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  1. Home
  3. Urinary Extracellular Vesicles For High-precision Bladder Cancer Subtyping And Prognosis.
  1. Home
  3. Urinary Extracellular Vesicles For High-precision Bladder Cancer Subtyping And Prognosis.

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

Zachary F Greenberg1, Tarun Hutchinson2, Jonathan Kahn3

  • 1Department of Pharmaceutics College of Pharmacy University of Florida Gainesville Florida USA.

Journal of Extracellular Biology
|May 4, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

We developed an AI-driven urinary extracellular vesicle (uEV) liquid biopsy pipeline for precise bladder cancer (BCa) subtyping and prognosis. This novel approach aids in stratifying patients and improving bladder cancer diagnosis and treatment decisions.

Keywords:
bladder cancerliquid biopsysubtypeurinary extracellular vesicles

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Area of Science:

  • Oncology
  • Biotechnology
  • Bioinformatics

Background:

  • Bladder cancer (BCa) presents molecular heterogeneity complicating diagnosis and prognosis.
  • Non-muscle invasive and muscle-invasive BCa subtypes have a significant risk of progression.
  • Urinary extracellular vesicles (uEVs) are promising biomarkers but face challenges due to urine's complex composition.

Purpose of the Study:

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

Main Methods:

  • Standardized EV isolation using NanoPom magnetic beads.
  • Transcriptomic profiling of uEVs for molecular subtyping.
  • Development of an AI-driven prognostic scoring algorithm.
  • External validation using UCSC Xena and comparison with existing BCa assays.
  • Correlation analysis with plasma-derived EVs and Next-Generation Sequencing (NGS).

    • Main Results:

    • The AI-driven pipeline successfully identified BCa subtype-specific gene signatures from NanoPom-isolated uEVs.
    • Performance of the pipeline surpassed existing BCa diagnostic biomarkers.
    • The prognostic score effectively stratified patients into low-, intermediate-, and high-grade risk groups.
    • uEV biomarkers correlated with plasma-derived EV biomarkers.

    Conclusions:

    • The AI-driven uEV liquid biopsy pipeline demonstrates high precision for BCa subtyping and prognosis.
    • This approach has the potential to facilitate clinical treatment decisions.
    • It offers advanced profiling of bladder tumor biology through uEV liquid biopsy.