【摘要】 目的依据基因表达芯片数据筛选原始神经外胚层肿瘤(primitive neurotodermal tumor,PNET)患者肿瘤组织的差异表达基因及关键蛋白,为其临床治疗提供新的理论依据。方法从基因芯片公共数据库(Gene Expression Omnibus,GEO)获取GSE74195基因芯片数据集,筛选PNET肿瘤组织与正常小脑组织的差异表达基因,同时进行功能注释(GO)、通路分析(KEGG)及蛋白互作网络分析。结果筛选出340个表达显著上调的差异基因(FC>3,P<0.01),经功能注释和通路分析,发现这些基因富集于细胞周期、有丝分裂及细胞增殖等过程,KEGG通路富集显示主要集中于细胞周期和ECM受体相互作用等通路。经蛋白质相互作用网络构建,筛选出5个关键蛋白分子,即UBA52、UBC、CDK1、CENPK及NDE1。结论筛选出PNET肿瘤中高表达基因及关键蛋白,为PNET发病机制及潜在的治疗靶点研究提供新思路。更多还原

【Abstract】 Objective To screen the differential expression genes and key proteins of gene expression microarray data in primitive neurotodermal tumor patients, to provide a new theoretical basis for clinical treatment. Methods Microarray data set GSE74195 was obtained from GEO to screen differentially expressed genes between PNET tumors and normal cerebellum tissues. Functional annotation(GO), pathway analysis(KEGG) and protein interaction network analysis were also performed. Results A total of 340 differentially expressed genes(FC>3, P<0.01) were screened. Functional annotation and pathway analysis showed that these genes were mainly concentrated in cell cycle, mitosis and cell proliferation. KEGG pathway enrichment showed that they were mainly concentrated in cell cycle and ECM receptor interaction. Five key protein molecules, namely UBA52, UBC, CDK1, CENPK and NDE1, were screened through the construction of protein interaction network. Conclusion Screening of genes and key protein molecules with high expression in PNET tumors provides a new way to study the pathogenesis and potential therapeutic targets of PNET.更多还原