Literature DB >> 27650663

Next generation testing strategy for assessment of genomic damage: A conceptual framework and considerations.

Kerry L Dearfield1, B Bhaskar Gollapudi2, Jeffrey C Bemis3, R Daniel Benz4, George R Douglas5, Rosalie K Elespuru6, George E Johnson7, David J Kirkland8, Matthew J LeBaron9, Albert P Li10, Francesco Marchetti5, Lynn H Pottenger11, Emiel Rorije12, Jennifer Y Tanir13, Veronique Thybaud14, Jan van Benthem15, Carole L Yauk5, Errol Zeiger16, Mirjam Luijten15.   

Abstract

For several decades, regulatory testing schemes for genetic damage have been standardized where the tests being utilized examined mutations and structural and numerical chromosomal damage. This has served the genetic toxicity community well when most of the substances being tested were amenable to such assays. The outcome from this testing is usually a dichotomous (yes/no) evaluation of test results, and in many instances, the information is only used to determine whether a substance has carcinogenic potential or not. Over the same time period, mechanisms and modes of action (MOAs) that elucidate a wider range of genomic damage involved in many adverse health outcomes have been recognized. In addition, a paradigm shift in applied genetic toxicology is moving the field toward a more quantitative dose-response analysis and point-of-departure (PoD) determination with a focus on risks to exposed humans. This is directing emphasis on genomic damage that is likely to induce changes associated with a variety of adverse health outcomes. This paradigm shift is moving the testing emphasis for genetic damage from a hazard identification only evaluation to a more comprehensive risk assessment approach that provides more insightful information for decision makers regarding the potential risk of genetic damage to exposed humans. To enable this broader context for examining genetic damage, a next generation testing strategy needs to take into account a broader, more flexible approach to testing, and ultimately modeling, of genomic damage as it relates to human exposure. This is consistent with the larger risk assessment context being used in regulatory decision making. As presented here, this flexible approach for examining genomic damage focuses on testing for relevant genomic effects that can be, as best as possible, associated with an adverse health effect. The most desired linkage for risk to humans would be changes in loci associated with human diseases, whether in somatic or germ cells. The outline of a flexible approach and associated considerations are presented in a series of nine steps, some of which can occur in parallel, which was developed through a collaborative effort by leading genetic toxicologists from academia, government, and industry through the International Life Sciences Institute (ILSI) Health and Environmental Sciences Institute (HESI) Genetic Toxicology Technical Committee (GTTC). The ultimate goal is to provide quantitative data to model the potential risk levels of substances, which induce genomic damage contributing to human adverse health outcomes. Any good risk assessment begins with asking the appropriate risk management questions in a planning and scoping effort. This step sets up the problem to be addressed (e.g., broadly, does genomic damage need to be addressed, and if so, how to proceed). The next two steps assemble what is known about the problem by building a knowledge base about the substance of concern and developing a rational biological argument for why testing for genomic damage is needed or not. By focusing on the risk management problem and potential genomic damage of concern, the next step of assay(s) selection takes place. The work-up of the problem during the earlier steps provides the insight to which assays would most likely produce the most meaningful data. This discussion does not detail the wide range of genomic damage tests available, but points to types of testing systems that can be very useful. Once the assays are performed and analyzed, the relevant data sets are selected for modeling potential risk. From this point on, the data are evaluated and modeled as they are for any other toxicology endpoint. Any observed genomic damage/effects (or genetic event(s)) can be modeled via a dose-response analysis and determination of an estimated PoD. When a quantitative risk analysis is needed for decision making, a parallel exposure assessment effort is performed (exposure assessment is not detailed here as this is not the focus of this discussion; guidelines for this assessment exist elsewhere). Then the PoD for genomic damage is used with the exposure information to develop risk estimations (e.g., using reference dose (RfD), margin of exposure (MOE) approaches) in a risk characterization and presented to risk managers for informing decision making. This approach is applicable now for incorporating genomic damage results into the decision-making process for assessing potential adverse outcomes in chemically exposed humans and is consistent with the ILSI HESI Risk Assessment in the 21st Century (RISK21) roadmap. This applies to any substance to which humans are exposed, including pharmaceuticals, agricultural products, food additives, and other chemicals. It is time for regulatory bodies to incorporate the broader knowledge and insights provided by genomic damage results into the assessments of risk to more fully understand the potential of adverse outcomes in chemically exposed humans, thus improving the assessment of risk due to genomic damage. The historical use of genomic damage data as a yes/no gateway for possible cancer risk has been too narrowly focused in risk assessment. The recent advances in assaying for and understanding genomic damage, including eventually epigenetic alterations, obviously add a greater wealth of information for determining potential risk to humans. Regulatory bodies need to embrace this paradigm shift from hazard identification to quantitative analysis and to incorporate the wider range of genomic damage in their assessments of risk to humans. The quantitative analyses and methodologies discussed here can be readily applied to genomic damage testing results now. Indeed, with the passage of the recent update to the Toxic Substances Control Act (TSCA) in the US, the new generation testing strategy for genomic damage described here provides a regulatory agency (here the US Environmental Protection Agency (EPA), but suitable for others) a golden opportunity to reexamine the way it addresses risk-based genomic damage testing (including hazard identification and exposure). Environ. Mol. Mutagen. 58:264-283, 2017.
© 2016 The Authors. Environmental and Molecular Mutagenesis Published by Wiley Periodicals, Inc. © 2016 The Authors. Environmental and Molecular Mutagenesis Published by Wiley Periodicals, Inc.

