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Quantitative Trait Loci Identify Functional Noncoding Variation in Cancer

The interpretation of noncoding alterations in cancer genomes presents an unresolved problem in cancer studies. While the impact of somatic variations in protein-coding regions is widely accepted, noncoding aberrations are mostly considered as passenger events. However, with the advance of genome-wi...

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Autor principal: Heyn, Holger
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4777413/
https://www.ncbi.nlm.nih.gov/pubmed/26938653
http://dx.doi.org/10.1371/journal.pgen.1005826
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author Heyn, Holger
author_facet Heyn, Holger
author_sort Heyn, Holger
collection PubMed
description The interpretation of noncoding alterations in cancer genomes presents an unresolved problem in cancer studies. While the impact of somatic variations in protein-coding regions is widely accepted, noncoding aberrations are mostly considered as passenger events. However, with the advance of genome-wide profiling strategies, alterations outside the coding context entered the focus, and multiple examples highlight the role of gene deregulation as cancer-driving events. This review describes the implication of noncoding alterations in oncogenesis and provides a theoretical framework for the identification of causal somatic variants using quantitative trait loci (QTL) analysis. Assuming that functional noncoding alterations affect quantifiable regulatory processes, somatic QTL studies constitute a valuable strategy to pinpoint cancer gene deregulation. Eventually, the comprehensive identification and interpretation of coding and noncoding alterations will guide our future understanding of cancer biology.
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spelling pubmed-47774132016-03-10 Quantitative Trait Loci Identify Functional Noncoding Variation in Cancer Heyn, Holger PLoS Genet Review The interpretation of noncoding alterations in cancer genomes presents an unresolved problem in cancer studies. While the impact of somatic variations in protein-coding regions is widely accepted, noncoding aberrations are mostly considered as passenger events. However, with the advance of genome-wide profiling strategies, alterations outside the coding context entered the focus, and multiple examples highlight the role of gene deregulation as cancer-driving events. This review describes the implication of noncoding alterations in oncogenesis and provides a theoretical framework for the identification of causal somatic variants using quantitative trait loci (QTL) analysis. Assuming that functional noncoding alterations affect quantifiable regulatory processes, somatic QTL studies constitute a valuable strategy to pinpoint cancer gene deregulation. Eventually, the comprehensive identification and interpretation of coding and noncoding alterations will guide our future understanding of cancer biology. Public Library of Science 2016-03-03 /pmc/articles/PMC4777413/ /pubmed/26938653 http://dx.doi.org/10.1371/journal.pgen.1005826 Text en © 2016 Holger Heyn http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Review
Heyn, Holger
Quantitative Trait Loci Identify Functional Noncoding Variation in Cancer
title Quantitative Trait Loci Identify Functional Noncoding Variation in Cancer
title_full Quantitative Trait Loci Identify Functional Noncoding Variation in Cancer
title_fullStr Quantitative Trait Loci Identify Functional Noncoding Variation in Cancer
title_full_unstemmed Quantitative Trait Loci Identify Functional Noncoding Variation in Cancer
title_short Quantitative Trait Loci Identify Functional Noncoding Variation in Cancer
title_sort quantitative trait loci identify functional noncoding variation in cancer
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4777413/
https://www.ncbi.nlm.nih.gov/pubmed/26938653
http://dx.doi.org/10.1371/journal.pgen.1005826
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