Identification of DNA damage response and crotonylation-related biomarkers for lung adenocarcinoma via machine learning and WGCNA.

DNA damage response (DDR) and crotonylation occur frequently in lung adenocarcinoma (LUAD), but their relationship is yet to be elucidated. RNA sequencing data from LUAD patients in GSE27262 and GSE140797 datasets were obtained. DDR-crotonylation-related differentially expressed genes were identified by differential analysis and weighted gene co-expression network analysis. Three machine learning algorithms were used to screen for foremost ones. Various analyses such as immune infiltration, genetic mutation, and drug sensitivity were carried out based on multiple databases and cytotoxicity tests. Three hub genes were extracted with the potential as diagnostic and predictive criteria. They were also related to immune infiltration, immune checkpoint expression and genome heterogeneity of LUAD. Additionally, drug sensitivity analysis pinpointed probable small molecule inhibitors targeting our hub genes. This study confirmed the activation of DDR and crotonylation in LUAD, which is characterized by abnormal expressions of the hub genes, and translated it into clinical applications. We also overviewed the relationships among those specific molecular features, metabolic reprogramming and immune evasion.