In Silico Screening of Circulating MicroRNAs as Potential Biomarkers for the Diagnosis of Ovarian Cancer

Current screening tests for the diagnosis of ovarian cancer (OC) face enduring challenges. However, microRNAs (miRNAs) are stable in the circulation and may be promising molecular biomarkers for OC prediction. Circulating miRNA expression profiles in OC were analyzed using sequencing data from the Gene Expression Omnibus database. Differentially expressed miRNAs were generated from GSE94533, of which some were selected as candidate miRNAs based on an electronic search of the literature and comprehensive evaluation. A meta-analysis was preformed to integrate an evaluation index for these miRNAs in diagnosing OC patients. An independent validation set (GSE106817) was also conducted to further confirm the roles of these miRNAs. We identified four MIR200 members (MIR200A, MIR200B, MIR200C, and MIR429) and MIR25 as being differentially expressed among malignant or benign ovarian tumor patients and healthy controls. In the meta-analysis, these five miRNAs yielded a pooled area under the receiver operating characteristic (ROC) curve (AUC) of 0.78 (sensitivity: 64%, specificity: 88%) in discriminating OC from healthy controls, while the four MIR200 members demonstrated a summary AUC of 0.81 (sensitivity: 92%, specificity: 69%) in differing OC cases from patients with benign disease. In the validation set, differential expression and ROC curve analyses of these miRNAs were consistent except for MIR25. The circulating MIR200 family has the potential to become reliable and noninvasive biomarkers for OC diagnosis. Studies with larger cohorts are warranted to validate the applicability of these miRNAs.