Using large-scale genome variation cohorts to decipher the molecular mechanism of cancer

C R Biol. 2016 Jul-Aug;339(7-8):308-13. doi: 10.1016/j.crvi.2016.05.008. Epub 2016 Jun 21.

Abstract

Characterizing genomic structural variations (SVs) in the human genome remains challenging, and there is a growing interest to understand somatic SVs occurring in cancer, a disease of the genome. A havoc-causing SV process known as chromothripsis scars the genome when localized chromosome shattering and repair occur in a one-off catastrophe. Recent efforts led to the development of a set of conceptual criteria for the inference of chromothripsis events in cancer genomes and to the development of experimental model systems for studying this striking DNA alteration process in vitro. We discuss these approaches, and additionally touch upon current "Big Data" efforts that employ hybrid cloud computing to enable studies of numerous cancer genomes in an effort to search for commonalities and differences in molecular DNA alteration processes in cancer.

Keywords: Big data; Cancer genomics; Chromothripsie; Chromothripsis; Genetic variation; Génomique du cancer; Hybrid cloud; Informatique en nuages hybrides; Mégadonnées; Structural variation; Variation génétique; Variation structurale.

Publication types

  • Review

MeSH terms

  • Animals
  • Antineoplastic Agents / pharmacology
  • Antineoplastic Agents / therapeutic use
  • Genome, Human
  • Genomic Structural Variation / drug effects
  • Genomic Structural Variation / genetics*
  • Humans
  • Molecular Biology
  • Neoplasms / drug therapy
  • Neoplasms / genetics*

Substances

  • Antineoplastic Agents