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Membrane protein-regulated networks across human cancers

Author

Listed:
  • Chun-Yu Lin

    (National Chiao Tung University
    Kyoto University)

  • Chia-Hwa Lee

    (Taipei Medical University
    Taipei Medical University
    Taipei Medical University)

  • Yi-Hsuan Chuang

    (National Chiao Tung University)

  • Jung-Yu Lee

    (National Chiao Tung University)

  • Yi-Yuan Chiu

    (National Chiao Tung University)

  • Yan-Hwa Wu Lee

    (National Chiao Tung University
    National Yang-Ming University
    National Chiao Tung University)

  • Yuh-Jyh Jong

    (National Chiao Tung University
    National Chiao Tung University
    Kaohsiung Medical University)

  • Jenn-Kang Hwang

    (The Chinese University of Hong Kong)

  • Sing-Han Huang

    (National Chiao Tung University)

  • Li-Ching Chen

    (Taipei Medical University
    Taipei Medical University Hospital
    Taipei Medical University)

  • Chih-Hsiung Wu

    (Taipei Medical University
    En Chu Kong Hospital)

  • Shih-Hsin Tu

    (Taipei Medical University
    Taipei Medical University Hospital
    Taipei Medical University
    Taipei Medical University)

  • Yuan-Soon Ho

    (Taipei Medical University
    Taipei Medical University
    Taipei Medical University
    Taipei Medical University Hospital)

  • Jinn-Moon Yang

    (National Chiao Tung University
    National Chiao Tung University
    National Chiao Tung University)

Abstract

Alterations in membrane proteins (MPs) and their regulated pathways have been established as cancer hallmarks and extensively targeted in clinical applications. However, the analysis of MP-interacting proteins and downstream pathways across human malignancies remains challenging. Here, we present a systematically integrated method to generate a resource of cancer membrane protein-regulated networks (CaMPNets), containing 63,746 high-confidence protein–protein interactions (PPIs) for 1962 MPs, using expression profiles from 5922 tumors with overall survival outcomes across 15 human cancers. Comprehensive analysis of CaMPNets links MP partner communities and regulated pathways to provide MP-based gene sets for identifying prognostic biomarkers and druggable targets. For example, we identify CHRNA9 with 12 PPIs (e.g., ERBB2) can be a therapeutic target and find its anti-metastasis agent, bupropion, for treatment in nicotine-induced breast cancer. This resource is a study to systematically integrate MP interactions, genomics, and clinical outcomes for helping illuminate cancer-wide atlas and prognostic landscapes in tumor homo/heterogeneity.

Suggested Citation

  • Chun-Yu Lin & Chia-Hwa Lee & Yi-Hsuan Chuang & Jung-Yu Lee & Yi-Yuan Chiu & Yan-Hwa Wu Lee & Yuh-Jyh Jong & Jenn-Kang Hwang & Sing-Han Huang & Li-Ching Chen & Chih-Hsiung Wu & Shih-Hsin Tu & Yuan-Soon, 2019. "Membrane protein-regulated networks across human cancers," Nature Communications, Nature, vol. 10(1), pages 1-17, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-10920-8
    DOI: 10.1038/s41467-019-10920-8
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    Cited by:

    1. Julian Petersen & Lukas Englmaier & Artem V. Artemov & Irina Poverennaya & Ruba Mahmoud & Thibault Bouderlique & Marketa Tesarova & Ruslan Deviatiiarov & Anett Szilvásy-Szabó & Evgeny E. Akkuratov & D, 2023. "A previously uncharacterized Factor Associated with Metabolism and Energy (FAME/C14orf105/CCDC198/1700011H14Rik) is related to evolutionary adaptation, energy balance, and kidney physiology," Nature Communications, Nature, vol. 14(1), pages 1-22, December.
    2. Alessandro Lanza & Serena Morigi & Giuseppe Recupero, 2025. "Variational graph p-Laplacian eigendecomposition under p-orthogonality constraints," Computational Optimization and Applications, Springer, vol. 91(2), pages 787-825, June.

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