Dataset Information

A panel of collagen genes are associated with prognosis of patients with gastric cancer and regulated by microRNA-29c-3p: an integrated bioinformatics analysis and experimental validation.

ABSTRACT: Background: The systematic expression characteristics and functions of collagen genes in gastric cancer (GC) have not been reported. Through public data integration, combined with bioinformatics analysis, we identified a panel of collagen genes overexpressed in GC. The functions of these genes were analyzed and validated in a GC-related cohort. microRNAs that may potentially target such genes were investigated in vitro. Methods: Four GC-related datasets retrieved from the Gene Expression Omnibus (GEO) were used to extract differentially expressed genes (DEGs) in GC. Functional annotation was performed to identify the potential roles of the identified DEGs. The association of candidate genes involved in the prognosis of GC patients (n=876) was determined using data provided by the Kaplan-Meier-plotter database, The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD) repository, and a GC-related dataset (GSE15459). The expression characteristics of candidate genes and their associations with clinical parameters were validated in our in-house cohort (n=58). MicroRNAs able to target the identified candidate genes were predicted and confirmed using qRT-PCR, Western blotting, and dual-luciferase reporter assays in vitro. Results: After the integration of four GEO datasets, 76 DEGs were identified. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis indicated that these DEGs were significantly enriched in ECM-related functions and pathways. A group of collagen genes was significantly upregulated in the GC tissues and constituted a protein-protein interaction network as important nodes. Some of these collagen genes were closely associated with poor prognosis in GC patients. Overexpression of COL1A1 and COL4A1 was confirmed in our in-house cohort, and this was related to prognosis and certain clinicopathological parameters. We found that microRNA-29c-3p could directly target COL1A1 and COL4A1 in BGC-823 cells. Conclusions: Collagen genes identified in this study were associated with patient prognosis in GC and may represent diagnostic markers or potential therapeutic targets. Aberrant expression of such candidate genes may be induced by microRNA-29c-3p.

SUBMITTER: Zhang QN

PROVIDER: S-EPMC6538884 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A panel of collagen genes are associated with prognosis of patients with gastric cancer and regulated by microRNA-29c-3p: an integrated bioinformatics analysis and experimental validation.

Zhang Qiang-Nu QN Zhu Hui-Li HL Xia Meng-Ting MT Liao Juan J Huang Xiao-Tao XT Xiao Jiang-Wei JW Yuan Cong C

Cancer management and research 20190524

Background: The systematic expression characteristics and functions of collagen genes in gastric cancer (GC) have not been reported. Through public data integration, combined with bioinformatics analysis, we identified a panel of collagen genes overexpressed in GC. The functions of these genes were analyzed and validated in a GC-related cohort. microRNAs that may potentially target such genes were investigated in vitro. Methods: Four GC-related datasets retrieved from the Ge ...[more]

PMID: 31213898

Similar Datasets

Project description:BackgroundGastric cancer (GC) is disease with a high morbidity. The purpose of this study was to identify genes essential to GC development in patients and to reveal the underlying mechanisms of progression.MethodsBioinformatics analysis is an effective tool for discovering essential genes of different disease states. We used the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs), the DAVID online tool to perform Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of DEGs, the STRING database to construct the protein-protein interaction (PPI) network of DEGs, the Oncomine and the Cancer Genome Atlas-Stomach Adenocarcinoma (TCGA-STAD) databases to analyze the gene expression differences, the Human pan-Cancer Methylation database (MethHC) to compare the DNA methylation of genes, and the Kaplan-Meier plotter to show the survival analysis of DEGs. We performed Real-Time quantitative PCR (RT-qPCR) experiment to confirm our analysis results.ResultsAfter the integration of four Gene Expression Series (GSEs), we identified 407 DEGs. GO and KEGG pathway analysis indicated that the upregulated DEGs were significantly enriched in Extracellular Matrix (ECM) related functions and pathways. The main DEGs were collagens (COLs). Moreover, the downregulated DEGs were enriched in ethanol oxidation. Several groups of DEGs, such as insulin-like growth factor binding protein (IGFBP), collagen (COL) and serpin peptidase inhibitors (SERPIN) gene families, constituted several PPI networks. In the Oncomine database, all of the collagen genes were highly expressed in breast cancer, esophageal cancer, GC, head and neck cancer and pancreatic cancer, compared with normal tissues. Consistently, from the TCGA-STAD database, most of the collagens (COLs) were highly expressed and exhibited methylated variation in GC patients. In GC patients, some of these collagen (COL) genes related to worse prognosis, as evidenced by the results from the Kaplan-Meier plotter database analysis. Our RT-qPCR results showed that collagen type III α1 chain (COL3A1) was highly expressed in GC cells. Collagen type V α1 chain (COL5A1) was highly expressed, except in AGS cells, which was consistent with our analysis.ConclusionsCollagen (COL) family genes might serve as progression and prognosis markers of GC.

