Analysis of matrix metalloproteinases in cancer cell signaling and extracellular behavior
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Despite the fact that over the past two decades the total death rate has declined up to twenty percent, cancer remains the second leading cause of death in the United States and accounts for nearly one in every four deaths. It is therefore of paramount importance that new strategies continue to develop in an effort to curb both incidence and treatment of disease. The current research landscape is focused on developing strategies to disrupt molecular signatures of cancer cell types, commonly known as targeted therapy. Of particular importance in the advancement of targeted therapies are matrix metalloproteinases (MMPs), a family of endopeptidases whose primary function lies in cleaving extracellular matrix (ECM) proteins and are frequently dysregulated in cancer. While research regarding MMPs is decades old, their significance in the signal transduction of several oncogenic pathways is yet to be fully explored. In addition, a dearth of quantitative data exists describing the action of MMPs in three dimensional (3D) networks, a configuration that causes cells to express vastly different behaviors compared to traditional two-dimensional (2D) in vitro culture methods. This dissertation aims to further elucidate the intimate relationships between MMPs, the ECM, cancer pathway signaling, and cell migration. First, the behavioral crosstalk between MMPs and the ECM is studied using quantitative methods in 3D matrices. Next, the role of MMPs in both Ras oncogenic and HER2 positive breast cancer is probed via extensive protein expression analysis. Finally, the behavioral aspects of MMPs in 3D are assessed marrying both in vitro data with a computational model to predict migration response. The results reveal that MMPs exhibit a bidirectional relationship with respect to matrix architecture, and the ability to regulate and be regulated by the ECM. In addition, it is concluded that MMPs play a significant role in both active Ras and HER2 upregulated cancer signaling. Finally, the data demonstrates the robustness and accuracy of our methods in manufacturing a model to predict migration in 3D matrices. The work described here promises to further enhance the knowledge of MMPs in cancer and potentially inform future drug development endeavors.