Molecular Typing Based on Oxidative Stress Genes and Establishment of Prognostic Characteristics of 7 Genes in Lung Adenocarcinoma

Abstract

Oxidative stress could maintain different biological processes in human cancer. However, the effect of oxidative stress on lung adenocarcinoma (LUAD) should be studied. This study analyzed the expression and clinical importance of oxidative stress in LUAD in detail. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were employed for obtaining LUAD expression profiles. Based on oxidative stress-related genes, molecular subtypes substantially correlated with the LUAD prognosis were discovered with ConsensusClusterPlus. Differentially expressed genes (DEGs) among subtypes were found using the Limma software package. Least absolute shrinkage and selection operator- (Lasso-) Cox analysis was employed to create the polygenic risk model. RiskScore and clinically relevant features were used to create nomograms. By utilizing oxidative stress-related genes and reliable clustering, stable molecular subtypes were first discovered. The prognosis, clinical characteristics, route characteristics, and immunological characteristics of these three molecular subtypes were all different. Subsequently, by using differential expression genes among molecular subtypes and Lasso, 7 main genes linked with the oxidative stress phenotype were discovered. A prognostic risk model was also built on the basis of major genes associated with the oxidative stress phenotype. The model demonstrated a high level of resilience and was unaffected by clinical-pathological features. It played a stable predictive role in independent datasets. Ultimately, to improve the prognosis model and survival prediction, RiskScore (RS) was combined with clinicopathological variables, and a decision tree model was used. The model exhibited a high prediction accuracy as well as the ability to predict survival. This research found that oxidative stress-related genes have a major involvement in the onset and progression of LUAD and that they may influence LUAD susceptibility to immunotherapy and standard chemotherapy. Furthermore, the identified risk models for 7 genes linked with oxidative stress exhibited could assist clinical treatment decisions and prognosis prediction. The classifier could be used as a molecular diagnostic tool for assessing LUAD patients’ prognosis risk.