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Antagonism and negative side-effects in combination therapy for cancer

The first author is supported by the Mathematical Biosciences Institute and the National Science Foundation under Grant DMS 0931642

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  • Most clinical trials with combination therapy fail. One of the reasons is that not enough forethought is given to the interaction between the different agents, as well as the potential negative side-effects that may arise in the combined therapy. In the present paper we consider a generic cancer model with combination therapy consisting of chemotherapy agent $ X $ and checkpoint inhibitor $ A $. We use a mathematical model to investigate the results of injecting different amounts $ \gamma_X $ of $ X $ and $ \gamma_A $ of $ A $. We show that there are some regions in the $ (\gamma_A,\gamma_X) $-plane where as increase in $ \gamma_X $ or $ \gamma_A $ actually decreases the tumor volume; such 'regions of antagonism' should be avoided in clinical trials. We also show how to achieve the same level of tumor volume reduction with least negative-side effects, where the side-effects are represented by the level of inflammation of the tumor microenvironment.

    Mathematics Subject Classification: Primary: 35R35, 35Q92, 92C50; Secondary: 35R37, 35K55, 92B05.


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  • Figure 1.  Interaction of immune cells with cancer cells. Sharp arrows indicate proliferation/activation, blocked arrow indicates killing/blocking, inverted sharp arrow indicates recruitment/chemoattraction. $ C $: cancer cells, $ T $: effector T cells

    Figure 2.  Average densities/concentrations, in $ {\rm g}/{\rm cm}^3 $, of all the variables of the model in control case (no drugs). All parameter values are the same as in Tables 2 and 3, for a mouse model

    Figure 3.  Growth of tumor volume under treatment with $ \gamma_X $ or $ \gamma_A $, or combination ($ \gamma_X,\gamma_A $). The chemotherapy or/and anti-PD-1 treatments. (a) $ \gamma_X = 5\times 10^{-13} $ $ {\rm g}/{\rm cm}^3\cdot {\rm day} $, $ \gamma_A = 2\times 10^{-11} $ $ {\rm g}/{\rm cm}^3\cdot {\rm day} $; (b) $ \gamma_X = 3\times 10^{-13} $ $ {\rm g}/{\rm cm}^3\cdot {\rm day} $, $ \gamma_A = 5\times 10^{-11} $ $ {\rm g}/{\rm cm}^3\cdot {\rm day} $. All other parameter values are the same as in Tables 2 and 3, for a mouse model

    Figure 4.  Efficacy of combination therapy at day 30 for different pair of $ (\gamma_X, \gamma_A) $. Here (a) $ \gamma_X = 0 - 2\times 10^{-12} $ $ {\rm g}/{\rm cm}^3 $ and $ \gamma_A = 0 - 1.8\times 10^{-10} $ $ {\rm g}/{\rm cm}^3 $. (b) $ \gamma_X = 0.9\times 10^{-12} - 2\times 10^{-12} $ $ {\rm g}/{\rm cm}^3 $ and $ \gamma_A = 1\times 10^{-10} - 1.8\times 10^{-10} $ $ {\rm g}/{\rm cm}^3 $. All other parameter values are the same as in Tables 2 and 3

    Figure 5.  Average T cell density at day 30 for different pair of $ (\gamma_X, \gamma_A) $. Here $ \gamma_X = 0 - 2\times 10^{-12} $ $ {\rm g}/{\rm cm}^3 $ and $ \gamma_A = 0 - 1.8\times 10^{-10} $ $ {\rm g}/{\rm cm}^3 $. All other parameter values are the same as in Tables 2 and 3

    Figure 6.  Average concentration of TNF-$ \alpha $ at day 30 for different pair of $ (\gamma_X, \gamma_A) $. Here $ \gamma_X = 0 - 2\times 10^{-12} $ $ {\rm g}/{\rm cm}^3 $ and $ \gamma_A = 0 - 1.8\times 10^{-10} $ $ {\rm g}/{\rm cm}^3 $. All other parameter values are the same as in Tables 2 and 3

    Table 1.  List of variables (in units of g/$ {\rm cm}^3 $)

    Notation Description Notation Description
    $D$ density of DCs $I_{12}$ IL-12 concentration
    $T$ density of effector T cells $M_P$ MCP-1 (CCL2) concentration
    $M_1$ density of proinflammatory macrophages M1 $I_{10}$ IL-10 concentration
    $M_2$ density of anti-proinflammatory macrophages M2 $T_\beta$ TGF- $\beta$ : concentration
    $C$ density of cancer cells $P$ PD-1 concentration
    $A$ concentration of anti-PD-1 $L$ PD-L1 concentration
    $X$ concentration of a chemotherapy agent $Q$ PD-1-PD-L1 concentration
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    Table 2.  Summary of parameter values

