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Prominent features of the amino acid mutation landscape in cancer
Cancer can be viewed as a set of different diseases with distinctions based on tissue origin, driver mutations, and genetic signatures. Accordingly, each of these distinctions have been used to classify cancer subtypes and to reveal common features. Here, we present a different analysis of cancer ba...
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/PMC5570307/ https://www.ncbi.nlm.nih.gov/pubmed/28837668 http://dx.doi.org/10.1371/journal.pone.0183273 |
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author | Szpiech, Zachary A. Strauli, Nicolas B. White, Katharine A. Ruiz, Diego Garrido Jacobson, Matthew P. Barber, Diane L. Hernandez, Ryan D. |
author_facet | Szpiech, Zachary A. Strauli, Nicolas B. White, Katharine A. Ruiz, Diego Garrido Jacobson, Matthew P. Barber, Diane L. Hernandez, Ryan D. |
author_sort | Szpiech, Zachary A. |
collection | PubMed |
description | Cancer can be viewed as a set of different diseases with distinctions based on tissue origin, driver mutations, and genetic signatures. Accordingly, each of these distinctions have been used to classify cancer subtypes and to reveal common features. Here, we present a different analysis of cancer based on amino acid mutation signatures. Non-negative Matrix Factorization and principal component analysis of 29 cancers revealed six amino acid mutation signatures, including four signatures that were dominated by either arginine to histidine (Arg>His) or glutamate to lysine (Glu>Lys) mutations. Sample-level analyses reveal that while some cancers are heterogeneous, others are largely dominated by one type of mutation. Using a non-overlapping set of samples from the COSMIC somatic mutation database, we validate five of six mutation signatures, including signatures with prominent arginine to histidine (Arg>His) or glutamate to lysine (Glu>Lys) mutations. This suggests that our classification of cancers based on amino acid mutation patterns may provide avenues of inquiry pertaining to specific protein mutations that may generate novel insights into cancer biology. |
format | Online Article Text |
id | pubmed-5570307 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-55703072017-09-09 Prominent features of the amino acid mutation landscape in cancer Szpiech, Zachary A. Strauli, Nicolas B. White, Katharine A. Ruiz, Diego Garrido Jacobson, Matthew P. Barber, Diane L. Hernandez, Ryan D. PLoS One Research Article Cancer can be viewed as a set of different diseases with distinctions based on tissue origin, driver mutations, and genetic signatures. Accordingly, each of these distinctions have been used to classify cancer subtypes and to reveal common features. Here, we present a different analysis of cancer based on amino acid mutation signatures. Non-negative Matrix Factorization and principal component analysis of 29 cancers revealed six amino acid mutation signatures, including four signatures that were dominated by either arginine to histidine (Arg>His) or glutamate to lysine (Glu>Lys) mutations. Sample-level analyses reveal that while some cancers are heterogeneous, others are largely dominated by one type of mutation. Using a non-overlapping set of samples from the COSMIC somatic mutation database, we validate five of six mutation signatures, including signatures with prominent arginine to histidine (Arg>His) or glutamate to lysine (Glu>Lys) mutations. This suggests that our classification of cancers based on amino acid mutation patterns may provide avenues of inquiry pertaining to specific protein mutations that may generate novel insights into cancer biology. Public Library of Science 2017-08-24 /pmc/articles/PMC5570307/ /pubmed/28837668 http://dx.doi.org/10.1371/journal.pone.0183273 Text en © 2017 Szpiech 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 Szpiech, Zachary A. Strauli, Nicolas B. White, Katharine A. Ruiz, Diego Garrido Jacobson, Matthew P. Barber, Diane L. Hernandez, Ryan D. Prominent features of the amino acid mutation landscape in cancer |
title | Prominent features of the amino acid mutation landscape in cancer |
title_full | Prominent features of the amino acid mutation landscape in cancer |
title_fullStr | Prominent features of the amino acid mutation landscape in cancer |
title_full_unstemmed | Prominent features of the amino acid mutation landscape in cancer |
title_short | Prominent features of the amino acid mutation landscape in cancer |
title_sort | prominent features of the amino acid mutation landscape in cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5570307/ https://www.ncbi.nlm.nih.gov/pubmed/28837668 http://dx.doi.org/10.1371/journal.pone.0183273 |
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