#AI reads Urine# Field-effect-informed urine liquid biopsy for bladder cancer

Published 20 April, 2026

This study developed a field effect correction method for urine liquid biopsy combined with the RePhyNERX algorithm. By eliminating tumor-associated normal tissue mutation interference, it identified three molecular response subtypes—surgical response, Bacillus Calmette-Guérin (BCG) response, and no response—in patients with non-muscle-invasive bladder cancer (NMIBC). The study confirmed that high tumor mutation burden (TMB) and pre-existing immune activation are specific molecular markers of BCG response, significantly enhancing the specificity of minimal residual disease (MRD) detection and the accuracy of recurrence prediction. This provides a novel approach for personalized treatment of NMIBC.

What are the unique advantages of urine biopsy over plasma liquid biopsy in the detection of bladder cancer? What are the key molecular characteristics of BCG response?

Answer: The core advantage of urine biopsy lies in its higher tumor DNA concentration and significantly superior detection sensitivity compared to plasma: the detection rate of tumor DNA in urine is 100% for NMIBC patients, whereas it is 0% for plasma; for MIBC patients, the detection rate in urine is 100%, but only 50% for plasma. Two key molecular features determine BCG response: first, high tumor mutation burden (TMB), with patients harboring ERCC2 gene mutations exhibiting higher TMB and better prognosis; second, pre-existing immune activation, characterized by enriched interferon signaling and inflammatory pathways in tumor tissues, along with a higher tumor-stromal enrichment score (TSE), indicating that the immune status of the tumor microenvironment is the core determinant of BCG efficacy.

 

Cell. 2026 Jan 27:S0092-8674(25)01503-X. doi: 10.1016/j.cell.2025.12.054.

Youhe Gao

Statement: During the preparation of this work the author(s) used Doubao / AI reading for summarizing the content. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the published article.

 

For earlier AI Reads Urine articles:

https://www.keaipublishing.com/en/journals/advances-in-biomarker-sciences-and-technology/ai-reads-urine/

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