The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Robust prediction of HLA class II epitopes by deep motif deconvolution of immunopeptidomes
Open accessAbstract
Predictions of epitopes presented by class II human leukocyte antigen molecules (HLA-II) have limited accuracy, restricting vaccine and therapy design. Here we combined unbiased mass spectrometry with a motif deconvolution algorithm to profile and analyze a total of 99,265 unique peptides eluted from HLA-II molecules. We then trained an epitope prediction algorithm with these data and improved prediction of pathogen and tumor-associated class II neoepitopes. HLA class II epitopes are accurately predicted by analysis of a large peptide dataset.
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Cites
Cox, J., & Mann, M. (2008) · Nature Biotechnology · doi:10.1038/nbt.1511 · Cited by 14,855
An immunogenic personal neoantigen vaccine for patients with melanoma
Ott, P. A., Hu, Z., Keskin, D. B., Shukla, S. A., Sun, J., Bozym, D. J., Zhang, W., Luoma, A., Giobbie-Hurder, A., Peter, L., et al. (2017) · Nature · doi:10.1038/nature22991 · Cited by 2,936
Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer
Sahin, U., Derhovanessian, E., Miller, M., Kloke, B.-P., Simon, P., Löwer, M., Bukur, V., Tadmor, A. D., Luxemburger, U., Schrörs, B., et al. (2017) · Nature · doi:10.1038/nature23003 · Cited by 2,488
Towards a systems understanding of MHC class I and MHC class II antigen presentation
Neefjes, J., Jongsma, M. L. M., Paul, P., & Bakke, O. (2011) · Nature Reviews Immunology · doi:10.1038/nri3084 · Cited by 2,044
Mutant MHC class II epitopes drive therapeutic immune responses to cancer
Kreiter, S., Vormehr, M., van de Roemer, N., Diken, M., Löwer, M., Diekmann, J., Boegel, S., Schrörs, B., Vascotto, F., Castle, J. C., et al. (2015) · Nature · doi:10.1038/nature14426 · Cited by 1,243
Veatch, J. R., Jesernig, B. L., Kargl, J., Fitzgibbon, M., Lee, S. M., Baik, C., Martins, R., Houghton, A. M., & Riddell, S. R. (2019) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-18-0402 · Cited by 89
Cited by
Reynisson, B., Alvarez, B., Paul, S., Peters, B., & Nielsen, M. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa379 · Cited by 2,361
Advances in the development of personalized neoantigen-based therapeutic cancer vaccines
Blass, E., & Ott, P. A. (2021) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-020-00460-2 · Cited by 1,042
Neoantigens: promising targets for cancer therapy
Xie, N., Shen, G., Gao, W., Huang, Z., Huang, C., & Fu, L. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-01270-x · Cited by 1,020
Marcu, A., Bichmann, L., Kuchenbecker, L., Kowalewski, D. J., Freudenmann, L. K., Backert, L., Mühlenbruch, L., Szolek, A., Lübke, M., Wagner, P., et al. (2021) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2020-002071 · Cited by 250
Xu, Y., Su, G.-H., Ma, D., Xiao, Y., Shao, Z.-M., & Jiang, Y.-Z. (2021) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-021-00729-7 · Cited by 163
“184 Racle et al. 103 developed a motif deconvolution algorithm, i.e., Modec, to train the deep learning MHC-II peptide predictor MixMHC2pred.”
Method
Metadata
- Authors
- Racle, J., Michaux, J., Rockinger, G. A., Arnaud, M., Bobisse, S., Chong, C., Guillaume, P., Coukos, G., Harari, A., Jandus, C., Bassani-Sternberg, M., & Gfeller, D.
- Venue
- Nature Biotechnology
- Published
- 2019-10-14
- Volume
- 37
- Issue
- 11
- Pages
- 1283-1286
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- OpenAlex
- W2979293383
- Cited by
- 289
- References
- 6
- FWCI
- 10.38
- Type
- journal article
- Language
- en
- Open access
- green
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- Racle, J., Michaux, J., Rockinger, G. A., Arnaud, M., Bobisse, S., Chong, C., Guillaume, P., Coukos, G., Harari, A., Jandus, C., Bassani-Sternberg, M., & Gfeller, D. (2019). Robust prediction of HLA class II epitopes by deep motif deconvolution of immunopeptidomes. Nature Biotechnology. https://doi.org/10.1038/s41587-019-0289-6
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