Dataset Information

Bioinformatics analysis of gene expression profiling for identification of potential key genes among ischemic stroke.

ABSTRACT: This study aimed to identify the key differentially expressed genes (DEGs) following ischemic stroke (IS).The GSE22255 microarray dataset, which contains samples from peripheral blood mononuclear cells of 20 IS patients and 20 sex- and age-matched controls, was downloaded from the Gene Expression Omnibus. After data pre-processing, DEGs were identified using the Linear Models for Microarray Data package in R. The Search Tool for the Retrieval of Interacting Genes database was used to predict the interactions among the products of DEGs, and then Cytoscape software was used to visualize the protein-protein interaction (PPI) network. DEGs in the PPI network were then analyzed using the Database for Annotation, Visualization, and Integrated Discovery online software to predict their underlying functions through functional and pathway enrichment analyses.A total of 144 DEGs were identified in IS samples compared with control samples, including 75 upregulated and 69 downregulated genes. Genes with higher degrees in the PPI network included FOS (degree?=?26), TP53 (degree?=?22), JUN (degree?=?20), EGR1 (degree?=?18), JUNB (degree?=?16), and ATF3 (degree?=?15), and these genes may function in IS by interacting with each other (e.g., EGR1-JUN, EGR1-TP53, ATF3-FOS, and JUNB-FOS). Functional enrichment analysis indicated that the downregulated TP53 gene was enriched in immune response and protein targeting categories.ATF3 and EGR1 may have an important protective effect on IS, whereas FOS, JUN, and JUNB may be associated with the development of IS. In addition, TP53 may function as an indicator of poor prognosis for IS through its association with the immune response and protein targeting.

SUBMITTER: Zhai K

PROVIDER: S-EPMC5571993 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Bioinformatics analysis of gene expression profiling for identification of potential key genes among ischemic stroke.

Zhai Kaihua K Kong Xiangli X Liu Boyu B Lou Jiyu J

Medicine 20170801 34

This study aimed to identify the key differentially expressed genes (DEGs) following ischemic stroke (IS).The GSE22255 microarray dataset, which contains samples from peripheral blood mononuclear cells of 20 IS patients and 20 sex- and age-matched controls, was downloaded from the Gene Expression Omnibus. After data pre-processing, DEGs were identified using the Linear Models for Microarray Data package in R. The Search Tool for the Retrieval of Interacting Genes database was used to predict the ...[more]

PMID: 28834871

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Project description:Gastric cancer (GC) is one of the most common types of cancer worldwide. Patients must be identified at an early stage of tumor progression for treatment to be effective. The aim of the present study was to identify potential biomarkers with diagnostic value in patients with GC. To examine potential therapeutic targets for GC, four Gene Expression Omnibus (GEO) datasets were downloaded and screened for differentially expressed genes (DEGs). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were subsequently performed to study the function and pathway enrichment of the identified DEGs. A protein-protein interaction (PPI) network was constructed. The CytoHubba plugin of Cytoscape was used to calculate the degree of connectivity of proteins in the PPI network, and the two genes with the highest degree of connectivity were selected for further analysis. Additionally, the two DEGs with the largest and smallest log Fold Change values were selected. These six key genes were further examined using Oncomine and the Kaplan-Meier plotter platform. A total of 99 upregulated and 172 downregulated genes common to all four GEO datasets were screened. The DEGs were primarily enriched in the Biological Process terms: 'extracellular matrix organization', 'collagen catabolic process' and 'cell adhesion'. These three KEGG pathways were significantly enriched in the categories: 'ECM-receptor interaction', 'protein digestion and absorption', and 'focal adhesion'. Based on Oncomine, expression of ATP4A and ATP4B were downregulated in GC, whereas expression of the other genes were all upregulated. The Kaplan-Meier plotter platform confirmed that upregulated expression of the identified key genes was significantly associated with worse overall survival of patients with GC. The results of the present study suggest that FN1, COL1A1, INHBA and CST1 may be potential biomarkers and therapeutic targets for GC. Additional studies are required to explore the potential value of ATP4A and ATP4B in the treatment of GC.

Dataset Information

Bioinformatics analysis of gene expression profiling for identification of potential key genes among ischemic stroke.

Publications

Bioinformatics analysis of gene expression profiling for identification of potential key genes among ischemic stroke.

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