Purpose Studies demonstrating bacterial DNA and cultivable bacteria in urine samples have challenged the clinical dogma that urine is sterile. Furthermore, studies now indicate that dysbiosis of the urinary microbiome is associated with pathological conditions. We propose that the urinary microbiome may influence chronic inflammation observed in the prostate, leading to prostate cancer development and progression. Therefore, we profiled the urinary microbiome in men with positive vs negative biopsies for prostate cancer. Materials and Methods Urine was collected from men prior to biopsy for prostate cancer. DNA was extracted from urine pellet samples and subjected to bacterial 16S rDNA Illumina® sequencing and 16S rDNA quantitative polymerase chain reaction. We determined the association between bacterial species and the presence or absence of cancer, cancer grade, and type and degree of prostate inflammation. Results Urine samples revealed diverse bacterial populations. There were no significant differences in α or β diversity and no clear hierarchical clustering of benign or cancer samples. We identified a cluster of pro-inflammatory bacteria previously implicated in urogenital infections in a subset of samples. Many species, including known uropathogens, were significantly and differentially abundant among cancer and benign samples, in low vs higher grade cancers and in relation to prostate inflammation type and degree. Conclusions To our knowledge we report the most comprehensive study to date of the male urinary microbiome and its relationship to prostate cancer. Our results suggest a prevalence of pro-inflammatory bacteria and uropathogens in the urinary tract of men with prostate cancer.

In health, the microbiome encourages homeostasis and helps educate the immune system. In dysbiosis, a systemic inflammatory state may be induced, predisposing remote anatomical sites to disease, including cancer. The microbiome's ability to affect systemic hormone levels may also be important, particularly in a disease such as prostate cancer that is dually affected by estrogen and androgen levels. Due to the complexity of the potential interconnectedness between prostate cancer and the microbiome, it is vital to further explore and understand the relationships that are involved.

Prostate adenocarcinoma is the second most commonly diagnosed cancer in men worldwide, and the initiating factors are unknown. Oncogenic TMPRSS2:ERG (ERG+) gene fusions are facilitated by DNA breaks and occur in up to 50% of prostate cancers. Infection-driven inflammation is implicated in the formation of ERG+ fusions, and we hypothesized that these fusions initiate in early inflammation-associated prostate cancer precursor lesions, such as proliferative inflammatory atrophy (PIA), prior to cancer development. We investigated whether bacterial prostatitis is associated with ERG+ precancerous lesions in unique cases with active bacterial infections at the time of radical prostatectomy. We identified a high frequency of ERG+ non–neoplastic-appearing glands in these cases, including ERG+ PIA transitioning to early invasive cancer. These lesions were positive for ERG protein by immunohistochemistry and ERG messenger RNA by in situ hybridization. We additionally verified TMPRSS2:ERG genomic rearrangements in precursor lesions using tricolor fluorescence in situ hybridization. Identification of rearrangement patterns combined with whole-prostate mapping in three dimensions confirmed multiple (up to eight) distinct ERG+ precancerous lesions in infected cases. We further identified the pathogen-derived genotoxin colibactin as a potential source of DNA breaks in clinical cases as well as cultured prostate cells. Overall, we provide evidence that bacterial infections can initiate driver gene alterations in prostate cancer. In addition, our observations indicate that infection-induced ERG+ fusions are an early alteration in the carcinogenic process and that PIA may serve as a direct precursor to prostate cancer.

Prostate cancer is the second leading cause of cancer death in men in the developed world. A more sensitive and specific detection strategy for lethal prostate cancer beyond serum prostate specific antigen (PSA) population screening is urgently needed. Diagnosis by canine olfaction, using dogs trained to detect cancer by smell, has been shown to be both specific and sensitive. While dogs themselves are impractical as scalable diagnostic sensors, machine olfaction for cancer detection is testable. However, studies bridging the divide between clinical diagnostic techniques, artificial intelligence, and molecular analysis remains difficult due to the significant divide between these disciplines. We tested the clinical feasibility of a cross-disciplinary, integrative approach to early prostate cancer biosensing in urine using trained canine olfaction, volatile organic compound (VOC) analysis by gas chromatography-mass spectroscopy (GC-MS) artificial neural network (ANN)-assisted examination, and microbial profiling in a double-blinded pilot study. Two dogs were trained to detect Gleason 9 prostate cancer in urine collected from biopsy-confirmed patients. Biopsy-negative controls were used to assess canine specificity as prostate cancer biodetectors. Urine samples were simultaneously analyzed for their VOC content in headspace via GC-MS and urinary microbiota content via 16S rDNA Illumina sequencing. In addition, the dogs’ diagnoses were used to train an ANN to detect significant peaks in the GC-MS data. The canine olfaction system was 71% sensitive and between 70–76% specific at detecting Gleason 9 prostate cancer. We have also confirmed VOC differences by GC-MS and microbiota differences by 16S rDNA sequencing between cancer positive and biopsy-negative controls. Furthermore, the trained ANN identified regions of interest in the GC-MS data, informed by the canine diagnoses. Methodology and feasibility are established to inform larger-scale studies using canine olfaction, urinary VOCs, and urinary microbiota profiling to develop machine olfaction diagnostic tools. Scalable multi-disciplinary tools may then be compared to PSA screening for earlier, non-invasive, more specific and sensitive detection of clinically aggressive prostate cancers in urine samples.

