Abstract 994: Diagnosing leukemia structural variations via a novel genome mapping approach

Abstract

Abstract Identification of structural variants (SVs) is critical to the prognosis of AML. SVs are not readily identified by next generation sequencing methods and are currently diagnosed by cytogenetics, an intrinsically low resolution tool. We have adapted a new method for determining large SVs as a clinical tool for evaluating AML and other cancer genomes. The Bionano Irys images in microfluidic nanochannels large (>150 Kb) segments of genomic DNA that have been bar coded by site specific nicking and local incorporation of fluorescent label. The complement of individual molecules can be assembled through matching bar codes to create a de novo map of the genome from which, by matching to a reference genome, identifies and catalogs structural variants at resolution of ca. 1 Kb. With this technology, we characterized structural variants signatures in breast cancer, renal clear cell carcinoma, and CML cell lines. Structural variants were then validated via PCR/Sanger sequencing, fluorescent in situ hybridization and whole genome sequencing. We identified a thorough compendium of consistent false positive rearrangements identified by this technology, most of which reflect errors in the reference human genome assembly. We then applied this methodology to ten AML patient samples, seven from archived blood samples and three directly obtained from newly diagnosed patients. Karyotyping on one archived sample identified a t(6:9) translocation in the majority of cells. We identified that rearrangement at a much higher resolution than cytogenetics, which allowed us to map the breakpoint via PCR/Sanger sequencing to nucleotide resolution and confirm a fusion of NUP214 to DEK, a known oncogene. We also discovered the reciprocal t(9:6) translocation, which had not been identified by cytogenetics. In the six other cases from archived samples, we have confirmed the translocation identified by cytogenetic karyotyping and in several cases found additional rearrangements. Moreover, in the first pediatric case, which we completed within five days of obtaining the sample, we have identified four distinct translocations, all of which have been associated previously with AML. Overall, this is technology has the ability to quickly and accurately identify SVs in cancer cell lines and AML patient samples with higher resolution than cytogenetics, demonstrating its clinical usefulness in the diagnosis and subsequent treatment of leukemia. Citation Format: Christopher Pool, Jie Xu, Darrin Bann, David Goldenberg, Arati Sharma, David Claxton, Feng Yue, James Broach. Diagnosing leukemia structural variations via a novel genome mapping approach [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 994. doi:10.1158/1538-7445.AM2017-994