West Ben, Kotidis Pavlos, Istrate Alena, Perna Daniele, Finka Gary, Wood A Jamie, Ungar Daniel
Departments of Biology, University of York, York, United Kingdom.
Biopharm Process Research, GlaxoSmithKline Research and Development, Stevenage, United Kingdom.
Front Cell Dev Biol. 2024 Dec 17;12:1504381. doi: 10.3389/fcell.2024.1504381. eCollection 2024.
-glycosylation plays a crucial role in defining the pharmacological properties and efficacy of therapeutic proteins, commonly referred to as biologics. The inherent complexity and lack of a templated process in glycosylation leads to a wide variation in glycan structures, posing significant challenges in achieving consistent glycan profiles on biologics. This study leverages omics technologies to predict which cell lines are likely to yield optimal glycosylation profiles, based on the existing knowledge of the functional impact of specific glycan structures on the pharmacokinetics, immunogenicity, and stability of therapeutic antibodies. The study highlights that bulk RNA-sequencing data holds predictive power for glycosylation outcomes in of monoclonal antibodies (mAbs). For instance, Alg5 is identified to be predictive, before beginning a mAb production run, of mAbs bearing higher levels of Man5. This is inferred to increase glycosylation site occupancy on endogenous proteins, thereby intensifying competition for glycosylation enzymes in the Golgi and indirectly influencing mAb glycan processing. Additionally, the elevation of the UDP-Gal transporter in cell lines expressing mAbs with a single galactose residue is also observed intranscriptomic data prior to beginning a production run. These findings suggest that early-stage transcriptomics can aid in the streamlined development of cell lines by enabling pre-emptive adjustments to enhance glycosylation. The study also underscores that while transcriptomic data can predict certain glycosylation trends, more crucial factors affecting glycan profiles, such as enzyme localization within the Golgi apparatus and endogenous competition for glycosylation machinery, are not captured within the transcriptomic data. These findings suggest that while transcriptomics provides valuable insights, enzyme localization and intracellular dynamics are critical determinants of glycosylation outcomes. Our study starts to address the relevant mechanisms essential for improving cell line development strategies and achieving consistent glycosylation in biologics production.
糖基化在确定治疗性蛋白质(通常称为生物制品)的药理特性和功效方面起着至关重要的作用。糖基化过程固有的复杂性和缺乏模板化流程导致聚糖结构存在广泛差异,这给在生物制品上实现一致的聚糖谱带来了重大挑战。本研究利用组学技术,基于特定聚糖结构对治疗性抗体的药代动力学、免疫原性和稳定性的功能影响的现有知识,预测哪些细胞系可能产生最佳的糖基化谱。该研究强调,大量RNA测序数据对单克隆抗体(mAb)的糖基化结果具有预测能力。例如,在开始单克隆抗体制备之前,发现Alg5可预测具有较高水平Man5的单克隆抗体。据推测,这会增加内源性蛋白质上糖基化位点的占有率,从而加剧高尔基体中糖基化酶的竞争,并间接影响单克隆抗体的聚糖加工。此外,在开始生产之前的转录组学数据中也观察到,表达具有单个半乳糖残基的单克隆抗体的细胞系中UDP - Gal转运体的升高。这些发现表明,早期转录组学可以通过进行先发制人的调整以增强糖基化,来帮助简化细胞系的开发。该研究还强调,虽然转录组学数据可以预测某些糖基化趋势,但影响聚糖谱的更关键因素,如高尔基体中的酶定位和糖基化机制的内源性竞争,并未在转录组学数据中体现。这些发现表明,虽然转录组学提供了有价值的见解,但酶定位和细胞内动态是糖基化结果的关键决定因素。我们的研究开始探讨改善细胞系开发策略和在生物制品生产中实现一致糖基化所必需的相关机制。