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[tracking no.]

TOXICOLOGICAL REVIEW

OF

INORGANIC ARSENIC

(CAS No. 7440-38-2)

In Support of Summary Information on the

Integrated Risk Information System (IRIS)

March 2009

NOTICE

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

(CAS No. 7440-38-2)

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

2. CHEMICAL AND PHYSICAL INFORMATION RELEVANT TO ASSESSMENTS 3

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

2.2 USES............................................................................................................................ 4

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

2.4 ENVIRONMENTAL FATE........................................................................................ 4

3. TOXICOKINETICS............................................................................................................. 4

3.1 ABSORPTION ............................................................................................................ 5

3.2 DISTRIBUTION.......................................................................................................... 7

3.2.1 Transport in Blood............................................................................................. 7

3.2.2 Tissue Distribution ............................................................................................ 9

3.2.3 Cellular Uptake, Distribution, and Transport.................................................. 11

3.3 METABOLISM......................................................................................................... 13

3.3.1 Reduction......................................................................................................... 16

3.3.2 Arsenic Methylation........................................................................................ 17

3.3.3 Species Differences in the Methylation of Arsenic......................................... 20

3.3.4 Thioarsenical Metabolites............................................................................... 21

3.4 ELIMINATION......................................................................................................... 22

3.5 PHYSIOLOGICALLY BASED TOXICOKINETIC MODELS............................... 23

4. HAZARD IDENTIFICATION.......................................................................................... 26

4.1 STUDIES IN HUMANS............................................................................................ 26

4.2 PRECHRONIC AND CHRONIC STUDIES AND CANCER BIOASSAYS IN 

ANIMALS—ORAL.................................................................................................. 52

4.2.1 Prechronic and Chronic Studies...................................................................... 52

4.2.2 Cancer Bioassays............................................................................................. 52

4.3 REPRODUCTIVE/DEVELOPMENTAL STUDIES—ORAL................................. 56

4.4 OTHER STUDIES..................................................................................................... 56

4.4.1 Possible Modes of Action (MOAs) and Key Events of Possible Importance. 56
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4.5 SYNTHESIS AND EVALUATION OF MAJOR NONCANCER EFFECTS ......... 79

4.6 WEIGHT-OF-EVIDENCE EVALUATION AND CANCER 

CHARACTERIZATION........................................................................................... 79

4.6.1 Summary of Overall Weight-of-Evidence....................................................... 79

4.6.2 Synthesis of Human, Animal, and Other Supporting Evidence ...................... 80

4.6.3 Mode of Action Information ........................................................................... 84

4.7 SUSCEPTIBLE POPULATIONS AND LIFE STAGES .......................................... 87

4.7.1 Possible Childhood Susceptibility................................................................... 87

4.7.2 Possible Gender Differences........................................................................... 89

4.7.3 Other................................................................................................................ 90

5. DOSE-RESPONSE ASSESSMENTS................................................................................ 95

5.1 ORAL REFERENCE DOSE (RfD)........................................................................... 95

5.2 INHALATION REFERENCE CONCENTRATION (RfC)...................................... 95

5.3 CANCER ASSESSMENT (Oral Exposure).............................................................. 95

5.3.1 Background: History of Cancer Risk Assessments for Arsenic.................... 95

5.3.2 Choice of Study/Data, Estimation Approach, and Input Assumptions......... 104

5.3.3 Dose-Response Model Selection for Cancer Mortality in Taiwan ............... 104

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

................................................................................................................................. 106

5.3.5 Non-Water Arsenic Intake and Drinking Water Consumption...................... 107

5.3.6 Dose-Response Data...................................................................................... 109

5.3.7 Risk Assessment Methodology ..................................................................... 110

5.3.8 Results........................................................................................................... 114

5.4 CANCER ASSESSMENT (Inhalation Exposure)................................................... 126

6. MAJOR CONCLUSIONS IN THE CHARACTERIZATION OF HAZARD AND 

DOSE RESPONSE.................................................................................................................... 126

6.1 HUMAN HAZARD POTENTIAL.......................................................................... 126

6.2 DOSE RESPONSE .................................................................................................. 128

6.2.1 Choice of Models .......................................................................................... 130

6.2.2 Dose Metric ................................................................................................... 131

6.2.3 Human Population Variability....................................................................... 131

7. REFERENCES.................................................................................................................. 133

APPENDIX A. SUMMARY OF EXTERNAL PEER REVIEW AND PUBLIC 

COMMENTS AND DISPOSITION........................................................................................ 173
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APPENDIX B: TABULAR DATA ON CANCER EPIDEMIOLOGY STUDIES............. 180

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

INORGANIC ARSENIC.......................................................................................................... 214

APPENDIX D. IMMUNOTOXICITY................................................................................... 395

APPENDIX E. QUANTITATIVE ISSUES IN THE CANCER RISK ASSESSMENT FOR 

INORGANIC ARSENIC.......................................................................................................... 401

E.1 Cancer Risk Assessment for the Taiwanese Population ......................................... 401

E.1.1 MLE Estimation of Dose-Response Parameters........................................... 402

E.1.2 Estimation of Upper Confidence Limits (UCLs) on the Arsenic DoseResponse Parameters............................................................................................... 402

E.2 Estimation of Risk for U.S. Populations Exposed to Arsenic in Drinking Water... 403

APPENDIX F. RISK ASSESSMENT FOR TOWNSHIPS AND LOW-EXPOSURE 

TAIWANESE POPULATIONS ............................................................................................. 405

F.1 Recent Studies of the Taiwanese Populations that Do Not Find Consistent ExposureResponse Relationships........................................................................................... 405

F.2 Limitations of the Recent Studies ........................................................................... 406

F.3 Calculations of Risks for Township Groups ........................................................... 407

F.4 Calculation of Arsenic-Related Cancer Risks for Low-Exposure Villages ............ 409
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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).................................................. 3

Table 4-1. Summary of Number of Rows Derived from Peer-reviewed Publications for 

Different Hypothesized Key Events* ................................................................... 60

Table 5-1. Historical Summary of Arsenic Risk Assessment Efforts.................................... 98

Table 5-2. Cancer Mortality Data used in the Arsenic Risk Assessment ............................ 110

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

Femalesa.............................................................................................................. 115

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

Population (Males and Females)......................................................................... 116

Table 5-5. Comparison of ED01 and LED01a Estimates From Past Studiesb with Those from 

the Current Analysis ........................................................................................... 117

Table 5-6. Comparison of Cancer Risk Assessment Results with Estimates from NRC 

(2001), and U.S. EPA (2005c)............................................................................ 119

Table 5-7. Drinking Water Intake and Body Weight Assumptions in Recent Arsenic Risk 

Assessments........................................................................................................ 119

Table 5-8. Sensitivity Analysis of Estimated Cancer Incidence Risks Associated with 10 

μg/L to Changes in Modeling Assumptions and Inputs...................................... 121

Table 5-9. Proportional Changes in Cancer Risks at 10 μg/L Associated with Changes in 

Modeling Inputs and Assumptions..................................................................... 122

Table B-1. Taiwan Cancer Studies ....................................................................................... 183

Table B-2. Japan Cancer Studies.......................................................................................... 197

Table B-3. South America Cancer Studies........................................................................... 198

Table B-4. North America Cancer Studies........................................................................... 203

Table B-5. China Cancer Studies.......................................................................................... 209

Table B-6. Finland Cancer Studies....................................................................................... 210

Table B-7. Denmark Cancer Studies..................................................................................... 212

Table B-8. Australia Cancer Studies..................................................................................... 213

Table C-1. In Vivo Human Studies Related to Possible Modes of Action of Arsenic in the 

Development of Cancer ...................................................................................... 232

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................... 242

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the 

Development of Cancer ...................................................................................... 267

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)........................ 396

Table F-1. Coefficients from Linear Regressions of Age-Adjusted Cancer Risk versus 

Arsenic Doses for Townships Identified by Lamm et al. (2006)........................ 409

Table F-2. Arsenic Dose Coefficients for Study Populations with Median Well Water 

Arsenic Concentrations Less than 127 ppb......................................................... 410
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LIST OF FIGURES

Figure 3–1. Traditional Metabolic Pathway for Inorganic Arsenic in Humans....................... 14

Figure 3–2. Alternative Metabolic Pathway for Inorganic Arsenic in Humans Proposed by 

Hayakawa et al. (2005)......................................................................................... 15

Figure 3-3 Thioarsenical Structures ....................................................................................... 21

Figure 4-1. Level of Significant Exposure of Adult Mice to Sodium Arsenite in Drinking 

Water in ppm As................................................................................................... 64

Figure 5-1. Estimated Oral Slope Factors for Individual and Combined Cancer Endpoints 116

Figure 5-2. Change in Arsenic-Related Unit Risk Estimates Associated with Variations in 

Input Assumptions.............................................................................................. 122

Figure F-1. Lifetime Crude Total Cancer Risk (Male + Female) for the Low- and HighExposure Villages............................................................................................... 408
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FOREWORD

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).
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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
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Susan M. Wells, MPH.

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

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

REVIEWERS

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

Washington, DC

Joyce Morrissey Donohue, Ph.D.

Office of Science and Technology

Office of Water

U.S. Environmental Protection Agency

Washington, DC

Hisham El-Masri, Ph.D.

National Health and Environmental Effects Research Laboratory

Office of Research and Development 

U.S. Environmental Protection Agency

Research Triangle Park, NC

Elaina Kenyon, Ph.D.

National Health and Environmental Effects Research Laboratory

Office of Research and Development 

U.S. Environmental Protection Agency

Research Triangle Park, NC

Kirk Kitchin, Ph.D.

National Health and Environmental Effects Research Laboratory

Office of Research and Development 

U.S. Environmental Protection Agency

Research Triangle Park, NC

Andrew Kligerman, Ph.D.

National Health and Environmental Effects Research Laboratory

Office of Research and Development 

U.S. Environmental Protection Agency

Research Triangle Park, NC

Danelle Lobdell, Ph.D.

National Health and Environmental Effects Research Laboratory

Office of Research and Development 
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U.S. Environmental Protection Agency

Research Triangle Park, NC

Bob Hetes

National Health and Environmental Effects Research Laboratory

Office of Research and Development 

U.S. Environmental Protection Agency

Research Triangle Park, NC

Stephen Nesnow, Ph.D.

National Health and Environmental Effects Research Laboratory

Office of Research and Development 

U.S. Environmental Protection Agency

Research Triangle Park, NC

Julian Preston, Ph.D.

National Health and Environmental Effects Research Laboratory

Office of Research and Development 

U.S. Environmental Protection Agency

Research Triangle Park, NC

David Thomas, Ph.D.

National Health and Environmental Effects Research Laboratory

Office of Research and Development 

U.S. Environmental Protection Agency

Research Triangle Park, NC

Nicole Shao

Office of Science Policy

Office of Research and Development 

U.S. Environmental Protection Agency

Washington, DC

Dennis Utterback

Office of Science Policy

Office of Research and Development 

U.S. Environmental Protection Agency

Washington, DC

Tim Wade, Ph.D.

National Health and Environmental Effects Research Laboratory

Office of Research and Development 

U.S. Environmental Protection Agency

Research Triangle Park, NC

Doug Wolf, DVM, Ph.D.
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National Health and Environmental Effects Research Laboratory

Office of Research and Development 

U.S. Environmental Protection Agency

Research Triangle Park, NC

EXTERNAL PEER REVIEWERS

Science Advisory Board (SAB) Arsenic Review Panel

CHAIR 

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

Johns Hopkins University, Baltimore, MD 

MEMBERS 

H. Vasken Aposhian, Ph.D.

The University of Arizona, Tucson, AZ 

Aaron Barchowsky, Ph.D.

University of Pittsburgh, Pittsburgh, PA 

David Brusick, Ph.D.

Retired, Convance Labs, Vienna, VA 

Kenneth P. Cantor, Ph.D.

National Cancer Institute, Bethesda, MD 

John (Jack) Colford, Ph.D.

University of California, Berkeley, CA 

Yvonne P. Dragan, Ph.D.

National Center for Toxicological Research (NCTR), Food and Drug Administration's (FDA), 

Jefferson, AR 

Sidney Green, Ph.D.

Howard University, Washington, DC 

Sioban Harlow, Ph.D.

University of Michigan, Ann Arbor, MI 

Steven Heeringa, Ph.D.

University of Michigan, Ann Arbor, MI 

Claudia Maria Hopenhayn, Ph.D.

University of Kentucky, Lexington, KY 
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James E. Klaunig, Ph.D.

Indiana University, Indianapolis, IN 

X. Chris Le, Ph.D.

University of Alberta, Edmonton, Alberta, Canada 

Michele Medinsky, Ph.D.

Toxcon, Durham, NC 

Kenneth Portier, Ph.D.

American Cancer Society, Atlanta, GA 

Barry Rosen, Ph.D.

Wayne State University, Detroit, MI 

Toby Rossman, Ph.D.

New York University, Tuxedo, NY 

Miroslav Styblo, Ph.D.

University of North Carolina, Chapel Hill, NC 

Justin Teeguarden, Ph.D.

Pacific Northwest National Laboratory, Richland, WA 

Michael Waalkes, Ph.D.

National Institute of Environmental Health Science, Research Triangle Park, NC 

Janice Yager, Ph.D.

Electric Power Research Institute, Palo Alto, CA 
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List of Abbreviations

∼ approximately (if before a listing of concentrations, it applies to all)

293 cells 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

AIC Akaike information criterion

AGT Average generation time

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, γ-GCS inhibitor)

BW or bw body weight

CA chromosome aberrations

Caco-2 Human intestinal cell line

CAE Cumulative arsenic exposure

CASRN CAS 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 human cell line thought to be derived from HeLa cells

CHO Chinese hamster ovary

CI confidence interval
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c-Jun or c-jun an AP-1 protein

CL3 cells human lung adenocarcinoma cells (established from a non-smallcell lung carcinoma)

COPD chronic obstructive pulmonary disease

DEB diepoxybutane (DNA cross linking 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

DMAIII dimethylarsenous acid

DMAV dimethylarsinic acid

DMA dimethyl arsenic (used when the oxidative state is unknown or not 

specified)

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

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

ER-α estrogen receptor-alpha

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 SV-40 transformed XPA human fibroblast NER-deficient cell line

GM-CSF granulocyte-macrophage colony-stimulating factor

GPx glutathione peroxidase

GSH Glutathione
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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 Substance Database

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 effective concentration

LOEL lowest observed effective 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

MMAIII monomethylarsonous acid

MMAV monomethyl arsonic acid

MMA monomethyl arsenic (used when oxidative state is unknown or not 

specified)

MMS methyl methanesulfonate

MN Micronuclei
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MNU N-methyl-N-nitrosourea

MOA mode(s) of action

MPR2/cMOAT Multi-drug resistance associated protein 2 transporter

MRP multidrug resistance protein

mRNA messenger ribonucleic acid

MTHFR methylene trihydrofolate reductase

NAC n-acetyl-cysteine

NAD nicotinamide adenine dinucleotide 

NADPH nicotinamide adenine dinucleotide phosphate-oxidase

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

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
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RT Real time

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

SIRs standard incidence ratios

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 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 an SV40-immortalized human urothelium cell line

UV ultraviolet radiation

V79 cells 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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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. IRIS Summaries may include oral reference dose (RfD) and inhalation reference 

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

assessment. 

The document is based on the EPA-sponsored 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. The NRC arsenic committee that 

wrote the reports took into consideration presentations at the committee’s public meetings, 

submitted public comments, 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 and external peer review by the Science Advisory Board (SAB).

Compared to the Toxicological Review submitted to the SAB in 2005, this assessment is 

expanded to provide a detailed review of epidemiological studies, and mode of action (MOA) 

studies, as well as the revisions in dose-response analysis to address the recommendations 

suggested by the SAB in 2007 (SAB, 2007). Specifically, additional sensitivity analysis on 

effects of modeling assumptions on estimated cancer risk is included in this revised 

Toxicological Review for cancer.

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) 

mode of action. 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 toxic effects for both the respiratory system (portal of entry) and for 

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 up to 30 days), and subchronic (>30 days up 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.
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The carcinogenicity assessment provides information on the carcinogenic hazard 

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

exposure 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 

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

low-dose extrapolation procedure. If derived, the oral slope factor 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. 

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

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

Research Council (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 Early-Life 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.
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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 states1

. 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 below.

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

Compounds (ATSDR, 2000; Merck Index, 1989)

As 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 5.727 3.738 4.32 1.87 1.87

Vapor Pressure 

(20°C)

--- --- --- --- ---

Water Solubility 

(g/100 mL)

insoluble 3.7 @ 20°C; 

11.5 @ 100°C

150 @ 16°C; 

76.7 @ 100°C

very soluble very soluble

Log Octanol/Water

Partition –

Coefficient (log 

Kow)

--- --- --- --- ---

Taste Threshold --- --- --- --- ---

Odor Threshold --- --- --- --- ---

Conversion Factor --- --- --- --- ---

--- No data available

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

arsenite can be abbreviated by either As(III) or AsIII. Both refer to trivalent inorganic arsenic compounds. This 

document uses the superscript abbreviation.
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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. Approximately 90% of the domestic 

consumption of arsenic is currently used with production of chromate copper arsenate (CCA), a 

wood preservative (ATSDR, 2007), the production of which is currently being phased out. 

2.3 OCCURRENCE

Arsenic naturally comprises ~ 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 1000–3400 ppb have been reported, especially in 

areas of the western United States). Average arsenic content in drinking water in the U.S. is 2 

ppb with 12% of water supplies from surface water in central portions of the U.S. and 12% of 

groundwater sources in western portions of the U.S. exceeding 20 ppb (ATSDR, 2007). Mean 

arsenic concentrations in ambient air have generally been found to range from 1 to 2000 ng/m3

(ATSDR, 2007). 

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. 

3. TOXICOKINETICS

Arsenic exposures discussed in this toxicology review are from oral waterborne arsenic 

exposure. Although inhalation exposures also are common, they are not addressed specifically 

in this report. Dermal exposure and exposure from food consumption, however, can potentially 

be significant and may be confounding variables in epidemiological studies. Therefore, 
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toxicokinetic information will focus mainly on oral exposure from water sources, but absorption 

issues from dermal exposure and arsenic in food also will be briefly addressed. 

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 the reactions 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 that will be seen 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 good evidence that key metabolic processes may be 

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

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. 

3.1 ABSORPTION

Water soluble forms of inorganic As (both trivalent and pentavalent) are readily absorbed 

from the GI tract of 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 7 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; and Hughes et al., 2005). Juhasz et 

al. (2006), however, using an in vivo swine test 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; 

and 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 and Juhasz et al., 2006). Laparra 

et al. (2005b) determined that while cooking rice (tested several types, but didn’t specify the 

types) 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-

17 fold over the raw rice. Rice samples (10 grams) were then subjected to an in vitro simulated 

digestion process. Levels of soluble arsenic were measured to determine 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. 

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 1000 ppb of AsV, which contained entirely inorganic As 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 is possibly a significant 

exposure route (Hostynek et al., 1993). The systemic absorption via the skin from less 
DRAFT—DO NOT CITE OR QUOTE 7

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 didn’t 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 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 seen 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 

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
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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; and 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 As elimination in humans has been observed to be triphasic, with first-order half-lives 

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 2 male chimpanzees had a half-life plasma elimination rate of 1.2 hour 

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; and Vahter et al., 

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 As 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 have presumably 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). 
DRAFT—DO NOT CITE OR QUOTE 9

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 Sadenosylmethionine (SAM; a proposed major reaction during arsenic metabolism; see below) 

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 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 As concentrations in these tissues of human subjects exposed to background levels 

of As ranged from 0.01 to 1.0 mg/kg of dry weight (Liebscher and Smith, 1968 and Cross et al., 

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

to inorganic arsenical medication, had higher As levels (0.8 to 8.9 ppm) than normal skin or 

malignant skin lesions from 6 subjects with no history of arsenic intake (0.4 to 1.0 ppm; Scott, 

1958). In West Bengal, India, where the average As concentration in the drinking water ranges 

from 193–737 ppb, As 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 

As species in the hair and fingernails of 41 subjects in West Bengal, India who were drinking As 

contaminated 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 As in these tissues resulting from other exposure pathways (e.g., 

dermal exposure) was not determined. 

The longest retention of inorganic As 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. As 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 As 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 As in the ocular lens or the 
DRAFT—DO NOT CITE OR QUOTE 10

thyroid (Vahter et al., 1982); however, intravenous administration of 74As-labelled DMA to mice 

resulted in accumulation of DMA in the ocular lens and the thyroid. Because marmoset 

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

thyroid, it would suggest that only the methylated species are retained in these organs. 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 9 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 As 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 As 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 As increased (this could indicate metabolic 

saturation or GSH depletion; see below for more details). A trimethylated form of As 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 As 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 As 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 As

V. 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 predominant 

form measure, while DMA was more prominent in the lungs and blood. The skin and urinary 
DRAFT—DO NOT CITE OR QUOTE 11

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 (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 compared to the liver in both 

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

AsIII and As

V, 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; and 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 

As 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 As in the 

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

mothers’ brains or in the newborns’ brains or livers. The level of total As 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 As 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 As 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 As 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 ppb 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 As 

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

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 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 
DRAFT—DO NOT CITE OR QUOTE 12

Cellular uptake of inorganic arsenic compounds also is dependent 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 As (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 As 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 by 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 

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

slower than in hamster RBCs. 

Cellular excretion of As species also is dependent 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) 1 transports AsIII

in the presence of GSH but did not transport AsV under any conditions, suggesting that AsV must 

be reduced to AsIII prior to its 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 
DRAFT—DO NOT CITE OR QUOTE 13

(Thomas, 2007). MRP2 expression was found to be five-fold higher in arsenic-resistant (R15) 

cells compared to the parent cell line (CL3). However, expression levels of MRP1 and MRP3 

were similar to 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; and 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 and Vahter and Marafante, 1985). Chemical 

inhibition of arsenic methylation in rabbits did not alter the intracellular distribution of arsenic 

(Marafante and Vahter, 1984 and Marafante et al., 1985). 

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

associated with increased As 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 As in the microsomal fraction 

of the liver in these rabbits were similar to those observed in the marmoset monkey (Vahter et 

al., 1982), indicating 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 below. 

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 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).

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 

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

monomethylarsonic diglutathione (MADG) was present. At concentrations of glutathione of 2.0 
DRAFT—DO NOT CITE OR QUOTE 14

mM or greater, there was a dose-dependent increase in DMAV levels, accompanied by a dosedependent decrease in AsV. 

Figure 3–1. Traditional Metabolic Pathway for Inorganic Arsenic in Humans

?

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

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 their article)2

 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 

(

, 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. 

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

named AS3MT. Therefore, in this document when an author refers to cyt19 it has been changed to AS3MT to avoid 

confusion and for uniform consistency. 
DRAFT—DO NOT CITE OR QUOTE 15

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

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

Figure 3–2. Alternative Metabolic Pathway for Inorganic Arsenic in Humans Proposed 

by Hayakawa et al. (2005) 

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

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

(2005) revised pathway. B6C3F1 mice administered MMAVper 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, greater 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 As metabolism (Thomas et al., 2001). 

In fact, pentavalent species of arsenic are not taken up by cells as readily as trivalent arsenicals 
DRAFT—DO NOT CITE OR QUOTE 16

(Dopp et al., 2004). In addition to this 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 

isolated from surgically removed liver tissue. Thomas et al. (2007) also state that 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 (2005) proposed pathway. Therefore, it is possible 

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 2–5 mM), suggesting that this indicated possible further methylation to 

DMAV. Since this is not part of the proposed Hayakawa et al. (2005) pathway, it would suggest 

that at least some of the MMAV is methylated through the classic pathway.

3.3.1 Reduction 

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

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

(Vahter and Envall, 1983; Vahter and Marafante, 1985; and 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; and 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 and 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 
DRAFT—DO NOT CITE OR QUOTE 17

(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 

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.

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 Escherichia coli (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 As 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; and 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. 
DRAFT—DO NOT CITE OR QUOTE 18

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

that the liver may be the primary site of arsenic methylation. However, the testes, kidney, 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 that oral administration of inorganic As 

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

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

through the liver first after oral administration. However, liver disease (i.e., alcoholic, postnecrotic 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 and Geubel et al., 1988). This appears to indicate that efficient 

methylation of arsenic continues in the presence of liver damage, possibly indicating 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. 

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 that 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 and 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 below in Section 3.4. 

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

concentrations of arsenic (Marafante and Vahter, 1984 and 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 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 
DRAFT—DO NOT CITE OR QUOTE 19

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).

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; 

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

the arsenic substrates (Lin et al., 2002 and 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 affect on DTT (1 mM)-

induced arsenic methylation. Drobná et al. (2004) linked the genetic polymorphism of AS3MT, 

with other cellular factors and to the interindividual variability in the capacity of primary human 

hepatocytes to retain and metabolize AsIII (see Section 4.7).

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. 

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, 
DRAFT—DO NOT CITE OR QUOTE 20

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 and Yamauchi and Yamamura, 1984). About 40% of urinary As 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 and 

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).

The rabbit (Marafante et al., 1981; Vahter and Marafante, 1983; and Maiorino and 

Aposhian, 1985) and hamster (Charbonneau et al., 1980; Yamauchi and Yamamura, 1984; and 

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 and Vahter, 1981). Guinea pigs (Healy et al., 

1997), marmoset monkeys (Vahter et al., 1982 and 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; and 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. 
DRAFT—DO NOT CITE OR QUOTE 21 

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 and 

NRC, 2001). 

 Although arsenic methylation is generally believed to take place in order to enhance 

excretion, there are several species (i.e., 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. In support of this is also 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. Hansen et al. (2004) tentatively 

identified the metabolite as dimethylmonothioarsinic acid (DMMTAIII), a sulfur containing 

derivative of DMAIII. 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 

the urine of Japanese men, but again, consumption of arsenosugars was suspected as a source of 

the observed arsenic containing species.

Figure 3-3 Thioarsenical Structures

DMMTAIII 

SH ─ AsIII ─ CH3

I 

CH3 

S 

II

 OH ─ AsV ─ CH3 

I 

CH3 

DMMTAV 

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 
DRAFT—DO NOT CITE OR QUOTE 22

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.

The above 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 

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; and 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 As elimination in humans has been observed to be triphasic, with first-order half-lives 

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 (oxidative states are 

generally not measured and/or specified) 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 As to DMA. The slow excretion is believed to be 
DRAFT—DO NOT CITE OR QUOTE 23

associated with retention of a significant portion of the DMA in erythrocytes (Odanaka et al., 

1980; Lerman and Clarkson, 1983; Vahter, 1983; and Vahter et al., 1984). The biliary excretion 

of inorganic As 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 

(MPR2/cMOAT) and that GSH is necessary for the transport, as arsenic-glutathione complexes 

accounted for the majority of arsenic found in the bile.

