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抗体片段内化的快速评估用于抗体片段-药物偶联物。

Rapid Evaluation of Antibody Fragment Endocytosis for Antibody Fragment-Drug Conjugates.

机构信息

Department of Systems Immunology, Division of Biomedical Convergence, College of Biomedical Science, Kangwon National University, Chuncheon, Gangwon 24341, Korea.

Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, and College of Medicine and College of Pharmacy, Seoul National University, Seoul 03080, Korea.

出版信息

Biomolecules. 2020 Jun 25;10(6):955. doi: 10.3390/biom10060955.

DOI:10.3390/biom10060955
PMID:32630402
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7355425/
Abstract

Antibody-drug conjugates (ADCs) have emerged as the most promising strategy in targeted cancer treatment. Recent strategies for the optimization ADCs include the development of antibody fragment-drug conjugates (FDCs). The critical factor in the successful development of ADCs and FDCs is the identification of tumor antigen-specific and internalizing antibodies (Abs). However, systematic comparison or correlation studies of internalization rates with different antibody formats have not been reported previously. In this study, we generated a panel of scFv-phage Abs using phage display technology and their corresponding scFv and scFv-Fc fragments and evaluated their relative internalization kinetics in relation to their antibody forms. We found that the relative rates and levels of internalization of scFv-phage antibodies positively correlate with their scFv and scFv-Fc forms. Our systematic study demonstrates that endocytosis of scFv-phage can serve as a predictive indicator for the assessment of Ab fragment internalization. Additionally, the present study demonstrates that endocytic antibodies can be rapidly screened and selected from phage antibody libraries prior to the conversion of phage antibodies for the generation of the conventional antibody format. Our strategic approach for the identification and evaluation of endocytic antibodies would expedite the selection for optimal antibodies and antibody fragments and be broadly applicable to ADC and FDC development.

摘要

抗体药物偶联物(ADCs)已成为靶向癌症治疗中最有前途的策略。最近优化 ADC 的策略包括开发抗体片段药物偶联物(FDCs)。成功开发 ADC 和 FDC 的关键因素是鉴定肿瘤抗原特异性和内化抗体(Abs)。然而,以前没有报道过不同抗体形式的内化率的系统比较或相关性研究。在这项研究中,我们使用噬菌体展示技术生成了一组 scFv-噬菌体 Abs,并生成了它们相应的 scFv 和 scFv-Fc 片段,并评估了它们与抗体形式相关的相对内化动力学。我们发现 scFv-噬菌体的相对内化速率和水平与其 scFv 和 scFv-Fc 形式呈正相关。我们的系统研究表明,scFv-噬菌体的内吞作用可以作为评估 Ab 片段内化的预测指标。此外,本研究表明,在将噬菌体抗体转化为常规抗体形式之前,可以从噬菌体抗体文库中快速筛选和选择内吞抗体。我们用于鉴定和评估内吞抗体的策略方法将加快对最佳抗体和抗体片段的选择,并广泛适用于 ADC 和 FDC 的开发。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad91/7355425/d5b3e78c3177/biomolecules-10-00955-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad91/7355425/d81d25179bfc/biomolecules-10-00955-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad91/7355425/3b1b2d136de6/biomolecules-10-00955-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad91/7355425/a82bb9ee50d3/biomolecules-10-00955-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad91/7355425/e56f1bd00c26/biomolecules-10-00955-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad91/7355425/1ee93e73f974/biomolecules-10-00955-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad91/7355425/e97c153202f1/biomolecules-10-00955-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad91/7355425/d5b3e78c3177/biomolecules-10-00955-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad91/7355425/d81d25179bfc/biomolecules-10-00955-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad91/7355425/3b1b2d136de6/biomolecules-10-00955-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad91/7355425/a82bb9ee50d3/biomolecules-10-00955-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad91/7355425/e56f1bd00c26/biomolecules-10-00955-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad91/7355425/1ee93e73f974/biomolecules-10-00955-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad91/7355425/e97c153202f1/biomolecules-10-00955-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad91/7355425/d5b3e78c3177/biomolecules-10-00955-g007.jpg

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Antibodies (Basel). 2018 Mar 31;7(2):16. doi: 10.3390/antib7020016.
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Deep Mining of Complex Antibody Phage Pools Generated by Cell Panning Enables Discovery of Rare Antibodies Binding New Targets and Epitopes.
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