Published in:
01-02-2015 | Original Article—Alimentary Tract
Microbial mucosal colonic shifts associated with the development of colorectal cancer reveal the presence of different bacterial and archaeal biomarkers
Published in: Journal of Gastroenterology | Issue 2/2015
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Background
Epidemiological studies demonstrate a link between gastrointestinal cancers and environmental factors such as diet. It has been suggested that environmental cancer risk is determined by the interaction between diet and microbes. Thus, the purpose of this study was to examine the hypothesis that microbiota composition during colorectal cancer (CRC) progression might differ depending on the stage of the disease.
Methods
A total of 28 age-matched and sex-matched subjects, seven with CRC adenocarcinoma, 11 with tubular adenomas and ten healthy subjects with intact colon, were included into the study. Microbiomes from mucosal and fecal samples were analyzed with 16S ribosomal RNA gene pyrosequencing, together with quantitative PCR of specific bacteria and archaea.
Results
The principal coordinates analysis clearly separated healthy tissue samples from polyps and tumors, supporting the presence of specific bacterial consortia that are associated with affected sites and that can serve as potential biomarkers of CRC progression. A higher presence of Fusobacterium nucleatum and Enterobacteriaceae was found by qPCR in samples from CRC compared to healthy controls. We observed a correlation between CRC process development and levels of Methanobacteriales (R = 0.537, P = 0.007) and Methanobrevibacterium (R = 0.574, P = 0.03) in fecal samples.
Conclusion
Differences in microbial and archaeal composition between mucosal samples from healthy and disease tissues were observed in tubular adenoma and adenocarcinoma. In addition, microbiota from mucosal samples represented the underlying dysbiosis, whereas fecal samples seem not to be appropriate to detect shifts in microbial composition. CRC risk is influenced by microbial composition, showing differences according to disease progression step and tumor severity.