Search

Funder: Canada Research Chairs; doi: http://dx.doi.org/10.13039/501100001804, Risk assessments are increasingly reliant on information from in vitro assays. The in vitro micronucleus test (MNvit) is a genotoxicity test that detects chromosomal abnormalities, including chromosome breakage (clastogenicity) and/or whole chromosome loss (aneugenicity). In this study, MNvit datasets for 292 chemicals, generated by the US EPA's ToxCast program, were evaluated using a decision tree-based pipeline for hazard identification. Chemicals were tested with 19 concentrations (n = 1) up to 200 µM, in the presence and absence of Aroclor 1254-induced rat liver S9. To identify clastogenic chemicals, %MN values at each concentration were compared to a distribution of batch-specific solvent controls; this was followed by cytotoxicity assessment and benchmark concentration (BMC) analyses. The approach classified 157 substances as positives, 25 as negatives, and 110 as inconclusive. Using the approach described in Bryce et al. (Environ Mol Mutagen 52:280-286, 2011), we identified 15 (5%) aneugens. IVIVE (in vitro to in vivo extrapolation) was employed to convert BMCs into administered equivalent doses (AEDs). Where possible, AEDs were compared to points of departure (PODs) for traditional genotoxicity endpoints; AEDs were generally lower than PODs based on in vivo endpoints. To facilitate interpretation of in vitro MN assay concentration-response data for risk assessment, exposure estimates were utilized to calculate bioactivity exposure ratio (BER) values. BERs for 50 clastogens and two aneugens had AEDs that approached exposure estimates (i.e., BER < 100); these chemicals might be considered priorities for additional testing. This work provides a framework for the use of high-throughput in vitro genotoxicity testing for priority setting and chemical risk assessment.

There is growing recognition across broad sectors of the scientific community that use of genomic biomarkers has the potential to reduce the need for conventional rodent carcinogenicity studies of industrial chemicals, agrochemicals, and pharmaceuticals through a weight-of-evidence approach. These biomarkers fall into 2 major categories: (1) sets of gene transcripts that can identify distinct tumorigenic mechanisms of action; and (2) cancer driver gene mutations indicative of rapidly expanding growth-advantaged clonal cell populations. This call-to-action article describes a collaborative approach launched to develop and qualify biomarker gene expression panels that measure widely accepted molecular pathways linked to tumorigenesis and their activation levels to predict tumorigenic doses of chemicals from short-term exposures. Growing evidence suggests that application of such biomarker panels in short-term exposure rodent studies can identify both tumorigenic hazard and tumorigenic activation levels for chemical-induced carcinogenicity. In the future, this approach will be expanded to include methodologies examining mutations in key cancer driver gene mutation hotspots as biomarkers of both genotoxic and nongenotoxic chemical tumor risk. Analytical, technical, and biological validation studies of these complementary genomic tools are being undertaken by multisector and multidisciplinary collaborative teams within the Health and Environmental Sciences Institute. Success from these efforts will facilitate the transition from current heavy reliance on conventional 2-year rodent carcinogenicity studies to more rapid animal- and resource-sparing approaches for mechanism-based carcinogenicity evaluation supporting internal and regulatory decision-making.

The growing number of chemicals in the current consumer and industrial markets presents a major challenge for regulatory programs faced with the need to assess the potential risks they pose to human and ecological health. The increasing demand for hazard and risk assessment of chemicals currently exceeds the capacity to produce the toxicity data necessary for regulatory decision making, and the applied data is commonly generated using traditional approaches with animal models that have limited context in terms of human relevance. This scenario provides the opportunity to implement novel, more efficient strategies for risk assessment purposes. This study aims to increase confidence in the implementation of new approach methods in a risk assessment context by using a parallel analysis to identify data gaps in current experimental designs, reveal the limitations of common approaches deriving transcriptomic points of departure, and demonstrate the strengths in using high-throughput transcriptomics (HTTr) to derive practical endpoints. A uniform workflow was applied across six curated gene expression datasets from concentration-response studies containing 117 diverse chemicals, three cell types, and a range of exposure durations, to determine tPODs based on gene expression profiles. After benchmark concentration modeling, a range of approaches was used to determine consistent and reliable tPODs. High-throughput toxicokinetics were employed to translate in vitro tPODs (µM) to human-relevant administered equivalent doses (AEDs, mg/kg-bw/day). The tPODs from most chemicals had AEDs that were lower (i.e., more conservative) than apical PODs in the US EPA CompTox chemical dashboard, suggesting in vitro tPODs would be protective of potential effects on human health. An assessment of multiple data points for single chemicals revealed that longer exposure duration and varied cell culture systems (e.g., 3D vs. 2D) lead to a decreased tPOD value that indicated increased chemical potency. Seven chemicals were flagged as outliers when comparing the ratio of tPOD to traditional POD, thus indicating they require further assessment to better understand their hazard potential. Our findings build confidence in the use of tPODs but also reveal data gaps that must be addressed prior to their adoption to support risk assessment applications.

Mutagenicity testing is an essential component of health safety assessment. Duplex Sequencing (DS), an emerging high-accuracy DNA sequencing technology, may provide substantial advantages over conventional mutagenicity assays. DS could be used to eliminate reliance on standalone reporter assays and provide mechanistic information alongside mutation frequency (MF) data. However, the performance of DS must be thoroughly assessed before it can be routinely implemented for standard testing. We used DS to study spontaneous and procarbazine (PRC)-induced mutations in the bone marrow (BM) of MutaMouse males across a panel of 20 diverse genomic targets. Mice were exposed to 0, 6.25, 12.5, or 25 mg/kg-bw/day for 28 days by oral gavage and BM sampled 42 days post-exposure. Results were compared with those obtained using the conventionallacZviral plaque assay on the same samples. DS detected significant increases in mutation frequencies and changes to mutation spectra at all PRC doses. Low intra-group variability within DS samples allowed for detection of increases at lower doses than thelacZassay. While thelacZassay initially yielded a higher fold-change in mutant frequency than DS, inclusion of clonal mutations in DS mutation frequencies reduced this discrepancy. Power analyses suggested that three animals per dose group and 500 million duplex base pairs per sample is sufficient to detect a 1.5-fold increase in mutations with >80% power. Overall, we demonstrate several advantages of DS over classical mutagenicity assays and provide data to support efforts to identify optimal study designs for the application of DS as a regulatory test.

