Research over the past decade has demonstrated that TGx methods of various types can be used to discriminate modes of mutagenesis as a function of dose. TGx can quickly inform safety evaluation regarding potential mechanisms of conventional outcomes and can provide essential dose-response information. This can then be used to ascertain the sequence of key events in a putative mode of action as may apply in quantitative cancer risk assessment. With the increasing complexity of research in mode of action investigations it is important to gain a better understand of approaches to data integration and health risk assessment. Furthermore, it is essential to consider how novel test systems and newer methods and approaches may be used in future to gain a better understanding of mechanisms.
Toxicogenomics in Predictive Carcinogenicity describes toxicogenomics methods in predictive carcinogenicity testing, mode of action and safety evaluation, and cancer risk assessment. It illustrates these methods using case studies that have yielded significant new information on compounds and classes of compounds that have proven difficult to evaluate using conventional methods alone. This book additionally covers current and potential toxicogenomic research using stem cells as well as new bioinformatics methods for drug discovery and environmental toxicology.
This publication is an indispensable tool for postgraduates, academics and industrialists working in biochemistry, genomics, carcinogenesis, pathology, pharmaceuticals, food technology, bioinformatics, risk assessment and environmental toxicology.
Зміст
Introduction to Predictive Toxicogenomics for Carcinogenicity; Genomic Biomarkers in Cell-based Drug Screening; Toxicogenomics In Vitro: Gene Expression Signatures for Differentiating Genotoxic Mechanisms; In Vivo Signatures of Genotoxic and Non-Genotoxic Chemicals; Transcriptomic Dose-Response Analysis for Mode of Action and Risk Assessment; Using transcriptomics to evaluate thresholds in genotoxicity dose-response; Dissecting Modes of Action of Non-Genotoxic Carcinogens; Human Embryonic Stem Cells as Biological Models to Examine the Impact of Xenobiotics on the Genome and Epigenome; Novel Data Streams in the Assessment of Mutagenicity and Carcinogenicity: Implications for Cancer Hazard Assessment; Conazoles and Cancer, a Review; Application of Transcriptomics in Exposed Human Populations: Benzene as an Example; Toxicogenomics Case Study: Furan; The Parallelogram Approach to Assess Human Relevance of Toxicogenomics Derived Toxicity Pathways in Human Health Risk Assessment; Bioinformatics of Genomics in the Assessment of Cancer;
Про автора
Michael D. Waters, holds a Ph.D. in Biochemistry from the University of North Carolina School of Medicine at Chapel Hill and a B.S. in Pre-medicine (Chemistry and Biology) from Davidson College. He is a former government scientist with more than 35 years of experience in research and research management positions at EPA and NIH/NIEHS and six years of private sector experience as Chief Scientific Officer at Integrated Laboratory Systems, Inc. His research interests have centered on the evaluation of chemically-induced mutations and altered molecular expression in the etiology of genetic disease. He is a widely-published scientist having published well over 100 peer-reviewed in authoritative international scientific journals. He has edited Mutation Research-Reviews for nearly 20 years and has held adjunct professorships at both the University of North Carolina and at Duke University for many years. He served as President of both the Environmental Mutagen Society and the International Association of Environmental Mutagen Societies (now the Environmental Mutagenesis and Genomics Society and the International Association of Environmental Mutagenesis and Genomics Societies, with more than seven thousand members worldwide). The databases he has developed and a number of his publications are recognized as important advances that have significantly impacted the fields of genetic toxicology, carcinogenesis, toxicogenomics, and risk assessment.
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