A pan-cancer proteomic perspective on The Cancer Genome Atlas

• Published in: Nature communications 2014-05, Vol.5 (1), p.3887-3887, Article 3887
• Main Authors: 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.
• Format: Article
• Language: English
• Subjects: 631/114; 631/61/475; 631/67/69; 82/1; 82/79; 82/80; Cluster Analysis; Gene Dosage; Genome, Human; Humanities and Social Sciences; Humans; multidisciplinary; Neoplasm Proteins - genetics; Neoplasm Proteins - metabolism; Neoplasms - genetics; Organ Specificity; Proteomics; Receptor, ErbB-2 - genetics; Receptor, ErbB-2 - metabolism; RNA, Messenger - genetics; RNA, Messenger - metabolism; Science; Science (multidisciplinary); Signal Transduction - genetics; Statistics, Nonparametric
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/ncomms4887

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. Analyses of genome and transcriptome data are unable to accurately predict protein levels and function in tumour samples. Here, the authors carry out a comprehensive protein analysis in 3,467 samples from the cancer genome atlas, providing a resource to study the prognostic and therapeutic potential of tumour proteins.