Error-corrected Duplex Sequencing (DuplexSeq) enables direct quantification of low-frequency mutations and offers tremendous potential for chemical mutagenicity assessment. We investigated the utility of DuplexSeq to quantify induced mutation frequency (MF) and spectrum in human lymphoblastoid TK6 cells exposed to a prototypical DNA alkylating agent,N-ethyl-N-nitrosourea (ENU). Furthermore, we explored appropriate experimental parameters for this application, and assessed inter-laboratory reproducibility. In two independent experiments in two laboratories, TK6 cells were exposed to ENU (25-200 µM) and DNA was sequenced 48, 72, and 96 h post-exposure. A DuplexSeq mutagenicity panel targeting twenty 2.4-kb regions distributed across the genome was used to sample diverse, genome-representative sequence contexts. A robust increase in MF that was unaffected by time was observed in both laboratories. Concentration-response in the MF from the two laboratories was strongly positively correlated (R2=0.95). C:G>T:A, T:A>C:G, T:A>A:T, and T:A>G:C mutations increased in consistent, concentration-dependent manners in both laboratories, with high proportions of C:G>T:A at all time points. The target sites responded similarly between the two laboratories and revealed a higher average MF in intergenic regions. These results, demonstrating remarkable reproducibility across time and laboratory for both MF and spectrum, support the high value of DuplexSeq for characterizing chemical mutagenicity in both research and regulatory evaluation.

The conventional battery for genotoxicity testing is not well suited to assessing the large number of chemicals needing evaluation. Traditional in vitro tests lack throughput, provide little mechanistic information, and have poor specificity in predicting in vivo genotoxicity. New Approach Methodologies (NAMs) aim to accelerate the pace of hazard assessment and reduce reliance on in vivo tests that are time-consuming and resource-intensive. As such, high-throughput transcriptomic and flow cytometry-based assays have been developed for modernized in vitro genotoxicity assessment. This includes: the TGx-DDI transcriptomic biomarker (i.e., 64-gene expression signature to identify DNA damage-inducing (DDI) substances), the MicroFlow® assay (i.e., a flow cytometry-based micronucleus (MN) test), and the MultiFlow® assay (i.e., a multiplexed flow cytometry-based reporter assay that yields mode of action (MoA) information). The objective of this study was to investigate the utility of the TGx-DDI transcriptomic biomarker, multiplexed with the MicroFlow® and MultiFlow® assays, as an integrated NAM-based testing strategy for screening data-poor compounds prioritized by Health Canada’s New Substances Assessment and Control Bureau. Human lymphoblastoid TK6 cells were exposed to 3 control and 10 data-poor substances, using a 6-point concentration range. Gene expression profiling was conducted using the targeted TempO-Seq™ assay, and the TGx-DDI classifier was applied to the dataset. Classifications were compared with those based on the MicroFlow® and MultiFlow® assays. Benchmark Concentration (BMC) modeling was used for potency ranking. The results of the integrated hazard calls indicate that five of the data-poor compounds were genotoxic in vitro, causing DNA damage via a clastogenic MoA, and one via a pan-genotoxic MoA. Two compounds were likely irrelevant positives in the MN test; two are considered possibly genotoxic causing DNA damage via an ambiguous MoA. BMC modeling revealed nearly identical potency rankings for each assay. This ranking was maintained when all endpoint BMCs were converted into a single score using the Toxicological Prioritization (ToxPi) approach. Overall, this study contributes to the establishment of a modernized approach for effective genotoxicity assessment and chemical prioritization for further regulatory scrutiny. We conclude that the integration of TGx-DDI, MicroFlow®, and MultiFlow® endpoints is an effective NAM-based strategy for genotoxicity assessment of data-poor compounds.

Since initial regulatory action in 2010 in Canada, bisphenol A (BPA) has been progressively replaced by structurally related alternative chemicals. Unfortunately, many of these chemicals are data-poor, limiting toxicological risk assessment. We used high-throughput transcriptomics to evaluate potential hazards and compare potencies of BPA and 15 BPA alternative chemicals in cultured breast cancer cells. MCF-7 cells were exposed to BPA and 15 alternative chemicals (0.0005–100 µM) for 48 h. TempO-Seq (BioSpyder Inc) was used to examine global transcriptomic changes and estrogen receptor alpha (ERα)-associated transcriptional changes. Benchmark concentration (BMC) analysis was conducted to identify 2 global transcriptomic points of departure: (1) the lowest pathway median gene BMC and (2) the 25th lowest rank-ordered gene BMC. ERα activation was evaluated using a published transcriptomic biomarker and an ERα-specific transcriptomic point of departure was derived. Genes fitting BMC models were subjected to upstream regulator and canonical pathway analysis in Ingenuity Pathway Analysis. Biomarker analysis identified BPA and 8 alternative chemicals as ERα active. Global and ERα transcriptomic points of departure produced highly similar potency rankings with bisphenol AF as the most potent chemical tested, followed by BPA and bisphenol C. Further, BPA and transcriptionally active alternative chemicals enriched similar gene sets associated with increased cell division and cancer-related processes. These data provide support for future read-across applications of transcriptomic profiling for risk assessment of data-poor chemicals and suggest that several BPA alternative chemicals may cause hazards at similar concentrations to BPA.

The OECD Test Guideline 488 (TG 488) for the Transgenic Rodent Gene Mutation Assay has undergone several revisions to update the recommended design for studying mutations in somatic tissues and male germ cells. The recently revised TG recommends a single sampling time of 28 days following 28 days of exposure (i.e., 28 + 28 days) for all tissues, irrespective of proliferation rates. An alternative design (i.e., 28 + 3 days) is appropriate when germ cell data is not required, nor considered. While the 28 + 28 days design is clearly preferable for slowly proliferating somatic tissues and germ cells, there is still uncertainty about the impact of extending the sampling time to 28 days for rapidly somatic tissues. Here, we searched the available literature for evidence supporting the applicability and utility of the 28 + 28 days design for rapidly proliferating tissues. A total of 79 tests were identified. When directly comparing results from both designs in the same study, there was no evidence that the 28 + 28 days regimen resulted in a qualitatively different outcome from the 28 + 3 days design. Studies with a diverse range of agents that employed only a 28 + 28 days protocol provide further evidence that this design is appropriate for rapidly proliferating tissues. Benchmark dose analyses demonstrate high quantitative concordance between the 28 + 3 and 28 + 28 days designs for rapidly proliferating tissues. Accordingly, our review confirms that the 28 + 28 days design is appropriate to assess mutagenicity in both slowly and rapidly proliferating somatic tissues, and germ cells, and provides further support for the recommended design in the recently adopted TG 488.

