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A Gene Expression Biomarker Predicts Heat Shock Factor 1 Activation in a Gene Expression Compendium
Citation:
Cervantes, P. AND C. Corton. A Gene Expression Biomarker Predicts Heat Shock Factor 1 Activation in a Gene Expression Compendium. CHEMICAL RESEARCH IN TOXICOLOGY. American Chemical Society, Washington, DC, 34(7):1721-1737, (2021). https://doi.org/10.1021/acs.chemrestox.0c00510
Impact/Purpose:
High-throughput transcriptomic (HTTr) technologies are being increasingly used to screen chemicals in human cell lines. The Environmental Protection Agency’s (EPA) Toxicity Forecaster (ToxCast) screening program is now using HTTr to augment the battery of individual ToxCast screening assays 20 with a targeted RNA-Seq technique called TempO-Seq 21. HTTr has the advantage over individual assays by examining the effects of environmental chemicals on essentially all pathways simultaneously, many of which are not examined by the battery of ToxCast assays 20. A major challenge for any transcript profiling strategy including HTTr is how to make linkages between chemical exposure and modulation of molecular targets. A number of approaches have been used to interpret the HTTr profiles, and these include typical pathway analysis as well as comparisons to archived profiles of reference chemicals (e.g., 22). While these approaches can lead to testable hypotheses as to the identity of chemical targets, they do not allow prediction with known accuracy. Gene expression biomarkers have emerged as a complementary approach to accurately identify specific molecular targets. Biomarkers are sets of genes known or predicted to be regulated by a particular transcription factor 23. The biomarker gene expression pattern is compared to gene expression profiles derived from human cells exposed to chemicals using a number of computational techniques that include correlation analysis 24. Gene expression biomarkers that predict modulation of estrogen receptor 25, androgen receptor 26, metal-induced transcription factor 1 27, and the oxidant-induced transcription factor NRF2 28 have been described. In addition, a biomarker that identifies chemical exposure conditions that lead to DNA damage has been extensively characterized 29,30 and is currently undergoing review by the Food and Drug Administration to be used as a tool to identify potential DNA damaging agents in human cells. A methodological analysis of gene expression profiles from cells exposed to reference chemicals as well as perturbations of the gene encoding the chemical target will eventually lead to a battery of highly predictive biomarkers that can be used to interpret HTTr data streams 23. The large quantity of microarray data that already exists in commercial databases and in public repositories will provide for in silico high-throughput screening (HTS) identification of chemical agents that activate or suppress human molecular targets. Approaches to assess HSF1 modulation in a large microarray compendium have not been previously described. In the present study, we developed procedures for predicting HSF1 perturbation in HTTr data. The biomarker was constructed from microarray profiles derived from cells treated with a HSP90 inhibitor in the presence or absence of HSF1 expression. The derived 44 genes were enriched for those involved in proteome maintenance, most of which were shown to be directly regulated by HSF1. The biomarker was used to screen a library of microarray profiles from cells treated with ~2600 organic chemicals to identify modulators of HSF1. The biomarker approach can readily identify chemical treatments known to activate HSF1, including inhibitors of HSP family members and inhibitors of the proteasome. Almost half of the chemical treatments that activated HSF1 also activated NRF2. Five chemicals were shown to activate NRF2 at lower doses or earlier times than HSF1, supporting a tiered cellular protection system. Our approach not only greatly expands the identification of chemicals that activate HSF1 but provides a proof of principle approach using a genetic-genomic strategy to build biomarkers that can be used to identify environmental chemicals that activate stress responses linked to human diseases.
Description:
The United States Environmental Protection Agency (US EPA) recently developed a tiered testing strategy to use advances in high-throughput transcriptomics (HTTr) testing to identify molecular targets of thousands of environmental chemicals that can be linked to adverse outcomes. Here, we describe a method that uses a gene expression biomarker to predict chemical activation of heat shock factor 1 (HSF1), a transcription factor critical for proteome maintenance. The HSF1 biomarker was built from transcript profiles derived from A375 cells exposed to a HSF1-activating heat shock protein (HSP) 90 inhibitor in the presence or absence of HSF1 expression. The resultant 44 identified genes included those that (1) are dependent on HSF1 for regulation, (2) have direct interactions with HSF1 assessed by ChIP-Seq, and (3) are in the molecular chaperone family. To test for accuracy, the biomarker was compared in a pairwise manner to gene lists derived from treatments with known HSF1 activity (HSP and proteasomal inhibitors) using the correlation-based Running Fisher test; the balanced accuracy for prediction was 96%. A microarray compendium consisting of 12,092 microarray comparisons from human cells exposed to 2670 individual chemicals was screened using our approach; 112 and 19 chemicals were identified as putative HSF1 activators or suppressors, respectively, and most appear to be novel modulators. A large percentage of the chemical treatments that induced HSF1 also induced oxidant-activated NRF2 (∼46%). For five compounds or mixtures, we found that NRF2 activation occurred at lower concentrations or at earlier times than HSF1 activation, supporting the concept of a tiered cellular protection system dependent on the level of chemical-induced stress. The approach described here could be used to identify environmentally relevant chemical HSF1 activators in HTTr data sets.
URLs/Downloads:
DOI: A Gene Expression Biomarker Predicts Heat Shock Factor 1 Activation in a Gene Expression Compendium
https://pubmed.ncbi.nlm.nih.gov/34170685/