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Quantitation of Molecular Endpoints for the Dose-Response Component of Cancer Risk Assessment

Environmental Carcinogenesis Division, National Health & Environmental Effects Research Laboratory, US Environmental Protection Agency, Research Triangle Park, North Carolinan, preston.julian{at}epa.gov

Cancer risk assessment involves the steps of hazard identification, dose-response assessment, exposure assessment, and risk characterization. The rapid advances in the use of molecular biology approaches has had an impact on all 4 components, but the greatest overall current and future impact will be on the dose-response assessment because this requires an understanding of the mechanisms of carcinogenesis, both background and induced by environmental agents. In this regard, hazard identification is a qualitative assessment and dose-response is a quantitative estimate. Thus, the latter will ultimately require a quantitative assessment of molecular endpoints that are used to describe the dose-response for cancer. It has been possible for many years to quantitate alterations at the level of the single gene. For example, analysis of mutation frequency by phenotypic selection, analysis of transcription (mRNA) by Northern blot, analysis of translation (proteins) by Western blot, and analysis of kinetics of metabolism from metabolite levels. However, it is becoming clear that it is necessary when considering risk for adverse health outcomes to develop quantitative approaches for whole cell phenotypes or organ effects. For example, cancer is a whole tissue phenotype, not a feature of single gene mutations, in spite of the multistep (multimutation) mode of formation of a tumor. Thus, there is the need to quantitate the circuitry of a cell: the metabolic/biochemical pathways, genetic regulation pathways, and signaling pathway s in normal and stressed conditions. The hypothesis presented by Hanahan and Weinberg of the requirement for 6 acquired characteristics for tumor development, independent of tissue type and species or inducer, seems to provide a viable approach. This hypothesi s can be addressed through whole cell molecular assessment using microarray s and quantitative PCR together with the emerging proteomic approaches. This is the world of the new computational cell biology.

Key Words: Gene mutations • chromosomal alterations • genomics • proteomics • biomarkers • bioindicators • cancer risk assessment.

