Genome-wide expressions in autologous eutopic and ectopic endometrium of fertile women with endometriosis

Abstract

Abstract Background In order to obtain a lead of the pathophysiology of endometriosis, genome-wide expressional analyses of eutopic and ectopic endometrium have earlier been reported, however, the effects of stages of severity and phases of menstrual cycle on expressional profiles have not been examined. The effect of genetic heterogeneity and fertility history on transcriptional activity was also not considered. In the present study, a genome-wide expression analysis of autologous, paired eutopic and ectopic endometrial samples obtained from fertile women (n = 18) suffering from moderate (stage 3; n = 8) or severe (stage 4; n = 10) ovarian endometriosis during proliferative (n = 13) and secretory (n = 5) phases of menstrual cycle was performed. Methods Individual pure RNA samples were subjected to Agilent’s Whole Human Genome 44K microarray experiments. Microarray data were validated (P Results Higher clustering effect of pairing (cluster distance, cd = 0.1) in samples from same individuals on expressional arrays among eutopic and ectopic samples was observed as compared to that of clinical stages of severity (cd = 0.5) and phases of menstrual cycle (cd = 0.6). Post hoc analysis revealed anomaly in the expressional profiles of several genes associated with immunological, neuracrine and endocrine functions and gynecological cancers however with no overt oncogenic potential in endometriotic tissue. Dys-regulation of three (CLOCK, ESR1, and MYC) major transcription factors appeared to be significant causative factors in the pathogenesis of ovarian endometriosis. A novel cohort of twenty-eight (28) genes representing potential marker for ovarian endometriosis in fertile women was discovered. Conclusions Dysfunctional expression of immuno-neuro-endocrine behaviour in endometrium appeared critical to endometriosis. Although no overt oncogenic potential was evident, several genes associated with gynecological cancers were observed to be high in the expressional profiles in endometriotic tissue.

Keywords

• Computational analysis
• Endometriosis
• Differential display
• Gene expression
• GSEA