Harnessing glycolysis- and cholesterol synthesis-related genes for prognostic modeling in lung adenocarcinoma

This study aimed to construct a prognostic model for LUAD based on glycolysis- and Cholesterol synthesis-related genes (GCSRGs). By performing regression analyses on expression profiles and clinical data from public databases, we established a robust risk stratification system. The results revealed significant survival differences between high- and low-risk groups, with the low-risk group exhibiting stronger immune cell infiltration and higher immune scores. Drug sensitivity analysis suggested that amonafide, AM-5992, and AZD-3147 may serve as potential therapeutic candidates. In conclusion, this model enables precise survival prediction and provides valuable insights for personalized immunotherapy and targeted treatment.