cells arrested at mitotic 

stage: At dose of 5, 35% 

of cells were arrested in 

that stage. Of 7 cell lines 

tested in this way, two 

others were almost as 

sensitive to this effect. 

Examination of cells 

arrested in mitosis 

showed abnormal mitotic 

figures and spindles, as 

well as deranged 

chromosomal 

congression. 

Huang and 

Lee, 1998 

U937 cells 

AsIII SA 

for both 

2.5, 5, 10 

for both 

durations 

24 hr 

48 hr 

2.5 

for both 

dura-tions 

Cell numbers counted 

with a Coulter counter: 

After 24 hr at the doses 

of 2.5, 5, and 10, there 

were approximately 

71%, 56%, and 43% as 

many cells as in the 

control group, 

respectively. 

After 48 hr at the doses 

of 2.5, 5, and 10, there 

were approximately 

54%, 38%, and 23% as 

many cells as in the 

control group, 

respectively. There was 

little if any cytotoxicity 

even at 48 hr at the dose 

of 5. 

McCollum 

et al., 2005 

C-129 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

U937 cells AsIII SA 5 8 hr 

The LOEC was 5. Centrifugal 

elutriation was used to enrich cells in 

different phases of the cell cycle so 

that the effect of inorganic arsenic 

could be tested on them. Progression 

of inorganic arsenic-treated cells from 

each cell cycle stage to the next was 

studied, and it was found that 

inorganic arsenic slowed cell growth 

in every phase of the cycle. For 

example, in asynchronous populations 

of untreated cells, DNA synthesis 

lasted 10 to 12 hr. However, in cells 

treated with 5 μM inorganic arsenic, it 

lasted 16 hr. In the presence of 

inorganic arsenic, cells in G1 entered 

the S phase more slowly, etc. Cell 

passage from any cell cycle phase to 

the next was inhibited by 5 μM 

inorganic arsenic arsenite. Clearly 

there was not induction of cell-cycle 

arrest at one specific checkpoint. The 

biggest inorganic arsenic-induced 

slowdown occurred between M and 

G1, and the next biggest was between 

G2 and M. By looking at caspase 

activity, they showed that inorganic 

arsenic induced apoptosis specifically 

in cell populations delayed in the 

G2/M phase. 

McCollum 

et al., 2005 

C-130 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

PARP-1+/+

MEF cells 

PARP-1-/-

MEF cells 

AsIII SA 

for both 

11.5, 23 

for both 

24 and 48 hr 

for both 

11.5 

for both 

at both 

times 

inorganic arsenic caused 

much disruption of cell 

cycle as shown by PI and 

RNase staining and flow 

cytometry when 

visualized as proportions 

of cells that were in 

G2/M, S, G1, or sub-G1 

(i.e., apoptotic) under the 

different conditions. 

Disruption was more 

extreme in PARP-1-/-

MEF cells. Results for 

apoptosis, which are 

easier to quantify, are 

detailed in separate rows. 

 Especially at the highest 

inorganic arsenic dose in 

PARP-1-/- cells, the 

proportion of G2/M cells 

became especially small, 

at least when the 

comparison was made to 

all cells and not just to 

non-apoptotic ones. 

Poonepalli 

et al., 2005 

CGL-2 cells AsIII SA 1, 2, 3, 4, 5, 7, 10 24 hr 1 

Cell survival was 

determined using a 

colony-forming assay: 

LC50 = 1.7. arsenic 

mitotic cells round-up, 

they can be separated 

from the attached 

interface cells by using 

the shake-off technique. 

When that technique was 

applied to a sample at the 

dose of 2, 96% of the 

attached cells were found 

to be alive, and 96% of 

the floating (i.e., mitotic) 

cells were found to be 

dead, thus indicating that 

inorganic arsenic 

induced mitosismediated cell death. 

Yih et al., 

2005 

C-131 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

CGL-2 cells AsIII SA 1, 2, 3, 4, 5, 10 24 hr 1 

Treatments caused a shift 

in percentages of cells in 

G1, S, and G2/M, with a 

dose-dependent ⇑ in 

G2/M cells over the 

range of doses of 0 

(∼25%) to 4 (∼85%), 

followed by a ⇓ above a 

dose of 5 that reached 

∼50% at dose of 10. 

G2/M cells were 

predominantly mitotic 

cells. Mitotic arrest was 

associated with inorganic 

arsenic-induced cell 

death (see row 

immediately above). 

When synchronized cells 

were treated with dose of 

2, all cells, whether 

treated in the G1, S, or 

G2 stage, progressed into 

and arrested at mitosis, 

where they were 

demonstrated to contain 

damaged DNA, as 

demonstrated by the 

appearance of the DNA 

double-strand-break 

marker phosphorylated 

histone H2A.X (γH2AX). 

Yih et al., 

2005 

CGL-2 cells AsIII SA 

Following on from row above, other experiments showed that inorganic 

arsenic appears to inhibit activation of the G2 DNA damage checkpoint and 

thereby allows cells with damaged DNA to proceed from G2 into mitosis. 

The subsequent arresting of cells with damaged DNA in mitosis is thought to 

enhance the induction of apoptosis. 

Yih et al., 

2005 

HeLa S3 cells AsIII SA 5, 10, 20, 50 1 hr 10 

Inhibition of mitotic exit 

after cells were arrested 

in mitosis by treatment 

with nocodazole and the 

nocodazole was removed 

before arsenic treatment. 

This shows that such a 

dose interferes with 

mitosis. 

Huang and 

Lee, 1998 

C-132 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HLFC cells 

HLFK cells 

(Ku70 

deficient) 

AsIII SA 

for both 

1, 2.5, 5, 10 

for both 

4 hr 

for both 

2.5 

2.5 

Following the 4-hr AsIII

treatment, cells were 

incubated in arsenic-free 

medium for 24 hr before 

determining the 

proliferation index and 

the proportions of cells 

in different parts of cell 

cycle. Both cell types 

had ⇓ proliferation index 

and an ⇑ in G0/G1 cells at 

dose of 2.5. Both effects 

were more extreme in 

HLFK than in HLFC 

cells at the 3 highest 

doses. 

Liu et al., 

2007b 

Human 

primary 

peripheral 

blood 

lymphocytes 

AsIII SA 

AsV

MMAIII

MMAV

DMAIII

DMAV

1.25–160 

1.25–500 

0.1–2.7 

10–10000 

0.11–12.26 

10–10000 

24 hr 

for all 

2.5 

50 

1.5 

10000 

1.02 

3000 

Replicative index (RI): 

All 6 compounds 

induced significant 

slowing of the cell cycle. 

 Methylated trivalent 

arsenicals were 3 orders 

of magnitude more 

potent than the 

methylated pentavalent 

arsenicals. Inorganic 

arsenic compounds were 

substantially more toxic 

than methylated 

pentavalent arsenicals. 

Kligerman 

et al., 2003 

Human 

primary 

peripheral 

blood 

lymphocytes 

AsIII SA 

AsV

MMAIII

MMAV

DMAIII

DMAV

1.25–160 

1.25–500 

0.1–2.7 

10–10000 

0.11–12.26 

10–10000 

24 hr 

for all 

20 

150 

1.8 

None 

1.02 

300 

Mitotic index (MI): 

⇓. 

⇓. 

⇓. 

NSE. 

⇑ to peak of 3x at 3.07. 

⇑ to peak of 6x at 1000. 

Both decreased abruptly 

near concentration at 

which RI showed ⇑

proportion of first 

division metaphases. 

This is consistent with 

disruption of spindle 

integrity. 

Kligerman 

et al., 2003 

C-133 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Human 

peripheral 

lymphocytes 

AsIII SA 5 24 hr 5 

There was delayed cell 

cycle progression. In 

treated cells, 73% and 

32% were still in the first 

mitotic division at 

fixation times of 72 and 

96 hr, respectively, 

whereas in untreated 

cells up to 90% were in 

second or subsequent 

divisions at these times. 

Jha et al., 

1992 

TR9-7 cells 

that were 

released from 

being mostly 

synchronized 

in G2 (using 

Hoechst 

33342) 

shortly before 

inorganic 

arsenic 

treatment 

began 

AsIII SA 5 1–24 hr 

Conclusions based on mitotic indices 

determined over the 24-hr period in 

cells made p53(+) or p53(-) by 

controlling tetracycline levels: 

inorganic arsenic delayed entry into 

mitosis in both p53(+) and 

p53(-) cells, with peak being delayed 

by ∼3 hr from that of cells unexposed 

to inorganic arsenic. Mitotic exit 

occurred at a normal rate in inorganic 

arsenic-treated p53(+) cells but was 

markedly delayed in p53(-) cells and 

only reached the baseline level after 

24 hr, by which time the inorganic 

arsenic-treated p53(+) cells had already 

reached that level and had begun to 

cycle again. 

McNeely 

et al., 2006 

PCI-1 cells AsIII ATO 1, 2, 3, 4 3 days 2 

Growth inhibition 

(growth measured by 

MTT assay): 

About 50% inhibition at 

2; cells were arrested in 

the G2-M phases. 

Growth inhibition was 

also induced in 3 other 

human head and neck 

squamous cell carcinoma 

cell lines. 

Seol et al., 

1999 

CHO cells 

treated with 

MMS before 

or after 

inorganic 

arsenic 

treatment 

AsIII SA 

10, as 

pretreatment 

10, as 

post-treatment 

24 hr 

24 hr 

10 

10 

Inhibition of mitosis and 

cell proliferation: 

⇓ in inhibition of both 

endpoints compared to 

MMS alone. 

⇑ in inhibition of both 

endpoints compared to 

MMS alone, synergistic 

interaction. 

Lee et al., 

1986 

C-134 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

MCF-7 cells AsIII ATO 3 24 hr 3 Treatment blocked the 

cell cycle in mitosis, 

resulting in a timedependent accumulation 

of cells in G2/M, with 

about 50% in G2/M at 

this time. 

Ling et al., 

2002 

Human 

lymphocytes 

AsIII SA 

10-10, 10-8, 10-6, 

10-4, 0.01, 1 2 hr 10-10

Induction of mitotic 

arrest: 

4 of 5 donors showed 

statistically significant 

increase at lowest dose. 

All showed significant 

increase from dose of 10-

8

 through 0.01. There 

was much interindividual variation, but 

there was a positive 

dose-response within 

data for each donor. 

There was a almost no 

response at dose of 1 

because of cytotoxicity. 

Vega et al., 

1995 

Chinese 

hamster V79 

cells 

AsIII SA 

DMAV

5 

2 mM 

24 hr 

for both 

5 

2 mM 

Accumulation of mitotic 

cells and other abnormal 

cells as follows 

(approximate 

percentages of cells of 

each type present after 

24-hr treatment): Control 

(assumed same as 

distribution at starting 

time): 97% 

mononucleated, 3% 

metaphase. 

 AsIII: 75% 

mononucleated, 11% 

metaphase, 10% 

binucleated, 4% 

multinucleated. 

DMAV: 24% 

mononucleated, 52% 

metaphase, 1% 

binucleated, 23% 

multinucleated. DMAV

caused disappearance of 

microtubule network and 

abnormalities of mitotic 

microtubules (i.e., 

spindles)—there was a 

big ⇑ increase in 

frequency of multipolar 

and aster-like spindles. 

Ochi et al., 

1999b 

C-135 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

SVEC4-10 

cells 

AsIII SA 2, 4, 8, 16 24 hr 4 

Fraction of cells in G2/M 

phases of cell cycle: 

slight ⇑ at 4, big ⇑ at 8 

and 16. Also an effect 

on rate of cell growth 

(tested at 4, 8, 12, 16): ⇓

at all doses, with a strong 

dose-response. 

Chao et al., 

2006a 

HCT116 cells 

 (securin +/+) 

HCT116 cells 

(securin -/-) 

AsIII SA 

for both 

4, 8, 12, 16 

for both 

24 hr 

for both 

12 

4 

Fraction of cells in G2/M 

phases of cell cycle: 

Similar ⇑ at 12 and 16 to 

∼39%. 

⇑ at 4 to ∼38% with a 

positive dose-response, 

reaching ∼49% at highest 

dose. Consistent with 

the conclusion, based on 

the above data, that 

securin protects against 

arsenic-induced cell 

cycle arrest, the -/- cells 

also showed a much 

bigger ⇑ in the mitotic 

index and in the fraction 

of cells in 

“anaphase/mitosis.” 

They also showed sisterchromatid separation. 

Chao et al., 

2006a 

SVEC4-10 

cells 

AsIII SA 20 24 hr 20 Cell numbers were 

counted using a 

hemocytometer: after 6 

days of culturing after 

the inorganic arsenic 

treatment, there were 

∼25% as many cells as in 

the control. 

Hsu et al., 

2005 

HT1197 cells AsIII SA 1, 5, 10 24 hr 5 

Complete inhibition of 

cell proliferation 

occurred eventually at 

the dose of 10, with an 

accumulation of cells in 

S-phase. At the dose of 

10, after 12 and 24 hr, 

1.5x and 2.1x more cells 

were in S-phase than in 

control, respectively, 

with a large deficit of 

cells in G1. 

Hernández

-Zavala 

 et al., 

2005 

C-136 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

CL3 cells, 

synchronous 

at G1 

AsIII SA 50 3 hr 50 Cell proliferation, based 

on cell number: ⇓ to 

∼35% of control. 

Survival was cut to 

20%–25% by cotreatment with PD98059 

or U0126. 

Li et al., 

2006a 

Human 

lymphoblastoi

d cells 

AsIII SA 

AsV

MMAIII

MMAV

DMAIII

DMAV

0.2, 0.4, 0.6, 1, 

2.5, 5, 10 μM 

0.5, 1, 2.5, 5, 7.5, 

10 mM

0.05, 0.1, 0.2, 0.3, 

0.4, 0.5, 1 μM 

0.5, 1, 2.5, 5, 7.5, 

10 mM 

0.05, 0.1, 0.2, 0.3, 

0.4, 0.5 μM 

0.5, 1, 2.5, 5, 7.5, 

10 mM 

6 hr 

for all 

None 

7.5 mM 

0.4 μM 

None 

None 

5 mM 

Effect on the mitotic 

index: 

NSE, but results were 

confounded by high 

toxicity. 

Slight statistically 

significant ⇑ in slope. 

Statistically significant ⇑

in slope. 

Slight statistically 

significant ⇑ in slope. 

Equivocal, highly 

variable, effects probably 

because of toxicity. 

Statistically significant ⇑

in slope. 

Kligerman 

et al., 2005 

Lyophilized 

bovine tubulin 

AsIII SA 

AsV

MMAIII

MMAV

DMAIII

DMAV

0.1, 1, 10 mM 

0.1, 1, 10 mM 

1, 10, 100 μM 

0.1, 1, 10 mM 

1, 10, 100 μM 

0.1, 1, 10 mM 

Time course 

over 1 hr 

1 mM 

None 

1 μM 

0.1 mM 

10 μM 

0.1 mM 

Effect on GTP-induced 

polymerization of 

lyophilized bovine 

tubulin: 

⇓ at 1 mM, ⇓⇓ at 10 

mM. 

NSE. 

Slight ⇑ at 1 μM, ⇓ at 10 

μM, ⇓⇓ at 100 μM. 

Slight ⇑ at 0.1 and 1 

mM, ⇑ at 10 mM. 

⇓ at 10 μM, ⇓⇓ at 100 

μM. 

⇓ at 0.1 mM, NSE at 1 

mM, ⇑ at 10 mM. 

Kligerman 

et al., 2005 

Cell Proliferation Stimulation 

C-137 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

K562 cells 

(human 

erythroleukem

ia cells) 

AsIII ATO 2.5 12 hr 

48 hr 

2.5 

2.5 

~27% of cells are 

mitotic. 

(In control, only 4% of 

cells are mitotic.) 

~55% of cells are 

mitotic. 

Li and 

Broome, 

1999 

NHEK cells 

AsIII SA 

AsV, 

MMAV, 

DMAV

0.001, 0.005, 0.01, 

0.05, 0.1, 0.5, 1, 5, 

10 for all 

24 hr 

for all 

0.005 

None 

Stimulation of cell 

proliferation, but with 

inhibition of cell 

proliferation at ≥ 0.05. 

Stimulation was 

measured as 

incorporation of 

3

[H]thymidine into 

cellular DNA. 

No stimulation of cell 

proliferation; inhibition 

of cell proliferation at 

0.05 or higher. 

Vega et al., 

2001 

NHEK cells AsIII SA 0.2, 0.4, 0.8 

1 day 

2 days 

3 days 

0.2 

0.4 

0.4 

Increase in proliferation 

based on cell counts: 

⇑ of 32%, 58%, and 

50%, respectively. 

⇑ of 20% and 21% at 

doses of 0.4 and 0.8, 

respectively. 

⇑ of 27%, only at dose of 

0.4. 

PI staining and FACS 

analysis after 2 days 

showed a significant 

shift from cells in G1 to 

cells in G2/S at both 

doses that showed an ⇑

in proliferation. 

Hwang et 

al., 2006 

C-138 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HaCaT cells AsIII SA 1.25, 2.5, 5 48 hr 1.25 

⇑ in fraction of cells in S 

phase: at doses of 0, 

1.25, 2.5, and 5, the 

percentages of cells in S 

were 24.9%, 29.8%, 

33.8%, and 38.7%, 

respectively. Since there 

was a corresponding ⇑ in 

fraction of cells in G2/M 

phase, it was concluded 

that inorganic arsenic 

promoted the transition 

from G1 to S. The 24-hr 

treatment caused a 

similar effect at the 2 

higher doses. 

Ouyang et 

al., 2005 

JB6 C141 

cells 

transfected as 

described for 

this assay 

AsIII SA 1.25 72 hr 1.25 

Proliferation was 

measured by using the 

CellTiter-Glo®

Luminescent Cell 

Viability Assay: ⇑ in 

proliferation index to 

∼1.62x. 

Ouyang et 

al., 2006 

JB6 C141 

cyclin D1-Luc 

mass1 cells 

AsIII SA 5 24 hr 5 

Fraction of cells in S 

phase and cell apoptosis 

(i.e., cell sub-G1 phase) 

were measured using PI 

staining with flow 

cytometry: ⇑ in fraction 

of cells in S from 

∼11.8% to ∼14.5%; there 

was no induction of 

apoptosis and no 

evidence of cytotoxicity. 

Ouyang et 

al., 2006 

HaCaT cells AsIII SA 0.5, 1.0 20 passages — 

Not a significantly 

increased growth rate, 

but the trend was in that 

direction with 

accumulated population 

doublings of 58 to 67 in 

the control and 1.0 

groups, respectively, 

with the value being ∼61 

in the 0.5 dose group. 

Chien et 

al., 2004 

C-139 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

C3H 10T1/2 

cell line 

(mouse cells 

with 

fibroblast 

morphology 

during routine 

culture but 

capable of 

differentiation 

into 

adipocytes) 

AsIII SA 6 8 wk 6 

Marked increase in FBSstimulated DNA 

synthesis (detected using 

[

3

H]thymidine 

incorporation) following 

dexamethasone/insulin 

treatment (to induce 

differentiation), but only 

after the arsenite 

exposure has been 

stopped—the increased 

mitogenic response is 

masked while the 

arsenite treatment 

continues. 

Trouba et 

al., 2000 

C3H 10T1/2 

cell line 

(mouse cells 

with 

fibroblast 

morphology 

during routine 

culture but 

capable of 

differentiation 

into 

adipocytes) 

AsIII SA 6 8 wk 6 

Marked increase in cell 

number compared to 

control cells following 

dexamethasone/insulin 

treatment (to induce 

differentiation), but 

increase only occurs 

after the arsenite 

exposure has been 

stopped. 

Trouba et 

al., 2000 

Both HL-60 

cells 

and HaCaT 

cells 

AsIII SA 0.1, 0.5, 1, 10, 20, 

40 

5 days 

0.5 but 

possibly 

0.1 

By use of MTT assay: ⇑

in cell number, with peak 

at 0.5; ⇓ in cell number 

to below control level at 

1, with a continuing 

decrease at higher 

concentrations. 

(Same general response, 

but to a lesser extent, 

with same treatments 

over 1 day or 3 days.) 

Zhang et 

al., 2003 

UROtsa cells AsIII SA 2, 4 72 hr 2 

Increase in cell 

proliferation based on 

statistically significant 

increase in 

[

3

H]thymidine 

incorporation; also there 

was a significantly 

higher fraction of cells in 

S-phase of cell cycle. 

Simeonova 

et al., 2000 

C-140 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

NHEK cells 

AsIII SA 

MMAIII

DMAIII

0.2, 0.4, 0.6, 0.8, 

1, 2, 4, 6, 12 

0.1, 0.2, 0.4, 0.5, 

0.8, 1, 2 

0.1, 0.2, 0.4, 0.5, 

0.6, 0.7, 0.8, 1, 2, 

3 

24 hr 

for all; index 

was then 

determined 

immediately 

2 

0.5 

0.6 

Proliferation index based 

on MTT assay; the 

statistical comparison 

was with the untreated 

control: 

⇑ at 3 doses from LOEC 

through 6. 

⇑ at 2 doses from LOEC 

through 0.8. 

⇑ at 2 doses from LOEC 

through 0.7. 

Significant cytotoxicity 

occurred at 12 μM and 

higher for inorganic 

arsenic and at 1 μM and 

higher for the other 

arsenicals. Cell cycle 

distributions were 

changed in many 

different ways. 

Mudipalli 

et al., 2005 

C-141 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

NHEK cells 

irradiated 

with 100 

mJ/cm2

 of 

UVB to arrest 

94.5% of cells 

in G0/G1

stages of cell 

cycle while 

only killing 

2-3% of the 

cells. 

AsIII SA 

MMAIII

DMAIII

0.2, 0.4, 0.6, 0.8, 

1, 2, 4, 6, 12 

0.1, 0.2, 0.4, 0.5, 

0.8, 1, 2 

0.1, 0.2, 0.4, 0.5, 

0.6, 0.7, 0.8, 1, 2, 

3 

24 hr 

for all; index 

was then 

determined 

Immediately 

0.6 

0.4 

0.4 

Proliferation index based 

on MTT assay; the 

statistical comparison 

was with the untreated 

control: 

⇑ at 6 doses from LOEC 

through 6. 

⇑ at 4 doses from LOEC 

through 1.0. 

⇑ at 5 doses from LOEC 

through 0.8. 

Significant cytotoxicity 

occurred at 12 μM for 

inorganic arsenic and at 

1 μM and higher for the 

other arsenicals. At all 

doses showing a 

significant effect on the 

proliferation index after 

arsenical exposure, the 

point estimate was 

always higher in the cells 

with prior UVB 

exposure. Cell cycle 

distributions were 

changed in many 

different ways. 

Mudipalli 

et al., 2005 

Postconfluent 

PAEC cells in 

a 

monolayer 

PAEC cells in 

midexponential 

growth in a 

monolayer 

AsIII SA 

for both 

1, 2.5, 5, 10, 20 

1, 2.5, 5, 10, 20 

4 hr for both 

1 

10 

Incorporation of 

[

3

H]thymidine into 

genomic DNA: 

⇑ at 1, 2.5, and 5, 

indicating a mitogenic 

response. Only the 

response at 5 is 

significantly higher, but 

the 2 lower doses are 

probably also higher; 

there was no effect at 

higher doses. 

⇓ in rate of DNA 

synthesis. (In the 

absence of any treatment, 

such cells have a higher 

rate of DNA synthesis 

than the postconfluent 

cells in a monolayer.) 

Barchowsk

y et al., 

1996 

C-142 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

PAEC from 

freshly 

harvested 

vessels 

AsIII

probably 

ATO, but 

called 

arsenite 

1, 5, 10 24 hr 1 

Extent of cell 

proliferation was 

estimated using 

fluorescent Cyquant 

assay: 

⇑ at 1 and 5, but ⇓ at 10. 

Barchowsk

y et al., 

1999a 

U-2OS cells AsIII SA 0.01, 0.05, 0.1, 

0.25, 0.5, 1, 2.5 

24 hr 0.01 

Cell survival was 

determined using the 

clonal survival treat-andplate method: 

At doses of 0.01 and 

0.05, clonal-forming 

ability was stimulated to 

120%–124% of the 

control, p < 0.006. 

There was no increase at 

a 72-hr exposure or at 

higher doses with a 24-hr 

exposure. Similar results 

were found with the 

neutral red and MTT 

assays, and sometimes 

with those assays the 

point estimates still 

showed an increase at 

the dose of 0.01 after the 

72-hr exposure. 

Komissaro

va et al., 

2005 

SHE cells DMAIIII 0.1, 0.25, 0.5, 1.0 1 day 0.1 

Cell growth (no. of 

viable cells): ⇑ at both 

0.1 and 0.25, and also 

big ⇑ for them after 2 

and 3 days. Increase by 

1 day at dose of 0.1 was 

∼8-fold. 

At dose of 1.0, ∼40% 

cytotoxicity. No clear 

effect at 0.5 until after 3 

days, then ∼40% 

cytotoxicity. 

Ochi et al., 

2004 

TM3 cells AsIII SA 

0.000008, 

0.00008, 0.0008, 

0.008, 0.08, 0.77 

72 hr 0.000008 

Increase in cell 

proliferation: a 

statistically significant 

increase at all doses 

except 0.77; the peak of 

∼152% of control was at 

0.00008. 

DuMond 

and Singh, 

2007 

C-143 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

UROtsa cells MMAIII 

for all 

0.05 

for all 

12 weeks 

24 weeks 

52 weeks 

0.05 

for all 

Shortened cell 

population doubling 

times (hr) based on 

counting cells in trypan 

blue exclusion assay: 

(control doubling time = 

42 hr) 

27 hr. 

25 hr. 

21 hr. 

Bredfeldt 

et al., 2006 

NHEK cells, 

both with and 

without 

irradiation 

with 100 

mJ/cm2

 of 

UVB to arrest 

94.5% of cells 

in G0/G1

stages of cell 

cycle while 

only killing 

2%–3% of the 

cells 

AsIII SA 

MMAIII

DMAIII

6 

0.8 

0.8 

24 hr 

for all 

6 

0.8 

0.8 

Examination of 

expression profiles of 

more than 10 cell cycle 

and cell signaling 

proteins that seem likely 

to influence cell 

proliferation showed that 

many large changes 

occurred following the 

UVB and arsenic 

treatments. arsenic 

examples, all 3 

arsenicals caused a big ⇑

in nuclear cyclin D1 in 

UVB irradiated cells, 

and, for nuclear PCNA 

in UVB-irradiated cells, 

MMA and DMA caused 

a big ⇑ while inorganic 

arsenic had no effect. 

Activation of JNK 

phosphorylation and 

increased EGF 

expression and 

phosphorylation of the 

EGF receptor occurred. 

Mudipalli 

et al., 2005 

HELF cells AsIII SA 0.1, 0.5, 1, 5, 10 24 hr 

0.1 for ⇑

5 for ⇓

Cell proliferation 

efficiency based on MTT 

assay: 

⇑ to 150% and 175% of 

control at 0.1 and 0.5, 

respectively; ⇓ to 60% of 

control at 5; significant 

stimulation of 

proliferation was also 

seen at dose of 0.5 after 

treatments of 12 and 48 

hr. 

Yang et 

al., 2007 

Chromosomal Aberrations and/or Genetic Instability 

C-144 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HaCaT cells AsIII SA 0.5, 1.0 20 passages 0.5 

Comparative genomic 

hybridization showed 

that all 11 cell lines 

derived from tumors (see 

malignant 

transformation) showed 

significant loss of 

chromosome 9q, and 7 

lines showed significant 

gain of chromosome 4q. 

Chien et 

al., 2004 

HaCaT cells AsIII SA 0.5, 1.0 20 passages 0.5 ⇑ MN; detected using 

the cytokinesis-block 

micronucleus assay, and 

scored only in 

binucleated cells. There 

was a positive doseresponse. 

Chien et 

al., 2004 

Primary 

Syrian 

hamster 

embryo cells 

(HEC) 

AsIII SA 

AsV

0.38, 3.8, 7.7 

3.2, 8, 16, 32 

24 hr for both 0.38 

16 

SCEs were induced; 

slight upward trend with 

dose. 

Larramend

y et al., 

1981 

Primary 

Syrian 

hamster 

embryo cells 

(HEC) 

AsIII SA 

AsV

7.7 

32 

24 hr for both 7.7 

32 

CAs were induced: 

mostly chromatid gaps 

and breaks, but some 

chromatid and 

chromosome exchanges. 

Larramend

y et al., 

1981 

Human 

peripheral 

lymphocytes 

AsIII SA 

AsV

0.77, 1.9 

16, 32 

48 hr for both 0.77 

16 

SCEs were induced; 

dose-independent 

response. 

Larramend

y et al., 

1981 

Human 

peripheral 

lymphocytes 

AsIII SA 

AsV

7.7 

32 

48 hr for both 7.7 

32 

CAs were induced: 

mostly chromatid and 

chromosome gaps and 

breaks, very few 

exchanges. 

Larramend

y et al., 

1981 

Human 

primary 

peripheral 

blood 

lymphocytes 

AsIII SA 

AsV

MMAIII

MMAV

DMAIII

DMAV

1.25–160 

1.25–500 

0.1–2.7 

10–10000 

0.11–12.26 

10–10000 

24 hr 

for all 

None 

None 

None 

1000 

0.34 

1000 

SCE/metaphase 

Top 3 in list were 

negative. Potency of 

others: 

DMAIII > DMAV > 

MMAV. 

All were weak inducers 

of SCE, with the most 

potent inducing ∼1 

SCE/metaphase/μM. 

Kligerman 

et al., 2003 

C-145 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Human 

primary 

peripheral 

blood 

lymphocytes 

AsIII SA 

AsV

MMAIII

MMAV

DMAIII

DMAV

1.25–160 

1.25–500 

0.1–2.7 

10–10000 

0.11–12.26 

10–10000 

24 hr 

for all 

2.5 

50 

0.6 

3000 

1.35 

3000 

Chromosomal 

aberrations: 

⇑ to 42.5% aberrant cells 

at 10.0. 

⇑ to 11.0% aberrant cells 

at 80.0. 

⇑ to 11.0% aberrant cells 

at 1.2. 

⇑ to 6.5% aberrant cells 

at 3000. 

⇑ to 22.0% aberrant cells 

at 2.70. 

⇑ to 57.0% aberrant cells 

at 10000. 

All 6 showed a positive 

dose-response. 

Chromatid and 

isochromatid deletions 

were most prevalent; 

exchanges were 

infrequent. 

Kligerman 

et al., 2003 

Syrian 

hamster 

embryo cells 

AsIII SA 

AsV

0.8, 3.0, 6.2, 10 

10, 20, 64, 96 

24 hr for both 

6.2 

64 

CAs and 

endoreduplication 

(also, with 48 hr 

treatment, polyploidy). 

Mainly chromatid gaps, 

breaks, and exchanges, 

but a few chromosometype aberrations 

(fragments and 

dicentrics). 

Barrett et 

al., 1989 

CHO K1 cells 

in late G1 of 

mitotic cycle 

AsIII SA 

40 4 hr 40 High frequency of CAs 

was induced; effect was 

markedly reduced by 

prior or simultaneous 

(but not by subsequent) 

treatment with 5 mM 

GSH. 

Huang et 

al., 1993 

Human 

peripheral 

lymphocytes 

AsIII SA 1, 5, 10 48 hr 1 Induction of chromatid 

aberrations; there was a 

positive dose-response. 

Jha et al., 

1992 

Human 

peripheral 

lymphocytes 

AsIII SA 0.5, 1.0, 1.5, 2.0 48 hr 2.0 Induction of 

chromosomal 

aberrations. 

Wiencke 

and Yager, 

1992 

C-146 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

AS52 cells AsIII SA 50, 100 4 hr 100 

Induction of gpt 

mutations at the ypt 

locus: 

The mutation frequency 

was twice that of the 

spontaneous mutation 

frequency at a high level 

of cytotoxicity (15% of 

the relative survival of 

the control). Taken as 

very weak evidence that 

AsIII is a gene mutagen; 

results are grouped here 

with CAs because most 

or all of the induced 

mutations were total 

deletions of the gene, 

perhaps caused by the 

cytotoxicity. 

Meng and 

Hsie, 1996 

G12 cells 

MMAIIIO 

DMAIIII 

0.2, 0.4, 0.6, 0.8, 

1.0 

0.1, 0.2, 0.3, 0.4 

3 days 

for both 

0.6 

0.3 

Induction of mutations at 

the gpt locus: 

DMAIIII: reached 5x 

control mutant frequency 

at 7% cell survival; 

MMAIIIO: reached 5x 

control mutant frequency 

at 11% cell survival. 

Taken as weak evidence 

that the arsenicals are 

gene mutagens with sublinear dose-responses; 

results are grouped here 

with chromosomal 

aberrations because 

~80% of the induced 

mutations were deletions 

of the gene, perhaps 

caused by the 

cytotoxicity. ~11% of 

non-deletion mutants 

exhibited altered DNA 

methylation. 

Klein et 

al., 2007 

CHO cells 

AsIII SA 

AsV

0.01, 0.1, 1, 10 

0.01, 0.1, 1, 10, 

100 

12 hr 

for both 

1 

100 

Induction of 

chromosomal 

aberrations: 

A positive doseresponse; 36.7% of cells 

with aberrations at dose 

of 10. 

8.0% of cells with 

aberrations at dose of 

100. 

Kochhar et 

al., 1996 

C-147 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

CHO cells 

AsIII SA 

AsV 

0.01, 0.1, 1, 10 

0.01, 0.1, 1, 10, 

100 

12 hr 

for both 

1 

None 

Induction of 

endoreduplication: 

A positive doseresponse; 22.0% of cells 

with endoreduplication at 

dose of 10. 

— 

Kochhar et 

al., 1996 

CHO cells 

AsIII SA 

AsV 

0.01, 0.1, 1, 10 

0.01, 0.1, 1, 10 

12 hr 

for both 

0.01 

0.01 

Induction of SCEs: 

10.94%/cell at lowest 

dose; 14.08%/cell at 

highest dose; slight 

upward trend with dose. 

11.38%/cell at lowest 

dose; 12.84%/cell at 

highest dose; no doseresponse. 

Kochhar et 

al., 1996 

MRC-5 cells AsIII SA 2.5, 5, 10 26 hr 2.5 

Induction of SCEs 

(frequencies): 

0, 3.24; 2.5, 5.23; 5, 6.2; 

10, no surviving cells 

could be found to 

evaluate. There was also 

much cytotoxicity at 

dose of 5. High level of 

cytotoxicity was also 

reflected in the 

proliferation index. 

Mourón et 

al., 2006 

MRC-5 cells DMAV 125, 250, 500 26 hr 125 

Induction of SCEs 

(frequencies): 

0, 4.25; 125, 5.89; 250, 

5.95; 500, 5.91; thus no 

dose-response for SCEs. 

 There was a significant 

⇓ in the proliferation 

index at the highest dose. 

Mourón et 

al., 2005 

C-148 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Human 

lymphocytes 

AsIII SA 10-10, 10-8, 10-6, 

10-4, 0.01 

24 hr 10-10

Induction of hypoploid 

and hyperploid cells: 

There was a statistically 

significant increase in 

hyperploidy at all dose 

levels in both 1st and 

2nd division cells. There 

was a positive (but 

shallow) dose-response. 

For example, in 2nd 

division cells, the 

frequency went from 

2.3% at dose of 10-10 to 

11.7% at dose of 0.01. 

The 4 donors showed 

variation, with 2 

showing no effect at 

lowest dose. It is unclear 

at what dose level 

induction of hypoploidy 

became significant, but 

there was a slight 

positive dose-response 

for it also. Data on CAs, 

which were reported 

only briefly, showed that 

roughly 40% of cells had 

CAs at the dose of 0.01. 

A concentration of 1 

only μM was highly 

cytotoxic in these cells 

with an exposure lasting 

only 2 hr. 

Vega et al., 

1995 

C-149 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Human 

lymphocytes 

AsIII SA 0.001, 0.01, 0.1 24 hr 0.001 

Increase in hyperdiploid 

frequency (based on 

FISH analysis, there was 

a statistically significant 

dose-related increase for 

each of the 2 

chromosomes tested 

from both donors). 

There was also an 

increase in hypodiploid 

frequency, but it was 

only seen (again at all 

doses) in 1 of the 2 

chromosomes tested and 

in only 1 donor. A 

related experiment 

showed that AsIII can 

disrupt the microtubule 

organization of 

lymphocytes at a dose as 

low as 0.001. 

Ramírez et 

al., 1997 

Primary 

cultured 

human 

umbilical cord 

fibroblasts 

AsIII SA 

AsV

MMAV

DMAV

TMAV

0.8, 2.3, 3.8, 7.7 

16, 32, 64, 160, 

321 

1.4, 3.6, 7.1 mM 

0.7, 1.4, 3.6 mM 

3.7, 7.6, 14.7 mM 

24 hr for all 

0.8 μM 

16 μM 

1.4 mM 

0.7 mM 

3.7 mM 

Induction of CAs: 

The percentages of 

abnormal cells at the 

LOECs for the 5 

chemicals in descending 

order, as listed to the left, 

were: 10%, 16%, 19%, 

28%, and 26%. 

Depletion of GSH by 

pretreatment of cells 

with BSO increased 

induction of CAs by AsIII

SA, AsV, and MMAV but 

decreased it for DMAV. 

In cells pretreated with 

BSO before treatment 

with DMAV, the presence 

of 5 mM or higher GSH 

in the medium markedly 

increased induction of 

CAs. Since GSH does 

not enter the cells itself, 

this suggests that some 

clastogenic chemical is 

generated in the medium 

by interaction of DMAV

with GSH. 

Oya-Ohta 

et al., 1996 

C-150 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

CHO-9 cells 

AsIII SA 

AsV

MMAIII

MMAV

DMAIII

DMAV

TMAV

10 to 10000 for all 30 min for all 

1000 

1000 

10 

None 

50 

None 

None 

Induction of 

chromosomal 

aberrations: 

Aberrations consisted 

mainly of chromatid 

exchanges and breaks; 

dicentrics and rings 

occurred rarely. 

Frequencies of 

aberrations per 100 cells 

at the most effective 

concentration for the 4 

positive chemicals 

ranged from 44 to 74x 

that of the control. 

Dopp et 

al., 2004 

CHO-9 cells 

AsIII SA 

AsV

MMAIII

MMAV

DMAIII

DMAV

TMAV

10 to 10000 for all 30 min 

1000 

1000 

10 

None 

50 

None 

None 

Induction of SCEs: 

For even the most potent 

inducers of SCE, the 

number of SCEs/cell was 

less than double that of 

the untreated control; 

thus they were weak 

inducers. 

Dopp et 

al., 2004 

Human 

primary 

peripheral 

blood 

lymphocytes 

AsIII SA 

0.8 48 hr 0.8 SCEs were induced; 

simultaneous treatment 

with SOD (an oxygen 

radical scavenger) 

blocked induction of 

SCEs. 

Nordenson 

and 

Beckman, 

1991 

CHO K1 cells AsIII SA 20 6 hr 20 SCEs were induced; 

simultaneous treatment 

with squalene at from 40 

to 160 μM significantly 

and dose-dependently 

inhibited induction of 

SCEs. 

Fan et al., 

1996 

Human 

peripheral 

lymphocytes 

AsIII SA 1, 5, 10 48 hr 1 SCEs were induced; 

there was a positive 

dose-response. 

Jha et al., 

1992 

C-151 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Human 

peripheral 

lymphocytes 

AsIII ATO 0.00036, 0.00072, 

0.0014 

24 hr 0.00036 

SCEs were induced; 

there was a positive 

dose-response; cotreatment with retinyl 

palmitate at the highest 

dose of AsIII caused a 

significant ⇓ to a SCE 

frequency like that seen 

at the middle dose; the 

same thing also occurred 

for PDT and AGT, 

showing that retinyl 

palmitate also reversed 

some of the arsenicinduced decrease in the 

rate of cell proliferation. 

Avani and 

Rao, 2007 

CHO K1 cells AsIII SA 5, 10, 20, 40 6 hr 5 

Induction of MN in 

binucleated cells, using 

cytochalasin B after 

arsenic treatment to 

block cytokinesis: 

simultaneous treatment 

with 80 μM squalene 

significantly reduced the 

effect. 

Fan et al., 

1996 

Mouse 

lymphoma 

cells 

(L5178Y/Tk+/-

–3.7.2C cells) 

MMAIII

DMAIII

0.19, 0.28, 0.38, 

0.47, 0.52, 0.57 

0.65, 0.83, 1.29, 

1.51 

4 hr for both 0.28 

1.51 

Mutations at Tk+/- locus 

in mouse lymphoma agar 

assay without exogenous 

metabolic activation: 

⇑ to 2.0x at 0.28, with a 

positive dose-response, 

reaching 7.2x at 0.57. 

⇑ 2.4x control at 

maximum concentration 

tested. 

Both compounds showed 

large excess of small 

colonies, which is 

indicative of 

chromosomal 

aberrations; generally 

similar results were 

found in a mouse 

lymphoma microwell 

assay, which was 

complicated by higher 

toxicity. 

Kligerman 

et al., 2003 

C-152 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Human 

peripheral 

lymphocytes 

AsIII SA 

AsV

MMAIII

MMAV

DMAV

TMAVO 

0.5, 1, 2, 4 

4, 8, 16, 32 

0.01, 0.05, 0.1, 

0.5, 

1, 2 

50, 100, 250, 500 

50, 100, 250 

400, 800, 1000 

72 hr for all 

2 

8 

1 

100 

250 

None 

Induction of MN in 

binucleated lymphocytes 

detected by the 

cytokinesis-block assay 

(using cytochalasin B): 

⇑ in 2 donors at 2 and in 

all 3 donors at 4. 

⇑ in 1 donor at 8 and in 

all 3 donors at 2 higher 

doses. 

⇑ in 1 donor at 1 and in 

all 3 donors at 2. 

⇑ in 2 donors at 100 and 

250 and in all 3 donors at 

500. 

⇑ in 1 donor at 250. 

NSE. 

Further analysis of 

MMAIII showed ⇑⇑ in 

centromere-positive 

micronuclei (∼80% of 

total), which is an 

indicator of induced 

aneuploidy. 

Colognato 

et al., 2007 

SY-5Y cells 

HEK 293 

cells 

AsIII ATO 

for all 

1 

for all 

24 hr 

48 hr 

72 hr 

1 

for all 

Induction of MN 

detected by Hoechst 

staining; response in 

comparison to control in 

SY-5Y and HEK 293 

cells, respectively, for 

each duration of 

treatment: 

At 24 hr: 3.70x, 3.35x. 

At 48 hr: 5.14x, 4.81x. 

At 72 hr: 4.00x, 3.16x. 

Florea et 

al., 2007 

Mouse 

lymphoma 

cells 

(L5178Y/Tk+/-

–3.7.2C cells) 

AsIII SA 

AsV

MMAV

DMAV

2.3, 5.4, 7.7, 8.5, 

10.8, 14.6, 16.2 

3.0, 15.2, 30.3, 

45.5, 60.6, 75.8, 

84.9 

6.2, 12.3, 15.4, 

18.5, 24.7, 30.9 

mM 

12.5, 25.0, 37.5, 

50.0, 56.3, 62.5 

mM 

4 hr 

for all 

8.5 

45.5 

18.5 mM 

56.3 mM 

Mutations at Tk+/- locus 

in mouse lymphoma agar 

assay without exogenous 

metabolic activation. 

