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Phase-specific cancer-immune model considering acquired resistance to therapeutic agents

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  • Byun, Jong Hyuk
  • Jung, Il Hyo

Abstract

We formulated a mechanistic model for the cancer-immune system associated with therapy. In this model, cancer is divided into two types: cancer that is sensitive to treatment (CST) and cancer that gradually acquires resistance to therapeutic agents (CRT). Cancer activates various mechanisms to evade the actions of therapeutic agents, including chemotherapy or targeted therapy. A positive response is observed at the early stage of treatment when cancer therapy is administered through subcutaneous or intravenous injection. However, over time, cancer acquires resistance against the treatment and begins to show rapid growth. Previous models have suggested strategies that can effectively suppress cancer by determining an appropriate dosing regimen but are limited in that cancer inhibition depends only on the dose amount and regimen. In contrast to a model in which there is a steady decline in cancer due to continuous-infusion therapy, the proposed model incorporates the fact that cancer cells may grow despite successive therapy administration, owing to the transition from CST to CRT. This consideration indicates that cancer suppression can be determined by the delay of therapy delivery to the site of action and the transition time. The delay of therapy and the transition time thus determine the period of cancer growth and the increase or decrease in cancer cell growth, respectively. This model was then used to the ratio of CST to CRT and to explore the therapy infusion rate under constant and periodic conditions in association with a pharmacokinetic model.

Suggested Citation

  • Byun, Jong Hyuk & Jung, Il Hyo, 2021. "Phase-specific cancer-immune model considering acquired resistance to therapeutic agents," Applied Mathematics and Computation, Elsevier, vol. 391(C).
  • Handle: RePEc:eee:apmaco:v:391:y:2021:i:c:s0096300320305117
    DOI: 10.1016/j.amc.2020.125555
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    References listed on IDEAS

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    1. Liu, Xiangdong & Li, Qingze & Pan, Jianxin, 2018. "A deterministic and stochastic model for the system dynamics of tumor–immune responses to chemotherapy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 162-176.
    2. Angstmann, C.N. & Henry, B.I. & McGann, A.V., 2016. "A fractional-order infectivity SIR model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 86-93.
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