Development and validation of an oxidative phosphorylation based prognostic model revealing tumor progression and immune microenvironment in lung adenocarcinoma

BACKGROUND: Lung adenocarcinoma (LUAD) remains a leading cause of cancer mortality worldwide. Although oxidative phosphorylation (OXPHOS) has been linked to tumor progression, its prognostic significance and underlying mechanisms in LUAD remain unclear. METHODS: RNA-seq data from TCGA were used as the discovery cohort, and multiple GEO datasets were used for independent validation. OXPHOS-related genes were obtained from MitoCarta3.0. Prognostic biomarkers were selected by LASSO-Cox regression. Immune cell infiltration was estimated using CIBERSORT and ssGSEA. Single-cell RNA-seq data were analyzed to examine biomarker expression, pathway enrichment, and cell-cell communication. RESULTS: Thirteen OXPHOS-associated genes were used to construct a prognostic model with robust predictive performance. Model performance was validated across independent cohorts and demonstrated reliable prognostic value. Higher risk scores correlated with poorer overall survival and reduced immune infiltration. UQCC3⁺ and RAB5IF⁺ epithelial cells were enriched in E2F target and G2M checkpoint pathways and showed enhanced interactions via TGF-β and Galectin signaling. CONCLUSIONS: We present an OXPHOS-based prognostic model for LUAD. OXPHOS reprogramming, particularly involving UQCC3 and RAB5IF in epithelial cells, may promote malignant proliferation and immunosuppression. These findings provide novel prognostic biomarkers and potential therapeutic targets, which may support personalized treatment strategies and guide future translational studies.