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Integrated analysis of the microbiome and transcriptome in stomach adenocarcinoma.


ABSTRACT: We aimed to characterize the stomach adenocarcinoma (STAD) microbiota and its clinical value using an integrated analysis of the microbiome and transcriptome. Microbiome and transcriptome data were downloaded from the Cancer Microbiome Atlas and the Cancer Genome Atlas databases. We identified nine differentially abundant microbial genera, including Helicobacter, Mycobacterium, and Streptococcus, which clustered patients into three subtypes with different survival rates. In total, 74 prognostic genes were screened from 925 feature genes of the subtypes, among which five genes were identified for prognostic model construction, including NTN5, MPV17L, MPLKIP, SIGLEC5, and SPAG16. The prognostic model could stratify patients into different risk groups. The high-risk group was associated with poor overall survival. A nomogram established using the prognostic risk score could accurately predict the 1, 3, and 5 year overall survival probabilities. The high-risk group had a higher proportion of histological grade 3 and recurrence samples. Immune infiltration analysis showed that samples in the high-risk group had a higher abundance of infiltrating neutrophils. The Notch signaling pathway activity showed a significant difference between the high- and low-risk groups. In conclusion, a prognostic model based on five feature genes of microbial subtypes could predict the overall survival for patients with STAD.

SUBMITTER: Zhou D 

PROVIDER: S-EPMC10350897 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Integrated analysis of the microbiome and transcriptome in stomach adenocarcinoma.

Zhou Daxiang D   Xiong Shu S   Xiong Juan J   Deng Xuesong X   Long Quanzhou Q   Li Yanjie Y  

Open life sciences 20230715 1


We aimed to characterize the stomach adenocarcinoma (STAD) microbiota and its clinical value using an integrated analysis of the microbiome and transcriptome. Microbiome and transcriptome data were downloaded from the Cancer Microbiome Atlas and the Cancer Genome Atlas databases. We identified nine differentially abundant microbial genera, including <i>Helicobacter</i>, <i>Mycobacterium</i>, and <i>Streptococcus</i>, which clustered patients into three subtypes with different survival rates. In  ...[more]

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