Evidence map›Paper›PMID 41663923›Full record

ArticleBMC microbiology2026

Integrative multi-cohort analysis identifies urinary microbiota as non-invasive biomarkers of bladder cancer.

Liwen Tao, Tingting Zhao, Yiyang Xu, Wanning Chen, Xinyue Zhu, Yuping Hao, Lixin Zhu, Na Jiao, Ming Cao, Xiaowen Pu and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Liwen TaoShanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Clinical and Translation Research Center, Shanghai First Maternity and Infant Hospital, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, People's Republic of China.
Tingting ZhaoShanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Clinical and Translation Research Center, Shanghai First Maternity and Infant Hospital, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, People's Republic of China.
Yiyang XuShanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Clinical and Translation Research Center, Shanghai First Maternity and Infant Hospital, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, People's Republic of China.
Wanning ChenShanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Clinical and Translation Research Center, Shanghai First Maternity and Infant Hospital, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, People's Republic of China.
Xinyue ZhuShanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Clinical and Translation Research Center, Shanghai First Maternity and Infant Hospital, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, People's Republic of China.
Yuping HaoResearch Institute, GloriousMed Clinical Laboratory Co, Ltd, Shanghai, 201318, People's Republic of China.
Lixin ZhuInstitutes of Biomedical Sciences, School of Life Sciences, Inner Mongolia University, Hohhot, 010070, People's Republic of China.
Na JiaoState Key Laboratory of Genetic Engineering, Fudan Microbiome Center, School of Life Sciences, Fudan University, Shanghai, 200438, People's Republic of China. najiao@fudan.edu.cn.
Ming CaoDepartment of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, People's Republic of China. chowming2007@gmail.com.
Xiaowen PuDepartment of Cervical Disease, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 201204, People's Republic of China. puxiaowen@51mch.com.
Ruixin ZhuShanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Clinical and Translation Research Center, Shanghai First Maternity and Infant Hospital, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, People's Republic of China. rxzhu@tongji.edu.cn.

Funding

National Natural Science Foundation of China 32470098National Natural Science Foundation of China 92251307Shanghai Oriental Talents Program BJJY2024098
6 · The paper itself

Abstract

backgroundBladder cancer (BC) is a prevalent urological malignancy where early detection is critical. However, traditional diagnostics like cystoscopy are invasive, and non-invasive methods perform suboptimally, especially in low-grade tumors. Emerging evidence links urinary microbiome dysbiosis to BC, yet its diagnostic potential remains unclear.

resultsReanalyzing 388 public 16S rRNA sequencing data and 65 in-house samples, we identified alterations in microbial composition and microbial-derived metabolism in BC. Six genera exhibited significant differential abundance: Anaerococcus, Fenollaria, and Finegoldia were enriched in BC, while Bacteroides, Muribaculaceae, and Escherichia-Shigella were depleted. Functional analysis indicated microbial metabolic perturbations, particularly in nucleoside/nucleotide metabolism and vitamin biosynthesis. qRT-PCR further validated changes in three nucleoside/nucleotide metabolism-related genes, including purL, adk, and pyrB. Leveraging these findings, we developed a classification model incorporating 20 urinary bacterial biomarkers, achieving an area under the curve (AUC) of 0.86 in the discovery cohort and demonstrating consistent performance in three independent validation cohorts (AUCs = 0.70, 0.75, 0.79). Notably, these biomarkers maintained diagnostic efficacy in low-grade tumors (AUC = 0.80) and exhibited high disease specificity.

conclusionsThis study presents an externally validated urinary microbiota-based diagnostic model for BC, providing both translational biomarkers and novel insights into microbiome-oncogenesis interactions.

Indexed as

BacteriaBiomarkers, TumorMicrobiotaUrinary Bladder NeoplasmsCohort StudiesDysbiosisFemaleHumansMaleRNA, Ribosomal, 16SBiomarkers, TumorRNA, Ribosomal, 16SMicrobial biomarkersNon-invasiveUrinary microbiomeUrothelial cancer

Identifiers

PMID41663923
PMCPMC12990511

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.