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.
Keywords: Breast cancer, microarray, MYBL1, self-organizing map, TNBC, Wnt.
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