Combination of FAIMS, Protein A Depletion, and Native Digest Conditions Enables Deep Proteomic Profiling of Host Cell Proteins in Monoclonal Antibodies.

Abstract

Host cell proteins (HCPs) are residual impurities generated by the expression cell line during the production of biopharmaceuticals. Although the majority of these contaminants are removed during purification, HCPs can represent a considerable risk to the efficacy and safety of a therapeutic protein if not actively monitored. The enzyme-linked immunosorbent assay (ELISA) is commonly used throughout production to monitor HCP levels but has limited ability to identify novel HCPs or provide detailed quantification. Liquid chromatography tandem mass spectrometry (LC-MS2) methods are increasingly being used in conjunction with established ELISA techniques to provide rapid adaptability to increasingly complex samples as well as highly quantitative and informative results. However, MS-based methods are still hindered by the large dynamic range between high abundance biopharmaceutical proteins and low abundance HCPs. Here, we propose a multifactorial approach designed to optimize HCP detection in purified monoclonal antibody samples with LC-MS2. By first depleting the sample of antibody on a protein A column, then specifically digesting HCPs while precipitating remaining antibody, and finally reducing spectral complexity through compensation voltage (CV) switching using high-field asymmetric waveform ion mobility spectrometry (FAIMS), we identified multiple-fold more HCPs in the NIST monoclonal antibody standard than any single established mass spectrometry technique reported in the literature. Our analyses consistently identified over 600 high confidence mouse HCPs, a multifold increase over established methods, while maintaining high reproducibility.