EURURO Vol. 72 No. 4

626 656

1. Introduction
Prostate cancer (PCa) remains among the most relevant
tumors in men . While age, ethnicity, and family history
maintain their etiologic role as risk factors, throughout the
last decades, viral and bacterial infections, inflammatory
stimuli, and environmental factors, such as diet and
lifestyle, have gained attention for their recognized
involvement in terms of prostate biology . All these
factors are known to affect the composition of microbiota,
the complex community of symbiotic bacteria, fungi,
parasites, and viruses living within the human body,
interacting with each other and with the host, and
eventually impacting overall health and physiology .
The advent of molecular-based methods of identification
and characterization of complex microbial populations (ie,
microbiome analysis) has led to a new era of microbial
discovery, thus unveiling important associations between
the microbiome composition and several pathological
conditions such as chronic inflammation, colon cancer,
diabetes, and obesity .
While inflammation has been proposed to play an
important role over malignant and benign prostatic growth,
potential stimuli that either induce or maintain tissue
inflammation, still remain poorly characterized. According
to previous demonstrations in different inflammatory and
tumor conditions, it is conceivable that modifications in
terms of bacterial populations could be also observed in PCa
lesions and partly contribute to cancer development by
either enhancing proinflammatory responses or modifying
the prostate extracellular environment . Many dif-
ferent pathogenic microorganisms are known to infect and
induce both symptomatic and asymptomatic inflammatory
responses in the prostate. These include both opportunistic
endogenous Enterobacteriaceae, such as Escherichia coli or
Pseudomonas spp., and sexually transmitted organisms such
as Neisseria gonorrhoeae, Chlamydia trachomatis, and
Trichomonas vaginalis More specifically,
Propionibacterium acnes, as detected by culture and direct
genome amplification in PCa samples, was associated with
increased organ inflammation However, despite the
growing body of literature reporting the composition of the
microbiome in various body niches and clinical conditions
a detailed and comprehensive analysis of the
microbial ecosystem of the pathologic and healthy prostate
tissues has not been reported yet. Similarly, the few
published data are not adequate with respect to the
competitive high-throughput sequencing and bioinformatics
tools currently available These considerations
prompted us to characterize the microbiome associated
with the nontumor, peri-tumor, and tumor tissue of the
human prostate by using massive ultradeep pyrosequencing
in order to assess its relevance upon the pathogenesis of PCa.
2. Materials and methods
2.1. Patient selection and specimen processing
Prostate specimens from16White Caucasian, nondiabetic, nonobese PCa
patients submitted to radical prostatectomy at the same institute
between 2011 and 2013 were considered for these analyses (Supple-
mentary Table 1). Patients with self-reported lower urinary tract
symptoms or a pathologic International Prostate Symptom Score were
excluded. None of the patients reported prior known sexually
transmitted infection or a recent history of urinary tract infections.
Data collection followed the principles outlined in the Declaration of
Helsinki; all patients had signed an informed consent agreeing to deliver
their own anonymous information for future studies. The study was
approved by our local ethical committee. The intact prostate glands were
delivered to our pathology laboratory under sterile conditions. Pickup
was followed by fixation of the samples in formalin and inclusion in
paraffin (FFPE). Specimens were postoperatively staged by a dedicated
uro-pathologist according to the TNM staging system and American
Joint Committee on Cancer stage groupings (I–IV). Matched tumoral (T),
peri-tumoral (PT), and nontumoral (NT) areas were isolated from each
FFPE peripheral zone of prostate tissue samples (Supplementary Fig. 1).
When more tumoral foci were present, the more representative tumoral
area has been selected according to the highest grade. Intraprostatic
inflammation of tumor specimens has been evaluated according to
Umbehr et al (Supplementary Table 2).
2.2. Prostate ultradeep pyrosequencing
Total DNA was purified from the samples using the QIAamp DNA FFPE
Tissue Kit (QIAGEN, Hilden, Germany), following the manufacturer’s
instructions. A detailed description of the amplification process and
following steps are reported in supplementary materials. Phylogenetic
diversity (defined as the minimum total length of all the phylogenetic
branches required to span a given set of taxa on a phylogenetic tree) was
calculated to determine alpha-diversity. Statistical differences among
groups in phylogenetic diversity were determined by comparison of
receiver operating characteristic curves. Beta-diversity analysis was
performed using weighted UniFrac distance metric, as implemented in
QIIME. Principal component analysis was performed in QIIME. For all
samples, at least 4000 sequences and a good coverage rate >99% were
obtained.
2.3. Statistical analysis
Data are presented as median (first quartile to the third quartile). The
statistical significance of differences among groups of specimens was
testedwith the one-way analysis of variance of Friedman’s test, with Dunn
posthoc test, for T versus PT versus NT and with Wilcoxon rank-sum test
for T + PT versus NT (according to data distribution). Weighted UniFrac
distance metric and principal component analysis were used to perform
beta-diversity analysis, in order to observe if there were overall changes in
species composition among tumoral, peri-tumoral, and nontumoral areas.
Statistical tests were performed using SPSS 21.0 (SPSS Inc., Chicago, IL,
USA). Microsoft Office Excel 2010 (Los Angelas, CA, USA) and Graphpad
Prism 5 (La Jolla, CA, USA) were used to create graphical representation of
the data. All tests were two sided, with a significance level set at 0.05.
3. Results
Supplementary Tables 1 and 2 detail clinical characteristics
and pathological parameters of the entire cohort of
patients/specimens.
3.1. Microbiome analysis of tissue prostate samples
We analyzed three distinct areas of each prostate, obtained
from radical prostatectomy: T, PT, and NT (Supplementary
Fig. 1).
E U R O P E A N U R O L O G Y 7 2 ( 2 0 1 7 ) 6 2 5 – 6 3 1 626