Dataset Information

Development of a transcriptomic biomarker to detect histone deacetylase inhibitors (HDACi) in TK6 cells

ABSTRACT: Transcriptomic signatures, or biomarkers, of toxicity can facilitate rapid mechanistic analysis of chemicals using high-content transcriptomic data and identification of potential hazards to human health. We developed an 81-gene transcriptomic biomarker, named TGx-HDACi, to detect histone deacetylase inhibitors (HDACi) in TK6 human lymphoblastoid cells after 4 hours of chemical exposure. This work leveraged an established transcriptomic biomarker of DNA damage, TGx-DDI, which was developed by Heng Hong Li et al. (2015); TGx-DDI contains 63 genes and can distinguish between DNA damage-inducing (DDI) and non-DDI agents after 4 hours of exposure in TK6 cells. TGx-HDACi was derived from Templated Oligo-Sequencing (TempO-Seq) whole transcriptome gene expression profiles of 20 reference compounds, consisting of 10 HDACi and 10 non-HDACi compounds. Fourteen of the TGx-HDACi reference compounds are also part of the 28-compound reference set for TGx-DDI. The nearest shrunken centroid (NSC) method was applied to the gene expression profiles and 81 genes were identified that accurately identified HDACi compounds in the NSC probability analysis. The classification performance of TGx-HDACi was validated using an additional set of 11 test compounds (4 HDACi and 7 non-HDACi). Thus far, TGx-HDACi has demonstrated 100% accuracy. The availability of TGx-HDACi increases the diversity of tools that can facilitate mode of action analysis of toxicants using gene expression profiling.

ORGANISM(S): blank sample Homo sapiens

PROVIDER: GSE164478 | GEO | 2021/04/14

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

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: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:Introduction: 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 CometChip® assay with the TGx-DDI transcriptomic biomarker (DDI = DNA damage-inducing) using high-throughput TempO-Seq® as an integrated genotoxicity testing approach. Objective: To determine if the high-throughput CometChip® assay and TGx-DDI biomarker analysis can be combined using human HepaRG™ cells to provide an efficient next-generation genotoxicity screening approach to identify DNA damage-inducing (DDI) chemicals. Methods: Metabolically competent human HepaRG™ cell cultures were exposed to increasing concentrations of 12 chemicals (9 DDI and 3 non-DDI) using a repeat exposure design (0 hr, 24 hr, 48 hr) in 96-well plates to measure and classify chemicals based on their ability to damage DNA. After a 4 hr recovery period, exposed cells were used to perform the Trevigen CometChip assay to assess DNA damage or used for TempO-Seq® S1500+ Targeted Transcriptome Sequencing for TGx-DDI classification purposes. Bioinformatics and statistical tools were used to classify chemicals as DDI or non-DDI using three separate analyses. Benchmark concentration analysis was also conducted for both assays for the purposes of potency ranking. Results: In combination, the CometChip® assay and the TGx-DDI 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 for all 12 chemicals were highly concordant (within four-fold) and resulted in identical potency rankings. Conclusions: These results suggest that these two assays can be integrated for efficient, high-throughput identification of DNA damage in HepaRG™ cells. This study provides evidence for the complementarity of the high-throughput CometChip® assay with TGx-DDI biomarker analysis. Integration of these two tests provides an effective and high-throughput approach to identify DDI agents. This work is a first step in accomplishing a more integrated genotoxicity testing strategy to derive mechanistic information to better inform human health risk assessment in a high-throughput manner.

Dataset Information

Development of a transcriptomic biomarker to detect histone deacetylase inhibitors (HDACi) in TK6 cells

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets