Dataset Information

Screening and Identification of Potential Hub Genes in Myocardial Infarction Through Bioinformatics Analysis.

ABSTRACT: Background: Myocardial infarction (MI) is a common cause of death worldwide. It is characterized by coronary artery occlusion that causes ischemia and hypoxia of myocardial cells, leading to irreversible myocardial damage.

Materials and methods: To explore potential targets for treatment of MI, we reorganized and analyzed two microarray datasets (GSE4648 and GSE775). The GEO2R tool was used to screen for differentially expressed genes (DEGs) between infarcted and normal myocardium. We used the Database for Annotation, Visualization and Integrated Discovery (DAVID) to perform Gene Ontology functional annotation analysis (GO analysis) and the Kyoto Encyclopedia of Genes and Genomes for pathway enrichment analysis (KEGG analysis). We examined protein-protein interactions to characterize the relationship between differentially expressed genes, and we screened potential hub genes according to the degree of connection. PCR and Western blotting were used to identify the core genes.

Results: At different times of infarction, a total of 35 genes showed upregulation at all times; however, none of the genes showed downregulation at all 3 times. Similarly, 10 hub genes with high degrees of connectivity were identified. In vivo and in vitro experiments suggested that expression levels of MMP-9 increased at various times after myocardial infarction and that expression increased in a variety of cells simultaneously.

Conclusion: Expression levels of MMP-9 increase throughout the course of acute myocardial infarction, and this expression has both positive and negative sides. Further studies are needed to explore the role of MMP-9 in MI treatment. The potential values of Il6, Spp1, Ptgs2, Serpine1, Plaur, Cxcl5, Lgals3, Serpinb2, and Cd14 are also worth exploring.

SUBMITTER: Yu YW

PROVIDER: S-EPMC7718865 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Screening and Identification of Potential Hub Genes in Myocardial Infarction Through Bioinformatics Analysis.

Yu Yong-Wei YW Xue Yang-Jing YJ Qian La-La LL Chen Zhi Z Que Jia-Qun JQ Huang Kai-Yu KY Liu Shuai S Weng Ying-Bei YB Rong Fang-Ning FN Ji Kang-Ting KT Zeng Jing-Ni JN

Clinical interventions in aging 20201201

<h4>Background</h4>Myocardial infarction (MI) is a common cause of death worldwide. It is characterized by coronary artery occlusion that causes ischemia and hypoxia of myocardial cells, leading to irreversible myocardial damage.<h4>Materials and methods</h4>To explore potential targets for treatment of MI, we reorganized and analyzed two microarray datasets (GSE4648 and GSE775). The GEO2R tool was used to screen for differentially expressed genes (DEGs) between infarcted and normal myocardium. ...[more]

PMID: 33293800

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Project description:Objective:Gastric cancer (GC) is the fourth most common cause of cancer-related deaths in the world. In the current study, we aim to identify the hub genes and uncover the molecular mechanisms of GC. Methods:The expression profiles of the genes and the miRNAs were extracted from the Gene Expression Omnibus database. The identification of the differentially expressed genes (DEGs), including miRNAs, was performed by the GEO2R. Database for Annotation, Visualization and Integrated Discovery was used to perform GO and KEGG pathway enrichment analysis. The protein-protein interaction (PPI) network and miRNA-gene network were constructed using Cytoscape software. The hub genes were identified by the Molecular Complex Detection (MCODE) plugin, the CytoHubba plugin and miRNA-gene network. Then, the identified genes were verified by Kaplan-Meier plotter database and quantitative real-time PCR (qRT-PCR) in GC tissue samples. Results:A total of three mRNA expression profiles (GSE13911, GSE79973 and GSE19826) were downloaded from the Gene Expression Omnibus (GEO) database, including 69, 20 and 27cases separately. A total of 120 overlapped upregulated genes and 246 downregulated genes were identified. The majority of the DEGs were enriched in extracellular matrix organization, collagen catabolic process, collagen fibril organization and cell adhesion. In addition, three KEGG pathways were significantly enriched, including ECM-receptor interaction, protein digestion and absorption, and the focal adhesion pathways. In the PPI network, five significant modules were detected, while the genes in the modules were mainly involved in the ECM-receptor interaction and focal adhesion pathways. By combining the results of MCODE, CytoHubba and miRNA-gene network, a total of six hub genes including COL1A2, COL1A1, COL4A1, COL5A2, THBS2 and ITGA5 were chosen. The Kaplan-Meier plotter database confirmed that higher expression levels of these genes were related to lower overall survival, except for COL5A2. Experimental validation showed that the rest of the five genes had the same expression trend as predicted. Conclusion:In conclusion, COL1A2, COL1A1, COL4A1, THBS2 and ITGA5 may be potential biomarkers and therapeutic targets for GC. Moreover, ECM-receptor interaction and focal adhesion pathways play significant roles in the progression of GC.

Dataset Information

Screening and Identification of Potential Hub Genes in Myocardial Infarction Through Bioinformatics Analysis.

Publications

Screening and Identification of Potential Hub Genes in Myocardial Infarction Through Bioinformatics Analysis.

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