Candidate biomarker assessment for pharmacological response

William C. Reinhold, Fathi Elloumi, Sudhir Varma, Jacques Robert, Gordon B. Mills, Yves Pommier

    Research output: Contribution to journalArticle

    Abstract

    Using the information from our CellMiner (https://discover.nci.nih.gov/cellminer/) and CellMinerCDB (https://discover.nci.nih.gov/cellminercdb/) web-based applications, we identified 3978 molecular events with significant links to pharmacological response for genes that are either targets, biomarkers, or have established causal linkage to drugs. Molecular events included DNA copy number, methylation and mutation; and transcript; and whole or phospho-protein expression for the NCI-60 human cancer cell lines. While all forms of molecular data were informative in some (gene-drug) pairings, the type of significantly linked molecular events was found to vary widely by drug. Some forms of molecular data were found to have more frequent significant correlation than others. Leading were phosphoproteins as measured by antibody (31%), followed by transcript as measured by microarray (16%), and total protein levels as measured by mass spectrometry or antibody (14%). All other measurements ranged between 5 and 11%. Data reliability was underscored by concordant results when using differing drugs with the same targets, as well as different measurements of the same molecular parameter. The significance of correlations of the various molecular parameters to the pharmacological responses provides functional indication of those parameters that are biologically relevant for each gene-drug pairing, as well as comparisons between measurement types.

    Original languageEnglish (US)
    Article number100830
    JournalTranslational Oncology
    Volume13
    Issue number10
    DOIs
    StatePublished - Oct 2020

    ASJC Scopus subject areas

    • Oncology
    • Cancer Research

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  • Cite this

    Reinhold, W. C., Elloumi, F., Varma, S., Robert, J., Mills, G. B., & Pommier, Y. (2020). Candidate biomarker assessment for pharmacological response. Translational Oncology, 13(10), [100830]. https://doi.org/10.1016/j.tranon.2020.100830