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  • PATHWAY  (3)
  • BINDING  (1)
  • 1
    Keywords: CANCER ; PATHWAY ; GENES ; ACTIVATION ; MUTATIONS ; SUBGROUPS ; LANDSCAPE ; TETRAPLOID TUMOR-CELLS ; TBR1
    Abstract: Medulloblastoma is an aggressively growing tumour, arising in the cerebellum or medulla/brain stem. It is the most common malignant brain tumour in children, and shows tremendous biological and clinical heterogeneity. Despite recent treatment advances, approximately 40% of children experience tumour recurrence, and 30% will die from their disease. Those who survive often have a significantly reduced quality of life. Four tumour subgroups with distinct clinical, biological and genetic profiles are currently identified. WNT tumours, showing activated wingless pathway signalling, carry a favourable prognosis under current treatment regimens. SHH tumours show hedgehog pathway activation, and have an intermediate prognosis. Group 3 and 4 tumours are molecularly less well characterized, and also present the greatest clinical challenges. The full repertoire of genetic events driving this distinction, however, remains unclear. Here we describe an integrative deep-sequencing analysis of 125 tumour-normal pairs, conducted as part of the International Cancer Genome Consortium (ICGC) PedBrain Tumor Project. Tetraploidy was identified as a frequent early event in Group 3 and 4 tumours, and a positive correlation between patient age and mutation rate was observed. Several recurrent mutations were identified, both in known medulloblastoma-related genes (CTNNB1, PTCH1, MLL2, SMARCA4) and in genes not previously linked to this tumour (DDX3X, CTDNEP1, KDM6A, TBR1), often in subgroup-specific patterns. RNA sequencing confirmed these alterations, and revealed the expression of what are, to our knowledge, the first medulloblastoma fusion genes identified. Chromatin modifiers were frequently altered across all subgroups. These findings enhance our understanding of the genomic complexity and heterogeneity underlying medulloblastoma, and provide several potential targets for new therapeutics, especially for Group 3 and 4 patients.
    Type of Publication: Journal article published
    PubMed ID: 22832583
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  • 2
    Keywords: PATHWAY ; ACTIVATION ; BINDING ; leukemia ; CHILDREN ; C-MYC ; T-CELL LYMPHOMA ; GTPASES ; cancer genes ; NUCLEOTIDE-EXCHANGE
    Abstract: Burkitt lymphoma (BL) is the most frequent B-cell lymphoma in childhood. Genetically, it is characterized by the presence of an IG-MYC translocation which is supposed to be an initiating but not sufficient event in Burkitt lymphomagenesis. In a recent whole-genome sequencing study of four cases, we showed that the gene encoding the ras homolog family member A (RHOA) is recurrently mutated in pediatric BL. Here, we analyzed RHOA by Sanger sequencing in a cohort of 101 pediatric B-cell lymphoma patients treated according to Non-Hodgkin's Lymphoma Berlin-Frankfurt-Munster (NHL-BFM) study protocols. Among the 78 BLs in this series, an additional five had RHOA mutations resulting in a total incidence of 7/82 (8.5%) with c.14G〉A (p.R5Q) being present in three cases. Modeling the mutational effect suggests that most of them inactivate the RHOA protein. Thus, deregulation of RHOA by mutation is a recurrent event in Burkitt lymphomagenesis in children. (c) 2014 Wiley Periodicals, Inc.
    Type of Publication: Journal article published
    PubMed ID: 25044415
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  • 3
    Keywords: CANCER ; CELLS ; PATHWAY ; CLASSIFICATION ; GENES ; SIGNAL ; DATABASE ; INTERFACE ; INTERACTION NETWORK ; PACKAGE
    Abstract: Characterizing the activating and inhibiting effect of protein-protein interactions (PPI) is fundamental to gain insight into the complex signaling system of a human cell. A plethora of methods has been suggested to infer PPI from data on a large scale, but none of them is able to characterize the effect of this interaction. Here, we present a novel computational development that employs mitotic phenotypes of a genome-wide RNAi knockdown screen and enables identifying the activating and inhibiting effects of PPIs. Exemplarily, we applied our technique to a knockdown screen of HeLa cells cultivated at standard conditions. Using a machine learning approach, we obtained high accuracy (82% AUC of the receiver operating characteristics) by cross-validation using 6,870 known activating and inhibiting PPIs as gold standard. We predicted de novo unknown activating and inhibiting effects for 1,954 PPIs in HeLa cells covering the ten major signaling pathways of the Kyoto Encyclopedia of Genes and Genomes, and made these predictions publicly available in a database. We finally demonstrate that the predicted effects can be used to cluster knockdown genes of similar biological processes in coherent subgroups. The characterization of the activating or inhibiting effect of individual PPIs opens up new perspectives for the interpretation of large datasets of PPIs and thus considerably increases the value of PPIs as an integrated resource for studying the detailed function of signaling pathways of the cellular system of interest.
    Type of Publication: Journal article published
    PubMed ID: 25255318
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