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Background: Several studies support the interplay between the urinary microbiome (ie, urobiome) and bladder cancer (BCa). Specific urinary bacteria may be responsible for chronic inflammation, which in turn promotes carcinogenesis. Different signatures of urobiome in BCa patients were identified depending on tumor type, geographical area, age, and sex. Objective: We explored the urobiome in BCa patients undergoing transurethral resection of bladder tumor (TURBT), to identify possible predictive biomarkers of cancer. Design, setting, and participants: The urobiome analysis was conducted in 48 patients (13 females) undergoing TURBT, of whom 30 with BCa (five females) and 18 with benign bladder tumor, analyzing bacterial 16S rRNA by next-generation sequencing in first-morning (FM) urine samples. Forty-three cancer-free individuals and 17 prostate cancer patients were used as controls. Outcome measurements and statistical analysis: First, we identified the better urine collection procedure to perform the urobiome analysis, comparing bacterial composition between catheterized (CAT) and FM urine samples in TURBT patients. Successively, we observed a specific urobiome in BCa patients rather than controls. A combined pipeline including the DESeq2 and linear discriminant analysis effect size tests was used to identify differential urinary taxa, strictly associated with BCa patients. Results and limitations: The bacterial composition of CAT and FM urine samples was comparable, so the latter was used for the following analyses. An increased abundance of Porphyromonas and Porphyromonas somerae was found in BCa patients compared with controls. This signature seems to be more related (p

To date, the increased awareness of the impact of microbes on human health has promoted scientific interest in microbiome studies for diagnostic and therapeutic purposes, revealing correlations between specific taxa and cancer. In particular, numerous species of Porphyromonas have been associated with several types of tumors. Previously, we studied the urobiome using Next-Generation Sequencing (NGS), and found an increase in Porphyromonas somerae in first morning urine of subjects affected by bladder cancer (BCa). Here, we aimed to confirm the presence of P. somerae in BCa patients by using droplet digital Polymerase Chain Reaction (ddPCR), testing a cohort of 102 male subjects over 50 years. Our findings showed a significant increase in P. somerae in the urine of the BCa group within both ddPCR and NGS, and a correlation between the two methods was observed at a statistical level. Moreover, P. somerae’s identification with ddPCR confirmed a significant association between this bacterium and the presence of BCa, highlighting its potential role as a biomarker. This allows us to propose the ddPCR as a suitable method for first-stage BCa screening and follow-up.