Abstract 184: SureSelect sequencing panels and algorithms to detect copy number variations (CNVs), DNA rearrangements, microsatellite Instability and tumor mutational burden (TMB) in FFPE specimens

Background: The current standard of genomic profiling of cancer tissues relies upon multiple separate technologies to aid in tumor characterization. Here we describe an NGS panel and analysis workflow for cancer samples that can detect single nucleotide polymorphisms (SNPs), insertions and deletions (INDEL), somatic copy number alterations (SCNAs), and translocations (TLs), Tumor Mutation Burden (TMB) and Microsatellite Instability (MSI) in a single assay. Methods: We have developed a SureSelect target enrichment sequencing panels for comprehensive profiling of single nucleotide variations (SNP/INDEL), gene copy number variations (CNV), and DNA translocations (TL) and relevant microsatellite regions in a single assay. The TMB panel gene list was curated based on genes found in cancer gene databases such as Clinical Interpretations of Variants in Cancer (CIViC), Cancer Genome Interpreter (CGIdb), Catalog of Somatic Mutations in Cancer Census (COSMIC), Precision Oncology Knowledge Base (OncoKB). An accompanying data analysis pipeline will provide highly sensitive and accurate detection of variants and allows for the determination TMB and MSI status. Probes have been selected for over 500 genes to detect SCNAs and translocation in several cancer subtypes. The probes are optimized with the SureSelect XTHS protocol, which enables sensitive and accurate detection of rare mutation events within a heterogeneous sample with molecular barcode-mediated error correction. The SCNAs probes target regions in the genome that help in decreasing the noise for SCNAs calling. The data analysis utilizes either a matched normal or standard control DNA to compute read depth log ratios. Aberrant regions of constant ploidy are first identified followed by the application of a variational streaming algorithm on log ratio and SNP allele frequencies to determine the major clones present in the tumor. Translocation detection was verified on lung cancer samples by analyzing split reads across the fusion breakpoints. Results: By diluting samples with known copy-number aberrations into normal DNA, a limit of detection of ⇐2.3 copies/cell was demonstrated, equivalent to the detection of 3 copies at 30% tumor fraction. A similar approach demonstrated an ability to detect EML4-ALK and SLC24A2-ROS1 translocations at 3% allele frequency. Performance of the assay was further evaluated using 100+ FFPE samples harboring rearrangements, gene amplifications, and SNP/Indels. Concordance to the reference methods (FISH, WES, WGS) was >90%. TMB and MSI algorithms were benchmarked using in silico analysis of TCGA data and performance of the assay was evaluated on FFPE samples with orthogonally-determined MSI/TMB status. Conclusions: This work represents an important advancement in the development of a single assay to detect copy number variation, DNA rearrangement and mutations, TMB and MSI status of a FFPE sample. Citation Format: Arjun Vadapalli, Akanksha Khare, Hanjun Shin, Ashutosh Ashutosh, Linus Forsmark, Anne Lucas, Scott Happe, Gilbert Amparo, Carlos Pabon, Jayati Ghosh, Tracy Liu, Jimmy Jin, Mike Ruvolo, Douglas Roberts. SureSelect sequencing panels and algorithms to detect copy number variations (CNVs), DNA rearrangements, microsatellite Instability and tumor mutational burden (TMB) in FFPE specimens [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 184.