Deep Sequencing of Urinary RNAs for Bladder Cancer Molecular Diagnostics

The majority of bladder cancer patients present with localized disease and are managed by transurethral resection. However, the high rate of recurrence necessitates lifetime cystoscopic surveillance. Developing a sensitive and specific urine-based test would significantly improve bladder cancer screening, detection, and surveillance. RNA-seq was used for biomarker discovery to directly assess the gene expression profile of exfoliated urothelial cells in urine derived from bladder cancer patients ( = 13) and controls ( = 10). Eight bladder cancer specific and 3 reference genes identified by RNA-seq were quantitated by qPCR in a training cohort of 102 urine samples. A diagnostic model based on the training cohort was constructed using multiple logistic regression. The model was further validated in an independent cohort of 101 urines. A total of 418 genes were found to be differentially expressed between bladder cancer and controls. Validation of a subset of these genes was used to construct an equation for computing a probability of bladder cancer score (P ) based on expression of three markers ( , and ). Setting P = 0.45 as the cutoff for a positive test, urine testing using the three-marker panel had overall 88% sensitivity and 92% specificity in the training cohort. The accuracy of the three-marker panel in the independent validation cohort yielded an AUC of 0.87 and overall 83% sensitivity and 89% specificity. Urine-based molecular diagnostics using this three-marker signature could provide a valuable adjunct to cystoscopy and may lead to a reduction of unnecessary procedures for bladder cancer diagnosis. .