Analysis of Immune Escape Variants from Antibody-Based Therapeutics against COVID-19: A Systematic Review

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Abstract

The accelerated SARS-CoV-2 evolution under selective pressure by massive deployment of neutralizing antibody-based therapeutics is a concern with potentially severe implications for public health. We review here reports of documented immune escape after treatment with monoclonal antibodies and COVID-19-convalescent plasma (CCP). While the former is mainly associated with specific single amino acid mutations at residues within the receptor-binding domain (e.g., E484K/Q, Q493R, and S494P), a few cases of immune evasion after CCP were associated with recurrent deletions within the N-terminal domain of the spike protein (e.g., ΔHV69-70, ΔLGVY141-144 and ΔAL243-244). The continuous genomic monitoring of non-responders is needed to better understand immune escape frequencies and the fitness of emerging variants.

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  1. SciScore for 10.1101/2021.11.11.21266207: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    We mined PubMed (which also indexes the bioRxiv and medrXiv preprint servers) for keywords related to COVID19 (“COVID19”, “SARS-CoV-2”), immune escape (“immune escape”, “treatment-emergent resistance”) and nAb-based therapeutics (“convalescent plasma”, “casirivimab”, “imdevimab”, “bamlanivimab”, etesevimab”, “sotrovimab, “regdanvimab”) both in vitro and in vivo.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    bioRxiv
    suggested: (bioRxiv, RRID:SCR_003933)
    The mutations identified in each condition of in vivo or in vitro selection were tabulated and highlighted on the structures using color coding with PyMOL [18].
    PyMOL
    suggested: (PyMOL, RRID:SCR_000305)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    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 did not find any issues relating to the usage of bar graphs.


    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.

    Results from scite Reference Check: We found no unreliable references.


    About SciScore

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