UNITED STATES ENVIRONMENTAL PROTECTION AGENCY 

WASHINGTON, D.C. 20460 

OFFICE OF THE ADMINISTRATOR 

 SCIENCE ADVISORY BOARD 

June 28, 2007 

EPA-SAB-07-008 

Honorable Stephen L. Johnson 

Administrator 

U.S. Environmental Protection Agency 

1200 Pennsylvania Avenue, N.W. 

Washington, D.C. 20460 

Subject: Advisory on EPA’s Assessments of Carcinogenic Effects of Organic 

and Inorganic Arsenic: A Report of the US EPA Science Advisory Board 

Dear Administrator Johnson: 

The U. S. Environmental Protection Agency’s (EPA) Office of Pesticide 

Programs (OPP), Office of Water (OW), and Office of Research and Development 

(ORD) coordinated the development of two scientific documents that address the 

carcinogenicity of Dimethylarsinic Acid (DMAV) and inorganic arsenic (iAs). In 

response to an Agency request, the Science Advisory Board (SAB) convened an expert 

panel to review and comment on key scientific issues presented in these two documents, 

including: (a) the metabolism and toxic responses of arsenic species; (b) mode(s) of 

carcinogenic action; (c) data selection for dose-response assessment; and (d) approaches 

and methods for low-dose extrapolation for DMAV and iAs. 

The SAB Panel supported the Agency’s conclusion that on the basis of available 

data, human exposure to DMAV appears to result in a narrower spectrum of active 

metabolites than those expected in the metabolic profile associated with exposure to iAs. 

Therefore, the Panel agreed with EPA that, in the absence of human data on DMAV, the 

bladder tumor data from DMAV rat bioassays is better suited for DMAV cancer risk 

assessment than is epidemiology data from iAs exposure. The Panel, however, noted that 

there remain significant uncertainties associated with the use of animal data for DMAV 

cancer risk assessment due to the observed metabolic differences between rats and 
humans. The Panel agreed with the Agency’s conclusion that DMAV-induced bladder 

cancer in rats, at high dose, is mediated by a cytotoxic mode of action, and that this MOA 

should be considered relevant to humans. However, the Panel concluded there are not 

sufficient data to support a reactive oxygenated species-mediated mode of direct genetic 

action for DMAV. The Panel supported the nonlinear approach for low dose 

extrapolation of DMAV and the use of uncertainty factors to account for interspecies 

differences and human variability for sensitive human populations, and concluded that 

presently there is no arsenic-specific information that can inform the choice of specific 

values. This means that, at least for now, such choices must be based on more general 

considerations, including EPA’s science policy judgment of the degree of precaution that 

it deems appropriate. 

EPA concluded that the mechanisms by which inorganic arsenic induces bladder 

cancer in humans are not yet known, but they are likely to be mediated by multiple 

modes of action. The Agency used a linear default approach for low dose extrapolation 

because it lacked a full understanding of the iAs modes of carcinogenic action. The 

Panel agreed that available human and animal data do not fully describe the shape of the 

iAs carcinogenic dose-response curve at low doses. Given the considerable uncertainties 

regarding low dose extrapolation, the Panel supported the use of a linear cancer risk 

model for iAs as recommended by the National Research Council in its 2001 report. The 

Panel also supported the use of the epidemiologic data on the Taiwanese population for 

estimating human cancer risk for iAs especially to identify the potential range of 

responses of human populations. However, the Panel recognized limitations to these 

data, and that there is some evidence on iAs from animal toxicology, pharmacokinetics, 

and pharmacodynamics research, that suggests other than a linear bladder cancer doseresponse. The Panel urged the Agency to consider other epidemiologic studies from the 

U.S. and other countries, utilizing a uniform set of evaluative criteria. The Panel also 

recommended sensitivity analyses be conducted to account for human variability in 

drinking water consumption rates, dietary intake of iAs from food, and certain other 

assumptions currently used in EPA’s assessment. The Panel made several suggestions 

for improvements in the currently applied risk model’s programming and documentation 

conventions. 

Finally, the Panel believes there is a critical need for a continued research effort to 

strengthen EPA’s cancer risk assessment for DMAV and iAs. The scientific bases for the 

Panel’s conclusions and research recommendations are detailed throughout this report. 

We look forward to receiving your response to this review and we appreciate the 

2
opportunity to provide EPA with advice on this important subject and stand ready to 

assist the Agency in any future efforts in updating the assessment. 

Sincerely, 

/Signed/ /Signed/ 

Dr. M. Granger Morgan, Chair Dr. Genevieve Matanoski, Chair 

EPA Science Advisory Board EPA Science Advisory Board 

 Arsenic Review Panel 

3
NOTICE 

This report has been written as part of the activities of the EPA Science Advisory Board, a public 

advisory committee providing extramural scientific information and advice to the Administrator 

and other officials of the Environmental Protection Agency. The Board is structured to provide 

balanced, expert assessment of scientific matters related to problems facing the Agency. This 

report has not been reviewed for approval by the Agency and, hence, the contents of this report 

do not necessarily represent the views and policies of the Environmental Protection Agency, nor 

of other agencies in the Executive Branch of the Federal government, nor does mention of trade 

names or commercial products constitute a recommendation for use. Reports of the EPA 

Science Advisory Board are posted on the EPA Web site at: http://www.epa.gov/sab. 
U.S. Environmental Protection Agency 

Science Advisory Board 

Arsenic Review Panel 

CHAIR 

Dr. Genevieve Matanoski, Professor, Department of Epidemiology, Johns Hopkins University, 

Baltimore, MD 

MEMBERS 

Dr. H. Vasken Aposhian, Professor, Department of Molecular and Cell Biology, The University 

of Arizona, Tucson, AZ 

Dr. Aaron Barchowsky, Associate Professor, Department of Environmental and Occupational 

Health, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 

Dr. David Brusick, Retired, Convance Labs, Vienna, VA 

Dr. Kenneth P. Cantor, Senior Investigator, Occupational and Environmental Epidemiology 

Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, 

MD 

Dr. John (Jack) Colford, Associate Professor, Division of Public Health, Biology & 

Epidemiology, School of Public Health, University of California, Berkeley, CA 

Dr. Yvonne P. Dragan, Director of the Division of Systems Toxicology (DST) and Chief of the 

Center for Hepatotoxicology, National Center for Toxicological Research (NCTR), Food and 

Drug Administration's (FDA), Jefferson, AR 

Dr. Sidney Green, Associate Professor, Department of Pharmacology, College of Medicine, 

Howard University, Washington, DC 

Dr. Sioban Harlow, Professor, Department of Epidemiology, School of Public Health, 

University of Michigan, Ann Arbor, MI 

Dr. Steven Heeringa, Research Scientist and Director, Statistical Design Group, Institute for 

Social Research (ISR), University of Michigan, Ann Arbor, MI 

Dr. Claudia Maria Hopenhayn, Associate Professor, Department of Epidemiology, 

Markey Cancer Control Program, College of Public Health, University of Kentucky, Lexington, 

KY 

Dr. James E. Klaunig, Professor and Director, Department of Pharmacology and Toxicology, 

School of Medicine, Indiana University, Indianapolis, IN 

ii 
Dr. X. Chris Le, Professor, Department of Public Health Sciences, Department of Chemistry & 

Department of Laboratory Medicine & Pathology, University of Alberta, Edmonton, Alberta, 

Canada 

Dr. Michele Medinsky, Toxicology Consultant, Toxcon, Durham, NC 

Dr. Kenneth Portier, Program Director, Department of Statistics and Evaluation, American 

Cancer Society, Atlanta, GA 

Dr. Barry Rosen, Professor and Chairman, Department of Biochemistry and Molecular Biology, 

School of Medicine, Wayne State University, Detroit, MI 

Dr. Toby Rossman, Professor, Environmental Medicine, School of Medicine, New York 

University, Tuxedo, NY 

Dr. Miroslav Styblo, Research Associate Professor, Department of Nutrition and the Center for 

Environmental Medicine, Asthma, and Lung Biology, University of North Carolina, Chapel Hill, 

NC 

Dr. Justin Teeguarden, Senior Scientist, Pacific Northwest National Laboratory, Richland, WA 

Dr. Michael Waalkes, Chief, Inorganic Carcinogenesis Section, Laboratory of Comparative 

Carcinogenesis, National Cancer Institute, National Institute of Environmental Health Science, 

Research Triangle Park, NC 

Dr. Janice Yager, Research Program Manager, Environment Department, Electric Power 

Research Institute, Palo Alto, CA 

SCIENCE ADVISORY BOARD STAFF 

Mr. Thomas Miller, Designated Federal Officer, EPA Science Advisory Board Staff Office 

iii 
U.S. Environmental Protection Agency 

Science Advisory Board 

CHAIR 

Dr. M. Granger Morgan, Professor and Head, Department of Engineering and Public Policy, 

Carnegie Mellon University, Pittsburgh, PA 

SAB MEMBERS 

Dr. Gregory Biddinger, Environmental Programs Coordinator, ExxonMobil Biomedical 

Sciences, Inc, Houston, TX 

Dr. James Bus, Director of External Technology, Toxicology and Environmental Research and 

Consulting, The Dow Chemical Company, Midland, MI 

Dr. Deborah Cory-Slechta, Director, Environmental and Occupational Health Sciences 

Institute, Robert Wood Johnson Medical School, University of Medicine and Dentistry of New 

Jersey and Rutgers State University, Piscataway, NJ 

Dr. Maureen L. Cropper, Professor, Department of Economics, University of Maryland, 

College Park, MD 

Dr. Virginia Dale, Corporate Fellow, Environmental Sciences Division, Oak Ridge National 

Laboratory, Oak Ridge, TN 

Dr. Kenneth Dickson, Professor, Institute of Applied Sciences, University of North Texas, 

Denton, TX 

Dr. Baruch Fischhoff, Howard Heinz University Professor, Department of Social and Decision 

Sciences, Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, 

PA 

Dr. James Galloway, Professor of Environmental Sciences, Environmental Sciences 

Department, University of Virginia, Charlottesville, VA 

Dr. Lawrence Goulder, Shuzo Nishihara Professor of Environmental and Resource Economics, 

Department of Economics, Stanford University, Stanford, CA 

Dr. James K. Hammitt, Harvard Center for Risk Analysis, Harvard University, Boston, MA 

Dr. Rogene Henderson, Scientist Emeritus, Lovelace Respiratory Research Institute, 

Albuquerque, NM 

Dr. James H. Johnson, Dean, College of Engineering, Architecture & Computer Sciences, 

Howard University, Washington, DC 

iv 
Dr. Agnes Kane, Dept. of Pathology and Laboratory Medicine, Brown University, Providence, 

RI. 

Dr. Meryl Karol, Associate Dean for Academic Affairs, Graduate School of Public Health, 

University of Pittsburgh, Pittsburgh, PA 

Dr. Catherine Kling, Professor, Department of Economics, Iowa State University, Ames, IA 

Dr. George Lambert, Associate Professor and Director, Center for Child and Reproductive 

Environmental Health & Pediatric Clinical Research Center, Department of Pediatrics, UMDNJRobert Wood Johnson Medical School/University of Medicine and Dentistry of New Jersey, 

New Brunswick, NJ 

Dr. Jill Lipoti, Director, Division of Environmental Safety and Health, New Jersey Department 

of Environmental Protection, Trenton, NJ 

Dr. Genevieve Matanoski, Professor, Department of Epidemiology, Johns Hopkins University, 

Baltimore, MD 

Dr. Michael McFarland, Associate Professor, Department of Civil and Environmental 

Engineering, Utah State University, Logan, UT 

Dr. Judith Meyer, Institute of Ecology, University of Georgia, Athens, GA. 

Dr. Jana Milford, Associate Professor, Department of Mechanical Engineering, University of 

Colorado, Boulder, CO 

Dr. Rebecca Parkin, Professor and Associate Dean, Environmental and Occupational Health, 

School of Public Health and Health Services, The George Washington University, Washington, 

DC 

Mr. David Rejeski, Foresight and Governance Project Director, Woodrow Wilson International 

Center for Scholars, Washington, DC 

Dr. Stephen Roberts, Department of Physiological Sciences, University of Florida, Gainesville, 

FL. 

Dr. Joan B. Rose, Professor and Homer Nowlin Chair for Water Research, Department of 

Fisheries and Wildlife, Michigan State University, E. Lansing, MI 

Dr. Jerald Schnoor, Department of Civil and Environmental Engineering, University of Iowa, 

Iowa City, IA. 

Dr. Kathleen Segerson, Professor, Department of Economics, University of Connecticut, Storrs, 

CT 

v 
Dr. Kristin Shrader-Frechette, O'Neil Professor of Philosophy- Concurrent Professor of 

Biological Sciences-and Director of the Center for Environmental Justice and Children's Health, 

Department of Biological Sciences and Philosophy Department, University of Notre Dame, 

Notre Dame, IN 

Dr. Philip Singer, Department of Environmental Sciences and Engineering, University of North 

Carolina, Chapel Hill, NC. 

Dr. Robert Stavins, Albert Pratt Professor of Business and Government, Environment and 

Natural Resources Program, John F. Kennedy School of Government, Harvard University, 

Cambridge, MA 

Dr. Deborah Swackhamer, Professor, Division of Environmental Health Sciences, School of 

Public Health, University of Minnesota, Minneapolis, MN 

Dr. Thomas L. Theis, Professor and Director, Institute for Environmental Science and Policy, 

University of Illinois at Chicago, Chicago, IL 

Dr. Valerie Thomas, Anderson Interface Associate Professor of Natural Systems, School of 

Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 

Dr. Barton H. (Buzz) Thompson, Jr., Robert E. Paradise Professor of Natural Resources Law, 

Stanford Law School, and Director, Woods Institute for the Environment , Stanford University, 

Stanford, CA 

Dr. Robert Twiss, Professor, University of California-Berkeley, Ross, CA 

Dr. Terry F. Young, Consultant, Environmental Defense, Oakland, CA 

Dr. Lauren Zeise, Chief, Reproductive and Cancer Hazard Assessment Section, California 

Environmental Protection Agency, Oakland, CA 

vi 
TABLE OF CONTENTS 

1. EXECUTIVE SUMMARY ....................................................................................................... 1 

2. INTRODUCTION ................................................................................................................... 12

2.1 Process for Developing this Report and Structure of the Report........................................ 12 

2.2 Background......................................................................................................................... 13

3. RESPONSE TO THE CHARGE.............................................................................................. 17 

3.1 Overview............................................................................................................................. 17 

3.2 Metabolism and Toxic Responses of Arsenic Species ....................................................... 17 

3.2.1 Metabolism and pharmacokinetics .............................................................................. 17 

3.2.2 Response to mixtures of metabolites ........................................................................... 20 

3.3 Modes of Carcinogenic Action for DMAV and Inorganic Arsenic..................................... 22 

3.3.1. Mode of Action of DMAV .......................................................................................... 22 

3.3.2 Human relevance of animal DMAV MOA................................................................... 26 

3.3.3 Modes of carcinogenic action from exposures to Inorganic Arsenic .......................... 27 

3.4 Selection of Data for Dose-Response Assessment ............................................................. 34 

3.4.1 Use of animal data for DMAV ..................................................................................... 34 

3.4.2. Use of human epidemiological data from direct inorganic arsenic exposure ............. 36 

3.5 Approaches to Low-Dose Extrapolation for Inorganic Arsenic and DMAV ...................... 40 

/ 3.5.1 Mode of carcinogenic action understanding for DMAV III........................................... 40 

3.5.2 Implementation of the recommendations of the NRC ................................................. 43 

3.5.3 EPA Model Re-Implementation .................................................................................. 45 

3.5.4 Available literature describing drinking water consumption rates ............................. 49 

3.5.5 Selection of an estimate of dietary intake of arsenic from food ................................. 51 

REFERENCES ........................................................................................................................... R-1 

APPENDIX A Charge to the EPA Science Advisory Board..................................................... A-1 

APPENDIX B Assignments to Charge-Specific Groups........................................................... B-1 

APPENDIX C Abbreviations .................................................................................................... C-1 

vii 
1. EXECUTIVE SUMMARY 

New information has been developed on the metabolism, pharmacokinetics (PK) 

and mode of carcinogenic action of arsenic and its methylated species and new 

epidemiology studies have been conducted on inorganic arsenic since the publication of 

reviews by the National Research Council (NRC, 1999, 2001). EPA considered this new 

science in the development of the Office of Pesticide Programs’ (OPP) Draft Science 

Issue Paper: Mode of Action for Cacodylic Acid (Dimethylarsinic Acid) and 

Recommendations for Dose Response Extrapolation (USEPA OPP, 2005) and the Office 

of Water’s (OW) Draft Toxicologic Review of Inorganic Arsenic (USEPA OW, 2005). 

EPA’s Office of Research and Development (ORD) further captured key scientific issues 

to be considered in its Issue Paper Cancer Risk Assessment for Organic Arsenical 

Herbicides: Comments on Mode of Action, Human Relevance and Implications for 

Quantitative Dose-Response Assessment (Appendix E of USEPA OPP, 2005, USEPA 

ORD, 2005). The Science Advisory Board (SAB) was asked to review these documents 

and offer advice on the metabolism, mode of action, dose-response, and approaches to 

low-dose extrapolation of cancer risk for Dimethylarsinic Acid (DMAV) and inorganic 

arsenic (iAs). The full charge to the SAB is in Appendix A to this document. 

In response to the Agency’s request, the SAB convened an expert Panel to 

provide advice to the Agency on these scientific issues. In responding to the EPA 

Charge, the Panel reviewed the EPA assessments mentioned above, and considered 

comments and information that members of the interested public provided during each of 

the Panel’s advisory meetings (during 2005 and 2006), and additional studies that are 

identified in the reference section of this report. The Panel considered expanding the 

Charge to include other health endpoints associated with arsenic and arsenic containing 

compounds. However, the Panel decided not to expand its activities beyond the EPA 

Charge that largely focused on bladder cancer and to some degree on lung cancer doseresponse issues. It is important to recognize that the Panel did not conduct its own 

arsenic risk assessment. To do so would have required an updated literature search and 

exploration and resolution of many issues that are discussed throughout this report. The 

Panel leaves the larger activity of completing a full risk assessment of all relevant health 

endpoints associated with arsenic, and arsenic containing compounds, to the Agency 

itself when it conducts its final arsenic assessments. 

The Panel was organized into small groups of three to seven members to evaluate 

and respond to each specific charge question (see Appendix B to this report for a list of 

those members assigned to each charge question). The Panel’s response to each question 

reflects consensus, though not necessarily unanimous agreement, among Panel Members 

that addressed each specific charge question. In addition, all Panel Members had the 

opportunity to participate in meeting discussions of each charge question and each was 

able to provide written comments on all questions during report drafting. Many Members 
participated in this way and each response reflects adjustments that were considered to be 

appropriate by the specific charge group that led the Panel’s efforts for each question. In 

that manner, this advisory report provides the Panel’s judgments on each specific issue. 

This advice is intended to assist the Agency’s continued efforts to complete its 

assessments on various arsenicals. There are many specific conclusions and 

recommendations on specific issues associated with each charge question, as well as 

recommendations for sensitivity analyses and additional research to answer many of the 

remaining questions on arsenic risk. The Panel’s advice on each charge question is 

discussed in the remainder of this Executive Summary and discussed in detail in Section 

3 of this report. 

1.1 Metabolism and Toxic Responses of Arsenic Species 

Charge Question A1 

EPA concluded that available in vivo and in vitro metabolism and pharmacokinetic studies in humans and laboratory animals suggest that the efficiency of 

methylation reactions and cellular uptake varies with the arsenic compound administered 

exogenously. Most studies suggest a predominantly one-way process in mammals and 

that after DMAV exposure, significant amounts of iAsIII, iAsV, methylarsonous acid 

(MMAIII), or methylarsinic acid (MMAV) are not expected at target tissues. EPA asked 

the SAB to comment on how best to consider the PK processes in cancer risk assessment 

based on data derived from direct dimethylarsinic acid (DMAV) exposure versus direct 

inorganic arsenic (iAs) exposure. 

