Improved MHC II epitope prediction - a step towards personalized medicine
- PMID: 31836878
- PMCID: PMC7223749
- DOI: 10.1038/s41571-019-0315-0
Improved MHC II epitope prediction - a step towards personalized medicine
Abstract
Numerous neoepitope-based vaccination strategies are in testing for clinical use in the treatment of cancer. Rapid identification of immunostimulatory neoantigen targets hastens neoantigen vaccine development. Papers recently published in Nature Biotechnology describe two independent machine-learning-based algorithms that demonstrate improved identification of MHC class II-binding peptides. Herein, we outline the benefits of these algorithms and their implications for future immunotherapies.
Conflict of interest statement
The authors declare no competing interests.
Comment on
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Predicting HLA class II antigen presentation through integrated deep learning.Nat Biotechnol. 2019 Nov;37(11):1332-1343. doi: 10.1038/s41587-019-0280-2. Epub 2019 Oct 14. Nat Biotechnol. 2019. PMID: 31611695 Free PMC article.
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Robust prediction of HLA class II epitopes by deep motif deconvolution of immunopeptidomes.Nat Biotechnol. 2019 Nov;37(11):1283-1286. doi: 10.1038/s41587-019-0289-6. Epub 2019 Oct 14. Nat Biotechnol. 2019. PMID: 31611696
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