Identification of Immunogenic cell death-Related Subgroups and Prognosis Model in lung adenocarcinoma

Abstract

Purpose: Immunogenic cell death (ICD), as a form of regulatory cell death (RCD), influences the occurrence and development of tumors by activating adaptive immune response and altering tumor microenvironment. This research aimed to determine the function of ICD in lung adenocarcinoma and constructed an ICD-related prognostic model. Methods: Download gene expression and clinical data from the TCGA Cancer Genome Atlas. Two ICD-related subtypes were identified by consensus clustering. Patients with lung adenocarcinoma (LUAD) in the TCGA database were then randomly divided into a training set and a test set in a 1:1 ratio. In the training set, Lasso Cox regression and multivariate Cox regression were used to construct a prognostic risk model, and patients were divided into high-risk and low-risk groups, which were validated in the test set. In addition, we established a prognostic Nomogram based on the TCGA-LUAD dataset. Results: Based on univariate Cox analysis, 28 ICD related genes were screened for consensus clustering analysis, and two ICD subgroups were established. The high expression subgroup of ICD was associated with poor prognosis and abundant immune cell infiltration. In addition, seven prognostic gene features were constructed to predict the OS of LUAD patients, and there was a certain correlation between immune cells and risk scores. Conclusion: In conclusion, we found ICD-related subtypes and prognostic genes in LUAD, which may have some guiding significance for the survival and treatment of lung adenocarcinoma patients.