Abstract 3520: Detection of low-frequency variants in highly degraded DNA and RNA samples

Abstract

Abstract Diagnostic tools based on next generation sequencing are fundamentally transforming clinical oncology. However, there is a lack of adequate library preparation strategies for highly degraded, clinically relevant samples, such as cell-free DNA (cfDNA) and formalin-fixed paraffin-embedded (FFPE) DNA. Due to the extreme heterogeneity of these sample types, targeted sequencing is often used to achieve deep coverage of genomic loci and enable detection of low-frequency variants. Commercially available protocols for library preparation require stringent size-selection to remove adapter-dimers, which reduces library complexity and variant detection power. Achieving high specificity can be challenging because low-frequency artifacts arise from a variety of sources, including DNA extraction, library construction, PCR, hybrid selection, and sequencing. These artifacts can be identified by “duplex sequencing”, where strand-specific unique molecular identifiers (UMIs) are used to confirm the presence of an alteration on both strands of an input molecule. However, duplex sequencing typically delivers low conversion rates with degraded samples due to poor ligation efficiency and template loss during size-selection. Here, we present the IDT library preparation kit optimized for low-input and degraded samples. Our novel library construction chemistry relies on an engineered DNA ligase and proprietary duplexed sequencing adapters that prevent chimeras, suppress dimer-formation (negating the need for size-selection), and enhance variant calling sensitivity. We adapted the workflow for both DNA and RNA applications and demonstrated efficacy using diverse sample types. To assess sensitivity, we created libraries with varied inputs using mixtures of Genome in a Bottle gDNA (NA12878 and NA24385) and performed hybrid capture using a 52 kb custom panel targeting: single nucleotide variants (SNVs), copy number variants (CNVs), and gene fusions. When compared to commercially available methods, our approach yielded a 1.5- to 4-fold increase in library complexity with improved sensitivity to 0.25% variants using 1-25 ng of cfDNA, and 0.5% using 25-250 ng FFPE DNA. We also obtained 100% specificity using duplexed UMI correction, which removed all false-positive calls. RNA libraries were constructed from FFPE NGS reference standards to evaluate the detection of ALK, RET, ROS, NTRK1, and NTRK3 fusions and sequenced to an average target depth of 10,000X. Our method provides superior sensitivity and specificity for detection of low-frequency variants, even with highly degraded DNA. Citation Format: Ariel Royall, Ushati Das Chakravarty, Katharine Dilger, Manqing Hong, Kevin Lai, Kristina Giorda, Keith Bryan, Yu Wang, Lynette Lewis, Scott Rose, Yu Zheng. Detection of low-frequency variants in highly degraded DNA and RNA samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3520.