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Updated: Jun 12, 2026
High Content Screening Analysis to Evaluate the Toxicological Effects of Harmful and Potentially Harmful Constituents HPHC
Published on: May 10, 2016
High-throughput toxicogenomic screening of chemicals in the environment using metabolically competent hepatic cell
Jill A Franzosa1, Jessica A Bonzo2, John Jack1
1Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. EPA, Research Triangle Park, NC, 27711, USA.
Abstract:
The ToxCast in vitro screening program has provided concentration-response bioactivity data across more than a thousand assay endpoints for thousands of chemicals found in our environment and commerce. However, most ToxCast screening assays have evaluated individual biological targets in cancer cell lines lacking integrated physiological functionality (such as receptor signaling, metabolism). We evaluated differentiated HepaRGTM cells, a human liver-derived cell model understood to effectively model physiologically relevant hepatic signaling. Expression of 93 gene transcripts was measured by quantitative polymerase chain reaction using Fluidigm 96.96 dynamic arrays in response to 1060 chemicals tested in eight-point concentration-response. A Bayesian framework quantitatively modeled chemical-induced changes in gene expression via six transcription factors including: aryl hydrocarbon receptor, constitutive androstane receptor, pregnane X receptor, farnesoid X receptor, androgen receptor, and peroxisome proliferator-activated receptor alpha. For these chemicals the network model translates transcriptomic data into Bayesian inferences about molecular targets known to activate toxicological adverse outcome pathways. These data also provide new insights into the molecular signaling network of HepaRGTM cell cultures.
Insights
This study used HepaRG™ cells to analyze gene expression changes in response to 1060 chemicals. The findings link chemical exposures to toxicological adverse outcome pathways through key transcription factors.
Area of Science:
- Toxicology
- Molecular Biology
- Genomics
Background:
- ToxCast provides in vitro data on chemical bioactivity but often lacks physiological relevance.
- Existing assays frequently use cancer cell lines without integrated signaling or metabolism.
- Differentiated HepaRG™ cells offer a physiologically relevant human liver model.
Purpose of the Study:
- To evaluate differentiated HepaRG™ cells as a model for chemical screening.
- To investigate chemical-induced gene expression changes and their relation to toxicological pathways.
- To explore the molecular signaling network within HepaRG™ cell cultures.
Main Methods:
- Quantitative polymerase chain reaction (qPCR) measured 93 gene transcripts.
- Fluidigm 96.96 dynamic arrays were used for high-throughput gene expression analysis.
- A Bayesian framework modeled chemical effects on six key transcription factors.
Main Results:
- Gene expression was analyzed for 1060 chemicals across eight concentration points.
- The model inferred chemical activity related to aryl hydrocarbon receptor, constitutive androstane receptor, pregnane X receptor, farnesoid X receptor, androgen receptor, and peroxisome proliferator-activated receptor alpha.
- Transcriptomic data were translated into Bayesian inferences about molecular targets activating toxicological adverse outcome pathways.
Conclusions:
- Differentiated HepaRG™ cells effectively model hepatic signaling relevant to toxicology.
- The study provides a network model linking chemical exposures to adverse outcome pathways via transcription factor activity.
- New insights into the HepaRG™ cell molecular signaling network were generated.
