Abstract 5385: Supporting neoantigen discovery and monitoring in plasma through analytical validation of a deep Augmented Content Enhanced (ACE) exome
Authors: Alla Ravi K. , Li Robin , Boyle Sean Michael , Luo Shujun , McClory Rena , McCord Rob , West John , Chen Richard 
Published: August 2018

Abstract
Neoantigens are increasingly critical in immuno-oncology as a therapeutic target for neoantigen-based personalized cancer vaccines and as a potential biomarker for immunotherapy response. An important step in identifying neoantigens is comprehensive exome and transcriptome sequencing of a tumor biopsy sample and the matched normal to enable identification of putative neoantigens derived from mutations in any gene in the genome. However, as tumor biopsy samples cannot always be obtained, and because tumor heterogeneity can result in an incomplete set of neoantigens from a single biopsy, we developed our Accuracy and Content Enhanced (ACE) circulating tumor DNA (ctDNA) Exome to (1) identify neoantigens in cell free DNA (cfDNA) as a complement to tumor biopsy derived neoantigens and (2) track neoantigens in the cfDNA post immuno-therapy treatment. Our ACE ctDNA Exome covers &gt;20,000 genes as neoantigens can occur in any gene across the genome. This is in contrast to most current tumor cfDNA tests which are designed to assess a small number of variants or genes (often &lt;100), and as such will miss many putative neoantigens. Our ACE ctDNA Exome is performed at very high sequencing depth to accurately identify lower allele frequency variants that are candidate neoantigens.To demonstrate the utility of the ACE ctDNA Exome for both identification and monitoring of neoantigens directly from cfDNA, we show preliminary results from two studies. Firstly, to monitor colorectal cancer (CRC) tumor-derived variants in cfDNA, we sequenced 8 late stage paired patient tumor, normal and cfDNA samples. We identify an average of 380 somatic events ranging from 10% to 100% Allele Frequency (AF) in each tumor and, through site-specific interrogation, were able to corroborate ~60%-98% of these events in cfDNA. This high concordance demonstrates strong sensitivity for tumor derived mutation monitoring using our platform. Secondly, to understand our de novo variant Limit of Detection (LOD), we assessed the sensitivity of our ACE ctDNA Exome for detecting single nucleotide variants (SNVs) down to 1% AF. We chose 3 Seracare cfDNA standards as our “Gold Set”. These samples harbor 25 SNVs at various AFs (2%, 1%, 0% control). We analyzed these data in a tumor-normal fashion using the cell line GM24385 as matched normal, identifying 24/25 (96%) variants in the 1% and 2% standards. To perform a genome wide assessment of sensitivity, we obtained cfDNA from 2 healthy donors, mixed them to create somatic variants with AFs down to 0.625% with analytical sensitivity calculated against &gt;10,000 variants. Initial results show that our deep ACE ctDNA Exome is able to identify low allele frequency SNVs with high accuracy. These results show the potential of using ACE ctDNA Exome to identify and monitor neoantigens as a complement to the results from sequencing of the tumor biopsy alone.
Citation Format: Ravi K. Alla, Robin Li, Sean Michael Boyle, Shujun Luo, Rena McClory, Rob McCord, John West, Richard Chen. Supporting neoantigen discovery and monitoring in plasma through analytical validation of a deep Augmented Content Enhanced (ACE) exome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5385.