Immune-related genes and their determined immune cell microenvironment to predict the prognosis of gastric adenocarcinoma

Abstract

Objective: Through bioinformatics analysis to screen key immune-related genes (IRGs) and cancer-related pathways in gastric adenocarcinoma (GAC) therapy, combining immune cell microenvironment to predict the prognosis of GAC. Methods: RNA sequencing and clinical data were obtained from public databases. Differentially expressed IRGs between GAC and normal tissues were identified by integrated bioinformatics analysis. Univariate and multivariate Cox regression analyses were applied to screen survival-associated IRGs. Then, we established the risk signature model and found another database for external validation. In addition, we explored the relationship with the immune cell microenvironment in each GAC sample using CIBERSORT algorithms. Results: A total of 78 differentially expressed IRGs were screened, including 47 up-regulated and 31 down-regulated genes. Subsequently, a five-IRGs signature (BMP8A、MMP12、NRG4、S100A9 and TUBB3) was significantly associated with the overall survival of GAC patients. Survival analysis indicated that patients in the high-risk group have a poor prognosis. The results of the multivariate analysis revealed that the risk score was an independent prognostic factor. Further analysis showed that the prognostic model had excellent predictive performance in both TCGA and GEO validated cohorts. Besides, the results of tumor-infiltrating immune cell analysis indicated that the risk score could reflect the status of the tumor immune microenvironment. Conclusion: BMP8A, MMP12, NRG4, S100A9 and TUBB3 with the risk signature model are associated with prognosis in patients with GAC, combined with tumor-infiltrating immune cells to provide new markers for immunotherapy in GAC.