Identification of three metabolic subtypes in gastric cancer and the construction of a metabolic pathway-based risk model that predicts the overall survival of GC patients

Front Genet. 2023 Feb 10:14:1094838. doi: 10.3389/fgene.2023.1094838. eCollection 2023.

Abstract

Gastric cancer (GC) is highly heterogeneous and GC patients have low overall survival rates. It is also challenging to predict the prognosis of GC patients. This is partly because little is known about the prognosis-related metabolic pathways in this disease. Hence, our objective was to identify GC subtypes and genes related to prognosis, based on changes in the activity of core metabolic pathways in GC tumor samples. Differences in the activity of metabolic pathways in GC patients were analyzed using Gene Set Variation Analysis (GSVA), leading to the identification of three clinical subtypes by non-negative matrix factorization (NMF). Based on our analysis, subtype 1 showed the best prognosis while subtype 3 exhibited the worst prognosis. Interestingly, we observed marked differences in gene expression between the three subtypes, through which we identified a new evolutionary driver gene, CNBD1. Furthermore, we used 11 metabolism-associated genes identified by LASSO and random forest algorithms to construct a prognostic model and verified our results using qRT-PCR (five matched clinical tissues of GC patients). This model was found to be both effective and robust in the GSE84437 and GSE26253 cohorts, and the results from multivariate Cox regression analyses confirmed that the 11-gene signature was an independent prognostic predictor (p < 0.0001, HR = 2.8, 95% CI 2.1-3.7). The signature was found to be relevant to the infiltration of tumor-associated immune cells. In conclusion, our work identified significant GC prognosis-related metabolic pathways in different GC subtypes and provided new insights into GC-subtype prognostic assessment.

Keywords: gastric cancer; metabolism; molecular subtypes; multi-omics; prognosis.

Grants and funding

This work was supported by the Basic Scientific Research Project of Wenzhou (Y20190055 and Y20190085); Basic Public Welfare Research Project of Zhejiang Province (grant number LGD20C060001 to LQ); Doctoral Fund of The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University to LQ and Academician He Lin New Medical Cooperation Demonstration Base Research Fund Project (grant number 19331205 to LQ).