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Cancer therapy tool informs COVID-19 vaccines


T cell vaccines against SARS-CoV-2 are being developed at a rapid pace, but it is imperative that the proteins or peptides they deliver bind to a large variety of HLA haplotypes in the global population. Using a computational tool designed to predict candidate neoantigens for cancer vaccines, this preprint identifies 1,103 unique 9-mer antigens from the SARS-CoV-2 peptidome, each of which binds to a median of 3 of 1,022 HLA class I alleles. This resulted in 6,748 peptide–MHC pairs with high binding affinity. Up to 684 peptides were derived from each viral protein tested. Furthermore, 12 of the identified SARS-CoV-2 epitopes match SARS-CoV epitopes that were previously shown to generate T cell responses ex vivo and in vitro. This publicly available dataset will be an important resource to guide vaccine development.


Original article

  1. Campbell, K. M. et al. Prediction of SARS-CoV-2 epitopes across 9360 HLA class I alleles. Preprint at bioRxiv (2020)

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Correspondence to Miriam Saffern.

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The author declares no competing interests.

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Saffern, M. Cancer therapy tool informs COVID-19 vaccines. Nat Rev Immunol 20, 352 (2020).

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