A 50-gene biomarker identifies estrogen receptor-modulating chemicals in a microarray compendium

• Published in: Chemico-biological interactions 2024-05, Vol.394, p.110952-110952, Article 110952
• Main Authors: Corton, J. Christopher, Matteo, Geronimo, Chorley, Brian, Liu, Jie, Vallanat, Beena, Everett, Logan, Atlas, Ella, Meier, Matthew J., Williams, Andrew, Yauk, Carole Lyn
• Format: Article
• Language: English
• Subjects: Benzhydryl Compounds - toxicity; Biomarker; Biomarkers - metabolism; Estrogen receptor; Estrogen Receptor Modulators - pharmacology; Gene Expression Profiling; High-throughput transcript profiling; Humans; MCF-7 Cells; MCF-7 cell line; Microarray; Oligonucleotide Array Sequence Analysis; Phenols - pharmacology; Phenols - toxicity; Receptors, Estrogen - genetics; Receptors, Estrogen - metabolism; Toxicogenomics
• ISSN: 0009-2797; 1872-7786
• DOI: 10.1016/j.cbi.2024.110952

High throughput transcriptomics (HTTr) profiling has the potential to rapidly and comprehensively identify molecular targets of environmental chemicals that can be linked to adverse outcomes. We describe here the construction and characterization of a 50-gene expression biomarker designed to identify estrogen receptor (ER) active chemicals in HTTr datasets. Using microarray comparisons, the genes in the biomarker were identified as those that exhibited consistent directional changes when ER was activated (4 ER agonists; 4 ESR1 gene constitutively active mutants) and opposite directional changes when ER was suppressed (4 antagonist treatments; 4 ESR1 knockdown experiments). The biomarker was evaluated as a predictive tool using the Running Fisher algorithm by comparison to annotated gene expression microarray datasets including those evaluating the transcriptional effects of hormones and chemicals in MCF-7 cells. Depending on the reference dataset used, the biomarker had a predictive accuracy for activation of up to 96%. To demonstrate applicability for HTTr data analysis, the biomarker was used to identify ER activators in a set of 15 chemicals that are considered potential bisphenol A (BPA) alternatives examined at up to 10 concentrations in MCF-7 cells and analyzed by full-genome TempO-Seq. Using benchmark dose (BMD) modeling, the biomarker genes stratified the ER potency of BPA alternatives consistent with previous studies. These results demonstrate that the ER biomarker can be used to accurately identify ER activators in transcript profile data derived from MCF-7 cells. [Display omitted] •High throughput transcriptomics profiling is being used to identify chemical targets.•Estrogen receptor (ER) is an important target of endocrine disruptors.•A gene expression biomarker that predicts ER activation was characterized.•The biomarker can identify ER activators with high accuracy (up to 96%).•The biomarker can stratify the ER potency of bisphenol A and alternatives.