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Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres
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Published on: July 22, 2020

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Non-coding driver mutations in human cancer

Kerryn Elliott1, Erik Larsson2

  • 1Department of Medical Biochemistry and Cell Biology, Institute of Biomedicine, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden.

Nature Reviews. Cancer
|July 7, 2021
PubMed

Insights

Cancer develops from random mutations, with driver mutations being key. While protein-coding mutations are well-studied, non-coding driver mutations are rare but significant, posing detection challenges.

Area of Science:

  • Genomics
  • Cancer Biology
  • Evolutionary Medicine

Background:

  • Tumorigenesis arises from random mutations and evolutionary selection of driver mutations.
  • Exome sequencing has identified numerous protein-coding somatic driver mutations, some clinically actionable.
  • Whole-genome analysis is advancing, enabling exploration of non-coding regions for driver mutations.

Purpose of the Study:

  • To review recent findings on non-coding driver mutations.
  • To discuss the challenges in identifying selection signals in non-coding DNA.
  • To explore reasons for the apparent infrequency of non-coding driver events.

Main Methods:

  • Review of current literature on cancer genomics and driver mutation discovery.
  • Analysis of challenges in detecting positive selection in non-coding DNA.
  • Comparative analysis of coding versus non-coding mutation landscapes.

Main Results:

  • Non-coding driver mutations appear relatively infrequent compared to coding mutations.
  • Despite their rarity, several notable non-coding driver mutations have been identified.
  • Detecting selection signals in the vast non-coding DNA remains a significant challenge.

Conclusions:

  • The landscape of cancer driver mutations is expanding beyond protein-coding regions.
  • Further research is needed to overcome challenges in identifying non-coding driver mutations.
  • Understanding non-coding drivers is crucial for a comprehensive view of tumorigenesis.

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