Identification of novel targets for breast cancer by exploring gene switches on a genome scale

Ming Wu, Li Liu, Christina Chan

    Research output: Contribution to journalArticle

    • 14 Citations

    Abstract

    Background: An important feature that emerges from analyzing gene regulatory networks is the "switch-like behavior" or "bistability", a dynamic feature of a particular gene to preferentially toggle between two steady-states. The state of gene switches plays pivotal roles in cell fate decision, but identifying switches has been difficult. Therefore a challenge confronting the field is to be able to systematically identify gene switches.Results: We propose a top-down mining approach to exploring gene switches on a genome-scale level. Theoretical analysis, proof-of-concept examples, and experimental studies demonstrate the ability of our mining approach to identify bistable genes by sampling across a variety of different conditions. Applying the approach to human breast cancer data identified genes that show bimodality within the cancer samples, such as estrogen receptor (ER) and ERBB2, as well as genes that show bimodality between cancer and non-cancer samples, where tumor-associated calcium signal transducer 2 (TACSTD2) is uncovered. We further suggest a likely transcription factor that regulates TACSTD2.Conclusions: Our mining approach demonstrates that one can capitalize on genome-wide expression profiling to capture dynamic properties of a complex network. To the best of our knowledge, this is the first attempt in applying mining approaches to explore gene switches on a genome-scale, and the identification of TACSTD2 demonstrates that single cell-level bistability can be predicted from microarray data. Experimental confirmation of the computational results suggest TACSTD2 could be a potential biomarker and attractive candidate for drug therapy against both ER+ and ER- subtypes of breast cancer, including the triple negative subtype.

    Original languageEnglish (US)
    Article number547
    JournalBMC Genomics
    Volume12
    DOIs
    StatePublished - Nov 3 2011

    Profile

    Neoplasm Genes
    Genome
    Breast Neoplasms
    Neoplasms
    Switch Genes
    Transducers
    Calcium
    Genes
    Estrogen Receptors
    Triple Negative Breast Neoplasms
    Gene Regulatory Networks
    Transcription Factors
    Biological Markers
    Drug Therapy

    ASJC Scopus subject areas

    • Biotechnology
    • Genetics

    Cite this

    Identification of novel targets for breast cancer by exploring gene switches on a genome scale. / Wu, Ming; Liu, Li; Chan, Christina.

    In: BMC Genomics, Vol. 12, 547, 03.11.2011.

    Research output: Contribution to journalArticle

    Wu, Ming; Liu, Li; Chan, Christina / Identification of novel targets for breast cancer by exploring gene switches on a genome scale.

    In: BMC Genomics, Vol. 12, 547, 03.11.2011.

    Research output: Contribution to journalArticle

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