Identification and validation of a prognostic risk score model for lung adenocarcinoma constructed based on immunogenic cell death

Abstract

Abstract Background Immunogenic cell death (ICD) has been classified as a form of regulated cell death (RCD) sufficient to activate adaptive immune responses, which may contribute to the immunotherapy. The identification of ICD-related biomarkers stratifying lung adenocarcinoma patients according to their benefit from ICD immunotherapy would be of great advantage.Methods We identified two ICD-related subtypes by consensus clustering. Univariate and multivariate Cox proportional risk analyses were used to identify prognostic risk models with prognostic value. Kaplan-Meier analysis, univariate and multivariate Cox regression analysis, and subject work characteristic (ROC) curve analysis were used to validate the risk models.Results High ICD subtypes are associated with favorable clinical outcomes, abundant immune cell infiltration, and highly active immune response signaling. We developed and validated an ICD-related prognostic model that predicts survival of lung adenocarcinoma patients and correlates with the tumor immune microenvironment. In addition, predictive line graphs were created to further validate the risk model as a new independent prognostic factor for patients with lung adenocarcinoma.Conclusions we established a new classification system of LUAD based on ICD signatures. This stratification had significant clinical outcomes for estimating prognosis, as well as the immunotherapy of LUAD patients.