Sylvia K. Plevritis
Professor of Radiology, and by courtesy, of Management Science & Engineering
Department of Radiology
Stanford University
Optimizing Combination Cancer Therapy Based on Single Cell Analysis
To improve the effectiveness of cancer drug combination therapy, personalized treatment strategies may be required that account for intratumor heterogeneity, particularly as the tumor evolves under exposure to different drug regimes. We aim to identify optimal cancer drug combinations based on the single cell characterization of an individual patient’s intratumoral heterogeneity in response to a screening panel of single drugs. Toward this aim, we elucidate the intratumoral response to drug exposure using a systems biology approach that analyzes high-dimensional data derived from a state-of-the-art single cell technology, namely mass cytometry, using novel biocomputational algorithms. Ultimately, our goal is to personalize optimal cancer drug combinations by capturing an individual patient’s intratumoral heterogeneity through integrative single-cell based analyses using proteomic, genomic and imaging data.
