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Background <p>Bladder 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.</p> Results <p>Reanalyzing 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: <i>Anaerococcus</i>, <i>Fenollaria</i>, and <i>Finegoldia</i> were enriched in BC, while <i>Bacteroides</i>, <i>Muribaculaceae</i>, and <i>Escherichia-Shigella</i> 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 <i>purL</i>, <i>adk</i>, and <i>pyrB</i>. Leveraging these findings,&#xa0;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&#xa0;(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.</p> Conclusions <p>This study presents an externally validated urinary microbiota-based diagnostic model for BC, providing both translational biomarkers and novel insights into microbiome-oncogenesis interactions.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月9日

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

摘要

Background

Bladder 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.

Results

Reanalyzing 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.

Conclusions

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