Multiscale modelling of cancer response to oncolytic viral therapy

Talal Alzahrani1, Raluca Eftimie1, Dumitru Trucu1

  • 1Division of Mathematics, University of Dundee, Dundee DD1 4HN United Kingdom.

Mathematical Biosciences
|February 8, 2019
PubMed

Insights

This study introduces a new multiscale model to understand how oncolytic viruses (OV) interact with tumors. The model shows that OV therapy can control and reduce cancer growth, potentially eliminating tumors.

Area of Science:

  • Mathematical Biology
  • Computational Oncology
  • Virology

Background:

  • Oncolytic virus (OV) therapy shows promise for cancer treatment but is limited by complex tumor-OV spatial interactions.
  • Understanding these interactions is crucial for optimizing OV therapy efficacy.

Purpose of the Study:

  • To develop and analyze a novel multiscale moving boundary model for tumor-oncolytic virus interactions.
  • To investigate the influence of extracellular matrix (ECM) dynamics and cell haptotaxis on tumor-OV interactions.

Main Methods:

  • A multiscale model coupling macro-scale (tissue) and micro-scale (cell) partial differential equations.
  • Incorporation of urokinase plasminogen activator (uPA) system dynamics for ECM degradation.
  • Numerical simulations of three scenarios exploring ECM taxis effects on tumor-OV dynamics.

Main Results:

  • The model successfully captures complex tumor-OV spatial dynamics.
  • Numerical simulations indicate that OV therapy can control and decrease tumor expansion.
  • In some cases, OV therapy demonstrated potential for complete tumor elimination.

Conclusions:

  • The developed multiscale modeling framework provides insights into tumor-OV interactions.
  • OV therapy shows potential for effective cancer treatment, warranting further investigation and validation.

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