Identifying Serum Small Extracellular Vesicle MicroRNA as a Noninvasive Diagnostic and Prognostic Biomarker for Ovarian Cancer
Lei Li, Fuchuang Zhang, Jiyang Zhang, Xiaohua Shi, Huanwen Wu, Xiaopei Chao, Shuiqing Ma, Jinghe Lang, Ming Wu, Dadong Zhang, Zhiyong Liang
Abstract
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.