Impact of process parameters on IgG glycosylation in CHO systems: a comprehensive quantitative analysis

化学 定量分析(化学) 糖基化 过程(计算) 色谱法 生物化学 定量蛋白质组学 免疫球蛋白G 抗体 定量评估
作者
Javier Bravo-Venegas,Jose Rodriguez-Siza,Mauricio Vergara,Mauro Torres,Alan J. Dickson,Jorge R. Toledo,M.C. Molina,Marcela A. Hermoso,Julio Berríos,Claudia Altamirano
出处
期刊:mAbs [Landes Bioscience]
卷期号:18 (1): 2643039-2643039
标识
DOI:10.1080/19420862.2026.2643039
摘要

Controlling glycosylation, a critical quality attribute of biopharmaceuticals such as monoclonal antibodies, is essential, as it significantly influences biological activity and therapeutic efficacy. Although numerous studies have examined the impact of process parameters (PP, e.g. temperature, pH, dissolved oxygen) on glycosylation, the lack of standardized reporting makes cross-study comparisons challenging and prevents clear conclusions. Here, we systematically reviewed the literature and applied a normalized quantitative framework, the Glycan Indices approach, as a standardized quantitative criterion to evaluate the impact of process parameters on glycoform distribution in IgG-producing CHO cell systems objectively. This methodology enabled the integration and reinterpretation of large, heterogeneous datasets, validating some well-known patterns while providing novel perspectives about process parameters. Our analysis revealed that PP manipulations of pH, dissolved oxygen or CO2 partial pressure rarely resulted in meaningful shifts in glycosylation, with changes <5% observed for galactose, fucose, or N-acetylneuraminic acid content. In contrast, for several cases temperature and osmolality changes notably affected galactosylation (>10%) and fucosylation (1-10%), variations that may have significant biological consequences. To our knowledge, this is the first comprehensive quantitative assessment of process parameters effects on glycosylation, showing that such influences are consistently limited, independent of CHO cell line or culture mode. Based in our observations we strongly recommend reporting both glycan distribution and glycan indices when performing glycan analysis. Dual reporting facilitates inter-study comparisons and prevents subtle shifts in sugar moieties from being masked by glycan redistribution.
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