The Meyer lab integrates data-driven and mechanistic computational approaches with cell biological experiments to study cell behavior.
Mapping Mechanisms of Resistance in Cancer
Targeted therapies extend many cancer patients’ lives but are limited in efficacy to a subset of patients and by the development of resistance. Efforts undertaken to identify mechanisms of resistance have uncovered numerous changes involving gene expression, post-translational regulation, and even tumor-extrinsic factors such as host-derived growth factors. Combination therapy can effectively combat resistance but requires accurate identification of the relevant resistance mechanism. Precision therapy must account for many genetic and non-genetic intrinsic and adaptive resistance mechanisms if it will accurately select these combinations.
In RTK-driven tumors, signals are transduced from the receptor to various kinases. Upon blocking the original cancer driver, resistance can be conferred by an untargeted receptor. Some receptors, however, do not provide essential resistance signals. By identifying the essential signals driving resistance from each receptor, we aim to develop measurements pinpointing the receptor causing resistance.
Projects in the lab include mapping the common essential signaling events that drive resistance, quantifying single cell heterogeneity in drug response, and exploring how the extracellular matrix environment directs resistance development.
Systems Approaches for Rational Immune Therapies
Many immune receptors operate as families with multiple ligands and receptors, expressed across diverse cell populations. The lab’s efforts operate around the central hypothesis that the multiple members of these families are present to perform computation-like regulation across cell populations. Further, we can use engineering analysis tools to measure and manipulate these systems.
The Fc portions of IgG antibodies enable communication with many cell populations of the immune system via Fcγ receptors. The consequence of these interactions is influenced by relative affinity among the receptors, valency, and the cell populations present, creating thousands of possibilities. Using a mechanism-based binding model and data-driven analytical techniques, we aim to engineer this communication.
We are studying regulation of families like the Tyro3, AXL, MerTK (TAM) tyrosine kinases, Fcγ, and common γ-chain cytokine receptors. In addition to studying how these receptors operate as a family, we are working to develop tools that make visualizing and manipulating family-wide behavior easier.