Development of a risk model for outcome prediction and treatment guidance in lung adenocarcinoma based on hypoxia, glycolysis, and lymph node metastasis-related genes

Hypoxia and glycolysis are closely linked to tumor progression. This study aims to explore the prognostic value of hypoxia-, glycolysis-, and lymph node metastasis (LNM)-related genes in lung adenocarcinoma (LUAD) patients. The data of LUAD patients were collected from TCGA and GEO databases. ssGSEA analysis was conducted to evaluate the hypoxia and glycolysis status. The signature genes were identified using differential expression analysis, univariate COX regression analysis, and least absolute shrinkage and selector operator (LASSO) regression analysis, followed by the construction of a risk score model. The prognosis value of the risk score model was evaluated. Finally, the correlations between the risk score model and clinical characteristics, immune infiltration status, tumor stemness, and sensitivity of immunotherapy and chemotherapy were investigated. The hypoxia- and glycolysis-related gene sets were significantly up-regulated in LUAD patients with LNM. Four signature genes were identified, and a risk score model was constructed, exhibiting good prognostic value. LUAD patients in the high-risk group had a poorer prognosis than those in the low-risk group. The clinical correlation analysis showed that age, N stage, T stage, stage, and primary therapy outcome success were related to risk score. Immune infiltration analysis found that macrophages M0 and mast cells resting were significantly correlated with risk score. LUAD patients in the high-risk group exhibited higher tumor stemness and IC50 value. The hypoxia-, glycolysis-, and LNM-related signature genes were identified and a risk score model was constructed, providing potential prognostic targets for LUAD patients.