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Extreme structural heterogeneity rewires glioblastoma chromosomes to sustain patient-specific transcriptional programs [Hi-C]

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NIAID Data Ecosystem2026-05-02 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE229962
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Glioblastoma multiforme encompasses a range of brain malignancies marked by phenotypic and transcriptional heterogeneity, which is thought to render these tumors aggressive, resistant to therapy, and inevitably recurrent. However, little is known about how the spatial organization of glioblastoma genomes underlies this heterogeneity and its effects. We compiled a cohort of 28 patient-derived glioblastoma stem-like lines (GSCs) known to reflect the properties of their tumor-of-origin; six of these came from primary-relapse tumor pairs in the same patient. We generated and analyzed kbp-resolution whole-genome chromosome conformation capture (Hi-C) data from all GSCs to systematically map >3,100 structural variants (SVs) and >6,300 neoloops. By combining Hi-C, histone modification, and gene expression data with 3D chromatin folding simulations, we explain how the pervasive, uneven, and idiosyncratic occurrence of neoloops sustains tumor-specific transcriptional programs via the formation of new enhancer-promoter contacts. We also exemplify how neoloops, albeit scarcely recurring, can help us infer potential patient-specific vulnerabilities. Thus, our data serve as a resource for dissecting glioblastoma biology and heterogeneity, as well as for informing therapeutic approaches. Hi-C and RNA-seq are applied to 28 low passage IDH-wild type GSC samples, including pairs of GSCs from primary and recurrent tumors from 3 patients. Cut&tag for H3K27me3 and CTCF are applied to 10 samples and 5 samples, respectively. NOTE FROM SUBMITTER: >>The raw data files have not been included due to privacy concerns<<
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2024-06-18
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