Very few, if any, large 

colony mutants were 

induced by all 

compounds. Induction 

of small colony mutants 

is indicative of induction 

of CAs. 

Moore et 

al., 1997a 

C-153 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Mouse 

lymphoma 

cells 

(L5178Y/Tk+/-

–3.7.2C cells) 

AsIII SA 

AsV

MMAV

DMAV

11.5, 13.1, 15.4 

60.6, 69.7, 84.9 

21.6, 24.7, 27.8 

mM 

50.0, 56.3, 62.5 

mM 

4 hr 

for all 

11.5 

60.6 

24.7 mM 

None 

Induction of CAs: 

Aberrations consisted 

mainly of chromatid 

exchanges and breaks; 

all concentrations 

reported showed 

induction of CAs except 

for DMAV, which gave 

results of borderline 

significance that were 

considered negative by 

the authors. Lower 

frequencies of induction 

were seen for MMAV

than for the inorganic 

arsenics in spite of the 

much higher doses. 

Moore et 

al., 1997a 

SHE cells AsIII SA 4, 6, 8 24 hr 

4 for first 

two 

effects 

Induction of CAs: 0, 1%; 

4, 9%; 6, 15%; 8, 32%. 

Induction of polyploidy 

and endoreduplication: 0, 

0%; 4, 6%; 6, 19%; 8, 

27%. 

Colony-forming 

efficiency relative to 

control after 7 days of 

culturing post-As 

treatment: 6, 77%; 8, 

49%. 

MI: 0, 9.2; 4, 10.9; 6, 

8.7; 8, 1.3. 

Hagiwara 

et al., 2006 

V79 cells 

AsIII SA 

AsV 50, 100, 250, 500 

for both 

1 hr 

for both 

50 

50 

Induction of CAs (no. of 

aberrations in 100 

metaphase cells): 

0, ∼7; 50, ∼49; 100, ∼99; 

250, ∼120; 500, ∼160. 

0, ∼6; 50, ∼32; 100, ∼44; 

250, ∼62; 500, ∼73. 

Aberrations were mainly 

chromatid breaks. Cotreatment or pretreatment 

with tea extracts reduced 

aberration frequencies by 

half or more, while posttreatments also reduced 

the level of effects, 

which was suggestive of 

enhanced repair. Tea 

extracts induced CAT 

and SOD activity. 

Sinha et 

al., 2005a 

C-154 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

V79 cells 

AsIII SA 

AsV

DMAV

50, 100, 250, 500 

for all 

1 hr 

for all 

100 or 

possibly 

50 for all 

Induction of micronuclei 

(MN) in cytochalasin B 

assay: (No. of MN per 

1000 binucleated cells): 

50, ∼105; 100, ∼110; 

250, ∼170; 500, ∼300. 

50, ∼80; 100, ∼105; 250, 

∼125; 500, ∼150. 

50, 52; 100, 70; 250, 99; 

500, 111. 

Co-treatments with tea 

extracts reduced MN 

frequencies by two-thirds 

or more for AsIII and by 

half or more for AsV and 

DMAV. Pretreatments 

with tea extracts also 

caused a large ⇓ in MN 

frequencies for all 3 

arsenicals. Posttreatments also reduced 

MN frequencies, which 

was suggestive of 

enhanced repair. The 

polyphenols EGCG and 

TF extracted from tea 

had similar effects in 

reducing MN 

frequencies. The LOECs 

are uncertain because no 

data were reported for 

the untreated controls. 

Sinha et 

al., 2005b 

Mouse 

lymphoma 

cells 

(L5178Y/Tk+/-

–3.7.2C cells) 

AsIII SA 

AsV

MMAV

DMAV

11.5, 13.1, 15.4 

60.6, 69.7, 84.9 

21.6, 24.7, 27.8 

mM 

50.0, 56.3, 62.5 

mM 

4 hr 

for all 

None 

60.6 

24.7 mM 

None 

Induction of MN in 

binucleated cells, using 

cytochalasin B after 

arsenic treatment to 

block cytokinesis: AsIII

SA gave results of 

borderline significance 

that were considered 

negative by the authors. 

Moore et 

al., 1997a 

C-155 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Don Chinese 

hamster cells 

AsIII SA 

AsV

arsenic 

pentoxide 

AsV

disodium 

arsenate 

7.7 

13.9 

32.1 

28 hr 

for all 

7.7 

13.9 

32.1 

SCEs were induced for 

all 3 chemicals at 1.56, 

1.61, and 1.46 times the 

control level, 

respectively. 

The concentrations 

tested for SCEs for all 3 

chemicals were the “50% 

inhibition doses” 

following culturing for 

72 hours and using a 

Giemsa test for viability. 

Ohno et 

al., 1982 

CHO cells 

AsIII SA 

AsV

1, 5, 10 

50, 80, 100 

24 hr 

for all 

1 

50 

Chromosome aberrations 

(breaks and exchanges) 

were induced by both 

compounds with a doseresponse relationship; 

AsIII was 5–10 times 

more effective than AsV

per unit dose; 80 μM 

was ~50% growth 

inhibition dose over 4 

days for AsIII. 

Wan et al., 

1982 

Human 

lymphocytes 

AsIII SA 0.5, 1.0, 5.0 48 hr 0.5 Chromosome aberrations 

(breaks and exchanges) 

were induced. 

Wan et al., 

1982 

CHO cells AsIII SA 1, 10 24 hr 1 SCEs were induced with 

a dose-response 

relationship. 

Wan et al., 

1982 

P388D1

macrophage 

cell line 

AsIII SA 

AsV 

DMAV

0.01, 0.1, 1 

0.1, 1, 10 

1,10 

48 hr 

for all 

None 

None 

None 

No more than slight hints 

of induction of SCEs 

under any of these 

experimental conditions. 

Andersen, 

1983 

Human 

peripheral 

lymphocytes 

AsIII SA 

DMAV

1 

1 

48 hr 

48 hr 

1 

1 

Induction of SCEs. 

Induction of SCEs. 

Andersen, 

1983 

Human 

peripheral 

lymphocytes 

AsIII SA 0.5, 1.0, 1.5, 2.0 48 hr 1.0 Induction of SCEs: in 2 

of the 3 donors, the 

LOEC was 1.5. Cells 

from one donor were 

more sensitive. 

Wiencke 

and Yager, 

1992 

C-156 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

BrdUsubstituted 

replicating 

human 

lymphocytes 

AsIII SA 

AsV

0.77, 1.54 

13.5, 26.9 

24 hr 

24 hr 

0.77 

13.5 

Induction of SCEs, but 

only in 2 of 4 subjects. 

Induction of SCEs, but 

only in 1 of 4 subjects; in 

2 subjects (1 at lower 

dose and 1 at higher 

dose) there was a slight 

but significant decrease 

in SCEs. 

Crossen, 

1983 

G0 human 

lymphocytes 

AsIII SA 

AsV

1.54 

26.9 

24 hr 

24 hr 

None 

None 

No induction of SCEs 

with either treatment. 

(4 subjects in each 

group.) 

Crossen, 

1983 

2BS cells AsIII SA 1.0, 3.0, 5.0, 10 5 hr 1.0 

DNA-protein crosslinks 

detected by alkaline 

elution; peak effect at 

3.0; no effect at 10.0; 

further testing of DNA 

showed the crosslinks to 

be protein-associated 

DNA-strand breaks. 

Dong and 

Luo, 1993 

V79-C13 

Chinese 

hamster cell 

line 

AsIII SA 10 24 hr 10 

Cells examined after 6, 

12, 18, and 24 hr and 

after 6, 24, and 48 hr of 

recovery: by 6 hr of 

treatment there were 

multinucleated cells and 

round cells, by 12 hr 

there were giant cells. 

Multinucleated cells 

persisted at high levels to 

48 hr after treatment. 

Also saw abnormal 

spindles and persistent 

(i.e., up to 5 days 

observed) aneuploidy 

and hyperdiploidy, but 

no statistically 

significant changes in 

CAs or MI. 

Sciandrello 

et al., 2002 

NB4 cells AsIII ATO 0.75 3 wk 0.75 

Enlarged cells were 

found that contained 

chromosomal end-to-end 

fusions. In 80 

karyotypes, there were 

an average of 2.4 fusion 

events per cell, and 32 

cells had polyploidy. 

FISH analysis showed 

that fusions are 

associated with attrition 

of telomeres. 

Chou et 

al., 2001 

C-157 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

NB4 cells 

HeLa cells 

AsIII ATO 

for both 

0.25 

1 

4, 5, 6 wk 

3, 4 wk 

0.25 

1 

Southern blot of digested 

genomic DNA: 

⇓ telomere length at all 3 

time points. 

⇓ telomere length at both 

time points. 

Chou et 

al., 2001 

PARP-1+/+

MEF cells 

PARP-1-/-

MEF cells 

AsIII SA 

for both 

11.5, 23 

for both 

24 hr 

for both 

None 

11.5 

Telomere length 

measured by flow FISH 

assay (point estimate 

comparisons were made 

to unexposed cells of the 

same genotype): 

~98% of control at 11.5, 

~91% of control at 23; 

both are NSEs. 

~76% of control at 11.5, 

~71% of control at 23. 

Poonepalli 

et al., 2005 

PARP-1+/+

MEF cells 

PARP-1-/-

MEF cells 

AsIII SA 

for both 

11.5, 23 

for both 

48 hr 

for both 

23 

11.5 

Telomere length 

measured by flow FISH 

assay (point estimate 

comparisons were made 

to unexposed cells of the 

same genotype): 

~99% of control at 11.5, 

~79% of control at 23; 

the one at 11.5 was NSE. 

~79% of control at 11.5, 

~41% of control at 23. 

inorganic arsenicinduced telomere 

attrition was thus much 

greater in PARP-1-/-

MEFs. 

Poonepalli 

et al., 2005 

PARP-1+/+

MEF cells 

PARP-1-/-

MEF cells 

AsIII SA 

for both 

11.5, 23 

for both 

24 hr 

for both 

11.5 

11.5 

Induced (experimental – 

control) % of MN in 

binucleated cells (with 

cytochalasin B posttreatment to block 

cytokinesis): 

~4% at 11.5, ~5% at 23. 

 

~18% at 11.5, ~13% at 

23. 

Poonepalli 

et al., 2005 

C-158 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

PARP-1+/+

MEF cells 

PARP-1-/-

MEF cells 

AsIII SA 

for both 

11.5, 23 

for both 

48 hr 

for both 

11.5 

11.5 

Induced (experimental – 

control) % of MN in 

binucleated cells (with 

cytochalasin B posttreatment to block 

cytokinesis): 

~6% at 11.5, ~6% at 23. 

 

~27% at 11.5, ~15% at 

23. 

Poonepalli 

et al., 2005 

PARP-1+/+

MEF cells 

PARP-1-/-

MEF cells 

AsIII SA 

for both 

11.5, 23 

for both 

24 hr 

for both 

None 

11.5 

Induced (experimental – 

control) frequency of 

CAs per cell, using FISH 

with a telomeric PNA 

probe: 

~0.04 at 11.5, ~0.04 at 

23; both are NSEs. 

~0.09 at 11.5, ~0.05 at 

23; only the one at 11.5 

was statistically 

significant. 

CAs included end-to-end 

fusions, chromosome 

breaks, and fragments. 

Poonepalli 

et al., 2005 

PARP-1+/+

MEF cells 

PARP-1-/-

MEF cells 

AsIII SA 

for both 

11.5, 23 

for both 

48 hr 

for both 

None 

11.5 

Induced (experimental – 

control) frequency of 

CAs per cell, using FISH 

with a telomeric PNA 

probe: 

~0.04 at 11.5, ~0.04 at 

23; both are NSEs. 

~0.11 at 11.5, ~0.03 at 

23; only the one at 11.5 

was statistically 

significant. 

CAs included end-to-end 

fusions, chromosome 

breaks, and fragments. 

Poonepalli 

et al., 2005 

C-159 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

293 cells 

AsIII ATO 

2 24 hr 2 

No. MN/1000 

binucleated cells (with 

cytochalasin B during 

treatments to block 

cytokinesis): untreated = 

∼35; dose of 2: big ⇑ to 

∼260. 

Effects of co-treatment 

(CoTr) with modulators 

at high doses: 

CoTr 200 μM DMSA: ⇓

from inorganic arsenic 

alone to ∼155. 

CoTr 100 μM DMPS: ⇓

from inorganic arsenic 

alone to ∼170. 

Effects of CoTr with 

modulators at low doses: 

CoTr 20 μM DMSA: ⇑

from inorganic arsenic 

alone to ∼605. 

CoTr 10 μM DMPS: ⇑

from inorganic arsenic 

alone to ∼670. 

Jan et al., 

2006 

293 cells MMAIII 2 24 hr 2 

No. MN/1000 

binucleated cells (with 

cytochalasin B during 

treatments to block 

cytokinesis): untreated = 

∼35; dose of 2: big ⇑ to 

∼230. 

Effects of CoTr with 

modulators at high 

doses: 

CoTr 200 μM DMSA: ⇓

from inorganic arsenic 

alone to ∼130. 

CoTr 100 μM DMPS: ⇓

from inorganic arsenic 

alone to ∼155. 

Effects of CoTr with 

modulators at low doses: 

CoTr 20 μM DMSA: ⇑

from inorganic arsenic 

alone to ∼465. 

CoTr 10 μM DMPS: ⇑

from inorganic arsenic 

alone to ∼470. 

Jan et al., 

2006 

C-160 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

293 cells DMAIII 2 24 hr 2 

No. MN/1000 

binucleated cells (with 

cytochalasin B during 

treatments to block 

cytokinesis): untreated = 

∼35; dose of 2: big ⇑ to 

∼315. 

Effects of CoTr with 

modulators at high 

doses: 

CoTr 200 μM DMSA: ⇓

from inorganic arsenic 

alone to ∼170. 

CoTr 100 μM DMPS: ⇓

from inorganic arsenic 

alone to ∼175. 

Effects of CoTr with 

modulators at low doses: 

CoTr 20 μM DMSA: ⇑

from inorganic arsenic 

alone to ∼630. 

CoTr 10 μM DMPS: ⇑

from inorganic arsenic 

alone to ∼635. 

Jan et al., 

2006 

SV-HUC-1 

cells 

AsIII ATO 2 24 hr 2 

No. MN/1000 

binucleated cells (with 

cytochalasin B during 

treatments to block 

cytokinesis): untreated = 

∼35; dose of 2: big ⇑ to 

∼330. 

Effects of CoTr with 

modulators at high 

doses: 

CoTr 200 μM DMSA: ⇓

from inorganic arsenic 

alone to ∼150. 

CoTr 100 μM DMPS: ⇓

from inorganic arsenic 

alone to ∼150. 

Effects of CoTr with 

modulators at low doses: 

CoTr 20 μM DMSA: ⇑

from inorganic arsenic 

alone to ∼680. 

CoTr 10 μM DMPS: ⇑

from inorganic arsenic 

alone to ∼645. 

Jan et al., 

2006 

C-161 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

SV-HUC-1 

cells 

MMAIII 2 24 hr 2 

No. MN/1000 

binucleated cells (with 

cytochalasin B during 

treatments to block 

cytokinesis): untreated = 

∼35; dose of 2: big ⇑ to 

∼270. 

Effects of CoTr with 

modulators at high 

doses: 

CoTr 200 μM DMSA: ⇓

from inorganic arsenic 

alone to ∼145. 

CoTr 100 μM DMPS: ⇓

from inorganic arsenic 

alone to ∼150. 

Effects of CoTr with 

modulators at low doses: 

CoTr 20 μM DMSA: ⇑

from inorganic arsenic 

alone to ∼570. 

CoTr 10 μM DMPS: ⇑

from inorganic arsenic 

alone to ∼470. 

Jan et al., 

2006 

SV-HUC-1 

cells 

DMAIII 2 24 hr 2 

No. MN/1000 

binucleated cells (with 

cytochalasin B during 

treatments to block 

cytokinesis): untreated = 

∼35; dose of 2: big ⇑ to 

∼400. 

Effects of CoTr with 

modulators at high 

doses: 

CoTr 200 μM DMSA: ⇓

from inorganic arsenic 

alone to ∼160. 

CoTr 100 μM DMPS: ⇓

from inorganic arsenic 

alone to ∼145. 

Effects of CoTr with 

modulators at low doses: 

CoTr 20 μM DMSA: ⇑

from inorganic arsenic 

alone to ∼620. 

CoTr 10 μM DMPS: ⇑

from inorganic arsenic 

alone to ∼650. 

Jan et al., 

2006 

C-162 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

SHE cells 

AsIII SA 

DMAIIII 

3, 10 

0.5, 1.0 

48 hr for both 

10 

0.5 

Aneuploidy detected by 

flow cytometry: 

Slight ⇑. 

Slight ⇑; ⇑⇑⇑ at 1.0. 

Other experiments 

showed that DMAIIII 

caused abnormalities of 

mitotic spindles, 

centrosomes, and 

microtubule elongation. 

Ochi et al., 

2004 

Primary rat 

hepatocytes 

AsIII SA 0.25, 0.5, 1, 2.5, 5, 

7.5, 10 

27 hr 1 

Induction of MN (mean 

no./1000 cells): 

17.4 at dose of 1, 

increasing with dose to 

24.4 at dose of 7.5; 

control = 13.7; too many 

cells were dead at dose 

of 10 to evaluate this 

endpoint. Co-treatment 

with 10 or 25 μM SbIIICl: 

⇓ in micronucleus 

frequency below 

expectation of an 

additive interaction; that 

chemical also induced 

MN. 

Hasgekar 

et al., 2006 

CL3 cells, 

synchronous 

at G1 

CL3 cells, 

asynchronous 

(asyn) 

CL3 cells, 

synchronous 

at G2/M 

AsIII SA 

for all 

50 

for all 

3 hr 

for all 

50 

for all 

Induction of MN; 

inorganic arsenic 

treatment was followed 

by culturing with 

cytochalasin B for 24 hr 

to block cytokinesis): 

induced no. of MN 

(experimental – 

control)/1000 

binucleated cells: G1, 

~181; asyn, ~141; 

G2/M, ~125; when G1 

cells were co-treated 

with inorganic arsenic 

and either PD98059 or 

U0126, this number ⇓

from ~181 to ~75-80. 

Percentages of 

binucleated cells: G1, 

14%; asyn, 47%; G2/M, 

39%. 

Li et al., 

2006a 

C-163 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

CL3 cells, 

synchronous 

at G1 

AsIII SA 50 3 hr 50 

Induction of MN; 

inorganic arsenic 

treatment was followed 

by culturing with 

cytochalasin B for 24 hr 

to block cytokinesis): 

induced frequency = 

~181/1000 binucleated 

cells (as in row above); 

percentage of 

binucleated cells: 14% 

(as in row above). 

Culturing of G1 cells 

with cytochalasin B for 

36-48 hr (instead of 24) 

caused marked ⇑ in 

percentages of 

binucleated cells and 

marked ⇓ in induced 

numbers of MN (1000 

binucleated cells) from 

181 to ~40-70. Also, 

when cultured with 

cytochalasin B for 40 hr 

(instead of 24 hr) after 

the co-treatment of 

inorganic arsenic with 

PD98059 or U0126, 

these 2 structurally 

dissimilar inhibitors of 

MEK1/2 caused no 

further ⇓ from inorganic 

arsenic alone. 

Li et al., 

2006a 

V79-C13 

Chinese 

hamster cells 

AsIII SA 10 24 hr 10 

After being expanded 

through 120 generations 

in the absence of arsenic 

and then being cloned, 

acquired genetic 

instability persisted and 

often came to include 

dicentric chromosomes 

and telomeric 

associations. These 

same clones, which were 

often aneuploid, 

micronucleated and/or 

multinucleated, were 

affected by the DNA 

hypomethylation that 

was seen globally in the 

cells immediately after 

the 24-hr treatment. 

Sciandrello 

et al., 2004 

C-164 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

CHO cell 

lines: 

K1 (parental 

to the 

following 

line) 

XRS-5 (X-ray 

and H2O2 

sensitive) 

AsIII SA 

10, 20, 40, 80 for 

both 

4 hr for both 

80 

10 

Induction of MN in 

binucleated cells, using 

cytochalasin B after 

arsenic treatment to 

block cytokinesis: the 

much less responsive K1 

cells have 6 times as 

much catalase activity as 

XRS-5 cells; both lines 

are similar in arsenic 

uptake and release, in 

GSH levels, and in GSH 

S-transferase activity. 

Wang and 

Huang, 

1994 

CHO cell 

lines: 

K1 (parental 

to the 

following 

lines) 

XRS-6 (X-ray 

sensitive) 

XRS-5 (X-ray 

and H2O2 

sensitive) 

AsIII SA 

20, 40, 80 

20, 40, 60 

10, 20, 30, 40, 60 

4 hr for all 

40 

20 

10 

Frequencies of MN per 

thousand binucleated 

cells per μM of arsenic 

for K1, XRS-6, and 

XRS-5 cells were 2.1, 

4.5, and 10.8, 

respectively. 

(Cytochalasin B was 

used after arsenic 

treatment to block 

cytokinesis.) K1 cells 

have 5.8 times as much 

catalase activity and 5.4 

times as much GPx 

activity as XRS-5 cells. 

K1 cells have 3.7 times 

as much catalase activity 

and 2.1 times as much 

GPx activity as XRS-5 

cells. The cells with 

intermediate amounts 

have an intermediate 

response. Co-treatment 

of XRS-5 cells with 

catalase or GPx 

eliminates induction of 

MN by AsIII SA. 

Treatment of K1 cells 

with inhibitors of 

catalase and GPx makes 

them much more 

sensitive to induction of 

MN by AsIII SA; when 

co-treated together, there 

is a synergistic effect. 

Wang et 

al., 1997 

C-165 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

CHO-9 cells 

AsIII SA 

AsV

MMAIII

MMAV

DMAV

DMAIII

TMAV

1, 5, 10, 50, 100, 

500 for both 

1, 5, 10, 30 

1, 5, 10, 30, 100, 

500, 5000 for both 

1, 5, 10 

1, 5, 10, 5000 

1 hr 

for all 

None 

None 

10 

5000 

5000 

1 

5000 

Induction of MN in 

binucleated cells: 

DMAIII was by far the 

most potent. Dopp et 

al., 2004 

HFW cells 

AsIII SA 

for both 

durations 

1.25, 2.5, 5, 10 

5, 10, 20, 40, 80 

24 hr 

4 hr 

1.25 

10 

Induction of MN, with 

about 70% being 

kinetochore-positive at 

maximum induction 

found at dose of 5. 

Induction of MN, with 

about 70% being 

kinetochore-negative at 

maximum induction 

found at dose of 40. 

Yih and 

Lee, 1999 

HLFC cells 

HLFK cells 

(Ku70 

deficient) 

AsIII SA 

for both 

1, 2.5, 5, 10 

for both 

24 hr 

for both 

2.5 

2.5 

Induction of micronuclei 

(% of cells with MN): 

Control, 5%; 1, 4%; 2.5, 

8%; 5, 10%, 10, 15%. 

Control, 4%; 1, 6%; 2.5, 

10%; 5, 21%, 10, 27%. 

At the 2 higher doses the 

% is significantly higher 

in the HLFK cells. Ku70 

is 1 of 3 subunits of 

DNA-dependent protein 

kinase, and the Ku70 

protein plays an 

important role in repair 

of DNA double-strand 

breaks. 

Liu et al., 

2007b 

C-166 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HLFC cells 

HLFK cells 

(Ku70 

deficient) 

AsIII SA 

for both 

1, 2.5, 5, 10 

for both 

24 hr 

for both 

5 

2.5 

Formation of abnormal 

nuclei (% of cells with 

abnormal nuclei): 

Control, 7%; 1, 9%; 2.5, 

10%; 5, 19%, 10, 23%. 

Control, 10%; 1, 12%; 

2.5, 21%; 5, 37%, 10, 

42%. At the 3 higher 

doses the % is 

significantly higher in 

the HLFK cells. Ku70 is 

1 of 3 subunits of DNAdependent protein 

kinase, and the Ku70 

protein plays an 

important role in repair 

of DNA double-strand 

breaks. 

Liu et al., 

2007b 

HFF cells AsIII SA 5 24 hr 5 

cen+ and cen- MN 

induced per 1000 cells: 

cen- MN: control, 

∼10/1000; inorganic 

arsenic, ∼17/1000. 

cen+ MN: control, 

∼2/1000; inorganic 

arsenic, ∼18/1000. 

Co-treatment with 170 

nM SAM essentially 

eliminated induction of 

cen+ MN without having 

any effect on induction 

of cen- MN. 

Ramírez et 

al., 2007 

HL-60 cells 

HaCaT cells

AsIII SA 0.5, 10, 20 3 days 

10 for ⇓

0.5 for ⇑, 

10 ⇓

Analysis of telomere 

length by TRF analysis 

using Southern blot 

assay: 

Telomeres were 

shortened compared to 

controls at 10 and 20. 

Telomeres were 

shortened compared to 

controls at 10 and 20, but 

in these cells only, the 

telomeres were slightly 

elongated at dose of 0.5. 

Zhang et 

al., 2003 

C-167 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Humanhamster 

hybrid AL

cells 

AsIII SA 3.8, 7.7, 15.4 1 day or 5 days Depends 

on locus 

Induction of mutations at 

both loci, with both 

showing higher response 

after 

5-day treatment than 

after 1-day treatment. 

After only 1 day of 

treatment, the LOECs 

were 3.8 at S1 locus and 

15.4 at the HPRT locus. 

This effect is not 

grouped with gene 

mutations because most 

mutations were large 

deletions; about 28 times 

as many mutations 

occurred at the Sl locus, 

and co-treatment with 

DMSO eliminated most 

of the mutation 

induction. 

Hei et al., 

1998 

Humanhamster 

hybrid AL

cells 

AsIII SA 11.5, 15.4 24 hr 11.5 

Induction of mutations at 

CD59 locus (formerly 

known as S1 locus); this 

effect is not grouped 

with gene mutations 

because most mutations 

were large multilocus 

deletions; co-treatment 

with SOD or catalase 

considerably reduced 

mutation induction. 

Kessel et 

al., 2002 

Humanhamster 

hybrid AL

cells 

AsIII SA 3.8 24 hr 3.8 Induction of mutations at 

CD59 locus; 

pretreatment with BSO 

(to reduce GSH levels) 

increased mutation rate 

about 3-fold. 

Kessel et 

al., 2002 

C-168 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Enucleated AL

hybrid cells 

treated with 

AsIII were 

fused with 

untreated 

nuclei to form 

reconstituted 

AL hybrid 

cells 

AsIII SA 15.4 3 hr 15.4 

Induction of mutations at 

CD59 locus: 

Mutant frequency >2x 

the frequency in control 

cells reconstituted from 

untreated enucleated 

cells and untreated 

nuclei. Induction of 

ROS was demonstrated 

in inorganic arsenictreated enucleated cells 

by using a fluorescent 

probe. These results 

suggest that 

mitochondria may be 

essential for induction of 

CD59-

 mutations (in 

nuclear DNA). 

Liu et al., 

2005 

AL hybrid 

cells made 

highly 

deficient in 

mitochondrial 

DNA by longterm 

ditercalinium 

treatment; 

then called ρ0

cells 

AsIII SA 7.7, 11.5, 13.5, 

15.4 

18 hr None 

No increase in CD59-

mutations; there was a 

dose-related increase in 

cytotoxicity. Analysis of 

DNA showed that 

mtDNA was >95% 

depleted in the ρ0

 cells. 

Suggests that 

mitochondrial function 

may be necessary for 

induction of CD59-

mutations by inorganic 

arsenic. 

Liu et al., 

2005 

Humanhamster 

hybrid AL

cells 

AsIII SA 

for both 

1.9, 3.8, 7.7 

for both 

16 days 

30 days 

1.9 

1.9 

Induction of mutations at 

the CD59-

 locus: 

increase in mutation 

frequency at all doses, 

with a positive doseresponse and at least a 

doubling of the control 

frequency at the higher 

dose. These cells 

showed a dose-related 

increase in cytotoxicity, 

with never less than a 

60% surviving fraction. 

After a 60-day exposure, 

there was an almost 3-

fold increase in the 

number of MN observed 

over the untreated 

control, but details were 

not provided. 

Partridge 

et al., 2007 

C-169 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Humanhamster 

hybrid AL

cells 

AsIII SA 0.8, 3.8, 7.7, 15.4 24 hr 3.8 Induction of CD59–

mutants: 

(Addition of BSO, which 

suppresses GSH, 

increased mutant 

frequencies more than 5-

fold.) 

Liu et al., 

2001 

Co-carcinogenesis 

Rat lung 

epithelial cell 

line 

Rat lung 

epithelial cell 

line exposed 

to 100 nM 

B[α]P for 24 

hr 

AsIII SA 

for both 

1.5 

for both 

12 wk without 

the B[α]P 

treatment or 

immediately 

following that 

treatment 

1.5 

for both 

Transformation (i.e., 

anchorage-independent 

growth in soft agar) 

occurred with 12-wk 

inorganic arsenic 

treatment alone or with 

B[α]P treatment alone. 

There was a synergistic 

interaction when the 

B[α]P treatment was 

followed by the 12-wk 

inorganic arsenic 

treatment, with the 

transformation rate then 

exceeding 500 and 200 

times that of the 

inorganic arsenic or 

B[α]P treatments alone, 

respectively. 

Lau and 

Chiu, 2006 

C-170 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Rat lung 

epithelial cell 

line 

Rat lung 

epithelial cell 

line exposed 

to 100 nM 

B[α]P for 24 

hr 

AsIII SA 

for both 

1.5 

for both 

12 wk without 

the B[α]P 

treatment or 

immediately 

following that 

treatment 

1.5 

for both 

Changes in the proteome 

of the transformed cells 

detected by MALDITOF-MS analysis and 

other methods: inorganic 

arsenic and B[α]P 

treatments alone caused 

changes in most of the 

following proteins alone. 

 The combined treatment 

often caused a 

synergistic interaction on 

the protein levels in the 

same direction as one or 

both treatments changed 

them alone. Affected 

proteins were as follows: 

3 proteins belonging to 

intermediate filaments 

were down-regulated; 6 

proteins belonging to 

antioxidative stress-, 

chaperone-, and 

glycolytic proteins were 

up-regulated. Also 

phosph-ERK1/2 and αactinin, which are 

associated with 

promotion of cell 

proliferation and dedifferentiation, were upregulated. 

Lau and 

Chiu, 2006 

C-171 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

GM04312C 

cells 

AsIII SA 10, 50 24 hr 10 

BPDE-DNA adducts 

were measured after a 

30-min treatment with 

0.5 μM BPDE that 

followed the inorganic 

arsenic pretreatment. 

Compared to no 

pretreatment, increases 

in these adducts at the 

doses of 10 and 50 were 

1.4x and 1.6x, 

respectively. In these 

NER-deficient cells, 

which could be used to 

dissect induction of 

DNA damage from DNA 

repair, it was shown that 

inorganic arsenic 

markedly increased the 

cellular uptake of BPDE 

in a dose-dependent 

manner. It was 

concluded that this effect 

contributes to the cocarcinogenesis in 

addition to arsenic’s 

“well demonstrated 

inhibitory effect on DNA 

repair.” 

Shen et al., 

2006 

Co-mutagenesis

E. coli WP2 

irradiated 

with 5.6 J/m2

of UV on 

plates that 

contained: 

AsIII SA 

AsV 

100, 250, 500, 750 

100, 300, 500 

— 100 

None 

Plating protocol for Trp+

revertants: synergistic 

interaction in inducing 

Trp+

 revertants at lower 

3 dose levels for SA 

only, with peak effect at 

250; synergistic 

interaction was seen only 

in a strain of E. coli that 

can carry out excision 

repair of pyrimidine 

dimers. Four E. coli 

strains that did not meet 

that criterion were tested, 

with no synergism being 

seen. 

Rossman, 

1981 

C-172 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

CHO K1 cells 

in late G1 of 

mitotic cycle 

exposed to 7 

J/m2

 of UV 

AsIII SA 40 2 hr 40 High frequency of 

chromosome aberrations 

was induced; effect was 

markedly reduced by 

prior or simultaneous 

(but not by subsequent) 

treatment with GSH. 

Huang et 

al., 1993 

CHO cells 

exposed to 1, 

2, 4, or 8 J/m2

of UV 

AsIII SA 5, 10 24 hr 5 

Induction of 

chromosomal 

aberrations: synergistic 

interaction was 

demonstrated at all dose 

levels of UV and 

inorganic arsenic except 

for 1 J/m2

 with the 10 

μM inorganic arsenic 

treatment. At other UV 

dose levels, the 

responses at 10 μM 

arsenic only slightly 

exceeded those at 5 μM. 

 UV or inorganic arsenic 

alone induced mainly 

chromatid-type 

aberrations, but in cells 

treated with both agents 

there was an apparent 

increase of chromatid 

breaks, chromatid 

exchanges, chromatid 

gaps, and chromosome 

breaks. 

Lee et al., 

1985 

CHO cells 

exposed to 1, 

2, 4, or 8 J/m2

of UV 

AsIII SA 5, 10 24 hr None Induction of SCEs: no 

statistically significant 

effect of the inorganic 

arsenic treatment was 

observed. 

Lee et al., 

1985 

Human 

peripheral 

lymphocytes 

simultaneousl

y treated with 

6 μM DEB 

AsIII SA 0.5, 1.0, 1.5, 2.0 48 hr 1.0 Induction of 

chromosomal 

aberrations: there was 

synergistic interaction 

between DEB and 

inorganic arsenic. 

Wiencke 

and Yager, 

1992 

C-173 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Human 

peripheral 

lymphocytes 

simultaneousl

y treated with 

6 μM DEB 

AsIII SA 0.5, 1.0, 1.5, 2.0 48 hr ~1.0 

Induction of SCEs: 

Unlike with CAs, there 

was not a synergistic 

interaction. Although no 

statistical comparisons 

were presented, the 

trends suggested 

additivity between the 

two mutagens. 

Wiencke 

and Yager, 

1992 

CHO cells 

exposed to 

2 or 4 J/m2

 of 

UV 

AsIII SA 5, 10 24 hr 5 Induction of gene 

mutations to 6-

thioguanine resistance: 

synergistic interaction 

was demonstrated at both 

dose levels of UV and 

inorganic arsenic. 

Lee et al., 

1985 

CHO cells 

exposed to 

2 or 4 J/m2

 of 

UV 

AsIII SA 5, 10 24 hr 5 Induction of gene 

mutations to ouabain 

resistance: inorganic 

arsenic had no effect. 

Lee et al., 

1985 

CHO K1 cells 

exposed to 

1.5 or 2.5 

J/m2

 of UV 

AsIII SA 10 24 hr 10 

Induction of 6-TGr

 gene 

mutations at the HPRT 

locus: synergistic 

interaction was 

demonstrated at both 

dose levels of UV; 

inorganic arsenic at 

doses of 10 to 40 had no 

effect on the mutation 

frequency by itself. 

Yang et 

al., 1992 

CHO cells 

treated with 

MMS before 

or after 

inorganic 

arsenic 

treatment 

AsIII SA 

10, as 

pretreatment 

10, as 

posttreatment 

24 hr 

24 hr 

10 

10 

Induction of gene 

mutations at the HGPRT 

locus: 

⇓ compared to MMS 

alone. 

⇑ compared to MMS 

alone, synergistic 

interaction. 

Lee et al., 

1986 

CHO cells 

treated with 

MMS before 

or after 

inorganic 

arsenic 

treatment 

AsIII SA 

5, 10, as 

pretreatments 

5, 10, as 

posttreatments 

24 hr 

24 hr 

None 

5 

Induction of 

chromosomal 

aberrations: 

No change from MMS 

alone. 

⇑ frequency compared to 

MMS alone, synergistic 

interaction with even 

bigger effect at 10. 

Lee et al., 

1986 

C-174 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

CHO cells 

treated with 

MMS before 

or after 

inorganic 

arsenic 

treatment 

AsIII SA 

5, 10, as 

pretreatments 

5, 10, as 

posttreatments 

24 hr 

24 hr 

None 

None 

Induction of SCEs: 

No change from MMS 

alone. 

No change from MMS 

alone. 

Lee et al., 

1986 

Human 

peripheral 

lymphocytes 

AsIII SA 5 

2 hr before 

X-rays, 30 min 

after 

X-rays 

5 

Synergistic interaction in 

causing dicentrics and 

rings in both donors; 

synergistic interaction in 

causing deletions in one 

of the donors and 

approximately an 

additive response in the 

other; doses of X-rays 

were 1 Gy or 2 Gy with 

the dose rate unspecified. 

Jha et al., 

1992 

VH16 cell 

line (human 

primary 

fibroblasts) 

exposed to 7.5 

J/m2

 of UV 

AsIII SA 5 24 hr 5 

inorganic arsenic 

exposure increased the 

frequencies of MN in 

binucleated cells and of 

SCEs over what they 

would have been with 

UV alone, but there was 

not a synergistic effect 

for MN. 

Jha et al., 

1992 

V79 cells 

treated with 

MNU 

AsIII SA 10 

5 

3 hr 

24 hr 

10 

5 

Induction of gene 

mutations at the HPRT 

locus: 

While neither inorganic 

arsenic treatment 

induced mutations by 

itself, as a post-treatment 

these inorganic arsenic 

treatments both caused 

an ⇑ in the mutation 

frequency compared to 

MNU alone; there was a 

synergistic interaction. 

Li and 

Rossman, 

1989a 

C-175 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

V79 cells 

exposed to 5-

15 J/m2

 of 

UVC 

AsIII SA 10 3 hr 10 

Induction of gene 

mutations at the HPRT 

locus: 

While the inorganic 

arsenic treatment 

induced no mutations by 

itself, as a post-treatment 

it caused an ⇑ in the 

mutation frequency 

compared to UVC 

irradiation alone; there 

was a synergistic 

interaction. 

Li and 

Rossman, 

1991 

V79 cells 

exposed to 

55-220 KJ/m2

of UVA 

AsIII SA 10 3 hr 10 

Induction of gene 

mutations at the HPRT 

locus: 

While the inorganic 

arsenic treatment 

induced no mutations by 

itself, as a post-treatment 

it caused an ⇑ in the 

mutation frequency 

compared to UVA 

irradiation alone; there 

was a synergistic 

interaction. 

Li and 

Rossman, 

1991 

V79 cells 

exposed to: 

400-800 J/m2

of UVB 

200 J/m2

 of 

UVB 

AsIII SA 

for both 

10 

5, 10, 15 

3 hr 

24 hr 

None 

10 

Induction of gene 

mutations at the HPRT 

locus: 

While the inorganic 

arsenic treatments 

induced no mutations by 

themselves, the 24-hr 

post-treatment caused an 

⇑ in the mutation 

frequency compared to 

UVB irradiation alone; 

there was a synergistic 

interaction. 

Li and 

Rossman, 

1991 

Mouse 

291.03C 

keratinocytes 

irradiated 

immediately 

after the 

arsenic 

treatment with 

a single dose 

of 0.30 kJ/m2

UV 

AsIII SA 2.5, 5.0 24 hr 5.0 

Effect on repair rate of 

UV-induced 

photodamage to genomic 

DNA measured at 2 and 

6 hr after the UV 

exposure ended: 

⇓ in repair rate of 6-4PPs 

by 48%, but no effect on 

the repair of CPDs. 

Wu et al., 

2005 

C-176 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

TK6 cells 

AsIII SA 

AsIII ATO 

0.1, 1, 10 

for both 

24 hr 

for both 

10 

10 

Induction of MN using 

flow cytometry assay: 

⇑ to 24.7% from 3.4% in 

control. 

⇑ to 17.4% from 3.4% in 

control; the text noted 

that it was sometimes 

difficult to distinguish 

between the MN and 

necrotic cell fragments 

due to toxicity at the 

dose of 10 for SA and 

ATO. 

Hornhardt 

et al., 2006 

TK6 cells 

irradiated 

with 1 or c3 

Gy of 69 

cGy/min 

gamma 

radiation at 

beginning of 

inorganic 

arsenic 

treatment 

AsIII SA 

AsIII ATO 

0.1, 1, 10 

for both 

24 hr 

for both 

1 

1 

Induction of MN using 

flow cytometry assay: 

At dose of 1: 1 Gy, 

10.2%; 3 Gy, 12.2%; 

12.2% was significantly 

higher than 9.8% in 

control. There was a 

statistically significant 

(additive) effect. 

At dose of 1: 1 Gy, 

10.0%; 3 Gy, 16.3%; 

16.3% was significantly 

higher than 9.8% in 

control. There was a 

statistically significant 

(possibly slightly 

synergistic) effect. 

Interpretation of results 

at dose of 10 was 

complicated by difficulty 

of distinguishing 

micronuclei and necrotic 

cell fragments. 

Responses were 

extremely different for 

the 2 arsenicals at dose 

of 3 Gy: 30.2% for SA 

and only 15.9% for 

ATO. 

Hornhardt 

et al., 2006 

Cytotoxicity 

NHEK cells 

AsIII SA 

AsV, 

MMAV, 

DMAV

0.001, 0.005, 0.01, 

0.05, 0.1, 0.5, 1, 5, 

10for all 

24 hr 

24hr 

0.005 

0.5 

Extent of viability 

determined by neutral 

red assay; viability was 

significantly reduced. 

Vega et al., 

2001 

C-177 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HOS cells 

AG06 cells 

W138 cells 

AsIII SA, 

AsV

IC50 

determinations 

100 hr for all — 

Extent of viability 

determined by neutral 

red assay: 

IC50s: 3.5 for AsIII, 11 for 

AsV. 

IC50s: 1.1 for AsIII, 16 for 

AsV. 

IC50s: 8.8 for AsIII, 30 for 

AsV. 

Hu et al., 

1998 

WI38 cells AsIII SA 0.25, 0.5, 1, 2 7 days 0.25 Clonal survival 

determined by crystal 

violet assay: 

LD50: ∼1.85. 

Vogt and 

Rossman, 

2001 

HaCaT cells AsIII SA 0.5, 1.0 20 passages 0.5 ⇑ resistance to 

cytotoxicity caused by 

exposure to 

concentrations of AsIII of 

1–16 μM for 72 hr. 

Chien et 

al., 2004 

HepG2 cells 

Dimethylarsinate, 

the usual 

form of 

DMAV in 

this table 

ThioDMAV

(i.e., 

Thiodimethylarsinate) 

0.01, 0.1, 0.5, 1, 5, 

10, 50 mM 

for both 

48 hr 

for both 

0.5 mM 

0.1 mM 

Cell survival was 

determined by WST-8 

assay: 

LC50s: regular DMA, 

∼0.2 mM; 

Thio-DMA, ∼0.02 mM. 

At 0.1 mM, regular 

DMA showed no 

cytotoxicity, but thioDMA resulted in only 

22% cell survival. 

Raml et 

al., 2007 

17 human 

cancer cell 

lines: 

4 bladder cell 

lines, 

2 lung cell 

lines, 

2 liver cell 

lines, 

1 leukemia 

cell line, 

and various 

others 

AsIII

ATO 

IC50 

determinations 

96 hr — 

Viability determined by 

sulphorhodamine B 

method: 

Bladder: IC50s: 0.34, 

0.47, 0.93, 1.38. 

Lung: : IC50s: 3.27, 4.17. 

