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The immunopeptidomic landscape of ovarian carcinomas.

Authors :
Schuster H
Peper JK
Bösmüller HC
Röhle K
Backert L
Bilich T
Ney B
Löffler MW
Kowalewski DJ
Trautwein N
Rabsteyn A
Engler T
Braun S
Haen SP
Walz JS
Schmid-Horch B
Brucker SY
Wallwiener D
Kohlbacher O
Fend F
Rammensee HG
Stevanović S
Staebler A
Wagner P
Source :
Proceedings of the National Academy of Sciences of the United States of America [Proc Natl Acad Sci U S A] 2017 Nov 14; Vol. 114 (46), pp. E9942-E9951. Date of Electronic Publication: 2017 Nov 01.
Publication Year :
2017

Abstract

Immunotherapies, particularly checkpoint inhibitors, have set off a revolution in cancer therapy by releasing the power of the immune system. However, only little is known about the antigens that are essentially presented on cancer cells, capable of exposing them to immune cells. Large-scale HLA ligandome analysis has enabled us to exhaustively characterize the immunopeptidomic landscape of epithelial ovarian cancers (EOCs). Additional comparative profiling with the immunopeptidome of a variety of benign sources has unveiled a multitude of ovarian cancer antigens (MUC16, MSLN, LGALS1, IDO1, KLK10) to be presented by HLA class I and class II molecules exclusively on ovarian cancer cells. Most strikingly, ligands derived from mucin 16 and mesothelin, a molecular axis of prognostic importance in EOC, are prominent in a majority of patients. Differential gene-expression analysis has allowed us to confirm the relevance of these targets for EOC and further provided important insights into the relationship between gene transcript levels and HLA ligand presentation.<br />Competing Interests: Conflict of interest statement: H.-G.R. is a shareholder of Immatics Biotechnologies, Tübingen, and CureVac GmbH, Tübingen. H.S. and D.J.K. are employees of Immatics Biotechnologies GmbH. The authors declare that Immatics did not provide neither financial nor scientific support in any direct relation to this manuscript or the underlying studies, and was not involved in data collection, analysis, or decision to publish.<br /> (Copyright © 2017 the Author(s). Published by PNAS.)

Details

Language :
English
ISSN :
1091-6490
Volume :
114
Issue :
46
Database :
MEDLINE
Journal :
Proceedings of the National Academy of Sciences of the United States of America
Publication Type :
Academic Journal
Accession number :
29093164
Full Text :
https://doi.org/10.1073/pnas.1707658114