Identification of a Prognostic Gene Signature for Chemoresistance Prediction in Lung Adenocarcinoma by Screening Mitochondrial Metabolism Gene Sets.

Chemoresistance is a major challenge in lung adenocarcinoma (LUAD) treatment and is associated with mitochondrial metabolism. Using publicly available LUAD transcriptome data, we established a five-gene prognostic signature (YWHAZ, HSPD1, NOTCH3, PGK1, and PPARG) for LUAD through differential gene expression profiling, univariate Cox analysis, and machine learning-based feature selection. Patients with LUAD were classified into a high-risk group (HRG) and a low-risk group (LRG) based on their risk scores. Enrichment analysis revealed significant differences between the HRG and LRG in multiple pathways related to metabolism and immunity. The immune microenvironment also differed significantly between the two groups, and the prognostic genes were correlated with infiltrating immune cells. A total of 110 compounds exhibited differential sensitivity across the groups. Molecular docking demonstrated a favorable binding affinity between the prognostic genes and the predicted drugs. Furthermore, YWHAZ knockdown significantly suppressed cancer cell proliferation in cell and animal models. In addition, YWHAZ knockdown markedly reduced cisplatin resistance by downregulating key regulators of the DNA replication and repair pathway, including POLA1 and MCM4. These results provide insight into the molecular mechanisms underlying chemoresistance and identify putative therapeutic targets for LUAD treatment.