The unit of evolutionary selection in cancer is the cell. Extraordinary progress in measurement technologies has made it possible to reliably and accurately sequence the genomes of individual cancer cells at scale. We have recently optimized biophysical techniques and hidden Markov model approaches to ascertain highly accurate copy number profiles of thousands of cancer cells. As such, studying the ‘population genetics’ of cancer cells is a tractable goal. We are developing phylogenetics and fitness computational models through measuring the population dynamics of thousands of individual cancer cells across timeseries, spatial samples and in the presence of genetic and pharmacologic intervention. These experiments and computational methods are improving our knowledge of background mutation rates, properties of positive and negative selection (not observable in bulk samples) and how phylogenetic topologies reflect the relative fitness of clones. Furthermore, as we integrate multi-modal measurements, profiling the evolving malignant population in the context of its tumour microenvironment will be a strong interest of the lab.
Single cell genomics of cancer
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