Abstract 3619: High quality library preparation and accurate sequencing from highly damaged matched patient sample sets

Abstract

Abstract Preparation of high quality next-generation sequencing (NGS) libraries is critical for accurate identification of disease-causing mutations, but clinical scientists are often limited by the input DNA quality. In cancer genomics, a common source of DNA is formalin-fixed, paraffin-embedded (FFPE) tissue from patient biopsy, and in most cases high quality fresh or frozen tissue samples are not available. FFPE DNA poses many notable challenges for preparing NGS libraries, including low input amounts and extensive damage from fixation, storage, and extraction methods. Sequencing artifacts arising from damaged DNA bases raise the level of apparent mutations, making it more difficult to discern true, low frequency, disease-related variants from noise. We developed a second-generation, multi-enzyme DNA repair mix (V2) that is designed to repair the most prevalent damage types found in FFPE DNA including cytosine deamination, oxidative damage, abasic sites, nicks, and gaps. We tested the application of the V2 enzymatic repair mix in Illumina library preparation for DNA samples extracted from a series of matched patient sample sets, which included: FFPE normal and tumor tissue, and frozen normal and tumor tissue for each patient. Following this, we performed target enrichment, deep sequencing, and variant calling analyses. Our library preparation workflow integrates enzymatic repair upstream of Illumina library preparation without an additional bead purification step, maximizing library yield and complexity from precious FFPE samples. Rescue of damaged DNA molecules for library conversion and repair of damaged DNA bases improved on-target rate, coverage uniformity, and duplication rates. With a matched frozen sample for each FFPE specimen, we demonstrate that repair of damaged DNA bases improves sequencing accuracy by reducing the number of false-positive variant calls. We propose that enzymatic repair enables researchers to capture as much useable, accurate data from poor quality FFPE samples as possible. Citation Format: Margaret R. Heider. High quality library preparation and accurate sequencing from highly damaged matched patient sample sets [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3619.