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

Area of Science:

• Environmental toxicology
• Molecular biology
• Genomics

Background:

• High throughput transcriptomics (HTTr) enables rapid identification of molecular targets for environmental chemicals.
• Estrogen receptor (ER) activity is a key pathway for assessing chemical impacts and adverse outcomes.

Purpose of the Study:

• To construct and characterize a 50-gene expression biomarker for identifying ER-active chemicals in HTTr datasets.
• To evaluate the biomarker's predictive accuracy and applicability in analyzing environmental chemical effects.

Main Methods:

• Genes exhibiting consistent expression changes upon ER activation or suppression were identified using microarray comparisons.
• The biomarker was validated using the Running Fisher algorithm against annotated gene expression datasets.
• The biomarker's performance was assessed on full-genome TempO-Seq data from MCF-7 cells exposed to potential bisphenol A (BPA) alternatives.

Main Results:

• The 50-gene biomarker demonstrated high predictive accuracy (up to 96%) for ER activation.
• The biomarker successfully identified ER activators among BPA alternatives, stratifying their potency consistent with prior studies.
• Benchmark dose (BMD) modeling confirmed the biomarker's utility in assessing ER activity.

Conclusions:

• The developed ER biomarker is a reliable tool for identifying ER activators in transcriptomic data.
• This biomarker facilitates the assessment of environmental chemicals for potential endocrine-disrupting activity.
• The findings support the use of HTTr and targeted biomarkers for chemical safety evaluations.