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Title: Non-coding regions are the main source of targetable tumor-specific antigens – DATASETS (k=33)

Type Dataset Céline M. Laumont, Krystel Vincent, Leslie Hesnard, Éric Audemard, Éric Bonneil, Jean-Philippe Laverdure, Patrick Gendron, Mathieu Courcelles, Marie-Pierre Hardy, Caroline Côté, Chantal Durette, Charles St-Pierre, Mohamed Benhammadi, Joël Lanoix, Suzanne Vobecky, Elie Haddad, Sébastien Lemieux, Pierre Thibault, Claude Perreault (2018): Non-coding regions are the main source of targetable tumor-specific antigens – DATASETS (k=33). Zenodo. Dataset. https://zenodo.org/record/1484490

Authors: Céline M. Laumont (IRIC, Université de Montréal) ; Krystel Vincent (IRIC, Université de Montréal) ; Leslie Hesnard (IRIC, Université de Montréal) ; Éric Audemard (IRIC, Université de Montréal) ; Éric Bonneil (IRIC, Université de Montréal) ; Jean-Philippe Laverdure (IRIC, Université de Montréal) ; Patrick Gendron (IRIC, Université de Montréal) ; Mathieu Courcelles (IRIC, Université de Montréal) ; Marie-Pierre Hardy (IRIC, Université de Montréal) ; Caroline Côté (IRIC, Université de Montréal) ; Chantal Durette (IRIC, Université de Montréal) ; Charles St-Pierre (IRIC, Université de Montréal) ; Mohamed Benhammadi (IRIC, Université de Montréal) ; Joël Lanoix (IRIC, Université de Montréal) ; Suzanne Vobecky (CHU Ste-Justine, Université de Montréal) ; Elie Haddad (CHU Ste-Justine, Université de Montréal) ; Sébastien Lemieux (IRIC, Université de Montréal) ; Pierre Thibault (IRIC, Université de Montréal) ; Claude Perreault (IRIC, Université de Montréal) ;

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Summary

Tumor-specific antigens (TSAs) represent ideal targets for cancer immunotherapy, but few have been identified thus far. We therefore developed a proteogenomic approach to enable the high-throughput discovery of TSAs coded by potentially all genomic regions. In two murine cancer cell lines and seven human primary tumors, we identified a total of 40 TSAs, about 90% of which derived from allegedly non-coding regions and would have been missed by standard exome-based approaches. Moreover, the majority of these TSAs derived from non-mutated yet aberrantly expressed transcripts (such as endogenous retroelements) that could be shared by multiple tumor types. In mice, the efficacy of TSA vaccination was influenced by two parameters that can be estimated in humans and could serve for TSA prioritization in clinical studies: TSA expression and the frequency of TSA-responsive T cells in the pre-immune repertoire. In conclusion, the strategy reported herein could considerably facilitate the identification and prioritization of actionable human TSAs.

More information

  • DOI: 10.5281/zenodo.1484490
  • Language: en

Subjects

  • RNA-sequencing, k-mers, Mass spectrometry, Identification of tumor-specific antigens, Thymic epithelial cells, MHC class I

Dates

  • Publication date: 2018
  • Issued: November 22, 2018

Notes

Other: k-mer database (k=33 nucleotides) generated from concatenated RNA-sequencing reads from human TEC (n=2) and mTEC (n=4), which was used in the following publication Laumont C.M., Vincent K. et al. Sci Trans Med (2018). If you use the data, please cite this paper. For methodological details, see section Study design of the Materials and Methods and sections Human TEC and mTEC extraction, RNA extraction, library preparation and sequencing and Generation of cancer and normal k-mer databases of the Supplementary Materials and Methods of the article cited above. For any questions or for assistance, please contact us using the following email address: perreault.lab@iric.ca

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Format

electronic resource

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