Abstract
Host cell protein (HCP) impurities are generated by the host organism during the production of therapeutic recombinant proteins, and are difficult to remove completely. Though commonly present in small quantities, if levels are not controlled, HCPs can potentially reduce drug efficacy and cause adverse patient reactions. A high resolution approach for thorough HCP characterization of therapeutic monoclonal antibodies is presented herein. In this method, antibody samples are first depleted via affinity enrichment (e.g., Protein A, Protein L) using milligram quantities of material. The HCP-containing flow-through is then enzymatically digested, analyzed using nano-UPLC-MS/MS, and proteins are identified through database searching. Nearly 700 HCPs were identified from samples with very low total HCP levels (< 1 ppm to ∼ 10 ppm) using this method. Quantitation of individual HCPs was performed using normalized spectral counting as the number of peptide spectrum matches (PSMs) per protein is proportional to protein abundance. Multivariate analysis tools were utilized to assess similarities between HCP profiles by: 1) quantifying overlaps between HCP identities; and 2) comparing correlations between individual protein abundances as calculated by spectral counts. Clustering analysis using these measures of dissimilarity between HCP profiles enabled high resolution differentiation of commercial grade monoclonal antibody samples generated from different cell lines, cell culture, and purification processes.