Catch my drift? Making sense of genomic intra-tumour heterogeneity

Biochim Biophys Acta Rev Cancer. 2017 Apr;1867(2):95-100. doi: 10.1016/j.bbcan.2016.12.003. Epub 2017 Jan 7.

Abstract

The cancer genome is shaped by three components of the evolutionary process: mutation, selection and drift. While many studies have focused on the first two components, the role of drift in cancer evolution has received little attention. Drift occurs when all individuals in the population have the same likelihood of producing surviving offspring, and so by definition a drifting population is one that is evolving neutrally. Here we focus on how neutral evolution is manifested in the cancer genome. We discuss how neutral passenger mutations provide a magnifying glass that reveals the evolutionary dynamics underpinning cancer development, and outline how statistical inference can be used to quantify these dynamics from sequencing data. We argue that only after we understand the impact of neutral drift on the genome can we begin to make full sense of clonal selection. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer? Edited by Dr. Robert A. Gatenby.

Keywords: Clonal evolution of cancer; Clones; Intra-tumour heterogeneity; Neutral evolution; Next generation sequencing; Selection.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Adaptation, Physiological
  • Animals
  • Biomarkers, Tumor / genetics*
  • Biomarkers, Tumor / metabolism
  • Cell Transformation, Neoplastic / genetics*
  • Cell Transformation, Neoplastic / metabolism
  • Cell Transformation, Neoplastic / pathology
  • Evolution, Molecular*
  • Gene Expression Regulation, Neoplastic
  • Genetic Drift*
  • Genetic Fitness*
  • Genetic Heterogeneity*
  • Genetic Predisposition to Disease
  • Genomics / methods
  • Heredity
  • Humans
  • Models, Genetic
  • Mutation
  • Neoplasms / drug therapy
  • Neoplasms / genetics*
  • Neoplasms / metabolism
  • Neoplasms / pathology
  • Pedigree
  • Phenotype
  • Signal Transduction / genetics
  • Time Factors

Substances

  • Biomarkers, Tumor