The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Antigen presentation profiling reveals recognition of lymphoma immunoglobulin neoantigens
Open accessAbstract
Cancer somatic mutations can generate neoantigens that distinguish malignant from normal cells. However, the personalized identification and validation of neoantigens remains a major challenge. Here we discover neoantigens in human mantle-cell lymphomas by using an integrated genomic and proteomic strategy that interrogates tumour antigen peptides presented by major histocompatibility complex (MHC) class I and class II molecules. We applied this approach to systematically characterize MHC ligands from 17 patients. Remarkably, all discovered neoantigenic peptides were exclusively derived from the lymphoma immunoglobulin heavy- or light-chain variable regions. Although we identified MHC presentation of private polymorphic germline alleles, no mutated peptides were recovered from non-immunoglobulin somatically mutated genes. Somatic mutations within the immunoglobulin variable region were almost exclusively presented by MHC class II. We isolated circulating CD4+ T cells specific for immunoglobulin-derived neoantigens and found these cells could mediate killing of autologous lymphoma cells. These results demonstrate that an integrative approach combining MHC isolation, peptide identification, and exome sequencing is an effective platform to uncover tumour neoantigens. Application of this strategy to human lymphoma implicates immunoglobulin neoantigens as targets for lymphoma immunotherapy.
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Cites
Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer
Rizvi, N. A., Hellmann, M. D., Snyder, A., Kvistborg, P., Makarov, V., Havel, J. J., Lee, W., Yuan, J., Wong, P., Ho, T. S., et al. (2015) · Science · doi:10.1126/science.aaa1348 · Cited by 7,802
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Self-citationGenomic correlates of response to CTLA-4 blockade in metastatic melanoma
Van Allen, E. M., Miao, D., Schilling, B., Shukla, S. A., Blank, C., Zimmer, L., Sucker, A., Hillen, U., Geukes Foppen, M. H., Goldinger, S. M., et al. (2015) · Science · doi:10.1126/science.aad0095 · Cited by 2,839
Semi-supervised learning for peptide identification from shotgun proteomics datasets
Käll, L., Canterbury, J. D., Weston, J., Noble, W. S., & MacCoss, M. J. (2007) · Nature Methods · doi:10.1038/nmeth1113 · Cited by 2,424
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
Predicting immunogenic tumour mutations by combining mass spectrometry and exome sequencing
Yadav, M., Jhunjhunwala, S., Phung, Q. T., Lupardus, P., Tanguay, J., Bumbaca, S., Franci, C., Cheung, T. K., Fritsche, J., Weinschenk, T., et al. (2014) · Nature · doi:10.1038/nature14001 · Cited by 1,186
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A “Proteomic Ruler” for Protein Copy Number and Concentration Estimation without Spike-in Standards
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Bystander CD8+ T cells are abundant and phenotypically distinct in human tumour infiltrates
Simoni, Y., Becht, E., Fehlings, M., Loh, C. Y., Koo, S.-L., Teng, K. W. W., Yeong, J. P. S., Nahar, R., Zhang, T., Kared, H., et al. (2018) · Nature · doi:10.1038/s41586-018-0130-2 · Cited by 1,370
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
Identification of tumor antigens with immunopeptidomics
Chong, C., Coukos, G., & Bassani-Sternberg, M. (2022) · Nature Biotechnology · doi:10.1038/s41587-021-01038-8 · Cited by 232
A high-stringency blueprint of the human proteome
Adhikari, S., Nice, E. C., Deutsch, E. W., Lane, L., Omenn, G. S., Pennington, S. R., Paik, Y.-K., Overall, C. M., Corrales, F. J., Cristea, I. M., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19045-9 · Cited by 210
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Self-citation
Metadata
- Authors
- Khodadoust, M. S., Olsson, N., Wagar, L. E., Haabeth, O. A. W., Chen, B., Swaminathan, K., Rawson, K., Liu, C. L., Steiner, D., Lund, P., Rao, S., Zhang, L., Marceau, C., Stehr, H., Newman, A. M., Czerwinski, D. K., Carlton, V. E. H., Moorhead, M., Faham, M., Kohrt, H. E., Carette, J., Green, M. R., Davis, M. M., Levy, R., Elias, J. E., & Alizadeh, A. A.
- Venue
- Nature
- Published
- 2017-03
- Volume
- 543
- Issue
- 7647
- Pages
- 723-727
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2599601523
- Cited by
- 261
- References
- 8
- FWCI
- 13.40
- Type
- journal article
- Language
- en
- Open access
- green
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