Amino acid metabolism related gene signatures for predicting prognosis and immune infiltration in gastric cancer

This study constructed a prognostic and immunotherapy predictive model for gastric cancer based on amino acid metabolism-related genes. Using data from TCGA and GEO databases, the model was built via Cox and Lasso regression and validated in independent cohorts. It effectively predicts patient survival and shows significant correlations with the tumor immune microenvironment, immune cell infiltration, and immune checkpoint expression. Drug sensitivity analysis suggests potential therapeutic options. This model may serve as a potential biomarker for predicting prognosis and immunotherapy efficacy in gastric cancer patients.