Analytical Study of the Existence of a Hopf Bifurcation in the Tumor Cell Growth Model with Time Delay

A. Yusnaeni, Kasbawati Kasbawati, Toaha Syamsuddin

Abstract


Abstract

In this paper, we study a mathematical model of an immune response system consisting of a number of immune cells that work together to protect the human body from invading tumor cells. The delay differential equation is used to model the immune system caused by a natural delay in the activation process of immune cells. Analytical studies are focused on finding conditions in which the system undergoes changes in stability near a tumor-free steady-state solution. We found that the existence of a tumor-free steady-state solution was warranted when the number of activated effector cells was sufficiently high. By considering the lag of stimulation of helper cell production as the bifurcation parameter, a critical lag is obtained that determines the threshold of the stability change of the tumor-free steady state. It is also leading the system undergoes a Hopf bifurcation to periodic solutions at the tumor-free steady-state solution.

Keywords: tumor–immune system; delay differential equation; transcendental function; Hopf bifurcation.

 

Abstrak

Dalam makalah ini, dikaji model matematika dari sistem respon imun yang terdiri dari sejumlah sel imun yang bekerja sama untuk melindungi tubuh manusia dari invasi sel tumor. Persamaan diferensial tunda digunakan untuk memodelkan sistem kekebalan yang disebabkan oleh keterlambatan alami dalam proses aktivasi sel-sel imun. Studi analitik difokuskan untuk menemukan kondisi di mana sistem mengalami perubahan stabilitas di sekitar solusi kesetimbangan bebas tumor. Diperoleh bahwa solusi kesetimbangan bebas tumor dijamin ada ketika jumlah sel efektor yang diaktifkan cukup tinggi. Dengan mempertimbangkan tundaan stimulasi produksi sel helper sebagai parameter bifurkasi, didapatkan lag kritis yang menentukan ambang batas perubahan stabilitas dari solusi kesetimbangan bebas tumor. Parameter tersebut juga mengakibatkan sistem mengalami percabangan Hopf untuk solusi periodik pada solusi kesetimbangan bebas tumor.

Kata kunci: sistem tumor–imun; persamaan differensial tundaan; fungsi transedental; bifurkasi Hopf.


Keywords


tumor–immune system; delay differential equation; transcendental function; Hopf bifurcation

References


G. M. Cooper and R. E. Hausman, The Cell: A Molecular Approach 2nd Edition. 2007.

Informedhealth.org, “How do cancer cells grow and spread?,” 2013. https://www.ncbi.nlm.nih.gov/books/NBK279410/ (accessed Jul. 24, 2018).

H. Gonzalez, C. Hagerling, and Z. Werb, “Roles of the immune system in cancer: From tumor initiation to metastatic progression,” Genes and Development. 2018, doi: 10.1101/GAD.314617.118.

L. M. E. Janssen, E. E. Ramsay, C. D. Logsdon, and W. W. Overwijk, “The immune system in cancer metastasis: Friend or foe?,” J. Immunother. Cancer, vol. 5, no. 1, pp. 1–14, 2017, doi: 10.1186/s40425-017-0283-9.

B. Alberts, A. Johnson, J. Lewis, and et al, Molecular Biology of the Cell: Studying Gene Expression and Function. 2002.

D. D. Chaplin, “Overview of the immune response,” J. Allergy Clin. Immunol., 2010, doi: 10.1016/j.jaci.2009.12.980.

G. Huang, H. Yokoi, Y. Takeuchi, T. Kajiwara, and T. Sasaki, “Impact of intracellular delay, immune activation delay and nonlinear incidence on viral dynamics,” Jpn. J. Ind. Appl. Math., vol. 28, no. 3, pp. 383–411, 2011, doi: 10.1007/s13160-011-0045-x.

M. Y. Li and H. Shu, “Joint effects of mitosis and intracellular delay on viral dynamics: Two-parameter bifurcation analysis,” J. Math. Biol., 2012, doi: 10.1007/s00285-011-0436-2.

K. A. Pawelek, S. Liu, F. Pahlevani, and L. Rong, “A model of HIV-1 infection with two time delays: Mathematical analysis and comparison with patient data,” Math. Biosci., 2012, doi: 10.1016/j.mbs.2011.11.002.

S. Feyissa and S. Banerjee, “Delay-induced oscillatory dynamics in humoral mediated immune response with two time delays,” Nonlinear Anal. Real World Appl., 2013, doi: 10.1016/j.nonrwa.2012.05.001.

F. A. Rihan, D. H. Abdel Rahman, S. Lakshmanan, and A. S. Alkhajeh, “A time delay model of tumour-immune system interactions: Global dynamics, parameter estimation, sensitivity analysis,” Appl. Math. Comput., 2014, doi: 10.1016/j.amc.2014.01.111.

V. A. Kuznetsov, I. A. Makalkin, M. A. Taylor, and A. S. Perelson, “Nonlinear dynamics of immunogenic tumors: Parameter estimation and global bifurcation analysis,” Bull. Math. Biol., 1994, doi: 10.1007/BF02460644.

Y. Dong, G. Huang, R. Miyazaki, and Y. Takeuchi, “Dynamics in a tumor immune system with time delays,” Appl. Math. Comput., 2015, doi: 10.1016/j.amc.2014.11.096.

M. Ahmadzadeh, S. F. Hussain, and D. L. Farber, “Effector CD4 T cells are biochemically distinct from the memory subset: Evidence for long-term persistence of effectors in vivo,” J. Immunol., 1999.

M. Casás-Selves and J. Degregori, “How Cancer Shapes Evolution and How Evolution Shapes Cancer,” Evolution: Education and Outreach. 2011, doi: 10.1007/s12052-011-0373-y.

B. R. Scott and S. Tharmalingam, “The LNT model for cancer induction is not supported by radiobiological data,” Chemico-Biological Interactions. 2019, doi: 10.1016/j.cbi.2019.01.013.

M. H. Amer, “Gene therapy for cancer: present status and future perspective,” Mol. Cell. Ther., 2014, doi: 10.1186/2052-8426-2-27.

Y. Song and S. Yuan, “Bifurcation analysis in a predator-prey system with time delay,” Nonlinear Anal. Real World Appl., 2006, doi: 10.1016/j.nonrwa.2005.03.002.

J. K. Hale and S. M. Verduyn Lunel, Introduction to Functional Differential Equations. 1933.


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DOI: 10.15408/inprime.v3i1.19515

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