Diagnostic potential of differentially regulated microRNAs among endometriosis, endometrioid ovarian cancer, and endometrial cancer.

<bold>Background: </bold>There is an increased risk of developing endometrioid ovarian and endometrial cancer in patients with endometriosis and there are no definitive diagnostic biomarkers available for these three associated diseases. Therefore, we evaluated the diagnostic potential of differentially expressed microRNAs (miRNAs) from the tissue samples of endometriosis, endometrioid ovarian cancer, and endometrial cancer to establish them as biomarkers for these diseases.<bold>Materials and Methods: </bold>Ten samples of each, i.e., endometriosis, endometrioid ovarian cancer, endometrial cancer and control healthy endometrium were enrolled after obtaining ethical clearance. Differential expression of miR-16, miR-20a, miR-99b, miR-125a, miR-143, and miR-145 and some of their target genes, i.e., vascular endothelial growth factor (VEGF), hypoxia inducible factor 1A (HIF1A), cyclooxygenase 2 (COX2), and tumor necrosis factor (TNF) were quantified using quantitative reverse transcription polymerase chain reaction. Receiver operating characteristic (ROC) curve analysis was performed to predict the diagnostic potential.<bold>Results: </bold>miR-16 and miR-20a were significantly downregulated, whereas miR-99b, miR-125a, and miR-143 were significantly upregulated in all three diseased samples. miR-145 was significantly upregulated in endometriosis and endometrioid ovarian cancer but significantly downregulated in endometrial cancer. mRNA levels of VEGF, HIF1A, COX2, and TNF were significantly increased in all three diseased samples as compared to control samples. ROC curve analysis revealed that for endometriosis, miR-99b, and miR-125a were giving highest area under curve (AUC) (0.950 and 0.733, respectively), for endometrioid carcinoma of ovary miR-143 was giving highest AUC (0.933) and for endometrioid endometrial cancer miR-16 (AUC = 0.815), miR-99b (AUC = 0.920), and miR-145 (AUC = 0.985) were found to be best predictors.<bold>Conclusion: </bold>These findings suggest that these miRNAs can act as good predictors and discriminators of these three diseases and might serve as potential biomarkers for them. [ABSTRACT FROM AUTHOR]