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10.1038/ncomms11938

http://scihub22266oqcxt.onion/10.1038/ncomms11938
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suck abstract from ncbi


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      Nat+Commun 2016 ; 7 (ä): 11938
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  • Chromatin accessibility maps of chronic lymphocytic leukaemia identify subtype-specific epigenome signatures and transcription regulatory networks #MMPMID27346425
  • Rendeiro AF ; Schmidl C ; Strefford JC ; Walewska R ; Davis Z ; Farlik M ; Oscier D ; Bock C
  • Nat Commun 2016[Jun]; 7 (ä): 11938 PMID27346425 show ga
  • Chronic lymphocytic leukaemia (CLL) is characterized by substantial clinical heterogeneity, despite relatively few genetic alterations. To provide a basis for studying epigenome deregulation in CLL, here we present genome-wide chromatin accessibility maps for 88 CLL samples from 55 patients measured by the ATAC-seq assay. We also performed ChIPmentation and RNA-seq profiling for ten representative samples. Based on the resulting data set, we devised and applied a bioinformatic method that links chromatin profiles to clinical annotations. Our analysis identified sample-specific variation on top of a shared core of CLL regulatory regions. IGHV mutation status-which distinguishes the two major subtypes of CLL-was accurately predicted by the chromatin profiles and gene regulatory networks inferred for IGHV-mutated versus IGHV-unmutated samples identified characteristic differences between these two disease subtypes. In summary, we discovered widespread heterogeneity in the chromatin landscape of CLL, established a community resource for studying epigenome deregulation in leukaemia and demonstrated the feasibility of large-scale chromatin accessibility mapping in cancer cohorts and clinical research.
  • |*Chromatin [MESH]
  • |*Epigenomics [MESH]
  • |*Gene Regulatory Networks [MESH]
  • |*Transcription, Genetic [MESH]
  • |Gene Expression Regulation, Neoplastic/*physiology [MESH]
  • |Humans [MESH]
  • |Leukemia, Lymphocytic, Chronic, B-Cell/*genetics [MESH]
  • |Machine Learning [MESH]


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