Elucidating the role of transcription factors in molecular pathways underlying infertility in endometriosis: a bioinformatics approach

Abstract Objective Endometriosis is a multifactorial inflammatory disease characterized by the growth of endometrial-like tissue outside the uterus, frequently causing chronic pelvic pain and infertility. This study aimed to identify conserved differentially expressed genes (DEGs) and robust hub genes across heterogeneous cohorts to elucidate key molecular mechanisms in endometriosis pathogenesis. Methods Transcriptomic data from four independent microarray datasets (GSE7305, GSE120103, GSE23339, GSE51981) were analyzed using the Limma package in R to identify DEGs. Common DEGs were intersected across datasets, and a protein-protein interaction (PPI) network was constructed using STRING and visualized in Cytoscape (version 3.10.4). Hub genes were selected through a multi-metric approach in cytoHubba (MCC, Degree, EPC, DMNC). Functional enrichment (GO and pathway) and GeneMANIA network analysis were performed to explore biological roles. Results Intersection of DEGs revealed conserved expression signatures despite cohort heterogeneity. A consensus set of 20 hub genes was identified, with 12 (60%) functioning as transcription factors. Enrichment analysis highlighted transcriptional regulation, DNA binding, developmental processes (e.g., tissue development, pattern specification, embryonic morphogenesis), and epithelial barrier components (e.g., tight junctions). Pathway analysis implicated nuclear receptor signaling, developmental biology pathways, and WNT signaling.GeneMANIA analysis confirmed strong co-expression and physical interactions among hub genes, particularly in transcriptional and developmental functions. Conclusion The conserved hub genes, enriched in transcription factors, suggest central roles for transcriptional dysregulation and developmental pathways in endometriosis across diverse populations. These findings provide robust candidates for further validation as potential biomarkers or therapeutic targets.