Cargando…

Oncodomains: A protein domain-centric framework for analyzing rare variants in tumor samples

The fight against cancer is hindered by its highly heterogeneous nature. Genome-wide sequencing studies have shown that individual malignancies contain many mutations that range from those commonly found in tumor genomes to rare somatic variants present only in a small fraction of lesions. Such rare...

Descripción completa

Detalles Bibliográficos
Autores principales: Peterson, Thomas A., Gauran, Iris Ivy M., Park, Junyong, Park, DoHwan, Kann, Maricel G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5398485/
https://www.ncbi.nlm.nih.gov/pubmed/28426665
http://dx.doi.org/10.1371/journal.pcbi.1005428
_version_ 1783230469280628736
author Peterson, Thomas A.
Gauran, Iris Ivy M.
Park, Junyong
Park, DoHwan
Kann, Maricel G.
author_facet Peterson, Thomas A.
Gauran, Iris Ivy M.
Park, Junyong
Park, DoHwan
Kann, Maricel G.
author_sort Peterson, Thomas A.
collection PubMed
description The fight against cancer is hindered by its highly heterogeneous nature. Genome-wide sequencing studies have shown that individual malignancies contain many mutations that range from those commonly found in tumor genomes to rare somatic variants present only in a small fraction of lesions. Such rare somatic variants dominate the landscape of genomic mutations in cancer, yet efforts to correlate somatic mutations found in one or few individuals with functional roles have been largely unsuccessful. Traditional methods for identifying somatic variants that drive cancer are ‘gene-centric’ in that they consider only somatic variants within a particular gene and make no comparison to other similar genes in the same family that may play a similar role in cancer. In this work, we present oncodomain hotspots, a new ‘domain-centric’ method for identifying clusters of somatic mutations across entire gene families using protein domain models. Our analysis confirms that our approach creates a framework for leveraging structural and functional information encapsulated by protein domains into the analysis of somatic variants in cancer, enabling the assessment of even rare somatic variants by comparison to similar genes. Our results reveal a vast landscape of somatic variants that act at the level of domain families altering pathways known to be involved with cancer such as protein phosphorylation, signaling, gene regulation, and cell metabolism. Due to oncodomain hotspots’ unique ability to assess rare variants, we expect our method to become an important tool for the analysis of sequenced tumor genomes, complementing existing methods.
format Online
Article
Text
id pubmed-5398485
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-53984852017-05-04 Oncodomains: A protein domain-centric framework for analyzing rare variants in tumor samples Peterson, Thomas A. Gauran, Iris Ivy M. Park, Junyong Park, DoHwan Kann, Maricel G. PLoS Comput Biol Research Article The fight against cancer is hindered by its highly heterogeneous nature. Genome-wide sequencing studies have shown that individual malignancies contain many mutations that range from those commonly found in tumor genomes to rare somatic variants present only in a small fraction of lesions. Such rare somatic variants dominate the landscape of genomic mutations in cancer, yet efforts to correlate somatic mutations found in one or few individuals with functional roles have been largely unsuccessful. Traditional methods for identifying somatic variants that drive cancer are ‘gene-centric’ in that they consider only somatic variants within a particular gene and make no comparison to other similar genes in the same family that may play a similar role in cancer. In this work, we present oncodomain hotspots, a new ‘domain-centric’ method for identifying clusters of somatic mutations across entire gene families using protein domain models. Our analysis confirms that our approach creates a framework for leveraging structural and functional information encapsulated by protein domains into the analysis of somatic variants in cancer, enabling the assessment of even rare somatic variants by comparison to similar genes. Our results reveal a vast landscape of somatic variants that act at the level of domain families altering pathways known to be involved with cancer such as protein phosphorylation, signaling, gene regulation, and cell metabolism. Due to oncodomain hotspots’ unique ability to assess rare variants, we expect our method to become an important tool for the analysis of sequenced tumor genomes, complementing existing methods. Public Library of Science 2017-04-20 /pmc/articles/PMC5398485/ /pubmed/28426665 http://dx.doi.org/10.1371/journal.pcbi.1005428 Text en © 2017 Peterson et al 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 Research Article
Peterson, Thomas A.
Gauran, Iris Ivy M.
Park, Junyong
Park, DoHwan
Kann, Maricel G.
Oncodomains: A protein domain-centric framework for analyzing rare variants in tumor samples
title Oncodomains: A protein domain-centric framework for analyzing rare variants in tumor samples
title_full Oncodomains: A protein domain-centric framework for analyzing rare variants in tumor samples
title_fullStr Oncodomains: A protein domain-centric framework for analyzing rare variants in tumor samples
title_full_unstemmed Oncodomains: A protein domain-centric framework for analyzing rare variants in tumor samples
title_short Oncodomains: A protein domain-centric framework for analyzing rare variants in tumor samples
title_sort oncodomains: a protein domain-centric framework for analyzing rare variants in tumor samples
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5398485/
https://www.ncbi.nlm.nih.gov/pubmed/28426665
http://dx.doi.org/10.1371/journal.pcbi.1005428
work_keys_str_mv AT petersonthomasa oncodomainsaproteindomaincentricframeworkforanalyzingrarevariantsintumorsamples
AT gauranirisivym oncodomainsaproteindomaincentricframeworkforanalyzingrarevariantsintumorsamples
AT parkjunyong oncodomainsaproteindomaincentricframeworkforanalyzingrarevariantsintumorsamples
AT parkdohwan oncodomainsaproteindomaincentricframeworkforanalyzingrarevariantsintumorsamples
AT kannmaricelg oncodomainsaproteindomaincentricframeworkforanalyzingrarevariantsintumorsamples