Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou 350108, China.
The Key Laboratory of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou 350108, China.
Int J Mol Sci. 2023 Oct 17;24(20):15259. doi: 10.3390/ijms242015259.
The use of metabolome genome-wide association studies (mGWAS) has been shown to be effective in identifying functional genes in complex diseases. While mGWAS has been applied to biomedical and pharmaceutical studies, its potential in predicting gastric cancer prognosis has yet to be explored. This study aims to address this gap and provide insights into the genetic basis of GC survival, as well as identify vital regulatory pathways in GC cell progression. Genome-wide association analysis of plasma metabolites related to gastric cancer prognosis was performed based on the Generalized Linear Model (GLM). We used a log-rank test, LASSO regression, multivariate Cox regression, GO enrichment analysis, and the Cytoscape software to visualize the complex regulatory network of genes and metabolites and explored in-depth genetic variation in gastric cancer prognosis based on mGWAS. We found 32 genetic variation loci significantly associated with GC survival-related metabolites, corresponding to seven genes, , , , , , , and . Furthermore, this study identified 722 Single nucleotide polymorphism (SNP) sites, suggesting an association with GC prognosis-related metabolites, corresponding to 206 genes. These 206 possible functional genes for gastric cancer prognosis were mainly involved in cellular signaling molecules related to cellular components, which are mainly involved in the growth and development of the body and neurological regulatory functions related to the body. The expression of 23 of these genes was shown to be associated with survival outcome in gastric cancer patients in The Cancer Genome Atlas (TCGA) database. Based on the genome-wide association analysis of prognosis-related metabolites in gastric cancer, we suggest that gastric cancer survival-related genes may influence the proliferation and infiltration of gastric cancer cells, which provides a new idea to resolve the complex regulatory network of gastric cancer prognosis.
基于广义线性模型（GLM）对与胃癌预后相关的血浆代谢物进行全基因组关联分析。我们使用对数秩检验、LASSO 回归、多变量 Cox 回归、GO 富集分析和 Cytoscape 软件来可视化基因和代谢物的复杂调控网络，并基于 mGWAS 深入探讨胃癌预后的遗传变异。我们发现 32 个遗传变异位点与 GC 生存相关代谢物显著相关，对应于七个基因、、、、、、和。此外，本研究还鉴定出 722 个单核苷酸多态性（SNP）位点，提示与 GC 预后相关代谢物相关，对应于 206 个基因。这些 206 个可能与胃癌预后相关的功能基因主要涉及与细胞成分相关的细胞信号分子，主要涉及身体的生长发育和与身体相关的神经调节功能。在癌症基因组图谱（TCGA）数据库中，这些基因中的 23 个基因的表达与胃癌患者的生存结果相关。基于胃癌预后相关代谢物的全基因组关联分析，我们提出胃癌生存相关基因可能影响胃癌细胞的增殖和浸润，这为解决胃癌预后的复杂调控网络提供了新的思路。
