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Meta-Analysis of Tumor Stem-Like Breast Cancer Cells Using Gene Set and Network Analysis

Author

Listed:
  • Won Jun Lee
  • Sang Cheol Kim
  • Jung-Ho Yoon
  • Sang Jun Yoon
  • Johan Lim
  • You-Sun Kim
  • Sung Won Kwon
  • Jeong Hill Park

Abstract

Generally, cancer stem cells have epithelial-to-mesenchymal-transition characteristics and other aggressive properties that cause metastasis. However, there have been no confident markers for the identification of cancer stem cells and comparative methods examining adherent and sphere cells are widely used to investigate mechanism underlying cancer stem cells, because sphere cells have been known to maintain cancer stem cell characteristics. In this study, we conducted a meta-analysis that combined gene expression profiles from several studies that utilized tumorsphere technology to investigate tumor stem-like breast cancer cells. We used our own gene expression profiles along with the three different gene expression profiles from the Gene Expression Omnibus, which we combined using the ComBat method, and obtained significant gene sets using the gene set analysis of our datasets and the combined dataset. This experiment focused on four gene sets such as cytokine-cytokine receptor interaction that demonstrated significance in both datasets. Our observations demonstrated that among the genes of four significant gene sets, six genes were consistently up-regulated and satisfied the p-value of

Suggested Citation

  • Won Jun Lee & Sang Cheol Kim & Jung-Ho Yoon & Sang Jun Yoon & Johan Lim & You-Sun Kim & Sung Won Kwon & Jeong Hill Park, 2016. "Meta-Analysis of Tumor Stem-Like Breast Cancer Cells Using Gene Set and Network Analysis," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-20, February.
    • Handle: RePEc:plo:pone00:0148818
    DOI: 10.1371/journal.pone.0148818
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