Abstract
BACKGROUND: Lung adenocarcinoma (LUAD) is one of the most common malignant tumors. Although several treatments have been proposed, the long-term prognosis of this cancer is poor. Lipid droplets and mitochondria are important organelles that regulate energy metabolism in cells and are postulated to promote the occurrence and progression of tumors. However, few risk prediction models have been constructed based on lipid drop-mitochondria-related genes (LMRGs). METHODS: In this study, we constructed a lipid drop-mitochondrial (LD-M) risk score model based on data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Biological functions and clinical benefits associated with the various risk scores were analyzed using R software, GraphPad Prism 9, and the online database system. RESULTS: An LD-M risk score model comprising ABLIM3, AK4, CAV2, CPS1, CYP24A1, DLGAP5, FGR, and SH3BP5, was developed and its predictive power was validated. The risk score was closely associated with the cell cycle. Immunophenoscore (IPS) and Tumor immune dysfunction and exclusion (TIDE) results demonstrated that the low-risk group was more sensitive to immunotherapy. Drug sensitivity analysis indicated that BMS-754807, ZM447439, SB216763, and other drugs had lower IC50 values in the low-risk group. CONCLUSION: Our results suggest that the LD-M risk score is an effective prognostic indicator for individualized treatment of LUAD.