Velcade影响K562细胞基因表达谱的分子机制

Effect of Velcade on the gene expression profiles of K562 cells: study of its molecular mechanism

目的应用生物信息学方法探索Velcade影响K562细胞基因表达谱的分子机制。方法提取并扩增Velcade处理组和溶剂对照组的K562细胞RNA,与22K Agilent Human1A基因芯片杂交,用Agilent Feature Extraction软件采集扫描数据,再以GeneSifter,GATHER等基因芯片数据分析工具,对差异表达基因进行基因本体分类、KEGG通路分析、蛋白互作网络分析和文献挖掘。结果获得228个差异表达基因,其中上调84个,下调144个。下调糜酶1基因幅度最大,对数比值达10.80倍,干扰素α-21基因也下调2.31倍。本体分类显示,衰老过程、白细胞活动等过程显著增强;KEGG通路分析显示,JAK-STAT信号通路,自然杀伤细胞介导的细胞毒作用和抗原处理与提呈等通路受显著影响;蛋白互作网络揭示泛素依赖的蛋白质降解通路、抗原提呈和免疫反应、JAK-STAT信号通路等处于网络中重要位置;文献挖掘显示差异表达基因与白血病、细胞凋亡、细胞周期、蛋白酶体、抑制剂、衰老和IκB等关键词高度关联。结论Velcade可能通过抑制NF-κB和JAK-STAT等促进细胞存活的信号通路,增强细胞毒作用,诱导肿瘤细胞凋亡;Velcade还可能参与抗原加工与提呈、免疫反应、炎症反应等过程;糜酶1基因可能是Velcade发挥抗肿瘤作用的关键靶标。

Objective To analyze alterations in the gene expression profiles of Velcade-treated K562 cells using bioinformatics methods. Methods The total RNAs of Velcade-treated and control K562 cells were amplified and labeled with fluorescent dyes. The labeled RNAs were hybridized to Agilent Human IA Microarray, and the raw expression data were processed with Agilent Feature Extraction Sottware. GeneSiRer and GATHER were used for data analysis of the differentially expressed genes to perform gene ontology classification, KEGG pathway analysis, functional protein association network construction and literature mining. Results Totally 228 differentially expressed genes were identified in the Velcade-treated K562 cells. including 84 up-regulated and 144 down-regulated genes. Chyrnase 1 gene had the greatest down-regulation by 10.80 folds （log ratio）, and interferon α-21 gene was also down-regulated by 2.31 folds. Gene ontology classification suggested enhanced aging and leukocyte activity. KEGG pathway analysis showed significant impact of Velcade on JAK-STAT signaling pathway, cytotoxicity mediated by natural killer cells, and antigen processing and presentation pathways. Protein-protein interaction analysis revealed that ubiquitin-dependent protein catabolism, antigen presentation and immune response, as well as JAK-STAT signaling pathway were the major elements of the protein network. Literature mining showed that the differentially expressed genes were strongly associated with terms such as leukemia, apoptosis, cell cycle, proteasome, inhibitor, aging and It, B, etc. Conclusions Velcade may inhibit the cell survival pathways such as NF-κB and JAK-STAT signaling pathways to enhance the cytotoxicity and inducing tumor cell apoptosis. Velcade might also be involved in antigen processing and presentation, immune response and inflammation. Chymase 1 gene is probably the key target of Velcade.