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 arseniccontaminated water in formula preparation. Parr et al. (1991) measured arsenic (as well as other 

elements) in the breast milk from 3 groups of mothers from four countries (i.e., Guatemala, 

Hungary, Nigeria, and the Philippines), and 1-2 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 quantitative dose-response (BBDR) assessment. 

The development of useful BBDR models has proved to be challenging because inorganic As 

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 As (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 
DRAFT—DO NOT CITE OR QUOTE 24

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 As 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 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; 

and 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; and Marafante and Vahter, 1987).

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 and 

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 As via drinking water, and occupational exposure to arsenic trioxide (ATO) 

(Harrington et al., 1978; Valentine et al., 1979; Buchet et al., 1981; and Vahter et al., 1986). The 

model predicted a slight decrease (i.e., 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 As species to MMA (pooled III and V oxidation 

states) and then to DMA were 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 and 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.
DRAFT—DO NOT CITE OR QUOTE 25

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 and 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). This data was 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) have not resulted in 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.

The Mann et al. (1996a,b) and Gentry et al. (2004) models are well-documented, 

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 

understand the mode(s) of action 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 related to arsenic methylation kinetics and suggested several 

steps for improving the PBPK models. El-Masri and Kenyon (2008; available online in October, 

2007) 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 As 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 also is 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 identifiability), and the model 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 and evaluation of the model for predicting the tissue and 

urinary concentrations of arsenicals in large number of subjects is needed. This model is an 
DRAFT—DO NOT CITE OR QUOTE 26

improvement over previous models because it can quantitatively assess impacts of parameter 

variability arising from genetic polymorphism.

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; Chen et 

al., 1988a,b; Wu et al., 1989; Hinwood et al., 1999; NRC, 1999; Tsai et al., 1999; Karagas et al., 

2001; Knobeloch et al., 2006; and Lamm et al., 2007). 

The SAB Arsenic Review Panel provided comments on key scientific issues associated 

with arsenicals on cancer risk estimation in July of 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-SAB-07-008, 

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. The 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 that the following issues be considered when reviewing “low-level” 

and “high level” studies: a) estimates of the level of exposure misclassification; b) temporal 

variability in assigning past arsenic levels from recent measurements; c) the extent of reliance on 

imputed exposure levels; d) the number of persons exposed at various estimated levels of 

waterborne arsenic; e) study response/participation rates; f) estimates of exposure variability; g) 

control selection methods in case-control studies; and h) 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 the 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 due to a wide range of concentrations 

employed and converting the arsenic levels or doses into ppb would not be reader friendly. 

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 (Tseng, 1977). Almost 

75% of the residence 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 ecologic 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. For this 

investigation 293 water samples were collected from the arseniasis endemic area from both deep 

artesian (n=134) and shallow (n=89) wells. The arsenic content was measured in 142 samples 

from 114 wells (110 artesian and 4 shallow) and ranged from 10 to 1820 ppb. The authors 

noted, however, that the arsenic content varied considerably over a two-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, 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 1000. 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 intra-epidermal carcinoma (51.7%), and the 
DRAFT—DO NOT CITE OR QUOTE 28

body areas most frequently involved were unexposed surfaces (74.5%). In addition, an 

extremely high percentage of cases with multiple skin cancer (99.5%) were 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, however, include the lack of individual exposure data 

(ecologic 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. 

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 1108 

patients with BFD (identified between 1958-1975). By the end of the follow-up period, almost 

half (i.e., 528) of the BFD patients had died. Tseng (1977) identified 428 cases (prevalence of 

10.6/1000) of skin cancer and 370 cases (prevalence of 9.0/1000) of BFD, and analyzed the 

relationship between the two. Skin cancer and BFD occurred in 61 cases (1.51/1000), but only 4 

cases (0.09/1000) 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 is important as it 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 (i.e., 28 and 19%, respectively) when compared to the 

general population of the endemic area (i.e., 13%) or to the entire population of Taiwan (i.e., 

8%).

Using the same 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 (cases/1000) 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 - 11.5, medium - 2.2, and low - 1.3); 40-59 years (high - 72.0, 

medium - 32.6, and low - 4.9); and 60+ years (high - 192.0, medium - 106.2, and low - 27.1). 

BFD prevalence rates by age and arsenic exposure group were as follows: 20-39 years (high -

14.2, medium - 13.2, and low - 4.5); 40-59 years (high - 46.9, medium - 32.0, and low - 10.5); 

60+ years (high - 61.4, medium - 32.2, and 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 arsenical 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. 

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 
DRAFT—DO NOT CITE OR QUOTE 29

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 compared to 

the remainder of Taiwan. Chen et al. (1985) cited arsenic results from 83,565 wells from all of 

Taiwan measured by Lo et al. (1977), which showed that 29.1% of the wells in the study areas 

had concentrations greater than 50 ppb (with the highest concentrations 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 1140 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 where only artesian wells were used 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, 

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. This study area was the same as examined by 

Chen et al. in 1985. Cases were selected from the Republic of China 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; however, there was a slightly higher proportion of male in liver 

cancer cases compared to controls. Other sociodemographic factors (marital status, educational, 

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 1140 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 
DRAFT—DO NOT CITE OR QUOTE 30

artesian well water and bladder and lung cancers (p<0.01) when other variable 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 that 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. 

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 life style, 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 

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; and >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 

dose-response 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.

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 in 

the Peimen, Hsuechia, Putai, and Ichu townships of southwest Taiwan and studied. 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 of the artesian well 

water in the BFD-endemic area. Study strengths are recall bias was minimized through 
DRAFT—DO NOT CITE OR QUOTE 31

interview techniques; interviews 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. The study weakness 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 cases received a urinary cytology 

examination. 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 possible other 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 significant weakness of this study. 

Wu et al. (1989) analyzed age-adjusted mortality rates using an ecologic study design to 

determine whether a dose-response relationship exits 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 life-style, access to medical care, and socioeconomic status were similar among 

the study groups. The use of mortality data can be considered as 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 
DRAFT—DO NOT CITE OR QUOTE 32

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 

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 were controlled for including socioeconomic differences (i.e., urbanization 

and industrialization), ecological correlations reported between arsenic content in well water and 

mortality from various cancers, and that 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. 

Chen et al. (1992) using an ecologic investigation 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 As 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 (i.e., 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 of drinking water from 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 of the liver, lung, bladder and 

kidney due to an intake of 10 μg/kg-day of arsenic was estimated to be 4.3 x 10-3

, 1.2 x 10-2, 1.2 

x 10-2

, and 4.2 x 10-3 for males and 3.6 x 10-3, 1.3 x 10-2, 1.7 x 10-2, and 4.8 x 10-3 for females,

respectively. Strengths include that potential confounders including age, gender, access to 

medical care, socioeconomic status, and life-style 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 included that the Armitage-Doll 

model constrains risk estimates to be monotonically increasing function of age, that dietary 

sources of arsenic were not quantified, and that age stratification was for under 30, over 70, and 

20-year strata.

 To determine whether a dose-response relationship exists between ingested inorganic As 
DRAFT—DO NOT CITE OR QUOTE 33

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 (i.e., Peimen, 

Hsuechia, Putai, and Ichu townships). Participants were followed for an average of 4.97 years 

(range: 0.05 to 7.69 years). Data concerning the consumption of artesian well water containing 

high levels of arsenic, sociodemographic characteristics, life-style and dietary habits, and cancer 

histories were obtained by means of 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 ecologic 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. Arsenic 

exposure in males was associated with adenocarcinomas of the bladder, but not in squamous cell 

carcinomas of the bladder or renal cell carcinomas or nephroblastomas of the kidney. Males also 

exhibited a positive association between the urbanization index and transitional cell carcinomas 

of the ureter. The results provide evidence to support the case that the carcinogenicity of arsenic 

may be cell-type specific. Analyses were adjusted for age, gender, urbanization, and smoking; 

however, the study’s ecologic design was a limitation. 

Tsai et al. (1999) conducted a cross-sectional study in BFD-endemic areas located in the 

southwest coast of Taiwan (i.e., 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=250-1140 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 
DRAFT—DO NOT CITE OR QUOTE 34

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 only one underlying cause of death (not multiple 

causes) was indicated on death certificate, resulting in possible distortion of association between 

exposure and disease; individual exposure data was 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-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 

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 ecologic study 

design. Depending on the model used and the comparison population used in the analysis, the 

1% excess risk dose (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. 
DRAFT—DO NOT CITE OR QUOTE 35

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. 

In summary, the Morales et al. (2000) analysis of the Taiwan data suggest 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 U.S. at the time of publication. The 

following are considered strengths of the study: person years at risk (PYR) were stratified by 5-

year age groups, gender, and median arsenic level for each village. Weaknesses include the 

ecologic study design (i.e., there was no individual monitoring data and individual exposures 

were not available), and potential confounders such as smoking, dietary arsenic, and the use of 

bottled water (U.S. population) were not controlled for in the analysis. 

Between 1991-1994, Chiou et al. (2001) recruited a cohort of 8102 residents aged 40 

years or older from 4 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, estimation of each 

study subject's individual exposure to inorganic As was determined. 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 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 relation 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 are 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.

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 was available from the previous investigation, and cases of skin cancer were identified 

using the Taiwanese National Cancer Registry. Data were analyzed with regression models 
DRAFT—DO NOT CITE OR QUOTE 36

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 2369 individuals with skin cancer 

(954 females and 1415 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. 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 ecologic study design. 

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 8798 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=2503) and the northeastern coast (Tungshan, Chuangwei, Chiaohsi, 

and Wuchieh; n=8088) of Taiwan. The amount of arsenic in well water from these areas ranged 
DRAFT—DO NOT CITE OR QUOTE 37

from less than 0.15 ppb to more than 3000 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 date of 

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), 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 arseniasis-hyperendemic 

southwestern coast villages, and residents living in the northeastern coast 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 when 

compared to non-smokers. A synergistic effect of ingested arsenic and cigarette smoking on 

lung cancer was noted, with synergy indices ranging from 1.62-2.52. 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). 

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 1971-2000. 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 the1983-1985 period (peak) and was 1.137 during 1998-2000. Data in 

males, however, showed fluctuations in liver cancer mortality rates. The SMR for liver cancer in 

males from 1989-1991 was 1.868 and 1.242 during 1998-2000. 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 ten 

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. 

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 
DRAFT—DO NOT CITE OR QUOTE 38

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. 

In a cross-sectional study, Yang et al. (2004) examined whether kidney cancer mortality 

decreased in the southwest coast of Taiwan (i.e., 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 1971-2000. 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 a -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 all births, deaths, marriages, divorces, and migration issues to 

the Household Registration Office in Taiwan, making it an accurate data source; a comparable 

study population (i.e., residents probably had similar socioeconomic status, living environments, 

lifestyles, dietary patterns; worked in farming, fisheries, or salt production); and had comparable 

access to medical care (i.e., all kidney cancer cases probably had similar access to medical care). 

Possible 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 U.S. and explore the potential 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% 
DRAFT—DO NOT CITE OR QUOTE 39

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. 

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. 

JAPAN

Tsuda et al. (1995) used a cohort study to investigate the long-term effect of ingesting 

arsenic in drinking water contaminated for estimated exposure period of 5 years (1955 and 

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 drunk 

well water containing a high concentration of arsenic (≥1000 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: 8.62-91.75). Cox's proportional hazard analyses demonstrated that the hazard ratios of 

the highest exposure level group (≥1000 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 3 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. 

SOUTH AMERICA
DRAFT—DO NOT CITE OR QUOTE 40

Hopenhayn-Rich et al. (1996a) used an ecologic study design to investigate bladder 

cancer mortality for the years 1986-1991 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 of 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 existed 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 study include the adjustment for age and gender, the use of stomach 

cancer as a non-arsenic-induced 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. 

To investigate dose-response relationships between arsenic exposure from drinking water 

and cancer mortality, Hopenhayn-Rich et al. (1998) conducted an ecologic study in Cordoba, 

Argentina. Cancer mortality from the lung, kidney, liver and skin during the period 1986-1991 

in 26 counties of Cordoba were studied. This investigation expanded the analysis of their 

previous study (Hopenhayn-Rich et al., 1996a), which only examined bladder cancer in Cordoba, 

Argentina. 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 
DRAFT—DO NOT CITE OR QUOTE 41

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 

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 As 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, dose 

response 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 one-month 

period in 1990). 

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 As 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 
DRAFT—DO NOT CITE OR QUOTE 42

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 

study during 1996-2000 in two Cordoba, Argentina 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 time-trend 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 ever smokers (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. 

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 reduced 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 in the period 1989-2000 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 
DRAFT—DO NOT CITE OR QUOTE 43

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 

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. 

Marshall et al. (2007) conducted an ecologic study to investigate lung and bladder cancer 

mortality from 1950-2000 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 1950-1970 identified 307,541 deaths from the two regions for 1971-2000. 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 until peaking between 1986 and 1997. The 

peak lung cancer mortality rate ratios for women and men were 3.26 (95% CI: 2.50 to 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 to 9.39), respectively. Together, lung 

and bladder cancer mortality rates in Region II were highest during the period 1992-1994, 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 infraction (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 15-20 year lag period following initial exposure to 

significantly elevated levels of arsenic from drinking water (1958-1970), mortality from bladder 

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 
DRAFT—DO NOT CITE OR QUOTE 44

on an individual basis, but were compared on a regional basis. 

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 were in the range 0.5-160 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 as well as 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 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, 

the results cannot be interpreted without consideration of potential confounders and bias 

resulting from the retrospective study design. 

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 Latter-day

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. 
DRAFT—DO NOT CITE OR QUOTE 45

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 increase risk for cancer of the bladder and other urinary 

organs (SMR=0.42, 95% CI: 0.08-1.22) in males. Among cohort females, there was no 

statistically significant increase in mortality observed. Females did, however, exhibit nonsignificant 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 air-borne), 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. A study weakness was that 

the study population was mostly rural and Morman (low tobacco and alcohol use). In addition, 

NRC (2001) identified that Lewis et al.’s (1999) 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, 

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 radio-therapy. 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 toenail arsenic concentrations 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. 

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. (2002) 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 
DRAFT—DO NOT CITE OR QUOTE 46

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 is 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 ecologic 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 

contain the largest populations historically exposed to arsenic via drinking water at levels of 

approximately 100 ppb. These populations provided Steinmaus et al. (2003) 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-supplies 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 were 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 
DRAFT—DO NOT CITE OR QUOTE 47

recent exposure, biasing the odds ratio towards the null. 

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 

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 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 accounts for arsenic exposure from other sources. A limitation of 

this study was that toenail samples were collected 2-3 years after diagnosis and therefore does 

not measure arsenic concentrations prior to diagnosis, resulting in possible exposure 

misclassification. 

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-

2.484 μg/g among bladder cancer cases and 0.009-1.077 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 ever smokers with 

the highest category of arsenic exposure with less than 15 years of use was identified (<15 years, 

OR=3.09, 95% CI: 0.80-1.19; ≥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 using a stratified 

analysis to evaluate the potential that an extended latency period was required for bladder cancer 

development and minimizing 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 
DRAFT—DO NOT CITE OR QUOTE 48

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 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. 

The Lamm et al. (2004) ecologic 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 groundwater arsenic concentration data were obtained for counties solely 

dependent on groundwater 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 was 

representative of actual arsenic content in the water, arsenic contribution from food sources were 

not analyzed, and 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, 2233 private wells were 

tested, and 6669 residents provided information on water consumption and health. Water arsenic 

levels ranged from less than 1.0 to 3100 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: 1) the large sample size; 2) a history of individual 

tobacco use; 3) arsenic well water analysis for each household; 4) an exposure duration of at 

least 10 years in participants who consumed water from the tested wells; and 5) the analysis 

controlled for age, gender, and tobacco use. Weaknesses include: 1) skin cancers were selfreported and not confirmed by a medical records review; 2) few people could provide 

information about specific types of cancer; 3) potential bias could have resulted from the 

participating families being concerned about arsenic exposure; 4) sun exposure and occupation 
DRAFT—DO NOT CITE OR QUOTE 49

were not controlled for in the analysis; and 5) food sources of arsenic were not considered. 

Meliker et al. (2007) performed an ecologic 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 groundwater 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 

that the ecologic study design did not provide individual arsenic exposure data and may not 

permit the detection of significant risk; possible 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. 

CHINA

Using an ecologic study design, Lamm et al. (2007) conducted dermatological 

examinations for 3179 of the 3228 (98.5%) residents of three villages (i.e., 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 2000 ppb. Individual water consumption histories were obtained for 

this population, and arsenic levels were measured for 184 wells. Arsenic exposures were 

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 (>30 years, Hei He-55.0%; Zhi Ji Liang and Tie 

Men Geng-42.4%). Participants (female or male) who reported occupations listed student or 

farmer. None of the examinations revealed any evidence of BFD. Analyses included frequencyweighted, simple linear regression, and most likely estimate models. Eight people were found to 

have skin cancer. In addition to skin cancer, these 8 cases also had both hyperkeratoses and 

dyspigmentation. Skin cancer cases were only identified in those participants with HAC 
DRAFT—DO NOT CITE OR QUOTE 50

exposures >150 ppb or whose CAE was less than 1000 ppb-years. The models showed a 

threshold of 122-150 ppb. Lamm et al. (2007) identified a general exposure-prevalence 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 HAC and CAE were used in the analyses, and that arsenic 

concentrations were measured in 184 wells. Confounders that were controlled for included age 

and differences in cumulative arsenic dose, and duration of exposure. A confounder not adjusted 

for in the analysis was sun exposure. An additional weakness of the investigation is the 

ecological study design, and the potential for recall or misclassification bias resulting from the 

collection of arsenic exposure histories through interviews. 

FINLAND

In a case-cohort study, Kurttio et al. (1999) examined the levels of arsenic in Finnish 

water wells and its 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 for cancer cases and for the reference cohort for two periods was estimated. 

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 1967-1980. 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 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 accessibility of Finnish Cancer Registry records; 

the 1985 Population Census file of the Statistics Finland was used to identify areas in which less 

than 10% of the population used the municipal water supply; and that 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. 

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–

1988 and 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 
DRAFT—DO NOT CITE OR QUOTE 51

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 they excluded toenail samples with non-detectable arsenic levels greater than 

0.09 μg/g, in an attempt to avoid potential misclassification of samples with high detection 

limits, and potential confounders were controlled for 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 toenail 

arsenic concentrations also could be considered a weakness because toenail arsenic is a 

biomarker of recent past exposure (covering about one year according to Cantor and Lubin, 

2007). The weakness of the study was that water consumption was not included in the total 

beverage intake variable. 

DENMARK

The Basstrup 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 of the prospective Danish cohort 

Diet, Cancer and Heath. 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 geographical 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 4954 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 nonmelanoma skin cancer (0.88, 95% CI: 0.84-0.94) decreased with per ppb increases in the timeweighted 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
DRAFT—DO NOT CITE OR QUOTE 52

possible misclassification bias. 

AUSTRALIA

Hinwood et al. (1999) conducted an ecologic 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-

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 

ecologic 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 and 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.
DRAFT—DO NOT CITE OR QUOTE 53

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. 

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. 

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), doseresponse 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, 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 this same procedure (except offspring were observed for 

104 weeks), but 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) were 
DRAFT—DO NOT CITE OR QUOTE 54

exposed to acetone or 12-O-tetradecanoyl phorbol-13-acetate (TPA; 2 μg/0.1 mL in acetone) 

twice a week to a shaved area of dorsal skin for 21 weeks after weaning in an attempt to promote 

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.

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 was 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.

Arsenic caused a statistically significant increase in the tumor multiplicity of all tumors 

in males (with or without TPA), which was not dependent on dose. Although females also had 

an increase in the tumor 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 dose-dependent in the 
DRAFT—DO NOT CITE OR QUOTE 55

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.

Waalkes et al. (2006a) used female CD1 mice, which have a low rate of spontaneous 

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 

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. 

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. 
DRAFT—DO NOT CITE OR QUOTE 56

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 and 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 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.

A critical review of the inhalation data was not conducted as part of this evaluation 

discussed in this report.

4.3 REPRODUCTIVE/DEVELOPMENTAL STUDIES—ORAL

Not addressed in this draft.

4.4 OTHER STUDIES

4.4.1 Possible Modes of Action (MOAs) and Key Events of Possible Importance
DRAFT—DO NOT CITE OR QUOTE 57

As discussed in Section 3.3, the metabolism of inorganic As 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 As 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 As are complex in mammals, 

with inorganic As 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 As 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 As 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 

where 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.

Based on its extensive review of health consequences of inorganic As in drinking water, 

NRC (1999) concluded that,

• “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 comutagenicity, 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 
DRAFT—DO NOT CITE OR QUOTE 58

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 their 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 (1999), report the prevailing view was that metabolism of 

inorganic As through several methylated forms represented a detoxification pathway. One of the 

fundamental changes in thinking about the effects of inorganic As since the NRC (1999) 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 As 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 As 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 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,

• “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 proto-oncogene (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 stress-response pathways; 

stimulation or inhibition of normal human keratinocyte cell proliferation, 
DRAFT—DO NOT CITE OR QUOTE 59

depending on the concentration; and altered function of the glucocorticoid 

receptor.”

 

Despite the extensive research on MOA up to that time, they 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.”

Tables were compiled in order to make a large amount of information on the biological

effects of inorganic As readily available. Appendix C contains Tables that deal with (1) in vivo

human studies (Table C-1), (2) in vivo experiments on laboratory animals (Table C-2), and (3) in 

vitro studies (Table C-3). An attempt was made to include in these tables as many experiments 

published from 2005 through August of 2007 as possible. Numerous earlier experiments have 

been included as well, based on various selection criteria, which included: being mentioned in 

the SAB Arsenic Review Panel comments of July of 2007 (SAB, 2007) or in NRC (NRC, 2001); 

or inclusion in an earlier draft that lacked tables (U.S. EPA, 2005c). The tables provide 

information on the (a) arsenic species tested, (b) the cell types, tissues, or species tested, (c) all 

concentrations or doses tested, (d) all durations of exposure, (e) estimates of the LOEC or LOEL 

(i.e., lowest observed effect concentration or level), (f) a summary of the most important results 

of each study, and (g) 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 the

categories for Apoptosis, Cytotoxicity, and Effects Related to Oxidative Stress (ROS).

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 As in drinking water) ranges from 20 to over 2000 ppb As (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 Events*

Hypothesized Key Events

Number of Rows in Tables 

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 Expressiona 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 Transformation or Morphological Transformation 0 0 13

Signal Transduction 1 2 51

* Details of the studies are presented in Appendix C. a

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 As in drinking water. Indeed four of the six studies related to 

the hypothesized key events of Aberrant Gene or Protein Expression compared groups of people 

with and without arsenic-related skin lesions following similar exposures to high levels of 

inorganic As in drinking water, and in three cases, they also compared them to groups of people 

with much lower inorganic As exposure levels. The genomics study by Argos et al. (2006)

showed that there were 312 additional genes down-regulated in the group with skin lesions than 

in the inorganic As-exposed group without such lesions. No genes were shown to be upregulated. 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 
DRAFT—DO NOT CITE OR QUOTE 61

transforming growth factor alpha (TGF-α) protein in bladder urothelial cells (Valenzuela et al., 

2007), and decreased levels of 3 integrins in and around skin lesions following exposures to 

inorganic As 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 As 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 

As-related urothelial cancer, but not in those from patients with non-As-related urothelial cancer 

(Hour et al., 2006).

The category of Chromosomal Aberrations and/or Genetic Instability 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 As 

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; and 

Moore et al., 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; and 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 cross-complementing 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 0.40 in that population (Banerjee et al., 2007). Although 

only some of the homozygotes heavily exposed to inorganic As in drinking water developed skin 

lesions or had chromosomal aberrations, those that were affected had both endpoints.

Table C-1 also provides data showing that oral inorganic As 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 (4 of whom died within about 12 hours after 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 
DRAFT—DO NOT CITE OR QUOTE 62

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 As 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 As 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 As 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 hypothesized key 

event category, and clearly some studies listed here under DNA Damage also relate to the

hypothesized key events of DNA Repair Inhibition or Stimulation and Effects Related to 

Oxidative Stress (ROS).

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 the key event of 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 the heading 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 and 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 arsenic-related 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 
DRAFT—DO NOT CITE OR QUOTE 63

showed no correlation (Fujino et al, 2005).

Evidence is presented under the category 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 

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. 

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, below.

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 row

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 
DRAFT—DO NOT CITE OR QUOTE 64

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 of the dose levels used exceed a couple thousand 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, more attention will be given in this discussion to doses that 

overlap higher exposure levels 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.

Figure 4-1. Level of Significant Exposure of Adult Mice to Sodium Arsenite in Drinking 

Water in ppm As

The aberrant gene or protein expression effects seen at those lower levels included 
DRAFT—DO NOT CITE OR QUOTE 65

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 and Soucy et al., 2005). However, 

increases in dose (up to 0.288 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 0.288 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 

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 (a) blood vessel number in Matrigel implants (Soucy et al., 

2005), (b) tumor growth rates after implantation of tumor cells (Kamat et al., 2005), and (c) 

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) As 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 As 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 As 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 and Shila et al., 2005a,b). By far the lowest dose tested among these 
DRAFT—DO NOT CITE OR QUOTE 66

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 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 As 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 3 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 As 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 2 doses (both cytotoxic) with the 2 noncytotoxic 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 As 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 dose 

response (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 2 genes was 

correlated with the extent of hypermethylation. Mice without tumors, whether control or Astreated, had normal (i.e., not reduced or eliminated) expression of these genes in their lungs. The 

authors concluded that epigenetic changes of tumor suppressor genes are involved in inorganic 

As-induced lung carcinogenesis (Cui et al., 2006). 

Of the experiments described in Table C-2 in which arsenic exposure occurred through 
DRAFT—DO NOT CITE OR QUOTE 67

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 

As 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: (a) arsenicinduced HCC tumors that developed in adult males; (b) normal appearing cells in livers of adult 

males; (c) fetal livers of males right at the end of treatment; (d) 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 As 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 estrogenrelated 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 
DRAFT—DO NOT CITE OR QUOTE 68

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 the categories 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 As 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 (and probably also of polyploidy) in mice that received 1.44 mg As/kg 

bw given as sodium arsenite by gavage once-per-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 As (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). 

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 5 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).
DRAFT—DO NOT CITE OR QUOTE 69

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; and 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: (a) 

the soft acid/soft base principle (which is related to trivalent arsenicals and sulfhydryl binding);

(b) the nucleophilicity of trivalent arsenicals; and (3) the formation of free radicals, ROS, or both 

by arsenicals (Kitchin et al., 2003). As noted by Kitchen et al. (2003),

• "If trivalent arsenicals acting as soft acids are causally important, then the likely 

modes of action of arsenic carcinogenesis may include altered DNA repair, 

altered growth factors, cell proliferation, altered DNA methylation patterns and 

promotion of carcinogenesis." 

