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.
