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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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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 |
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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 |
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