A comprehensive library of canonical and non-canonical MHC class I antigens for cancer vaccine development

Georges Bedran; Tongjie Wang; Dominika Pankanin; Kenneth Weke; Alexander Laird; Christophe Battail; Fabio Massimo Zanzotto; Catia Pesquita; Håkan Axelson; Ajitha Rajan; David J. Harrison; Aleksander Palkowski; Maciej Pawlik; Maciej Parys; Robert O'Neill; Paul M. Brennan; Stefan Symeonides; David R. Goodlett; Kevin Litchfield; Robin Fahraeus; Ted R. Hupp; Sachin Kote; Javier A. Alfaro

A comprehensive library of canonical and non-canonical MHC class I antigens for cancer vaccine development

Georges Bedran, Tongjie Wang, Dominika Pankanin, Kenneth Weke, Alexander Laird, Christophe Battail, Fabio Massimo Zanzotto, Catia Pesquita, Håkan Axelson, Ajitha Rajan, David J. Harrison, Aleksander Palkowski, Maciej Pawlik, Maciej Parys, Robert O'Neill, Paul M. Brennan, Stefan Symeonides, David R. Goodlett, Kevin Litchfield, Robin FahraeusTed R. Hupp, Sachin Kote^*, Javier A. Alfaro^*

^*Corresponding author for this work

Research output: Working paper › Preprint

Abstract

A longstanding disconnect between the growing number of MHC Class I immunopeptidomic studies and genomic medicine hinders cancer vaccine design. We develop COD-dipp to genomically map the full spectrum of detected canonical and non-canonical (non-exonic) MHC Class I antigens from 26 cancer studies. We demonstrate that patient mutations in regions overlapping physically identified antigens better predict immunotherapy response when compared to neoantigen predictions. We suggest a vaccine design approach using 140,966 highly immune-visible regions of the genome annotated by their expression and haplotype frequency in the human population. These regions tend to be highly conserved, mutated in cancer and harbor 7.8 times more immunogenicity. Intersecting pan-cancer mutations with these immune surveilled regions revealed a potential to create off-the-shelf multi-epitope vaccines against public neoantigens. Here we release COD-dipp, a cancer vaccine toolkit as a web-application (https://www.proteogenomics.ca/COD-dipp) and open-source high-throughput resource.

Original language	English
Publisher	bioRxiv
Number of pages	38
Publication status	Published - 17 Jan 2022

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https://www.biorxiv.org/content/10.1101/2022.01.13.475872v1Licence: CC BY-NC-ND

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KATY: KATY: Knowledge At the Tip of Your fingers: Clinical Knowledge for Humanity
Harrison, D. (PI)
European Commission Joint Research Centre
1/01/21 → 31/12/24
Project: Standard

1 Article

The immunopeptidome from a genomic perspective: establishing the non-canonical landscape of MHC class I–associated peptides
Bedran, G., Gasser, H.-C., Weke, K., Wang, T., Bedran, D., Laird, A., Battail, C., Zanzotto, F. M., Pesquita, C., Axelson, H., Rajan, A., Harrison, D. J., Palkowski, A., Pawlik, M., Parys, M., O'Neill, J. R., Brennan, P. M., Symeonides, S. N., Goodlett, D. R. & Litchfield, K. & 4 others, Fahraeus, R., Hupp, T. R., Kote, S. & Alfaro, J. A., 1 Jun 2023, In: Cancer Immunology Research. 11, 6, p. 747-762 16 p.
Research output: Contribution to journal › Article › peer-review

Open Access
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Bedran, G., Wang, T., Pankanin, D., Weke, K., Laird, A., Battail, C., Zanzotto, F. M., Pesquita, C., Axelson, H., Rajan, A., Harrison, D. J., Palkowski, A., Pawlik, M., Parys, M., O'Neill, R., Brennan, P. M., Symeonides, S., Goodlett, D. R., Litchfield, K., ... Alfaro, J. A. (2022). A comprehensive library of canonical and non-canonical MHC class I antigens for cancer vaccine development. bioRxiv. https://www.biorxiv.org/content/10.1101/2022.01.13.475872v1

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title = "A comprehensive library of canonical and non-canonical MHC class I antigens for cancer vaccine development",

abstract = "A longstanding disconnect between the growing number of MHC Class I immunopeptidomic studies and genomic medicine hinders cancer vaccine design. We develop COD-dipp to genomically map the full spectrum of detected canonical and non-canonical (non-exonic) MHC Class I antigens from 26 cancer studies. We demonstrate that patient mutations in regions overlapping physically identified antigens better predict immunotherapy response when compared to neoantigen predictions. We suggest a vaccine design approach using 140,966 highly immune-visible regions of the genome annotated by their expression and haplotype frequency in the human population. These regions tend to be highly conserved, mutated in cancer and harbor 7.8 times more immunogenicity. Intersecting pan-cancer mutations with these immune surveilled regions revealed a potential to create off-the-shelf multi-epitope vaccines against public neoantigens. Here we release COD-dipp, a cancer vaccine toolkit as a web-application (https://www.proteogenomics.ca/COD-dipp) and open-source high-throughput resource.",

