生物信息学方法对人类和小鼠共同肝癌相关基因的筛选

目的:研究应用生物信息学技术,对基因芯片产生的大量数据进行系统地挖掘和分析,筛选出人类和小鼠不同种属间在肝癌发生发展过程中起关键作用的共同基因.方法:首先通过文献检索和收集,在GEO数据库中下载符合纳入标准的9套样本基因芯片数据,运用bioconductor和Rversion的2.10.1版本对已下载数据进行标准化处理,运用软件包affy中的RMA算法对affymetrix平台的原始数据进行背景校正、标准化和log2转换;其次使用excel的TTEST函数计算每一个基因的显著性,DAVID进行探针基因名称转换,建立基因名称与样本对应的表达数据表;再进行Meta分析计算人类及小鼠的共同差显基因,并通过DAVID中的KEGG库富集调控通路.结果:人类与小鼠在肝癌发生发展过程中的共同表达基因52个,其中5个为上调基因,4个为下调基因;富集出7条通路,其中甘氨酸、丝氨酸、苏氨酸代谢通路和轴突引导通路是文献已报道的与肝癌发生发展密切相关通路.结论:通过生物信息学可快速筛选出人类与小鼠在肝癌发生发展过程中的共同关键基因及与肝癌发生发展密切相关通路.

Bioinformatic screening of key genes expressed in both human and mouse hepatocellular carcinoma

AIM:To mine and analyze large amounts of data generated by gene chips and screen key genes expressed in both human and mouse hepatocellular carcinoma using bioinformatic methods.METHODS:Through literature search and collection,nine sets of gene chip data that meet the criteria were downloaded from GEO database.The data were standardized by using Bioconductor and R version 2.10.1.The original Affymetrix data were normalized,background corrected,standardized and log2 transformed using the RMA algorithm.Excel’s TTEST function was used to calculate the significance of each gene.DAVID was used for gene ID conversion and a table was established for samples and the corresponding gene expression data.A meta-analysis was then performed to screen genes expressed in both human and mouse hepatocellular carcinoma.KEGG pathways were then enriched.RESULTS:A total of 52 genes were found to be expressed in both human and mouse hepatocellular carcinoma.Five of them were up-regulated,while four of them down-regulated.Seven KEGG pathways were enriched,of which glycine,serine,threonine metabolic pathways and axon guidance pathway have been previously reported to associated with the development of hepatocellular carcinoma.CONCLUSION:Bioinformatic tools allow us to identify key genes and pathways that are closely related to the development of hepatocellular carcinoma in both human and mice.