Exploring Urinary EV Gene Expression for Early Detection of Bladder Cancer

Abstract

Bladder cancer is one of the most prevalent malignancies affecting the urinary system, where early detection plays a crucial role in improving clinical outcomes. Urinary extracellular vesicles (EVs), which contain molecular cargo such as mRNA, offer a promising non-invasive source of biomarkers in early diagnosis. In this study, we analyzed a gene expression dataset derived from urinary EVs to identify potential diagnostic markers for bladder cancer. The analysis focused on four genes: LASS2, GALNT, ARHGEF39, and FOXO3. Notably, LASS2 and GALNT1 are expressed in cancer patient EVs, whereas ARHGEF39 and FOXO3 were expressed only in non-cancer controls. All four genes have previously been implicated in tumor-related pathways. After filtering out low-variability probes, we performed bioinformatic analyses and visualized gene expression patterns using dimensionality reduction and clustering tools. The results revealed a clear separation between cancer-associated and non-cancer-associated gene groups, suggesting that LASS2 and GALNT1 may serve as reliable biomarkers for early-stage bladder cancer. This study highlights the potential of urinary EV-derived mRNA profiling as a powerful, non-invasive approach for cancer detection and patient stratification.