Microbiome, a new dimension in cancer research

Profiling the Bladder Microbiota in Patients With Bladder Cancer

Evidence suggests that microbiota may contribute to the pathogenesis of several diseases, including cancer. In the case of bladder cancer, preliminary studies have found alterations in the urinary microbiota of patients with urothelial carcinoma compared with healthy individuals. Conversely, the urinary microbiota differ between men and women, and it has been hypothesized that these differences are associated with the lower incidence of bladder cancers in women. The objective of this study was to characterize the bladder microbiota in paired samples of tumor and non-tumor mucosa of patients with malignant bladder neoplasia using next-generation sequencing. In addition, we aimed to study potential differences in microbial composition in tumor samples according to clinical and pathological variables, and to determine possible microbial profiles. We found significant differences in microbial richness at the genus level, with a higher richness observed in the non-tumor compared with the tumor mucosa. It was also shown that Actinobacteria were significantly more enriched in the non-tumor compared with the tumor mucosa (P = 0.014). In the multivariate analysis, we found significant differences in microbial composition according to tumor grade (P = 0.03 and 0.04 at the phylum and genus levels, respectively). Moreover, we detected a higher microbial richness in non-tumor vs. tumor tissues which agrees with the global assumption that microbial richness is an indicator of health. The greater abundance of members of the Actinobacteria phylum in the non-neoplastic bladder mucosa samples supports the hypothesis that a higher abundance of Actinomycetes is associated with a lower rate of bladder cancer in women and suggests a protective role for these microbiota. We detected a microbial profile that was enriched for Enterococcus in low-grade tumors. Finally, we identified the presence of two clusters in the microbial composition of the tumor mucosa samples, significantly enriched for the genera Barnesiella, Parabacteroides, Prevotella, Alistipes, and Lachnospiracea_incertae_sedis (Cluster 1), or Staphylococcus (Cluster 2). Further longitudinal studies are needed to assess the role of the bladder microbiota in carcinogenesis.

Alterations in Urobiome in Patients With Bladder Cancer and Implications for Clinical Outcome: A Single-Institution Study

Numerous studies indicate that resident microbiome exists in urine of healthy individuals and dysbiosis of the urobiome (urinary microbiome) may be associated with pathological conditions. This study was performed to characterize the alterations in urobiome and explore its implications of clinical outcome in male patients with bladder cancer. 62 male patients with bladder cancer and 19 non-neoplastic controls were recruited. The follow-up study cohort included 40 patients who were diagnosed with non-muscle invasive bladder cancer (NMIBC) and underwent transurethral resection of bladder tumor (TURBT). Mid-stream urine samples were collected from all the participants the day before cystoscopy. DNA was extracted from urine pellet samples and processed for high throughput 16S rRNA amplicon sequencing of the V4 region using Illumina MiSeq. Sequencing reads were filtered using QIIME and clustered using UPARSE. We found bacterial richness indices (Observed Species index, Chao1 index, Ace index; all P < 0.01) increased in cancer group when compared with non-neoplastic group, while there were no differences in Shannon and Simpson index between two groups. During a median follow-up time of 12 (5.25–25) months, 5/40 (12.5%)of the patients developed recurrence and no patient suffered from progression to muscle-invasive disease. Species diversity of the microbiome was significantly higher in the recurrence group compared with non-recurrence group in patients with NMIBC after TURBT. The LEfSe analysis demonstrated that 9 genera were increased (e.g., Micrococcus and Brachybacterium) in recurrence group. To our knowledge we report the relative comprehensive study to date of the male bladder cancer urinary microbiome and its relationship to pathogenesis and clinical outcomes. Given our preliminary data, additional studies evaluating the urine microbiome in relation to clinical outcomes are warranted to improve our understanding of tumor recurrence after TURBT.

Bayesian hierarchical negative binomial models for multivariable analyses with applications to human microbiome count data

The analyses of large volumes of metagenomic data extracted from aggregate populations of microscopic organisms residing on and in the human body are advancing contemporary understandings of the integrated participation of microbes in human health and disease. Next generation sequencing technology facilitates said analyses in terms of diversity, community composition, and differential abundance by filtering and binning microbial 16S rRNA genes extracted from human tissues into operational taxonomic units. However, current statistical tools restrict study designs to investigations of limited numbers of host characteristics mediated by limited numbers of samples potentially yielding a loss of relevant information. This paper presents a Bayesian hierarchical negative binomial model as an efficient technique capable of compensating for multivariable sets including tens or hundreds of host characteristics as covariates further expanding analyses of human microbiome count data. Simulation studies reveal that the Bayesian hierarchical negative binomial model provides a desirable strategy by often outperforming three competing negative binomial model in terms of type I error while simultaneously maintaining consistent power. An application of the Bayesian hierarchical negative binomial model using subsets of the open data published by the American Gut Project demonstrates an ability to identify operational taxonomic units significantly differentiable among persons diagnosed by a medical professional with either inflammatory bowel disease or irritable bowel syndrome that are consistent with contemporary gastrointestinal literature.

Integration of transcriptome and proteome profiles in glioblastoma: looking for the missing link

Background

Glioblastoma (GB) is the most common and aggressive tumor of the brain. Genotype-based approaches and independent analyses of the transcriptome or the proteome have led to progress in understanding the underlying biology of GB. Joint transcriptome and proteome profiling may reveal new biological insights, and identify pathogenic mechanisms or therapeutic targets for GB therapy. We present a comparison of transcriptome and proteome data from five GB biopsies (TZ) vs their corresponding peritumoral brain zone (PBZ). Omic analyses were performed using RNA microarray chips and the isotope-coded protein label method (ICPL).

Results

As described in other cancers, we found a poor correlation between transcriptome and proteome data in GB. We observed only two commonly deregulated mRNAs/proteins (neurofilament light polypeptide and synapsin 1) and 12 altered biological processes; they are related to cell communication, synaptic transmission and nervous system processes. This poor correlation may be a consequence of the techniques used to produce the omic profiles, the intrinsic properties of mRNA and proteins and/or of cancer- or GB-specific phenomena. Of interest, the analysis of the transcription factor binding sites present upstream from the open reading frames of all altered proteins identified by ICPL method shows a common binding site for the topoisomerase I and p53-binding protein TOPORS. Its expression was observed in 7/11 TZ samples and not in PBZ. Some findings suggest that TOPORS may function as a tumor suppressor; its implication in gliomagenesis should be examined in future studies.

Conclusions

In this study, we showed a low correlation between transcriptome and proteome data for GB samples as described in other cancer tissues. We observed that NEFL, SYN1 and 12 biological processes were deregulated in both the transcriptome and proteome data. It will be important to analyze more specifically these processes and these two proteins to allow the identification of new theranostic markers or potential therapeutic targets for GB.

Electronic supplementary material

The online version of this article (10.1186/s12867-018-0115-6) contains supplementary material, which is available to authorized users.