Evidence map›Paper›PMID 42694772›Full record

ReviewFrontiers in cellular and infection microbiology2026

Urinary microbiota in bladder cancer: insights into pathogenesis, diagnosis, and therapeutic potential.

Zhaoyang Sheng, Jinpeng Zhu, Jianming Sun, ShuXiong Zeng, Jun Ding, ZhenSheng Zhang

Abstract readReview
In one paragraph

Review in Frontiers in cellular and infection microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Zhaoyang Sheng *Department of Urology, Shanghai Changhai Hospital, Naval Medical University, Shanghai, China.
Jinpeng Zhu *Department of Urology, Shanghai Changhai Hospital, Naval Medical University, Shanghai, China.
Jianming Sun *Department of Urology, The 904th Hospital, Joint Logistics Support Force, Wuxi, China.
ShuXiong ZengDepartment of Urology, Shanghai Changhai Hospital, Naval Medical University, Shanghai, China.
Jun DingDepartment of Urology, The 904th Hospital, Joint Logistics Support Force, Wuxi, China.
ZhenSheng ZhangDepartment of Urology, Shanghai Changhai Hospital, Naval Medical University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bladder cancer is a prevalent urinary malignancy with high global incidence and mortality. Despite advances in diagnosis and treatment, challenges persist, particularly due to high recurrence rates and unpredictable progression. Recent evidence highlights the role of urinary tract microbiota in BC initiation, progression, and recurrence. The urinary tract, once thought sterile, is now recognized as a complex microbial environment influencing local immunity and carcinogenesis. Differences in microbiota composition between cancer patients and controls, as well as variations by gender, age, and lifestyle factors like smoking, have been observed. The microbiota may impact tumor staging, grading, recurrence, and treatment responses, particularly to Bacillus Calmette-Guérin therapy. Mechanisms include immune modulation, inflammation, and epithelial barrier disruption. This review synthesizes current research on urinary microbiota's role in BC, emphasizing its potential as a biomarker and therapeutic target. Large-scale studies are needed to better understand these associations and develop microbiota-based strategies for improved BC management.

Indexed as

MicrobiotaUrinary Bladder NeoplasmsUrinary TractHumansBCGbladder cancermechanismmicrobiotatreatment

Identifiers

PMID42694772
PMCPMC13539508

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.