RESUMO
BACKGROUND: Gonadotropins are a class of heavily glycosylated protein hormones, thus extremely challenging to characterize by mass spectrometry. As biopharmaceuticals, gonadotropins are prescribed for the treatment of infertility and are derived from different sources: either from pooled urine of pregnant women or upon production in genetically modified Chinese Hamster Ovary cells. Human chorionic gonadotropin (hCG) is sold as a biopharmaceutical under the name Pregnyl® (urinary hCG, u-hCG) and Ovitrelle® (recombinant hCG, r-hCG), and recombinant human follicle stimulating hormone (r-hFSH) is marketed as Gonal-f®. Recently, we reported the exhaustive characterization of r-hCG at different structural levels. RESULTS: We implement size exclusion (SE) HPLC-MS to automatize the acquisition of native mass spectra of r-hCG dimer, but also u-hCG and r-hFSH, comparing the drug products up to intact heterodimer level. A hybrid HPLC-MS approach was employed for the characterization of r-hCG, u-hCG and r-hFSH drug products at different structural levels. Released glycans were analyzed by porous graphitized carbon (PGC)-HPLC-MS/MS, glycopeptides by reversed-phase (RP)-HPLC-MS/MS, subunits by RP-HPLC-MS and finally the intact native heterodimers by semi-automated online buffer exchange SE-HPLC-MS. The data were integrated using bioinformatic tools, to finally unravel the composition of 1481 co-existing dimeric glycoforms for r-hCG, 1167 glycoforms for u-hCG, and 1440 glycoforms for r-hFSH, and to compare critical quality attributes of the different drug products such as their degree of sialylation and O-glycosylation. SIGNIFICANCE AND NOVELTY: The strong alliance of bioanalytics and bioinformatics data integration at the different structural levels allowed the identification of more than thousand different glycoforms of r-hCG, u-hCG, and r-hFSH. The results showed that these biopharmaceuticals differ considerably in their glycosylation patterns and highlight the importance of in-depth characterization of biopharmaceuticals for quality control. © 2017 Elsevier Inc. All rights reserved.