Liver: IC50s: 5.17, 7.17. 

Leukemia: IC50s: 0.64. 

All 17 lines: LC50 range 

was 0.34–7.17. There 

was a strong positive 

correlation between GSH 

content of cells and 

magnitude of IC50: 

Yang et 

al., 1999 

C-178 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

4 of above 17 

human cancer 

cell lines with 

high levels of 

GSH 

AsIII ATO IC50 

determinations 

96 hr — 

Viability determined by 

sulphorhodamine B 

method: 

10 μM BSO, which 

depletes cellular GSH, 

was incubated with cells 

for 4 days, causing them 

all to become very 

sensitive to arsenic, as 

follows: 

IC50s without BSO: 0.47, 

2.59, 2.08, 9.89. 

IC50s with BSO: 0.19, 

0.14, 0.40, 0.20, 

respectively. 

Yang et 

al., 1999 

Hepa-1 cells 

(mouse 

hepatoma) 

AsIII SA 2, 5, 10, 25, 50 

12 hr 

24 hr 

None 

10 

Viability determined by 

LDH release method 

Maier et 

al., 2000 

NHEK cells AsIII SA IC50

determinations 

72 hr — 

Extent of viability 

determined by neutral 

red assay: 

IC50: 10.8 

Snow et 

al., 1999 

AG06 cells AsIII SA 0.1, 0.3, 1, 3 48 hr 3 

3 

0.3 

0.1 

Extent of viability 

determined by neutral 

red assay: 

Values below at 3: 

~90% of cells viable if 

no pretreatment (pt) to 

change GSH level. 

~85% of cells viable if 

NAC pt to ⇑ GSH level. 

~20% of cells viable if 

BSO pt to ⇓ GSH level. 

~20% of cells viable if 

CHE pt to ⇓ GSH level. 

Snow et 

al., 1999 

Humanhamster 

hybrid AL

cells 

AsIII SA 0.8, 3.8, 7.7, 15.4 24 hr 3.8 No. of colonies counted 

to determine surviving 

fraction: LC50 = about 

7.7. 

(Addition of BSO, which 

suppresses GSH 

markedly, increased 

cytotoxicity.) 

Liu et al., 

2001 

Primary 

cultures of rat 

cerebellar 

neurons 

AsIII SA 

DMAV

5, 10, 15 

1, 5, 30 mM 

12 hr 

48 hr 

5 

5 mM 

Viability determined 

using MTT metabolism 

assay. 

Namgung 

and Xia, 

2001 

C-179 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Chang human 

hepatocytes 

AsIII SA, 

AsV, 

MMAIII, 

MMAV, 

DMAV

LC50 

determinations 

24 hr — 

LC50s using LDH 

leakage assay in 

phosphate media: 

AsIII: 68.0. 

AsV: 1,628. 

MMAIII: 6.0. 

MMAV: 8,235. 

DMAV: 9,125. 

Petrick et 

al., 2000 

Chang human 

hepatocytes 

AsIII SA, 

AsV, 

MMAIII, 

MMAV, 

DMAV

LC50 

determinations 

24 hr — 

LC50s using K+

 leakage 

assay in phosphate 

media: 

AsIII: 19.8. 

AsV: 1,006. 

MMAIII: 6.3. 

MMAV: 9,283. 

DMAV: 4,109. 

Petrick et 

al., 2000 

Chang human 

hepatocytes 

AsIII SA, 

AsV, 

MMAIII, 

MMAV, 

DMAV

LC50 

determinations 

24 hr — 

LC50s using the XTT 

assay in phosphate 

media: 

AsIII: 164. 

AsV: 3,050. 

MMAIII: 13.6. 

MMAV: 42,000. 

DMAV: 91,440. 

Petrick et 

al., 2000 

Raji cells 

(human Blymphocytes) 

AsIII SA 

MMAIII

DMAIII

0.2, 1, 10, 20, 40, 

100 for all 

4 hr 

4hr 

2 hr 

10 

40 

10 

Extent of viability 

determined by trypan 

blue assay: 

Viabilities at maximum 

dose for each: 

AsIII: ∼85%. 

MMAIII: ∼85%. 

DMAIII: 60%. 

Gómez et 

al., 

2005 

Jurkat cells 

AsIII SA 

MMAIII

DMAIII

0.2, 1, 10, 20, 40, 

100 for all 4 hr 

4hr 

2 hr 

40 

0.2 

10 

Extent of viability 

determined by trypan 

blue assay: 

Viabilities at maximum 

dose for each: 

AsIII: ∼95%. 

MMAIII: ∼52%. 

DMAIII: ∼58%. 

Gómez et 

al., 2005 

A549 cells 

AsIII SA 

AsV

DMAV

0.016, 0.08, 0.4, 

2.0, 10 

30, 100, 300 

2, 20, 200, 2000 

7 days for all 

0.016 

30 

None 

Colony-forming 

efficiency assay with 

Giemsa staining: 

LC50s: AsIII, ∼0.08; AsV, 

∼100 . 

Mass and 

Wang, 

1997 

C-180 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

CHO K1 cells AsIII SA 10 4 hr None 

Clonogenic survival 

assay for cytotoxicity: 

12-hr pretreatment with 

BSO depletes GSH; with 

BSO at 50 and 400 μM, 

survival was 9% and 1%, 

respectively; other 

experiments showed that 

an increase in GSH 

markedly reduced the 

cytotoxicity of an AsIII

treatment following UV 

irradiation. 

Huang et 

al., 1993 

CHO cells: 

Wild-type 

V 850 

R 120 

AsIII SA 

for all 

5, 10, 15, 20, 30, 

50, 75, 100 for 

most 

48 hr for all 5 

20 

10 (lowest 

for it) 

Comparative inhibition 

of cell growth was based 

on numbers of cells 

present compared to 

control: 

V 850 cells were adapted 

to 850 μM H2O2 over 

about 4 months of 

exposures to increasing 

concentrations; R 120 

cells had then been 

cultured 4 months 

without exposure to 

H2O2. IC50 values: Wildtype, 17.2; V 850, 62.45; 

R 120, 26.6. Results 

after pretreatment with 

BSO suggest that 

intracellular thiol levels 

(GSH mainly) may 

account for the arsenic 

resistance seen in V 850 

cells. 

Cantoni et 

al., 1994 

CHO K1 cells AsIII SA 20, 40, 80 4 hr 20 Colony formation assay Wang et 

al., 1996 

CHO cell 

lines: 

K1 (parental 

to the 

following 

line) 

XRS-5 (X-ray 

and H2O2 

sensitive) 

AsIII SA 10, 20, 40 for both 4 hr 

40 

20 

Clonogenic survival with 

crystal violet staining: 

ID50 s: line K1, 37.8; 

line XRS-5, 17.0; the 

much less responsive K1 

cells have 6 times as 

much catalase activity as 

XRS-5 cells; both lines 

are similar in arsenic 

uptake and release, in 

GSH levels, and in GST 

activity. 

Wang and 

Huang, 

1994 

C-181 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

CHO cell 

lines: 

K1 (parental 

to the 

following 

lines) 

XRS-6 (X-ray 

sensitive) 

XRS-5 (X-ray 

and H2O2 

sensitive) 

AsIII SA 

20, 40, 80, 160 

20, 40, 80, 160 

20, 40, 80, 160 

4 hr 

160 

80 

20 

Inhibition of cell growth: 

ID50 values were: K1, 

235; XRS-6, 108; XRS5, 33. 

K1 cells have 5.8 times 

as much catalase activity 

and 5.4 times as much 

GPx activity as XRS-5 

cells. K1 cells have 3.7 

times as much catalase 

activity and 2.1 times as 

much GPx activity as 

XRS-5 cells. The cells 

with intermediate 

amounts have an 

intermediate response. 

Wang et 

al., 1997 

CHO-9 cells 

AsIII SA 

AsV

MMAIII

MMAV

DMAIII

DMAV

TMAVO 

0.1, 1, 10, 100, 

500 

for all 

1 hr 

for all 

1 

1 

500 

100 

0.1 

500 

None 

Extent of viability 

determined by trypan 

blue assay: 

DMAIII was by far the 

most cytotoxic at all 

concentrations tested, 

with the percentages of 

living cells at 1, 10, and 

100 being approximately 

45, 41, and 0%, 

respectively. 

Dopp et 

al., 2004 

BFTC905 

cells and 

NTUB1 cells 

AsIII SA 

AsV

MMAIII

MMAV

DMAIII

DMAV

IC50

determinations 

7 days — 

Clonogenic survival in a 

colony-forming assay, 

IC50 values in BFTC905 

and NTUB1 cells, 

respectively: 

0.13, 0.16. 

9.25, 9.00. 

0.13, 0.15. 

3.04, 2.64. 

0.52, 0.58. 

0.38, 0.63. 

Wang et 

al., 2007 

CHO K1 cells AsIII SA 20 6 hr 20 Colony-forming assay: 

this concentration caused 

 ~32 % survival; 

squalene at up to 160 μM 

had no effect on 

cytotoxicity. 

Fan et al., 

1996 

C-182 DRAFT—DO NOT CITE OR QUOTE
LOECa Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

CHO cells 

treated with 

MMS before 

or after 

inorganic 

arsenic 

treatment 

AsIII SA 

5, 10, as 

pretreatments 

5, 10, as posttreatments 

24 hr 

24 hr 

None 

5 

Colony-forming assay: 

No change from MMS 

alone. 

⇑ in cytotoxicity 

compared to MMS alone, 

synergistic interaction 

with even less survival at 

10. 

Lee et al., 

1986 

CHO K1 cells 

exposed to 

1.5 or 2.5 

J/m2

 of UV 

AsIII SA 10 24 hr 10 

Colony-forming assay: 

Synergistic ⇑ in 

cytotoxicity because of 

the inorganic arsenic 

post-treatment. 

Yang et 

al., 1992 

C-33A cells 

HeLa cells 

Jurkat cells 

LCL-EBV 

cells 

AsIII SA 

for all 

0.1, 1, 10, 25, 50 

for all 

24 hr 

10 

50 

0.1 

10 

Cell viability determined 

by Trypan blue 

exclusion: 

~35% viability at 50. 

~75% viability at 50. 

~55% viability at 50. 

~60% viability at 50. 

Salazar et 

al., 1997 

Jurkat cells 

and human 

lymphocytes 

AsIII SA 0.1, 1, 10, 25, 50 

for both 

24 hr 

for both 

0.1 

 for both 

Cell viability determined 

by Trypan blue 

exclusion: 

When both of these cell 

types were transfected 

with mutant p53 genes 

(by electroporation) there 

was substantially 

increased cytotoxicity. 

This ⇑ was already 

apparent at a dose of 0.1 

(i.e., the LOEC) in the 1 

p53 mutation tested in 

Jurkat cells and in 1 of 2 

p53 mutations tested in 

PHA-stimulated 

lymphocytes. 

Salazar et 

al., 1997 

Mouse 

291.03C 

keratinocytes 

AsIII SA 0.05, 0.1, 0.5, 1, 5 7 days 0.5 

Cytotoxicity based on 

colony survival, using 

crystal violet staining: 

LC50 = 0.9; almost all 

dead at dose of 5. 

Wu et al., 

2005 

C-183 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Chinese 

hamster V79 

cells 

AsIII SA 

DMAV

1, 2, 5, 10 

∼0.8, 1, 2, 5, 10 

mM 

24 hrs 

for both 

1 

2 mM 

Cytotoxicity based on 

number of viable cells 

compared to control: 

LC50s: AsIII, ∼5.5; DMAV: 

∼3.5 mM. 

Ochi et al., 

1999b 

A2780 cells 

H460 cells 

MCF-7 cells 

AsIII ATO 

for all 

IC50 

determinations 72 hr — 

Cell survival was 

determined using the 

MTT assay: 

IC50 values: A2780, 

2.80; H460, 14.60; 

MCF-7, 3.00. 

Ling et al., 

2002 

BALB/c 3T3 

cells 

(derived from 

mice) 

AsIII SA 

AsV

MMAV

DMAV

TMAV

IC50 

determinations 18 hr — 

Cell survival was 

determined using the 

MTT assay: 

IC50 values: AsIII SA, 

16.9; AsV, 64; MMAV, 

14.7 mM; DMAV, 4.35 

mM; 

TMAV, >74 mM. 

Depletion of GSH in 

cells by co-treatment 

with 0.2 mM BSO 

markedly reduced the 

cytotoxicity of DMAV

even though it markedly 

increased the 

cytotoxicity of the other 

4 compounds. 

Ochi et al., 

1994 

G12 cells 

AsIII SA 

MMAIIIO 

DMAIIII 

0.05, 0.1, 0.5, 1, 

2.5, 5, 10 

0.2, 0.4, 0.6, 0.8, 1 

0.1, 0.2, 0.3, 0.4 

72 hr 

1 

0.2 

0.1 

Cell survival was 

determined using the 

clonal survival assay: 

LC50 values: AsIII SA, 

∼8; MMAIIIO, 0.51; 

DMAIIII, 0.15. 

The 2 methylated forms 

were also tested at 4 and 

24 hr and showed 

cytotoxicity at both; for 

MMAIIIO, cytotoxicity 

was >50% at both times 

at highest dose. 

Klein et 

al., 2007 

U-2OS cells AsIII SA 0.01, 0.05, 0.1, 

0.25, 0.5, 1, 2.5 

10 days 0.05 Cell survival was 

determined using the 

clonal survival assay: 

LC50 = 0.68; 100% cell 

killing at 2.5. 

Komissaro

va et al., 

2005 

C-184 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

U-2OS cells AsIII SA 

for all 

LC50 

determinations 

24 hr 

48 hr 

72 hr 

— 

— 

— 

Cell survival was 

determined using the 

clonal survival treat-andplate (CSTP), neutral red 

(NR), and MTT assays, 

for the different 

durations: 

LC50: CSTP, 1.1; MTT, 

3.8; NR, 4.8. 

LC50: CSTP, 0.9; MTT, 

0.99; NR, 1.05. 

LC50: CSTP, 0.8; MTT, 

0.8; NR, 0.84. 

Komissaro

va et al., 

2005 

U118MG 

cells 

AsIII ATO 

1, 5, 10, 25, 50 24 hr 5 

Cell survival was 

determined using the 

MTT assay: slightly > 

50% survival at dose of 

5; co-treatment with 

lipoic acid blocked 

cytotoxicity. Other tests 

showed no ⇑ in either 

apoptotic cell death or 

intracellular peroxide 

levels; cell death was 

shown to be autophagic. 

Cheng et 

al., 2007 

Undifferentiat

ed PC12 cells 

AsIII ATO 1, 10, 100, 1000 24 hr 1 

Cell survival was 

determined using the 

MTT assay: LC50 = 8. 

(At dose of 8, about 75% 

cell survival at 12 hr.) 

Effects of pretreatment 

or co-treatment with 

antioxidants on 

cytotoxicity: NAC: big 

⇓, 

 but α-Toc, GSH, 17βestradiol, or BO653: 

NSE. 

Piga et al., 

2007 

FGC4 cells 

HepG2 cells 

Rat 

hepatocytes 

AsIII SA 

for all 

50, 75, 100, 125 

25, 50, 75, 100, 

125 

2, 10, 25, 35, 45, 

55 

24 hr 

for all 

75 

50 

25 

Cell survival was 

determined by the NR 

uptake assay: 

LC50s: FGC4, ∼90; 

HepG2, ∼70; 

hepatocytes, ∼30. 

Gottschalg 

et al., 2006 

SVEC4-10 

cells 

AsIII SA 2, 4, 8, 12, 16 24 hr 4 Cytotoxicity determined 

by the MTT assay: LC50

= ∼13. 

Chao et al., 

2006a 

C-185 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HCT116 cells 

 (securin +/+) 

HCT116 cells 

(securin -/-) 

AsIII SA 

for both 

4, 8, 12, 16 

for both 

24 hr 

for both 

4 

4 

Cytotoxicity determined 

by the MTT assay: 

LC50s = securin +/+, 

∼17; securin -/-, ∼11. 

There was significantly 

more cytotoxicity in null 

mutant at doses of 8, 12 

and 16. 

Chao et al., 

2006a 

RKO cells 

(p53 wt) 

SW480 cells 

(p53 mutant) 

AsIII SA 

for both 

8, 16, 24, 32 

for both 

24 hr 

for both 

8 

8 

Cytotoxicity determined 

by the MTT assay: 

LC50s = RKO, ∼20; 

SW480, ∼27. There was 

significantly more 

cytotoxicity in 

wt p53 cell line at doses 

of 16, 24 and 32. 

Chao et al., 

2006a 

U-2OS cells 

AsIII SA 

for all 

0.1, 1, 10 24 hr 1 or 10; 

see 

explanation 

Trypan blue exclusion 

assay to identify necrotic 

cells (which take up 

stain) after additional 

periods of post-treatment 

culturing of 0, 24, or 48 

hr in arsenic-free 

medium: 

At dose of 0.1, no 

increase in necrotic cells 

at any time. At dose of 

1, necrotic cells were 

~0%, ~20%, and ~40% 

of total cells, 

respectively. At dose of 

10, necrotic cells were 

~70%, ~95%, and ~95% 

of total cells, 

respectively. Note that a 

24-hr treatment with SA 

affected the amount of 

necrosis at a dose of 1 

only if there was an 

additional 24-hr or 

longer period of 

culturing in SA-free 

medium between the end 

of the SA treatment and 

when the assay was 

done. 

Komissaro

va et al., 

2005 

C-186 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HaCaT cells 

CRL1675 

cells 

THP-1 + 

A23187 cells 

AsIII ATO 

for all 

LD10 and LD25

determinations 

for each cell line 

72 hr — 

Cytotoxicity assessed 

using fluorescein 

diacetate assay: 

LD10 = 1.9 ; LD25 = 15.2. 

LD10 = 1.0; LD25 = 1.9. 

LD10 = 1.9; LD25 = 3.8. 

GrahamEvans et 

al., 2004 

HaCaT cells 

CRL1675 

cells 

THP-1 + 

A23187 cells 

AsIII ATO 

for all 

LD10 and LD25

determinations for 

each cell line 

72 hr under 

chronic 

exposure 

conditions 

— 

Testing for cytotoxicity 

was preceded by 

exposure to 1.0 μM AsIII

ATO for at least 8 

passages to establish 

chronic-exposure 

conditions. Then, 

following exposures to 

various doses for 72 hr, 

cytotoxicity was 

assessed using 

fluorescein diacetate 

assay: 

LD10 = 2.0 ; LD25 = 4.0. 

LD10 = 0.5; LD25 = 1.3. 

LD10 = 0.5; LD25 = 5.1. 

GrahamEvans et 

al., 2004 

Alveolar 

macrophages 

(AMs) from 

CDF1 mice 

Peritoneal 

macrophages 

(PMs) from 

CDF1 mice 

AsIII SA 

AsV

MMAV

DMAV

TMAV

IC50 

determinations 

48 hr — Cell survival was 

determined using the 

AlamarBlue assay (said 

to be similar to the MTT 

assay): 

IC50 values of AM cells: 

AsIII SA, 4; AsV, 400; 

MMAV, >10 mM; DMAV, 

5 mM; TMAV, >>10 

mM. 

IC50 values of PM cells: 

AsIII SA, 5; AsV, 650; 

MMAV, >10 mM; DMAV, 

5 mM; TMAV, >>10 

mM. 

DMAV caused almost 

entirely apoptotic cell 

death, while the 

inorganic arsenicals 

caused mainly necrotic 

cell death. SOD, CAT. 

and a peptide inhibitor 

ICE inhibited the 

cytotoxicity of AsIII but 

not of DMAV. 

Sakurai et 

al., 1998 

C-187 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

RHMVE cells 

MMAV

DMAV

TMAVO 

0.25, 0.5, 1, 2.5, 5, 

10, 25, 50, 100 

mM 

for all 

24 hr 

25 mM 

1 mM 

None 

Cell survival was 

determined using a 

modified MTT assay: 

LC50s: MMAV, 33.6 mM; 

DMAV, 2.54 mM; 

TMAVO, cell number 

increased by dose of 1 

mM, reaching 135% of 

control at dose of 25 

mM. Another study 

showed LC50s: AsIII, 36; 

AsV, 220 (both μM). 

Co-treatment with NAC 

caused ⇓ in cellular 

arsenic content and 

cytotoxicity by DMAV

but not by MMAV. Cotreatment with BSO 

caused big ⇑ in 

cytotoxicity of MMAV

but slight ⇓ in 

cytotoxicity of DMAV. 

Hirano et 

al., 2004 

HLFC cells 

HLFK cells 

(Ku70 

deficient) 

AsIII SA 

for both 

5, 10, 20, 40, 80 

for both 

24 hr 

for both 

10 

for both 

Viability was determined 

by trypsin blue exclusion 

assay: 

LC5os: HLFC, 27.38; 

HLFK, 21.80; 

cytotoxicity was 

significantly greater for 

HLFK than HLFC at 

doses of 20, 40 and 80. 

Liu et al., 

2007b 

C-188 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

NB4 cells 

NB4-M-AsR2 

cells 

IM9 cells 

AsIII ATO 

for all 

0.5, 1 

2, 4 

0.5, 1 

6 days 

for all 

0.5 

4 

0.5 

Cell viability (% of 

control) for ATO alone 

and for ATO with 100 

μM Trolox, determined 

using trypan blue 

exclusion: 

At 0.5: 75% alone, 43% 

with Trolox; at 1: 30% 

alone, 3% with Trolox. 

At 2: 100% alone, ~80% 

with Trolox; at 4: ~63% 

alone, ~30% with 

Trolox. 

At 0.5: ~80% alone, 

~70% with Trolox; at 1: 

~50% alone, ~25% with 

Trolox. 

Thus, Trolox enhanced 

ATO-induced 

cytotoxicity (or growth 

inhibition) in all 3 cell 

lines. 

Diaz et al., 

2005 

MCF-7 cells, 

T47D cells, 

and 

MDA-MB231 cells 

AsIII ATO 

for all IC50 

determinations 

3 days — 

Cell viability for ATO 

without and with 100 μM 

Trolox co-treatment, 

respectively, determined 

using trypan blue 

exclusion assay: 

MCF-7: 2.07 and 1.02; 

T47D: 3.22 and 1.56; 

MDA-MB-231: 2.27 and 

0.98. 

Thus, co-treatment with 

Trolox enhanced ATO 

growth inhibition 

similarly to what was 

seen in the row above. 

Diaz et al., 

2005 

C-189 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Human 

PBMCs 

cultured in 

various ways 

AsIII ATO 1 15 days 1 Colony-forming ability 

was assessed for ATO 

alone and for cotreatment with Trolox by 

counting CFUerythrocytes, CFUgranulocytesmacrophages, and BFUerythrocytes. Biggest 

effect of ATO alone: 

62% ⇓ for CFUerythrocytes. In all 3 

cases, co-treatment with 

Trolox had little or no 

effect. 

Diaz et al., 

2005 

MDAH 2774 

cells 

AsIII ATO 1, 2, 5, 8 72 hr 1 or 2 Cytotoxicity assessed 

using trypan blue 

exclusion assay: 

uncertainty about LOEC 

exists because control 

value was not reported: 

LC50 = 5. 

Terek et 

al., 2006 

SVEC4-10 

cells 

AsIII SA 5, 10, 20, 40 24 hr 10 Cell survival was 

determined using the 

MTT assay: LC50 = ∼13. 

Hsu et al., 

2005 

1RB3AN27

cells 

AsIII SA 0.1, 0.5, 1, 5, 10 72 hr 1 Cell survival was 

determined using the 

MTT assay: there 

probably was 

cytotoxicity at dose of 1; 

statistically significant 

cytotoxicity at dose of 5; 

LC50 = ∼8; all 

experiments on ROS or 

induction of transcription 

factors were at doses of 

≤10 for ≤4 hr, and under 

those conditions, there 

was no cytotoxicity. 

Felix et al., 

2005 

BEAS-2B 

cells 

AsIII ATO 10, 20, 50 24 hr 10 Cell survival was 

determined using the 

MTT assay: LC50 = ∼15. 

Han et al., 

2005 

HT1197 cells AsIII SA 1, 5, 10, 25, 50 24 hr 10 Cell survival was 

determined using the 

trypan blue exclusion 

assay: 

LC50 = ∼35. 

Hernández

-Zavala 

 et al., 

2005 

C-190 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HL-60 cells 

U266 cells 

AsIII ATO 

for both 

1, 2, 3, 5, 10 

for both 

24 hr 

for both 

2 

1 

Cell survival was 

determined using the 

trypan blue exclusion 

assay: 

LC50s = HL-60, ∼7; 

U266, ∼2. 

Effects of modulators in 

both cell lines: 

(Cells were loaded with 

high concentrations of 

intracellular AA [icAA] 

by incubating them with 

DHA prior to inorganic 

arsenic treatments, thus 

avoiding generation of 

extracellular ROS in 

tissue culture media 

caused by direct addition 

to it of AA.) icAA 

caused big ⇓ in 

cytotoxicity of inorganic 

arsenic. GSH depletion 

by BSO treatment caused 

big ⇑ in inorganic 

arsenic-induced 

cytotoxicity. icAA 

caused big ⇓ in 

cytotoxicity caused by 

inorganic arsenic in 

GSH-depleted cells. 

Extracellular AA caused 

big ⇑ in inorganic 

arsenic-induced 

cytotoxicity, including 

after GSH depletion. 

Relatively limited data 

from a methylcellulose 

colony-forming assay in 

both cell lines (with 48-

hr inorganic arsenic 

treatment and 10-14 days 

to form colonies) and 

from cytotoxicity testing 

of RPMI-8226 cells 

supported some of the 

above conclusions. 

Effect of NAC was 

tested in HL60 cells; it 

caused big ⇓ in inorganic 

arsenic-induced 

cytotoxicity. 

Karasavva

s et al., 

2005 

C-191 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Embryonic 

mesenchymal 

cells prepared 

from CF-1 

mouse 

conceptuses at 

gestation day 

11 

AsIII SA 5.8, 11.6, 15.4, 

30.8 

2 hr 5.8 

Cell survival was 

determined using the 

MTT assay: LC50 = ∼27; 

15-min pretreatment with 

0.5% (v/v) DMSO 

completely blocked the 

inorganic arsenic effect 

at dose of 15.4, whereas 

15-min pretreatment with 

0.1% or 0.2% (v/v) 

DMSO partially blocked 

it. 

PérezPastén et 

al., 2006 

HCT15 cells 

HeLa cells 

PLC/PR/5 

cells 

Chang cells 

AsIII SA 

for all 

LC50

determinations 

24 hr — Cell survival determined 

by MTT cell 

proliferation assay: 

LC50s: HCT15, 278.33; 

HeLa, 200.33; 

PLC/PR/5, 376.66; 

Chang, 328.33. 

Othumpan

gat et al., 

2005 

K562 cells, 

AR230-s 

cells, AR230-

r cells, 

KCL22-s 

cells, KCL22-

r cells, NB4 

cells 

AsIII ATO IC50

determinations 

for all 

3 days — 

Antiproliferative activity 

as determined by MTS 

assay—some would 

interpret such results as 

cytotoxicity and present 

results as LC50s: 

IC50s: K562, 0.9; 

AR230-s, 2.6; AR230-r, 

6.9; KCL22-s, 2.6; 

KCL22-r, 2.8; NB4, 0.4. 

 A dose of 2 represents 

the upper margin of the 

clinically useful range 

for ATO. There was a 

positive correlation 

between GSH content of 

cells and resistance to 

the antiproliferative (i.e., 

cytotoxic) effect. 

Konig et 

al., 2007 

C-192 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

AR230-s 

cells, 

AR230-r 

cells, 

KCL22-s 

cells, KCL22-

r cells 

AsIII ATO 

 

1 2 days None 

Cell survival was 

determined by trypan 

blue assay: 

100 μM BSO treatment 

was shown to greatly ⇓

GSH levels in all 4 cells 

types both with and 

without inorganic arsenic 

exposure. In all 4 cell 

types, the inorganic 

arsenic + BSO treatment 

caused big to huge ⇓ in 

number of viable cells, 

whereas untreated cells 

or cells treated with 

inorganic arsenic or BSO 

showed ∼2-fold ⇑. A 

similar assay in primary 

cultures of mononuclear 

cells from 4 patients in 

blast crisis with imatinibresistant CML also 

showed maximum 

cytotoxicity for the 

combined inorganic 

arsenic + BSO treatment. 

Konig et 

al., 2007 

H1355 cells AsIII ATO 3.125, 6.25, 12.5, 

25, 50, 100, 200 

24 hr 6.25 Cell survival was 

determined using the 

MTT assay: 

Cytotoxicity increased 

with dose, with ∼57% 

cell survival at dose of 

200. 

Cheng et 

al., 2006 

C-193 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

TRL 1215 

cells = X in 

this row 

TRL 1215 

cells that had 

been treated 

with 1.3 mM 

MMAV for 20 

weeks prior to 

acute arsenic 

treatments = 

Y in this row 

AsIII SA, 

AsV, 

DMAV

for both 

LC50

determinations 

for both 

48 hr 

for both 

— 

Cell survival based on 

AB assay: 

LC50s for AsIII: X, 16.3; 

Y, 74.1. 

LC50s for AsV: X, 157.1; 

Y, 2743.8. 

LC50s for DMAV: X, 

2090; Y, 6950. Thus the 

MMAV pretreatment 

caused marked resistance 

to cytotoxicity for all 3 

arsenicals. Much of this 

resistance was lost if Y 

cells were cultured for 8 

more weeks with no 

arsenic in media. The 

20-week pretreatment 

caused no cytotoxicity, 

gave the Y cells an 

arsenic content of 135.4 

± 12.0 ng/mg cellular 

protein, and did not 

induce malignant 

transformation. 

Arsenicals were not 

methylated or 

demethylated in these 

cells. 

Kojima et 

al., 2006 

C-194 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

TRL 1215 

cells = X in 

this row 

TRL 1215 

cells that had 

been treated 

with 0.7 mM 

DMAV for 20 

weeks prior to 

acute arsenic 

treatments = 

Y in this row 

AsIII SA, 

AsV, 

DMAV

for both 

LC50

determinations 

for both 

48 hr 

for both 

— 

Cell survival based on 

AB assay: 

LC50s for AsIII: X, 16.3; 

Y, 19.2. 

LC50s for AsV: X, 157.1; 

Y, 182.2. 

LC50s for DMAV: X, 

2090; Y, 4730. 

Thus the DMAV

pretreatment caused 

marked resistance to 

cytotoxicity for only the 

DMAV treatment, and the 

slight differences for the 

other 2 arsenicals were 

not statistically 

significant. When Y 

cells were cultured for 8 

more weeks with no 

arsenic in media, there 

was no change regarding 

the lack of resistance to 

AsIII, but the resistance to 

the other 2 arsenicals 

increased substantially. 

The 20-week 

pretreatment caused no 

cytotoxicity, gave the Y 

cells an arsenic content 

of 41.8 ± 2.5 ng/mg 

cellular protein, and did 

not induce malignant 

transformation. 

Arsenicals were not 

methylated or 

demethylated in these 

cells. 

Kojima et 

al., 2006 

C-195 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

TRL 1215 

cells = X in 

this row 

TRL 1215 

cells that had 

been treated 

with 10.0 mM 

TMAVO for 

20 weeks 

prior to acute 

arsenic 

treatments = 

Y in this row 

AsIII SA, 

AsV, 

DMAV

for both 

LC50

determinations 

for both 

48 hr 

for both 

— 

Cell survival based on 

AB assay: 

LC50s for AsIII: X, 16.3; 

Y, 54.8. 

LC50s for AsV: X, 157.1; 

Y, 684.1. 

LC50s for DMAV: X, 

2090; Y, 4500. Thus the 

TMAVO pretreatment 

caused marked resistance 

to cytotoxicity for all 3 

arsenicals. Much of this 

resistance was lost 

regarding DMAV, and all 

of it was lost regarding 

the other 2 arsenicals, if 

Y cells were cultured for 

8 more weeks with no 

arsenic in media. The 

20-week pretreatment 

caused no cytotoxicity, 

gave the Y cells an 

arsenic content of 543.8 

± 12.0 ng/mg cellular 

protein, and did not 

induce malignant 

transformation. 

Arsenicals were not 

methylated or 

demethylated in these 

cells. 

Kojima et 

al., 2006 

C-196 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

NB4 cells 

AsIII SA 

AsIII ATO 

MMAIII

DMAIII

1, 2, 3, 4 

1, 2, 3, 4 

0.25, 0.5, 1, 2 

2, 4, 6, 8 

72 hr 

1 

1 

0.25 

4 

Cell survival was 

determined using the 

MTT assay: 

LC50s: AsIII SA, ∼3.4; 

AsIII ATO, ∼2.2; MMAIII, 

∼1.2; DMAIII, ∼5.8. 

Co-treatment (CoTr) 

with 3000 μM DTT 

markedly decreased 

cytotoxicity of all 

arsenicals: Maximum 

cytotoxicities with 3000 

μM DTT CoTr: 

AsIII SA, ∼17%; AsIII

ATO, ∼12%; MMAIII, 

∼25%; DMAIII, ∼12%. 

CoTr with 100 μM DTT 

markedly increased 

cytotoxicity of all 

arsenicals: 

LC50s with 100 μM DTT 

CoTr: AsIII SA, ∼2.2; 

AsIII ATO, ∼1.0; 

MMAIII, ∼0.28; DMAIII, 

∼4.0. 

Jan et al., 

2006 

293 cells 

AsIII ATO 0.5, 1, 2, 3, 4 12 days 1 

Cell survival was 

determined by colonyforming assay (% of cells 

forming colonies): ∼73% 

at dose of 4; LC25 = 

∼3.6. 

Co-treatment with 200 

μM DMSA increased 

survival: ∼87% at dose 

of 4. 

Co-treatment with 20 μM 

DMSA decreased 

survival: ∼61% at dose 

of 4; 

LC25 = ∼1.6. Cotreatment with 100 μM 

DMPS increased 

survival: ∼86% at dose 

of 4. Co-treatment with 

10 μM DMPS decreased 

survival: ∼50% at dose 

of 4; LC25 = ∼1.2. 

Jan et al., 

2006 

C-197 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

SV-HUC-1 

cells 

AsIII ATO 0.5, 1, 2, 3, 4 12 days 0.5 

Cell survival was 

determined by colonyforming assay (% of cells 

forming colonies): ∼62% 

at dose of 4; LC25 = 

∼2.2. Co-treatment with 

200 μM DMSA 

increased survival: ∼73% 

at dose of 4; LC25 = 

∼3.5. Co-treatment with 

20 μM DMSA decreased 

survival: ∼43% at dose 

of 4; LC25 = ∼1.4. Cotreatment with 100 μM 

DMPS increased 

survival: ∼79% at dose 

of 4. Co-treatment with 

10 μM DMPS decreased 

survival: ∼47% at dose 

of 4; LC25 = ∼1.2 

Jan et al., 

2006 

HeLa cells AsIII SA 10, 100 24 hr 10 Cell survival determined 

using a LIVE/DEAD 

viability/cytotoxicity kit: 

LC50: ~95. 

Hansen et 

al., 2006 

Primary rat 

hepatocytes 

AsIII SA 2.5, 5, 7.5, 10, 15, 

20, 25, 30, 40, 50 

24 hr 7.5 Cell survival was 

determined using the 

MTT assay: LC50 = ∼18. 

Hasgekar 

et al., 2006 

A431 cells AsIII ATO 1.25, 2.5, 5, 10, 20 

for both 

24 hr 

48 hr 

2.5 

1.25 

Cell survival was 

determined using the 

MTT assay: 

At 24 hr: LC50 = ∼20. 

At 48 hr: LC50 = ∼3. 

Huang et 

al., 2006 

RAW264.7 

cells 

AsIII SA 2.5, 5, 10, 25 24 hr 2.5 Cell survival based on 

neutral red uptake assay: 

LC50 = ∼13. 

Szymczyk 

et al., 2006 

C-198 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

NIH 3T3 cells AsIII SA 5, 10, 20, 50, 100, 

200 

6 hr 20 for ⇓ Cell viability assayed 

using CellTiter-Glo 

assay: possibly slight ⇑

at 5 and 10; 

⇓ at 20, LC50 = ∼90. 

Pre-induction of HSP by 

conditioning heat shock 

(2 hr at 42°C on prior 

day) or by constitutive 

expression of HSP70 

markedly reduced the 

cytotoxicity, as follows: 

with heat: LOEC = 100 

and ∼80% viability at 

dose of 200, with 

constitutive expression: 

LOEC = 50 and ∼70% 

viability at dose of 200. 

Khalil et 

al., 2006 

NHEK cells AsIII SA 0.2, 0.4, 0.8 1, 2, 3, 4 days 

0.2 for ⇑

on all 

days 

Cell survival was 

determined using the NR 

uptake assay: 

⇑ to ~1.1-1.4x at doses 

of 0.2 and 0.4 on all 

days; point estimates at 

dose of 0.8 were always 

higher than control, but 

the ⇑ was always a NSE. 

Hwang et 

al., 2006 

BAEC cells 

AsIII SA 

1, 5, 10 24 hr 

48 hr 

5 

1 

Cell survival was 

determined using a 

variation of the MTT 

assay: LC50s: ~7.5 at 24 

hr, ~5.0 at 48 hr. Unlike 

co-treatment with ZnII

, 

FeII, or CuII

, 

only co-treatment with 

MnII increased inorganic 

arsenic toxicity at 

concentrations at which 

it (the metal) did not 

cause cytotoxicity alone. 

Bunderson 

et al., 2006 

H22 cells 

BAEC cells 

AsIII ATO 

for both 0.5, 1, 2, 4 

for both 

24 hr, 48 hr 

24 hr, 48 hr 

1, 0.5 

2, 1 

Cell survival (also called 

the proliferation index) 

was determined using the 

MTT assay: 

LC50s for H22: ~2.0 at 

24 hr, ~1.2 at 48 hr. 

LC50s for BAEC: ~4.5 at 

24 hr, ~2 at 48 hr 

Liu et al., 

2006e 

C-199 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HEK 293 

cells 

HEK 293 

cells 

transfected 

with OATP-C 

AsIII SA 

AsV

MMAV

DMAV

LC50

determinations 

72 hr 

Cell survival was determined using the 

MTT assay: 

LC50s without and with OATP-C, 

respectively: AsIII: 10.9, 5.6; AsV: 

98.1, 53; 

MMAV: 4319.3, 4211.6 (this 

comparison: NSE); 

DMAV: 994.1, 899.3 (this comparison: 

NSE). 

The OATP-C transfected cells 

accumulated 43% more AsIII and 34% 

more AsV than the non-transfected 

cells while they did not accumulate 

more of the methylated arsenicals. 

Co-treatment of the AsIII- or AsVtreated cells with rifampin or 

taurocholic acid eliminated the 

difference between the two cell types. 

 OATP-C can transport inorganic 

arsenic in a (GSH)-dependent manner 

but this may not be the major pathway 

for arsenic transport. 

Lu et al., 

2006 

U937 cells AsIII SA 

for all 

0.5, 1, 2.5, 5, 10, 

20 

for all 

24 hr 

48 hr 

72 hr 

20 

10 

10 

Cell survival was 

determined using the PIexclusion assay: 

At 24 hr, ~74% survival 

at dose of 20. 

At 48 hr, ~62% survival 

at dose of 20. 

At 72 hr, ~40% survival 

at dose of 20, LC50: 

~17.5. 

McCollum 

et al., 2005 

TRL 1215 

cells 

TRL 1215 

cells 

pretreated 

with 50 μM 

BSO for 24 hr 

to deplete 

GSH levels 

and then cotreated with 

50 μM BSO 

MMAV 

for both 

1.25, 2.5, 5, 10 

mM 

for both 

48 hr 

for both 

10 mM 

2.5 mM 

Cell survival was 

determined using the AB 

assay: 

Without BSO: ~80% cell 

survival at dose of 10 

mM; at 5 mM, survival 

may 

have been higher than 

that of control 

LC50 with BSO: 3.2 mM. 

Similar results were 

obtained using CV assay. 

Sakurai et 

al., 2005a 

C-200 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Gclm+/+ MEF 

cells 

Gclm+/- MEF 

cells 

Gclm-/- MEF 

cells, from 

GCLM 

knockout 

mice 

AsIII SA 

for all 

4, 8, 16, 32, 64 

for all 

8 hr 

for all 

16 or 64 

16 or 64 

4 

Cell survival was 

determined using the 

MTT assay: 

It was unclear which of 

the first two genotypes 

had the LOEC of 16; one 

had an LOEC of 64, and 

the LOEC for the other 

one was 16; 

LC50s: +/+, 86; +/-, 86; -

/-, 11; 

pretreatment with tBHQ 

protected Gclm-/- and 

Gclm+/- MEF cells from 

inorganic arsenicinduced cytotoxicity in a 

dose- and timedependent manner. 

Kann et 

al., 2005b 

HeLa cells 

U937 cells 

Primary 

human skin 

fibroblasts 

AsIII ATO 

for all 2 for all 3 days 

2 

2 

None 

Cell survival was 

determined using the 

MTS assay: 

∼77% survival in HeLa 

and ∼85% survival in 

U937; no hint of 

cytotoxicity in 

fibroblasts. Cotreatment with 10 μM 

emodin apparently 

sensitized HeLa and 

U937 cells (but not 

fibroblasts) to 

cytotoxicity. The 

addition of 1.5 mM NAC 

to the co-treatment of 

HeLa cells with 10 μM 

emodin and 2 μM 

inorganic arsenic 

eliminated all 

cytotoxicity; effect of 

NAC was not tested in 

U937 cells. Emodin was 

used because it has a 

semiquinone structure 

that is likely to increase 

the generation of 

intracellular ROS. 

Yi et al., 

2004 

C-201 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

MCF-7 cells 

AsIII ATO 

0.5, 1, 2, 4, 8, 16 

24 hr, 48 hr, or 

96 hr 

2 at 24 hr; 

1 at 48 

and 

96 hr 

Cell survival was 

determined using the 

MTT assay: LC50s at 24, 

48, and 96 hr were 8.6, 

3.3, and 1.86, 

respectively. Apoptosis 

was shown to be the 

mechanism of cell death 

after treatment with a 

dose of 5 for 3 days. 

Ye et al., 

2005 

MYP3 cells 

AsIII SA 

AsV 

MMAIII

DMAIII

DMAV

TMAVO 

2, 3 

35, 40 

1, 1.5 

0.6, 1 

0.6 mM, 1 mM 

15 mM, 20 mM 

7 days 

for all 

2 

35 

1 

0.6 

0.6 mM 

15 mM 

Cell survival was 

determined using the 

MTT assay: 

∼33% at 2, ∼9% at 3. 

∼37% at 35, ∼28% at 40. 

∼60% at 1, ∼7% at 1.5. 

∼28% at 0.6, ∼10% at 1. 

∼45% at 0.6 mM, ∼28% 

at 1 mM. 

∼28% at 15 mM, ∼18% 

at 20 mM. 

Co-treatments with 

antioxidants that work by 

different mechanisms 

yielded the following 

results: melatonin 

slightly inhibited 

cytotoxicity of AsIII. 

NAC inhibited 

cytotoxicity of MMAIII, 

DMAIII, DMAV and 

TMAVO. Vitamin C 

inhibited cytotoxicity of 

AsIII, AsV, MMAIII and 

DMAIII. Tiron and 

Trolox did not affect 

cytotoxicity of any 

arsenical. 

