Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

The Immunopeptidome from a Genomic Perspective : Establishing the Noncanonical Landscape of MHC Class I–Associated Peptides

Bedran, Georges ; Gasser, Hans Christof ; Weke, Kenneth ; Wang, Tongjie ; Bedran, Dominika ; Laird, Alexander ; Battail, Christophe ; Zanzotto, Fabio Massimo ; Pesquita, Catia and Axelson, Hákan LU , et al. (2023) In Cancer immunology research 11(6). p.742-762
Abstract

Tumor antigens can emerge through multiple mechanisms, including translation of noncoding genomic regions. This noncanonical category of tumor antigens has recently gained attention; however, our understanding of how they recur within and between cancer types is still in its infancy. Therefore, we developed a proteogenomic pipeline based on deep learning de novo mass spectrometry (MS) to enable the discovery of noncanonical MHC class I–associated peptides (ncMAP) from noncoding regions. Considering that the emergence of tumor antigens can also involve posttranslational modifications (PTM), we included an open search component in our pipeline. Leveraging the wealth of MS-based immunopeptidomics, we analyzed data from 26 MHC class I... (More)

Tumor antigens can emerge through multiple mechanisms, including translation of noncoding genomic regions. This noncanonical category of tumor antigens has recently gained attention; however, our understanding of how they recur within and between cancer types is still in its infancy. Therefore, we developed a proteogenomic pipeline based on deep learning de novo mass spectrometry (MS) to enable the discovery of noncanonical MHC class I–associated peptides (ncMAP) from noncoding regions. Considering that the emergence of tumor antigens can also involve posttranslational modifications (PTM), we included an open search component in our pipeline. Leveraging the wealth of MS-based immunopeptidomics, we analyzed data from 26 MHC class I immunopeptidomic studies across 11 different cancer types. We validated the de novo identified ncMAPs, along with the most abundant PTMs, using spectral matching and controlled their FDR to 1%. The noncanonical presentation appeared to be 5 times enriched for the A03 HLA supertype, with a projected population coverage of 55%. The data reveal an atlas of 8,601 ncMAPs with varying levels of cancer selectivity and suggest 17 cancer-selective ncMAPs as attractive therapeutic targets according to a stringent cutoff. In summary, the combination of the open-source pipeline and the atlas of ncMAPs reported herein could facilitate the identification and screening of ncMAPs as targets for T-cell therapies or vaccine development.

(Less)
Please use this url to cite or link to this publication:
author
; ; ; ; ; ; ; ; and , et al. (More)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; and (Less)
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Cancer immunology research
volume
11
issue
6
pages
21 pages
publisher
American Association for Cancer Research
external identifiers
  • pmid:36961404
  • scopus:85160968693
ISSN
2326-6066
DOI
10.1158/2326-6066.CIR-22-0621
language
English
LU publication?
yes
id
99376444-8a1d-4578-97c5-1356fd996be1
date added to LUP
2023-08-15 14:42:25
date last changed
2024-11-16 22:43:27
@article{99376444-8a1d-4578-97c5-1356fd996be1,
  abstract     = {{<p>Tumor antigens can emerge through multiple mechanisms, including translation of noncoding genomic regions. This noncanonical category of tumor antigens has recently gained attention; however, our understanding of how they recur within and between cancer types is still in its infancy. Therefore, we developed a proteogenomic pipeline based on deep learning de novo mass spectrometry (MS) to enable the discovery of noncanonical MHC class I–associated peptides (ncMAP) from noncoding regions. Considering that the emergence of tumor antigens can also involve posttranslational modifications (PTM), we included an open search component in our pipeline. Leveraging the wealth of MS-based immunopeptidomics, we analyzed data from 26 MHC class I immunopeptidomic studies across 11 different cancer types. We validated the de novo identified ncMAPs, along with the most abundant PTMs, using spectral matching and controlled their FDR to 1%. The noncanonical presentation appeared to be 5 times enriched for the A03 HLA supertype, with a projected population coverage of 55%. The data reveal an atlas of 8,601 ncMAPs with varying levels of cancer selectivity and suggest 17 cancer-selective ncMAPs as attractive therapeutic targets according to a stringent cutoff. In summary, the combination of the open-source pipeline and the atlas of ncMAPs reported herein could facilitate the identification and screening of ncMAPs as targets for T-cell therapies or vaccine development.</p>}},
  author       = {{Bedran, Georges and Gasser, Hans Christof and Weke, Kenneth and Wang, Tongjie and Bedran, Dominika and Laird, Alexander and Battail, Christophe and Zanzotto, Fabio Massimo and Pesquita, Catia and Axelson, Hákan and Rajan, Ajitha and Harrison, David J. and Palkowski, Aleksander and Pawlik, Maciej and Parys, Maciej and O’Neill, J. Robert and Brennan, Paul M. and Symeonides, Stefan N. and Goodlett, David R. and Litchfield, Kevin and Fahraeus, Robin and Hupp, Ted R. and Kote, Sachin and Alfaro, Javier A.}},
  issn         = {{2326-6066}},
  language     = {{eng}},
  number       = {{6}},
  pages        = {{742--762}},
  publisher    = {{American Association for Cancer Research}},
  series       = {{Cancer immunology research}},
  title        = {{The Immunopeptidome from a Genomic Perspective : Establishing the Noncanonical Landscape of MHC Class I–Associated Peptides}},
  url          = {{http://dx.doi.org/10.1158/2326-6066.CIR-22-0621}},
  doi          = {{10.1158/2326-6066.CIR-22-0621}},
  volume       = {{11}},
  year         = {{2023}},
}