Optimal Choice Between Chemotherapy and Immunotherapy for Leukemia Treatment Depends on Individual Patients’ Patho-physiological State

  • Probir Kumar Dhar
  • Tarun Kanti Naskar
  • Durjoy Majumder
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 710)

Abstract

Chemotherapy is the firsthand choice of any cancer therapy including leukemia. However, immunosuppression is commonly seen in leukemic patients. So for the management of leukemia, cytokine-based immunotherapy is also suggested as either a combination therapy along with the conventional chemotherapy or alone. However, therapy is applied on individual patients on the basis of evidence-based medicine, i.e., population-based statistical analysis and/or on the basis of clinicians’ personal experience. Here, we propose an analytical rationality for therapeutic selection among these two options. Our simulation runs suggest that choice would be based on individual patients’ patho-physiological state like immunity profile or another hematological status. Simulation runs also suggest that in some cases chemotherapy may bring detrimental effect and direct immunotherapy would be beneficial for long-term successful therapeutic outcome. Further, this model helps in the optimization of cytokine-based immunotherapy protocol.

Keywords

Delay ordinary differential equation Feedback Optimization Immunotherapy Leukemia 

Notes

Acknowledgements

PKD is pursuing Ph.D. from Jadavpur University. All authors acknowledge the logistic support provided by Society for Systems Biology & Translational Research.

References

  1. 1.
    DeLsi, C., Rescigno, A.: Immnue surveillance and neoplasia 1 a minimal mathematical model. Bulletin of Mathematical Biology. 39 (1977) 201–221.Google Scholar
  2. 2.
    Grossman, B.G.: Tumour escape from immune elimination J Theor Biol 83 (1980) 267–296.Google Scholar
  3. 3.
    Kustnetsov, V.A., Malakin, A.M., Taylor, M.A., Perelson, A.S.: Nonlinear dynamics of immunogenic tumors: Parameter estimation and global bifurcation analysis, Bull. Math. Bio. 56 (1994) 295–321.Google Scholar
  4. 4.
    Preziosi, L.: From population dynamics to modeling the competition between tumors and immune system Mathl. Comput. Modelling. 23 (1996) 135–152.Google Scholar
  5. 5.
    Michor, F., Beal, K.: Improving cancer treatment via mathematical modeling of population dynamics. Cell. 163 (2015) 1059–1063.Google Scholar
  6. 6.
    Bellomo, N., Forni, G.: Dynamics of tumor interaction with the host immune system, Mathl. Comput. Modelling 20 (1994) 107–122.Google Scholar
  7. 7.
    Kolev, M.: Mathematical modeling of the competition between tumors and immune system considering the role of the antibodies. Mathl. Comput. Modelling. 37 (2003) 1143–1152.Google Scholar
  8. 8.
    Kim, P.S., Lee, P.P., Levy, D.: Dynamics and potential impact of the immune response to chronic myelogenous leukemia, PLoS Comp Biol. 4 (2008):e1000095.Google Scholar
  9. 9.
    Kim, P.S., Lee, P.P., Levy, D.: A PDE model for imatinib-treated chronic myelogenous leukemia. Bull. Math. Biol. 70 (2008) 1994–2016.Google Scholar
  10. 10.
    Foo, J., Drummond, M.W., Clarkson, B., Holyoke, T., Michor, F.: Eradication of chronic myeloid leukemia stem cells: a novel mathematical model predicts no therapeutic benefit of adding G-CSF to imatinib. PLoS Computational Biology. 5 (2009), e10000503.Google Scholar
  11. 11.
    Dhar, P.K., Mukherjee, A., Majumder, D.: Difference delay equation-based analytical model of hematopoiesis. Aut. Contrl. Physiol. State. Func. 1 (2012) 1–11.Google Scholar
  12. 12.
    Dhar, P.K., Majumder, D.: Development of the analytical model for the assessment of the efficiencies of different therapeutic modalities in leukaemia. J. Comp. Syst. Biol. 1 (2015) 1–45.Google Scholar
  13. 13.
    Michor, F., Hughes, T.P., Iwasa, Y., Branford, S., Shah, N.P., Sawyers, C.L., Nowak, M.A.: Dynamics of chronic myeloid leukemia. Nature 435 (2005) 1267–1270.Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Probir Kumar Dhar
    • 1
    • 2
    • 4
  • Tarun Kanti Naskar
    • 2
    • 4
  • Durjoy Majumder
    • 3
    • 4
  1. 1.ECE DepartmentBCETDurgapur, BurdwanIndia
  2. 2.Department of Mechanical EngineeringJadavpur UniversityKolkataIndia
  3. 3.Department of PhysiologyWest Bengal State UniversityKolkataIndia
  4. 4.Society for Systems Biology & Translational ResearchKolkataIndia

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