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Oncolytic viral therapy under type I interferon regulation: Mathematical modeling and analysis

Prathibha Ambegoda1, Hsiu-Chuan Wei2, Sophia R-J Jang3

  • 1Department of Mathematics, Stark State College, North Canton, OH, USA.

Mathematical Biosciences
|March 16, 2026
PubMed

Insights

Oncolytic viral therapy (OVT) efficacy depends on balancing viral infectivity, immune response, and interferon (IFN-I) dynamics. Personalized strategies accounting for these factors are crucial for optimizing OVT outcomes in cancer treatment.

Area of Science:

  • Mathematical Biology
  • Immunology
  • Virology
  • Oncology

Background:

  • Oncolytic viral therapy (OVT) shows promise for cancer treatment.
  • Understanding the complex interplay between tumor cells, the immune system, and viruses is critical for OVT efficacy.
  • Type I interferon (IFN-I) signaling plays a significant role in antiviral defense and immune modulation.

Purpose of the Study:

  • To develop and analyze a delay differential equation model of OVT.
  • To investigate the impact of tumor-immune-virus interactions, IFN-I dynamics, and viral infection cycle delays on treatment outcomes.
  • To identify key parameters driving tumor control in OVT.

Main Methods:

  • Development of a delay differential equation model.
  • Analytical and numerical analysis of the model.
  • Bifurcation analysis to study system dynamics.
  • Global sensitivity analysis to identify key drivers.

Main Results:

  • Treatment efficacy is determined by the balance of viral infectivity, IFN-mediated suppression, and immune recruitment.
  • Intracellular delay can destabilize tumor-virus coexistence, while immune responses lead to complex dynamics like bistability.
  • IFN production, IFN-induced immune suppression, viral infectivity, and immune proliferation are critical for tumor control.

Conclusions:

  • IFN-I has a dual role, potentially promoting viral clearance or persistence, influencing therapeutic outcomes.
  • The model highlights the importance of considering IFN signaling, immune status, and viral dynamics for personalized OVT strategies.
  • Optimizing OVT requires tailored approaches based on individual patient and viral characteristics.
Keywords:
Discrete delayHopf bifurcation.Mathematical modelOncolytic viral therapyOrdinary differential equations

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