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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 conduct a full data mining of mass data obtained from the anatomy of tumor genome to screen differentially expressed genes in gastric cancer. Methods A total of 300,783 gene expression data from four gastric cancer and two normal gastric tissue libraries in the TGA Genome Database were analyzed by using digital gene differential display technique. Results 136 differentially expressed genes were screened out, of which 54 were up-regulated, 82 were down-regulated, and 65 were EST sequences, of which 24 were up-regulated and 41 were down-regulated. Northern blot and digitization showed that the differentially expressed Gene PTMA constructed a normal gene expression profile of normal and tumor tissues. Conclusion Making full use of bioinformatics tools can rapidly and effectively screen tumor differentially expressed genes and guide experimental research in subsequent molecular biology. The differentially expressed genes that are screened out are verified to be the new molecular target of gastric cancer.