    NotationDescriptionValue usedReferences
    $\delta_D$ diffusion coefficient of DCs $8.64 \times 10^{-7}$ ${\rm cm}^2$ ${\rm day}^{-1}$ [8]
    $\delta_T$ diffusion coefficient of T cells $8.64\times 10^{-7}$ ${\rm cm}^2$ ${\rm day}^{-1}$ [8]
    $\delta_M$ diffusion coefficient of macrophages $8.64\times 10^{-7}$ ${\rm cm}^2$ ${\rm day}^{-1}$ [8]
    $\delta_C$ diffusion coefficient of tumor cells $8.64\times 10^{-7}$ ${\rm cm}^2$ ${\rm day}^{-1}$ [8]
    $\delta_{I_{12}}$ diffusion coefficient of IL-12 $6.05\times 10^{-2}$ ${\rm cm}^2$ ${\rm day}^{-1}$ [16]
    $\delta_{T_{\beta}}$ diffusion coefficient of TGF-$\beta$ $8.52\times 10^{-2}$ ${\rm cm}^2$ ${\rm day}^{-1}$ [16]
    $\delta_{I_{10}}$ diffusion coefficient of IL-10 $9.11\times 10^{-2}$ ${\rm cm}^2$ ${\rm day}^{-1}$ [16]
    $\delta_{T_\alpha}$ diffusion coefficient of TNF-$\alpha$ $8.46\times 10^{-2}$ ${\rm cm}^2$ ${\rm day}^{-1}$ [16]
    $\delta_{M_P}$ diffusion coefficient of MCP-1 $1.12\times 10^{-1}$ ${\rm cm}^2$ ${\rm day}^{-1}$ [16]
    $\delta_A$ diffusion coefficient of anti-PD-1 $4.73\times 10^{-2}$ ${\rm cm}^2$ ${\rm day}^{-1}$ estimated
    $\delta_X$ diffusion coefficient of $X$ $0.27$ ${\rm cm}^2$ ${\rm day}^{-1}$ estimated
    $\sigma_0$ flux rate of $T$ cells at the boundary1 ${\rm cm}^{-1}$ [8]
    $\chi_M$ chemoattraction coefficient of MCP-1 $10$ ${\rm cm}^5/{\rm g}\cdot {\rm day}$ [13,14]
    $\lambda_{DC}$ activation rate of DCs by tumor cells $ 10$ ${\rm g}/{\rm cm}^3\cdot{\rm day}$ [16]
    $\lambda_{TI_{12}}$ activation rate of T cells by IL-12 $16.2$ ${\rm day}^{-1}$ estimated
    $\lambda_{M_1}$ activation rate of M1 macrophages $1.35$ ${\rm day}^{-1}$ [16]
    $\lambda_{M_2}$ activation rate of M2 macrophages $1.01$ ${\rm day}^{-1}$ [16]
    $\beta_{M_1}$ phenotype change rate of M1 to M2 macrophages $0.3$ ${\rm day}^{-1}$ estimated
    $\beta_{M_2}$ phenotype change rate of M2 to M1 macrophages $ 4.68\times 10^{-3}$ ${\rm day}^{-1}$ estimated
    $\lambda_{C}$ growth rate of cancer cells $1.92$ ${\rm day}^{-1}$ estimated
    $\lambda_{I_{12}D}$ production rate of IL-12 by DCs $1.38\times 10^{-6}$ ${\rm day}^{-1}$ [16]
    $\lambda_{I_{12}M_1}$ production rate of IL-12 by M1 macrophages $5.52\times 10^{-6}$ ${\rm day}^{-1}$ [16]
    $\lambda_{T_\beta C}$ production rate of TGF-$\beta$ by cancer cells $2.79\times 10^{-10} $ ${\rm day}^{-1}$ estimated
    $\lambda_{T_\beta M_2}$ production rate of TGF-$\beta$ by M2 macrophages $6.97 \times 10^{-9} $ ${\rm day}^{-1}$ estimated
    $\lambda_{I_{10} C}$ production rate of IL-10 by cancer cells $2.07\times 10^{-8} $ ${\rm day}^{-1}$ [16]
    $\lambda_{I_{10} M_2}$ production rate of IL-10 by M2 macrophages $1.65\times 10^{-9}$ ${\rm day}^{-1}$ [16]
    $\lambda_{T_\alpha M_1}$ production rate of TNF $\alpha$ by M1 macrophages $1.36\times 10^{-5}$ ${\rm day}^{-1}$ [16]
    $\lambda_{T_\alpha T}$ production rate of TNF $\alpha$ by Th1 cells $9.06\times 10^{-8}$ ${\rm day}^{-1}$ estimated
    $\lambda_{M_PM_2}$ production rate of MCP-1 by M2 macrophages $1.2\times 10^{-8} $ ${\rm day}^{-1}$ [16]
    $\lambda_{M_PC}$ production rate of MCP-1 by cancer cells $8.24\times 10^{-7} $ ${\rm day}^{-1}$ [16]
    $d_{D}$ death rate of DCs0.1 ${\rm day}^{-1}$ [8]
    $d_{T}$ death rate of T cells $0.18 $ ${\rm day}^{-1}$ [8]
    $d_{M_1}$ death rate of M1 macrophage $0.015$ ${\rm day}^{-1}$ [9]
    $d_{M_2}$ death rate of M2 macrophage $0.015$ ${\rm day}^{-1}$ [9]
    $d_{C}$ death rate of tumor cells $0.17$ ${\rm day}^{-1}$ [8]
    $d_{I_{12}}$ degradation rate of IL-12 $1.38$ ${\rm day}^{-1}$ [8]
    $d_{T_\beta}$ degradation rate of TGF-$\beta$ $499.066$ ${\rm day}^{-1}$ [16]
    $d_{I_{10}}$ degradation rate of IL-10 $8.3178$ ${\rm day}^{-1}$ [16]
    $d_{T_\alpha}$ degradation rate of TGF-$\alpha$ $55.01$ ${\rm day}^{-1}$ [16]
    $d_{M_P}$ degradation rate of MCP-1 $55.01$ ${\rm day}^{-1}$ [10]
    $d_{A}$ degradation rate of anti-PD-1 $0.047$ ${\rm day}^{-1}$ [16]
    $d_X$ degradation rate of docetexel $1.11$ ${\rm day}^{-1}$ estimated
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    Table 3.  Summary of parameter values

