Measuring evolutionary cancer dynamics from genome sequencing, one patient at a time
Caravagna Giulio ()
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Caravagna Giulio: Department of Mathematics and Geosciences, University of Trieste, Via Valerio 12/1, 34127, Trieste, Italy
Statistical Applications in Genetics and Molecular Biology, 2020, vol. 19, issue 4-6, 12
Cancers progress through the accumulation of somatic mutations which accrue during tumour evolution, allowing some cells to proliferate in an uncontrolled fashion. This growth process is intimately related to latent evolutionary forces moulding the genetic and epigenetic composition of tumour subpopulations. Understanding cancer requires therefore the understanding of these selective pressures. The adoption of widespread next-generation sequencing technologies opens up for the possibility of measuring molecular profiles of cancers at multiple resolutions, across one or multiple patients. In this review we discuss how cancer genome sequencing data from a single tumour can be used to understand these evolutionary forces, overviewing mathematical models and inferential methods adopted in field of Cancer Evolution.
Keywords: bulk genome sequencing; clonal evolution; subclonal deconvolution (search for similar items in EconPapers)
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