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PROVIDER: PRJNA1189498 | ENA |
REPOSITORIES: ENA
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Project description:This study used high-throughput transcriptomics (HTTr) to evaluate the gene expression effects of 133 per- and polyfluoroalkyl substances (PFAS) in HepaRG cells. The PFAS chemicals were selected using a category-based prioritization approach developed by the U.S. Environmental Protection Agency (EPA) to ensure representation of structurally diverse compounds with relevance to human exposure and regulatory interest (Patlewicz et al., 2019; https://doi.org/10.1289/EHP4555). Differentiated HepaRG cells were exposed to each PFAS in concentration-response format (0.1 to 100 µM) for 24 hours. Transcriptomic changes were measured using the TempO-Seq platform (BioSpyder Technologies), enabling expression profiling of approximately 20,000 human genes. The resulting gene expression data were used to characterize the concentration-dependent molecular responses to PFAS exposure using connectivity mapping and to derive transcriptomic points of departure (tPODs). This dataset contributes to a broader effort to screen the bioactivity of environmental chemicals using HTTr in human liver-derived cells. It supports the use of transcriptomic profiling to identify bioactive PFAS, elucidate affected molecular pathways, and inform chemical hazard assessment.
2025-11-21 | GSE296248 | GEO
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.
2021-07-21 | GSE171360 | GEO
Project description:High-Throughput Transcriptomics Platform for Screening Environmental Chemicals
| PRJNA683595 | ENA
Project description:With thousands of chemicals in commerce and the environment, rapid identification of potential hazards is a critical need. Combining broad molecular profiling with targeted in vitro assays, such as high-throughput transcriptomics (HTTr) and receptor screening assays, could improve identification of chemicals that perturb key molecular targets associated with adverse outcomes. We aimed to link transcriptomic readouts to individual molecular targets and integrate transcriptomic predictions with orthogonal receptor-level assays in a proof-of-concept framework for chemical hazard prioritization. Transcriptomic profiles generated via TempO-Seq in U-2 OS and HepaRG cell lines were used to develop signatures comprised of genes uniquely responsive to reference chemicals for distinct molecular targets. These signatures were applied to 75 reference and 1,126 non-reference chemicals screened via HTTr in both cell lines. Selective bioactivity towards each signature was determined by comparing potency estimates against the bulk of transcriptomic bioactivity for each chemical. Chemicals predicted by transcriptomics were confirmed for target bioactivity and selectivity using available orthogonal assay data from US EPA’s ToxCast program. A subset of 37 selectively acting chemicals from HTTr that did not have sufficient orthogonal data were prospectively tested using one of five receptor-level assays. Of the 1,126 non-reference chemicals screened, 201 demonstrated selective bioactivity in at least one transcriptomic signature, and 57 were confirmed as selective nuclear receptor agonists. Chemicals bioactive for each signature were significantly associated with orthogonal assay bioactivity, and signature-based points-of-departure were equally or more sensitive than biological pathway altering concentrations in 81.2% of signature-prioritized chemicals. Prospective profiling found that 18 of 37 (49%) chemicals without prior orthogonal assay data were bioactive against the predicted receptor. Our work demonstrates that integrating transcriptomics with targeted orthogonal assays in a tiered framework can support Next Generation Risk Assessment by informing putative molecular targets and prioritizing chemicals for further testing. NOTE: this GEO entry only includes the HepaRG cell line data; the U-2 OS cell line data can be located via GEO accession number GSE274318.