Summary Response 

The Panel agreed that: 

i) Metabolism of iAs appears to be a one-way process in which iAs is 

converted to monomethylarsenic (MMA), dimethylarsenic (DMA), and in 

some species to trimethylarsenic (TMA) metabolites with arsenic in +3 or 

+5 oxidation states. Thus, significant amounts of MMA or iAs are not 

expected to be found in tissues or urine of rats or humans as a result of 

exposure to DMAV, although iAs may be present in human tissues or urine 

from other sources. 

ii) In contrast, exposure to iAs may result in production, tissue retention, and 

urinary excretion of a variety of tri- and pentavalent iAs and methylated 

arsenic species. 

iii) The uptake and reduction of DMAV to dimethylarsinous acid (DMAIII) are 

apparently critical steps in activation of DMAV – though it is not clear if, 

where and to what extent these processes occur in humans exposed to 

DMAV. 

iv) The capacity to reduce DMAV to DMAIII seems to exist in human tissues 

and the conversion of even a small amount of exogenous DMAV to 

DMAIII is of toxicological concern. 

2
v) Given the differences in the metabolic pattern for iAs and DMAV, the 

Panel believes data derived from DMAV exposure, not from iAs exposure, 

is better suited for cancer risk assessment of DMAV. 

vi) Significant uncertainties are associated with this approach. The 

toxicologic data on DMAV are mainly from rat studies, and considering 

several key differences between rats and humans in the metabolism of 

arsenic, these uncertainties should be considered in the assessment of 

DMAV cancer risk. Additional uncertainties include methylation and 

demethylation of arsenic compounds in humans by intestinal bacteria, coexposures to other environmental contaminants, deficiencies in nutrients, 

and malnutrition. 

vii) The physiologically based pharmacokinetic (PBPK) model under 

development by EPA may be a useful approach but it is not yet 

sufficiently robust to conduct interspecies extrapolations. 

viii) EPA should continue developing the arsenic PBPK model and conducting 

research to obtain kinetic constants needed to describe rates of uptake, 

efflux, metabolism, and elimination of DMAV in rats and humans. 

ix) There is a need to validate such models for predicting tissue 

concentrations of active species regardless of the source of arsenic 

exposure. 

Charge Question A2 

EPA concluded that direct exposure to iAsIII or iAsV is expected to result in a 

more complex mixture of toxic metabolites than with DMAV exposure given that 

mixtures of metabolites vary based on which chemical is administered exogenously. 

EPA expects a less complex mixture of metabolites following DMAV exposure than 

following iAs exposure. EPA further expects that the tumorigenic profiles vary with the 

arsenical compound administered. For its DMAV assessment, EPA asked the SAB to 

comment on the use of data derived from rodent exposures to organic arsenicals versus 

data derived from direct human exposure to iAs. 

Summary Response 

The Panel agreed that: 

i) Neither rodent laboratory data on organic arsenicals nor data from studies 

of human exposure to inorganic arsenic provide an optimal basis for the 

assessment of DMAV exposure in humans because of differences between 

the metabolic profiles for inorganic arsenic and DMA and because of 

interspecies differences in their metabolism. Despite these uncertainties, 

for now, the data from rodent exposures to DMAV appear to be the most 

reasonable approach for the DMAV assessment, though this approach has 

a significant degree of uncertainty (see charge question A1). 

ii) The metabolism of iAs yields a wide spectrum of metabolites which are 

apparently not produced during the metabolism of DMAV. 

3
iii) Production of iAs and MMA metabolites may be associated with specific 

toxic or cancer endpoints that are absent in DMAV exposure to rats or 

humans. 

iv) All published data on toxicological responses to DMAV are from studies 

in rodents, mainly rats; no human data are available. As noted in the 

response to A1 above, these differences raise concerns for risk 

assessments based on these data. 

1.2. Modes of Carcinogenic Action for DMAV and Inorganic Arsenic 

Charge question B1 

EPA’s approach to cancer risk assessment incorporates two key science policy 

assumptions when there are inadequate human data and it needs to rely on laboratory 

animal data: (a) animal tumor data are predictive of human cancer and (b) effects found 

at high experimental doses in animals predict human risk at lower exposure levels. 

Understanding a mode of action (MOA) for a chemical can help to inform the agency 

about these assumptions and the most appropriate approach to follow in low dose 

extrapolation. EPA asked the SAB to comment on the scientific soundness of the 

postulated MOA for DMAV-induced bladder carcinogenesis in the rat. 

Summary Response 

The Panel concluded that: 

i) There are adequate data to support an MOA for bladder carcinogenesis 

induced by high doses of DMAV in the rat and that MOA involves 

cytotoxicity to the bladder epithelium and increased, sustained 

regenerative proliferation as key events. 

ii) The rat metabolizes a significant fraction of exogenous DMAV to 

trimethylarsine oxide (TMAVO) and possibly trimethylarsine (TMAIII) and 

that these compounds cannot be excluded as additional mediators of the 

necrotic cytotoxicity in the bladder of exposed rats. 

iii) There are not sufficient data to invoke reactive oxygen species (ROS)-

induced DNA damage as a key event in the carcinogenic process 

associated with exposures to DMAV and DMAIII. 

iv) The Panel’s postulated MOA for DMAV is: 

a) Reductive metabolism of DMAV to DMAIII, 

b) High concentrations of DMAIII (and possibly DMAV) in urine cause 

urothelial cytotoxicity, and 

c) Continuous exposure and persistent stress-associated regenerative cell 

proliferation leads to genomic instability, acquisition of genetic 

alterations, clonal expansion of altered cells and eventually tumors. 

v) The Panel suggested several high priority research needs for this issue. 

4
Charge question B2 

EPA concluded that their postulated MOA for DMAV induced bladder 

carcinogenesis in the rat would be relevant to humans as there are little or no data to 

suggest that key precursor events and ultimately tumor formation would not occur in 

exposed humans if sufficient DMAIII were present. EPA asked the SAB to comment on 

the relevance of the postulated key events to tumors in humans and how differences in 

humans and experimental animals should be accounted for in DMAV risk assessments. 

Summary Response 

The Panel concluded that: 

i) If high enough concentrations of DMAV or DMAIII were present in human 

urine or the bladder after exposure to DMAV it is plausible that a similar 

response would take place; however, no data are available to support or 

reject this assumption. 

ii) The suggested greater conversion of DMAV to TMAVO or possibly TMAIII 

in rats vs. in humans, may contribute to induction of bladder cancer in rats, 

however, the extent of the contribution is unknown. 

iii) No studies have been conducted to determine whether the DMAV 

carcinogenic risk differs by life stage, e.g., among the young, or elderly. 

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. 

Summary Response 

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, 

iASIII and 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. 

5
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. 

1.3. Selection of Data for Dose-Response Assessment 

Charge Question C1 

In the absence of human data, EPA proposed to use the bladder tumor data from 

the DMAV rat bioassay for quantifying potential human cancer risk to DMAV. EPA 

asked the SAB to comment on the appropriateness of this approach. The SAB was also 

asked to comment on whether the iAs epidemiology data can be used to inform the 

DMAV dose-response assessment which is now based on data derived from studies in rats 

dosed with DMAV. 

Summary Response 

The Panel agreed that: 

i) Given the lack of human data, the bladder tumor data from DMAV rat 

bioassays, are the most suitable data set for quantifying potential human 

cancer risk from DMAV. The Panel stated that the available data suggest 

that the uncertainty associated with extrapolation across forms of arsenic 

in the DMAV risk assessment would be greater than interspecies 

extrapolation. 

ii) The Panel strongly suggested that EPA’s DMAV assessment discuss the 

key uncertainties in using data from studies in rats to conduct human 

health risk assessments. Panel responses to charge questions A1 and C1 

discuss issues that members considered important to discuss in EPA’s 

Science Issue Paper. These issues relate to the pharmacokinetic and 

pharmacodynamic similarities and differences between rats and humans in 

response to arsenic exposure, the use of rodent bladder tumor models in 

general, and issues in the use of rodent data for human risk assessment. 

iii) The Panel considers research on these issues to be a high priority. 

iv) The Panel concluded that without more detailed information on target 

tissue dosimetry for arsenic species, the iAs epidemiology data would be 

of limited use to inform the DMAV dose-response assessment derived 

6
from rat data with DMAV. Additional details are contained in the Panel’s 

response to charge question C1. 

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. 

Summary Response 

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 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. 

7
1.4 Approaches to Low-Dose Extrapolation for iAs and DMAV 

Charge Question D1 

EPA’s Guidelines for Carcinogen Risk Assessment underscore the importance of 

understanding the MOA as the basis for making judgments on how to best extrapolate 

cancer risk at lower exposures. EPA concluded that available data on DMAV are not 

sufficient to support development of biologically-based models and therefore opted to use 

a default nonlinear low-dose extrapolation method. The SAB was asked to comment on 

the Agency’s scientific rationale in support of this approach and how uncertainty should 

be incorporated into low-dose extrapolation. 

Summary Response 

The Panel concluded that: 

i) Though there are adequate data to support the proposed EPA MOA, 

neither the MOA postulated by the Panel, nor those postulated by EPA’s 

ORD or OPP contain key events expected to be a linear function of dose 

of DMAV. 

ii) Several processes important to some postulated key events would have 

non-linear components or are non-linear (e.g., saturable metabolic 

processes, cytotoxicity, formation of heritable alterations in DNA by ROS, 

cell proliferation, repair of ROS-induced DNA damage). 

iii) The linear approach would be consistent with evidence for direct 

genotoxicity of DMAIII/V; however, it is generally accepted that DMAV is 

not directly genotoxic and neither DMAIII nor DMAV react directly with 

DNA. 

DMA

iv) There are insufficient data to invoke ROS-induced DNA damage as a key 

event in the carcinogenic process associated with exposures to DMAV or 

III . 

v) The nonlinear approach is more consistent with available DMAV data and 

current concepts of chemical carcinogenesis. 

vi) Uncertainty is best incorporated through the use of uncertainty factors that 

capture pharmacokinetic and pharmacodynamic differences across species 

and differences associated with sensitive populations. 

vii) There are not sufficient data on comparative dosimetry in rats and humans 

to make any conclusive statements about species differences in 

pharmacokinetics, though available data on uroepithelial cell cytotoxicity 

might allow EPA to assemble a case for pharmacodynamic equivalency. 

There is presently no arsenic-specific information that can inform the 

choice of uncertainty factors for sensitive human populations. Thus, at 

least for now, such choices must be based on more general considerations 

including EPA’s science policy judgment of the degree of precaution that 

it deems appropriate. 

8
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. 

Summary Response 

The Panel concluded that: 

i) Inorganic arsenic has the potential for a highly complex mode of action. 

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. 

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. 

Summary Response: 

The Panel concluded: 

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 

9
model to alternative formulations of the hazard function and aggregate 

population data inputs. 

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. 

Summary Response 

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-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 genderspecific 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). 

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 dietary intake of iAs for both the control population and study 

population of Southwestern Taiwan. 

10
Summary Response 

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 per day to perhaps as high as 200 μg per 

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. 

11
2. INTRODUCTION 

2.1. Process for Developing this Report and Structure of the Report 

In response to the Agency’s request (USEPA, 2005a), the SAB convened an 

expert Panel to review the Agency’s hazard and dose-response assessments for 

dimethylarsinic acid (DMAV) and inorganic arsenic (iAs). The full EPA charge to the 

SAB is in Appendix A to this advisory report. The Panel was established in accordance 

with the SAB Panel Formation Process: Immediate Steps to Improve Policies and 

Procedures (EPA-SAB-EC-COM-02-003). The Panel held public telephone conference 

meetings and a face-to-face meeting to plan for and conduct its advisory activities. The 

Panel met on September 12-13, 2005 to discuss the issues and deliberate on its response 

to the charge questions. The Panel held three subsequent public telephone conference 

meetings on January 24, 2006, February 23, 2006 and February 28, 2006 (see GPO, 

2005a; 2005b; 2005c; 2005d; 2005e; and 2005f). The Panel considered written comments 

and oral statements from the public during each of these advisory meetings. This was 

also the case for the chartered SAB’s public telephone conference meeting held on 

November 27, 2006 to conduct a review of the draft Panel report (see GPO 2006). 

Written public comments submitted for consideration at these meetings are available on 

the SAB web page. 

Several individuals from the public requested that the Panel consider broadening 

its charge to include other human health endpoints associated with exposure to arsenic 

and to undertake a quantitative dose-response assessment for arsenic induced bladder 

cancer. While the Panel recognized that there is a need for the Agency to conduct a 

complete and thorough review of all health effects endpoints associated with arsenic 

exposure, the Panel limited its advisory to issues relevant to carcinogenicity of various 

arsenicals as requested by EPA. The Panel did not conduct a full risk assessment of the 

arsenicals of interest itself, because this was beyond the scope of the project and the 

resources available to the SAB to conduct such an analysis. 

Throughout the Panel’s report writing and editing process, and during the 

Chartered SAB’s quality review, some Panel Members, and some of the interested public, 

suggested that additions to literature subsequent to the Panel’s deliberations be evaluated 

and referenced in the panel’s report. The Panel did not add such studies to its discussions 

because its active deliberations were complete. The Panel’s advice to EPA considers the 

review of other relevant studies to be within its suggestion to EPA to evaluate other 

endpoints, and other studies, as the Agency completes its arsenic assessments. 

This advisory report is structured according to the charge questions submitted by 

EPA. Subgroups of Panel members were assigned to focus on specific charge questions 

(see Appendix B), and each such group was responsible for leading the discussions for 

specific charge questions during the public meetings and for drafting the written 

responses to the charge questions based upon the Panel’s discussions and deliberations at 

the meetings. All Panel members were encouraged to participate in all discussions as 

well as to provide comments on the draft responses for each question during the entire 

12
advisory process. The Panel’s draft report (dated September 15, 2006) was reviewed by 

the chartered SAB and approved conditional to the Panel Chair making the series of 

clarifying editorial revisions; that are now reflected in this final report which has been 

approved by the Panel Chair and the SAB Chair. 

2.2 Background 

EPA’s Office of Research and Development (ORD), the Office of Water (OW) 

and the EPA Office of Pesticide Programs (OPP), requested that the EPA SAB evaluate 

certain components of the EPA draft assessment of potential human carcinogenicity 

associated with arsenic, and arsenic containing compounds. Information from the EPA 

request is summarized in the remainder of this section of the Panel’s report. 

Inorganic arsenic (iAs) is found naturally in the environment and it is typically 

present in soil and water at some determinate level. Human exposure to inorganic arsenic 

can come from drinking water, food, air and anthropogenic sources such as wood 

preservatives, industrial wastes, and certain pesticides containing organic arsenic. 

Specific statutory mandates require that EPA consider human health risks 

associated with arsenic and arsenic containing compounds. The Safe Drinking Water Act 

(SDWA) directs EPA to establish national standards for arsenic containing compounds, 

among other contaminants, in public drinking water supplies. EPA’s Superfund and 

Resource Conservation and Recovery Act (RCRA) programs require the evaluation of 

exposure to arsenic containing compounds at locations undergoing clean up or 

remediation, and the Clean Air Act, requires EPA to set air emissions standards for 

certain sources of arsenic. EPA’s OPP evaluates the exposure and health risks associated 

with arsenicals used as pesticides in the U.S. and under the mandate of the Food Quality 

Protection Agency (FQPA) is reevaluating tolerances for arsenicals, and other pesticides. 

Tolerances are legal limits of pesticides on or in food or animal feed. Several organic 

arsenic containing herbicides are undergoing reregistration and/or tolerance reassessment 

(e.g., cacodylic acid which is often referred to as dimethylarsinic acid or DMAV, and the 

monosodium, disodium, and calcium salts of methanearsonate acid --MSMA, DSMA, 

and CAMA, collectively as referred as MMAV). 

Arsenic, and arsenic containing compounds, have been the focus of many EPA 

assessments as the above statutory authorities suggest. In addition, the National Research 

Council (NRC) of the National Academy of Sciences (NAS) has conducted 

comprehensive health sciences reviews of arsenic on at least two occasions (NRC, 1999; 

NRC, 2001). EPA SAB Panels have also considered inorganic arsenic issues (US EPA 

SAB, 2000; USEPA SAB, 2001). 

Since the 2001 NAS review, new information has been developed on the mode of 

carcinogenic action, metabolism and pharmacokinetics (PK) of arsenic and its methylated 

species, and new epidemiology studies have been conducted on inorganic arsenic. EPA 

considered this new information in its hazard characterization for tolerance assessment of 

dimethylarsinic acid (DMAV) and methylarsonic acid (MMAV)(USEPA OPP, 2005 and 

13
USEPA ORD, 2005). EPA also developed a revised hazard and dose response 

assessment for inorganic Arsenic (USEPA OW, 2005) which relies on the two NRC 

reviews and provides an updated human health effects and dose-response assessment for 

inorganic arsenic. In its charge to the SAB, EPA asked for advice on the soundness of 

the major science conclusions in these two documents. These documents focus on the 

assessment of DMAV and inorganic arsenic carcinogenicity (more specifically, 

metabolism, mode of action, dose-response, and approaches to low-dose extrapolation of 

cancer risk (see the specific Charge questions in subsections 2.2.1 through 2.2.4 and in 

Appendix A to the report). 

2.2.1 Metabolism and Toxic Responses of Arsenic Species 

Charge Question A1. Metabolism and pharmacokinetics: Please comment on 

how pharmacokinetic processes are best considered regarding the use of data derived 

from direct DMAV exposure versus direct iAs exposure for cancer risk assessment. 

Charge Question A2. Response to mixtures of metabolites: Given the 

toxicological response profiles observed following direct exposures to iAs versus MMAV 

and DMAV, and the differences in human and rodent toxicologic responses to arsenicals, 

please comment on the use of data derived from rodent exposures to the organic 

arsenicals versus use of data derived from direct iAs human exposure, in the DMAV 

assessment. 

2.2.2 Modes of Carcinogenic Action for DMAV and Inorganic Arsenic 

Charge Question B1. Mode of action of DMAV: Please comment on the 

sufficiency of evidence to establish the animal mode of carcinogenic action for DMAV. 

Are the scientific conclusions sound and consistent with the available evidence on DMAV 

and the current state of knowledge for chemical carcinogenesis. Please comment on 

whether the key events in DMA’s mode of action are supported by the available data. 

Specifically comment on the role of: a) reactive oxygen species in producing 

chromosomal damage and the strength of the evidence supporting oxidative damage as a 

causal key event in DMAV/DMAIII‘s mode of carcinogenic action versus an associative 

event or a secondary consequence of cytotoxicity; b) cell proliferation and cytotoxicity 

and the strength of the evidence as causal key events in DMAV/DMAIII‘s mode of 

carcinogenic action versus associative or secondary events, and c) other potential modes 

of action that have substantial scientific support that may be contributing to the 

carcinogenicity of DMA. 

Charge Question B2. Human relevance of animal DMAV MOA: Please 

comment on the relevance of the postulated key events (see B1) to tumors in humans. 

Please comment on how, if at all, differences in the human population vs. experimental 

animals should be accounted for in the risk assessment for DMAV. Please comment on 

the Agency’s conclusion that the young are likely to respond like the adult to the 

formation of bladder tumors following exposure to DMA. 

14
Charge Question B3. Modes of carcinogenic action from exposure to inorganic 

arsenic: Please comment on the conclusion that the available data support the hypothesis 

that multiple modes of action may be operational following exposure to inorganic 

arsenic. 

2.2.3 Selection of Data for Dose-Response Assessment

Charge Question C1. Use of animal data for DMAV: Please comment on the use 

of the bladder tumor data from the DMAV rat bioassay as the most suitable dataset for 

quantifying potential human cancer risk to DMAV, including the weight of evidence to 

support this conclusion. Please comment on whether the iAs epidemiology data can be 

used to inform the DMAV dose-response assessment derived from rat data with DMAV. 

If so, please discuss how such information might be used. 

Charge Question C2. Use of human epidemiological data from direct iAs 

exposure: Does the SAB agree that the Taiwanese dataset remains the most appropriate 

choice for estimating cancer risk in humans? Please discuss the rationale for your 

response. Do these data provide adequate characterization of the impact of childhood 

exposure to iAs? Please discuss the rationale for your response. 

2.2.4 Approaches to Low-Dose Extrapolation for Inorganic Arsenic 

and DMAV 

Charge Question D1. Mode of carcinogenic action understanding for DMAV/III 

and implications for dose response extrapolation to estimate human cancer risk: Please 

comment on the scientific evidence and biological rationale in support of nonlinear 

versus linear low dose extrapolation approaches, which approach is more consistent with 

the available data on DMAV and current concepts of chemical carcinogenesis, and how 

scientific uncertainty should most appropriately be incorporated into low-dose 

extrapolation. 

Charge Question D2. Implementation of the recommendations of the NRC 

(2001): Does the panel concur with the selection of a linear model following the 

recommendations of the NRC (2001) to estimate cancer risk at this time? Please discuss 

your response in light of the highly complex mode of action for iAs with its metabolites. 

Charge Question D3. EPA re-implemented the model presented in the NRC 

(2001) in the language R as well as in an Excel spreadsheet format. In addition, 

extensive testing of the resulting code was conducted: Please comment upon precision 

and accuracy of the re-implementation of the model. 

Charge Question D4. Evaluation of Available literature describing drinking water 

consumption rates for the southwestern Taiwanese study population: What drinking water 

value does the panel recommend for use in deriving the cancer slope factor for inorganic 

arsenic? 

15
Charge Question D5. Selection of an estimate of dietary intake of arsenic from 

food: What background dietary intake (of arsenic) value does the panel recommend for 

both the control population and study population of Southwestern Taiwan used in 

deriving the cancer slope factor for inorganic arsenic? 

16
3. RESPONSE TO THE CHARGE 

3.1 Overview

The SAB Arsenic Review Panel was asked to comment on the i) toxicity/ 

metabolic profile/bioavailability for different arsenic species, ii) the Agency’s 

understanding of the mode of action of arsenic carcinogenesis and implications of that on 

dose response extrapolation for DMAV and inorganic arsenic, and iii) the implications of 

newer epidemiology studies as well as the 2001 National Research Council 

recommendations on modeling of the human cancer slope factor for inorganic arsenic. 

The SAB Panel’s advice is contained in sections 3.2 through 3.5 that follow. 

3.2. Metabolism and Toxic Responses of Arsenic Species 

3.2.1 Metabolism and pharmacokinetics (Charge Question A1) 

EPA’s charge states that, “Evidence from in vivo and in vitro metabolism and 

pharmacokinetic studies with humans and laboratory animals suggests that the efficiency 

of the methylation reaction(s) and cellular uptake varies based on which arsenical 

compound is administered exogenously. Most available studies suggest that the 

metabolic process in most mammals is primarily a one-way process and that following 

direct exposure to DMAV significant amounts of [arsenite] (iAs III), [arsenate] (iAsV), 

[methylarsonous acid] (MMAIII), or [methylarsonic acid] (MMAV) at the target tissue are 

not expected” (USEPA, 2005a). Charge Question A1 asks the SAB to “...comment on 

how pharmacokinetic processes are best considered regarding the use of data derived 

from direct DMAV

 exposure versus direct iAs exposure for cancer risk assessment.” 

Charge questions A1 and A2 address exposure to and the metabolic fate of DMAV 

associated organoarsenic-containing herbicides. DMAV from these herbicides can be 

degraded by microorganisms, both in the environment and in the intestinal tract, to yield 

a variety of methylated and inorganic arsenic species, which have specific metabolic fates 

and toxicities. The Panel’s responses to questions A1 and A2 do not take into 

consideration potential byproducts of the microbial degradation of DMAV in the 

environment. This is because EPA representatives stated during the September, 2005 

Arsenic Review Panel meeting that the environmental conversion of DMAV from 

organoarsenic pesticides, and the risk associated with exposures to these conversion 

products, will be addressed later by EPA in a separate document. 

The panel agrees with the Agency’s reasoning behind this question which is 

summarized at the beginning of this subsection (3.2.1). In mammalian tissues/cells 

(including human), the metabolism of inorganic arsenic (iAs) appears to be a one-way 

process in which iAs is converted to MMA, DMA and in some species to TMA 

metabolites containing arsenic in +3 or +5 oxidation states (Vahter, 1999; Thomas, et al., 

2001). There is no evidence for demethylation of methylated arsenic species in either 

animal or human tissues, though as noted in the preceding paragraph and in subparagraph 

17
“d” below microbial transformation is possible in the intestine. However, this issue 

needs further investigation. While the step-wise addition of methyl groups is likely a 

one-way process, a cycling between +3 and +5 arsenic species may occur at each of the 

methylation steps due to a spontaneous oxidation of +3 species (Gong, et al., 2001; 

Aposhian, et al., 2003) and non-enzymatic (Delnomdedieu, et al., 1994; Scott et al., 

1993) or enzymatic (Zakharayn and Aposhian, 1999; Radabaugh and Aposhian, 2000; 

Waters et al., 2004) reduction of +5 species. Given the likely one-way character of 

arsenic methylation, significant amounts of MMA or iAs are not anticipated as products 

of DMAV metabolism in either rat or human tissues or urine on the basis of available 

data. 

DMA

In contrast, exposure to iAs may result in the production, tissue retention, and 

urinary excretion of all the above iAs and methylated arsenic species. Based on data 

from rodent studies, both the uptake and reduction of DMAV to DMAIII are apparently 

critical steps in the activation of exogenous DMAV. It is not clear, where and to what 

extent (if at all) these processes occur in humans exposed to DMAV, although it appears 

that uptake may be rate limiting for further metabolism of DMAV. DMAIII is a urinary 

metabolite in individuals chronically exposed to iAs (Le et al., 2000; Aposhian, et al., 

2000; Mandal, Ogra and Suzuki, 2001; Del Razo et al., 2001; Valenzuela, et al., 2005), 

indicating that the capacity to reduce DMAV to DMAIII exists in human tissues. The 

Panel pointed out that even the conversion of a small amount/fraction of exogenous 

DMAV to DMAIII is of toxicological significance due to the significant toxicity of 

III. Thus, strictly from the point of view of the metabolic pattern, data derived from 

DMAV exposure (in the rat), not from iAs exposure in humans, is better suited for cancer 

risk assessment of DMAV. However, this approach is uncertain because of specific 

metabolic differences between rats and humans, and other factors, including: 

a) The uptake pathway or pathways for DMAV in humans is/are 

unidentified. The expression or properties of DMAV transporters may 

differ in rats and humans, leading to differences in uptake of DMAV in 

tissues and organs. 

b) Results of laboratory and epidemiological studies suggest that the 

pattern for DMAV metabolism in rats is different from that in humans 

(Figure 1). Rats metabolize DMAV to DMAIII, trimethylarsine oxide 

(TMAVO) (Yoshida et al., 1997; Yoshida et al., 1998; Cohen et al., 

2002), and possibly, trimethylarsine (TMAIII) (Waters et al., 2004). 

DMAV, DMAIII, and TMAVO are urinary metabolites of DMAV in the 

rat. In addition, TMAVO was also detected in urine of rats chronically 

exposed to iAs (Yoshida et al., 1998). In contrast, little or no TMAVO 

was found in human urine after a single dose of DMAV (Marafante et 

al, 1987; Buchet et al., 1981) or after acute (Mahieu, et al., 1981; 

Apostoli et al., 1997; Benramdane et al., 1999) or chronic exposures to 

iAs (Vahter, 1999; Thomas et al., 2001). These data suggest that the 

capacity to produce TMAVO from iAs or DMAV or to excrete TMAVO 

in urine is lower in humans compared to rats. Thus, while it is 

possible that the urinary TMAV/III metabolites significantly affect the 

18
overall toxic or cancerous outcomes in the bladder of rats exposed to 

DMAV, the relative lack of these metabolites in human urine suggests 

that the outcome in humans would not be as severe as in rats. 

However, because the suggested toxicity differences above reflect a 

very limited human data set, more research is needed to characterize 

the role of TMAV/III metabolites in bladder carcinogenesis induced in 

rats by chronic exposures to DMAV. Research is also needed to 

determine whether the apparent absence of these metabolites in 

humans is associated with a decreased susceptibility to the 

carcinogenic effects of DMAV. 

c) Accumulation of DMAIII in rat erythrocytes, due to a high-affinity for 

binding to hemoglobin (Lu et al., 2004) contributes to a specific 

kinetic pattern for DMAV in rats. It is not clear how and to what 

extent this factor affects the yield and concentration of the active 

arsenic species (e.g., DMAIII, TMAVO, or TMAsIII) in urine or in 

target tissues of rats and how lower accumulation in human 

erythrocytes would alter the kinetic pattern for DMAV and 

toxic/cancerous outcomes of DMAV exposure in humans. 

d) Microorganisms, including intestinal bacteria, have a capacity to either 

methylate or demethylate arsenicals (Hall et al., 1997; Cullen et al., 

1984; Cullen et al, 1989; Lehr et al., 2003; Bently and Chasten, 2002; 

Tamaki and Frankenberger, 1992; Mukhopadhyay et al, 2002; Ridley 

et al., 1977; Qin, et al., 2006). Although the patterns and extent of 

DMAV metabolism by human intestinal microflora are not known, it is 

possible that oral exposure to DMAV results in the absorption of a 

wide spectrum of arsenic metabolites produced by bacteria in the 

gastrointestinal tract of exposed individuals. In contrast, bacterial 

metabolism would not affect the absorption of DMAV after inhalation 

or dermal exposures. Thus, arsenic species found in tissues may differ 

with different routes of exposure. Interspecies differences in 

endogenous intestinal bacteria may further complicate extrapolation 

from rats to humans. 

e) Additional factors may affect the metabolic profiles for DMAV in 

humans, including co-exposures to other environmental contaminants, 

deficiencies of specific nutrients (e.g., selenium) or malnutrition. For 

example, poor nutrition has been shown to induce expression of 

aquaglyceroporin-9 (AQP9), an iAsIII/MMAIII transporter (Liu et al., 

2002; Liu et al., 2004; Liu et al., 2006), 20-fold (Carbrey et al., 2003). 

All the above concerns should be considered in the risk assessment of DMAV 

exposure. 

EPA’s briefing documents presented information on a physiologically based 

pharmacokinetic (PBPK) model for arsenic disposition and metabolism that is under 

development. PBPK modeling might be a useful approach for integrating tissue and 

excreta concentrations of arsenic metabolites resulting from exposure to the various 

19
forms of arsenic, including DMAV, in laboratory animals and humans. For now, the 

modeling work described by EPA is in the developmental stage and is not considered 

sufficiently robust to conduct interspecies extrapolations. However, the Panel strongly 

encourages the Agency to proceed with PBPK model development, including laboratory 

studies to obtain the kinetic constants needed to describe rates of uptake, efflux, 

metabolism, and elimination of DMAV in both rats and humans. When sufficiently 

validated, this model could simulate concentrations of active (toxic or carcinogenic) 

metabolites in urine and bladder tissue following exposure to DMAV. This approach 

could be used for dose response analysis in cancer risk assessment. Such models must be 

validated for predicting tissue concentrations of active species regardless of the source of 

arsenic exposure. 

3.2.2 Response to mixtures of metabolites (Charge Question A2) 

EPA’s Charge stated that, “Tumorigenic profiles vary based on which arsenical 

compound is administered exogenously. In vivo and in vitro studies indicate that each of 

the arsenical compounds exhibit similarities and differences in their profiles of biological 

activities. Direct exposure to iAsIII or iAs V is expected to result in more of a mixture of 

toxic metabolites than for direct exposure to DMAV; the mixture of metabolites is 

expected to vary based on which chemical is administered exogenously. The potential 

mixture of metabolites following direct exposure to DMAV appears less complex as 

compared to iAs” (USEPA, 2005a). Charge Question A2 asks, “Given the toxicological 

response profiles observed following direct exposures to iAs versus MMAV

 and DMAV, 

and the differences in human and rodent toxicologic responses to arsenicals, please 

comment on the use of data derived from rodent exposures to the organic arsenicals 

versus use of data derived from direct iAs human exposure, in the DMAV

 assessment.” 

The Panel believes that neither rodent laboratory data on organic arsenicals nor 

data from studies of the results of human exposures to inorganic arsenic provide an 

optimal basis for the assessment of DMAV exposures in humans. This is because of the 

differences between the metabolic profiles for inorganic arsenic and DMA, and because 

of interspecies differences in the metabolism of both arsenicals. The panel agrees that 

using the data from rodent exposures to DMAV may, at this time, be the most reasonable 

approach for the DMAV assessment. 

The reasoning behind this response is linked to the answer to charge question A1 

above (see section 3.2.1). The metabolism of iAs yields a wide spectrum of metabolites 

(Figure 1) some of which (iAsIII/V, MMAIII/V) are apparently not produced during the 

metabolism of exogenous DMAV. The production of iAs and MMA metabolites may be 

associated with specific toxic or cancerous endpoints that are absent in DMAV exposure 

in rats or humans except when there is a significant co-exposure to iAs as is often found 

in U.S. drinking water supplies, or in food or the environment. The Panel notes that there 

are no published data on toxicological responses to DMAV in humans. The toxic and 

carcinogenic effects of DMAV have been examined only in rodents, mainly in rats. 

20
AsVO4 3-+ 2e­ → AsIIIO3 3- 3 + → CH3AsVO3 2- ­ → CH3As O2 2- + CH3 + → (CH3)2AsVO2 - ­ → 3)2AsIIIO­ 3 + → 

V) (iAs ) ( V) ( ) V) ( III) 

ite l l di i 

acid

Rat 

+ CH + 2e III + 2e (CH + CH 

 (iAs III MMA MMAIII (DMA DMA 

arsenate arsen methy arsonic methy arsonous methylars nic dimethylarsinous 

acid acid acid 

Human 

Figure 1. Schema of Inorganic Arsenic Metabolism in the Rat and Human: The metabolic pathway fo

the rat and human involves a stepwise addition of methyl groups to yield methylarsenic (MMA), dimethylarsenic 

trimethylarsenic (TMA) metabolites that contain trivalent arsenic (AsIII) or pentavalent arsenic (AsV). Results of 

laboratory studies suggest that while MMA and DMA are products of this metabolic pathway in both rats and hu

excrete significant amounts of TMAVO in urine when exposed to inorganic arsenic, MMA or DMA. In addition, 

of inorganic arsenic by recombinant rat, but not human arsenic (+3 oxidation state) methyltransferase produces T

alternative pathways have been suggested for inorganic arsenic metabolism and additional methylated metabolite

urine of rats and humans exposed to arsenicals, more research is needed to determine the significance of these pafor inorganic arsenic or DMA metabolism in both species. 

21
However, a significant degree of uncertainty is associated with this approach due 

to the metabolic differences between rats and humans and due to other factors, including 

those listed in the response to charge question A1 above. The differences in the 

production and urinary excretion of TMAIII/V species that could affect the toxic and 

cancer outcomes of DMAV exposure are of a particular concern to this panel. TMAVO is 

a hepatocarcinogen in rats (Shen et al., 2003). TMAIII is apparently more potent than 

DMAIII in damaging purified DNA in in vitro systems (Andrews, et al., 2003). On the 

other hand, both TMAVO and TMAIII are less acutely toxic or cytotoxic than DMAIII 

(Yamauchi et al., 1990; Cullen, 2005; Sakurai et al., 1998; Ochi et al., 1994). The 

contribution of these two metabolites to cytotoxicity and carcinogenesis in the urinary 

bladder of rats exposed to DMAV remains unclear. This uncertainty should be properly 

addressed in the risk assessment for DMAV exposure in humans. 

3.3 Modes of Carcinogenic Action for DMAV and Inorganic Arsenic 

3.3.1. Mode of Action of DMAV (Charge Question B1) 

EPA’s Charge stated that, “When relying on laboratory animal data, two critical 

assumptions are made: (i) data on animal tumors are predictive of human cancer, and (ii) 

animal tumor effects found at high experimental doses predict human risk at lower 

exposures. An understanding of a chemical mode of carcinogenic action can help inform 

the above assumptions. In the case of DMAV, mode of action (MOA) data are available 

and were evaluated using the framework described in EPA’s cancer guidelines” (USEPA, 

2005a). Charge Question B1 asks the SAB to “... comment on the sufficiency of evidence 

to establish the animal mode of carcinogenic action for DMAV

. Are the scientific 

conclusions sound and consistent with the available evidence on DMAV and the current 

state of knowledge for chemical carcinogenesis?” In addition, the Charge asks the SAB 

to “...comment on whether the key events in DMA’s mode of action are supported by the 

available data. Specifically comment on the role of: a) reactive oxygen species in 

producing chromosomal damage and the strength of the evidence supporting oxidative 

damage as a causal key event in DMAV

/DMAIII‘s mode of carcinogenic action versus an 

associative event or a secondary consequence of cytotoxicity; b) cell proliferation and 

cytotoxicity and the strength of the evidence as causal key events in DMAV

/DMAIII‘s mode 

of carcinogenic action versus associative or secondary events, and c) other potential 

modes of action that have substantial scientific support that may be contributing to the 

carcinogenicity of DMA. 

The Panel concluded that there are adequate data to support a MOA for bladder 

carcinogenesis induced by high doses of DMAV in the rat that involves cytotoxicity to the 

bladder epithelium and increased, sustained regenerative proliferation as key events. The 

urine of DMAV-treated rats contains DMAIII at levels that cause necrotic cytotoxicity in 

vitro, so it is reasonable to postulate that DMAIII might mediate the necrotic cytotoxicity 

in the rat bladder. However, the rat (unlike the human) metabolizes a significant fraction 

of exogenous DMAV to TMAVO (Cohen et al., 2002; Yoshida et al., 1997, 1998) and 

22
possibly to TMAIII (Waters et al., 2004). Thus, these compounds cannot be excluded as 

additional mediators of the necrotic cytotoxicity in the bladder of rats exposed to DMAV. 

The Panel thought that there are not sufficient data to invoke reactive oxygen 

species (ROS)-induced DNA damage as a key event in the carcinogenic process 

associated with exposures to DMAV or DMAIII for the reasons discussed in the following 

paragraphs. 

Chemically, neither oxidation of AsIII to AsV nor reduction of AsV to AsIII can 

produce an oxygen radical in the absence of other reactants. Arsenic can only undergo 

two-electron reduction (no free electron or radical to donate to oxygen). Although there 

are indirect sources of ROS that can participate in arsenite-stimulated cell signaling (e.g. 

stimulation of NADPH oxidase; Smith et al., 2001) or arsenic trioxide-mediated 

apoptosis via mitochondrial collapse (Jing et al., 1999), these have not been demonstrated 

for DMA. Arsenic compounds could also increase ROS by promoting an inflammatory 

response in many tissues. This may contribute to carcinogenesis, but it is not likely to be 

the primary MOA for carcinogenesis. 

Much of the argument suggesting that the mode of action of DMAV-induced 

bladder cancer involves ROS-induced chromosome damage derives from studies on 

DMAIII-induced DNA damage. Very high cytotoxic concentrations of DMAIII have been 

shown to induce DNA damage in cell-free systems and in intact cells (Mass et al., 2001), 

possibly via an ROS-mediated mechanism or by dimethylarsine (Yamanaka et al., 2003; 

Kitchin and Ahmad, 2003; Nesnow et al, 2002; Andrews et al., 2003). However, cellular 

genetic toxicology assays of DMA do not support an ROS-dependent mechanism. 

Neither DMAV nor DMAIII is significantly mutagenic at loci which are known to detect 

oxidant DNA damage. Neither compound was mutagenic in the Ames Salmonella strain 

TA104, a strain developed primarily to aid in the detection of oxidative mutagens, nor 

were 8 prophage induced (Kligerman et al., 2003). Prophage induction (which depends 

on the E. coli SOS system, a system responsive to DNA damage) was readily detectable 

after treatment with other agents acting by oxidant mechanisms, such as bleomycin, 

carbon tetrachloride (+S9), hydrogen peroxide, and iron compounds (Rossman et al., 

1991). 

DMAV was either negative or very weakly positive at extremely high doses in a 

number of other test systems which can detect oxidative mutagens (Moore et al., 1997, 

Kligerman et al., 2003; Oya-Ohta et al., 1996). Treatment of MutaTMmouse with DMAV 

(10.6 mg/kg per day) IP for 5 days caused only a (not significant) 1.3-fold increase in 

lacZ mutations in the lung, but not in the bladder or bone marrow (Noda et al., 2002). 

DMAV presumably could be converted to DMAIII in mouse liver. (Arsenite also gave 

negative results in this assay.) 

The single study of DMAIII in the mouse lymphoma assay (Kligerman et al., 

2003), which detects clastogens as well as point mutagens at the TK locus, showed no 

significant effect on mutant fraction at concentrations <1.5 μM (38% survival) in the agar 

assay. “Significant” was defined as at least a 2-fold increase over control, but no 

23
statistical analysis was done, only a single assay is shown, and there is only one 

“significant” response, at 1.51 μM. (This assumes a background mutant fraction of 

between 38 and 50 X 10-6). A microwell assay using the same cells showed a 

“significant” effect at 2.56 μM (9% survival). 

Kligerman et al. (2003) argued that DMAIII (and MMAIII) are basically clastogens 

and not point mutagens. The clastogenesis studies suffer from the same problems as the 

mutagenesis studies: no statistical analysis and single data points at some doses. 

