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急性胰腺炎基因表达谱芯片的生物信息学分析及药物筛选
A bioinformatics analysis of acute pancreatitis based on gene expression microarray and drug screening
文章发布日期:2020年02月17日  来源:  作者:董小鹏,王丽娟,赵春霖,等  点击次数:220次  下载次数:56次

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【摘要】:目的 应用生物信息学方法筛选急性胰腺炎(AP)差异表达基因(DEGs)及相应的候选治疗药物。方法 从基因表达数据库(GEO)中下载小鼠AP 相关的高通量芯片数据集(GSE109227和GSE65146),使用GEO2R筛选DEGs。利用DAVID数据库对DEGs进行基因本体功能富集和通路富集分析。在String数据库中建立蛋白-蛋白相互作用关系(PPI)并利用Cytoscape软件进行可视化,筛选出子网络模块和关键基因。预测关键基因相关的miRNAs并通过比较毒物遗传学数据库(CTD)针对关键基因进行治疗药物的筛选。结果 从高通量芯片数据集GSE109227和GSE65146中共筛选到130个上调基因和16个下调基因。DEGs主要参与炎症反应、中性粒细胞趋化、TNF介导的细胞反应、正调控基因表达等生物学过程,且参与细胞外基质受体相互作用、肌动蛋白细胞骨架的调控、白细胞内皮迁移、Focal adhesion等信号通路。在PPI网络中,共筛选出12个关键基因和6个子网络模块。miR-199a-5p、miR-1-3p等miRNAs可能作用于关键基因转录后调控。CTD数据库中筛选到染料木黄酮、白藜芦醇、槲皮素可降低关键基因表达水平。结论 利用生物信息学方法筛选的相关基因可能在AP发生中具有重要作用,并可作为药物的筛选依据。
【Abstract】:Objective To screen out differentially expressed genes (DEGs) and related candidate therapeutic drugs for acute pancreatitis (AP) using the bioinformatics method. Methods High-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). Results A 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. Conclusion Related 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.
【关键字】:胰腺炎, 急性坏死性; 基因芯片; 基因表达; 计算生物学
【Key words】:pancreatitis, acute necrotizing; gene microarray; gene expression; computational biology
【引证本文】:DONG XP, WANG LJ, ZHAO CL, et al. A bioinformatics analysis of acute pancreatitis based on gene expression microarray and drug screening[J]. J Clin Hepatol, 2020, 36(3): 636-640. (in Chinese)
董小鹏, 王丽娟, 赵春霖, 等. 急性胰腺炎基因表达谱芯片的生物信息学分析及药物筛选[J]. 临床肝胆病杂志, 2020, 36(3): 636-640.

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