Construction and validation of a prognostic model based on metabolism-related genes for patients with gastric cancer
Objective To construct and varify a prognostic model based on metabolism-related genes for patients with gastric cancer(GC).Methods Transcriptomic data and clinical information of GC patients were obtained from the gene expression omnibus(GEO)database.Integrated network analysis was conducted to identify key metabolism-related genes that regulate the epithelial-mesenchymal transition(EMT)subtype of GC.A metabolism-related prognostic model for GC was constructed using Cox regression,and risk stratification of GC patients was performed according to this model.The Kaplan-Meier survival curve was used to evaluate the prognostic prediction of the model,and gene set enrichment analysis(GSEA)was used to assess the inherent biological significance of the model.Results Integrated network analysis identified 3 metabolism marker genes(phospholipiol phosphatase related 4,glutamine-fructose-6-phosphate transaminase 2,and sulfatase 1)that were the main regulators of the EMT subtype,based on which a prognostic model was developed.According to the model,GC patients were classified as high-risk and low-risk groups.The Kaplan-Meier survival curves showed that patients in the high-risk group had a worse prognosis,and consistent results were observed in multiple validation datasets.GSEA analysis showed that pathways associated with malignant features such as TGF-β signaling and EMT were significantly enriched in the high-risk group;in addition,high-risk group is also significantly associated with the infiltration of M2 macrophages,MO macrophages,and neutrophils.Conclusion A risk prediction model based on metabolism-related genes has been developed in the study,which may be used for predict the prognosis of gastric cancer patients.
万方数据
维普
