Abstract
Background: With the rapid development of immunotherapy for solid tumors, the exploration of immune characteristics becomes more and more important. Due to the high morbidity and mortality of LUAD in Chinese population, it is of great significance to explore its immune characteristics.
Methods: Eight GEO cohorts were used to screen for immune and prognostically relevant genes. An IRGS predictive model was constructed using the ssGSEA algorithm and internally validated. The performance of the model was further verified in five external validation cohorts. To evaluate immune cell infiltration, TIMER, XCELL, and CIBERSORT were applied to quantify the relative proportions of infiltrating immune cells.
Results: Patients with high IRGS exhibited significantly better overall survival (OS) compared to those with low IRGS (HR = 0.56, 95% CI 0.46-0.68, P <0.001) in the training set. The same results were obtained in the validation set (HR = 0.45, 95% CI 0.33-0.6, P <0.001). Further validation in five external cohorts yielded consistent results (GSE31210: P <0.001; GSE68465: P =0.039; Chen_2019: P =0.031; TCGA_LUAD: P =0.002; CPTAC_LUAD: P =0.036). In the tumor microenvironment (TME) analysis, patients with high IRGS had higher levels of T cells, B cells, DC cells, and neutrophils. Immunotherapy cohort analysis in a public cohort showed that patients with high IRGS had better progression-free survival (PFS) after immunotherapy (P=0.013).
Conclusions: Patients with high IRGS demonstrated better prognosis and improved immune efficacy. The IRGS model may possess better predictive performance compared to existing immune and genomic instability markers, indicating its potential value for clinical applications.