    NotationDescriptionValue usedReferences
    $K_D$half-saturation of dendritic cells $4\times 10^{-4}$ g/${\rm cm}^3$[16]
    $K_{T}$half-saturation of T cells $3\times 10^{-3}$ g/${\rm cm}^3$[16]
    $K_{M_1}$half-saturation of M1 macrophages $10^{-4}$ ${\rm g}/{\rm cm}^3$[16]
    $K_{M_2}$half-saturation of M2 macrophages $3.2\times 10^{-3}$ ${\rm g}/{\rm cm}^3$[16]
    $K_{C}$half-saturation of tumor cells $0.4$ g/${\rm cm}^3$[8]
    $K_{I_{12}}$half-saturation of IL-12 $8\times 10^{-10}$ g/${\rm cm}^3$[16]
    $K_{T_\beta}$half-saturation of TGF-$\beta$ $2.68\times 10^{-13}$ ${\rm g}/{\rm cm}^3$[16]
    $K_{I_{10}}$half-saturation of IL-10 $8.75\times 10^{-11}$ g/${\rm cm}^3$[16]
    $K_{T_\alpha}$half-saturation of TNF-$\alpha$ $3\times 10^{-11}$ g/${\rm cm}^3$[11]
    $K_{M_P}$half-saturation of MCP-1 $2\times 10^{-7}$ ${\rm g}/{\rm cm}^3$[10]
    $K_{X}$half-saturation of $X$ $8.02\times 10^{-11}$ ${\rm g}/{\rm cm}^3$estimated
    $K_{TI_{10}}$inhibition of function of T cells by IL-10 $4.375\times 10^{-11}$ g/${\rm cm}^3$[16]
    $K_{TQ}$inhibition of function of T cells by PD-1-PD-L1 $4.86\times 10^{-20}$ ${\rm g}^2/{\rm cm}^6$estimated
    $K_{CX}$inhibition of proliferation of cancer cells by docetexel $8.02\times 10^{-10}$ ${\rm g}/{\rm cm}^3$estimated
    $D_0$density of inactive DCs $2\times 10^{-5}$ g/${\rm cm}^3$[8]
    $T_{0}$density of naive T cells in tumor $6\times 10^{-4}$ g/${\rm cm}^3$estimated
    $M_{10}$density of monocytes$1.2\times 10^{-4}$ $ {\rm g}/{\rm cm}^3$[16]
    $M_{20}$density of monocytes$3.84\times 10^{-3}$ $ {\rm g}/{\rm cm}^3$[16]
    $C_M$carrying capacity of cancer cells $0.8$ g/${\rm cm}^3$[8]
    $\hat T$density of T cells from lymph node $6\times 10^{-3}$ g/${\rm cm}^3$[16]
    $\eta$killing rate of tumor cells by T cells $210$ $ {\rm cm}^3/{\rm g}\cdot {\rm day}$[16]
    $\mu_{XC}$absorbtion rate of $X$ by cancer cellsestimated
    $\rho_P$expression of PD-1 in T cells $2.49\times 10^{-7} $[15]
    $\rho_L$expression of PD-L1 in T cells $3.25\times 10^{-7} $[15]
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