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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. [ABSTRACT FROM AUTHOR]

The ICH S6(R1) recommendations on safety evaluation of biotherapeutics have led to uncertainty in determining what would constitute a cause for concern that would require genotoxicity testing. A Health and Environmental Sciences Institute's Genetic Toxicology Technical Committee Workgroup was formed to review the current practice of genotoxicity assessment of peptide/ protein-related biotherapeutics. There are a number of properties of peptide/protein-related biotherapeutics that distinguish such products from traditional 'small molecule' drugs and need to be taken into consideration when assessing whether genotoxicity testing may be warranted and if so, how to do it appropriately. Case examples were provided by participating companies and decision trees were elaborated to determine whether and when genotoxicity evaluation is needed for peptides containing natural amino acids, non-natural amino acids and other chemical entities and for unconjugated and conjugated proteins. From a scientific point of view, there is no reason for testing peptides containing exclusively natural amino acids irrespective of the manufacturing process. If non-natural amino acids, organic linkers and other non-linker chemical components have already been tested for genotoxicity, there is no need to re-evaluate them when used in different peptide/protein-related biotherapeutics. Unless the peptides have been modified to be able to enter the cells, it is generally more appropriate to evaluate the peptides containing the nonnatural amino acids and other non-linker chemical moieties in vivo where the cleavage products can be formed. For linkers, it is important to determine if exposure to reactive forms are likely to occur and from which origin. When the linkers are anticipated to be potential mutagenic impurities they should be evaluated according to ICH M7. If linkers are expected to be catabolic products, it is recommended to test the entire conjugate in vivo, as this would ensure that the relevant 'free' linker forms stemming from in vivo catabolism are tested. [ABSTRACT FROM AUTHOR]

We live in an era of 'big data', where the volume, velocity, and variety of the data being generated is increasingly influencing the way toxicological sciences are practiced. With this in mind, a workgroup was formed for the 2017 International Workshops on Genotoxicity Testing (IWGT) to consider the use of high information content data in genetic toxicology assessments. Presentations were given on adductomics, global transcriptional profiling, error-reduced single-molecule sequencing, and cellular phenotype-based assays, which were identified as methodologies that are relevant to present-day genetic toxicology assessments. Presenters and workgroup members discussed the state of the science for these methodologies, their potential use in genetic toxicology, current limitations, and the future work necessary to advance their utility and application. The session culminated with audience-assisted SWOT (strength, weakness, opportunities, and threats) analyses. The summary report described herein is structured similarly. A major conclusion of the workgroup is that while conventional regulatory genetic toxicology testing has served the public well over the last several decades, it does not provide the throughput that has become necessary in modern times, and it does not generate the mechanistic information that risk assessments ideally take into consideration. The high information content assay platforms that were discussed in this session, as well as others under development, have the potential to address aspect(s) of these issues and to meet new expectations in the field of genetic toxicology., (Copyright © 2019 Elsevier B.V. All rights reserved.)

A database of 91 chemicals with published data from both transgenic rodent mutation (TGR) and rodent comet assays has been compiled. The objective was to compare the sensitivity of the two assays for detecting genotoxicity. Critical aspects of study design and results were tabulated for each dataset. There were fewer datasets from rats than mice, particularly for the TGR assay, and therefore, results from both species were combined for further analysis. TGR and comet responses were compared in liver and bone marrow (the most commonly studied tissues), and in stomach and colon evaluated either separately or in combination with other GI tract segments. Overall positive, negative, or equivocal test results were assessed for each chemical across the tissues examined in the TGR and comet assays using two approaches: 1) overall calls based on weight of evidence (WoE) and expert judgement, and 2) curation of the data based on a priori acceptability criteria prior to deriving final tissue specific calls. Since the database contains a high prevalence of positive results, overall agreement between the assays was determined using statistics adjusted for prevalence (using AC1 and PABAK). These coefficients showed fair or moderate to good agreement for liver and the GI tract (predominantly stomach and colon data) using WoE, reduced agreement for stomach and colon evaluated separately using data curation, and poor or no agreement for bone marrow using both the WoE and data curation approaches. Confidence in these results is higher for liver than for the other tissues, for which there were less data. Our analysis finds that comet and TGR generally identify the same compounds (mainly potent mutagens) as genotoxic in liver, stomach and colon, but not in bone marrow. However, the current database content precluded drawing assay concordance conclusions for weak mutagens and non-DNA reactive chemicals., (Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.)

