Label-free Assessment of Complement-dependent Cytotoxicity of Therapeutic Antibodies Via a Whole-cell MALDI Mass Spectrometry Bioassay

Overview

Journal Sci Rep

Specialty Science

Date 2024 Sep 13

PMID 39271690

Authors

Stefan Schmidt

Alexander Geisel

Thomas Enzlein

Bjorn C Frohlich

Louise Pritchett

Melanie Verneret

Christian Graf

Carsten Hopf

Affiliations

Soon will be listed here.

Abstract

Potency assessment of monoclonal antibodies or corresponding biosimilars in cell-based assays is an essential prerequisite in biopharmaceutical research and development. However, cellular bioassays are still subject to limitations in sample throughput, speed, and often need costly reagents or labels as they are based on an indirect readout by luminescence or fluorescence. In contrast, whole-cell Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-TOF) Mass Spectrometry (MS) has emerged as a direct, fast and label-free technology for functional drug screening being able to unravel the molecular complexity of cellular response to pharmaceutical reagents. However, this approach has not yet been used for cellular testing of biologicals. In this study, we have conceived, developed and benchmarked a label-free MALDI-MS based cell bioassay workflow for the functional assessment of complement-dependent cytotoxicity (CDC) of Rituximab antibody. By computational evaluation of response profiles followed by subsequent m/z feature annotation via fragmentation analysis and trapped ion mobility MS, we identified adenosine triphosphate and glutathione as readily MS-assessable metabolite markers for CDC and demonstrate that robust concentration-response characteristics can be obtained by MALDI-TOF MS. Statistical assay performance indicators suggest that whole-cell MALDI-TOF MS could complement the toolbox for functional cellular testing of biopharmaceuticals.

Citing Articles

M2ara: unraveling metabolomic drug responses in whole-cell MALDI mass spectrometry bioassays.

Enzlein T, Geisel A, Hopf C, Schmidt S Bioinformatics. 2024; 40(11).

PMID: 39558590 PMC: 11601156. DOI: 10.1093/bioinformatics/btae694.

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