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Elucidating Novel Targets for Ovarian Cancer Antibody–Drug Conjugate Development: Integrating In Silico Prediction and Surface Plasmon Resonance to Identify Targets with Enhanced Antibody Internalization Capacity
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David James ,
Jezabel Garcia-Parra ,
John Sinfield,
Anna Moberg,
Zoe Coombes ,
Jenny Worthington,
Nicole Williams,
Lewis Webb Francis,
Steve Conlan ,
Deya Gonzalez
Antibodies, Volume: 12, Issue: 4, Start page: 65
Swansea University Authors:
Steve Conlan , Deya Gonzalez
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© 2023 by the authors.This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
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DOI (Published version): 10.3390/antib12040065
Abstract
Antibody–drug conjugates (ADCs) constitute a rapidly expanding category of biopharmaceuticals that are reshaping the landscape of targeted chemotherapy. The meticulous process of selecting therapeutic targets, aided by specific monoclonal antibodies’ high specificity for binding to designated antige...
| Published in: | Antibodies |
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| ISSN: | 2073-4468 |
| Published: |
MDPI AG
2023
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa65401 |
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| Abstract: |
Antibody–drug conjugates (ADCs) constitute a rapidly expanding category of biopharmaceuticals that are reshaping the landscape of targeted chemotherapy. The meticulous process of selecting therapeutic targets, aided by specific monoclonal antibodies’ high specificity for binding to designated antigenic epitopes, is pivotal in ADC research and development. Despite ADCs’ intrinsic ability to differentiate between healthy and cancerous cells, developmental challenges persist. In this study, we present a rationalized pipeline encompassing the initial phases of the ADC development, including target identification and validation. Leveraging an in-house, computationally constructed ADC target database, termed ADC Target Vault, we identified a set of novel ovarian cancer targets. We effectively demonstrate the efficacy of Surface Plasmon Resonance (SPR) technology and in vitro models as predictive tools, expediting the selection and validation of targets as ADC candidates for ovarian cancer therapy. Our analysis reveals three novel robust antibody/target pairs with strong binding and favourable antibody internalization rates in both wild-type and cisplatin-resistant ovarian cancer cell lines. This approach enhances ADC development and offers a comprehensive method for assessing target/antibody combinations and pre-payload conjugation biological activity. Additionally, the strategy establishes a robust platform for high-throughput screening of potential ovarian cancer ADC targets, an approach that is equally applicable to other cancer types. |
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| Keywords: |
ovarian cancer; antibody–drug conjugates; bioinformatics; in silico; biomarkers; therapeutics; internalization; SPR; Biacore |
| College: |
Faculty of Medicine, Health and Life Sciences |
| Funders: |
This research was funded by the Welsh Government through the SMARTExpertise Programme, grant Cluster for Epigenomic and ADC Therapeutics (CEAT) project (2017/COL/004). |
| Issue: |
4 |
| Start Page: |
65 |