PO.MCB08.03 · 分子与细胞生物学
针对FFPE样本优化的WGS工作流程：实现用于MRD监测的高置信度变异检测
An optimized WGS workflow for FFPE samples: Enabling high-confidence variant detection for MRD surveillance
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
本研究旨在通过评估不同的提取和文库制备方法如何影响覆盖度均一性以及对复杂、可指导用药变异的可靠检测，为基于FFPE的全基因组测序（WGS）确定一套稳健且具协同作用的工作流程。尽管福尔马林固定石蜡包埋（FFPE）样本占肿瘤标本的绝大多数，但其存在显著的DNA质量问题，挑战变异检出的准确性，并限制其在精准肿瘤学中进行全基因组测序（WGS）的潜力。因此，优化DNA提取和文库制备对于最大限度提高FFPE样本的WGS数据质量至关重要，尤其是对于组织指导下的微小残留病灶（MRD）监测等敏感应用。在本研究中，我们评估了不同工作流程组合对WGS数据质量的影响。我们比较了使用两种提取方法和两种文库制备试剂盒制备的四份GIAB FFPE对照样本（HG002/3/4/5）的文库。这项工作在既往研究结果的基础上进行了扩展，纳入了对复杂变异、覆盖度均一性以及临床相关变异检出的生物信息学分析。性能通过以下方面进行评估：1）大片段插入缺失（INDELs >16 bp）的精确度和准确度，2）全基因组覆盖度均一性，以及3）临床可指导用药的Tier 1A基因变异中的SNP/INDEL变异检出。我们对大片段INDELs（>16 bp）的分析证实了在小变异数据中观察到的趋势。Covaris提取与文库制备相结合的工作流程与其他组合相比，展现出显著更高的精确度和准确度。全基因组覆盖度分布分析表明，该工作流程产生了更优的覆盖度均一性，具有更低的变异系数（CV）和更高的基因组覆盖百分比。在临床可指导用药的Tier 1A变异检出方面，Covaris工作流程再次实现了最高的F1值、精确度和召回率。这些分析表明，一套针对提取和文库制备双重优化的工作流程为基于FFPE的WGS提供了稳健的解决方案。该方法确保了更高的数据质量、更均一的基因组覆盖度，以及对复杂和临床可指导用药变异更可靠的检测。这种高保真的变异检出直接解决了基于FFPE的精准肿瘤学中的一个核心挑战，为包括肿瘤图谱分析和MRD监测在内的应用提供了必需的可靠变异检测。
查看英文原文 English abstract
This study aimed to define a robust and synergistic workflow for FFPE-based whole genome sequencing (WGS) by evaluating how different extraction and library preparation methods impact coverage uniformity and the reliable detection of complex, actionable variants.Despite representing the vast majority of tumor specimens, formalin-fixed paraffin-embedded (FFPE) samples present significant DNA quality issues that challenge variant calling accuracy and limit their potential for whole genome sequencing (WGS) in precision oncology. Optimizing DNA extraction and library preparation is therefore essential to maximize WGS data quality from FFPE samples, particularly for sensitive applications like tissue-informed Minimal Residual Disease (MRD) monitoring. In this study, we evaluated the impact of different workflow combinations on WGS data quality. We compared libraries from four GIAB FFPE control samples (HG002/3/4/5) prepared using two extraction methods and two library preparation kits. This work expands on previous findings by including bioinformatic analysis of complex variants, coverage uniformity, and clinically relevant variant calling. Performance was assessed via: 1) precision and accuracy of large insertion-deletions (INDELs >16 bp), 2) genome-wide coverage uniformity, and 3) SNP/INDEL variant calling in clinically actionable Tier 1A gene variants. Our analysis of large INDELs (>16 bp) confirmed trends observed in small variant data. The combined Covaris extraction and library prep workflow demonstrated significantly higher precision and accuracy compared to other combinations. Analysis of genome-wide coverage distribution showed that the workflow produced superior coverage uniformity, with a lower coefficient of variation (CV) and a higher percentage of the genome covered. Regarding the calling of clinically actionable Tier 1A variants, the Covaris workflow again achieved the highest F1, precision, and recall. These analyses demonstrate that a workflow optimized for both extraction and library preparation provides a robust solution for FFPE-based WGS. This approach ensures higher data quality, more uniform genome coverage, and more reliable detection of complex and clinically actionable variants. This high-fidelity variant calling directly addresses a central challenge in FFPE-based precision oncology, providing the confident variant detection essential for applications including tumor profiling and MRD surveillance.
利益披露 Disclosure
B. Pfeiffer, None..
G. l Lipof, None..
A. Villareal, None..
K. Amirault, None..
S. Vasantgadkar, None..
M. Ambavaram, None..
V. Process, None..
S. Khanal, None..
M. Werner, None..
G. Endress, None..
U. Thomann, None..
E. Daviso, None.