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PCa dynamics with neuroendocrine differentiation and distributed delay

  • Leo Turner
  • , Andrew Burbanks
  • , Marianna Cerasuolo*
  • *Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    113 Downloads (Pure)

    Abstract

    Prostate cancer is the fifth most common cause of death from cancer, and the second most common diagnosed cancer in men. In the last few years many mathematical models have been proposed to describe the dynamics of prostate cancer under treatment. So far one of the major challenges has been the development of mathematical models that would represent in vivo conditions and therefore be suitable for clinical applications, while being mathematically treatable. In this paper, we take a step in this direction, by proposing a nonlinear distributed-delay dynamical system that explores neuroendocrine transdifferentiation in human prostate cancer in vivo. Sufficient conditions for the existence and the stability of a tumour-present equilibrium are given, and the occurrence of a Hopf bifurcation is proven for a uniform delay distribution. Numerical simulations are provided to explore differences in behaviour for uniform and exponential delay distributions. The results suggest that the choice of the delay distribution is key in defining the dynamics of the system and in determining the conditions for the onset of oscillations following a switch in the stability of the tumour-present equilibrium.
    Original languageEnglish
    Pages (from-to)8577-8602
    Number of pages26
    JournalMathematical Biosciences and Engineering
    Volume18
    Issue number6
    DOIs
    Publication statusPublished - 8 Oct 2021

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Keywords

    • distributed delay
    • prostate cancer
    • androgen deprivation therapy (ADT)
    • dynamical systems
    • stability switches
    • local asymptotic stability

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