Exploiting drug-induced network rewiring to identify effective treatment for cancer

Preliminary data from the Nguyen-Daly lab has identified Fibroblast growth factor receptors (FGFRs) as promising therapeutic targets for triple-negative breast cancer (TNBC) that express high level of this receptor protein. Interestingly, treatment of TNBC cells with agents directed at FGFRs led to a remarkable reprogramming of cancer cell signaling networks which activate alterative pathways, evade the drug effect and cause drug resistance. Using state-of-the-art experimental techniques including antibody arrays, cell signalling and biological assays, this project first aims to characterize how such network reprogramming occurs over time. Importantly, the data will be used to develop dynamic and predictive model of FGFR signaling in TNBC. Model simulations will help predict intervention strategies through drug combinations that can counteract the network reprogramming and re-sensitize TNBC cells to the combined treatments. Predictions will then be tested experimentally in the wet lab. Our lab has both dry- and wet-lab capacities that enable the iterative cycles of model refinement and experimental validation integral to this systems approach. Students will work in a highly stimulating and interdisciplinary research environment consisting of both computational and experimental scientists. Students with either excellent computational (physics, maths, engineering, etc.) or experimental background (or both) are encouraged to apply.