Multiscale Mathematical Modeling of Cancer Progression

描述（由申请人提供）：我们申请的首要主题是量化癌细胞异质性对肿瘤生长和治疗耐药性的影响。它从逻辑上延伸了之前资助期的结果，指出表型异质性是进展和侵袭的关键决定因素。我们将考虑在ICBP-43乳腺癌细胞系面板和耐药乳腺癌或辐射反应性肺癌细胞系中表型性状（增殖、运动和代谢）的异质性。性状异质性将主要通过高含量自动化显微镜和图像处理进行量化。在细胞系之间，性状变异将作为平均值和分布形状进行比较。在细胞系内，细胞间的差异（可能是非遗传的）将通过统计建模（例如贝叶斯信息标准和聚类算法）表示为亚种群。为了估计适应性，我们将测量性状对模拟肿瘤微环境条件的扰动的响应变化。这个庞大的数据集（>10扰动下>50系中的3个性状）将被输入到数学和计算预测模型中，追踪单个癌细胞的命运和肿瘤生长过程中的时空微环境。加上实验部分，这套理论模型形成了一个中心“骨干”，部署在三个项目上。项目1将通过将细胞性状异质性数据纳入利用进化动力学和博弈论概念的数学和计算模型来量化癌症进展中的适应性优势。项目2将测量性状异质性和适应度成本在乳腺癌对一线和二线药物（阿霉素、激素治疗和HER2酪氨酸激酶抑制剂）耐药性上升中的影响。项目3将尝试通过将实验定义的放射表型异质性与预测模型相结合，改善和/或预测肺癌细胞系放射治疗的结果。项目1-3中的假设/预测将通过实验和理论的迭代循环在体外和小鼠肿瘤中得到验证。最后，我们将继续开展教育/推广工作，例如，亲自动手的癌症模型研讨会，以吸引物理和生物科学家，特别是新一代中最聪明的科学家。

DESCRIPTION (provided by applicant): The overarching theme of our application is to quantify the impact of cancer cell heterogeneity in tumor growth and treatment resistance. It logically extends results from the previous funding period, pointing to phenotypic heterogeneity as key determinant of progression and invasion. We will consider heterogeneity with respect to phenotypic traits (Proliferation, Motility and Metabolism), in the ICBP-43 breast cancer cell line panel and in drug resistant breast, or radiation responsive lung, cancer cell lines. Trait heterogeneity will be quantified primarily by high-content automated microscopy and image processing. Between cell lines, trait variability will be compared as averages and distribution shapes. Within a cell line, ceil-to-cell variability (presumably non-genetic) will be represented as subpopulations by statistical modeling, e.g., bayesian information criteria and clustering algorithms. To estimate adaptability, we will measure trait variation in response to perturbations mimicking tumor microenvironment conditions. This large dataset (3 traits in >50 lines under >10 perturbations) will be input to mathematical and computational predictive models, tracking the fate of individual cancer cells and the microenvironment in space-time during tumor growth. With the experimental component, this suite of theoretical models forms a Center "Backbone" deployed towards three Projects. Project 1 will quantify adaptive advantage in cancer progression by incorporating cell trait heterogeneity data into mathematical and computational models that exploit evolution dynamics and game theory concepts. Project 2 will measure impact of trait heterogeneity and fitness cost in the rise of breast cancer resistance to first- and second-line drugs (doxorubicin, hormone therapy and HER2 tyrosine kinase inhibitors). Project 3 will attempt to improve and/or predict outcomes of radiation treatment in lung cancer cell lines by coupling experimentally defined radio-phenotype heterogeneity to predictive models. Hypotheses/predictions from Projects 1-3 will be validated in vitro and in mouse tumors, by iteration loops of experimentation and theory. Finally, we will continue education/outreach efforts, e.g., hands-on cancer modeling workshops, to attract physical and biological scientists, especially the brightest of the new generations.