Developing Mathematical Models for Immune Interactions in Cancer, Cachexia, and the Microbiome

开发癌症、恶病质和微生物组中免疫相互作用的数学模型

• 批准号: RGPIN-2018-04205
• 负责人: Wilkie, Kathleen
• 金额: $ 1.17万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=712318
• 关键词: Developing; Mathematical; Models; Immune; Interactions

Mathematical models can tease apart the nonlinear dynamics of complex biological interactions by examining individual elements in a controlled manner. Interactions between human immunity and physiology are difficult to examine through traditional animal or cell line models due to the heterogeneous populations and many confounding variables. This research program creates new mathematical models describing the interactions between the immune system, normal tissues, and cancer, resulting in the creation of new model formulations and improved understanding of the biological system. This proposal contains three main objectives that all involve the creation of novel multi-compartment systems of differential equations to describe the interactions of the immune system with cancer or other host tissues. The first objective examines the immune-cancer relationship, including inflammation and aging effects on immune function. The second objective examines the loss of muscle or adipose tissue in cancer cachexia. While the third objective examines the relationship between the gut microbiome, immune system, and cancer. Newly developed differential equation-based models will describe the cellular interactions in a formulation that can be analyzed computationally. Genomic data analyses will be used to suggest possible biological mechanisms responsible for the cellular dysfunctions resulting from cancer presence. These mechanisms will be encoded into the model formulations where they can be rigorously studied. Experimental data will be used for model construction and validation, guaranteeing the creation of good quality predictive tools. The mathematical models created in objective three, describing immune-microbiome-cancer interactions, will be the first of their kind. The formulations used in objectives one and two are unique to this research program, are more biologically accurate than existing models, and are worthy of further research and development. Newly created models will extend the mathematical atlas available to mathematical biologist, evolutionary ecologists, and others who study nonlinear population dynamics. This work will formalize methods of data integration into mathematical modelling by distilling genomic data into fundamental biological mechanisms that can be encoded into model forms and parameters. The developed models may lead to future experimental or clinical applications where implications to human health and cancer treatment can be made. Indeed, improved understanding of the nonlinear dynamics occurring between the immune system, host physiology, and cancer, through mathematical modelling, can only lead to improved interventions for health maintenance and disease treatment, including immunotherapy and intestinal microbiome manipulation.

数学模型可以通过以受控的方式检查单个元素来梳理复杂生物相互作用的非线性动力学。人类免疫和生理之间的相互作用是很难通过传统的动物或细胞系模型，由于异质群体和许多混杂变量检查。该研究项目创建了描述免疫系统，正常组织和癌症之间相互作用的新数学模型，从而创建了新的模型配方并提高了对生物系统的理解。 该提案包含三个主要目标，所有这些目标都涉及创建新的微分方程多室系统，以描述免疫系统与癌症或其他宿主组织的相互作用。 第一个目标是研究免疫与癌症的关系，包括炎症和衰老对免疫功能的影响。第二个目的是检查癌症恶病质中肌肉或脂肪组织的损失。第三个目标是研究肠道微生物组，免疫系统和癌症之间的关系。新开发的基于微分方程的模型将以可以通过计算分析的公式描述细胞相互作用。基因组数据分析将被用来提出可能的生物学机制，负责细胞功能障碍所造成的癌症的存在。这些机制将被编码到模型公式中，在那里它们可以被严格地研究。实验数据将用于模型构建和验证，以确保创建高质量的预测工具。 在目标三中创建的数学模型描述了免疫-微生物组-癌症的相互作用，这将是此类模型中的第一个。目标一和目标二中使用的配方是本研究项目所独有的，比现有模型在生物学上更准确，值得进一步研究和开发。新创建的模型将扩展数学生物学家，进化生态学家和其他研究非线性种群动力学的数学图谱。这项工作将通过将基因组数据提炼成可以编码成模型形式和参数的基本生物机制，将数据整合到数学建模中的方法正式化。所开发的模型可能会导致未来的实验或临床应用，其中可以对人类健康和癌症治疗产生影响。事实上，通过数学建模，提高对免疫系统，宿主生理学和癌症之间发生的非线性动力学的理解，只会导致改善健康维护和疾病治疗的干预措施，包括免疫治疗和肠道微生物组操纵。