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Cited by 722

The DOI matches its Crossref record; 204 of the 204 references it cites were found in a registry or an index.

Brain immunology and immunotherapy in brain tumours

Open access
Sampson, John H., Gunn, Michael D., Fecci, Peter E., Ashley, David M.·2020·Nature Reviews Cancer

Abstract

Gliomas, the most common malignant primary brain tumours, remain universally lethal. Yet, seminal discoveries in the past 5 years have clarified the anatomy, genetics and function of the immune system within the central nervous system (CNS) and altered the paradigm for successful immunotherapy. The impact of standard therapies on the response to immunotherapy is now better understood, as well. This new knowledge has implications for a broad range of tumours that develop within the CNS. Nevertheless, the requirements for successful therapy remain effective delivery and target specificity, while the dramatic heterogeneity of malignant gliomas at the genetic and immunological levels remains a profound challenge. This Review discusses how advances in our understanding of the immune system within the brain have implications for the successful implementation of immunotherapy to treat brain tumours, despite challenges such as effective delivery, target specificity and intratumour heterogeneity.

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Crossref · 10.1038/s41568-019-0224-7

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Metadata

Authors
Sampson, J. H., Gunn, M. D., Fecci, P. E., & Ashley, D. M.
Venue
Nature Reviews Cancer
Published
2019-12-05
Volume
20
Issue
1
Pages
12-25
ISSN
  • 1474-175X (ISSN-L)
  • 1474-1768
OpenAlex
W2994525341
Cited by
722
References
204
FWCI
11.66
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Brain immunology and immunotherapy in brain tumours. https://app.cochat.ai/papers/10.1038/s41568-019-0224-7
The paper
Sampson, J. H., Gunn, M. D., Fecci, P. E., & Ashley, D. M. (2020). Brain immunology and immunotherapy in brain tumours. Nature Reviews Cancer. https://doi.org/10.1038/s41568-019-0224-7

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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.