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Cited by 269

The DOI matches its Crossref record; 82 of the 82 references it cites were found in a registry or an index.

How to select IgG subclasses in developing anti-tumor therapeutic antibodies

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Yu, Jifeng, Song, Yongping, Tian, Wenzhi·2020·Journal of Hematology & Oncology
DOI 10.1186/s13045-020-00876-4
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Abstract

The intact antibody of human immunoglobulin (IgG) is composed of the fragment for antigen binding (Fab) and the crystallizable fragment (Fc) for binding of Fcγ receptors. Among the four subclasses of human IgG (IgG1, IgG2, IgG3, IgG4), which differ in their constant regions, particularly in their hinges and CH2 domains, IgG1 has the highest FcγR-binding affinity, followed by IgG3, IgG2, and IgG4. As a result, different subclasses have different effector functions such as antibody-dependent cell-mediated cytotoxicity (ADCC) and antibody-dependent cellular phagocytosis (ADCP). Fcγ receptors include six subtypes (FcγRI, FcγRIIA, FcγRIIB, FcγRIIC, FcγRIIIA, FcγRIIIB) which differ in cellular distribution, binding affinity to Fc, and the resulting biological activity. Therefore, when developing anti-tumor therapeutic antibodies, including single-targeted antibodies, bi-specific antibodies (BsAbs), and antibody-drug conjugates (ADCs), many factors, such as target biology, cellular distribution of the targets, the environments of particular tumor types, as well as the proposed mechanism of action (MOA), must be taken into consideration. This review outlines fundamental strategies that are required to select IgG subclasses in developing anti-tumor therapeutic antibodies.

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Metadata

Authors
Yu, J., Song, Y., & Tian, W.
Venue
Journal of Hematology & Oncology
Publisher
Springer Science and Business Media LLC
Published
2020-05-05
Volume
13
Issue
1
Pages
45-45
ISSN
1756-8722 (ISSN-L)
DOI
10.1186/s13045-020-00876-4
OpenAlex
W3021099711
Cited by
269
References
82
FWCI
11.65
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: How to select IgG subclasses in developing anti-tumor therapeutic antibodies. https://app.cochat.ai/papers/10.1186/s13045-020-00876-4
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Yu, J., Song, Y., & Tian, W. (2020). How to select IgG subclasses in developing anti-tumor therapeutic antibodies. Journal of Hematology & Oncology. https://doi.org/10.1186/s13045-020-00876-4

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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.