Proteolytic network dynamics in breast cancer and tumor associated macrophages

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Shockey, William Andrew
Platt, Manu O.
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Breast cancer metastasis is a complex process, promoted by a variety of cell types including cancerous mammary epithelial cells and stromal cells such as tumor associated macrophages (TAMs), which can make up 50% of tumor mass in late-stage, primary breast tumors. TAMs promote tumor growth, angiogenesis and metastasis through the release of inflammatory chemokines, growth factors and proteolytic enzymes including the cysteine cathepsins B, L, K, S and V. Cathepsins are potent catalysts of extracellular matrix degradation, but have also been identified as regulators of cellular process that operate through the activation of signaling pathways and the cleavage of receptor proteins, chemokines, and cellular adhesion molecules. Despite the development of highly specific, tight binding inhibitors that have shown clinical efficacy in treating multiple cathepsin-linked diseases, no cathepsin inhibitor has yet received FDA approval due to the emergence of unexpected side effects in trial participants. Cysteine cathepsins are components of complicated regulatory proteolytic networks, which include multiple biochemical and biomechanical stimuli, endogenous protease inhibitors, and other proteases capable of activating or degrading proteases while degrading substrates and inhibitors simultaneously. Unraveling the complicated proteolytic web of interactions between enzymes, substrates and inhibitors will be critical to the development of cathepsin inhibitor treatments capable of suppressing cancer metastasis and other related diseases. This work combines experimental and computational methods to explore the regulatory connections between cathepsin family members that could be responsible for off-target effects caused by pharmaceutical cathepsin inhibitors. A mechanistic model of an inhibitor-induced increase in active protease in breast cancer was developed to predict responses to inhibitor treatment. A mechanistic model of protease-on-protease degradation in the tumor microenvironment was also created to identify proteolytic network dynamics that modulate protease activity in cancer.
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