Membrane protein-regulated networks across human cancers

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 Ho () and Jinn-Moon Yang ()
Additional contact information
Chun-Yu Lin: National Chiao Tung University
Chia-Hwa Lee: 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
Yuh-Jyh Jong: National Chiao Tung University
Jenn-Kang Hwang: The Chinese University of Hong Kong
Sing-Han Huang: National Chiao Tung University
Li-Ching Chen: Taipei Medical University
Chih-Hsiung Wu: Taipei Medical University
Shih-Hsin Tu: Taipei Medical University
Yuan-Soon Ho: Taipei Medical University
Jinn-Moon Yang: National Chiao Tung University

Nature Communications, 2019, vol. 10, issue 1, 1-17

Abstract: 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.

Date: 2019
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DOI: 10.1038/s41467-019-10920-8

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