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A pan-cancer proteomic perspective on The Cancer Genome Atlas

Author

Listed:
  • 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
    Centre for Cancer Biomarkers, The University of Bergen)

  • 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
    Kumoh National Institute of Technology)

  • 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
    The Netherlands Cancer Institute)

  • 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
    1515 Holcombe Blvd, 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
    Cancer Research UK Cambridge Institute, School of Clinical Medicine, University of Cambridge, Robinson Way)

  • 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)

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.

Suggested Citation

  • 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 & Pr, 2014. "A pan-cancer proteomic perspective on The Cancer Genome Atlas," Nature Communications, Nature, vol. 5(1), pages 1-15, September.
    • Handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms4887
    DOI: 10.1038/ncomms4887
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    Cited by:

    1. Sophie A. Herbst & Mattias Vesterlund & Alexander J. Helmboldt & Rozbeh Jafari & Ioannis Siavelis & Matthias Stahl & Eva C. Schitter & Nora Liebers & Berit J. Brinkmann & Felix Czernilofsky & Tobias R, 2022. "Proteogenomics refines the molecular classification of chronic lymphocytic leukemia," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    2. Lishan Fang & Dane Ford-Roshon & Max Russo & Casey O’Brien & Xiaozhe Xiong & Carino Gurjao & Maximilien Grandclaudon & Srivatsan Raghavan & Steven M. Corsello & Steven A. Carr & Namrata D. Udeshi & Ja, 2022. "RNF43 G659fs is an oncogenic colorectal cancer mutation and sensitizes tumor cells to PI3K/mTOR inhibition," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    3. Masashi Fujita & Mei-Ju May Chen & Doris Rieko Siwak & Shota Sasagawa & Ayako Oosawa-Tatsuguchi & Koji Arihiro & Atsushi Ono & Ryoichi Miura & Kazuhiro Maejima & Hiroshi Aikata & Masaki Ueno & Shinya , 2022. "Proteo-genomic characterization of virus-associated liver cancers reveals potential subtypes and therapeutic targets," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    4. Yiqun Zhang & Fengju Chen & Darshan S. Chandrashekar & Sooryanarayana Varambally & Chad J. Creighton, 2022. "Proteogenomic characterization of 2002 human cancers reveals pan-cancer molecular subtypes and associated pathways," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    5. Fengju Chen & Yiqun Zhang & Darshan S. Chandrashekar & Sooryanarayana Varambally & Chad J. Creighton, 2023. "Global impact of somatic structural variation on the cancer proteome," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    6. María Bueno Álvez & Fredrik Edfors & Kalle Feilitzen & Martin Zwahlen & Adil Mardinoglu & Per-Henrik Edqvist & Tobias Sjöblom & Emma Lundin & Natallia Rameika & Gunilla Enblad & Henrik Lindman & Marti, 2023. "Next generation pan-cancer blood proteome profiling using proximity extension assay," Nature Communications, Nature, vol. 14(1), pages 1-13, December.

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