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Proteogenomics guided identification of functional neoantigens in non-small cell lung cancer

Proteogenomics guided identification of functional neoantigens in non-small cell lung cancer
Proteogenomics guided identification of functional neoantigens in non-small cell lung cancer
Non-small cell lung cancer (NSCLC) has poor survival in both the short and long term even for those receiving modern checkpoint inhibitor therapies.

One attractive strategy for NSCLC therapy is personalised vaccines based upon short peptide neoantigens containing tumour mutations, presented to cytotoxic T-cells by human leukocyte antigen (HLA) molecules. However, identification of therapeutically relevant neoantigens is challenging. Existing methodologies yield positive functional assay responses in around 6% of candidate neoantigens tested, and neoantigen based vaccines in melanoma, glioblastoma and pancreatic cancer yield an immune response in around 50% of patients.

Here we report a proteogenomics approach to identify neoantigens in tumours from a cohort of 24 NSCLC patients: 15 adenocarcinoma, 9 squamous cell carcinoma. We characterised the mutational and HLA immunopeptide landscapes of NSCLC using whole exome sequencing, transcriptomics and mass spectrometry immunopeptidomics. We directly identified one neoantigen, and additional predicted neoantigens were generated using an existing in silico neoantigen prediction workflow. Using the immunopeptidomes to filter for candidate predicted neoantigens we identified positive functional assay responses for 5 out of the 6 patients we tested, with an overall success rate of 13%, inclusive of the directly observed neoantigen.

Finally, for one patient using scRNAseq we identified a CD8+ effector T-cell clonotype expanded only in response to the putative class I HLA neoantigen.

These results represent an improvement in both the quantity of neoantigens identified and the specificity of immune responses to neoantigens, utilising knowledge of the HLA peptides presented on a tumour. Thus immunopeptidomics has the potential to improve the efficacy of neoantigen based personalised cancer vaccine workflows.
Neoantigen personalised vaccines, proteogenomics, cancer , non small cell lung cancer
bioRxiv
Nicholas, Ben
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Bailey, Alistair
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McCann, Katy J.
da5bded0-d922-4838-b2e2-69829d2d95aa
Wood, Oliver
df7189aa-56e1-44d5-b44a-a059fcf0fa07
Currall, Eve
f0f8fdd3-52ae-41fc-9124-d998d36610db
Johnson, Peter
570fdb72-488f-4f45-ae58-eddb7abf82de
Elliott, Tim
58856483-cf9d-4158-a0a7-35049c8080b6
Ottensmeier, Christian
80e5342d-ee85-4705-854a-35c16c354c8e
Skipp, Paul
1ba7dcf6-9fe7-4b5c-a9d0-e32ed7f42aa5
Nicholas, Ben
01cab7d7-32c0-413f-804b-d4133070268b
Bailey, Alistair
a24b14c9-5f1b-4885-b31d-07ecded94e38
McCann, Katy J.
da5bded0-d922-4838-b2e2-69829d2d95aa
Wood, Oliver
df7189aa-56e1-44d5-b44a-a059fcf0fa07
Currall, Eve
f0f8fdd3-52ae-41fc-9124-d998d36610db
Johnson, Peter
570fdb72-488f-4f45-ae58-eddb7abf82de
Elliott, Tim
58856483-cf9d-4158-a0a7-35049c8080b6
Ottensmeier, Christian
80e5342d-ee85-4705-854a-35c16c354c8e
Skipp, Paul
1ba7dcf6-9fe7-4b5c-a9d0-e32ed7f42aa5

[Unknown type: UNSPECIFIED]

Record type: UNSPECIFIED

Abstract

Non-small cell lung cancer (NSCLC) has poor survival in both the short and long term even for those receiving modern checkpoint inhibitor therapies.

One attractive strategy for NSCLC therapy is personalised vaccines based upon short peptide neoantigens containing tumour mutations, presented to cytotoxic T-cells by human leukocyte antigen (HLA) molecules. However, identification of therapeutically relevant neoantigens is challenging. Existing methodologies yield positive functional assay responses in around 6% of candidate neoantigens tested, and neoantigen based vaccines in melanoma, glioblastoma and pancreatic cancer yield an immune response in around 50% of patients.

Here we report a proteogenomics approach to identify neoantigens in tumours from a cohort of 24 NSCLC patients: 15 adenocarcinoma, 9 squamous cell carcinoma. We characterised the mutational and HLA immunopeptide landscapes of NSCLC using whole exome sequencing, transcriptomics and mass spectrometry immunopeptidomics. We directly identified one neoantigen, and additional predicted neoantigens were generated using an existing in silico neoantigen prediction workflow. Using the immunopeptidomes to filter for candidate predicted neoantigens we identified positive functional assay responses for 5 out of the 6 patients we tested, with an overall success rate of 13%, inclusive of the directly observed neoantigen.

Finally, for one patient using scRNAseq we identified a CD8+ effector T-cell clonotype expanded only in response to the putative class I HLA neoantigen.

These results represent an improvement in both the quantity of neoantigens identified and the specificity of immune responses to neoantigens, utilising knowledge of the HLA peptides presented on a tumour. Thus immunopeptidomics has the potential to improve the efficacy of neoantigen based personalised cancer vaccine workflows.

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2024.05.30.596609v1.full - Author's Original
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Published date: 2 June 2024
Keywords: Neoantigen personalised vaccines, proteogenomics, cancer , non small cell lung cancer

Identifiers

Local EPrints ID: 491335
URI: http://eprints.soton.ac.uk/id/eprint/491335
PURE UUID: 7ffce66f-eeb9-4ddb-a158-6561c578a6b4
ORCID for Paul Skipp: ORCID iD orcid.org/0000-0002-2995-2959

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Date deposited: 20 Jun 2024 16:34
Last modified: 22 Jun 2024 01:33

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Contributors

Author: Ben Nicholas
Author: Alistair Bailey
Author: Katy J. McCann
Author: Oliver Wood
Author: Eve Currall
Author: Peter Johnson
Author: Tim Elliott
Author: Christian Ottensmeier
Author: Paul Skipp ORCID iD

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