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@ARTICLE{Kommoss:148317,
      author       = {F. K. F. Kommoss and D. Stichel$^*$ and D. Schrimpf$^*$ and
                      M. Kriegsmann and B. Tessier-Cloutier and A. Talhouk and J.
                      N. McAlpine and K. T. E. Chang and D. Sturm$^*$ and S. M.
                      Pfister$^*$ and L. Romero-Pérez and T. Kirchner and T. G.
                      P. Grünewald$^*$ and R. Buslei and H.-P. Sinn and G.
                      Mechtersheimer and P. Schirmacher and D. Schmidt and H.-A.
                      Lehr and F. Sahm and D. G. Huntsman and C. B. Gilks and F.
                      Kommoss and A. von Deimling$^*$ and C. Koelsche},
      title        = {{DNA} methylation-based profiling of uterine neoplasms: a
                      novel tool to improve gynecologic cancer diagnostics.213},
      journal      = {Journal of cancer research and clinical oncology},
      volume       = {146},
      number       = {1},
      issn         = {0171-5216},
      address      = {Berlin},
      publisher    = {Springer42162},
      reportid     = {DKFZ-2019-02875},
      pages        = {97-104},
      year         = {2020},
      note         = {2020 Jan;146(1):97-104 / #LA:B300#},
      abstract     = {Uterine neoplasms comprise a broad spectrum of lesions,
                      some of which may pose a diagnostic challenge even to
                      experienced pathologists. Recently, genome-wide DNA
                      methylation-based classification of central nervous system
                      tumors has been shown to increase diagnostic precision in
                      clinical practice when combined with standard
                      histopathology. In this study, we describe DNA methylation
                      patterns of a diverse set of uterine neoplasms and test the
                      applicability of array-based DNA methylation profiling.A
                      multicenter cohort including prototypical epithelial and
                      mesenchymal uterine neoplasms was collected. Tumors were
                      subject to pathology review and array-based DNA methylation
                      profiling (Illumina Infinium HumanMethylation450 or EPIC
                      [850k] BeadChip). Methylation data were analyzed by
                      unsupervised hierarchical clustering and t-SNE
                      analysis.After sample retrieval and pathology review the
                      study cohort consisted of 49 endometrial carcinomas (EC), 5
                      carcinosarcomas (MMMT), 8 uterine leiomyomas (ULMO), 7
                      uterine leiomyosarcomas (ULMS), 15 uterine tumor resembling
                      ovarian sex cord tumors (UTROSCT), 17 low-grade endometrial
                      stromal sarcomas (LGESS) and 9 high-grade endometrial
                      stromal sarcomas (HGESS). Analysis of methylation data
                      identified distinct methylation clusters, which correlated
                      with established diagnostic categories of uterine neoplasms.
                      MMMT clustered together with EC, while ULMO, ULMS and
                      UTROSCT each formed distinct clusters. The LGESS cluster
                      differed from that of HGESS, and within the branch of HGESS,
                      we observed a notable subgrouping of YWHAE- and
                      BCOR-rearranged tumors.Herein, we describe distinct DNA
                      methylation signatures in uterine neoplasms and show that
                      array-based DNA methylation analysis holds promise as an
                      ancillary tool to further characterize uterine neoplasms,
                      especially in cases which are diagnostically challenging by
                      conventional techniques.},
      cin          = {B300 / B062 / HD01},
      ddc          = {610},
      cid          = {I:(DE-He78)B300-20160331 / I:(DE-He78)B062-20160331 /
                      I:(DE-He78)HD01-20160331},
      pnm          = {312 - Functional and structural genomics (POF3-312)},
      pid          = {G:(DE-HGF)POF3-312},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:31768620},
      doi          = {10.1007/s00432-019-03093-w},
      url          = {https://inrepo02.dkfz.de/record/148317},
}