Wei et al., 

2005 

C-202 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Primary 

keratinocytes 

(in third 

passage) 

obtained from 

foreskins of 

adults 

AsIII SA 0.001, 0.01, 0.1, 1, 

5, 10, 100, 1000 

24 hr 

48 hr 

72 hr 

5 for ⇓

1 ⇑; 5 ⇓ 

0.1 ⇑; 

5 ⇓ 

Cell survival was 

determined using the 

XTT assay: 

⇑ in viability 

(proliferation) to 1.18x 

and 1.32x at dose of 1 at 

48 and 72 hr, 

respectively. 

LC50s at 24, 48, and 72 

hr were ∼160, ∼10, and 

∼4.2, respectively. 

Liao et al., 

2004 

Huh7 cells AsIII SA 0.5, 1, 3, 5, 10, 20 24 hr 

1 for ⇑

20 for ⇓

Cell survival was 

determined using the 

MTT assay: ⇑ to ~1.1x at 

doses of 1 and 3; ⇓ to 

58% at dose of 20. In 

co-treatments with 10nM 

TCDD, inorganic arsenic 

doses of 5 and 10 caused 

0% and 10% 

cytotoxicity, 

respectively. 

Chao et al., 

2006b 

CL3 cells, 

synchronous 

at G1 

CL3 cells, 

asynchronous 

(asyn) 

CL3 cells, 

synchronous 

at S 

CL3 cells, 

synchronous 

at G2/M 

AsIII SA 

for all 

50, 100 

for all 

3 hr 

for all 

— 

Cell survival was 

determined using a 

colony-forming assay: 

% survival at dose of 50: 

G1, 45%; asyn, 35%; 

S, 29%; G2/M, 17%. 

Survival at dose of 50 in 

G1 cells was cut from 

45% to 25% to 30% by 

co-treatment with 

PD98059 or U0126, 

which are these 2 

structurally dissimilar 

inhibitors of MEK1/2. 

Li et al., 

2006a 

C-203 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Human 

neuroblastom

a cell lines: 

IMR-32 

SK-N-DZ 

SK- N-BE(2)

SK-N-AS 

SH-SY5Y

All 4 lines ± 

co-treatment 

with 25 μM 

DCHA 

AsIII ATO 1 48 hr 

- or + 

DCHA

None, 1 

None, 1 

1, 1 

1,1 

1,1 

Cell survival (% of 

control) was determined 

using the MTT assay: 

inorganic arsenic alone, 

DCHA alone, (inorganic 

arsenic + DCHA)

NSE, NSE, 35%. 

NSE, NSE, 45%. 

73%, NSE, 41%. 

56%, NSE, 39%. 

61%, NSE, 40%. 

co-treatment of 

(inorganic arsenic 

+DCHA) with vitamin E 

blocked much of the 

cytotoxicity in line IMR32. 

Lindskog 

et al., 2006 

HaCaT cells 

AsIII SA 

AsV

MMAIII

DMAIII

0.5, 1, 1.5, 2.5, 4, 

6, 7, 8, 10, 12, 13, 

14, 16, 18, 20, 22 

10, 20, 30, 40, 50, 

60, 80, 100, 120, 

160, 200, 240, 

280, 320, 360 

0.1, 0.5, 1, 2, 2.5, 

3, 3.5, 4, 4.5, 5, 

5.5, 6, 6.5, 8, 10 

0.1, 0.5, 1, 2, 3, 4, 

5, 6, 7, 8, 9, 10, 11 

24 hr 

for all 

0.5 for ⇑

12 for ⇓

10 for ⇑

100 for ⇓

0.1 for ⇑

2.5 for ⇓

None for 

⇑

3 for ⇓

Cell survival was 

determined using the 

MTT assay, with a 

proliferative effect being 

seen at lower doses: 

Peak of 141% at dose of 

1; first point estimate 

below 100% at dose of 8; 

about 50% cytotoxicity 

at 22. 

Peak of 145% at dose of 

10; first point estimate 

below 100% at dose of 

80; about 50% 

cytotoxicity at 320. 

Peak of 160% at dose of 

1; first point estimate 

below 100% at dose of 

2.5; about 50% 

cytotoxicity at 4.5. 

About 60% cytotoxicity 

at 11. 

Ganyc et 

al., 2007 

C-204 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Mouse 

lymphoma 

cells 

(L5178Y/Tk+/-

–3.7.2C cells) 

AsIII SA 

AsV

MMAV

DMAV

2.3, 3.1, 4.6, 6.2, 

7.7, 9.2, 10.8, 

11.5, 13.1, 13.9, 

14.6, 15.4 

6.1, 15.2, 30.3, 

45.5, 48.5, 54.6, 

60.6, 66.7, 69.7, 

72.8, 78.8, 84.9 

12.3, 15.4, 18.5, 

21.6, 24.7, 27.8 

mM 

12.5, 18.8, 25.0, 

31.3, 37.5, 43.8, 

50.0, 56.3, 62.5 

mM 

4 hr 

for all 

4.6 

15.2 

12.3 mM 

18.8 mM 

Cell survival, as percent 

of relative total growth 

compared to the vehicle 

control: 

Estimates of LC50s: 

AsIII SA, ∼7.3 μM; AsV, 

∼50.3 μM; 

MMAV, ∼16.1 mM; 

DMAV, ∼38.8 mM. 

Moore et 

al., 1997a 

V79 cells 

treated with 

MNU 

AsIII SA 

10 

5 

3 hr 

24 hr 

10 

5 

Cell survival, percent of 

control: both inorganic 

arsenic treatments caused 

4% or less cytotoxicity; 

however, as posttreatments they both 

considerably increased 

the cytotoxicity caused 

by the MNU treatments. 

Li and 

Rossman, 

1989a 

V79 cells 

exposed to 

UVA, UVB, 

or UVC over 

a wide range 

of doses 

AsIII SA 10 3 hr 10 

Cell survival, percent of 

control: 

The inorganic arsenic 

treatments caused 8% or 

less cytotoxicity; 

however, as posttreatments they increased 

the cytotoxicity caused 

by the UV treatments. 

Li and 

Rossman, 

1991 

Humanhamster 

hybrid AL

cells 

AsIII SA 3.8, 7.7, 15.4 1 day or 5 days 3.8 Colony-forming assay; 

~55% survival with 1-

day treatment at 7.7. 

Hei et al., 

1998 

C-205 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

1T1 cells 

MYP3 cells 

AsIII SA 

AsV

MMAIIII2

MMAV

DMAIIII 

DMAV

TMAVO 

LC50 

determinations for 

all 

7 days — 

LC50s based on trypan 

blue assay for viability: 

AsIII SA: 4.8 in 1T1; 0.4 

in MYP3. 

AsV: 31.3 in 1T1; 5.3 in 

MYP3. 

MMAIIII2: 1.0 in 1T1; 0.8 

in MYP3. 

MMAV: 1.7 mM in both 

lines. 

DMAIIII: 0.8 in 1T1; 0.5 

in MYP3. 

DMAV: 0.50 mM in 1T1; 

1.1 mM in MYP3. 

TMAVO: 1.7 mM in 

1T1; 4.5 mM in MYP3. 

Cohen et 

al., 2002 

AG06 cells AsIII SA 0.2, 4, 20 24 hr 

pretreatment 

0.2 for ⇑

4 for ⇓

Extent of viability 

determined by NR assay: 

⇑ in viability over that 

seen for MNNG alone at 

~1–15 μM MNNG. 

⇓ in viability below that 

seen for MNNG alone at 

~15–40 μM MNNG 

(synergistic interaction). 

Snow et 

al., 1999 

Human cells: 

AG06 

(keratinocytes

) 

AG06 

(keratinocytes

) 

HaCaT 

(keratinocytes

) 

NHEK 

(keratinocytes

) 

GM847 

(fibroblasts) 

WI38 

(fibroblasts) 

AsIII SA 

MMAIII

AsIII SA 

AsIII SA 

AsIII SA 

AsIII SA

IC50 

determinations 

48 hr — 

Extent of viability 

determined by NR assay: 

IC50: 7.2. 

IC50: ∼7.5. 

IC50: 11.6. 

IC50: 12.3. 

IC50: 10.7. 

IC50: 11.2. 

Snow et 

al., 2001 

AG06 cells AsIII SA 

MMAIII

1, 5, 10, 20, 30 5 hr — 

Extent of viability 

determined by NR assay: 

~20 kills 20% of cells. 

~20 kills 50% of cells. 

Snow et 

al., 2001 

K562 cells AsIII ATO 2.5 12 hr 2.5 ~50% of cells die. Li and 

Broome, 

1999 

C-206 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Human 

kidney 

carcinoma 

cell lines: 

UOK123 

UOK109 

UOK121 

Human lung 

carcinoma 

cell line: 

A549 

AsIII SA IC50 

determinations 

7 days — 

Extent of viability 

determined by colonyformation efficiency 

assay: 

0.020. 

0.021. 

0.020. 

0.4. 

Zhong and 

Mass, 

2001 

HFW cells 

(diploid 

human 

fibroblasts) 

AsIII SA 2.5, 5, 10, 20 6 hr 2.5 

Cytotoxicity determined 

by a colony-forming 

assay; co-treatment with 

catalase (but not heatinactivated catalase) at 

100 μg/mL markedly 

reduced cytotoxicity; 

increasing GSH levels 

with ß-mercaptoethanol 

reduced cytotoxicity; 

decreasing GSH levels 

with BSO increased 

cytotoxicity. 

Lee and 

Ho, 1995 

HFW cells 

(diploid 

human 

fibroblasts) 

AsIII SA 1.25, 2.5, 5, 10 

5, 10, 20, 40, 80 

24 hr 

4 hr 

1.25 

∼10 

Cytotoxicity determined 

by a colony-forming 

assay. 

Yih and 

Lee, 1999 

V79-C13 

Chinese 

hamster cell 

line 

AsIII SA 5, 10, 20, 30, 40, 

50, 60 

24 hr 10 Cytotoxicity determined 

by a colony-forming 

assay: survival at 10 was 

76.3 ± 2.61% of control; 

IC50: ~20. 

Sciandrello 

et al., 2002 

Syrian 

hamster 

embryo cells 

AsIII SA 

AsV

∼0.7, 1.4, 2, 3, 4, 

5, 6 

∼5, 10, 20, 50, 75, 

100, 130, 160, 200 

7 days 

for all 

0.7⇑, 5⇓

10⇑, 100⇓

Cytotoxicity determined 

by measuring CFE: 

Small but reproducible ⇑

from 0.7 to about 1.5 

followed by a 

logarithmic decrease in 

CFE with a linear 

increase in dose. 

Small but reproducible ⇑

from 10 to 50 followed 

by a logarithmic 

decrease in CFE with a 

linear increase in dose. 

Barrett et 

al., 1989 

C-207 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

UROtsa cells AsIII SA 0.1, 10, 25, 50, 

100, 200 

24 hr 50 

Viability determined 

using MTT assay: IC50 = 

∼100; doses ≤10 were 

said to stimulate 

mitochondrial activity 

(i.e., the curve went up; 

the assay tests 

mitochondrial function), 

but the stimulation was 

not statistically 

significant. 

Co-treatment with BSO: 

big ⇑ in cytotoxicity, 

with IC50 = ∼15. 

Bredfeldt 

et al., 2004 

UROtsa cells MMAIII 

for all 

0.5, 1, 2, 5, 10 

for all 

24 hr 

48 or 72 hr 

5 

5 

Viability determined 

using MTT assay: 

IC50 = ∼5. 

All cells (or almost all 

cells) were dead at 

LOEC. 

Bredfeldt 

et al., 2006 

UROtsa cells 

AsIII SA 

AsV 

MMAIIIO 

MMAV

DMAIIII 

DMAV

0.1, 0.5, 1, 5 

1, 200 

0.1, 0.5, 1, 5 

1, 200 

0.1, 0.5, 1, 5 

1, 200 

24 hr 

for all 

None 

None 

5 

None 

None 

None 

Viability determined 

using MTT assay: 

With MMAIIIO: 50% 

cytotoxicity was 

estimated to result from 

dose of about 2.5, with 

about 90% cytotoxicity 

at dose of 5. 

Drobná et 

al., 2002 

BALB/c 3T3 

A31-1-1 cells 

(derived from 

mice) 

AsIII SA 

AsV DA 

MMAV

DMAV

2, 5, 10, 15, 20 

10, 15, 20, 25, 30 

1, 2, 5, 10 mM 

0.5, 1, 2, 5 mM 

72 hr for all 

5 

10 

5 mM 

1 mM 

Cytotoxicity based on 

percent cell growth 

compared to treatment 

with distilled water: 

IC50 values: AsIII SA, 4.8; 

AsV DA, 17; 

MMAV, 9.8 mM; DMAV, 

3.2 mM. 

Tsuchiya 

et al., 2005 

TK6 cells 

AsIII SA 

AsIII ATO 

0.1, 0.5, 1, 10, 

100, 1000 

0.1, 1, 10, 100 

24 hr 

for both 

10 

10 

Cytotoxicity based on 

trypan blue exclusion 

assay: 

For both: LC50 between 3 

and 4. 

Hornhardt 

et al., 2006 

HL-60 cells AsIII ATO 

0.2, 0.4, 0.8, 1.6, 

3.1, 6.3, 13, 25, 

50, 100 

24 hr 0.8 Viability determined 

using MTT assay: 

LC50 = 32. 

Yedjou 

and 

Tchounwo

u, 2007 

C-208 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

IEC cells 

(primary 

culture) 

IEC-6 cells 

AsIII SA 

for both 

7.7, 15, 38, 77, 

116, 154 for both 

24 hr 

for both 

15 

15 

Viability determined 

using MTT assay: 

At dose of 77: IEC, 

∼45% dead; IEC-6, 

∼55% dead; the 

cytotoxicity of the 2 cells 

types was almost 

identical at most doses; 

based on this and their 

rather similar 

concentration-dependent 

declines in membrane 

enzymes and constituents 

(e.g., alkaline 

phosphatase, hexose, 

sialic acid, cholesterol, 

and phospholipid), the 

primary and established 

cultures gave 

approximately similar 

toxic responses. 

Upreti et 

al., 2007 

MDAH 2774 

cells 

AsIII ATO 1, 2, 5, 8 72 hr 

1 or 2 

(uncertain since 

control 

not 

shown) 

Cytotoxicity estimated 

by XXT proliferation 

assay 

and alternatively by 

trypan blue dyeexclusion assay (for 

which treatment time 

was either 72 or 96 hr—

it was unclear from 

methods): IC50 by both 

methods: 5. 

Askar et 

al., 2006 

HPBMs 

exposed to 

M-CSF for 7 

days and 

considered 

Mmacrophages 

AsIII SA 

AsV

MMAV

DMAV

LC50 

determinations 

48 hr — 

Viability based on AB 

assay: 

LC50 values: AsIII, 7.0; 

AsV, 1900; 

MMAV, 2500; DMAV, 

800. 

Sakurai et 

al., 2006 

HPBMs 

exposed to 

GM-CSF for 

7 days and 

considered 

GMmacrophages 

AsIII SA 

AsV

MMAV

DMAV

LC50 

determinations 

48 hr — 

Viability based on AB 

assay: 

LC50 values: AsIII, 5.8; 

AsV, 2800; 

MMAV, 2000; DMAV, 

2000. 

Sakurai et 

al., 2006 

C-209 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

The following 

cell lines: HL60, U-937, 

TIG-112, 

CRL-1609, 

RAW264.7, 

mouse normal 

embryo cells, 

mouse 

embryo cells 

that were MT 

+/+ and 

MT -/-, and 

the following 

3 types of 

human 

immune cells: 

peripheral 

Tlymphocytes, 

immature 

dendritic cells 

and multinucleated 

giant cells 

AsIII SA LC50 

determinations 

48 hr — 

Viability based on AB 

assay: 

LC50 values: HL-60, 13; 

U-937, 12; 

TIG-112, 25; CRL-1609, 

17; RAW264.7, 25; 

MT +/+ cells, 4.8; MT -

/- cells , 5.8; 

T-lymphocytes, 3.3; 

dendritic, 8.2; giant, 2.3. 

Sakurai et 

al., 2006 

GM04312C 

cells 

AsIII SA 2.5, 10, 50 24 hr 2.5 Viability based on 

neutral red assay: LC50 = 

~20. However, when 

viability was based on 

colony-forming assay: 

LC50 = ~6 with LOEC of 

2.5 

Shen et al., 

2006 

C-210 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Primary 

mouse 

hepatocytes 

AsIII SA 60, 100, 200 24 hr 60 

Viability determined 

using MTT assay: LC50

= ~200 (LC50 = 30 for 

48-hr treatment). 

Pretreatment with SFN 

caused big ⇓ in 

cytotoxicity. SFN 

activates transcription 

factor Nrf2 and causes 

significant ⇑ of protein 

expressions responsible 

for excretion of arsenic 

into extracellular space. 

SFN caused big ⇑ in 

intracellular GSH levels 

and big ⇓ in intracellular 

arsenic levels. Also, 

pretreatments with BSO, 

EA, or MK-571, which ⇑

arsenic accumulation in 

hepatocytes, caused big 

⇑ in cytotoxicity. 

Shinkai et 

al., 2006 

SV-HUC-1 

cells 

AsIII SA 

MMAIII

DMAIII

0.5, 1, 2, 5, 10 

0.1, 0.25, 0.5, 1 

0.25, 0.5, 1, 2, 5 

3 days for all 

1 

0.25 

0.5 

Viability determined by 

SRB assay: 

LC50 values: AsIII, 2.91; 

MMAIII, 0.46; 

DMAIII, 1.59. 

Su et al., 

2006 

JB6 C141 

cells 

JB6 C141 

cells exposed 

to 0.1, 0.2, 

0.5, 1, 2, 3, 4, 

5, 6, 7, or 8 

kJ/m2

 of UVB 

at end of 

pretreatment 

with inorganic 

arsenic 

AsIII SA 

for both 

0.1, 1, 5, 10, 20, 

50, 100, 500, 1000 

10 

24 hr for both 

5 

10 

Viability determined by 

MTS assay: 

LC50 = ∼15, decreased 

with dose until reached 

∼12% of control at top 3 

doses. 

Probably some 

cytotoxicity at UVB dose 

of 5, and there was 

significant cytotoxicity at 

UVB dose of 6. 

Viability was ∼70% of 

control at highest UVB 

dose. 

Tang et al., 

2006 

DNA Damage 

WRL-68 

(human 

hepatic cell 

line) 

AsIII SA 0.001, 0.01, 0.1, 

10 

16 hr 0.001 Induction of DNAprotein crosslinks 

(methylated forms of 

arsenic could not be 

detected in the cells). 

Ramírez et 

al., 2000 

C-211 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Human aorta 

VSMCs 

(vascular 

smooth 

muscle cells) 

AsIII SA ∼1.2, 2.5, 5, 10 4 hr ∼1.2 

DNA strand breaks 

(double and single strand 

breaks and alkali-labile 

sites) detected by comet 

assay; the effect was 

similar in 

nonproliferating VSMCs. 

Lynn et al., 

2000 

 

PHAstimulated 

and 

unstimulated 

human 

lymphocytes 

AsIII ATO 

10 2 hr 10 

Oxidative damage to 

DNA measured by the 

comet assay, including 

SSBs—after digestion 

with FPG, arsenicinduced base damage 

was converted to a large 

increase in SSBs and 

some FPG-created 

DSBs. (FPG cleaves 

purines including 7,8-

dihydro-8-oxoguanine 

(8-oxoG), 

formamidopyrimidines, 

and AP sites.) Like the 

damage induced by 

H2O2, arsenic-induced 

DNA damage was 

repaired more slowly in 

unstimulated 

lymphocytes. 

Li et al., 

2001 

L-132 cells 

(human 

diploid 

alveolar 

epithelial type 

II cells) 

AsIII SA 

MMAV

DMAV

100 

100 

5, 10, 100 

6 hr 

for all 

None 

None 

5 

Induction of DNA SSB 

resulting from inhibition 

of repair polymerization 

by polymerization 

inhibitors aphidicolin 

and hydroxyurea. DMAV

induced them in a dosedependent manner 

(measured by alkaline 

elution). 

Yamanaka 

et al., 1997 

L-132 cells 

(human 

diploid 

alveolar 

epithelial type 

II cells) 

AsIII SA 

MMAV

DMAV

100 

for all 

3 hr 

for all 

None 

None 

100 

Induction of DNA repair 

synthesis using the BrdU 

photolysis assay (singlestrand DNA breaks 

induced by UVirradiation were 

measured by alkaline 

elution). Follow-up 

experiment with same 

DMAV treatment for 1, 3, 

or 6 hr showed increases 

with longer durations of 

treatment. 

Yamanaka 

et al., 1997 

C-212 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

L-132 cells 

(human 

diploid 

alveolar 

epithelial type 

II cells) 

MMAV

100 with 10 mM 

SAM present 6 hr 100 

Induction of DNA repair 

synthesis using the BrdU 

photolysis assay (singlestrand DNA breaks 

induced by UVirradiation are measured 

by alkaline elution). 

This and other evidence 

strongly suggests that the 

DNA damage was not 

directly induced by 

MMAV but by 

dimethylated arsenic that 

was produced 

metabolically by reaction 

of MMAV with SAM. 

Yamanaka 

et al., 1997 

φX174 RF I 

DNA 

Naked 

doublestranded 

circular DNA 

AsIII SA 

MMAIII

DMAIII

DMAV

0.1, 1, 10, 100, 

300 mM 

10, 15, 20, 25, 30, 

60 mM 

40, 80, 150, 250 

μM 

0.1, 1, 10, 100, 

300 mM 

2 hr 

for all 

None 

30 mM 

150 μM 

None 

Nicked DNA in DNA 

nicking assay. 

Mass et 

al., 2001 

Human 

primary 

peripheral 

blood 

lymphocytes 

AsIII SA 

AsV

MMAIII

MMAV

DMAIII

DMAV

1–1000 

1–1000 

1.25–80 

Not reported–875 

1.4–91 

Not reported–1000 

2 hr 

for all 

Not 

reported 

for any of 

them 

Breaks and/or alkalilabile lesions in DNA 

detected in the singlecell gel comet assay—

the relative potencies 

based on slopes are 

shown below (the larger 

the number, the bigger 

the effect): 

 AsIII 1

 AsV 1.4

 MMAIII 77

MMAV <1

 DMAIII 386

DMAV <1

AsIII and AsV caused a 

significant effect, and 

they were not 

significantly different 

from each other. MMAIII

and DMAIII were thus 77 

and 386 times more 

potent in causing DNA 

damage than SA. 

Mass et 

al., 2001 

C-213 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

E. coli

WP2s(λ) 

(lon11, sulA1, 

trpE65, 

uvrA155, 

lamB+

) 

MMAIII

DMAIII

0.01, 0.10, 1.0, 10 

for all 

Overnight 

for all 

None 

None 

Assay to test for 

induction of prophage 

with and without 

exogenous metabolic 

activation: 

No statistically 

significant induction of 

prophage by either 

compound. 

Kligerman 

et al., 2003 

Raji cells 

(human 

Blymphocytes) 

AsIII SA 

MMAIII

DMAIII

0.2, 1, 10, 20, 40, 

100 for all 

4 hr 

4 hr 

2 hr 

10 

0.2 

10 

Extent of DNA damage 

detected by single-cell 

gel electrophoresis 

(comet) assay: 

At 0.2 and 1: MMAIII >> 

DMAIII = AsIII. 

At 100: all 3 chemicals 

had roughly the same 

level of DNA damage as 

MMAIII had at 0.2, but 

MMAIII still has 

significantly more DNA 

damage than the other 

two chemicals. 

Gómez et 

al., 2005 

Jurkat cells 

AsIII SA 

MMAIII

DMAIII

0.2, 1, 10, 20, 40, 

100 for all 

4 hr 

4hr 

2 hr 

10 

0.2 

10 

Extent of DNA damage 

detected by single-cell 

gel electrophoresis 

(comet) assay: 

At 0.2 and 1: MMAIII >> 

DMAIII = AsIII. 

At 40 and 100: DMAIII > 

MMAIII > AsIII. 

Gómez et 

al., 2005 

C-214 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

NB4 cells 

HL-60 cells 

CHO-K1 cells 

AsIII SA 

for all 

0.25, 0.5, 1 

0.25, 0.5, 1 

0.25, 0.5, 1, 2 

4 hr for all 0.25 

0.25 

None 

The LOECS shown are 

for DNA strand breaks 

(termed ADSB by the 

authors) detected by the 

comet assay without any 

additional treatments of 

DNA to digest and 

reveal ODA or DPC. 

They also treated the 

damaged DNA with FPG 

or PK to yield estimates 

of ODA or DPC, 

respectively. The LOEC 

was 0.25 for all 3 cell 

types for ODA, DPC, or 

ODA+DPC. Clearly 

much more DNA 

damage is revealed by 

treatments with FPG, 

PK, or both. DNA 

damage was induced at 

levels causing no 

cytotoxicity. 

Wang et 

al., 2001 

Human 

peripheral 

blood 

lymphocytes 

from 2 

donors, with 

results 

reported 

separately 

AsIII SA 

MMAIII

DMAIII

5, 10 

2.5, 5, 10, 20, 40, 

80, 100 

2.5, 5, 10, 20, 40, 

80 

4 hr for all 

None 

2.5 

5 

The LOECs apply to the 

extent of DNA damage 

detected by SCGE 

(comet) assay at pH > 

13. There was no 

cytotoxicity at doses up 

to 20. Much lower 

responses for all 

arsenicals were seen in 

comet assay at pH of 

12.1, with the difference 

between this and pH 13 

being defined as alkaline 

labile sites. DNA 

damage by both 

methylated arsenicals 

was markedly reduced 

by co-exposures to the 

antioxidants Se-Met or 

vitamin C. DNA-double 

strand breaks were not 

induced. 

SotoReyes et 

al., 2005 

C-215 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

MRC-5 cells AsIII SA 2.5, 5, 10 2 hr 2.5 

DNA SSBs detected by 

the standard alkaline (pH 

> 13) comet assay: ⇑

with dose of both tail 

length and tail moment at 

doses of 2.5 and 5, but a 

⇓ for both effects at dose 

of 10 to less than effect 

seen at dose of 2.5. NSE 

on cytotoxicity at any of 

the tested doses. 

Mourón et 

al., 2006 

MRC-5 cells AsIII SA 2.5, 5, 10 2 hr 

2.5 for 

SSBs 

10 for 

proteinDNA 

adducts 

Protein-DNA adducts 

and DNA SSBs detected 

by alkaline (pH > 13) 

comet assay done with 

and without 

posttreatment with 

proteinase K, 

respectively: 

Experiment without 

proteinase K: ⇑ of both 

tail length and tail 

moment at doses of 2.5 

and 5, but a ⇓ of both 

effects at dose of 10 to 

less than effect seen at 

other doses. 

Experiment with 

proteinase K: ⇑ of both 

tail length and tail 

moment at doses of 2.5 

and 5, and a further large 

⇑ in both parameters at 

dose of 10. NSE on 

cytotoxicity at any of the 

tested doses in either 

experiment. Evidence 

for protein-DNA adducts 

(or crosslinks) came 

from ⇑ observed at dose 

of 10, which is thus the 

LOEC for that effect. 

Proteinase K breaks the 

crosslinks that hinder the 

DNA fragmentation 

caused by the DNA 

SSBs. 

Mourón et 

al., 2006 

C-216 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

MRC-5 cells DMAV 125, 250, 500 2 hr 

500 for ⇓

in SSBs 

(see row 

below) 

DNA SSBs detected by 

the standard alkaline (pH 

> 13) comet assay: slight 

⇑ in tail moment (TM) at 

dose of 125 (a NSE); 

point estimates of TM 

were below control at 2 

higher doses, with that at 

500 being significantly 

below it; actual data: 

TMs: 0, 13.4; 125, 14.6; 

250, 13.1; 500, 9.7. NSE 

on cytotoxicity at any of 

the tested doses. 

Mourón et 

al., 2005 

MRC-5 cells DMAV 125, 250, 500 2 hr 

125 for 

both 

proteinDNA 

adducts 

and SSBs 

Protein-DNA adducts 

and DNA SSBs detected 

by alkaline (pH > 13) 

comet assay done with 

and without 

posttreatment with 

proteinase K, 

respectively: 

Experiment without 

proteinase K (buffer 

only): progressive ⇓ in 

tail moment (TM) with 

increasing dose; actual 

data: TMs: 0, 7.7; 125, 

6.7; 250, 5.3; 500, 4.9. 

Experiment with 

proteinase K: ⇑ in TM, 

with a positive doseresponse; actual data: 

TMs: 0, 8.3; 125, 11.9; 

250, 22.2; 500, 23.3. 

NSE on cytotoxicity at 

any of the tested doses in 

either experiment. 

Proteinase K breaks the 

crosslinks that hinder the 

DNA fragmentation 

caused by the DNA 

SSBs. 

Mourón et 

al., 2005 

C-217 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

L-132 cells 

(human 

alveolar type 

II cells) 

DMAV 5, 7.5, 10 mM 12 hr 5 mM 

DNA SSB detected by 

alkaline elusion: there 

was a dose-response. 

Early in the exposure 

period, there was marked 

suppression of 

replicative DNA 

synthesis, and the chain 

length of the nascent 

DNA was shorter than 

that of the control, which 

suggests that the 

template DNA was 

modified by more than 

just strand breaks. 

Tezuka et 

al., 1993 

HepG2 cells AsIII SA 7.5 24 hr 7.5 

Induction of DNA DSBs 

by immunodetection of 

γH2A.X foci: 

⇑ to ∼6x control level; 

co-treatment with 170 

nM SAM did not change 

the induced DSB 

frequency. 

Ramírez et 

al., 2007 

NB4 cells 

AsIII SA 

AsIII ATO 

MMAIII

DMAIII

0.5 30 min 0.5 

Experiments with ENIII, 

FPG and NE (from NB4 

cells) as well as 

experiments using 

immunodepletion of NE 

with antibodies directed 

against proteins known 

to be involved in 

excision repair suggest 

that these trivalent 

arsenicals induce only 

oxidative DNA adducts 

and that OGG1, MYH 

and APE are involved in 

the excision of the 

oxidative DNA adducts. 

Pu et al., 

2007 

HL-60 cells 

AsIII

ATOc 12.5, 25, 50 24 hr 12.5 

DNA damage detected 

by alkaline SCGE 

(comet) assay: while the 

response was barely 

statistically significant at 

the lowest dose, it was 

strong at the other 2 

doses, with a positive 

dose-response. 

Yedjou 

and 

Tchounwo

u, 2007 

C-218 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

PARP-1+/+

MEF cells 

PARP-1-/-

MEF cells 

AsIII SA 

for both 

11.5, 23 

for both 

30 min 

for both 

11.5 

11.5 

Extent of DNA damage 

detected by SCGE 

(comet) assay at pH >13, 

reported as induced 

damage (experimental – 

control) in units of TM 

length: 

~0.4 at 11.5, ~0.7 at 23. 

~2.9 at 11.5, ~3.4 at 23. 

All 4 estimates were 

statistically significant. 

Poonepalli 

et al., 2005 

PARP-1+/+

MEF cells 

PARP-1-/-

MEF cells 

AsIII SA 

for both 

11.5, 23 

for both 

24 hr 

for both 

11.5 

11.5 

Extent of DNA damage 

detected by single-cell 

gel electrophoresis 

(comet) assay at pH >13, 

reported as induced 

damage (experimental – 

control) in units of tail 

moment length: 

~2.0 at 11.5, ~3.6 at 23. 

~4.8 at 11.5, ~5.5 at 23. 

All 4 estimates were 

statistically significant. 

Poonepalli 

et al., 2005 

HaCaT cells 

CRL1675 

cells 

THP-1 + 

A23187 cells 

AsIII ATO 

for all 

72-hr LD10 and 

LD25 for each cell 

line: 

1.9, 15.2 

1.0, 1.9 

1.9, 3.8 

72 hr for all 

15.2 

None 

1.9 

DNA single-strand 

breaks detected by 

SCGE (comet assay) 

following alkaline 

treatment: 

NSE at LD10; ⇓ at LD25

(perhaps stimulates 

repair). 

NSE at LD10; NSE at 

LD25. 

⇑ at LD10; ⇑ at LD25. 

GrahamEvans et 

al., 2004 

C-219 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HaCaT cells 

CRL1675 

cells 

THP-1 + 

A23187 cells 

AsIII ATO 

for all 

72-hr LD10 and 

LD25 for each cell 

line under 

chronic-exposure 

conditions, as 

follows: 

2.0, 4.0 

0.5, 1.3 

0.5, 5.1 

Under chronic 

exposure 

conditions: 

72 hr for all 

2.0 

1.3 

0.5 

Testing for DNA singlestrand breaks was 

preceded by exposure to 

1.0 μM AsIII ATO for at 

least 8 passages to 

establish chronicexposure conditions. 

Then, following 

exposures to various 

doses for 72 hr, DNA 

single-strand breaks 

were detected by singlecell gel electrophoresis 

(comet assay) following 

alkaline treatment: 

⇑ at LD10; ⇑⇑ at LD25. 

NSE at LD10; ⇑ at LD25. 

⇑⇑ at LD10; ⇑⇑ at LD25.

GrahamEvans et 

al., 2004 

293 cells 

AsIII ATO 

1 6 hr 1 

DNA damage reported in 

units of tail moment in a 

comet assay that used 

nuclear extraction 

incubation: untreated = 

∼11 units; dose of 1: big 

⇑ to ∼58 units. 

Effects of co-treatment 

(CoTr) with modulators 

at high doses: 

CoTr 200 μM DMSA: ⇓

from inorganic arsenic 

alone to ∼38 units. 

CoTr 100 μM DMPS: ⇓

from inorganic arsenic 

alone to ∼39 units. 

Effects of CoTr with 

modulators at low doses: 

CoTr 20 μM DMSA: ⇑

from inorganic arsenic 

alone to ∼104 units. 

CoTr 10 μM DMPS: ⇑

from inorganic arsenic 

alone to ∼84 units. 

Jan et al., 

2006 

C-220 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

SV-HUC-1 

cells 

AsIII ATO 1 6 hr 1 

DNA damage reported in 

units of tail moment in a 

comet assay that used 

nuclear extraction 

incubation: untreated = 

∼10 units; dose of 1: big 

⇑ to ∼49 units. 

Effects of CoTr with 

modulators at high 

doses: 

CoTr 200 μM DMSA: ⇓

from inorganic arsenic 

alone to ∼34 units. 

CoTr 100 μM DMPS: ⇓

from inorganic arsenic 

alone to ∼35 units. 

Effects of CoTr with 

modulators at low doses: 

CoTr 20 μM DMSA: ⇑

from inorganic arsenic 

alone to ∼99 units. 

CoTr 10 μM DMPS: ⇑

from inorganic arsenic 

alone to ∼89 units. 

Jan et al., 

2006 

UROtsa cells 

AsIII SA 

MMAIII

1, 10 

0.05, 0.5, 5 

30 min 

for both 

1 

0.05 

Detection of 8-oxo-dG 

(measure of oxidative 

DNA damage): 

⇑ to 3x control at 1, ⇑ to 

2x control at 10. 

⇑ to 5x control at 0.05, ⇑

to 4x control at 0.5, NSE 

at 5. 

Eblin et 

al., 2006 

UROtsa cells 

AsIII SA 

MMAIII

1, 10 

0.05, 0.5, 5 

60 min 

for both 

10 

0.05 

Detection of 8-OHdG 

formation (measure of 

oxidative DNA damage): 

NSE at 1, big ⇓ from 

control at 10. 

⇑ to 3x control at 0.05, ⇑

to 3.3x control at 0.5, ⇑

to 4.3x control at 5. 

Thus MMAIII showed a 

time delay just as it did 

for ROS production. 

Eblin et 

al., 2006 

E. coli strain 

WP2S(λ) 

AsIII SA Up to 3.2 mM 20 hr None No induction of λ phage 

(part of “SOS” system) 

using 8 serial 2-fold 

dilutions from a 

concentration that 

inhibits growth. 

Rossman 

et al., 1984 

C-221 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Humanhamster 

hybrid AL

cells 

AsIII SA 30.8 24 hr 30.8 Induction of 8-OHdG; 

co-treatment with SOD 

or catalase considerably 

reduced induction of this 

oxidative DNA damage. 

Kessel et 

al., 2002 

HaCaT cells 

AsIII SA 

AsV

5, 10, 20, 30 

10, 20, 30, 50, 100 

24 hr 10 

20 

Induction of 8-OHdG; 

pre-incubation with 

SOD, CAT or DMSO 

almost completely 

blocked this. 

Oxidative DNA damage 

by 20 μM AsIII SA: preincubation with 

MnTMPyP, L-NAME or 

FeTMPyP substantially 

blocked such damage. 

Ding et al., 

2005 

TK6 cells 

AsIII SA 

AsIII ATO 

0.1, 1, 10 

for both 

22 hr 

for both 

1 

10 

Induction of DPCs 

detected by a decrease in 

DNA damage detected in 

the comet assay when an 

arsenic treatment was 

followed by exposure to 

1 or 2 Gy of 69 cGy/min 

gamma radiation. The 

DPCs kept the damaged 

DNA from moving 

during electrophoresis. 

While both SA and ATO 

caused a significant 

effect, the effect was 

more pronounced for SA. 

Hornhardt 

et al., 2006 

φX174 RF I 

DNA 

Naked 

doublestranded 

circular DNA 

AsIII unspecified 

MMAIII

DMAIII

10μM–30 mM in 

log increments 

10, 20, 30, 40, 50 

37.5, 75, 150, 300, 

1000 

24 hr 

for all 

None 

10 

37.5 

Nicked DNA in DNA 

nicking assay. 

Nesnow et 

al., 2002 

C-222 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Supercoiled 

DNA 

(plasmid pBR 

322); 

similar results 

were found 

for plasmid 

φΧ174, but 

details were 

not reported 

AsIII SA 

AsV

MMAIII

MMAV

Monomethylarsine 

DMAIII

DMAV

Dimethylarsine 

Trimethylarsine 

≥ 5 mM 

≥ 5 mM 

≥ 5 mM 

≥ 5 mM 

≥ 5 mM 

<5 mM 

≥ 5 mM 

<0.5 mM 

<0.5 mM 

2 hr 

for all 

None 

None 

≥ 5 mM 

None 

≥ 5 mM 

<5 mM 

None 

<0.5 mM 

<0.5 mM 

Damage to DNA 

detected by agarose gel 

electrophoresis: 

The arsines were 

produced in aqueous 

reaction mixtures of 

sodium borohydride and 

the appropriate arsenical. 

 Trimethylarsine and 

dimethylarsine were 

about 100 times more 

potent than DMAIII. 

When NADH or 

NADPH, which are 

biological hydride 

donors, were incubated 

with DMAIII for 2 hr, 

DNA damage was 

increased by at least 10-

fold, possibly because of 

the generation of 

dimethylarsine. 

Andrewes 

et al., 2003 

DNA Repair Inhibition or Stimulation 

CHO K1 cells AsIII SA 5, 10, 20, 40, 80 6 hrs 5 

DNA single-strand 

breaks detected by 

alkaline elution: those 

induced by MMS were 

repaired after incubation 

in a drug-free medium 

for 6 hr; however, 

posttreatment with 

sodium arsenite 

accumulated MMSinduced breaks with a 

dose-response for the 

arsenite exposure. Both 

alkali-labile sites and 

frank breaks were 

enhanced, with the latter 

occurring at higher doses 

of MMS and arsenite. 

Lee-Chen 

et al., 1993 

C-223 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

V79 cells, 

strain 743-3-6 

AsIII SA 

for both 

10 μM 3 hr 10 μM 

Similar decreases in 

inducible total nuclear 

DNA ligase activity and 

in inducible nuclear 

DNA ligase II activity 

were demonstrated after 

arsenic treatments given 

before or after MNU 

treatments, thereby 

demonstrating that most 

of the inhibited activity 

was DNA ligase II. 

Li and 

Rossman, 

1989b 

HeLa S3 cells 

MMAIII

MMAV

DMAIII

DMAV

0.0001, 0.001, 

0.01, 0.1, 1 

0.01, 0.1, 1, 10, 

100, 500 

0.0001, 0.001, 

0.01, 0.1 

0.01, 0.1, 1, 10, 

100, 250 

For all: 

18 hr + 5 

min more 

while also 

being treated 

with 

100 μM 

H2O2 

0.001 

None 

0.001 

None 

Effect on H2O2-induced 

poly(ADP-ribosyl)ation: 

⇓ with dose, 59% of 

control at dose of 1. 

NSE. 

⇓ with dose, 49% of 

control at dose of 0.1. 

NSE. 

Other experiments 

showed that the above 

effects were real 

decreases (not merely 

delayed responses). All 

above measurements 

were at dose levels with 

little to no cytotoxicity. 

After 18 hr incubation, 

these arsenicals had NSE 

on the extent of gene 

expression of PARP-1 at 

doses up to 0.1 and 100 

for methylated and 

pentavalent arsenicals, 

respectively. 

Walter et 

al., 2007 

C-224 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Isolated 

recombinant 

PARP-1 

AsIII SA 

MMAIII

DMAIII

10, 50, 100, 200, 

500 

for all 

For all: 

10 min 

preincubation 

before 

PARP-1 

reaction with a 

nicked plasmid 

as substrate 

10 

10 

10 

Effect on activity of 

PARP-1: 

⇓ with dose, 58% of 

control at dose of 500. 

⇓ with dose, 24% of 

control at dose of 500. 

⇓ with dose, 15% of 

control at dose of 500. 

These data suggest that 

trivalent arsenicals 

inhibit cellular 

poly(ADP-ribosyl)ation 

by reducing PARP-1 

activity. 

Walter et 

al., 2007 

Jurkat cells AsIII SA 0.01, 0.1, 1, 5, 10 24 hr 0.01 

⇓ ERCC1 mRNA level; 

not said to be statistically 

significant until dose of 

1, but means ± SDs 

suggest 45% ⇓ at 0.01 

and 60% ⇓ at 0.1. 

Decreases of 60%, 95%, 

and 85% at doses of 1, 5, 

and 10, respectively 

Andrew et 

al., 2006 

Jurkat cells AsIII SA 1 24 hr 1 

⇓ in repair following a 2-

hr in vitro treatment with 

4 μM 2-AAAF 

immediately after the 

inorganic arsenic 

treatment. DNA damage 

measured by SCGE 

(comet) assay: 

inorganic arsenic group 

had ⇑ DNA damage after 

2-hr 2-AAAF treatment 

and following a 

4-hr repair period. No 

difference in DNA 

damage before 2-AAAF. 

Andrew et 

al., 2006 

HLFC cells 

HLFK cells 

(Ku70 

deficient) 

AsIII SA 

for both 

1, 2.5, 5, 10 

for both 

2 hr 

for both 

2.5 

1 

DNA DSB damage as 

measured with neutral 

SCGE assay: 

This type of damage was 

significantly greater for 

HLFK than HLFC at all 

4 doses. 

Liu et al., 

2007b 

C-225 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HLFC cells 

HLFK cells 

(Ku70 

deficient) 

AsIII SA 

for both 

5 for both 2 hr 

for both 

5 

5 

The LOECs are for 

induction of DNA DSBs. 