References

• Aebersold R., Rist B., Gygi SP (2000). Quantitative proteome analysis: Methods and applications. Ann NY Acad Sci 919: 33—47.[Medline] [Order article via Infotrieve]
• Albertini RJ (1998). The use and interpretation of biomarkers of environmental genotoxicity in humans. Biotherapy 11: 155—167.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
• Alter O., Brown PO, Botstein D. (2000). Singular value decomposition for genome-wide expression data processing and modeling. Proc Natl Acad Sci USA 97:10101—10106.[Abstract/Free Full Text]
• Beaudet AL, Scriver CR, Sly WS, Valle D. (1998). A human genetics primer. In: The Genetic Basis of Human Cancer, Vogelstein B, Kinzler KW (eds). McGraw-Hill, New York, pp 3—31.
• Bentham G., Wolfreys AM, Liu Y., Cortopassi G., Green MH, Arlett CF, Cole J. ( 1999). Frequencies of hprt(-)mutations and bcl-2 translocations in circulating human lymphocytes are correlated with United Kingdom sunlight records. Mutagenesis 14: 527—532.[Abstract/Free Full Text]
• Bonassi S., Hagmar L., Stromberg U., Montagud AH, Tinnerberg H., Forni A., Heikkila P., Wanders S. Wilhardt P., Hansteen IL, Kundsen LE, Norppa H. (2000). Chromosomal aberrations in lymphocytes predict human cancer independently of exposure to carcinogens. European study group on cytogenetic biomarkers and health. Cancer Res 60: 1619—1625.[Abstract/Free Full Text]
• Burke HB (2000). Discovering patterns in microarray data. Mol Diagn 5: 349—357.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
• Denissenko MF, Koudriakova TB, Smith L., O'Connor TR, Riggs AD, Pfeifer GP (1998). The p53 codon 249 mutational hotspot in hepatocellular carcinoma is not related to selective formation or persistence of aflatoxin B1 adducts. Oncogene 17: 3007—3014.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
• Dong G., Loukinova E., Chen Z., Gangi L., Chaturita TI, Liu ET, Van Waes C. (2001). Molecular profiling of transformed and metastatic murine squamous carcinoma cells by differential display and cDNA microarray reveals altered expression of multiple genes related to growth, apoptosis, angiogenesis, and the NF-B signal pathway. Cancer Res 61: 4797— 4808.[Abstract/Free Full Text]
• EPA (US Environmental Protection Agency) (1986). Guidelines for Carcinogen Risk Assessment. Fed Reg 51: 33992—34003.
• EPA (US Environmental Protection Agency) (1996). Proposed Guidelines for Carcinogen Risk Assessment. EPA/600P/P-92/003c. Office of Research and Development. US Environmental Protection Agency, Washington, DC.
• Fauth C., Speicher MR (2001). Classifying by colors: FISH-based genome analysis. Cytogenet Cell Genet 93: 1—10.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
• Foulds L. (1954). The Experimental Study of Tumor Progression, Volumes I—III. Academic Press, London.
• Hanahan D., Weinberg RA (2000). The hallmarks of cancer. Cell 100: 57 —70.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
• He Y.D, Friend SH (2001). Microarrays—The 21st century divining rod? Nat Med 7: 658—659.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
• Hedenfalk I., Duggan D., Chen Y., Radmacher M., Bittner M., Simon R., Meltzer P., Gusterson B., Esteller M., Kallioniemi O-P., Wilfond B., Borg A., Trent J. (2001). Gene-expression profiles in hereditary breast cancer. N Engl J Med 344: 539—548.[Abstract/Free Full Text]
• Kallioniemi OP (2001). Biochip technologies in cancer research. Ann Med 33: 142—147.[Web of Science][Medline] [Order article via Infotrieve]
• Kinzler KW, Vogelstein B. (1996). Lessons from hereditary colorectal cancer. Cell 87: 159—170.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
• Ladner DP, Leamon JH, Hamann S., Tarafa G., Strugnell T., Dillon D., Lizardi P., Costa J. (2001). Multiplex detection of hotspot mutations by rolling circle-enabled universal microarrays. Lab Invest 81: 1079—1086.[Web of Science][Medline] [Order article via Infotrieve]
• Moolgavkar S., Krewski D., Schwarz M. (1999). Mechanisms of carcinogenesis and biologically based models for estimation and prediction of risk. IARC Sci Pub 131: 179—237.
• Natarajan AT, Darroudi F., Ramalho AT (1994). Cytogenetic indicators of radiation exposure. Adv Biosci 94: 263—269.
• NRC (National Research Council) (1994). Science and Judgement in Risk Assessment. National Academy Press, Washington, DC.
• Page NP, Singh DV, Farland W., Goodman JI, Conolly RB, Andersen ME, Clewell HJ, Frederick CB, Yamasaki H., Lucier G. (1997). Implementation of EPA revised cancer assessment guidelines: Incorporation of mechanistic and pharmacokinetic data. Fundam Appl Toxicol 37: 16— 36.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
• Perera F. (2000). Molecular epidemiology: On the path to prevention? J Natl Cancer Inst 92: 602—612.[Abstract/Free Full Text]
• StolerDL, Chen N., BasikM, Kahlenberg MS, Rodriguez-Bigas MA, Petrelli NJ, Anderson GR (1999). The onset and extent of genomic instability in sporadic colorectal tumor progression. Proc Natl Acad Sci USA 96: 15121— 15126.[Abstract/Free Full Text]
• Zhao L., Hayes K., Khan Z., Glassman A. (2001). Spectral karyotyping study of chromosomal abnoramalities in human leukemia. Cancer Genet Cytogenet 127: 143—147.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
• Zhong XB, Lizardi PM, Huang XH, Bray-Ward PL, Ward DC ( 2001). Visualization of oligonucleotide probes and point mutations in interphase nuclei and DNA fibers using rolling circle DNA amplification. Proc Natl Acad Sci USA 98: 3940—3945.[Abstract/Free Full Text]

Toxicologic Pathology, Vol. 30, No. 1, 112-116 (2002)
DOI: 10.1080/01926230252824798


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This Article Abstract Free Full Text (Free PDF) Free Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Julian Preston, R. Search for Related Content PubMed PubMed Citation Articles by Julian Preston, R. Social Bookmarking                         What's this?