Multi-omics prediction of immune-related adverse events during checkpoint immunotherapy

Ying Jing, Jin Liu, Youqiong Ye, Lei Pan, Hui Deng, Yushu Wang, Yang Yang, Lixia Diao, Steven H. Lin, Gordon B. Mills, Guanglei Zhuang, Xinying Xue, Leng Han

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Immune-related adverse events (irAEs), caused by anti-PD-1/PD-L1 antibodies, can lead to fulminant and even fatal consequences and thus require early detection and aggressive management. However, a comprehensive approach to identify biomarkers of irAE is lacking. Here, we utilize a strategy that combines pharmacovigilance data and omics data, and evaluate associations between multi-omics factors and irAE reporting odds ratio across different cancer types. We identify a bivariate regression model of LCP1 and ADPGK that can accurately predict irAE. We further validate LCP1 and ADPGK as biomarkers in an independent patient-level cohort. Our approach provides a method for identifying potential biomarkers of irAE in cancer immunotherapy using both pharmacovigilance data and multi-omics data.

    Original languageEnglish (US)
    Article number4946
    JournalNature communications
    Volume11
    Issue number1
    DOIs
    StatePublished - Dec 1 2020

    ASJC Scopus subject areas

    • Chemistry(all)
    • Biochemistry, Genetics and Molecular Biology(all)
    • Physics and Astronomy(all)

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