 After the 2-hr AsIII

treatment, cells were 

incubated in arsenic-free 

medium to measure 

repair of DNA DSBs 

using the neutral SCGE 

assay at 0.5, 1, 1.5, and 2 

hr. At all time points 

there was significantly 

and substantially less 

repair in HLFK, showing 

that the Ku70 deficiency 

decreases the efficacy of 

repair of arsenic-induced 

DSBs. 

Liu et al., 

2007b 

CHO-K1 cells AsIII SA 0.1, 0.5, 1, 5, 10 24 hr 0.1 DNA polymerase β

promoter activity: big ⇑

at 0.1; slight ⇑ at 0.5; no 

effect at 1; big ⇓ at 5 and 

10. 

Snow et 

al., 2005 

GM847 cells 

HaCaT cells 

AsIII SA 

for both 

0.1, 0.5, 1, 5, 10 

for both 

24 hr 

for both 

0.1 

0.1 

DNA polymerase β

protein levels: 

Big ⇑ at 0.1 and 0.5, 

slight ⇑ at 1, no effect at 

5 and big ⇓ at10. 

Big ⇑ at 0.1 and 0.5, no 

effect at 1, big ⇓ at 5 and 

10. 

Snow et 

al., 2005 

W138 cells 

for both 

AsIII SA 

for both 

0.1, 0.5, 1, 5, 10 

for both 

24 hr 

48 hr 

0.1 

0.1 

DNA ligase activity: 

⇑ at 0.1, big ⇑ at 0.5, 

huge ⇑ at 1, ⇓ at 5, big ⇓

at 10. 

No effect at 0.1, big ⇑ at 

0.5 and 1, no effect at 5, 

big ⇓ at 10. 

Two other experiments 

of 72 and 96 hr duration 

showed generally even 

more subdued increases 

and decreases than the 

48-hr experiment. 

Snow et 

al., 2005 

C-226 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Effects Related to Oxidative Stress (ROS) 

Hepa-1 cells 

(mouse 

hepatoma) 

stably 

transformed 

with 

pEpREβgeo 

AsIII SA 0.1, 1, 5, 25, 50 6 hr 5 

Activated a βgalactosidase gene 

reporter system: suggests 

there was induced 

oxidative stress—5.6-

fold response; 

progressively and 

markedly decreasing 

responses at 2 higher 

doses. 

Maier et 

al., 2000 

WI38 (human 

fibroblasts) 

AsIII SA 

0.05, 0.5, 5

(24 hr 

pretreatment) 

followed by 60 

min 

exposure to H2O2

at 

1, 10 or 50 mM 

for 1 hr and then 

24 hr to recover 

24 hr 

pretreatment 

0.05 

Extent of viability 

determined by NR assay: 

Compared to control 

cells exposed to H2O2, 

with no pretreatment: 

⇑ viability at 1 mM H2O2

only. At dose of 5, there 

was an ⇑ in viability at 

10 mM H2O2 but a ⇓ in 

viability at 50 mm H2O2. 

Snow et 

al., 2001 

Purified 

thioredoxin 

enzyme from 

mouse liver; 

to test the 

NADPHdependent 

reduction of 

DTNB 

AsIII SA 

MMAIII

DMAIII

AsV

MMAV

DMAV

~0.2–800 

~0.2–800 

~0.2–800 

~10–6000 

~10–6000 

~10–6000 

— 

~100 

~0.2 

~3 

~300 

— 

— 

Approximate IC50s 

(inhibition of enzyme 

activity): 

~200. 

~0.4. 

~30. 

~3000. 

Never more than ~80% 

inactivation. 

Never more than ~80% 

inactivation. 

Lin et al., 

1999 

Primary 

culture of rat 

hepatocytes 

AsIIISA 

MMAIII

1–50 

0.1–10 

30 min 

for both 

— 

Decreased thioredoxin 

enzyme activity (the 

NADPH-dependent 

reduction of DTNB) 

IC50: >> 100. 

IC50: ~3. 

Lin et al., 

2001 

Humanhamster 

hybrid AL

cells 

AsIII SA 30.8 Within 5 min 30.8 Production of ROS, 

measured by ESR and 

with about a 3-fold 

increase in amplitude of 

signals; concurrent 

treatment with the 

radical scavenger DMSO 

eliminates the effect. 

Liu et al., 

2001 

C-227 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Human aorta 

VSMCs 

(vascular 

smooth 

muscle cells) 

AsIII SA ∼1.2, 2.5, 5, 10 4 hr ∼1.2 

Numerous experiments 

in this study led to the 

conclusion that arsenite 

activates NADH oxidase 

to produce superoxide, 

which then causes 

oxidative DNA damage. 

Lynn et al., 

2000 

HFW cells 

(diploid 

human 

fibroblasts) 

AsIII SA 

1.25, 2.5, 5, 10 

5, 10, 20, 40, 80 

24 hr 

4 hr 

1.25 

20 

Micronuclei were 

induced in both 

protocols; the yield of 

micronuclei was greatly 

reduced by the presence 

of the antioxidants 

catalase or NAC (the 

precursor of GSH), 

which suggests that 

oxidative stress was 

involved in the induction 

of micronuclei. 

Yih and 

Lee, 1999 

Jurkat cells 

AsIII SA 

MMAIII

DMAIII

0.2, 10, 20, 100 

for all 

2 hr 

2hr 

2 hr 

None 

10 

10 

Level of intracellular 

peroxides determined by 

flow cytometry using 

cell permeable 

fluorogenic marker 

DHR123: 

At 10 and 20: DMAIII >> 

MMAIII >> AsIII. 

At 100: MMAIII > DMAIII

about equal to AsIII. 

(Cell lysis may explain 

the reduction of DMAIII

at dose of 100 to 1/3 

level seen at 20.) 

Control value was not 

reported. If control 

value was actually 0 (and 

thus the baseline in the 

figure), then the LOEC 

for all 3 arsenicals would 

have been 0.2, with a 

rather similar slight 

response for all of them. 

Gómez et 

al., 2005 

C-228 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Whole blood 

lymphocytes 

from 2 human 

donors, with 

results 

reported 

separately 

MMAIII

DMAIII

2.5, 5, 10, 20 for 

both 

4 hr for all 

2.5 

10 

Levels of MDA as lipid 

peroxidation marker in 

human plasma: 

For MMAIII both donors 

showed significant 

increase over control at 

all doses except 10, for 

which only 1 was 

significant. For DMAIII

both donors showed 

significant increase over 

control at 20, but only 1 

did at 10. There was no 

cytotoxicity at the dose 

levels tested. 

SotoReyes et 

al., 2005 

HaCaT cells 

AsIII SA 

AsV

5, 10, 15, 20 

for both 

24 hr 

5 

10 

Induction of 3-NT, 

which is a diagnostic 

marker for RNS in vivo; 

pre-incubation with 

SOD, MnTMPyP, LNAME or FeTMPyP 

almost completely 

blocked this protein 

damage by 20 μM AsIII

SA; pre-incubation with 

CAT or DMSO had no 

effect, in sharp contrast 

to what happened for 

ROS-damage to DNA. 

Ding et al., 

2005 

L-132 cells DMAV 

10 mM alone 

10 mM + 0.5 mM 

PQ 

2 hr 

1 hr 

None 

10 mM 

DNA single-strand 

breaks detected by 

alkaline elusion: coexposure with PQ or 

sequential exposures of 1 

hr (with either one first) 

yielded a strong 

response.

Kawaguchi 

et al., 1996 

C-229 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

PAEC cells 

harvested 

from freshly 

isolated 

vessels 

AsIII SA 5, 10 1 hr 5 

Various experiments 

showed that inorganic 

arsenic activates a 

NADPH-dependent 

oxidase located in the 

plasma membrane that 

results in superoxide 

accumulation. Both the 

p67phox and Rac1 

subunits of the oxidase 

were shown to be 

essential for the 

response, and the 

oxidase is dependent on 

exogenous NAD(P)H for 

activity. The peak effect 

occurred within 1 hr and 

was higher at a dose of 5 

than 10. 

Smith et 

al., 2001 

NB4 cells 

AsIII ATO 

1 4 hr 1 

Generation of ROS led 

to decrease (and eventual 

loss, with continued 

treatment) of 

mitochondrial membrane 

potential, with 

subsequent outer 

mitochondrial membrane 

permeability changes. 

Jing et al., 

1999 

PAEC from 

freshly 

harvested 

vessels 

AsIII

probably 

ATO, but 

called 

arsenite 

5 5–15 min 5 ⇑ in superoxide and 

H2O2 accumulation. 

Barchowsk

y et al., 

1999b 

HFW cells AsIII SA 5, 10, 20 24 hr 5 DCF fluorescence to 

indicate formation of 

cellular oxidants; cotreatment with BHT (a 

radical scavenger) 

completely blocked this 

effect. 

Lee and 

Ho, 1995 

Cell free 

buffer 

DMAIIII — — — 

Oxidative damage was 

induced in thymine to 

form cis-thymine glycol. 

 SOD and CAT did not 

alter this reaction. Other 

tests suggest that the 

reaction requires the 

formation of a reactive 

arsenic peroxide, 

probably dimethylated 

arsenic peroxide. 

Yamanaka 

et al., 2003 

C-230 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Postconfluent 

PAEC cells in 

a monolayer 

AsIII SA 1, 2.5, 5, 10, 20 30 min 1 

DCF fluorescence as a 

direct measure of 

intracellular oxidant 

concentrations (i.e., 

accumulation of ROS): 

likely ⇑ at all doses, with 

a peak at 5 that is ~45% 

higher than control, a 

difference that is 

statistically significant. 

Barchowsk

y et al., 

1996 

Humanhamster 

hybrid AL

cells 

AsIII SA 11.5, 15.4 24 hr 11.5 

Induction of CD59-

mutations: dose-related 

increase in mutation 

frequency; pretreatment 

+ co-treatment with LNMMA (a nitric oxide 

synthase inhibitor) 

substantially reduced the 

mutation frequencies at 

both doses. Similar 

treatment with DNMMA (the inactive 

enantiomer) had no 

effect. These findings 

were taken as evidence 

that peroxynitrites have 

an important role in 

inorganic arsenicinduced genotoxicity. 

That conclusion was 

supported by a Western 

blot analysis of 

nitrotyrosine-modified 

proteins induced by 

inorganic arsenic 

treatments and mostly 

blocked by L-NMMA. 

Liu et al., 

2005 

C-231 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HepG2 cells 

AsIII ATO 20 6 hr 20 

Analysis of 481 selected 

genes in a DNA 

microarray experiment: 

hierarchical clustering 

analysis showed that 

inorganic arsenic 

exposure closely 

resembled DMNQ 

exposure (and was 

extremely different from 

DMN or phenol 

exposure) regarding 

patterns of genes that 

were up-regulated and 

down-regulated. In 

phase 1 of this 

experiment, DMNQ was 

selected as a model 

chemical that generates 

ROS and is known to 

induce genes associated 

with cell proliferative 

responses. Exposure to 

inorganic arsenic caused 

significant up-regulation 

of 38 genes and downregulation of 20 genes; 

dose used had >80% cell 

viability. 

Kawata et 

al., 2007 

NB4 cells 

NB4-M-AsR2 

cells 

IM9 cells 

AsIII ATO 

for all 

0.5, 1 

2, 4 

0.5, 1 

24 hrs 

for all 

0.5 

2 

0.5 

HMOX-1 protein (a 

stress-responsive 

protein) levels after 

treatment with ATO 

alone and co-treatment 

with 100 μM Trolox: 

At 0.5: slight ⇑ alone, 

big ⇑ with Trolox; at 1: 

⇑ alone, huge ⇑ with 

Trolox. 

At 2: slight ⇑ alone, big 

⇑ with Trolox; at 4: ⇑

alone, huge ⇑ with 

Trolox. 

At 0.5: slight ⇑ alone, 

big ⇑ with Trolox; at 1: 

⇑ alone, huge ⇑ with 

Trolox. 

Diaz et al., 

2005 

C-232 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

NB4 cells 

AsIII ATO 

for all 

Regarding row above, other indications that Trolox potentiates ATO-mediated 

oxidative stress: bigger ⇑ in protein carbonyls (indicator of oxidative damage 

to proteins) and 8-iso-PGF2α (indicator of lipid peroxidation) by combined 

ATO and Trolox treatment(s) than by ATO treatment(s) alone. Other 

experiments showed that the synergistic effect of Trolox on ATO-mediated 

apoptosis was not related to extracellular H2O2 production. ATO was shown 

to induce the formation of Trolox phenoxyl radicals by electronic spin 

resonance spectroscopy. 

Diaz et al., 

2005 

BFTC905 

cells and 

NTUB1 cells 

AsIII SA 

AsV

MMAIII

MMAV

DMAIII

DMAV

0.2 

for all 

24 hr 

for all 

0.2 

0.2 

0.2 

None 

0.2 

None 

Relative extent of 

oxidative damage 

(peroxidation) in lipids, 

measured as 

malonaldehyde 

formation; ranking of 

those with statistically 

significant ⇑ over control 

(i.e., unranked arsenicals 

had NSE): 

In BFTC905 cells: 

AsIII>DMAIII>MMAIII>> 

AsV. 

in NTUB1 cells: 

DMAIII>>MMAIII>AsIII. 

Wang et 

al., 2007 

BFTC905 

cells and 

NTUB1 cells 

AsIII SA 

AsV

MMAIII

MMAV

DMAIII

DMAV

0.2 

for all 

24 hr 

for all 

0.2 

0.2 

0.2 

0.2 

0.2 

None 

Relative extent of 

oxidative damage 

(carbonylation) in 

proteins; ranking of 

those with statistically 

significant ⇑ over control 

(i.e., unranked arsenicals 

had NSE): 

In BFTC905 cells: 

MMAIII>AsIII>DMAIII>> 

AsV. 

In NTUB1 cells: 

AsIII>MMAIII>DMAIII>>

AsV>MMAV. 

Consistent with these 

effects, increased levels 

of nitric oxide, 

superoxide ions, 

hydrogen peroxide, and 

the cellular free iron pool 

were consistently 

detected in both cell 

lines after treatments by 

the 3 trivalent arsenicals. 

Wang et 

al., 2007 

C-233 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

BFTC905 

cells and 

NTUB1 cells 

AsIII SA 

AsV

MMAIII

MMAV

DMAIII

DMAV

0.2 

for all 

24 hr 

for all 

0.2 

0.2 

0.2 

0.2 

0.2 

0.2 

Relative extent of 

oxidative damage (comet 

assay) in DNA; ranking 

of those with statistically 

significant ⇑ over control 

(i.e., unranked arsenicals 

had NSE): 

Without enzyme 

digestion: 

In BFTC905 cells: AsIII = 

MMAIII>MMAV> DMAV. 

In NTUB1 cells: AsIII = 

MMAIII>DMAIII = 

MMAIII = DMAV. 

With EnIII + FPG 

digestion: 

In BFTC905 cells: 

AsIII>MMAIII>DMAIII> 

MMAV. 

In NTUB1 cells: 

AsIII>MMAIII>DMAIII>M

MAV> 

DMAV = AsV.

Wang et 

al., 2007 

Gclm-/- MEF 

cells, from 

GCLM 

knockout 

mice 

AsIII SA 

for all 

See rows under Apoptosis and Cytotoxicity for this citation for experimental 

conditions. The high level of arsenic-induced oxidative stress from some 

treatments was not significantly decreased by tBHQ. Yet, tBHQ pretreatment 

or co-treatment greatly decreased inorganic arsenic induced apoptosis and 

cytotoxicity. 

Kann et 

al., 2005b 

NB4 cells AsIII ATO 0.75 

Results were obtained from various experiments, 

including Affymetrix oligonucleotide microarray 

analysis using a chip that contained 22,000 open reading 

frames from the human genome. Treatment for 10 days 

increased the expression of a set of genes responsible for 

ROS production. Genes were identified that responded 

to inorganic arsenic and H2O2 but whose response to 

inorganic arsenic was reversed by NAC. It was found 

that 26% of the genes significantly responsive to 

inorganic arsenic might have been directly altered by 

ROS. Inorganic arsenic treatment induced ROS, which 

in turn oxidized the Sp1 transcription factor, with a 

corresponding decrease in its in situ binding to the 

promoters of the 3 genes hTERT, C17, and c-Myc, with 

the result that their expressions were significantly 

suppressed (e.g., hTERT: ⇓ expression to < 1% normal). 

Chou et 

al., 2005 

1RB3AN27

cells 

AsIII SA 0.1, 0.5, 1, 5, 10 2 hr 0.5 ROS production using 

DCFH-DA assay: ⇑ with 

a positive dose-response; 

the increase at dose of 1 

was blocked by cotreatment with either 

NAC or α-Toc. 

Felix et al., 

2005 

C-234 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

BEAS-2B 

cells 

AsIII ATO 

5, 10, 20 24 hr 5 

Production of 8-

isoprostane, a by-product 

of lipid peroxidation: ⇑

with a positive doseresponse; 2x control at 5, 

6x control at 20. In 

addition, electron spin 

resonance studies 

(involving co-treatments 

with CAT, SF, NAC, or 

NADPH) and confocal 

microscope studies 

showed that inorganic 

arsenic can produce 

ROS, such as H2O2 and •

OH, as a result of 

reduction reactions 

within cells. 

Han et al., 

2005 

Embryonic 

mesenchymal 

cells prepared 

from CF-1 

mouse 

conceptuses at 

gestation day 

11 

AsIII SA 5.8, 11.6, 15.4 2 hr 5.8 

Production of ROS 

detected by a variant of 

the DCF assay using 

CM-H2DCFDA: 

Induced RFUs (i.e., 

experimental – control): 

5.8, ∼950; 11.6, ∼2050; 

15.4, ∼2700. 

15-min pretreatment with 

0.2 or 0.5% (v/v) DMSO 

blocked all or almost all 

inorganic arsenicinduced production of 

ROS at dose of 15.4, 

whereas 15-min 

pretreatment with 0.1% 

(v/v) DMSO partially 

blocked it. 

PérezPastén et 

al., 2006 

RAW264.7 

cells 

AsIII SA 2.5, 5, 10, 25 3 hr 5 

Extracellular H2O2

production quantified 

using the Amplex Red 

Hydrogen Peroxide 

Assay: there was a 

positive dose-response, 

reaching 

~1.4x control. 

Szymczyk 

et al., 2006 

HELF cells AsIII SA 0.1, 0.5, 1, 5, 10 4 hr 0.5 Production of ROS 

detected by the DCFHDA assay in the 15 min 

after inorganic arsenic 

treatment: ⇑ with dose to 

>2x control at dose of 

10. 

Yang et 

al., 2007 

C-235 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HELF cells AsIII SA 0.1, 0.5, 1, 5, 10 3, 6, 12, 24, 

 or 48 hr 

Various 

SOD activity after 24 hr: 

⇑ at 0.5, ⇓ at 5 and 10; 

hint of similar change of 

direction in response also 

in treatments of some 

other durations. 

GPx activity after 24 or 

48 hr: ⇓ at 5 and 10; but 

hints of ⇑ at lower doses 

and ⇓ at higher doses in 

treatments of some 

durations. 

MDA content (measure 

of LPO) after 24 or 48 

hr: ⇑ at 5 and 10; tended 

to increase with time and 

dose in treatments of all 

durations. 

Yang et 

al., 2007 

NB4 cells AsIII ATO 1, 3 16 hr 1 

Effect on cellular total 

antioxidant capacity 

determined using the 

ABTS assay 

(Troiloc-equivalent 

antioxidant capacity in 

units of nmol/mg 

protein): 

Control = ∼420; 

inorganic arsenic at dose 

of 3: ∼150; inorganic 

arsenic at dose of 1: 

∼240. 

Effects of co-treatment 

(CoTr): 

inorganic arsenic at 3 + 

CoTr with 1000 μM 

DTT: ∼275. 

inorganic arsenic at 3 + 

CoTr with 2000 μM 

DTT: ∼340. 

inorganic arsenic at 1 + 

CoTr with 25 μM DTT: 

∼150. 

inorganic arsenic at 1 + 

CoTr with 50 μM DTT: 

∼125. 

Jan et al., 

2006 

C-236 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

NB4 cells 

AsIII ATO 

0.5 2 hr 0.5 

Intracellular H2O2 level 

(units of Amplex red 

assay): control = ∼20; 

inorganic arsenic ∼45. 

Effects of co-treatment 

(CoTr): 

CoTr with 80 μM DTT: 

∼72. 

CoTr with 100 μM 

DMSA: ∼67. 

CoTr with 20 μM 

DMPS: ∼72. 

Jan et al., 

2006 

BFTC905 

cells and 

NTUB1 cells 

DMAV 1, 2 24 hr 

for all 

1 in at 

least one 

cell line 

for all 3 

effects 

 ⇑ oxidative damage 

(peroxidation) in lipids, 

measured as 

malonaldehyde 

formation: at both doses 

in BFTC905 cells, at 

dose of 2 in NTUB1 

cells. 

⇑ oxidative damage 

(carbonylation) in 

proteins: at higher dose 

in BFTC905 cells, at 

lower dose in NTUB1 

cells. 

⇑ oxidative damage 

(comet assay) in DNA, 

without enzyme 

digestion: at both doses 

in both cell lines. 

Wang et 

al., 2007 

A549 cells AsIII ATO 2 48 hr 

Loss of MMP determined by flow 

cytometry using JC-1: 2 μM inorganic 

arsenic: ⇑ to ∼1.25x; 

200 μM sulindac: ⇑ to ∼1.15x; (2 μM 

inorganic arsenic + 200 μM sulindac): 

⇑ to ∼1.9x. 

There was also a synergistic 

interaction between these treatments in 

causing big ⇑ in cytochrome C protein 

level in the cytosol, which is thought 

to result from damage to 

mitochondrial membranes that permits 

cytochrome C release to the cytosol. 

Pretreatment with NAC almost 

entirely blocked the MMP and 

cytochrome C effects. (Sulindac is a 

NSAID that inhibits COX-2.) 

Jin et al., 

2006b 

C-237 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

A549 cells AsIII ATO 2 48 hr 2 

Production of ROS using 

carboxy-H2DCFDA 

assay: control, ∼0.8 unit; 

2 μM inorganic arsenic, 

∼4.2 units; 200 μM 

sulindac: ∼4.5x; (2 μM 

inorganic arsenic + 200 

μM sulindac): ∼7.5x. 

Thus there was only 

additivity. Pretreatment 

with NAC before 

combined treatment: ⇓ to 

∼3.9 units. 

Jin et al., 

2006b 

HeLa cells AsIII SA 10, 100 4 hr 

10 for 

Trx1 and 

Trx2; 

none for 

GSH/ 

GSSG 

Effects on Trx1 and Trx2 

redox states determined 

using Redox Western 

blot methods: 

Trx1: ⇑ in oxidation at 

10, slightly bigger ⇑ at 

100. 

Trx2: huge ⇑ in 

oxidation at 10, slightly 

bigger ⇑ at 100. 

In contrast, inorganic 

arsenic had little effect 

on the GSH/GSSG redox 

state, as determined by 

HPLC. 

Hansen et 

al., 2006 

BAEC cells AsIII SA 5, 10 1 hr 5 ⇑ in peroxynitrite to 

~1.4x and ~1.6x at 5 and 

10, respectively. 

Bunderson 

et al., 2006 

BAEC cells AsIII SA 10 24 hr 10 ⇑ in nitrotyrosine 

formation to ~1.15x. 

Bunderson 

et al., 2006 

HEK 293 

cells and 

SV-HUC-1 

cells 

AsIII SA 

MMAIII

DMAIII

0.2 

for all 

24 hr 

for all 

0.2 

0.2 

0.2 

Relative extent of 

oxidative damage 

(peroxidation) in lipids, 

measured as 

malonaldehyde 

formation; ranking of 

those with statistically 

significant ⇑ over control 

(all were significant): 

In HEK 293 cells: 

AsIII>>MMAIII>DMAIII. 

In SV-HUC-1 cells: 

AsIII>DMAIII>MMAIII. 

Wang et 

al., 2007 

C-238 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HEK 293 

cells and 

SV-HUC-1 

cells 

AsIII SA 

MMAIII

DMAIII

0.2 

for all 

24 hr 

for all 

0.2 

0.2 

0.2 

Relative extent of 

oxidative damage (comet 

assay) in DNA; ranking 

of those with statistically 

significant ⇑ over control 

(all were significant): 

Without enzyme 

digestion: 

In HEK 293 cells: 

AsIII>MMAIII = DMAIII. 

In SV-HUC-1 cells: 

MMAIII = AsIII = DMAIII. 

With EnIII + FPG 

digestion: 

In HEK 293 cells: AsIII = 

MMAIII = DMAIII. 

In SV-HUC-1: 

AsIII>DMAIII = MMAIII.

Wang et 

al., 2007 

TRL 1215 

cells 

TRL 1215 

cells 

pretreated 

with 50 μM 

BSO for 24 hr 

to deplete 

GSH levels 

and then cotreated with 

50 μM BSO 

MMAV 

for both 

5 mM 24 hr 

None 

5 mM 

Cellular ROS levels 

based on DCFH-DA 

assay: 

MMAV: NSE. 

MMAV + BSO: ⇑ to 

∼2.22x . 

Sakurai et 

al., 2005a 

TRL 1215 

cells 

TRL 1215 

cells 

pretreated 

with 50 μM 

BSO for 24 hr 

to deplete 

GSH levels 

and then cotreated with 

50 μM BSO 

MMAV 

for both 

5 mM 48 hr 

None 

5 mM 

Cell survival determined 

by AB assay: 

MMAV: 100% survival. 

MMAV + BSO: ∼3% 

survival. 

Co-treatment with 10 

mM DMPO during the 

MMAV + BSO treatment 

blocked most of the 

cytotoxicity, resulting in 

∼72% survival. DMPO 

effectively scavenged 

cellular radical 

molecules. 

Sakurai et 

al., 2005a 

C-239 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

TRL 1215 

cells 

TRL 1215 

cells 

pretreated 

with 50 μM 

BSO for 24 hr 

to deplete 

GSH levels 

and then cotreated with 

50 μM BSO 

MMAV 

for both 

5 mM 48 hr 

None 

None 

with 

DMPO 

Caspase 3 activity 

(related to apoptosis): 

MMAV: NSE. 

MMAV + BSO: ⇑ to 

∼1.66x. 

Co-treatment with 10 

mM DMPO during the 

MMAV + BSO treatment 

completely blocked the 

⇑ of caspase 3 activity. 

DMPO effectively 

scavenged cellular 

radical molecules. 

Sakurai et 

al., 2005a 

HeLa cells AsIII ATO 2 Various up 

to 24 hr 

2 

ROS levels were shown 

by DCFH-DA assay to 

be significantly elevated 

by inorganic arsenic and 

to ⇑ roughly 3x higher 

than for inorganic 

arsenic alone following a 

combined inorganic 

arsenic plus 10 μM 

emodin treatment; the 

addition of 1.5 mM NAC 

as a co-treatment 

attenuated (but did not 

completely block) that ⇑

in ROS levels. 

Yi et al., 

2004 

HeLa cells AsIII ATO 2 1 hr 2 

Analysis of GSH/GSSG 

ratios showed that cotreatment of inorganic 

arsenic with emodin had 

a major oxidative impact 

on the cellular redox 

state, as shown by 

following ratios: control, 

∼62; inorganic arsenic, 

∼52; 10 μM emodin, 

∼34; inorganic arsenic 

plus 10 μM emodin, ∼13; 

pretreatment with 1.5 

mM NAC attenuated 

(but did not completely 

block) this effect. 

Yi et al., 

2004 

Jurkat cells 

Namalwa 

cells 

NB4 cells 

U937 cells 

AsIII ATO 

for all 2 

24 hr 

for all 

None 

2 

2 

None 

⇑ in H2O2 levels as 

detected by FACS after 

staining with DCFH-DA: 

large effect seen in 

Namalwa and NB4 cells 

only; NSE in other cell 

lines. 

Chen et al., 

2006 

C-240 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

U937 cells AsIII ATO 1 24 hr None 

⇑ in H2O2 levels as 

detected by FACS after 

staining with DCFH-DA: 

large effect was seen 

only following a cotreatment with BSO for 

24 hr; the ⇑ was 

substantially decreased 

by a 4-hr treatment with 

either 10 mM NAC or 

200 units of catalase. 

Chen et al., 

2006 

 

HEK293 cells AsIII ATO 2 48 hr 2 

Cell survival was 

determined by the WST1 cell proliferation assay: 

inorganic arsenic 

treatment resulted in 

∼22% cell survival; cotreatment with 1 mM 

Tiron or 400 U/mL CAT 

significantly ⇑ cell 

survival although more 

than 60% of the cells still 

died; co-treatment with 

200 U/mL SOD 

markedly ⇓ cell survival. 

 These and other data 

suggested that inorganic 

arsenic induced both 

superoxide anion and 

H2O2 through the 

activation of NAD(P)H 

oxidase. Presence of 

superoxide anion in cells 

that resulted from 

inorganic arsenic 

treatment was confirmed. 

Sasaki et 

al., 2007 

C-241 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

PRCCs 

 HEK293 

cells 

AsIII ATO 

for both 

0.01, 0.05, 0.1, 

0.5, 1, 5, 10, 20 

for both 

48 hr 

for both 

0.5 

0.1 

Cell survival was 

determined by the WST1 cell proliferation assay: 

LC50s in PRCC: 

inorganic arsenic, ∼10; 

co-treatment of inorganic 

arsenic with 10 μM αlipoic acid, ∼25. 

LC50s in HEK293: 

inorganic arsenic, ∼1; cotreatment of inorganic 

arsenic with 10 μM αlipoic acid, ∼7. In both 

cell types, this 

antioxidant markedly 

attenuated inorganic 

arsenic’s cytotoxicity, 

and in HEK293 cells it 

was shown to suppress 

superoxide anion 

generation. 

Sasaki et 

al., 2007 

NB4 cells 

HL60 cells 

KMS12BM 

cells 

U266 cells 

AsIII ATO 

for all 

~0.01, 0.05, 0.1, 

0.5, 1, 2, 5, 10, 50 

for first three 

~0.05, 0.1, 0.6, 

1.2, 6 

48 hr 

for all 

~0.1 

∼5 

∼0.2 

∼0.6 

Cell survival was 

determined by the WST1 cell proliferation assay: 

LC50s: NB4, ∼0.2; HL60, 

∼8; KMS12BM, ∼0.3; 

U266, ∼0.3. In all 4 cell 

lines, co-treatment of 

inorganic arsenic with 10 

μM α-lipoic acid resulted 

in a remarkably similar 

dose-related pattern of 

cell survival to that seen 

with inorganic arsenic 

alone, this being in sharp 

contrast to the 

attenuation of 

cytotoxicity caused by it 

that was seen in PRCCs 

and HEK293 cells. Note 

that the LOEC is higher 

than the estimated LC50

of 0.3 for U266 cells 

because the next lower 

dose of 0.1 had no effect, 

and the LC50 was 

estimated from the doseresponse curve that was 

presented. 

Sasaki et 

al., 2007 

C-242 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

JAR cells AsIII ATO 5 2, 4, 6, 16, 

24 hr 

5 ⇑ in HMOX-1 protein 

level in cytoplasm by 2 

hr, with time-related 

response becoming huge 

by 16 hr. 

Massrieh 

et al., 2006 

JAR cells AsIII ATO 5 6 hr 5 Intracellular H2O2 level 

detected by DCFH-DA 

and flow cytometry 

assay: 

⇑ to 2x. 

Massrieh 

et al., 2006 

BEAS-2B 

cells 

AsIII SA 

1, 2.5, 5 for 

mRNA 

2.5, 5 for protein 

8 hr 

for both 

1 for 

mRNA 

2.5 for 

protein 

 Big ⇑ in HMOX-1 

mRNA level at 1, bigger 

⇑ of the same at 2.5, 

huge ⇑ of the same at 5. 

Big ⇑ in HMOX-1 

protein level at 2.5, huge 

⇑ of the same at 5. 

O’Hara et 

al., 2006 

Undifferentiat

ed PC12 cells 

AsIII ATO 8 Various up to 

6 hr 8 

Detection of ROS shown 

by increase of DCFfluorescence in DCFHDA assay: 

⇑ to ∼2x control for 

several time points 

during first hr; no hint of 

effect at 3–6 hr; 

fluorescence was 

observed before the 

onset of cell death. 

Piga et al., 

2007 

C-243 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

UROtsa cells 

AsIII SA 

MMAIII

1, 10, 100 

0.05, 0.5, 5 

10 min 

50 min 

1 

0.05 

Detection of ROS using 

CM-H2DCFDA assay: 

Slight ⇑ at 1, big ⇑ at 10, 

huge ⇑ at 100. When 

quantified at dose of 10 

over 10 min: 20 RFU by 

4.5 min, 110 RFU by 10 

min. Pretreatment with 

PEG-SOD or PEG-CAT 

blocked most ROS 

production. 

⇑ at 0.05, huge ⇑ at 0.5, 

slightly weaker response 

at dose of 5 than at dose 

of 0.05. When 

quantified at dose of 0.5 

over 10 min: 0 RFU. 

When quantified at dose 

of 0.5 over 50 min: 10 

RFU by 42 min, 65 RFU 

by 50 min. Pretreatment 

with PEG-CAT blocked 

most ROS production, 

and co-treatment with 

PEG-SOD blocked some 

ROS production; less 

effect for both than for 

inorganic arsenicIII, 

suggesting a difference 

in the ROS they produce. 

Eblin et 

al., 2006 

Humanhamster 

hybrid AL

cells 

AsIII SA 

For both 

7.7 60 days 7.7 

Effects related to 

mitochondria: 

fluorescence microscopy 

showed that arsenic 

treatment led to 

considerable variation in 

the distribution of 

mitochondria between 

cells and caused the 

fraction of them with 

elongated morphology to 

increase from 6% to 

66%; ∼50% ⇓ in COX 

activity; ∼40% ⇓ in 

oxygen consumption; 

∼40% ⇑ in citrate 

synthase activity. 

Partridge 

et al., 2007 

C-244 DRAFT—DO NOT CITE OR QUOTE
Type of 

Cell/Tissue 

Arsenic 

Species 

Concentration(s) 

Tested (μM) 

Duration of 

Treatment 

LOECa 

(μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Humanhamster 

hybrid AL

cells 

AsIII SA 

for both 

1.9, 3.8, 7.7 

1.9, 3.8, 7.7 

60 days 

1 day 

3.8 for 

copy # 

1.9 for 

deletions 

mtDNA copy number: ⇓

to ~0.84x at 3.8; ⇓ to 

~0.65x at 7.7. 

SA induced large 

heteroplasmic deletions 

in mitochondrial DNA, 

and the frequencies of 

induction increased with 

dose and time of 

exposure. 

Partridge 

et al., 

2007 

Splenic 

lymphocytes 

from 

Sod1tm1Leb

knockout 

mice 

AsIII SA 50, 100, 200 2 hr 50 

Breaks and/or alkalilabile lesions in DNA 

detected in the singlecell gel (comet) assay: 

big ⇑ in effect in the 

SOD -/- mice, which 

were also shown to have 

big ⇓ in levels of SOD in 

spleens (and also in 

livers and kidneys). 

SOD +/- mice were 

intermediate in SOD 

levels and DNA damage. 

 Results suggest ROS 

may be involved in AsIIIinduced DNA damage. 

Kligerman 

and 

Tennant, 

2007 

Lyophilized 

bovine tubulin 

DMAIII 50 

Time course 

over 1 hr 50 

Big ⇓ in GTP-induced 

polymerization of 

lyophilized bovine 

tubulin. 

Effects of modulators: 

NAC blocked the 

inhibition by DMAIII, 

while AA, CAT, DMSO, 

Tiron, or Trolox® had 

NSE on it, which 

suggests that ROS is not 

involved in the 

inhibition. Premixing of 

inorganic arsenicV, 

MMAV, or DMAV for 2 hr 

with a 5-fold molar 

excess of GSH greatly 

decreased the 

polymerization of tubulin 

(i.e., increased the 

inhibition). 

Kligerman 

and 

Tennant, 

2007 

C-245 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

W138 cells 

and HaCaT 

cells 

AsIII SA 0.5 24 hr 0.5 

ROS (peroxide) levels 

based on DCF assay:⇓ in 

both cell lines compared 

to control, and less in 

W138 than in HaCaT. 

The average activities of 

3 important intracellular 

redox agents, GSH, GR, 

and GST are ~3X higher 

in WI38 cells than in 

HaCaT cells. After the 

inorganic arsenic 

treatment, there was a 

60-min menadione 

treatment followed by a 

60-min recovery period. 

During this 120 min, 

ROS levels in W138 

cells never reached 

control levels, while the 

control level was 

substantially exceeded in 

HaCaT cells after 60 min 

of the menadione 

treatment and later. 

Snow et 

al., 2005 

C-246 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

NB4 cells 

HL-60 cells 

AsIII SA 

for all 

2 for all assays, 

which tested 

effects of various 

co-treatments 

described in 

Results column 

4 hr 

 for all 

— 

— 

This row relates only to 

the effects seen after cotreatments in an attempt 

to learn how SA causes 

DNA damage. They 

assayed DNA strand 

breaks (ADSB) detected 

using the comet assay. 

In the absence of a cotreatment, a significant 

increase would be 

expected with a dose of 

only 0.25. Conclusions 

always were supported 

by data on ODA and 

DPC individually. 

Chemicals used 

individually in cotreatments were: 

catalase, calcium 

chelators, and inhibitors 

of nitric oxide synthase, 

SOD, and 

myeloperoxidase. On 

the basis of the large 

reduction in DNA strand 

breaks seen following 

the co-treatments, they 

concluded that arsenite 

induces DNA adducts 

through calciummediated production of 

peroxynitrite, 

hypochlorous acid, and 

hydroxyl radicals. 

Wang et 

al., 2001 

PAEC cells 

isolated from 

freshly 

harvested 

vessels 

AsIII SA 5 Up to 20 min 5 

⇑ oxygen consumption 

associated with ⇑

superoxide (O2

-

) 

formation; 

⇑ extracellular 

accumulation of H2O2, 

with same time and dose 

dependence as 

superoxide formation. 

Pretreatment of the cells 

with DPI, apocynin, or 

SOD abolished arsenitestimulated superoxide 

(O2

-

) formation. 

Barchowsk

y et al., 

1999b 

CHO K1 cells AsIII SA 20, 40, 80, 160 4 hr 40 ⇑ intracellular peroxide 

level (strong hint of same 

effect at dose of 20) 

Wang et 

al., 1996 

C-247 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

φX174 RF I 

DNA 

Naked 

doublestranded 

circular DNA 

in presence of 

ROS 

inhibitors 

MMAIII

DMAIII

10, 20, 30, 40, 50 

37.5, 75, 150, 300, 

1000 

24 hr 

for all 

— 

— 

This row relates only to 

the effects seen after cotreatments in an attempt 

to learn how SA causes 

DNA damage. 

Significant (and usually 

complete) reduction in 

nicked DNA (in DNA 

nicking assay) was found 

when ROS inhibitors 

Trolox, melatonin, or 

Tiron were present 

individually during the 

arsenic treatment. Spin 

trap agent DMPO was 

also effective in 

preventing DNA nicking 

by these compounds. 

Thus, production of ROS 

by these chemicals is 

associated with their 

DNA-cutting activity. 

Genotoxicity is an 

indirect effect via the 

generation of ROS. 

Nesnow et 

al., 2002 

Both 

HL-60 cells 

and 

HaCaT cells 

AsIII SA 0.1, 0.5, 1, 10, 20, 

40 

5 days 0.5 but 

possibly 

0.1 

By use of MTT assay, in 

presence of 2.5 mM 

DMPO: ⇑ in cell 

number, with peak at 0.5 

(DMPO has no effect); ⇓

in cell number to below 

control level at 1 for HL60 and at 10 for HaCaT, 

and DMPO significantly 

lessens reduction in cell 

number at ≥10 (possibly 

1) for HL-60 and at ≥20 

(possibly 10) for HaCaT. 

Zhang et 

al., 2003 

HL-60 cells AsIII SA 10 3 days — 

Analysis of TRF using 

Southern blot assay in 

presence of 2.5 mM 

DMPO: 

With DMPO present, 

telomere length was 

longer than it was with 

arsenic alone; interpreted 

to mean that DMPO 

provided some protection 

against arsenic-induced 

telomere shortening. 

Zhang et 

al., 2003 

C-248 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HL-60 cells 

HaCaT cells

AsIII SA 

for both 

0.1, 0.5, 1, 10, 20, 

40 for both 

5 days 

for both 

1 but 

possibly 

0.5 

10 

By use of Hoechst/PI 

staining assay, in 

presence of 2.5 mM 

DMPO: 

⇑ in apoptosis for both; 

however, DMPO 

significantly reduced the 

amount of apoptosis at 

≥1 for HL-60 and at ≥10 

for HaCaT. 

Zhang et 

al., 2003 

Enzyme Activity Inhibition 

AG06 cells 

were 

pretreated for 

24 hr with 

unspecified 

low dose of 

As, and then 

extracts of the 

cells were 

tested for 

activity of: 

GSH 

peroxidase 

and 

ligase 

AsIII SA IC50

determinations 

Rate over 6 

min — 

IC50s: 

2.0 (was 0.13 mM for 

purified enzyme with no 

arsenic pretreatment) 

14.5 (was 6.5 mM with 

no arsenic pretreatment). 

The same paper 

presented the IC50sfor a 

similar treatment with 

AsV for GSH peroxidase, 

and it was 173 μM. The 

paper also presented 

IC50s for numerous 

purified enzymes with 

both SA and AsV, but 

they were almost all far 

above a physiologically 

interesting range and are 

thus not presented here. 

Most were in the range 

of 6.3 to 381 mM for SA 

and usually even higher 

for AsV. 

Snow et 

al., 1999 

Cell-free 

system using 

purified 

human 

enzymes 

AsIII SA 

AsV

IC50

determinations 

Rate of 

reaction over 6 

min 

— 

Inhibition of PDH: IC50s: 

5.6 μM for inorganic 

arsenicIII, 206 mM for 

AsV; 

7 other enzymes 

involved in aspects of 

DNA repair and/or 

cellular stress response 

had IC50s for AsIII of 6.3–

381mM. Only PDH, 

with its lipoic acid 

cofactor, was inhibited 

by physiologically 

relevant, micromolar 

concentrations of AsIII. 

Hu et al., 

1998 

C-249 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Cell-free 

system using 

purified 

human 

enzymes 

AsIII SA 

AsV

~0.0007, 0.001, 

0.007, 0.01, 0.07, 

0.1 

~0.01, 0.07, 0.1, 1, 

10, 25, 75, 100, 

125 

Rate of 

reaction over 1 

min 

~0.001 

~25 

Inhibition of PDH. Hu et al., 

1998 

Cell-free 

system using 

purified 

porcine heart 

PDH 

AsIII SA 

 MMAIII

25, 75, 100, 200 

(all approximate) 

8, 16, 30, 50, 100 

30 min 

for both 

∼25 

∼8 

Inhibition of PDH 

(IC50s): 

106.1. 

17.6. 

Petrick et 

al., 2001 

Cell-free 

system using 

hamster 

kidney PDH 

AsIII SA 

 MMAIII

∼20 to ∼400 

∼20 to ∼400 

30 min 

for both 

— 

Inhibition of PDH 

(IC50s): 

115.7. 

