Pharma Technical Development, Genentech, South San Francisco, CA 94080, USA.
Pharma Technical Development, Roche Diagnostics GmbH, 82377 Penzberg, Germany.
Molecules. 2023 Apr 12;28(8):3392. doi: 10.3390/molecules28083392.
Large molecule protein therapeutics have steadily grown and now represent a significant portion of the overall pharmaceutical market. These complex therapies are commonly manufactured using cell culture technology. Sequence variants (SVs) are undesired minor variants that may arise from the cell culture biomanufacturing process that can potentially affect the safety and efficacy of a protein therapeutic. SVs have unintended amino acid substitutions and can come from genetic mutations or translation errors. These SVs can either be detected using genetic screening methods or by mass spectrometry (MS). Recent advances in Next-generation Sequencing (NGS) technology have made genetic testing cheaper, faster, and more convenient compared to time-consuming low-resolution tandem MS and Mascot Error Tolerant Search (ETS)-based workflows which often require ~6 to 8 weeks data turnaround time. However, NGS still cannot detect non-genetic derived SVs while MS analysis can do both. Here, we report a highly efficient Sequence Variant Analysis (SVA) workflow using high-resolution MS and tandem mass spectrometry combined with improved software to greatly reduce the time and resource cost associated with MS SVA workflows. Method development was performed to optimize the high-resolution tandem MS and software score cutoff for both SV identification and quantitation. We discovered that a feature of the Fusion Lumos caused significant relative under-quantitation of low-level peptides and turned it off. A comparison of common Orbitrap platforms showed that similar quantitation values were obtained on a spiked-in sample. With this new workflow, the amount of false positive SVs was decreased by up to 93%, and SVA turnaround time by LC-MS/MS was shortened to 2 weeks, comparable to NGS analysis speed and making LC-MS/MS the top choice for SVA workflow.
大分子蛋白治疗药物稳步增长，现已成为整体医药市场的重要组成部分。这些复杂的疗法通常使用细胞培养技术制造。序列变异（SV）是不期望的次要变异，可能来自细胞培养生物制造过程，从而可能影响蛋白治疗的安全性和有效性。SV 具有意外的氨基酸取代，可能来自遗传突变或翻译错误。这些 SV 可以使用遗传筛选方法或质谱（MS）检测到。与耗时的低分辨率串联 MS 和基于 Mascot 容错搜索（ETS）的工作流程相比，新一代测序（NGS）技术的最新进展使基因检测变得更便宜、更快、更方便，后者通常需要大约 6 到 8 周的数据分析周转时间。然而，NGS 仍然无法检测非遗传衍生的 SV，而 MS 分析可以同时做到这两点。在这里，我们报告了一种使用高分辨率 MS 和串联质谱结合改进软件的高效序列变异分析（SVA）工作流程，大大降低了与 MS SVA 工作流程相关的时间和资源成本。为了优化高分辨率串联 MS 和软件评分截止值，以进行 SV 鉴定和定量，我们进行了方法开发。我们发现 Fusion Lumos 的一个功能会导致低水平肽的相对定量不足，因此将其关闭。对常见的 Orbitrap 平台的比较表明，在添加的样品中获得了类似的定量值。使用这种新的工作流程，假阳性 SV 的数量减少了多达 93%，并且 LC-MS/MS 的 SVA 周转时间缩短到 2 周，与 NGS 分析速度相当，使 LC-MS/MS 成为 SVA 工作流程的首选。
