Identification Target Genes for Potential Biomarkers in Endometriosis from Transcriptomics Database

Abstract

Endometriosis is a common benign gynecological disease characterized by the ectopic growth of endometrial tissue. Its pathogenesis is influenced by complex genetic and epigenetic factors, making diagnosis and treatment challenging. This study aimed to identify molecular pathways and candidate genes associated with endometriosis using transcriptomic data. Three datasets (GSE7307, GSE23339, and GSE25628) were retrieved from the Gene Expression Omnibus (GEO) database and analyzed to identify differentially expressed genes (DEGs). A total of 339 intersecting DEGs were obtained and subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. The results indicated enrichment in biological processes related to epithelial cell proliferation and angiogenesis, cellular components associated with the lysosomal lumen and extracellular matrix, and molecular functions involving Wnt-activated receptor activity and low-density lipoprotein particle binding. Ten genes (TAGLN, C7, TCF21, GATA6, GPC3, FZD7, TCEAL2, KLF2, FMO1, and HOXC6) were identified as potential candidate biomarkers. These findings provide preliminary molecular insights into endometriosis and may support future experimental and clinical studies for biomarker development.