Breast cancer quantitative proteome and proteogenomic landscape

Gene expression profiles can classify breast cancer into five clinically relevant subtypes. Here, the authors perform an in-depth quantitative profiling of the proteome of 45 breast tumors, and show they can recapitulate the transcriptome-based classifications and identify many potentially antigenic...

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Autores principales:	Henrik J. Johansson, Fabio Socciarelli, Nathaniel M. Vacanti, Mads H. Haugen, Yafeng Zhu, Ioannis Siavelis, Alejandro Fernandez-Woodbridge, Miriam R. Aure, Bengt Sennblad, Mattias Vesterlund, Rui M. Branca, Lukas M. Orre, Mikael Huss, Erik Fredlund, Elsa Beraki, Øystein Garred, Jorrit Boekel, Torill Sauer, Wei Zhao, Silje Nord, Elen K. Höglander, Daniel C. Jans, Hjalmar Brismar, Tonje H. Haukaas, Tone F. Bathen, Ellen Schlichting, Bjørn Naume, Consortia Oslo Breast Cancer Research Consortium (OSBREAC), Torben Luders, Elin Borgen, Vessela N. Kristensen, Hege G. Russnes, Ole Christian Lingjærde, Gordon B. Mills, Kristine K. Sahlberg, Anne-Lise Børresen-Dale, Janne Lehtiö
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/6d38d3e496e94ae593fe7bedce5833e0
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spelling	oai:doaj.org-article:6d38d3e496e94ae593fe7bedce5833e02021-12-02T15:35:49ZBreast cancer quantitative proteome and proteogenomic landscape10.1038/s41467-019-09018-y2041-1723https://doaj.org/article/6d38d3e496e94ae593fe7bedce5833e02019-04-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-09018-yhttps://doaj.org/toc/2041-1723Gene expression profiles can classify breast cancer into five clinically relevant subtypes. Here, the authors perform an in-depth quantitative profiling of the proteome of 45 breast tumors, and show they can recapitulate the transcriptome-based classifications and identify many potentially antigenic tumour-specific peptides.Henrik J. JohanssonFabio SocciarelliNathaniel M. VacantiMads H. HaugenYafeng ZhuIoannis SiavelisAlejandro Fernandez-WoodbridgeMiriam R. AureBengt SennbladMattias VesterlundRui M. BrancaLukas M. OrreMikael HussErik FredlundElsa BerakiØystein GarredJorrit BoekelTorill SauerWei ZhaoSilje NordElen K. HöglanderDaniel C. JansHjalmar BrismarTonje H. HaukaasTone F. BathenEllen SchlichtingBjørn NaumeConsortia Oslo Breast Cancer Research Consortium (OSBREAC)Torben LudersElin BorgenVessela N. KristensenHege G. RussnesOle Christian LingjærdeGordon B. MillsKristine K. SahlbergAnne-Lise Børresen-DaleJanne LehtiöNature PortfolioarticleScienceQENNature Communications, Vol 10, Iss 1, Pp 1-14 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Henrik J. Johansson Fabio Socciarelli Nathaniel M. Vacanti Mads H. Haugen Yafeng Zhu Ioannis Siavelis Alejandro Fernandez-Woodbridge Miriam R. Aure Bengt Sennblad Mattias Vesterlund Rui M. Branca Lukas M. Orre Mikael Huss Erik Fredlund Elsa Beraki Øystein Garred Jorrit Boekel Torill Sauer Wei Zhao Silje Nord Elen K. Höglander Daniel C. Jans Hjalmar Brismar Tonje H. Haukaas Tone F. Bathen Ellen Schlichting Bjørn Naume Consortia Oslo Breast Cancer Research Consortium (OSBREAC) Torben Luders Elin Borgen Vessela N. Kristensen Hege G. Russnes Ole Christian Lingjærde Gordon B. Mills Kristine K. Sahlberg Anne-Lise Børresen-Dale Janne Lehtiö Breast cancer quantitative proteome and proteogenomic landscape
description	Gene expression profiles can classify breast cancer into five clinically relevant subtypes. Here, the authors perform an in-depth quantitative profiling of the proteome of 45 breast tumors, and show they can recapitulate the transcriptome-based classifications and identify many potentially antigenic tumour-specific peptides.
format	article
author	Henrik J. Johansson Fabio Socciarelli Nathaniel M. Vacanti Mads H. Haugen Yafeng Zhu Ioannis Siavelis Alejandro Fernandez-Woodbridge Miriam R. Aure Bengt Sennblad Mattias Vesterlund Rui M. Branca Lukas M. Orre Mikael Huss Erik Fredlund Elsa Beraki Øystein Garred Jorrit Boekel Torill Sauer Wei Zhao Silje Nord Elen K. Höglander Daniel C. Jans Hjalmar Brismar Tonje H. Haukaas Tone F. Bathen Ellen Schlichting Bjørn Naume Consortia Oslo Breast Cancer Research Consortium (OSBREAC) Torben Luders Elin Borgen Vessela N. Kristensen Hege G. Russnes Ole Christian Lingjærde Gordon B. Mills Kristine K. Sahlberg Anne-Lise Børresen-Dale Janne Lehtiö
author_facet	Henrik J. Johansson Fabio Socciarelli Nathaniel M. Vacanti Mads H. Haugen Yafeng Zhu Ioannis Siavelis Alejandro Fernandez-Woodbridge Miriam R. Aure Bengt Sennblad Mattias Vesterlund Rui M. Branca Lukas M. Orre Mikael Huss Erik Fredlund Elsa Beraki Øystein Garred Jorrit Boekel Torill Sauer Wei Zhao Silje Nord Elen K. Höglander Daniel C. Jans Hjalmar Brismar Tonje H. Haukaas Tone F. Bathen Ellen Schlichting Bjørn Naume Consortia Oslo Breast Cancer Research Consortium (OSBREAC) Torben Luders Elin Borgen Vessela N. Kristensen Hege G. Russnes Ole Christian Lingjærde Gordon B. Mills Kristine K. Sahlberg Anne-Lise Børresen-Dale Janne Lehtiö
author_sort	Henrik J. Johansson
title	Breast cancer quantitative proteome and proteogenomic landscape
title_short	Breast cancer quantitative proteome and proteogenomic landscape
title_full	Breast cancer quantitative proteome and proteogenomic landscape
title_fullStr	Breast cancer quantitative proteome and proteogenomic landscape
title_full_unstemmed	Breast cancer quantitative proteome and proteogenomic landscape
title_sort	breast cancer quantitative proteome and proteogenomic landscape
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/6d38d3e496e94ae593fe7bedce5833e0
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Breast cancer quantitative proteome and proteogenomic landscape

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