Master of Science
Sarah J. Moore
Cancer-Diagnosis, Cancer-Treatment, Protein engineering, Mesothelin, Yeast surface display, Theranostics, Directed evolution
Targeted therapeutics have made significant impacts in cancer treatment, resulting in increased efficacy and reduced toxicity. However, many patients with ovarian, triple-negative breast, pancreatic, or lung cancer do not yet have reliable targeted therapeutic options. Mesothelin (MSLN), a cell surface protein with limited expression in healthy tissues, is frequently overexpressed on the surface of these tumor cells, and correlates with poor prognosis. Furthermore, the interaction of MSLN with tumor cell surface biomarker MUC16 leads to increased tumor invasiveness and metastasis. Blocking this interaction would have a direct therapeutic effect.
MSLN has broad potential as a novel tumor target for diagnosis and therapy, yet no MSLN-targeted molecules are currently FDA approved. Thus, there is a critical need for MSLN-targeted therapeutics and for molecular diagnostics that can identify patients who are most likely to respond to such therapies. This project proposes to engineer stable MSLN targeting agents using the fibronectin non-antibody protein scaffold, for use as both a targeted therapeutic and molecular diagnostic. Targeting agents that can serve as both therapeutics and diagnostics have the potential to identify the specific patient population most likely to respond to the partner therapeutic. To develop candidate theranostics, we used directed evolution and yeast surface display to engineer high affinity MSLN-binding proteins based on the fibronectin protein scaffold. We will engineer proteins specifically to block the binding interaction of MSLN and MUC16. A broad outcome of our proposed work is to validate the fibronectin protein scaffold for development of therapeutic/diagnostics, with implications for developing theranostics for other tumor biomarkers.
Sirois, Allison R., "Engineering proteins targeting tumor biomarker mesothelin toward applications as cancer diagnostics and therapeutics" (2016). Masters Thesis, Smith College, Northampton, MA.
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