There remains a lack of effective and noninvasive methods for the diagnosis and prognosis prediction of epithelial ovarian carcinoma (EOC). Here, we investigated the possibility of serum-derived small extracellular vesicle (sEV) microRNAs (miRNAs) as potential biomarkers for distinguishing between benign and malignant adnexal masses and predicting the prognosis of EOC patients. A serum sEV miRNA model for identifying the EOC (sEVmiR-EOC) was successfully established in the training cohort. Furthermore, the sEVmiR-EOC model was confirmed in the testing cohort and validation cohort, demonstrating robust diagnostic accuracy. The sEVmiR-EOC model showed better performance than carbohydrate antigen 125 (CA125) in discriminating patients with stage I EOC from benign patients. Using EOC samples and follow-up data, we identified miR-141-3p and miR-200c-3p as potential prognostic predictors. Finally, we confirmed the change of the sEVmiR-EOC RiskScore between the preoperative and postoperative samples and found that the sEVmiR-EOC model could predict the prognosis of EOC patients.
Keywords: diagnostic and prognostic biomarker; microRNA; noninvasive; ovarian cancer; sEVmiR-EOC model; serum small extracellular vesicle.