A Bioinformatics-Based Analysis of an Cuproptosis and Ferroptosis-Related Gene Signature Predicts the Prognosis of Patients with lung adenocarcinoma

Abstract

Abstract Background Cuproptosis and ferroptosis acts important defense for the organism by preventing tumor cells migration and preventing their growth. In this study, cuproptosis and ferroptosis-related genes were used to construct a prognostic model for lung adenocarcinoma (LUAD) patients. Methods TCGA database was used to acquire RNA sequencing data and clinical information for LUAD samples. The Cox and LASSO regression analysis were performed to construct the prognostic genes signature. In addition, GSEA, GO, KEGG were performed to investigate the potential molecular mechanism. Moreover, we analyzed the relationship between our identified signature and immune cell infiltration, tumor microenvironment, immunotherapy response, drug sensitivity analysis. Results Three prognosis related genes were selected (SRXN1, GLS2, SLC2A1). Finally, in vitro experiments we performed qRT-PCR, western blot, scratch test, colony-formation, lipid ROS analysis to validate the expression and function of SRXN1 gene. Conclusion Combined with clinicopathological characteristics, the risk model was validated as a new independent prognostic factor for LUAD.