Genotoxicity testing relies on the detection of gene mutations and chromosome damage and has been used in the genetic safety assessment of drugs and chemicals for decades. However, the results of standard genotoxicity tests are often difficult to interpret due to lack of mode of action information. The TGx-DDI transcriptomic biomarker provides mechanistic information on the DNA damage-inducing (DDI) capability of chemicals to aid in the interpretation of positive in vitro genotoxicity data. The CometChip® assay was developed to assess DNA strand breaks in a higher-throughput format. We paired the TGx-DDI biomarker with the CometChip® assay in TK6 cells to evaluate three model agents: nitrofurantoin (NIT), metronidazole (MTZ), and novobiocin (NOV). TGx-DDI was analyzed by two independent labs and technologies (nCounter® and TempO-Seq®). Although these anti-infective drugs are, or have been, used in human and/or veterinary medicine, the standard genotoxicity testing battery showed significant genetic safety findings. Specifically, NIT is a mutagen and causes chromosome damage, and MTZ and NOV cause chromosome damage in conventional in vitro tests. Herein, the TGx-DDI biomarker classified NIT and MTZ as non-DDI at all concentrations tested, suggesting that NIT’s mutagenic activity is bacterial specific and that the observed chromosome damage by MTZ might be a consequence of in vitro test conditions. In contrast, NOV was classified as DDI at the second highest concentration tested, which is in line with the fact that NOV is a bacterial DNA-gyrase inhibitor that also affects topoisomerase II at high concentrations. The lack of DNA damage for NIT and MTZ was confirmed by the CometChip® results, which were negative for all three drugs except at overtly cytotoxic concentrations. This case study demonstrates the utility of combining the TGx-DDI biomarker and CometChip® to resolve conflicting genotoxicity data and provides further validation to support the reproducibility of the biomarker.

Per- and polyfluoroalkyl substances (PFAS) are some of the most prominent organic contaminants in human blood. Although the toxicological implications of human exposure to perfluorooctane sulfonate (PFOS) and perfluorooctanoate (PFOA) are well established, data on lesser-understood PFAS are limited. New approach methodologies (NAMs) that apply bioinformatic tools to high-throughput data are being increasingly considered to inform risk assessment for data-poor chemicals. The aim of this study was to compare the potencies (ie, benchmark concentrations: BMCs) of PFAS in primary human liver microtissues (3D spheroids) using high-throughput transcriptional profiling. Gene expression changes were measured using TempO-seq, a templated, multiplexed RNA-sequencing platform. Spheroids were exposed for 1 or 10 days to increasing concentrations of 23 PFAS in 3 subgroups: carboxylates (PFCAs), sulfonates (PFSAs), and fluorotelomers and sulfonamides. PFCAs and PFSAs exhibited trends toward increased transcriptional potency with carbon chain-length. Specifically, longer-chain compounds (7–10 carbons) were more likely to induce changes in gene expression and have lower transcriptional BMCs. The combined high-throughput transcriptomic and bioinformatic analyses support the capability of NAMs to efficiently assess the effects of PFAS in liver microtissues. The data enable potency ranking of PFAS for human liver cell spheroid cytotoxicity and transcriptional changes, and assessment of in vitro transcriptomic points of departure. These data improve our understanding of the possible health effects of PFAS and will be used to inform read-across for human health risk assessment.

Per- and poly-fluoroalkyl substances (PFAS) are widely found in the environment because of their extensive use and persistence. Although several PFAS are well studied, most lack toxicity data to inform human health hazard and risk assessment. This study focused on 4 model PFAS: perfluorooctanoic acid (PFOA; 8 carbon), perfluorobutane sulfonate (PFBS; 4 carbon), perfluorooctane sulfonate (PFOS; 8 carbon), and perfluorodecane sulfonate (PFDS; 10 carbon). Human primary liver cell spheroids (pooled from 10 donors) were exposed to 10 concentrations of each PFAS and analyzed at 4 time points. The approach aimed to: (1) identify gene expression changes mediated by the PFAS, (2) identify similarities in biological responses, (3) compare PFAS potency through benchmark concentration analysis, and (4) derive bioactivity exposure ratios (ratio of the concentration at which biological responses occur, relative to daily human exposure). All PFAS induced transcriptional changes in cholesterol biosynthesis and lipid metabolism pathways, and predicted PPARα activation. PFOS exhibited the most transcriptional activity and had a highly similar gene expression profile to PFDS. PFBS induced the least transcriptional changes and the highest benchmark concentration (ie, was the least potent). The data indicate that these PFAS may have common molecular targets and toxicities, but that PFOS and PFDS are the most similar. The transcriptomic bioactivity exposure ratios derived here for PFOA and PFOS were comparable to those derived using rodent apical endpoints in risk assessments. These data provide a baseline level of toxicity for comparison with other known PFAS using this testing strategy.

International audience; Background: Decades of research to understand the impacts of various types of environmental occupational and medical stressors on human health have produced a vast amount of data across many scientific disciplines. Organizing these data in a meaningful way to support risk assessment has been a significant challenge. To address this and other challenges in modernizing chemical health risk assessment, the Organisation for Economic Cooperation and Development (OECD) formalized the Adverse Outcome Pathway (AOP) framework, an approach to consolidate knowledge into measurable key events (KEs) at various levels of biological organization causally linked to disease based on the weight of scientific evidence (http://oe.cd/aops). Currently, AOPs have been considered predominantly in chemical safety but are relevant to radiation. In this context, the Nuclear Energy Agency’s (NEA’s) High-LevelGroup on Low Dose Research (HLG-LDR) is working to improve research co-ordination, including radiological research with chemical research, identify synergies between the fields and to avoid duplication of efforts and resource investments. To this end, a virtual workshop was held on October 7-8th , 2020 with experts from the OECD AOP Programme together with the radiation and chemical research/regulation communities. The workshop, was a coordinated effort of Health Canada, the Electric Power Research Institute (EPRI), and the Nuclear Energy Agency (NEA). The AOP approach was discussed including key issues to fully embrace its value andcatalyze implementation in areas of radiation risk assessment. Conclusion: A joint chemical and radiological expert group was proposed as a means to encourage cooperation between risk assessors and an initial vision was discussed on a path forward. A global survey was suggested as a way to identify priority health outcomes of regulatory interest for AOP development. Multidisciplinary teams were needed to address the challenge of producing the appropriate data for risk assessments. Data management and machine learning tools were highlighted as a way to progress from weight of evidence to computational causal inference

