Abstract 398: Using off-target data from comprehensive genomic profiling to characterize the genomic architecture of copy number alterations in tumor sequencing data

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Abstract Background Copy number alterations are common driver mutations in cancer. Identifying genes which show altered copy number and knowing the breakpoints of copy number alterations gives insight into their functionality as well as the mechanisms responsible for the alterations. While copy number alterations have been well-studied in common tumor types, there are still many rare tumor types which have not been characterized. Targeted genomic profiling using capture methods results in sequencing a subset of genes to extremely high coverage (>500x) and sequencing off-target regions spanning the rest of the genome to low (0.5x – 1x) coverage. We used this data to identify the approximate breakpoints of alterations that extend beyond targeted regions and to identify novel, recurrent copy number alterations in clinical tumor samples. Methods We used standard methods to identify copy number alterations in the off-target regions. Briefly, we calculated coverage in 10 kb windows across the genome, excluding the targeted regions which are sequenced at high coverage, corrected for GC-bias, calculated the log ratio of coverage for the tumor compared to an unrelated normal sample, and then used a segmentation algorithm to segment the genome into copy number regions and identify regions with significantly different copy number than the surrounding regions. We sequenced cell line DNA with known copy number variants and used this data to assess the accuracy and precision of these methods. Copy number alterations were filtered against known common copy number variant regions, and we identified copy number alterations overlapping known genes to identify potentially functional alterations. Results We applied these methods to tumor samples that underwent comprehensive genomic profiling as part of clinical care. Our cohort consisted of a large and diverse set of “real world” unbiased clinical specimens and contained many rare and unusual tumors not included in larger sequencing efforts. Using this data, we characterized the landscape of copy number variants genome-wide in rare tumor types which have not previously been characterized and identified unique copy number alterations in these tumor types. Further, we characterized the breakpoints of copy number alterations across the cohort. Conclusions We will present novel copy number alterations in rare tumor types and the recurrent breakpoints for common alterations across multiple tumor types. These findings will provide insight into the mechanisms of cancer progression. Citation Format: Caitlin F. Connelly, Zachary R. Chalmers, Philip J. Stephens, Garrett M. Frampton. Using off-target data from comprehensive genomic profiling to characterize the genomic architecture of copy number alterations in tumor sequencing data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 398. doi:10.1158/1538-7445.AM2017-398