AI Article Synopsis

  • Glycosylation significantly influences the pharmacological properties of biologics, leading to variability in their glycan structures and posing challenges for consistent therapeutic development.
  • The study uses omics technologies, specifically RNA-sequencing, to predict optimal cell lines for producing specific glycosylation profiles in monoclonal antibodies (mAbs), identifying Alg5 and UDP-Gal transporter levels as key predictive markers.
  • While transcriptomic data is useful in forecasting glycosylation trends, it fails to capture important factors like enzyme localization and cellular dynamics that are crucial for the actual outcomes of glycosylation.

Article Abstract

-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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11686447PMC
http://dx.doi.org/10.3389/fcell.2024.1504381DOI Listing

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