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 and 101 combinations of 10 machine-learning algorithms based on module genes. The predictive value of PRS was thoroughly assessed in relation to p

SUBMITTER: Fu Z 

PROVIDER: S-EPMC12375524 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature