Ontology highlight
ABSTRACT: Background
In recent years, significant molecules have been found in gastric cancer research. However, their precise roles in the disease's development and progression remain unclear. Given gastric cancer's heterogeneity, prognosis prediction is challenging. This study aims to assess patient prognosis and immune therapy efficacy using multiple key molecules.Method
The WGCNA algorithm was employed to identify modules of genes closely related to immunity. A prognostic model was established using the Lasso-Cox method to predict patients' prognosis. Single-sample gene set enrichment analysis (ssGSEA) was conducted to quantify the relative abundance of 16 immune cell types and 13 immune functions. The relationship between risk score and TMB, MSI, immune checkpoints, and DNA repa
SUBMITTER: Sun W
PROVIDER: S-EPMC10616298 | biostudies-literature | 2023
REPOSITORIES: biostudies-literature