Entities:  

Keywords:  exposure assessment; genetic toxicology; integrated testing strategy; mutagenicity; risk assessment

Mesh:

Substances:

Year:  2016        PMID: 27650663     DOI: 10.1002/em.22045

Source DB:  PubMed          Journal:  Environ Mol Mutagen        ISSN: 0893-6692            Impact factor:   3.216


  15 in total

1.  Genetic toxicology in silico protocol.

Authors:  Catrin Hasselgren; Ernst Ahlberg; Yumi Akahori; Alexander Amberg; Lennart T Anger; Franck Atienzar; Scott Auerbach; Lisa Beilke; Phillip Bellion; Romualdo Benigni; Joel Bercu; Ewan D Booth; Dave Bower; Alessandro Brigo; Zoryana Cammerer; Mark T D Cronin; Ian Crooks; Kevin P Cross; Laura Custer; Krista Dobo; Tatyana Doktorova; David Faulkner; Kevin A Ford; Marie C Fortin; Markus Frericks; Samantha E Gad-McDonald; Nichola Gellatly; Helga Gerets; Véronique Gervais; Susanne Glowienke; Jacky Van Gompel; James S Harvey; Jedd Hillegass; Masamitsu Honma; Jui-Hua Hsieh; Chia-Wen Hsu; Tara S Barton-Maclaren; Candice Johnson; Robert Jolly; David Jones; Ray Kemper; Michelle O Kenyon; Naomi L Kruhlak; Sunil A Kulkarni; Klaus Kümmerer; Penny Leavitt; Scott Masten; Scott Miller; Chandrika Moudgal; Wolfgang Muster; Alexandre Paulino; Elena Lo Piparo; Mark Powley; Donald P Quigley; M Vijayaray Reddy; Andrea-Nicole Richarz; Benoit Schilter; Ronald D Snyder; Lidiya Stavitskaya; Reinhard Stidl; David T Szabo; Andrew Teasdale; Raymond R Tice; Alejandra Trejo-Martin; Anna Vuorinen; Brian A Wall; Pete Watts; Angela T White; Joerg Wichard; Kristine L Witt; Adam Woolley; David Woolley; Craig Zwickl; Glenn J Myatt
Journal:  Regul Toxicol Pharmacol       Date:  2019-06-11       Impact factor: 3.271

2.  In vitro human cell-based aneugen molecular mechanism assay.

Authors:  Nikki E Hall; Kyle Tichenor; Steven M Bryce; Jeffrey C Bemis; Stephen D Dertinger
Journal:  Environ Mol Mutagen       Date:  2022-04-22       Impact factor: 3.579

3.  Predictions of genotoxic potential, mode of action, molecular targets, and potency via a tiered multiflow® assay data analysis strategy.

Authors:  Stephen D Dertinger; Andrew R Kraynak; Ryan P Wheeldon; Derek T Bernacki; Steven M Bryce; Nikki Hall; Jeffrey C Bemis; Sheila M Galloway; Patricia A Escobar; George E Johnson
Journal:  Environ Mol Mutagen       Date:  2019-02-27       Impact factor: 3.216

4.  Applied genetic toxicology: From principles to practice.

Authors:  Catherine F Gibbons; Matthew J LeBaron
Journal:  Environ Mol Mutagen       Date:  2017-06       Impact factor: 3.579

Review 5.  Utility of a next-generation framework for assessment of genomic damage: A case study using the pharmaceutical drug candidate etoposide.

Authors:  John Nicolette; Mirjam Luijten; Jennifer C Sasaki; Laura Custer; Michelle Embry; Roland Froetschl; George Johnson; Gladys Ouedraogo; Raja Settivari; Veronique Thybaud; Kerry L Dearfield
Journal:  Environ Mol Mutagen       Date:  2021-11-22       Impact factor: 3.579

6.  Stem cell proliferation patterns as an alternative for in vivo prediction and discrimination of carcinogenic compounds.

Authors:  An-Sofie Stevens; Maxime Willems; Michelle Plusquin; Jan-Pieter Ploem; Ellen Winckelmans; Tom Artois; Karen Smeets
Journal:  Sci Rep       Date:  2017-05-03       Impact factor: 4.379

Review 7.  Strategies and Methodologies for Developing Microbial Detoxification Systems to Mitigate Mycotoxins.

Authors:  Yan Zhu; Yousef I Hassan; Dion Lepp; Suqin Shao; Ting Zhou
Journal:  Toxins (Basel)       Date:  2017-04-07       Impact factor: 4.546

8.  Comparing BMD-derived genotoxic potency estimations across variants of the transgenic rodent gene mutation assay.

Authors:  John W Wills; George E Johnson; Hannah L Battaion; Wout Slob; Paul A White
Journal:  Environ Mol Mutagen       Date:  2017-09-25       Impact factor: 3.216

9.  Utility of a next generation framework for assessment of genomic damage: A case study using the industrial chemical benzene.

Authors:  Mirjam Luijten; Nicholas S Ball; Kerry L Dearfield; B Bhaskar Gollapudi; George E Johnson; Federica Madia; Lauren Peel; Stefan Pfuhler; Raja S Settivari; Wouter Ter Burg; Paul A White; Jan van Benthem
Journal:  Environ Mol Mutagen       Date:  2019-11-27       Impact factor: 3.216

10.  The epigenetic mechanisms of nanotopography-guided osteogenic differentiation of mesenchymal stem cells via high-throughput transcriptome sequencing.

Authors:  Longwei Lv; Yunsong Liu; Ping Zhang; Xiangsong Bai; Xiaohan Ma; Yuejun Wang; Hongyi Li; Li Wang; Yongsheng Zhou
Journal:  Int J Nanomedicine       Date:  2018-09-20
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