Advances for studying clonal evolution in cancer

Cancer Lett. 2013 Nov 1;340(2):212-9. doi: 10.1016/j.canlet.2012.12.028. Epub 2013 Jan 23.

Abstract

The "clonal evolution" model of cancer emerged and "evolved" amid ongoing advances in technology, especially in recent years during which next generation sequencing instruments have provided ever higher resolution pictures of the genetic changes in cancer cells and heterogeneity in tumors. It has become increasingly clear that clonal evolution is not a single sequential process, but instead frequently involves simultaneous evolution of multiple subclones that co-exist because they are of similar fitness or are spatially separated. Co-evolution of subclones also occurs when they complement each other's survival advantages. Recent studies have also shown that clonal evolution is highly heterogeneous: different individual tumors of the same type may undergo very different paths of clonal evolution. New methodological advancements, including deep digital sequencing of a mixed tumor population, single cell sequencing, and the development of more sophisticated computational tools, will continue to shape and reshape the models of clonal evolution. In turn, these will provide both an improved framework for the understanding of cancer progression and a guide for treatment strategies aimed at the elimination of all, rather than just some, of the cancer cells within a patient.

Keywords: Cancer; Clonal evolution; Tumor heterogeneity.

Publication types

  • Research Support, N.I.H., Extramural
  • Review

MeSH terms

  • Animals
  • Biomarkers, Tumor / genetics*
  • Clonal Evolution*
  • Computational Biology
  • Gene Expression Profiling
  • Gene Expression Regulation, Neoplastic
  • Genetic Predisposition to Disease
  • Genetic Testing
  • Genome, Human*
  • Genomics / methods*
  • Humans
  • Neoplasms / diagnosis
  • Neoplasms / genetics*
  • Neoplasms / therapy
  • Neoplastic Stem Cells / metabolism*
  • Neoplastic Stem Cells / pathology
  • Phenotype
  • Precision Medicine
  • Predictive Value of Tests
  • Prognosis
  • Sequence Analysis, DNA*

Substances

  • Biomarkers, Tumor