Metabolic and aging related gene risk score for therapeutic stratification and precision oncology in gastric cancer.

Gastric cancer (GC) exhibits marked heterogeneity, patients with identical stage receive divergent outcomes. Metabolic reprogramming and aging are pivotal in reshaping the tumor microenvironment. However, their interplay in GC prognosis remains unexplored. We analyzed RNA-seq and clinical data from The Cancer Genome Atlas Program and Gene Expression Omnibus databases. Using univariate Cox, LASSO, and multivariate Cox regression, we identified candidate genes and constructed a prognostic signature. Immune contexture, genomic alterations and drug sensitivity were compared between high- and low-risk group. The metabolic and aging related risk score, comprising 4 genes (GNAI1, GSTA1, APOC3, and LOX), was developed. Validation across multiple cohorts confirmed its robust prognostic performance. The model also effectively stratified patients into distinct risk subgroups with differential immune profiles and responses to immunotherapy. Notably, high-risk patients showed reduced sensitivity to common chemotherapeutic agents but may benefit from targeting the PI3K/mTOR pathway. Metabolic and aging related risk score serves as a promising tool for individualized risk assessment and therapeutic guidance in GC, warranting further clinical validation.