Microfluidic Urinary Exosome-Based Diagnostic Model for Bladder Cancer

Overview

Bladder cancer is one of the most common malignancies of the urinary system and is characterized by high recurrence rates and poor long-term outcomes. Early detection and accurate diagnosis are essential for improving clinical management. This prospective diagnostic accuracy study aims to develop and validate a precision diagnostic model for bladder cancer based on microfluidic isolation and multiplex detection of urinary exosomes. A novel microfluidic platform will be developed for rapid and efficient urinary exosome enrichment. Multi-omics approaches, including RNA sequencing and proteomic profiling, will be used to identify bladder cancer-associated urinary exosome biomarkers. A multiplex microfluidic detection chip will subsequently be developed for simultaneous detection of multiple biomarkers. A diagnostic model integrating urinary exosome biomarker profiles and clinical characteristics will be developed in a training cohort and prospectively validated in an independent cohort. Diagnostic performance will be evaluated using pathological diagnosis as the reference standard. This study aims to establish a non-invasive, rapid, and accurate diagnostic strategy for bladder cancer.

This study aims to establish and validate a urinary exosome-based diagnostic model for bladder cancer using microfluidic technologies. The study consists of four stages: First, a novel microfluidic urinary exosome isolation platform will be developed using magnetic stirring-assisted resuspension and tangential flow washing technologies to improve exosome recovery efficiency. Second, bladder cancer-associated urinary exosome biomarkers will be identified using transcriptomic and proteomic approaches. Candidate nucleic acid and protein biomarkers will be screened and validated. Third, a multiplex microfluidic detection chip will be developed to enable simultaneous detection of multiple urinary exosome-derived biomarkers. Fourth, a diagnostic model integrating biomarker expression profiles and clinical characteristics will be constructed in a training cohort and prospectively validated in an independent cohort. Pathological diagnosis will serve as the reference standard for evaluating diagnostic performance.

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