title: Cancer Evolution and the Limits of Predictability in Precision Cancer Medicine.
abstract: The ability to predict the future behavior of an individual cancer is crucial for precision cancer medicine. The discovery of extensive intratumor heterogeneity and ongoing clonal adaptation in human tumors substantiated the notion of cancer as an evolutionary process. Random events are inherent in evolution and tumor spatial structures hinder the efficacy of selection, which is the only deterministic evolutionary force. This review outlines how the interaction of these stochastic and deterministic processes, which have been extensively studied in evolutionary biology, limits cancer predictability and develops evolutionary strategies to improve predictions. Understanding and advancing the cancer predictability horizon is crucial to improve precision medicine outcomes.
authors.affiliation: Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK.
authors.forename: Kamil A
authors.initials: KA
authors.lastname: Lipinski
authors.affiliation: Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK.
authors.forename: Louise J
authors.initials: LJ
authors.lastname: Barber
authors.affiliation: Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK.
authors.forename: Matthew N
authors.initials: MN
authors.lastname: Davies
authors.affiliation: Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK.
authors.forename: Matthew
authors.initials: M
authors.lastname: Ashenden
authors.affiliation: Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK.
authors.forename: Andrea
authors.initials: A
authors.lastname: Sottoriva
authors.affiliation: Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK; Gastrointestinal Cancer Unit, The Royal Marsden Hospital, London, UK. Electronic address: marco.gerlinger@icr.ac.uk.
authors.forename: Marco
authors.initials: M
authors.lastname: Gerlinger
keywords: cancer evolution; cancer genetics; drug resistance; precision cancer medicine; predictive biomarkers; prognostic biomarkers