Integrative Analysis Reveals Regulatory Programs in Endometriosis.

Area of Science:

• Gynecology
• Genomics
• Molecular Biology

Background:

• Endometriosis affects 10% of reproductive-age women.
• Gene expression changes in endometriosis are known, but regulatory transcription factors (TFs) are poorly understood.
• Systematic investigation of TFs governing endometriosis gene expression is lacking.

Purpose of the Study:

• To construct an integrated regulatory network (IRN) for endometriosis by combining gene expression, TF binding, and protein-protein interaction data.
• To identify key transcription factors (TFs) involved in the pathology of endometriosis.
• To explore the regulatory mechanisms of TFs in endometriosis.

Main Methods:

• Developed a novel method to integrate gene expression data with TF binding and protein-protein interaction data.
• Constructed an Integrated Regulatory Network (IRN) for endometriosis.
• Utilized enrichment analysis (hypergeometric distribution) on published gene expression datasets (GSE7305, GSE7307) to predict TFs.
• Validated selected TF regulation using quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC).

Main Results:

• Identified RUNX1 as the most significantly regulated gene in endometriosis, targeted by 14 TFs.
• Predicted 40 TFs involved in endometriosis, including known factors like androgen receptor (AR), estrogen receptor α, and estrogen receptor β.
• Identified novel TFs, including FOXA2 and TFAP2C, whose regulation was experimentally confirmed.
• Found that androgen receptor (AR) and p53 function in endometriosis is primarily regulated by posttranscriptional changes, not differential gene expression.

Conclusions:

• The developed IRN provides novel insights into the regulatory programs underlying endometriosis.
• Identified key TFs and regulatory pathways implicated in endometriosis pathogenesis.
• Highlights the importance of posttranscriptional regulation for certain TFs in endometriosis.