In search of key genes associated with endometriosis using bioinformatics approach

OBJECTIVE: The aim of this study was to identify key genes associated with endometriosis. STUDY DESIGN: Microarray data GSE7846 was downloaded from Gene Expression Omnibus. The differentially expressed genes (DEGs) in human endometrial endothelial cells derived from eutopic endometrium of patients with endometriosis compared with controls without endometriosis were identified using Linear Models for Microarray Data (LIMMA) package in R. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and gene ontology (GO) enrichment analyses were performed using DAVID. Moreover, the protein-protein interaction (PPI) network was constructed by STRING and subsequently significantly enriched modules were mined by ClusterONE. Finally, protein domains and KEGG pathway enrichment analyses were performed for PPI modules. RESULTS: A total of 687 DEGs were identified, including 584 up- and 103 down-regulated genes. The up-regulated DEGs, such as epidermal growth factor (EGF) and interleukin 1 beta (IL-1β) were significantly enriched in KEGG pathways of focal adhesion, ECM-receptor interaction and calcium signaling pathway. Similarly, only one module was obtained form PPI network, and the genes, like angiotensin II receptor, Type 1 (AGTR1) in the module were mainly enriched in protein domain of rhodopsin-like G protein-coupled receptors and most altered pathways of neuroactive ligand-receptor interaction, calcium signaling pathway and vascular smooth muscle contraction. CONCLUSIONS: Our findings indicate that EGF, IL-1β and AGTR1 may play important roles in the pathogenesis of endometriosis.