CAREER: Mathematical modeling of angiogenesis signaling and crosstalk in tumor cells

职业：肿瘤细胞中血管生成信号传导和串扰的数学模型

• 批准号: 1552065
• 负责人: Stacey Finley
• 金额: $ 50万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2023-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1552065&HistoricalAwards=false
• 关键词: CAREER; Mathematical; modeling; angiogenesis; signaling

1552065Finley, Stacey This project will identify novel strategies needed for inhibiting cancer cell growth by targeting angiogenesis signaling pathways. Angiogenesis is the formation of new blood vessels from pre-existing vessels and is critical to tumor growth and development. There are many interactions between the angiogenic factors, which tumor cells must interpret and respond to. The PI proposes to apply mathematical modeling to address fundamental questions regarding the dynamics of angiogenesis signaling in tumor cells and the effects of crosstalk and cell heterogeneity. Ultimately, a detailed understanding of the signaling events involved in angiogenesis pathways can lead to effective strategies for altering angiogenesis in a range of normal and diseased conditions, including cancer. The research objectives are tightly integrated with a multi-year outreach and educational training plan to impact students ranging from K-12 through graduate school. The PI will develop a hands-on, interactive curricular resource called 'DrEAMM' (Driving Enthusiasm About Mathematical Modeling) that brings to life mathematical concepts and engages students in computational thinking. The research objective of this proposal is to provide a predictive computational model of angiogenic signaling pathways in tumor cells. A quantitative and molecular-detailed description of these signaling networks is required to understand and inhibit tumor growth. To accomplish this goal, the PI will construct the first mathematical model to specifically identify the concentration profiles of the angiogenesis signaling molecules involved in cell proliferation and apoptosis in tumor cells. The model will establish, for the first time, a quantitative description of the balance of pro- and anti-angiogenic factors and the implications of their crosstalk in cancer cells. The PI will use sensitivity analyses to explore the parameter space and a robust, data-driven parameter estimation technique to fit the model to experimental measurements, including new data generated by the PI. The model will predict the average angiogenesis signaling dynamics of a population of cells, as well as the responses of individual cells. As such, the project will include both deterministic and stochastic simulations. The model will be applied to identify the mechanisms that enable precise shifting of the angiogenic balance in favor of anti-angiogenic signaling species that promote cell death. The expected outcome of completing the proposed research objectives is a molecular-detailed description of novel strategies that lead to tumor apoptosis by targeting angiogenesis signaling. More broadly, this work can lead to breakthrough strategies needed for inhibiting cell growth by targeting angiogenesis signaling pathways in a range of cell types and conditions. The PI will pursue a multi-year outreach and educational training plan closely integrated with the proposed research. The proposed activities will bring to life mathematical concepts for students ranging from K-12 through graduate school and engage the students in computational thinking. The goals for the educational plan are to spark and cultivate enthusiasm in STEM fields among K-12 students from under-represented groups and enliven concepts presented in undergraduate and graduate level systems biology classes.

1552065芬利，斯泰西 该项目将确定通过靶向血管生成信号通路抑制癌细胞生长所需的新策略。血管生成是从预先存在的血管形成新血管，并且对肿瘤生长和发展至关重要。血管生成因子之间存在许多相互作用，肿瘤细胞必须对其进行解释和响应。PI建议应用数学建模来解决有关肿瘤细胞中血管生成信号传导动力学以及串扰和细胞异质性影响的基本问题。最终，对血管生成途径中涉及的信号事件的详细了解可以导致在一系列正常和疾病条件下（包括癌症）改变血管生成的有效策略。研究目标与多年的推广和教育培训计划紧密结合，以影响从K-12到研究生院的学生。PI将开发一个名为“DrEAMM”（驾驶数学建模热情）的动手互动课程资源，使数学概念栩栩如生，并使学生参与计算思维。本研究的目的是提供一个肿瘤细胞血管生成信号通路的预测计算模型。这些信号网络的定量和分子详细描述是理解和抑制肿瘤生长所必需的。为了实现这一目标，PI将构建第一个数学模型，以专门识别肿瘤细胞中参与细胞增殖和凋亡的血管生成信号分子的浓度分布。该模型将首次建立对促血管生成因子和抗血管生成因子的平衡及其在癌细胞中的串扰的影响的定量描述。PI将使用敏感性分析来探索参数空间，并使用稳健的数据驱动参数估计技术来使模型与实验测量值（包括PI生成的新数据）相匹配。该模型将预测细胞群体的平均血管生成信号动力学，以及单个细胞的反应。因此，该项目将包括确定性和随机模拟。该模型将被应用于确定的机制，使精确的血管生成的平衡，有利于抗血管生成信号种类，促进细胞死亡的转变。完成所提出的研究目标的预期结果是通过靶向血管生成信号传导导致肿瘤凋亡的新策略的分子详细描述。更广泛地说，这项工作可以导致通过靶向一系列细胞类型和条件下的血管生成信号通路来抑制细胞生长所需的突破性策略。主要研究者将实施一项与拟议研究密切结合的多年外联和教育培训计划。拟议的活动将为从K-12到研究生院的学生带来生活中的数学概念，并使学生参与计算思维。教育计划的目标是激发和培养来自代表性不足的群体的K-12学生对STEM领域的热情，并活跃本科和研究生水平系统生物学课程中提出的概念。