Analysis of bacterial diversity and community structure in gastric juice of patients with advanced gastric cancer

Author:

Wei Qiang,Zhang Qi,Wu Yinhang,Han Shuwen,Yin Lei,Zhang Jinyu,Gao Yuhai,Shen Hong,Zhuang Jing,Chu Jian,Liu Jiang,Wei Yunhai

Abstract

AbstractBackgroundThe occurrence and development of gastric cancer are related to microorganisms, which can be used as potential biomarkers of gastric cancer.ObjectiveTo screen the microbiological markers of gastric cancer from the microorganisms of gastric juice.MethodsGastric juice samples were collected from 61 healthy people and 78 patients with gastric cancer (48 cases of early gastric cancer and 30 cases of advanced gastric cancer). The bacterial 16 S rRNA V1-V4 region of gastric juice samples was sequenced. The Shannon index, Simpson index, Ace index and Chao index were used to analyze the diversity of gastric juice samples. The RDP classifier Bayesian algorithm was used to analyze the community structure of 97% OTU representative sequences with similar levels. Linear discriminant analysis and ST-test were used to analyze the differences. Six machine learning algorithms, including the logistic regression algorithm, random forest algorithm, neural network algorithm, support vector machine algorithm, Catboost algorithm and gradient lifting tree algorithm, were used to construct risk prediction models for gastric cancer and advanced gastric cancer.ResultsThe microbiota diversity and the abundance of bacteria was different in the healthy group, early gastric cancer and advanced gastric cancer (P < 0.05). The top five abundant bacteria among the three groups wereStreptococcus, Rhodococcus, Prevotella, PseudomonasandHelicobacter.Bacterial flora such asStreptococcus, RhodococcusandOchrobactrumwere significantly different between the healthy group and the gastric cancer group. The accuracy of the random forest prediction model is the highest (82.73% correct). The bacteria with the highest predictive value includedStreptococcus, LactobacillusandOchrobactrum. The abundance of bacteria such asFusobacterium, Capnocytophaga, Atopobium, Corynebacteriumwas high in the advanced gastric cancer group.ConclusionGastric juice bacteria can be used as potential biomarkers to predict the occurrence and development of gastric cancer.

Funder

Public Welfare Technology Application Research Program of Huzhou

Publisher

Springer Science and Business Media LLC

Subject

Cancer Research,Endocrine and Autonomic Systems,Endocrinology,Oncology,Endocrinology, Diabetes and Metabolism

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