Machine learning-based characterization of a PANoptosis-associated model for enhancing prognosis and immunotherapy response in lung adenocarcinoma patients

Abstract Backgrounds: PANoptosis is a new form of inflammatory programmed cell death, that emphasizes the interaction between pyroptosis, apoptosis and necroptosis. This study aimed to investigate clinical implications of PANoptosis in lung adenocarcinoma. Methods: The ConsensusClusterPlus software was firstly utilized to identify molecular subtypes in lung adenocarcinoma (LUAD) based upon expression of PANoptosis-related regulators. Then, subtype-associated modules were further screened by using the weight gene correlation network analysis (WGCNA). A PANoptosis-related signature (PRS) was developed using a 10-fold cross-validation framework