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 () and Gordon B. Mills ()
Additional contact information
Rehan Akbani: 1400 Pressler St., The University of Texas MD Anderson Cancer Center
Patrick Kwok Shing Ng: 1515 Holcombe Blvd, The University of Texas MD Anderson Cancer Center
Henrica M. J. Werner: 1515 Holcombe Blvd, The University of Texas MD Anderson Cancer Center
Maria Shahmoradgoli: 1515 Holcombe Blvd, The University of Texas MD Anderson Cancer Center
Fan Zhang: 1515 Holcombe Blvd, The University of Texas MD Anderson Cancer Center
Zhenlin Ju: 1400 Pressler St., The University of Texas MD Anderson Cancer Center
Wenbin Liu: 1400 Pressler St., The University of Texas MD Anderson Cancer Center
Ji-Yeon Yang: 1400 Pressler St., The University of Texas MD Anderson Cancer Center
Kosuke Yoshihara: 1400 Pressler St., The University of Texas MD Anderson Cancer Center
Jun Li: 1400 Pressler St., The University of Texas MD Anderson Cancer Center
Shiyun Ling: 1400 Pressler St., The University of Texas MD Anderson Cancer Center
Elena G. Seviour: 1515 Holcombe Blvd, The University of Texas MD Anderson Cancer Center
Prahlad T. Ram: 1515 Holcombe Blvd, The University of Texas MD Anderson Cancer Center
John D. Minna: Hamon Center for Therapeutic Oncology, Internal Medicine, Pharmacology, 1801 Inwood Rd, University of Texas Southwestern Medical Center
Lixia Diao: 1400 Pressler St., The University of Texas MD Anderson Cancer Center
Pan Tong: 1400 Pressler St., The University of Texas MD Anderson Cancer Center
John V. Heymach: 1515 Holcombe Blvd, The University of Texas MD Anderson Cancer Center
Steven M. Hill: Medical Research Council Biostatistics Unit
Frank Dondelinger: Medical Research Council Biostatistics Unit
Nicolas Städler: Medical Research Council Biostatistics Unit
Lauren A. Byers: 1515 Holcombe Blvd, The University of Texas MD Anderson Cancer Center
Funda Meric-Bernstam: 1515 Holcombe Blvd, The University of Texas MD Anderson Cancer Center
John N. Weinstein: 1400 Pressler St., The University of Texas MD Anderson Cancer Center
Bradley M. Broom: 1400 Pressler St., The University of Texas MD Anderson Cancer Center
Roeland G. W. Verhaak: 1400 Pressler St., The University of Texas MD Anderson Cancer Center
Han Liang: 1400 Pressler St., The University of Texas MD Anderson Cancer Center
Sach Mukherjee: Medical Research Council Biostatistics Unit
Yiling Lu: 1515 Holcombe Blvd, The University of Texas MD Anderson Cancer Center
Gordon B. Mills: 1515 Holcombe Blvd, The University of Texas MD Anderson Cancer Center

Nature Communications, 2014, vol. 5, issue 1, 1-15

Abstract: 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.

Date: 2014
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DOI: 10.1038/ncomms4887

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