应用基因芯片筛选伊马替尼和尼洛替尼处理K562细胞表达差异基因  

Identification of Imatinib and Nilotinib Treated Differentially Expressed Genes in K562 Cells with DNA Microarray

作　　者：付伟 曹洁 代芳 蒋艳 胡彬[2] 高晓彤[2] 谢东 梁英民[2] 

机构地区：[1]解放军第四十四医院血液科,贵州贵阳550009 [2]第四军医大学唐都医院血液科,陕西西安710032

出　　处：《现代生物医学进展》2016年第30期5829-5832,共4页Progress in Modern Biomedicine

基　　金：贵州省卫生计生委科学技术基金项目(gzwjkj2014-1-058)

摘　　要：目的:探讨两种酪氨酸激酶抑制剂(TKIs)处理K562细胞的基因表达谱变化,为认识慢性粒细胞白血病(CML)的发病机制、耐药机制提供新的思路,同时也为治疗寻找潜在重要靶标分子。方法:利用GEO数据库下载慢性粒细胞细胞系(K562)基因表达芯片数据,通过差异基因的筛选,趋势分析、GO分析,信号通路分析,最后获得的重要差异表达核心基因,并建立相互作用网络。结果:获得显著表达差异基因1000,通过趋势分析、功能富集分析及信号通路分析提示主要涉及到代谢途径、细胞凋亡、癌症的途径、细胞周期、p53信号通路。相互作用网络分析及同表达相互作用网络分析,得到重要的核心节点基因:AK2、ADSL、PKLR、PKM、SHMT2、ATIC、LDHA、ENO1、CTH、GOT1;YARS、CYP3A5、CTH、GYPA、ALAS2、MTHFD2、BLVRB、GUK1、CTSH、LMO2。结论:利用生物信息学的方法,分析慢性粒细胞白血病细胞基因芯片得到参与不同TKIs处理K562细胞的重要的细胞功能及信号通路主要涉及代谢通路及增殖凋亡信号途径,并且寻找到核心节点基因,为认识K562的耐药机制及治疗靶点提供新的思路。Objective： To screen different express genes of K562 cells treated by two kinds of TKIs by using the GEO database and explore the bioinformatics information, so as to provide the new molecular markers for treatment and resistance. Methods： The microarray data were collected from GEO database. SAM was used to find the DEGs, and then all DEGs were analyzed by STC, GO and Pathway analysis, finally created the gene signal network and gene coexpression networks. Results： There were 1000 DEGs, moreover the main results of GO and pathway analysis of DEGs were Metabolic pathways, Apoptosis, Pathways in cancer, Cell cycle, p53 signaling pathway. At last, we found the top 20 core of node genes, there were AK2, ADSL, PKLR, PKM, SHMT2, ATIC, LDI-tA, ENO1, CTH,GOT1, YARS, CYP3A5, CTH, GYPA, ALAS2, MTHFD2, BLVRB, GUK1, CTSH, LMO2. Conclusion： By using bioinformatics methods, we analyzed the gene chips of K562 ,which helped us to understand the mechanism during TKI resistance and provided new potential treatment of targeted genes.

关 键 词：慢性粒细胞白血病 尼洛替尼 伊马替尼 基因芯片 

分 类 号：R332[医药卫生—人体生理学] R733.7[医药卫生—基础医学]