目的:利用心肌肥大病理过程中基因表达谱的变化,构建基因/蛋白质调控网络.方法:以苯肾上腺素诱导新生大鼠心肌细胞肥大为模型,在分析肥大心肌细胞基因表达谱变化的基础上,进一步利用Pathwaystudio和Agilent Literature Search软件结合文献挖掘方法,构建基因/蛋白质相互作用网络.结果:构建的网络包含450个相互作用的基因/蛋白质(节点)以及592个它们之间相互作用的关系(边).拓扑分析表明该网络具有无尺度特性,同时分析确定14个基因/蛋白质是网络的关键节点.通过GO (gene ontology)分析,发现在苯肾上腺素诱导新生大鼠心肌细胞肥大的过程中,与物质代谢、细胞信号转导及细胞骨架等密切相关的基因可能发挥了重要作用.结论:构建基因/蛋白质网络为研究心肌肥大的分子机制提供了有用的信息和方法.%AIM: To construct a genomic regulatory network based on gene expression profiling of hypertrophic cardiomyocytes induced by phenylephrine in neonatal rats. METHODS: Cultured neonatal hypertrophic cardiomyocytes were induced by phenylephedrine. The gene expression profiles of these cells were assessed by using a cDNA microarray, and the microarray data were further analyzed by Pathwaystudio and Agilent Literature Search software. RESULTS: A genes/proteins interaction network was constructed with 450 nodes and 592 edges by analyzing the gene expression in hypertrophic cardiomyocytes and literature mining. The network belongs to scale - free network by topological analysis, and 14 genes/proteins as key nodes, including PTPN11, TRAF6, HSPA8, VIM, RPS6KA3, PTHRP, GRB2 and PI3K, were predicted. Based on GO analysis, the genes/proteins associated with metabolism, signal transduction and cytoskeleton may play important roles in the process of cardiomyocytes hypertrophy induced by phenylephedrine in neonatal rat. CONCLUSION : The genomic regulatory network based on gene expression profiling and literature mining may provide integrated clue to elaborate hypotheses about the evolution of cardiomyocyte hypertrophy.
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