Exosome-Related Gene Signature Predicts Prognosis and Immunotherapy in Gastric Cancer

Exosomes play a crucial role in tumor progression. However, reliable exosome-related biomarkers for predicting prognosis in gastric cancer (GC) remain scarce. This study is aimed at developing an exosome-related gene risk signature (ERGRS) to predict the survival outcomes and immunotherapy sensitivity in GC patients. RNA sequencing data from exoRbase and TCGA datasets were analyzed to identify differentially expressed exosome-related genes associated with survival in GC. A multivariate Cox regression model was used to construct the ERGRS and a prognostic nomogram. The ERGRS's predictive performance was assessed using the Kaplan-Meier and receiver operating characteristic (ROC) curve analyses in both training and validation datasets. Furthermore, the relationship between the ERGRS risk score and clinical features, copy number variation, and immunotherapy sensitivity was explored through data mining. Western blotting was performed to validate protein expression levels of key exosome-related genes in GC tissues. Four exosome-related genes-TRAF2, ASCL2, NOX4, and MMRN1-were identified as independent prognostic factors. GC Patients with low-risk scores showed significantly better survival outcomes. Univariate and multivariate Cox regression analyses confirmed the ERGRS as an independent predictor of survival in GC. A prognostic nomogram incorporating risk score, age, and tumor stage was developed to effectively predict patient survival. Immune checkpoint analysis suggested that patients with low-risk scores may respond better to immunotherapy. The ERGRS represents a promising tool for prognostic prediction and guides the clinical care of GC patients.