The recent revisions of the Organisation for Economic Co-operation and Development (OECD) genetic toxicology test guidelines emphasize the importance of historical negative controls both for data quality and interpretation. The goal of a HESI Genetic Toxicology Technical Committee (GTTC) workgroup was to collect data from participating laboratories and to conduct a statistical analysis to understand and publish the range of values that are normally seen in experienced laboratories using TK6 cells to conduct the in vitro micronucleus assay. Data from negative control samples from in vitro micronucleus assays using TK6 cells from 13 laboratories were collected using a standard collection form. Although in some cases statistically significant differences can be seen within laboratories for different test conditions, they were very small. The mean incidence of micronucleated cells/1000 cells ranged from 3.2/1000 to 13.8/1000. These almost four-fold differences in micronucleus levels cannot be explained by differences in scoring method, presence or absence of exogenous metabolic activation (S9), length of treatment, presence or absence of cytochalasin B or different solvents used as vehicles. The range of means from the four laboratories using flow cytometry methods (3.7-fold: 3.5-12.9 micronucleated cells/1000 cells) was similar to that from the nine laboratories using other scoring methods (4.3-fold: 3.2-13.8 micronucleated cells/1000 cells). No laboratory could be identified as an outlier or as showing unacceptably high variability. Quality Control (QC) methods applied to analyse the intra-laboratory variability showed that there was evidence of inter-experimental variability greater than would be expected by chance (i.e. over-dispersion). However, in general, this was low. This study demonstrates the value of QC methods in helping to analyse the reproducibility of results, building up a 'normal' range of values, and as an aid to identify variability within a laboratory in order to implement processes to maintain and improve uniformity., (Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.)

Accumulated evidence has shown that in vitro mammalian cell genotoxicity assays produce high frequencies of "misleading" positive results, i.e. predicted hazard is not confirmed in in vivo and/or carcinogenicity studies [1], raising the question of relevance to human risk assessment. A recent study of micronucleus (MN) induction [2] showed that commonly used p53-deficient rodent cell lines (CHL, CHO and V79) gave a higher frequency of "misleading" positive results with 9 non-DNA reactive, Ames-negative and in vivo negative chemicals [3] than human p53-competent cells (blood lymphocytes, TK6 and HepG2 cell lines). This raised the question of whether these differences were due to p53 status or species origin. This present study compared human versus mouse and p53-competent versus p53-mutated function. The same 9 chemicals were tested for induction of MN in mouse lymphoma L5178Y (mutated p53), human TK6 (functional p53) and WIL2-NS (TK6 related, with mutated p53) cells. Six chemicals provided clear positive increases in MN frequency in at least one cell type. L5178Y cells yielded clear positive responses with more chemicals than either TK6 or WIL2-NS, indicating origin rather than p53 functionality was most relevant. Apoptosis induction (measured via caspase-3/7) was also investigated with clear differences in the timing and extent of apoptosis induction between mouse and human cells noted. With curcumin in TK6 cells, induction of caspase-3/7 activity coincided with MN induction, whereas for L5178Y cells, MN induction occurred in the absence of increased caspase activity. By contrast, with MMS in TK6 cells, MN induction preceded increased caspase-3/7 activity. These data suggest that MN induction by "misleading positive" genotoxins in p53-competent human cell lines may result from apoptosis, whereas in p53-defective rodent cells such as L5178Y, MN induction may be independent of apoptosis., (Copyright © 2015 Elsevier B.V. All rights reserved.)