Oncogene-tumor suppressor gene feedback interactions and their control

  • Received: 01 September 2014 Accepted: 29 June 2018 Published: 01 August 2015
  • MSC : Primary: 92B05, 92C42; Secondary: 34C23.

  • We propose the hypothesis that for a particular type of cancer there exists a key pair of oncogene (OCG) and tumor suppressor gene (TSG) that is normally involved in strong stabilizing negative feedback loops (nFBLs) of molecular interactions, and it is these interactions that are sufficiently perturbed during cancer development. These nFBLs are thought to regulate oncogenic positive feedback loops (pFBLs) that are often required for the normal cellular functions of oncogenes. Examples given in this paper are the pairs of MYC and p53, KRAS and INK4A, and E2F1 and miR-17-92. We propose dynamical models of the aforementioned OCG-TSG interactions and derive stability conditions of the steady states in terms of strengths of cycles in the qualitative interaction network. Although these conditions are restricted to predictions of local stability, their simple linear expressions in terms of competing nFBLs and pFBLs make them intuitive and practical guides for experimentalists aiming to discover drug targets and stabilize cancer networks.

    Citation: Baltazar D. Aguda, Ricardo C.H. del Rosario, Michael W.Y. Chan. Oncogene-tumor suppressor gene feedback interactions and their control[J]. Mathematical Biosciences and Engineering, 2015, 12(6): 1277-1288. doi: 10.3934/mbe.2015.12.1277

    Related Papers:

  • We propose the hypothesis that for a particular type of cancer there exists a key pair of oncogene (OCG) and tumor suppressor gene (TSG) that is normally involved in strong stabilizing negative feedback loops (nFBLs) of molecular interactions, and it is these interactions that are sufficiently perturbed during cancer development. These nFBLs are thought to regulate oncogenic positive feedback loops (pFBLs) that are often required for the normal cellular functions of oncogenes. Examples given in this paper are the pairs of MYC and p53, KRAS and INK4A, and E2F1 and miR-17-92. We propose dynamical models of the aforementioned OCG-TSG interactions and derive stability conditions of the steady states in terms of strengths of cycles in the qualitative interaction network. Although these conditions are restricted to predictions of local stability, their simple linear expressions in terms of competing nFBLs and pFBLs make them intuitive and practical guides for experimentalists aiming to discover drug targets and stabilize cancer networks.


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