title: Advances in understanding tumour evolution through single-cell sequencing.
abstract: The mutational heterogeneity observed within tumours poses additional challenges to the development of effective cancer treatments. A thorough understanding of a tumour's subclonal composition and its mutational history is essential to open up the design of treatments tailored to individual patients. Comparative studies on a large number of tumours permit the identification of mutational patterns which may refine forecasts of cancer progression, response to treatment and metastatic potential. The composition of tumours is shaped by evolutionary processes. Recent advances in next-generation sequencing offer the possibility to analyse the evolutionary history and accompanying heterogeneity of tumours at an unprecedented resolution, by sequencing single cells. New computational challenges arise when moving from bulk to single-cell sequencing data, leading to the development of novel modelling frameworks. In this review, we present the state of the art methods for understanding the phylogeny encoded in bulk or single-cell sequencing data, and highlight future directions for developing more comprehensive and informative pictures of tumour evolution. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.
authors.affiliation: Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland; Swiss Institute of Bioinformatics, Basel, Switzerland.
authors.forename: Jack
authors.initials: J
authors.lastname: Kuipers
authors.affiliation: Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland; Swiss Institute of Bioinformatics, Basel, Switzerland.
authors.forename: Katharina
authors.initials: K
authors.lastname: Jahn
authors.affiliation: Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland; Swiss Institute of Bioinformatics, Basel, Switzerland.
authors.forename: Niko
authors.initials: N
authors.lastname: Beerenwinkel
mesh_terms: D000222:Adaptation, Physiological; D000818:Animals; D014408:Biomarkers, Tumor / Q000235:genetics* / Q000378:metabolism; D002471:Cell Transformation, Neoplastic / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D019143:Evolution, Molecular; D015972:Gene Expression Regulation, Neoplastic; D056084:Genetic Fitness; D018740:Genetic Heterogeneity; D020022:Genetic Predisposition to Disease; D040941:Heredity; D006801:Humans; D008957:Models, Genetic; D009154:Mutation; D009369:Neoplasms / Q000188:drug therapy / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D010375:Pedigree; D010641:Phenotype; D010802:Phylogeny; D017422:Sequence Analysis, DNA; D015398:Signal Transduction / Q000235:genetics; D059010:Single-Cell Analysis / Q000379:methods*; D013997:Time Factors
chemical_list: D014408:Biomarkers, Tumor
keywords: Cancer evolution; Phylogenetics; Single-cell sequencing; Tumour heterogeneity