Gut Microbiota Signatures Associated with Metastatic Prostatic Cancer Treated with Androgen Receptor Pathway Inhibitor (ARPI) Therapy

Metastatic prostate cancer (MPCa) remains an aggressive disease despite the introduction of androgen receptor pathway inhibitors (ARPIs), and biomarkers predicting progression are still lacking. The aim of this study was to investigate gut microbiota (GM) composition and functional potential associated with advanced disease and progression under ARPI therapy. The GM of 15 patients with metastatic PCa receiving ARPIs, including 5 patients with disease progression, was compared with that of 39 patients with untreated (UT) PCa using shallow shotgun metagenomic sequencing. The metastatic PCa cohort receiving ADT plus ARPI therapy showed reduced microbial alpha diversity and significant taxonomic and functional differences compared with the untreated, clinically localized PCa reference cohort. In patients with advanced disease, microbial functions related to dietary carbohydrate utilization, fermentation, epithelial interaction, and microbial structural maintenance were predominantly underrepresented, whereas stress-responsive and redox-associated functions were overrepresented. These alterations may reflect reduced metabolic and ecological versatility alongside increased adaptation to host-associated stress conditions. Compared with the UT group, in patients with progression we found that Bifidobacterium longum, Anaerobutyricum hallii, Ruminococcus sp., and Blautia obeum (LinDA coefficients 5.7, 2.6, 2.6 and 2.4, respectively) were enriched, whereas Sutterella wadsworthensis, Butyricimonas, Bilophila wadsworthia, Alistipes indistinctus, and Intestinimonas were depleted (LinDA coefficients −8.4, −5.9, −5, −5 and −3, respectively). Together, these findings identify distinct taxonomic and functional features associated with metastatic PCa under systemic therapy and microbial features observed in patients experiencing progression during ARPI treatment, providing potential candidates for biomarker development and generating testable hypotheses regarding microbiome–host metabolic interactions in treatment resistance. The GM may therefore represent a potential source of biomarkers for advanced PCa and progression under ARPI therapy, although longitudinal and multi-omics studies are required to determine their predictive value and functional relevance.