Exposure to environmental mutagens increases the risk of cancer and genetic disorders. We used Duplex Sequencing (DS), a high-accuracy error-corrected sequencing technology, to analyze mutation induction across twenty 2.4 kb intergenic and genic targets in the bone marrow of MutaMouse males exposed to benzo(a)pyrene (BaP), a widespread environmental pollutant. DS revealed a linear dose-related induction of mutations across all targets with low intra-group variability. Heterochromatic and intergenic regions exhibited the highest mutation frequencies (MF). C:G > A:T transversions at CCA, CCC and GCC trinucleotides were enriched in BaP-exposed mice consistent with the known etiology of BaP mutagenesis. However, GC-content had no effect on mutation susceptibility. A positive correlation was observed between DS and the “gold-standard” transgenic rodent gene mutation assay. Overall, we demonstrate that DS is a promising approach to study in vivo mutagenesis and yields critical insight into the genomic features governing mutation susceptibility, spectrum, and variability across the genome.

Transgenic rodent (TGR) models use bacterial reporter genes to quantify in vivo mutagenesis. Pairing TGR assays with next-generation sequencing (NGS) enables comprehensive mutation pattern analysis to inform mutational mechanisms. We used this approach to identify 2751 independent lacZ mutations in the bone marrow of MutaMouse animals exposed to four chemical mutagens: benzo[a]pyrene, N-ethyl-N-nitrosourea, procarbazine, and triethylenemelamine. We also collected published data for 706 lacZ mutations from eight additional environmental mutagens. We report that lacZ gene sequencing generates chemical-specific mutation signatures observed in human cancers with established environmental causes. For example, the mutation signature of benzo[a]pyrene, a carcinogen present in tobacco smoke, matched the signature associated with tobacco-induced lung cancers. Our results suggest that the analysis of chemically induced mutations in the lacZ gene shortly after exposure provides an effective approach to characterize human-relevant mechanisms of carcinogenesis and propose novel environmental causes of mutation signatures observed in human cancers., Marc A. Beal, Matt J. Meier et al. use a transgenic rodent model with NGS to inform mutational signature analyses. They analyze lacZ mutations from the bone marrow of MutaMouse animals exposed to chemical mutagens. They report that lacZ sequencing generates chemical-specific mutation signatures observed in human cancers with established environmental causes.

Biomarkers predictive of molecular and toxicological effects are needed to interpret emerging high-throughput transcriptomics (HTTr) data streams. To address the limited approaches available for identifying epigenotoxicants, we previously developed and validated an 81-gene biomarker that accurately predicts histone deacetylase inhibition (HDACi) in transcript profiles derived from chemically-treated TK6 cells. In the present study, we sought to determine if this biomarker (TGx-HDACi) could be used to identify HDACi chemicals in other cell lines using the Running Fisher correlation test. Using microarray comparisons derived from human cells exposed to HDACi, we found considerable heterogeneity in correlation with the TGx-HDACi biomarker dependent on chemical exposure conditions and tissue from which the cell line was derived. Using a defined set of conditions that overlapped with our earlier study, the biomarker was able to accurately identify HDACi chemicals (90-100% balanced accuracy). In an in silico screen of 2427 chemicals in 9660 chemical versus control comparisons, the biomarker coupled with the Running Fisher test was able to identify 14 additional HDACi chemicals as well as other chemicals not previously associated with HDACi. Most notable were 12 inhibitors of bromodomain (BRD) and extraterminal (BET) family proteins including BRD4 that bind to acetylated histones. The BET protein inhibitors could be distinguished from the HDACi based on differences in the expression of a small set of biomarker genes. Our results indicate that the TGx-HDACi biomarker will be useful for identifying inhibitors of two classes of epigenome effectors in HTTr screening studies.

The Genetic Toxicology Technical Committee (GTTC) of the Health and Environmental Sciences Institute (HESI) is developing adverse outcome pathways (AOPs) that describe modes of action leading to potentially heritable genomic damage. The goal was to enhance the use of mechanistic information in genotoxicity assessment by building empirical support for the relationships between relevant molecular initiating events (MIEs) and regulatory endpoints in genetic toxicology. Herein, we present an AOP network that links oxidative DNA damage to two adverse outcomes (AOs): mutations and chromosomal aberrations. We collected empirical evidence from the literature to evaluate the key event relationships between the MIE and the AOs, and assessed the weight of evidence using the modified Bradford-Hill criteria for causality. Oxidative DNA damage is constantly induced and repaired in cells given the ubiquitous presence of reactive oxygen species and free radicals. However, xenobiotic exposures may increase damage above baseline levels through a variety of mechanisms and overwhelm DNA repair and endogenous antioxidant capacity. Unrepaired oxidative DNA base damage can lead to base substitutions during replication and, along with repair intermediates, can also cause DNA strand breaks that can lead to mutations and chromosomal aberrations if not repaired adequately. This AOP network identifies knowledge gaps that could be filled by targeted studies designed to better define the quantitative relationships between key events, which could be leveraged for quantitative chemical safety assessment. We anticipate that this AOP network will provide the building blocks for additional genotoxicity-associated AOPs and aid in designing novel integrated testing approaches for genotoxicity.

