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Cited by 299

The DOI matches its Crossref record; 157 of the 157 references it cites were found in a registry or an index.

Chimeric Antigen Receptors Modified T-Cells for Cancer Therapy

Open access
Dai, Hanren, Wang, Yao, Lu, Xuechun, Han, Weidong·2016·JNCI: Journal of the National Cancer Institute

Abstract

The genetic modification and characterization of T-cells with chimeric antigen receptors (CARs) allow functionally distinct T-cell subsets to recognize specific tumor cells. The incorporation of costimulatory molecules or cytokines can enable engineered T-cells to eliminate tumor cells. CARs are generated by fusing the antigen-binding region of a monoclonal antibody (mAb) or other ligand to membrane-spanning and intracellular-signaling domains. They have recently shown clinical benefit in patients treated with CD19-directed autologous T-cells. Recent successes suggest that the modification of T-cells with CARs could be a powerful approach for developing safe and effective cancer therapeutics. Here, we briefly review early studies, consider strategies to improve the therapeutic potential and safety, and discuss the challenges and future prospects for CAR T-cells in cancer therapy.

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Crossref · 10.1093/jnci/djv439

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Metadata

Authors
Dai, H., Wang, Y., Lu, X., & Han, W.
Venue
JNCI: Journal of the National Cancer Institute
Published
2016-01-27
Volume
108
Issue
7
ISSN
  • 0027-8874 (ISSN-L)
  • 1460-2105
OpenAlex
W2316953565
Cited by
299
References
157
FWCI
19.62
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Chimeric Antigen Receptors Modified T-Cells for Cancer Therapy. https://app.cochat.ai/papers/10.1093/jnci/djv439
The paper
Dai, H., Wang, Y., Lu, X., & Han, W. (2016). Chimeric Antigen Receptors Modified T-Cells for Cancer Therapy. JNCI: Journal of the National Cancer Institute. https://doi.org/10.1093/jnci/djv439

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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.