Unraveling the role of exercise in cancer suppression: insights from a mathematical model.

IF 2 4区生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY

Physical biology Pub Date : 2024-11-07 DOI:10.1088/1478-3975/ad899d

Jay Taylor, T Bagarti, Niraj Kumar

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Abstract

Recent experimental studies have shown that physical exercise has the potential to suppress tumor progression. Such suppression has been reported to be mediated by the exercise-induced activation of natural killer (NK) cells through the release of IL-6, a cytokine. Aimed at shedding light on how exercise-induced NK cell activation helps in the suppression of cancer, we developed a coarse-grained mathematical model based on a system of ordinary differential equations describing the interaction between IL-6, NK-cells, and tumor cells. The model is then used to study how exercise duration and exercise intensity affect tumor suppression. Our results show that increasing exercise intensity or increasing exercise duration leads to greater and sustained tumor suppression. Furthermore, multi-bout exercise patterns hold promise for improving cancer treatment strategies by adjusting exercise intensity and frequency. Thus, the proposed mathematical model provides insights into the role of exercise in tumor suppression and can be instrumental in guiding future experimental studies, potentially leading to more effective exercise interventions.

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揭示运动在抑制癌症中的作用：数学模型的启示

最近的实验研究表明，体育锻炼有可能抑制肿瘤的发展。据报道，这种抑制作用是通过释放细胞因子 IL-6 激活自然杀伤（NK）细胞介导的。为了揭示运动诱导的 NK 细胞活化如何帮助抑制癌症，我们开发了一个粗粒度数学模型，该模型基于一个常微分方程系统，描述了 IL-6、NK 细胞和肿瘤细胞之间的相互作用。然后利用该模型研究运动持续时间和运动强度如何影响肿瘤抑制。我们的研究结果表明，增加运动强度或延长运动时间会导致更强、更持久的肿瘤抑制作用。此外，多回合运动模式有望通过调整运动强度和频率来改善癌症治疗策略。因此，所提出的数学模型有助于深入了解运动在抑制肿瘤中的作用，并有助于指导未来的实验研究，从而可能带来更有效的运动干预措施。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Physical biology 生物-生物物理

CiteScore

4.20

自引率

0.00%

发文量

审稿时长

3 months

期刊介绍： Physical Biology publishes articles in the broad interdisciplinary field bridging biology with the physical sciences and engineering. This journal focuses on research in which quantitative approaches – experimental, theoretical and modeling – lead to new insights into biological systems at all scales of space and time, and all levels of organizational complexity. Physical Biology accepts contributions from a wide range of biological sub-fields, including topics such as: molecular biophysics, including single molecule studies, protein-protein and protein-DNA interactions subcellular structures, organelle dynamics, membranes, protein assemblies, chromosome structure intracellular processes, e.g. cytoskeleton dynamics, cellular transport, cell division systems biology, e.g. signaling, gene regulation and metabolic networks cells and their microenvironment, e.g. cell mechanics and motility, chemotaxis, extracellular matrix, biofilms cell-material interactions, e.g. biointerfaces, electrical stimulation and sensing, endocytosis cell-cell interactions, cell aggregates, organoids, tissues and organs developmental dynamics, including pattern formation and morphogenesis physical and evolutionary aspects of disease, e.g. cancer progression, amyloid formation neuronal systems, including information processing by networks, memory and learning population dynamics, ecology, and evolution collective action and emergence of collective phenomena.