Cholesterol metabolism reprogramming serves a pivotal role in tumor onset and progression. The present study investigated lung adenocarcinoma (LUAD), focusing on the regulatory impact of cholesterol metabolism‑related genes (CMRGs). Consensus clustering identified distinct cholesterol metabolism‑related clusters in LUAD, followed by survival analysis and immune infiltration profiling for each cluster. A predictive model, constructed using cluster‑specific differentially expressed genes and the LASSO algorithm, was validated with an independent dataset. Furthermore, the model was utilized to predict potential responses to immunotherapy and chemotherapy for patients with LUAD. The functional role of the key gene GJB3 in LUAD progression was confirmed through in vitro experiments. Two distinct cholesterol metabolism‑related clusters were identified, exhibiting significant differences in prognosis, biological function and immune cell infiltration. A survival model, based on four genes, demonstrated strong predictive performance across multiple datasets. The low‑risk group showed improved responses to immunotherapy, while the high‑risk group exhibited heightened sensitivity to chemotherapy. In vitro assays revealed that GJB3 knockdown suppressed LUAD cell proliferation and invasion, significantly reducing the expression of epithelial‑mesenchymal transition‑related genes. These findings highlight CMRGs as potential prognostic biomarkers and suggest a foundation for personalized treatment strategies in LUAD.
Keywords: GJB3; cholesterol metabolism; immunotherapy; lung adenocarcinoma; prognosis.