A microRNA biomarker panel for the non-invasive detection of bladder cancer

Abstract

The development of accurate, non-invasive urinary assays for bladder cancer would greatly facilitate the detection and management of a disease that has a high rate of recurrence and progression. In this study, we employed a discovery and validation strategy to identify microRNA signatures that can perform as a non-invasive bladder cancer diagnostic assay. Expression profiling of 754 human microRNAs (TaqMan low density arrays) was performed on naturally voided urine samples from a cohort of 85 subjects of known bladder disease status (27 with active BCa). A panel of 46 microRNAs significantly associated with bladder cancer were subsequently monitored in an independent cohort of 121 subjects (61 with active BCa) using quantitative real-time PCR (RT-PCR). Multivariable modeling identified a 25-target diagnostic signature that predicted the presence of BCa with an estimated sensitivity of 87% at a specificity of 100% (AUC 0.982). With additional validation, the monitoring of a urinary microRNA biomarker panel could facilitate the non-invasive evaluation of patients under investigation for BCa.

Keywords: bladder cancer; diagnostic biomarkers; microRNA; multiplex; urinalysis.

Figure 1. ROC curve illustrating the diagnostic accuracy of miRNA set classifiers for predicting the presence of bladder cancer

Curves are presented for prediction models comprised of 25, 20, 15 and 10 miRNAs.