Literature DB >> 17978572

Meta- and gene set analysis of stomach cancer gene expression data.

Seon-Young Kim1, Jeong-Hwan Kim, Heun-Sik Lee, Seung-Moo Noh, Kyu-Sang Song, June-Sik Cho, Hyun-Yong Jeong, Woo Ho Kim, Young-Il Yeom, Nam-Soon Kim, Sangsoo Kim, Hyang-Sook Yoo, Yong Sung Kim.   

Abstract

We generated gene expression data from the tissues of 50 gastric cancer patients, and applied meta-analysis and gene set analysis to this data and three other stomach cancer gene expression data sets to define the gene expression changes in gastric tumors. By meta-analysis we identified genes consistently changed in gastric carcinomas, while gene set analysis revealed consistently changed biological themes. Genes and gene sets involved in digestion, fatty acid metabolism, and ion transport were consistently down-regulated in gastric carcinomas, while those involved in cellular proliferation, cell cycle, and DNA replication were consistently up-regulated. We also found significant differences between the genes and gene sets expressed in diffuse and intestinal type gastric carcinoma. By gene set analysis of cytogenetic bands, we identified many chromosomal regions with possible gross chromosomal changes (amplifications or deletions). Similar analysis of transcription factor binding sites (TFBSs), revealed transcription factors that may have caused the observed gene expression changes in gastric carcinomas, and we confirmed the overexpression of one of these, E2F1, in many gastric carcinomas by tissue array and immunohistochemistry. We have incorporated the results of our meta- and gene set analyses into a web accessible database (http://human-genome.kribb.re.kr/stomach/).

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Year:  2007        PMID: 17978572

Source DB:  PubMed          Journal:  Mol Cells        ISSN: 1016-8478            Impact factor:   5.034


  10 in total

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Review 7.  Key issues in conducting a meta-analysis of gene expression microarray datasets.

Authors:  Adaikalavan Ramasamy; Adrian Mondry; Chris C Holmes; Douglas G Altman
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Journal:  J Cancer       Date:  2020-01-01       Impact factor: 4.207

  10 in total

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