Abstract
This study aimed to identify prognostic genes related to palmitoylation and explore their value in predicting outcomes and treatment response in lung adenocarcinoma (LUAD). We employed the single-sample Gene Set Enrichment Analysis (ssGSEA) algorithm to compute the palmitoylation pathway score(PPS) and utilized lasso regression for feature selection to identify hub palmitoylation pathway score-related genes(PPSGs). A palmitoylation-related prognostic risk score model(PM model) was developed and validated across cohorts. Functional enrichment analysis, immune profiling, and drug sensitivity analyses were performed. Additionally, the expression levels of hub PPSGs were evaluated using qPCR in lung adenocarcinoma cell lines and patient tissue samples. Fifteen hub PPSGs were used to construct the PM model, which demonstrated moderate but consistent predictive accuracy (AUCs: 0.737, 0.693, 0.676 for 1-, 2-, 5-year survival). The risk score derived from the PM model (PM score) correlated with immune suppression and cytoskeleton-related pathways. Clinically, high PM score was associated with advanced stage, male patients, reduced immunotherapy response, and enhanced sensitivity to select chemotherapies. Five key genes (TPPP, FAAH, CACNB1, GLOD5, CCNA2) were validated in local LUAD samples. The PM model serves as a clinically relevant tool for prognosis and treatment prediction in LUAD, highlighting the potential role of palmitoylation in tumor progression and therapy stratification.