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, Kitchen and Wallace (2006) suggested that dithiol- and trithiolbinding 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 the heading 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 As with organisms 

at early stages in multiple key event(s) leading to tumor development.
DRAFT—DO NOT CITE OR QUOTE 70

Much data is summarized in Table C-3 under the hypothesized key event category 

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 2000 

genes, the LOECs for SV40 large T-transformed 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. 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 with regard to the key event 

categories of Aberrant Gene or Protein Expression, Signal Transduction, and Effects Related to 

Oxidative Stress (ROS), all of which have large densities of data.

Table C-3 also presents details as to the genes and proteins affected and changes related 

to dose and time. The possible significance of such changes is also provided when available. A 

few examples are as follows. 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 also 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 regarding time and dose can be 

complicated and subject to many influences. 
DRAFT—DO NOT CITE OR QUOTE 71

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. A positive association between telomerase activity in cell lines and 

their susceptibility to induction of apoptosis by exposure to sodium arsenite was found. 

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 concentrations higher than those stated, 

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 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 ATOinduced 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; and 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 category of Cell Cycle Arrest or Reduced Proliferation 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 
DRAFT—DO NOT CITE OR QUOTE 72

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 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 As

III 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 As

III, 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 the category 

Chromosomal Aberrations and/or Genetic Instability to show that inorganic As 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 

As

III, 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 As

III, and it 

appears that CAs, SCEs, and MN are all induced to roughly the same extent by As

III. Some 

experiments fail to show a dose response, which makes them difficult to interpret.

Several of the experiments on CAs provided evidence of arsenic induced changes in 

chromosome number (e.g., Barret et al., 1989 and Ochi et al., 2004). In the Ochi et al. (2004) 
DRAFT—DO NOT CITE OR QUOTE 73

experiment, DMAIII was much more potent than As

III, 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 and 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 As

III

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 

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 As

III markedly increased the cellular uptake of BPDE in a 

dose-dependent manner. 

The results found under the category 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 Nmethyl-N-nitrosourea (MNU). Many of the types of mutations affected were gene mutations
DRAFT—DO NOT CITE OR QUOTE 74

(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 

hypoxanthine-guanine 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 in the category 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 AsIIIwere 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 3 different 

cytotoxicity assays yielded substantially different 24-hour LC50s for each of 5 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 As

III, 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 

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 As 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 doseresponse 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 much experimental data is 

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 
DRAFT—DO NOT CITE OR QUOTE 75

crosslinks, and DNA damage was induced at levels of sodium arsenite that caused no 

cytotoxicity in 2 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 arsenitewas shown to 

be effective. However, MMAIII was shown to be about 200 times more effective than As

III (with 

an LOEC of 0.05 μM) following a one-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 category of DNA Repair Inhibition or Stimulation 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 

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 category Effects Related to Oxidative Stress (ROS) 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 As

III 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 As

III, 
DRAFT—DO NOT CITE OR QUOTE 76

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 cells 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. 

Little information is included in Table C-3 regarding Enzyme Activity Inhibition. Hu et 

al. (1998) and Snow et al. (1999) tested the effect of sodium arsenite on the activity of several 

purified enzymes 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 As

III 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; and Mure et al., 2003). 

Takahashi et al. (2002) showed that several neoplastic transformed cell lines produced by 48-

hour treatments with either ≤ 8 μM As

III

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 dose 

response 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 and 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 
DRAFT—DO NOT CITE OR QUOTE 77

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).

The category Immune System Response in 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 provides a 

much more detailed discussion of some aspects of the immunotoxicity of inorganic arsenic, 

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 As

III 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 0.06–0.70 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 As

III. 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 
DRAFT—DO NOT CITE OR QUOTE 78

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 

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 As

III 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 arsenitewas 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, As

III 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 arsenitewas shown to delay differentiation and preserve the proliferative potential of 

keratinocytes (Patterson et al., 2005 and 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 hrs 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 the category Malignant Transformation or Morphological Transformation, Table 

C-3 shows that concentrations of less than 1 μM of As

III, MMAIII, or DMAIII are capable of 

causing transformation. HaCaT cells exposed to 0.5 μM As

III 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 that there was 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). In contrast, at a dose of 10 μM after the same exposure duration 

of 48 hours, As

III had only transformed 0.48% of the surviving cells.
DRAFT—DO NOT CITE OR QUOTE 79

Many findings related to the category Signal Transduction are summarized in Table C-3 

even though considerable data found under Aberrant Gene or Protein Expression could 

alternatively 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 direction 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 one hour activated the pro-survival 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 SY5Y and the human embryonic kidney cell line HEK 293).

4.5 SYNTHESIS AND EVALUATION OF MAJOR NONCANCER EFFECTS

Not addressed in this document.

4.6 WEIGHT-OF-EVIDENCE EVALUATION AND CANCER 

CHARACTERIZATION

4.6.1 Summary of Overall Weight-of-Evidence

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. Arsenic is a multisite carcinogen with numerous studies finding arsenic 

associated with increased incidences of a number of different types of cancers. The carcinogenic 
DRAFT—DO NOT CITE OR QUOTE 80

effect of arsenic has been reported for populations in many different countries. While the studies 

detailed in this report provide evidence for cancer after oral exposure to arsenic, the fact that 

arsenic also has been associated with cancer after inhalation exposure (U.S. EPA, 1994) provides 

additional support.

 

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, etc.), 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 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., life style 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 non-water 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 1973-1986). 

Population 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.

Although there have been dose-response relationships 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 Begal, India the contribution of arsenic from food was the main 
DRAFT—DO NOT CITE OR QUOTE 81

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. Average estimate of inorganic As consumption in food ranges from 1.34

μg/day in infants to a high of 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 towards 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 (Kuritto 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 is very little animal data demonstrating arsenic’s carcinogenic potential. This is 

likely due to the fact that rodents, which are the most likely animal model, are better methylators 

of arsenic than humans (Vahter, 1999a). Since it has been noted that humans that 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; and 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 

look at 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; and 

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. 

Beane-Freeman et al. (2004) also found an increase in the risk of melanoma with elevated toenail 
DRAFT—DO NOT CITE OR QUOTE 82

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, 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 sun block 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 

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 10-20 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 10-20 year lag period after removal of the arsenic source, mortality from bladder

cancers still exceeded that observed in regions with consistently low arsenic exposure. 
DRAFT—DO NOT CITE OR QUOTE 83

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, U.S., and Denmark. 

Although inorganic As 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.

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 As in mice when exposed during gestation. Pregnant dams were exposed 

for 10 days during gestation only; thereby, increasing 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.

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, it 

provides 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 and El-Masri and 

Kenyon, 2008) and in 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.
DRAFT—DO NOT CITE OR QUOTE 84

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 

As 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 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. 

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 a full understanding of the dose 

response of the identified key events mediating the carcinogenesis is known.

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 
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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 As would lead to more than the critical (threshold) 

concentration of DMAIII for a particular individual for a sufficient time could result in bladder 

cancer.

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 fulfils 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. 

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 As 

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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• “ ...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.” 

Oxidative stress seems particularly attractive as an important early step for some of the following 

reasons. Some ROS species 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, highlevel 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; Shackelford et al., 2000; Bolton, et al. 2000; and 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 base-pair 

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; and Lander, 1997). Activation of 

signal transduction pathways that enhance cell proliferation, reduce antiproliferative signaling, 

and override checkpoint 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 that suggest inorganic As 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 review can be caused by inorganic arsenic at exposure levels comparable to, or 

smaller 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 As 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 
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carcinogenesis, various scientific tools (e.g., genomic tools, human pharmacokinetic and 

biologically based dose response 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 inorganic arsenic’s MOA is unknown, a linear lowdose 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; and 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 

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. 

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 to25% as MMA. Concha et al. 
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(1998b), however, determined children ingesting 200 ppb (μg/L) arsenic in their drinking water 

excreted about 49% as inorganic As 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; and 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. 

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; and Jin et al., 2006a). 

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 emigrated 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 

 3 The artesian wells were introduced in 1910 to 1920, prior sources of fresh water included ponds, streams, 

or rainwater (Tseng, 1968).
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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 As 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, and 

2006a). Thus demonstrating 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 slope factor 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.

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 compared to women 

in a variety of populations tested, including in the U.S. (Hopenhayn-Rich et al., 1996b and 

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, and sometime by exposure level. 

Based on mean urinary metabolites 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., 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.

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 and 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 
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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 eleven families (father, mother, and 2 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 

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. 

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 to11 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, which in turn had lower MMA:DMA ratios than 

individuals lacking the alleles. Because the proportion of ingested inorganic As 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 1041 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 
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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. 

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 woman 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.

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 As ratio was associated with a 1.5-fold increase in risk of 

skin lesions. There was a significant interactive affect between GSTT1 wildtype and secondary 

methylation on skin lesions, but no interactive affects 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 wildtype (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 woman 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.

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 compared to 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 2-2.5 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 

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 compared to 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 (Se) has been demonstrated to reduce the teratogenic, clastogenic, and 

cytogenic effects of arsenic (ATSDR, 1993). Chen et al. (2007) found 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. Christian et al. (2006) found in 93 pregnant women from Antofagasta 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 

proportion of urinary MMA was fairly consistent in the study population. Using 4 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 As excreted decreased with increasing selenium intake, but only in the 
DRAFT—DO NOT CITE OR QUOTE 94

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.

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 caused a significant increase in 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. In Heck et al.’s (2007) study, they 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 were small in comparison with the known 

magnitude of interindividual 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 
DRAFT—DO NOT CITE OR QUOTE 95

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 

two-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 U.S. 

Although the results indicated increased MMA was associated with increased cancer risk, the 

number of cases was too small to estimate separate odds ratios for never-smokers and eversmokers.

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.

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 1820 μg/L. The 

occurrence of skin cancer was estimated in a survey lasting approximately two 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. 
DRAFT—DO NOT CITE OR QUOTE 96

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 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; 

additional modeling analyses were recommended. NRC 1999 applied absolute Taiwan risks to 

the U.S. populations. 

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 cancer slope factors 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 requested 

the 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 the Agency’s Science Advisory Board (SAB) for review and comment. 

The 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 
DRAFT—DO NOT CITE OR QUOTE 97

EPA’s reimplementation of the technical cancer risk modeling recommendations in NRC (2001), 

with additional examination of arsenic exposure assumptions and taking into account SAB’s

(2007) advice for the expansion of sensitivity analyses of modeling methods and choices.
DRAFT—DO NOT CITE OR QUOTE 98

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, but was

“not a risk assessment”

Test dose-response 

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 

epidemiological 

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 representations, 

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 of 

arseniasis endemic 

area

With and without AllTaiwanNone, southwest 

Taiwan, All-Taiwan

None All-Taiwan, 

southwest Taiwan 

southwest Taiwan

-As Concentration Stratified; 0-300, 

300-600, 600-900

μg/L in well water, 

unknown exposure 

Median well As 

concentrations

Median well As 

concentrations

Median well As

concentrations

Median; 

sensitivity 

analysis of other 

values

Median well As 

concentrations
DRAFT—DO NOT CITE OR QUOTE 99

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

Recommendations 

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)

-Non-Water As 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 US 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 US 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 = 

3x10-5 per μg/L 

(females), 

7x10-5 per μg/L 

(males); 

Slope factors = 

1 to 2x10-3 per 

mg/kg-day 

(incidence) 

Lifetime bladder 

cancer risk at 10 μg/L 

= 3x10-3 (males), 

9x10-3 (females)

ED01 = 404-431 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

Slope Factors 

derived from 

Morales et al. 

(2000) ED01, LED 

01 values.

Unit risk, per 

μg/L:

Male bladder= 

2.5x10-5 (MLE), 

3.1x10-5 (UCL)

Male lung = 

2.8x10-5 (MLE), 

3.4x10-5 (UCL)

Female bladder = 

4.0x10-5 (MLE), 

4.7x10-5 (UCL) 

Female lung=

3.9x10-5, (MLE), 

4.7x10-5 (UCL) 

Lifetime cancer 

risk incidence 

from 10 μg/L:

Male

lung = 1.8x10-3

bladder = 2.3x10-3

Female

lung = 1.4x10-3

bladder = 1.2x10-3

Female lung + 

bladder incidence:

Unit Risk = 

1.6x10-4 per μg/L

Incidence at 10 

μg/L in drinking 

water = 1.6x10-3

; 

Drinking water 

concentration for 

10-4 incidence risk 

= 0.63 μg/L
DRAFT—DO NOT CITE OR QUOTE 101

The techniques and assumptions used in the 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, this 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:

• The scope and goals of each assessment. 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, 2008) 

• Selection of critical studies for use in the risk assessment. As noted above the 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 epidemiological 

studies (Wu, 1989; Chen et al., 1988a, 1992), which provide information on person-years 

at risk and cancer mortality in narrowly defined age strata, and exposure concentrations 

from individual water supply wells. 

• 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 substantial 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 
DRAFT—DO NOT CITE OR QUOTE 102

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 1964-1966 for the each of 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 is little 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 

followed this consensus. Following other analyses, this assessment assumes an average 

body weight of 50 kg for both Taiwanese men and women. 

• Non-water 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 non-water arsenic intake. 

The various assumptions used in previous analyses are summarized in Table 5-1, and the 

basis for non-water 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 non-water 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.
DRAFT—DO NOT CITE OR QUOTE 103

• 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. Another ingredient required to predict cancer risks 

in the U.S. population are estimates of the drinking water intake and typical body weight 

of the exposed 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, 

cancer slope factors, 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 assessment, since converting from one measure to another can require 

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), estimate 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 have also varied from assessment to 

assessment. As discussed above, the cancer slope factor from U.S. EPA’s (1988b) 

assessment, which is derived based on skin cancer prevalence, is not directly comparable to 

slope factors derived from internal cancer data in the later assessments. Modeling methods 

and assumptions used in the current assessment, and precisely how they differ from previous 

analyses, are discussed in more detail in 5.3.8.2. 
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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 sufficient quality data to use in 

human dose-response modeling (NRC, 2001 and 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) agree 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 (40,421), 

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, to the extent practicable 

within resource and time constraints.

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 other 10 villages water was supplied by 2 wells; however, 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.

In addition to villages where drinking water arsenic concentrations were measured, the 

epidemiological data used in this assessment includes information on the cancer mortality in two 
DRAFT—DO NOT CITE OR QUOTE 105

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 non-water 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 

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. 

NRC (2001) reviewed the U.S. EPA (2001) cancer assessment including application of 

the model from the Morales et al. 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, and
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• 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 (non-water 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 

and NRC, 2001). Oral slope factors 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 

southwest Taiwanese population were 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 were 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.

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 one percent 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
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Carcinogen Risk Assessment (U.S. EPA, 2005a) and the NRC (2001) cancer assessment, risk 

estimates are derived based a linear extrapolation from the points of departure (LED01s for lung, 

bladder, and combined cancers).

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 U.S. 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 2000-2003 (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.

5.3.5 Non-Water Arsenic Intake and Drinking Water Consumption

It is important to clarify that the non-water arsenic intake value corresponds to the 

arsenic amount from dietary sources (rice and yam, the staple diet in Taiwanese population in 

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 (see below).

For the baseline risk calculations, the non-water 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 2-16 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 potatoes (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 ranging 

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 nonendemic 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 non-water 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 non-water arsenic 

intake (food sources) in baseline calculations. Alternate values of non-water 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 
DRAFT—DO NOT CITE OR QUOTE 108

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 non-water intake values in the exposed 

populations. It is not clear if NRC (2001) assumed any non-water arsenic intake value for the 

reference populations. In the draft Toxicological Review submitted to SAB in 2005 (U.S. EPA, 

2005c), non-water 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 

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 non-water inorganic arsenic intake value for the reference population. 

Given the state of the available data and the recommendations from SAB, EPA has 

assumed 10 μg/day non-water 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 in NRC reports (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 yam (staple 

diets in 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 
DRAFT—DO NOT CITE OR QUOTE 109

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) 

where the climate is close to Taiwan. The average drinking water intake values for children, 

adult females and adult males were reported as 2.0, 3.0, and 4.0 L/day, respectively.

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 slope factor 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 person-years at risk (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. Data from only one well were available for twentyone of the 42 villages. Between 2 and 47 well concentrations were provided for the other 22 

villages (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 

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: 

• 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 non-water 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 

years 2000-2003 (NCI, 2006) were used as the reference values for calculating U.S. 

Gender

Village Water 

Concentration, 

μg/L

Age 20-30 30-49 50-69 >70 Total

Male

<100

PYRa 35,818 34,196 21,040 4,401 95,455 

Deathsb (0, 0, 0) (1, 10, 2) (6, 17, 12) (10, 4, 14) (17, 31, 28) 

100-299 PYR 18,578 16,301 10,223 2,166 47,268 

Deaths (0, 0, 0) (0, 4, 3) (7, 15, 14) (2, 4, 13) (9, 23, 30) 

300-599 PYR 27,556 25,544 15,747 3,221 72,068 

Deaths (0, 3, 0) (5, 7, 9) (15, 23, 30) (12, 6, 14) (32, 39, 53) 

>600 PYR 16,609 15,773 8,573 1,224 42,179 

Deaths (0, 0, 1) (4, 12, 3) (15, 15, 23) (8, 2, 6) (27, 29, 33) 

Total PYR 98,561 91,814 55,583 11,012 256,970 

Deaths (0, 3, 1) (10, 33, 17) (43, 70, 79) (32, 16, 47) (85, 122, 144)

Female

<100 PYR 27,901 32,471 21,556 5,047 86,975 

Deaths (0, 0, 0) (3, 1, 5) (9, 6, 18) (9, 5, 5) (21, 12, 29) 

100-299 PYR 13,381 15,514 11,357 2,960 43,212 

Deaths (0, 0, 0) (0, 3, 4) (9, 6, 10) (2, 5, 5) (11, 14, 19) 

300-599 PYR 19,831 24,343 16,881 3,848 64,903 

Deaths (0, 0, 0) (0, 5, 6) (19, 6, 20) (11, 2, 10) (30, 13, 36) 

>600 PYR 12,988 15,540 9,084 1,257 38,869 

Deaths (0, 0, 0) (0, 4, 6) (21, 7, 28) (7, 1, 4) (28, 12, 38) 

Total

PYR 74,101 87,868 58,878 13,112 233,959 

Deaths (0, 0, 1) (3, 13, 21) (58, 25, 76) (29, 13, 24) (90, 51, 122) 
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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). 

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 cancer 

slope factors. Unit Risks and slope factors calculations adjusted for differences between body 

weights and drinking water ingestion rates in Taiwan and the U.S. 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) (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 person years at risk (PYR) data were available for five-year 

ranges for ages 20-84. 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 

criteria4

:

h(x,t) = exp(a1 + a2*age + a3*age2) * (1 + b* dose) (5-2)

Where: a1, a2, a3 = age coefficients

b = dose coefficient

 4 Results obtained using alternative model forms are discussed in Section 5.3.8.4.
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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 five-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 five-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 non-water 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 non-water 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 

“nuisance parameters” implies that the calculated confidence limits are only approximate. 
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Confidence limit calculations using other methods (empirical Bayesian simulation5 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 the previous section). The BEIR 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 equaled 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 cancer slope factor. 

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 2000-2003 were obtained from the National Cancer Institute’s SEER 

(surveillance epidemiology and end result) program (NCI, 2006). Arsenic intakes resulting in 

10-2 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 Cancer Slope Factor for the endpoint:

Oral Cancer Slope Factor (per mg/kg-day) = 0.01/LED01 (5-3)

 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 U.S.
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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) = Cancer Slope Factor (per mg/kg-day) * 0.001 * DW/BW

(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 US 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 Cancer Slope Factors and Unit Risks 

Table 5-3 presents the estimated risk metrics for lung, bladder, and combined cancers in 

males and females under baseline assumptions (see Footnote “a” to the table for baseline 

modeling assumptions).

The estimated oral slope factor 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 slope factors for males and 

females are comparable (11.2 and 10.5 per mg/kg-day, respectively). Drinking water unit risks 

for lung cancer are 1.9x10-4 and 4.8x10-4 per μg/L, respectively, for males and females while the 

drinking water unit risks for bladder cancer are 3.2x10-4 and 3.0x10-4 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 slope factor, 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 slope factor, 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 non-water 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.

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 are 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 uncertainty in the two cancer 

slope factors are both normally distributed. If this is the case, the 95% upper bound, U, for the 

combined cancer potency can be calculated as:

2

22

2

21 11 −+−++= mumummU )()()( (5-5) 

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 4.8x10-4 per μg/L; for females, the estimated value is 7.3x10-4

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 slope factor, 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

 

Figure 5-1 shows the estimated oral slope factors for each of the endpoints separately, 

along with oral slope factor estimates for the combined cancers in males and females. In 

keeping with EPA policy, the combined cancer slope factor for women (25.7 per mg/kgday) is appropriate for use in establishing health criteria, since, based on the available 

data, women appear to be the more sensitive group. 

Figure 5-1. Estimated Oral Slope Factors for Individual and Combined Cancer 

Endpoints

0

5

10

15

20

25

30

Male Lung Male

Bladder

Male

Combined 

Female

Lung 

Female

Bladder

Female

Combined

Cancer Slope Factor, per mg/kg-day

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 and U.S. 
DRAFT—DO NOT CITE OR QUOTE 117

EPA, 2005c). Note that the results of the U.S. EPA (1988b) analysis, which estimated a cancer 

slope factor of 1.0 – 2.0 per mg/kg-day, are not comparable to the results of the current 

assessment (slope factor 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 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.

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

1992). 

NRC calculated ED01 and LED01 values for lung and bladder cancer mortality from the 

same Taiwanese cohort as 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.

Table 5-5. Comparison of ED01 and LED01a Estimates From Past Studiesb with Those 

from the Current Analysis

Study Male Lung Female Lung Male Bladder Female Bladder

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 four-year 

period in 8000 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. 

 

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 the 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 greater than 100 μg/L in water; 

non-water 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. 

Estimated Risk Associated with 10 μg/L Drinking Water Arsenic from NRC (2001) and 

U.S. EPA (2005c) 
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Table 5-6 provides an additional set of comparisons between the current risk estimates 

and the results from two previous analyses by NRC and EPA. 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). As expected, the minor differences in 

assessment methods between the NRC (2001) and U.S. EPA (2005c) analyses had very little 

impact on the risk estimates. For all four endpoints, the difference in risks estimated in the two 

studies is less than 10%.

 

Table 5-6. Comparison of Cancer Risk Assessment Results with Estimates from NRC 

(2001), and U.S. EPA (2005c)

Source of 

Estimate

Estimated Cancer Incidence at 10 μg/L Arsenic in 

Drinking Water (per 10,000 exposed population)

Bladder Lung

Male Female Male Female 

NRC (2001), Taiwan 23 12 14 18

EPA (2005c)a 21 11 13 18

Current Analysis 32 30 19 48 a The original mortality risk estimates from U.S. EPA (2005c) were multiplied by incidence-mortality 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). 

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 

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 seen in Table 5-6. The lower ratio in the current analysis translates into a two-fold greater 

estimated risk for females in the current assessment than in the NRC (2001) and U.S. EPA 

(2005c) analyses. 

Table 5-7. Drinking Water Intake and Body Weight Assumptions in Females in Recent 

Arsenic Risk Assessments

Assessment

Body Weight, kg Water Intake, L/day Ratio of 

Taiwan/U.S. 

Drinking 

Taiwan U.S. Taiwan U.S. 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
DRAFT—DO NOT CITE OR QUOTE 120

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 non-water arsenic intake also would be expected to 

have small to moderate affects on the results within the range in question. In this assessment, 

both the reference and exposed populations are assumed to receive 10 μg/day non-water arsenic 

intake (see Section 5.3.5). Section 5.3.8.3 presents the results of uncertainty analyses which 

explore the effects of changes in selected modeling assumptions, including non-water arsenic 

intake, on the risk estimates. 

5.3.8.3 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: 

• Varying the assumed daily non-water arsenic intake of the exposed and reference 

populations. Sensitivity cases were run in which the non-water 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 non-water arsenic exposure. Because the 

Poisson risk model for female bladder cancer is particularly sensitive to changes in 

assumptions related to non-water arsenic intakes (see below), non-water arsenic intake 

was limited to below 50 μg/day in reference populations.

• 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.
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• 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 5-8 and 5-9 summarize the results of the sensitivity analysis runs. Table 5-8 

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 5-9 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.

Table 5-8. 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

Non-water As intake = 0μg/day (reference and exposed 

populations) 1.9E-03 4.6E-03 3.0E-03 2.6E-03

Non-water As intake = 30 μg/day (reference and 

exposed populations) 2.0E-03 5.1E-03 3.5E-03 4.5E-03

Non-water As intake = 50 μg/day (reference and 

exposed populations) 2.0E-03 5.5E-03 3.9E-03 1.1E-02

Non-water As intake (exposed population) = 0 μg/day 1.9E-03 4.8E-03 3.2E-03 3.0E-03

Non-water As intake (exposed population) = 100 μg/day 1.8E-03 4.4E-03 3.0E-03 2.8E-03

Non-water As intake (exposed population) = 200 μg/day 1.7E-03 3.9E-03 2.8E-03 2.4E-03

Taiwan H20 consumption = 3.0 L/day (M), 2.0 L/day (F) 2.3E-03 4.8E-03 3.8E-03 3.0E-03

Taiwan H20 consumption = 5.1 L/day (M), 4.1 L/day (F) 1.3E-03 2.3E-03 2.2E-03 1.4E-03

Taiwan H20 consumption = 2.75 L/day (M, F) 2.5E-03 3.4E-03 4.1E-03 2.1E-03

Village H20 As concentrations = minimum values 2.5E-03 5.7E-03 4.0E-03 4.0E-03

Village H20 As 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 non-water 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 5-9. 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%

Non-water As intake = 0 μg/day (reference and exposed 

populations) 0% -4% -6% -13%

Non-water As intake = 30 μg/day (reference and exposed 

populations) 5% 6% 9% 50%

Non-water As intake = 50 μg/day (reference and exposed 

populations) 5% 15% 22% 267%

Non-water As intake (exposed population) = 0 μg/day 0% 0% 0% 0%

Non-water As intake (exposed population) = 100 μg/day -5% -8% -6% -7%

Non-water As intake (exposed population) = 200 μg/day -11% -19% -13% -20%

Taiwan H20 consumption = 3.0 L/day (M), 2.0 L/day (F) 21% 0% 19% 0%

Taiwan H20 consumption = 5.1 L/day (M), 4.1 L/day (F) -32% -52% -31% -53%

Taiwan H20 consumption = 2.75 L/day (M, F) 32% -29% 28% -30%

Village H20 As concentrations = minimum values 32% 19% 25% 33%

Village H20 As 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.

