Urinary microRNA Profiles Discriminate Bladder Cancer from Healthy Individuals: A Pilot Study Using qPCRAcross Urine Fractions.

Abstract

The development of reliable non-invasive diagnostic tools for bladder cancer remains a significant challenge. We hypothesized that the combined quantification of selected urinary microRNAs could differentiate bladder cancer cases from healthy controls. Using qPCR, we analyzed five candidate microRNAs (miR-21-5p, miR-141-3p, miR-210-3p, miR-200a-3p, and miR-103-3p) across three urine fractions: whole urine, pellet, and supernatant from a small cohort (n = 9). Although individual gene expression differences between cases and controls were not statistically significant (Wilcoxon p > 0.05), multivariate clustering using Mclust modeling and PCA showed clear separation, especially in the whole urine fraction. These results suggest that combined miRNA expression profiling, rather than individual markers, may provide diagnostic value for bladder cancer. Even though further evaluation in a larger population is necessary, our findings indicate that a cost-effective and easily implementable non-invasive diagnostic approach for bladder cancer may be within reach.