中国人前列腺癌发病关键基因的生物信息学研究  

Key genes in the pathogenesis of prostate cancer in Chinese men:A bioinformatic study

作　　者：王刚[1] 杨阔[1] 孟帅[2] 徐勇[1] 杨志华[3] 刘妍[1] 

机构地区：[1]天津医科大学第二医院泌尿外科/天津市泌尿外科研究所,天津300211 [2]北京协和医学院医药生物技术研究所,北京100050 [3]天津医科大学生物医学工程系,天津300070

出　　处：《中华男科学杂志》2010年第4期320-324,共5页National Journal of Andrology

基　　金：天津市科技计划项目(07ZCGYSF01000)~~

摘　　要：目的:利用国内相关研究中已筛选出的前列腺癌差异表达基因,构建基因相互作用网络,通过统计学分析,进一步筛选对该网络具有重大影响的基因,探寻对前列腺癌发生起关键作用的基因,进而阐述中国人前列腺癌发病的分子机制。方法:查找近年来国内发表的相关文献,利用其筛选出的有关中国人前列腺癌基因表达谱数据,归纳出前列腺癌差异表达基因;运用NCBI中OMIM数据库分析其功能,总结出基因之间的相互关系,构建基因相互关系网络模型;运用统计学方法(节点收缩法)比较关键基因的重要度。结果:综合国内发表的有关论文中的基因表达谱数据,得到差异表达基因113条,其中上调基因51条,下调基因62条;运用OMIM数据库构建出一个包含68条基因的具有相互关系的基因网络模型;用节点收缩法统计出各个基因的重要度,从而找出了网络中起关键作用的基因,包括c-MYC、VEGF、HSPCA、TGFβ1、RANTES、EGR1等共12条基因,这些基因很可能在前列腺癌的发生发展中起着重要作用。结论:本研究运用生物信息学方法对国内前列腺癌基因芯片结果进行分析和研究,将含有基因信息的OMIM数据库和评价网络节点重要性的节点收缩法结合,对一批前列腺癌差异表达基因建立了相互作用网络,并对网络中的关键基因进行评估,从而构建了一个在整体水平上对基因表达谱数据进行分析的网络模型,为后续工作中对前列腺癌发病机制的研究提供了新的途径。Objective：The purpose of this study was to construct a pathway-based network using differentially expressed genes in prostate cancer（PCa） screened by cDNA microarray chips in domestic research to visualize the relations among the genes obtained from the microarray data,and identify the genes with significant influence on this network by statistical analysis.It also aimed to search for the genes that play key roles in the tumorigenesis of PCa,and probe into the molecular mechanism of PCa pathogenesis in Chinese men.Methods：The relevant domestic literature of recent years were reviewed to sum up differentially expressed genes in PCa according to the screened microarray data.The OMIM database was used to analyze the relations among these genes and build a network of biological pathway.Furthermore,a statistical method,namely node contraction,was employed to compare the importance of the key genes.Results：According to the gene expression profiling data,there were 113 differentially expressed genes,51 up-regulated and 62 down-regulated.A pathway-based network including 68 inter-related genes was constructed using the OMIM database.The importance of every key node was calculated using the method of node contraction,and 12 key genes were identified,incuding c-MYC,VEGF,HSPCA,TGFβ1,RANTES,EGR1,etc,which probably played important roles in the pathogenesis and progression of prostate cancer.Conclusion：We applied bioinformatics to the analysis of the gene expression profiling data in China,constructed a network of the differentially expressed genes using the OMIM database and method of node contraction,appraised the importance of the key genes,and established a method for the overall analysis of the gene chip data,which have paved a new ground for further researches on the pathogenesis of prostate cancer in Chinese men.

关 键 词：前列腺癌 基因表达谱 OMIM数据库 基因网络 节点收缩 

分 类 号：R737.25[医药卫生—肿瘤]