Figure 5-2. Change in Arsenic-Related Unit Risk Estimates Associated with Variations 

in Input Assumptions

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 Baseline

Taiwan

Male Lung

Female Lung

Male Bladder

Female Bladder
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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 non-water arsenic 

intake for the reference and/or exposed populations results in small changes (<25%) in the 

estimated oral slope factor and cancer risks at 10 μg/L in drinking water. Risk estimates for 

female bladder cancer, in contrast, are quite sensitive to changes in non-water arsenic intake in 

the range from zero to 50 μg/day. When non-water 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 non-water arsenic intake 

increases to 50 μg/day, female bladder cancer risks increases by 267% compared to baseline. 

The sensitivity of the risks estimates are greater for changes in reference population arsenic 

intake; when non-water intake increases to 100 and 200 μg/day for the exposed populations 

alone, the impact on female bladder cancer risks is 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 show 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 

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 non-water arsenic intake by the reference population in the range 

between zero 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.

5.3.8.4 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 5-2 shows EPA’s baseline model, which is “linear Poisson” 

with the form:

h(x,t) = exp(a1 + a2*age + a3*age2

) * (1 + b* dose) (5-2)

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) (5-6)

In addition, two models in which the dose dependence was exponential, one linear and one 

quadratic, also were tested:

h(x,t) = exp(a1 + a2*age + a3*age2) * Exp(b0 + b1*dose) (5-7)

h(x,t) = exp(a1 + a2*age + a3*age2) * Exp(b0 + b1*dose + b2*dose2) (5-8)

The last model (Equation 5-8) was specifically recommended by SAB (2007) for 

evaluation. In the discussion that follows, these four models will be referred to, respectively, as 

the “linear” (baseline) model (Equation 5-2), quadratic model (Equation 5-6), linear exponential 

model (Equation 5-7), and quadratic exponential model (Equation 5-8).7

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 zero to 0.05 mg/kg-day in 

males, which corresponds to an arsenic drinking water concentration range of 0 to 710 μg/L

 7 “Absolute risk” models, (models where 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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(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 60-65 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. 

5.3.8.5 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 et al. 

(2003) found that combined male and female lung, bladder, and liver cancer 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 

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.

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 
DRAFT—DO NOT CITE OR QUOTE 126

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 Kayanjanian’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. 

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 cancer slope factor was developed for inorganic arsenic and posted on the 

IRIS database in 1988. A re-assessment of the cancer dose-response estimation for inhalation 

exposure to inorganic arsenic is not addressed in this document. 

6. MAJOR CONCLUSIONS IN THE CHARACTERIZATION OF HAZARD AND 

DOSE RESPONSE

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 
DRAFT—DO NOT CITE OR QUOTE 127

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. 

After absorption, inorganic As can undergo a complicated series of enzymatic and nonenzymatic 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 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, there have been 

numerous epidemiological studies examining the carcinogenic potential of inorganic As via oral 

exposure. Although each of the investigations has their own inherent strengths and weaknesses, 

the combination of all the study results supports an association between oral exposure to 

inorganic As and cancer including bladder, kidney, skin, lung, liver, and prostate. Because the 

association between arsenic and these cancers have 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 individuals that 

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 life-style factors contribute to the 

interindividual variations.

Although there has been dose-response relationships 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 and 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 towards 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 and Lewis et al., 1999), skin (Hinwood et al., 1999; Karagas et al, 
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2001; Beane-Freeman et al., 2004; and Knobeloch et al., 2006), and bladder (Kuritto et al., 1999; 

Steinmaus et al., 2003; and Karagas et al, 2004). In most cases, however, there is no doseresponse with increases observed at the highest concentrations only and in many cases 

significant results occurred in smokers only. 

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 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 were then estimated by 
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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 slope factors for lung and bladder cancers in U.S. males and females were 

derived using the following assumptions: non-water 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 U.S. consumes 2.0 L/day of water (Section 5.3.5). The oral slope factor 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 10-4 lifetime cancer risk, etc.). Sensitivity analyses were 

performed to test the effects of differences in drinking water intake assumptions, non-water 

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 to be relatively stable and react predictably to 

reasonable changes in exposure assumptions. Female bladder cancer estimates were particularly 

sensitive to variations in non-water arsenic intake. 

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 

exposure-response 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 and U.S. EPA, 2005c). The bulk of 
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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 

relating to the relative drinking water consumption by women in Taiwan and the U.S., and by 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 slope factor 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, first, because the data used in the 

dose-response assessment come from human epidemiology rather than animal bioassays. The 

Taiwanese 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 endemic area versus 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, a reference population, and adjusts for 

differences between the exposed and target (i.e., U.S.) populations.

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 versus 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 the Agency and others, and has incorporated 

comments and recommendations by NRC (2001) and the Science Advisory Board (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. 
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Sensitivity analyses of other models (quadratic, exponential linear, and exponential quadratic 

dose transformation) were also evaluated (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 the 

2000-2003 (NCI, 2006) were used as inputs to the BEIR IV model.

6.2.2 Dose Metric 

Inorganic As 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; and McCarthy et al., 2007a); therefore, the 

actual carcinogenic moiety may not be proportional to administered exposure and use of 

administered exposure may provide a bias in the model. However, the exposure assessment for 

the model is ecological in nature and provides 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. 

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 As 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 40-49 born 

between 1950-1957 and in males aged 30-49 born between 1950 and 1970. However, the risks 

associated with early childhood exposures and/or in utero exposures were not compared to risks 
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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 

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 undergone a formal external peer 

review performed by scientists in accordance with EPA guidance on peer review (U.S. EPA, 

2000a). For the external peer review, the reviewers 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 external peer review panel (SAB) 

was supplied with questions regarding both DMAV and inorganic arsenic, only questions and 

responses pertaining to inorganic arsenic will be addressed in this Appendix. Charge question 

B3 asked the 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 the 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. 

Charge Question B3

EPA concluded that iAs causes human cancer most likely by many different modes of 

action. This is based on the observed findings that iAs 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 the SAB to comment on the soundness of its 

conclusion. 

SAB Comments

The Panel concluded that: 

i) Multiple modes of action may operate in carcinogenesis induced by iAs because 

there is simultaneous exposure to multiple metabolic products as well as 

multiple target organs and the composition of metabolites can differ in different 

organs. 

ii) Each arsenic metabolite has its own cytotoxic and genotoxic capability. 

iii) 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, iAs can 

act as a transplacental carcinogen and a cocarcinogen. 
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iv) 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 iAs. 

v) 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 dataset remains the most appropriate choice 

for estimating cancer risk in humans. The 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 iAs. 

SAB Comments

The Panel concluded that: 

i) Because of various factors (e.g., 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. 

ii) 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. 

iii) The Panel also suggests that published epidemiology studies of US 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 
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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. 

iv) Regarding childhood exposure to iAs, 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 consideration of additional studies, EPA agreed with the 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). With regard to children, 

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 as to the 

differential susceptibility of children to arsenic exposure. EPA notes that recent animal studies 

demonstrating the potential for cancer after in utero arsenic exposures gives rise to additional 

concerns regarding exposures early in development. 

Charge Question D2

EPA determined that the most prudent approach for modeling cancer risk from iAs 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 the 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 iAs. 

SAB Comments

The Panel concluded that: 

i) Inorganic arsenic has the potential for a highly complex mode of action. 
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ii) Until more is learned about the complex PK and PD properties of iAs and its 

metabolites there is not sufficient justification for the choice of a specific 

nonlinear form of the dose-response relationship. 

iii) The NRC (2001) recommendation to base risk assessments on a linear dose 

response model that includes the Southwestern Taiwan population as a 

comparison group seems the most appropriate approach. 

iv) 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 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 non-water 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 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 non-linear low-dose 

extrapolation from the point of departure (POD).

Charge Question D3

EPA employed the Microsoft Excel software that was previously used by the NRC 

(2001) to project estimated cancer risks from iAs exposure. The SAB was asked to comment on 

the precision and accuracy of this program. 

SAB Comments

The Panel concluded: 
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i) 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. 

ii) 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. 

iii) 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. 

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 US general population from drinking water 

exposure to iAs, the EPA utilized 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 

USEPA, 2005b), EPA utilized water intake adjustments for 2 to 3.5 liters/day. EPA asked the 

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 dose-
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response 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: 

i) 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). 

ii) 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. 

iii) Conduct sensitivity analyses of the impact of using a range of 

consumption values for the Taiwanese population. 

iv) 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. 

v) 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 

(non-water) arsenic intake in the Taiwanese study populations. EPA, therefore, conducted a 

series of sensitivity analyses involving ranges of drinking water consumption and “background” 

(non-water) arsenic consumption that the Agency believes spans a reasonable range of values for 

these parameters. Arsenic dose-response models were fit assuming non-water arsenic intakes of 

0, 10, 30, 50, 100, and 200 μg/day in the exposed populations, non-water arsenic intake of 0, 30, 

and 50 μg/day in the reference population, and for male (Taiwanese) daily water consumption 

ranging from 2.75-5.1 L/day and female water consumption ranging from 2.0-4.1 L/day. 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 non-water 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 the NRC (2001) EPA considered the background dietary intake of 

iAs and incorporated adjustment values of 0, 10, 30, and 50 μg per day into the cancer modeling 

based on available new data. The SAB was asked to recommend a value for the background 
DRAFT—DO NOT CITE OR QUOTE 179

dietary intake of iAs 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: 

i) 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. 

ii) Not assume that the control population has an intake value of zero arsenic from food. 

iii) Apply greater rigor in their discussions of data used in these assessments (e.g., sources, 

methodological and analytical issues, bioavailability). 

iv) Give immediate research attention to the issue of arsenic bioavailability.

EPA Response

As discussed in the previous response, EPA conducted sensitivity analyses that assumed 

non-water arsenic intakes (doses) for the exposed populations ranging from 0-200 μg/day and 

ranging from 0-50 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 non-water dietary arsenic and bioavailability 

thereof. 
DRAFT—DO NOT CITE OR QUOTE 180

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 of 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-SAB-07-008, 

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. The 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 that the following issues be considered when 

reviewing “low-level” and “high level” studies: a) estimates of the level of exposure 

misclassification; b) temporal variability in assigning past arsenic levels from recent 

measurements; c) the extent of reliance on imputed exposure levels; d) the number of persons 

exposed at various estimated levels of waterborne arsenic; e) study response/participation rates; 

f) estimates of exposure variability; g) control selection methods in case-control studies; and h) 

the resulting influence of these factors on the magnitude and statistical stability of cancer risk 

estimates.

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 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 the 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 

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).

Cross-sectional studies have inherent limitations including: 1) difficulty in making causal 

inference; 2) data collected for only one point in time, and 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. 
DRAFT—DO NOT CITE OR QUOTE 181

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 ecologicalstudies arise from the fact that estimates of effect do not equate to estimates of 

biological effect obtained from individual level analysis, that 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 postselecting 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 that comprise the study population have any 

control over whether or not they are allowed to participate. An individuals’ decision to 

participate in a study may be associated with other factors that affect the study, which results in 
DRAFT—DO NOT CITE OR QUOTE 182

the participants being a non-representative sample.

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.
DRAFT—DO NOT CITE OR QUOTE 183

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 overL=48.1, M=163.4, H=255.3, 

U=148.2

Total all males combinedL= 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 overL= 9.1, M= 62.0, H= 110.1, U= 

62.9 

Total all females combinedL= 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 overL=27.1, M= 106.2, H= 192.0, 

U= 107.9 

Total both genders combinedL= 2.6, M= 10.1, H= 21.4, U= 

10.4 

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 were information on 

smoking histories, and the arsenic 

concentration from individual wells 

varied over time. 

Tseng et al., 

1968

Ecological
DRAFT—DO NOT CITE OR QUOTE 184

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

Observed rate/1000:

Hyperpigmentation = 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 yearsL =1.3, M = 2.2, H = 11.5

40-59 yearsL = 4.9, M = 32.6, H = 72.0

60+ yearsL = 27.1, M = 106.2, H = 192.0

Blackfoot disease

20-39 yearsL = 4.5, M = 13.2, H = 14.2

40-59 yearsL = 10.5, M = 32.0, H = 46.9

60+ yearsL = 20.3, M = 32.2, H = 61.4

Skin cancer and BFD combinedObserved – 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

1968-

1982 Subjects from 

BFD endemic 

area

Median arsenic concentration 

(ppb): 

artesian well water- 780 

(range, 350-1140)

shallow well water40 (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 –

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:

Chen et al., 

1985

ecological
DRAFT—DO NOT CITE OR QUOTE 185

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

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)

-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

January 

1980-

December 

1982

Deceased 

cancer cases69 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 valueBladder 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

Case-control

1973-

1986

Blackfoot 

endemic area 

residents

Population of 

Taiwan as 

reference 

population

World 

population as 

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

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
DRAFT—DO NOT CITE OR QUOTE 186

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

reference 

population

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 

January 

1968-

December 

1983

241 cases

759 controls

General 

population of 

Taiwan 

Local endemic 

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) 

Strengths:

-Cases consisted of black foot 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.

Chen et al., 

1988b

Cohort/ 

Nested casecontrol
DRAFT—DO NOT CITE OR QUOTE 187

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

area population

Significant SMRs (p values) 

(compared to population of BFD 

endemic area):

Cancers –

bladder = 2.55 (<0.01)

skin = 4.51 (<0.05)

lung = 2.84 (<0.01)

liver = 2.48 (<0.01)

Weakness:

-Arsenic dose levels were not 

provided.

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

Case-control

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 testCancersboth 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.

-Life-style, 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
DRAFT—DO NOT CITE OR QUOTE 188

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

1972-

1983

Arsenic 

exposed 

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 of the 

remainder of the wells were 

not given.

Multivariate adjusted regression 

coefficient for cancers (SE): 

Malesliver = 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);

Femalesliver = 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

1973-

1986

Arsenic 

exposed 

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): malesliver = 4.3 x 10-3 

lung = 1.2 x 10-2 

bladder = 1.2 x 10-2 

kidney = 4.2 x 10-3 

women –

liver = 3.6 x 10-3 

lung = 1.3 x 10-2 

bladder = 1.7 x 10-2 

kidney = 4.8 x 10-3

Strengths:

-Potential confounders included age, 

gender, access to medical care, 

socioeconomic status, and life-style 

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 the assumption was made that 

an individuals arsenic intake remained 

Chen et al., 

1992

Ecological 
DRAFT—DO NOT CITE OR QUOTE 189

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

constant from birth to the end of the 

follow-up period.

-Assumption that an individual’s 

arsenic intake remained constant from 

birth to the end of the follow-up period 

and the possible underestimation of 

risk because other sources of arsenic 

exposure were not considered.

Followedup for 

0.05-7.69 

years 

[4.97 

±1.72 

(SD) 

years] 

until 

January 

1993

263 BFD cases 

2293 healthy 

residents

Artesian well water median 

arsenic level=

780 ppb

Shallow well water median 

arsenic level=

40 ppb 

Multivariate adjusted RR (95% 

CI), cancer:

All sitesAge: Every-l-yr increment =1.05 

(1.03-1.06)*

Sex : Men =1.00, 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 x 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)

LungAge: 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-.57)*

Cumulative arsenic exposure 

Strengths:

-Showed a significant dose response 

relationship with increasing 

concentrations of arsenic.

-Analysis adjusted for BFD status, age, 

sex, and smoking.

-Reported incidence data.

Weaknesses:

-Artesian well water arsenic 

concentration was unknown for some 

study subjects.

Chiou et al., 

1995

Cohort
DRAFT—DO NOT CITE OR QUOTE 190

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

(mg/liter x 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)

BladderAge: 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:

No = 1.00, Yes = 4.41 (2.06-

9.45)*

Cumulative arsenic exposure 

(mg/liter x 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:

MalesBladder 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)

FemalesUrethral 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
DRAFT—DO NOT CITE OR QUOTE 191

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.

MalesBFD 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)

FemalesBFD 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<.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

Cross-sectional

1973-

1986

42 arseniasis 

endemic 

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

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
DRAFT—DO NOT CITE OR QUOTE 192

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

500-600 ppb = 3.32

600+ ppb = 5.14

Liver cancer SMRs*:

0-50 ppb = 1.18

50-100 ppb = .65

100-200 ppb = 1.74

200-300 ppb = 1.44

300-400 ppb = .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.

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 organs10.1-50.0= 1.5 (0.3-8.0)

Strengths:

- Showed a significant dose response 

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 was 

collected from various community 

Chiou et al., 

2001

Cohort
DRAFT—DO NOT CITE OR QUOTE 193

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

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)

hospitals.

-Possible recall bias resulting from 

self-reported information.

- Short duration of follow-up, which 

limited the number of person-years of 

observation.

-Possible misclassification especially 

in the low-dose region due to lack of 

arsenic exposure information in the 

food.

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)* :

MalesBasal 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)**

FemalesSquamous 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 board certified 

pathologists.

-Potential confounders adjusted for in 

the analysis included gender and age.

Weakness:

-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 board certified 

pathologists.

-Potential confounders adjusted for 

included gender and age.

Weaknesses:

Guo, 2003

Ecological
DRAFT—DO NOT CITE OR QUOTE 194

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

-Limitations of ecological study 

design. (No monitoring data were 

presented).

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, 

1989-91 = 1.868

1998-2000 = 1.242

Females, 

1983-85 = 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

January 

1971-

December 

1990

1078 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 person years

Women: 

18.93/100,00 person years 

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.

Guo, 2004

Ecological
DRAFT—DO NOT CITE OR QUOTE 195

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

Weaknesses:

-Limitations of ecological studies.

-Smoking was not controlled for in the 

analysis. 

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

Cross-sectional

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

Cross-sectional

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)

Strengths:

-All bladder cancer cases in the area 

probably had similar access to medical 

care. 

Yang et al., 

2005

Cross-sectional
DRAFT—DO NOT CITE OR QUOTE 196

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

Females = 14.89 (7 vs. 0.47)

2000: 

Males = 2.15 (5 vs. 2.32)

Females = 7.63 (10 vs. 1.31)

-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.
DRAFT—DO NOT CITE OR QUOTE 197

Table B-2. Japan Cancer Studies

Study 

Period

Subjects/ 

Controls Exposure 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):

malesall 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)

femalesall 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
DRAFT—DO NOT CITE OR QUOTE 198

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 categoryMen

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.

Hopenhayn-Rich, 

et al.

1996a

Ecological

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 cancerMen

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)

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.

Hopenhayn-Rich 

et al. 

1998

Ecological
DRAFT—DO NOT CITE OR QUOTE 199

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

medium= 1.34 (1.12-1.58)

high= 2.16 (1.83-2.52)

P < 0.001 in trend test

1989-

1993

390,340 

residents

national 

mortality 

data from 

1991

Population of 

Chile used as 

reference 

group

Region II average water 

arsenic level (ppb):

1950-54 = 123

1955-59 = 569

1960-64 = 568

1965-69 = 568

1970-74 = 272

1975-79 = 176

1980-84 = 94

1985-89 = 71

1990-94 = 43

SMRs (95% CI, p value)

≥ 30 years old: 

menbladder - 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)

womenbladder - 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

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)

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

Case-control
DRAFT—DO NOT CITE OR QUOTE 200

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

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)

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

Case-control

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 

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-

Strengths: 

-Extensive documentation of arsenic in 

drinking water in the Antofagasta water 

system.

Weaknesses: 

-Residence was determined from death 

Smith et al., 2006

Cohort
DRAFT—DO NOT CITE OR QUOTE 201

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

water supply. 1971) with probable exposure in 

utero and early childhood:

lung cancer = 6.1 

(3.5-9.9, p<0.001)

certificates and relates to residence at 

the time at death.

-Reliance on death certificates resulting 

in potential diagnostic bias.

-Information bias (smoking history).

1950-

2000

Region II 

residents 

Region V 

residents as 

comparison 

group

Population of 

Chile

Average arsenic concentration 

(ppb):

Region II

1950-54 = 123

1955-59 = 569

1960-64 = 568

1965-69 = 568

1970-74 = 272

1975-79 = 176

1980-84 = 94

1985-89 = 71

1990-94 = 43

Region V

Unexposed

Peak Rate Ratios (95% CI) 

compared to Region V and Chile:

Lung Cancer 

1992-94 

Men

3.61 (3.13-4.16) (Region V)

4.20 (3.76-4.70) (Chile)

1989-91

Women

3.26 (2.50-4.23) (Region V)

3.41 (2.76-4.22) (Chile)

Bladder Cancer

1986-88

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

1950-

2000

314,807 

exposed

1,230,498 

unexposed

Average water concentration 

(ppb) in Region II:

Before arsenic removal plant1950-1957 = 90 

1958-1970 = 870

After arsenic removal plant1971-1985 = 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

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, 

Yuan et al., 2007 

Ecological
DRAFT—DO NOT CITE OR QUOTE 202

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

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

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.
DRAFT—DO NOT CITE OR QUOTE 203

Table B-4. North America Cancer Studies

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

39 years 

(endpoint1978 

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 mgyears).

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 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

Case-control

1996

2,203 

deceased 

individuals 

from Millard 

County 

General Utah 

population 

used as 

comparison

Arsenic exposure index (ppbyears)-

low: <1000

medium: 1000-4999

high: >5000 

Cancer SMRs (95% CI):

kidneymales = 1.75 (0.80-3.32)

females = 1.60 (0.44-4.11)

bladder and other urinary organsmales = 0.42 (0.08-1.22)

females = 0.81 (0.10-2.93)

melanoma of the skinfemales = 1.82 (0.50-4.66)

prostate = 1.45* (1.07-1.91)

*p ≤ 0.05

Strengths:

-Major strength of the study is that it 

measured the effects of chronic arsenic 

exposure in U. S. population.

-Advantages of cohort design including 

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 

Lewis et al., 1999

Cohort 
DRAFT—DO NOT CITE OR QUOTE 204

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

arsenic from food were potential 

confounder.

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 arsenic induced skin cancer 

unknown, follow-up period may have 

been inadequate.

-Toenail arsenic measurements only 

account for recent past exposure.

Karagas et al., 

2001

Case-Control

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 

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.

Steinmaus et al., 

2003

Case-control
DRAFT—DO NOT CITE OR QUOTE 205

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

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.

Weaknesses:

-Information bias (next- of -kin 

interviews).

-Arsenic exposures outside the study 

area were not incorporated.

-In the arsenic exposed areas, the 

percentage of nonparticipants was five 

percent 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.

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% C.I. = 1.4-3.3, 

p-trend = 0.001) for increased risk 

of melanoma with elevated 

toenail arsenic concentrations

OR=6.6 (C.I. = 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 assured 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 

Beane-Freeman et 

al., 

2004

Case-control
DRAFT—DO NOT CITE OR QUOTE 206

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

misclassification. 

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

Case-Control

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 groundwater 

(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)

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 

Lamm et al., 2004

Ecological
DRAFT—DO NOT CITE OR QUOTE 207

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

All levels combined =

0.94 (0.90-0.98)

actual arsenic content of water. 

-Analysis did not directly adjust for 

smoking, urbanization, and 

industrialization.

-Arsenic contribution from food was not 

measured.

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)

Genderfemale = referent

males = 2.25 (1.33-3.79)

Cigarette useno = 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 self-reported 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

Cross-sectional

1979-

1997

Residents of 

six Michigan 

counties

Remainder of 

Michigan 

population as 

comparison

Population-weighted mean 

arsenic concentration (ppb) 

exposed counties = 11.00 

remainder of Michigan= 2.98

Elevated cancer SMRs (95% CI)

malesliver/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)

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 

Meliker et al., 

2007

Ecological
DRAFT—DO NOT CITE OR QUOTE 208

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

bladder = 0.94 (0.82-1.08)

kidney/urinary =1.06 (0.91-1.22)

femalesliver/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

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.
DRAFT—DO NOT CITE OR QUOTE 209

Table B-5. China Cancer Studies

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

1990 3179 

residents

HAC (ppb):

<10

10-

30-

50-

60-

100-

150-

500+

CAE (ppb-year):

<10

10-

32-

100-

316-

1000-

3162-

10000+

Crude and (age adjusted) 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 (age-adjusted) 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 ecologic study 

design.

-Did not control for sun exposure.

Lamm et al., 2007

Ecological
DRAFT—DO NOT CITE OR QUOTE 210

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 latencyWater 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 latencyWater 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 the 

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

1985-

1988 and 

April 

1999

280 incident 

bladder 

cancer cases

293 controls

Arsenic exposure quartiles 

(μg/g):

I - <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 toe nail 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 

Michaud et al., 

2004

Cohort/ Nested 

case- control
DRAFT—DO NOT CITE OR QUOTE 211

Study 

Period

Subjects/ 

Controls Exposure Assessment Study Outcome 

Strengths/

Weaknesses

Reference/

Type of Study

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.
DRAFT—DO NOT CITE OR QUOTE 212

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:

Copenhagenmelanoma = 0.73 (0.46-1.14)

non-melanoma = 

1.09 (0.95-1.24)

breast = 1.04 (0.88-1.22)

Aarhusmelanoma =0.85 (0.61-1.20)

non-melanoma = 

0.97 (0.90-1.05)

breast = 1.06 (1.01-1.11)

Cumulative exposure:

Copenhagenmelanoma = 0.94 (0.81-1.08)

non-melanoma = 

1.01 (0.97-1.06)

breast =1.01 (0.95-1.06)

Aarhusmelanoma = 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
DRAFT—DO NOT CITE OR QUOTE 213

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 leukemia1.54 (1.13-2.10)

females, breast1.10 (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
DRAFT—DO NOT CITE OR QUOTE 214

Appendix C. Tables for Studies on Possible Mode of Action for Inorganic Arsenic

This appendix contains three tables that deal with possible modes of action (MOA) of 

arsenic in the development of cancer based on (1) in vivo human studies (Table C-1), (2) in vivo

experiments on laboratory animals (Table C-2), and (3) in vitro studies (Table C-3). They 

describe numerous experiments published from 2005 through August of 2007, as well as earlier 

experiments that were mentioned in the (a) Science Advisory Board Arsenic Review Panel 

comments of July of 2007 (SAB, 2007), (b) 2001 NRC document on arsenic (NRC, 2001), or (c) 

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.

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 that 

the expansion of the vertical height of the table was not be impacted so much by the description 

of the results. 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 

(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. 

