Evidence map›Paper›PMID 38155964›Full record

ArticleFrontiers in immunology2023

Preclinical immune efficacy against SARS-CoV-2 beta B.1.351 variant by MVA-based vaccine candidates.

Patricia Pérez, Guillermo Albericio, David Astorgano, Sara Flores, Cristina Sánchez-Corzo, Pedro J Sánchez-Cordón, Joanna Luczkowiak, Rafael Delgado, José M Casasnovas, Mariano Esteban and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.2field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 6 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 4 institutions in 1 country.

Patricia Pérez *Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología (CNB), Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain.
Guillermo Albericio *Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología (CNB), Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain.
David Astorgano *Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología (CNB), Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain.
Sara FloresDepartment of Molecular and Cellular Biology, Centro Nacional de Biotecnología (CNB), Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain.
Cristina Sánchez-CorzoDepartment of Molecular and Cellular Biology, Centro Nacional de Biotecnología (CNB), Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain.
Pedro J Sánchez-CordónPathology Department, Centro de Investigación en Sanidad Animal (CISA), Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain.
Joanna LuczkowiakCentro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Madrid, Spain.
Rafael DelgadoCentro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Madrid, Spain.
José M CasasnovasDepartment of Macromolecular Structures, Centro Nacional de Biotecnología (CNB), Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain.
Mariano EstebanDepartment of Molecular and Cellular Biology, Centro Nacional de Biotecnología (CNB), Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain.
Juan García-ArriazaDepartment of Molecular and Cellular Biology, Centro Nacional de Biotecnología (CNB), Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain.
Centro Nacional de Biotecnología · ESCentro de Investigación Biomédica en Red · ESConsejo Superior de Investigaciones Científicas · ESUniversidad Complutense de Madrid · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The constant appearance of new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VoCs) has jeopardized the protective capacity of approved vaccines against coronavirus disease-19 (COVID-19). For this reason, the generation of new vaccine candidates adapted to the emerging VoCs is of special importance. Here, we developed an optimized COVID-19 vaccine candidate using the modified vaccinia virus Ankara (MVA) vector to express a full-length prefusion-stabilized SARS-CoV-2 spike (S) protein, containing 3 proline (3P) substitutions in the S protein derived from the beta (B.1.351) variant, termed MVA-S(3Pbeta). Preclinical evaluation of MVA-S(3Pbeta) in head-to-head comparison to the previously generated MVA-S(3P) vaccine candidate, expressing a full-length prefusion-stabilized Wuhan S protein (with also 3P substitutions), demonstrated that two intramuscular doses of both vaccine candidates fully protected transgenic K18-hACE2 mice from a lethal challenge with SARS-CoV-2 beta variant, reducing mRNA and infectious viral loads in the lungs and in bronchoalveolar lavages, decreasing lung histopathological lesions and levels of proinflammatory cytokines in the lungs. Vaccination also elicited high titers of anti-S Th1-biased IgGs and neutralizing antibodies against ancestral SARS-CoV-2 Wuhan strain and VoCs alpha, beta, gamma, delta, and omicron. In addition, similar systemic and local SARS-CoV-2 S-specific CD4

Indexed as

COVID-19VaccinesAnimalsAntibodies, ViralCOVID-19 VaccinesHumansMiceMice, Inbred C57BLSARS-CoV-2Vaccinia virusAntibodies, ViralCOVID-19 VaccinesVaccinesCOVID-19efficacyimmunogenicitymiceMVA-based vaccineSARS-CoV-2S proteinvariants of concern

Identifiers

PMID38155964
PMCPMC10754519
OpenAlexW4389614735

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.