61.0. 

Petrick et 

al., 2001 

Gene Amplification

Mouse 3T6 

cells 

AsIII SA 

AsV

0.2, 0.4, 0.8, 1.6, 

3.2, 6.4 

1, 2, 4, 8, 16 

Not reported 

0.4 

2 

Gene amplification of 

dhfr gene detected by 

MTX-selection assay: 

Both compounds showed 

positive dose-response 

extending to highest 

concentrations tested. 

Barrett et 

al., 1989 

AG06 cells AsIII SA 7, 10, 17, 20 3.5 hr None Amplification of SV40: 

none observed at 

concentrations causing 

from 40% to 98% 

cytotoxicity. 

Rossman 

and 

Wolosin, 

1992 

AG06 cells AsIII SA 6 

Assay’s 

maximal 

response time 

6 

Amplification of 

endogenous dhfr genes 

(determined by MTXselection assay): highly 

effective at this 

concentration, which 

caused 50% survival. 

“Amplification factor” 

was ∼3 even though it 

was 1 (i.e., no induction) 

for same concentration 

for amplification of 

SV40. 

Rossman 

and 

Wolosin, 

1992 

Human 

osteosarcoma 

TE85 (HOS) 

cells 

AsIII SA 0.0125, 0.025, 

0.05, 0.1 for both 

durations 

6 wk 

8 wk 

0.025 

0.0125 

Amplification of 

endogenous dhfr genes 

(determined by MTXselection assay): doseresponse was the same 

for both durations 

beginning with 0.025; it 

increased with dose to 

0.05 and then plateaued. 

Mure et 

al., 2003 

C-250 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

SHE cells 

AsIII SA 

AsV

6, 8 

50, 100, 150 

48 hr 

for both 

6 

50 

From among these 

treatment groups, 5 

neoplastic transformed 

cell lines were produced 

that were shown to be 

tumorigenic. Of these: 3 

had c-Ha-ras (oncogene) 

gene amplification; 2 had 

c-myc (oncogene) gene 

amplification; 

a few other arsenictreated cell lines also 

showed this same gene 

amplification. 

Takahashi 

et al., 2002 

Gene Mutations 

E. coli 

(several 

strains) 

AsIII SA Up to 25 mM Various None Several assays (spot 

tests, treat and plate 

protocols, and 

fluctuation tests) for Trp+

revertants yielded no 

evidence of induction of 

gene mutations. Also, 

there was no induction of 

λ prophage. 

Rossman 

et al., 1980 

V79 cells AsIII SA 

0.5 

5, 20, 100 

2 days 

Up to 1.5 hr 

None 

None 

In several assays, 

ouabain resistance and 

thioguanine resistance 

were used as genetic 

markers. No evidence 

was found of induction 

of gene mutations. Only 

the dose of 100 caused 

cytotoxicity (33.1% the 

survival of the control). 

Rossman 

et al., 1980 

G12 cells AsIII SA 

5, 10, 15 

10, 25, 50 

24 hr 

3 hr 

None 

None 

No statistically 

significant induction of 

mutations at the gpt

locus in an assay that can 

detect multilocus 

deletions, point 

mutations, and small 

deletions (tested up to 

cytotoxicity of 61.9% of 

cells killed). 

Li and 

Rossman, 

1989a 

C-251 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Salmonella 

typhimurium

strains TA98, 

TA100, 

TA104 

AsIII SA 

AsV

MMAIII

MMAV

DMAIII

DMAV

Tested up to 

concentrations 

limited by 

cytotoxicity or to 

the limit 

concentration for 

the assay 

3 days 

for all 

None 

Salmonella mutagenicity 

plate incorporation assay 

with and without 

exogenous metabolic 

activation: 

There was no indication 

of any induction of gene 

mutations over 

background levels by 

any of the compounds. 

Kligerman 

et al., 2003 

Syrian 

hamster 

embryo cells 

AsIII SA 

AsV

∼0.8, 1.6, 3, 3.5, 5 

∼8, 16, 32, 64, 128 

Not reported 

None 

None 

Gene mutation assays for 

the Na+

/K+ ATPase and 

HPRT loci. 

Barrett et 

al., 1989 

Human 

osteosarcoma 

TE85 (HOS) 

cells 

AsIII SA 

MMAIII

0.0125, 0.025, 

0.05, 0.1 

0.00625, 0.0125, 

0.025, 0.05 

8 wk for all 

0.0125 

None 

Mutations in the HPRT 

gene: positive doseresponse to highest 

concentration for AsIII; 

no increase until almost 

15 generations of 

continuous exposure. 

Mure et 

al., 2003 

TM3 cells AsIII SA 

for both 

0.008, 0.77, 7.7 

for both 

∼25 days 

∼75 days 

0.008 

0.008 

Detection of DNA 

changes by RAPD-PCR: 

gain or loss of loci and 

changes in the intensity 

of loci were detected at 

the DNA sequence level; 

although the nature of 

the “mutations” and 

whether they were actual 

gene mutations is 

unknown. 

Singh and 

DuMond, 

2007 

C-252 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Hypermethylation of DNA

Human 

kidney 

carcinoma 

cell lines: 

UOK123 

UOK109 

Human lung 

carcinoma 

cell line: 

A549 

AsIII SA 

for all 

0.010, 0.020, 

0.050 

0.007, 0.021, 

0.093 

0.08, 0.4, 2.0 

4 wk 

4 wk 

2 wk 

≤0.050 

≤0.093 

≤2.0 

The number of specific 

DNA sequences shown 

to undergo 

hypermethylation 

changes by methylation 

sensitive AP-PCR 

following exposure to 

SA: 

1 from line UOK123, 4 

from line UOK 109, and 

1 from line A549. 

The concentrations used 

to treat these lines were 

known to be the IC30, 

IC50, and IC80

concentrations for UOK 

cells and the IC20, IC50, 

and IC80 concentrations 

for A549 cells. It was 

not reported which 

concentrations yielded 

the hypermethylation 

changes, but the LOECs 

could not be higher than 

the maximum 

concentration used for 

each cell line. 

Zhong and 

Mass, 

2001 

A549 cells 

(human 

adenocarcino

ma) 

AsIII SA 

AsV

DMAV

0.08, 0.4, 2.0 

3, 10, 30, 100, 300 

2, 20, 200, 2000 

7 days for all 

0.08 

30 

None 

Hypermethylation within 

a 341-base-pair fragment 

of the promoter of p53. 

For the two inorganic 

forms, there was a 

positive dose-response 

throughout the range of 

concentrations tested. 

Mass and 

Wang, 

1997 

Hypomethylation of DNA 

TRL 1215 

cells (normal 

rat liver) 

AsIII SA 0.125, 0.250, 

0.500 

19 wk 0.125 

Global DNA 

hypomethylation, 

thought to be caused by 

continuous methyl 

depletion. 

Zhao et al., 

1997 

C-253 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Human 

kidney 

carcinoma 

cell line: 

UOK121 

Human lung 

carcinoma 

cell line: 

A549 

AsIII SA 

for all 

0.009, 0.020, 

0.074 

0.08, 0.4, 2.0 

4 wk 

2 wk 

≤0.074 

≤2.0 

The number of specific 

DNA sequences shown 

to undergo 

hypomethylation 

changes by methylation 

sensitive AP-PCR 

following exposure to 

SA: 

1 from line UOK121 and 

1 from line A549. 

The concentrations used 

to treat these lines were 

known to be the IC30, 

IC50, and IC80

concentrations for 

UOK121 cells and the 

IC20, IC50, and IC80

concentrations for A549 

cells. It was not reported 

which concentrations 

yielded the 

hypermethylation 

changes, but the LOECs 

could not be higher than 

the maximum 

concentration used for 

each cell line. 

Zhong and 

Mass, 

2001 

Untransforme

d and 

immortalized 

RWPE-1 cells 

(human 

prostate 

epithelial cell 

line) 

AsIII SA 5 30 wk 5 

Global hypomethylation 

of DNA (up to 131% 

increase in unmethylated 

DNA compared to the 

control); 

hypomethylation still 

present 6 weeks after end 

of exposure. The cells 

became tumorigenic after 

29 weeks of treatment 

and were then called the 

CAsE-PE cell line. 

Benbrahim

-Tallaa et 

al., 2005 

C-254 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

SHE cells 

AsIII SA 

AsV

6, 8 

50, 100, 150 

48 hr 

for both 

— 

From among these 

treatment groups, 5 

neoplastic transformed 

cell lines were produced 

that were shown to be 

tumorigenic. Testing of 

them using the 

methylation-sensitive 

restriction endonuclease 

isoschizomers HpaII and 

MspI revealed 

hypomethylation of cmyc and c-Ha-ras in the 

5'-CCGG sequence. 

Both of these oncogenes 

were often shown to 

exhibit gene 

amplification and 

⇑ mRNA expression. 

Takahashi 

et al., 2002 

TM3 cells 

AsIII SA 

for both 

0.008, 0.77, 7.7 

for both 

∼25 days 

∼75 days 

0.008 

0.008 

Detection of methylation 

changes in DNA by 

RAPD-PCR using 

methylation-sensitive 

restriction endonuclease 

isoschizomers HpaII and 

MspI: methylation 

changes were detected at 

18 loci, with some 

showing 

hypomethylation and 

others hypermethylation. 

 Some loci were only 

affected by the shorterterm exposure, and viceversa. 

Singh and 

DuMond, 

2007 

HaCaT cells AsIII SA 0.2 

For 10 serial 

passages in 

folic-aciddepleted media 

0.2 

Genomic 

hypomethylation as 

demonstrated by a 27% 

⇓ in the level of 

5-methyl-dCMP 

compared with cells 

cultured for the same 

number of passages in 

medium without AsIII. 

This dose was too low to 

have much, if any, effect 

on the proliferation rate. 

Reichard 

et al., 2007 

C-255 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HaCaT cells AsIII SA 0.5, 1.5, 5 72 hr Various 

⇓ DNMT1 mRNA at 0.5, 

and progressively larger 

decreases at 2 higher 

doses; 

⇓ DNMT3A mRNA at 

1.5, and larger ⇓ at dose 

of 5. These cells did not 

show any detectable 

quantities of the other 2 

mammalian DNA 

methyltransferases. 

Big ⇑ HMOX-1 RNA at 

1.5 with very big ⇑ at 5. 

Reichard 

et al., 2007 

Immune System Response 

(Human 

myeloma-like 

cell lines) 

RPMI 8226 

Karpas 707 

U266 

AsIII ATO 

0.5, 1, 2 72 hr 0.5 

Induction of cell lysis by 

LAK effector cells was 

apparent by 36 hours and 

maximal at 72 hours. 

The extent of lysis was 

determined by the 51Cr 

release assay. At these 

concentrations, arsenic 

trioxide had no effect on 

viability (using trypanblue assay) or apoptosis. 

Deaglio et 

al., 2001 

HPBMs coexposed to 

M-CSF 

AsIII SA 

AsV

MMAV

DMAV

IC50 

determinations 

7 days — 

Viability of M-type 

macrophages based on 

AB assay was used to 

estimate the arsenic 

concentration at which 

maturation into M-type 

macrophages was 

inhibited by 50%: IC50

values: AsIII, 0.06; AsV, 

200; 

MMAV, 750; DMAV, 300. 

Sakurai et 

al., 2006 

HPBMs coexposed to 

GM-CSF 

AsIII SA 

AsV

MMAV

DMAV

IC50 

determinations 

7 days — 

Viability of GM-type 

macrophages based on 

AB assay was used to 

estimate the arsenic 

concentration at which 

maturation into GM-type 

macrophages was 

inhibited by 50%: IC50

values: AsIII, 0.38; AsV, 

300; 

MMAV, 700; DMAV, 550. 

Sakurai et 

al., 2006 

C-256 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HPBMs coexposed to 

GM-CSF and 

IL-4 

AsIII SA IC50 determination 7 days — Viability of immature 

dendritic cells based on 

AB assay was used to 

estimate the arsenic 

concentration at which 

maturation into immature 

dendritic cells was 

inhibited by 50%: IC50

value: 0.70. 

Sakurai et 

al., 2006 

HPBMs coexposed to 

GM-CSF and 

IL-4 

AsIII SA IC50 determination 14 days — Viability of 

multinucleated giant 

cells based on AB assay 

was used to estimate the 

arsenic concentration at 

which maturation into 

multinucleated giant 

cells was inhibited by 

50%: IC50 value: 0.33. 

Sakurai et 

al., 2006 

HPBMs coexposed to 

GM-CSF 

AsIII SA 

With regard to 4 rows immediately above this one, SA at doses of 0.05 to 0.5 

induced abnormal morphological changes in the HPBMs to form small 

nonadhesive and CD14-positive cells called arsenite-induced cells that 

displayed a dendritic morphology with delicate membrane projections. This 

response was not produced by treatments with many other metallic 

compounds (e.g., chromium, mercury, and zinc) including inorganic arsenicV, 

MMAV and DMAV. This effect was not seen at doses exceeding 1. 

Sakurai et 

al., 2006 

HPBMs coexposed to 

GM-CSF 

AsIII SA 0.5 7 days 0.5 

In comparison to the 

cells not treated with 

inorganic arsenic, there 

was 43.3% less 

metabolic activity, 0.6% 

as much adherent ability, 

a 76% higher cellular 

GSH concentration, 

256% as much NO2

–

production, 185% as 

much IL-1α production 

in the supernatant, 412% 

as much IL-1α

production in the lysate, 

and 576 ng/g cellular 

protein of IL-12 in the 

lysate even though none 

was detected in arsenicuntreated cells. 

Sakurai et 

al., 2006 

HUVECs AsIII SA 0.5 3 hr 0.5 

Both HUVECs and 

PMNs were pretreated 

for 24 hr with GLN 

(glutamine) at 0, 300, 

600, or 1000 μM. Those 

HUVECs were then 

exposed to the same 

concentration of GLN 

with or without the 

Hou et al., 

2005 

C-257 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

inorganic arsenic 

treatment for 3 hr. The 

pretreated PMNs were 

added to wells and 

allowed to migrate 

across the pretreated 

HUVECs for 2 hr, after 

which surface 

expressions on HUVECs 

of ICAM-1 and VCAM1 were measured, with 

the following results: 

ICAM-1: ⇑ in inorganic 

arsenic only group and 

huge ⇑ at all 3 dose 

levels of GLN; VCAM1: NSE in inorganic 

arsenic only group and ⇑

at all 3 dose levels of 

GLN, with largest ⇑ at 

300 μM. Clearly 

HUVECs were activated 

by inorganic arsenic. 

Also at this time, PMN 

expressions of CD11b 

and IL-8 receptor were 

measured, with the 

following results: CD11-

b: ⇑ in inorganic arsenic 

only group and bigger ⇑

at all 3 dose levels of 

GLN; IL-8 receptor: ⇑ in 

inorganic arsenic only 

group and at all 3 dose 

levels of GLN. Clearly 

PMNs were activated by 

the inorganic arsenic 

treatment of the 

HUVECs. 

Effects on PMN 

migration: 

In absence of GLN 

pretreatment, inorganic 

arsenic caused slight ⇓

from 36% to 30% 

migrated. In the 

inorganic arsenic + 300 

μM GLN group: ⇑ from 

∼40% (for GLN alone) to 

∼50% migrated (for 

inorganic arsenic + 

GLN), which was the 

most migration observed. 

C-258 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

PBMCs cotreated 

with GM-CSF 

AsIII ATO 0.125, 0.25, 0.5, 1, 

2 

6 days 0.125 

Induced apoptosis (i.e., 

experimental – control) 

detected using A5/SG 

assays: approximate 

induced frequencies at 

the 5 doses: 6%, 20%, 

29%, 48%, and 62%, 

respectively, with all 

being statistically 

significant except first 

one. Ιnduced frequency 

of necrotic cells was 

~20% at the highest 

dose, and there were 

smaller numbers of 

necrotic cells induced at 

the lower doses. 

 After dose of 1 for 3 

days: ⇑ caspase-3 

activity, ⇑ caspase-8 

activity, big ⇑ in active 

caspase-3 subunit p17. 

ATO was shown to 

reduce DNA binding of 

the transcriptionally 

active p65 NF-κB 

subunit to the κB 

consensus sites in GMCSF treated PBMCs, 

which was thought to be 

important in 

development of 

apoptosis. Other 

experiments showed that 

ATO inhibited 

macrophagic 

differentiation of 

PBMCs. 

Lemarie et 

al., 2006a 

PBMCs cotreated 

with M-CSF 

AsIII ATO 1 6 days 1 Induced apoptosis (i.e., 

experimental – control) 

detected using A5/SG 

assays: 

~44%. The induced 

frequency of necrotic 

cells was ~23%. 

Lemarie et 

al., 2006a 

C-259 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

U937 cells 

co-treated 

with PMA 

AsIII ATO 1, 4 4 days 4 

Induced apoptosis (i.e., 

experimental – control) 

detected using A5/SG 

assays: approximate 

induced frequencies at 

the 2 doses: 3% and 

35%, respectively, with 

the higher one being 

statistically significant. 

Ιnduced frequency of 

necrotic cells was ~9% at 

the highest dose. Other 

experiments showed (1) 

that ATO induced 

apoptosis through 

inhibition of NF-κB 

signals and (2) that ATO 

inhibited macrophagic 

differentiation of U937 

cells. 

Lemarie et 

al., 2006a 

U937 cells 

co-treated 

with PMA 

AsIII ATO 4 4 days 4 ⇓ FLIPL protein level, ⇓

XIAP protein level. 

Lemarie et 

al., 2006a 

PBMCs cotreated 

with GM-CSF 

AsIII ATO 1 3 days 1 ⇓ FLIPL protein level 

and ⇓ FLIPL mRNA 

level; 

⇓ XIAP protein level and 

⇓ XIAP mRNA level. 

Lemarie et 

al., 2006a 

Differentiated 

macrophages 

developed 

from PBMCs 

treated with 

GM-CSF 

for 6 days 

before 

inorganic 

arsenic 

treatment 

AsIII ATO 

1, 4 

1, 4 

3 days 

6 days 

4 

4 

Induced apoptosis (i.e., 

experimental – control) 

detected using A5/SG 

assays: 

No induced apoptosis at 

dose of 1 at either time. 

At dose of 4: ∼22% and 

∼50% after 3 and 6 days, 

respectively; thus these 

cells are resistant to 

induction of apoptosis by 

ATO at low doses. 

Lemarie et 

al., 2006a 

Differentiated 

macrophages 

developed 

from PBMCs 

treated with 

GM-CSF for 

6 days before 

inorganic 

arsenic 

treatment 

AsIII ATO 1 6 days None for 

⇓

NSE regarding FLIPL

protein level; 

big ⇑ XIAP protein 

level. 

Lemarie et 

al., 2006a 

C-260 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Differentiated 

macrophages 

developed 

from PBMCs 

treated with 

GM-CSF for 

6 days before 

inorganic 

arsenic 

treatment 

AsIII ATO 4 3 4 Big ⇓ FLIPL protein 

level; big ⇓ XIAP 

protein level. 

Lemarie et 

al., 2006a 

Differentiated 

macrophages 

developed 

from PBMCs 

treated with 

GM-CSF 

for 6 days 

before 

inorganic 

arsenic 

treatment 

AsIII ATO 0.25, 0.5, 1 6 days 0.25 

Major alterations in the 

morphology, adhesion, 

and actin organization 

with the impression that 

inorganic arsenic “dedifferentiated” 

macrophages back into 

monocytic cells. The 

effect was timedependent with rounded 

and contracted 

morphology first 

observed at dose of 1 

after only 8 hr. By 6 

days at dose of 1 only 

31% as many cells were 

adherent as in control. 

Inorganic arsenic 

induced a reorganization 

of the F-actin 

cytoskeleton. The series 

of experiments suggested 

that the effects occurred 

because of the activation 

of a RhoA/ROCK 

pathway. 

Lemarie et 

al., 2006b 

Differentiated 

macrophages 

developed 

from PBMCs 

treated with 

GM-CSF 

for 6 days 

before 

inorganic 

arsenic 

treatment 

AsIII ATO 0.5, 1, 2, 4 6 days 2 

Induced apoptosis (i.e., 

experimental – control) 

detected using A5/SG 

assays: approximate 

induced frequencies at 

the 4 doses: 0%, 0%, 

20%, and 50%, 

respectively. Ιnduced 

frequency of necrotic 

cells was ~4% at the 

highest dose. 

18 days of treatment at 

dose of 1 caused no 

cytotoxicity. 

Lemarie et 

al., 2006b 

C-261 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Differentiated 

macrophages 

developed 

from PBMCs 

treated with 

GM-CSF 

for 6 days 

before 

inorganic 

arsenic 

treatment 

AsIII ATO 1 6 days 1 

Changes in surface 

markers: CD14: ⇑ 5.1x; 

CD71: ⇓ to 45% of 

control; 

CD29: ⇓ to 49% of 

control; CD11b: ⇓ to 

42% of control. 

Changes in major 

functions: marked ⇓ in 

endocytosis and 

phagocytosis. Changes 

in surface markers and 

morphology were shown 

to be reversible when 

inorganic arsenic was 

removed and cells were 

cultured with GM-CSF 

for 6 days. 

Lemarie et 

al., 2006b 

Differentiated 

macrophages 

developed 

from PBMCs 

treated with 

GM-CSF 

for 6 days 

before 

inorganic 

arsenic 

treatment 

AsIII ATO 1 6 days 1 

Ability to secrete 

inflammatory cytokines 

in response to cotreatment of inorganic 

arsenic (dose of 1) and 

200 ng/mL LPS for 8 or 

24 hr 

(control = macrophages 

treated with LPS only): 

TNF-α secretion: ⇑

∼3.0x and ∼3.0x at 8 and 

24 hr, respectively. 

IL-8 secretion: ⇑ ∼3x 

and ∼4.5x at 8 and 24 hr, 

respectively. 

Much more extreme 

potentiation was 

demonstrated for both 

cytokines at the mRNA 

level at 8 hr. The text 

implies that the 

potentiation of both 

secretion and mRNA 

production does not 

occur without the 

6-day inorganic arsenic 

treatment. 

Lemarie et 

al., 2006b 

C-262 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Differentiated 

macrophages 

developed 

from PBMCs 

treated with 

GM-CSF 

for 6 days 

before 

inorganic 

arsenic 

treatment 

AsIII ATO 1 6 days 1 

The inorganic arsenictreated macrophages 

differentiated into 

dendritic-like cells when 

exposed to GM-CSF and 

IL-4 in the absence of 

inorganic arsenic for 6 

days. This conclusion 

was based on the ∼9x 

increase in the 

expression of the typical 

dendritic marker CD1a. 

The increase was similar 

to that seen in PBMCs 

treated with GM-CSF 

and IL-4 for 6 days, and 

in both cases the 

dendritic-like cells were 

nonadherent. In contrast, 

fully differentiated 

macrophages (i.e., 

PBMCs treated with 

GM-CSF for 6 days 

without inorganic 

arsenic) did not show 

this response. 

Lemarie et 

al., 2006b 

Differentiated 

macrophages 

developed 

from PBMCs 

treated with 

GM-CSF 

for 6 days 

before 

inorganic 

arsenic 

treatment 

AsIII ATO 1 8 hr 1 

⇑ GTP-binding fraction 

of RhoA; 

⇑ phospho-Moesin 

protein level. 

(Phosphorylated-Moesin 

is a major cytoskeleton 

adaptor protein involved 

in RhoA regulation. 

RhoA is a small GTPase

protein known to 

regulate the actin

cytoskeleton in the 

formation of stress 

fibers.) 

Lemarie et 

al., 2006b 

C-263 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Differentiated 

macrophages 

developed 

from PBMCs 

treated with 

GM-CSF 

for 6 days and 

then 

pretreated 

with ROCK 

inhibitor Y27632 for 2 hr 

before 

inorganic 

arsenic 

treatment 

AsIII ATO 1 72 hr 1 

Pretreatment with the 

ROCK inhibitor 

prevented both the Factin reorganization and 

cellular rounding of 

macrophages treated 

with inorganic arsenic. 

It also considerably 

blunted damage to the 

phagocytosis function 

caused by the inorganic 

arsenic treatment. 

Lemarie et 

al., 2006b 

HepG2 cells AsIII SA 0.04, 0.4, 4, 40 

48-hr 

pretreatment 4 

After the inorganic 

arsenic pretreatment, 

there was a 30-min 

treatment with IL-6, 

which induced STAT3 

activity unless inhibited 

by the pretreatment. 

Level of STAT3 activity: 

huge ⇓ at 4; no activity 

at 40. 

Cheng et 

al., 2004 

C-264 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HepG2 cells AsIII SA 0.04, 0.4, 4, 40, 

400 

48-hr 

pretreatment 40 

After the inorganic 

arsenic pretreatment, 

there was a 30-min 

treatment with IL-6, 

which induced both 

STAT3 tyrosine 

phosphorylation and 

STAT3 serine 

phosphorylation. Only 

the tyrosine 

phosphorylation was 

inhibited by the 

inorganic arsenic 

pretreatment, with slight 

⇓ at 40 and huge ⇓ at 

400. Inorganic arsenic is 

thought to inactivate the 

JAK-STAT signaling 

pathway by means of 

inhibition of STAT3 

tyrosine phosphorylation. 

 Other inflammatory 

stimulants, stress agents, 

and cadmium failed to 

induce similar effects on 

the tyrosine 

phosphorylation of 

STAT3. 

Cheng et 

al., 2004 

C-265 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

HepG2 cells AsIII SA 4, 40, 400 

30-min 

pretreatment 

and 1-hr 

co-treatment 

with IL-6 

4 

Huge ⇓ in Cis mRNA 

and in SOCS mRNAs for 

5 of 6 forms tested (⇓ for 

the other form); the ⇓ at 

higher doses was usually 

the same or more severe; 

⇓ in STAT mRNAs for 4 

of 6 forms tested, the ⇓

at higher doses was 

usually the same or more 

severe. The decreases 

for STAT mRNAs were 

very slight compared to 

those for SOCS. The 

inhibition of induction of 

SOCS mRNA confirmed 

that JAK-STAT 

signaling had been 

turned off. Other 

experiments showed that 

the effect of inorganic 

arsenic on JAK-STAT 

inactivation is 

independent of ligandreceptor action and is a 

result of the direct action 

of arsenic on the JAK1 

protein. 

Cheng et 

al., 2004 

HepG2 cells AsIII SA 0.04, 0.4, 4, 40, 

400 

inorganic arsenic (in co-treatment with IL-6 for 

unknown duration) activated all 3 subfamilies of MAP 

kinases (i.e., there was phosphorylation of ERK 1/2, 

p38, and JNKs) with LOECs of 40, 0.04, and 0.04 

respectively. Such activation was independent of IL-6 

stimulation at least at higher doses. Experiments with 

specific inhibitors of the 3 MAP kinases showed that 

inorganic arsenic selectively targeted JAK tyrosine 

kinase and that the inhibition of JAK-STAT activity by 

inorganic arsenic did not require the participation of any 

MAP kinases. 

Cheng et 

al., 2004 

PBMCs 

treated with 

1000 U/mL of 

M-CSF at the 

same time as 

with inorganic 

arsenic 

AsIII SA 0.005, 0.010, 

0.050, 0.10, 0.50 

7 days 0.050 

Cell survival 

demonstrated by trypan 

blue exclusion assay: 

LC50: 0.22; about 25% 

survival at dose of 0.5. 

The cells differentiated 

into adhesive M-type 

macrophages that were 

elongated and had a 

spindle-like morphology. 

Sakurai et 

al., 2005b 

C-266 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

PBMCs 

treated with 

5000 U/mL of 

GM-CSF at 

the same time 

as with 

inorganic 

arsenic 

AsIII SA 0.005, 0.010, 

0.050, 0.10, 0.50 

7 days 0.10 

Cell survival 

demonstrated by trypan 

blue exclusion assay: 

∼85% survival at 2 

highest doses; up to dose 

of 0.050, all cells 

differentiated into GMMp, which had a round 

saucer-like appearance; 

at dose of 0.10, ∼80% of 

living cells were GM-Mp 

and the rest were 

abnormal “arseniteinduced cells”; at dose of 

0.50, ∼10% of living 

cells were GM-Mp and 

the rest were “arseniteinduced cells.” 

Sakurai et 

al., 2005b 

PBMCs 

treated with 

5000 U/mL of 

GM-CSF at 

the same time 

as with 

inorganic 

arsenic 

AsIII SA 0.50 7 days 0.50 

In comparison to 

controls (i.e., PBMCs 

treated with 5000 U/mL 

of GM-CSF and no 

inorganic arsenic), the 

resulting 

morphologically, 

phenotypically, and 

functionally altered 

“arsenite-induced cells” 

had: ⇑ HLA-DR to 5.0x; 

⇓ CD11b to 0.71x; 

⇑ CD14 to 1.4x; ⇓ CD54 

to 42% of control; big ⇓

in phagocytic ability; ⇑

in effectiveness in 

inducing allogeneic or 

autologous T-cell 

responses; and huge ⇑ in 

response to bacterial LPS 

by inflammatory 

cytokine release. 

Sakurai et 

al., 2005b 

C-267 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

PBMCs 

treated with 

5000 U/mL of 

GM-CSF at 

the same time 

as with 

inorganic 

arsenic 

AsIII SA 0.50 7 days 0.50 

The resulting high 

numbers of “arseniteinduced cells” were 

markedly reduced by cotreatment with DMPO, 

DMSO, or BHT, all of 

which are membranepermeable radical 

trapping reagents. 

Further indication that 

ROS might impact 

development of the 

“arsenite-induced cells” 

was that by using 

DCFH-DA it was shown 

that ROS levels were 

much higher throughout 

the 7 days of culturing 

and ≥2x higher on days 

1–4 of that period. 

Sakurai et 

al., 2005b 

PBMCs 

treated 

with 1000 

U/mL of 

M-CSF or 

5000 U/mL of 

GM-CSF at 

the same time 

as with 

inorganic 

arsenic 

AsV LC50 

determinations 

7 days >1 

Cell survival 

demonstrated by trypan 

blue exclusion assay: 

LC50: 300 for simple 

cytotoxicity for both 

treatments and with no 

toxic effect on 

differentiation into 

macrophages up to dose 

of 1. 

Sakurai et 

al., 2005b 

C-268 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

PBMCs 

stimulated 

with PHA for 

96 hr starting 

24 hr after the 

beginning of 

the inorganic 

arsenic 

treatment 

AsIII SA 1, 2, 3, 4, 5 120 hr 1 

Number of rounds of cell 

division estimated using 

CFSE dilution assay with 

FACS (control had 6 

rounds): 

5, 4, 3, 2, and 1 rounds 

of cell division were 

observed after doses of 

1, 2, 3, 4, and 5, 

respectively; there was a 

marked dose-related ⇓ in 

both proliferation and the 

percentage of divided 

cells. Additional 

staining with 7-AAD 

revealed that, at even the 

higher doses, most cells 

were viable but unable to 

divide. The reduced 

proliferation resulted 

from an ⇑ in the fraction 

of non-dividing cells and 

a delay in the cell cycle, 

with only a comparative 

small ⇑ in the number of 

dead cells. At the 

highest dose, 63% of the 

cells were non-dividing, 

and 2/3 of them were 

alive. 

Tenorio 

and 

Saavedra, 

2005 

PBMCs 

stimulated 

with PHA for 

96 hr starting 

24 hr after the 

beginning of 

the inorganic 

arsenic 

treatment 

AsIII SA 1, 2, 3, 4, 5 120 hr 1 

Expression of CD4 and 

CD8 molecules was 

determined using CFSE 

staining during the 

inorganic arsenic 

treatment and then, after 

the 96 hr incubation, by 

indirect 

immunofluorescence 

using OKT4 or OKT8 

hybridoma supernatants 

and goat anti-mouse 

IgG-PE, followed by 7-

AAD staining and FACS 

analysis. The dose of 1 

slightly modified the 

expression of both CD4 

and CD8. At doses ≥3: a 

marked ⇓ in number of 

cells expressing CD4; at 

doses ≥4: a marked ⇓ in 

number of cells 

expressing CD8. 

Tenorio 

and 

Saavedra, 

2005 

C-269 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

PBMCs 

stimulated 

with PHA for 

96 hr starting 

24 hr after the 

beginning of 

the inorganic 

arsenic 

treatment 

AsIII SA 1, 2, 3, 4, 5 120 hr 1 

Evaluation of blast 

transformation of both 

CD4+

 and CD8+ T cells 

suggested that they have 

different sensitivities to 

inorganic arsenic. There 

was an accumulation of 

resting CD8+

 cells with a 

positive dose-response; 

that accumulation was 

not seen for CD4+

 cells. 

Tenorio 

and 

Saavedra, 

2005 

Human CD4+

cells 

stimulated 

with PHA for 

96 hr starting 

24 hr after the 

beginning of 

the inorganic 

arsenic 

treatment 

Human CD8+

cells 

stimulated 

with PHA for 

96 hr starting 

24 hr after the 

beginning of 

the inorganic 

arsenic 

treatment 

AsIII SA 

for both 

1, 2, 3, 5 

for both 

120 hr 

for both 

1 

for both: 

 a slight 

but 

significant effect 

Number of rounds of cell 

division estimated using 

CFSE dilution assay with 

FACS (control CD4+ and 

CD8+ cells had 6 and 5 

rounds, respectively): 

At a dose of 1: only 5 

rounds in CD4+

 but no ⇓

in rounds in CD8+

; 

however, CD8+ cells had 

⇓ in cell number in the 

last 3 rounds. arsenic 

doses increased in both 

cell types: decreasing 

numbers of cell divisions 

and of numbers of cells 

in each round. Effects 

were generally more 

extreme in CD8+ cells. 

Tenorio 

and 

Saavedra, 

2005 

C-270 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Human CD4+

cells 

stimulated 

with PHA for 

96 hr starting 

24 hr after the 

beginning of 

the inorganic 

arsenic 

treatment 

Human CD8+

cells 

stimulated 

with PHA for 

96 hr starting 

24 hr after the 

beginning of 

the inorganic 

arsenic 

treatment 

AsIII SA 

for both 

1, 2, 3, 4, 5 

for both 

120 hr 

for both 

1 

for both: 

 a slight 

but 

significant effect 

CFSE dilution assay with 

7-AAD staining and 

FACS: 

In both cell types there 

were apparent 

differences from the 

control at the dose of 1, 

and there was a 

progressive ⇓ in viable 

proliferating cells with 

increasing dose. arsenic 

doses increased from 0 to 

3, there was a much 

faster ⇑ in the fraction of 

resting cells that was 

alive among CD8+

 cells 

than among CD4+

 cells, 

and that fraction 

remained higher. 

Tenorio 

and 

Saavedra, 

2005 

PBMCs 

stimulated 

with PHA 

during the 

inorganic 

arsenic 

treatment, 

CD4+

 and 

CD8+ T cells 

were analyzed 

separately 

AsIII SA 1, 2, 3, 4, 5 

24 hr 

48 hr 

72 hr 

2 

1 

1 

LOECs were based on 

FACS patterns that 

seemed substantially 

different as to kinetics of 

expression of CD25 and 

CD69 in CD4+

 T cells. 

Inorganic arsenic 

delayed both the 

expression of CD25 and 

the down-regulation of 

CD69, suggesting that 

inorganic arsenic delays 

the activation kinetics of 

CD4+

 T cells. CD4+ T 

cells exposed to the 

highest dose for 72 hr 

showed a very similar 

pattern to that seen in 

non-inorganic arsenicexposed cells stimulated 

for only 24 hr. A similar 

analysis of CD8+ T cells 

showed similar results; 

however, with them there 

were somewhat more 

CD25-

CD69- cells (i.e., 

cells unable to activate) 

as dose increased. 

Tenorio 

and 

Saavedra, 

2005 

C-271 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

SV-HUC-1 

cells 

AsIII SA 2, 4, 8, 10, 40 48 hr 

2 for 

all effects 

Labeling indices (LIs) 

for immunochemistry of 

cells: 

Bcl-6: ⇑ at 2, increases 

with dose as follows: LIs 

of 0, 1.04, 3.05, 6.01, 

8.24, and 23.94 for 

control and doses listed, 

respectively. 

JAK2: ⇓ at 2, decreases 

with dose as follows: LIs 

of 100, 58.1, 48.9, 13.0, 

5.1, and 0.8 for control 

and doses listed, 

respectively. 

p-STAT3 (Tyrosine 

705): ⇑ at 2 with peak at 

dose of 4 before 

decreasing, as follows: 

LIs of 100, 111.7, 151.0, 

125.2, 119.0, and 50.8 

for control and doses 

listed, respectively. All 

experimental LIs above 

differed from control, 

p < 0.05. 

Huang et 

al., 2007b 

SV-HUC-1 

cells 

AsIII SA 2, 4, 8, 10, 40 48 hr 

2 for 

all effects 

Effects on protein levels 

determined by Western 

blotting: 

Bcl-6: ⇑ at 2 and 

increases with dose. 

JAK2: ⇓ at 2 and 

decreases with dose. 

p-STAT3 (Tyrosine 

705): ⇑ at 2, peak at 4, 

less than control at 40. 

Results at different doses 

were highly consistent 

with results obtained 

using immunochemistry, 

as shown in row above. 

Huang et 

al., 2007b 

C-272 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

SV-HUC-1 

cells 

AsIII SA 2, 4, 8, 10, 40 48 hr 

2 for 

all effects 

Microscopy and 

immunochemistry 

showed Bcl-6 and pSTAT3 (Tyrosine 705) 

to be localized in the 

nucleus and JAK-2 to be 

localized in the 

cytoplasm. 

Morphological changes 

began to appear at dose 

of 2. At dose of 4, cells 

became round and 

exhibited nuclear 

condensation. At highest 

two doses, there was 

cellular shrinkage and 

cytoplasmic 

vacuolization. 

Huang et 

al., 2007b 

BAEC cells AsIII SA 10 48 hr 10 

⇑ in LTE4 to ~5x. Cotreatment with 50 μM 

MnII, which caused ~9x 

⇑ by itself, caused an 

approximately additive ⇑

to ~12x. Addition of LNAME to the inorganic 

arsenic/Mn co-treatment 

boosted LTE4 level to 

~24x. Addition of ETU 

to inorganic arsenic/Mn 

co-treatment boosted 

LTE4 level to slightly 

above that of inorganic 

arsenic/Mn combination. 

 Addition of AA-861 to 

inorganic arsenic/Mn cotreatment reduced LTE4

level by ~80%. 

Bunderson 

et al., 2006 

Thymocytes 

(freshly 

isolated) 

AsV 67, 150, 315, 680, 

1000, 2000 

24 hr 315 Cell survival determined 

using XTT assay: 

LC50: 442. 

Stepnik et 

al., 2005 

Splenocytes 

(freshly 

isolated) 

AsV 67, 150, 315, 680, 

1000, 2000 

24 hr 150 Cell survival determined 

using XTT assay: LC50: 

427. 

Stepnik et 

al., 2005 

C-273 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Thymocytes 

(freshly 

isolated) 

AsV 67, 315, 680 24 hr 315 

Point estimates of 

induced apoptosis 

(experimental minus 

control) determined by 

TUNEL staining: 5% at 

67 (NSE); 16% at 315 

(NSE); and 24% at 680. 

27% of control cells 

were apoptotic. Agarose 

gel electrophoresis of 

DNA showed high (and 

indistinguishable) levels 

of apoptosis in control 

group and at the 3 

experimental dose levels. 

Stepnik et 

al., 2005 

Splenocytes 

(freshly 

isolated) 

AsV 67, 315, 680 24 hr 315 

Point estimates of 

induced apoptosis 

(experimental minus 

control) determined by 

TUNEL staining: 1% at 

67 (NSE); 16% at 315; 

and 33% at 680. 29% of 

control cells were 

apoptotic. Agarose gel 

electrophoresis of DNA 

showed high (and 

indistinguishable) levels 

of apoptosis in control 

group and at the 3 

experimental dose levels. 

Stepnik et 

al., 2005 

Inhibition of Differentiation 

C3H 10T1/2 

cell line 

(mouse cells 

with 

fibroblast 

morphology 

during routine 

culture but 

capable of 

differentiation 

into 

adipocytes) 

AsIII SA 6 8 wk 6 

Complete inhibition of 

differentiation into 

adipocytes induced by 

dexamethasone/insulin 

(dexI) treatment. The 

effect is the same if 

arsenic is removed just 

before the dexI 

treatment. 

Trouba et 

al., 2000 

C-274 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

C3H 10T1/2 

cell line 

(mouse cells 

with 

fibroblast 

morphology 

during routine 

culture but 

capable of 

differentiation 

into 

adipocytes) 

AsIII SA 0.1, 1, 3, 6, 10 48 hr 3 

Dose-related inhibition 

of differentiation into 

adiopocytes induced by 

dexamethasone/insulin 

(dexI) treatment. These 

concentrations do not 

cause cytotoxicity. 

Trouba et 

al., 2000 

SIK cells 

treated in 

surface 

cultures 

beginning 

when they 

reached 

confluence, 

which is when 

their rate of 

division 

decreases as 

differentiation 

increases 

AsIII SA 2 Various 2 

CFE based on assay 

using Rhodanile blue 

staining: on 1 day postconfluence both 

experimental and control 

groups had CFEs of 

~11%, by 4 days their 

CFEs were ~9.2% and 

~5.2%, and by 14 days 

they were ~4.7% and 

~0.6%, respectively. 

Thus, inorganic arsenic 

decreased the exit of 

cells from the 

germinative 

compartment under 

conditions that promote 

differentiation. 

Patterson 

et al., 2005 

hEp cells 

treated in 

surface 

cultures 

beginning 

when they 

reached 

confluence, 

which is when 

their rate of 

division 

decreases as 

differentiation 

increases 

AsIII SA 2 Various 2 

CFE based on assay 

using Rhodanile blue 

staining: at 4 days postconfluence experimental 

and control groups had 

CFEs of ~1.1% and 

0.25%, by 11 days their 

CFEs were ~1.0% and 

~0.05%, and by 14 days 

they were ~1.0% and 

~0%, respectively. Thus, 

inorganic arsenic 

decreased the exit of 

cells from the 

germinative 

compartment under 

conditions that promote 

differentiation. 

Patterson 

et al., 2005 

C-275 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

SIK cells, 

with inorganic 

arsenic 

treatment 

beginning 1 

day before 

suspension 

and 

continuing 

while cells 

were in 

suspension, 

which drives 

such cells 

prematurely 

into the 

differentiation 

pathway 

AsIII SA 2 

1, 2, 3, 4 or 5 

days, when 

including the 1 

day of 

treatment 

before being 

put into 

suspension 

2 

CFE based on assay 

using Rhodanile blue 

staining comparison with 

control (C): 

At 1 day: C, ~11.0%, 

inorganic arsenic, 

~10.8%. 

At 2 days: C, ~0.5%; 

inorganic arsenic, 

~2.3%. 

At 3 days: C, ~0.1%; 

inorganic arsenic, 

~2.0%. 

At 4 days: C, ~0%; 

inorganic arsenic, 

~1.3%. 

At 5 days: C, ~0%; 

inorganic arsenic, 

~0.8%. 

