Urinary extracellular vesicles for high-precision bladder cancer subtyping and prognosis

Area of Science:

• Oncology
• Biotechnology
• Bioinformatics

Background:

• Bladder cancer's molecular heterogeneity complicates diagnosis and prognosis.
• Non-muscle invasive and muscle-invasive bladder cancer subtypes have a 25-50% progression-free survival rate, necessitating advanced prognostic strategies.
• Urinary extracellular vesicles (uEVs) are potential carriers of tumor biomarkers, but their clinical utility is hindered by diverse origins and urine composition.

Purpose of the Study:

• To develop and validate an AI-driven liquid biopsy pipeline using uEVs for precise bladder cancer subtyping and prognosis.
• To compare the efficacy of NanoPom-isolated uEVs against other isolation methods for identifying bladder cancer-specific gene signatures.
• To establish a prognostic scoring algorithm for stratifying bladder cancer patients based on risk.

Main Methods:

• Standardized uEV isolation using NanoPom magnetic beads.
• Transcriptomic profiling of uEVs for molecular subtyping.
• External validation of gene signatures using UCSC Xena and correlation with plasma-derived EVs.

Main Results:

• The AI-driven pipeline identified bladder cancer subtype-specific gene signatures that outperformed existing diagnostic biomarkers.
• NanoPom isolation demonstrated superior performance compared to ExoEasy and Fujifilm MagCapture.
• The developed prognostic score effectively stratified patients into low-, intermediate-, and high-grade risk groups.

Conclusions:

• The AI-driven uEV liquid biopsy pipeline offers a high-precision strategy for bladder cancer subtyping and prognosis.
• This approach has the potential to aid treatment decisions and advance the understanding of bladder tumor biology.
• uEV liquid biopsy represents a promising non-invasive tool for personalized bladder cancer management.