Adverse outcome pathways (AOPs) synthesize toxicological information to convey and weigh evidence in an accessible format. AOPs are constructed in modules that include key events (KEs) and key event relationships (KERs). This modular structure facilitates AOP expansion and network development. AOP development requires finding relevant information to evaluate the weight of evidence supporting each KER. To do this, the use of transparent/reproducible search methods, such as systematic review (SR), have been proposed. Applying SR to AOP development in a data-rich area is difficult as SR requires screening each article returned from a search. Here we describe a case study to integrate a single new KE into an existing AOP. We explored the use of SR concepts and software to conduct a transparent and documented literature search to identify empirical data supporting the incorporation of a new KE, increase in cellular reactive oxygen species (ROS), upstream of an existing AOP: “Oxidative DNA Damage Leading to Chromosomal Aberrations and Mutations”. Connecting this KE to the AOP is supported by the development of five new KERs, the most important being the first adjacent KER (increase in ROS leading to oxidative DNA damage). We initially searched for evidence of all five KERs and screened 100 papers to develop a preliminary evidence map. After removing papers not containing relevant data based on our Population, Exposure, Comparator and Outcome statement, 39 articles supported one or more KERs; these primarily addressed temporal or dose concordance of the non-adjacent KERs with limited evidence supporting the first adjacent KER. We thus conducted a second focused set of searches using search terms for specific methodologies to measure these first two KEs. After screening, 12 articles were identified that contained quantitative evidence supporting the first adjacent KER. Given that integrating a new KE into an existing AOP requires the development of multiple KERs, this approach of building a preliminary evidence map, focusing evidence gathering on the first adjacent KER, and applying reproducible search strategies using specific methodologies for the first adjacent KER, enabled us to prioritize studies to support expansion of this data-rich AOP.

Risk assessments are increasingly reliant on information from in vitro assays. The in vitro micronucleus test (MNvit) is a genotoxicity test that detects chromosomal abnormalities, including chromosome breakage (clastogenicity) and/or whole chromosome loss (aneugenicity). In this study, MNvit datasets for 292 chemicals, generated by the US EPA's ToxCast program, were evaluated using a decision tree-based pipeline for hazard identification. Chemicals were tested with 19 concentrations (n = 1) up to 200 µM, in the presence and absence of Aroclor 1254-induced rat liver S9. To identify clastogenic chemicals, %MN values at each concentration were compared to a distribution of batch-specific solvent controls; this was followed by cytotoxicity assessment and benchmark concentration (BMC) analyses. The approach classified 157 substances as positives, 25 as negatives, and 110 as inconclusive. Using the approach described in Bryce et al. (Environ Mol Mutagen 52:280-286, 2011), we identified 15 (5%) aneugens. IVIVE (in vitro to in vivo extrapolation) was employed to convert BMCs into administered equivalent doses (AEDs). Where possible, AEDs were compared to points of departure (PODs) for traditional genotoxicity endpoints; AEDs were generally lower than PODs based on in vivo endpoints. To facilitate interpretation of in vitro MN assay concentration-response data for risk assessment, exposure estimates were utilized to calculate bioactivity exposure ratio (BER) values. BERs for 50 clastogens and two aneugens had AEDs that approached exposure estimates (i.e., BER 100); these chemicals might be considered priorities for additional testing. This work provides a framework for the use of high-throughput in vitro genotoxicity testing for priority setting and chemical risk assessment.

The present AOP describes the prolonged activation of Cyp2E1 resulting in liver cancer. Cyp2E1 is a cytochrome P450 mono-oxygenase that bioactivates over 85 substrates, thereby creating electrophilic metabolites and oxidative stress. Mono-oxygenation of these substrates to their reactive metabolites, and the accompanying oxidative stress produced during metabolism, pose health risks because they lead to hepatotoxicity and, often, to liver cancer. The MIE occurs when Cyp2E1 binds a substrate. The Cyp2E1 catalytic cycle is prone to decoupling, which produces oxidative stress (KE1), and mono-oxidation of substrates produces reactive metabolites. Both reactive oxygen species and metabolites cause cytotoxicity (KE2). However, following injury, the liver is able to regenerate itself through an increase in cellular proliferation (KE3). Under conditions of chronic activation of Cyp2E1, excessive chronic increases in levels of reactive oxygen species and cell death, and subsequent dysregulated cellular proliferation, leads to tumour formation (AO).

Despite the widespread use of transcriptomics technologies in toxicology research, acceptance of the data by regulatory agencies to support the hazard assessment is still limited. Fundamental issues contributing to this are the lack of reproducibility in transcriptomics data analysis arising from variance in the methods used to generate data and differences in the data processing. While research applications are flexible in the way the data are generated and interpreted, this is not the case for regulatory applications where an unambiguous answer, possibly later subject to legal scrutiny, is required. A reference analysis framework would give greater credibility to the data and allow the practitioners to justify their use of an alternative bioinformatic process by referring to a standard. In this publication, we propose a method called omics data analysis framework for regulatory application (R-ODAF), which has been built as a user-friendly pipeline to analyze raw transcriptomics data from microarray and next-generation sequencing. In the R-ODAF, we also propose additional statistical steps to remove the number of false positives obtained from standard data analysis pipelines for RNA-sequencing. We illustrate the added value of R-ODAF, compared to a standard workflow, using a typical toxicogenomics dataset of hepatocytes exposed to paracetamol.

Advances in the biological sciences have led to an ongoing paradigm shift in toxicity testing based on expanded application of high-throughput in vitro screening and in silico methods to assess potential health risks of environmental agents. This review examines progress on the vision for toxicity testing elaborated by the US National Research Council (NRC) during the decade that has passed since the 2007 NRC report on Toxicity Testing in the 21st Century (TT21C). Concomitant advances in exposure assessment, including computational approaches and high-throughput exposomics, are also documented. A vision for the next generation of risk science, incorporating risk assessment methodologies suitable for the analysis of new toxicological and exposure data, resulting in human exposure guidelines is described. Case study prototypes indicating how these new approaches to toxicity testing, exposure measurement, and risk assessment are beginning to be applied in practice are presented. Overall, progress on the 20-year transition plan laid out by the US NRC in 2007 has been substantial. Importantly, government agencies within the United States and internationally are beginning to incorporate the new approach methodologies envisaged in the original TT21C vision into regulatory practice. Future perspectives on the continued evolution of toxicity testing to strengthen regulatory risk assessment are provided.

Based on increasing use of mechanistic information in risk assessment, Health Canada's (HC) Task Force on Scientific Risk Assessment established a working group to review and report on the application of toxicogenomics across HC's risk assessment bureaus. The aim was to review current applications and needs for toxicogenomics at HC, to document existing challenges and to promote consistent/coherent risk assessments that consider toxicogenomics. Overall, HC foresees a role for toxicogenomics in risk assessment. To date, select bureaus have incorporated toxicogenomic data, primarily in weight of evidence approaches, to support mode of action analysis. Future efforts to foster networks for increasing expertise/capacity around toxicogenomic data interpretation were viewed as valuable endeavours, and continued support of research to advance applications was recommended.

