Prognostic risk model of gastric adenocarcinoma based on exosome-related genes

Gastric cancer is a prevalent and fatal malignancy. Research has indicated a significant association between exosomes and gastric cancer progression; however, there is a paucity of established exosome-related risk models for this disease. Differential expression analysis identified differential gene expression profiles between the normal and tumor groups. Subsequently, The Cancer Genome Atlas dataset was utilized to develop an exosome-related gene risk model for patients with stomach adenocarcinoma (STAD) through the application of least absolute shrinkage and selection operator regression analysis and multivariate Cox regression analysis. We used GEO datasets to verify the prediction accuracy of the model. Utilizing the obtained risk score, additional analyses were conducted, including gene set enrichment analysis, immune-related score assessment, tumor-related score evaluation, mutation analysis, and drug sensitivity analysis. We constructed a prognostic risk model for STAD comprising APOA1, SERPINE1, and APOD. Significant variances in immune correlation and tumor microenvironment correlation were observed between the high- and low-risk groups. The high-risk group exhibited a poorer prognosis, potentially attributable to immunosuppression and decreased tumor purity. Drug sensitivity analysis indicated that bortezomib, docetaxel, and epothilone B were more effective in the high-risk group. The exosome-related risk model constructed in this study can effectively predict the prognosis of patients with STAD.