Date(s) - 11/18/2019
3:00 pm - 4:00 pm
Researchers have recognized that a one-size-fits-all approach is not effective at treating cancer and that tumor heterogeneity plays an important role in response. Hanahan & Weinberg have defined a toolbox, the “Hallmarks of Cancer,” that enumerate some tools of pathogenesis, in which protease dysfunction plays a multitude of roles. Proteases are enzymes that degrade proteins as part of cellular homeostasis. When proteins are aged, defective, or taken up by the cell, these proteins are degraded by enzymes in the lysosomes, such as cysteine cathepsins. In addition to their proteolytic activity inside lysosomes, cathepsins secreted from cells degrade extracellular matrix (ECM). These potent enzymes are up-regulated in tissue-destructive diseases such as cancer; however, researchers have not been successful in alleviating cathepsin dysfunction. This research develops a mechanistic understanding of how cathepsins interact with ECM and each other through mathematical modelling, mutant-protease experiments, and biological machines application. Additionally, this integrated systems biology approach used to explore proteolysis was then harnessed for developing a computational framework to quantify tumor heterogeneity across a leukemia cohort for patient stratification and personalized medicine.
Meghan Ferrall-Fairbanks received her B.S. in Mechanical Engineering with a Biomechanics minor at the University of Florida in 2012. She earned her PhD in Biomedical Engineering in 2017 from the join Georgia Tech and Emory program under the guidance of Dr. Manu O. Platt. In her graduate dissertation work, Meghan focused on integrating wet-lab experimental and computational methods to tease apart complex enzyme-on-enzyme interactions in proteolytic networks up-regulated in tissue destructive diseases. In August 2017, she began her postdoctoral studies in the Department of Integrated Mathematical Oncology at Moffitt Cancer Center and Research Institute with Dr. Philipp M. Altrock. In her postdoctoral work, Meghan has focused on applying mathematical and computational methods to model cancer evolution in hematopoietic malignancies.