Dataset Information

Gastric Mucosa-Associated Microbial Signatures of Early Gastric Cancer.

ABSTRACT: Alterations in the microbiome are associated with the development of gastric cancer. Our study aimed to identify dysbiotic features in early gastric cancer (EC). The gastric microbiome was assessed in EC (n = 30), advanced gastric cancer (AC) (n = 30), and chronic gastritis (CG) (n = 60). The results demonstrated significant differences in the microbial profile and composition between EC and AC, suggesting alterations associated with gastric cancer progression. Linear discriminant analysis (LDA) effect size (LEfSe) analyses identified 32 bacterial genera that were associated with EC. Functional analyses of the gastric microbiome showed that the production of urease and synthesis of bacterial flagella were weakened in EC, while the glycolysis of fructose and hydrolysis of glycosides were enhanced. A classifier based on a random forest (RF) machine learning algorithm identified a microbial signature that distinguished EC from CG or AC with high accuracy. The correct identification of the signature was further validated in independent cohorts. This signature enriched of bacteria with varied abundance, high degree of bacterial interactions and carcinogenic potentials. Constrained principal coordinate analyses revealed that the presence of Helicobacter pylori and the cagA and vacA virulence genotypes influenced the structure of the gastric microbiome. To determine the impacts of host genetic variations on the gastric microbiome, six previously reported single nucleotide polymorphisms (SNPs) were examined. The minor allele of MUC1 rs4072037 was associated with an increased abundance of Ochrobactrum. The gastric microbiome altered in EC, which might be attributed in part to host genetic variations, H. pylori infection, bacterial virulence and environmental adaptations. The identified microbial signature could serve as biomarkers for clinical assessment of gastric cancer risk in high-risk patients.

SUBMITTER: Wang L

PROVIDER: S-EPMC7358557 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Gastric Mucosa-Associated Microbial Signatures of Early Gastric Cancer.

Wang Lili L Xin Yongning Y Zhou Jianhua J Tian Zibin Z Liu Chenguang C Yu Xinjuan X Meng Xinying X Jiang Weina W Zhao Shoufeng S Dong Quanjiang Q

Frontiers in microbiology 20200707

Alterations in the microbiome are associated with the development of gastric cancer. Our study aimed to identify dysbiotic features in early gastric cancer (EC). The gastric microbiome was assessed in EC (n = 30), advanced gastric cancer (AC) (n = 30), and chronic gastritis (CG) (n = 60). The results demonstrated significant differences in the microbial profile and composition between EC and AC, suggesting alterations associated with gastric cancer progression. Linear discri ...[more]

PMID: 32733423

Similar Datasets

Project description:The link between microbiota and gastric cancer (GC) has attracted widespread attention. However, the phylogenetic profiles of niche-specific microbiota in the tumor microenvironment is still unclear. Here, mucosa-associated microorganisms from 62 pairs of matched GC tissues and adjacent non-cancerous tissues were characterized by 16S rRNA gene sequencing. Functional profiles of the microbiota were predicted using PICRUSt, and a co-occurrence network was constructed to analyze interactions among gastric microbiota. Results demonstrated that mucosa-associated microbiota from cancerous and non-cancerous tissues established micro-ecological systems that differed in composition, structure, interaction networks, and functions. Microbial richness and diversity were increased in cancerous tissues, with the co-occurrence network exhibiting greater complexity compared with that in non-cancerous tissue. The bacterial taxa enriched in the cancer samples were predominantly represented by oral bacteria (such as Peptostreptococcus, Streptococcus, and Fusobacterium), while lactic acid-producing bacteria (such as Lactococcus lactis and Lactobacillus brevis) were more abundant in adjacent non-tumor tissues. Colonization by Helicobacter pylori, which is a GC risk factor, also impacted the structure of the microbiota. Enhanced bacterial purine metabolism, carbohydrate metabolism and denitrification functions were predicted in the cancer associated microbial communities, which was consistent with the increased energy metabolism and concentration of nitrogen-containing compounds in the tumor microenvironment. Furthermore, the microbial co-occurrence networks in cancerous and non-cancerous tissues of GC patients were described for the first time. And differential taxa and functions between the two groups were identified. Changes in the abundance of certain bacterial taxa, especially oral microbiota, may play a role in the maintenance of the local microenvironment, which is associated with the development or progression of GC.

Project description:BackgroundFew studies have examined prognostic outcomes-associated molecular signatures other than overall survival (OS) for gastric cancer (GC). We aimed to identify DNA methylation biomarkers associated with multiple prognostic outcomes of GC in an epigenome-wide association study.MethodsBased on the Cancer Genome Atlas (TCGA), DNA methylation loci associated with OS (n = 381), disease-specific survival (DSS, n = 372), and progression-free interval (PFI, n = 383) were discovered in training set subjects (false discovery rates < 0.05) randomly selected for each prognostic outcome and were then validated in remaining subjects (P-values < 0.05). Key CpGs simultaneously validated for OS, DSS, and PFI were further assessed for disease-free interval (DFI, n = 247). Gene set enrichment analyses were conducted to explore the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways simultaneously enriched for multiple GC prognostic outcomes. Methylation correlated blocks (MCBs) were identified for co-methylation patterns associated with GC prognosis. Based on key CpGs, risk score models were established to predict four prognostic outcomes. Spearman correlation analyses were performed between key CpG sites and their host gene mRNA expression.ResultsWe newly identified DNA methylation of seven CpGs significantly associated with OS, DSS, and PFI of GC, including cg10399824 (GRK5), cg05275153 (RGS12), cg24406668 (MMP9), cg14719951(DSC3), and cg25117092 (MED12L), and two in intergenic regions (cg11348188 and cg11671115). Except cg10399824 and cg24406668, five of them were also significantly associated with DFI of GC. Neuroactive ligand-receptor interaction pathway was suggested to play a key role in the effect of DNA methylation on GC prognosis. Consistent with individual CpG-level association, three MCBs involving cg11671115, cg14719951, and cg24406668 were significantly associated with multiple prognostic outcomes of GC. Integrating key CpG loci, two risk score models performed well in predicting GC prognosis. Gene body DNA methylation of cg14719951, cg10399824, and cg25117092 was associated with their host gene expression, whereas no significant associations between their host gene expression and four clinical prognostic outcomes of GC were observed.ConclusionsWe newly identified seven CpGs associated with OS, DSS, and PFI of GC, with five of them also associated with DFI, which might inform patient stratification in clinical practices.

Dataset Information

Gastric Mucosa-Associated Microbial Signatures of Early Gastric Cancer.

Publications

Gastric Mucosa-Associated Microbial Signatures of Early Gastric Cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets