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Published in: Journal of Applied Mathematics and Computing 1-2/2020

04-10-2019 | Original Research

Mathematical modeling and dynamic analysis of anti-tumor immune response

Authors: Liuyong Pang, Sanhong Liu, Xinan Zhang, Tianhai Tian

Published in: Journal of Applied Mathematics and Computing | Issue 1-2/2020

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Abstract

The competitive interaction of tumor-immune system is very complex. We aim to establish a simple and realistic mathematical model to understand the key factors that impact the outcome of an antitumor response. Based on the principle that lymphocytes undergo two stages of development (namely immature and mature), we develop a new anti-tumor-immune response model and investigate its property and bifurcation. The corresponding sufficient criteria for the asymptotic stabilities of equilibria and the existence of stable periodic oscillations of tumor levels are obtained. Theoretical results indicate that the system orderly undergoes different states with the flow rate of mature immune cells increasing, from the unlimited expansion of tumor, to the stable large tumor-present equilibrium, to the periodic oscillation, to the stable small tumor-present equilibrium, and finally to the stable tumor-free equilibrium, which exhibits a variety of dynamic behaviors. In addition, these dynamic behaviors are in accordance with some phenomena observed clinically, such as tumor dormant, tumor periodic oscillation, immune escape of tumor and so on. Numerical simulations are carried out to verify the results of our theoretical analysis.

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Literature
2.
go back to reference Chen, W., Zheng, R., Baade, P., et al.: Cancer statistics in China, 2015. CA Cancer J. Clin. 66, 115–132 (2016)CrossRef Chen, W., Zheng, R., Baade, P., et al.: Cancer statistics in China, 2015. CA Cancer J. Clin. 66, 115–132 (2016)CrossRef
3.
go back to reference Parish, C.: Cancer immunotherapy: the past, the present and the future. Immunol. Cell Biol. 81, 106–113 (2003)CrossRef Parish, C.: Cancer immunotherapy: the past, the present and the future. Immunol. Cell Biol. 81, 106–113 (2003)CrossRef
4.
go back to reference Smyth, M., Godfrey, D.: A fresh look at tumor immunosurveillance and immunotherapy. Nat. Immunol. 2, 293–299 (2001)CrossRef Smyth, M., Godfrey, D.: A fresh look at tumor immunosurveillance and immunotherapy. Nat. Immunol. 2, 293–299 (2001)CrossRef
5.
go back to reference Galach, M.: Dynamics of the tumor-immune system competition-the effect of time delay. Int. J. Appl. Math. Comput. Sci. 13, 395–406 (2003)MathSciNetMATH Galach, M.: Dynamics of the tumor-immune system competition-the effect of time delay. Int. J. Appl. Math. Comput. Sci. 13, 395–406 (2003)MathSciNetMATH
6.
go back to reference Raluca, E., Bramson, J., Earn, D.: Interactions between the immune system and cancer: a brief review of non-spatial mathematical models. Bull. Math. Biol. 73, 2–23 (2011)MathSciNetCrossRef Raluca, E., Bramson, J., Earn, D.: Interactions between the immune system and cancer: a brief review of non-spatial mathematical models. Bull. Math. Biol. 73, 2–23 (2011)MathSciNetCrossRef
7.
go back to reference Rosenberg, S., Yang, J., Restifo, N.: Cancer immunotherapy: moving beyond current vaccines. Nat. Med. 10, 909–915 (2004)CrossRef Rosenberg, S., Yang, J., Restifo, N.: Cancer immunotherapy: moving beyond current vaccines. Nat. Med. 10, 909–915 (2004)CrossRef
8.
go back to reference Riddell, S.: Progress in cancer vaccines by enhanced self-presentation. Proc. Natl. Acad. Sci. USA 98, 8933–8935 (2001)CrossRef Riddell, S.: Progress in cancer vaccines by enhanced self-presentation. Proc. Natl. Acad. Sci. USA 98, 8933–8935 (2001)CrossRef
9.
go back to reference Hirayama, M., Nishimur, Y.: The present status and future prospects of peptide-based cancer vaccines. Int. Immunol. 28, 319–328 (2016)CrossRef Hirayama, M., Nishimur, Y.: The present status and future prospects of peptide-based cancer vaccines. Int. Immunol. 28, 319–328 (2016)CrossRef
10.
go back to reference Scott, A., Wolchok, J.: Antibody therapy of cancer. Nat. Rev. 12, 278–287 (2012)CrossRef Scott, A., Wolchok, J.: Antibody therapy of cancer. Nat. Rev. 12, 278–287 (2012)CrossRef
11.
go back to reference Pincetic, A., Bournazos, S., DiLillo, D., et al.: Type I and type II Fc receptors regulate innate and adaptive immunity. Nat. Immunol. 15, 707–16 (2014)CrossRef Pincetic, A., Bournazos, S., DiLillo, D., et al.: Type I and type II Fc receptors regulate innate and adaptive immunity. Nat. Immunol. 15, 707–16 (2014)CrossRef
12.
go back to reference Weiner, L., Surana, R., Wang, S.: Monoclonal antibodies: versatile platforms for cancer immunotherapy. Nat. Rev. 10, 317–27 (2010) Weiner, L., Surana, R., Wang, S.: Monoclonal antibodies: versatile platforms for cancer immunotherapy. Nat. Rev. 10, 317–27 (2010)
13.
go back to reference Adam, J., Bellomo, T.: Survey of models for tumor-immune system dynamics. Birkhauser, Boston (1997)CrossRef Adam, J., Bellomo, T.: Survey of models for tumor-immune system dynamics. Birkhauser, Boston (1997)CrossRef
14.
go back to reference Chaplain, M., Matzavions, A.: Mathematical modeling of spation-temporal phenomena in tumor immunology. Tutor. Math. Biosci. 3, 131–183 (2006)CrossRef Chaplain, M., Matzavions, A.: Mathematical modeling of spation-temporal phenomena in tumor immunology. Tutor. Math. Biosci. 3, 131–183 (2006)CrossRef
15.
go back to reference Kirschner, D., Panetta, J.: Modeling immunotherapy of the tumor-immune interaction. J. Math. Biol. 37, 235–252 (1998)CrossRef Kirschner, D., Panetta, J.: Modeling immunotherapy of the tumor-immune interaction. J. Math. Biol. 37, 235–252 (1998)CrossRef
16.
go back to reference Mallet, D., Pillis, L.: A cellular automata model of tumor-immune system interactions. J. Theor. Biol. 239, 334–350 (2006)MathSciNetCrossRef Mallet, D., Pillis, L.: A cellular automata model of tumor-immune system interactions. J. Theor. Biol. 239, 334–350 (2006)MathSciNetCrossRef
17.
go back to reference d’Onofrio, A.: A general framework for modeling tumor-immune system competition and immunotherapy: mathematical analysis and biomedical inferences. Physica D 208, 220–235 (2005)MathSciNetCrossRef d’Onofrio, A.: A general framework for modeling tumor-immune system competition and immunotherapy: mathematical analysis and biomedical inferences. Physica D 208, 220–235 (2005)MathSciNetCrossRef
18.
go back to reference Kirschner, D., Tsygvintsev, A.: On the global dynamics of a model for tumor immunotherapy. Math. Biosci. Eng. 6, 573–583 (2009)MathSciNetCrossRef Kirschner, D., Tsygvintsev, A.: On the global dynamics of a model for tumor immunotherapy. Math. Biosci. Eng. 6, 573–583 (2009)MathSciNetCrossRef
19.
go back to reference Pang, L., Zhao, Z., Hong, S.: Dynamic analysis of an antitumor model and investigation of the therapeutic effects for different treatment regimens. Comput. Appl. Math. 36, 537–560 (2017)MathSciNetCrossRef Pang, L., Zhao, Z., Hong, S.: Dynamic analysis of an antitumor model and investigation of the therapeutic effects for different treatment regimens. Comput. Appl. Math. 36, 537–560 (2017)MathSciNetCrossRef
20.
go back to reference Lejeune, O., Chaplain, M., Akili, I.: Oscillations and bistability in the dynamics of cytotoxic reactions medicated by the response of immune cells to solid tumours. Math. Comput. Model. 47, 649–662 (2008)CrossRef Lejeune, O., Chaplain, M., Akili, I.: Oscillations and bistability in the dynamics of cytotoxic reactions medicated by the response of immune cells to solid tumours. Math. Comput. Model. 47, 649–662 (2008)CrossRef
21.
go back to reference Pang, L., Zhao, Z., Song, X.: Cost-effectiveness analysis of optimal strategy for tumor treatment. Chaos Solitions Fractals 87, 293–301 (2016)MathSciNetCrossRef Pang, L., Zhao, Z., Song, X.: Cost-effectiveness analysis of optimal strategy for tumor treatment. Chaos Solitions Fractals 87, 293–301 (2016)MathSciNetCrossRef
22.
go back to reference Pang, L., Shen, L., Zhao, Z.: Mathematical modeling and analysis of the tumor treatment regimens with pulsed immunotherapy and chemotherapy. Comput. Math. Methods Med. 2016, 1–12 (2016)CrossRef Pang, L., Shen, L., Zhao, Z.: Mathematical modeling and analysis of the tumor treatment regimens with pulsed immunotherapy and chemotherapy. Comput. Math. Methods Med. 2016, 1–12 (2016)CrossRef
23.
go back to reference Kuznetsov, V.A., Zhivoglyadov, V.P., Stepanova, L.A.: Kinetic approach and estimation of parameters of cellular interaction between immunity system and a tumor. Arch. Immunol. Ther. Exp. 2, 465–476 (1992) Kuznetsov, V.A., Zhivoglyadov, V.P., Stepanova, L.A.: Kinetic approach and estimation of parameters of cellular interaction between immunity system and a tumor. Arch. Immunol. Ther. Exp. 2, 465–476 (1992)
24.
go back to reference Bell, G.I.: Predator–prey equations simulating an immune response. Math. Biosci. 16, 291–314 (1973)CrossRef Bell, G.I.: Predator–prey equations simulating an immune response. Math. Biosci. 16, 291–314 (1973)CrossRef
25.
go back to reference Kuznetsov, V.A., Makalkin, L.A., Talor, M.A., perelson, A.S.: Nonlinear dynamics of immunogenic tumors: parameter estimation and global bifurcation analysis. Bull. Math. Biol. 56, 295–321 (1994)CrossRef Kuznetsov, V.A., Makalkin, L.A., Talor, M.A., perelson, A.S.: Nonlinear dynamics of immunogenic tumors: parameter estimation and global bifurcation analysis. Bull. Math. Biol. 56, 295–321 (1994)CrossRef
26.
go back to reference de Pillis, L.G., Radunskaya, A.E., Wiseman, C.L.: A validated mathematical model of cell-mediated immune response to tumor growth. Cancer Res. 65, 7950–7958 (2005)CrossRef de Pillis, L.G., Radunskaya, A.E., Wiseman, C.L.: A validated mathematical model of cell-mediated immune response to tumor growth. Cancer Res. 65, 7950–7958 (2005)CrossRef
27.
go back to reference de Pillis, L.G., Radunskaya, A.: A mathematical tumor model with immune resistance and drug therapy : an optimal control approach. J. Theor. Med. 3, 79–100 (2000)CrossRef de Pillis, L.G., Radunskaya, A.: A mathematical tumor model with immune resistance and drug therapy : an optimal control approach. J. Theor. Med. 3, 79–100 (2000)CrossRef
28.
go back to reference de Pillis, L.G., Fister, K.Renee, et al.: Mathematical model creation for cancer chemo-immuntherapy. Comput. Math. Methods Med. 10, 165–184 (2009)MathSciNetCrossRef de Pillis, L.G., Fister, K.Renee, et al.: Mathematical model creation for cancer chemo-immuntherapy. Comput. Math. Methods Med. 10, 165–184 (2009)MathSciNetCrossRef
29.
go back to reference Liu, D., Ruan, S., Zhu, D.: Stable periodic oscillations in a two-stage cancer model of tumor and immune system interactions. Math. Biosci. Eng. 9, 347–368 (2012)MathSciNetCrossRef Liu, D., Ruan, S., Zhu, D.: Stable periodic oscillations in a two-stage cancer model of tumor and immune system interactions. Math. Biosci. Eng. 9, 347–368 (2012)MathSciNetCrossRef
30.
go back to reference DeLisi, C., Rescigno, A.: Immune surveillance and neoplasia-I: a minimal mathematical model. Bull. Math. Biol. 39, 201–221 (1977)MathSciNetMATH DeLisi, C., Rescigno, A.: Immune surveillance and neoplasia-I: a minimal mathematical model. Bull. Math. Biol. 39, 201–221 (1977)MathSciNetMATH
31.
go back to reference Skipper, H., Schabel, F.: Quantitative and cytokinetic studies in experimental tumor systems. Cancer Med. 2, 636–648 (1982) Skipper, H., Schabel, F.: Quantitative and cytokinetic studies in experimental tumor systems. Cancer Med. 2, 636–648 (1982)
32.
go back to reference Roitt, I., Brostoff, J., Male, D.: Immunology. Mosby, St. Louis (1993) Roitt, I., Brostoff, J., Male, D.: Immunology. Mosby, St. Louis (1993)
33.
go back to reference Shilnikov, L., Shilnikov, A., Turaev, D., Chua, L.: Methods of Qualitative Theory in Nonlinear Dynamics, Part 1. World Scientific Publishing Co. Pte. Ltd., Singapore (1998)CrossRef Shilnikov, L., Shilnikov, A., Turaev, D., Chua, L.: Methods of Qualitative Theory in Nonlinear Dynamics, Part 1. World Scientific Publishing Co. Pte. Ltd., Singapore (1998)CrossRef
34.
35.
go back to reference Hassard, B., Kazarinoff, N., Wan, Y.: Theory and Applications of Hopf Bifurcation. Cambridge University Press, Cambridge (1981)MATH Hassard, B., Kazarinoff, N., Wan, Y.: Theory and Applications of Hopf Bifurcation. Cambridge University Press, Cambridge (1981)MATH
36.
go back to reference Kumar, S., Srivastava, S., Chingakham, P.: Hopf bifurcation and stability analysis in a harvested one-predator–two-prey model. Appl. Math. Comput. 129, 107–118 (2002)MathSciNetMATH Kumar, S., Srivastava, S., Chingakham, P.: Hopf bifurcation and stability analysis in a harvested one-predator–two-prey model. Appl. Math. Comput. 129, 107–118 (2002)MathSciNetMATH
37.
go back to reference Allison, E., Coltobetal, A.: A mathematical model of the effector cell response to cancer. Math. Comput. Model. 39, 1313–1327 (2004)MathSciNetCrossRef Allison, E., Coltobetal, A.: A mathematical model of the effector cell response to cancer. Math. Comput. Model. 39, 1313–1327 (2004)MathSciNetCrossRef
Metadata
Title
Mathematical modeling and dynamic analysis of anti-tumor immune response
Authors
Liuyong Pang
Sanhong Liu
Xinan Zhang
Tianhai Tian
Publication date
04-10-2019
Publisher
Springer Berlin Heidelberg
Published in
Journal of Applied Mathematics and Computing / Issue 1-2/2020
Print ISSN: 1598-5865
Electronic ISSN: 1865-2085
DOI
https://doi.org/10.1007/s12190-019-01292-9

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