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.

Recent Publications

Zeng J, Alvarez-Yela AC, Casarez E, Jiang Y, Wang L, Kelly BE, Jenkins T, Ke E, Atkins KA, Janes KA, Slack-Davis JK, Zong H. (2023) Dichotomous ovarian cancer-initiating potential of Pax8+ cells revealed by a mouse genetic mosaic model.  iScience, 26, 106742. [Article]
Netterfield TS, Ostheimer GJ, Tentner AR, Joughin BA, Dakoyannis AM, Sharma CD, Sorger PK, Janes KA, Lauffenburger DA, Yaffe MB. (2023) Biphasic JNK-Erk signaling separates the induction and maintenance of cell senescence after DNA damage induced by topoisomerase II inhibition.  Cell Syst, 14, 582-604.e10. [Article]
Zeng J, Singh S, Zhou X, Jiang Y, Casarez E, Atkins KA, Janes KA, Zong H. (2023) A genetic mosaic mouse model illuminates the pre-malignant progression of basal-like breast cancer.  Dis Model Mech, 16, dmm050219. [Article]
  • Editor’s Choice:  Blyth, K. (2023) Lighting the way to track early progression of basal-like breast cancer.  Dis Model Mech, 16, dmm050565.  [Link]