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Cited by 365

The DOI matches its Crossref record; 147 of the 147 references it cites were found in a registry or an index.

Prospects for gene-engineered T cell immunotherapy for solid cancers

Open access
Klebanoff, Christopher A, Rosenberg, Steven A, Restifo, Nicholas P·2016·Nature Medicine

Abstract

Adoptive transfer of receptor-engineered T cells has produced impressive results in treating patients with B cell leukemias and lymphomas. This success has captured public imagination and driven academic and industrial researchers to develop similar 'off-the-shelf' receptors targeting shared antigens on epithelial cancers, the leading cause of cancer-related deaths. However, the successful treatment of large numbers of people with solid cancers using this strategy is unlikely to be straightforward. Receptor-engineered T cells have the potential to cause lethal toxicity from on-target recognition of normal tissues, and there is a paucity of truly tumor-specific antigens shared across tumor types. Here we offer our perspective on how expanding the use of genetically redirected T cells to treat the majority of patients with solid cancers will require major technical, manufacturing and regulatory innovations centered around the development of autologous gene therapies targeting private somatic mutations.

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Metadata

Authors
Klebanoff, C. A., Rosenberg, S. A., & Restifo, N. P.
Venue
Nature Medicine
Published
2016-01
Volume
22
Issue
1
Pages
26-36
ISSN
  • 1078-8956 (ISSN-L)
  • 1546-170X
OpenAlex
W2232549736
Cited by
365
References
147
FWCI
28.12
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Prospects for gene-engineered T cell immunotherapy for solid cancers. https://app.cochat.ai/papers/10.1038/nm.4015
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Klebanoff, C. A., Rosenberg, S. A., & Restifo, N. P. (2016). Prospects for gene-engineered T cell immunotherapy for solid cancers. Nature Medicine. https://doi.org/10.1038/nm.4015

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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.