Identification and validation of a hypoxia-immune signature for overall survival prediction in lung adenocarcinoma

Objective: The interaction between immunity and hypoxia in tumor microenvironment (TME) has clinical significance, and this study aims to explore immune-hypoxia related biomarkers in LUAD to guide accurate prognosis of patients. Methods: The LUAD gene expression dataset was downloaded from GEO and TCGA databases. The immune-related genes and hypoxia-related genes were acquired from ImmPort and MSigDB databases, respectively. Genes related to immune and hypoxia in LUAD were obtained by intersection. The significantly prognostic genes in LUAD were obtained by LASSO and Cox regression analyses and a prognostic model was constructed. Kaplan-Meier and receiver operating characteristic curves were generated to evaluate and validate model reliability. Single-sample gene set enrichment analysis (ssGSEA) and gene set variation analysis (GSVA) were employed to analyze immune cell infiltration and pathway differences between high- and low-risk groups. Nomogram and calibration curves for survival curve and clinical features were drawn to measure prognostic value of the model. Results: The prognosis model of LUAD was constructed based on seven immune-hypoxia related genes: S100P, S100A16, PGK1, TNFSF11, ARRB1, NCR3, and TSLP. Survival analysis revealed a poor prognosis in high-risk group. ssGSEA result suggested that activities of immune cells in high-risk group was remarkably lower than in low-risk group, and GSVA result showed that immune-related pathway was notably activated in low-risk group. Conclusion: Immune-hypoxia related genes were found to be prognostic biomarkers for LUAD patients, based on which a 7-immune-hypoxia related gene-signature was constructed. This model can assess immune status of LUAD patients, and provide clinical reference for individualized prognosis, treatment and follow-up of LUAD patients.