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 
DRAFT—DO NOT CITE OR QUOTE 215

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, for example, there were 6 concentrations tested, 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 is 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, which mean that they are 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; however, 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 As 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. 
DRAFT—DO NOT CITE OR QUOTE 216

Abbreviations for Tables in Appendix C

⇑ increase

⇓ decrease

∼ approximately (if before a listing of concentrations, it applies to all)

≈ approximately equal

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

AL hybrid cells 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 sites sites of base loss [apurinic/apyrimidinic (AP) sites]

AP-PCR arbitrarily-primed polymerase chain reaction

Aprt adenosine phosphoribosyl transferase

ARE Antioxidant response element

AR230 cells a CML cell line that expresses large amounts of Bcr-Abl

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

AS52 cells pSV2 gpt-transformed Chinese hamster ovary cell line. They 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
DRAFT—DO NOT CITE OR QUOTE 217

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)

B[a]P benzo[a]pyrene

BAEC Bovine aortic endothelial cells

BALF Bronchoalveolar lavage fluid

BEAS-2B cells human bronchial (pulmonary) epithelial cell line

BCS Bathocuproinedisulphonic acid

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, γ-GCS inhibitor)

BUC bladder urothelial cells

B0653 2,3-dihydro-5-hydroxy-2,2-dipentyl-4,6-di-tert-butylbenzofuran

B16-F10 cells mouse melanoma cells

CAs chromosome aberrations

CAM cell adhesion molecule

CAM assay chorioallantoic membrane assay of angiogenesis

CAT catalase (decomposes H2O2)

Cdc Cell division cycle

Cdc42 a small GTPase in the Rho/Rac subfamily of Ras-like GTPases

cen+ centromere positive (micronuclei)

cen- centromere negative (micronuclei)

CFE Colony-forming efficiency

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 human cell line thought to be derived from HeLa cells

ChAT choline acetyltransferase

CHO Chinese hamster ovary

CI Confidence interval

CK8 cytokeratin 8
DRAFT—DO NOT CITE OR QUOTE 218

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 As SA

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

CRL1675 cells human melanocytes 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

c-Fos an AP-1 protein

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

c-met the oncogene that encodes HGF (hepatocyte growth factor) receptor

c-Mos Proto-oncogene

C-33A cells a transformed human non-differentiated carcinoma cell line

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
DRAFT—DO NOT CITE OR QUOTE 219

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

DMPO 5,5′-dimethyl-1-pyrroline N-oxide (a spin-trap agent)

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

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

DNMT DNA methyltransferase

DPC DNA protein cross-links

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 human prostate carcinoma cell line

DW drinking water

D-NMMA NG-methyl-D-arginine, the inactive enantiomer of a nitric oxide 

synthase inhibitor

EA ethacrynic acid (a GST inhibitor)

EB ethidium bromide

E. coli Escherichia coli

EDR3 cells 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
DRAFT—DO NOT CITE OR QUOTE 220

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

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)

EROD Ethoxyresorufin-O-deethylase

Erk or ERK extracellular signal-regulated kinase

ER-α estrogen receptor-α

ESR electron spin resonance

ETU S-ethylisothiourea, a NOS inhibitor

E2N Ubiquitin-conjugating enzyme

E7 cells Immortalized human bladder cell line

FACS fluorescence-activated cell sorting

FADD Fas-associated death domain protein

FAK focal adhesion kinase

FBS fetal bovine serum

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 NFκB

FLIPL long-splice variant of FLIP

Fox O3a An oxidative stress inducible forkhead transcription factor

FPG formamidopyrimidine-DNA glycosylase (digestion of DNA)

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 SV-40 transformed XPA human fibroblast NER-deficient cell line

GM847 cells SV-40-transformed human lung fibroblast cell line
DRAFT—DO NOT CITE OR QUOTE 221

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)

G12 cells 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.

HaCat cells human keratinocyte cell line

HaCaT cells human epidermal keratinocytes cell line

Hb Hemoglobin

HCC hepatocellular carcinoma

HCT116 cells human colorectal cancer cell line (available in securin-wild-type and 

securin-null forms)

HCT15 cells human colon adenocarcinoma cell line

HEC Hamster embryo cells

HEK 293 cells 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 human hepatocellular liver carcinoma cell line (Caucasian)

HeLa cells human cervical adenocarcinoma cell line

HeLa S3 cells human cervical carcinoma cell line, derived from the parent HeLa cell 

line and is adapted to grow in suspension (spinner) culture and has the 

same virus susceptibility as the parent line

HELF cells human embryo lung fibroblast cell line

hEp cells normal human epidermal cells derived from foreskin

HEL cells an AML cell line that is a cytokine-independent human 

erythroleukemia cell line that has constitutive STAT3 activity

HFF cells human foreskin fibroblasts cell line

HFW cells diploid human fibroblast cell line

HGF hepatocyte growth factor

HGPRT hypoxanthine-guanine phosphoribosyltransferase

HIF Hypoxia inducible factor

HK-2 cells human proximal tubular cell line

HLA human leukocyte antigen
DRAFT—DO NOT CITE OR QUOTE 222

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

HL-60 cells human promyelocytic leukemia cells 

HMEC-1 cells human microvascular endothelial cells

HMOX-1 heme oxygenase 1 

HO∙ Hydroxyl radicals

HOS cells human osteogenic sarcoma cell line

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 human sarcoma cell line

hTER RNA component of telomerase

hTERT human telomerase reverse transcriptase

HT1197 cells human (Caucasian) epithelial bladder cancer cell line 

HU Hydroxyurea

Huh7 cells human hepatoma cell line

HuR RNA binding protein

HUVEC cells human umbilical vein endothelial cell line (or HUVECs)

H1355 cells human lung adenocarcinoma cell line

H2O2 Hydrogen peroxide

H22 cells hepatocellular carcinoma cell line

H411E cells rat hepatoma cell line

H460 cells human non-small-cell lung cancer cell line (also called human lung 

large cell carcinoma cells)

H9c2 cells immortalized myoblast cell line derived from fetal rat hearts

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
DRAFT—DO NOT CITE OR QUOTE 223

IEC-6 cells rat intestinal epithelial cell line

IEC cells primary culture of rat intestinal epithelial cells

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 human multiple myeloma cell line

IRE iron responsive element

IRP-1 iron regulatory protein 1

JAK Janus kinase

JAR cells human placental choriocarcinoma cell line

JB6 C141 cells 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

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)

J82 cells human bladder tumor cells

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 human multiple myeloma cell line

Ku70 one of the 3 subunits of DNA-dependent protein kinase

K1735-SW1 cells 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

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
DRAFT—DO NOT CITE OR QUOTE 224

LOEC Lowest observed effect concentration

LOEL Lowest observed effect level

LOH loss of heterozygosity

LPO lipid peroxidation

Luc the PEPCK-luciferase construct

LU1205 cells 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

L-132 cells human alveolar type II cells

Maf musculoaponeurotic fibrosarcoma (transcription factor)

MAP mitogen-activated protein

MAPK mitogen-activated protein kinase

MCA 20-methylcholanthrene

MC/CAR Human multiple myeloma cell line

MCF-7 cells human breast carcinoma cell line

MCR mineralocorticoid receptor

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 human breast cancer cell line (an invasive estrogen unresponsive cell 

line)

MDA-MB-435 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 mouse embryonic fibroblast cell line

MEK MAP/ERK kinase (also, a family of related serine-threonine protein 

kinases that regulate mitogen-activated protein kinase)

MGC-803 cells 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

MMAIII monomethylarsonous acid

MMAV monomethyl arsonic acid

MMA monomethyl arsenic (used when oxidative state is unknown or not 

specified)

MMAIIIO Methylarsine oxide
DRAFT—DO NOT CITE OR QUOTE 225

MMC mitomycin C

MMP mitochondrial membrane potential

MMP-2 matrix metalloproteinase-2

MMP-9 matrix metalloproteinase-9

Mmp13 Matrix metalloproteinase-13

MMS methyl methanesulfonate

MN micronuclei

MNNG 1-methyl-3-nitro-1-nitrosoguanidine

mRNA messenger ribonucleic acid

MnTMPyP Mn(III)tetrakis(1-methyl-4-pyridyl) porphyrin pentachloride (a cell 

permeable SOD mimic)

MNU N-methyl-N-nitrosourea

MRC-5 human lung fibroblast cell line

MRP multidrug resistance-associated protein

Mrps efflux transporters encoded by MRP genes

MS mass spectrometer or mass spectrometry

mtDNA mitochondrial DNA

MT metallothionein

MT2A gene symbol for metallothionein 2A

MT-1 metallothionein-1

MTOC microtubule-organizing center

MTS assay 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-

sulfophenyl)-2H-tetrazolium, 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

MW molecular weight

MYH MutY homolog, an endonuclease

MYP3 cells rat epithelial cells line (urinary bladder cells)

M-CSF macrophage colony-stimulating factor

NAC n-acetyl-cysteine (precursor of GSH; it elevates cellular GSH levels, 

also an antioxidant), also N-acetyl-L-cysteine

NADH reduced form of nicotinamide adenine dinucleotide

NADPH nicotinamide adenine dinucleotide phosphate-oxidase

Namalwa cells human Burkitt’s lymphoma cell line

NB4 cells 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 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 Human myeloma cell line

NE nuclear extract

NER nucleotide excision repair (pathway)
DRAFT—DO NOT CITE OR QUOTE 226

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 phosphate-quinone 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) 

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

N-18 cells mouse neuroblastoma cell line

OATP-C organic anion transporting polypeptide-C

ODA oxidative DNA adducts

OGG1 8-oxoguanine DNA glycosylase

OM431 cells human melanoma cell line

ONOO– peroxynitrite

OR Odds ratio

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)

PCE polychromatic erythrocyte

PCI-1 cells human head and neck squamous cell carcinoma cell line

PCNA Proliferating cell nuclear antigen

PCR polymerase chain reaction

PC12 cells rat sympathetic (neuronal) pheochromocytoma cell line

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

PHEN o-phenanthroline (an iron chelator)

PHA phytohemagglutinin

PI propidium iodide
DRAFT—DO NOT CITE OR QUOTE 227

PI3K phosphatidylinositol 3-kinase

PK proteinase K

PLAP Placental alkaline phosphatase

PLC/PR/5 cells human hepatocellular carcinoma cell line

PMA phorbol 12-myristate 13-acetate

PMN polymorphonuclear neutrophils (or PMNs)

PMs Peritoneal macrophages

PNA peptide nucleic acid

ppb Parts per billion

ppm Parts per million

PQ paraquat (a generator of O2

–

)

PR progesterone receptor

PRCC primary renal cortical cell

PSH protein thiol

pt pretreatment

PTEN phosphatase and tensin homolog (mutated in multiple advanced 

cancers 1)

p21 a cyclin-dependent kinase inhibitor

p-STAT3 phosphorylated-STAT3

P-gp P-glycoprotein, the efflux transporter encoded by MDR

P-PKB phosphorylated protein kinase B

p-XSC 1,4-phenylenebis(methylene)selenocyanate

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 name of a proto-oncogene

RAGE receptor for advanced glycation end products

RAPD-PCR random(ly) amplified polymorphic DNA polymerase chain reaction

RANKL receptor activator of NFκB ligand

Ras a name of a proto-oncogene

RAW264.7 cells 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 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 human myeloma cell line
DRAFT—DO NOT CITE OR QUOTE 228

RT-PCR reverse transcription-polymerase chain reaction

RWPE-1 Human prostate epithelial cell line

R-3T3 cells Ras-transformed NIH 3T3 cells, a mouse fibroblast cell line

SA sodium arsenite

SACs slowly adhering cells; epidermal cell fraction that contains cells 

undergoing terminal differentiation, with little ability to form colonies

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

Ser serine, an amino acid

Se-Met selenomethionine

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)

SMC cells human bladder smooth muscle cells

SLC30A1 gene symbol for the zinc transporter, solute carrier family 30, member 

1

SMART somatic mutation and recombination test

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

SV-40 Simian virus 40

SVEC4-10 cells C3H/HeN mouse vascular endothelium cell line (also called 

immortalized mouse endothelial cell line)

SV-HUC-1 cells SV40 large T-transformed human urothelial cell line (non-tumor cells, 

derived from urethra, immortalized)

SW13 cells human adrenal carcinoma cell line

SW480 cells colorectal adenocarcinoma cell line derived from a Caucasian male that 

has two base-pair substitution mutations in the p53 gene

SY-5Y cells human neuroblastoma cell line
DRAFT—DO NOT CITE OR QUOTE 229

T3 thyroid hormone triiodothyronine

T4 thyroid hormone thyroxine

TAM tamoxifen

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 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 transforming growth factor 

THP-1 + A23187 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

TM3 cells immortalized Leydig cells derived from normal mouse testis

TMAVO trimethylarsine oxide

TNF-α tumor necrosis factor α (an inflammatory cytokine)

TPA 12-O-tetradecanoylphorbol-13-acetate

TRAIL TNF-related apoptosisTRAIL-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

Trx1 cytoplasmic thioredoxin-1

Trx2 mitochondrial thioredoxin-2

TrxR thioredoxin reductase

TrxR1 cytosolic thioredoxin reductase

TR9-7 cells a spontaneously immortalized human fibroblast cell line, derived from 

a Li-Fraumeni patient, and subsequently stably transfected with a 

tetracycline-regulated p53 expression vector

TUNEL assay terminal deoxynucleotidyl transferase-mediated deoxyuridine nick-end 

labeling assay

T47D cells human mammary adenocarcinoma cell line

Ub ubiquitin
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UROtsa an SV40-immortalized human urothelium cell line

UV ultraviolet radiation

UVA ultraviolet radiation A 

UVB ultraviolet radiation B 

UVC ultraviolet radiation C

U0126 inhibitor of MEK1/2, which are ERK upstream kinases (structurally 

unrelated to PD98059)

U118MG cells human glioblastoma cell line, also called U118MG (ATCC HTB-15) 

cells

U266 cells human multiple myeloma cell line

U937 cells 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 human osteogenic sarcoma cell line

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

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

wk week(s)

wt wild-type

WM9 cells human melanoma cell line

WRL-68 Human hepatic cell line

WT-1 Wilm’s tumor protein-1

W138 cells human diploid lung fibroblast cell line

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]-2H-tetrazolium-5-

carboxanilide

YC-1 a small molecule inhibitor of HIF signaling

ypt locus xanthine-guanine phosphoribosyltransferase locus

ZPP zinc protoporphyrin

Z-DEVD-FMK benzyloxycarbonyl-L-Asp-Glu-Val-Asp-fluoromethyl ketone, a 

caspase 3 inhibitor

Z-VAD-FMK Z-Val-Ala-DL-Asp-fluoromethylketone, a general caspase inhibitor

1RB3AN27 cells immortalized dopamine-producing rat mesencephalic cell line

1T1 cells human epithelial cell line
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293 cells 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

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 longterm treatment with ditercalinium 
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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 iAs 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 As 

in DW) with subjects from Tucson (∼5 ppb 

of As in DW). They also determined total 

iAs 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 iAs concentrations in urine in individuals in 

those cities, a comparison was also made using iAs levels in urine. The regression 

analysis yielded a significant negative association between urinary total iAs 

concentrations and RAGE concentrations in sputum. Thus iAs exposure caused ⇓ in 

RAGE level as was seen in mice.

Lantz et al., 2007

Effect of iAs exposure 

from DW on serum levels 

of extracellular domain of 

EGFR (i.e., EGFR ECD)

Araihazar area of 

Bangladesh

Estimates of iAs exposure level were based 

on well water As (ranged from 0.1 to 768 

ppb), urinary As, and cumulative As 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 iAs exposure, with the association being strongest 

among individuals with As-induced skin lesions. 

Li et al., 2007

Effect of iAs exposure 

from DW on levels of 

TGF-α in bladder 

urothelial cells (BUC)

3 towns in central 

part of Mexico

Estimates of iAs exposure level were based 

on levels of different metabolites of As in 

urine from 72 women who used drinking 

water that contained 2–378 ppb As

Found significant positive correlation between TGF-α protein levels in exfoliated 

BUC and each of 6 arsenic species present in urine. Women from areas with high 

As exposures had significantly higher TGF-α protein levels in BUC than those from 

areas of low As exposure. BUC cells from people with As-induced skin lesions 

contained significantly more TGF-α.

Valenzuela et al., 

2007

Microarray–based gene 

expression study 

comparing groups with and 

without arsenical skin 

lesions, both of which were 

exposed to iAs in DW but 

to different extents

Bangladesh

Compared subjects with cutaneous signs of 

arsenicism (mean of 343±258 ppb of As in 

DW) with asymptomatic individuals (mean 

of 40±50 ppb of As 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 Asinduced 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 nonAs-related urothelial 

cancer

Taiwan, patients with 

urothelial cancer

All 33 patients with As-related urothelial 

cancer had been living in the arseniasis 

endemic 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 

non-As-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 As-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 up-regulation of these 2 oncoproteins 

may play important roles in As-mediated urothelial carcinogenesis. Cellular GSH 

content was down-regulated in both types of tumors, but to a greater extent in the 

As-induced ones.

Hour et al., 2006
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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

Comparison of expression

of several integrins 

between people with Asrelated 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 iAs. 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 Asrelated keratosis in 

individuals exposed to As 

in DW

West Bengal, India

Compared 177 As-exposed subjects with 

keratosis (mean of 177 ppb of As in DW) 

with 189 As-exposed subjects without such 

skin lesions (mean of 180 ppb of As in DW), 

and looked for association of keratosis with 3 

specific p53 polymorphisms. Used As 

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 Asinduced keratosis. In both cases the OR was 2.086 and the 95% CI did not overlap 

1. Urinary excretion of As was slightly lower (NSE) in the group with keratosis 

suggesting higher retention of As in the body, which was reflected in significantly 

higher As content in nails and hair.

De Chaudhuri et 

al., 2006

Chromosomal Aberrations and/or Genetic Instability

Nested case-control study/

CAs and/or SCEs as 

biomarkers for the 

prediction of cancer 

development

Blackfoot endemic 

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 As in DW) with 

asymptomatic individuals (5.5 ppb of As in 

DW). Also used As 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 As-exposed subjects with 

cutaneous signs of arsenicism (mean of 242 

ppb of As in DW), As-exposed subjects 

without cutaneous signs of arsenicism (mean 

of 202 ppb of As in DW), and As-unexposed 

subjects (mean of 7.2 ppb of As in DW), and 

looked for association of effects with 

different GSTT1 and GSTM1 genotypes. 

Used As concentration comparisons in DW, 

urine, nails, and hair.

As-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
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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

Association between a 

polymorphism in ERCC2

codon 751 that probably 

improves NER and (a) the 

incidence of CAs and (b) 

the presence of iAsinduced hyperkeratosis

West Bengal, India

Comparisons were made between people 

with hyperkeratosis and individuals with no 

skin lesions that were drinking similar iAs 

contaminated water. Groups with and 

without hyperkeratosis had means of 195 and 

185 ppb As 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 iAsinduced 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 iAs but not having hyperkeratosis, 18% more in those

exposed to iAs and having hyperkeratosis, and 31% in both groups combined. Also, 

CAs were significantly more frequent in iAs-exposed people with hyperkeratosis.

Banerjee et al., 

2007

Induction of MN

(bladder cells) Chile, men

Compared subjects having high (average 600 

ppb of As in DW) and low (average 15 ppb 

of As 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 

As 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 

biopsy-proven skin 

cancers

Nothing is known about doses; duration of 

treatment with iAs 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 iAs (7 

men in each group)

The total doses of iAs were from 300 to 1200 

mg for the 7 with known doses. iAs 

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 iAs treatment and an even bigger ⇑ in

comparison to healthy untreated males. iAs treatment had NSE on SCE frequency.

Nordenson et al., 

1979

Induction of CAs 

(mostly airborne iAs, 

lymphocytes)

9 workers exposed to 

iAs 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
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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

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 As (mostly > 100 ppb 

As) for at least 5 years and the control 

sample of 86 used DW containing <50 ppb 

As (and often much less) for the same period. 

No hint of any effect of iAs on CA or SCE frequencies was seen even though there 

was an approximately 9-fold difference in the mean iAs 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 As 

concentrations in urine and blood and 

concentrations of As metabolites.

iAs 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 factor of 2.3 times in oral mucosa and by 4.3 times 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 iAs 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 iAs and methylated metabolites in urine.

iAs 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 iAs plus methylated metabolites. In contrast, iAs 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 iAs 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 iAs 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 As 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 As and 

its metabolites.

Moore et al., 1996
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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

Induction of CAs and 

SCEs (lymphocytes for 

CAs)

People in Santa Ana 

(high dose) and 

Nuevo Leon (low 

exposure group), 

Mexico

The high exposure group of 11 used DW 

containing a mean of 390 ppb As (98% as 

AsV), and the low exposure group of 13 used 

DW that ranged from 19 to 60 ppb As. They 

also considered As 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 high exposure 

group was considered suggestive of a possible effect of iAs. Average generation 

times (AGT) of lymphocytes were 19.02 hr in the laboratory control, 19.90 hr in the 

low exposure 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.

Ostrosky-Wegman 

et al., 1991

DNA Damage

DNA damage detected 

using SCGE (comet) assay

(lymphocytes)

New Hampshire, 

USA

Low-exposure (control) group had < 0.7 ppb 

As in DW and high-exposure group had ≥13 

(and up to 93) ppb As 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 iAs exposure only) to ∼1.8x. Two hours after identical 

in vitro 2-AAAF treatments to cells from both high- and low-iAs-exposure groups, 

cells from both groups showed big ⇑ in DNA damage, with iAs-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 high exposure group (∼1.54x), and essentially all 2-AAAF-induced DNA damage 

had been repaired in the control cells.

Andrew et al., 2006
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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

Oxidative DNA damage

Residents of 

Bayingnormen 

(Ba Men), 

Inner Mongolia, 

China, with exposures 

to a wide range of 

concentrations of iAs 

in DW

Concentrations of iAs in DW were 

determined for individuals; ∼70% of subjects 

used DW containing nondetectable As 

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 As 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 As-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 As 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 As was 0.25.) It thus appears that 

exposure of healthy people to these 3 metals under normal conditions may increase 

oxidative DNA damage. Urinary As 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
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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

DNA damage in peripheral 

blood lymphocytes 

detected by alkaline comet 

assay

West Bengal, India

Low-exposure (control) group had 7.7±0.5 

ppb As in DW. High-exposure group had 

247±19 ppb As in DW. They also 

considered As 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 As 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) As in DW. 

High-exposure group had 10.4-74.7 ppb 

(average of 32) As in DW. Subjects from 

Colonia Allende had 5.5 ± 0.20 ppb As in 

DW, and those from Esperanza had 43.3 ± 

8.4 ppb As 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 

As levels in urine and toenails.

Earlier work suggested that iAs 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). iAs 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 iAs levels in their DW and in their 

toenails.

Toenail and DW As levels were inversely correlated with expression of ERCC1, 

XPB, and XPF. The As levels in toenails were more strongly negatively correlated 

with the changes in gene expression that the As concentrations in DW. In these 

comparisons, expression levels were compared between high and low levels of As 

exposure. By definition a high level in DW was anything ≥2 ppb As 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 iAs 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 iAs 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 As 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 As and Cr were at a higher level in urine, there was a 

highly significant ⇑ of 39% in urinary 8-OHdG.

Wong et al., 2005
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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

Evidence of oxidative 

damage to DNA caused by 

iAs in DW, and the 

relationship of that DNA 

damage to As-related skin 

lesions

2 villages in Wuyuan 

prefecture in Hetao 

Plain, Inner 

Mongolia, China

Adults from low-As-exposure village (mean 

of 5.3 ppb As in DW) and from high-Asexposure village (mean of 158.3 ppb As 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-Asexposure village were at least 17x higher 

than they were in the low-As-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 As-related 

skin lesions in the high-As-exposure village, there was no statistically significant 

correlation found between iAs, MMA, or DMA and 8-OHdG adducts in the urine. 

However, for subjects with As-related skin lesions in the high-As-exposure village, 

there was a significant positive correlation in urine between levels of each those 3 

types of As 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 highAs village compared to the low-As village, even if restricted to only those with Asrelated lesions. An overall comparison did, however, show an excess of 8-OHdG 

adducts in urine in the high-arsenic 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 (low 

exposure group), 

Mexico

The high-exposure group of 11 used DW 

containing a mean of 390 ppb As (98% as 

AsV), and the low exposure group of 13 used 

DW that ranged from 19 to 60 ppb As. They 

also considered As 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. 

Ostrosky-Wegman 

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 

As 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 As-induced skin cancer in comparison to those 

with skin cancer unrelated to iAs exposure, but this comparison did not reach 

statistical significance (p < 0.2)

Chanda et al., 2006

Relationship between 

epigenetic silencing of 3 

tumor suppressor genes 

and exposure to As 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 As in their 

toenails, and 318 had < 0.26 ppm As in their 

toenails. 0.26 ppm was the 95th percentile of 

As exposure in this population.

They applied methylation-specific PCR. A significant relationship was identified 

between As 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
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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

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 

As 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 

As exposure showed hypomethylation. Hypomethylation occurs only after 

prolonged As exposure at higher doses. The authors noted that cases of both hyperand 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 

iAs exposure from DW

Ajo and Tucson, 

Arizona, USA

40 subjects were from the high-As-exposure 

town of Ajo (20.3 ± 3.7 ppb As in DW), and 

33 were from the low-As-exposure town of 

Tucson (4.0 ± 2.3 ppb As in DW). They also 

measured iAs 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 log-normalized 

concentrations of these 3 substances in induced sputum were not significantly 

different between these towns. However, after adjusting for town, asthma, diabetes, 

urinary MMA/iAs, and smoking history, total urinary As was negatively associated 

with MMP-2 and TIMP-1 levels and positively associated with the ratio of MMP2/TIMP-1 and MMP-9/TIMP-1. This suggests an association between changes in 

sensitive markers of lung inflammation and levels of iAs of only ∼20 ppb in DW. It 

appears that iAs levels in DW and the extent of As methylation may be important 

predictors of lung metalloproteinase concentrations.

Josyula et al., 2006

Signal Transduction
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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

Association between TGFα and/or EGFR and 

cumulative iAs 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 As exposure. 

Those with As exposure were further divided 

on the basis of cumulative As dose (i.e., total 

DW iAs levels x years of exposure) into the 

following 2 groups: 32 with ≤6 ppm-years 

and 34 with > 6 ppm-years. 

Blood plasma was collected and tested for TGF-α and EGFR levels using 

immunoassays. No relationship between As 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 As 

exposure group than in the control group. After adjusting for age and sex, there was 

also a significant linear trend between cumulative As exposure and the prevalence 

of plasma TGF-α overexpression.

Hsu et al., 2006
DRAFT—DO NOT CITE OR QUOTE 242

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 As1

(in units stated)

Duration of 

treatment LOEL2 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 up-regulated and 42 downregulated. 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: GST-omega-1, 

RAGE, contraspin, and apolipoproteins A-I and A-IV.

Lantz et al., 2007

Urothelial cells/rat

(F344, female)

DMAV 

sodium 

cacodylatetrihydrate

* 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% down-regulated by ≥3-fold.

Sen et al., 2005

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 steroidrelated 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 Se-adequate diet;

liver: ⇓ of DI-I to ∼0.30x when Se-deficient diet;

All other comparisons were either slight or NSE. 