“Significant” (defined as a 2-fold increase) effects are seen only at toxic doses (toxicity 

data are not given but can be inferred from other mammalian cell data). In addition, since 

cytogenetic assays do not require cell survival for scoring, when clastogenic effects are 

seen in a population of cells with low survival, it is not possible to determine whether 

those cells with chromosome aberrations would be among the survivors, and thus capable 

of resulting in a tumor. Examination of chromosomes in tumor and pre-tumor tissues in 

the rat bladder model might establish whether specific chromosome aberrations are 

associated with DMAV-induced bladder cancers. 

Even model clastogens such as ionizing radiation can also be detected as 

mutagens at single gene loci such as HPRT, a useful locus for studying mutations in vitro 

as well as in vivo (unlike TK). Thus, if DMAIII was really a clastogen acting by ROS, it 

should cause increased deletion mutagenesis at the HPRT locus. More research on the 

ability of arsenic metabolites to induce gene mutations in vivo should be carried out. 

The fact that (some) antioxidants blocked DMAV-induced bladder cancer in the 

rat does not provide evidence as to the origin of the oxidants nor where they act. 

Activation of NADPH oxidase (Smith et al., 2001) or inhibition of GSH reductase 

(Styblo et al., 1997) could increase oxidants. Tissues subjected to continuing cellular 

assault produce a number of cytokines whose signaling may be modulated by oxidants 

(even in the absence of frank inflammation). Nuclear factor-kappaB (NFkB), which is 

activated by low-dose arsenite via oxidants (Barchowsky et al., 1996), is thought to 

provide a link between inflammatory signaling and carcinogenesis, as well as providing 

survival signaling to block apoptosis in damaged cells that might otherwise die. NFkB is 

a transcriptional regulator of genes including cyclooxygenase-2 (COX-2), which is also 

induced by arsenite (Trouba and Germolec, 2004). Research is needed to determine 

whether bladder cells undergoing stress-related proliferation in the rat DMAV 

carcinogenesis model show effects on NFkB and other signaling pathways, similar to 

those seen with arsenite. 

Given the preponderance of scientific evidence to date (which is reviewed above 

in this section), the principal MOA for DMAV does not appear to be mediated via the 

ROS-induced DNA damage pathway. Rather, the MOA is likely to be sustained 

cytotoxicity followed by genomic instability as a result of stress-related proliferation. 

Permanent genetic change is necessary for carcinogenesis, and it is unlikely that 

increased proliferation alone in the absence of increased genomic instability will result in 

the multiple changes needed to transform a normal cell into a tumor cell. The mechanism 

of cell killing by DMAV or DMAIII is not known. Regardless of how the cells die, there 

24
is substantial evidence supporting the hypothesis that continual proliferation of surviving 

cells under conditions of stress results in genomic instability (Karpinets and Foy, 2005). 

For example, in the case of arsenite this would involve such factors as: 

a) Inducing intracellular proliferative signals and over-riding cell cycle 

checkpoints (reviewed in Rossman, 2003), 

b) Blocking DNA repair (reviewed in Rossman, 2003), 

c) Inhibiting GSH reductase (Styblo et al., 1997) and thioredoxin reductase (Lin et 

al., 2001), 

d) Inducing stress-related survival signals to block apoptosis (Pi et al., 2005; Wu et 

al. 2005), 

e) Effects on thiols in tubulin and cytoskeletal proteins, interfering with 

microfilament function and cytoskeletal changes (Li et al., 1992; Ling et al., 

2002; Ochi et al., 1999), 

f) Affecting DNA methylation levels, (Chen et al., 2004), 

g) Inducing oxidant signaling (Barchowsky et al., 1999), and 

h) Effects on hormone function (Bodwell et al., 2004). 

More research should be carried out on cells undergoing stress-related proliferation 

in the rat bladder model to determine whether these same programs have come into play 

for DMAV. Changes in DNA methylation patterns have just been demonstrated in 

arsenic-associated human bladder cancers (Marsit et al. 2006), making this a priority for 

study in the rat model. 

Live cells exposed to the contents of necrotic cells may experience additional stress 

signals similar to that seen in the “bystander effect” after ionizing radiation (Iyer and 

Lehnert, 2000) or via cytokines from inflammatory cells. Although there is no direct 

evidence to support this mechanism in the rat bladder cancer model, it is of interest that 

heat-killed E. coli instilled into the bladder was found to increase bladder carcinogenesis 

by N-methyl-N-Nitrosourea (Yamamoto et al., 1992), presumably by an inflammatory 

mechanism. Research on this topic should be carried out both in vivo and in vitro. 

Further, generation of low levels of oxidants from enzymatic sources (Smith et al., 2001) 

or possibly by uncoupling of mitochondrial oxidations (if DMAV can act in a manner 

similar to arsenate) may contribute to effects on cell signaling and transcriptional 

activation, as well as increase oxidant DNA damage. 

In summary, the Panel postulates that the mode of action for DMAV involves the 

following key events: 

a) Reductive metabolism of DMAV to DMAIII. 

b) High concentrations of DMAIII in urine cause urothelial cytotoxicity. Some 

toxicity may also be caused by DMAV itself. 

c) Continuous exposure and persistent stress associated regenerative cell 

proliferation leads to genomic instability, acquisition of genetic alterations, 

clonal expansion of altered cells and eventually tumors. 

25
This MOA, as well as the original MOA suggested by EPA, depends upon 

prolonged extensive cytotoxicity in the bladder. Without the continual cytotoxicity, 

sustained stress-associated proliferation would not occur. The tumor response in the rat 

bladder system is non-linear, as is the key event (i.e. the necessity for necrotic 

cytotoxicity). Since the MOA involves cytotoxicity, doses below those causing 

cytotoxicity would not be expected to cause tumors. The other events mentioned above 

would not be sufficient to cause tumors in the absence of the cytotoxicity and the 

resulting proliferative response. 

3.3.2 Human relevance of animal DMAV MOA (Charge Question B2) 

EPA states that, “There are little or no scientific data to suggest that if sufficient 

DMAIII were present, key precursor events and ultimately tumor formation would not 

occur in humans directly exposed to DMAV” Charge Question B2 asks the SAB to 

“...comment on the relevance of the postulated key events (see B1) to tumors in 

humans...”and to comment on how, if at all, differences in the human population vs. 

experimental animals should be accounted for in the risk assessment for DMAV

. 

If high enough (cytotoxic) concentrations of DMAV or DMAIII were present in the 

human urine or bladder after exposure to DMAV, it is plausible that a similar response 

(necrosis followed by regenerative, stress-associated proliferation) would take place. 

However, no data are available to support or reject this assumption. No studies have 

been carried out on DMAV-induced bladder cancer in humans, so it is not known at this 

time whether there have been any cases. Concentrations high enough to cause necrosis in 

the bladder might be achievable in an industrial accident or deliberate poisoning. It is not 

clear whether a repeated or chronic exposure to DMAV from the environment could 

produce cytotoxic concentrations of critical metabolites in human urine. Even in the case 

of high exposure, the exposures would probably have to be repeated often enough to 

produce persistent necrosis and regeneration in order to cause cancer. 

As already mentioned in Charge Question A1 above, DMAV is converted to 

TMAVO, and possibly TMAIII, more efficiently by rats than by humans. TMAVO is a 

hepatocarcinogen in rats (Shen et al., 2003). TMAIII is more potent than DMAIII in 

damaging DNA in in vitro systems (Andrews et al, 2003). Thus, although acute toxicities 

of TMAVO and TMAIII are lower than that of DMAIII (Ochi et al., 1994; Sakurai and 

Kaise, 1998; Yamauchi et al., 1990), these metabolites could contribute to the MOA for 

DMAV-induced bladder cancer in rats. The extent of this contribution is unknown. 

However, it is possible that the rat data overestimates the human risk for bladder cancers 

from DMAV. 

No studies have been done in either animal models or in human populations to 

determine whether the young are at greater or lesser risk with regard to DMAV-induced 

carcinogenesis, or whether there is greater or lesser risk during any other life stages. 

26
3.3.3 Modes of carcinogenic action from exposures to inorganic 

arsenic (Charge Question B3) 

EPA stated that, “Inorganic arsenic (iAs) undergoes successive methylation steps 

in humans, resulting in the intermediate production of iAs III, MMAV, MMAIII, DMAV, 

and DMAIII. Each arsenical metabolite exhibits its own toxicity.” Charge Question B3 

asks the SAB to “...comment on the conclusion that the available data support the 

hypothesis that multiple modes of action may be operational following exposure to 

inorganic arsenic.” 

The Panel agrees that multiple modes of action may operate in carcinogenesis 

induced by inorganic arsenic. This is because there is simultaneous exposure to multiple 

metabolic products as well as multiple target organs. There are differences in metabolic 

capability and probably transport into and out of different organs for different metabolic 

products, so that the composition of the metabolites can differ in different organs as well. 

Each of the metabolites has its own cytotoxic and genotoxic capability. In general, the 

pentavalent compounds are less cytotoxic and genotoxic than are the trivalent 

compounds. 

In the remainder of this section of the report, the Panel discusses studies of 

indirect genotoxic effects associated with iAs and/or its metabolites, as well as the notion 

that iAs might have some beneficial effects at very low doses. Taken together, these 

studies suggest the possibility of a threshold. However, the Panel does not identify what 

the threshold might be, nor does it describe the shape of the dose-response curve, rather it 

leaves that to be addressed by EPA in its final assessment based on the outcome of EPA’s 

evaluation of the relevant literature. The Panel identifies this as an extremely important 

area for research attention. 

In the strictest (and original) definition, genotoxic carcinogens, i.e., direct 

carcinogens (or their metabolites) damage DNA by covalently binding to DNA or 

intercalating into the DNA-helix. Indirect genotoxicity occurs through interactions with 

non-DNA targets leading to genotoxic effects. Non-DNA targets, (e.g. proteins) exist in 

many copies per cell, thus a single event is unlikely to have any significant consequences. 

This suggests a threshold for effects associated with such events. The modes of action of 

“non-genotoxic” carcinogens are numerous, and can include regenerative cell growth 

following cytotoxic effects, modulation of metabolizing enzymes, inhibition of DNA 

repair, induction of peroxisome proliferation, stimulation of oxidative stress or other 

signaling resulting in suppression of apoptosis, loss of cell cycle control, and stimulation 

of proliferation. A number of indirect genotoxic events are listed in Table 1. 

The genetic toxicology of iAsIII has been previously reviewed (Rossman, 1998, 

2003; Basu et al., 2001). The interpretation of the genotoxicity of arsenic compounds is 

difficult because of the very high cytotoxic concentrations used in many studies and the 

lack of analysis for statistical significance in many studies. Another part of the problem 

27
Table 1. Some potential mechanisms for indirect genotoxicity of 

Inorganic Arsenic (iAs) 

Potential Mechanisms 

Interference with DNA repair 

 Interference with cell cycle control proteins 

Interference with DNA replication 

 Blocking apoptosis of cells with DNA damage

 Interaction with nuclear proteins such as topoisomerases or spindle 

proteins 

 Nuclease and protease release from lysosomes or dead cells 

 Protein denaturation leading to genomic instability 

 Production of or change in reactive oxygen species leading to altered 

signaling 

 Other changes in gene expression (e.g., COX-2; Trouba and 

 Germolec, 2004) 

 Interference with oxidative phosphorylation 

 Changes in ionic concentration, pH, or osmolarity 

Altered DNA methylation 

stems from inappropriate (or absent) assessment of toxicity of arsenic compounds 

(Komissarova et al., 2005). Low concentrations (even 1 μM) of iAsIII can cause 

apoptosis in human cells that can only be detected 48 hours (or more) after exposure and 

cytotoxicity assays (other than clonal survival) are usually performed too soon after 

exposure to enable identification of apoptotic cells after arsenite exposure. Thus, many 

“positive” genotoxicity results (especially in cytogenetic assays) could have been 

conducted too soon and thus they could be reported for dead or dying cells. In such 

cases, they would only be useful in describing a MOA if the cells continued to live and if 

the genotoxic effect noticed was consistent with effects seen in tumorigenesis studies in 

animals and in human tumors. In the absence of such tumorigenesis data, cell 

transformation studies can yield some insight into MOA. 

Arsenite, i.e., iAsIII (and other arsenicals) does not exhibit direct DNA binding 

and the inability of iAsIII to induce the SOS system in E. coli is consistent with its lack of 

reaction with DNA (Rossman et al., 1984). In mammalian cells, highly toxic 

concentrations of both inorganic and organic arsenic compounds in vitro cause 

chromosome breakage, which some have attributed to ROS-induced DNA strand breaks 

but which might be caused directly by other free radical species (Yamanaka and Okada, 

1994; Andrews, et al. 2003). Cellular DNA strand breakage and clastogenicity are 

limited almost exclusively to trivalent species. Unlike many other carcinogens, iAsIII is 

28
an extremely weak (or insignificant) mutagen at single gene loci such as HPRT or TK in 

mammalian cells (Rossman, 1998, 2003). However, iAsIII (but not MMAIII) at low 

(nontoxic) concentrations can induce delayed indirect mutagenesis at the HPRT locus 

after >15 generations as a secondary result of genomic instability (Mure et al., 2003). 

The argument has been made that arsenite is a clastogen that causes 

predominantly multilocus deletions, and that such deletions near the HPRT locus (which 

is located on a single active X chromosome) may be lethal, accounting for the lack of (or 

extremely weak) mutagenesis by arsenicals at the HPRT locus (Hei et al., 1998). 

However, molecular analysis of mutations in the HPRT gene shows that large deletions 

(up to ~3.5 Mb) can be tolerated in the HPRT region of the human X chromosome 

(Nelson et al., 1995; Lippert et al., 1995). Despite this, attempts have been made to find 

genetic markers more likely to detect large deletions. Also, iAsIII was an insignificant 

mutagen, and only at toxic doses, in transgenic Chinese hamster G12 cells (a derivative 

of V79 cells) (Li and Rossman, 1991). These cells can detect clastogens causing 

deletions in the single copy of the E. coli gpt gene inserted into Chinese hamster 

chromosome 1. Similar results (extremely weak mutagenesis at toxic arsenite 

concentrations) are seen in mouse lymphoma cells, which can tolerate deletions at the TK 

locus due to its autosomal location (Moore et al., 1997), at the transgenic gpt locus of 

AS52 Chinese hamster ovary cells (Meng and Hsie, 1996) and in AL cells, which are 

CHO-K1 cells containing a single copy of human chromosome 11 (Hei et al., 1998). 

In vivo, iAsIII induced micronuclei (MN) in mouse peripheral blood lymphocytes 

and in mouse bone marrow (Tinwell et al., 1991; Noda et al., 2002). Humans exposed to 

iAsIII show increased MN and sometimes chromosome aberrations in lymphocytes, 

exfoliated bladder epithelial cells, and buccal epithelial cells (reviewed in Basu et al., 

2001). In vivo studies on genotoxic activity of methylated arsenic species are limited to a 

small number of studies in rodents. IP injections of high doses of DMAV induced a slight 

but insignificant increase in mutagenesis in the MutaTMMouse lung, but not in bladder or 

bone marrow. Also, iAsIII was negative in this assay (Noda et al., 2002). High 

concentrations of DMAV administered orally to mice caused oxidative damage and DNA 

strand breaks in the lung (not a target organ for DMAV carcinogenesis). The strand 

breaks were attributed to dimethylarsine, via the dimethylarsenic peroxy radical 

(CH3)2AsOO· (Yamanaka and S. Okada, 1994). DMAV also induced aneuploidy in 

mouse bone marrow cells (Kashiwada et al., 1998). 

As noted in the previous paragraph, micronuclei are induced by iAsIII in vivo, and 

MN frequency is increased in humans exposed to iAsIII in drinking water. Because of 

this, it is important to consider the significance of MN for MOA. MN are defined as 

small, round, DNA-containing cytoplasmic bodies formed during cell division by loss of 

either acentric chromatin fragments or whole chromosomes. The two basic phenomena 

leading to the formation of MN are chromosome breakage (double strand breaks 

associated with clastogenesis) and dysfunction of the mitotic apparatus leading to 

aneuploidy (change in chromosome number from the normal diploid or haploid number 

other than an exact multiple). MN as a result of clastogenesis contain acentric 

chromosome or chromatid fragments while MN associated with aneuploidy contain 

29
whole chromosomes. Currently, the most widespread and reliable assay to identify whole 

chromosomes in MN is by fluorescent label of their kinetochores (with antibodies) or 

their centromeres (with DNA probes). However, only a few laboratories routinely use 

these techniques because they are very costly. In most studies, there is not enough 

information to determine whether the MN result from: 1) toxicity, 2) clastogenicity, or 3) 

non-dysjunction (leading to aneuplody). Also, MN in cells trigger apoptosis, so many 

cells with MN will have no progeny. 

In a study of 18 arsenic-exposed individuals (average 1,312 μg arsenic/L drinking 

water) and 18 matched controls (16 μg/L), the exposed group had a 1.65-fold increase in 

MN with acentric fragments (p=0.07) and a 1.37-fold increase in MN with whole 

chromosomes (p=0.15) (Moore et al., 1996). The combined difference (1.8-fold) was 

significant. Thus, exposure to iAsIII induces MN by multiple mechanisms. In normal 

human fibroblasts, low dose, long term exposure to iAsIII is aneugenic, inducing MN with 

whole chromosomes, but high dose, short term exposure is clastogenic, inducing MN 

with chromosome fragments (Yih and Lee, 1999). Evidence supports an aneugenic role 

for iAsIII in many other cells at concentrations lower than those causing chromosome 

aberrations (Kochhar et al., 1996; Vega et al., 1995; Ramirez et al., 1997; Huang and Lee, 

1998; Moore et al., 1997; Sciandrello et al., 2002). Of importance is the association of 

aneuploidy with malignant transformation induced by arsenite and DMAIII (Ochi et al., 

2004; Chien et al., 2004). Aneuploidy is an event that has a threshold (Kirsch-Volders et 

al., 2002), whereas many people assume that clastogenesis does not (at least for ionizing 

radiation) even though repair of radiation-induced DNA damage exists. The 

development of aneuploidy is a marker of genomic instability and is typical of many 

tumors. IP injection of DMAV in mice induced aneuploidy, but no chromosome 

aberrations, in bone marrow (Kashiwada et al., 1998). (DMAV would be converted to 

DMAIII in the mouse, so the active agent may be DMAIII). Bladder tumors in patients 

with high iAsIII exposure showed higher levels of aneuploidy compared with other 

bladder tumors (Moore et al., 2002). 

Genomic instability can result from changes in DNA methylation in iAsIII-treated 

cells. The first report of arsenite inducing DNA methylation changes was the increased 

cytosine methylation in the p53 promoter in human adenocarcinoma A549 cells (Mass 

and Wang, 1997). Later it was found that there was both hypo- and hypermethylation (of 

different genes) in human kidney UOK cells treated with iAsIII (Zhong and Mass, 2001). 

When SHE cells or rat liver TRL1215 cells were transformed by iAsIII, specific 

oncogenes were more highly expressed due to hypomethylation (Zhao et al., 1997; 

Takahashi et al., 2002) and there was evidence of decreased DNA methyltransferase 

activity (Zhao et al., 1997). These findings are consistent with the usual DNA 

methylation changes observed in cancer, in which global methylation is reduced but some 

gene specific promoter methylation is increased (Baylin and Herman, 2000). Arsenite 

(iAsIII)-induced DNA hypomethylation and altered gene expression has been 

demonstrated in mouse liver (Chen et al., 2004), in hepatocellular carcinoma derived 

from transplacental iAsIII exposure (Waalkes et al., 2003), and in prostate epithelium 

where the hypomethylation was shown to activate K-ras (Benbrahim-Tallaa, et al., 2005). 

In a study of iAsIII exposed individuals in India, increased levels of hypermethylated p16 

30
and p53 gene promoters were seen in blood DNA (Chanda et al., 2006). Methylated CpG 

sites are mutational hotspots (e.g. by a second agent), methylation changes affect gene 

expression, and hypomethylation leads to genomic instability. Low concentrations of 

iAsIII induce delayed mutagenesis and chromosome aberrations that might be mediated 

by hypomethylation (Mure et al. 2003; Sciandrello et al., 2004). This is a mechanism 

that might also explain transplacental carcinogenesis. 

