Integrated analysis of the microbiome and transcriptome in stomach adenocarcinoma

被引:3
|
作者
Zhou, Daxiang [2 ]
Xiong, Shu [1 ]
Xiong, Juan [3 ]
Deng, Xuesong [1 ]
Long, Quanzhou [2 ]
Li, Yanjie [2 ]
机构
[1] Chongqing Three Gorges Med Coll, Dept Basic Med, 666 Tianxing Rd, Chongqing 404120, Peoples R China
[2] Chongqing Three Gorges Univ, Coll Biol & Food Engn, Chongqing Engn Lab Green Planting & Deep Proc Famo, Chongqing 404120, Peoples R China
[3] Jiulongpo Peoples Hosp Chongqing, Dept Neonatol, Chongqing 400050, Peoples R China
来源
OPEN LIFE SCIENCES | 2023年 / 18卷 / 01期
关键词
stomach adenocarcinoma; microbiota; subtype; prognostic model; immune infiltration; CANCER;
D O I
10.1515/biol-2022-0528
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
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页数:14
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