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HGG-41. STRUCTURAL VARIANT DRIVERS IN PEDIATRIC HIGH-GRADE GLIOMA

Neuro-Oncology(2020)

Dana Farber Canc Inst | Broad Inst | McGill Univ | Hopp Childrens Canc Ctr Heidelberg KiTZ | Dana Farber Boston Childrens Canc & Blood Disorde | NYU | Inst Canc Res | Inst Gustave Roussy | Tromboprotea

Cited 2|Views43
Abstract
Abstract BACKGROUND Driver single nucleotide variants (SNV) and somatic copy number aberrations (SCNA) of pediatric high-grade glioma (pHGGs), including Diffuse Midline Gliomas (DMGs) are characterized. However, structural variants (SVs) in pHGGs and the mechanisms through which they contribute to glioma formation have not been systematically analyzed genome-wide. METHODS Using SvABA for SVs as well as the latest pipelines for SCNAs and SNVs we analyzed whole-genome sequencing from 174 patients. This includes 60 previously unpublished samples, 43 of which are DMGs. Signature analysis allowed us to define pHGG groups with shared SV characteristics. Significantly recurring SV breakpoints and juxtapositions were identified with algorithms we recently developed and the findings were correlated with RNAseq and H3K27ac ChIPseq. RESULTS The SV characteristics in pHGG showed three groups defined by either complex, intermediate or simple signature activities. These associated with distinct combinations of known driver oncogenes. Our statistical analysis revealed recurring SVs in the topologically associating domains of MYCN, MYC, EGFR, PDGFRA & MET. These correlated with increased mRNA expression and amplification of H3K27ac peaks. Complex recurring amplifications showed characteristics of extrachromosomal amplicons and were enriched in coding SVs splitting protein regulatory from effector domains. Integrative analysis of all SCNAs, SNVs & SVs revealed patterns of characteristic combinations between potential drivers and signatures. This included two distinct groups of H3K27M DMGs with either complex or simple signatures and different combinations of associated variants. CONCLUSION Recurrent SVs associate with signatures shaped by an underlying process, which can lead to distinct mechanisms to activate the same oncogene.
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要点】:论文系统分析了儿童高级别胶质瘤中的结构变异(SVs),揭示了SVs在肿瘤形成中的机制,并确定了与已知驱动癌基因相关的特征性SV组合。

方法】:使用SvABA分析SVs,以及最新的管道分析单核苷酸变异(SNVs)和体细胞拷贝数异常(SCNAs),对174名患者的全基因组测序数据进行分析。

实验】:通过分析包括60个未发表样本(其中43个为弥漫中线胶质瘤DMGs)的全基因组测序数据,使用算法识别了显著重复的SV断点,并将发现与RNAseq和H3K27ac ChIPseq数据相关联,结果显示pHGG中的SV特征分为三组,分别与复杂的、中间的或简单的特征活动相关,并与已知的驱动癌基因的不同组合相关。