PO.CL01.08 · 临床研究

一种用于超灵敏分子残留病灶检测(MRD)的新型双链全基因组测序(WGS)方法

A novel dual-strand whole-genome sequencing (WGS) method for ultra-sensitive molecular residual disease detection (MRD)

编号 2595 展板 14 时间 4/20 09:00–12:00 区域 Section 46 主讲 Jeff Tsai
分会场 Liquid Biopsies: Circulating Nucleic Acids 2
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作者与单位 Authors & Affiliations

Andrew Slatter1, Jessica Moore1, Esther Musgrave-Brown1, Dhamayanthi Pugazhendhi1, Trevor Ho1, Alex Calderwood1, Dale Weekes1, Seong Won Cha2, Christopher Edlund2, Sven Bilke2, Huihong You2, Chris Truong2, Jeff Tsai2, Khai Luong2, Li Liu2, Yunjiao Zhu2, Jeff Fisher2, Traci Pawlowski2, James Han2, Fiona Kaper2, Cande Rogert2

1Illumina, Cambridge, United Kingdom,2Illumina, San Diego, CA

摘要 Abstract

中文摘要
对循环游离DNA(cfDNA)进行全基因组测序(WGS),可利用全基因组范围内的突变实现超灵敏的循环肿瘤DNA(ctDNA)检测。然而,检测灵敏度仍受错误的限制。在此,我们描述了一种新型高Q值WGS文库制备方法的性能,该方法能够实现>Q60的cfDNA测序,并展示了其在分子残留病灶(MRD)检测中的应用。该方法通过对双链cfDNA片段的正链和负链同时进行测序来提高准确性,且无需使用唯一分子标识符(UMIs)。简言之,将寡核苷酸接头连接到cfDNA样本上,随后进行处理以生成同时包含正链和负链的文库结构。样本附加条形码后混合,在标准的NovaSeq X TM仪器上进行测序。源自DNA损伤、文库制备或测序的错误通过信息学方法被检测并屏蔽,从而生成双链共识序列(duplex consensus reads)。采用一种新型q值预测算法来预测所报告碱基为错误的概率,以及特定替换类型的错误概率。使用HG002细胞系DNA测定经验q值。为评估肿瘤指导的MRD应用中的性能,对从健康供者提取的cfDNA样本进行测序,并针对使用Illumina Oncology WGS制备方法从组织WGS中获得的患者特异性体细胞变异进行分析。使用SeraCare MRD参考物质在0至50 ppm(百万分率)稀释的7个目标VAF水平上各设5个重复来评估检测限(LoD),分析采用DRAGEN TM MRD流程。由10 ng cfDNA制备的文库可提供约50倍去重后的双链共识覆盖度,其中>80%的通过过滤的簇提供高质量的双链共识序列。所得碱基识别的质量经验测定为>Q60准确度,某些特定替换类型的错误率测定为>Q70。健康血浆用于建立在不同分析特异性目标下判定ctDNA存在的统计学评分。这些数值随后用于确定LoD研究中的检出情况。综合而言,结果表明该方法可实现2.5 ppm的LoD95,分析特异性为99.8%。本文所述方法展示了在MRD检测中实现高灵敏度和高特异性ctDNA检测的潜力。
查看英文原文 English abstract
Whole genome sequencing (WGS) of circulating cell-free DNA (cfDNA) enables ultra-sensitive circulating tumor DNA (ctDNA) detection by leveraging genome-wide mutations. However, the detection sensitivity remains limited by errors. Here we describe the performance of a new, high-Q WGS library prep method, which enables >Q60 cfDNA sequencing, and demonstrate its application in molecular residual disease (MRD) testing. The method enables increased accuracy by sequencing both top and bottom strands of double stranded cfDNA fragments without requiring unique molecular identifiers (UMIs). Briefly, oligonucleotide adaptors are attached to cfDNA samples and are subsequently processed to generate a library structure that contains both top and bottom strands. Samples are appended with barcodes and pooled for sequencing on a standard NovaSeq X TM instrument. Errors originating from DNA damage, library preparation or sequencing are informatically detected and masked, creating duplex consensus reads. A novel q-score prediction algorithm is employed to predict the probability a reported base is an error, as well as substitution-specific error probabilities. Empirical q-score was measured using HG002 cell line DNA. To measure performance in tumor informed MRD application, cfDNA samples extracted from healthy donors were sequenced and analyzed against patient-specific somatic variants derived from tissue WGS using the Illumina Oncology WGS prep. Limit of detection (LoD) was assessed using 5 replicates at each of the 7 target VAF levels from 0-50 parts-per-million (ppm) dilutions of the SeraCare MRD reference material, with analysis by the DRAGEN TM MRD pipeline.Libraries prepared from 10 ng cfDNA delivered ~50x deduplicated duplex consensus coverage with >80% of passed-filter clusters delivering high quality duplex consensus reads. The quality of the resulting base calls was empirically measured at >Q60 accuracy, and certain substitution-specific error rates were measured at >Q70. Healthy plasma was used to establish statistical scores for determining ctDNA presence at different analytical specificity goals. These values were subsequently used to determine the detection in the LoD study. In aggregate, the results showed the method can achieve a LoD95 of 2.5 ppm with analytical specificity of 99.8%. The method presented herein demonstrates the potential of highly sensitive and specific ctDNA detection for MRD testing.
利益披露 Disclosure
A. Slatter, Illumina Employment. J. Moore, Illumina Employment. E. Musgrave-Brown, Illumina Employment. D. Pugazhendhi, Illumina Employment. T. Ho, Illumina Employment. A. Calderwood, Illumina Employment. D. Weekes, Illumina Employment. S. Cha, Illumina Employment. C. Edlund, Illumina Employment. S. Bilke, Illumina Employment. H. You, Illumina Employment. C. Truong, Illumina Employment. J. Tsai, Illumina Employment. K. Luong, Illumina Employment. L. Liu, Illumina Employment. Y. Zhu, Illumina Employment. J. Fisher, Illumina Employment. T. Pawlowski, Illumina Employment. J. Han, Illumina Employment. F. Kaper, Illumina Employment. C. Rogert, Illumina Employment.

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