Abstract 5271: Optimization and detection of focal somatic copy number variants in whole genome, whole exome and panel sequencing for tumor/normal matched pairs and tumor only analysis

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Abstract Often in the clinical setting, tumor samples may be derived from historical tissue or from fresh frozen tissue and it may not be feasible to obtain normal tissue from the individual. Comparing unmatched tissues from different individuals possess a unique challenge of addressing common copy number variations not faced when comparing matched samples. In addition to the challenges of comparing unmatched samples, DNA extracted from samples preserved as formalin-fixed, paraffin-embedded (FFPE) tissue is often highly degraded and when compared to more intact DNA extracted from different source (e.g. blood) can increase the inherent noise in the system. Here we analytically characterize the accuracy and performance of algorithmic approaches for separating germline inherited copy number variation from somatic copy number changes, focusing on both filtering approaches and use of pooled reference samples sequenced under similar conditions. Example approaches include filtering known common copy number variation within 1000 Genomes Phase 3 and Database of Genomic Variants (DGV) Gold Standard. Additionally, we utilized a tumor/reference pool based analysis where a reference pool was constructed by equimolar pooling of multiple individuals. Determination of fold changes between tumor and reference was calculated by determining physical coverage of read pair fragments in 100 bases increments. Next, to address differences in sequencing performance between tumor and reference, the read depth data for each sample is collapsed/averaged into a lower resolution according to user-selected parameters (e.g. distance between points and read depth). Normalized log2 fold-changes between tumor and reference samples are then calculated and an adjustable smoothing window is applied. In addition, we utilize tumor allele frequencies of known heterozygous germline SNPs identified within the normal to both evaluate potential false positives and correct biases. Lastly, a segmentation algorithm is applied to summarize the individual log2 fold-changes into intervals with a constant copy number state. We will present the advantages and limitations of these approaches both when a germline normal is available and when tumor only analysis is necessary. Citation Format: Jessica Aldrich, Jonathan J. Keats, Austin Christofferson, Winnie S. Liang, John D. Carpten, Lisa Baumbach-Reardon, David W. Craig. Optimization and detection of focal somatic copy number variants in whole genome, whole exome and panel sequencing for tumor/normal matched pairs and tumor only analysis. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 5271.