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Breast cancer quantitative proteome and proteogenomic landscape
In the preceding decades, molecular characterization has revolutionized breast cancer (BC) research and therapeutic approaches. Presented herein, an unbiased analysis of breast tumor proteomes, inclusive of 9995 proteins quantified across all tumors, for the first time recapitulates BC subtypes. Add...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6453966/ https://www.ncbi.nlm.nih.gov/pubmed/30962452 http://dx.doi.org/10.1038/s41467-019-09018-y |
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author | Johansson, Henrik J. Socciarelli, Fabio Vacanti, Nathaniel M. Haugen, Mads H. Zhu, Yafeng Siavelis, Ioannis Fernandez-Woodbridge, Alejandro Aure, Miriam R. Sennblad, Bengt Vesterlund, Mattias Branca, Rui M. Orre, Lukas M. Huss, Mikael Fredlund, Erik Beraki, Elsa Garred, Øystein Boekel, Jorrit Sauer, Torill Zhao, Wei Nord, Silje Höglander, Elen K. Jans, Daniel C. Brismar, Hjalmar Haukaas, Tonje H. Bathen, Tone F. Schlichting, Ellen Naume, Bjørn Luders, Torben Borgen, Elin Kristensen, Vessela N. Russnes, Hege G. Lingjærde, Ole Christian Mills, Gordon B. Sahlberg, Kristine K. Børresen-Dale, Anne-Lise Lehtiö, Janne |
author_facet | Johansson, Henrik J. Socciarelli, Fabio Vacanti, Nathaniel M. Haugen, Mads H. Zhu, Yafeng Siavelis, Ioannis Fernandez-Woodbridge, Alejandro Aure, Miriam R. Sennblad, Bengt Vesterlund, Mattias Branca, Rui M. Orre, Lukas M. Huss, Mikael Fredlund, Erik Beraki, Elsa Garred, Øystein Boekel, Jorrit Sauer, Torill Zhao, Wei Nord, Silje Höglander, Elen K. Jans, Daniel C. Brismar, Hjalmar Haukaas, Tonje H. Bathen, Tone F. Schlichting, Ellen Naume, Bjørn Luders, Torben Borgen, Elin Kristensen, Vessela N. Russnes, Hege G. Lingjærde, Ole Christian Mills, Gordon B. Sahlberg, Kristine K. Børresen-Dale, Anne-Lise Lehtiö, Janne |
author_sort | Johansson, Henrik J. |
collection | PubMed |
description | In the preceding decades, molecular characterization has revolutionized breast cancer (BC) research and therapeutic approaches. Presented herein, an unbiased analysis of breast tumor proteomes, inclusive of 9995 proteins quantified across all tumors, for the first time recapitulates BC subtypes. Additionally, poor-prognosis basal-like and luminal B tumors are further subdivided by immune component infiltration, suggesting the current classification is incomplete. Proteome-based networks distinguish functional protein modules for breast tumor groups, with co-expression of EGFR and MET marking ductal carcinoma in situ regions of normal-like tumors and lending to a more accurate classification of this poorly defined subtype. Genes included within prognostic mRNA panels have significantly higher than average mRNA-protein correlations, and gene copy number alterations are dampened at the protein-level; underscoring the value of proteome quantification for prognostication and phenotypic classification. Furthermore, protein products mapping to non-coding genomic regions are identified; highlighting a potential new class of tumor-specific immunotherapeutic targets. |
format | Online Article Text |
id | pubmed-6453966 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-64539662019-04-10 Breast cancer quantitative proteome and proteogenomic landscape Johansson, Henrik J. Socciarelli, Fabio Vacanti, Nathaniel M. Haugen, Mads H. Zhu, Yafeng Siavelis, Ioannis Fernandez-Woodbridge, Alejandro Aure, Miriam R. Sennblad, Bengt Vesterlund, Mattias Branca, Rui M. Orre, Lukas M. Huss, Mikael Fredlund, Erik Beraki, Elsa Garred, Øystein Boekel, Jorrit Sauer, Torill Zhao, Wei Nord, Silje Höglander, Elen K. Jans, Daniel C. Brismar, Hjalmar Haukaas, Tonje H. Bathen, Tone F. Schlichting, Ellen Naume, Bjørn Luders, Torben Borgen, Elin Kristensen, Vessela N. Russnes, Hege G. Lingjærde, Ole Christian Mills, Gordon B. Sahlberg, Kristine K. Børresen-Dale, Anne-Lise Lehtiö, Janne Nat Commun Article In the preceding decades, molecular characterization has revolutionized breast cancer (BC) research and therapeutic approaches. Presented herein, an unbiased analysis of breast tumor proteomes, inclusive of 9995 proteins quantified across all tumors, for the first time recapitulates BC subtypes. Additionally, poor-prognosis basal-like and luminal B tumors are further subdivided by immune component infiltration, suggesting the current classification is incomplete. Proteome-based networks distinguish functional protein modules for breast tumor groups, with co-expression of EGFR and MET marking ductal carcinoma in situ regions of normal-like tumors and lending to a more accurate classification of this poorly defined subtype. Genes included within prognostic mRNA panels have significantly higher than average mRNA-protein correlations, and gene copy number alterations are dampened at the protein-level; underscoring the value of proteome quantification for prognostication and phenotypic classification. Furthermore, protein products mapping to non-coding genomic regions are identified; highlighting a potential new class of tumor-specific immunotherapeutic targets. Nature Publishing Group UK 2019-04-08 /pmc/articles/PMC6453966/ /pubmed/30962452 http://dx.doi.org/10.1038/s41467-019-09018-y Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Johansson, Henrik J. Socciarelli, Fabio Vacanti, Nathaniel M. Haugen, Mads H. Zhu, Yafeng Siavelis, Ioannis Fernandez-Woodbridge, Alejandro Aure, Miriam R. Sennblad, Bengt Vesterlund, Mattias Branca, Rui M. Orre, Lukas M. Huss, Mikael Fredlund, Erik Beraki, Elsa Garred, Øystein Boekel, Jorrit Sauer, Torill Zhao, Wei Nord, Silje Höglander, Elen K. Jans, Daniel C. Brismar, Hjalmar Haukaas, Tonje H. Bathen, Tone F. Schlichting, Ellen Naume, Bjørn Luders, Torben Borgen, Elin Kristensen, Vessela N. Russnes, Hege G. Lingjærde, Ole Christian Mills, Gordon B. Sahlberg, Kristine K. Børresen-Dale, Anne-Lise Lehtiö, Janne Breast cancer quantitative proteome and proteogenomic landscape |
title | 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_short | Breast cancer quantitative proteome and proteogenomic landscape |
title_sort | breast cancer quantitative proteome and proteogenomic landscape |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6453966/ https://www.ncbi.nlm.nih.gov/pubmed/30962452 http://dx.doi.org/10.1038/s41467-019-09018-y |
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