There are a number of non-genotoxic actions of arsenite (and perhaps MMAIII and 

DMAIII) that can contribute to the carcinogenic process. The role of ROS in (low dose) 

arsenic carcinogenesis is probably via signaling changes rather than as a genotoxicant 

(otherwise, one would expect more mutagenesis). This may contribute to carcinogenesis, 

but it is not likely the primary MOA for arsenic carcinogenesis. Cell signaling can be 

affected by arsenite via low levels of oxidants that do not cause DNA damage (reviewed 

in Simeonova and Luster, 2004). Low iAsIII concentrations increased oxidant signaling 

and oxidant-dependent activation of nuclear factor kappaB (NFkB) in the absence of 

DNA damage in human endothelial cells (Barchowsky et al., 1999). The increased 

oxidants appear to result from activation of membrane-bound NAD(P)H oxidase. 

Arsenite (iAsIII)-induced signaling results in expression of inflammatory cytokines such 

as IL-8 that can mediate atherogenesis (Simeonova and Luster, 2004). Arsenite (iAsIII) 

also increases ROS by promoting an inflammatory response in many tissues. In addition, 

there is redox chemistry involved in iAsIII-dependent signaling in that arsenite binds to 

protein thiols (particularly vicinal thiols) to stimulate signaling cascades or affect DNA 

repair. Arsenite (iAsIII) interaction with thiols is a redox reaction, but oxygen radicals are 

not involved. 

Exposure to low, non-toxic doses of iAsIII enhances positive growth signaling 

(reviewed in Rossman 2003), which can readily contribute to hyperplastic pre-cancerous 

skin growth. Arsenite (iAsIII) can disrupt glucocorticoid receptor (GR) and other steroid 

signaling at very low doses, and it has been suggested that these effects on GR may affect 

carcinogenesis (Kaltreider et al., 2001). This may also affect other disease processes, 

such as cardiovascular disease, diabetes and other diseases that have been associated with 

iAs exposure, since GR and other steroid receptors have been shown to be important in 

these diseases as well. 

Animal studies indicate that for some organs, transplacental carcinogenesis after 

maternal exposure to iAsIII occurs. This includes the formation in C3H mice of tumors of 

the lung and liver, target sites of potential human relevance, after exposure to arsenic in 

utero. In addition, in utero arsenic induces tumors of the ovary and adrenal, sites not 

observed in humans to date. The C3H mouse was selected in these studies because it is, 

in general, sensitive to chemical carcinogenesis, although this strain shows spontaneous 

tumor formation in several tissues. Recent work has shown that with gestational 

exposure to CD1 mice, inorganic arsenic is a complete carcinogen in the female offspring 

(Waalkes, et. al., 2006). The CD1 mouse strain is noteworthy as having a well defined, 

low rate of spontaneous tumors. EPA’s revised assessment document should take note of 

this important development. Other studies indicate that in skin, neither iAsIII nor iAsV is 

a complete carcinogen, but they act as enhancers (cocarcinogens, sometimes mistakenly 

31
called “promoters”) with other agents. Arsenite (iAsIII) acts as a cocarcinogen with solar 

UV light (Rossman et al. 2001; Burns et al., 2004) and arsenate is cocarcinogenic with 

9,10 dimethyl1-2-benzanthracene (Motiwale et al., 2005). This leaves open the 

possibility that a cocarcinogenic MOA may also operate for other organs, but this 

remains to be investigated. 

Arsenite (iAsIII)-enhanced UV carcinogenesis could result from acquired 

resistance to UV-induced apoptosis. Such resistance was recently demonstrated in 

human keratinocytes (HaCaT) treated with 0.1 μM arsenite for 28 weeks (Pi et al., 2005). 

In mouse keratinocytes, the repair of UV-induced 6-4 photoproducts was slowed by acute 

5.0 μM (24 hr) arsenite exposure, which also inhibited the UV-induced apoptosis as 

indicated by TUNEL flow cytometry and by reduction of caspase 3/7 activities (Wu, et 

al., 2005). Arsenite (iAsIII) also blocked UVB-induced apoptosis in human keratinocytes 

(Chen et al., 2005). One mechanism by which iAsIII may perturb apoptotic pathways is 

by PI3K-mediated phosphorylation of PKB (Akt). When PI3K activity was inhibited by 

Wortmannin or LY294002, arsenic-induced apoptotic resistance was also blocked (Pi et 

al., 2005). 

Table 2 lists some activities of iAsIII (or its metabolites) that might explain how 

iAsIII can act as a transplacental carcinogen and a cocarcinogen but not a complete 

carcinogen in neonatal and older animals. 

In the future, it will be important to determine whether the trivalent arsenic 

metabolites can induce tumors in vivo or transform or mutate keratinocytes and other 

major target cells of arsenic at biologically relevant concentrations. The mechanism of 

iAs-induced carcinogenesis is likely to be different in different tissues, with contributions 

from all the various arsenic species present in that tissue. 

There have been a number of reports claiming an essential role for iAs in various 

animal species (chick, goat, hamster, pig, rat), but many of these reports exist only in 

abstracts or in meeting reports (reviewed in Uthus, 1992; Nielson, 1996). Reports in the 

peer-reviewed literature follow. A study of arsenic-deprived goats found muscle atrophy, 

reduction in oxidative enzymes and abnormal mitochondria in muscle, possibly via 

disturbance of calcium metabolism (Schmidt et al., 1984). Studies by Uthus (1990, 1992) 

suggest that iAs has a role in methionine/methyl metabolism. Arsenic (iAs)-deprived rats 

had decreased plasma taurine, hepatic polyamines, and S-adenosylmethionine 

decarboxylase (needed for polyamine synthesis). Arsenic (iAs)-deprivation as well as 

iAs excess caused DNA hypomethylation in rat liver. The same effect was seen in Caco2 cells. Arsenic (iAs) deprivation or excess also increased the formation of aberrant 

colon crypts in rats treated with dimethyl hydrazine (Uthus and Davis, 2005), suggesting 

a cocarcinogenic effect. So far, no exact biochemical mechanism linking any iAs species 

with methionine/methyl metabolism has been found, but the fact that many laboratories 

have reported effects of iAsIII on DNA methylation makes this an important area of study. 

32
Table 2. Activities of iASIII that may contribute to its cocarcinogenic 

and/or transplacental carcinogenic action 

Activities 

 DNA repair inhibition 

 Increased oxidants (signaling changes) 

 Gene dosage effects (aneuploidy, amplification) 

Altered DNA methylation 

Proliferative response 

Increased angiogenesis 

 Effects on immune system (not discussed; see Vega et al., 2004) 

Inhibition of apoptosis 

 Hormonal effects 

 Delayed mutagenesis (not enough generations in vivo but maybe 

 enough if transplacental or added to a genotoxic agent?) 

Hormetic effects of iAs (beneficial effects at very low doses) have also been 

suggested and need further investigation even if arsenic should not be essential. In cell 

culture, subtoxic concentrations of iAsIII reduced the levels of ROS in keratinocytes and 

fibroblasts by upregulating thioredoxin and glutathione reductase (Snow et al., 2005). 

Some DNA repair proteins are also upregulated. The same paper also describes 

protection of mice from skin tumors induced by dimethylbenzanthracine + phorbol 12­

tetradecanoate 13-acetate if the mice were given drinking water containing 0.2-2 ppb 

arsenate. Inorganic arsenic (iAs) has both positive and negative effects on the growth 

and function of blood vessels (Soucy et al., 2003, 2005; Kamat et al., 2005). Low 

concentrations fuel angiogenesis, while higher concentrations injure endothelial cells and 

promote the vessel dysfunctions seen in ischemic diseases and peripheral vascular 

diseases. Thus, iAs may provide improved vascularization and growth of normal tissues, 

which could reduce cardiovascular risks. However, this process could also pose risks for 

iAs increasing the vascularization and growth of both atherosclerotic lesions (Simeonova 

and Luster, 2004) and tumors from a secondary source (Kamat et al., 2005). Mice 

drinking 10-250 ppb iAsIII had increased metastases from transplacental tumors (Kamat 

et al., 2005). However, iAs at high doses has been used to destroy the tumor vasculature 

(Griffin et al., 2003). 

While mechanistic studies suggest that there should be a threshold for iAs bladder 

cancer, available data, and data from epidemiological studies, are lacking or problematic 

with regard to low-dose effects. This critically important issue should be the subject of 

additional mechanistic and epidemiologic research. This research should attempt to 

determine whether the suggested hormetic or beneficial effects of arsenic, for several 

endpoints at very low doses, exist more broadly and whether they apply to all life stages. 

If iAs is shown to be essential, i.e., necessary for certain life-sustaining functions or 

processes, then a threshold would not be at zero. If iAs would be shown to have hormetic 

effects, then the issue of a threshold would be less clear and while a threshold might be 

33
possible for one health endpoint, it might not exist for another iAs associated health 

endpoint. Research should also further illuminate the shape of the dose response curve at 

low doses for the biological effects of arsenic. 

3.4 Selection of Data for Dose-Response Assessment 

3.4.1 Use of animal data for DMAV (Charge Question C1) 

EPA’s Charge stated that, “A number of different rodent bioassays (standard 

bioassay, transgenic animals, susceptible rodent strains, initiation and promotion studies) 

are available on DMAV.” Charge Question C1 asks the SAB to “...comment on the use of 

the bladder tumor data from the DMAV rat bioassay as the most suitable dataset for quantifying 

potential human cancer risk to DMAV 

, including the weight of evidence to support this 

conclusion. 

The consensus of the panel is that, given the lack of human data, the bladder 

tumor data from the DMAV rat bioassay is the most suitable data set for quantifying 

potential human cancer risk to DMAV. Given the differences in metabolic fates of 

DMAV and iAs, the use of human data from iAs exposure to predict risk from DMAV is 

not recommended. In this case, reliance on interspecies extrapolation using the rat 

bioassay data is the best alternative. 

This question indirectly raises the issue as to the largest source of uncertainty for 

DMAV risk assessment—conventional interspecies extrapolation or extrapolation across 

various forms of arsenic. The available material suggests that extrapolation across 

various forms of arsenic would lead to the greatest degree of uncertainty in a risk 

assessment. Although the panel agreed that use of the rat DMAV bioassay data is the 

preferred method, the panel also felt strongly that a discussion of the key uncertainties 

with using data from testing in rats to conduct human risk assessment should be included 

in EPA’s Office of Pesticide Programs report “Science Issue Paper: Model of 

Carcinogenic Action for Cacodylic Acid (Dimethylarsinic Acid, DMAV

) and 

Recommendations for Dose Response Extrapolation.” Issues that panel members 

consider important to discuss in EPA’s Science Issue Paper are discussed in more detail 

below and in Section 3.2.1. These issues include the pharmacokinetic and 

pharmacodynamic similarities and differences between rats and humans in response to 

arsenic exposure (e.g., the role of TMAIII/V species); the use of rodent bladder tumor 

models in general; shared MOAs with iAs due to the possibility of DMAV demethylation 

by intestinal bacteria (see section 3.2.1); and issues related to in the use of rodent data for 

human risk assessment. The panel also recommends that the EPA consider applying the 

Human Relevance Framework (HRF) proposed by the International Life Sciences 

Institute-Risk Science Institute (ILSI-RSI) (Seed, et al, 2005) to the mode of action. 

Application of the framework or its elements may assist EPA in evaluating the human 

relevance of the DMAV rat data. This framework has been used to assess the relevance of 

rodent liver tumors to human cancer risk (Holsapple et al, 2006). 

Several pharmacokinetic differences between rats and humans have been reported 

after arsenic exposure. For example, arsenic methylation in rat hepatocytes proceeds at a 

34
faster rate than in human hepatocytes (Styblo, et al., 1999). Additionally, rats have a 

considerably slower whole body clearance of DMAV compared with humans. This 

slower whole body clearance in rats results from a significant portion of DMA being 

retained in the erythrocytes of rats (Vahter, et al., 1984). The affinity of rat hemoglobin 

to bind DMAIII is 15 to 20 fold higher than that of human hemoglobin (Lu, et al, 2004). 

These differences in metabolism and pharmacokinetics may be consistent with a greater 

sensitivity of the rat to induction of bladder tumors by DMAV. However, without a more 

complete data set demonstrating that exposure of the bladder epithelium (urothelial cells) 

to DMAV metabolites (particularly DMAIII) is greater in rats than in humans for a given 

dose, the data are not sufficient to support reduction of interspecies uncertainty factors 

based on differences in pharmacokinetics. Clearly, this is a high priority area of research 

with the potential to reduce uncertainty in the risk assessment of DMAV. 

In the EPA Science Issue Paper consideration should be given to the 

pharmacodynamic similarities and differences between rats and humans and the 

relevance of the rat response to human risk assessment. Although data illustrating the 

mode of action for DMAV as a bladder carcinogen in rats seem quite convincing, it 

should be noted that rats are more sensitive to DMAV in carcinogenicity testing than are 

mice (Rossman, 2003; Arnold, et al., 2003). While the relative in vivo sensitivities of rats 

and humans to DMAIII are unknown, it has been shown that in vitro rat and human 

urothelial cell lines are equally sensitive in terms of acute toxicity to DMAIII in the 

micromolar range (Cohen et al., 2002). For arsenite, however, the rat MYP3 urothelial 

cell line showed toxicity at about one tenth (LC50 of 0.4 μM) the concentration as did the 

human 1T1 urothelial cell line (LC50 of 4.8 μM). As a result of the Panel’s analysis of 

the information on this key pharmacodynamic response, urothelial cell cytotoxicity, the 

consensus was the EPA could explore a case for pharmacodynamic equivalency between 

the test species, rats, and humans from existing experimental data. Pharmacodynamic 

equivalency could be incorporated into the assessment as a reduction of the 

pharmacodynamic component of the interspecies uncertainty factor, which is 3, to a value 

of one. However, as discussed in the response to question D1, there remains considerable 

uncertainty due to limited comparative in vivo data across species. The final EPA risk 

assessment should fully discuss the interspecies similarities and differences and the 

implications for risk assessment as well as explore opportunities to reduce uncertainty 

factors. 

EPA’s Science Issue Paper should discuss similarities and differences between 

rats and humans in the development of bladder tumors and how these differences impact 

interspecies extrapolation. Studies suggest that in rats it takes two or more years of 

continuous high dose exposure to DMAV to induce these tumors. Human bladder tumors 

are also late occurring. The Science Issue Paper should specifically discuss the 

similarities and differences in the time for induction of DMAV related tumors in rats with 

the pattern observed with humans and arsenic associated urinary bladder cancer. 

EPA’s Science Issue Paper should also discuss general issues associated with rat 

urinary bladder cancer. One such issue is the relationship between the induction of 

tumors and high concentrations of arsenic in the urine. Also, there is a need to address 

35
evidence that simple enhancement of proliferation is not associated with carcinogenesis 

in many tissues. Studies by Gur et al. (cited on page 97 of the DMA MOA Science Issue 

Paper, US EPA OPP, 2005) on the carcinogenicity of DMAV were never published and 

thus cannot be critically evaluated by the Panel. The Science Issue Paper notes that the 

Gur studies in rats and mice are key bioassay studies. Reliance on these studies would be 

stronger if the studies had the benefit of peer review. 

The EPA’s Science Issue Paper expresses concern with the mouse transplacental 

model for inorganic arsenic because the strain of mice used (namely C3H) in the original 

two studies had a significant rate of spontaneous tumors in several tissues that are also 

targets of arsenic. Recent follow-up work has shown that gestational exposure to 

inorganic arsenic in CD1 mice is a complete carcinogen in the female offspring 

(Waalkes, et al., 2006). The CD1 mouse strain is noteworthy as having a well defined, 

low rate of spontaneous tumors. The Science Issue Paper should take note of this 

important development. 

Charge Question C1.B also asks the SAB to “...comment on whether the iAs 

epidemiology data can be used to inform the DMAV

 dose-response assessment derived 

from rat data with DMAV

. If so, please discuss how such information might be used.” 

(See Appendix A). 

The panel consensus was that without more detailed information on target tissue 

dosimetry of arsenic species the iAs epidemiology data would be of limited use to inform 

the DMAV dose-response assessment derived from rat data with DMAV. Direct exposure 

to iAs elicits a different cascade of metabolite concentrations with related differential 

kinetics compared to direct exposure to DMAV, therefore the iAs epidemiology data 

cannot reasonably be used to inform the DMAV dose-response assessment derived from 

rat data with DMAV. In the absence of specific information on target tissue levels, 

assumptions would have to be made regarding the proportion of the iAs for human and 

DMAV for rodents that reaches the bladder tissue as the toxic DMA species. 

In principle, epidemiology data from iAs exposed humans could be used to 

inform the DMA assessment to the extent that the data might be able to address the 

appropriateness of interspecies extrapolation, specifically the relative sensitivities of rat 

and human to bladder cancer following arsenic exposure. However, as noted above, in 

order to be useful some information on target tissue dose of DMA following human 

exposure to iAs and rodent exposure to DMAV would be necessary. With both in vivo 

tumor indices (human and rodent) expressed in terms of the same tissue dose of relevant 

metabolites, rather than iAs or DMAV exposure levels, the relative sensitivities of the 

human and rodent could be assessed. 

3.4.2. Use of human epidemiological data from direct iAs exposure 

(Charge Question C2) 

EPA’s Charge states that, “Since the NRC (2001) report on iAs, an additional 

body of literature has developed describing epidemiology data from populations in the 

36
U.S. exposed to iAs in drinking water” (USEPA, 2005a). Charge Question 2 asks, 

“Does the SAB agree that the Taiwanese dataset remains the most appropriate choice for 

estimating cancer risk in humans? Please discuss the rationale for your response.” 

For reasons noted below in this section, it is the Panel’s view that, at this time, the 

Taiwanese database remains the most appropriate choice for EPA’s use in deriving the 

cancer unit risk for iAs. However, the Panel suggests that EPA also conduct adjunct analyses 

to test the robustness of results against their assumptions, determine the impact of variability in 

some parameters, compare the results against those from other data sets, and provide a transparent 

assessment of the available epidemiological data using a consistent set of criteria. 

The Taiwanese dataset consists of population and mortality data from 42 villages 

in southwest Taiwan for the years 1973-1986. Arsenic levels in wells from these villages 

were measured in 1964-1966. The database is one of the largest that has been evaluated 

for cancer risk relative to arsenic exposures. A total of almost 900,000 person years of 

follow-up were included, with 1,152 cancer deaths (637 males, 515 females). Among the 

cancer deaths were 181 due to bladder cancer (85 males, 96 females), 268 lung cancer 

(147 males, 121 females), and several hundred due to other types of cancer. These data 

have been subject to several ecologic analyses, starting with the original publications by 

Chen et al. (1988) and Wu et al. (1989), followed by further analyses by Morales et al. 

(2000) and by the National Research Council (1999 and 2001). 

Among the 42 villages, the arsenic concentration ranged from 10 to 934 ppb 

(μg/L). Twenty of these 42 villages used a single well. Among many of the 22 villages 

with multiple wells, many had wide variability in the measured arsenic level in their 

wells. Analyses using the full dataset give results comparable to results from a reduced 

dataset including only the villages with single wells, providing some confidence in the 

stability of the overall results (National Research Council, 1999). The Panel recognizes 

the limitations of the southwest Taiwan database, including its ecologic character, lack of 

smoking information, limited precision of exposure estimates, especially among villages 

with multiple wells, and the possible issue of compromised nutrition among segments of 

the exposed population. However, 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 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. 

 Given the concerns regarding the use of the median well water concentrations in 

some of the 42 villages in southwest Taiwan that have more than a single measurement, 

the Panel recommends that EPA conduct a sensitivity analysis. This should include the 

range of exposures in said villages to provide a range of risk estimates. One alternative 

(suggested in response to D-3) is a full Monte Carlo analysis in which the individual well 

concentrations for 22 villages with multiple wells are taken into account. The Panel 

recognizes the difficulties with this approach including the issue of how to allocate cases 

to wells within villages. A simpler, but useful first approach would be to test the 

37
sensitivity of the model fitting when arsenic concentrations for multiple-well villages are 

set to: 1) a low level concentration from the range for the village (10th percentile, 20th 

percentile); 2) the median (current procedure); and 3) a high level concentration from the 

village range (90th percentile, 80th percentile). 

New studies have been published since the NRC report in 2001 and the Panel 

considered some of these (and additional information provided by the public during this 

review process) in its evaluation regarding the Taiwanese data sets that are the focus of 

this charge question. To be clear, the panel did not do an exhaustive review of all 

possible toxicologic and epidemiologic literature during its review. That was beyond the 

scope of the Panel’s charge. The Panel recognizes that this must be done in EPA’s final 

assessment and calls on the Agency to do so. 

