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Publications

Journal Article Ahead of print

PubMed: 42508406 DOI: 10.1016/j.xcrm.2026.102941

DNA methylation profiling enables subclassification of mucinous ovarian carcinoma and distinguishes it from extraovarian mucinous metastases.

Cell Rep Med

Authors: Teodor G Calina, Elena Grafenhorst, Simon Schallenberg, Markus Möbs, Bjarne Daenekas, Alexandru A Sabo, BaoQing Chen, Ines Koch, Tobias Janik, Michael Churchman, Charlie Gourley, Elizabeth L Christie, Catalin Vasilescu, Vlad Herlea, Wolfgang D Schmitt, Nicolae Leopold, Florian Heitz, Angelina Vlaski, Yuri Tolkach, Felix Bremmer, Frederick Klauschen, Reinhard Büttner, Philipp Ströbel, Eike Burandt, Guido Sauter, Frank L Heppner, Eliane T Taube, Jalid Sehouli, Ioana E Braicu, Philipp Euskirchen, David Horst, Kylie L Gorringe, David Capper, Mihnea P Dragomir

Affiliations

  • Faculty of Physics, Babeş-Bolyai University, Cluj-Napoca, Romania; TGC Ventures UG, Berlin, Germany.
  • Institute of Pathology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.
  • German Cancer Consortium (DKTK), Partner Site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Neuropathology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.
  • Department of Pediatric Cardiology, Pulmonology and Pediatric Intensive Care Medicine, University Children's Hospital Tübingen, Tübingen, Germany.
  • State Key Laboratory of Oncology in South China, Collaborative Innovation Centre for Cancer Medicine, Guangdong Esophageal Cancer Institute, Guangzhou, China; Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China.
  • Nicola Murray Centre for Ovarian Cancer Research, CRUK Scotland Centre, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, Scotland, UK.
  • The Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia; Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.
  • Department of Surgery, Fundeni Clinical Institute, Bucharest, Romania.
  • Department of Pathology, Fundeni Clinical Institute, Bucharest, Romania.
  • Faculty of Physics, Babeş-Bolyai University, Cluj-Napoca, Romania.
  • Department of Gynecology and Gynecologic Oncology, Evangelische Kliniken Essen-Mitte, Essen, Germany.
  • Institute of Pathology, Ludwig-Maximilians-Universität Munich, Munich, Germany.
  • Institute of Pathology, University Hospital Cologne, Köln, Germany.
  • Institute of Pathology, University Medical Center Göttingen, Göttingen, Germany.
  • Institute of Pathology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany; German Cancer Consortium (DKTK), Partner Site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany; Institute of Pathology, Ludwig-Maximilians-Universität Munich, Munich, Germany.
  • Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Department of Neuropathology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany; German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany.
  • Department of Gynaecology, European Competence Center for Ovarian Cancer, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany; North Eastern German Society for Gynecological Cancer, Tumor Bank Ovarian Cancer Network, Berlin, Germany.
  • Institute of Pathology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany; German Cancer Consortium (DKTK), Partner Site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Institute of Pathology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany; German Cancer Consortium (DKTK), Partner Site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany; Berlin Institute of Health, Berlin, Germany.

Abstract

Mucinous ovarian carcinoma (MOC) is an epithelial ovarian cancer subtype that is frequently misclassified as extraovarian mucinous metastasis (EOM) because of overlapping features. To address this diagnostic challenge, we perform genome-wide DNA methylation profiling of 58 MOCs, 38 EOMs, and 18 mucinous borderline ovarian tumors (mBOTs) collected from six institutions. Methylation analysis defines two mBOT groups, one epigenetically similar to normal ovary and one resembling MOC. Unsupervised clustering reveals two distinct MOC methylation subtypes with potential prognostic relevance in the internal cohort. Using these data together with 389 external profiles, we develop and validate a three-step machine-learning classifier that distinguishes MOC from EOM with 95.5% accuracy. External validation of this classifier on 21 MOCs and 24 EOMs yields an accuracy of 91.11% for differentiating MOC from EOM. These findings establish an epigenetic framework for mucinous ovarian tumors and provide a robust clinical classification tool.

MeSH

Biological Science Disciplines, Ovary, Neoplasms, Machine Learning, Dna Methylation, Neoplasm Metastasis, Ovarian Neoplasms, Dna