MBI Publications

MBI Publications for Clay Marsh (6)

  • B. Szomolay, T. Eubank, R. Roberts, C. Marsh and A. Friedman
    Modeling Inhibition of breast cancer growth by GM-CSF: A mathematical model
    Bulletin of Mathematical Biology (2008) (Submitted)

    Abstract

  • B. Aguda, Y. Kim, M. Piper-Hunter, A. Friedman and C. Marsh
    MicroRNA Regulation of a Cancer Network: Consequences of the Feedback Loops Involving miR-17-92, E2F, and Myc
    PNASVol. 105 No. 50 (2008) pp. 19678-19683

    Abstract

  • B. Aguda, Y. Kim, M. Piper-Hunter, A. Friedman and C. Marsh
    MicroRNA Regulation of a Cancer Network: Consequences of the Feedback Loops Involving miR-17-92, E2F, and Myc
    PNASVol. 105 No. 50 (2008) pp. 19678-19683

    Abstract

    The transcription factors E2F and Myc participate in the control of cell proliferation and apoptosis, and can act as oncogenes or tumor suppressors depending on their levels of expression. Positive feedback loops in the regulation of these factors are predicted-and recently shown experimentally-to lead to bistability, which is a phenomenon characterized by the existence of low and high protein levels ("off" and "on" levels, respectively), with sharp transitions between levels being inducible by, for example, changes in growth factor concentrations. E2F and Myc are inhibited at the posttranscriptional step by members of a cluster of microRNAs (miRs) called miR-17-92. In return, E2F and Myc induce the transcription of miR-17-92, thus forming a negative feedback loop in the interaction network. The consequences of the coupling between the E2F/Myc positive feedback loops and the E2F/Myc/miR-17-92 negative feedback loop are analyzed using a mathematical model. The model predicts that miR-17-92 plays a critical role in regulating the position of the off-on switch in E2F/Myc protein levels, and in determining the on levels of these proteins. The model also predicts large-amplitude protein oscillations that coexist with the off steady state levels. Using the concept and model prediction of a "cancer zone," the oncogenic and tumor suppressor properties of miR-17-92 is demonstrated to parallel the same properties of E2F and Myc.
  • B. Szomolay, T. Eubank, R. Roberts, C. Marsh and A. Friedman
    Modeling inhibition of breast cancer growth by GM-CSF
    J. of Theor. Biol. (2012) (Accepted)

    Abstract

  • D. Chen, J. Roda, C. Marsh, T. Eubank and A. Friedman
    Hypoxia Inducible Factors-mediated inhibition of cancer by GM-CSF: A mathematical model
    (2012) (Under Review)

    Abstract

  • D. Chen, J. Roda, C. Marsh, T. Eubank and A. Friedman
    Hypoxia inducible factors mediated-inhibition of cancer by GM-CSF: A mathematical model
    Bulletin of Mathematical Biology (2012)

    Abstract

    Under hypoxia, tumor cells, and tumor-associated macrophages produce VEGF (vascular endothelial growth factor), a signaling molecule that induces angiogenesis. The same macrophages, when treated with GM-CSF (granulocyte/macrophage colony-stimulating factor), produce sVEGFR-1 (soluble VEGF receptor-1), a soluble protein that binds with VEGF and inactivates its function. The production of VEGF by macrophages is regulated by HIF-1α (hypoxia inducible factor-1α), and the production of sVEGFR-1 is mediated by HIF-2α. Recent experiments measured the effect of inhibiting tumor growth by GM-CSF treatment in mice with HIF-1α-de?cient or HIF-2α-de?cient macrophages. In the present paper, we represent these experiments by a mathematical model based on a system of partial differential equations. We show that the model simulations agree with the above experiments. The model can then be used to suggest strategies for inhibiting tumor growth. For example, the model qualitatively predicts the extent to which GM-CSF treatment in combination with a small molecule inhibitor that stabilizes HIF-2α will reduce tumor volume and angiogenesis.

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