Identification and Experimental Verification of a Cuproptosis-Associated Gene Signature for Overall Survival Prediction in Patients with Non-Small Cell Lung Cancer

Abstract

Abstract Non-small cell lung cancer (NSCLC) is a heterogeneous disease, which makes the prognostic prediction challenging. Cuproptosis, a recently discovered mode of regulated cell death (RCD), may be associated with the development of multiple diseases. However, the prognostic value of cuproptosis-related genes in NSCLC remains uncertain. In this study, we obtained the mRNA expression profiles and corresponding clinical data of NSCLC patients online and made some analysis. Our results showed that 16 cuproptosis-related genes were differentially expressed between NSCLC and normal tissues. GO and KEGG enrichment analysis revealed that these genes were mainly enriched in cellular energy metabolism-related pathways. According to the survival analysis of these 16 genes, the up-regulation of 13 genes predicted a poor overall survival (OS) rate in patients with NSCLC. Then, A 13-genes signature model was built to distinguish the patients into two risk groups. Patients in the high-risk group showed significantly a poor OS rate compared with patients in the low-risk group (P < 0.001 in the TCGA cohort). The tumor grade, tumor stage, and tumor vascular invasion also differ in two groups (P < 0.01 in the TCGA cohort). Receiver operating characteristic (ROC) curve analysis proved the model's predictive capacity. The same model was used in the ICGC cohort and similar results were confirmed. Finally, we verified the differential expression of several genes in our model between NSCLC and normal tissues. By detecting intracellular Cu2+ levels before and after gene knockdown, we found that four genes may affect the progression of NSCLC by regulating cuproptosis. In conclusion, a novel cuproptosis-related gene signature can predict the prognostic of NSCLC. Targeting cuproptosis may be a therapeutic approach for NSCLC.