一种考虑缺氧影响的肿瘤溶瘤病毒疗法数学模型
A phenotype-structured mathematical model for the influence of hypoxia on oncolytic virotherapy
AI总结：
本文提出一种数学模型，研究缺氧对肿瘤溶瘤病毒疗法的影响，分析肿瘤空间异质性和表观遗传异质性，揭示缺氧对病毒复制和肿瘤进化动态的影响，为个性化癌症治疗提供理论支持。
摘要：
肿瘤微环境中的多个因素显著影响肿瘤溶瘤病毒疗法的有效性，这些因素会降低病毒感染癌细胞的能力。本文聚焦缺氧对这一疗法的影响，开发了一个新的连续数学模型，考虑肿瘤的空间和表观遗传异质性。我们研究了肿瘤内氧梯度如何影响肿瘤和溶瘤病毒的空间分布和复制，重点分析严重缺氧区域与正常氧区域的差异。此外，我们分析了缺氧条件下肿瘤细胞的进化动态及其对病毒感染易感性的影响。我们的发现表明，缺氧细胞的代谢活性降低可能显著影响病毒疗法效果；因此，了解肿瘤的氧合情况可能建议最适合的病毒类型以优化治疗结果。数值模拟和模型平衡值的理论结果结合，有助于阐明病毒、肿瘤进化和氧动态之间的复杂相互作用，最终促进更有效和个性化的癌症治疗。
英文摘要：
The effectiveness of oncolytic virotherapy is significantly affected by several elements of the tumour microenvironment, which reduce the ability of the virus to infect cancer cells. In this work, we focus on the influence of hypoxia on this therapy and develop a novel continuous mathematical model that considers both the spatial and epigenetic heterogeneity of the tumour. We investigate how oxygen gradients within tumours affect the spatial distribution and replication of both the tumour and oncolytic viruses, focusing on regions of severe hypoxia versus normoxic areas. Additionally, we analyse the evolutionary dynamics of tumour cells under hypoxic conditions and their influence on susceptibility to viral infection. Our findings show that the reduced metabolic activity of hypoxic cells may significantly impact the virotherapy effectiveness; the knowledge of the tumour's oxygenation could, therefore, suggest the most suitable type of virus to optimise the outcome. The combination of numerical simulations and theoretical results for the model equilibrium values allows us to elucidate the complex interplay between viruses, tumour evolution and oxygen dynamics, ultimately contributing to developing more effective and personalised cancer treatments.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