In view of the limitations of this database, the Panel recommends that the other 

relevant epidemiologic databases from studies of arsenic-exposed populations be used to 

compare the unit risks at high exposure levels that emerge from the Taiwan data. Several 

of these studies had the advantage of data with excellent exposure assessment. In 

addition, some populations likely differed from the Taiwanese population with regard to 

their nutritional status. The accuracy and precision of exposure assessment is a major 

issue in all environmental epidemiologic studies, and in particular, in studies of arsenic in 

drinking water. Misclassification of exposure in such studies (when non-differential) can 

have a profound effect in attenuating the magnitude of the observed risk. The excellence 

of exposure assessment is an especially strong aspect of several studies from northern 

Chile, and the Panel recommends that the findings of Smith et al. (1998) and of Ferreccio 

et al. (2000) be included by EPA in evaluation of other datasets as described below. In 

addition, arsenic exposures appear to be well characterized in cohort studies of Chiou et 

al.(2001) of transitional cell carcinoma (mostly bladder cancers) and Chen et al. (2004) of 

lung cancer, from arsenic-exposed cohorts in southwest and northeast Taiwan. The latter 

study also provides data on the joint effects of arsenic and cigarette smoking in the 

Taiwanese population. 

The accuracy of estimated long-term exposures to arsenic is of concern for recent 

studies with water concentrations below 100 ppb. Misclassification of exposure may 

compromise their overall utility in assessing concordance with risk estimates obtained 

from the Taiwan study. The Panel suggests that results on bladder cancer risk from 

published epidemiology studies of U.S. and other populations chronically exposed to 

arsenic levels ranging from 0.5 to 160 μg/L inorganic arsenic in drinking water, be 

critically evaluated. A sensitivity analysis to evaluate the potential impact of sources of 

bias in the low level case control and cohort studies could be informative. Several 

arsenic epidemiology studies have the advantage of data with drinking water arsenic 

exposure levels ostensibly most relevant to the U.S. population [Bates, et al., 1995; 

Karagas et al., 2004; Lewis et al., 1999; Kurttio et al., 1999; Steinmaus, et al., 2003; 

Bates et al., 2004; Michaud et al., 2004; Chiou et al, 2001; Ferreccio et al., 2000]. Most 

of these populations have a nutritional and genetic background similar to that of the U.S. 

or the studies were conducted in a U.S. population. EPA should determine the potential 

utility of these studies in exploring overall concordance of the cancer risk estimates 

38
derived from their data with risk estimates obtained from extrapolation of the Taiwan 

data. The Panel suggests that if findings from a critical review of “low-level” studies 

indicate that some or all studies are potentially of value in further analyses, that results 

from these studies should be explored in secondary analyses, particularly on bladder 

cancer risk, and compared with the main analysis for concordance. Analyses integrating 

health outcome information from a number of epidemiology studies can result in 

improved statistical power and precision of the estimates; these factors represent an 

additional advantage of utilizing a larger dataset. 

When reviewing these “low-level” studies (and the “high level” studies as well), 

EPA should consider at least the following issues: 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 

risk estimates. Most populations in the U.S. and many other countries differ from the 

Taiwanese population of interest in genetic background (e.g., genetic polymorphisms), 

dietary intake, and background exposure concentrations to inorganic arsenic, and if one 

or more of these studies are shown to be of potential utility, comparative analyses of the 

U.S. and Taiwan data may lead to further insights into the possible influence of these 

differences on population responses to arsenic in drinking water. For compounds such as 

arsenic for which there are human data beyond the Taiwanese study on which human 

cancer risk has been based, data from the other investigations at high exposure levels 

(>150 μg/L) can be used to gauge the Taiwanese findings [Smith et al.(1998), Ferreccio 

et al.(2000), Chen et al.(2004), Chiou et al.(2001)]. 

All of these studies, including those from Taiwan, Chile, Argentina and the U.S. 

as described above, should be judged by the same set of criteria, with the comparative 

assessment of those criteria across studies clearly laid out in a tabular format. Some of 

the criteria have been listed in the previous paragraph. The relative strengths and 

weaknesses of each study need to 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. Included in the risk assessment background document should be a complete 

and transparent treatment of variability within and among studies and how it affects risk 

estimates. The present lack of transparency in the application of the criteria in the 

process of study selection was pointed out by several panel members. 

Charge Question C2 also asks, “Do these data provide adequate characterization 

of the impact of childhood exposure to iAs? Please discuss the rationale for your 

response.” 

The Taiwanese data are inadequate to characterize the impact of childhood 

exposure to inorganic arsenic with respect to carcinogenesis. That is, it is not clear 

whether children differ from adults with regard to their sensitivity to the carcinogenic 

effects of arsenic in drinking water. More data are needed to fully characterize the 

39
impact of transplacental exposures. However, data from the studies in southwestern 

Taiwan which include childhood exposures in the calculation of lifetime dose show that 

in the population under 30 years of age there were no bladder cancer cases, and only 5 

lung cancer cases but few cases are actually expected in that age group. Childhood 

exposures are included in the lifetime dose estimates. Smith et al (1998) report the 

highest excessive risk for male lung cancer in the 30-39 year old age group, suggesting 

the importance of childhood exposure and risk and perhaps smoking behavior as young 

adults. For 533 women exposed to arsenic in drinking water from tube wells at greater 

than 50 μg/L compared with those exposed at 50μg/L or less, findings suggest that there 

are significantly increased odds ratios for spontaneous abortion, stillbirth and neonatal 

death (Milton et al., 2005). Another reproductive study in Chile, which followed over 

800 pregnancies, found that pregnant women drinking water containing 40 μg/L gave 

birth to infants of lower birth weight than a comparable group drinking water containing 

very low arsenic concentrations (<1 μg/L) (Hopenhayn et al, 2003). Thus maternal 

exposure at moderately high levels may have toxic effects; the issue of childhood 

carcinogenic susceptibility has had only limited study. 

3.5 Approaches to Low-Dose Extrapolation for Inorganic Arsenic and DMAV 

3.5.1 Mode of carcinogenic action understanding for DMAV/III and 

implications for dose-response extrapolation to estimate human 

cancer risk (Charge Question D1) 

EPA’s Charge stated that, “The use of mode of action data in the assessment of 

potential carcinogens is a main focus of EPA’s 2005 cancer guidelines. As stated in 

th[o]se guidelines ‘The approach to dose-response assessment for a particular agent is 

based on the conclusion reached as to its potential mode(s) of action.’ Although a 

biologically-based model is the preferred approach to estimating cancer risk, there are 

insufficient data on DMAV to support development of such a model.” Charge Question 

D1 asks the SAB to “...comment on the scientific evidence and biological rationale in 

support of nonlinear versus linear low dose extrapolation approaches, which approach is 

more consistent with the available data on DMAV

 and current concepts of chemical 

carcinogenesis, and how scientific uncertainty should most appropriately be 

incorporated into low-dose extrapolation.” 

3.5.1.1 Please comment on the scientific evidence and biological 

rationale in support of the nonlinear versus linear low dose 

extrapolation approaches 

The Panel believes, based on the review of EPA’s analyses, that there are 

adequate data to support much of the EPA-postulated MOA for bladder carcinogenesis 

induced by high doses of DMAV in the rat. The MOA involves cytotoxicity of the bladder 

epithelium and increased, sustained regenerative proliferation, as key events. However, 

the Panel concluded that there are insufficient data to invoke ROS-induced DNA damage 

as a key event in the carcinogenic process, associated with exposures to DMAV or 

DMAIII (see Charge Question B1). 

40
The postulated MOA for DMAV is: 

a) Reductive metabolism of DMAV to DMAIII. 

b) High concentrations of DMAIII in urine cause urothelial cytotoxicity. Some 

toxicity may also be caused by DMAV itself. 

c) Continuous exposure and persistent, stress associated, regenerative cell 

proliferation leads to genomic instability, acquisition of genetic alterations, 

clonal expansion of altered cells and eventually tumors. 

Neither the MOA postulated here, nor those postulated by ORD or OPP (USEPA 

OPP, 2005; USEPA ORD, 2005), contain key events expected to be a linear function of 

dose. Reductive metabolism of DMAV is likely to be saturable and therefore non-linear 

but this does not necessarily imply a threshold-based response. In vitro cytotoxicity of 

uroepithelial cells, using rat (MYP3) and human (1T1) bladder cell lines, occurs only at 

concentrations greater than ~0.35 μM (rat, 0.38 μM DMAIII; human 1T1 0.35 μM 

DMAIII) (unpublished data1

). In vivo, cytotoxicity of the uroepithelium occurred at the 

lowest tested dietary DMAV concentration (2 ppm), but the incidence and severity 

increased, and the latency decreased significantly as a function of dose. Statistically 

significant increases in regenerative cell proliferation only occur in rats at DMAV dietary 

concentrations greater than 40 ppm, again, a nonlinear or apparent threshold response. 

Even ROS production, and its interaction with DNA, would be expected to be 

linear at some low dose, but nonlinear across the larger dose range. Formation of 

heritable alterations in DNA by ROS is believed to be a nonlinear or curvilinear effect 

(USEPA ORD, 2005) best represented by a quadratic function with a low-dose linear 

component (USEPA OPP, 2005). The formation rate of heritable alterations is a function 

of the rate of DNA damage and the rates the various DNA repair processes and finally the 

rate of DNA misreplication (USEPA OPP, 2005). The latter being a function of 

cytotoxicity and regenerative cell proliferation which in the case of DMAV, are also 

highly nonlinear functions of dose (USEPA ORD, 2005). With respect to repair of 

postulated ROS induced DNA damage, highly specific enzymatic systems that exist for 

1

 Personal communication from L. Arnold of Dr. Cohen’s Lab with the EPA SAB Designated Federal 

Officer; 4.4.2006. Samuel M. Cohen, M.D., Ph.D. Professor and Chair, Pathology and Microbiology 

Havlik-Wall Professor of Oncology University of Nebraska Medical Center, Text of the email is provided 

below: “During the process of determining the LC50 for the various arsenicals we did develop some data 

concerning the no effect level especially in the MYP3 rat bladder cell line. We do not have as much data 

for the 1T1 human bladder cell line since we used concentrations that we had already determined caused 

cytotoxicity in the MYP3 cell line. We do have detailed data for DMAIII for both cell lines since there was 

a very sharp drop between concentrations which had no effect on the cell viability and concentrations 

which were cytotoxic. In the MYP3 rat bladder cell line, DMAIII concentrations of 0.38 μM and below had 

no effect on the viability of MYP3 cells but at a concentration of 0.39 μM DMAIII the cell viability dropped 

to 69%. In the 1T1 human bladder cell line, DMAIII concentrations of 0.35 μM and below had no effect on 

viability but at 0.40 μM the viability dropped to 76%. The following data show doses for other arsenicals 

at which there was no effect on cell viability however, the no effect dose may be somewhat higher but we 

do not have enough data points to determine an exact concentration. 

MYP3 rat bladder cell line: 

 Arsenite-0.05 μM; Arsenate-1 μM; MMAIII-0.5μM; MMAV-1mM; DMAV-0.05mM; 

 TMAO-0.1mM 

41
their repair (Slupphaug et al., 2003) protect the genome, whether from exogenous 

chemicals or the high levels of endogenous ROS induced DNA damage. These 

enzymatic repair processes are expected to be nonlinear processes. EPA’s position on a 

linear oxidative stress MOA induced by DMAV is likely not defensible and should not be 

used. The state of the science is overwhelmingly in favor of a nonlinear approach for the 

risk assessment of DMAV. In summary, the Panel’s opinion is that the available data 

support the nonlinear approach for the low dose extrapolation of DMAV. 

The linear approach would be consistent with evidence for direct genotoxicity of 

DMAIII/V. There are no compelling data demonstrating that DMAIII/V are directly 

genotoxic. It is generally accepted that DMAV is not directly genotoxic (not DNA 

reactive). This conclusion is well supported by the data presented in the Science Issue 

Paper: Model of Carcinogenic Action for Cacodylic Acid (Dimethylarsinic Acid, DMAV

) 

and Recommendations for Dose Response Extrapolation, and in section 3.3.1 of this 

report. 

3.5.1.2 Charge Question D1 further asks the SAB, “Which 

approach is more consistent with the available data on DMAV 

and current concepts of chemical carcinogenesis,” 

The non-linear approach is more consistent with the available data and current concepts of 

chemical carcinogenesis (see section 3.5.1.1, above). 

3.5.1.3 Charge Question D1 asks the SAB, “How [should] 

scientific uncertainty most appropriately be incorporated into 

low-dose extrapolation?” 

After some discussion, the Panel viewed this question from the perspective of the 

EPA’s RfC guidelines (USEPA, 1994). Similar guidelines for the derivation of chemical 

specific uncertainty factors have been developed by the International Program for 

Chemical Safety (IPCS 2001). These guidelines provide an approach for incorporating 

uncertainty into risk assessments in the form of uncertainty factors. Uncertainties in the 

interspecies extrapolation of the rat dose-response data can be broadly grouped into a) 

those related to interspecies differences in pharmacokinetics, b) those related to 

interspecies differences in pharmacodynamics, and c) those associated with sensitive 

populations such as children and the elderly. The default value for interspecies 

differences in pharmacokinetics is 3, the default for interspecies differences in 

pharmacodynamics is 3, and the default for sensitive populations is 10, made up of two 

factors of 3 each, one for pharmacokinetic differences and one for pharmacodynamic 

differences. 

While it was the opinion of the Panel that rats might deliver a higher dose of the 

proximate toxicant, DMAIII to the bladder for a given dose of DMAV than humans, the 

Panel recognized that there was insufficient data on the comparative dosimetry in rats and 

humans to make any conclusive statements about species differences in 

pharmacokinetics. The possible role of microbial demethylation in humans is another 

42
potential issue for consideration. Therefore, the uncertainty factor for interspecies 

differences in pharmacokinetics should be 3, the default value. However, there appears to 

be emerging data on DMAV kinetics which might be brought to bear on the question and 

the agency is encouraged to consider these data with respect to pharmacokinetic 

differences between the species and the characterization of this component of uncertainty 

in the dose response assessment. 

As a result of the Panel’s analysis of the data for the key pharmacodynamic 

response, uroepithelial cell cytotoxicity, the consensus was the EPA could assemble a 

case for pharmacodynamic equivalency between the test species, rats, and humans from 

existing experimental data. Cohen et al. showed LC50s of 0.5 and 0.8 μM DMAIII for rat 

and human bladder epithelial cells lines (Cohen, 2002). In the context of EPA and 

International Program on Chemical Safety (IPCS) guidelines, this finding could be 

incorporated in the assessment as a reduction of the pharmacodynamic component of the 

interspecies uncertainty factor (typically a default value of 3), to a value of one. 

However, this suggestion is based upon limited comparative in vitro data. The 

application of uncertainty factors has also been addressed in the Panel’s response to 

question C1. There is presently no arsenic-specific information that can inform the choice 

of uncertainty factors for sensitive human populations. For now, the choice of these 

factors must be based on more general considerations, including EPA’s science policy 

judgment of the degree of precaution that it deems appropriate. 

3.5.2 Implementation of the recommendations of the NRC (2001)(Charge 

Question D2) 

EPA believes that the most prudent approach for modeling cancer risk from 

exposure to iAs is to use a linear model because there are significant remaining 

uncertainties regarding which of the metabolite(s) may be the ultimate carcinogenic 

moiety and whether or not mixtures of toxic metabolites interact at the site(s) of action” 

(USEPA, 2005A). EPA asked if the SAB concurs, for now, with the selection of a linear 

model to estimate cancer risk for inorganic arsenic [i.e., following the recommendations 

of the NRC (2001)]. EPA also asked that the SAB discuss its response in light of the 

highly complex mode of action for iAs. 

The Panel recognizes the potential for a highly complex mode of action of iAs 

and its metabolites, and until more is learned about the complex PK and PD properties of 

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

nonlinear form of the dose-response relationship. Therefore, based on information in this 

section and on the Panel’s understanding of the EPA’s 2005 Guidelines for Cancer Risk 

Assessment, the final recommendation of NRC (2001) to base current risk assessments 

on a linear dose response model that includes the SW Taiwan population as a comparison 

group, seems to be the most appropriate approach. Below, the Panel suggests that EPA 

conduct sensitivity analyses to address uncertainties in this issue. 

Existing epidemiologic studies have been mentioned in the response to charge 

question C2. These studies of different populations across different countries seem to 

43
support a possible linear dose-response between exposure from drinking water and 

internal cancer risks (particularly in Taiwan, Chile and Argentina). These dose-response 

relationships are observed at higher exposure levels (>100 ppb). The Panel believes that 

because of limitations in the epidemiologic studies conducted to date, that adequate 

human data at the lower range of iAs exposure is lacking. 

Some recent studies have included populations with exposures in the lower range 

(<100 ppb), but they tend to be problematic for use in dose-response analysis for lower 

exposure levels. In particular, when studies are based almost exclusively on low dose 

exposure populations (Lamm et al, 2004; Bates et al, 2003; Steinmaus et al, 2003), they 

lack statistical power and the estimations of low dose risk tend to be unstable and to have 

a high degree of uncertainty. Some of these studies also have problems related to study 

design. For example, in the Lamm et al. (2004) ecological study, exposure assessment is 

highly problematic given that a single median county-level exposure value is assigned to 

all the person-years contributed by each county in the analysis, even though it is not clear 

that these are the arsenic exposure values for a large number of residents within each 

county. A recent follow-up of the Taiwanese cohort reports a monotonic trend in lung 

cancer risk for exposure to arsenic levels ranging from <10 to 700 μg/L, however this 

study also has limited power to examine the form of the dose-response relationship 

within the 10-100 μg/L range (Chen et al 2004). There are no human data available that 

is adequate to characterize the shape of the dose response curve below a given point of 

departure. 

At present the experimental evidence on mode of action of inorganic arsenic 

supports a possible nonlinear dose-response at low exposure levels yet there is no clear 

indication of what shape a nonlinear dose-response would take for application to human 

cancer risks at low exposures (<50 or <100 ppb). In examining the dose-response 

relationships of arsenicals in inducing direct or indirect mutagenic responses (including 

effects thought to be clastogenic in nature), it is clear that effects are only seen at doses 

that induce cytotoxicity. This implies a threshold (Rossman, T.G. 2003). Until more is 

learned about the complex properties and MOAs of iAs and its metabolites there is 

insufficient justification for the choice of a specific nonlinear form of the dose-response 

relationship. Under these circumstances, the EPA’s 2005 Guidelines for Cancer Risk 

Assessment are clear that linear extrapolation below the point of departure is the method 

to be used. 

Although the EPA has chosen a linear model for the arsenic dose component of 

the hazard model for lung and bladder cancer, the Panel encourages the Agency to test 

the sensitivity of the assumption of linearity by comparing its corresponding estimate of 

excess life risk to an alternative hazard model that has a dose contribution that is 

multiplicative and nonlinear in form (see question D3 for additional information). 

In summary, the Panel recognizes the potential for a highly complex mode of 

action of iAs and its metabolites, but 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. Based on this and the EPA’s 

44
2005 Guidelines for Cancer Risk Assessment, the final recommendation of NRC (2001) 

to base current risk assessments on a linear dose response model that includes the 

southwest Taiwan population as a comparison group seems the most appropriate 

approach. However, the Panel also recommends performing a sensitivity analysis with 

different exposure metrics with the subgroup of villages with more than one well 

measurement (as discussed in responses to charge questions C2 and D3) and using a 

multiplicative model that includes a quadratic term for dose, as performed by NRC 

(2001) and as discussed in charge question D3. 

3.5.3 EPA Model Re-Implementation (Charge Question D3) 

The Charge states that, “EPA re-implemented the model presented in the NRC 

(2001) in the language R as well as in an Excel spreadsheet format. In addition, 

extensive testing of the resulting code was conducted” (USEPA, 2005a). Charge 

Question D3 asks the SAB to “... comment upon precision and accuracy of the reimplementation of the model.” 

Question D3 suggests that the estimation of the dose-response model and the 

hazard assessment were originally programmed in the R language. Page 63 of the issue 

paper indicates that the Poisson hazard model was originally estimated in the R language 

(optim routine) but neither the main text of the paper nor its appendices provided any 

additional information. A clarifying question from the panel through the Designated 

Federal Officer provided clarifying information, stating that: 

“The reference to the implementation in R in question D.3 is outdated, and should 

have been removed. This was an oversight on EPA's part. The model 

implementation in Excel is our implementation of record, and was used to prepare 

the results in the draft toxicological review. We would ask the Panel to please 

review and comment only on the implementation in Excel. (Background: EPA 

did originally implement its model in R. However we found that version to be not 

very transparent, and hard to debug. We then re-implemented the model in Excel, 

found and corrected some errors, and used that corrected version to prepare the 

tox review. While Excel may not be the best choice from the standpoint of 

numerical accuracy, it is greatly superior in the transparency of the 

implementation, and is powerful enough to perform the entire model calculation 

from start to finish, even including the nonlinear optimization. Once the Panel is 

satisfied that the implementation in Excel is correct and appropriate, then the 

model can be re-implemented in R or some other numerically superior 

language.)” 

