How Subclonal Modeling Is Changing the Metastatic Paradigm

Clin Cancer Res. 2017 Feb 1;23(3):630-635. doi: 10.1158/1078-0432.CCR-16-0234. Epub 2016 Nov 18.

Abstract

A concerted effort to sequence matched primary and metastatic tumors is vastly improving our ability to understand metastasis in humans. Compelling evidence has emerged that supports the existence of diverse and surprising metastatic patterns. Enhancing these efforts is a new class of algorithms that facilitate high-resolution subclonal modeling of metastatic spread. Here we summarize how subclonal models of metastasis are influencing the metastatic paradigm. Clin Cancer Res; 23(3); 630-5. ©2016 AACR.

Publication types

  • Review

MeSH terms

  • Algorithms
  • Animals
  • Cell Communication
  • Cell Lineage
  • Clone Cells / pathology
  • DNA Mutational Analysis
  • DNA, Neoplasm / genetics
  • Disease Progression
  • Humans
  • Mice
  • Models, Biological*
  • Mutation
  • Neoplasm Metastasis / genetics
  • Neoplasm Metastasis / pathology*
  • Neoplasm Metastasis / physiopathology
  • Neoplastic Cells, Circulating
  • Neoplastic Stem Cells / pathology*
  • Sequence Analysis, DNA
  • Time Factors
  • Whole Genome Sequencing

Substances

  • DNA, Neoplasm