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Webinar: Biostatistics seminar – “Network-Based Dynamic Models of Oncogenic Signaling Can Predict Therapeutic Strategies”
November 19, 2020, 12:00 pm to 1:00 pm
“Network-Based Dynamic Models of Oncogenic Signaling Can Predict Therapeutic Strategies” will be presented by Réka Albert, PhD, Distinguished Professor of Physics and Biology, Penn State.
Mechanistic models of within-cell signal transduction networks can explain how these networks integrate internal and external inputs to give rise to the appropriate cellular response. These models can be fruitfully used in cancer cells, whose aberrant decision-making regarding their survival or death, proliferation or quiescence can be connected to errors in the state of nodes or edges of gene regulatory or signal transduction networks. During more than fifteen years of collaboration with wet-bench scientists, Dr. Albert’s group has found that discrete dynamic modeling is very useful in synthesizing qualitative interaction information into a predictive model. This talk will present the results of two collaborative projects, one on epithelial to mesenchymal transition and one on proliferation of breast cancer cells. The group’s models integrate a large compendium of interaction information and recapitulate known dynamic outcomes, for example known resistance mechanisms to targeted therapy. The models predict novel combinatorial interventions to block metastasis, stop abnormal cell proliferation or kill cancer cells; several of these predictions were validated experimentally. Network-based models will play an increasing role in the rational design of high-order therapeutic combinations.
Participants may also join by calling 929-205-6099, meeting ID 322 043 373. If prompted, enter passcode 167660.