Glycopeptide-based classification of erythropoietin biopharmaceuticals by microseparation techniques coupled to mass spectrometry and multivariate analysis.

In the present study, a bottom-up approach was followed to characterize three recombinant human erythropoietin (rhEPO) biopharmaceuticals: two commercially available drugs (EPO cim and EPO crs) and one currently under clinical evaluation for neurodegenerative diseases (NeuroEPO plus). After tryptic digestion, the resulting glycopeptides were analyzed using two complementary microseparation techniques: capillary electrophoresis and capillary liquid chromatography, both coupled to mass spectrometry (CE-MS and capLC-MS, respectively). These techniques enabled the detection of glycopeptide glycoforms displaying different degrees of sialylation and branching. CE-MS provided faster analyses and higher peak efficiency, whereas capLC-MS offered greater sensitivity, allowing the identification of a larger number of glycoforms. Given the complexity of the generated datasets, unsupervised and supervised multivariate data analysis was applied to explore glycosylation differences among the biopharmaceuticals and facilitate sample classification. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) achieved clear differentiation of the three rhEPOs and revealed batch-to-batch variability with both microseparation techniques. In addition, the glycopeptide glycoforms that most strongly contributed to the product differentiation were identified. Specifically, EPO cim and EPO crs displayed higher relative abundances of tri- and tetra-sialylated structures, whereas NeuroEPO plus was characterized by a greater proportion of low-sialylated glycoforms. Moreover, EPO cim and EPO crs mainly differed in the relative abundance of N-glycolylneuraminic acid-containing glycoforms at O126 and the relative abundance of glycoforms containing additional lactosamine units at N83 despite being considered very similar rhEPOs. These results demonstrated that the established methodologies show great potential for applications in quality control, biosimilar assessment, and the characterization of glycoprotein-based therapeutics.