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:BackgroundGastric cancer (GC) is one of the leading causes of cancer-related mortality worldwide. There are great geographical differences in the incidence of GC, and somatic mutation rates of driver genes are also different. The present study is aimed at screening core prognosis-related candidate genes in Chinese gastric cancer population based on integrated bioinformatics for the early diagnosis and prognosis of GC.MethodsIn the present study, the differentially expressed genes (DEGs) in GC were identified using four microarray datasets from the Gene Expression Omnibus (GEO) database. The samples of these datasets were all from China. Functional enrichment analysis of DEGs was conducted to evaluate the underlying molecular mechanisms involved in GC. Protein-protein interaction (PPI) network and cytoHubba were performed to determine hub genes associated with GC. Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) were performed to validate the hub genes.ResultsA total of 240 DEGs were obtained through the RRA method, including 80 upregulated genes and 160 downregulated genes. Upregulated genes were mainly enriched in extracellular matrix organization, extracellular matrix, and extracellular matrix structural constituent. The downregulated genes were mainly enriched in digestion, extracellular space, and oxidoreductase activity. The KEGG pathway enrichment analysis showed that the upregulated genes were mainly associated with ECM-receptor interaction, focal adhesion, and PI3K-Akt signaling pathway. And downregulated genes were mainly associated with the metabolism of xenobiotics by cytochrome P450, metabolic pathways, and gastric acid secretion. The transcriptional and translational expression levels of the genes including COL1A1, COL5A2, COL12A1, and VCAN were higher in GC tissues than normal tissues.ConclusionA total of four genes including COL1A1, COL5A2, COL12A1, and VCAN were considered potential GC biomarkers in the Chinese population. And ECM-receptor interaction, focal adhesion, and PI3K-Akt signaling pathway were revealed to be important mechanisms of GC. Our findings provide novel insights into the occurrence and progression of GC in the Chinese population.

Project description:Background aimsGastric cancer is the most frequent gastrointestinal tumor in adults and is the most lethal form of human cancer. Despite of the improvements in treatments, the underlying mechanism of gastric carcinogenesis is not well known. To define novel modulators that regulate susceptibility to tumorgenesis, we focused on miR-219-2-3p.MethodsQuantitative RT-PCR was employed to investigate the level of miR-219-2-3p in gastric cancer (GC) tissues (n = 113) and their matched adjacent normal tissues (n = 113). In vitro cell proliferation, apoptosis assays, cell migration, and invasion assays were performed to elucidate biological effects of miR-219-2-3p. Since silencing of miRNA by promoter CpG island methylation may be an important mechanism in tumorgenesis, GC cells were treated with 5-aza-2'-deoxycytidine and trichostatin A, and expression changes of miR-219-2-3p were subsequently examined by quantitative RT-PCR. Finally, the methylation status of CpG island upstream of miR-219-2-3p was analyzed by methylation-specific PCR in GC tissues (n = 22).ResultsmiR-219-2-3p was down-regulated in GC and cell lines. In addition, the experiments documented the lower expression of miR-219-2-3p in GC specimens with higher grade and later stage tumors. Meanwhile, miR-219-2-3p exerted antiproliferative, proapoptotic, and antimetastatic roles and reduced levels of p-ERK1/2 in GC cells. Furthermore, 5-aza-2'-deoxycytidine and trichostatin A increased the expression (~2 fold) of miR-219-2-3p in GC cells. By methylation-specific PCR, DNA methylation in the upstream region of miR-219-2-3p was detected in both adjacent normal tissues and cancer tissues. As expected, the methylation level was considerably higher in the miR-219-2-3p down-regulated group than up-regulated group.ConclusionsmiR-219-2-3p is potentially involved in gastric cancer progression and metastasis by regulating ERK1/2-related signal pathways, which may provide a novel therapeutic strategy for treatment of gastric cancer. Methylation mechanism may be involved in modulating the expression level of miR-219-2-3p in gastric cancer.

Dataset Information

A panel of collagen genes are associated with prognosis of patients with gastric cancer and regulated by microRNA-29c-3p: an integrated bioinformatics analysis and experimental validation.

Publications

A panel of collagen genes are associated with prognosis of patients with gastric cancer and regulated by microRNA-29c-3p: an integrated bioinformatics analysis and experimental validation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets