Urinary Peptidomic Signatures Predict Overall and Progression‐Free Survival in Bladder Cancer

Clinicopathologic calculators for bladder cancer (BC) provide only moderate prognostic accuracy and do not capture the underlying molecular phenotypes. Herein, we applied capillary electrophoresis-mass spectrometry (CE-MS) to identify prognostic signatures in urine linked to BC outcome. In a discovery cohort (n = 131; mean follow-up 623 days), 114 survival-associated peptides were significant prognostic factors for overall survival (OS) and were integrated into, and optimized as a 110-peptide support vector machine (SVM) classifier (BC110). Validation of the BC110 classifier was performed in an independent cohort (n = 102; mean follow-up 1605 days), resulting in an AUC of 0.78 (p = 0.03). Functional enrichment analysis revealed that the BC110 peptide panel predominantly reflects extracellular matrix (ECM) remodeling and collagen-related pathways, alongside additional biological processes including coagulation, complement activation, oxidative stress, and RNA processing, consistent with active tumor-stroma crosstalk. This urine-based classifier enables non-invasive risk stratification and may complement guideline calculators by identifying high-risk patients for adjuvant therapy and low-risk groups for reduced surveillance, potentially lowering reliance on repeated cystoscopy.