The Agency staff is to be commended for deciding to test its original R-language 

version of the model program through a separate implementation in Excel. The Excel 

version serves as a check of programming performed in alternative systems (e.g. R, S) 

and provides transparency for review by non-specialists. For the calculations required in 

this model of hazard and excess risk, the Excel computations should provide sufficient 

numerical accuracy. If the EPA returns to another model program, it should begin with 

45
the original model formulas and not simply transcribe the programming from the existing 

Excel version of the model. As a debugging and error-checking tool, comparisons of 

intermediate results from the two model implementations should be performed to verify 

the equivalence of the two model systems. 

Overview of the EXCEL spreadsheet implementation of the model: The Excel 

model implementation is described in Appendix B (pages 105-106) of the Issue Paper. 

The Issue Paper (page 65) referenced a URL, www.epa.gov/waterscience.sab; however 

this proved to be not available. EPA staff notified the panel of the correct address, 

http://epa.gov/waterscience/sab/. The Issue Paper suggests that a listing of the variable 

and parameter input field is provided in Table B-3 but the current draft of the Issue Paper 

did not include this table. (The fields in the spreadsheet model were interpreted by the 

Panel based on the description provided in the text of the Issue Paper and general 

understanding of the model fitting procedure employed.) 

The spreadsheet model requires two Excel files and associated macros. The first 

of these is MCCancerfit.XLS. This workbook component of the model consists of eight 

worksheets in four pairs (e.g. fblad and MC fblad for female bladder cancer) that cover 

the two cancers of interest (lung and bladder) and gender (male, female). The initial 

worksheet (e.g. fblad) in each of the four cancer/gender pairs contains the input data for 

fitting the hazard model. The first step in the model fitting algorithm is to employ the 

Excel Solver to find initial values of a1, a2, a3 and β (Cells G2:G5) that maximize the 

Poisson likelihood under the following model: 

2 λ , = exp(a + a2 ⋅ age + a3 ⋅ age ) ⋅(1+ β ⋅ dose) i dose 1 i i 

where :

age = the midpoint of a five-year age range, e.g. 22.5 for 20-24; i 

dose = the arsenic dose in ppb. 

This is the model described by the EPA in the Issue Paper and is one of two models that 

appeared to provide best fit to the data based on the Akaike Information Criterion (NRC, 

2001). 

The second worksheet in each the four disease/gender pairs (e.g. MC fblad) is 

used in conjunction with the initial starting values, generated by Solver and stored in Cell 

N2, to simulate the empirical Bayes posterior distribution of the model parameters based 

on a set of 1000 random perturbations of the coefficient vector (a1,a2,a3, β) about the 

maximum likelihood estimates produced by Solver. The perturbation involves 

independent, random (uniform) dispersion of the coefficient estimates in a relative range 

of +/- 10% about the point estimates generated by Solver. Parameter draws outside this 

range are not performed since the posterior likelihood takes on a near zero value outside 

the boundaries +/- 10% of MLE. The corresponding macro (e.g. mcfblad) is then 

invoked to apply the observed data and these perturbed coefficient values to establish the 

value of the posterior log-likelihood for each of the 1000 draws. The empirical Bayes 

46
estimate of the slope parameter and its lower confidence limit are then estimated based on 

the mean and standard deviation of the simulated posterior distribution: 

1000 

∑bj ⋅ Lj 

b = j=1 Lmax

1000

∑ Lj 

j =1 Lmax 

⎧ 1000 ⎡ Lj 2

⎪1000 j =1 ⎣ Lmax 

⋅(bj − b ) ⎪ ∑ ⎢ ⎥ ⎪

⎤ ⎫

sd b () = sqrt ⎨ ⋅ ⎬

⎦ ⎪

1000 ⎪ 999 ∑ Lj ⎪ ⎪ j =1 Lmax ⎪ ⎩ ⎭

and , 

UCL b b () = + 2 ⋅sd b ( )

The estimated UCL(b) is then carried forward to the BEIR.IV computation of the 

excess lifetime risk in the BEIR.xls spreadsheet. 

Based on its review, the Panel noted that for the given data inputs, the empirical 

Bayes estimation algorithm programmed in the MCCancerFit.xls spreadsheet does match 

the form of the model and the general description of the parameter fitting algorithm 

outlined in the Issue Paper. 

As described in the Issue Paper, the EPA data inputs for at risk populations and 

cancer deaths agree with Morales, et al. (2000). In general, the panel recommends that 

all tables of inputs for these models be published in appendices to the Issue Paper or final 

risk assessment so that reviewers can independently reference and verify the critical 

inputs to the hazard and excess risk analysis. 

The MCCancerft.xls spreadsheet includes an adjustment of 50 μg/day of arsenic 

from food intake. Based on the formula provided on page 103 of the Issue Paper, the 

current model assumes a combined daily intake of 2 liters/day of cooking and drinking 

water. The Issue Paper suggests that the current analysis uses 30 μg/day. Although the 

Issue Paper notes the NRC (2001) finding that dietary intake had no significant effect on 

the estimated cancer slope factor, the apparent discrepancy between the value of 30 

μg/day cited in the Issue Paper and the 50 μg/day value used in the spreadsheet model 

should be resolved. The model does not allocate a food input of arsenic to the control 

population. This is a decision that presumes food-based intake of arsenic originates from 

cooking water only. 

The second Excel workbook in the risk assessment model employs estimates of 

the dose response model parameter, β, and its upper bound to evaluate excess lifetime 

risk under the BEIR-IV formula. The BEIR.xls workbook includes four worksheets, one 

47
for each cancer type by gender combination ( flung, mlung, fblad, mblad). The estimates 

of the linear dose response parameter and its estimated 95% UCL (see above) are 

manually pasted from the corresponding worksheet in MCCancerFit.xls. The excess risk 

is computed in cell T15. Solver can be applied to the dose value in Cell T11 (not U10 as 

indicated on Page 105 in the Issue Paper) to establish the dose level required to produce a 

user-specified values of excess risk (i.e., ED01). 

The columns of each worksheet in the BEIR.xls spreadsheet incorporate data for a 

specific age range of the U.S. population. These columns are not labeled with the 

corresponding age range. Identifying labels should be applied to all rows and columns in 

these worksheets. By deduction, column 3 applies to individuals age 20-24, column 4 to 

age 25-29, etc. If this is correct, the Panel recommends that the entry in cell B3 of each 

of the four BEIR.xls spreadsheets be verified. It appears that this mortality figure may 

apply to more than just the 20-24 year old population represented in Column 3. Referring 

to the data inputs for 20-24 year olds in the flung spreadsheet in BEIR.xls, the population 

value is 9,423,000, all deaths are 18,121 and the baseline hazard is .00192. Moving over 

one column to the 25-29 year olds, the population is nearly the same at 9,491,000, all 

deaths are 1580 and the baseline hazard is .00017—less than 1/10th that for the previous 

five year age group. 

The BEIR.xls spreadsheet implementation of the BEIR-IV excess risk calculation 

includes a 3-fold divisor to transform the risk to a U.S. population base (assuming 

exposure per kg is 3-fold higher in the SW Taiwanese population). This scaling occurs in 

the calculation of the age-specific cancer hazard (Row 11). It should be documented and 

also should be a target for future sensitivity studies. Since this is a model parameter it 

should identified as a distinct input on the spreadsheet instead of simply embedded in the 

calculations. 

The notation for the BEIR-IV formula on Page 102 in the Issue Paper does not 

distinguish between total survivorship (Si) and survivorship adjusted for the added risk of 

cancer. However, the spreadsheet implementation of the model decomposes survival into 

the product of baseline survival and a survival factor that reflects excess cancer deaths 

due to the prior age group’s exposure to arsenic. Based on a version of the spreadsheet 

downloaded from the Office of Water website, calculation of cancer-specific survival 

(Row 13) appears to incorporate mortality through age interval I, not interval I-1 as it 

should. This should be checked. The calculation of baseline survival appears to be 

correct – the survival parameter at age interval I includes only mortality through the end 

of time period I-1. With this exception, calculation of Excess Risk follows the BEIR IV 

formula. 

Following the series of checks and corrections to the model listed above, the 

Panel encourages the Agency to extend its testing of the model sensitivity to alternative 

models forms and model assumptions. Specific areas where the Panel felt additional 

sensitivity testing is warranted include: 

48
a) A Monte Carlo analysis in which the individual well concentrations for 22 

villages with multiple wells are taken into account. The Panel recognizes the 

difficulties with this approach including the issue of how to allocate cases to 

wells within villages. 

b) MCCancerFit.xls: 

a. A test of the sensitivity of the model to the choice of the reference 

population (SW Taiwan). 

b. A test of the sensitivity of model results to the assumption that the 

reference population has 0 intake of arsenic via food. 

c. A contrast of results for the linear dose model employed in this program 

to alternative hazard models that are multiplicative and nonlinear in 

form. For example, the following multiplicative, quadratic model is one 

of several that NRC(2001) found to have best fit to the data based on the 

Akaike Information Criterion (AIC): 

2 2 λ , = exp( a + a2 ⋅ age + a3 ⋅ age ) ⋅ exp( β + β ⋅ dose + β ⋅ dose ) iC 1 i i 0 1 2 

c) BEIR.xls 

a. The Panel recommends a sensitivity analysis be conducted to 

investigate the effect of the age groupings used to estimate the baseline 

hazard and excess lifetime risk. In addition to the current practice of 

using 5-year intervals (e.g. 20-24, 25-29, etc.), a logical choice is to 

test the sensitivity of the model results to using 10-year groupings (e.g. 

20-29, 30-39...). 

b. The exposure/kg parameter used to transfer the dose/response model 

from the original SW Taiwanese population to a U.S. general 

population is a major driver in the computation of excess lifetime risk. 

In preparing its final risk assessment, the EPA should conduct a 

sensitivity analysis to determine precisely how much the choice of a 

factor of 3 impacts the final estimates of excess lifetime risk. 

3.5.4 Available literature describing drinking water consumption 

rates for the Southwestern Taiwanese study population (Charge 

Question D4) 

EPA, as well as the NRC (2001) state that the drinking water consumption rate, as 

well as variability of that rate in both U.S. and Taiwanese populations, are important 

factors to consider. EPA notes that in calculating risk estimates for U.S. populations 

exposed to arsenic through drinking water, NRC used a drinking water consumption rate 

of 1 L/day for the U.S. population and two possible consumption rates for the Taiwanese 

population: 1 L/day (identical to the U.S. population) and 2.2 L/day with little or no 

supporting rationale. Since publication of NRC 2001, a number of new studies have 

become available and are summarized in the Cancer Slope Factor Workgroup Issue 

Paper. Agency reviews of the relevant literature suggest that the mean drinking water 

49
(for the Taiwanese study population) consumption rate is between 1 to 4.6 L/day. EPA’s 

current cancer modeling includes water intake adjustments for 2.0 and 3.5 L/day” 

(USEPA, 2005a). Charge Question D4 asks what drinking water value the panel 

recommended for use in deriving the cancer slope factor for inorganic arsenic? 

The Panel agrees that assumptions about water consumption levels in the U.S. and 

in Taiwan have a substantial impact on the risk assessment. Relative to U.S. 

consumption, overestimating water consumption in Taiwan decreases potency estimates 

and underestimating consumption increases potency estimates. Evidence for gender 

differences in consumption is limited, but considerable within-population variability in 

consumption occurs (NRC, 2001). EPA should evaluate the impact of drinking water 

consumption rates associated with more highly exposed population groups with 

potentially different exposures and susceptibilities (e.g., children, pregnant women) in its 

arsenic exposure estimates as the Agency determines the overall affects of drinking water 

consumption rates on arsenic risk. 

U.S. water consumption data are obtained from comprehensive U.S. surveys 

including surveys by the U.S. Department of Agriculture (USDA) and as part of the 

National Health and Nutrition Examination Survey (NHANES) (as cited in USEPA, 

2005), among others. These studies provide information on tap water consumption as 

well as water consumption attributable to other beverage consumption and consumption 

of food prepared with water containing arsenic. Estimates of mean daily drinking water 

consumption and total water consumption (including water used in food preparation) 

range from 1.0 to 2.8 L/day and from 1.2 to 3.2 L/day respectively. 

In comparison, information on water-consumption in Taiwan derives from a small 

study by Yang and Blackwell and an EPA informal, anecdotal assessment (as cited in 

USEPA, 2005) that include only information on drinking water consumption. 

Information on water consumption in South Asia, another world region with high arsenic 

levels in the water supply, is available from a large population based survey in India 

(Chowdhury et al., 2001 cited in EPA 2005) and a small study from Bangladesh 

(Watanabe et al., 2004). The South Asian studies include information on water 

consumption associated with food preparation. Although similar in socioeconomic 

characteristics, the diet and climate differ in Taiwan and South Asia, with temperatures 

higher in South Asia. These studies report mean daily drinking water intake of 1 to 3.5 L, 

with an additional 1 L associated with food preparation. 

The Panel recommends that: 

a) EPA incorporate variability parameters for individual water consumption into 

their analysis for the Taiwanese population as they have done for the U.S. 

population estimates as NRC recommended; 

b) Because assumptions about water consumption are an important source of 

variability in the risk estimates, EPA should conduct sensitivity analyses of 

the impact of using a range of consumption values for the Taiwanese 

population. 

50
c) Because data on gender differences in consumption in Taiwan are limited, a 

better justification for assuming different consumption levels by gender is 

needed, particularly given the lack of sex difference in consumption in U.S. 

and observed in studies from other countries (Watanabe et al., 2004). In the 

absence of such a justification, the panel recommends an additional sensitivity 

analysis to examine the impact of equalizing the gender-specific consumption 

level. 

d) The source of data for intake from other beverages and cooking water needs to 

be more fully discussed and documented. Specifically, the document should 

more clearly articulate how different sources of water intake are incorporated 

into the risk model including beverages other than water (e.g. green tea) and 

water used in food preparation. Clarification of both the assumed 

consumption level and how water consumption and consumption variability is 

introduced within the model is needed. 

3.5.5 Selection of an estimate of dietary intake of arsenic from food 

(Charge Question D5) 

EPA stated that, “The issue of intake of arsenic from food (e.g., dry rice, sweet 

potatoes) has been distinguished from the issue of intake of arsenic from drinking water. 

The NRC addressed the issue of arsenic in food by determining how sensitive the 

calculation of ED01 was to the consumption rate. NRC found that changing the 

consumption rate from 50 μg/day to 30 μg/day did not change the calculated ED01 

significantly (about 1% difference). Since the publication of NRC 2001, a number of 

new studies have become available, summarized in the Cancer Slope Factor Workgroup 

Issue Paper. EPA’s current cancer modeling includes dietary intake adjustments for 0, 

10, 30, and 50 μg/day” (USEPA, 2005a).” Charge Question D5 asks the SAB”... what 

background dietary arsenic intake value it recommends for both the control population 

and study population of Southwestern Taiwan (which is used in deriving the cancer slope 

factor for inorganic arsenic?)” 

The Panel did not recommend a specific value for EPA to use; however, it did 

recommend a sensitivity analysis to assess the impact of a range of dietary intakes on risk 

from lung and bladder cancer risk associated with arsenic in drinking water used by this 

population (e.g. 50 to as high as 200 μg/day). The Panel stated that an intake of zero 

arsenic from food should not be assumed. 

Three studies that summarize daily arsenic consumption as derived from food in 

areas of high arsenic intake are listed in Table 4 (USEPA OPP, 2005). Based on the 

NRC’s recommendations, EPA used a range of 30-50 μg per day total arsenic intake from 

dry rice (uncooked) and dried yams in the diet of southeastern Taiwan that also was 

based on the work of Schoof et al. (1998) as listed in this table. In materials presented 

and submitted to the Panel (Schoof, 2005), Dr. Schoof, stated her belief that the field had 

not been recently treated given the levels she found (7 to 8 ppm) but that seasonality and 

recent application of arsenicals should influence the levels of arsenic found in the field 

51
and in plants grown on those fields. Thus the Schoof et al. (1998) data cited in Table 4 

may underestimate the dietary arsenic intake from food in this population. 

In the following paragraphs, the term total arsenic indicates the sum of all 

inorganic and organic arsenic species. The term inorganic arsenic as stated in published 

literature on analysis of arsenic in food generally refers to the sum of the inorganic 

arsenic species (iAs III and iAsV). Unless specifically stated otherwise, the term organic 

arsenic indicates total organic arsenic compounds in food. In reference to seafood, 

arsenobetaine is generally the major organic arsenic compound present when organic 

arsenic compounds are specifically identified in the analysis; other minor organic 

arsenicals may also be present. The methylated arsenic metabolites (MMAIII MMAV, 

DMAIII, DMAV) are organic arsenic compounds, however, they are not generally 

determined in food. 

Daily intake of arsenic from food observed by Chowdhury et al. (2001) and 

Watanabe et al., (2004) suggest total arsenic intakes ranging from a mean of 120 to 285 

μg/day from food in Bangladeshi and Indian populations exposed to high levels of 

naturally occurring arsenic. Mean total arsenic intakes for males were shown to be 214 

μg /day and for females 120 μg /day (Watanabe et al., 2004). In studies conducted in 

West Bengal in which both chemical analysis of food items and interviews for food 

intake were conducted to assess exposure, Roychowdhury et al., (2002) show daily 

dietary intakes from food for adults (based on 34 families in 5 villages) ranging from 

171-189 μg/day and for children of about 10 years ranging from 91-101 μg/day. These 

figures are ranges of means for two different geographic areas – standard deviations were 

not published. Although these data are not derived specifically from the area of Taiwan 

studied, they indicate along with ancillary information presented here and elsewhere that 

dietary exposure from food in this geographic area may be higher than previously 

thought. Raw rice, a staple of the area, has been shown in other studies to contain among 

the highest iAs values in food (Schoof, et al., 1999) while for vegetables approximately 

95% of total arsenic is organic arsenic (Chowdhury et al., 2001). Variation in arsenic 

concentration and speciation occurs relative to rice cultivar (Williams et al., 2005). 

Duxbury et al. (2003) estimates that 30-85% of arsenic in rice is inorganic arsenic. 

Diet is the largest source of total arsenic exposure in the U.S. relative to water and 

air exposures. Average intake is about 40 μg/day total arsenic (ATSDR, 2006) compared 

with the approximately five-fold higher total dietary arsenic intake observed in Asian 

studies cited in the foregoing paragraph. The estimated range of daily intake of total 

arsenic from food in the U.S. is reported at 2-92 μg/day (Tao and Bolger, 1999) while 

U.S. daily total intake of iAs at the 10th and 90th percentiles is estimated to be 1.8 to 11.4 

μg/day for males and 1.3 to 9.4 μg/day for females (Meacher, et al, 2002). The U.S. 

dietary intake of inorganic arsenic is estimated to range from 1 to 20 μg/day (ATSDR, 

2006). U.S. shellfish and other marine foods contain the highest total arsenic 

concentrations and are the largest dietary source (76% - 96%) of arsenic, however, most 

of the arsenic in seafood is present as the organic arsenic compound arsenobetaine, which 

is excreted rapidly and unchanged and does not appear to be harmful to humans 

(ATSDR, 2006). It is known, however, that fish may contain some portion of iAs further 

52
pointing to the need for the sensitivity analysis described below. Certain seafood may 

also contain DMA that may also contribute to background exposure from food relative to 

water sources (Huang, et al., 2003). 

It is clear that the adjustment for background iAs intake from food is extremely 

important given that the total exposure dose from all sources does likely matter in terms 

of toxicity and cancer induction and that the U.S. population likely has a considerably 

lower total arsenic intake from food than do populations in Asia. 

The Panel recommends that a range of values from at least 50 to 100 μg/day and 

up to perhaps as high as 200 μg/day be run in a sensitivity analysis to assess the impact of 

this range of dietary intakes on risk of lung and bladder cancer from exposure via 

drinking water in this population. The cancer risk model needs to be evaluated using a 

wider range of iAs food values above 50 μg/day to determine if there is a change in the 

arsenic cancer exposure-response slope as a result. It also cannot be assumed that the 

control population has an intake of zero arsenic from food. 

