Identification of lung adenocarcinoma subtypes based on mitochondrial energy metabolism-related genes

Abstract

Background Identifying subtypes of lung adenocarcinoma (LUAD) patients based on mitochondrial energy metabolism and immunotherapy sensitivity is essential for precision cancer treatment. Methods LUAD subtypes were identified using unsupervised consensus clustering, and results were subjected to immune and tumor mutation analyses. DEGs between subtypes were identified by differential analysis. Functional enrichment and PPI network analyses were conducted. Patients were classified into high and low expression groups based on the expression of the top 10 hub genes, and survival analysis was performed. Drugs sensitive to feature genes were screened based on the correlation between hub gene expression and drug IC50 value. qRT-PCR and western blot were used for gene expression detection, and CCK-8 and flow cytometry were for cell viability and apoptosis analysis. Results Cluster-1 had significantly higher overall survival and a higher degree of immunoinfiltration and immunophenotypic score, but a lower TIDE score, DEPTH score, and TMB. Enrichment analysis showed that pathways and functions of DEGs between two clusters were mainly related to the interaction of receptor ligands with intracellular proteases. High expression of hub genes corresponded to lower patient survival rates. The predicted drugs with high sensitivity to feature genes were CDK1: Ribavirin (0.476), CCNB2: Hydroxyurea (0.474), Chelerythrine (0.470), and KIF11: Ribavirin (0.471). KIF11 and CCNB2 were highly expressed in LUAD cells and promoted cell viability and inhibited cell apoptosis. Conclusion This study identified two subtypes of LUAD, with cluster-1 being more suitable for immunotherapy. These results provided a reference for the development of precision immunotherapy for LUAD patients.