Identification of tumor antigens with immunopeptidomics.

Details

Serval ID
serval:BIB_0938B9EC9DC3
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
Identification of tumor antigens with immunopeptidomics.
Journal
Nature biotechnology
Author(s)
Chong C., Coukos G., Bassani-Sternberg M.
ISSN
1546-1696 (Electronic)
ISSN-L
1087-0156
Publication state
Published
Issued date
02/2022
Peer-reviewed
Oui
Volume
40
Number
2
Pages
175-188
Language
english
Notes
Publication types: Journal Article ; Review
Publication Status: ppublish
Abstract
The identification of actionable tumor antigens is indispensable for the development of several cancer immunotherapies, including T cell receptor-transduced T cells and patient-specific mRNA or peptide vaccines. Most known tumor antigens have been identified through extensive molecular characterization and are considered canonical if they derive from protein-coding regions of the genome. By eluting human leukocyte antigen-bound peptides from tumors and subjecting these to mass spectrometry analysis, the peptides can be identified by matching the resulting spectra against reference databases. Recently, mass-spectrometry-based immunopeptidomics has enabled the discovery of noncanonical antigens-antigens derived from sequences outside protein-coding regions or generated by noncanonical antigen-processing mechanisms. Coupled with transcriptomics and ribosome profiling, this method enables the identification of thousands of noncanonical peptides, of which a substantial fraction may be detected exclusively in tumors. Spectral matching against the immense noncanonical reference may generate false positives. However, sensitive mass spectrometry, analytical validation and advanced bioinformatics solutions are expected to uncover the full landscape of presented antigens and clinically relevant targets.
Pubmed
Web of science
Create date
19/10/2021 12:22
Last modification date
15/07/2022 6:35
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