Such a sensitivity analysis of the impact of dietary arsenic uptake using a range of 

data from high arsenic-exposed populations is unlikely to introduce larger uncertainty 

than the myriad dietary differences – protein deficiency, Se, Zn, folate deficiency etc. – 

between this Taiwanese population and the U.S. population 

Much greater rigor needs to be applied in discussing and presenting documented 

data sources and making clear the basis on which assumptions are being made and the 

relative strength of those assumptions. Comparisons of the impact of differing levels of 

iAs intake from food between the exposed and reference population need to be made on 

the basis of comparative relative risk. Clearer statements are needed on the data 

limitations of past daily dietary arsenic intake for the Blackfoot endemic area of Taiwan 

and for the reference population(s). 

EPA needs to be aware of and include a discussion of methodological and 

analytical issues related to reported arsenic concentrations in food, because these values 

are dependent upon differential extraction processes and analytical procedures applied by 

diverse laboratories on a variety of food stuffs. Only the arsenic extracted from food can 

be measured. More importantly, laboratory extraction procedures are not designed to 

equate with that portion of arsenic in food that is bioavailable. Thus, the arsenic value 

resulting from extraction and measurement is not necessarily related to the concentration 

that is bioavailable to humans from specific sample sources. There is an immediate need 

for thorough research on the bioavailability of arsenic from food. 

53
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APPENDIX A 

Charge to EPA Science Advisory Board Arsenic Review Panel 

July 25, 2005 

Background: There are both natural and anthropogenic sources of arsenic and arsenic 

containing compounds (or arsenicals). Exposure to arsenicals can be through different 

environmental media including drinking water, food, soil, and air. EPA assesses and 

regulates the potential exposure and health risks associated with exposure to arsenic and 

arsenic containing compounds through several statutory authorities. The Safe Drinking 

Water Act (SDWA), directs EPA to establish national standards for contaminants 

including arsenical compounds in public drinking water supplies. EPA’s Superfund and 

Resource Conservation and Recovery Act (RCRA) programs evaluate exposure to arsenic 

compounds at sites selected for clean up or remediation. Under the Clean Air Act, EPA’s 

Office of Air and Radiation sets emissions standards for sources of arsenic to air. These 

include standards based on control technology and those based on risks to human health 

from inhalation of airborne arsenic or ingestion of arsenic arising from air sources. 

EPA’s Office of Pesticide Programs (OPP) evaluates the exposure and health risks 

associated with arsenicals used as pesticides in the U.S. Under the mandate of the Food 

Quality Protection Agency (FQPA), EPA must reevaluate all pesticide food tolerances 

(the legal limits of pesticides on/in food or animal feed) in the U.S. by August, 2006. 

There are several organic arsenic herbicides that are undergoing reregistration and/or 

tolerance reassessment including cacodylic acid (referred to as dimethylarsinic acid or 

DMAV), monosodium, disodium, and calcium salts of methanearsonate acid (MSMA, 

DSMA, and CAMA, collectively as referred as MMAV). In 2003, most residential uses 

of chromated copper arsenate (CCA) as a wood preservative were cancelled. 

The health effects of arsenicals have been the subject of two reviews by the 

National Research Council (NRC) of the National Academy of Sciences (NAS) (NRC 

1999; 2001). Since the 2001 NAS review, there has been substantial new information 

developed on the mode of carcinogenic action and metabolism and toxicokinetics for 

arsenic and its methylated species, and new epidemiology on inorganic arsenic. The 

Agency has considered this new science in regards to the hazard characterization required 

for tolerance assessment of DMAV (and MMAV ) as described in the draft OPP Science 

Issue Paper: Mode of Action for Cacodylic Acid (Dimethylarsinic Acid) and 

Recommendations for Dose Response Extrapolation, and also in the ORD Issue Paper - 

Cancer Risk Assessment for Organic Arsenical Herbicides: Comments on Mode of 

Action, Human Relevance and Implications for Quantitative Dose-Response Assessment 

(See Appendix E). In addition, the Agency has developed a revised hazard and dose 

response assessment/characterization of inorganic Arsenic (Toxicological review of 

inorganic arsenic in Support of Summary Information on the Integrated Risk Information 

System (IRIS)) which relies on the two NRC reviews and provides an updated human 

health effects and dose-response assessment for inorganic arsenic. The Agency seeks 

comment and advice from the SAB on the scientific soundness of major science 

conclusions drawn in these two documents regarding the carcinogenic assessments of 

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DMAV and inorganic arsenic and the appropriateness of the Agency’s application of its 

own Guidelines for Carcinogen Risk Assessment for arsenicals. 

Overview of Science and Assessment Issues: Ingestion of inorganic arsenic has been 

demonstrated to cause cancer of the skin, lung, and urinary bladder in humans. 

Historically, standard chronic bioassays with exposure to inorganic arsenic in rodents 

have been negative for increased tumor formation. There are, however, more recent 

studies at high doses, in transgenic animals, and following transplacental exposures 

which have demonstrated cancer potential in rodent studies following exposure to 

inorganic arsenic. The NRC 1999 report advises that the bladder and lung cancer human 

mortality data, particularly from the southwestern Taiwanese studies provide the best 

dose-response data for evaluating the long-term effects of ingestion of inorganic arsenic. 

In the 2001 NRC report, a number of recommendations were made to EPA to revise the 

oral cancer slope for inorganic arsenic. Given the available database, and recognizing that 

the mode(s) of action by which inorganic arsenic causes cancer has not been fully 

established, the draft Toxicological Review of Arsenic, consistent with advice from the 

NRC uses linear low dose extrapolation to estimate cancer risks from ingestion of arsenic 

at low dose and has addressed many of the NRC recommendations. 

In approaching the cancer assessment on the pesticide cacodylic acid (DMAV), an 

organic arsenical, EPA has confronted a number of challenging issues. No human 

epidemiological information is available for DMAV. Rodent cancer bioassay data have 

shown that dietary administration of DMAV can result in bladder carcinogenesis in the 

rat. DMA, however, is a key urinary metabolite from exposure to inorganic arsenic. 

Thus, the question is raised regarding the extent the cancer epidemiology on inorganic 

arsenic may provide an appropriate dataset or may inform the low dose extrapolation for 

the cancer risk associated with direct exposure to DMAV. Available in vivo and in vitro 

pharmacokinetic, metabolism studies, and toxicology studies were reviewed to address 

this issue. The draft OPP Science Issue Paper states that the evidence indicates inorganic 

arsenic and DMAV have different pharmacokinetic and pharmacodynamic 

characteristics, EPA proposes to use the rat bioassay data on DMAV to estimate its cancer 

risk. The ORD Issue Paper (Appendix E of the OPP Science Issue Paper: Cancer Mode of 

Action of Cacodylic Acid (Dimethylarsinic Acid) and Recommendations for Dose 

Response Extrapolation) provides additional discussion on the MOA issues and 

perspective on the nexus between science issues for organic and inorganic arsenicals. 

The use of mode of action data in the assessment of potential carcinogens is a main focus 

of EPA’s 2005 cancer guidelines. Mode of action data are available on DMA and were 

evaluated to guide the low dose extrapolation. 

The Agency seeks comments and advice from the SAB on key science issues 

concerning (A) the metabolism and toxic responses of arsenic species, (B) the mode of 

action for carcinogenesis and implications for dose-response extrapolation for DMAV and 

inorganic arsenic, (C) the selection of data for dose-response, and (D) approaches to lowdose extrapolation. In addition, the Agency is requesting comment on the implications of 

newer epidemiology and the incorporation of the 2001 NRC recommendation on 

modeling the human cancer data for inorganic arsenic. 

A-2
Issues and Charge Questions 

A. Metabolism and Toxic Responses of Arsenic Species 

A1. Metabolism and pharmacokinetics: Evidence from in vivo and in vitro 

metabolism and pharmacokinetic studies with humans and laboratory animals 

suggests that the efficiency of the methylation reaction(s) and cellular uptake 

varies based on which arsenical compound is administered exogenously. Most 

available studies suggest that the metabolic process in most mammals is primarily 

a one-way process and that following direct exposure to DMAV significant 

amounts of iAsIII, iAsV, MMAIII, or MMAV at the target tissue are not expected. 

Please comment on how pharmacokinetic processes are best considered regarding the 

use of data derived from direct DMAV

 exposure versus direct iAs exposure for cancer risk 

assessment. 

A2. Response to mixtures of metabolites: Tumorigenic profiles vary based on 

which arsenical compound is administered exogenously. In vivo and in vitro studies 

indicate that each of the arsenical compounds exhibit similarities and differences in their 

profiles of biological activities. Direct exposure to iAsIII or iAs V is expected to result in 

more of a mixture of toxic metabolites than for direct exposure to DMAv; the mixture of 

metabolites is expected to vary based on which chemical is administered exogenously. 

The potential mixture of metabolites following direct exposure to DMAV appears less 

complex as compared to iAs. 

Given the toxicological response profiles observed following direct exposures to iAs 

versus MMAv

 and DMAV, and the differences in human and rodent toxicologic responses 

to arsenicals, please comment on the use of data derived from rodent exposures to the 

organic arsenicals versus use of data derived from direct iAs human exposure, in the 

DMAV

 assessment. 

B. Modes of Carcinogenic Action for DMAV and Inorganic Arsenic 

B1. Mode of action of DMAv

: When relying on laboratory animal data, two 

critical assumptions are made: (i) data on animal tumors are predictive of human 

cancer, and (ii) animal tumor effects found at high experimental doses predict 

human risk at lower exposures. An understanding of a chemical mode of 

carcinogenic action can help inform the above assumptions. In the case of 

DMAV, mode of action (MOA) data are available and were evaluated using the 

framework described in EPA’s cancer guidelines. 

Please comment on the sufficiency of evidence to establish the animal mode of 

carcinogenic action for DMAV

. Are the scientific conclusions sound and consistent with 

the available evidence on DMAV and the current state of knowledge for chemical 

carcinogenesis. 

Please comment on whether the key events in DMA’s mode of action are supported by the 

available data. Specifically comment on the role of: a) reactive oxygen species in 

A-3
producing chromosomal damage and the strength of the evidence supporting oxidative 

damage as a causal key event in DMAV

/DMAIII‘s mode of carcinogenic action versus an 

associative event or a secondary consequence of cytotoxicity; b) cell proliferation and 

cytotoxicity and the strength of the evidence as causal key events in DMAV

/DMAIII‘s mode 

of carcinogenic action versus associative or secondary events, and c) other potential 

modes of action that have substantial scientific support that may be contributing to the 

carcinogenicity of DMA. 

B2. Human relevance of animal DMAV MOA: There are little or no 

scientific data to suggest that if sufficient DMAIII were present, key precursor 

events and ultimately tumor formation would not occur in humans directly 

exposed to DMAV. 

Please comment on the relevance of the postulated key events (see B1) to tumors in 

humans. 

Please comment on how, if at all, differences in the human population vs. experimental 

animals should be accounted for in the risk assessment for DMAV

. 

There are little to no chemical specific data regarding an increased susceptibility 

of humans for bladder tumor development during different life stages. 

Please comment on the Agency’s conclusion that the young are likely to respond like the 

adult to the formation of bladder tumors following exposure to DMA. 

B3. Modes of carcinogenic action from exposure to inorganic arsenic: 

DMA

Inorganic arsenic (iAs) undergoes successive methylation steps in humans, 

resulting in the intermediate production of iAsIII, MMAV, MMAIII, DMAV, and

III. Each arsenical metabolite exhibits its own toxicity. 

Please comment on the conclusion that the available data support the hypothesis that 

multiple modes of action may be operational following exposure to inorganic arsenic. 

C. Selection of Data for Dose-Response Assessment 

C1. Use of animal data for DMAV : A number of different rodent bioassays 

(standard bioassay, transgenic animals, susceptible rodent strains, initiation and 

promotion studies) are available on DMAV. 

Please comment on the use of the bladder tumor data from the DMAV

 rat bioassay 

as the most suitable dataset for quantifying potential human cancer risk to DMAV

, 

including the weight of evidence to support this conclusion. 

Please comment on whether the iAs epidemiology data can be used to inform the DMAV 

dose-response assessment derived from rat data with DMAV

. If so, please discuss how 

such information might be used. (See Appendix). 

A-4
C2. Use of human epidemiological data from direct iAs exposure: Since the 

NRC (2001) report on iAs, an additional body of literature has developed 

describing epidemiology data from populations in the US exposed to iAs in 

drinking water. 

Does the SAB agree that the Taiwanese dataset remains the most appropriate choice for 

estimating cancer risk in humans? Please discuss the rationale for your response. 

Do these data provide adequate characterization of the impact of childhood exposure to 

iAs? Please discuss the rationale for your response. 

D. Approaches to Low-Dose Extrapolation for Inorganic Arsenic and DMAV 

D1. Mode of carcinogenic action understanding for DMAV/III and 

implications for dose response extrapolation to estimate human cancer risk: The 

use of mode of action data in the assessment of potential carcinogens is a main 

focus of EPA’s 2005 cancer guidelines. As stated in these guidelines “The 

approach to dose-response assessment for a particular agent is based on the 

conclusion reached as to its potential mode(s) of action”. Although a biologicalbased model is the preferred approach to estimating cancer risk, there are 

insufficient data on DMAV to support development of such a model. 

Please comment on the scientific evidence and biological rationale in support of 

nonlinear versus linear low dose extrapolation approaches, which approach is 

more consistent with the available data on DMAV

 and current concepts of 

chemical carcinogenesis, and how scientific uncertainty should most 

appropriately be incorporated into low-dose extrapolation. 

D2. Implementation of the recommendations of the NRC (2001): EPA has 

determined that the most prudent approach for modeling cancer risk from 

exposure to iAs is to use a linear model because there are significant remaining 

uncertainties regarding which of the metabolite(s) may be the ultimate 

carcinogenic moiety and whether or not mixtures of toxic metabolites interact at 

the site(s) of action. 

Does the panel concur with the selection of a linear model following the 

recommendations of the NRC (2001) to estimate cancer risk at this time? Please discuss 

your response in light of the highly complex mode of action for iAs with its metabolites. 

D3. EPA re-implemented the model presented in the NRC (2001) in the 

language R as well as in an Excel spreadsheet format. In addition, extensive 

testing of the resulting code was conducted. 

Please comment upon precision and accuracy of the re-implementation of the model. 

D4. Available literature describing drinking water consumption rates for 

the southwestern Taiwanese study population: NRC (2001) stated that the 

A-5
drinking water consumption rate, as well as variability of that rate in both US and 

Taiwanese populations, are important factors to consider. In calculating risk 

estimates for U.S. populations exposed to arsenic through drinking water, NRC 

used a drinking water consumption rate of 1 L/day for the US population and two 

possible consumption rates for the Taiwanese population: 1 L/day (identical to 

the US population) and 2.2 L/day with little or no supporting rationale. Since 

publication of NRC 2001, a number of new studies have become available and are 

summarized in the Cancer Slope Factor Workgroup Issue Paper. Agency reviews 

of the relevant literature suggests that the mean drinking water (for the Taiwanese 

study population) consumption rate is between 1 to 4.6 L/day. EPA’s current 

cancer modeling includes water intake adjustments for 2.0 and 3.5 L/day. 

What drinking water value does the panel recommend for use in deriving the cancer 

slope factor for inorganic arsenic? 

D5. Selection of an estimate of dietary intake of arsenic from food: The 

issue of intake of arsenic from food (e.g., dry rice, sweet potatoes) has been 

distinguished from the issue of intake of arsenic from drinking water. The NRC 

addressed the issue of arsenic in food by determining how sensitive the 

calculation of ED01 was to the consumption rate. NRC found that changing the 

consumption rate from 50 μg/day to 30 μg/day did not change the calculated ED01 

significantly (about 1% difference). Since the publication of NRC 2001, a 

number of new studies have become available, summarized in the Cancer Slope 

Factor Workgroup Issue Paper. EPA’s current cancer modeling includes dietary 

intake adjustments for 0, 10, 30, and 50 μg/day. 

What background dietary intake (of arsenic) value does the panel recommend for both 

the control population and study population of Southwestern Taiwan used in deriving the 

cancer slope factor for inorganic arsenic? 

A-6
APPENDIX B 

Assignments to Charge-Specific Groups (revised on 8/24/05) 

Issue A: Metabolism and Toxic Responses of Arsenic Species 

Question A1: Metabolism and Pharmacokinetics 

Dr. Aposhian 

Dr. Medinsky 

Dr. Le 

Dr. Rosen 

Dr. Styblo 

 Dr. Hopenhayn 

Question A2: Response to mixtures of metabolites 

Dr. Aposhian 

Dr. Medinsky 

Dr. Le 

Dr. Rosen 

Dr. Styblo 

 Dr. Hopenhayn 

Issue B: Modes of Carcinogenic Action for DMA and iAs 

Question B1: Mode of Action of DMAV 

Dr. Barchowsky Dr. Rossman 

Dr. Brusick Dr. Styblo 

Dr. Dragan Dr. Waalkes 

Dr. Klaunig 

Question B2: Human relevance of animal DMAV MOA 

Dr. Barchowsky Dr. Rossman 

Dr. Brusick Dr. Styblo 

Dr. Dragan Dr. Waalkes 

Dr. Klaunig 

Question B3: Modes of carcinogenic action from exposure to inorganic 

arsenic 

Dr. Barchowsky Dr. Klaunig 

Dr. Brusick Dr. Rossman 

Dr. Dragan Dr. Waalkes 

Issue C: Selection of Data for Dose-Response Assessment 

Question C1: Use of animal data for DMAV 

Dr. Cantor 

Dr. Green 

Dr. Medinsky 

Dr. Teeguarden 

Dr. Waalkes 

Dr. Yager 

B-1
Question C2: Use of human epidemiological data from direct iAs exposure 

Dr. Cantor 

Dr. Colford 

Dr. Harlow 

Dr. Hopenhayn 

Dr. Rosen 

Dr. Rossman 

Dr. Yager 

Issue D: Approaches to Low-Dose Extrapolation for iAs and DMAV 

Question D1: Mode of Carcinogenic action understanding for DMAV/III and 

implications for dose response extrapolation to estimate human cancer risk 

Dr. Cantor Dr. Medinsky 

Dr. Colford Dr. Teeguarden 

Dr. Green Dr. Waalkes 

Dr. Klaunig 

Question D2: Implementation of the recommendations of the NRC (2001) 

Dr. Colford 

Dr. Harlow 

Dr. Hopenhayn 

Dr. Heeringa 

Dr. Portier 

Dr. Rosen 

Dr. Rossman 

Question D3: EPA re-implementation of the NRC (2001) model in language 

R and Excel spreadsheet. 

Dr. Heeringa 

Dr. Portier 

Dr. Teeguarden 

Question D4: Literature describing drinking water consumption rates for 

the southwestern Taiwanese study population 

Dr. Barchowsky 

Dr. Harlow 

Dr. Colford 

Dr. Yager 

Question D5: Selection of an estimate for dietary intake of arsenic 

Dr. Aposhian 

Dr. Barchowsky 

Dr. Harlow 

Dr. Styblo 

Dr. Yager 

B-2 
APPENDIX C 

ABBREVIATIONS 

Abbreviations Meaning 

ARP US EPA SAB Arsenic Review Panel 

As Arsenic 

BEIR Biological Effects of Ionizing Radiation 

CAMA Calcium salt of MMAV 

CCA Chromated copper arsenate 

DMAIII Dimethylarsinous acid 

DMAV Dimethylarsinic acid, Cacodylic Acid 

DSMA Disodium salt of MMAV 

EPA US Environmental Protection Agency 

FIFRA Federal Insecticide, Fungicide, and Rodenticide Act 

FQPA The Food Quality Protection Act 

GPO US Government Printing Office 

iAs Inorganic arsenic 

iAsIII Arsenite, Trivalent inorganic arsenic 

NFkB Nuclear factor-kappa B 

iAsV Arsenate, Pentavalent inorganic arsenic 

MLE Maximum Likelihood Estimates 

MMAIII Methylarsonous acid 

MMAV Methanearsonate acid, methylarsenic acid 

MN Micronuclei 

MOA Mode of Action 

MSMA Monosodium salt of MMAV 

NAS National Academy of Sciences 

NHANES National Health and Nutrition Examination Survey 

NRC National Research Council of the NAS 

OPP US EPA Office of Pesticide Programs 

ORD US EPA Office of Research & Development 

OW US EPA Office of Water 

PBPK Physiologically Based Pharmacokinetic Models 

PD Pharmacodynamics 

PK Pharmacokinetics 

RCRA Resource Conservation and Recovery Act 

ROS Reactive Oxygen Species 

SAB US EPA Science Advisory Board 

TMAIII Trimethylarsine 

TMAVO Trimethylarsine oxide 

C-1