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A Gene Expression Biomarker Identifies Chemical Modulators of Estrogen Receptor α in an MCF-7 Microarray Compendium.

John Rooney1, Natalia Ryan1, Jie Liu1

  • 1Center for Computational Toxicology and Exposure, US-EPA, Research Triangle Park, North Carolina 27711, United States.

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|January 6, 2021
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A 46-gene biomarker accurately predicts estrogen receptor alpha (ERα) modulation. Screening identified ~170 potential ERα modulators, including novel activators and suppressors, aiding endocrine disruption prediction.

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Area of Science:

  • Endocrinology
  • Toxicology
  • Genomics

Background:

  • Endocrine disruption prediction is crucial for public health.
  • A previously identified 46-gene biomarker accurately predicts estrogen receptor alpha (ERα) modulation in MCF-7 cells.

Purpose of the Study:

  • To identify potential ERα modulators using a 46-gene biomarker.
  • To screen a large chemical compendium for ERα activity.
  • To validate findings using various assays.

Main Methods:

  • Screening a microarray compendium (~1600 gene expression comparisons, ~1200 chemicals) using a 46-gene biomarker.
  • Utilizing the Connectivity Map 2.0 and Tox21 10K chemical library.
  • Performing gene expression analysis in wild-type and ERα-null cells, transactivation assays, and cell-free ERα coregulator interaction assays.

Main Results:

  • Identified ~170 potential ERα modulators.
  • Predicted 75 activators and 39 suppressors of ERα in the Connectivity Map 2.0.
  • Confirmed known and identified novel ERα activators (e.g., apigenin, digoxin, ivermectin) and suppressors (e.g., emetine, mifepristone).

Conclusions:

  • The 46-gene biomarker is effective for high-throughput screening of ERα modulators.
  • The strategy can identify environmentally relevant ERα modulators.
  • This approach aids in predicting endocrine-disrupting chemicals.