The Role of Viral Dynamics and Infectivity in Models of Oncolytic Virotherapy for Tumours with Different Motility

David Morselli1,2, Federico Frascoli3, Marcello E Delitala4

  • 1Department of Mathematics, University College London, 25 Gordon Street, London, WC1H 0AY, United Kingdom. d.morselli@ucl.ac.uk.

Insights

Mathematical models reveal that viral infectivity is crucial for successful tumor virotherapy. Understanding viral dynamics and infectivity can improve cancer treatment outcomes.

Area of Science:

  • Oncology
  • Mathematical Biology
  • Virology

Background:

  • Engineered viruses offer promising cancer therapeutic strategies.
  • Current virotherapy protocols lack consistent efficacy across diverse tumors.
  • Mathematical modeling can elucidate key factors in virotherapy success.

Purpose of the Study:

  • To investigate the role of viral infectivity and dynamics in tumor virotherapy outcomes.
  • To compare different mathematical models of virotherapy, including probabilistic and continuous approaches.
  • To analyze the impact of tumor motility and viral infectivity representations on therapeutic results.

Main Methods:

  • Comparison of probabilistic, individual-based models with continuous, spatially inhomogeneous models.
  • Analysis of tumor motility and various mathematical representations of viral infectivity.
  • Mathematical characterization of viral infection wave propagation within tumors.

Main Results:

  • Tumor motility, stochasticity, and diffusivity influence virotherapy outcomes.
  • Viral infectivity emerged as a more critical factor than tumor motility or reproduction in some scenarios.
  • Mathematical models provided insights into the dynamics of viral infection spread.

Conclusions:

  • Viral infectivity is a key determinant of successful tumor virotherapy.
  • Mathematical modeling enhances understanding of viral dynamics in cancer treatment.
  • Findings may guide clinicians towards more effective virotherapy strategies.

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