Variations in oral microbiota associated with oral cancer - PubMed (original) (raw)

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Variations in oral microbiota associated with oral cancer

Hongsen Zhao et al. Sci Rep. 2017.

Abstract

Individual bacteria and shifts in microbiome composition are associated with human disease, including cancer. To unravel the connections underlying oral bacterial dysbiosis and oral squamous cell carcinoma (OSCC), cancer lesion samples and anatomically matched normal samples were obtained from the same patients. We then profiled the bacteria within OSCC lesion surface samples at the species level using next-generation sequencing to comprehensively investigate bacterial community composition and functional genes in these samples. Significantly greater bacterial diversity was observed in the cancer samples than in the normal samples. Compared with previous studies, we identified many more taxa demonstrating remarkably different distributions between the groups. In particular, a group of periodontitis-correlated taxa, including Fusobacterium, Dialister, Peptostreptococcus, Filifactor, Peptococcus, Catonella and Parvimonas, was significantly enriched in OSCC samples. Additionally, several operational taxonomic units (OTUs) associated with Fusobacterium were highly involved in OSCC and demonstrated good diagnostic power. Our study revealed drastic changes in surface bacterial communities of OSCC. The findings enrich knowledge of the association between oral bacterial communities and oral cancer.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Figure 1

Figure 1

Comparison of oral microbiota structures in the N and T groups. (a) Rarefaction analysis of bacterial 16 S rRNA gene sequences was performed to evaluate whether further sequencing would likely detect additional taxa, indicated by a plateau. Different colors represent different samples. (b) Shannon index curves were constructed to evaluate the numbers of samples likely required to identify additional taxa, indicated by a plateau. Different colors represent different samples. (c) Box plots depict differences in bacterial diversity between the N and T groups according to the Shannon index. (d) PCA at the OTU level. (e) Partial least square discriminant score plot of oral microbiota between the N and T groups. N, clinical normal samples; T, oral cancer samples.

Figure 2

Figure 2

Composition of bacterial communities across samples at the phylum and genus levels. (a) Relative abundance of bacterial phyla among the N and T groups. (b) Classification tree of the 50 most abundant genera across all samples. The outer cycle colored bars represent the relative abundances of taxa in each group. N, clinical normal samples; T, oral cancer samples.

Figure 3

Figure 3

Distinct taxa identified in the N and T groups using LEfSe analysis. (a) Cladogram constructed using the LEfSe method to indicate the phylogenetic distribution of bacteria that were remarkably enriched in the N and T groups. (b) LDA scores showed significant bacterial differences within groups at the phylum level.(c) LDA scores showed significant bacterial differences within groups at the genus level. N, clinical normal samples; T, oral cancer samples.

Figure 4

Figure 4

Co-occurrence network of Fusobacterium comprising OTUs and the diagnostic power of selected OTUs. (a) Each node represents an OTU colored for its genus-level phylotypes, and each edge represents a significant co-occurrence relationship colored according to its association (red: positive, green: negative). (b) ROC curves for selected Fusobacterium OTUs were constructed to predict diagnostic power.

Figure 5

Figure 5

Co-occurrence and co-exclusion analysis of bacterial genera. Pearson correlations among the top 30 most abundant bacterial genera were calculated and analyzed; groups are shown on the left and right. Correlation values ranged from −1.00 (green) to 1.00 (red).

Figure 6

Figure 6

LDA scores predict gene function enriched in different groups using PICRUSt. N, clinical normal samples; T, oral cancer samples.

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