Machine Learning Identifies Ponatinib as a Potent Inhibitor of SARS-CoV2-induced Cytokine Storm

  1. Marina Chan
  2. Siddharth Vijay
  3. M. Juliana McElrath
  4. Eric C. Holland
  5. Taranjit S Gujral

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Abstract

Although 15-20% of COVID-19 patients experience hyper-inflammation induced by massive cytokine production, cellular triggers of this process and strategies to target them remain poorly understood. Here, we show that the N-terminal domain (NTD) of the spike protein from the SARS-CoV-2 and emerging variants B1.1.7 and B.1.351 substantially induces multiple inflammatory molecules in human monocytes and PBMCs. Further, we identified several protein kinases, including JAK1, EPHA7, IRAK1, MAPK12, and MAP3K8, as essential downstream mediators of NTD-induced cytokine release. Additionally, we found that the FDA-approved, multi-kinase inhibitor Ponatinib is a potent inhibitor of the NTD-mediated cytokine storm. Taken together, we propose that agents targeting multiple kinases required for the SARS-CoV-2-mediated cytokine storm, such as Ponatinib, may represent an attractive therapeutic option for treating moderate to severe COVID-19.

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    SciScore for 10.1101/2021.04.07.438871: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIRB: Fred Hutchinson Cancer Research Center Institutional Review Board approved all aspects of this study (IRB 10440, 00001080 and 00022371).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Beads are washed then incubated 1 hour with biotinylated anti-cytokine antibodies, washed again then incubated 30 minutes with a phycoerythrin-streptavidin conjugate.
    anti-cytokine
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Peripheral blood mononuclear cells (PBMCs) from healthy donors spanning various age groups were obtained from Bloodworks NW, Seattle, Washington. PBMCs and THP-1 cells were cultured in RPMI1640 media supplemented with 10% FBS, 1% P/S, 1 mM sodium pyruvate.
    THP-1
    suggested: None
    Raw264.7 cells were maintained in Dulbecco’s minimum essential medium supplemented with 10% FBS (Sigma) and 1% Penn Strep.
    Raw264.7
    suggested: None
    Software and Algorithms
    SentencesResources
    The quantified data was normalized to untreated control and plotted in Prism (Graphpad software, San Diego, CA, USA).
    Prism
    suggested: (PRISM, RRID:SCR_005375)
    Graphpad
    suggested: (GraphPad, RRID:SCR_000306)

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2021.04.07.438871v1 on bioRxiv