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@ARTICLE{Reyna:177484,
      author       = {M. A. Reyna and D. Haan and M. Paczkowska and L. P. C.
                      Verbeke and M. Vazquez and A. Kahraman and S. Pulido-Tamayo
                      and J. Barenboim and L. Wadi and P. Dhingra and R. Shrestha
                      and G. Getz and M. S. Lawrence and J. S. Pedersen and M. A.
                      Rubin and D. A. Wheeler and S. Brunak and J. M. G.
                      Izarzugaza and E. Khurana and K. Marchal and C. von Mering
                      and S. C. Sahinalp and A. Valencia and P. Drivers and
                      FunctionalInterpretationWorkingGroup and J. Reimand and J.
                      M. Stuart and B. J. Raphael and PCAWGConsortium},
      title        = {{P}athway and network analysis of more than 2500 whole
                      cancer genomes.},
      journal      = {Nature Communications},
      volume       = {11},
      number       = {1},
      issn         = {2041-1723},
      address      = {[London]},
      publisher    = {Nature Publishing Group UK},
      reportid     = {DKFZ-2021-02571},
      pages        = {729},
      year         = {2020},
      note         = {siehe Correction: DKFZ Autoren affiliiert im PCAWG
                      Consortium: https://inrepo02.dkfz.de/record/212441 /
                      https://doi.org/10.1038/s41467-022-32334-9},
      abstract     = {The catalog of cancer driver mutations in protein-coding
                      genes has greatly expanded in the past decade. However,
                      non-coding cancer driver mutations are less
                      well-characterized and only a handful of recurrent
                      non-coding mutations, most notably TERT promoter mutations,
                      have been reported. Here, as part of the ICGC/TCGA
                      Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium,
                      which aggregated whole genome sequencing data from 2658
                      cancer across 38 tumor types, we perform multi-faceted
                      pathway and network analyses of non-coding mutations across
                      2583 whole cancer genomes from 27 tumor types compiled by
                      the ICGC/TCGA PCAWG project that was motivated by the
                      success of pathway and network analyses in prioritizing rare
                      mutations in protein-coding genes. While few non-coding
                      genomic elements are recurrently mutated in this cohort, we
                      identify 93 genes harboring non-coding mutations that
                      cluster into several modules of interacting proteins. Among
                      these are promoter mutations associated with reduced mRNA
                      expression in TP53, TLE4, and TCF4. We find that biological
                      processes had variable proportions of coding and non-coding
                      mutations, with chromatin remodeling and proliferation
                      pathways altered primarily by coding mutations, while
                      developmental pathways, including Wnt and Notch, altered by
                      both coding and non-coding mutations. RNA splicing is
                      primarily altered by non-coding mutations in this cohort,
                      and samples containing non-coding mutations in well-known
                      RNA splicing factors exhibit similar gene expression
                      signatures as samples with coding mutations in these genes.
                      These analyses contribute a new repertoire of possible
                      cancer genes and mechanisms that are altered by non-coding
                      mutations and offer insights into additional cancer
                      vulnerabilities that can be investigated for potential
                      therapeutic treatments.},
      keywords     = {Chromatin Assembly and Disassembly / Computational Biology:
                      methods / Databases, Genetic / Gene Expression Regulation,
                      Neoplastic / Genome, Human / Humans / Metabolic Networks and
                      Pathways: genetics / Mutation / Neoplasms: genetics /
                      Neoplasms: metabolism / Promoter Regions, Genetic / RNA
                      Splicing},
      cin          = {B080 / B240 / B370 / B330 / HD01 / B060 / B360 / BE01 /
                      B062 / B066 / B063 / W190 / B260 / W610 / B087},
      ddc          = {500},
      cid          = {I:(DE-He78)B080-20160331 / I:(DE-He78)B240-20160331 /
                      I:(DE-He78)B370-20160331 / I:(DE-He78)B330-20160331 /
                      I:(DE-He78)HD01-20160331 / I:(DE-He78)B060-20160331 /
                      I:(DE-He78)B360-20160331 / I:(DE-He78)BE01-20160331 /
                      I:(DE-He78)B062-20160331 / I:(DE-He78)B066-20160331 /
                      I:(DE-He78)B063-20160331 / I:(DE-He78)W190-20160331 /
                      I:(DE-He78)B260-20160331 / I:(DE-He78)W610-20160331 /
                      I:(DE-He78)B087-20160331},
      pnm          = {312 - Functional and structural genomics (POF3-312)},
      pid          = {G:(DE-HGF)POF3-312},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:32024854},
      pmc          = {pmc:PMC7002574},
      doi          = {10.1038/s41467-020-14367-0},
      url          = {https://inrepo02.dkfz.de/record/177484},
}