Research progress and clinical translation prospects of the urinary tract microbiome in prostate cancer

Abstract

Prostate cancer (PCa) is one of the most common malignancies in men worldwide, and its development is influenced by multiple factors, including genetic susceptibility, hormonal dysregulation, chronic inflammation, immune dysregulation, and remodeling of the tumor microenvironment. In recent years, the urinary tract microbiome has emerged as an important component of the tumor ecosystem and has attracted increasing attention in PCa research. Accumulating evidence indicates that patients with PCa exhibit characteristic microbial alterations in urine, expressed prostatic secretions, semen, and prostate tissue, and that certain taxa are associated with tumor grade, stage, and recurrence risk. These microbes may participate in tumor initiation and progression through a variety of mechanisms, such as inducing chronic inflammation, activating signaling pathways including TLR/NF-κB and STAT3, modulating the Treg/Th17 balance, influencing macrophage polarization, and interfering with androgen metabolism. Meanwhile, advances in 16S rRNA sequencing, metagenomics, metatranscriptomics, and multi-omics integration have provided powerful tools for characterizing host–microbe interactions and their functional relevance. In addition, microbiome-based biomarkers derived from non-invasive samples such as urine, together with artificial intelligence and causal inference approaches applied to multi-cohort data, may offer promising opportunities for early screening, risk stratification, treatment monitoring, and personalized intervention in PCa. However, current evidence remains largely associative, and the causal relationship between microbial changes and PCa has not yet been fully established. Major challenges, including contamination in low-biomass samples and inter-cohort heterogeneity, continue to hinder clinical translation. Future research should focus on longitudinal cohort studies, multicenter validation, standardized sampling workflows, and mechanistic experiments to clarify key microbial signatures and their biological functions, thereby accelerating the clinical application of the urinary tract microbiome in precision diagnosis and treatment of PCa.