The MutaMouse transgenic rodent model is widely used for assessing in vivo mutagenicity. Here, we report the characterization of MutaMouse’s whole genome sequence and its genetic variants compared to the C57BL/6 reference genome. High coverage (>50X) next-generation sequencing (NGS) of whole genomes from multiple MutaMouse animals from the Health Canada (HC) colony showed ~5 million SNVs per genome, ~20% of which are putatively novel. Sequencing of two animals from a geographically separated colony at Covance indicated that, over the course of 23 years, each colony accumulated 47,847 (HC) and 17,677 (Covance) non-parental homozygous single nucleotide variants. We found no novel nonsense or missense mutations that impair the MutaMouse response to genotoxic agents. Pairing sequencing data with array comparative genomic hybridization (aCGH) improved the accuracy and resolution of copy number variants (CNVs) calls and identified 300 genomic regions with CNVs. We also used long-read sequence technology (PacBio) to show that the transgene integration site involved a large deletion event with multiple inversions and rearrangements near a retrotransposon. The MutaMouse genome gives important genetic context to studies using this model, offers insight on the mechanisms of structural variant formation, and contributes a framework to analyze aCGH results alongside NGS data.

Formalin-fixed paraffin-embedded (FFPE) tissues provide an important resource for toxicogenomic research. However, variability in the integrity or quality of RNA obtained from archival FFPE specimens can lead to unreliable data and wasted resources, and standard protocols for measuring RNA integrity do not adequately assess the suitability of FFPE RNA. The main goal of this study was to identify improved methods for evaluating FFPE RNA quality for whole-genome sequencing. We examined RNA quality metrics conducted prior to RNA-sequencing in paired frozen and FFPE samples with varying levels of quality based on age in block and time in formalin. RNA quality was measured by the RNA integrity number (RIN), a modified RIN called the paraffin-embedded RNA metric, the percentage of RNA fragments >100–300 nucleotides in size (DV100–300), and 2 quantitative PCR-based methods. This information was correlated to sequencing read quality, mapping, and gene detection. Among fragmentation-based methods, DV and PCR-based metrics were more informative than RIN or paraffin-embedded RNA metric in determining sequencing success. Across low- and high-quality FFPE samples, a minimum of 80% of RNA fragments >100 nucleotides (DV100 > 80) provided the best indication of gene diversity and read counts upon sequencing. The PCR-based methods further showed quantitative reductions in amplifiable RNA of target genes related to sample age and time in formalin that inform input quantity of FFPE RNA for sequencing. These results should aid in screening and prioritizing archival FFPE samples for retrospective analyses of gene expression.

Higher-throughput, mode-of-action-based assays provide a valuable approach to expedite chemical evaluation for human health risk assessment. In this study, we combined the high-throughput alkaline DNA damage-sensing CometChip® assay with the TGx-DDI transcriptomic biomarker (DDI = DNA damage-inducing) using high-throughput TempO-Seq®, as an integrated genotoxicity testing approach. We used metabolically competent differentiated human HepaRG™ cell cultures to enable the identification of chemicals that require bioactivation to cause genotoxicity. We studied 12 chemicals (nine DDI, three non-DDI) in increasing concentrations to measure and classify chemicals based on their ability to damage DNA. The CometChip® classified 10/12 test chemicals correctly, missing a positive DDI call for aflatoxin B1 and propyl gallate. The poor detection of aflatoxin B1 adducts is consistent with the insensitivity of the standard alkaline comet assay to bulky lesions (a shortcoming that can be overcome by trapping repair intermediates). The TGx-DDI biomarker accurately classified 10/12 agents. TGx-DDI correctly identified aflatoxin B1 as DDI, demonstrating efficacy for combined used of these complementary methodologies. Zidovudine, a known DDI chemical, was misclassified as it inhibits transcription, which prevents measurable changes in gene expression. Eugenol, a non-DDI chemical known to render misleading positive results at high concentrations, was classified as DDI at the highest concentration tested. When combined, the CometChip® assay and the TGx-DDI biomarker were 100% accurate in identifying chemicals that induce DNA damage. Quantitative benchmark concentration (BMC) modeling was applied to evaluate chemical potencies for both assays. The BMCs for the CometChip® assay and the TGx-DDI biomarker were highly concordant (within 4-fold) and resulted in identical potency rankings. These results demonstrate that these two assays can be integrated for efficient identification and potency ranking of DNA damaging agents in HepaRG™ cell cultures.

Transcriptomic biomarkers can be used to inform molecular initiating and key events involved in a toxicant’s mode of action. To address the limited approaches available for identifying epigenotoxicants, we developed and assessed a transcriptomic biomarker of histone deacetylase inhibition (HDACi). First, we assembled a set of 10 prototypical HDACi and 10 non-HDACi reference compounds. Concentration-response experiments were performed for each chemical to collect TK6 human lymphoblastoid cell samples after 4 hours of exposure and to assess cell viability following a 20h-recovery period in fresh media. One concentration was selected for each chemical for whole transcriptome profiling and transcriptomic signature derivation, based on cell viability at the 24-hour time point and on maximal induction of HDACi-response genes (RGL1, NEU1, GPR183) or cellular stress-response genes (ATF3, CDKN1A, GADD45A) analyzed by TaqMan qPCR assays after 4 hours of exposure. Whole transcriptomes were profiled after 4 hour exposures by Templated Oligo-Sequencing (TempO-Seq). By applying the nearest shrunken centroid (NSC) method to the whole transcriptome profiles of the reference compounds, we derived an 81-gene toxicogenomic (TGx) signature, referred to as TGx-HDACi, that classified all 20 reference compounds correctly using NSC classification and the Running Fisher test. An additional four HDACi and seven non-HDACi were profiled and analyzed using TGx-HDACi to further assess classification performance; the biomarker accurately classified all 11 compounds, including three non-HDACi epigenotoxicants, suggesting a promising specificity toward HDACi. The availability of TGx-HDACi increases the diversity of tools that can facilitate mode of action analysis of toxicants using gene expression profiling.