Miyazaki et al., 2005
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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 As1

(in units stated)

Duration of 

treatment LOEL2 Results Reference

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 Se-deficient diet

liver: ⇓ of TrxR to ∼0.78x when Se-deficient 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

Liver, kidney & 

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
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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 As1

(in units stated)

Duration of 

treatment LOEL2 Results Reference

Liver & 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

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 realtime RT-PCR 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
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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 As1

(in units stated)

Duration of 

treatment LOEL2 Results Reference

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 (iAs + DES) did not 

significantly increase ER-α expression. iAs alone did not ⇑ expression 

of pS2, CYP2A4, or lactoferrin. However, DES alone caused large ⇑ in 

expression of all 3 of these genes, and (iAs + 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 iAs 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 down-regulated. 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

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 downregulated. 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 non-tumorous 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
DRAFT—DO NOT CITE OR QUOTE 246

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 As1

(in units stated)

Duration of 

treatment LOEL2 Results Reference

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 non-tumorous 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

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 realtime 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
DRAFT—DO NOT CITE OR QUOTE 247

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 As1

(in units stated)

Duration of 

treatment LOEL2 Results Reference

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 TPA-treatment-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 iAs/TPA exposed non-tumorous livers and in iAs/TPA-induced 

tumors. The tumors themselves generally had more pronounced alterations in gene 

expression than the normal tissue around them. In general, the iAs/TPA induced gene 

expression alterations were similar to those seen in liver samples from male mice 

exposed only to iAs in utero. It should be noted that while in utero iAs-exposed 

males developed hepatocellular carcinoma without the TPA treatment, in utero iAsexposed females only developed those tumors after TPA treatment.

Liu et al., 2006b

Bladder and liver/rat

(Fisher 344, male)

MMAV

DMAV

TMAVO

* 121 ppm (DW)3

* 109 ppm (DW)3

* 110 ppm (DW)3

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, Mmp13 and other genes specific to cell proliferation, cell 

signaling, and xenobiotic metabolism. 

Kinoshita et al., 

2007b

Liver cells/rat

(Sprague Dawley)

AsV as 

Na2HAsO4• 

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
DRAFT—DO NOT CITE OR QUOTE 248

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 As1

(in units stated)

Duration of 

treatment LOEL2 Results Reference

Liver cells/rat

(Sprague Dawley)

AsV as 

Na2HAsO4• 

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

Heart/mouse

(C57BL/6NCr, male) AsIII SA

* 28.8, 144, 288 ppb

(DW)

Note in ppb!

5, 10, 20 wk Various

mRNA levels determined by RT-PCR:

VEGF165: ⇑ at 144 and 288 at wk 5; ⇑ at all doses at wk 10; NSE at wk 

20;

VEGFR1: NSE at wk 5 and 10; big ⇑ at 144 and big ⇓ at 288 at wk 20;

VEGFR2: ⇑ at 288 at wk 5; NSE at wk 10; ⇑ at 28.8 and 144 and 

⇓ at 288 at wk 20;

PAI-1: NSE at wk 5; ⇑ at 288 at wk 10; ⇑ at 144 and 288 at wk 20; 

Endothelin-1: NSE at wk 5 and 10; ⇑ at 28.8 and big ⇑ at 144 at wk 20;

MMP-9: NSE at wk 5; ⇑ at 288 at wk 10; ⇑ at all doses at wk 20

Soucy et al., 2005

Blood plasma/mouse

(C57BL/6NCr, male) AsIII SA * 288 ppb (DW)

Note in ppb! 20 wk 288 ppb 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 * 5.8, 28.8, 115 ppb (DW)

Note in ppb! 9 wk 5.8 ppb 

Protein levels in primary melanoma tumors determined by 

immunohistochemical staining:

⇑ HIF-1α at 5.8 and 28.8 only; ⇑ VEGF at 5.8 and 115 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)3

* 109 ppm (DW)3

* 110 ppm (DW)3

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
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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 As1

(in units stated)

Duration of 

treatment LOEL2 Results Reference

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

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 cotreatment 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 co-treatment 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/mouse

(C57BL/6, female)

AsV as 

Na2HAsO4• 

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
DRAFT—DO NOT CITE OR QUOTE 250

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 As1

(in units stated)

Duration of 

treatment LOEL2 Results Reference

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

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 iAs exposure, there was a marked ⇑ in the number of 

skin papillomas compared to single treatments, whereas no papillomas 

developed in iAs-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. iAs acted like a co-promoter.

Germolec et al., 

1998

Skin/mouse

(hairless swiss-bald 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 iAs 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 iAs treatment, there was PCNA ⇑ to ∼5.3x. DMBA 

treatment alone caused ⇑ to only 2.9x. Mice that were untreated or 

treated with iAs alone developed no papillomas or skin tumors. DMBA 

treatment alone induced development of squamous cell papillomas. 

Combined iAs and DMBA treatment caused development of well 

differentiated squamous cell carcinomas. iAs acted as a skin tumor 

promoter by promoting abnormal cell proliferation. Findings suggest 

that iAs is toxic to normal skin cells and that preneoplastic cells are 

more resistant to iAs.

Motiwale et al., 2005
DRAFT—DO NOT CITE OR QUOTE 251

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 As1

(in units stated)

Duration of 

treatment LOEL2 Results Reference

Lung/mouse

(ddY, male)

DMAV

assumed to 

be 

dimethylarsinic 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

Cell Cycle Arrest or Reduced Proliferation

Heart/mouse

(C57BL/6NCr, male) AsIII SA * 288 ppb (DW)

Note in ppb! 5, 10, 20 wk 288 ppb 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 in 0 of 10 rats in control 

and in 1 of 10 rats with co-treatment with DMPS. 

Cohen et al., 2002

Liver/rat

(Fischer 344, male)

They used normalappearing 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 normal-appearing 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)3

* 109 ppm (DW)3

* 110 ppm (DW)3

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
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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 As1

(in units stated)

Duration of 

treatment LOEL2 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: iAs alone, 9% (NSE); 

DES alone, 12% (NSE); TAM alone, 10% (NSE); (iAs + DES), 45%; 

(iAs + TAM), 30%. All induced percentages were the same for total 

proliferative lesions, except for (iAs + TAM), which was 40%. The 

lesions induced by iAs 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: iAs alone, 23%; 

DES alone, 0%; TAM alone, 0%; (iAs + DES), 24%; (iAs + 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: iAs alone, 12% (NSE); 

DES alone, 0% (NSE); TAM alone, -3% (NSE); (iAs + DES), 26%; 

(iAs + TAM), 23%. All induced percentages were the same for total 

proliferative lesions, except for (iAs + DES), which was 35%, and (iAs 

+ TAM), which was 26%. Unlike in the male offspring, iAs did not 

induce hyperplasia in kidneys.

Waalkes et al., 

2006a

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 iAs treatment: ⇑ to ∼3x (NSE); 

knockout Ogg1-/- without iAs: ⇑ to ∼6x; 

knockout Ogg1-/- with iAs 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
DRAFT—DO NOT CITE OR QUOTE 253

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 As1

(in units stated)

Duration of 

treatment LOEL2 Results Reference

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

* 0.6, 2.9, 5.8, 

28.8 ppb (DW)

Note in ppb!

5 wk 0.6 ppb

Blood vessel no. determined in Matrigel implants surgically inserted 

during last 2 wk of iAs treatment: probable ⇑ to ∼1.8x at dose of 0.6; 

statistically significant ⇑ to ∼2.4x at the higher 3 doses. Implants were 

supplemented with recombinant FGF-2; iAs-enhanced neovascularization did not occur without FGF-2. Data suggest that iAs potentiates, 

but does not directly cause, neovascularization in Matrigel implants. 

Soucy et al., 2005

Matrigel implants/mouse

(C57BL/6NCr, male) AsIII SA * 28.8, 144, 288 ppb (DW)

Note in ppb! 5, 10, 20 wk 28.8 ppb for 

each duration

Blood vessel number determined in Matrigel implants surgically 

inserted during last 2 wk of iAs 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 28.8 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 * 5.8, 28.8, 115 ppb (DW)

Note in ppb! 8 wk 5.8 ppb 

Tumor volume and tumor growth rate, after implantation of tumor cells 

(into external surface at the base of right ear) 5 wk after iAs treatment 

began:

Volume: 5.8, ∼1.4x (NSE); 28.8, ∼2.2x; 115, ∼3.0x;

Rate: 5.8, ∼1.9x (NSE); 28.8, ∼2.2x; 115, ∼3.2x.

Kamat et al., 2005

Tumors that developed 

from B16-F10 (GFP) 

melanoma tumor 

cells/mice 

(NCr nu/nu, male)

AsIII SA * 5.8, 28.8, 115 ppb (DW)

Note in ppb! 8 wk 5.8 ppb 

Mean no. of lung metastases/lobe, after implantation of tumor cells 

(into external surface at the base of right ear) 5 wk after iAs treatment 

began:

5.8, ∼1.6x; 28.8, ∼2.0x; 115, ∼2.0x (statistically significant at 5.8 and 

115); the metastases were significantly larger at the 2 lower doses.

Kamat et al., 2005
DRAFT—DO NOT CITE OR QUOTE 254

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 As1

(in units stated)

Duration of 

treatment LOEL2 Results Reference

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 iAs effect. 10μM iAs + YC-1 caused no change from control, but 

iAs 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 BrdU-positive 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 

disodium

hydrogen 

arsenate

* 4.0 mg As/kg bw

(unspecified route of 

administration)

15, 21 days 4.0 mg/kg

Chromosomal analysis of Giemsa-stained 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

Bone marrow/mouse

(albino Swiss, male) AsIII SA

* 1.44 mg/kg x 4, 5, and 6 

times at weekly intervals, 

(gavage)

Single dose 

each week 1.44 x 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 iAs treatment caused a significant reduction in the frequency of 

CAs after 4 and 6 iAs treatments. 

Patra et al., 2005

Bone marrow/mouse

(C57BL/6J/Han, female)

AsV as 

Na2HAsO4•

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: iAs 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 iAs-treated mice 

unexposed to UV developed no skin tumors. Of mice exposed to UV, 

skin tumor yields per mouse at the different doses of iAs 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 iAs 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
DRAFT—DO NOT CITE OR QUOTE 255

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 As1

(in units stated)

Duration of 

treatment LOEL2 Results Reference

Skin/mouse

(Hairless CrL:SK1-hrBD, 

female, weanling)

Starting 3 wk after iAs 

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 ⇑;

iAs alone at 5.8 ppm (earlier experiment): ⇑;

iAs + UV (this experiment): huge ⇑;

Co-treatment with vitamin E or p-XSC: ⇑ (i.e., a significant reduction 

in iAs + UV effect). Above effects roughly paralleled those for SCC 

induction, except that no tumors were caused by As alone.

Uddin et al., 2005

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 

co-treatment 

with B[α]P

Frequencies of induction of PLAP+ cells (result from frameshift 

mutations) in (A) untreated control, (B) group with iAs 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 & 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 basepairs 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
DRAFT—DO NOT CITE OR QUOTE 256

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 As1

(in units stated)

Duration of 

treatment LOEL2 Results Reference

Urothelium/rat

(F344, female)

DMAV as 

sodium 

cacodylatetrihydrate

* 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 dose response.

Sen et al., 2005

DNA Damage

Liver/rat

(Fischer 344, male)

They used normalappearing 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

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 iAs treatment: ⇑ to ∼1.6x (NSE);

knockout Ogg1-/- without iAs: ⇑ to ∼7.8x; 

knockout Ogg1-/- with iAs treatment: ⇑ to ∼13.1x;

Kinoshita et al., 

2007b

Peripheral blood 

leukocytes/mouse

(C57BL/6J/Han, female)

AsV as 

Na2HAsO4• 

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 iAs 

effects were seen at 3 months, perhaps because water consumption (and 

thus iAs 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 dose response. 

Palus et al., 2006

Lung/mouse

(ddY, male)

DMAV

assumed to 

be 

dimethylarsinic 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
DRAFT—DO NOT CITE OR QUOTE 257

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 As1

(in units stated)

Duration of 

treatment LOEL2 Results Reference

Liver/rat

(Fisher 344, male)

MMAV

DMAV

TMAVO

* 121 ppm (DW)3

* 109 ppm (DW)3

* 110 ppm (DW)3

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)3

* 109 ppm (DW)3

* 110 ppm (DW)3

20 days 

for all

None

109 ppm

None

8-OHdG formation assessed by HPLC:

DMAV: ⇑ to ∼1.62x Kinoshita et al., 

2007a

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 posttreatment with NAC and/or DMSA.

Flora, 1999

Liver/rat

(Fisher 344, male)

MMAV

DMAV

TMAVO

* 121 ppm (DW)3

* 109 ppm (DW)3

* 110 ppm (DW)3

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 & 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 iAs-induced 

effects (either ⇑ or ⇓) on all 4 endpoints in kidneys and on all but GSH 

in livers.

Sohini and Rana, 

2007
DRAFT—DO NOT CITE OR QUOTE 258

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 As1

(in units stated)

Duration of 

treatment LOEL2 Results Reference

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 

x 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 iAs-induced 

effects (either ⇑ or ⇓) on all 4 endpoints in kidneys and on all but GSH 

in livers.

Sohini and Rana, 

2007

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
DRAFT—DO NOT CITE OR QUOTE 259

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 As1

(in units stated)

Duration of 

treatment LOEL2 Results Reference

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

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
DRAFT—DO NOT CITE OR QUOTE 260

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 As1

(in units stated)

Duration of 

treatment LOEL2 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): (This is the same experiment as in the previous row; 

findings not already listed in that row are listed here.) 

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-α-lipoic acid markedly reduced all of 

these effects.

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 iAs-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 As concentrations (especially in kidney and liver) and 

blocked oxidative damage to variable degrees.

Nandi et al., 2005
DRAFT—DO NOT CITE OR QUOTE 261

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 As1

(in units stated)

Duration of 

treatment LOEL2 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 & 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 & 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. Cotreatment with both DL-α-lipoic acid and DMSA markedly reduced all 

of these effects.

Kokilavani et al., 

2005
DRAFT—DO NOT CITE OR QUOTE 262

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 As1

(in units stated)

Duration of 

treatment LOEL2 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
DRAFT—DO NOT CITE OR QUOTE 263

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 As1

(in units stated)

Duration of 

treatment LOEL2 Results Reference

Liver/mouse

(BALB/c, male)

Unspecified 

arsenical, but 

from 

discussion 

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 DMA-induced 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 As 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
DRAFT—DO NOT CITE OR QUOTE 264

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 As1

(in units stated)

Duration of 

treatment LOEL2 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 As 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 x 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 iAs-contaminated water began, half 

of the mice were also exposed to B[α]P for 8 wk by skin painting. Skin 

was assayed for DAP-resistant (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 iAs and/or B[α]P 

exposure, and thus there was no evidence that iAs 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 iAs alone, and 

30% for them together. Because there was much variability, these 

seemingly large differences were not statistically significant.

Fischer et al., 2006

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 iAs 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
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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 As1

(in units stated)

Duration of 

treatment LOEL2 Results Reference

Hypermethylation of DNA

Lung/mice

(A/J, male)

AsV as

Na2HAsO4• 

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 iAs exposed 

mice compared to the control, based on methylation-specific 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 iAs-treated 

mice. They concluded that epigenetic changes of tumor suppressor genes are 

involved in iAs-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

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 iAs. 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
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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 As1

(in units stated)

Duration of 

treatment LOEL2 Results Reference

Kidney, rat

(Wistar, male) AsIII ATO * 30.3 mg/kg,15 times (gavage)

Every other day 

for 30 days 30.3 x 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, IGF-BP1, 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), L-myc (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 ER-α expression; in contrast, 

normal adult lung and DENA-induced lung adenocarcinoma showed 

little evidence of ER-α expression.

Shen et al., 2007

1

When doses were reported in mg arsenic/L or in ppm As, it was assumed that the doses included adjustment for the amount of As 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 As in the dose. 2

Lowest Observed Effect Level 3

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 As 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. 
DRAFT—DO NOT CITE OR QUOTE 267

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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, apoptosis related 

proteins, cytokines and cytokine-related 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

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 iAs, then reached plateau of 

∼18% at doses of 5-15 (based on EROD assay); iAs 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 iAs, followed by a dose-related ⇓ 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 iAs 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
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Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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

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 time dependent 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 iAs 

treatment.

Sasaki et al., 2007
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Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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

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.

Othumpangat et 

al., 2005

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 iAs, 0.099, with iAs, 0.049;

HeLa: no iAs, 0.041, with iAs, 0.029;

PLC/PR/5: no iAs, 0.051, with iAs, 0.028;

Chang: no iAs, 0.018, with iAs, 0.019

(Judging from their SEs, the result for PLC/PR/5 must have been of borderline 

significance.)

Othumpangat 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

Othumpangat 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 iAs stimulated ubiquitination and the resulting proteolysis play an important role in 

reducing eIF4E protein levels.

Othumpangat et 

al., 2005

TR9-7 cells that were 

released from being 

mostly synchronized in 

G2 (using Hoechst 

33342) 

shortly before iAs 

treatment began

AsIII SA 5 3-24 hr

Conclusions based on determining protein levels using Western blot assays until 24-hr of 

iAs treatment in cells made p53(+) or p53(-) by controlling tetracycline levels: big ⇑ in ID1, 

but it occurred only when there was p53 protein present. As 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

TR9-7 cells that were 

released from being 

mostly synchronized in 

G2 (using Hoechst 

33342) 

shortly before iAs 

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 iAs 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
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Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

HeLa cells

AsIII

ATO 2 6 and 24 hr

In a cDNA microarray-based global transcription profiling experiment that compared the 

iAs treatment with a co-treatment of the same iAs 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, cell-cycle 

control, redox regulation, and apoptosis. The manner of data presentation did not permit 

identification of genes affected exclusively by iAs.

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:

AFP: ⇑ at 0.250, big ⇑ at 0.500; WT-1: ⇑ at 0.125, big ⇑ at 0.250 and 0.500;

effects on oncogenes

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

TRL 1215 cells AsIII SA 0.125, 0.250, 0.500 24 weeks Various

mRNA levels determined by real time RT-PCR:

HMOX-1: ⇑ at 0.125 and 0.250, big ⇑ at 0.500; SOD: ⇑ at 0.250, big ⇑ at 

0.500;

effects on stress-related genes

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:

Cyclin D1: ⇑ at 0.125, then ⇑ with dose to 0.500; 

effects on cell cycle regulators

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

TRL 1215 cells AsIII SA 0.125, 0.250, 0.500 24 weeks Various

mRNA levels determined by real time RT-PCR:

c-met: big ⇑ at 0.125, then ⇑ with dose to 0.500;

effects on growth factor genes

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
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Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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

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

TRL 1215 cells AsIII SA 0.500 24 weeks Various

mRNA levels determined by real time RT-PCR:

effects of 72-hr post-treatment with 5 μM 5-aza-dC, (Results were compared to 

cells with iAs 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 iAs 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 iAs pretreatment became more sensitive to MMC-induced 

cytotoxicity and less sensitive to ADM-induced cytotoxicity. Co-treatment 

with MMC and the Nqo1 inhibitor DIC resulted in big ⇑ in cell survival (even 

higher than after MMC treatment without an iAs pretreatment). CL3R15 cells, 

which have much higher levels of Nqo1 activity than CL3 cells, are also much 

more sensitive to MMC-induced cytotoxicity than CL3 cells. 

Lin et al., 2006

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 iAs 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 iAs 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
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Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 iAs treatment, enzymes of the glycolytic pathway were seen to be 

substantially elevated. This dose of iAs suppressed differentiation but did not cause cell 

loss.

Lee et al., 2005

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 

arsenic-induced cytotoxicity that resulted from these treatments.

Kojima et al., 

2006

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 iAs 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 iAs. At a dose of 5 of iAs, the 

interaction became only additive. The interaction between iAs and B[α]P 

regarding Cyp1b1 mRNA was never more than additive. In Ahr-/- MEFs, there 

was no interaction of iAs 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 iAs, 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 iAs, 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 

iAs 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 

iAs/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
DRAFT—DO NOT CITE OR QUOTE 273

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

AG06 cells As

III 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

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 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

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
DRAFT—DO NOT CITE OR QUOTE 274

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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 β-catenin. These findings suggest that arsenic-induced 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; up-regulation 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

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., counter-receptors] 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.) ⇓ α-actin 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
DRAFT—DO NOT CITE OR QUOTE 275

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

Untransformed and 

immortalized RWPE-1 

cells (human prostate 

epithelial cell line)

As

III 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 over-expression of K-ras preceded malignant 

transformation. There was no indication of mutations being induced in K-ras 

gene and no indication that hypomethylation of K-ras 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.

Barchowsky et al., 

1999a

HeLa S3 cells As

III 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
DRAFT—DO NOT CITE OR QUOTE 276

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 iAs dose of 20 for 4-20 hr: 

transitory activation of Akt & transitory ⇑ phosphorylation of FoxO3a. iAs 

induced accumulation of GADD45α mRNA and did not affect the degradation 

of GADD45α protein. iAs stabilized GADD45α mRNA through nucleolin; it 

induced the binding of mRNA stabilizing proteins, nucleolin and less potently, 

HuR, to GADD45α mRNA. iAs did not affect the expression of nucleolin; iAs 

treatment resulted in redistribution of nucleolin from nucleoli to nucleoplasm. 

Silencing of nucleolin reversed iAs-induced stabilization of the GADD45α 

mRNA.

Zhang et al., 2006

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 iAs. 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. iAs 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 iAs 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 iAs-induced gene deregulation in Gclm+/+ but not in Gclm-/- MEFs. These results suggested that regulation of 

GSH levels by GCLM determines the sensitivity to iAs-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 c-jun, after treatment with ATO 

alone and co-treatment 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 iAs 

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 iAs 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
DRAFT—DO NOT CITE OR QUOTE 277

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 iAs 

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 iAs 

treatment

AsIII SA

for both

5, 10

1, 5, 10

24 hrs

for both

5

5

⇓ UVB-induced p53 phophorylation (at serines 15 and 392); bigger ⇓ at 10;

⇓ UVB-induced p53 DNA binding activity; bigger ⇓ at 10;

Other experiments not involving UVB showed that iAs inhibited casein kinase 

2α activity and decreased p53-regulated p21 protein expression.

Tang et al., 2006

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

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
DRAFT—DO NOT CITE OR QUOTE 278

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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 & 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 dose-related decrease to 70% of control 

at dose of 50; 

co-treatment with NAC blocked this effect of iAs. 

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

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 iAs 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 iAs-induced effect.

Szymczyk et al., 

2006

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
DRAFT—DO NOT CITE OR QUOTE 279

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

FGC4 cells AsIII SA 

50, 65

Equivalent to ≤5% 

and 20-25% 

cytotoxicity

24 hr Various

Effects on protein levels of SPs:

MT, HSP60 & 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 & 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

Rat hepatocytes AsIII SA 

10, 20

Equivalent to ≤5% 

and 20-25% 

cytotoxicity

24 hr Various

Effects on protein levels of SPs: MT, HSP60 & 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 high-molecular-weight Ub-conjugated 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

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
DRAFT—DO NOT CITE OR QUOTE 280

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

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 iAs exposure, and its 

induction is independent of p53. ATF4 binds to a GADD45a promoter element in response to iAs stress. 

Exposure to iAs 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

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
DRAFT—DO NOT CITE OR QUOTE 281

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

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 bell-shaped 

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 non-specific 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 iAs 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

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
DRAFT—DO NOT CITE OR QUOTE 282

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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 ATO-induced down-regulation of 

survivin and increase of PARP cleavage; however, blockage of ERK 1/2 or 

ubiquitin-proteasome did not attenuate those same effects. Also, only inhibitors 

of p38 and JNK affected ATO-induced 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

A549 cells

AsIII

ATO 2 48 hr

Protein levels and mRNA levels: 

2 μM iAs: NSE on survivin. 200 μM sulindac: NSE on survivin.

(Sulindac is a NSAID that inhibits COX-2.)

(2 μM iAs + 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 down-regulation of survivin by the (2 μM iAs + 200 μM sulindac) 

treatment. (It is known that p53 binds to the survivin promoter and suppresses its 

transcription.) Transfected cells with a survivin-luciferase 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 iAs 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

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 iAs 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 dose-related ⇓ at 

other 3 doses reaching 47% of control at dose of 10. Lee et al., 2006b
DRAFT—DO NOT CITE OR QUOTE 283

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

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, phophorylation of p42/44 MAPK, and DNA synthesis. Tests 

with various modulators showed that iAsIII 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

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, c-jun, 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
DRAFT—DO NOT CITE OR QUOTE 284

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

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 

As

III 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 co-treatment 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

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
DRAFT—DO NOT CITE OR QUOTE 285

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

Normal human 

keratinocytes treated 

with 50 mJ/cm2 UVB 

before or after iAs 

treatment

AsIII SA

for both

1, as pretreatment

1, as post-treatment

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 iAs-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 arsenic-treated cell lines also showed the same effects.

Takahashi et al., 

2002
DRAFT—DO NOT CITE OR QUOTE 286

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 iAsIII dose of 5. 

Cheng et al., 2007

HaCaT cells 

(immortalized,

non-tumorigenic 

human keratinocyte 

cell line)

As-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

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
DRAFT—DO NOT CITE OR QUOTE 287

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

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 V-FITC 

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
DRAFT—DO NOT CITE OR QUOTE 288

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 HL-60 (which was higher) and HaCaT. Thus 

there is a strong positive correlation between telomerase activity and 

susceptibility to arsenic-induced 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 co-treated 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

TRL 1215 cells

TRL 1215 cells 

pretreated with 50 μM 

BSO for 24 hr to 

deplete GSH levels and 

then co-treated 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 annexin-positive 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 co-treated 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
DRAFT—DO NOT CITE OR QUOTE 289

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 co-treated 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 co-treated 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-DEVD-FMK 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

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 

Fas-associated pathway in iAs-induced 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 iAs alone; ∼3% for 10 μM emodin alone;

∼41% for iAs plus 10 μM emodin; ∼14% for iAs with both 10 μM emodin and 

1.5 mM NAC. Other experiments showed that the effect of emodin in 

enhancing iAs-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
DRAFT—DO NOT CITE OR QUOTE 290

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 V-FITC/PI 

flow cytometry: 27.0% for iAs alone; 6.9% for 30 μM emodin alone; 44.1% 

for iAs plus 30 μM emodin; 20.4% for iAs with both 30 μM emodin and 1.5 

mM NAC. Emodin and iAs synergistically interacted to greatly ⇑ the ROS 

level and to cause cytotoxicity. Pretreatment or co-treatment with NAC 

blocked the synergism for both effects. A 2μM iAs 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 cells 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

AR230-r cells, 

KCL22-r cells

AsIII

ATO

1 24 hr None

Western blot analyses: iAs alone caused NSE on protein levels of tyrosine 

phosphorylated Bcr-Abl or total cellular Bcr-Abl in etiher cell line. In both cell 

lines, combined treatment of iAs with 100 μM BSO yielded huge ⇓ in both 

proteins. In non-imatinib resistant CML cells, unlike in these 2 imatinibresistant cell lines, iAs 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 co-treatment with PI3K inhibitors 

LY294002 and wortmannin, and by the Akt inhibitor Akti5.

