Comparative Panel Sequencing of DNA Variants in cf-, ev- and tumorDNA for Pancreatic Ductal Adenocarcinoma Patients.

Abstract

Simple SummaryPancreatic ductal adenocarcinoma (PDAC) has still a dismal prognosis. To improve treatment, personalized medicine uses next-generation DNA sequencing to monitor disease and guide treatment decisions. Tumor samples for sequencing are usually obtained by invasive fine-needle biopsy. Recently, the focus has been increasingly shifting to blood-based liquid biopsies, including circulating free (cf)DNA or DNA isolated from extracellular vesicles (evDNA). To evaluate the detection performance of DNA alterations, we directly compared tumor-, cf- and evDNA from patients with advanced PDAC upon panel sequencing. Copy number variations (CNVs), single nucleotide variants (SNVs) and insertions and deletions (indels) were compared for their concordance with tumorDNA. Compared to cfDNA, evDNA contained significantly larger DNA fragments, which improved the concordance of SNVs and indels with tumorDNA. In line with previous observations, CNV detection was mostly uninformative for cf- and evDNA. However, the combination of both liquid biopsy analytes was clearly superior for SNV detection, pointing to potentially improved actionable variant prediction.Pancreatic ductal adenocarcinomas (PDACs) are tumors with poor prognosis and limited treatment options. Personalized medicine aims at characterizing actionable DNA variants by next-generation sequencing, thereby improving treatment strategies and outcomes. Fine-needle tumor biopsies are currently the gold standard to acquire samples for DNA profiling. However, liquid biopsies have considerable advantages as they are minimally invasive and frequently obtainable and thus may help to monitor tumor evolution over time. However, which liquid analyte works best for this purpose is currently unclear. Our study aims to directly compare tumor-, circulating free (cf-) and extracellular vesicle-derived (ev)DNA by panel sequencing of matching patient material. We evaluated copy number variations (CNVs), single nucleotide variants (SNVs) and insertions and deletions (indels). Our data show that evDNA contains significantly larger DNA fragments up to 5.5 kb, in line with previous observations. Stringent bioinformatic processing revealed a significant advantage of evDNA with respect to cfDNA concerning detection performance for SNVs and a numerical increase for indels. A combination of ev- and cfDNA was clearly superior for SNV detection, as compared to either single analyte, thus potentially improving actionable variant prediction upon further optimization. Finally, calling of CNVs from liquid biopsies still remained challenging and uninformative.