A pan-cancer proteomic perspective on the cancer genome atlas

Rehan Akbani; Patrick Kwok Shing Ng; Henrica M.J. Werner; Maria Shahmoradgoli; Fan Zhang; Zhenlin Ju; Wenbin Liu; Ji Yeon Yang; Kosuke Yoshihara; Jun Li; Shiyun Ling; Elena G. Seviour; Prahlad T. Ram; John D. Minna; Lixia Diao; Pan Tong; John V. Heymach; Steven M. Hill; Frank Dondelinger; Nicolas Städler; Lauren A. Byers; Funda Meric-Bernstam; John N. Weinstein; Bradley M. Broom; Roeland G.W. Verhaak; Han Liang; Sach Mukherjee; Yiling Lu; Gordon B. Mills

doi:10.1038/ncomms4887

A pan-cancer proteomic perspective on the cancer genome atlas

Rehan Akbani, Patrick Kwok Shing Ng, Henrica M.J. Werner, Maria Shahmoradgoli, Fan Zhang, Zhenlin Ju, Wenbin Liu, Ji Yeon Yang, Kosuke Yoshihara, Jun Li, Shiyun Ling, Elena G. Seviour, Prahlad T. Ram, John D. Minna, Lixia Diao, Pan Tong, John V. Heymach, Steven M. Hill, Frank Dondelinger, Nicolas StädlerLauren A. Byers, Funda Meric-Bernstam, John N. Weinstein, Bradley M. Broom, Roeland G.W. Verhaak, Han Liang, Sach Mukherjee, Yiling Lu, Gordon B. Mills

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350 Scopus citations

Abstract

Protein levels and function are poorly predicted by genomic and transcriptomic analysis of patient tumours. 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 analyse 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 are integrated with genomic and transcriptomic analyses of the same samples to identify commonalities, differences, emergent pathways and network biology within and across tumour lineages. In addition, tissue-specific signals are reduced computationally to enhance biomarker and target discovery spanning multiple tumour 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.

Original language	English (US)
Article number	3887
Journal	Nature communications
Volume	5
DOIs	https://doi.org/10.1038/ncomms4887
State	Published - May 29 2014
Externally published	Yes

ASJC Scopus subject areas

Chemistry(all)
Biochemistry, Genetics and Molecular Biology(all)
Physics and Astronomy(all)

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10.1038/ncomms4887

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Akbani, R., Ng, P. K. S., Werner, H. M. J., Shahmoradgoli, M., Zhang, F., Ju, Z., Liu, W., Yang, J. Y., Yoshihara, K., Li, J., Ling, S., Seviour, E. G., Ram, P. T., Minna, J. D., Diao, L., Tong, P., Heymach, J. V., Hill, S. M., Dondelinger, F., ... Mills, G. B. (2014). A pan-cancer proteomic perspective on the cancer genome atlas. Nature communications, 5, [3887]. https://doi.org/10.1038/ncomms4887

Akbani, R, Ng, PKS, Werner, HMJ, Shahmoradgoli, M, Zhang, F, Ju, Z, Liu, W, Yang, JY, Yoshihara, K, Li, J, Ling, S, Seviour, EG, Ram, PT, Minna, JD, Diao, L, Tong, P, Heymach, JV, Hill, SM, Dondelinger, F, Städler, N, Byers, LA, Meric-Bernstam, F, Weinstein, JN, Broom, BM, Verhaak, RGW, Liang, H, Mukherjee, S, Lu, Y & Mills, GB 2014, 'A pan-cancer proteomic perspective on the cancer genome atlas', Nature communications, vol. 5, 3887. https://doi.org/10.1038/ncomms4887

@article{f79aa1d6445d4296b0eacf3d0cc80c46,

title = "A pan-cancer proteomic perspective on the cancer genome atlas",

abstract = "Protein levels and function are poorly predicted by genomic and transcriptomic analysis of patient tumours. 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 analyse 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 are integrated with genomic and transcriptomic analyses of the same samples to identify commonalities, differences, emergent pathways and network biology within and across tumour lineages. In addition, tissue-specific signals are reduced computationally to enhance biomarker and target discovery spanning multiple tumour 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.",