Patterson 

et al., 2005 

hEp cells, 

with inorganic 

arsenic 

treatment 

beginning 1 

day before 

suspension 

and 

continuing 

while cells 

were in 

suspension, 

which drives 

such cells 

prematurely 

into the 

differentiation 

pathway 

AsIII SA 2 

1 or 2 days, 

when 

including the 1 

day of 

treatment 

before being 

put into 

suspension 

2 

CFE based on assay 

using Rhodanile blue 

staining comparison with 

control (C): 

At 1 day: C, ~1.15%, 

inorganic arsenic, 

~1.37%. 

At 2 days: C, ~0.08%; 

inorganic arsenic, 

~0.68%. 

Patterson 

et al., 2005 

SIK cells, 

with inorganic 

arsenic 

treatment 

beginning 

when they 

were put into 

suspension, 

which drives 

such cells 

prematurely 

into the 

differentiation 

pathway 

AsIII SA 0.1, 0.2, 0.5, 2 4 days 0.1 

CFE based on assay 

using Rhodanile blue 

staining (control CFE = 

~ 0.03%): 

Experimental CFEs: 0.1, 

~ 0.10%; 0.2, ~ 0.23%; 

0.5, ~ 0.40%; 2, ~ 

0.80%. 

Patterson 

et al., 2005 

C-276 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

RACs from 

either the SIK 

or hEp cell 

line 

(did not 

specify 

which) 

treated in 

surface 

culture 

AsIII SA 2 4, 7, 11, or 14 

days 

2 

Mean no. of colonies 

present, comparison with 

control (C): 

At 4 days: C, ~3.0; 

inorganic arsenic, ~18.2. 

At 7 days: C, ~0.8; 

inorganic arsenic, ~10.5. 

At 11 days: C, ~0.7; 

inorganic arsenic, ~7.8. 

At 14 days: C, ~0.4; 

inorganic arsenic, ~5.0. 

Patterson 

et al., 2005 

SACs from 

either the SIK 

or hEp cell 

line 

(did not 

specify 

which) 

treated in 

surface 

culture 

AsIII SA 2 4, 7, 11, or 14 

days 

2 

Mean no. of colonies 

present, comparison with 

control (C): 

At 4 days: C, ~1.3; 

inorganic arsenic, ~5.5. 

At 7 days: C, ~0.5; 

inorganic arsenic, ~1.8. 

At 11 days: C, ~0.6; 

inorganic arsenic, ~1.5. 

At 14 days: C, ~0.3; 

inorganic arsenic, ~1.3. 

Patterson 

et al., 2005 

SIK cells, 

with inorganic 

arsenic 

treatment 

beginning 

when cultures 

reached 90% 

confluence 

AsIII SA 2 3 days 2 

Relative CFEs based on 

Rhodanile blue assay, 

with values relative to 

the CFE of untreated 

cells in medium normally 

contained insulin (was 

set at 1): 

⇑ to ∼2.6; if inorganic 

arsenic + EGF in 

medium: ⇑ to ∼4.1. 

If EGF alone: ∼1.9; if no 

insulin in medium (± 

EGF): ∼3.5. Thus, 

inorganic arsenic delays 

differentiation and 

preserves the 

proliferative potential of 

keratinocytes. 

Patterson 

and Rice, 

2007 

C-277 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

hEp cells, 

with inorganic 

arsenic 

treatment 

beginning 

when cultures 

reached 90% 

confluence 

AsIII SA 2 3 days 2 

Relative CFEs based on 

Rhodanile blue assay, 

with values relative to 

the CFE of untreated 

cells in medium normally 

contained insulin (was 

set at 1): 

⇑ to ∼2.6; if inorganic 

arsenic + EGF in 

medium: ⇑ to ∼4.1; if 

EGF alone: ∼2.1; if 

neither EGF nor insulin: 

∼2.1; if EGF but no 

insulin: ∼5.3. Thus, 

inorganic arsenic delays 

differentiation and 

preserves the 

proliferative potential of 

keratinocytes. 

Patterson 

and Rice, 

2007 

SIK cells, 

with inorganic 

arsenic 

treatment 

beginning 

when cultures 

reached 90% 

confluence 

AsIII SA 2 9 days 2 

Relative CFEs based on 

Rhodanile blue assay, 

with values relative to 

the CFE of untreated 

cells in medium normally 

contained insulin (was 

set at 1): 

⇑ to ∼3.8; if inorganic 

arsenic + EGF in 

medium: ⇑ to ∼5.1; if 

EGF alone: ∼1.3; if no 

insulin in medium: ∼5.5. 

 In the absence of 

insulin, EGF 

substantially augmented 

CFE while inorganic 

arsenic had no effect. 

Thus, inorganic arsenic 

delays differentiation and 

preserves the 

proliferative potential of 

keratinocytes. 

Patterson 

and Rice, 

2007 

C-278 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

SIK and 

hEPcells, with 

inorganic 

arsenic 

treatment 

beginning 

when cultures 

reached 90% 

confluence 

AsIII SA 2 

With regard to effects in the previous 3 rows, EGFR 

inhibitors AG1478 and PD 158780 kept inorganic 

arsenic from increasing the CFE regardless of the 

addition of EGF. They did not affect CFE in the 

presence of insulin but largely prevented the ⇑ in CFE 

resulting from insulin removal. Inorganic arsenic 

treatment caused big ⇑ in active Ras protein, a 

downstream effector of EGFR; co-treatment with 

AG1478 blocked that effect. Other experiments showed 

that the inorganic arsenic treatment blocked the ⇓ in 

active EGFR protein and the ⇓ in active β-catenin that 

normally occur after confluence as cells exit the 

proliferative pool and differentiate. Also, expression of 

a dominant negative β-catenin suppressed the ⇑ in 

colony-forming ability and yield of putative stem cells 

induced by inorganic arsenic and EGF. 

Patterson 

and Rice, 

2007 

Interference With Hormone Function 

EDR3 cells 

transfected as 

described in 

paper 

AsIII SA 

0.045, 0.09, 0.18, 

0.27, 0.36, 0.45, 

0.54, 0.675, 0.9, 

1.8, 2.7 

∼18 hr ~0.09 

⇑ of hormone-activated 

GCR-mediated gene 

transcription of reporter 

genes containing TAT 

glucocorticoid response 

elements in the presence 

of activated GCR; peak 

response was at ∼0.5; 

however, inorganic 

arsenic was inhibitory at 

doses of 1.8 and 2.7. 

Other experiments 

showed a similar effect 

on the endogenous TAT 

gene and also that the 

central DNA binding 

domain of the GCR is 

the minimal region 

required for the arsenic 

effect. 

Bodwell et 

al., 2004 

COS-7 cells 

transfected as 

described in 

paper 

AsIII SA 0.1, 0.5, 1.0, 2.0, 

3.0 

∼18 hr None inorganic arsenic had no 

effect on transcriptional 

repression by GCR. 

That is, arsenic had no 

effect on the ability of 

hormone-activated GCR 

to inhibit AP1 expression 

or 

NF-κB-mediated gene 

expression. 

Bodwell et 

al., 2004 

C-279 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

EDR3 cells 

transfected as 

described in 

paper 

AsIII SA 

0.045, 0.09, 0.18, 

0.27, 0.36, 0.45, 

0.54, 0.675, 0.9, 

1.8, 2.7 

∼18 hr ~0.09 

⇑ of hormone-activated 

GCR-mediated gene 

transcription of reporter 

genes containing TAT 

response elements in the 

presence of activated PR; 

peak response was at 

∼0.5; however, inorganic 

arsenic was inhibitory at 

doses of 0.9, 1.8 and 2.7. 

Bodwell et 

al., 2006 

EDR3 cells 

transfected as 

described in 

paper 

AsIII SA 

0.045, 0.09, 0.18, 

0.27, 0.36, 0.45, 

0.54, 0.675, 0.9, 

1.8, 2.7 

∼18 hr ~0.09 

⇑ of hormone-activated 

GCR-mediated gene 

transcription of reporter 

genes containing TAT 

response elements in the 

presence of activated 

MCR; peak response was 

at ∼0.5; however, 

inorganic arsenic was 

inhibitory at doses of 1.8 

and 2.7. 

Bodwell et 

al., 2006 

EDR3 cells 

transfected as 

described in 

paper 

AsIII SA 

For all 3 steroid receptors tested (GCR, PR and MCR—see 3 rows 

immediately above this one), the degree of stimulation at lower inorganic 

arsenic concentrations or repression at higher inorganic arsenic concentrations 

was highly dependent on, and inversely related to, the amount of activated 

steroid receptor within cells. The relative increases in transcription noted 

above, which were up to ~2x or more above control levels, were at the lowest 

levels of activated steroid receptor within cells that were tested. Other studies 

showed that iA (1) had no significant effect on cellular steroid levels or on 

binding of steroid to the receptor, (2) did not activate or act as an agonist for 

GCR, (3) did not act as a competitive antagonist, (4) did not appear to affect 

the ability of the hormone to bind to or activate GCR, (5) did not appear to 

affect hormone-stimulated nuclear translocation of GCR, and (6) did not 

significantly alter the level of GCR for either cells expressing endogenous 

GCR or those expressing stably integrated GCR. Dimerization is not critical 

for the response to inorganic arsenic. In summary, it is clear that inorganic 

arsenic can simultaneously disrupt multiple hormone receptor systems. 

Bodwell et 

al., 2006 

NHEK cells 

AsIII SA 

AsV, 

MMAV, 

DMAV

0.001, 0.005, 0.01, 

0.05, 0.1, 0.5, 1, 5 

for all 

24 hr 

24 hr 

0.001 

0.001–0.5 

For cytokines GM-CSF, 

TNF-α, and IL-6: 

substantial ⇑ at 0.001–

0.01, but no change or ⇓

(sometimes markedly) at 

0.05–5. 

No change or ⇓

(sometimes markedly). 

Vega et al., 

2001 

C-280 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Hormoneresponsive 

H4IIE (rat 

hepatoma cell 

line) 

AsIII SA 0.3, 1.0, 2.0, 3.3 2 hr 0.3 

⇓ in hormone-inducible 

expression of GRE2-Luc 

with a 2-hr AsIII

pretreatment before an 

18-hr Dex treatment. 

The pretreatment did not 

block the normal Dexinduced nuclear 

translocation of 

glucocorticoid receptor. 

AsIII selectively inhibited 

glucocorticoid-receptormediated transcription. 

Kaltreider 

et al., 2001 

Malignant Transformation or Morphological Transformation 

HaCaT cells AsIII SA 0.5, 1.0 20 passages 0.5 Cells became 

tumorigenic; tumors 

were produced by 2 

months after injection of 

cells into Balb/c nude 

mice; cells from tumors 

were much more 

malignant. 

Chien et 

al., 2004 

TRL 1215 

cells (normal 

rat liver) 

AsIII SA 

0.125, 0.250, 

0.500 

18 wk 0.250 Transformed cells 

produced aggressive 

tumors capable of 

metastasis after 

inoculation into nude 

mice. 

Zhao et al., 

1997 

JB6 Cl41 

cells 

simultaneousl

y treated with 

10 ng/mL 

EGF 

AsIII SA 

AsV

25, 50, 200 

12.5, 50, 200 

14 days for 

both 

50 

12.5 

Inhibition of EGFinduced cell 

transformation: 

The effect was much 

stronger for AsV (sodium 

arsenate) with complete 

blockage of 

transformation at 50 and 

200. 

Huang et 

al., 1999b 

 

JB6 Cl41 

cells 

AsIII SA 25, 50, 100 

4 wk followed 

by 4 wk at 

lower 

concentration 

25 

Transformed cells, as 

shown by growth of 

colonies in soft agar; 

transformation did not 

occur at the 2 higher 

doses; SA-induced 

transformation was 

blocked by introduction 

of dominant negative 

Erk2. 

Huang et 

al., 1999a 

Primary 

Syrian 

hamster 

embryo cells 

(HEC) 

AsV 13, 27 7–8 days 13 Morphologically 

transformed cells. 

DiPaolo 

and Casto, 

1979 

C-281 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Syrian 

hamster 

embryo cells 

AsIII SA 

AsV

∼0.8, 1.6, 3, 3.5, 5 

∼8, 16, 32, 64, 128 

7 days 

for all 

0.8 

8 

Morphological 

transformation: 

For both chemicals: a 

positive dose-response 

throughout the dose 

range tested. 

Barrett et 

al., 1989 

Human 

osteosarcoma 

TE85 (HOS) 

cells 

AsIII SA 

MMAIII

0.0125, 0.025, 

0.05, 0.1 

0.00625, 0.0125, 

0.025, 0.05 

6 and 8 wk 

for both 

0.025 at 8 

wk; 0.05 

at 

6 wk 

None 

Transformation to 

anchorage-independence 

in soft agar AsIII: positive 

dose-response to highest 

concentration; 8 weeks 

was ∼40 generations; 

MMAIII was more toxic 

than inorganic arsenicIII. 

Mure et 

al., 2003 

Untransforme

d and 

immortalized 

RWPE-1 cells 

(human 

prostate 

epithelial cell 

line) 

AsIII SA 5 29 wk 5 Aggressive tumors were 

produced after cells 

showing ⇑ secretion of 

MMP-9 were inoculated 

into nude mice. 

Achanzar 

et al., 2002 

SHE cells 

AsIII SA 

DMAIIII 

1, 3, 10 

0.1, 0.2, 0.4, 1.0 

48 hr 

for both 

1 

0.1 

Morphological 

transformation (% of 

surviving colonies 

transformed at each 

concentration): 

1, 0.11%; 3, 0.23%; 10, 

0.48%. 

0.1, 0.28%; 0.2, 0.51%; 

0.4, 3.41%, 1.0, 3.35%. 

Ochi et al., 

2004 

SHE cells 

AsIII SA 

AsV

3, 6, 8, 10 

50, 100, 150 

48 hr 

for both 

6 

50 

Neoplastic 

transformation based on 

anchorage-independent 

growth and/or 

tumorigenicity in 

newborn hamsters. All 5 

anchorage-independent 

cultures tested were 

tumorigenic. 

Takahashi 

et al., 2002 

C-282 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

UROtsa cells MMAIII 0.05 52 weeks 0.05 

Anchorage-independent 

growth as detected by 

colony formation in soft 

agar; cells from those 

colonies showed 

enhanced tumorigenicity 

in SCID mouse 

xenografts. After only 

24 weeks there was also 

much anchorageindependent growth, but 

those cells did not show 

the enhanced 

tumorigenicity. 

Bredfeldt 

et al., 2006 

NIH 3T3 cells AsIII SA 2, 5, 10, 20, 50, 

100, 200 

7 days 2 

Anchorage-independent 

growth in soft agar 

assayed using 

AlamarBlue dye assay 

and microscopic 

examination: ⇑ to ∼1.4x 

control at 2 and 5; NSE 

at 10, marked doserelated ⇓ at higher doses. 

 A daily 2-hr 42°C heat 

shock (which would 

induce HSPs) boosted 

induction of anchorageindependent growth for 

up to 3 repetitions, but 5 

heat-shock repetitions 

markedly reduced such 

growth. When the same 

experiment was repeated 

in R-3T3 (transformed) 

cells, there was NSE by 

inorganic arsenic or heat 

shock on the already 

high level of anchorageindependent growth; 

inorganic arsenic caused 

⇓ at dose of 20, and at 

higher doses the ⇓

became marked, as it did 

also at all doses 

following 5 daily 

repetitions of the heatshock treatment. 

Khalil et 

al., 2006 

C-283 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

BALB/c 3T3 

A31-1-1 cells 

(derived from 

mice) 

AsIII SA 

AsV DA 

MMAV

DMAV

2, 5, 10, 15, 20 

10, 15, 20, 25, 30 

1, 2, 5, 10 mM 

0.5, 1, 2, 5 mM 

72 hr for all 

5 

15 

10 mM 

1 mM 

Caused initiation in a 

two-stage transformation 

assay; based on a 

significant increase in 

the number of 

transformed cells after an 

initiating treatment with 

an arsenic compound for 

72 hr followed by posttreatment with 0.1 

μg/mL TPA for 18 days. 

 Except for AsIII SA, 

responses were stronger 

at higher doses; with it, 

the peak response was at 

10, with a steep decline 

by 20. Slight but 

significant 

transformation occurred 

even without TPA at the 

2 highest doses of AsIII

SA and for 2 mM DMAV. 

 The ranges of positive 

effects in foci/dish in the 

two-stage transformation 

assay (from the LOEC to 

the peak) for each 

arsenical were as 

follows: AsIII SA, 1.80–

3.90; AsV DA, 1.20–

2.90; MMAV, 1.10 (only 

1 positive value); DMAV, 

1.0–3.10. The control 

value was 0.30. 

Tsuchiya 

et al., 2005 

Signal Transduction 

MGC-803 

(human 

gastric 

cancer) 

AsIII ATO 0.01–1 48 hr 0.01 Increase in intracellular 

Ca2+ as measured by a 

Ca2+ sensitive 

fluorescent probe Indo1/AM in flow cytometric 

assays, which parallels 

the effect on apoptosis. 

Zhang et 

al., 1999 

Primary 

cultures of rat 

cerebellar 

neurons 

AsIII SA 

DMAV

10 

5 mM 

4 hr 

8hr 

10 

5mM 

For both: ⇑ in activated 

p38 MAP kinase. 

 

Namgung 

and Xia, 

2001 

C-284 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Primary 

cultures of rat 

cerebellar 

neurons 

AsIII SA 10 1 hr 10 

⇑ JNK3 MAP kinase. 

No change in JNK1 and 

JNK2 MAP kinases. 

(Blocking the p38 and 

JNK signaling pathways 

inhibited arseniteinduced apoptosis.) 

Namgung 

and Xia, 

2001 

SY-5Y cells 

HEK 293 

cells 

AsIII ATO 

for both 

0.1, 1 

for both 

∼1 hr 

for both 

0.1 

0.1 

The Ca2+ concentration 

in cells was substantially 

increased (and by rather 

similar amounts) by both 

doses; inorganic arsenic 

triggered 3 different 

kinds of Ca2+ signals: 

slow (sustained), 

transient elevations, and 

calcium spikes. The 

irreversible increases 

were independent of 

extracellular Ca2+ and 

dependent on internal Ca 

stores, which could 

become depleted. Little 

or no cytotoxicity 

resulted from these doses 

during the time of 

measuring Ca2+

concentrations. 

Florea et 

al., 2007 

C-285 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

UROtsa cells 

AsIII SA 

AsV 

MMAIIIO 

MMAV

DMAIIII 

DMAV

0.1, 0.5, 1, 5 

1, 10, 100 

0.1, 0.5, 1, 5 

1, 10, 100 

0.1, 0.5, 1, 5 

1, 10, 100 

Up to 

2 hr 

for all 

Various 

None 

Various 

None 

Various 

None 

Phosphorylation of 

ERK2: ⇑ with potencies: 

MMAIIIO >> DMAIIII >> 

AsIII

AP-1 binding activity: 

for AsIII: ⇓ at 0.1 and 0.5; 

for MMAIIIO, big ⇑ at 

0.1, 0.5, 1.0 but no 

increase at 5; for 

DMAIIII: ⇓ at 0.1, 0.5, 

and 1, and big ⇑ at 5. 

Phosphorylation of cJun: for AsIII: ⇓ at 0.1 

and 0.5 and ⇑ at 1 and 5; 

for MMAIIIO, big ⇑ at 1 

and 5; for DMAIIII: ⇑ at 

0.1, big ⇑ at 5. 

Also trivalent arsenicals 

caused changes in Fra-1 

and induced AP-1 

dependent gene 

transcription. There was 

no effect on c-Jun Nterminal kinases or p38 

kinases. 

Drobná et 

al., 2002 

Postconfluent 

PAEC cells in 

a monolayer 

AsIII SA 0.5, 2, 5 1 hr 2 

EMSA analysis: ⇑

nuclear retention of NFκB binding proteins; ⇑

nuclear translocation of 

NF-κB binding proteins. 

 Supershift analysis 

showed that p65/p50 

heterodimers accounted 

for the majority of 

proteins binding 

consensus κB sequences 

in cells treated with AsIII

or oxidants. These and 

other experiments 

suggest that AsIII initiates 

vascular dysfunction by 

activating oxidantsensitive endothelial cell 

signaling. Increased 

binding of proteins to 

genomic κB sites could 

induce a mitogenic or 

inflammatory response. 

Barchowsk

y et al., 

1996 

C-286 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Gclm+/+ MEF 

cells 

AsIII SA 

for all 

See rows under Apoptosis and Cytotoxicity for this citation for experimental 

conditions. Inorganic arsenic inhibits NFκB activation and nuclear 

translocation. Co-treatment or pretreatment with tBHQ appears to reverse the 

inorganic arsenic-mediated inhibition of NF-κB translocation, and it triggers 

the nuclear accumulation of the transcription factor Nrf2. tBHQ may cause its 

cytoprotective effects by inducing gene expression changes though activation 

of at least NF-κB and Nrf2. 

Kann et 

al., 2005b 

Hepa-1c1c7 

cells 

AsIII SA 6, 12, 25, 50 1 hr 6 

⇑ AhR nuclear 

translocation, with a 

positive dose-response; 

other experiments 

showed that the 

translocation occurs by 

different mechanisms 

from those followed by 

ligands and that AhRdependent gene 

expression is only 

weakly up-regulated by 

inorganic arsenic. 

Kann et 

al., 2005a 

1RB3AN27

cells 

AsIII SA 0.1, 0.5, 1, 5, 10 240 min Various 

Activation of nuclear 

transcription factors 

detected by EMSA: NFκB: slight ⇑ at 0.5, ⇑ at 

1, huge ⇑ at 5 and 10; 

effect at dose of 1 was 

considerably suppressed 

by co-treatment with 

NAC. Inorganic arsenicinduced degradation of 

IκBα was demonstrated 

in the cytosolic fraction. 

 AP-1: ⇑ at 0.1, slight ⇑

at 0.5, huge ⇑ at 1, 5, and 

10; effect at dose of 1 

was completely blocked 

by co-treatment with 

NAC. 

Felix et al., 

2005 

1RB3AN27

cells 

AsIII SA 0.1, 0.5, 1 120 min 0.1 Phosphorylation 

(activation) of ERK 

detected by EMSA: huge 

⇑ at all 3 doses. 

Felix et al., 

2005 

C-287 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

JB6 C141 

cells 

AsIII SA 

for both 

20, 40 

40 

12 hr 

for both 

20 

40 

⇑ COX-2 protein level. 

⇑ COX-2 transcription. 

However, deletion of 

NF-κB binding sites 

from the 

COX-2 promoter 

blocked this effect. 

Other experiments, 

including some in MEF 

cells, confirmed the 

requirement of the 

IKKβ/NF-κB pathway 

for the induction of 

COX-2 by AsIII (shown 

at protein and 

transcription levels). 

Ouyang et 

al., 2007 

Hepa-1c1c7 

cells 

AsIII SA 

2, 5, 10 

0.1, 1, 2, 5, 10 

2, 5, 10 

2, 5, 10 

5 hr 

48 hr 

5 hr 

5 hr 

2 

0.1 

None 

2 

⇑ Nqo1 mRNA 

expression, with a 

positive dose-response. 

⇑ Nqo1 enzyme activity, 

with a slightly higher 

and rather similar 

response at doses 1–10. 

NSE on Nrf2 mRNA 

levels. 

⇑ Nrf2 protein level, 

with a positive doseresponse. 

These and other 

experiments showed that 

Nqo1 induction occurred 

through the Nrf2/ARE 

pathway with the 

following important 

steps: (1) inorganic 

arsenic markedly 

stabilizes Nrf2; (2) 

inorganic arsenic 

disrupts the Nrf2-Keap1-

Cul3 complex in the 

nucleus, and (3) 

inorganic arsenic recruits 

Nrf2 and Maf to the 

ARE of Nqo1. Inorganic 

arsenic does not recruit 

Keap1, Cul3, ubiquitin, 

c-Jun, or c-Fos to the 

ARE of Nqo1. 

He et al., 

2006 

C-288 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

WM9 cells 

OM431 cells 

K1735-SW1 

cells 

and other 

melanoma 

cell lines 

AsIII SA 2, 4, 6 

A series of experiments (usually with durations of 

treatment between 30 min and 16 hr) demonstrated that 

inorganic arsenic up-regulated TRAIL-mediated 

apoptosis. Inorganic arsenic up-regulated surface levels 

of death receptors, TRAIL-R1 and TRAIL-R2, through 

increased translocation of these proteins from cytoplasm 

to cell surface. Furthermore, activation of cJun and 

suppression of NF-κB by inorganic arsenic caused upregulation of the endogenous TRAIL and downregulation of cFLIP gene expression, which was 

followed by cFLIP protein degradation and, finally, by 

acceleration of TRAIL-induced apoptosis. cFLIP is one 

of the main 

anti-apoptotic proteins in melanomas. 

Ivanov and 

Hei, 2006 

HeLa cells AsIII SA 100 4 hr 100 Big ⇑ in 

autophosphorylation 

(activation) of ASK1 

determined by 

autoradiography. 

Hansen et 

al., 2006 

A431 cells AsIII ATO 20 

Many experiments, usually at dose of 20, and over 

various durations, and often involving inhibitors or other 

modulators, yielded the following information and 

conclusions: inorganic arsenic had following effects: ⇑

p21 promoter activity, ⇑ p21 mRNA level, ⇑ p21 protein 

level. Transfection with a p21 siRNA reduced inorganic 

arsenic-induced p21 expression and reduced the 

inorganic arsenic-induced cytotoxicity after 24 hr by 

half. Conclusions: inorganic arsenic induced p21 

activation via the EGFR-Ras-Raf-ERK1/2 pathway. 

ERK1/2 and JNK may differentially contribute to 

inorganic arsenic-induced p21 expression via the EGFRRas-Raf-ERK1/2 pathway. The ERK 1/2 and JNK 

pathways play opposing roles in inorganic arsenicinduced cytotoxicity. 

Huang et 

al., 2006 

NHEK cells 

AsIII SA 0.4 1, 3, 5, 7 

0.4 

on days 3 

and 5 only 

Cyclin D mRNA level: 

⇑ to ~3.2x on day 3; ⇑ to 

~1.5x on day 5; NSE on 

other days. 

Hwang et 

al., 2006 

NHEK cells AsIII SA 0.4 1, 3, 5, 7 0.4 

on day 3 

only 

Binding of transcription 

factors to their respective 

binding motifs within the 

cyclin D1 promoter by 

demonstrated by EMSA: 

⇑ for AP1 to 1.9x; NSE 

on other days; ⇑ for 

CREBP to 1.6x; NSE on 

other days. Note the 

correspondence with ⇑ in 

mRNA level in row 

above; there was a hint 

of an ⇑ for both on day 

7. 

Hwang et 

al., 2006 

C-289 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

NHEK cells 

AsIII SA 

0.1, 0.2, 0.4 1, 2, 3, 4, 7 

0.4 

on days 

2–7 

Cyclin D protein level: ⇑

to ~1.35x on days 2-4; ⇑

to 2x on day 7. 

Hwang et 

al., 2006 

DU145 cells AsIII SA 50, 100, 200 1 hr 50 

AMPK activation: ⇑ at 

50, big ⇑ at 100, ⇑ at 

200; 

activation was blocked 

by preincubation with 

CAT, GSH, or NAC; 

tests with a dominant 

negative form of AMPK 

showed that AMPK 

activity is necessary for 

inorganic arsenicinduced VEGF 

expression. Other 

experiments showed that 

the arsenic-induced 

AMPK signaling 

pathway is independent 

of the p38 MAP kinase 

and 

PI-3 kinase pathways 

and that the blocking of 

AMPK activation 

markedly increased 

cytotoxicity from 

inorganic arsenic 

exposures of 50 or 100. 

Lee et al., 

2006c 

HaCaT cells, 

trans-fected 

for use in a 

luciferase 

reporter assay 

AsIII SA 1.25, 2.5, 5 12 hr 1.25 ⇑ cyclin D1 transcription 

to 1.9x and then ⇑ with 

dose to 2.4x at highest 

dose. 

Ouyang et 

al., 2005 

HaCaT cells AsIII SA 0.31, 1.25, 5 12 hr 0.31 

Protein levels determined 

by Western blot assay: ⇑

cyclin D1 and then ⇑

with dose to highest 

dose; other experiments 

showed that induction of 

cyclin D1 required 

activation of NF-κB and 

also required IKKβ. It 

was suggested that the 

inorganic arsenicinduced stimulation of 

the transition from G1 to 

S phase that was 

reported in this paper 

occurred through a 

IKKβ/NF-κB/cyclin D1-

dependent pathway. 

Ouyang et 

al., 2005 

C-290 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

Primary 

keratinocytes 

(in third 

passage) 

obtained from 

foreskins of 

adults 

AsIII SA 0.1, 1, 5, 10 48 hr Various 

Enzyme activities 

detected by luciferase 

assays: NF-κB: ⇑ to 

∼1.8x at 0.1, 

⇑ to ∼5x at 1, ⇑ to ∼3.8x 

at 5, NSE at 10. AP-1: 

NSE at 0.1, ⇑ to ∼1.7x at 

1, 

⇑ to ∼2.7x at 5, ⇑ to 

∼4.5x at 10. All results 

were confirmed at the 

protein level. 

Liao et al., 

2004 

H9c2 cells AsIII SA 1, 2.5, 5 

for 1 or 2 days 

There was a large dose-related ⇓ in cell migration rates 

at the 2 higher doses at both durations. NSE on viability 

(based on MTT assay) at these 3 doses, but at the dose 

of 10, which was not tested for other effects, there was a 

⇓ in viability. There was a dose-related ⇓ in focal 

adhesions per cell at all doses and a ⇓ in 

F-actin content of cells at the dose of 5. At doses of 2.5 

and 5, there was a ⇓ in tyrosine phosphorylation of 

FAK, a ⇓ in phosphorylation of FAK at phosphotyrosine 

397, and a ⇓ in tyrosine phosphorylation of FAK’s 

substrate paxillin. Inorganic arsenic affected focal 

adhesion structure or formation and not the turnover or 

amounts of focal adhesion proteins. Focal adhesions are 

involved in integrin signaling, and the inorganic arsenicinduced changes may disrupt cell contraction and 

signaling. It was concluded that inorganic arsenic 

decreases cell migration through an effect on focal 

adhesions and by disruption of cell interactions with the 

extracellular matrix. 

Yancy et 

al., 2005 

MEFs from 

wild type or 

Ikkβ gene 

knockout 

(IKKβ-/-) 

mouse 

embryos 

AsIII

(AsCl3) 

Various between 

1.25 and 50 

In a series of experiments lasting for 2-32 hr, the main 

findings were as follows. In knockout MEFs, which 

exhibit NF-κB inhibition due to IKKβ deficiency, (1) 

there was a big ⇑ in basal levels of mRNAs of the 

following genes: gadd45α, gadd45β, gadd45γ and 

gadd153; (2) there was a big ⇑ in inorganic arsenicinduced (usually at 20 μM for 4 hr) levels of mRNAs for 

gadd45α and gadd153; and (3) there was no induction by 

arsenic (same conditions) of mRNAs for gadd45β and 

gadd45γ. It appears that NF-κB activation is an 

inhibitory signal for the expression of gadd45α and 

gadd153. C-myc expression was reduced in knockout 

cells, and IKKβ deficiency did not affect p53 or Akt 

signaling and the expression of FoxO3a. 

Zhang et 

al., 2005 

JAR cells AsIII ATO 0.5, 1, 2.5, 5, 10 6 hr 0.5 Big ⇑ in nuclear Nrf2 

protein level, with doserelated ⇑ becoming huge 

by dose of 10; also 

similar ⇑ in cytoplasmic 

Nrf2 protein level. 

Massrieh 

et al., 2006 

C-291 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

JAR cells AsIII ATO 5 2, 4, 6, 16, 

24 hr 

Various Big ⇑ in nuclear Nrf2 

protein level at first 4 

time points, but small ⇑

at 24 hr. Slight ⇑ in 

MafF protein level at 

many time points, but 

NSE on 2 other 

dimerization partners of 

Nrf2, namely MafG and 

MafK. Experiments 

done in part in HEK293T 

cells suggested that in 

JAR cells there is an ⇑ in 

binding of endogenous 

Nrf2/small Maf DNAbinding complexes to a 

StRE site. 

Massrieh 

et al., 2006 

BEAS-2B 

cells 

AsIII SA 5 4 hr 5 Huge ⇑ in nuclear Nrf2 

protein level. Other 

experiments showed 

inorganic arsenic caused 

⇑ in Nrf2 transcriptional 

complex binding to the 

HMOX-1 ARE cis

element. 

O’Hara et 

al., 2006 

SVEC4-10 

cells 

AsIII SA 10 3 min to 4 hr 10 inorganic arsenic 

induced actin filament 

reorganization to form 

lamellipodia and 

filopodia structures at the 

leading edge of the cells 

and rosette-like 

structures in the cell 

bodies. Effects were 

noted after only 3 min; 

longer treatments did 

more damage. 

Reorganization of actin 

filament occurred 

through the activation of 

Cdc42. 

Qian et al., 

2005 

SVEC4-10 

cells 

AsIII SA 10 3 min to 4 hr 10 Huge ⇑ in activation of 

Cdc42 already after 3 

min and level of 

activation stayed almost 

as high for at least 1 hr; 

by 4 hr the level of 

activation was similar to 

that of control. See 

comment in row above. 

Qian et al., 

2005 

C-292 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

SVEC4-10 

cells 

AsIII SA 10 Various As more information about series of 

experiments described in 2 rows 

immediately above, it was shown that 

inorganic arsenic-stimulated Cdc42-

induced actin filament reorganization 

regulated the activation of NADPH 

oxidase. Authors suggested that the 

formation of superoxide anion radicals 

observed after inorganic arsenic 

treatment occurred through the 

activation of NADPH oxidase. Rac 

activities were required for Cdc42-

mediated superoxide anion radical 

production, and NADPH oxidase 

activity was involved in inorganic 

arsenic-stimulated cell migration via 

Cdc42-mediated actin filament 

reorganization. 

Qian et al., 

2005 

JB6 C141 

cyclin D1-Luc 

mass1 cells 

AsIII SA 5 24 hr 5 Protein level determined 

by Western blot assay: 

huge ⇑ in cyclin D1; 

separate treatments with 

vanadate, cadmium, or 

NiCl2: NSE. 

Ouyang et 

al., 2006 

JB6 C141 

cyclin 

D1-Luc 

mass1 cells 

AsIII SA 2 12 hr 2 mRNA level determined 

by luciferase reporter 

assay: 

⇑ in cyclin D1 to ∼3.2x. 

Ouyang et 

al., 2006 

JB6 C141 

cells 

AsIII SA 0.1, 0.5, 1, 5, 10 1 hr Various Protein levels determined 

by Western blot assay: 

Phosphorylation of Akt 

Ser473: ⇑ at 0.1–5, big ⇑

at 10. 

Phosphorylation of Akt 

Thr308: slight ⇓ at 0.1, ⇓

at 0.5, ⇑ at 1 and 5, big ⇑

at 10. 

Phosphorylation of 

p70S6K Thr389: big ⇑ at 

0.1–10. 

Phosphorylation of 

p70S6K Thr421/Ser424: ⇑

at 0.1–10. 

Ouyang et 

al., 2006 

C-293 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

JB6 C141 

cells 

AsIII SA 5 20 min 5 Protein level determined 

by Western blot assay: 

big ⇑ in PI-3K activation 

as shown by big ⇑ in 

PIP3; inhibition 

experiments showed that 

inorganic arsenic 

triggered a 

PI-3K/Akt/IKKβ/NF-κB 

signal cascade that 

played essential roles in 

inducing cyclin D1 

expression. 

Ouyang et 

al., 2006 

HEL cells 

AsIII ATO 

0.25, 0.5, 1, 2, 5, 

8, 10 for P-STAT3 

0.5, 1, 2, 4, 6, 8, 

10 

for HSP70 

6 hr 

for both 

0.5 

1 

Western blot analysis: 

⇓ P-STAT3 protein level 

(IC50s = 1.334); 3 HSP90 

inhibitors all markedly 

potentiated the effect 

with iC50s of 0.0468, 

0.395, and 0.745. 

⇑ HSP70 protein level. 

Dose of ∼2.9 doubled the 

control level. 3 HSP90 

inhibitors all markedly 

potentiated the effect. 

HSP70 inhibits 

apoptosis. Much more 

inorganic arsenic was 

needed to kill half the 

cells in 6 hr (LC50, 6 hr = 

80) than to 

down-regulate P-STAT3 

by 50% in 6 hr (1.334, as 

above). The trypan blue 

assay was used to 

determine cell survival. 

Wetzler et 

al., 2007 

A549 cells AsIII SA 1, 5, 10, 20 24 hr 10 

inorganic arsenic 

activated the binding of 

IRP-1 to IRE: ⇑ to 1.35x, 

with smaller ⇑ to 1.25x 

at dose of 20; 10 and 20 

μM inorganic arsenic 

caused a slight ⇑ in HIF1α protein level (only 

∼2% above control). 

Inorganic arsenic at dose 

of 20 had NSE on ferritin 

protein level. 

Li et al., 

2006b 

C-294 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

CL3 cells, 

synchronous 

at G1 

AsIII SA 50, 100 3 hr 50 

At 50, ⇑ in 

phosphorylation 

(activation) of ERK1/2 

to 1.7x right after 

treatment and to 2.0x 

after a 24-hr recovery 

period. At 100: ⇑ to 

2.3x immediately; no 

activation of ERK1/2 

occurred following cotreatment with PD98059 

or U0126. 

Li et al., 

2006a 

CL3 cells, 

synchronous 

at G1 

AsIII SA 5, 10, 25, 50 3 hr Varied 

Dose-related ⇑ in 

phosphorylation 

(activation) of ERK1/2 

to ∼1.45x at 25 and 

∼1.8x at 50, LOEC = 10. 

 Dose-related ⇓ in 

efficiency of synthesis of 

NER to ∼50% and ∼41% 

of control at doses of 25 

and 50, respectively. 

LOEC = 25; for both 

ERK1/2 and NER, the 

changes at 5 and 10 were 

NSE. NER synthesis 

efficiency was 

determined based on 

whole cell extracts of 

treated cells in an assay 

with UV-irradiated 

pUC19 plasmids. Cotreatment of inorganic 

arsenic with either 

PD98059 or U0126 

blocked much of the 

phosphorylation of 

ERK1/2 and restored 

50%–80% of the NER 

synthesis efficiency. In 

summary, co-treatments 

of inorganic arsenic with 

inhibitors that blocked 

activation of ERK1/2 did 

the following: (1) ⇑ NER 

synthesis efficiency, (2) 

⇓ induction of 

micronuclei, (3) ⇓

survival, and (4) ⇓ rate 

of proliferation. 

Li et al., 

2006a 

C-295 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

A431 cells AsIII ATO 20 

Effects detected by Western blot assay following 30-min 

treatment: increases in p-EGFR, p-ERK, p-JNK, 

pp-38, and p21WAF1/CIPI (an immunoblot assay was used 

for p21). NSE for JNK. A series of experiments 

involving modulators and reporter genes showed that: 

(1) EGFR activation can mediate inorganic arsenicinduced p21 expression, (2) activation of EGFR by 

inorganic arsenic occurred later than by EGF, (3) c-Src 

was involved in inorganic arsenic-induced ERK 

activation and p21 expression, (4) the 

EGFR/Ras/Raf/ERK pathway is involved in inorganic 

arsenic-induced p21 gene expression, (5) Sp1 binding 

sites in the promoter are essential for inorganic arsenicinduced p21 activation, and (6) a post-transcriptional or 

post-translational stabilization mechanism is essential 

for 

inorganic arsenic-induced p21 expression. 

Liu and 

Huang, 

2006 

MDA-MB435 cells 

AsIII SA 1, a non-cytotoxic 

dose 

0.5 hr, 

1 hr 

2 hr 

4 hr 

6 hr 

— 

Effects on the nuclear 

binding of the following 

4 transcription factors, 

relative to control and in 

sequential order of the 5 

time periods: 

AP-1: NSE, NSE, ⇑

2.5x, ⇑ 2.5x, NSE. 

NF-κB: NSE, ⇓ 0.5x, ⇑

3.5x, ⇑ 3.5x, ⇑ 1.5x. 

Sp1: ⇓ 0.5x, ⇓ 0.5x, ⇑

3x, NSE, NSE. 

YB-1: NSE, NSE, ⇑ 9x, 

⇑ 3x, ⇑ 3x. 

Another experiment 

using a highly cytotoxic 

dose of 100 resulted in 

markedly different 

patterns over time within 

approximately the same 

ranges of effect. 

Kaltreider 

et al., 1999 

C-296 DRAFT—DO NOT CITE OR QUOTE
LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

H411E cells AsIII SA 0.33, a 

non-cytotoxic 

dose 

0.5 hr, 

1 hr 

2 hr 

4 hr 

6 hr 

— 

Effects on the nuclear 

binding of the following 

4 transcription factors, 

relative to control and in 

sequential order of the 5 

time periods: 

AP-1: NSE, ⇑ 5.5x, ⇑

8.5x, NSE, ⇓ 0.5x. 

NF-κB: ⇑ 1.3x, NSE, ⇑

1.5x, NSE, NSE. 

Sp1: NSE at any time. 

YB-1: ⇑ 3x, ⇑ 3x, ⇑

3.2x, NSE, ⇓ 0.5x. 

Another experiment 

using a highly cytotoxic 

dose of 333 resulted in 

markedly different 

patterns over time within 

approximately the same 

ranges of effect. 

Kaltreider 

et al., 1999 

SIK cells, 

with inorganic 

arsenic 

treatment 

beginning 1 

day before 

suspension 

and 

continuing 

while cells 

were in 

suspension 

AsIII SA 2 

 2 or 5 days, 

when 

including the 1 

day of 

treatment 

before being 

put into 

suspension 

2 

Protein levels determined 

by immunoblotting 

assay: β-catenin: ⇑ to 

3.2x on day 2 and to 3.6x 

on day 5; β1-integrin: ⇑

to 2.7x on day 2 and to 

4.0x on day 5; p-GSK3β

(the inactive form): ⇑ to 

2.5x on day 2 and to 2.2x 

on day 5. 

On day 1, in cells 

harvested before 

suspension, there was ⇑

in p-GSK3β to 1.5x and 

NSE for other two 

proteins. Consistent 

with inorganic arsenic 

maintaining the cell’s 

proliferative potential, 

levels of these 3 proteins 

decreased much less 

rapidly during the 4 days 

in suspension if treated 

with inorganic arsenic.

Patterson 

et al., 2005 

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LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

SIK cells 

treated while 

being 

maintained in 

surface 

cultures 

AsIII SA 2 Various 2 

Protein levels determined 

by immunoblotting 

assay: nuclear β-catenin: 

⇑ to 3.4x on day 9; 

cytoplasmic β-catenin: ⇑

to 2.5x on day 11; p-βcatenin: ⇓ to 0.45x on 

day 1; β1-integrin: ⇑ to 

1.6x on day 7 and to 4.5x 

on day 11; 

p-GSK3β (the inactive 

form): ⇑ to 1.8x on day 7 

and to 3.1x on day 11. 

Consistent with 

inorganic arsenic 

maintaining the cell’s 

proliferative potential, 

inorganic arsenic 

decreased the rate of 

post-confluent loss of all 

of these proteins except 

P-β-catenin. 

