E-GEOD-3547 - Comprehensive analysis of the gene expression profiles in human gastric cancer cell lines

Status
Submitted on 2 November 2005, released on 2 November 2005, last updated on 27 March 2012
Organism
Homo sapiens
Samples (54)
Arrays (5)
Protocols (2)
Description
Gastric adenocarcinoma is one of the major malignancies worldwide. Gastric cell lines have been widely used as the model to study the genetics, pharmacology and biochemistry of gastric cancers. Here we describe a comprehensive survey of the gene expression profiles of 12 gastric carcinoma cell lines, using cDNA microarray with 43 000 clones. For comparison, we also explored the gene expression patterns of 15 cell lines derived from lymphoid, endothelial, stromal and other epithelial cancers. Expression levels of specific genes were validated through comparison to protein expression by immunohistochemistry using cell block arrays. We found sets of genes whose expression corresponds to the molecular signature of each cell type. In the gastric cancer cell lines, apart from genes that are highly expressed corresponding to their common epithelial origin from the gastrointestinal tract, we found marked heterogeneity among the gene expression patterns of these cell lines. Some of the heterogeneity may reflect their underlying molecular characteristics or specific differentiation program. Two putative gastric carcinoma cell lines were found to be B-cell lymphoma, and another one had no epithelial specific gene expression and hence was of doubtful epithelial origin. These cell lines should no longer be used in gastric carcinoma research. In conclusion, our gene expression database can serve as a powerful resource for the study of gastric cancer using these cell lines Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Using regression correlation
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unknown experiment type 
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Citation
Comprehensive analysis of the gene expression profiles in human gastric cancer cell lines. Ji J, Chen X, Leung SY, Chi JT, Chu KM, Yuen ST, Li R, Chan AS, Li J, Dunphy N, So S.
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