We have applied a combination of whole genome sequencing and optical genomic mapping to a number of adult and pediatric leukemia samples, which revealed in each of these samples a large number of structural variants not recognizable by current standard genomic analyses. We developed computational methods to determine which of those variants likely arose as somatic mutations. The method identified 97% of the translocations previously reported by karyotype analysis of these samples and revealed an additional fivefold more such somatic rearrangements. The method identified on average tens of previously unrecognizable inversions and duplications and hundreds of previously unrecognizable insertions and deletions. These structural variants affected a number of leukemia associated genes as well as cancer driver genes not previously associated with leukemia and genes not previously associated with cancer. A number of variants only affected intergenic regions but caused cis-acting alterations in expression of neighboring genes. Analysis of TCGA data indicates that several of the recurrently mutated genes significantly affect survival of AML patients. Our results suggest that current genomic analysis methods fail to identify a majority of structural variants in leukemia samples and this lacunae may hamper diagnostic and prognostic efforts.

Note: This abstract was not presented at the meeting.

Citation Format: James R. Broach, Jie Xu, Emily Schleicher, Christopher Pool, Max Hennessy, Kathryn Sheldon, Charyguly Annageldiyev, Arati Sharma, Yuanyuan Chang, Alex Hastie, Barbara Miller, David Goldenberg, David Claxton, George-Lucian Moldovan, Feng Yue. An integrated framework for genome analysis reveals numerous previously unrecognizable structural variants in leukemia patients’ samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1708.