Spherical self-organizing map detects MYBL 1 as candidate gene for triple-negative breast cancer

Masashi Ikeda, Kazuki Kumon, Kazuya Omoto, Yuh Sugii, Akifumi Mizutani, Arun Vaidyanath, Takayuki Kudoh, Tomonari Kasai, Shinobu Masuda, Masaharu Seno

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Background: Discovering mechanism of pathogenesis, growth or metastasis of triplenegative breast cancer (TNBC) is necessary to establish future therapy. An effective analysis is required for microarray information to identify genes highly involved to a disease phenotype from thousands of genes. Methods: We have applied self-organizing map, a clustering method that could simplify complex high-dimensional data as concise low-dimensional and graphical maps, for analysis of large amounts of microarray data. In this study, similarities of expression data of the genes expressing in breast cancer were visually represented by spherical self-organizing map (sSOM). Results: sSOM presented transcription factor MYBL1 as an inversely-related gene to estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2) associating itself to subtypes of breast cancer. MYBL1 correlated to cell growth related genes including Wnt/β-catenin signal or cancer stem cell-associated gene CD44, implying its involvement in the growth of TNBC. Conclusion: sSOM showed transcription factor MYBL1 has negatively related to expression pattern to ER/HER2 and associates itself with other cell growth related genes in breast cancer.

Original languageEnglish
Pages (from-to)94-101
Number of pages8
JournalNeuroscience and Biomedical Engineering
Issue number2
Publication statusPublished - Dec 1 2015


  • Breast cancer
  • MYBL1
  • Microarray
  • Self-organizing map
  • TNBC
  • Wnt

ASJC Scopus subject areas

  • Neuroscience (miscellaneous)
  • Bioengineering
  • Biomedical Engineering


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