#AI reads Urine# Exploring bladder cancer through urinary microbiota: innovative "urinetypes" classification and establishment of a diagnostic model
Published 24 July, 2025
This study explores bladder cancer through the analysis of urinary microbiota, aiming to develop a non-invasive diagnostic model and propose a novel "urinetypes" classification. The research includes a discovery cohort (104 bladder cancer patients, 56 with other malignant urological cancers, 98 with benign urinary diseases, and 42 healthy controls) and a validation cohort (66 bladder cancer patients, 5 with other malignant urological cancers, 51 with benign urinary diseases, and 22 healthy controls). Using 16S rRNA gene sequencing, the urinary microbiota composition is analyzed to assess diversity, identify biomarkers, and construct diagnostic models, with clustering analysis applied to establish "urinetypes" .
Results show that bladder cancer patients have greater urinary microbiota richness and diversity, with significant differences in beta diversity across groups. Certain genera like Sphingomonas, Anaerococcus, Acinetobacter are more abundant in bladder cancer patients, while Lactobacillus and Gardnerella are less so, suggesting their potential as biomarkers . Carbohydrate and nucleotide metabolism are more active in bladder cancer patients, meeting cancer cell metabolic needs . A random forest model based on 12 microbial genera achieves high accuracy in the discovery cohort (AUC=89.08%) and validation cohort (AUC=70.8%), and a "Patient Differentiation Index" also shows good predictive performance (AUC=86.17% in the discovery cohort and 78% in the validation cohort) . Additionally, distinct "urinetypes" are identified, with those dominated by Prevotella and Corynebacterium more prevalent in bladder cancer patients, possibly representing high-risk subtypes .
The study characterizes the urinary microbiota of bladder cancer patients, provides a reliable non-invasive diagnostic method based on urinary microbiota for the first time, and the innovative "urinetypes" concept and identification of high-risk subtypes offer potential for improving diagnostic and therapeutic strategies .
J Transl Med. 2025 Jul 22;23(1):809. doi: 10.1186/s12967-025-06518-y.
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.
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