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

Calina, TG; Grafenhorst, E; Schallenberg, S; M&#246;bs, M; Daenekas, B; Sabo, AA; Chen, B; Koch, I; Janik, T; Churchman, M; Gourley, C; Christie, EL; Vasilescu, C; Herlea, V; Schmitt, WD; Leopold, N; Heitz, F; Vlaski, A; Tolkach, Y; Bremmer, F; Klauschen, F; B&#252;ttner, R; Str&#246;bel, P; Burandt, E; Sauter, G; Heppner, FL; Taube, ET; Sehouli, J; Braicu, IE; Euskirchen, P; Horst, D; Gorringe, KL; Capper, D; Dragomir, MP

Author(s): Calina, TG; Grafenhorst, E; Schallenberg, S; Möbs, M; Daenekas, B; Sabo, AA; Chen, B; Koch, I; Janik, T; Churchman, M; Gourley, C; Christie, EL; Vasilescu, C; Herlea, V; Schmitt, WD; Leopold, N; Heitz, F; Vlaski, A; Tolkach, Y; Bremmer, F; Klauschen, F; Büttner, R; Ströbel, P; Burandt, E; Sauter, G; Heppner, FL; Taube, ET; Sehouli, J; Braicu, IE; Euskirchen, P; Horst, D; Gorringe, KL; Capper, D; Dragomir, MP;
Details: Publication Year 2026-08-18,Volume 7,Issue #8,Page 102941
Journal Title: Cell Reports Medicine
Publication Type: Research article
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.
Publisher: Elsevier
Keywords: Humans; Female; *DNA Methylation/genetics; *Ovarian Neoplasms/genetics/pathology/classification/diagnosis; *Adenocarcinoma, Mucinous/genetics/pathology/classification/diagnosis; Machine Learning; Neoplasm Metastasis; Epigenesis, Genetic; Middle Aged; DNA methylation; epigenetics; metastasis; molecular subtypes; mucinous borderline ovarian tumor; mucinous ovarian cancer
Department(s): Laboratory Research
Publisher's Version: https://doi.org/10.1016/j.xcrm.2026.102941
Open Access at Publisher's Site: https://doi.org/10.1016/j.xcrm.2026.102941
Terms of Use/Rights Notice: Refer to copyright notice on published article.

Creation Date: 2026-08-11 02:01:20

Last Modified: 2026-09-03 12:44:10