摘要
目的:通过生物信息学方法分析胰腺癌蛋白质组学数据。方法:对通过蛋白质组学方法筛选出的98种胰腺癌表达上调蛋白使用NCI-Nature、Osprey1.2.0和DAVID软件分别进行信号通路分析、蛋白质相互作用分析及基因本体论(Gene On-tology,GO)分析。结果:98种基因共涉及50条信号通路,其中富集度P值<0.05的信号通路有15条,最具显著性的为HIFα-转录因子信号通路;98种基因在"细胞骨架生成"、"细胞骨架"及"蛋白结合"3种GO中富集度最为显著;在蛋白相互作用网络中,连接度最高的为Ezrin和Vimentin。结论:利用生物信息学方法对蛋白质组学数据进行挖掘,可以为进一步了解胰腺癌的发病机制提供新的思路。
OBJECTIVE： To analyze the bioinformatics in order to analyze the proteomics data of pancreatic cancer.METHODS： A total of 98 up-regulated proteins,previously obtained from our proteomic experiments,were analysed for signal pathway,protein-protein interaction and gene ontology by using NCI-Nature,Osprey1.2.0 and DAVID sofwares,respectively.RESULTS： Ninety-eight genes were involved in 50 individual signal pathways,among which 15 had significance with enrichment P value 〈0.05 and the HIF-1-α transcription factor network was the most significant pathway.For Gene ontology analysis,the genes involved in cytoskeleton organization and biogenesis,cytoskeleton and protein binding were significant.Ezrin and Vimentin had the most connections with other proteins in the constructed protein-protein interaction network.CONCLUSION： Bioinformatics provides a useful tool for further mining the proteomic data,and also provides new clues in the understanding of molecular mechanism in pancreatic cancer.
出处
《中华肿瘤防治杂志》
CAS
2010年第6期423-426,共4页
Chinese Journal of Cancer Prevention and Treatment
基金
山东省科技攻关计划重大科技专项(2005GG1102003)
