Identification of gastric cancer-related genes by multiple high throughput analysis and data mining

To investigate gastric cancer-related genes by combined multiple high throughput analysis and data mining, and to further identify gene markers that may be useful in the diagnosis and treatment of gastric cancer. Data of expressed sequence tags (EST) and serial analysis of gene expression (SAGE) in...

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Bibliographic Details
Published inZhonghua wei chang wai ke za zhi Vol. 10; no. 2; p. 169
Main Authors Meng, Ling-xin, Li, Qiang, Xue, Ying-jie, Guo, Ren-de, Zhang, Yu-qing, Song, Xi-yuan
Format Journal Article
LanguageChinese
Published China 01.03.2007
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Summary:To investigate gastric cancer-related genes by combined multiple high throughput analysis and data mining, and to further identify gene markers that may be useful in the diagnosis and treatment of gastric cancer. Data of expressed sequence tags (EST) and serial analysis of gene expression (SAGE) in Cancer Genome Anatomy Project (CGAP) were employed to analyze differential gene expression between normal and cancerous gastric epithelium,the obtained genes were further analyzed by virtual Northern blotting and compared with microarray data from Stanford Microarray Database (SMD). NCBI digital differential display (DDD), cDNA digital gene expression displayed (DGED) and SAGE DGED produced 165,286 and 181 differential expression genes.All these genes were analyzed by virtual Northern blotting and 45 genes were obtained. Comparing with microarray data, candidate genes were reduced to 12. Further RT-PCR analyses validated 4 genes, including ANXA1, MSMB, ANXA10 and PSCA, were differentially expressed in normal and ca
ISSN:1671-0274