Microbial dysbiosis and inferred functional profiling reveals the potential role of Methylobacterium in prostate cancer

Background and objective – Prostate cancer (PCa) is a leading malignancy in men, with a multifactorial aetiology involving genetic, hormonal, and microbial factors. Although emerging evidence implicates tumour-associated microbial communities in cancer biology, microbial signatures in PCa, particularly in Arab populations, remain underexplored. This study aimed to characterize the prostate tissue microbiota in an Arab cohort and explore associations with clinical features. Methods – In this retrospective study, 40 formalin-fixed paraffin-embedded (FFPE) prostate tissue samples (23 PCa and 17 benign prostatic hyperplasia [BPH]) were analysed using 16S rRNA gene sequencing. Microbial diversity, taxonomic composition, and predicted functional potential inferred from 16S data were assessed using DADA2 (v1.30.0), phyllode (v1.46.0), and PICRUSt2 (v2.5.2), with taxonomic classification based on the SILVA database (release 138). Beta diversity differences were tested using PERMANOVA (999 permutations), and differential abundance analyses were corrected using false discovery rate (FDR). Key findings and limitations – PCa tissues demonstrated higher alpha diversity than BPH samples, with greater heterogeneity in beta diversity. Among the identified genera, Methylobacterium was enriched in PCa samples and remained directionally consistent after multivariable adjustment. Exploratory analyses suggested higher abundance in advanced and deceased cases; however, survival findings were limited by sample size. Functional inference indicated enrichment of predicted pathways for carbohydrate and nitrogen metabolism. Conclusions – This exploratory study identified Methylobacterium as a candidate microbial signature associated with PCa in an Arab cohort. Given the modest sample size and the inferential nature of functional predictions, these findings require validation in larger prospective studies using direct metagenomic and metabolomic approaches.