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Cited by 746

The DOI matches its Crossref record; 154 of the 154 references it cites were found in a registry or an index.

Immunotherapy for glioma: Current management and future application

Open access
Xu, Shengchao, Tang, Lu, Li, Xizhe, Fan, Fan, Liu, Zhixiong·2020·Cancer Letters

Abstract

Gliomas are intrinsic brain tumors that originate from neuroglial progenitor cells. Conventional therapies, including surgery, chemotherapy, and radiotherapy, have achieved limited improvements in the prognosis of glioma patients. Immunotherapy, a revolution in cancer treatment, has become a promising strategy with the ability to penetrate the blood-brain barrier since the pioneering discovery of lymphatics in the central nervous system. Here we detail the current management of gliomas and previous studies assessing different immunotherapies in gliomas, despite the fact that the associated clinical trials have not been completed yet. Moreover, several drugs that have undergone clinical trials are listed as novel strategies for future application; however, these clinical trials have indicated limited efficacy in glioma. Therefore, additional studies are warranted to evaluate novel therapeutic approaches in glioma treatment.

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Crossref · 10.1016/j.canlet.2020.02.002

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Metadata

Authors
Xu, S., Tang, L., Li, X., Fan, F., & Liu, Z.
Venue
Cancer Letters
Publisher
Elsevier BV
Published
2020-04
Volume
476
Pages
1-12
ISSN
0304-3835 (ISSN-L)
OpenAlex
W3005468192
Cited by
746
References
154
FWCI
44.15
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Immunotherapy for glioma: Current management and future application. https://app.cochat.ai/papers/10.1016/j.canlet.2020.02.002
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Xu, S., Tang, L., Li, X., Fan, F., & Liu, Z. (2020). Immunotherapy for glioma: Current management and future application. Cancer Letters. https://doi.org/10.1016/j.canlet.2020.02.002

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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.