Project description:Background: Modern testing paradigms seek to apply human-relevant cell culture models and integrate data from multiple test systems to accurately inform potential hazards and modes of action for chemical toxicology. In genetic toxicology, the use of metabolically competent human hepatocyte cell culture models provides clear advantages over other more commonly used cell lines that require the use of external metabolic activation systems, such as rat liver S9. HepaRG™ cells are metabolically competent cells that express Phase I and II metabolic enzymes and differentiate into mature hepatocyte-like cells, making them ideal for toxicity testing. We assessed the performance of the flow cytometry in vitro micronucleus (MN) test and the TGx-DDI transcriptomic biomarker to detect DNA damage-inducing (DDI) chemicals in human HepaRG™ cells after a 3-day repeat exposure. The biomarker, developed for use in human TK6 cells, is a panel of 64 genes that accurately classifies chemicals as DDI or non-DDI. Herein, the TGx-DDI biomarker was analyzed by Ion AmpliSeq whole transcriptome sequencing to assess its classification accuracy using this more modern gene expression technology as a secondary objective. Methods: HepaRG™ cells were exposed to increasing concentrations of 10 test chemicals (six genotoxic chemicals, including one aneugen, and four non-genotoxic chemicals). Cytotoxicity and genotoxicity were measured using the In Vitro MicroFlow® kit, which was run in parallel with the TGx-DDI biomarker. Results: A concentration-related decrease in relative survival and a concomitant increase in MN frequency were observed for genotoxic chemicals in HepaRG™ cells. All five DDI and five non-DDI agents were correctly classified (as genotoxic/non-genotoxic and DDI/non-DDI) by pairing the test methods. The aneugenic agent (colchicine) yielded the expected positive result in the MN test and negative (non-DDI) result by TGx-DDI. Conclusions: This next generation genotoxicity testing strategy is aligned with the paradigm shift occurring in the field of genetic toxicology. It provides mechanistic insight in a human-relevant cell-model, paired with measurement of a conventional endpoint, to inform the potential for adverse health effects. This work provides support for combining these assays in an integrated test strategy for accurate, higher throughput genetic toxicology testing in this metabolically competent human progenitor cell line.

Project description: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-SeqTM 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.

Project description:There is a need to move from binary hazard assessment to more quantitative assessment of genotoxicity to better inform human health risk assessment and understand the relevance of positive in vitro genotoxicity findings. New approach methodologies (NAMs), including transcriptomic biomarkers combined with high-throughput technologies, enable the testing of a broad concentration range, which allows quantitative assessment of in vitro results. Initial work with the transcriptomic GENOMARK and TGx-DDI biomarkers demonstrate their potential use for hazard identification and chemical prioritization; however, no study has evaluated the concordance and complementarity of GENOMARK and TGx-DDI. The overall aim of this study is to examine if a combined approach of integrating both transcriptomic biomarkers for genotoxicity in human relevant HepaRGTM cells increases the certainty in hazard calls and potency rankings of chemicals. A sub-aim is to investigate whether GENOMARK is applicable to the TempO-Seq® high-throughput sequencing technology, to collect concentration-response data to rapidly perform hazard classification and potency ranking. Therefore, HepaRGTM cells were exposed to 10 chemicals (i.e. eight known in vivo genotoxicants and two in vivo non-genotoxicants) in increasing concentrations over 72h. TempO-Seq® was used to obtain concentration-response data for both biomarkers. Benchmark concentration (BMC) modelling of chemicals that were classified positive was conducted to obtain BMCs and transcriptomic points of departure (tPODs) for potency ranking. The results confirm that GENOMARK is applicable to TempO-Seq® since it achieved 100% predictive accuracy. In addition, a high concordance was observed in the hazard classifications and potency rankings between both biomarkers. Overall, our findings show that in vitro transcriptomic data can be used to rapidly and effectively identify genotoxic hazards while simultaneously providing additional insights on potency that is more informative in a modern hazard assessment paradigm. The results of this case study support the high value of integrating these NAMs in a weight of evidence evaluation of genotoxicity using the important human-liver cell line.

Dataset Information

CometChip® and TempO-Seq®: A high-throughput 96-well platform to measure and classify DNA damaging agents in human HepaRG™ Cells [HCC3]

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