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Qualitative analysis of kinetic-based models for tumor-immune system interaction

  • * Corresponding author: Maria Groppi

    * Corresponding author: Maria Groppi 
Abstract Full Text(HTML) Figure(9) / Table(1) Related Papers Cited by
  • A mathematical model, based on a mesoscopic approach, describing the competition between tumor cells and immune system in terms of kinetic integro-differential equations is presented. Four interacting components are considered, representing, respectively, tumors cells, cells of the host environment, cells of the immune system, and interleukins, which are capable to modify the tumor-immune system interaction and to contribute to destroy tumor cells. The internal state variable (activity) measures the capability of a cell of prevailing in a binary interaction. Under suitable assumptions, a closed set of autonomous ordinary differential equations is then derived by a moment procedure and two three-dimensional reduced systems are obtained in some partial quasi-steady state approximations. Their qualitative analysis is finally performed, with particular attention to equilibria and their stability, bifurcations, and their meaning. Results are obtained on asymptotically autonomous dynamical systems, and also on the occurrence of a particular backward bifurcation.

    Mathematics Subject Classification: Primary: 37N25; Secondary: 82C40.


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  • Figure 1.  Phase portrait of system (15) for $A>1/X$

    Figure 2.  Comparison of the time evolution of solutions to system (14) and (15) (thickest curves) for $G = 5$ (left) and $G = 50$ (right)

    Figure 3.  Nullcline surfaces of system (15)

    Figure 4.  Comparison between the trajectories of the nonautonomous system (18) (solid curves) and of the limit system (19) (dashed curves) respectively; the dotted line represents the intersection of the tangent plane to the stable manifold in $E_2$ with the plane $Y_3 = 0$, that can be considered an approximation of the right boundary of $R$; the curve $\gamma$ is dash-dotted

    Figure 5.  Solutions for increasing values of D

    Figure 6.  Qualitative bifurcation diagram versus $A$ for $C^*<BG/F+G/(FX)$ : forward bifurcation of equilibria (parameter values used: $B = 1, C^* = 4.5, F = 1, G = 1, X = 1/5$)

    Figure 7.  Qualitative bifurcation diagram versus $A$ for $C^*>BG/F+G/(FX)$ : backward bifurcation of equilibria (parameter values used: $B = 1, C^* = 9, F = 1, G = 1, X = 1/5$)

    Figure 8.  Phase portrait, representative of the case $C^*>BG/F+G/(FX)$ and $A^*<A<1/X$

    Figure 9.  Comparison of the time evolution of solutions to system (14) and (21) (thickest curves) for $D = 1$ (left) and $D = 10$ (right), with $D/E = 1.5$

    Table 1.  Threshold values $D^*$ versus initial data $Y_{10}$

    $Y_{10}$ $0.2$ $0.3$ $0.4$ $0.5$ $0.6$ $0.7$ $0.8$ $1.0$ $2.0$
    $D^*$ $1.43$ $2.7$ $4.08$ $5.52$ $7.02$ $8.54$ $10.1$ $13.26$ $29.67$
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