Evidence map›Paper›PMID 40859051›Full record

ArticleImmunologic research2025

A nasal vaccine candidate based on S2 and N proteins from SARS-CoV-2 generates a broad antibody response systemically and in the lower respiratory tract.

Yadira Lobaina, Rong Chen, Dania Vazquez-Blomquist, Edith Suzarte, Miaohong Zhang, Zhiqiang Zhou, Yaqin Lan, Gerardo Guillen, Wen Li, Yasser Perera and 1 more

Abstract read
PubMed Publisher
In one paragraph

Article in Immunologic research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Review
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.

Yadira LobainaCCBJIC: Research Department, China-Cuba Biotechnology Joint Innovation Center (CCBJIC) Lengshuitan District, Yongzhou City, Hunan, 425000, China. ylobainamato@ccbjic.com.
Rong ChenCCBJIC: Research Department, China-Cuba Biotechnology Joint Innovation Center (CCBJIC) Lengshuitan District, Yongzhou City, Hunan, 425000, China.
Dania Vazquez-BlomquistCCBJIC: Research Department, China-Cuba Biotechnology Joint Innovation Center (CCBJIC) Lengshuitan District, Yongzhou City, Hunan, 425000, China.
Edith SuzarteCIGB: Research Department, Center for Genetic Engineering and Biotechnology, Havana, 10600, Cuba.
Miaohong ZhangHunan PRIMA Drug Research Center Co., Ltd, National Liuyang Economic and Technological Development Zone, 123 Kangtian Road, Changsha City, Hunan, China.
Zhiqiang ZhouHunan PRIMA Drug Research Center Co., Ltd, National Liuyang Economic and Technological Development Zone, 123 Kangtian Road, Changsha City, Hunan, China.
Yaqin LanCCBJIC: Research Department, China-Cuba Biotechnology Joint Innovation Center (CCBJIC) Lengshuitan District, Yongzhou City, Hunan, 425000, China.
Gerardo GuillenCIGB: Research Department, Center for Genetic Engineering and Biotechnology, Havana, 10600, Cuba.
Wen LiCCBJIC: Research Department, China-Cuba Biotechnology Joint Innovation Center (CCBJIC) Lengshuitan District, Yongzhou City, Hunan, 425000, China. liwen@ccbjic.com.
Yasser PereraCCBJIC: Research Department, China-Cuba Biotechnology Joint Innovation Center (CCBJIC) Lengshuitan District, Yongzhou City, Hunan, 425000, China.
Lisset HermidaCCBJIC: Research Department, China-Cuba Biotechnology Joint Innovation Center (CCBJIC) Lengshuitan District, Yongzhou City, Hunan, 425000, China. lhermida@oc.biocubafarmacu.com.

Funding

Hunan Provincial Base for Scientific and Technological Innovation Cooperation 2019CB1012Hunan Provincial Innovative Construction Program 2020WK2031MOST "National key R&D program of China 2021YFE0192200The Science and Technology Innovation Program of Hunan Province 2020RC5035
6 · The paper itself

Abstract

Since the beginning of the COVID-19 pandemic, various groups around the world have intensively worked in the development of vaccine candidates against SARS-CoV-2. Several vaccines have been approved in the past years; the majority is based on the Spike or RBD proteins and employs parenteral administration routes. Considering the recent history of coronavirus zoonotic events, which are known to have caused serious human health problems, the development of vaccines with a broad scope of protection and the potential to cut/reduce the transmission remains in the spotlight. The current global pandemic preparedness initiatives have also promoted the preclinical evaluation of a new group of coronavirus vaccines. In line with current needs, the goal of the present work is the preclinical evaluation, in two different mice strains, of a novel nasal vaccine candidate based on two highly conserved sarbecovirus proteins, S2 and nucleocapsid (N). The vaccine preparation, containing a CpG ODN as adjuvant, was able to generate high antibody titers against both antigens, in sera and bronchoalveolar lavages. This humoral response results cross-reactive to SARS-CoV-1 and MERS-CoV. In addition, the preparation induces IFNγ secretion, and a marked IgG2a response, against both proteins at the systemic compartment, consistent with the development of a Th1 pattern. Although further evaluations should be done, the level of cross-reactivity and the mucosal response obtained constitute promising features of this vaccine candidate.

Indexed as

Antibodies, ViralCoronavirus Nucleocapsid ProteinsCOVID-19COVID-19 VaccinesPhosphoproteinsSARS-CoV-2Spike Glycoprotein, CoronavirusAdministration, IntranasalAnimalsCross ReactionsFemaleHumansMiceMice, Inbred BALB CAntibodies, ViralCoronavirus Nucleocapsid ProteinsCOVID-19 Vaccinesnucleocapsid phosphoprotein, SARS-CoV-2PhosphoproteinsSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2Cross-reactivityImmune responseNasalSARS-CoVVaccines

Identifiers

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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.