Abstract
BACKGROUND: Non-muscle invasive bladder cancer (NMIBC) is characterized by frequent recurrence, requiring repeated cystoscopic surveillance that is invasive and burdensome for patients. Although liquid biopsy approaches have been explored, clinically applicable non-invasive biomarkers that directly reflect tumor burden remain limited. As a proof-of-concept, we investigated whether somatic mutant proteins derived from bladder cancer cells can be detected and quantified in urinary extracellular vesicles (EVs) using a proteogenomic strategy. METHODS: Tumor tissues, cultured tissue-derived EVs, and urinary EVs were collected from five patients with bladder cancer. Whole-exome sequencing was performed to generate patient-specific mutation databases. Deep proteomic profiling by LC/MS was conducted for each specimen type, followed by a proteogenomic pipeline to identify somatic mutant proteins. To explore clinical feasibility, selected mutant proteins were further evaluated by targeted mass spectrometry with absolute quantification in prospectively collected urine samples. RESULTS: Comprehensive proteomic analyses identified 11, 207 proteins in tumor tissues, 9, 809 in tissue-derived EVs, and 5, 828 in urinary EVs. Across these matched sample sets, 39, 32, and 4 somatic mutant proteins were detected, respectively, demonstrating that tumor-specific mutant proteins are incorporated into EVs and released into urine. Importantly, absolute quantification of selected mutant proteins (LCP1_D321H, TKT_K102N, and PLCD1_R639H) revealed a clear association between urinary EV mutant protein levels and cystoscopic tumor burden, supporting their potential utility for non-invasive disease monitoring. CONCLUSION: This proof-of-concept study provides the first evidence that somatic mutant proteins can be directly detected and quantified in urinary EVs using a proteogenomic approach. Our findings establish a conceptual framework for mutation-informed, protein-level liquid biopsy and suggest that urinary EV-associated mutant proteins may serve as highly specific, non-invasive biomarkers for monitoring bladder cancer recurrence.