There remains a pressing need for rapid and facile platforms which characterize therapeutic sensitivity, and enable: real-time decision making, identification of rare subpopulations with therapeutic resistance, analysis of very small samples (e.g. minimal residual disease), and preservation of viability to facilitate downstream assays that characterize phenotypic, genotypic, transcriptional and other determinants of sensitivity. My lab, together with collaborators at DFCI (Drs. Weinstock, Ligon, Munshi and Hahn) and MIT (Drs. Shalek and Lauffenburger), are addressing this need by applying new strategies for predicting therapeutic response. This approach is based on measuring multiple functional properties from the same individual cells. Measurements are acquired over relatively short time periods (several hours) following ex vivo treatment of patient tumor cells, and include transcriptomic (scRNA-Seq) and biophysical parameters (e.g. mass and mass accumulation rate) which are known to be rapidly altered by effective therapeutics and precede longer-term phenotypes (e.g. loss of viability). Cells that exhibit particular biophysical properties (e.g. responders or non-responders) are isolated and analyzed for transcriptomic determinants of these properties. In this talk, I will show progress towards applying this strategy to model systems for leukemia and glioblastoma multiforme (GBM). Our ultimate goal is to design and optimize therapeutic approaches to overcome intra-tumor heterogeneity in drug susceptibility that drive treatment failure and relapse.
Seminars are open to alumni, friends of the Department, and the general public.