Evidence map›Paper›PMID 41295491›Full record

ReviewVaccines2025

T-Cell-Based Universal Dengue Vaccine Design for Robust Protective Response.

Yi Fei Sun, Adeline Yeo Syin Lian, Meng Ling Moi

Abstract readReview
In one paragraph

Review in Vaccines, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

3 authors.

Yi Fei SunDepartment of Developmental Medical Sciences, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan.ORCID 0009-0002-3241-5828
Adeline Yeo Syin LianDepartment of Developmental Medical Sciences, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan.
Meng Ling MoiDepartment of Developmental Medical Sciences, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan.ORCID 0000-0002-8103-6659

Funding

AMED JP233fa627001 and JP243fa627001
6 · The paper itself

Abstract

Dengue virus remains a major global health threat due to the lack of a safe and broadly effective vaccine. Traditional antibody-based vaccines often show limited protection and can exacerbate disease severity in individuals without prior exposure. A new generation of T-cell epitope-based vaccines offers a promising and safer approach by activating the cellular arm of the immune system to complement antibody responses. Instead of targeting only surface structural proteins, these vaccines focus on highly conserved peptide regions within non-structural proteins, particularly NS3 and NS5, that are shared across all four dengue virus serotypes. Peptides such as DTTPFGQQR, KPGTSGSPI, and MYFHRRDLRL have been identified as potent immunogenic targets capable of inducing strong cytotoxic and helper T-cell responses, promoting viral clearance and long-term immune memory. Advanced immunoinformatic enables precise prediction and selection of epitopes with high binding affinity to human leukocyte antigens and broad cross-serotype conservation. These peptides can be integrated into next-generation vaccine delivery systems, including messenger RNA and nanoparticle platforms, which enhance antigen presentation, improve molecular stability, and reduce the risk of antibody-dependent disease enhancement. Together, this integrative design represents a rational path toward a safer, cross-protective, and durable dengue vaccine that closely mimics the balanced cellular and humoral immunity observed after natural infection, offering renewed hope for effective global dengue prevention.

Indexed as

antibody-dependent enhancementdengue feverepitope predictionnext-generation platformsserotype diversityT-cell epitope-based vaccine

Identifiers

PMID41295491
PMCPMC12656997

What OpenQuestion holds

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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.