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Mathematical Modelling of the Interaction Between Cancer Cells and an Oncolytic Virus: Insights into the Effects of Treatment Protocols

2018/04/11 by Adrianne L. Jenner, Chae-Ok Yun, Chae‐Ok Yun +4 · 79 citations
Biochemistry, Genetics and Molecular Biology · Mathematics · Medicine · #Antibody #Biology #CAR-T cell therapy research #Cancer #Cancer cell #Cancer research #Cancer treatment #Clearance #Immunology #Infectivity #Medicine #Monoclonal antibody #Oncolytic virus #PEG ratio #PEGylation #Polyethylene glycol #Viral Infectious Diseases and Gene Expression in Insects #Virology #Virotherapy #Virus #Virus-based gene therapy research #math.DS #q-bio.CB #q-bio.TO

paper · pdf · doi:10.1007/s11538-018-0424-4

published in Bulletin of Mathematical Biology 80(6), 1615-1629 (Springer Science+Business Media) · 15 pages, 6 figures

openalex publication_date 2018/04/11 · arxiv created 2019/11/28 · arxiv updated 2019/12/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

Oncolytic virotherapy is an experimental cancer treatment that uses genetically engineered viruses to target and kill cancer cells. One major limitation of this treatment is that virus particles are rapidly cleared by the immune system, preventing them from arriving at the tumour site. To improve virus survival and infectivity modified virus particles with the polymer polyethylene glycol (PEG) and the monoclonal antibody herceptin. While PEG modification appeared to improve plasma retention and initial infectivity it also increased the virus particle arrival time. We derive a mathematical model that describes the interaction between tumour cells and an oncolytic virus. We tune our model to represent the experimental data by Kim et al. (2011) and obtain optimised parameters. Our model provides a platform from which predictions may be made about the response of cancer growth to other treatment protocols beyond those in the experiments. Through model simulations we find that the treatment protocol affects the outcome dramatically. We quantify the effects of dosage strategy as a function of tumour cell replication and tumour carrying capacity on the outcome of oncolytic virotherapy as a treatment. The relative significance of the modification of the virus and the crucial role it plays in optimising treatment efficacy is explored.

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