Guidelines on lung adenocarcinoma prognosis based on immuno-glycolysis-related genes.

ABSTRACT:

Objectives

This study developed a new model for risk assessment of immuno-glycolysis-related genes for lung adenocarcinoma (LUAD) patients to predict prognosis and immunotherapy efficacy.

Methods

LUAD samples and data obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases are used as training and test columns, respectively. Twenty-two (22) immuno-glycolysis-related genes were screened, the patients diagnosed with LUAD were divided into two molecular subtypes by consensus clustering of these genes. The initial prognosis model was developed using the multiple regression analysis method and Receiver Operating characteristic (ROC) analysis was used to verify its predictive potential. Gene set enrichment analysis (GSEA) showed the immune activiti

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC10025218 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature