AUTHOR=Pei Xin , Liu Lei , Han Yuping 

TITLE=Advances in human microbiome and prostate cancer research

JOURNAL=Frontiers in Immunology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2025.1576679

DOI=10.3389/fimmu.2025.1576679

ISSN=1664-3224

ABSTRACT=Prostate cancer (PCa) is the second most common malignant tumor in men worldwide, and its metastatic and heterogeneous nature makes it significantly more difficult to treat. Recent studies have revealed the critical role of microbiota in PCa occurrence, progression, and treatment. Accumulating evidence from 16S rRNA and metagenomic sequencing suggests the presence of specific microbiota in prostate tissues and macrogenomics techniques: cancerous tissues are enriched with pro-inflammatory genera (e.g., Fusobacterium, Propionibacterium acnes), whereas commensal bacteria (e.g., Pseudomonas) are more common in paracancerous tissues. The microbiota drive tumor progression through activation of the NF-κB/STAT3 pathway to induce chronic inflammation, modulation of the immune microenvironment (e.g., Treg/Th17 imbalance and M2-type macrophage polarization), and metabolite (e.g., LPS, short-chain fatty acids)–mediated hormonal and epigenetic regulation. In terms of clinical translation, urinary microbiota characterization combined with metabolomics analysis may enhance diagnostic specificity, while gut flora modulation (e.g., probiotic interventions or fecal transplants) may improve resistance to androgen deprivation therapy. Current challenges include sequencing accuracy of low-biomass samples, limitations of causal mechanism validation models, and large cohort heterogeneity. In the future, it will be necessary to integrate multi-omics technologies to explore the bidirectional regulation of the “gut-prostate axis” and develop personalized therapeutic strategies targeting microorganisms. In this paper, we systematically review the interactions between microbiota and PCa and their clinical potentials to provide a theoretical basis for precision diagnosis and treatment.