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Analysis of the expression, function, prognosis and co-expression genes of DDX20 in gastric cancer.

ABSTRACT: DDX20 (DEAD-box polypeptide 20) is implicated in many cellular processes involving alteration of RNA secondary structure. The role of DDX20 in gastric cancer is still unknown. In the research, the expression of DDX20 and the functional roles of DDX20 in gastric cancer were detected. The increased DDX20 expression in gastric cancer tissue compared with normal gastric tissue was observed. Functional experiments indicated that DDX20 promoted gastric cancer MGC-803 and AGS cells growth, migration, and invasion in vitro. Surprisingly, survival analysis showed that high expression of DDX20 is a favorable prognostic factor for patients with gastric cancer. In addition, enrichment analysis revealed that there is a positive correlation between DDX20 expression and T cell activation in gastric cancer. but not in normal gastric tissues. Furthermore, we found that DDX20 expression level has significant positive correlations with activated CD8 + T cells and activated CD4 + T cells in gastric cancer. Therefore, we hypothesize that the prognostic role of DDX20 in gastric cancer patients may be due to patients with high DDX20 expression contained better immune activation. Taken together, these findings suggest that DDX20 can promote the progression of gastric cancer in vitro and its prognostic value in gastric cancer may be related to many factors, including immune activation.

SUBMITTER: Wang Q

PROVIDER: S-EPMC7509587 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Analysis of the expression, function, prognosis and co-expression genes of DDX20 in gastric cancer.

Wang Qingshui Q Ye Yan Y Lin Rongbo R Weng Shuyun S Cai Fan F Zou Mei M Niu Haitao H Ge Lilin L Lin Yao Y

Computational and structural biotechnology journal 20200914

DDX20 (DEAD-box polypeptide 20) is implicated in many cellular processes involving alteration of RNA secondary structure. The role of DDX20 in gastric cancer is still unknown. In the research, the expression of DDX20 and the functional roles of DDX20 in gastric cancer were detected. The increased DDX20 expression in gastric cancer tissue compared with normal gastric tissue was observed. Functional experiments indicated that DDX20 promoted gastric cancer MGC-803 and AGS cells growth, migration, a ...[more]

PMID: 33005307

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Project description:Background and aimsGastric cancer (GC) is one of the most common cancers worldwide, and its pathogenesis is related to a complex network of gene interactions. The aims of our study were to find hub genes associated with the progression and prognosis of GC and illustrate the underlying mechanisms.MethodsWeighted gene co-expression network analysis (WGCNA) was conducted using the microarray dataset and clinical data of GC patients from Gene Expression Omnibus (GEO) database to identify significant gene modules and hub genes associated with TNM stage in GC. Functional enrichment analysis and protein-protein interaction network analysis were performed using the significant module genes. We regarded the common hub genes in the co-expression network and protein-protein interaction (PPI) network as "real" hub genes for further analysis. Hub gene was validated in another independent dataset and The Cancer Genome Atlas (TCGA) dataset.ResultsIn the significant purple module (R 2=0.35), a total of 12 network hub genes were identified, among which six were also hub nodes in the PPI network of the module genes. Functional annotation revealed that the genes in the purple module focused on the biological processes of system development, biological adhesion, extracellular structure organization and metabolic process. In terms of validation, CDH11 had a higher correlation with the TNM stage than other hub genes and was strongly correlated with biological adhesion based on GO functional enrichment analysis. Data obtained from the Gene Expression Profiling Interactive Analysis (GEPIA) showed that CDH11 expression had a strong positive correlation with GC stages (P<0.0001). In the testing set and Oncomine dataset, CDH11 was highly expressed in GC tissues (P<0.0001). Survival analysis indicated that samples with a high CDH11 expression showed a poor prognosis. Cox regression analysis demonstrated an independent predictor of CDH11 expression in GC prognosis (HR=1.482, 95% CI: 1.015-2.164). Furthermore, gene set enrichment analysis (GSEA) demonstrated that multiple tumor-related pathways, especially focal adhesion, were enriched in CDH11 highly expressed samples.ConclusionCDH11 was identified and validated in association with progression and prognosis in GC, probably by regulating biological adhesion and focal adhesion-related pathways.

