#AI reads Urine# Ancestry-Dependent Immunologic and Prognostic Effects Characterize the Prostate Cancer Urinary Proteome

This study focuses on the urinary proteome of patients with prostate cancer, enrolling 329 patients with localized prostate cancer (135 self-identified as White and 194 self-identified as Black). By detecting proteins in their post-digital rectal exam (DRE) urine and analyzing in combination with clinical information, it was found that after adjusting for factors such as age, PSA level, and tumor grade, there were significant differences in 110 proteins in the urine between Black and White patients. Urine from Black patients contained more immune-related proteins, while urine from White patients had more prostate-specific proteins, and the urinary proteome characteristics of Black patients were more similar to those of highly aggressive tumors. Meanwhile, the prognostic predictive effects of some urinary proteins on biochemical recurrence of prostate cancer differed in opposite ways between patients of different races (e.g., the CTSG protein). Additionally, the consistent trend of differences in relevant genes/proteins between urine and tissue was verified using prostate cancer tissue data from The Cancer Genome Atlas (TCGA). The study points out that race/ancestry differences need to be considered when developing urinary biomarkers for prostate cancer, and also mentions limitations such as a relatively small sample size, lack of genetic ancestry information, and failure to account for some lifestyle and socioeconomic factors, laying a foundation for the subsequent development of race-adapted detection methods.🔶

bioRxiv [Preprint]. 2025 Aug 19:2025.08.14.670396. doi: 10.1101/2025.08.14.670396.

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/