REGEN-COV protects against viral escape in preclinical and human studies

  1. Richard Copin
  2. Alina Baum
  3. Elzbieta Wloga
  4. Kristen E. Pascal
  5. Stephanie Giordano
  6. Benjamin O. Fulton
  7. Anbo Zhou
  8. Nicole Negron
  9. Kathryn Lanza
  10. Newton Chan
  11. Angel Coppola
  12. Joyce Chiu
  13. Min Ni
  14. Yi Wei
  15. Gurinder S. Atwal
  16. Annabel Romero Hernandez
  17. Kei Saotome
  18. Yi Zhou
  19. Matthew C. Franklin
  20. Andrea T. Hooper
  21. Shane McCarthy
  22. Sara Hamon
  23. Jennifer D. Hamilton
  24. Hilary M. Staples
  25. Kendra Alfson
  26. Ricardo Carrion
  27. Shazia Ali
  28. Thomas Norton
  29. Selin Somersan- Karakaya
  30. Sumathi Sivapalasingam
  31. Gary A. Herman
  32. David M. Weinreich
  33. Leah Lipsich
  34. Neil Stahl
  35. Andrew J. Murphy
  36. George D. Yancopoulos
  37. Christos A. Kyratsous

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Monoclonal antibodies against SARS-CoV-2 are a clinically validated therapeutic option against COVID-19. As rapidly emerging virus mutants are becoming the next major concern in the fight against the global pandemic, it is imperative that these therapeutic treatments provide coverage against circulating variants and do not contribute to development of treatment emergent resistance. To this end, we investigated the sequence diversity of the spike protein and monitored emergence of minor virus variants in SARS-COV-2 isolates found in COVID-19 patients or identified from preclinical in vitro and in vivo studies. This study demonstrates that a combination of non-competing antibodies, REGEN-COV, not only provides full coverage against current variants of concern/interest but also protects against emergence of new such variants and their potential seeding into the population in a clinical setting.

Article activity feed

  1. Version published to 10.1101/2021.03.10.434834v4 on bioRxiv
  2. Version published to 10.1101/2021.03.10.434834v3 on bioRxiv
  3. Version published to 10.1101/2021.03.10.434834v2 on bioRxiv
  4. ScreenIT

    SciScore for 10.1101/2021.03.10.434834: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Antibodies
    SentencesResources
    Cryo-EM sample preparation and data collection: Fab fragments of REGN10985 and REGN10989 antibodies were digested with FabALACTICA kit (Genovis) and purified by size-exclusion chromatography.
    REGN10989
    suggested: None
    Software and Algorithms
    SentencesResources
    Variant calling analysis: Swift amplicon bulk RNA-seq reads were aligned to the SARS-COV-2 reference genome Wuhan-Hu-1 (accession: MN908947) using Minimap2 (v2.17)(Li, 2018).
    Minimap2
    suggested: (Minimap2, RRID:SCR_018550)
    Duplicate reads were removed using the Picard package (https://github.com/broadinstitute/picard) and target coverage was summarized for each sample with custom scripts.
    Picard
    suggested: (Picard, RRID:SCR_006525)
    GATK HaplotypeCaller (v4.1.8) (McKenna et al., 2010) was used to perform single nucleotide polymorphism (SNP) calling.
    GATK
    suggested: (GATK, RRID:SCR_001876)
    At each SNP, the frequency of viral mutations inferred from the sequencing reads were calculated from samtools (v1.9) pileup output(Li et al., 2009).
    samtools
    suggested: (SAMTOOLS, RRID:SCR_002105)
    In brief, Blastn was used to align the Wuhan-Hu-1 spike nucleotide sequence (accession: MN908947) against each individual genome.
    Blastn
    suggested: (BLASTN, RRID:SCR_001598)
    Model of RBD-REGN10985-REGN10933-REGN10987: The cryoEM structure of RBD-REGN10933-REGN10987 PDB (6XDG) and the cryoEM structure of RBD-REGN10989-REGN10985 (Fig S4) were superimposed using the software Pymol with the command align for the RBD, where only REGN10933, REGN10987 and REGN10985 are shown.
    Pymol
    suggested: (PyMOL, RRID:SCR_000305)
    Cryo-EM data processing: All cryo-EM data processing was carried out using cryoSPARC v2.14.21.
    cryoSPARC
    suggested: (cryoSPARC, RRID:SCR_016501)
    These models were then manually rebuilt using Coot and real-space refined against the map using Phenix.
    Coot
    suggested: (Coot, RRID:SCR_014222)
    Phenix
    suggested: (Phenix, RRID:SCR_014224)

    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: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04666441RecruitingCOVID-19 Study Assessing the Virologic Efficacy of REGN10933…
    NCT04426695RecruitingSafety, Tolerability, and Efficacy of Anti-Spike (S) SARS-Co…
    NCT04452318RecruitingCOVID-19 Study Assessing the Efficacy and Safety of Anti-Spi…

    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.

    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.

  5. Version published to 10.1101/2021.03.10.434834v1 on bioRxiv