author = "Georges Bedran and Tongjie Wang and Dominika Pankanin and Kenneth Weke and Alexander Laird and Christophe Battail and Zanzotto, {Fabio Massimo} and Catia Pesquita and H{\aa}kan Axelson and Ajitha Rajan and Harrison, {David J.} and Aleksander Palkowski and Maciej Pawlik and Maciej Parys and Robert O'Neill and Brennan, {Paul M.} and Stefan Symeonides and Goodlett, {David R.} and Kevin Litchfield and Robin Fahraeus and Hupp, {Ted R.} and Sachin Kote and Alfaro, {Javier A.}",

note = "Funding: C.B. received support from the GRAL LabEX (ANR-10-LABX-49-01) with the frame of the CBH-EUR-GS (ANR-17-EURE-0003). H.A is supported by the Swedish Cancer Society (grant 2018/694). C.P is supported by FCT through the LASIGE Research Unit (UIDB/00408/2020 and UIDP/00408/2020). KATY Consortium is supported by the EU programme Horizon 2020/H2020-SCI-FA-DTS-2020-1 (contract number 101017453).",

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Bedran, G, Wang, T, Pankanin, D, Weke, K, Laird, A, Battail, C, Zanzotto, FM, Pesquita, C, Axelson, H, Rajan, A, Harrison, DJ, Palkowski, A, Pawlik, M, Parys, M, O'Neill, R, Brennan, PM, Symeonides, S, Goodlett, DR, Litchfield, K, Fahraeus, R, Hupp, TR, Kote, S & Alfaro, JA 2022 'A comprehensive library of canonical and non-canonical MHC class I antigens for cancer vaccine development' bioRxiv. <https://www.biorxiv.org/content/10.1101/2022.01.13.475872v1>

TY - UNPB

T1 - A comprehensive library of canonical and non-canonical MHC class I antigens for cancer vaccine development

AU - Bedran, Georges

AU - Wang, Tongjie

AU - Pankanin, Dominika

AU - Weke, Kenneth

AU - Laird, Alexander

AU - Battail, Christophe

AU - Zanzotto, Fabio Massimo

AU - Pesquita, Catia

AU - Axelson, Håkan

AU - Rajan, Ajitha

AU - Harrison, David J.

AU - Palkowski, Aleksander

AU - Pawlik, Maciej

AU - Parys, Maciej

AU - O'Neill, Robert

AU - Brennan, Paul M.

AU - Symeonides, Stefan

AU - Goodlett, David R.

AU - Litchfield, Kevin

AU - Fahraeus, Robin

AU - Hupp, Ted R.

AU - Kote, Sachin

AU - Alfaro, Javier A.

N1 - Funding: C.B. received support from the GRAL LabEX (ANR-10-LABX-49-01) with the frame of the CBH-EUR-GS (ANR-17-EURE-0003). H.A is supported by the Swedish Cancer Society (grant 2018/694). C.P is supported by FCT through the LASIGE Research Unit (UIDB/00408/2020 and UIDP/00408/2020). KATY Consortium is supported by the EU programme Horizon 2020/H2020-SCI-FA-DTS-2020-1 (contract number 101017453).

PY - 2022/1/17

Y1 - 2022/1/17

N2 - A longstanding disconnect between the growing number of MHC Class I immunopeptidomic studies and genomic medicine hinders cancer vaccine design. We develop COD-dipp to genomically map the full spectrum of detected canonical and non-canonical (non-exonic) MHC Class I antigens from 26 cancer studies. We demonstrate that patient mutations in regions overlapping physically identified antigens better predict immunotherapy response when compared to neoantigen predictions. We suggest a vaccine design approach using 140,966 highly immune-visible regions of the genome annotated by their expression and haplotype frequency in the human population. These regions tend to be highly conserved, mutated in cancer and harbor 7.8 times more immunogenicity. Intersecting pan-cancer mutations with these immune surveilled regions revealed a potential to create off-the-shelf multi-epitope vaccines against public neoantigens. Here we release COD-dipp, a cancer vaccine toolkit as a web-application (https://www.proteogenomics.ca/COD-dipp) and open-source high-throughput resource.

AB - A longstanding disconnect between the growing number of MHC Class I immunopeptidomic studies and genomic medicine hinders cancer vaccine design. We develop COD-dipp to genomically map the full spectrum of detected canonical and non-canonical (non-exonic) MHC Class I antigens from 26 cancer studies. We demonstrate that patient mutations in regions overlapping physically identified antigens better predict immunotherapy response when compared to neoantigen predictions. We suggest a vaccine design approach using 140,966 highly immune-visible regions of the genome annotated by their expression and haplotype frequency in the human population. These regions tend to be highly conserved, mutated in cancer and harbor 7.8 times more immunogenicity. Intersecting pan-cancer mutations with these immune surveilled regions revealed a potential to create off-the-shelf multi-epitope vaccines against public neoantigens. Here we release COD-dipp, a cancer vaccine toolkit as a web-application (https://www.proteogenomics.ca/COD-dipp) and open-source high-throughput resource.

M3 - Preprint

BT - A comprehensive library of canonical and non-canonical MHC class I antigens for cancer vaccine development

PB - bioRxiv

ER -

A comprehensive library of canonical and non-canonical MHC class I antigens for cancer vaccine development

Abstract

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KATY: KATY: Knowledge At the Tip of Your fingers: Clinical Knowledge for Humanity

Research output

The immunopeptidome from a genomic perspective: establishing the non-canonical landscape of MHC class I–associated peptides

Cite this