Project description:The solute carrier 30 (SLC30) family genes play a fundamental role in various cancers. However, the diverse expression patterns, prognostic value, and potential mechanism of SLC30A family genes in gastric cancer (GC) remain unknown. Herein, we analyzed the expression and survival data of SLC30A family genes in GC patients using multiple bioinformatic approaches. Expression data of SLC30A family genes for GC patients were extracted from the Cancer Genome Atlas (TCGA) and genetic alteration frequency assessed by using cBioportal database. And validated the expression of SLC30A family genes in GC tissues and corresponding normal tissues. The prognostic value of SLC30A family genes in gastric cancer patients were explored using Kaplan-Meier plotter database. Functional enrichment analysis performed using DAVID database and clusterProfiler package. And ssGSEA algorithm was performed to explore the relationship between the SLC30A family genes and the infiltration of immune cells. We found that the median expression levels of SLC30A1-3, 5-7, and 9 were significantly upregulated in gastric cancer tissues compared to non-cancerous tissues, while SLC30A4 was downregulated. Meanwhile, SLC30A1-7, and 9 were significantly correlated with advanced tumor stage and nodal metastasis status, SLC30A5-7, and 9-10 were significantly related to the Helicobacter pylori infection status of GC patients. High expression of five genes (SLC30A1, 5-7, and 9) was significantly correlated with better overall survival (OS), first progression survival (FPS), and post progression survival (PPS). Conversely, upregulated SLC30A2-4, 8, and 10 expression was markedly associated with poor OS, FP and PPS. And SLC30A family genes were closely associated with the infiltration of immune cells. The present study implied that SLC30A5 and 7 may be potential biomarkers for predicting prognosis in GC patients, SLC30A2 and 3 play an oncogenic role in GC patients and could provide a new strategy for GC patients treatment.

Project description:BackgroundGastric cancer (GC) is a major public health problem worldwide. In recent decades, the treatment of gastric cancer has improved greatly, but basic research and clinical application of gastric cancer remain challenges due to the high heterogeneity. Here, we provide new insights for identifying prognostic models of GC.MethodsWe obtained the gene expression profiles of GSE62254 containing 300 samples for training. GSE15459 and TCGA-STAD for validation, which contain 200 and 375 samples, respectively. Weighted gene co-expression network analysis (WGCNA) was used to identify gene modules. We performed Lasso regression and Cox regression analyses to identify the most significant five genes to develop a novel prognostic model. And we selected two representative genes within the model for immunohistochemistry staining with 105 GC specimens from our hospital to verify the prediction efficiency. Moreover, we estimated the correlation coefficient between our model and immune infiltration using the CIBERSORT algorithm. The data from GSE15459 and TCGA cohort validated the robustness and predictive accuracy of this prognostic model.ResultsOf the 12 gene modules identified, 1,198 green-yellow module genes were selected for further analysis. Multivariate Cox analysis was performed on genes from univariate Cox regression and Lasso regression analysis using the Cox proportional hazards regression model. Finally, we constructed a five gene prognostic model: Risk Score = [(-0.7547) * Expression (ARHGAP32)] + [(-0.8272) * Expression (KLF5)] + [1.09 * Expression (MAMLD1)] + [0.5174 * Expression (MATN3)] + [1.66 * Expression (NES)]. The prognosis of samples in the high-risk group was significantly poorer than that of samples in the low-risk group (p = 6.503e-11). The risk model was also regarded as an independent predictor of prognosis (HR, 1.678, p < 0.001). The observed correlation with immune cells suggested that this risk model could potentially predict immune infiltration.ConclusionThis study identified a potential risk model for prognosis and immune infiltration prediction in GC using WGCNA and Cox regression analysis.

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Analysis of the expression, function, prognosis and co-expression genes of DDX20 in gastric cancer.

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Analysis of the expression, function, prognosis and co-expression genes of DDX20 in gastric cancer.

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