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Prostate cancer is the second leading cause of cancer death in men in the developed world. A more sensitive and specific detection strategy for lethal prostate cancer beyond serum prostate specific antigen (PSA) population screening is urgently needed. Diagnosis by canine olfaction, using dogs trained to detect cancer by smell, has been shown to be both specific and sensitive. While dogs themselves are impractical as scalable diagnostic sensors, machine olfaction for cancer detection is testable. However, studies bridging the divide between clinical diagnostic techniques, artificial intelligence, and molecular analysis remains difficult due to the significant divide between these disciplines. We tested the clinical feasibility of a cross-disciplinary, integrative approach to early prostate cancer biosensing in urine using trained canine olfaction, volatile organic compound (VOC) analysis by gas chromatography-mass spectroscopy (GC-MS) artificial neural network (ANN)-assisted examination, and microbial profiling in a double-blinded pilot study. Two dogs were trained to detect Gleason 9 prostate cancer in urine collected from biopsy-confirmed patients. Biopsy-negative controls were used to assess canine specificity as prostate cancer biodetectors. Urine samples were simultaneously analyzed for their VOC content in headspace via GC-MS and urinary microbiota content via 16S rDNA Illumina sequencing. In addition, the dogs’ diagnoses were used to train an ANN to detect significant peaks in the GC-MS data. The canine olfaction system was 71% sensitive and between 70-76% specific at detecting Gleason 9 prostate cancer. We have also confirmed VOC differences by GC-MS and microbiota differences by 16S rDNA sequencing between cancer positive and biopsy-negative controls. Furthermore, the trained ANN identified regions of interest in the GC-MS data, informed by the canine diagnoses. Methodology and feasibility are established to inform larger-scale studies using canine olfaction, urinary VOCs, and urinary microbiota profiling to develop machine olfaction diagnostic tools. Scalable multi-disciplinary tools may then be compared to PSA screening for earlier, non-invasive, more specific and sensitive detection of clinically aggressive prostate cancers in urine samples.

Prostate adenocarcinoma is the second most commonly diagnosed cancer in men worldwide and the initiating factors are unknown. Oncogenic TMPRSS2:ERG (ERG+) gene fusions are facilitated by DNA breaks and occur in up to 50% of prostate cancers1,2. Infection-driven inflammation is implicated in the formation of ERG+ fusions3, and we hypothesized that these fusions initiate in early inflammation-associated prostate cancer precursor lesions, such as proliferative inflammatory atrophy (PIA), prior to cancer development. We investigated whether bacterial prostatitis is associated with ERG+ precancerous lesions in unique cases with active bacterial infections at time of radical prostatectomy. We identified a high frequency of ERG+ non-neoplastic-appearing glands in these cases, including ERG+ PIA transitioning to early invasive cancer. We verified TMPRSS2:ERG genomic rearrangements in precursor lesions using tri-color fluorescence in situ hybridization. Identification of rearrangement patterns combined with whole prostate mapping in 3 dimensions confirmed multiple (up to 8) distinct ERG+ precancerous lesions in infected cases. Finally, we identified the pathogen-derived genotoxin colibactin as a potential source of DNA breaks in clinical cases as well as cultured prostate cells. Overall, we provide evidence that bacterial infections initiate driver gene alterations in prostate cancer. Furthermore, infection-induced ERG+ fusions are an early alteration in the carcinogenic process and PIA may serve as a direct precursor to prostate cancer.

No abstract