利用基因表达系列分析数据库进行数字化基因差异显示筛选胃癌相关基因

The distinguishing of gastric cancer associated genes by digital gene expression displayer using serial analysis of gene expression database

目的对肿瘤基因组解剖计划获得的海量数据进行充分数据挖掘,筛选胃癌差异表达基因。方法采用数字化基因差异显示技术对肿瘤基因组解剖计划数据库中的4个胃癌和2个正常胃组织文库共300,783条基因表达系列分析数据进行了分析。结果筛选出差异表达的已知基因136个,其中胃癌中表达上调的有54个,下调82个,EST序列65条,其中上调24条,下调41,虚拟Northern和数字化显示对筛选出的差异表达基因PTMA构建了全身正常组织和肿瘤组织的基因表达图谱。结论充分利用生物信息学工具可以快速有效地筛选肿瘤差异表达基因,指导后续分子生物学实验研究。筛选出来的差异表达基因通过验证,有望成为新的胃癌分子靶标。

Objective To proceed deep data mining in large database obtained by Cancer Genome Anatomy Project and to distinguish the difference expression genes of gastric carcinoma. Methods The 300, 783 serial analysis of gene expression records from 4 libraries of gastric cancer and 2 libraries of normal gastric tissue in database of the Cancer Genome Anatomy Project were analyzed by digital gene expression displayer. Results The 201 difference expression tags represented 136 genes （54 up-regulated and 82 down-regulated） and 65 ESTs （24 up-regulated and 41 down-regulated） were distinguished, and these genes were involved in biological process and signal transduction pathways, such as cell cycle regulation, cell proliferation and apoptosis. The gene expression profile in whole body normal and cancer tissues of PTMA were constructed by digital Northern based on serial analysis of gene expression database and by virtual Northern based on cDNA database, respectively. Conclusion The difference expression genes of gastric cancer can be distinguished effectively with bioinformatics, and the results will guide our further molecular biology research. If validated by molecular biology experiment, the difference expression genes will be used as molecular targets of gastric carcinoma.