Urinary Extracellular Vesicles for High-Precision Bladder Cancer Subtyping and Prognosis

Bladder cancer (BCa) exhibits molecular heterogeneity that complicates early diagnosis and prognosis, and drives confounding clinical outcomes. Non-muscle invasive and muscle-invasive subtypes, especially for intermediate to high grade, carry a 25%-50% progression-free survival rate, underscoring the need for high-precision prognostic strategy. Urinary extracellular vesicles (uEVs) are promising carriers of tumour-derived RNAs and proteins. However, significant challenges in studying uEVs arise from the diverse cellular origin of uEVs associated with the dynamic composition of urine, which presents roadblocks for developing the clinical utility of uEVs. We developed an AI-driven EV liquid biopsy pipeline that integrates (1) standardised EV isolation via NanoPom magnetic beads, (2) transcriptomic profiling for molecular subtyping and (3) prognostic scoring algorithm. In a discovery cohort of 16 BCa patients including both muscle-invasive bladder cancer (MIBC) and non-muscle-invasive bladder cancer (NMIBC), we compared NanoPom isolated uEVs with ExoEasy and Fujifilm MagCapture isolated uEVs, for identifying BCa subtype-specific gene signatures, and externally validated them using UCSC Xena. The result outperformed currently reported BCa diagnostic biomarkers from assays including Galeas, CxBladder and Xpert. In a validation cohort composed of seven individuals with MIBC, NMIBC and healthy individuals, we confirmed with plasma-derived EVs for correlating with uEV biomarkers from NGS sequencing. The prognostic score stratified patients into low-, intermediate- and high-grade risk groups based on Xena's BCa survival outcomes. Our AI-driven uEV liquid biopsy pipeline proves the concept for high precision BCa subtyping and prognosis, which could potentially facilitate treatment decision and lead to advanced profiling of bladder tumour biology using uEV liquid biopsy.