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Tumor Immunotherapy

Tumor Immunotherapy

Immunotherapy is a treatment that boosts or manipulates the immune system to fight diseases, including cancer. For instance, by stimulating an immune response through vaccinations against viruses that cause cancers, like hepatitis B virus and human papillomavirus, these diseases can be prevented. Nonetheless, some cancer cells can avoid the immune system due to their rapid mutation and division. The immune response to many cancers involves three phases: elimination, equilibrium, and escape.

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Updated: Sep 11, 2025

Analysis of Human T Cell Activity in an Allogeneic Co-Culture Setting of Pre-Treated Tumor Cells

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Optimal Control of Immune Checkpoint Inhibitor Therapy in a Heart-Tumour Model.

Solveig A van der Vegt¹, Ruth E Baker¹, Sarah L Waters²

¹Mathematical Institute, University of Oxford, Oxford, UK.

Bulletin of Mathematical Biology

|August 11, 2025

Summary

Mathematical models for cancer therapy now include autoimmune myocarditis, a fatal side effect of immune checkpoint inhibitors (ICIs). This approach optimizes ICI dosing schedules by balancing treatment benefits against cardiac risks.

Keywords:

Autoimmune myocarditis Immune checkpoint inhibitors Optimal control Tumour growth

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Flow Cytometry-Based Isolation and Therapeutic Evaluation of Tumor-Infiltrating Lymphocytes in a Mouse Model of Pancreatic Cancer

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Published on: January 17, 2025

Area of Science:

Oncology
Immunology
Mathematical Biology

Background:

Immune checkpoint inhibitors (ICIs) are vital cancer therapies but can cause autoimmune myocarditis, a rare, fatal cardiac side effect.
Current mathematical models for cancer therapy optimization often exclude critical side effects like myocarditis.
This omission limits the ability to predict and mitigate treatment-related toxicities.

Purpose of the Study:

To develop a mathematical model integrating the effects of ICIs on both tumors and the heart.
To investigate the conditions leading to autoimmune myocarditis as a consequence of ICI therapy.
To design optimized ICI dosing schedules that balance therapeutic efficacy with cardiac safety.

Main Methods:

Developed a two-compartment mathematical model to simulate ICI impact on tumor and heart.
Employed an optimal control framework to determine dosing schedules.
Analyzed three distinct types of ICI therapy.

Main Results:

The model successfully incorporates the dual effects of ICIs on cancer and cardiac tissue.
Explicit inclusion of autoimmune myocarditis significantly alters predicted optimal dosing schedules.
Optimized schedules were designed to mitigate cardiac risks while maintaining therapeutic benefits.

Conclusions:

Integrating side effects like autoimmune myocarditis into mathematical models is crucial for safe and effective cancer therapy.
A holistic approach considering both efficacy and toxicity is essential for optimizing ICI treatment regimens.
This modeling framework provides a basis for personalized cancer treatment strategies that account for potential adverse events.