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Urinary microRNAs (miRNAs) are potential biomarkers for the noninvasive diagnosis of bladder cancer (BC). In this study, we aimed to develop a urinary miRNAs panel for diagnosing and predicting recurrence of BC. Genome-wide miRNAs analysis by deep sequencing followed by two phases of quantitative real-time PCR assays were performed on urine supernatant of 276 BC patients and 276 controls. We identified a seven-miRNA panel (miR-7-5p, miR-22-3p, miR-29a-3p, miR-126-5p, miR-200a-3p, miR-375, and miR-423-5p) that provided high diagnostic accuracy of BC with an AUC of 0.923 and 0.916 in training and validation set, respectively. The corresponding AUCs of this panel for Ta, T1 and T2-T4 were 0.864, 0.930 and 0.978, significantly higher than those of urine cytology, which were 0.531, 0.628 and 0.724, respectively (all p &lt; 0.05). Moreover, Kaplan-Meier analysis showed that nonmuscle-invasive BC (NMIBC) patients with high miR-22-3p and low miR-200a-3p level had worse recurrence-free survival (RFS) (p = 0.002 and 0.040, respectively). Multivariate Cox regression analysis revealed that miR-22-3p and miR-200a-3p were independently associated with RFS of NMIBC (p = 0.024 and 0.008, respectively). In conclusion, our results suggested that urinary miRNAs may have considerable clinical value in diagnosis and recurrence prediction of BC.

Cell-free microRNA expression signatures in urine serve as novel noninvasive biomarkers for diagnosis and recurrence prediction of bladder cancer