Dataset Information

[Bioinformatics analysis of expression and function of EXD3 gene in gastric cancer].

ABSTRACT: OBJECTIVE:To investigate the differentially expressed genes between gastric cancer and normal gastric mucosa by bioinformatics analysis, identify the important gene participating in the occurrence and progression of gastric cancer, and predict the functions of these genes. METHODS:The gene expression microarray data GSE100935 (including 18 gastric cancer samples and normal gastric mucosal tissues) downloaded from the GEO expression profile database were analyzed using Morpheus to obtain the differentially expressed genes in gastric cancer, and a cluster analysis heat map was constructed. The online database UALCAN was used to obtain the expression levels of these differentially expressed genes in gastric cancer and normal gastric mucosa. The prognostic value of the differentially expressed genes in gastric cancer was evaluated with Kaplan-Meier survival analysis. GO functional enrichment analysis was performed using Fun-Rich software, and the STRING database was exploited to establish a PPI network for the differentially expressed genes. RESULTS:A total of 45119 differentially expressed genes were identified from GSE100935 microarray data. Analysis with UALCAN showed an obvious high expression of EXD3 gene in gastric cancer, and survival analysis suggested that a high expression level of EXD3 was associated with a poorer prognosis of the patients with gastric cancer. GO functional enrichment analysis found that the differentially expressed genes in gastric cancer were involved mainly in the regulation of nucleotide metabolism and the activity of transcription factors in the cancer cells. CONCLUSIONS:EXD3 may be a potential oncogene in gastric cancer possibly in relation to DNA damage repair. The up-regulation of EXD3 plays an important role in the development and prognosis of gastric cancer, and may serve as an important indicator for prognostic evaluation of the patients.

SUBMITTER: Sun D

PROVIDER: S-EPMC6765637 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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[Bioinformatics analysis of expression and function of EXD3 gene in gastric cancer].

Sun Dengzhong D Liu Mulin M Huang Fuxin F Huang Fuxin F

Nan fang yi ke da xue xue bao = Journal of Southern Medical University 20190201 2

<h4>Objective</h4>To investigate the differentially expressed genes between gastric cancer and normal gastric mucosa by bioinformatics analysis, identify the important gene participating in the occurrence and progression of gastric cancer, and predict the functions of these genes.<h4>Methods</h4>The gene expression microarray data GSE100935 (including 18 gastric cancer samples and normal gastric mucosal tissues) downloaded from the GEO expression profile database were analyzed using Morpheus to ...[more]

PMID: 30890511

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Project description:BackgroundGastric cancer (GC) is one of the common gastrointestinal malignancy worldwide and exhibits a poor prognosis. Increasing studies have indicated that microRNAs play critical roles in the cancer progression and have shown great potential as useful biomarkers. The search for potential diagnostic and prognostic biomarkers of gastric cancer (GC) with integrated bioinformatics analyses has been undertaken in previous studies.MethodsIn this study, the robust rank aggregation (RRA) method was used to perform an integrated analysis of differentially expressed miRNAs (DEMs) from five microarray datasets in the Gene Expression Omnibus (GEO) database to find robust biomarkers for GC. Ultimately, seven miRNAs were filtered from fourteen primary miRNAs using the validation set of The Cancer Genome Atlas (TCGA) database. Based on these results, diagnostic and survival analyses were performed, and logistic regression and Cox regression were used to determine the clinicopathological characteristics of the DEM expression and overall survival.ResultsNine eligible miRNA datasets related to GC were selected from the GEO database for integrated analysis in this study. Diagnostic analysis implied that these miRNAs could be regarded as promising candidate diagnostic biomarkers in GC tissues, but whether the results of the tissue analysis are consistent with those of peripheral blood analysis requires further validation. The logistic regression indicated that the ectopic expression of these DEMs was relevant to the histological type, anatomical region, and pathological grade of GC. However, the survival and Cox regression analyses suggested that the poor prognosis of GC patients was not strongly dependent on the ectopic expression of the seven miRNAs, but rather, a poor prognosis was associated with age, metastasis, and histological grade.ConclusionsBased on the results presented in this study it can be concluded that these miRNAs (miR-455-3p, miR-135b-5p, let-7a-3p, miR-195-5p, miR-204-5p, miR-149-5p, and miR-143-3p) might be potential biomarkers for the early diagnosis of GC patients, but this finding should be regarded with caution. A large-scale, prospective, and multicenter cohort study should be performed.

Project description:PurposeGastric 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.MethodsWe 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 'ggplot2' and "circlize" packages.ResultsIn 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.ConclusionThis 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.

Project description:ObjectiveTo investigate the expression of BUB1 gene in gastric cancer.MethodsOncomine, GEPIA, BioGPS and Kaplan-Meier Plotter databases were used to analyze the difference of BUB1 gene expression between gastric cancer tissue and normal gastric tissue. The association of BUB1 expression level with the prognosis of gastric cancer patients was also analyzed. The Cancer Cell Line Encyclopedia (CCLE) was explored to analyze the expression of BUB1 in T cells and B cells in gastric cancer patients, and the String database was used to generate the network map of BUB1-related proteins and functional annotation of gene ontology (GO). The related pathways of KEGG were analyzed. Tumor immune assessment resource (TIMER) database was used to analyze the expression of BUB1 in immune infiltration and its effect on prognosis of gastric cancer patients. To further verify the results of gene chip analysis in Oncomine database, we collected 30 pairs of surgical specimens of gastric adenocarcinoma and adjacent tissues from patients admitted to the First Affiliated Hospital of Chengdu Medical College from March, 2018 to July, 2019. The results of BUB1 gene expression in Oncomine database were verified by PCR and immunohistochemistry.ResultsOncomine, GEPIA and BioGPS analyses showed that BUB1 was highly expressed in gastric cancer compared with normal gastric tissue. Kaplan-Meier survival analysis showed that the progression-free survival time (HR=0.52, 95% CI:0.41-0.67, P < 0.05) and the overall survival time (HR=0.67, 95% CI:0.55-0.82, P < 0.05) were prolonged in gastric cancer patients with a high expression of BUB1. Through String data collection, BUB1-related proteins were mainly enriched in 13 cellular components, 4 molecular functions and 12 biological processes, involving 4 signal pathways. TIMER database analysis showed that CD4+ T cells and macrophages with high expressions of BUB1 mRNA in the immune microenvironment were associated with a favorable 5-year survival outcome of patients with gastric cancer. In the surgical specimens, real-time quantitative PCR showed that the expression level of BUB1 mRNA was significantly higher in gastric cancer tissues than in the adjacent gastric mucosa tissues, and immunohistochemical results demonstrated positive BUB1 staining in the gastric cancer tissues.ConclusionsBUB1 gene is highly expressed in gastric cancer. BUB1 may reduce tumor immunosuppression and helps to evaluate the prognosis of patients with gastric cancer.

Dataset Information

[Bioinformatics analysis of expression and function of EXD3 gene in gastric cancer].

Publications

[Bioinformatics analysis of expression and function of EXD3 gene in gastric cancer].

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