Profiling the Urinary Microbiome in Men with Positive versus Negative Biopsies for Prostate Cancer

Abstract

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.

Keywords: bacteria; inflammation; microbiota; prostatic neoplasms; urinary tract.

Figure 1

Genera identified in urine pellet samples from men with or without biopsy proven prostate cancer diagnosis. Stacked bar plots represent sequence abundances of 15 most abundant genus or family level taxa identified. Percent sequence abundance is shown as number of reads matching given genus per total reads for that sample. SB, prostate cancer diagnosed on subsequent biopsy.

Figure 2

Bacterial load in urine pellet samples. A, load was determined by 16S rDNA qPCR and is shown as estimated number of operon copies of 16S rDNA present per urine pellet. Mocks, mock DNA extractions. B, percent sequence abundance of genus or family level taxa in samples with highest bacterial load (A).

Figure 3

Dendrogram shows log transformed unsupervised clustering of 16S rDNA Illumina sequencing results from urine pellet samples by genus based on hierarchical clustering of Euclidean distance between samples in combined benign, cancer and SB groups.

Figure 4

Dendrogram shows log transformed unsupervised clustering of 16S rDNA Illumina sequencing results from urine pellet samples by species based on hierarchical clustering of Euclidean distance between samples in combined benign, cancer and SB groups. Boxed area represents species level cluster (fig. 5).

Figure 5

Cluster of pro-inflammatory bacterial species differentially present in cancer samples identified in hierarchical clustering of all samples (fig. 4).

Figure 6

Mean percent differential abundance of select species of bacteria in benign, cancer and cancer SB samples. Adj., adjusted.