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Sökning: WFRF:(Herrmann Alexander) > (2020)

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1.
  • Carlevaro-Fita, Joana, et al. (författare)
  • Cancer LncRNA Census reveals evidence for deep functional conservation of long noncoding RNAs in tumorigenesis
  • 2020
  • Ingår i: COMMUNICATIONS BIOLOGY. - : NATURE PUBLISHING GROUP. - 2399-3642. ; 3:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Joana Carlevaro-Fita, Andres Lanzos et al. present the Cancer LncRNA Census (CLC), a manually curated dataset of 122 long noncoding RNAs (lncRNAs) with experimentally-validated functions in cancer based on data from the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. CLC lncRNAs have unique gene features, and a number display evidence for cancer-driving functions that are conserved from humans to mice. Long non-coding RNAs (lncRNAs) are a growing focus of cancer genomics studies, creating the need for a resource of lncRNAs with validated cancer roles. Furthermore, it remains debated whether mutated lncRNAs can drive tumorigenesis, and whether such functions could be conserved during evolution. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we introduce the Cancer LncRNA Census (CLC), a compilation of 122 GENCODE lncRNAs with causal roles in cancer phenotypes. In contrast to existing databases, CLC requires strong functional or genetic evidence. CLC genes are enriched amongst driver genes predicted from somatic mutations, and display characteristic genomic features. Strikingly, CLC genes are enriched for driver mutations from unbiased, genome-wide transposon-mutagenesis screens in mice. We identified 10 tumour-causing mutations in orthologues of 8 lncRNAs, including LINC-PINT and NEAT1, but not MALAT1. Thus CLC represents a dataset of high-confidence cancer lncRNAs. Mutagenesis maps are a novel means for identifying deeply-conserved roles of lncRNAs in tumorigenesis.
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2.
  • Rheinbay, Esther, et al. (författare)
  • Analyses of non-coding somatic drivers in 2,658 cancer whole genomes
  • 2020
  • Ingår i: ; 578:7793, s. 102-111
  • Tidskriftsartikel (refereegranskat)abstract
    • The discovery of drivers of cancer has traditionally focused on protein-coding genes(1-4). Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium(5) of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers(6,7), raise doubts about others and identify novel candidates, including point mutations in the 5' region of TP53, in the 3' untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.
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