Abstract 4355: Identification and functional characterization of glioma structural variants

Adult diffuse gliomas are a diverse class of brain tumors that ultimately result in fatal malignant progression. The highly variable disease progression intervals and poor treatment response observed in glioma have been explained, in part, by the extent of heterogeneity within and across gliomas. Somatic structural variants such as deletions, duplications, insertions, inversions, translocations, and extrachromosomal DNA contribute to glioma heterogeneity by generating genomic instability, a hallmark of cancer genomes. While comprehensive approaches such as whole genome sequencing have begun to catalog the glioma structural variant landscape, the molecular mechanisms by which they contribute to tumor progression remains poorly understood. Here, we identified genomic rearrangements in the whole genomes of 147 gliomas and glioma cell lines. Among the whole-genome sequencing samples were 62 glioblastomas (TCGA), 52 low-grade gliomas (TCGA), and our own set of 33 patient-derived glioma sphere-forming cells. On average, glioblastomas demonstrated a greater frequency of high-confidence structural variants (162 per tumor) than low-grade gliomas (130 per tumor, P=0.02) with two glioblastomas displaying evidence of chromothripsis. Across the World Heath Organization9s molecular classifications, the IDH-mutant 1p/19q co-deleted tumors demonstrated the lowest structural variant burden when compared with both IDH-wildtype and IDH-mutant non-co-deleted tumors. Structural variant frequencies were found to be similar between patient tumors and an independent set of patient-derived cell lines. Across all samples, a majority of the structural variant breakpoints were found in intronic (42%) and intergenic regions (55%) suggesting that rearrangements predominantly impact distal regulatory regions. To investigate the functional consequences of structural variants in these regions we integrated these samples with available RNA-sequencing and epigenetic data to characterize deregulated transcriptional circuits. Analyses examining the association between genomic rearrangements and chromatin states to determine potential mechanisms of oncogene activation in select tumor and cell line samples are now underway. Together, our study demonstrates the importance of integrating structural variant calls from whole genome sequencing with expression and epigenetic data to define functional genomic rearrangements. Citation Format: Kevin C. Johnson, Floris P. Barthel, Ming Tang, Samirkumar Amin, Qianghu Wang, Erik P. Sulman, Kunal Rai, Roel G.W Verhaak. Identification and functional characterization of glioma structural variants [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4355.