A bioinformatics analysis of acute pancreatitis based on gene expression microarray and drug screening

ObjectiveTo screen out differentially expressed genes (DEGs) and related candidate therapeutic drugs for acute pancreatitis (AP) using the bioinformatics method. MethodsHigh-throughput microarray datasets (GSE109227 and GSE65146) associated with AP in mice were downloaded from gene expression omnibu...

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Main Author: DONG Xiaopeng
Format: Article
Language:zho
Published: Editorial Department of Journal of Clinical Hepatology 2020-03-01
Series:Linchuang Gandanbing Zazhi
Online Access:http://www.lcgdbzz.org/qk_content.asp?id=10626
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spelling doaj-fcd654c896d1493c90a1f9797a6547b62020-11-25T02:50:25ZzhoEditorial Department of Journal of Clinical HepatologyLinchuang Gandanbing Zazhi1001-52561001-52562020-03-01363636640A bioinformatics analysis of acute pancreatitis based on gene expression microarray and drug screeningDONG Xiaopeng0 Gansu University of Chinese MedicineObjectiveTo screen out differentially expressed genes (DEGs) and related candidate therapeutic drugs for acute pancreatitis (AP) using the bioinformatics method. MethodsHigh-throughput microarray datasets (GSE109227 and GSE65146) associated with AP in mice were downloaded from gene expression omnibus, and GEO2R was used to screen out DEGs. Database for Annotation, Visualization and Integrated Discovery was used to perform gene ontology and pathway enrichment analysis. Protein-protein interaction (PPI) was established in String database and visualized by Cytoscape, and then subnetwork modules and hub genes were screened out. The microRNAs associated with the hub genes were predicted and candidate drugs were screened out using Comparative Toxicogenomics Database (CTD). ResultsA total of 130 upregulated and 16 downregulated DEGs were screened out in the high-throughput microarray datasets GSE109227 and GSE65146. DEGs were mainly involved in the biological processes such as inflammatory response, neutrophil chemotaxis, tumor necrosis factor-mediated cellular response, and positive regulation of gene expression, and they were also involved in the signaling pathways of extracellular matrix-receptor interaction, regulation of actin cytoskeleton, leukocyte transendothelial migration, and focal adhesion. A total of 12 hub genes and 6 subnetwork modules were screened out in the PPI network. The microRNAs including miR-199a-5p and miR-1-3p might regulate the post-transcriptional regulation of key genes. Genistein, resveratrol, and quercetin which were screened out from CTD database could reduce the expression of key genes. ConclusionRelated genes screened out by the bioinformatics method may play an important role in the development of AP and can be used as the basis for drug screening.http://www.lcgdbzz.org/qk_content.asp?id=10626
collection DOAJ
language zho
format Article
sources DOAJ
author DONG Xiaopeng
spellingShingle DONG Xiaopeng
A bioinformatics analysis of acute pancreatitis based on gene expression microarray and drug screening
Linchuang Gandanbing Zazhi
author_facet DONG Xiaopeng
author_sort DONG Xiaopeng
title A bioinformatics analysis of acute pancreatitis based on gene expression microarray and drug screening
title_short A bioinformatics analysis of acute pancreatitis based on gene expression microarray and drug screening
title_full A bioinformatics analysis of acute pancreatitis based on gene expression microarray and drug screening
title_fullStr A bioinformatics analysis of acute pancreatitis based on gene expression microarray and drug screening
title_full_unstemmed A bioinformatics analysis of acute pancreatitis based on gene expression microarray and drug screening
title_sort bioinformatics analysis of acute pancreatitis based on gene expression microarray and drug screening
publisher Editorial Department of Journal of Clinical Hepatology
series Linchuang Gandanbing Zazhi
issn 1001-5256
1001-5256
publishDate 2020-03-01
description ObjectiveTo screen out differentially expressed genes (DEGs) and related candidate therapeutic drugs for acute pancreatitis (AP) using the bioinformatics method. MethodsHigh-throughput microarray datasets (GSE109227 and GSE65146) associated with AP in mice were downloaded from gene expression omnibus, and GEO2R was used to screen out DEGs. Database for Annotation, Visualization and Integrated Discovery was used to perform gene ontology and pathway enrichment analysis. Protein-protein interaction (PPI) was established in String database and visualized by Cytoscape, and then subnetwork modules and hub genes were screened out. The microRNAs associated with the hub genes were predicted and candidate drugs were screened out using Comparative Toxicogenomics Database (CTD). ResultsA total of 130 upregulated and 16 downregulated DEGs were screened out in the high-throughput microarray datasets GSE109227 and GSE65146. DEGs were mainly involved in the biological processes such as inflammatory response, neutrophil chemotaxis, tumor necrosis factor-mediated cellular response, and positive regulation of gene expression, and they were also involved in the signaling pathways of extracellular matrix-receptor interaction, regulation of actin cytoskeleton, leukocyte transendothelial migration, and focal adhesion. A total of 12 hub genes and 6 subnetwork modules were screened out in the PPI network. The microRNAs including miR-199a-5p and miR-1-3p might regulate the post-transcriptional regulation of key genes. Genistein, resveratrol, and quercetin which were screened out from CTD database could reduce the expression of key genes. ConclusionRelated genes screened out by the bioinformatics method may play an important role in the development of AP and can be used as the basis for drug screening.
url http://www.lcgdbzz.org/qk_content.asp?id=10626
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