Abstract 1381: NGS-based CNV detection sensitivity is dependent upon nucleic acid input quality

Copy number variations (CNV) impact more of the cancer genome than all other mutation types combined. Recent advances in next-generation sequencing (NGS) have enabled simultaneous detection of CNVs and other somatic mutations from FFPE-derived samples, but NGS-based detection of low level CNVs (ie 2-3x) remains challenging. Nucleic acid from FFPE is a common starting material for NGS-based cancer genotyping; however, this material is often of low complexity due to a variety of factors including limited mass amount, excessive fragmentation, or chemical crosslinking. Current practices often measure input mass, or the nanograms of DNA that are added to a reaction, yet it is input complexity, or the amount of nucleic acid available for NGS library generation, that truly dictates the amount of information that can be recovered from a given sample. Archer™ VariantPlex™ assays are targeted NGS panels that permit simultaneous detection of SNVs, in/dels, and CNVs using Anchored Multiplex PCR (AMP™). Molecular barcoded adapters are ligated to each input molecule prior to any amplification. This permits the unique identification of individual input molecules thus facilitating precise copy number measurements. In addition, AMP enables amplification of highly fragmented FFPE inputs as short fragments are captured between the ligated adapter and the enrichment probe. To determine the effect of input quality on sensitivity of CNV calling we characterized over 150 tumor sample input qualities and their resulting library metrics. In addition we modeled the effect of low tumor cellularity on CNV sensitivity by carrying out dilution experiments of CNV-positive samples into samples of normal copy number. Using Archer VariantPlex assays in conjunction with Archer Analysis, we have successfully detected CNVs as small as 2X in both FFPE and cell line DNA. We found that input nucleic acid quality, as measured by a qPCR-based assay called Archer PreSeq™ DNA QC, strongly impacted the sensitivity of CNV calling. Assessment of input complexity using the PreSeq DNA QC Assay is predictive of limit of detection for CNVs and identifies an input quantity that will result in high quality NGS libraries. Our dilution experiments confirmed the expected relationship between actual and measured copy number in our population-averaging assay. Nucleic acid damage typical of FFPE samples reduces CNV calling sensitivity; however, this loss of sensitivity can be partially mitigated by increasing the