A critical challenge in biomedical engineering is a need to control the process of blood vessel formation, also known as "angiogenesis." Controlling angiogenesis is important, because blood vessels supply the nutrients necessary for our organs and tissues to function properly. Efforts to control angiogenesis in cancer focus on starving and possibly killing the tumor by cutting off tumor blood supply, typically by looking at a single protein. This project proposes to overcome current limitations in this type of cancer therapy and meet the general challenge of controlling angiogenesis by tackling a more difficult, "big-data"-like problem: understanding how combinations of proteins control angiogenesis. This project will tackle the problem by: 1) experimentally determining important protein characteristics; 2) determining mathematical equations that describe the behaviors of these proteins; and 3) developing computer simulations that include both the experimental data and the mathematical equations to determine how the proteins work to cause angiogenesis. The education and outreach portion of this project will introduce sophomores to research and computer modeling in an introductory-level course in order to excite them about STEM. The activities will include mentoring of underrepresented students to increase their interest and persistence within STEM majors.
The directed control of angiogenesis remains a pressing need due to its involvement in the pathology of over 70 diseases. A promising approach for angiogenesis control involves going beyond the traditional emphasis on the vascular endothelial growth factor (VEGF)-VEGF receptor (VEGFR) axis towards a new focus: cross-axis signaling (protein binding across families). The objective in this project is to pioneer a shift towards understanding cross-axis angiogenic signaling via three aims grounded in quantitative biology (qBio), omputational biology (cBio), and integrative systems biology (sBio). Quantitative biology will be used to measure cross-axis binding and concentrations or relevant protein ligands, including through the development of new quantitative tools for multiplex measurement of receptor concentrations. Computational biology will be used to construct validated cross-axis models that will predict how adapter activation contributes to angiogenic hallmarks, cell proliferation, and migration. Systems biology will be used to predict the role of cross-axis signaling in angiogenesis by applying the qBio and cBio tools to angiogenesis in vitro. Ligand, receptor, and adapter concentrations will be measured, and the magnitude of cross-axis signaling will be predicted. These predictions will be validated by demonstrating control of vessel formation (inhibition and stimulation) in vitro. This research will be integrated with teaching by creating undergraduate research pathways via a core course. This will introduce systems biology to sophomore students who will develop computational models of ligand-receptor signaling in angiogenesis. Students will also be offered opportunities to continue their work within the PI's research laboratory. Additional mentoring will be provided to underrepresented students to support their persistence within STEM fields.
