Current tools for predicting cancer-specific T cell immunity.

Détails

ID Serval
serval:BIB_D584F684242A
Type
Article: article d'un périodique ou d'un magazine.
Sous-type
Synthèse (review): revue aussi complète que possible des connaissances sur un sujet, rédigée à partir de l'analyse exhaustive des travaux publiés.
Collection
Publications
Institution
Titre
Current tools for predicting cancer-specific T cell immunity.
Périodique
Oncoimmunology
Auteur(s)
Gfeller D., Bassani-Sternberg M., Schmidt J., Luescher I.F.
ISSN
2162-4011 (Print)
ISSN-L
2162-4011
Statut éditorial
Publié
Date de publication
2016
Peer-reviewed
Oui
Volume
5
Numéro
7
Pages
e1177691
Langue
anglais
Notes
Publication types: Journal Article ; Review
Publication Status: epublish
Résumé
Tumor exome and RNA sequencing data provide a systematic and unbiased view on cancer-specific expression, over-expression, and mutations of genes, which can be mined for personalized cancer vaccines and other immunotherapies. Of key interest are tumor-specific mutations, because T cells recognizing neoepitopes have the potential to be highly tumoricidal. Here, we review recent developments and technical advances in identifying MHC class I and class II-restricted tumor antigens, especially neoantigen derived MHC ligands, including in silico predictions, immune-peptidome analysis by mass spectrometry, and MHC ligand validation by biochemical methods on T cells.
Pubmed
Open Access
Oui
Création de la notice
23/09/2016 18:58
Dernière modification de la notice
20/08/2019 16:55
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