Current tools for predicting cancer-specific T cell immunity.

Details

Serval ID
serval:BIB_D584F684242A
Type
Article: article from journal or magazin.
Publication sub-type
Review (review): journal as complete as possible of one specific subject, written based on exhaustive analyses from published work.
Collection
Publications
Institution
Title
Current tools for predicting cancer-specific T cell immunity.
Journal
Oncoimmunology
Author(s)
Gfeller D., Bassani-Sternberg M., Schmidt J., Luescher I.F.
ISSN
2162-4011 (Print)
ISSN-L
2162-4011
Publication state
Published
Issued date
2016
Peer-reviewed
Oui
Volume
5
Number
7
Pages
e1177691
Language
english
Notes
Publication types: Journal Article ; Review
Publication Status: epublish
Abstract
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
Yes
Create date
23/09/2016 18:58
Last modification date
20/08/2019 16:55
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