The DOI matches its Crossref record; 96 of the 96 references it cites were found in a registry or an index.
Integrated proteogenomic deep sequencing and analytics accurately identify non-canonical peptides in tumor immunopeptidomes
Open accessAbstract
Efforts to precisely identify tumor human leukocyte antigen (HLA) bound peptides capable of mediating T cell-based tumor rejection still face important challenges. Recent studies suggest that non-canonical tumor-specific HLA peptides derived from annotated non-coding regions could elicit anti-tumor immune responses. However, sensitive and accurate mass spectrometry (MS)-based proteogenomics approaches are required to robustly identify these non-canonical peptides. We present an MS-based analytical approach that characterizes the non-canonical tumor HLA peptide repertoire, by incorporating whole exome sequencing, bulk and single-cell transcriptomics, ribosome profiling, and two MS/MS search tools in combination. This approach results in the accurate identification of hundreds of shared and tumor-specific non-canonical HLA peptides, including an immunogenic peptide derived from an open reading frame downstream of the melanoma stem cell marker gene ABCB5 . These findings hold great promise for the discovery of previously unknown tumor antigens for cancer immunotherapy.
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Promises and challenges of adoptive T-cell therapies for solid tumours
Morotti, M., Albukhari, A., Alsaadi, A., Artibani, M., Brenton, J. D., Curbishley, S. M., Dong, T., Dustin, M. L., Hu, Z., McGranahan, N., et al. (2021) · British Journal of Cancer · doi:10.1038/s41416-021-01353-6 · Cited by 269
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
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
Self-citationThe Peptide Vaccine of the Future
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Metadata
- Authors
- Chong, C., Müller, M., Pak, H., Harnett, D., Huber, F., Grun, D., Leleu, M., Auger, A., Arnaud, M., Stevenson, B. J., Michaux, J., Bilic, I., Hirsekorn, A., Calviello, L., Simó-Riudalbas, L., Planet, E., Lubiński, J., Bryśkiewicz, M., Wiznerowicz, M., Xenarios, I., Zhang, L., Trono, D., Harari, A., Ohler, U., Coukos, G., & Bassani-Sternberg, M.
- Venue
- Nature Communications
- Published
- 2020-03-10
- Volume
- 11
- Issue
- 1
- Pages
- 1293-1293
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W3010737707
- Cited by
- 346
- References
- 96
- FWCI
- 18.69
- Type
- journal article
- Language
- en
- Open access
- gold
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- Chong, C., Müller, M., Pak, H., Harnett, D., Huber, F., Grun, D., Leleu, M., Auger, A., Arnaud, M., Stevenson, B. J., Michaux, J., Bilic, I., Hirsekorn, A., Calviello, L., Simó-Riudalbas, L., Planet, E., Lubiński, J., Bryśkiewicz, M., Wiznerowicz, M., . . . Bassani-Sternberg, M. (2020). Integrated proteogenomic deep sequencing and analytics accurately identify non-canonical peptides in tumor immunopeptidomes. Nature Communications. https://doi.org/10.1038/s41467-020-14968-9
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
