DZIP1 Expression as a Prognostic Marker in Gastric Cancer: A Bioinformatics-Based Analysis

PURPOSE: Gastric cancer (GC) is a common type of cancer worldwide. It can relapse and metastasize even after standard treatment; therefore, it has a poor prognosis. Moreover, sensitive biomarkers for prognosis prediction in GC are lacking. In this study, using a bioinformatics approach, we aimed to examine the value of DAZ Interacting Protein 1 (DZIP1) as a prognostic predictor and therapeutic target in GC. METHODS: We explored the clinical relevance, function, and molecular role of DZIP1 in GC using MethSurv, cBioPortal, TIMER, Gene Expression Profiling Interactive Analysis, IMEx, ONCOMINE, MEXPRESS, and EWAS Atlas databases. The GSE118919 dataset was used to plot receiver operating characteristic curves. Using The Cancer Genome Atlas, we developed a Cox regression model and assessed the clinical significance of DZIPs. In addition, we used the “xCELL” algorithm to make reliable immune infiltration estimations. Western blot and immunohistochemistry were used to examine protein expression. The results were visualized with the ‘ggplot2ʹ and “circlize” packages. RESULTS: In GC patients, DZIP1 was over-expressed at both the mRNA and protein levels. High levels of DZIP1 were found to be associated with poor survival in patients with GC. Our results indicated that DZIP1 could be involved in multiple cancer-related pathways such as the PI3K-Akt signaling pathway, WNT signaling pathway, and RAS signaling pathway, and its expression was correlated with the infiltration of activated myeloid dendritic cells, naive CD4+ T cells, and naive CD8+ T cells. Furthermore, we found that mutations in DZIP1 were correlated with a good prognosis in GC patients. Finally, we demonstrated a correlation between hypomethylation of the DZIP1 gene promoter and a poor prognosis in GC. CONCLUSION: This study is the first to demonstrate a significant correlation between high levels of DZIP1 and a poor prognosis in GC patients. Our results clarify multiple potential mechanisms that could contribute to this correlation and may thus provide novel insights into the clinical diagnosis and treatment of GC.