Abstract
BACKGROUND: Endometriosis is one of the chronic and prevalent diseases among women. There is limited knowledge about its pathophysiology at the cellular and molecular levels, causing a lack of a definite cure for this disease. In this study, differentially expressed genes (DEGs) between ectopic and paired eutopic endometrium in women with endometriosis were analyzed through bioinformatics analysis for better understanding of the molecular pathogenesis of endometriosis. METHODS: Gene expression data of ectopic and paired eutopic endometrium were taken from the Gene Expression Omnibus database. DEGs were screened by the Limma package in R with considering specific criteria. Then, the protein-protein interaction network was reconstructed between DEGs. The fast unfolding clustering algorithm was used to find sub-networks (modules). Finally, the three most relevant modules were selected and the functional and pathway enrichment analyses were performed for the selected modules. RESULTS: A total of 380 DEGs (245 up-regulated and 135 down-regulated) were identified in the ectopic endometrium and compared with paired eutopic endometrium. The DEGs were predominantly enriched in an ensemble of genes encoding the extracellular matrix and associated proteins, metabolic pathways, cell adhesions and the innate immune system. Importantly, DPT, ASPN, CHRDL1, CSTA, HGD, MPZ, PED1A, and CLEC10A were identified as novel DEGs between the human ectopic tissue of endometrium and its paired eutopic endometrium. CONCLUSION: The results of this study can open up a new window to better understanding of the molecular pathogenesis of endometriosis and can be considered for designing new treatment modalities.