Mathematical Validation of a Cancer Model

Fuente: arXiv
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Main Authors: Reale, Marcela V., Paccosi, Gustavo, Margarit, David H., Romanelli, Lilia
Format: Preprint
Published: 2025
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author Reale, Marcela V.
Paccosi, Gustavo
Margarit, David H.
Romanelli, Lilia
author_facet Reale, Marcela V.
Paccosi, Gustavo
Margarit, David H.
Romanelli, Lilia
contents Understanding cancer cell differentiation is essential for advancing its detection, diagnosis, and treatment. Mathematical models significantly contribute to this by providing a theoretical framework to understand the complex interactions between cancer stem cells, differentiated cancer cells, and immune system components. Such models depend on experimental data and computational simulations to predict tumor dynamics, offering insights into how different cell populations evolve over time. However, to ensure their realistic and consistent outcomes, rigorous mathematical analysis is required, including verification of solution uniqueness, stability, viability, positivity, and boundedness. Such validation guarantees that model's results can be used in both oncological research and clinical applications. In this study, we conduct a comprehensive analysis of an integrative mathematical model of cancer cell differentiation, with a particular focus on its interactions with immune cells. The model captures the dynamic balance between cancer stem cell self-renewal, differentiation into mature tumor cells, and immune-mediated elimination. By employing analytical and numerical techniques, we assess the model's feasibility, stability, and long-term behavior under various biological conditions. Our findings demonstrate that immune system engagement can significantly influence tumor composition and growth, highlighting potential therapeutic targets. This work not only advances theoretical cancer modeling but also provides a foundation for future experimental validation and the development of combined differentiation-immunotherapy approaches. The results underscore the importance of interdisciplinary collaboration in the fight against cancer.
format Preprint
id arxiv_https___arxiv_org_abs_2508_10910
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Mathematical Validation of a Cancer Model
Reale, Marcela V.
Paccosi, Gustavo
Margarit, David H.
Romanelli, Lilia
Tissues and Organs
Understanding cancer cell differentiation is essential for advancing its detection, diagnosis, and treatment. Mathematical models significantly contribute to this by providing a theoretical framework to understand the complex interactions between cancer stem cells, differentiated cancer cells, and immune system components. Such models depend on experimental data and computational simulations to predict tumor dynamics, offering insights into how different cell populations evolve over time. However, to ensure their realistic and consistent outcomes, rigorous mathematical analysis is required, including verification of solution uniqueness, stability, viability, positivity, and boundedness. Such validation guarantees that model's results can be used in both oncological research and clinical applications. In this study, we conduct a comprehensive analysis of an integrative mathematical model of cancer cell differentiation, with a particular focus on its interactions with immune cells. The model captures the dynamic balance between cancer stem cell self-renewal, differentiation into mature tumor cells, and immune-mediated elimination. By employing analytical and numerical techniques, we assess the model's feasibility, stability, and long-term behavior under various biological conditions. Our findings demonstrate that immune system engagement can significantly influence tumor composition and growth, highlighting potential therapeutic targets. This work not only advances theoretical cancer modeling but also provides a foundation for future experimental validation and the development of combined differentiation-immunotherapy approaches. The results underscore the importance of interdisciplinary collaboration in the fight against cancer.
title Mathematical Validation of a Cancer Model
topic Tissues and Organs
url https://arxiv.org/abs/2508.10910