Statistiskt seminarium

Abstract: Tumour heterogeneity is an important driver of treatment failure in cancer, as therapies often select for drug-tolerant or drug-resistant cellular subpopulations that drive tumour growth and recurrence. Profiling the drug-response heterogeneity of tumour samples using traditional genomic deconvolution methods has yielded limited results, due in part to the imperfect mapping between genomic variation and functional characteristics. In this seminar, I will demonstrate how to leverage mechanistic population modeling to develop a statistical framework for profiling phenotypic heterogeneity from standard drug-screen data on bulk tumour samples. This approach allows us to reliably identify tumour subpopulations exhibiting differential drug responses and estimate their drug sensitivities and frequencies within the bulk population. I will discuss the advantages and disadvantages of using deterministic versus stochastic birth-death population models. These methods are applied to synthetically generated cell populations, mixed cell-line in vitro experiments, and multiple myeloma patient samples.