Correlation study of AADAC with prognosis and immunoinfiltration of gastric cancer based on bioinformatics analysis

Abstract

Abstract Objective Using bioinformatics to screen key prognostic genes for gastric cancer and exploring the immune infiltration relevance of these genes, providing new therapeutic targets for the diagnosis and treatment of gastric cancer. Methods Screening of differentially expressed genes based on TCGA and GEO databases, and performing GO and KEGG pathway enrichment analysis. Further selection of key prognostic genes for gastric cancer through COX regression and Lasso regression algorithms, and construction of a prognostic risk model. Drawing ROC curve and K-M survival curve to evaluate the prognostic value of genes. Analyzing the immune infiltration level of genes using CIBERSORT, ssGSEA algorithm, and TIMER database, and combining with HPA database to analyze the gene expression. Results: A total of 67 differentially expressed genes were screened out,the key prognostic gene AADAC in gastric cancer was identified, and a risk prognostic model was constructed. The ROC curve and AUC value indicate that the risk model has good predictive value. The K-M survival curve indicates that patients with high expression of AADAC have a worse survival outcome. The results of immune infiltration analysis suggest that the infiltration levels of activated B cells, CD56(dim) natural killer cells, central memory CD4 + T cells, central memory CD8 + T cells, eosinophils, immature B cells, macrophages, mast cells, monocytes, and helper T cells are positively correlated with the risk score. The expression of AADAC is weakly positively correlated with B cells, CD4 + T cells, and macrophages. Immunohistochemical results from the HPA database suggest that the staining intensity of AADAC in normal gastric mucosal tissues is weaker than that in gastric cancer tissues. Conclusion AADAC can effectively predict the prognosis of gastric cancer patients and is moderately correlated with the level of immune infiltration, providing a new direction for the diagnosis and immunotherapy of gastric cancer.