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ABSTRACT: Background
Lung adenocarcinoma (LUAD) is the major non-small-cell lung cancer pathological subtype with poor prognosis worldwide. Herein, we aimed to build an energy metabolism-associated prognostic gene signature to predict patient survival.Methods
The gene expression profiles of patients with LUAD were downloaded from the TCGA and GEO databases, and energy metabolism (EM)-related genes were downloaded from the GeneCards database. Univariate Cox and LASSO analyses were performed to identify the prognostic EM-associated gene signatures. Kaplan-Meier and receiver operating characteristic (ROC) curves were plotted to validate the predictive effect of the prognostic signatures. A CIBERSORT analysis was used to evaluate the correlation between the risk model and immune cells. A
SUBMITTER: Mu T
PROVIDER: S-EPMC9047773 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature