引用本文:童 也,许 斌,刘晓伟.DGKZ基因沉默条件下人骨肉瘤细胞芯片的生物信息学分析[J].中国临床新医学,2020,13(1):42-47.
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DGKZ基因沉默条件下人骨肉瘤细胞芯片的生物信息学分析
童 也,许 斌,刘晓伟
233000 安徽,蚌埠医学院(童 也);210002 南京,东部战区总医院(许 斌,刘晓伟)
摘要:
[摘要] 目的 基于生物信息学方法分析二酰甘油激酶ζ(diacylglycerol kinase zeta,DGKZ)基因沉默的人骨肉瘤细胞芯片并探寻其分子机制。方法 从GEO数据库中获取人骨肉瘤细胞芯片,在R软件中筛选DGKZ沉默处理组与对照组的差异基因(differential expression genes,DEGs);DEGs提交至DAVID数据库进行基因功能与通路富集分析;利用STRING数据库和Cytoscape软件构建蛋白互作网络,寻找网络结构中的核心基因并预测其转录因子。结果 共筛选出368个DEGs,其中包含105个上调的基因与263个下调的基因。GO富集分析结果表明DEGs主要富集的生物学过程有成骨细胞分化的负调控、血管生成、RNA聚合酶Ⅱ启动子转录的负调控、脂肪细胞分化的正调控、细胞周期和Wnt信号通路;KEGG通路富集分析结果表明DEGs主要涉及的通路有TGF-β信号转导通路、癌症通路、胰腺癌、致癌病毒、MAPK信号转导通路以及代谢通路。经STRING数据库与Cytoscape软件找出度值前10的核心基因有SIRT1、EP300、PTGS2、BMP2、HIF1A、RB1、HIST1H2BO、NT5E、H1F0、HIST1H2AC,核心基因通过iRegulon插件预测的转录因子中标准化富集分数最高的是YY1。结论 在DGKZ基因沉默条件下,转录因子YY1及相关靶基因能在骨肉瘤中发挥重要作用。
关键词:  骨肉瘤  生物信息学  二酰甘油激酶ζ  GEO数据库
DOI:10.3969/j.issn.1674-3806.2020.01.10
分类号:R 738
基金项目:原南京军区医药卫生科研基金项目(编号:15DX019)
Bioinformatics analysis of human osteosarcoma cell microarray with DGKZ gene silencing
TONG Ye, XU Bin, LIU Xiao-wei
Bengbu Medical College, Anhui 233000, China
Abstract:
[Abstract] Objective To analyze human osteosarcoma cell microarray silenced by diacylglycerol kinase zeta(DGKZ) gene based on the bioinformatics method and explore its molecular mechanism. Methods Human osteosarcoma cell microarrays were obtained from Gene Expression Omnibus(GEO) database. Differential expression genes(DEGs) in the DGKZ silencing treatment group and the control group were screened by R software. DEGs were submitted to DAVID database for gene function and pathway enrichment analysis. STRING database and Cytoscape software were used to construct protein-protein interaction(PPI) network and search for the hub genes in the network and predict hub gene transcription factors. Results A total of 368 DEGs were screened out, including 105 up-regulated genes and 263 down-regulated genes. Gene Ontology(GO) enrichment analysis showed that the main biological processes of DEGs enrichment were negative regulation of osteoblast differentiation, angiogenesis, negative regulation of transcription from RNA polymerase Ⅱ promoter, positive regulation of fat cell differentiation, cell cycle and Wnt signaling pathway. KEGG pathway enrichment analysis suggested that the main pathways involved in DEGs were TGF-β signaling pathway, pathways in cancer, pancreatic cancer, viral carcinogenesis, MAPK signaling pathway and metabolic pathways. The hub genes of the top 10 were identified by STRING database and Cytoscape software as SIRT1, EP300, PTGS2, BMP2, HIF1A, RB1, HIST1H2BO, NT5E, H1F0, HIST1H2AC, and the highest standardized enrichment fraction of transcription factors predicted by iRegulon plug-in for hub genes was YY1. Conclusion Transcription factor YY1 and the related target genes can play an important role in osteosarcoma under the condition of DGKZ silencing.
Key words:  Osteosarcoma  Bioinformatics  Diacylglycerol kinase zeta (DGKZ)  Gene Expression Omnibus(GEO) database