Transcriptomic Analysis of Endometrium in Patients with Adenomyosis and Endometriosis

Abstract

<h3>Study Objective</h3> to analyze specific gene expression patterns and signaling pathways activation level in endometrial samples of patients with adenomyosis and endometriosis. <h3>Design</h3> Retrospective cohort study. <h3>Setting</h3> University Clinic. <h3>Patients or Participants</h3> 50 women with endometriosis, 20 women with adenomyosis, 35 women with tubal factor infertility (control group). <h3>Interventions</h3> Laparoscopic excision of endometriotic foci and adenomyomas, hysteroscopy with endometrial sampling. RNA was isolated from all samples and stored in RNA Later. Following histologic analysis of all samples, RNA sequencing was performed using Illumina HiSeq 3000 equipment for single-end sequencing. We normalized all gene expression and pathway activation profiles of studied samples on endometrial samples of women from the control group, and then proceeded with identification of strongly differentially expressed genes and activated signaling pathways. <h3>Measurements and Main Results</h3> We performed transcriptomic analysis of 50 endometrial samples of patients with endometriosis, 20 endometrial samples of patients with adenomyosis, and 35 endometrial samples from patients of control group. Statistically significant difference in transcriptomic profiles of endometrium of women with endometriosis and adenomyosis was found. Top-10 most strongly similarly and differentially expressed genes and up- and down-activated signaling pathways were identified. <h3>Conclusion</h3> Our findings suggest that both adenomyosis and endometriosis are associated with specific molecular changes in endometrium. Such data could be potentially used for early diagnosis of adenomyosis, even when it is missed on ultrasonography. Moreover, identification of molecular differences between endometrium in adenomyosis and endometriosis can have important implications on understanding of the etiological aspects and can help in identifying novel drug targets.