The DOI matches its Crossref record; 102 of the 102 references it cites were found in a registry or an index.
Immune checkpoint pathways in immunotherapy for head and neck squamous cell carcinoma
Open accessAbstract
With the understanding of the complex interaction between the tumour microenvironment and immunotherapy, there is increasing interest in the role of immune regulators in the treatment of head and neck squamous cell carcinoma (HNSCC). Activation of T cells and immune checkpoint molecules is important for the immune response to cancers. Immune checkpoint molecules include cytotoxic T lymphocyte antigen 4 (CTLA-4), programmed death 1 (PD-1), T-cell immunoglobulin mucin protein 3 (TIM-3), lymphocyte activation gene 3 (LAG-3), T cell immunoglobin and immunoreceptor tyrosine-based inhibitory motif (TIGIT), glucocorticoid-induced tumour necrosis factor receptor (GITR) and V-domain Ig suppressor of T cell activation (VISTA). Many clinical trials using checkpoint inhibitors, as both monotherapies and combination therapies, have been initiated targeting these immune checkpoint molecules. This review summarizes the functional mechanism and use of various immune checkpoint molecules in HNSCC, including monotherapies and combination therapies, and provides better treatment options for patients with HNSCC.
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Cited by
Huo, J.-L., Wang, Y.-T., Fu, W.-J., Lu, N., & Liu, Z.-S. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.956090 · Cited by 176
Metadata
- Authors
- Mei, Z., Huang, J., Qiao, B., & Lam, A. K.-Y.
- Venue
- International Journal of Oral Science
- Published
- 2020-05-28
- Volume
- 12
- Issue
- 1
- Pages
- 16-16
- ISSN
- 1674-2818 (ISSN-L)
- 2049-3169
- OpenAlex
- W3030560367
- Cited by
- 257
- References
- 102
- FWCI
- 8.58
- Type
- journal article
- Language
- en
- Open access
- gold
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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.
