Michael A Liss1, James Robert White2, Martin Goros3, Jonathan Gelfond3, Robin Leach4, Teresa Johnson-Pais4, Zhao Lai5, Elizabeth Rourke4, Joseph Basler4, Donna Ankerst4, Dimpy P Shah3. 1. Department of Urology, University of Texas Health Science Center, San Antonio, TX, USA; South Texas Veterans Healthcare System, San Antonio, TX, USA. Electronic address: liss@uthscsa.edu. 2. Resphera Biosciences, Baltimore, MD, USA. 3. Department of Epidemiology and Biostatistics, University of Texas Health Science Center, San Antonio, TX, USA. 4. Department of Urology, University of Texas Health Science Center, San Antonio, TX, USA. 5. Greehey Children's Cancer Research Institute, San Antonio, TX, USA.
Abstract
BACKGROUND: The fecal microbiome is associated with prostate cancer risk factors (obesity, inflammation) and can metabolize and produce various products that may influence cancer but have yet to be defined in prostate cancer. OBJECTIVE: To investigate gut bacterial diversity, identify specific metabolic pathways associated with disease, and develop a microbiome risk profile for prostate cancer. DESIGN, SETTING, AND PARTICIPANTS: After prospective collection of 133 rectal swab samples 2 wk before the transrectal prostate biopsy, we perform 16S rRNA amplicon sequencing on 105 samples (64 with cancer, 41 without cancer). Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) was applied to infer functional categories associated with taxonomic composition. The p values were adjusted using the false discovery rate. The α- and β-diversity analyses were performed using QIIME. The Mann-Whitney U test was employed to evaluate the statistical significance of β-diversity distances within and between groups of interest, and least absolute shrinkage and selection operator (LASSO) regression analysis was used to determine pathway significance. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The detection of prostate cancer on transrectal prostate needle biopsy and 16s microbiome profile. RESULTS AND LIMITATIONS: We identified significant associations between total community composition and cancer/non-cancer status (Bray-Curtis distance metric, p<0.01). We identified significant differences in enrichments of Bacteroides and Streptococcus species in cancer (all p<0.04). Folate (LDA 3.8) and arginine (LDA 4.1) were the most significantly altered pathways. We formed a novel microbiome-derived risk factor for prostate cancer based on 10 aberrant metabolic pathways (area under curve=0.64, p=0.02). CONCLUSIONS: Microbiome analyses on men undergoing prostate biopsy noted mostly similar bacterial species diversity among men diagnosed with and without prostate cancer. The microbiome may have subtle influences on prostate cancer but are likely patient-specific and would require paired analysis and precise manipulation, such as improvement of natural bacterial folate production. PATIENT SUMMARY: Microbiome evaluation may provide patients with personalized data regarding the presence or absence of particular bacteria that have metabolic functions and implications regarding prostate cancer risk. The study provides a basis to investigate the manipulation of aberrant microbiomes to reduce prostate cancer risk. Published by Elsevier B.V.
BACKGROUND: The fecal microbiome is associated with prostate cancer risk factors (obesity, inflammation) and can metabolize and produce various products that may influence cancer but have yet to be defined in prostate cancer. OBJECTIVE: To investigate gut bacterial diversity, identify specific metabolic pathways associated with disease, and develop a microbiome risk profile for prostate cancer. DESIGN, SETTING, AND PARTICIPANTS: After prospective collection of 133 rectal swab samples 2 wk before the transrectal prostate biopsy, we perform 16S rRNA amplicon sequencing on 105 samples (64 with cancer, 41 without cancer). Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) was applied to infer functional categories associated with taxonomic composition. The p values were adjusted using the false discovery rate. The α- and β-diversity analyses were performed using QIIME. The Mann-Whitney U test was employed to evaluate the statistical significance of β-diversity distances within and between groups of interest, and least absolute shrinkage and selection operator (LASSO) regression analysis was used to determine pathway significance. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The detection of prostate cancer on transrectal prostate needle biopsy and 16s microbiome profile. RESULTS AND LIMITATIONS: We identified significant associations between total community composition and cancer/non-cancer status (Bray-Curtis distance metric, p<0.01). We identified significant differences in enrichments of Bacteroides and Streptococcus species in cancer (all p<0.04). Folate (LDA 3.8) and arginine (LDA 4.1) were the most significantly altered pathways. We formed a novel microbiome-derived risk factor for prostate cancer based on 10 aberrant metabolic pathways (area under curve=0.64, p=0.02). CONCLUSIONS: Microbiome analyses on men undergoing prostate biopsy noted mostly similar bacterial species diversity among men diagnosed with and without prostate cancer. The microbiome may have subtle influences on prostate cancer but are likely patient-specific and would require paired analysis and precise manipulation, such as improvement of natural bacterial folate production. PATIENT SUMMARY: Microbiome evaluation may provide patients with personalized data regarding the presence or absence of particular bacteria that have metabolic functions and implications regarding prostate cancer risk. The study provides a basis to investigate the manipulation of aberrant microbiomes to reduce prostate cancer risk. Published by Elsevier B.V.
Entities:
Keywords:
B vitamins; Biomarker; Biotin; Folate; Microbiome; Prostate cancer
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