Literature DB >> 19010444

Improving prediction of chemical carcinogenicity by considering multiple mechanisms and applying toxicogenomic approaches.

Kathryn Z Guyton1, Amy D Kyle2, Jiri Aubrecht3, Vincent J Cogliano4, David A Eastmond5, Marc Jackson6, Nagalakshmi Keshava7, Martha S Sandy8, Babasaheb Sonawane7, Luoping Zhang2, Michael D Waters6, Martyn T Smith2.   

Abstract

While scientific knowledge of the potential health significance of chemical exposures has grown, experimental methods for predicting the carcinogenicity of environmental agents have not been substantially updated in the last two decades. Current methodologies focus first on identifying genotoxicants under the premise that agents capable of directly damaging DNA are most likely to be carcinogenic to humans. Emphasis on the distinction between genotoxic and non-genotoxic carcinogens is also motivated by assumed implications for the dose-response curve; it is purported that genotoxicants would lack a threshold in the low dose region, in contrast to non-genotoxic agents. However, for the vast majority of carcinogens, little if any empirical data exist to clarify the nature of the cancer dose-response relationship at low doses in the exposed human population. Recent advances in scientific understanding of cancer biology-and increased appreciation of the multiple impacts of carcinogens on this disease process-support the view that environmental chemicals can act through multiple toxicity pathways, modes and/or mechanisms of action to induce cancer and other adverse health outcomes. Moreover, the relationship between dose and a particular outcome in an individual could take multiple forms depending on genetic background, target tissue, internal dose and other factors besides mechanisms or modes of action; inter-individual variability and susceptibility in response are, in turn, key determinants of the population dose-response curve. New bioanalytical approaches (e.g., transcriptomics, proteomics, and metabolomics) applied in human, animal and in vitro studies could better characterize a wider array of hazard traits and improve the ability to predict the potential carcinogenicity of chemicals.

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Year:  2008        PMID: 19010444     DOI: 10.1016/j.mrrev.2008.10.001

Source DB:  PubMed          Journal:  Mutat Res        ISSN: 0027-5107            Impact factor:   2.433


  34 in total

1.  Predictive modeling of chemical hazard by integrating numerical descriptors of chemical structures and short-term toxicity assay data.

Authors:  Ivan Rusyn; Alexander Sedykh; Yen Low; Kathryn Z Guyton; Alexander Tropsha
Journal:  Toxicol Sci       Date:  2012-03-02       Impact factor: 4.849

Review 2.  Voluntary exploratory data submissions to the US FDA and the EMA: experience and impact.

Authors:  Federico M Goodsaid; Shashi Amur; Jiri Aubrecht; Michael E Burczynski; Kevin Carl; Jennifer Catalano; Rosane Charlab; Sandra Close; Catherine Cornu-Artis; Laurent Essioux; Albert J Fornace; Lois Hinman; Huixiao Hong; Ian Hunt; David Jacobson-Kram; Ansar Jawaid; David Laurie; Lawrence Lesko; Heng-Hong Li; Klaus Lindpaintner; James Mayne; Peter Morrow; Marisa Papaluca-Amati; Timothy W Robison; John Roth; Ina Schuppe-Koistinen; Leming Shi; Olivia Spleiss; Weida Tong; Sharada L Truter; Jacky Vonderscher; Agnes Westelinck; Li Zhang; Issam Zineh
Journal:  Nat Rev Drug Discov       Date:  2010-06       Impact factor: 84.694

3.  Improving prediction of carcinogenicity to reduce, refine, and replace the use of experimental animals.

Authors:  Todd Bourcier; Tim McGovern; Lidiya Stavitskaya; Naomi Kruhlak; David Jacobson-Kram
Journal:  J Am Assoc Lab Anim Sci       Date:  2015-03       Impact factor: 1.232

4.  Prediction of carcinogenicity for diverse chemicals based on substructure grouping and SVM modeling.

Authors:  Kazutoshi Tanabe; Bono Lučić; Dragan Amić; Takio Kurita; Mikio Kaihara; Natsuo Onodera; Takahiro Suzuki
Journal:  Mol Divers       Date:  2010-02-26       Impact factor: 2.943

Review 5.  Toxicogenomic profiling of chemically exposed humans in risk assessment.

Authors:  Cliona M McHale; Luoping Zhang; Alan E Hubbard; Martyn T Smith
Journal:  Mutat Res       Date:  2010-04-09       Impact factor: 2.433

6.  Genotoxic, histologic, immunohistochemical, morphometric and hormonal effects of di-(2-ethylhexyl)-phthalate (DEHP) on reproductive systems in pre-pubertal male rats.

Authors:  Gözde Karabulut; Nurhayat Barlas
Journal:  Toxicol Res (Camb)       Date:  2018-05-11       Impact factor: 3.524

7.  Emerging approaches in predictive toxicology.

Authors:  Luoping Zhang; Cliona M McHale; Nigel Greene; Ronald D Snyder; Ivan N Rich; Marilyn J Aardema; Shambhu Roy; Stefan Pfuhler; Sundaresan Venkatactahalam
Journal:  Environ Mol Mutagen       Date:  2014-07-09       Impact factor: 3.216

8.  Dose-response assessment of four genotoxic chemicals in a combined mouse and rat micronucleus (MN) and Comet assay protocol.

Authors:  Leslie Recio; Cheryl Hobbs; William Caspary; Kristine L Witt
Journal:  J Toxicol Sci       Date:  2010-04       Impact factor: 2.196

Review 9.  Bridging epidemiology and model organisms to increase understanding of endocrine disrupting chemicals and human health effects.

Authors:  Tracey J Woodruff
Journal:  J Steroid Biochem Mol Biol       Date:  2010-11-26       Impact factor: 4.292

Review 10.  A niche for infectious disease in environmental health: rethinking the toxicological paradigm.

Authors:  Beth J Feingold; Leora Vegosen; Meghan Davis; Jessica Leibler; Amy Peterson; Ellen K Silbergeld
Journal:  Environ Health Perspect       Date:  2010-04-12       Impact factor: 9.031

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