A Highly Efficient Workflow for Detecting and Identifying Sequence Variants in Therapeutic Proteins with a High...

Area of Science:

• Biopharmaceutical Manufacturing
• Analytical Chemistry
• Proteomics

Background:

• Large molecule protein therapeutics are crucial in modern medicine, manufactured via cell culture.
• Sequence variants (SVs) are critical impurities arising during biomanufacturing, potentially impacting therapeutic safety and efficacy.
• Current detection methods include genetic screening (e.g., Next-Generation Sequencing - NGS) and mass spectrometry (MS), each with limitations.

Purpose of the Study:

• To develop a highly efficient and rapid Sequence Variant Analysis (SVA) workflow using high-resolution mass spectrometry (MS).
• To optimize MS/MS parameters and software for accurate SV identification and quantitation, reducing time and cost.
• To establish LC-MS/MS as a competitive alternative to NGS for SV detection.

Main Methods:

• Development and optimization of a high-resolution tandem MS and LC-MS/MS SVA workflow.
• Utilized improved software for SV identification and quantitation, including optimization of score cutoffs.
• Investigated and mitigated a specific instrument feature (Fusion Lumos) causing peptide under-quantitation.

Main Results:

• Reduced false positive SVs by up to 93% compared to previous MS workflows.
• Shortened the SVA turnaround time using LC-MS/MS to two weeks, comparable to NGS.
• Demonstrated comparable quantitation values across different Orbitrap platforms.

Conclusions:

• The optimized high-resolution MS/MS workflow provides a rapid, accurate, and cost-effective method for Sequence Variant Analysis.
• This enhanced LC-MS/MS workflow rivals NGS in speed and offers the advantage of detecting non-genetic SVs.
• The developed workflow positions LC-MS/MS as a preferred method for biopharmaceutical sequence variant analysis.