Inhaled aerosol viral-vectored vaccines against tuberculosis.


Journal

Current opinion in virology
ISSN: 1879-6265
Titre abrégé: Curr Opin Virol
Pays: Netherlands
ID NLM: 101560941

Informations de publication

Date de publication:
03 Apr 2024
Historique:
received: 18 01 2024
revised: 08 03 2024
accepted: 08 03 2024
medline: 5 4 2024
pubmed: 5 4 2024
entrez: 4 4 2024
Statut: aheadofprint

Résumé

Bacille Calmette-Guérin (BCG) remains the sole licensed vaccine against tuberculosis (TB), despite its variable efficacy in protecting against pulmonary TB. The development of effective TB vaccines faces significant challenges, marked by the absence of validated correlates of protection and predictive animal models. Strategic approaches to enhance TB vaccines and augment BCG efficacy include utilising prime-boost strategies with viral-vectored vaccines and exploring innovative delivery techniques, such as mucosal vaccine administration. Viral vectors offer numerous advantages, including the capacity to accommodate genes encoding extensive antigenic fragments and the induction of robust immune responses. Aerosol delivery aligns with the route of Mycobacterium tuberculosis infection and holds the potential to enhance protective mucosal immunity. Aerosolised viral-vectored vaccines overcome anti-vector immunity, facilitating repeated aerosol deliveries.

Identifiants

pubmed: 38574628
pii: S1879-6257(24)00022-1
doi: 10.1016/j.coviro.2024.101408
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

101408

Informations de copyright

Crown Copyright © 2024. Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare no conflict of interest.

Auteurs

Elena Stylianou (E)

The Jenner Institute, Old Road Roosevelt Drive, Oxford OX3 7DQ, UK. Electronic address: elena.stylianou@ndm.ox.ac.uk.

Iman Satti (I)

The Jenner Institute, Old Road Roosevelt Drive, Oxford OX3 7DQ, UK. Electronic address: iman.satti@ndm.ox.ac.uk.

Classifications MeSH