The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer
Abstract
T cells directed against mutant neo-epitopes drive cancer immunity. However, spontaneous immune recognition of mutations is inefficient. We recently introduced the concept of individualized mutanome vaccines and implemented an RNA-based poly-neo-epitope approach to mobilize immunity against a spectrum of cancer mutations. Here we report the first-in-human application of this concept in melanoma. We set up a process comprising comprehensive identification of individual mutations, computational prediction of neo-epitopes, and design and manufacturing of a vaccine unique for each patient. All patients developed T cell responses against multiple vaccine neo-epitopes at up to high single-digit percentages. Vaccine-induced T cell infiltration and neo-epitope-specific killing of autologous tumour cells were shown in post-vaccination resected metastases from two patients. The cumulative rate of metastatic events was highly significantly reduced after the start of vaccination, resulting in a sustained progression-free survival. Two of the five patients with metastatic disease experienced vaccine-related objective responses. One of these patients had a late relapse owing to outgrowth of β2-microglobulin-deficient melanoma cells as an acquired resistance mechanism. A third patient developed a complete response to vaccination in combination with PD-1 blockade therapy. Our study demonstrates that individual mutations can be exploited, thereby opening a path to personalized immunotherapy for patients with cancer.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“For example, intranodal vaccination with free mRNA encoding ten neoepitopes of 13 patients with metastatic melanoma generated T cell immunity against multiple neoepitopes in all patients209.”
From Lipid nanoparticles for mRNA delivery (2021) · cites this paper as [209]
In the citing paper
“A first-in-human trial demonstrated the clinical feasibility and safety of this approach for advanced melanoma cancers: all vaccinated patients developed CD4 + and CD8 + T cell responses against the selected antigens, with some patients showing objective antitumor responses [15].”
From Three decades of messenger RNA vaccine development (2019) · cites this paper as [15]
Citations
Cites
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607
PD-1 and PD-L1 Immune Checkpoint Blockade to Treat Breast Cancer
Hartkopf, A. D., Taran, F., Wallwiener, M., Walter, C. B., Krämer, B., Grischke, E., & Brucker, S. Y. (2016) · Breast Care · doi:10.1159/000453569 · Cited by 30,989
Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.
Langmead, B., Trapnell, C., Pop, M., & Salzberg, S. L. (2009) · Genome Biology · doi:10.1186/gb-2009-10-3-r25 · Cited by 21,849
Mapping and quantifying mammalian transcriptomes by RNA-Seq
Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., & Wold, B. (2008) · Nature Methods · doi:10.1038/nmeth.1226 · Cited by 13,696
Primer3—new capabilities and interfaces
Untergasser, A., Cutcutache, I., Kõressaar, T., Ye, J., Faircloth, B., Remm, M., & Rozen, S. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks596 · Cited by 9,165
Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration
Thorvaldsdottir, H., Robinson, J. T., & Mesirov, J. P. (2013) · Briefings in Bioinformatics · doi:10.1093/bib/bbs017 · Cited by 9,049
<tt>BLAT</tt> —The <tt>BLAST</tt> -Like Alignment Tool
Kent, W. J. (2002) · Genome Research · doi:10.1101/gr.229202 · Cited by 8,480
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
Self-citationPD-1 blockade induces responses by inhibiting adaptive immune resistance
Tumeh, P. C., Harview, C. L., Yearley, J. H., Shintaku, I. P., Taylor, E. J. M., Robert, L., Chmielowski, B., Spasic, M., Henry, G., Ciobanu, V., et al. (2014) · Nature · doi:10.1038/nature13954 · Cited by 6,609
Pembrolizumab versus Ipilimumab in Advanced Melanoma
Robert, C., Schachter, J., Long, G. V., Arance, A., Grob, J. J., Mortier, L., Daud, A., Carlino, M. S., McNeil, C., Lotem, M., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1503093 · Cited by 5,887
Cited by
Sorted by citations
The biology and management of non-small cell lung cancer
Herbst, R. S., Morgensztern, D., & Boshoff, C. (2018) · Nature · doi:10.1038/nature25183 · Cited by 4,891
mRNA vaccines — a new era in vaccinology
Pardi, N., Hogan, M. J., Porter, F. W., & Weissman, D. (2018) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2017.243 · Cited by 4,667
A guide to cancer immunotherapy: from T cell basic science to clinical practice
Waldman, A. D., Fritz, J. M., & Lenardo, M. J. (2020) · Nature Reviews Immunology · doi:10.1038/s41577-020-0306-5 · Cited by 4,154
Lipid nanoparticles for mRNA delivery
Hou, X., Zaks, T., Langer, R., & Dong, Y. (2021) · Nature Reviews Materials · doi:10.1038/s41578-021-00358-0 · Cited by 4,076
Approaches to treat immune hot, altered and cold tumours with combination immunotherapies
Galon, J., & Bruni, D. (2019) · Nature Reviews Drug Discovery · doi:10.1038/s41573-018-0007-y · Cited by 3,520
Metadata
- Authors
- Sahin, U., Derhovanessian, E., Miller, M., Kloke, B.-P., Simon, P., Löwer, M., Bukur, V., Tadmor, A. D., Luxemburger, U., Schrörs, B., Omokoko, T., Vormehr, M., Albrecht, C., Paruzynski, A., Kuhn, A. N., Buck, J., Heesch, S., Schreeb, K. H., Müller, F., Ortseifer, I., Vogler, I., Godehardt, E., Attig, S., Rae, R., Breitkreuz, A., Tolliver, C., Suchan, M., Martic, G., Hohberger, A., Sorn, P., Diekmann, J., Ciesla, J., Waksmann, O., Brück, A.-K., Witt, M., Zillgen, M., Rothermel, A., Kasemann, B., Langer, D., Bolte, S., Diken, M., Kreiter, S., Nemecek, R., Gebhardt, C., Grabbe, S., Höller, C., Utikal, J., Huber, C., Loquai, C., & Türeci, Ö.
- Affiliations
- BioNTech (Germany) (DE)
- Johannes Gutenberg University Mainz (DE)
- University Medical Center of the Johannes Gutenberg University Mainz (DE)
- Medical University of Vienna (AT)
- German Cancer Research Center (DE)
- ORCID
- Venue
- Nature
- Published
- 2017-07-05
- Volume
- 547
- Issue
- 7662
- Pages
- 222-226
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2724264513
- Cited by
- 2,488
- References
- 43
- Citations by year
- 2026: 228 · 2025: 255 · 2024: 259 · 2023: 299 · 2022: 277 · 2021: 317 · 2020: 290 · 2019: 262 · 2018: 239 · 2017: 58
- FWCI
- 105.75
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Life Sciences › Immunology and Microbiology › Immunology › Immunotherapy and Immune Responses
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
- Keywords
- neoantigens, melanoma, cancer immunotherapy, T cell response, metastasis prevention, anti-PD-1 therapy, acquired resistance, beta2-microglobulin deficiency, vaccine safety and tolerability, tumor cell killing, tumor-infiltrating T cells
- MeSH terms
- Nivolumab, Antibodies, Monoclonal, Epitopes, beta 2-Microglobulin, Humans, Immunotherapy, Melanoma, Mutation, Neoplasm Metastasis, Neoplasm Recurrence, Local, RNA, T-Lymphocytes, Vaccination, CD8 Antigens, Cancer Vaccines, Precision Medicine, B7-H1 Antigen, Programmed Cell Death 1 Receptor
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review