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A Method to Define the Effects of Environmental Enrichment on Colon Microbiome Biodiversity in a Mouse Colon Tumor Model
Published on: February 28, 2018
Oral microbial profile polymorphisms predict early Siewert II adenocarcinoma of esophagogastric junction
Fangrui Zou1,2, Han Chen1,2, Xin Yu1,2
1Department of Gastroenterology, The First Affiliated Hospital with Nanjing Medical University, 300# Guangzhou Road, Nanjing, Jiangsu Province, China.
Background:
Dysbiosis of the oral microbiota has been shown to be associated with the development of esophageal and gastric cancer. Nevertheless, little research explores how oral microbiota might contribute to the occurrence and progression of adenocarcinoma of the esophagogastric junction (AEG).
Method:
16 S rRNA V3-V4 amplicon sequencing was performed on 106 oral microbiota samples from 55 AEG patients and 51 controls. To determine key microbial indicators, Linear Discriminant Analysis Effect Size (LEfSe) analysis, Random Forest model, and species composition heatmaps were utilised. Spearman correlation analysis assessed the relationship between oral microbiota and clinicopathological variables. PICRUSt2 was employed to predict microbial functions and investigate the association with KEGG metabolic pathways.
Results:
A total of 584 oral genera and 647 oral species were observed in AEG and controls, excluding unidentified species. The abundance of 24 oral genera significantly increased in AEG patients, with Neisseria, Streptococcus, Rothia, Gemella, and Capnocytophaga being the five most abundant. Lefse, RF model and Species composition heatmap identified that genera enriched in the AEG group including Streptococcus, Neisseria, Rothia, Gemella, and genera depleted including Prevotella, Veillonella, Centipeda, Nanosynbacter were determined as biological markers to distinguish AEG from healthy controls. The genera with decreased abundance in AEG patients showed a positive association with WBC levels, neutrophil levels, and CA724 levels in the Mantel correlation test. PICRUSt analysis revealed significant differences in the abundance of 12 KEGG pathways. Carbohydrate metabolism, drug resistance, infectious diseases, lipid metabolism, nucleotide metabolism, and membrane transport pathways were positively correlated with genera enriched in the AEG group such as Streptococcus and Rothia, while negatively correlated with depleted genera like Prevotella.
Conclusion:
Our research may suggest that dysbiosis of the oral microbiota and alterations in the KEGG metabolic pathway are linked to the development of AEG. In the future, we will conduct comprehensive verification through animal experiments and large-scale multicentre studies.

