Background
Despite being a controversial marker, serum PSA is the most widely used tool for prostate cancer (PCa) screening and early diagnosis. However, elevated levels can reflect non-cancerous conditions such as benign prostatic hyperplasia or prostatitis. Consequently, second-level diagnostic investigations, such as digital rectal examination (DRE) and, in suspicious cases, MRI followed by fusion biopsy, are often performed, leading to potential over-diagnosis and unnecessary procedures.
Objectives
Fondazione Edo ed Elvo Tempia coordinates the observational DP3 trial, which collects plasma, serum, peripheral blood mononuclear cells (PBMC), urine, tumor tissue and lifestyle data from men over 50. The over 1000 enrolled subjects include: 1) men adhering to opportunistic PCa screening (PSA/DRE testing, followed-up every 6 months for 2 years); 2) men with suspected PCa prior to fusion biopsy; and 3) men diagnosed with PCa prior to radical prostatectomy (both clinical groups followed according to standard practice). We report the preliminary results investigating the role of the urinary microbiome in discriminating between men with and without PCa, specifically within the cohort recalled for fusion biopsy.
Methods
First-morning urine samples were collected prior to antibiotic prophylaxis, before biopsy. An innovative urine-based application of the PathoChip array (developed at the University of Pennsylvania) was established by our lab enabling the simultaneous analysis of both DNA- and RNA-derived pathogens within a single experiment (4200 viruses, 320 bacteria, 360 fungi, 130 protozoa, and 1200 parasitic worms). DNA and RNA were isolated from sediments isolated
from 8mL of urines, a blank control, and the BJAB human B-cell line (used as reference for hybridization control/background normalization). Sample and reference nucleic acids underwent whole-genome and transcriptome amplification, differential labeling, and co-hybridization onto the PathoChip array. After scanning with the Agilent dual laser microarray scanner and Feature Extraction software processing, a circulating pathogen analysis pipeline was applied, where fluorescence signals from the sample and the reference were compared to detect sample-specific probes (figure 1, green dots). Specifically, a linear model (Y ~ X) was fitted to the log2-transformed red (X) and green (Y) intensities. Residuals were calculated, and a local threshold, decreasing with increasing X intensity, was defined. Probes with residuals exceeding this adaptive threshold and lying above the diagonal (Y > X) were flagged as outliers and considered specifically expressed in the urine samples. The blank control, processed identically to the patient samples, was used to subtract reagent-related pathogen contributions.
Results
Preliminary results from the first 35 urinary samples reveal that specific pathogens are detectable exclusively in PCa patients and not in subjects with suspected tumors (benign conditions).
Conclusions
These findings suggest that the urinary microbiota may serve as a novel, non-invasive biomarker to significantly improve PCa diagnosis and reduce the need for unnecessary biopsies in men with elevated PSA levels.

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