The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Targeting a CAR to the TRAC locus with CRISPR/Cas9 enhances tumour rejection
Open accessAbstract
Chimeric antigen receptors (CARs) are synthetic receptors that redirect and reprogram T cells to mediate tumour rejection. The most successful CARs used to date are those targeting CD19 (ref. 2), which offer the prospect of complete remission in patients with chemorefractory or relapsed B-cell malignancies. CARs are typically transduced into the T cells of a patient using γ-retroviral vectors or other randomly integrating vectors, which may result in clonal expansion, oncogenic transformation, variegated transgene expression and transcriptional silencing. Recent advances in genome editing enable efficient sequence-specific interventions in human cells, including targeted gene delivery to the CCR5 and AAVS1 loci. Here we show that directing a CD19-specific CAR to the T-cell receptor α constant (TRAC) locus not only results in uniform CAR expression in human peripheral blood T cells, but also enhances T-cell potency, with edited cells vastly outperforming conventionally generated CAR T cells in a mouse model of acute lymphoblastic leukaemia. We further demonstrate that targeting the CAR to the TRAC locus averts tonic CAR signalling and establishes effective internalization and re-expression of the CAR following single or repeated exposure to antigen, delaying effector T-cell differentiation and exhaustion. These findings uncover facets of CAR immunobiology and underscore the potential of CRISPR/Cas9 genome editing to advance immunotherapies.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“AAV6 homologous donor DNA templates are an efficient way to deliver donor templates for sensitive primary immune cells, including HSPCs and T-Cells15,35–40.”
From A high-fidelity Cas9 mutant delivered as a ribonucleoprotein complex enables efficient gene editing in human hematopoietic stem and progenitor cells (2018) · cites this paper as [39]
Experimental — accuracy not yet measuredIn the citing paper
“More recent work has revealed potential advantages of targeted integrations of antigen receptor genes into defined genomic loci (Eyquem et al., 2017), which can be achieved with programmable nucleases such as CRISPR-Cas9 along with viral or non-viral knock-in templates (Gwiazda et al., 2016; Eyquem et al., 2017; Roth et al., 2018).”
From Pooled Knockin Targeting for Genome Engineering of Cellular Immunotherapies (2020) · cites this paper as Eyquem et al., 2017
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Molecular and cellular insights into T cell exhaustion
Wherry, E. J., & Kurachi, M. (2015) · Nature Reviews Immunology · doi:10.1038/nri3862 · Cited by 4,652
Brentjens, R. J., Davila, M. L., Riviere, I., Park, J., Wang, X., Cowell, L. G., Bartido, S., Stefanski, J., Taylor, C., Olszewska, M., et al. (2013) · Science Translational Medicine · doi:10.1126/scitranslmed.3005930 · Cited by 2,063
Self-citationBlackburn, S. D., Shin, H., Haining, W. N., Zou, T., Workman, C. J., Polley, A., Betts, M. R., Freeman, G. J., Vignali, D. A. A., & Wherry, E. J. (2009) · Nature Immunology · doi:10.1038/ni.1679 · Cited by 2,062
A human memory T cell subset with stem cell–like properties
Gattinoni, L., Lugli, E., Ji, Y., Pos, Z., Paulos, C. M., Quigley, M. F., Almeida, J. R., Gostick, E., Yu, Z., Carpenito, C., et al. (2011) · Nature Medicine · doi:10.1038/nm.2446 · Cited by 1,974
Long, A. H., Haso, W. M., Shern, J. F., Wanhainen, K. M., Murgai, M., Ingaramo, M., Smith, J. P., Walker, A. J., Kohler, M. E., Venkateshwara, V. R., et al. (2015) · Nature Medicine · doi:10.1038/nm.3838 · Cited by 1,815
Human T-lymphocyte cytotoxicity and proliferation directed by a single chimeric TCRζ /CD28 receptor
Maher, J. F., Brentjens, R. J., Gunset, G., Rivière, I., & Sadelain, M. (2002) · Nature Biotechnology · doi:10.1038/nbt0102-70 · Cited by 1,031
Self-citationBiology and Applications of CRISPR Systems: Harnessing Nature’s Toolbox for Genome Engineering
Wright, A. V., Nuñez, J. K., & Doudna, J. A. (2016) · Cell · doi:10.1016/j.cell.2015.12.035 · Cited by 989
Sommermeyer, D., Hudecek, M., Kosasih, P. L., Gogishvili, T., Maloney, D. G., Turtle, C. J., & Riddell, S. R. (2015) · Leukemia · doi:10.1038/leu.2015.247 · Cited by 890
Zhao, Z., Condomines, M., van der Stegen, S. J. C., Perna, F., Kloss, C. C., Gunset, G., Plotkin, J., & Sadelain, M. (2015) · Cancer Cell · doi:10.1016/j.ccell.2015.09.004 · Cited by 843
Self-citationTolerance and exhaustion: defining mechanisms of T cell dysfunction
Schietinger, A., & Greenberg, P. D. (2013) · Trends in Immunology · doi:10.1016/j.it.2013.10.001 · Cited by 704
Cited by
Sorted by citations
Items 1,001–1,002 of 1,002
Gene Augmentation and Editing to Improve TCR Engineered T Cell Therapy against Solid Tumors
Lo Presti, V., Buitenwerf, F., van Til, N. P., & Nierkens, S. (2020) · Vaccines · doi:10.3390/vaccines8040733 · Cited by 14
CRISPR-Cas9 genome editing for cancer immunotherapy: opportunities and challenges
Chen, M., Xu, J., Zhou, Y., Zhang, S., & Zhu, D. (2020) · Briefings in Functional Genomics · doi:10.1093/bfgp/elz027 · Cited by 12
Metadata
- Authors
- Eyquem, J., Mansilla-Soto, J., Giavridis, T., van der Stegen, S. J. C., Hamieh, M., Cunanan, K. M., Odak, A., Gönen, M., & Sadelain, M.
- Affiliations
- Memorial Sloan Kettering Cancer Center (US)
- Corresponding author
- Sadelain, Michel
- ORCID
- Venue
- Nature
- Published
- 2017-02-22
- Volume
- 543
- Issue
- 7643
- Pages
- 113-117
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC5558614
- OpenAlex
- W2589417329
- Semantic Scholar
- 47af46911569825ab86ac946a5c9cd502504aa3f
- Cited by
- 1,831
- References
- 33
- Citations by year
- 2026: 191 · 2025: 175 · 2024: 206 · 2023: 201 · 2022: 224 · 2021: 238 · 2020: 190 · 2019: 186 · 2018: 151 · 2017: 68
- FWCI
- 71.74
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Cancer Institute (P30CA008748)
- Topics
- Health Sciences › Medicine › Oncology › CAR-T cell therapy research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Virus-based gene therapy research
- Keywords
- chimeric antigen receptor, CRISPR/Cas9 genome editing, CD19, chimeric antigen receptor T cells, T cell exhaustion, T cell differentiation, acute lymphoblastic leukemia, tumor rejection, targeted gene integration
- MeSH terms
- Gene Editing, Animals, Cell Differentiation, Disease Models, Animal, Gene Expression Regulation, Humans, Immunotherapy, Lymphocyte Activation, Male, Promoter Regions, Genetic, Receptors, Antigen, T-Cell, T-Lymphocytes, Receptors, Antigen, T-Cell, alpha-beta, Antigens, CD19, Mice, Precursor Cell Lymphoblastic Leukemia-Lymphoma, Genetic Loci, Translational Research, Biomedical, CRISPR-Cas Systems
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