Evaluation Of Urinary Microbiome As A Diagnostic Biomarkers And Prognostic Predictor For Bladder Cancer

BackgroundThe etiology and pathogenesis of bladder cancer is still ill-defined.Approximately 70-75%of bladder malignancies are diagnosed as non-muscle-invasive bladder cancer(NMIBC),which is characterized by high recurrence and progression rate.However,there is still a lack of independent predictor for clinical outcome and clinical management remains challenging.The study of microbiome has overturned the knowledge about diseases of infection,tumor,metabolism,and has been proved to have the potential of biomarkers,which may be useful for the early diagnosis of specific diseases.The dogma that urine in healthy individuals must be sterile has been overturned.Dysbiosis of the urinary microbiome may be associated with pathological conditions We hypothesized that the urinary microbiota may play a role in the pathogenesis of bladder cancer and be associated with clinical outcomes.Therefore,we performed this study to characterize the potential urinary microbial community possibly associated with bladder cancer.Materials and methods1.Subject Recruitment and Specimen CollectionFrom August 2017 to September 2019,male patients with bladder cancer in the Nanfang Hospital and healthy volunteers were enrolled in this study.The follow-up study cohort consisted of patients with NMIBC who underwent TURBT.2.DNA Isolation and 16S rDNA Gene SequencingSamples were obtained from midstream urine(30?50 mL).We used a BiOstic Bacteremia DNA Isolation(MOBIO,USA)to isolate DNA.Primer sets specific for V3-V4 regions of 16S rDNA gene were applied to PCR amplification.Illumina MiSeq sequencer(Illumina,USA)were used to sequence the amplified sequences.3.Bioinformatics AnalysisSequencing data was imported into QIIME and clustered into operational taxonomic units(OTUs).Based on the analysis results of OTUs,the ? and ? diversity comparison of urine microbiota was performed.The Linear discriminant analysis effect size(LEfSe)online tool was used to identify bacteria that were significantly different in genus levels.4.Statistical AnalysisData are presented as median(first quartile to the third quartile)for continuous variables or number of cases(%)for counts data.The statistical significance of differences between groups were evaluated using Mann-Whitney U-test for continuous variables and Pearson's chi-square test or Fisher's Exact Test for count data through SPSS software(Version 22.0).Kaplan-Meier survival analysis was used to compare tumor recurrence free survival.Results1.The microbial richness indices(Observed Species index,Chao1 index,Ace index;all P<0.01)were significantly higher in the cancer cohort than in the control cohort,while there were no differences in species diversity indices(Simpson index,Shannon index;both P>0.05)between groups.We used beta-diversity to generate a principal coordinate analysis(PCoA)using unweighted-UniFrac distances.A clear clustering between OTUs from bladder cancer and control group was revealed,suggesting that the microbial communities exhibit phylogenetic closeness within each group(P<0.05).2.To explore the potential ability of the microbiome to identify bladder cancer status,we constructed an ROC(receiver operating characteristic)curve analysis to analyze the clinical accuracy of using the urinary microbiome for the diagnosis of bladder cancer.The result shows that AUC(area under the curve)was 0.79(Observed Species index),0.82(Chao1 index)and 0.84(Ace index),suggesting that microbiome richness might play a role in the diagnosis of bladder cancer.3.We then compared the microbial community of the recurrence groups and non-recurrence groups.Higher Shannon index(diversity,P<0.05)and lower Simpson index(diversity,P<0.05)were presented in recurrence group,which means that alpha-diversity of the microbiome was significantly higher in the recurrence group compared with non-recurrence group.While no statistically significant differences were observed among the Sobs,Ace and Chao1 indices in recurrence group.Based on these results,we then tested the relationship between microbial diversity and clinical outcome by stratifying the patients into two groups based on median diversity obtained by Shannon index.We found that patients with high alpha diversity had significantly prolonged recurrence-free survival than those with low alpha diversity using univariate Cox proportional hazard models.4.We identified the specific taxa associated with recurrence by using LEfSe analysis.The results showed that 9 genera were overrepresented in patients with recurrence,such as Anoxybacillus,Massilia.ConclusionOur study suggests that urinary microbiota may be associated with bladder cancer and clinical outcomes of patients with NMIBC after TURBT,but the cause-effect relationship remains unclear.Prospective studies are needed to disentangle the association between cancer development and microbiome dysbiosis,as well as the possible role of these bacterial communities in the metabolism of carcinogenic compounds present in the urinary tract.