Context Human studies consistently show an association between exposure to persistent organic pollutants, including 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD, aka “dioxin”), and increased diabetes risk. We previously showed that a single high-dose TCDD exposure (20 µg/kg) decreased plasma insulin levels in male and female mice in vivo, but effects on glucose homeostasis were sex-dependent. Objective The current study assessed whether prolonged exposure to a physiologically relevant low-dose of TCDD impacts glucose homeostasis and/or the islet phenotype in a sex-dependent manner in chow-fed or high-fat diet (HFD)-fed mice. Methods Male and female mice were exposed to 20 ng/kg/d TCDD 2×/week for 12 weeks and simultaneously fed standard chow or a 45% HFD. Glucose homeostasis was assessed by glucose and insulin tolerance tests, and glucose-induced plasma insulin levels were measured in vivo. Histological analysis was performed on pancreas from male and female mice, and islets were isolated from females for TempO-Seq transcriptomic analysis. Results Low-dose TCDD exposure did not lead to adverse metabolic consequences in chow-fed male or female mice, or in HFD-fed males. However, TCDD accelerated the onset of HFD-induced hyperglycemia and impaired glucose-induced plasma insulin levels in females. TCDD caused a modest increase in islet area in males but reduced the percent beta cell area within islets in females. TempO-Seq analysis suggested abnormal changes to endocrine and metabolic pathways in female TCDDHFD islets. Conclusion Our data suggest that prolonged low-dose TCDD exposure has minimal effects on glucose homeostasis and islet morphology in chow-fed male and female mice but promotes maladaptive metabolic responses in HFD-fed females.

Per- and polyfluoroalkyl substances (PFAS) are some of the most prominent organic contaminants in human blood. Although the toxicological implications from human exposure to perfluorooctane sulfonate (PFOS) and perfluorooctanoate (PFOA) are well established, data on lesser-understood PFAS are limited. New approach methodologies (NAMs) that apply bioinformatic tools to high-throughput data are being increasingly considered to inform risk assessment for data-poor chemicals. The aim of this investigation was to identify biological response potencies (i.e., benchmark concentrations: BMCs) following PFAS exposures to inform read-across for risk assessment of data-poor PFAS. Gene expression changes were measured in primary human liver cell microtissues (i.e., 3D spheroids) after 1-day and 10-day exposures to increasing concentrations of 23 PFAS. The cells were treated with four subgroups of PFAS: carboxylates (PFCAs), sulfonates (PFSAs), fluorotelomers, and sulfonamides. An established pipeline to identify differentially expressed genes and transcriptomic BMCs was applied. We found that both PFCAs and PFSAs exhibited a trend toward increased transcriptional changes with carbon chain-length. Specifically, longer-chain compounds (7 to 10 carbons) were more likely to induce changes in gene expression, and have lower transcriptional BMCs. The combined high-throughput transcriptomic and bioinformatic analyses supports the capability of NAMs to efficiently assess the effects of PFAS in liver microtissues. The data enable potency ranking of PFAS for human liver cell spheroid cytotoxicity and transcriptional changes, and assessment of in vitro transcriptomic points of departure. These data improve our understanding of the health effects of PFAS and will be used to inform read-across for human health risk assessment.

Bisphenol A (BPA) is a chemical used in the manufacturing of plastics to which human exposure is ubiquitous. Numerous studies have linked BPA exposure to many adverse health outcomes prompting the replacement of BPA with various analogues including bisphenol-F (BPF) and bisphenol S (BPS). Other bisphenols are used in various consumer applications, such as 3,3′,5,5’-Tetrabromobisphenol A (TBBPA), which is used as a flame retardant. Few studies to date have examined the effects of BPA and its analogues in stem cells to explore potential developmental impacts. Here we used transcriptomics to investigate similarities and differences of BPA and three of its analogues in the estrogen receptor negative, human embryonic stem cell line H9 (WA09). H9 cells were exposed to increasing concentrations of the bisphenols and analyzed using RNA-sequencing. Our data indicate that BPA, BPF, and BPS have similar potencies in inducing transcriptional changes and perturb many of the same pathways. TBBPA, the least structurally similar bisphenol of the group, exhibited much lower potency. All bisphenols robustly impacted gene expression in these cells, albeit at concentrations well above those observed in estrogen-positive cells. Overall, we provide a foundational data set against which to explore the transcriptional similarities of other bisphenols in embryonic stem cells, which may be used to assess the suitability of chemical grouping for read-across and for preliminary potency evaluation.

Per- and poly-fluoroalkyl substances (PFAS) are widely found in the environment because of their extensive use and persistence. Although several PFAS are well studied, most lack toxicity data to inform human health hazard and risk assessment. This study focussed on four model PFAS: perfluorooctanoic acid (PFOA; 8 carbon), perfluorobutane sulfonate (PFBS; 4 carbon), perfluorooctane sulfonate (PFOS; 8 carbon), and perfluorodecane sulfonate (PFDS; 10 carbon). Human primary liver cell spheroids (pooled from 10 donors) were exposed to 10 concentrations of each PFAS and analyzed at four time-points. The approach aimed to: (1) identify gene expression changes mediated by the PFAS; (2) identify similarities in biological responses; (3) compare PFAS potency through benchmark concentration analysis; and (4) derive bioactivity exposure ratios (ratio of the concentration at which biological responses occur, relative to daily human exposure). All PFAS induced transcriptional changes in cholesterol biosynthesis and lipid metabolism pathways, and predicted PPARα activation. PFOS exhibited the most transcriptional activity and had a highly similar gene expression profile to PFDS. PFBS induced the least transcriptional changes and the highest benchmark concentration (i.e., was the least potent). The data indicate that these PFAS may have common molecular targets and toxicities, but that PFOS and PFDS are the most similar. The transcriptomic bioactivity exposure ratios derived here for PFOA and PFOS were comparable to those derived using rodent apical endpoints in risk assessments. These data provide a baseline level of toxicity for comparison with other known PFAS using this testing strategy.

