Cargando…

Challenges in identifying cancer genes by analysis of exome sequencing data

Massively parallel sequencing has permitted an unprecedented examination of the cancer exome, leading to predictions that all genes important to cancer will soon be identified by genetic analysis of tumours. To examine this potential, here we evaluate the ability of state-of-the-art sequence analysi...

Descripción completa

Detalles Bibliográficos
Autores principales: Hofree, Matan, Carter, Hannah, Kreisberg, Jason F., Bandyopadhyay, Sourav, Mischel, Paul S., Friend, Stephen, Ideker, Trey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4947162/
https://www.ncbi.nlm.nih.gov/pubmed/27417679
http://dx.doi.org/10.1038/ncomms12096
_version_ 1782443122236588032
author Hofree, Matan
Carter, Hannah
Kreisberg, Jason F.
Bandyopadhyay, Sourav
Mischel, Paul S.
Friend, Stephen
Ideker, Trey
author_facet Hofree, Matan
Carter, Hannah
Kreisberg, Jason F.
Bandyopadhyay, Sourav
Mischel, Paul S.
Friend, Stephen
Ideker, Trey
author_sort Hofree, Matan
collection PubMed
description Massively parallel sequencing has permitted an unprecedented examination of the cancer exome, leading to predictions that all genes important to cancer will soon be identified by genetic analysis of tumours. To examine this potential, here we evaluate the ability of state-of-the-art sequence analysis methods to specifically recover known cancer genes. While some cancer genes are identified by analysis of recurrence, spatial clustering or predicted impact of somatic mutations, many remain undetected due to lack of power to discriminate driver mutations from the background mutational load (13–60% recall of cancer genes impacted by somatic single-nucleotide variants, depending on the method). Cancer genes not detected by mutation recurrence also tend to be missed by all types of exome analysis. Nonetheless, these genes are implicated by other experiments such as functional genetic screens and expression profiling. These challenges are only partially addressed by increasing sample size and will likely hold even as greater numbers of tumours are analysed.
format Online
Article
Text
id pubmed-4947162
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Nature Publishing Group
record_format MEDLINE/PubMed
spelling pubmed-49471622016-07-27 Challenges in identifying cancer genes by analysis of exome sequencing data Hofree, Matan Carter, Hannah Kreisberg, Jason F. Bandyopadhyay, Sourav Mischel, Paul S. Friend, Stephen Ideker, Trey Nat Commun Article Massively parallel sequencing has permitted an unprecedented examination of the cancer exome, leading to predictions that all genes important to cancer will soon be identified by genetic analysis of tumours. To examine this potential, here we evaluate the ability of state-of-the-art sequence analysis methods to specifically recover known cancer genes. While some cancer genes are identified by analysis of recurrence, spatial clustering or predicted impact of somatic mutations, many remain undetected due to lack of power to discriminate driver mutations from the background mutational load (13–60% recall of cancer genes impacted by somatic single-nucleotide variants, depending on the method). Cancer genes not detected by mutation recurrence also tend to be missed by all types of exome analysis. Nonetheless, these genes are implicated by other experiments such as functional genetic screens and expression profiling. These challenges are only partially addressed by increasing sample size and will likely hold even as greater numbers of tumours are analysed. Nature Publishing Group 2016-07-15 /pmc/articles/PMC4947162/ /pubmed/27417679 http://dx.doi.org/10.1038/ncomms12096 Text en Copyright © 2016, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Hofree, Matan
Carter, Hannah
Kreisberg, Jason F.
Bandyopadhyay, Sourav
Mischel, Paul S.
Friend, Stephen
Ideker, Trey
Challenges in identifying cancer genes by analysis of exome sequencing data
title Challenges in identifying cancer genes by analysis of exome sequencing data
title_full Challenges in identifying cancer genes by analysis of exome sequencing data
title_fullStr Challenges in identifying cancer genes by analysis of exome sequencing data
title_full_unstemmed Challenges in identifying cancer genes by analysis of exome sequencing data
title_short Challenges in identifying cancer genes by analysis of exome sequencing data
title_sort challenges in identifying cancer genes by analysis of exome sequencing data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4947162/
https://www.ncbi.nlm.nih.gov/pubmed/27417679
http://dx.doi.org/10.1038/ncomms12096
work_keys_str_mv AT hofreematan challengesinidentifyingcancergenesbyanalysisofexomesequencingdata
AT carterhannah challengesinidentifyingcancergenesbyanalysisofexomesequencingdata
AT kreisbergjasonf challengesinidentifyingcancergenesbyanalysisofexomesequencingdata
AT bandyopadhyaysourav challengesinidentifyingcancergenesbyanalysisofexomesequencingdata
AT mischelpauls challengesinidentifyingcancergenesbyanalysisofexomesequencingdata
AT friendstephen challengesinidentifyingcancergenesbyanalysisofexomesequencingdata
AT idekertrey challengesinidentifyingcancergenesbyanalysisofexomesequencingdata