Patterson 

et al., 2005 

B16-F10 cells 

AsIII SA 

for all 

0.01, 0.1, 1, 10 

0.01, 0.1, 1, 10 

0.01, 0.033, 0.1 

4 hr 

72 hr 

7 days 

None 

0.01 

0.01 

HIF-1α protein levels: 

No ⇑ seen; no mention if 

there were decreases. 

Small ⇑, but decreased to 

no change from control 

at 0.1, and at higher 

doses a 

⇓ from control. 

Big ⇑, but decreased to 

almost 2 times control at 

0.033, and there was no 

change from control at 

0.1. 

Kamat et 

al., 2005 

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LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

B16-F10 cells AsIII SA 

for all 

0.01, 0.1, 1, 10 

0.01, 0.1, 1, 10 

0.01, 0.1 

4 hr 

72 hr 

7 days 

0.1 

0.01 

0.01 

VEGF secretion: 

Small ⇑ seen at two 

middle doses. 

Big ⇑; much smaller 

increase over control at 

0.1; no change from 

control at 1.0, and a ⇓

from control at 10. 

Big ⇑, but ⇓ from control 

at 0.1. Also, both 7-day 

treatments showed ⇑

HRE transactivation that 

was mostly or 

completely blocked by 

co-treatment with YC-1. 

Kamat et 

al., 2005 

J82 cells 

HMEC-1 cells 

SMC cells 

AsIII SA 

for all 

0.01, 0.1 

0.01, 0.1 

0.01, 0.1 

7 days 

for all 

0.01 

0.01 

0.01 

HIF-1α protein levels: 

⇑, but ⇓ from control at 

0.1. 

⇑, but ⇓ from control at 

0.1. 

Big ⇑ at both dose 

levels. 

Kamat et 

al., 2005 

J82 cells 

HMEC-1 cells 

SMC cells 

AsIII SA 

for all 

0.01, 0.1 

0.01, 0.1 

0.01, 0.1 

7 days 

for all 

0.01 

0.01 

None 

VEGF secretion: 

⇑, but no change from 

control at 0.1. 

⇑, but no change from 

control at 0.1. 

— 

Kamat et 

al., 2005 

H22 cells AsIII ATO 0.5, 1, 2, 4 36 hr 0.5 Huge ⇑ in VEGF protein 

level in cell lysates, with 

similar response at all 

doses (Westen blot 

assay). 

Liu et al., 

2006e 

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LOECa Concentration(s) 

Tested (μM) 

Type of 

Cell/Tissue 

Arsenic 

Species 

Duration of 

Treatment (μM) 

Results (Compared 

With Controls, With 

All Concentrations 

Being 

in μM Unless Noted) Reference 

MCF-7 cells AsIII ATO 0.5, 2, 5, 10 60 min Various 

Results of Western blot 

analysis: ⇑

phosphorylation (i.e., 

activation) of ERK1/2 at 

2 with a dose-related 

increase to 10; ⇑

phosphorylation (i.e., 

activation) of p38 at 2 

with a dose-related 

increase to 10; NSE on 

JNK1/2. Thus, inorganic 

arsenic activates the 

prosurvival mitogenactivated MEK/ERK 

pathway. 

Ye et al., 

2005 

MCF-7 cells 

AsIII ATO 

2, 5 

The findings in the row above prompted investigation 

whether a combination treatment with either of the MEK 

inhibitors U0126 (at 10 μM) and PD98059 (at 20 μM) 

could lead to enhanced growth inhibition and apoptosis. 

 They did, augmenting apoptosis approximately 2x 

compared to the effects of inorganic arsenic and either 

inhibitor alone, based by Hoechst 33258 or annexin V/PI 

staining and flow cytometry. Treatment with a p38 

inhibitor did not prevent inorganic arsenic-induced 

apoptosis; there was a slight but nonsignificant ⇑ in 

apoptosis. 

Ye et al., 

2005 

HeLa cells 

AsIII ATO 

2 Various None 

Experiments showed that 

NF-κB and AP-1 

activation served as 

prosurvival or 

antiapoptotic forces and 

that their activation by 

PMA was suppressed by 

co-treatment with 10 μM 

emodin plus inorganic 

arsenic, whereas emodin 

or inorganic arsenic 

alone had rather little or 

no suppressive effect. 

The synergistic 

suppression was thought 

to be caused, at least in 

part, by cellular ROS 

because pretreatment or 

co-treatment with NAC 

reduced the effect. 

Yi et al., 

2004 

a Lowest observed effect concentration. 

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APPENDIX D. IMMUNOTOXICITY 

Arsenic has been observed to affect the immune system. While changes to the immune 

system are not directly related to any specific disease or cancer endpoint, disruptions to the 

immune function can impact the individual and likely increase their risk for developing a disease 

or cancer outcome. This may, in part, be why there are so many cancers and diseases associated 

with arsenic exposure. In addition, arsenic’s effects on the immune response may play some role 

in acting as a co-carcinogen with other compounds. Therefore, immunotoxicity is listed as a key 

event in this review, and many studies are detailed in the MOA section (4.4.1). The effects, 

however, on the immune system are important to note in and of themselves, and a few are 

detailed here. 

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 Gonsebatt et al. (1994) selected two populations from Comarca Lagunera (Mexico) to 

study the labeling, mitotic, and replication indexes (LI, MI, and RI, respectively) of peripheral 

blood lymphocytes. The exposed population consisted of 33 individuals from Santa Ana, 

Coahuila, who had arsenic levels in the drinking water ranging from 375 to 392 ppb (92% in the 

form of AsV and 8% in the form of AsIII) for several years. Approximately 50% of the exposed 

individuals had cutaneous signs of arsenic poisoning. The control population consisted of 30 

individuals (selected based on similar proportions of age and sex as the exposed population) 

from Nazareno, Durango, who had arsenic levels from the preceding 2 years ranging from 19 to 

26 ppb (>95% as AsV). Urine and blood samples were obtained from all subjects. Average total 

arsenic in the urine and blood of the control group was 36.7 and 37.2 μg/L, respectively, and 

758.4 and 412.0 μg/L, respectively, in exposed subjects. Peripheral blood lymphocyte counts 

were significantly greater in the exposed population (3.1 × 106 cells) compared to the control 

population (2.6 × 106 cells), with a greater increase noted in females. In females, the average 

36-hour LI was lower in the exposed population than the control population, regardless of the 

presence or absence of skin lesions (Table D-1 below). Only exposed males with skin lesions, 

however, exhibited a lower average 36-hour LI; males without skin lesions had an increase in LI. 

 MI were significantly increased in both sexes after a 72-hour incubation period (Table D-1), but 

were not after 48 or 60 hours of incubation. Exposed females had a significantly lower RI after 

48, 60, and 72 hours of incubation, while males were unaffected. 

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Table D-1. Lymphocyte counts and labeling, mitotic, and replication indexes (mean ± se) in 

the peripheral blood lymphocytes in populations exposed to low (control) and 

high (exposed) levels of arsenic (Gonsebatt et al., 1994) 

Control Exposed 

Males Females Total Males Females Total 

Lymphocyte 

Count (x106

cells/ml) 

2.7±1.2 2.4±1.1 2.6±1.1 3.0±1.2 3.1±0.8a 3.1±1.0a

 

Labeling Index 

(36 hours) 

with skin lesions 

without skin 

lesions 

3.32±1.06 4.77±1.06 3.37±0.61 

2.14±0.86 

4.05±1.31 

2.74±0.32 

3.90±0.49 

2.42±0.49a

 

3.95±0.56 

Mitotic Index 

48 hours 1.15±0.23 2.52±0.48 1.89±0.30 1.59±0.29 1.59±0.26 1.59±0.20 

60 hours 2.53±0.30 4.90±0.79 3.85±0.50 3.35±0.39 3.65±0.48 3.50±0.32 

72 hours 3.52±0.37 3.96±0.52 3.78±0.34 6.00±0.55b 6.60±0.69b

 6.34±0.45b 

Replication Index

48 hours 1.07±0.01 1.16±0.02 1.12±0.01 1.05±0.01 1.10±0.02a

 1.08±0.01a

60 hours 1.43±0.03 1.54±0.04 1.49±0.03 1.39±0.04 1.37±0.04a

 1.38±0.02a

72 hours 1.93±0.09 2.08±0.04 2.01±0.04 1.89±0.09 1.84±0.05a

 1.86±0.05a

a

 Statistically different (p < 0.05) from the control (two-tailed Mann-Whitney U-test). 

b

 Statistically different (p < 0.001) from the control (two-tailed Mann-Whitney U-test). 

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A previous study by Ostrosky-Wegman et al. (1991), in which cell-cycle kinetics of 

peripheral blood lymphocytes showed a significantly longer average generation time (AGT) for 

the highly exposed group as compared to the control group. The AGT was 19.90 hours in the 

low-exposure group compared to 28.70 hours in the high-exposure group. The AGT in the 

control group was 19.02 hours. The exposed group consisted of 11 individuals (9 females and 2 

males) from Santa Ana, Coahuila, with drinking water containing an average of 390 ppb (98% as 

AsV). The control group consisted of 13 individuals (11 females and 2 males) from Nuevo 

Leon, Coahuila (drinking water concentrations not reported). Average urine arsenic/creatinine 

levels were 0.121 μg/mL in the control group and 1.565 μg/ml in the exposed group. There were 

no incidence of skin lesions in the control subjects, but 4 of the 11 exposed subjects had skin 

lesions (i.e., hyperkeratosis, hypo- and hyperpigmentation, and skin horns). 

IgG and IgE levels were significantly elevated in arsenic-exposed individuals who 

presented clinical symptoms of arsenic exposure (i.e., skin lesions) (Islam et al., 2007). As 

exposure duration increased, so did the severity of the skin lesions. The level of IgE also was 

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greater with longer durations of arsenic exposure. IgG levels were highest during the initial 

stages of skin lesions. There was a smaller, but significant, increase in IgA in individuals with 

arsenicosis compared to the control group, but no change was observed in IgM levels. Arsenicexposed individuals also had a greater incidence (63% of subjects) of respiratory complications, 

such as chest sounds, shortness of breath and breathing complications, irritation of the upper and 

lower respiratory tract, cough, bronchitis, and asthma than the control group (7%). The IgE level 

in individuals with respiratory complications was greater than in arsenic-exposed individuals 

without complications. Because the difference in IgE levels could not be explained by 

differences in eosinophil levels, it was suggested that the reason may be inflammatory reactions 

due to arsenic exposure. 

Yu et al. (1998) found that patients with Bowen’s disease (skin carcinoma in situ) from 

an arsenic-endemic area in the southwest coast of Taiwan had significantly decreased T-cells, 

increased B-cells, decreased T-helper cells, decreased IFN-γ release, decreased TNF-α release, 

increased IL-2 release, decreased soluble IL-2 receptor release, and changes in soluble CD4 and 

soluble CD8 release (increases in spontaneous release, but decreases in phytohaemagglutinininduced release) in comparison to normal controls, as well as non-Bowen’s patients in the 

endemic region. Results indicate a depressed cell-mediated immunity in patients with Bowen’s 

disease. The deficient immune response appears to be related to an impairment of the membrane 

IL-2R expression in lymphocytes after stimulation. This study, however, could not associate 

arsenic with these changes because individuals without Bowen’s disease who lived in the 

endemic region did not demonstrate the same effects. In addition, a cause and effect relationship 

could not be determined. Since arsenic has been demonstrated to affect the immune response in 

other studies, it is possible that individuals developing Bowen’s disease were more susceptible to 

the effects of arsenic on the immune system. 

The development of skin lesions is a typical symptom of arsenic-exposed individuals. 

However, not all individuals exposed, even those within the same family, develop skin lesions. 

Mahata et al. (2004) examined some effects on peripheral lymphocytes in arsenic-exposed 

individuals with or without skin lesions and compared those results to a group of subjects that 

were unexposed. Six individuals (3 males and 3 females) were selected from each group: 

symptomatic (with lesions and exposure), asymptomatic (without lesions and exposure), and 

unexposed. Where possible, symptomatic and asymptomatic were selected from the same 

family. The 6 controls (3 males and 3 females) were selected for similar socio-economic status, 

age, and gender. Levels of arsenic in urine, nail, and hair demonstrated that the control group 

had little exposure to arsenic. Individuals with skin lesions were noted to have less arsenic in 

their urine and more in their hair and nails. This indicated individual differences in distribution 

and excretion (for more information on this see Section 4.7.3.1 on genetic polymorphism) that 

may be related to the individual’s susceptibility to developing skin lesions. When the blood of 

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the individuals from all three groups was exposed to further arsenite in vitro, all groups 

demonstrated a dose-dependent increase in chromosomal aberrations in the lymphocytes, with a 

significant increase observed even at the lowest concentration (1 μM). Untreated lymphocytes, 

however, had a greater level of chromosome aberrations in arsenic-exposed individuals. In 

addition, individuals with skin lesions had a 1.7-fold increase in “background” chromosomal 

aberrations compared to asymptomatic individuals. Although the arsenic-exposed individuals 

had more chromosomal aberrations in the absence of additional arsenic exposure in vitro, the in 

vitro exposure to arsenite caused a smaller increase in chromosome aberrations in lymphocytes 

of exposed individuals compared to unexposed individuals, indicating a greater sensitivity in the 

control lymphocytes to the in vitro effects of AsIII. 

The JAK-STAT pathway is essential in mediating the normal functions of different 

cytokines in the hematopoietic and immune systems. In vitro studies by Cheng et al. (2004) 

suggest that arsenic exposure in the range of 0.4 to 400 μM caused inactivation of the JAKSTAT signaling pathway in HepG2 cells (a human hepatocarcinoma cell line). This inactivation 

was caused by the direct interaction of arsenic with JAK tyrosine kinase and was independent of 

arsenic activation of mitogen-activated protein (MAP) kinase. Exposure to sodium arsenite 

abolished the STAT activity-dependent expression of cytokine signaling suppressors by 

inhibiting IL-6-inducible STAT3 tyrosine phosphorylation. This effect on the STAT3 tyrosine 

phosphorylation induced by arsenic was not observed with other inflammatory stimulants, stress 

agents, or cadmium (metal). 

Harrison and McCoy (2001) performed an in vitro study to examine the role of apoptosis 

and enzyme inhibition in arsenic’s suppression of the immune response. Cysteine cathepsins are 

lysosomal enzymes that are critical in antigen processing. Because of AsIII interactions with 

sulfhydryl groups, cathepsin L (a member of the papain superfamily of cysteine proteases and a 

major lysosomal protease involved in cleaving exogenous protein antigens into peptide 

fragments) was examined as a potential target for arsenic inhibition. AsIII caused a dosedependent inhibition of cathepsin L, both as a purified enzyme and in active murine B cells. 

Inhibition occurred in TA3 cells even at concentrations that did not affect cell viability; greater 

inhibition was obtained with the purified enzyme. Addition of DTT caused a complete reversal 

of the inhibition. AsV was not able to inhibit cathepsin L, therefore, indicating the involvement 

of the sulfhydryl groups. Although cathepsin L was inhibited by 4 hours, exposure for 18 hours 

led to increases in apoptosis even at the lowest concentration (0.8 μM). Apoptosis was observed 

at concentrations about 100-fold lower than those inhibiting cathepsin L, suggesting that 

apoptosis likely plays a more important role in immunosuppression than inhibition of lysosomal 

cathepsins. 

De La Fuente et al. (2002) found a significant increase in apoptosis in PMBCs from 

healthy donors at concentrations of 15 μM AsIII after 48 hours of exposure; an increase also was 

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noted at 5 μM, but did not reach statistical significance. Results did not show a dose-response; 

instead apoptosis levels were similar between 15 and 75 μM of arsenite. Lower concentrations 

of AsIII (i.e., 1 μM and 2.5 μM) also were able to increase apoptosis levels, but required at least 

96 hours of exposure compared to only 16 hours of exposure needed with 15 μM of AsIII. 

Measuring the levels of apoptosis in the PMBCs of children chronically exposed to arsenic 

(urinary levels of arsenic between 94 and 240 μg/g of creatine) also demonstrated an increase in 

apoptosis when compared to the control group. However, exposing the cells of chronically 

exposed children to arsenic in vitro demonstrated a decrease in apoptosis when compared to 

controls. Therefore, these data support the data of Mahata et al. (2004), which suggested that 

control PMBCs are more sensitive to in vitro arsenic exposure. 

In contrast, González-Rangel et al. (2005) found the opposite response. Although their 

data also show an increase in basal apoptosis in PMBCs lymphocytes and monocytes (but not 

natural killer [NK] cells) in an exposed individual compared to six non-exposed individuals, the 

data also show an increased sensitivity to in vitro arsenite-mediated apoptosis in lymphocytes 

and NK cells in the exposed individual. This study, however, used a higher concentration of 

arsenite (30 μM) compared to the other studies (which used at most 15 μM) and only used one 

exposed individual compared to 6 unexposed individuals. Therefore, results could be different 

due to dose or because of inter-individual variation. 

Although Harrison and McCoy (2001) and De La Fuente et al. (2002) observed an 

increase in the apoptosis in PMBCs, Chen et al. (2005b) did not observe any effect on the 

apoptosis of human keratinocytes (obtained from the adult foreskin through routine 

circumcision) with 1 μM of arsenite. When cells were exposed to AsIII for 24 hours prior to 

exposure to UVB, however, the AsIII protected against UVB-induced apoptosis, indicating a 

possible mechanism for arsenic’s observed co-carcinogenic nature. Exposing the cells to AsIII

after UVB exposure did not cause a reduction in apoptosis and possibly increased the level of 

apoptosis. 

Galicia et al. (2003) isolated PBMC from healthy, non-smoking, males (22–40 years old) 

who were not exposed to arsenic to examine the effects of AsIII on cell proliferation. Although 

there was individual variability, a dose-dependent decreased in cell proliferation in PHA-induced 

cells was observed. In all cases, the highest concentration used (1 μM) decreased the percent of 

dividing cells, with a reduction of 12% to 54%. Although cell proliferation was affected, there 

was relatively little affect on cell viability. After further examination, it was suggested that 

proliferation of T lymphocytes was affected and there was a reduction in CD3+ cells producing 

IL-2. Although arsenic prevents cells from entering the cell cycle and slows down the 

progression through the cell cycle, no alteration in the expression of CD69 or CD25 activation 

molecules was observed. Thus, it was concluded that the reduction in T cell proliferation was 

caused by a decrease in the production and secretion of IL-2, thereby blocking the T cells in G1. 

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Di Gioacchino et al. (2007) examined the effects of arsenic compounds (i.e., AsIII, AsV, 

MMAV, and DMAV) on PBMC proliferation and cytokine release. AsIII had the greatest effect 

on the cells. At 10-4 M, AsIII caused the greatest decrease in PHA-induced cell proliferation and 

the greatest reduction in IFN-γ and TNF-α release. At 10-4 M, the effect on cell proliferation by 

compound was AsIII>AsV>DMAV>MMAV. At 10-7 M, however, AsIII caused a significant 

increase in cell proliferation. DMAV also caused a significant increase in cell proliferation at 10-

7 M, but had no effect on cell proliferation at 10-4 M. DMAV and AsV caused a significant 

decrease in IFN-γ release at 10-4 M, but did not affect TNF-α release. Although the text 

indicates that dose-response analyses were performed, the article provides no data. It was 

concluded that the immunotoxicity of arsenic was dependent on the chemical speciation of 

arsenic. 

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AsV (0.5, 5, or 50 mg As/L) administered for 12 weeks via drinking water to female 

C57BL/6J/Han mice (8-12 weeks old) was determined to decrease NO and superoxide 

production (Arkusz et al., 2005). While there was a concentration-dependent decrease in ROS 

production, the decrease observed in NO was similar across the three doses. The AsV did not 

appear to affect TNF-α production. It should be noted, that in testing for the NO and superoxide 

production, 2 × 105 cells/well were plated. Therefore, a cell to cell comparison was made 

between the isolated macrophages from the control group and arsenate-treated mice. The AsV 

treatment, however, was noted to cause a concentration-dependent increase in the number of 

peritoneal macrophages isolated. The percent increase compared to control (55%, 77%, and 

101%, respectively) was such that it may have compensated for the changes noted in NO and 

superoxide production. This, however, was not tested. 

Nayak et al. (2007), however, did test the immune response in zebra fish to virus or 

bacterial infection. Zebra fish embryos (one-cell stage) were exposed to 2 or 10 ppb AsIII in 

water until 4 days post-fertilization. Seven days later fish were infected or left uninfected. Viral 

and bacterial loads were then examined. Viral load was significantly increased in both AsIII

treatment groups compared to the infected control group, with a concentration-dependent 

increase in the viral load. There also was a significant increase in the bacterial load in treated 

fish; however, the increase was similar across both treatments. AsIII was also found to decrease 

ROS burst, interferon, Mx mRNA expression, IL-1β, and TNF-α mRNA levels. The maximum 

response for these cytokines was also found to be delayed compared to the controls. 

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APPENDIX E. QUANTITATIVE ISSUES IN THE CANCER RISK ASSESSMENT FOR 

INORGANIC ARSENIC 

As discussed in Section 5.3, the arsenic cancer risk assessment involved two distinct 

phases. The first phase involved the derivation and fitting of dose-response models using the 

Taiwanese epidemiological data of Chen et al. (1988a, 1992) and Wu et al. (1989). The outputs 

of this phase of the analysis were arsenic dose-response coefficients that described the 

relationship between estimated arsenic intake in the Taiwanese population and proportional 

increases in age-specific lung and bladder cancer mortality risk. A key assumption underlying 

this relative risk model is that the risk of arsenic-related cancer is a constant multiplicative 

function of arsenic dose and the ”background” age profile of risks. 

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The second phase of the risk assessment involved the estimation of arsenic-related cancer 

risks in a (hypothetical) U.S. population exposed to arsenic at varying levels in drinking water. 

This phase of the analysis involved the application of the dose-response coefficients for arsenic 

derived from the Taiwanese data to the age-specific background population risks for the U.S. 

population. In addition, the risk estimates were converted from mortality-based values to 

incidence-based estimates. The following sections describe each of these phases. 

E.1. CANCER RISK ASSESSMENT FOR THE TAIWANESE POPULATION 

The calculation of cancer risks from the Taiwanese epidemiological data was performed 

using Excel workbook files. The files contained the input data for the dose-response models and 

spreadsheets to accept user-specified inputs, perform calculations, and summarize outputs from 

the assessment. Input data included male and female lung and bladder cancer mortality and 

person-years at risk (PYR) data for arsenic-exposed populations from 42 villages obtained from 

Morales et al. (2000), village water arsenic concentrations (minimum, median, and maximum 

data sets), and southwest Taiwan and all Taiwan reference population mortality and PYR data. 

The user first specifies drinking water consumption and body weights for the Taiwanese 

population in the “Poisson Model” page of the risk calculation files. Solver® is then invoked to 

estimate the age coefficients (a1, a2, and a3) and the arsenic dose-response coefficient (b) in 

equation E-1 by maximizing the likelihood function that is coded into the spreadsheets. Solver is 

then reconfigured to calculate the upper confidence limit (UCL) on “b” using the profile 

likelihood method (see below). The resulting UCL value is then input to the “BEIR Model” 

sheet and the LED01 for cancer incidence is calculated, again using Solver®. The LED01 value is 

transferred to the “Summary” sheet, where other risk metrics (unit risk, cancer risks at different 

drinking water concentrations, and the drinking water concentration corresponding to 10-4 

lifetime risk) are calculated. Risk metrics are calculated based on user-specified drinking water 

intake and body weight for the U.S. population. Likelihood calculations for most of the 

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endpoints were replicated using a different optimizer in the Non-Linear Estimation module of the 

Statistica® software package. 

E.2. MLE ESTIMATION OF DOSE-RESPONSE PARAMETERS 

The Taiwan risk model spreadsheets calculate the dose-response parameters for the 

Poisson model, fitting separate models for each endpoint: 

h(x,t) = exp(a1 + a2 × age + a3 × age2

) × (1 + b × dose) (Equation E-1) 

In this model, the midpoints of the age group strata are normalized (placed on a “zscale”) before risk is estimated; age is thus treated as a “nuisance parameter” in the model. 

Dose, as noted above, is calculated from dietary arsenic and village water concentrations and is 

expressed in terms of mg/kg-day. Each age-dose group is represented by a row on the 

spreadsheet. There are 42 villages with arsenic well water data and the reference population, 

each divided into 13 age strata, for a total of 559 population groups. The model begins with 

randomly selected values for the four parameters and then calculates the Poisson log likelihood 

values for each group: 

log likelihood = observed × ln[hCURRENT(x,t)] – predicted (Equation E-2) 

where: 

observed = the number of cancer deaths in groups age t, exposed at dose x 

hCURRENT(x,t) = the estimated total cancer risk in age group t at dose x, based on 

the current parameter estimates 

predicted = the predicted number of cancer deaths in age group t at dose x, = 

hCURRENT(x,t) × PYR, where PYR = person-years at risk 

 The sum of the log likelihood across all the age groups is then maximized using 

standard optimization methods (Excel Solver®) to provide the MLE estimates of the age and 

dose parameters. 

29 E.2.1. Estimation of Upper Confidence Limits on the Arsenic Dose-Response Parameters 

ED01 values are derived based on the MLE dose-response parameter estimates. The 

LED01 estimates are derived from the 95% upper confidence limits (UCLs) on the dose-response 

parameters. The UCLs on the dose-response “b” parameters were estimated using the “profile 

likelihood” method (Venson and Moolgavkar, 1988). In this approach, the value of the dose 

parameter, b, was varied from its estimated mean value, and the changes in log-likelihood were 

calculated. The ratio of the log likelihood for the best-fit model to the log likelihood for other 

values of “b” is known to follow an approximate chi-squared distribution with one degree of 

freedom. Thus, the 5th and 95th confidence limits on the dose coefficient “b” correspond to the 

values where the likelihood ratio is equal to 1.92. Upper and lower confidence limits were 

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calculated using Solver®. The fact that the profile likelihood method ignores the likelihood 

impact of the age “nuisance parameters” implies that the calculated confidence limits are only 

approximate. Confidence limit calculations using other methods (empirical Bayesian simulation 

and “bootstrap-t”) gave similar values (within a few percent). 

E.3. ESTIMATION OF RISK FOR U.S. POPULATIONS EXPOSED TO ARSENIC IN 

DRINKING WATER 

LED01 values were calculated using a life-table method that is a variation on the “BEIR 

IV” model recommended by NRC (2001). Specifically, the approach includes a modification 

suggested by Gail et al. (1999) for obtaining more accurate estimates of incidence within multiyear age strata. The BEIR IV relative risk model takes as its inputs the arsenic dose-response 

“b” coefficient from the Poisson model, background cancer incidence data, along with agespecific mortality data to directly estimate lifetime bladder and lung cancer incidence for the 

target (U.S. adult) population. Lung and bladder cancer incidence reference data for the years 

2000–2003 were obtained from the National Cancer Institute’s SEER program (NCI, 2006). 

U.S. gender and age-specific population data and all-causes mortality data came from the 

National Center for Health Statistics (NCHS, 2000). 

Formulas for calculating LED01 values were implemented on separate Excel spreadsheets 

for each endpoint. The following calculations were implemented in separate lines on each 

spreadsheet. In all of the equations, the subscript “i” refers to age group: 

( )

( ) = ∑ −

=

i

ii

i

i )r1(T

xs

xc

cancer ofrisk lifetime )x(L xdoseat incidence

19 (Equation E-3)

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Numerator Terms: 

ci(x) = cancer incidence hazard at dose (x), age interval (i) 

ci(x) = ci(0) × (1 + beta × dose) (beta comes from the linear Poisson model) 

ci(0) = background cancer incidencei / cancer free populationi 

Background cancer incidence c i comes from SEER, cancer-free populationi, see (7) 

bi = background cancer incidencei / alive populationi (SEER data) 

Yi = exp (- 5bi) 

Fi = initial estimated background probability of survival without cancer to the 

end of interval (i - 1) 

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Fi Yi

j

j i

= =

= − ∏ 11

1 (Equation E-4) 

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5 

Gi = initial estimated background probability of survival without cancer to 

the middle of interval (i) 

Gi Fi bi = ( .* ) −2 5

6 (Equation E-5) 

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Cancer-free populationi = alive populationi × Gi 

Denominator Terms: 

si(x) = total noncancer mortality and cancer incidence hazard, at dose (x) 

in age interval (i) 

si(x) = background noncancer mortality (x, i) + cancer incidence hazard (x, i) 

si(x) = (di – hi) + ci(0) × (1 + beta × dose) 

di = total mortality (background) in age interval (i) 

di = total deathsi / populationi (Census, Vital Stat. U.S.)

hi = cancer deathsi / populationi (Census, Vital Stat. U.S.) 

Survival (Ti and ri) Estimation: 

Ti = probability of survival without cancer to end of interval (i - 1) 

Ti ri Wi Wib

j

j i

j

j i

j

j i

= = =

= −

=

= −

=

= −

* ∏∏∏

1

1

1

1

1

1

 (Equation E-6) 

ri = probability of survival cancer free through interval (i), given survival to beginning of 

interval (i) 

ri = Wi × Wib 

Wi = exp (- 5di + 5hi – 5ci) 

Wib = exp (- 5ci × Beta × x) 

To calculate ED01 values, the value of the daily arsenic dose used to calculate hi(x), and 

hence L(x), was varied until L(x) = 0.01 (1%). For the MLE estimation, Solver was used to 

estimate LED01 values in the model spreadsheets. 

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APPENDIX F. RISK ASSESSMENT FOR TOWNSHIPS AND LOW-EXPOSURE 

TAIWANESE POPULATIONS 

F.1. RECENT STUDIES OF THE TAIWANESE POPULATIONS THAT DO NOT FIND 

CONSISTENT EXPOSURE-RESPONSE RELATIONSHIPS 

As discussed in Section 5.3.8.5, several recently published studies have called into 

question the strength and significance of the exposure-response relationship for arsenic in the 

Taiwanese population studies (Chen et al., 1988a, 1992; Wu et al., 1989). This appendix 

provides a brief analysis of some of these concerns. 

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Based on “graphical and regression analysis,” Lamm et al. (2003) found no significant 

dose-response relationship for arsenic-related bladder cancer in the subset of the Taiwanese 

population with median drinking water well concentrations less than 400 ppb (μg/L). 

Significant, positive dose-response slopes were found for villages with median well 

concentrations above 400 ppb. They also observed that all of the villages “solely dependent” on 

artesian wells had median arsenic concentrations above 350 ppb, and that the median well 

concentrations in villages not solely dependent on artesian wells were generally below this 

value. Based on these observations, Lamm et al. (2003) suggested that the nature of the villages’ 

water sources (artesian vs. non-artesian), rather than arsenic concentration, explained the 

observed variations in bladder cancer risk in the Taiwanese population. 

Kayajanian (2003) also argued that EPA is misinterpreting the data from the Taiwanese 

population. Kayajanian stratified median well arsenic concentration into 10 ranges from 10 to 

934 ppb. The author then calculated combined mortality rates for lung, bladder, and liver cancer 

for each stratum of the population. They calculated that crude (age-unadjusted) cancer mortality 

for both males and females was significantly elevated in the lowest exposure groups, decreased 

to minimums for villages with water arsenic concentrations between 42 and 60 ppb, and then 

again increased with increasing arsenic exposure. They argued on this basis (and based on the 

analysis of cancer mortality data from another epidemiological study) that health standards for 

arsenic should be set in the vicinity of 50 μg/L (ppb) in order to minimize the risk of arsenicassociated cancer, and that lower exposures would actually result in increased risk in the U.S. 

population. 

In a more recent study, Lamm et al. (2006) reported additional analyses of the 

relationship between cancer risks and drinking water arsenic in the same Taiwanese population. 

In this analysis, they divided the epidemiological data according to six “township” designations 

provided by the original Chinese investigators (townships 0, 2, 3, 4, 5, and 6).1

 They stratified 

the data into two groups: townships that (by their characterization) “showed a significant doseresponse relationship” with arsenic (2, 4, 6) and townships “that did not” (0, 3, and 5). They 

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then applied linear regression to characterize the relationship between combined bladder and 

lung cancer standardized mortality ratios (SMRs) and arsenic exposures in the Taiwanese 

villages. They found that (1) dummy variables related to township were significant (along with 

arsenic well concentration) when all the townships were included in the analysis, and (2) the 

dose-response parameter for arsenic exposure became insignificant for arsenic well 

concentrations less than 151 ppb when only townships 2, 4, and 6 were included in the 

regression. Based on these results, they concluded that location (township) was an important 

explanatory variable for cancer risks and that 151 ppb represented a “threshold” well arsenic 

concentration below which no exposure-response relationship for arsenic could be detected. 

F.2. LIMITATIONS OF THE RECENT STUDIES 

The studies discussed above all have significant limitations, relating both to the methods 

used to select or stratify data for the risk assessment and to the methods used in analyzing 

exposure-response data. In the first place, it is important to recognize the complexity and 

limitations of the data. Cancer mortality and person-years at risk observations are provided for a 

large number (559) of relatively small age- and village-stratified populations (median personyears at risk ~ 340 for both males and females). Most population groups have zero cancer 

deaths, and the data are very “noisy.” Cancer mortality is strongly age-dependent, and 

simultaneously evaluating the age-and dose-dependence of cancer mortality based on a data set 

in which cancer deaths are “rare events” requires appropriately structured models. All of these 

features of the data drove the selection of the Poisson regression methods described in Section 5, 

and the use of simpler models (linear regression, for example) can (and did) lead to misleading 

results. 

With regard to the Lamm et al. (2003) paper, it is likely that the use of linear regression 

and the failure to account for the age-dependency of bladder cancer risks combined to make it 

impossible to detect a significant exposure-response relationship in villages with water arsenic 

levels less than 400 ppb. In addition, it should be noted that Lamm et al. (2003) did not have 

data regarding the actual sources of drinking water in the various villages; instead they relied on 

the arsenic concentration to assess the degree of dependency of specific villages on artesian 

(generally high-arsenic) versus shallow (low-arsenic) wells. When defined in this circular 

fashion, it is inevitable that including the degree of “artesian well dependence” in a multiple 

regression along with arsenic concentration would deprive the latter variable of much of its 

explanatory power and statistical significance. Finally, the rationale for excluding valid data on 

southwestern or all-Taiwan reference populations from the analysis is highly questionable, and 

again lowers the likelihood of detecting significant exposure-response relationships. 

The major limitation of Kayajanian’s (2003) analysis of the Taiwanese data is that it 

breaks the data into strata that are too small to be used to calculate reliable mortality risks, and 

that it is very sensitive to the specific way that the data are stratified. The relatively high cancer 

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mortality risks seen in the low-dose strata are associated with a small number of villages that 

happen to have a (relatively) large number of deaths. The observed trend in cancer mortality 

versus arsenic dose would be very different if only few cancer deaths were misclassified, or if 

the pattern of cancer deaths had been slightly different by chance. Again, failure to use a model 

that adequately addresses the distribution of cancer deaths as rare events (or that incorporates 

age dependence) resulted in results that are misleading. 

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Lamm et al.’s (2006) failure to find a significant exposure-response relationship in 

villages with arsenic water concentrations below 151 ppb can also be explained by (1) the use of 

linear regression without age-adjustment and (2) the omission of data from three of the six 

townships from some of the regressions. Lamm et al. (2006) did not explain the specific criteria 

for determining if a township “showed a dose-response relationship,” but based on the 

description of their methods provided in the article, it may be assumed that they used linear 

regression to characterize the relationship between SMRs and arsenic exposure in each village in 

the various townships. Given the small number of villages in each township, this approach and 

the rationale for leaving townships 0, 3, and 5 out of the analysis appear arbitrary and 

unjustified. In the following sections, we present alternative analyses that further investigate 

the nature of arsenic exposure-response relationships in the various townships and in villages 

with low arsenic drinking water concentrations. 

F.3. CALCULATIONS OF RISKS FOR TOWNSHIP GROUPS 

To address the issues raised by Lamm et al. (2003, 2006), EPA compared the patterns of 

cancer risks for subjects in the two groups of townships (0, 3, and 5 vs. 2, 4, and 6) to see 

whether there were any differences. As noted above, it is not believed that Lamm et al.’s 

approach to omitting townships because they lack an internal dose-response relationship is valid, 

so EPA did not do so. 

First, to get a rough idea of the patterns in cancer incidence versus exposure, the crude 

cancer risks (population-weighted deaths per person-year for all age groups) and populationweighted average arsenic exposure concentrations were calculated for each of the six villages. 

The results are shown in Figure F-1. This figure simply illustrates that, even without ageadjustments, arsenic dose-response relationships across the villages are quite robust. 

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0.E+00

5.E-04

1.E-03

2.E-03

2.E-03

0 100 200 300 400 500 600

Population-Weighted Drinking Water As, micrograms/L

Total Cancer Risk (Male+Female, 

Lung + Bladder)

Villages 0,3,5

Villages 2,4,6

Reference Population

Figure F-1. Lifetime crude total cancer risk (male + female) for the 

low- and high-exposure villages 

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For both sets of villages (low- and high-exposure), crude cancer risks increase with 

average arsenic drinking water concentration. Age distributions were very similar in all cohorts, 

so the lack of age-adjustment did not seriously bias the results. While total cancer risks are 

dominated by male lung cancer, the other endpoints showed generally the same pattern. This 

finding suggests that the positive exposure-response relationship for arsenic is not being 

seriously confounded by a “village effect.” Given the small populations, populations at risk, and 

numbers of cancer deaths in the individual villages, it is not clear that analyzing exposureresponse relationships within these villages (as defined by Lamm et al.) is justified. 

Exposure-response relationships in the various townships were also investigated using a 

variant of the multiple regression method applied by Lamm et al. (2006). In this analysis, 

however, the non-linear relationship between cancer risk and age was explicitly recognized, and 

the analysis was conducted for township both “with” and “without” significant exposureresponse relationships by Lamm et al.’s definition. First, male and female combined cancer 

mortality risks (bladder + lung) were regressed against the same non-linear age dependency 

incorporated into the Poisson model shown in Equation 5-2. That is, the following equation was 

fit to both the male and female cancer data from the various age groups in the low- and highexposure villages: 

risk (age) = exp(a1 + a2 × age + a3 × age2

) 

Then, the residuals from these regressions (the cancer risks with the effect of age 

removed) were regressed against estimated arsenic dose levels. The dose levels were calculated 

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assuming a nonwater arsenic intake of 10 μg/day for exposed and reference populations, which 

is consistent with the assumptions outlined in Section 5.3.5. The regressions were population- 

(person-year) weighted, in effect giving a linear regression of age-adjusted cancer risks versus 

arsenic dose. The results are shown in Table F-1. 

Table F-1. Coefficients from linear regressions of age-adjusted cancer risk versus arsenic 

doses for townships identified by Lamm et al. (2006) 

Township Numbers All Townships Townships 2, 4, and 6 Townships 0, 3, and 5 

Reference 

Populationa

Included Excluded Included Excluded Included Excluded 

Male arsenic dose 

coefficient (p-value)

0.035 

(0.043) 

0.032 

(0.068) 

0.092 

(0.0002) 

0.091 

(0.001) 

-0.0093 

(0.787) 

-0.002 

(0.487) 

Female arsenic dose 

(p-value) 

0.12 

(0.0002) 

0.12 

(0.0004) 

0.11 

(0.0001) 

0.12 

(0.0001) 

0.14 (0.015) 0.13 (0.026) 

a

Southwest Taiwan. 

The estimated dose coefficients for age-adjusted women’s cancer risk (the linear “slope” 

of the relationship between cancer mortality, with the effect of age removed, and arsenic dose

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) 

are positive and statistically significant for all combinations of townships. Coefficients for male 

age-adjusted cancer risk are positive and significant when all townships are included (although 

marginally significant when the reference population is excluded). Similarly, age-adjusted male 

cancer risk coefficients are positive and highly significant for townships 2, 4, and 6, with or 

without the reference population. In contrast, the arsenic dose-response coefficients for male 

age-adjusted cancer risks are negative, but very small and not significant, for townships 0, 3, and 

5. 

This analysis illustrates that, even using the less-desirable linear regression approach, 

when the cancer risk for the genders separated, and with proper age adjustment, female arsenic 

dose-response relationships are robust and significant for both village groups. For males, the 

arsenic dose-response relationships are significant when a reference population is included, 

except for townships 0, 3, and 5. As noted above, the rationale for analyzing groups of 

townships separately is questionable, as is the omission of a reference population. The results 

showing apparently insignificant associations between male cancer risks and arsenic exposure 

2

 This approach is not particularly desirable from the standpoint of finding the best fit to the data because it restricts 

the effect of arsenic on cancer risk to being linear, and assumes that regression residuals are normally distributed, 

which is unlikely to be true. This approach has been used to illustrate that even using simple models, positive doseresponse relationships can be detected in the data. Due to the different form of this model, the slope coefficients 

derived in this section are also not comparable to those shown in Tables 5-3 and 5-4. 

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more than anything reflect the limitations of this less-than-optimal approach to risk modeling for 

these data. 

F.4. CALCULATION OF ARSENIC-RELATED CANCER RISKS FOR LOWEXPOSURE VILLAGES 

Rather than stratify the Taiwanese population by township, a better way to test the 

significance of exposure-response relationships at low doses is to simply restrict the analysis to 

the villages with low arsenic water concentrations, but use the appropriate Poisson regression 

methodology. In the analysis summarized in Table F-2, the Poisson model shown in Equation 5-

2 was fit to data from the approximately one-half of subject groups with median arsenic drinking 

water concentrations less than 150 ppb. Lamm et al. (2006) considered this concentration to be a 

natural breakpoint because the median arsenic concentrations in the Wu et al. (1989) and Chen et 

al. (1992) population cluster into two groups, one group with 10–126 ppb and the other with 

256–934 ppb. Arsenic “b” coefficients (the dose coefficients in the Poisson model) were 

estimated separately for lung and bladder cancer and for both endpoints combined, for men and 

women. 

Table F-2. Arsenic dose coefficients for study populations with median well water arsenic 

concentrations less than 127 ppb 

Endpoint Arsenic "b" Coefficient 

(95% UCL, LCL) 

Male lung 85.7 (13.1, 172.1) 

Male bladder 586 (335, 877) 

Male combined 160 (83.4, 247) 

Female lung 615 (412, 836) 

Female bladder 2639 (2021, 3307) 

Female combined 924 (721, 1139) 

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For all of the endpoints, the arsenic dose coefficients are positive with lower confidence 

limits that are also positive.3

 This finding indicates that for population groups with water arsenic 

concentrations less than or equal to 126 ppb, the dose-response relationships are positive and 

statistically significant. 

On the whole, the analyses presented in this section provide support for statistically 

significant dose-response relationships for arsenic-related cancer, even in the population groups 

with relatively low exposures. When the data are artificially stratified, when no reference 

population is included, and when inappropriate statistical models are employed, it is possible to 

3 As in Section 5.3.8, the upper and lower confidence limits were calculated using profile likelihood; similar results are 

obtained using bootstrap methods. 

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find insignificant or negative dose-response relationships for arsenic for some portions of the 

data. When appropriate models are used, however, the Taiwanese data show robust and 

significant positive associations between arsenic exposures and cancer risks for all of the 

endpoints analyzed, even in low-exposure groups. No evidence was found that either 400 ppb or 

150 ppb represent “threshold” arsenic concentrations in drinking water below which cancer risks 

are not increased. Likewise, the analyses do not support the existence of a “village effect” 

related to the degree of dependence on artesian versus shallow wells. 

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