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Global gene expression analysis of gastric cancer by oligonucleotide microarrays


ABSTRACT: To gain molecular understanding of carcinogenesis, progression, and diversity of gastric cancer, 22 primary human advanced gastric cancer tissues and 8 noncancerous gastric tissues were analyzed by high-density oligonucleotide microarray in this study. Based on expression analysis of approximately 6800 genes, a two-way clustering algorithm successfully distinguished cancer tissues from noncancerous tissues. Subsequently, genes that were differentially expressed in cancer and noncancerous tissues were identified; 162 and 129 genes were highly expressed (P < 0.05) >2.5-fold in cancer tissues and noncancerous tissues, respectively. In cancer tissues, genes related to cell cycle, growth factor, cell motility, cell adhesion, and matrix remodeling were highly expressed. In noncancerous tissues, genes related to gastrointestinal-specific function and immune response were highly expressed. Furthermore, we identified several genes associated with lymph node metastasis including Oct-2 or histological types including Liver-Intestine Cadherin. These results provide not only a new molecular basis for understanding biological properties of gastric cancer, but also useful resources for future development of therapeutic targets and diagnostic markers for gastric cancer. Keywords: other

ORGANISM(S): Homo sapiens

SUBMITTER: Shogo Yamamoto 

PROVIDER: E-GEOD-2685 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Global gene expression analysis of gastric cancer by oligonucleotide microarrays.

Hippo Yoshitaka Y   Taniguchi Hirokazu H   Tsutsumi Shuichi S   Machida Naoko N   Chong Ja-Mun JM   Fukayama Masashi M   Kodama Tatsuhiko T   Aburatani Hiroyuki H  

Cancer research 20020101 1


To gain molecular understanding of carcinogenesis, progression, and diversity of gastric cancer, 22 primary human advanced gastric cancer tissues and 8 noncancerous gastric tissues were analyzed by high-density oligonucleotide microarray in this study. Based on expression analysis of approximately 6800 genes, a two-way clustering algorithm successfully distinguished cancer tissues from noncancerous tissues. Subsequently, genes that were differentially expressed in cancer and noncancerous tissues  ...[more]

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