author = "Rehan Akbani and Ng, {Patrick Kwok Shing} and Werner, {Henrica M.J.} and Maria Shahmoradgoli and Fan Zhang and Zhenlin Ju and Wenbin Liu and Yang, {Ji Yeon} and Kosuke Yoshihara and Jun Li and Shiyun Ling and Seviour, {Elena G.} and Ram, {Prahlad T.} and Minna, {John D.} and Lixia Diao and Pan Tong and Heymach, {John V.} and Hill, {Steven M.} and Frank Dondelinger and Nicolas St{\"a}dler and Byers, {Lauren A.} and Funda Meric-Bernstam and Weinstein, {John N.} and Broom, {Bradley M.} and Verhaak, {Roeland G.W.} and Han Liang and Sach Mukherjee and Yiling Lu and Mills, {Gordon B.}",

note = "Funding Information: We acknowledge contributions from the TCGA Research Network and its TCGA Pan-Cancer Analysis Working Group coordinated by J.M. Stuart, C. Sander and I. Shmulevich. This study was supported by the National Institutes of Health (TCGA CA143883 and CCSG grant P30 CA016672 to J.N.W. and G.B.M., NCI P50CA70907 to J.D.M. and J.V.H., NCI U54 CA112970 to S.M.); and by the Chapman Foundations and the Michael & Susan Dell Foundation (Lorraine Dell Program in Bioinformatics for Personalization of Cancer Medicine) to J.N.W. Additional support was provided to S.M. by the Cancer Systems Biology Center grant from the Netherlands Organisation for Scientific Research. L.A.B. acknowledges support from the UTMDACC Physician Scientist Award, LUNGevity Foundation, the North Carolina Chapter of National Lung Cancer Partnership, and The Sidney Kimmel Foundation for Cancer Research.",

year = "2014",

month = may,

day = "29",

doi = "10.1038/ncomms4887",

language = "English (US)",

volume = "5",

journal = "Nature Communications",

issn = "2041-1723",

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T1 - A pan-cancer proteomic perspective on the cancer genome atlas

AU - Akbani, Rehan

AU - Ng, Patrick Kwok Shing

AU - Werner, Henrica M.J.

AU - Shahmoradgoli, Maria

AU - Zhang, Fan

AU - Ju, Zhenlin

AU - Liu, Wenbin

AU - Yang, Ji Yeon

AU - Yoshihara, Kosuke

AU - Li, Jun

AU - Ling, Shiyun

AU - Seviour, Elena G.

AU - Ram, Prahlad T.

AU - Minna, John D.

AU - Diao, Lixia

AU - Tong, Pan

AU - Heymach, John V.

AU - Hill, Steven M.

AU - Dondelinger, Frank

AU - Städler, Nicolas

AU - Byers, Lauren A.

AU - Meric-Bernstam, Funda

AU - Weinstein, John N.

AU - Broom, Bradley M.

AU - Verhaak, Roeland G.W.

AU - Liang, Han

AU - Mukherjee, Sach

AU - Lu, Yiling

AU - Mills, Gordon B.

N1 - Funding Information: We acknowledge contributions from the TCGA Research Network and its TCGA Pan-Cancer Analysis Working Group coordinated by J.M. Stuart, C. Sander and I. Shmulevich. This study was supported by the National Institutes of Health (TCGA CA143883 and CCSG grant P30 CA016672 to J.N.W. and G.B.M., NCI P50CA70907 to J.D.M. and J.V.H., NCI U54 CA112970 to S.M.); and by the Chapman Foundations and the Michael & Susan Dell Foundation (Lorraine Dell Program in Bioinformatics for Personalization of Cancer Medicine) to J.N.W. Additional support was provided to S.M. by the Cancer Systems Biology Center grant from the Netherlands Organisation for Scientific Research. L.A.B. acknowledges support from the UTMDACC Physician Scientist Award, LUNGevity Foundation, the North Carolina Chapter of National Lung Cancer Partnership, and The Sidney Kimmel Foundation for Cancer Research.

PY - 2014/5/29

Y1 - 2014/5/29

N2 - Protein levels and function are poorly predicted by genomic and transcriptomic analysis of patient tumours. 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 analyse 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 are integrated with genomic and transcriptomic analyses of the same samples to identify commonalities, differences, emergent pathways and network biology within and across tumour lineages. In addition, tissue-specific signals are reduced computationally to enhance biomarker and target discovery spanning multiple tumour 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.

AB - Protein levels and function are poorly predicted by genomic and transcriptomic analysis of patient tumours. 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 analyse 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 are integrated with genomic and transcriptomic analyses of the same samples to identify commonalities, differences, emergent pathways and network biology within and across tumour lineages. In addition, tissue-specific signals are reduced computationally to enhance biomarker and target discovery spanning multiple tumour 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.

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A pan-cancer proteomic perspective on the cancer genome atlas

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