A comprehensive proteogenomic pipeline for neoantigen discovery to advance personalized cancer immunotherapy.

Details

Serval ID
serval:BIB_14DC47CDBB48
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
A comprehensive proteogenomic pipeline for neoantigen discovery to advance personalized cancer immunotherapy.
Journal
Nature biotechnology
Author(s)
Huber F., Arnaud M., Stevenson B.J., Michaux J., Benedetti F., Thevenet J., Bobisse S., Chiffelle J., Gehert T., Müller M., Pak H., Krämer A.I., Altimiras E.R., Racle J., Taillandier-Coindard M., Muehlethaler K., Auger A., Saugy D., Murgues B., Benyagoub A., Gfeller D., Laniti D.D., Kandalaft L., Rodrigo B.N., Bouchaab H., Tissot S., Coukos G., Harari A., Bassani-Sternberg M.
ISSN
1546-1696 (Electronic)
ISSN-L
1087-0156
Publication state
In Press
Peer-reviewed
Oui
Language
english
Notes
Publication types: Journal Article
Publication Status: aheadofprint
Abstract
The accurate identification and prioritization of antigenic peptides is crucial for the development of personalized cancer immunotherapies. Publicly available pipelines to predict clinical neoantigens do not allow direct integration of mass spectrometry immunopeptidomics data, which can uncover antigenic peptides derived from various canonical and noncanonical sources. To address this, we present an end-to-end clinical proteogenomic pipeline, called NeoDisc, that combines state-of-the-art publicly available and in-house software for immunopeptidomics, genomics and transcriptomics with in silico tools for the identification, prediction and prioritization of tumor-specific and immunogenic antigens from multiple sources, including neoantigens, viral antigens, high-confidence tumor-specific antigens and tumor-specific noncanonical antigens. We demonstrate the superiority of NeoDisc in accurately prioritizing immunogenic neoantigens over recent prioritization pipelines. We showcase the various features offered by NeoDisc that enable both rule-based and machine-learning approaches for personalized antigen discovery and neoantigen cancer vaccine design. Additionally, we demonstrate how NeoDisc's multiomics integration identifies defects in the cellular antigen presentation machinery, which influence the heterogeneous tumor antigenic landscape.
Pubmed
Web of science
Open Access
Yes
Create date
25/10/2024 8:44
Last modification date
25/10/2024 14:57
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