Global Analysis of Microbiota Signatures in Four Major Types of Gastrointestinal Cancer

Abstract

The gut microbiota has been previously linked with tumorigenesis and gastrointestinal cancer progression; however, intra-tumor microbiota analysis has just emerged and deserves increasing attention. Based on the public databases of The Cancer Microbiome Atlas (TCMA) and The Cancer Genome Atlas (TCGA), this study identified the tissue/organ microbial signatures generated from 443 biosamples of four major gastrointestinal cancer types, including esophageal carcinoma (ESCA), which further includes esophageal adenocarcinoma (EAD) and esophageal squamous cell carcinoma (ESCC), stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD), and rectum adenocarcinoma (READ). According to partial least squares discrimination analysis (PLS-DA), the profile differences in microbial communities between the tumor and normal samples were not particularly noticeable across the four cancer cohorts, whereas paired comparison analyses revealed several specific differences in bacteria between tumor and normal samples in the EAD, STAD, and COAD samples. The taxa classified from the phylum to genus level revealed a trend of distinguishable microbial profiles between upper and lower gastrointestinal tumors. The Bacteroidetes/Firmicutes ratio in lower gastrointestinal tract tumors was nearly three times that in upper gastrointestinal tract tumors. We also determined the relative tissue/organ-prevalent microbes for each of the four cohorts at the order and genus levels. Microbe Alistipes, Blautia, Pasteurellales, and Porphyromonas compositions were correlated with the clinical characteristics of patients with gastrointestinal cancer, particularly colorectal cancer. Taken together, our findings indicate that microbial profiles shift across different gastrointestinal cancer types and that microbial colonization is highly site-specific. Composition of specific microbes can be indicative of cancer stage or disease progression. Overall, this study indicates that the microbial community and abundance in human tissues can be determined using publicly available data, and provides a new perspective for intra-tissue/organ microbiota research.