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Identification of Single Nucleotide Non-coding Driver Mutations in Cancer

Recent whole-genome sequencing studies have identified millions of somatic variants present in tumor samples. Most of these variants reside in non-coding regions of the genome potentially affecting transcriptional and post-transcriptional gene regulation. Although a few hallmark examples of driver m...

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Autores principales: Gan, Kok A., Carrasco Pro, Sebastian, Sewell, Jared A., Fuxman Bass, Juan I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5801294/
https://www.ncbi.nlm.nih.gov/pubmed/29456552
http://dx.doi.org/10.3389/fgene.2018.00016
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author Gan, Kok A.
Carrasco Pro, Sebastian
Sewell, Jared A.
Fuxman Bass, Juan I.
author_facet Gan, Kok A.
Carrasco Pro, Sebastian
Sewell, Jared A.
Fuxman Bass, Juan I.
author_sort Gan, Kok A.
collection PubMed
description Recent whole-genome sequencing studies have identified millions of somatic variants present in tumor samples. Most of these variants reside in non-coding regions of the genome potentially affecting transcriptional and post-transcriptional gene regulation. Although a few hallmark examples of driver mutations in non-coding regions have been reported, the functional role of the vast majority of somatic non-coding variants remains to be determined. This is because the few driver variants in each sample must be distinguished from the thousands of passenger variants and because the logic of regulatory element function has not yet been fully elucidated. Thus, variants prioritized based on mutational burden and location within regulatory elements need to be validated experimentally. This is generally achieved by combining assays that measure physical binding, such as chromatin immunoprecipitation, with those that determine regulatory activity, such as luciferase reporter assays. Here, we present an overview of in silico approaches used to prioritize somatic non-coding variants and the experimental methods used for functional validation and characterization.
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spelling pubmed-58012942018-02-16 Identification of Single Nucleotide Non-coding Driver Mutations in Cancer Gan, Kok A. Carrasco Pro, Sebastian Sewell, Jared A. Fuxman Bass, Juan I. Front Genet Genetics Recent whole-genome sequencing studies have identified millions of somatic variants present in tumor samples. Most of these variants reside in non-coding regions of the genome potentially affecting transcriptional and post-transcriptional gene regulation. Although a few hallmark examples of driver mutations in non-coding regions have been reported, the functional role of the vast majority of somatic non-coding variants remains to be determined. This is because the few driver variants in each sample must be distinguished from the thousands of passenger variants and because the logic of regulatory element function has not yet been fully elucidated. Thus, variants prioritized based on mutational burden and location within regulatory elements need to be validated experimentally. This is generally achieved by combining assays that measure physical binding, such as chromatin immunoprecipitation, with those that determine regulatory activity, such as luciferase reporter assays. Here, we present an overview of in silico approaches used to prioritize somatic non-coding variants and the experimental methods used for functional validation and characterization. Frontiers Media S.A. 2018-02-02 /pmc/articles/PMC5801294/ /pubmed/29456552 http://dx.doi.org/10.3389/fgene.2018.00016 Text en Copyright © 2018 Gan, Carrasco Pro, Sewell and Fuxman Bass. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Gan, Kok A.
Carrasco Pro, Sebastian
Sewell, Jared A.
Fuxman Bass, Juan I.
Identification of Single Nucleotide Non-coding Driver Mutations in Cancer
title Identification of Single Nucleotide Non-coding Driver Mutations in Cancer
title_full Identification of Single Nucleotide Non-coding Driver Mutations in Cancer
title_fullStr Identification of Single Nucleotide Non-coding Driver Mutations in Cancer
title_full_unstemmed Identification of Single Nucleotide Non-coding Driver Mutations in Cancer
title_short Identification of Single Nucleotide Non-coding Driver Mutations in Cancer
title_sort identification of single nucleotide non-coding driver mutations in cancer
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5801294/
https://www.ncbi.nlm.nih.gov/pubmed/29456552
http://dx.doi.org/10.3389/fgene.2018.00016
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