The Organisation for Economic Co-Operation and Development Test Guideline 488 (TG 488) uses transgenic rodent models to generate in vivo mutagenesis data for regulatory submission. The recommended design in TG 488, 28 consecutive daily exposures with tissue sampling three days later (28 + 3d), is optimized for rapidly proliferating tissues such as bone marrow (BM). A sampling time of 28 days (28 + 28d) is considered more appropriate for slowly proliferating tissues (e.g., liver) and male germ cells. We evaluated the impact of the sampling time on mutant frequencies (MF) in the BM of MutaMouse males exposed for 28 days to benzo[a]pyrene (BaP), procarbazine (PRC), isopropyl methanesulfonate (iPMS), or triethylenemelamine (TEM) in dose–response studies. BM samples were collected + 3d, + 28d, + 42d or + 70d post exposure and MF quantified using the lacZ assay. All chemicals significantly increased MF with maximum fold increases at 28 + 3d of 162.9, 6.6, 4.7 and 2.8 for BaP, PRC, iPMS and TEM, respectively. MF were relatively stable over the time period investigated, although they were significantly increased only at 28 + 3d and 28 + 28d for TEM. Benchmark dose (BMD) modelling generated overlapping BMD confidence intervals among the four sampling times for each chemical. These results demonstrate that the sampling time does not affect the detection of mutations for strong mutagens. However, for mutagens that produce small increases in MF, sampling times greater than 28 days may produce false-negative results. Thus, the 28 + 28d protocol represents a unifying protocol for simultaneously assessing mutations in rapidly and slowly proliferating somatic tissues and male germ cells.

ObjectiveHuman studies consistently show an association between exposure to persistent organic pollutants, including 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD, aka “dioxin”), and increased diabetes risk, but rarely consider potential sex differences. We previously showed that a single high-dose TCDD exposure (20 µg/kg) decreased plasma insulin levels in both male and female mice in vivo, but effects on glucose homeostasis were sex-dependent. The purpose of the current study was to determine whether prolonged exposure to a physiologically relevant low-dose of TCDD impacts glucose homeostasis and/or the islet phenotype in a sex-dependent manner in either chow-fed or high fat diet (HFD)-fed mice.MethodsMale and female mice were exposed to 20 ng/kg/d TCDD 2x/week for 12 weeks and simultaneously fed standard chow or a 45% HFD. Glucose homeostasis was assessed by glucose and insulin tolerance tests, and glucose-induced plasma insulin levels were measured in vivo. Histological analysis was performed on pancreas from male and female mice, and islets were isolated from females at 12 weeks for Tempo-Seq® analysis.ResultsLow-dose TCDD exposure did not lead to adverse metabolic consequences in chow-fed male or female mice, or in HFD-fed males. However, TCDD accelerated the onset of HFD-induced hyperglycemia and impaired glucose-induced plasma insulin levels in female mice. TCDD caused a modest increase in islet area in males irrespective of diet, but reduced % beta cell area within islets in females. RNAseq analysis of female islets also revealed abnormal changes to endocrine and metabolic pathways in TCDD-exposed HFD-fed females compared chow-fed females.ConclusionsOur data suggest that prolonged low-dose TCDD exposure has minimal effects on glucose homeostasis and islet morphology in chow-fed male and female mice, but promotes maladaptive metabolic responses in HFD-fed females.

Polycyclic aromatic hydrocarbons like benzo[a]pyrene (BaP) are ubiquitous environmental contaminants formed during incomplete combustion of organic materials. Our prior work showed that transplacental exposure to BaP depletes ovarian follicles and increases prevalence of epithelial ovarian tumors later in life. We used the MutaMouse transgenic rodent model to address the hypothesis that ovarian mutations play a role in tumorigenesis caused by prenatal exposure to BaP. Pregnant MutaMouse females were treated with 0, 10, 20, or 40 mg/(kg day) BaP orally on gestational days 7-16, covering critical windows of ovarian development. Female offspring were euthanized at 10 weeks of age; some ovaries with oviducts were processed for follicle counting; other ovaries/oviducts and bone marrow were processed for determination of lacZ mutant frequency (MF). Mutant plaques were pooled within dose groups and sequenced to determine the mutation spectrum. BaP exposure caused highly significant dose-related decreases in ovarian follicles and increases in ovarian/oviductal and bone marrow mutant frequencies at all doses. Absence of follicles, cell packets, and epithelial tubular structures were observed with 20 and 40 mg/(kg day) BaP. Depletion of ovarian germ cells was inversely associated with ovarian MF. BaP induced primarily G > T and G > C transversions and deletions in ovaries/oviducts and bone marrow cells and produced a mutation signature highly consistent with that of tobacco smoking in human cancers. Overall, our results show that prenatal BaP exposure significantly depletes ovarian germ cells, causes histopathological abnormalities, and increases the burden of ovarian/oviductal mutations, which may be involved in pathogenesis of epithelial ovarian tumors. Environ. Mol. Mutagen. 60:410-420, 2019. © 2018 Her Majesty the Queen in Right of Canada.

In 2012, the Organization for Economic Cooperation and Development (OECD) formally launched the Adverse Outcome Pathway (AOP) Programme. The AOP framework has the potential for predictive utility in identifying early biological endpoints linked to adverse effects. It uses the weight of correlative evidence to identify a minimal set of measurable key events that link molecular initiating events to an adverse outcome. AOPs have the capability to identify knowledge gaps and priority areas for future research based on relevance to an adverse outcome. In addition, AOPs can identify pathways that are common among multiple stressors, thereby allowing for the possibility of refined risk assessments based on co-exposure considerations. The AOP framework is increasingly being used in chemical and ecological risk assessment; however, its use in the development of radiation-specific pathways has yet to be fully explored. To bring awareness of the AOP framework to the Canadian radiation community, a workshop was held in Canada in June 2018 that brought together radiation experts from Health Canada, the Canadian Nuclear Laboratories, and the Canadian Nuclear Safety Commission.The purpose of the workshop was to share knowledge on the AOP framework, specifically (1) to introduce the concept of the AOP framework and its possible utility to Canadian radiation experts; (2) to provide examples on how it has advanced risk assessment; (3) to discuss an illustrative example specific to ionizing radiation; and lastly (4) to identify the broad benefits and challenges of the AOP framework to the radiation community.The participants showed interest in the framework, case examples were described and areas of challenge were identified. Herein, we summarize the outcomes of the workshop.Overall, participants agreed that by building AOPs in the radiation field, a network of data-sharing initiatives will enhance our interpretation of existing knowledge where current scientific evidence is minimal. They would provide new avenues to understand effects at low-dose and dose-rates and help to quantify the combined effect of multiple stressors on shared mechanistic pathways.