2025-03-25 | GSE284321 | GEO
Project description:High-Throughput Transcriptomic Profiling of PFAS Chemicals for Molecular Targets and Potency in HepaRG Cells
| PRJNA1254200 | ENA
Project description:Rapidly increasing number of man-made chemicals urges the development of reliable time- and cost-effective approaches for the carcinogen detection and identification. Considering this, the utility of high throughput microarray gene expression profiling for the identification of genotoxic and non-genotoxic carcinogens in vitro was investigated. Human terminally differentiated hepatic HepaRG cells were treated with model liver carcinogens, genotoxic carcinogen aflatoxin B1 (AFB1) and non-genotoxic carcinogen methapyrilene, at IC10 and IC25 concentrations for 72 hours, and transcriptomic profiles were determined. Treatment of HepaRG cells with IC10 and IC25 concentrations of AFB1 resulted in altered expression of 538 and 3033 genes (p-value ≤0.01 and fold change ≥2.0), respectively, and treatment of HepaRG cells with methapyrilene at the IC10 and IC25 concentrations altered the expression of 1255 and 1861 genes, respectively. Pathway analysis of transcriptomic signatures in HepaRG cells treated with minimally cytotoxic IC10 concentrations of AFB1 and methapyrilene demonstrated a strong enrichment in genes involved in key carcinogen-associated pathways, including receptor-mediated effects, detoxification response, cell death and apoptosis, cell proliferation and survival, oxidative stress and inflammation. Importantly, DNA damage and repair, cell cycle progression, and cell cycle checkpoint control pathways were uniquely activated in AFB1-treated HepaRG cells, whereas receptor-mediated signaling detoxification response pathway was predominantly altered in methapyrilene-treated HepaRG cells. In summary, high throughput microarray gene expression approach identifies specific carcinogen-exposure-associated transcriptomic responses and identifies affected molecular pathways, and categorize pathways associated with carcinogen exposure in a short-term in vitro test.
2016-09-17 | GSE87028 | GEO
Project description:Multiple new approach methods (NAMs) are being developed to rapidly screen large numbers of chemicals to aid in hazard evaluation and risk assessments. High-throughput transcriptomics (HTTr) in human cell lines has been proposed as a first-tier screening approach for determining the types of bioactivity a chemical can cause (activation of specific targets vs. generalized cell stress) and for calculating transcriptional points of departure (tPODs) based on changes in gene expression. In the present study, we examine a range of computational methods to calculate tPODs from HTTr data, using six data sets in which MCF7 cells cultured in two different media formulations were treated with a panel of 44 chemicals for 3 different exposure durations (6, 12, 24 hr).
2023-12-05 | GSE249377 | GEO
Project description:New approach methodologies (NAMs) aim to accelerate the pace of chemical risk assessment while simultaneously reducing cost and dependency on animal studies. High Throughput Transcriptomics (HTTr) is an emerging NAM in the field of chemical hazard evaluation for establishing in vitro points-of-departure and providing mechanistic insight. In the current study, 1,201 test chemicals were screened for bioactivity at eight concentrations using a 24-hour exposure duration in the human- derived U-2 OS osteosarcoma cell line with HTTr. Assay reproducibility was assessed using three reference chemicals that were screened on every assay plate. The resulting transcriptomics data were analyzed by aggregating signal from genes into signature scores using gene set enrichment analysis, followed by concentration-response modeling of signatures scores. Signature scores were used to predict putative mechanisms of action, and to identify biological pathway altering concentrations (BPACs). BPACs were consistent across replicates for each reference chemical, with replicate BPAC standard deviations as low as 5.6×10-3 µM, demonstrating the internal reproducibility of HTTr-derived potency estimates. BPACs of test chemicals showed modest agreement (R2 = 0.55) with existing phenotype altering concentrations from high throughput phenotypic profiling using Cell Painting of the same chemicals in the same cell line. Altogether, this HTTr based chemical screen contributes to an accumulating pool of publicly available transcriptomic data relevant for chemical hazard evaluation and reinforces the utility of cell based molecular profiling methods in estimating chemical potency and predicting mechanism of action across a diverse set of chemicals.
2024-08-20 | GSE274318 | GEO
Project description:The experiment investigates the effects of five well-known chemicals on the transcriptome of the HepaRG cell line, a metabolically competent hepatic cell line. The cells were treated individually with an increasing concentrations of aflatoxin B1, benzo[a]pyrene, cyclosporine A, rotenone or trichostatin A at five exposure time points followed by targeted RNA-seq using TempO-Seq technology (the panel of human whole transcriptome). The aim of the study was to explore how and to what extent the point-of-departure (POD) obtained from an in vitro transcriptomics study varied as a function of exposure time.
2023-08-01 | E-MTAB-13168 | biostudies-arrayexpress
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.
2020-02-18 | GSE136009 | GEO