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A pan-cancer proteomic perspective on The Cancer Genome Atlas
Protein levels and function are poorly predicted by genomic and transcriptomic analysis of patient tumors. Therefore, direct study of the functional proteome has the potential to provide a wealth of information that complements and extends genomic, epigenomic and transcriptomic analysis in The Cance...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4109726/ https://www.ncbi.nlm.nih.gov/pubmed/24871328 http://dx.doi.org/10.1038/ncomms4887 |
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author | Akbani, Rehan Ng, Patrick Kwok Shing Werner, Henrica M.J. Shahmoradgoli, Maria Zhang, Fan Ju, Zhenlin Liu, Wenbin Yang, Ji-Yeon Yoshihara, Kosuke Li, Jun Ling, Shiyun Seviour, Elena G. Ram, Prahlad T. Minna, John D. Diao, Lixia Tong, Pan Heymach, John V. Hill, Steven M. Dondelinger, Frank Städler, Nicolas Byers, Lauren A. Meric-Bernstam, Funda Weinstein, John N. Broom, Bradley M. Verhaak, Roeland G.W. Liang, Han Mukherjee, Sach Lu, Yiling Mills, Gordon B. |
author_facet | Akbani, Rehan Ng, Patrick Kwok Shing Werner, Henrica M.J. Shahmoradgoli, Maria Zhang, Fan Ju, Zhenlin Liu, Wenbin Yang, Ji-Yeon Yoshihara, Kosuke Li, Jun Ling, Shiyun Seviour, Elena G. Ram, Prahlad T. Minna, John D. Diao, Lixia Tong, Pan Heymach, John V. Hill, Steven M. Dondelinger, Frank Städler, Nicolas Byers, Lauren A. Meric-Bernstam, Funda Weinstein, John N. Broom, Bradley M. Verhaak, Roeland G.W. Liang, Han Mukherjee, Sach Lu, Yiling Mills, Gordon B. |
author_sort | Akbani, Rehan |
collection | PubMed |
description | Protein levels and function are poorly predicted by genomic and transcriptomic analysis of patient tumors. Therefore, direct study of the functional proteome has the potential to provide a wealth of information that complements and extends genomic, epigenomic and transcriptomic analysis in The Cancer Genome Atlas (TCGA) projects. Here we use reverse-phase protein arrays to analyze 3,467 patient samples from 11 TCGA “Pan-Cancer” diseases, using 181 high-quality antibodies that target 128 total proteins and 53 post-translationally modified proteins. The resultant proteomic data is integrated with genomic and transcriptomic analyses of the same samples to identify commonalities, differences, emergent pathways and network biology within and across tumor lineages. In addition, tissue-specific signals are reduced computationally to enhance biomarker and target discovery spanning multiple tumor lineages. This integrative analysis, with an emphasis on pathways and potentially actionable proteins, provides a framework for determining the prognostic, predictive and therapeutic relevance of the functional proteome. |
format | Online Article Text |
id | pubmed-4109726 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
record_format | MEDLINE/PubMed |
spelling | pubmed-41097262014-11-29 A pan-cancer proteomic perspective on The Cancer Genome Atlas Akbani, Rehan Ng, Patrick Kwok Shing Werner, Henrica M.J. Shahmoradgoli, Maria Zhang, Fan Ju, Zhenlin Liu, Wenbin Yang, Ji-Yeon Yoshihara, Kosuke Li, Jun Ling, Shiyun Seviour, Elena G. Ram, Prahlad T. Minna, John D. Diao, Lixia Tong, Pan Heymach, John V. Hill, Steven M. Dondelinger, Frank Städler, Nicolas Byers, Lauren A. Meric-Bernstam, Funda Weinstein, John N. Broom, Bradley M. Verhaak, Roeland G.W. Liang, Han Mukherjee, Sach Lu, Yiling Mills, Gordon B. Nat Commun Article Protein levels and function are poorly predicted by genomic and transcriptomic analysis of patient tumors. Therefore, direct study of the functional proteome has the potential to provide a wealth of information that complements and extends genomic, epigenomic and transcriptomic analysis in The Cancer Genome Atlas (TCGA) projects. Here we use reverse-phase protein arrays to analyze 3,467 patient samples from 11 TCGA “Pan-Cancer” diseases, using 181 high-quality antibodies that target 128 total proteins and 53 post-translationally modified proteins. The resultant proteomic data is integrated with genomic and transcriptomic analyses of the same samples to identify commonalities, differences, emergent pathways and network biology within and across tumor lineages. In addition, tissue-specific signals are reduced computationally to enhance biomarker and target discovery spanning multiple tumor lineages. This integrative analysis, with an emphasis on pathways and potentially actionable proteins, provides a framework for determining the prognostic, predictive and therapeutic relevance of the functional proteome. 2014-05-29 /pmc/articles/PMC4109726/ /pubmed/24871328 http://dx.doi.org/10.1038/ncomms4887 Text en http://www.nature.com/authors/editorial_policies/license.html#terms Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms |
spellingShingle | Article Akbani, Rehan Ng, Patrick Kwok Shing Werner, Henrica M.J. Shahmoradgoli, Maria Zhang, Fan Ju, Zhenlin Liu, Wenbin Yang, Ji-Yeon Yoshihara, Kosuke Li, Jun Ling, Shiyun Seviour, Elena G. Ram, Prahlad T. Minna, John D. Diao, Lixia Tong, Pan Heymach, John V. Hill, Steven M. Dondelinger, Frank Städler, Nicolas Byers, Lauren A. Meric-Bernstam, Funda Weinstein, John N. Broom, Bradley M. Verhaak, Roeland G.W. Liang, Han Mukherjee, Sach Lu, Yiling Mills, Gordon B. A pan-cancer proteomic perspective on The Cancer Genome Atlas |
title | A pan-cancer proteomic perspective on The Cancer Genome Atlas |
title_full | A pan-cancer proteomic perspective on The Cancer Genome Atlas |
title_fullStr | A pan-cancer proteomic perspective on The Cancer Genome Atlas |
title_full_unstemmed | A pan-cancer proteomic perspective on The Cancer Genome Atlas |
title_short | A pan-cancer proteomic perspective on The Cancer Genome Atlas |
title_sort | pan-cancer proteomic perspective on the cancer genome atlas |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4109726/ https://www.ncbi.nlm.nih.gov/pubmed/24871328 http://dx.doi.org/10.1038/ncomms4887 |
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