An average cancer cell is driven by 5–10 mutations, roughly similar to the number of proteins encoded by an average virus. Transformation or viral infection reconfigures cellular phenotype, but the logic of either complex perturbation is difficult to explain by inspection and intuition. Our laboratory tackles these challenges with a systems bioengineering approach that combines quantitative measurements, computational models, experimental manipulations, and data mining. We pursue systems bioengineering research that scales from genes and proteins in cells to tissues and tumors in animals to large-scale observations in human populations. Explanatory and predictive understanding at the systems level will one day lead to therapeutic strategies that are innovative and tailored to the complexity of each disease.
- Editor’s Choice: Blyth, K. (2023) Lighting the way to track early progression of basal-like breast cancer. Dis Model Mech, 16, dmm050565. [Link]