Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Szpiech, Zachary A., Strauli, Nicolas B., White, Katharine A., Ruiz, Diego Garrido, Jacobson, Matthew P., Barber, Diane L., Hernandez, Ryan D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
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
_version_ 1783259155805503488
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
work_keys_str_mv AT szpiechzacharya prominentfeaturesoftheaminoacidmutationlandscapeincancer
AT straulinicolasb prominentfeaturesoftheaminoacidmutationlandscapeincancer
AT whitekatharinea prominentfeaturesoftheaminoacidmutationlandscapeincancer
AT ruizdiegogarrido prominentfeaturesoftheaminoacidmutationlandscapeincancer
AT jacobsonmatthewp prominentfeaturesoftheaminoacidmutationlandscapeincancer
AT barberdianel prominentfeaturesoftheaminoacidmutationlandscapeincancer
AT hernandezryand prominentfeaturesoftheaminoacidmutationlandscapeincancer