Development of a Prognostic Model for Gastric Cancer Based on Apoptosis- and Hypoxia-Related Genes: Predictive Insights into Survival and Immune Landscape.

Gastric cancer (GC) is the fifth most prevalent malignancy worldwide, characterized by poor prognosis. Apoptosis is interacted with hypoxia in tumorigenesis. This study attempted to delineate potential value of apoptosis and hypoxia-related genes (AHRGs) in prognosis of gastric cancer. Differential expression analysis was performed on GC transcriptomic data from TCGA. Apoptosis-related genes (ARGs) and hypoxia-related genes (HRGs) were obtained from MSigDB, followed by intersecting them with differentially expressed genes (DEGs) in GC. A prognostic model was constructed using univariate, LASSO, and multivariate regression analyses. The model was validated using a Gene Expression Omnibus dataset. DEGs between risk groups were subjected to enrichment analysis. A nomogram was plotted by incorporating clinical information. Non-negative matrix factorization based on core prognostic genes from the multifactorial model was employed to cluster tumor samples. The subsequent analyses involved immunophenoscore, immune landscape, Tumor Immune Dysfunction and Exclusion (TIDE) score, and chemosensitivity for distinct subtypes. A prognostic model based on AHRGs was established, and its predictive capability was verified in external cohorts. Riskscore was determined as an independent prognostic factor, and it was used, combined with other clinical features, to plot a prognostic nomogram. Patients were clustered into cluster1 and cluster2 based on prognostic model genes. Cluster2 showed poorer prognosis and IPS scores, higher immune cell infiltration, immune function and TIDE scores than cluster1. Distinct therapeutic potential for various chemotherapeutic agents was observed between the two clusters. The developed AHRG scoring introduced a novel and effective avenue for predicting GC prognosis and identifying potential targets for further investigation.