Prediction of the Survival Status, Immunotherapy Response, and Medication of Lung Adenocarcinoma Patients Based on Hypoxia- and Apoptosis-Related Genes.

Abstract

To predict patient survival prognosis, we aimed to establish a novel set of gene features associated with hypoxia and apoptosis. RNA-seq and clinical data of LUAD were sourced from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, while hypoxia and apoptosis-related genes were obtained from the Molecular Signatures Database (MsigDB). A 13-gene-prognostic model incorporating hypoxia and apoptosis genes was developed using univariate/multivariate Cox regression, Nonnegative Matrix Factorization (NMF) clustering, and LASSO regression. Patients were divided into high-risk (HR) and low-risk (LR) groups according to the median risk score. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed distinct biological processes between HR and LR groups, including hormone regulation and lipid metabolism pathways. Single sample gene set enrichment analysis (ssGSEA) indicated elevated cell infiltration levels of Neutrophils and T_helper_cells in the LR group, while NK cells and Th1cells were higher in the HR group. Immunophenoscore (IPS) and tumor immune dysfunction and exclusion (TIDE) analyses suggested potential benefits of immunotherapy for LR group patients. In conclusion, this prognostic feature integrating hypoxia- and apoptosis-related genes offers insights into predicting survival, immune status, and treatment response in LUAD patients, paving the way for personalized treatment strategies.