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Validation of a urinary microRNA signature reveals high sensitivity for non-invasive detection of bladder urothelial carcinoma in patients undergoing surveillance

Sapre N. Macintyre G.J. Kowalczyk A. Costello A.J. Anderson P. Corcoran N.M. Hovens C.M.

BJU International 2014;113 (Suppl 4):48-9.

Abstract


Introduction The long-term surveillance mandated for non-muscle invasive bladder cancer (NMIBC) patients is expensive and resource intensive and no non-invasive biomarker currently exists to identify patients with disease recurrence. The objective of this retrospective translational study was to determine if microRNA (miRNA) profiling of urine can identify the presence of urothelial carcinoma (UC) in the bladder in patients undergoing surveillance, and to compare its test performance characteristics to that of cystoscopy.

Patients and Methods Urine samples from bladder cancer patients at Royal Melbourne Hospital collected from 2011-2013 were used for this study. In the discovery cohort we screened 60 patients, which included 30 non-recurrers (patients with a history of TCC but no recurrence at cystoscopy) and 30 recurrers (patients with TCC identified at cystoscopy) using a panel of 16 miRNAs. Seven of these miRNAs were selected for validation in an independent cohort of patients, which included 25 non-recurrers and 25 recurrers. Total RNA was extracted and preselected miRNA assays used for profiling by real time quantitative polymerase chain reaction (RT-qPCR) in triplicate. A centroid classifier was trained on the discovery cohort using a three-fold cross-validation approach and applied to the validation cohort to predict recurrence status. This was then compared to the outcome of cystoscopy to calculate performance of the miRNA panel using the area under the receiver operator characteristic curve (AUC).

Results In the validation cohort, the best predictor of the presence of UC was achieved using a combination of 6 miRNAs - miR 16, 21,34a, 200c, 205, 222 (AUC = 0.83). The difference in miRNA expression profiles between the recurrers and non-recurrers was highest for patients with presence of larger tumours (Size > 3cm: AUC = 0.90) and higher T-stage (T1: AUC = 0.94; T2: AUC = 1.00). This 6-miRNA signature detected UC with a high sensitivity (88%) and sufficient specificity (60%). Overall this panel identified 88% of UC and could have reduced cystoscopy rates by 58%. Most importantly, almost all significant cancers were detected accurately. This panel of miRNAs missed 2 small Ta high-grade cancers but detected all large cancers ( > 3cm) and all invasive cancers (T1/T2).

Conclusions This study suggests that urinary profiling using this panel of miRNAs can safely detect most clinically significant cancers non-invasively and could reduce the number of cystoscopies during surveillance.

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