| Literature DB >> 31442030 |
Bifan Chen1, Ziqing Lin2,3, Yanlong Zhu2,3, Yutong Jin1, Eli Larson1, Qingge Xu2,3, Cexiong Fu4, Zhaorui Zhang4, Qunying Zhang4, Wayne A Pritts4, Ying Ge1,2,3.
Abstract
Antibody-drug conjugates (ADCs) are designed to combine the target specificity of monoclonal antibodies and potent cytotoxin drugs to achieve better therapeutic outcomes. Comprehensive evaluation of the quality attributes of ADCs is critical for drug development but remains challenging due to heterogeneity of the construct. Currently, peptide mapping with reversed-phase liquid chromatography (RPLC) coupled to mass spectrometry (MS) is the predominant approach to characterize ADCs. However, it is suboptimal for sequence characterization and quantification of ADCs because it lacks a comprehensive view of coexisting variants and suffers from varying ionization effects of drug-conjugated peptides compared to unconjugated counterparts. Here, we present the first middle-down RPLC-MS analysis of both cysteine (Adcetris; BV) and lysine (Kadcyla; T-DM1) conjugated ADCs at the subunit level (∼25 kDa) with electron transfer dissociation (ETD). We successfully achieved high-resolution separation of subunit isomers arising from different drug conjugation and subsequently localized the conjugation sites. Moreover, we obtained a comprehensive overview of the microvariants associated with each subunits and characterized them such as oxidized variants with different sites. Furthermore, we observed relatively high levels of conjugation near complementarity-determining regions (CDRs) from the heavy chain but no drug conjugation near CDRs of light chain (Lc) from lysine conjugated T-DM1. Based on the extracted ion chromatograms, we accurately measured average drug to antibody ratio (DAR) values and relative occupancy of drug-conjugated subunits. Overall, the middle-down MS approach enables the evaluation of multiple quality attributes including DAR, positional isomers, conjugation sites, occupancy, and microvariants, which potentially opens up a new avenue to characterize ADCs.Entities:
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Year: 2019 PMID: 31442030 PMCID: PMC7493829 DOI: 10.1021/acs.analchem.9b02194
Source DB: PubMed Journal: Anal Chem ISSN: 0003-2700 Impact factor: 6.986