Identification of Circular RNAs as a Novel Biomarker for Ovarian Endometriosis

Background Endometriosis is a challenging disease with symptoms such as dysmenorrhea and infertility. However, its etiology is still vague and there is still no effective markers or treatment. This study aimed to profile the circular RNAs (circRNAs) expressed in eutopic endometrium from patients with ovarian endometriosis and explore potential clues to the pathogenesis of endometriosis, providing an evidence for clinical diagnosis and treatment. Methods A total of 63 clinical samples, including control endometrium (n = 22) and eutopic endometrium (n = 41), were collected from Peking Union Medical College Hospital between May 1, 2016, and December 31, 2016. Of them, four samples in each group were used for circRNA microarray. Then, four upregulated circRNAs were screened out for quantitative real-time polymerase chain reaction (qRT-PCR) validation. After that, bioinformatics analysis was performed to predict miRNAs targeted by validated circRNAs and investigate the circRNA-miRNA-mRNA interactions. Results Among 88 differentially expressed circRNAs, 11 were upregulated and 77 were downregulated in eutopic endometrium of patients with endometriosis. qRT-PCR validation results for two upregulated circRNAs (circ_0004712 and circ_0002198) matched the microarray results. The area under the receiver operating characteristic curve of circ_0002198 for distinguishing ovarian endometriosis was 0.846 (95% confidence interval [CI]: 0.752-0.939; P < 0.001) while that of circ_0004712 was 0.704 (95% CI: 0.571-0.837; P = 0.008). On the basis of target prediction, we depicted the molecular interactions between the identified circRNAs and their dominant target miRNAs, as well as constructed a circRNA-miRNA-mRNA network. Conclusions This study provides evidence that circRNAs are differentially expressed between eutopic and normal endometrium, which suggests that circRNAs are candidate factors in the activation of endometriosis. circ_0002198 and circ_0004712 may be potential novel biomarkers for the diagnosis of ovarian endometriosis.