Article

A Step Toward Optimization of Cancer Therapeutics [Chronobiological Investigations]

Inst. Nat. de Recherche en Inf. et en Autom., Rocquencourt
IEEE Engineering in Medicine and Biology Magazine (Impact Factor: 26.3). 02/2008; DOI: 10.1109/MEMB.2007.907363
Source: IEEE Xplore

ABSTRACT An integrative physiology model has been designed, which takes into account the cell proliferation at the level of a population of cells by age-structured partial differential equations (PDEs), its control by cell cycle proteins, and the control of these molecular mechanisms by the circadian system, designed as a network of coupled oscillators also described by ODEs. Cancer growth and response to therapy by anticancer drugs have been shown to be dependent on circadian clock inputs. This multiscale modeling framework will provide clinicians with a theoretical tool to bridge the gap between the pharmaceutical clinical control level and the molecular pharmacological hidden level of drug action.

0 Followers
 · 
101 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: The therapeutic control of a solid tumour depends critically on the responses of the individual cells that constitute the entire tumour mass. A particular cell's spatial location within the tumour and intracellular interactions, including the evolution of the cell-cycle within each cell, has an impact on their decision to grow and divide. They are also influenced by external signals from other cells as well as oxygen and nutrient concentrations. Hence, it is important to take these into account when modelling tumour growth and the response to various treatment regimes ('cell-kill therapies'), including chemotherapy. In order to address this multiscale nature of solid tumour growth and its response to treatment, we propose a hybrid, individual-based approach that analyses spatio-temporal dynamics at the level of cells, linking individual cell behaviour with the macroscopic behaviour of cell organisation and the microenvironment. The individual tumour cells are modelled by using a cellular automaton (CA) approach, where each cell has its own internal cell-cycle, modelled using a system of ODEs. The internal cell-cycle dynamics determine the growth strategy in the CA model, making it more predictive and biologically relevant. It also helps to classify the cells according to their cell-cycle states and to analyse the effect of various cell-cycle dependent cytotoxic drugs. Moreover, we have incorporated the evolution of oxygen dynamics within this hybrid model in order to study the effects of the microenvironment in cell-cycle regulation and tumour treatments. An important factor from the treatment point of view is that the low concentration of oxygen can result in a hypoxia-induced quiescence (G0/G1 arrest) of the cancer cells, making them resistant to key cytotoxic drugs. Using this multiscale model, we investigate the impact of oxygen heterogeneity on the spatio-temporal patterning of the cell distribution and their cell-cycle status. We demonstrate that oxygen transport limitations result in significant heterogeneity in HIF-1 α signalling and cell-cycle status, and when these are combined with drug transport limitations, the efficacy of the therapy is significantly impaired.
    Journal of Theoretical Biology 05/2012; 308:1-19. DOI:10.1016/j.jtbi.2012.05.015 · 2.30 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: The paper proposes a systematic method for fixed-point bifurcation analysis in circadian cells and similar biological models using interval polynomials theory. The stages for performing fixed-point bifurcation analysis in such biological systems comprise (i) the computation of fixed points as functions of the bifurcation parameter and (ii) the evaluation of the type of stability for each fixed point through the computation of the eigenvalues of the Jacobian matrix that is associated with the system's nonlinear dynamics model. Stage (ii) requires the computation of the roots of the characteristic polynomial of the Jacobian matrix. This problem is nontrivial since the coefficients of the characteristic polynomial are functions of the bifurcation parameter and the latter varies within intervals. To obtain a clear view about the values of the roots of the characteristic polynomial and about the stability features they provide to the system, the use of interval polynomials theory and particularly of Kharitonov's stability theorem is proposed. In this approach, the study of the stability of a characteristic polynomial with coefficients that vary in intervals is equivalent to the study of the stability of four polynomials with crisp coefficients computed from the boundaries of the aforementioned intervals. The efficiency of the proposed approach for the analysis of fixed-point bifurcations in nonlinear models of biological neurons is tested through numerical and simulation experiments.
    Biological Cybernetics 05/2014; 108(3). DOI:10.1007/s00422-014-0605-7 · 1.93 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: We study proliferation in tissues from the point of view of physiologically structured partial differential models, focusing on age synchronisation in the cell division cycle in cell populations and its control at phase transition checkpoints. We show how a recent fluorescence-based technique (FUCCI) performed at the single cell level in proliferating cell populations allows identifying model parameters and how it may be applied to investigate healthy and cancer cell populations. We show how this modelling approach allows designing original optimisation methods for cancer chronotherapeutics, by controlling eigenvalues of differential operators underlying proliferation dynamics, in tumour and in healthy cell populations.
    Proceedings of ICNAAM 2011, Kallithea Chalkidis (Greece); 01/2011

Full-text (2 Sources)

Download
36 Downloads
Available from
Jun 6, 2014