Ramos et al., 2005

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 p-Akt, 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
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Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

HK-2 cells AsIII SA 0.1, 1, 10, 25 24 hr 0.1

Induced apoptosis (experimental – control) detected by Annexin V-FITC/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 iAs 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 FITC-annexin 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

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
DRAFT—DO NOT CITE OR QUOTE 292

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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

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; iAs 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 iAs induced PARP cleavage in a dosedependent 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

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 iAs-induced cytochrome c release. At 

concentrations of 125 and higher, Bax and Bak became irrelevant to the mechanism of cytotoxicity and cell 

death resulted form 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: iAs, ∼6%; iAs + 10 μM BSO, ∼29%;

NB4 cells: iAs, ∼8%; iAs + 10 μM BSO, ∼47%.

BSO treatments markedly reduced GSH levels.

Chen et al., 2006
DRAFT—DO NOT CITE OR QUOTE 293

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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: iAs, NSE; iAs + 10 μM BSO, ∼25%;

U937 cells: iAs, NSE; iAs + 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 cells lines following co-treatment of 

iAs 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 

co-treatment). 

Chen et al., 2006

Jurkat cells

U937 cells 

AsIII

ATO

for both 

1

for both

Various, for 

6-72 hr

Time course experiments for co-treatment 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

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 iAs + 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 co-treatment with 10 μM BSO; NSE on these 3 proteins after iAs or 

BSO alone. Experiments with inhibitors suggested that (1) both caspase- and 

JNK-mediated pathways (due to activation of NF-κB) participate in the 

induction of apoptosis that occurs following co-treatment with iAs and BSO 

and (2) that JNK increases DR5 protein levels that in turn mediate that 

apoptosis.

Chen et al., 2006
DRAFT—DO NOT CITE OR QUOTE 294

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 iAs of 0.125-10 μM. Tests of MEK1 

mRNA knockdown using iAs treatments and MEK1 inhibitors (namely, PD98059 at 40 μM and PD184352 at 1 μM) showed that 

MEK1 inhibitors and iAs synergize to induce apoptosis. Although iAs 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. Phophorylated 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 iAs 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 iAs 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. iAs 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 iAs-induced up-regulation of 

∆Np73, with the result that the TAp73/∆Np73 ratio increased, leading to more apoptosis. At 1 μM, iAs induced only p73, but at 

doses ≥ 2 μM) it also promoted accumulation of p53 protein levels, which also caused apoptosis. 

Lunghi et al., 

2006

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 iAs 

treatment

AsIII SA

for both

1, as pretreatment

1, as post-treatment

begun 24 hr after 

irradiation

24 hr for both

1

 

None

Apoptosis as detected by PI staining and TUNEL assay: The iAs treatment 

alone did not induce a significant increase in apoptosis or cytotoxicity;

⇓ the level of UV-induced 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

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
DRAFT—DO NOT CITE OR QUOTE 295

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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 iAs-induced 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

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
DRAFT—DO NOT CITE OR QUOTE 296

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

HaCaT cells 

(immortalized,

non-tumorigenic 

human keratinocyte 

cell line)

 

As-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 As-TL 

cells was seen to apoptosis induction by 25 J/cm2 of UVA, as well as by 

cisplatin, etoposide, and doxorubicin. As-TL cells showed greatly increased 

stability of nuclear P-PKB, and pretreatment with chemicals that inhibit PKB 

phosphorylation blocked iAs-induced acquired apoptotic resistance.

Pi et al., 2005

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 post-treatment 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.

Komissarova et 

al., 2005

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.

Komissarova et 

al., 2005

Undifferentiated 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
DRAFT—DO NOT CITE OR QUOTE 297

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 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

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 

COX-2 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 COX-2 

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 apoptosis: 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
DRAFT—DO NOT CITE OR QUOTE 298

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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

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
DRAFT—DO NOT CITE OR QUOTE 299

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 iAs 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 iAs + 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

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 ATO-mediated 

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

durations

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 co-treatment or pretreatment with 

tBHQ partially or completely blocked iAs-induced apoptosis.

Kann et al., 2005b

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 & 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
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Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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/Bak-dependent mechanism.

Bustamante et al., 

2005

Isolated rat liver 

mitochondria loaded 

with Ca2+

AsIII

ATO 

10, 50, 100 2 min 10

There was a dose-dependent, 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 iAs 

which, however, appeared to cause oxidative modification of thiol groups of 

pore-forming proteins, notably adenine nucleotide translocase.

Bustamante 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 iAs doses, 

thus showing that it prevented induction of apoptosis by iAs.

Szymczyk et al., 

2006

NIH 3T3 cells AsIII SA 5, 10, 20, 50, 100, 

200

6 hr 10

Induction of caspase 3/7 activity assayed using Caspase-Glo 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. 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 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 iAs treatments, thus avoiding generation of 

extracellular ROS in tissue culture media caused by direct addition to it of 

AA.)

Induced apoptosis for iAs + icAA = 1% (NSE)

Results using annexin V/FITC assay gave a consistent but milder effect.

Karasavvas et al., 

2005
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Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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: dose-related marked ⇓ in NuFr 

reaching ∼20%;

Co-treatments with 50-200 μM DMPS: dose-related 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: dose-related marked ⇑ in NuFr reaching 

∼90%;

Co-treatments with 10-40 μM DMSA: dose-related marked ⇑ in NuFr reaching 

∼75%;

Co-treatments with 5-20 μM DMPS: dose-related marked ⇑ in NuFr reaching 

∼80%

Jan et al., 2006

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 iAs alone to ∼26%;

CoTr 100 μM DMPS: ⇓ from iAs alone to ∼37%.

Effects of CoTr with modulators at low doses:

CoTr 20 μM DMSA: ⇑ from iAs alone to ∼83%;

CoTr 10 μM DMPS: ⇑ from iAs alone to ∼88%.

Jan et al., 2006
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Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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 iAs alone to ∼22%;

CoTr 100 μM DMPS: ⇓ from iAs alone to ∼28%.

Effects of CoTr with modulators at low doses:

CoTr 20 μM DMSA: ⇑ from iAs alone to ∼70%;

CoTr 10 μM DMPS: ⇑ from iAs alone to ∼72%.

Jan et al., 2006

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: 

iAs at dose of 2: NSE; 200 μM sulindac: NSE;

(2 μM iAs + 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 iAs: NSE; 200 μM sulindac: NSE;

(2 μM iAs + 200 μM sulindac): ⇑ to ∼1.4x.

Regarding caspase 9 protein levels: 2 μM iAs: ⇑ to 1.05x; 200 μM sulindac: NSE;

(2 μM iAs + 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 hypo-diploid 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 iAs yielded no more than an additive 

effect.

Ivanov and Hei, 

2006

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 post-treatment 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
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Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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

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 post-treatment 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 HPRT-proficient to HPRT-deficient cells, thereby 

allowing recovery of the 6-thioguanine-resistant (HPRT-deficient) cells.

Tsuchiya et al., 

2005

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
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Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

UROtsa cells

AsIII SA

AsV

MMAIII

O

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 [3H]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

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

durations

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
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Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 iAs could be tested on them. Progression of iAs-treated cells 

from each cell cycle stage to the next was studied, and it was found that iAs 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 iAs, it lasted 

16 hr. In the presence of iAs, 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 iAs arsenite. Clearly 

there was not induction of cell-cycle arrest at one specific checkpoint. The biggest iAsinduced slowdown occurred between M and G1, and the next biggest was between G2 and 

M. By looking at caspase activity, they showed that iAs induced apoptosis specifically in 

cell populations delayed in the G2/M phase.

McCollum et al., 

2005

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

iAs 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 iAs 

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 nonapoptotic 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. As 

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 iAs 

induced mitosis-mediated cell death.

Yih et al., 2005

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 iAs-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 (γ-H2AX). 

Yih et al., 2005

CGL-2 cells AsIII SA 

Following on from row above, other experiments showed that iAs 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
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Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

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. iAs 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

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 

iAs 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: iAs delayed entry into mitosis in both p53(+) and

p53(-) cells, with peak being delayed by ∼3 hr from that of cells unexposed to iAs. Mitotic 

exit occurred at a normal rate in iAs-treated p53(+) cells but was markedly delayed in p53(-)

cells and only reached the baseline level after 24 hr, by which time the iAs-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
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Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

CHO cells treated with 

MMS before or after 

iAs 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

MCF-7 cells AsIII

ATO

3 24 hr 3

Treatment blocked the cell cycle in mitosis, resulting in a time-dependent 

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

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 sister-chromatid 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 iAs treatment, there were ∼25% as many cells as in the control. Hsu et al., 2005
DRAFT—DO NOT CITE OR QUOTE 308

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

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 co-treatment with PD98059 or U0126.

Li et al., 2006a

Human lymphoblastoid 

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 effect, 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

K562 cells (human 

erythroleukemia 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
DRAFT—DO NOT CITE OR QUOTE 309

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

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 

iAs 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
DRAFT—DO NOT CITE OR QUOTE 310

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 FBS-stimulated 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

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 iAs and at 1 μM and 

higher for the other arsenicals. Cell cycle distributions were changed in many 

different ways.

Mudipalli et al., 

2005
DRAFT—DO NOT CITE OR QUOTE 311

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 iAs 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 [3H]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.)

Barchowsky et al., 

1996

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 Barchowsky 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-and-plate 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.

Komissarova 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
DRAFT—DO NOT CITE OR QUOTE 312

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

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. As 

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 iAs 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

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 dose response.

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.

Larramendy 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

Larramendy 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

Larramendy et al., 

1981
DRAFT—DO NOT CITE OR QUOTE 313

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

Larramendy 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

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 chromosome-type 

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

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
DRAFT—DO NOT CITE OR QUOTE 314

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

G12 cells

MMAIII

O

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 sub-linear 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 dose-response; 36.7% of cells with aberrations at dose of 10.

8.0% of cells with aberrations at dose of 100.

Kochhar et al., 

1996

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 dose-response; 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 dose response.

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

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
DRAFT—DO NOT CITE OR QUOTE 315

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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

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 form 44-74x 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
DRAFT—DO NOT CITE OR QUOTE 316

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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; co-treatment 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 

arsenic-induced 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

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 anueploidy.

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
DRAFT—DO NOT CITE OR QUOTE 317

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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. 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

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. Co-treatment 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
DRAFT—DO NOT CITE OR QUOTE 318

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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

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 dose-response 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
DRAFT—DO NOT CITE OR QUOTE 319

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

BrdU-substituted 

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 proteinassociated 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

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
DRAFT—DO NOT CITE OR QUOTE 320

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 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.

iAs-induced 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 post-treatment to block cytokinesis):

~4% at 11.5, ~5% at 23;

~18% at 11.5, ~13% 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

11.5

11.5

Induced (experimental – control) % of MN in binucleated cells (with 

cytochalasin B post-treatment 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
DRAFT—DO NOT CITE OR QUOTE 321

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 iAs alone to ∼155;

CoTr 100 μM DMPS: ⇓ from iAs alone to ∼170.

Effects of CoTr with modulators at low doses:

CoTr 20 μM DMSA: ⇑ from iAs alone to ∼605;

CoTr 10 μM DMPS: ⇑ from iAs 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 iAs alone to ∼130;

CoTr 100 μM DMPS: ⇓ from iAs alone to ∼155.

Effects of CoTr with modulators at low doses:

CoTr 20 μM DMSA: ⇑ from iAs alone to ∼465;

CoTr 10 μM DMPS: ⇑ from iAs alone to ∼470.

Jan et al., 2006

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 iAs alone to ∼170;

CoTr 100 μM DMPS: ⇓ from iAs alone to ∼175.

Effects of CoTr with modulators at low doses:

CoTr 20 μM DMSA: ⇑ from iAs alone to ∼630;

CoTr 10 μM DMPS: ⇑ from iAs 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 iAs alone to ∼150;

CoTr 100 μM DMPS: ⇓ from iAs alone to ∼150.

Effects of CoTr with modulators at low doses:

CoTr 20 μM DMSA: ⇑ from iAs alone to ∼680;

CoTr 10 μM DMPS: ⇑ from iAs alone to ∼645.

Jan et al., 2006
DRAFT—DO NOT CITE OR QUOTE 322

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 iAs alone to ∼145;

CoTr 100 μM DMPS: ⇓ from iAs alone to ∼150.

Effects of CoTr with modulators at low doses:

CoTr 20 μM DMSA: ⇑ from iAs alone to ∼570;

CoTr 10 μM DMPS: ⇑ from iAs 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 iAs alone to ∼160;

CoTr 100 μM DMPS: ⇓ from iAs alone to ∼145.

Effects of CoTr with modulators at low doses:

CoTr 20 μM DMSA: ⇑ from iAs alone to ∼620;

CoTr 10 μM DMPS: ⇑ from iAs alone to ∼650.

Jan et al., 2006

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; iAs 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 iAs 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
DRAFT—DO NOT CITE OR QUOTE 323

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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; iAs 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 iAs with 

PD98059 or U0126, these 2 structurally dissimilar inhibitors of MEK1/2 

caused no further ⇓ from iAs 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

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 

As

III SA; when co-treated together, there is a synergistic effect.

Wang et al., 1997
DRAFT—DO NOT CITE OR QUOTE 324

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 DNAdependent protein kinase, and the Ku70 protein plays an important role in 

repair of DNA double-strand breaks. 

Liu et al., 2007b

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; iAs, ∼17/1000

cen+ MN: control, ∼2/1000; iAs, ∼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
DRAFT—DO NOT CITE OR QUOTE 325

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

Human-hamster 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

Human-hamster 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

Human-hamster 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

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 iAs-treated 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 

long-term 

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 iAs. 

Liu et al., 2005

Human-hamster 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 dose response 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
DRAFT—DO NOT CITE OR QUOTE 326

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

Human-hamster 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 iAs 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 

iAs treatment, with the transformation rate then exceeding 500 and 200 times 

that of the iAs or B[α]P treatments alone, respectively.

Lau and Chiu, 

2006

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 MALDI-TOFMS analysis and other methods: iAs 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 downregulated; 6 proteins belonging to antioxidative stress-, chaperone-, and 

glycolytic proteins were 

up-regulated. Also phosph-ERK1/2 and α-actinin, which are associated with 

promotion of cell proliferation and de-differentiation, were up-regulated.

Lau and Chiu, 

2006

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 iAs 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 iAs markedly 

increased the cellular uptake of BPDE in a dose-dependent manner. It was 

concluded that this effect contributes to the co-carcinogenesis in addition to 

arsenic’s “well demonstrated inhibitory effect on DNA repair.”

Shen et al., 2006

Co-mutagenesis
DRAFT—DO NOT CITE OR QUOTE 327

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

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 iAs except for 1 J/m2 with the 10 

μM iAs treatment. At other UV dose levels, the responses at 10 μM arsenic 

only slightly exceeded those at 5 μM. UV or iAs 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 iAs treatment was 

observed.

Lee et al., 1985

Human peripheral 

lymphocytes 

simultaneously 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 iAs.

Wiencke and 

Yager, 1992

Human peripheral 

lymphocytes 

simultaneously 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 iAs

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: iAs 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; iAs 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 

iAs 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
DRAFT—DO NOT CITE OR QUOTE 328

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

CHO cells treated with 

MMS before or after 

iAs 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

CHO cells treated with 

MMS before or after 

iAs 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

iAs 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 iAs treatment induced mutations by itself, as a post-treatment 

these iAs treatments both caused an ⇑ in the mutation frequency compared to 

MNU alone; there was a synergistic interaction.

Li and Rossman, 

1989a

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 iAs 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 iAs 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
DRAFT—DO NOT CITE OR QUOTE 329

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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 iAs 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

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 3 Gy of 69 

cGy/min gamma 

radiation at beginning 

of iAs 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
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Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

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

Dimethyl

-arsinate, 

the usual 

form of 

DMAV

in this 

table

ThioDMAV

(i.e., 

Thiodimethyl

-arsinate)

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 thio-DMA 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
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Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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

Human-hamster 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

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
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Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 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

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: Wild-type, 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
DRAFT—DO NOT CITE OR QUOTE 333

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 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

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; XRS-5, 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
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Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

CHO cells treated with 

MMS before or after 

iAs 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 iAs 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

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
DRAFT—DO NOT CITE OR QUOTE 335

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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 MMAIII

O, 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

Komissarova et 

al., 2005

U-2OS cells AsIII SA 

for all

LC50

Determinations

24 hr

48 hr

72 hr

-

-

-

Cell survival was determined using the clonal survival treat-and-plate (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.

Komissarova 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

Undifferentiated 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, 17β-estradiol, 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
DRAFT—DO NOT CITE OR QUOTE 336

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 arsenicfree 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.

Komissarova et 

al., 2005

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

Graham-Evans 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

Graham-Evans et 

al., 2004
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Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

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. Co-treatment 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

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-MB-231 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

Human PBMCs 

cultured in various 

ways

AsIII

ATO 1 15 days 1

Colony-forming ability was assessed for ATO alone and for co-treatment with 

Trolox by counting CFU-erythrocytes, CFU-granulocytes-macrophages, and 

BFU-erythrocytes. Biggest effect of ATO alone: 62% ⇓ for CFU-erythrocytes. 

In all 3 cases, co-treatment with Trolox had little or no effect.

Diaz et al., 2005
DRAFT—DO NOT CITE OR QUOTE 338

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

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 iAs 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 iAs. GSH depletion by BSO treatment caused big ⇑ in iAsinduced cytotoxicity. icAA caused big ⇓ in cytotoxicity caused by iAs in GSHdepleted cells. Extracellular AA caused big ⇑ in iAs-induced cytotoxicity, 

including after GSH depletion. Relatively limited data from a methylcellulose 

colony-forming assay in both cell lines (with 48-hr iAs 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 iAs-induced cytotoxicity.

Karasavvas et al.,

2005

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 iAs effect 

at dose of 15.4, whereas 15-min pretreatment with 0.1% or 0.2% (v/v) DMSO 

partially blocked it.

Pérez-Pastén 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

Othumpangat et 

al., 2005
DRAFT—DO NOT CITE OR QUOTE 339

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

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 iAs exposure. In all 4 cell types, the iAs + BSO 

treatment caused big to huge ⇓ in number of viable cells, whereas untreated 

cells or cells treated with iAs or BSO showed ∼2-fold ⇑. A similar assay in 

primary cultures of mononuclear cells from 4 patients in blast crisis with 

imatinib-resistant CML also showed maximum cytotoxicity for the combined 

iAs + 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

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

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
DRAFT—DO NOT CITE OR QUOTE 340

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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

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 colony-forming 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. Co-treatment 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

SV-HUC-1 cells AsIII

ATO

0.5, 1, 2, 3, 4 12 days 0.5

Cell survival was determined by colony-forming 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. Co-treatment 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
DRAFT—DO NOT CITE OR QUOTE 341

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

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 iAs 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

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 AsV-treated cells with rifampin or taurocholic acid eliminated 

the difference between the two cell types. OATP-C can transport iAs in a (GSH)-

dependent manner but this may not be the major pathway for arsenic transport. 

Lu et al., 2006
DRAFT—DO NOT CITE OR QUOTE 342

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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 PI-exclusion 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 co-treated 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

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 iAsinduced cytotoxicity in a dose- and time-dependent 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. Co-treatment 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 iAs 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

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
DRAFT—DO NOT CITE OR QUOTE 343

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

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, iAs 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 25-30% by cotreatment with PD98059 or U0126, which are these 2 structurally dissimilar 

inhibitors of MEK1/2.

Li et al., 2006a
DRAFT—DO NOT CITE OR QUOTE 344

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

Human neuroblastoma 

cell lines: 

IMR-32

SK-N-DZ

SK- N-BE(2)

SK-N-AS

SH-SY5Y

All 4 lines ± cotreatment with 25 μM 

DCHA

AsIII

ATO

1 48 hr

- or +

None, 1

DCHA

None, 1

1, 1

1,1

1,1

Cell survival (% of control) was determined using the MTT assay:

NSE, NSE, 35%;

iAs alone, DCHA alone, (iAs + DCHA)

NSE, NSE, 45%;

73%, NSE, 41%;

56%, NSE, 39%;

61%, NSE, 40%;

co-treatment of (iAs +DCHA) with vitamin E blocked much of the cytotoxicity 

in line IMR-32.

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
DRAFT—DO NOT CITE OR QUOTE 345

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 iAs treatments caused 4% or less 

cytotoxicity; however, as post-treatments 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 iAs treatments caused 8% or less cytotoxicity; however, as post-treatments 

they increased the cytotoxicity caused by the UV treatments.

Li and Rossman, 

1991

Human-hamster 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

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
DRAFT—DO NOT CITE OR QUOTE 346

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

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 colony-formation 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 heat-inactivated 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)

As

III 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
DRAFT—DO NOT CITE OR QUOTE 347

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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 10–50 followed by a logarithmic decrease in 

CFE with a linear increase in dose

Barrett et al., 1989

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

MMAIII

O

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
DRAFT—DO NOT CITE OR QUOTE 348

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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 

Tchounwou, 2007

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 dye-exclusion 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 

M-macrophages

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 

GM-macrophages

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
DRAFT—DO NOT CITE OR QUOTE 349

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

The following cell 

lines: HL-60, 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 

T-lymphocytes, 

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

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 As 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 ⇑ As 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 iAs

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
DRAFT—DO NOT CITE OR QUOTE 350

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

DNA Damage

WRL-68 (human 

hepatic cell line) AsIII SA 0.001, 0.01, 0.1, 10 16 hr 0.001

Induction of DNA-protein crosslinks

(Methylated forms of arsenic could not be detected in the cells.) Ramírez et al., 

2000

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

PHA-stimulated 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, arsenic-induced 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 dose-dependent 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 UV-irradiation 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

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 UV-irradiation 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 double-stranded 

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
DRAFT—DO NOT CITE OR QUOTE 351

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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

1–1000

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 alkali-labile lesions in DNA detected in the single-cell 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

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 

B-lymphocytes)

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 & 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 & 1: MMAIII >> DMAIII = AsIII;

at 40 & 100: DMAIII > MMAIII > AsIII.

Gómez et al. , 

2005

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
DRAFT—DO NOT CITE OR QUOTE 352

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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.

Soto-Reyes et al., 

2005

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

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 dose response; 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
DRAFT—DO NOT CITE OR QUOTE 353

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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

ATO 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 

Tchounwou, 2007

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

Graham-Evans et 

al., 2004
DRAFT—DO NOT CITE OR QUOTE 354

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 chronicexposure 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 single-strand breaks 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, DNA single-strand 

breaks were detected by single-cell gel electrophoresis (comet assay) following 

alkaline treatment:

⇑ at LD10; ⇑⇑ at LD25

NSE at LD10; ⇑ at LD25

⇑⇑ at LD10; ⇑⇑ at LD25

Graham-Evans 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 iAs alone to ∼38 units;

CoTr 100 μM DMPS: ⇓ from iAs alone to ∼39 units.

Effects of CoTr with modulators at low doses:

CoTr 20 μM DMSA: ⇑ from iAs alone to ∼104 units;

CoTr 10 μM DMPS: ⇑ from iAs alone to ∼84 units.

Jan et al., 2006

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 iAs alone to ∼34 units;

CoTr 100 μM DMPS: ⇓ from iAs alone to ∼35 units.

Effects of CoTr with modulators at low doses:

CoTr 20 μM DMSA: ⇑ from iAs alone to ∼99 units;

CoTr 10 μM DMPS: ⇑ from iAs 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
DRAFT—DO NOT CITE OR QUOTE 355

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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 twofold 

dilutions from a concentration that inhibits growth

Rossman et al., 

1984

Human-hamster 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: pre-incubation with MnTMPyP, LNAME 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 As 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 double-stranded 

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

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

Dimethyl

-arsine

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
DRAFT—DO NOT CITE OR QUOTE 356

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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 MMS-induced 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

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

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(ADPribosyl)ation by reducing PARP-1 activity.

Walter et al., 2007
DRAFT—DO NOT CITE OR QUOTE 357

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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 iAs treatment. DNA damage measured by SCGE (comet) assay:

iAs 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

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

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 β-galactosidase 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
DRAFT—DO NOT CITE OR QUOTE 358

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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 

NADPH-dependent 

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

Human-hamster 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

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
DRAFT—DO NOT CITE OR QUOTE 359

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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.

Soto-Reyes 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; preincubation with SOD, MnTMPyP, L-NAME 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: co-exposure with PQ 

or sequential exposures of 1 hr (with either one first) yielded a strong response.

Kawaguchi et al., 

1996

PAEC cells harvested 

from freshly isolated 

vessels

AsIII SA 5, 10 1 hr 5

Various experiments showed that iAs 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 Barchowsky et al., 

1999b

HFW cells AsIII SA 5, 10, 20 24 hr 5 DCF fluorescence to indicate formation of cellular oxidants; co-treatment 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

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.

Barchowsky et al., 

1996
DRAFT—DO NOT CITE OR QUOTE 360

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

Human-hamster 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 L-NMMA (a nitric oxide synthase inhibitor) 

substantially reduced the mutation frequencies at both doses. Similar treatment 

with D-NMMA (the inactive enantiomer) had no effect. These finding were 

taken as evidence that peroxynitrites have an important role in iAs-induced 

genotoxicity. That conclusion was supported by a Western-blot analysis of 

nitrotyrosine-modified proteins induced by iAs treatments and mostly blocked 

by L-NMMA.

Liu et al., 2005

HepG2 cells

AsIII

ATO

20 6 hr 20

Analysis of 481 selected genes in a DNA microarray experiment: hierarchical 

clustering analysis showed that iAs 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 iAs caused significant up-regulation of 38 genes and 

down-regulation 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

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
DRAFT—DO NOT CITE OR QUOTE 361

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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

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

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>MMAV>

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 As-induced oxidative 

stress from some treatments was not significantly decreased by tBHQ. Yet, tBHQ pretreatment or co-treatment greatly decreased 

iAs 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 iAs and H2O2 but whose response to iAs was reversed by NAC. It was found that 26% of the 

genes significantly responsive to iAs might have been directly altered by ROS. iAs 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 co-treatment with either NAC or α-Toc 

Felix et al., 2005

BEAS-2B cells

AsIII

ATO 5, 10, 20 24 hr 5

Production of 8-isoprostane, a by-product of lipid peroxidation: ⇑ with a 

positive dose response; 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 iAs can produce ROS, 

such as H2O2 and •OH, as a result of reduction reactions within cells.

