Comprehensive Analysis of the Cuproptosis-Related Model to Predict Prognosis and Indicate Tumor Immune Infiltration in Lung Adenocarcinoma

BackgroundCuproptosis is a novel form of programmed cell death termed as Cu-dependent cytotoxicity. However, the roles of cuproptosis-associated genes (CAGs) in lung adenocarcinoma (LUAD) have not been explored comprehensively.MethodsWe obtained CAGs and utilized consensus molecular clustering by “non-negative matrix factorization (NMF)” to stratify LUAD patients in TCGA (N = 511), GSE13213 (N = 117), and GSE31210 (N = 226) cohorts. The ssGSEA and CIBERSORT algorithms were used to evaluate the relative infiltration levels of immune cell types in tumor microenvironment (TME). The risk score based on CAGs was calculated to predict patients’ survival outcomes.ResultsWe identified three cuproptosis-associated clusters with different clinicopathological characteristics. We found that the cuproptosis-associated cluster with the worst survival rates exhibited a high enrichment of activated CD4/8+ T cells. In addition, we found that the cuproptosis-associated risk score could be used for patients’ prognosis prediction and provide new insights in immunotherapy of LUAD patients. Eventually, we constructed a nomogram-integrated cuproptosis-associated risk score with clinicopathological factors to predict overall survival in LUAD patients, with 1-, 3-, and 5-year area under curves (AUCs) being 0.771, 0.754, and 0.722, respectively, all of which were higher than those of the TNM stage.ConclusionsIn this study, we uncovered the biological function of CAGs in the TME and its correlations with clinicopathological parameters and patients’ prognosis in LUAD. These findings could provide new angles for immunotherapy of LUAD patients.