Han et al., 2005
DRAFT—DO NOT CITE OR QUOTE 362

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 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 

iAs-induced production of ROS at dose of 15.4, whereas 15-min pretreatment 

with 0.1% (v/v) DMSO partially blocked it

Pérez-Pastén 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 DCFH-DA assay in the 15 min after iAs 

treatment: ⇑ with dose to >2x control at dose of 10.

Yang et al., 2007

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; iAs at dose of 3: ∼150; iAs at dose of 1: ∼240;

Effects of co-treatment (CoTr):

iAs at 3 + CoTr with 1000 μM DTT: ∼275;

iAs at 3 + CoTr with 2000 μM DTT: ∼340

iAs at 1 + CoTr with 25 μM DTT: ∼150;

iAs at 1 + CoTr with 50 μM DTT: ∼125

Jan et al., 2006

NB4 cells AsIII

ATO

0.5 2 hr 0.5

Intracellular H2O2 level (units of Amplex red assay): Control = ∼20; iAs ∼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
DRAFT—DO NOT CITE OR QUOTE 363

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

A549 cells AsIII

ATO

2 48 hr

Loss of MMP determined by flow cytometry using JC-1: 2 μM iAs: ⇑ to ∼1.25x; 

200 μM sulindac: ⇑ to ∼1.15x; (2 μM iAs + 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

A549 cells AsIII

ATO

2 48 hr 2

Production of ROS using carboxy-H2DCFDA assay: control, ∼0.8 unit; 2 

μM iAs, ∼4.2 units; 200 μM sulindac: ∼4.5x; (2 μM iAs + 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, iAs 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

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
DRAFT—DO NOT CITE OR QUOTE 364

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 co-treated 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 co-treated 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

TRL 1215 cells

TRL 1215 cells 

pretreated with 50 μM 

BSO for 24 hr to 

deplete GSH levels and 

then co-treated 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 

iAs and to ⇑ roughly 3x higher than for iAs alone following a combined iAs 

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 co-treatment of iAs with emodin 

had a major oxidative impact on the cellular redox state, as shown by 

following ratios: control, ∼62; iAs, ∼52; 10 μM emodin, ∼34; iAs plus 10 μM 

emodin, ∼13; pretreatment with 1.5 mM NAC attenuated (but did not 

completely block) this effect.

Yi et al., 2004
DRAFT—DO NOT CITE OR QUOTE 365

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 

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

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 co-treatment 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 WST-1 cell proliferation assay: iAs 

treatment resulted in ∼22% cell survival; co-treatment 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 iAs induced both superoxide anion and H2O2

through the activation of NAD(P)H oxidase. Presence of superoxide anion in 

cells that resulted from iAs treatment was confirmed.

Sasaki et al., 2007

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 WST-1 cell proliferation assay: 

LC50s in PRCC: iAs, ∼10; co-treatment of iAs with 10 μM α-lipoic acid, ∼25; 

LC50s in HEK293: iAs, ∼1; co-treatment of iAs with 10 μM α-lipoic acid, ∼7. 

In both cell types, this antioxidant markedly attenuated iAs’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 WST-1 cell proliferation assay: 

LC50s: NB4, ∼0.2; HL60, ∼8; KMS12BM, ∼0.3; U266, ∼0.3. In all 4 cells 

lines, co-treatment of iAs with 10 μM α-lipoic acid resulted in a remarkably 

similar dose-related pattern of cell survival to that seen with iAs 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 dose-response curve that was 

presented.

Sasaki et al., 2007

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
DRAFT—DO NOT CITE OR QUOTE 366

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

Undifferentiated PC12 

cells

AsIII

ATO 8

Various up to 

6 hr 8

Detection of ROS shown by increase of DCF-fluorescence in DCFH-DA 

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

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 PEGSOD blocked some ROS production; less effect for both than for iAsIII, 

suggesting a difference in the ROS they produce.

Eblin et al., 2006

Human-hamster 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

Human-hamster 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 alkali-labile lesions in DNA detected in the single-cell 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 AsIII- induced DNA damage.

Kligerman and 

Tennant, 2007
DRAFT—DO NOT CITE OR QUOTE 367

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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 iAsV, 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

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 iAs 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

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 co-treatments 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 co-treatment, 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 co-treatments 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 calcium-mediated 

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 arsenite-stimulated superoxide (O2

-

) formation.

Barchowsky 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

φX174 RF I DNA

Naked double-stranded 

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 co-treatments 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
DRAFT—DO NOT CITE OR QUOTE 368

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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 HL-60 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

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 As pretreatment)

14.5 (was 6.5 mM with no As 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 iAsIII, 206 mM for As

V;

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

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
DRAFT—DO NOT CITE OR QUOTE 369

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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 40–98% 

cytotoxicity.

Rossman and 

Wolosin, 1992

AG06 cells AsIII SA 6

Assay’s 

maximal 

response time 

6

Amplification of endogenous dhfr genes (determined by MTX-selection 

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 MTX-selection 

assay): dose response was the same for both durations beginning with 0.025; it 

increased with dose to 0.05 and then plateaued.

Mure et al., 2003

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 arsenic-treated 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
DRAFT—DO NOT CITE OR QUOTE 370

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

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 dose response 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

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
DRAFT—DO NOT CITE OR QUOTE 371

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

A549 cells (human 

adenocarcinoma)

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

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

Untransformed 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

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 c-myc 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 methylationsensitive 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 shorter-term 

exposure, and vice-versa.

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
DRAFT—DO NOT CITE OR QUOTE 372

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 trypan-blue assay) or apoptosis.

Deaglio et al., 

2001

HPBMs co-exposed 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 co-exposed 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

HPBMs co-exposed 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 co-exposed 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 co-exposed 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 iAsV, MMAV and DMAV. This effect was not seen at doses exceeding 1.

Sakurai et al., 

2006

HPBMs co-exposed to 

GM-CSF 

AsIII SA 0.5 7 days 0.5

In comparison to the cells not treated with iAs, 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 arsenic-untreated cells. 

Sakurai et al., 

2006
DRAFT—DO NOT CITE OR QUOTE 373

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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 iAs 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 VCAM-1 were measured, with the following results: ICAM-1: ⇑

in iAs only group and huge ⇑ at all 3 dose levels of GLN; VCAM-1: NSE in 

iAs only group and ⇑ at all 3 dose levels of GLN, with largest ⇑ at 300 μM. 

Clearly HUVECs were activated by iAs. Also at this time, PMN expressions of 

CD11b and IL-8 receptor were measured, with the following results: CD11-b: 

⇑ in iAs only group and bigger ⇑ at all 3 dose levels of GLN; IL-8 receptor: ⇑

in iAs only group and at all 3 dose levels of GLN. Clearly PMNs were 

activated by the iAs treatment of the HUVECs. Effects on PMN migration: In 

absence of GLN pretreatment, iAs caused slight ⇓ from 36% to 30% migrated. 

In the iAs + 300 μM GLN group: ⇑ from ∼40% (for GLN alone) to ∼50% 

migrated (for iAs + GLN), which was the most migration observed.

Hou et al., 2005

PBMCs co-treated 

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 co-treated 

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

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
DRAFT—DO NOT CITE OR QUOTE 374

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

PBMCs co-treated

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 iAs

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 iAs 

treatment

AsIII

ATO

1 6 days None 

for ⇓

NSE regarding FLIPL protein level,

big ⇑ XIAP protein level Lemarie et al., 

2006a

Differentiated 

macrophages 

developed from 

PBMCs

treated with GM-CSF 

for 6 days before iAs 

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 iAs

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 iAs “de-differentiated’ macrophages back into monocytic cells. 

The effect was time-dependent 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. iAs 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 iAs

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
DRAFT—DO NOT CITE OR QUOTE 375

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 iAs

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 

iAs 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 iAs

treatment

AsIII

ATO

1 6 days 1

Ability to secrete inflammatory cytokines in response to co-treatment of iAs 

(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 iAs treatment.

Lemarie et al., 

2006b

Differentiated 

macrophages 

developed from 

PBMCs

treated with GM-CSF

for 6 days before iAs

treatment

AsIII

ATO

1 6 days 1

The iAs-treated macrophages differentiated into dendritic-like cells when 

exposed to GM-CSF and IL-4 in the absence of iAs 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 iAs) did not show this response.

Lemarie et al., 

2006b

Differentiated 

macrophages 

developed from 

PBMCs

treated with GM-CSF

for 6 days before iAs

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
DRAFT—DO NOT CITE OR QUOTE 376

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 Y-27632 for 2 

hr before iAs treatment

AsIII

ATO

1 72 hr 1

Pretreatment with the ROCK inhibitor prevented both the F-actin 

reorganization and cellular rounding of macrophages treated with iAs. It also 

considerably blunted damage to the phagocytosis function caused by the iAs 

treatment. 

Lemarie et al., 

2006b

HepG2 cells AsIII SA 0.04, 0.4, 4, 40 48-hr

pretreatment

4

After the iAs 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

HepG2 cells AsIII SA 0.04, 0.4, 4, 40, 400

48-hr

pretreatment 40

After the iAs 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 iAs 

pretreatment, with slight ⇓ at 40 and huge ⇓ at 400. iAs 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

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 iAs on JAK-STAT inactivation is independent of 

ligand-receptor 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

iAs (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 iAs selectively targeted JAK tyrosine kinase and that the inhibition of 

JAK-STAT activity by iAs 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 iAs

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
DRAFT—DO NOT CITE OR QUOTE 377

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 iAs

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 GM-Mp, which 

had a round saucer-like appearance; at dose of 0.10, ∼80% of living cells were 

GM-Mp and the rest were abnormal “arsenite-induced cells”; at dose of 0.50, 

∼10% of living cells were GM-Mp and the rest were “arsenite-induced cells”.

Sakurai et al., 

2005b

PBMCs treated with 

5000 U/mL of GMCSF at the same time 

as with iAs

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 iAs), 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

PBMCs treated with 

5000 U/mL of 

GM-CSF at the same 

time as with iAs

AsIII SA 0.50 7 days 0.50

The resulting high numbers of “arsenite-induced cells” were markedly 

reduced by co-treatment with DMPO, DMSO, or BHT, all of which are 

membrane-permeable 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 GMCSF at the same time 

as with iAs

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

PBMCs stimulated 

with PHA for 96 hr 

starting 24 hr after the 

beginning of the iAs 

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
DRAFT—DO NOT CITE OR QUOTE 378

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 iAs 

treatment

AsIII SA 1, 2, 3, 4, 5 120 hr 1

Expression of CD4 and CD8 molecules was determined using CFSE staining 

during the iAs 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

PBMCs stimulated 

with PHA for 96 hr 

starting 24 hr after the 

beginning of the iAs 

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 iAs. 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 iAs 

treatment 

Human CD8+ cells 

stimulated with PHA

for 96 hr starting 

24 hr after the 

beginning of the iAs 

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. As 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

Human CD4+ cells 

stimulated with PHA 

for 96 hr starting 

24 hr after the 

beginning of the iAs 

treatment 

Human CD8+ cells 

stimulated with PHA 

for 96 hr starting 

24 hr after the 

beginning of the iAs 

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. As 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
DRAFT—DO NOT CITE OR QUOTE 379

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

PBMCs stimulated 

with PHA during the 

iAs treatment, CD4+

 

and CD8+ T cells were 

analyzed separately

As

III 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. iAs delayed both 

the expression of CD25 and the down-regulation of CD69, suggesting that iAs 

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-iAsexposed 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

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

SV-HUC-1 cells AsIII SA 2, 4, 8, 10, 40 48 hr

2 for

all 

effects

Microscopy and immunochemistry showed Bcl-6 and p-STAT3 (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. Co-treatment with 50 μM MnII, which caused ~9x ⇑ by 

itself, caused an approximately additive ⇑ to ~12x. Addition of L-NAME to the 

iAs/Mn co-treatment boosted LTE4 level to ~24x. Addition of ETU to iAs/Mn 

co-treatment boosted LTE4 level to slightly above that of iAs/Mn combination. 

Addition of AA-861 to iAs/Mn co-treatment 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
DRAFT—DO NOT CITE OR QUOTE 380

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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

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

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 post-confluence 

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, iAs decreased the exit of cells from the germinative 

compartment under conditions that promote differentiation.

Patterson et al., 

2005
DRAFT—DO NOT CITE OR QUOTE 381

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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 post-confluence 

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, iAs decreased the exit of cells from the germinative 

compartment under conditions that promote differentiation. 

Patterson et al., 

2005

SIK cells, with iAs 

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%, iAs, ~10.8%; 

at 2 days: C, ~0.5%; iAs, ~2.3%; 

at 3 days: C, ~0.1%; iAs, ~2.0%;

at 4 days: C, ~0%; iAs, ~1.3%;

at 5 days: C, ~0%; iAs, ~0.8%

Patterson et al., 

2005

hEp cells, with iAs 

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%, iAs, ~1.37%; 

at 2 days: C, ~0.08%; iAs, ~0.68%

Patterson et al., 

2005

SIK cells, with iAs 

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
DRAFT—DO NOT CITE OR QUOTE 382

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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; iAs, ~18.2;

at 7 days: C, ~0.8; iAs, ~10.5;

at 11 days: C, ~0.7; iAs, ~7.8;

at 14 days: C, ~0.4; iAs, ~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; iAs, ~5.5; 

at 7 days: C, ~0.5; iAs, ~1.8; 

at 11 days: C, ~0.6; iAs, ~1.5;

at 14 days: C, ~0.3; iAs, ~1.3; 

Patterson et al., 

2005

SIK cells, with iAs 

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 iAs + EGF in medium: ⇑ to ∼4.1;

if EGF alone: ∼1.9; if no insulin in medium (± EGF): ∼3.5. Thus, iAs delays 

differentiation and preserves the proliferative potential of keratinocytes.

Patterson and 

Rice, 2007

hEp cells, with iAs 

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 iAs + 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, iAs delays 

differentiation and preserves the proliferative potential of keratinocytes.

Patterson and 

Rice, 2007

SIK cells, with iAs 

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 iAs + 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 iAs had no effect. Thus, iAs delays differentiation and preserves the 

proliferative potential of keratinocytes.

Patterson and 

Rice, 2007

SIK and hEPcells, with 

iAs 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 iAs 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. iAs treatment caused big ⇑ in active Ras 

protein, a downstream effector of EGFR; co-treatment with AG1478 blocked that effect. Other experiments 

showed that the iAs 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 iAs and EGF.

Patterson and 

Rice, 2007

Interference with Hormone Function
DRAFT—DO NOT CITE OR QUOTE 383

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 glucocorticoid response elements in the presence of activated 

GCR; peak response was at ∼0.5; however, iAs 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 iAs 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

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, iAs 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, iAs 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 

iAs concentrations or repression at higher iAs 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 iAs. In summary, it is clear that iAs 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

Hormone-responsive 

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-receptor-mediated transcription.

Kaltreider et al., 

2001

Malignant Transformation or Morphological Transformation
DRAFT—DO NOT CITE OR QUOTE 384

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 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 

simultaneously 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 EGF-induced 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

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 iAsIII.

Mure et al., 2003

Untransformed 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
DRAFT—DO NOT CITE OR QUOTE 385

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 anchorage-independent 

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 dose-related ⇓ at higher doses. A daily 2-hr 42°C heat shock (which 

would induce HSPs) boosted induction of anchorage-independent 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 iAs or heat shock on the already high level of anchorageindependent growth; iAs 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 

heat-shock treatment.

Khalil et al., 2006

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 post-treatment with 0.1 μg/mL TPA 

for 18 days. Except for As

III 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 

Indo-1/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

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 arsenite-induced 

apoptosis.)

Namgung and 

Xia, 2001
DRAFT—DO NOT CITE OR QUOTE 386

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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; iAs 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

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 c-Jun: 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 N-terminal 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 NF-κB 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 

oxidant-sensitive endothelial cell signaling. Increased binding of proteins to 

genomic κB sites could induce a mitogenic or inflammatory response.

Barchowsky et al., 

1996

Gclm+/+ MEF cells 

AsIII SA 

for all

See rows under Apoptosis and Cytotoxicity for this citation for experimental conditions. iAs inhibits NFκB activation and nuclear 

translocation. Co-treatment or pretreatment with tBHQ appears to reverse the iAs-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 AhR-dependent gene expression is only weakly 

up-regulated by iAs.

Kann et al., 2005a
DRAFT—DO NOT CITE OR QUOTE 387

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

1RB3AN27 cells AsIII SA 0.1, 0.5, 1, 5, 10 240 min Various

Activation of nuclear transcription factors detected by EMSA: NF-κB: slight ⇑

at 0.5, ⇑ at 1, huge ⇑ at 5 and 10; effect at dose of 1 was considerably 

suppressed by co-treatment with NAC. iAs-induced degradation of IκBα was 

demonstrated in the cytosolic fraction. AP-1: ⇑ at 0.1, slight ⇑ at 0.5, huge ⇑ at 

1, 5 & 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

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 As

III (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 dose response.

These and other experiments showed that Nqo1 induction occurred through the 

Nrf2/ARE pathway with the following important steps: (1) iAs markedly 

stabilizes Nrf2; (2) iAs disrupts the Nrf2-Keap1-Cul3 complex in the nucleus, 

and (3) iAs recruits Nrf2 and Maf to the ARE of Nqo1. iAs does not recruit 

Keap1, Cul3, ubiquitin, c-Jun, or c-Fos to the ARE of Nqo1.

He et al., 2006

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 

iAs up-regulated TRAIL-mediated apoptosis. iAs 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 iAs caused up-regulation of the endogenous 

TRAIL and down-regulation 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
DRAFT—DO NOT CITE OR QUOTE 388

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(μM)

Results (compared with controls, with all concentrations being 

in μM unless noted) Reference

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: iAs had following effects: ⇑ p21 promoter 

activity, ⇑ p21 mRNA level, ⇑ p21 protein level. Transfection with a p21 siRNA reduced iAs-induced p21 

expression and reduced the iAs-induced cytotoxicity after 24 hr by half. Conclusions: iAs induced p21 

activation via the EGFR-Ras-Raf-ERK1/2 pathway. ERK1/2 and JNK may differentially contribute to iAsinduced p21 expression via the EGFR-Ras-Raf-ERK1/2 pathway. The ERK 1/2 and JNK pathways play 

opposing roles in iAs-induced 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

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 

iAs-induced VEGF expression. Other experiments showed that the arsenicinduced 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 iAs exposures of 50 or 100.

Lee et al., 2006c

HaCaT cells, transfected 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 

iAs-induced 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
DRAFT—DO NOT CITE OR QUOTE 389

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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. iAs 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 iAs-induced changes 

may disrupt cell contraction and signaling. It was concluded that iAs 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, (a) there was a big ⇑ in basal levels of mRNAs of the 

following genes: gadd45α, gadd45β, gadd45γ and gadd153, (b) there was a big ⇑ in iAs-induced (usually at 

20 μM for 4 hr) levels of mRNAs for gadd45α and gadd153, and (c) there was no induction by As (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 dose-related ⇑ becoming huge by 

dose of 10; also similar ⇑ in cytoplasmic Nrf2 protein level.

Massrieh et al., 

2006

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 DNA-binding 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 iAs 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 

iAs 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
DRAFT—DO NOT CITE OR QUOTE 390

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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, 

its was shown that iAs-stimulated Cdc42-induced actin filament reorganization regulated 

the activation of NADPH oxidase. Authors suggested that the formation of superoxide 

anion radicals observed after iAs 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 iAs-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

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 iAs 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 iAs 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

iAs activated the binding of IRP-1 to IRE: ⇑ to 1.35x, with smaller ⇑ to 1.25x 

at dose of 20; 10 and 20 μM iAs caused a slight ⇑ in HIF-1α protein level 

(only ∼2% above control). iAs at dose of 20 had NSE on ferritin protein level.

Li et al., 2006b
DRAFT—DO NOT CITE OR QUOTE 391

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 co-treatment 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. Co-treatment of iAs with either 

PD98059 or U0126 blocked much of the phophorylation of ERK1/2 and 

restored 50-80% of the NER synthesis efficiency. In summary, co-treatments 

of iAs 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

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 iAs-induced p21 

expression, (2) activation of EGFR by iAs occurred later than by EGF, (3) c-Src was involved in iAsinduced ERK activation and p21 expression, (4) the EGFR/Ras/Raf/ERK pathway is involved in iAsinduced p21 gene expression, (5) Sp1 binding sites in the promoter are essential for iAs-induced p21 

activation, and (6) a post-transcriptional or post-translational stabilization mechanism is essential for 

iAs-induced p21 expression. 

Liu and Huang, 

2006

MDA-MB-435 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
DRAFT—DO NOT CITE OR QUOTE 392

Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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 iAs 

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 iAs maintaining the cell’s

proliferative potential, levels of these 3 proteins decreased much less rapidly 

during the 4 days in suspension if treated with iAs.

Patterson et al., 

2005

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-β-catenin: ⇓ 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 iAs maintaining the cell’s proliferative potential, iAs 

decreased the rate of post-confluent loss of all of these proteins except P-βcatenin.

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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Table C-3. In Vitro Studies Related to Possible Modes of Action of Arsenic in the Development of Cancer

Type of cell/tissue

Arsenic

species

Concentration(s) 

tested (μM)

Duration of 

treatment

LOEC1

(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

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, iAs activates the prosurvival mitogen-activated 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 iAs and either 

inhibitor alone, based by Hoechst 33258 or annexin V/PI staining and flow cytometry. Treatment with a p38 

inhibitor did not prevent iAs-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 iAs, whereas emodin or iAs 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
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1

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 a vast array of 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.

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 from19–26 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 

(3.1x106 cells) compared to the control population (2.6x106 cells), with a greater increase 

noted in females. In females, the average 36-hour LI was lower in the exposed population 

compared to the control population, regardless of the presence or absence of skin lesions 

(Table D-1 below). Exposed males, however, only exhibited a lower average 36-hour LI in 

those with skin lesions; 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±0.8* 3.1±1.0*

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±0.49*

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±0.55** 6.60±0.69** 6.34±0.45**

Replication Index

48 hours 1.07±0.01 1.16±0.02 1.12±0.01 1.05±0.01 1.10±0.02* 1.08±0.01*

60 hours 1.43±0.03 1.54±0.04 1.49±0.03 1.39±0.04 1.37±0.04* 1.38±0.02*

72 hours 1.93±0.09 2.08±0.04 2.01±0.04 1.89±0.09 1.84±0.05* 1.86±0.05*

* Statistically different (p <0.05) from the control (two-tailed Mann-Whitney U-test)

** 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 

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. Arsenic 

exposed 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, couch, bronchitis and asthma as compared to 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 due to inflammatory reactions due to arsenic exposure.

Yu et al. (1998) found that patients with Bowden’s disease (skin carcinoma in situ) 

from an arsenic endemic area in the southwest coast of Taiwan had significantly decreased Tcells, increased B-cells, decreased T-helper cells, decreased IFN-γ release, TNF-α release, 

increased IL-2 release, decreased soluble IL-2 receptor release, 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-Bowden’s patients in the 

endemic region. Results indicate a depressed cell mediated immunity in patients with 

Bowden’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 Bowden’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 Bowden’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: 
DRAFT—DO NOT CITE OR QUOTE 398

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 

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 on arsenic 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. As

III 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 

lead 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 
DRAFT—DO NOT CITE OR QUOTE 399

that apoptosis is likely 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 

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, this data supports the data by 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, thus, 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 affects 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. As

III 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 affect 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 at10-7

M, but had no affect 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 responses analyses were performed, there is no data provided in the article. It 

was concluded that the immunotoxicity of arsenic was dependent on the chemical speciation of 

arsenic. 

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, 2x105 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. 

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 that 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 

endpoints were replicated using a different optimizer in the Non-linear Estimation module of 

Statistica® software package. 
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E.1.1 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) (E-1)

In this model, the midpoints of the age group strata are normalized (placed on a “z-scale”) prior 

to estimating risk; 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 (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.

E.1.2 Estimation of Upper Confidence Limits (UCLs) 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% 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 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).
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E.2 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 models, 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:

ci( ) = ∑ x T − i ( ) i(1 ri)

si x

L(x) = lifetime risk of cancer incidence at dose x

 

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) (1) 

ci(0) = background cancer incidencei / cancer free populationi (2) 

Background cancer incidence c i comes from SEER, cancer-free 

populationi, see (7)

bi = background cancer incidencei / alive populationi (SEER data) (3)

Yi = exp (- 5bi) (4)

Fi = Initial estimated background probability of survival without cancer to the 

end of interval (i - 1) 

 

Fi Yi

j

j i

= =

= − ∏ 11

 (5) 

Gi = Initial estimated background probability of survival without cancer to 

the middle of interval (i)
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Gi = Fi (−2.5*bi)

 (6) 

Cancer-free populationi = alive populationi * Gi (7) 

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) (8) 

di = Total mortality (background) in age interval (i)

di = total deathsi / populationi (Census, Vital Stat. U.S.) (9)

hi = cancer deathsi / populationi (Census, Vital Stat. U.S.) (10)

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

 (11) 

ri = Probability of survival cancer free through interval (i), given survival to beginning of 

interval (i)

ri = Wi * Wib (12) 

Wi = exp (- 5di + 5hi – 5ci) (13) 

Wib = exp (- 5ci * Beta * x) (14)

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 (one percent). 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 populations studies (Chen et al., 1988a, 1992 and Wu et al., 1989). This appendix 

provides a brief analysis of some of these concerns. 

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 observation 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 

values. 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 et al. (2003) have also argued that the data from the Taiwanese population 

are being misinterpreted by EPA. In their analysis, they stratify median well arsenic 

concentration into ten ranges from 10 to 934 ppb. They 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 were significantly elevated in the 

lowest exposure groups, decreased to minimums for villages with water arsenic concentrations in 

the range 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 arsenic-associated 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).8

 8 Each township included subsets of the 42 “villages” used as the basic units of analysis in the current assessment. 

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 

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 
DRAFT—DO NOT CITE OR QUOTE 406

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 

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 (and that does not 

incorporate age dependence) resulted in results that are misleading. 

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 
DRAFT—DO NOT CITE OR QUOTE 407

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 the 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), the patterns of cancer risks for 

subjects living in two townships (0, 3, and 5 vs. 2, 4, and 6) villages were evaluated 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. 

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 also 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.
DRAFT—DO NOT CITE OR QUOTE 408

Figure F-1. Lifetime Crude Total Cancer Risk (Male + Female) for the Low- and HighExposure Villages

 

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 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.

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
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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 dose9

) 

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. 

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 

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 

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 Low-Exposure 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-

 9 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. 
DRAFT—DO NOT CITE OR QUOTE 410

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

End Point 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)

For all of the endpoints, the arsenic dose coefficients are positive with lower confidence 

limits that are also positive.10 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 

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.

 10 As in Section 5.3.8, the upper and lower confidence limits were calculated using profile likelihood; similar results are 

obtained using Bootstrap methods.