TY  - JOUR
AU  - Pohl, Lara C
AU  - Leitheiser, Maximilian
AU  - Obrecht, Denise
AU  - Schweizer, Leonille
AU  - Wefers, Annika K
AU  - Eckhardt, Alicia
AU  - Raffeld, Mark
AU  - Sturm, Dominik
AU  - Pajtler, Kristian W
AU  - Rutkowski, Stefan
AU  - Fukuoka, Kohei
AU  - Ichimura, Koichi
AU  - Bockmayr, Michael
AU  - Schüller, Ulrich
TI  - Molecular characteristics and improved survival prediction in a cohort of 2023 ependymomas.
JO  - Acta neuropathologica
VL  - 147
IS  - 1
SN  - 0001-6322
CY  - Heidelberg
PB  - Springer
M1  - DKFZ-2024-00207
SP  - 24
PY  - 2024
AB  - The diagnosis of ependymoma has moved from a purely histopathological review with limited prognostic value to an integrated diagnosis, relying heavily on molecular information. However, as the integrated approach is still novel and some molecular ependymoma subtypes are quite rare, few studies have correlated integrated pathology and clinical outcome, often focusing on small series of single molecular types. We collected data from 2023 ependymomas as classified by DNA methylation profiling, consisting of 1736 previously published and 287 unpublished methylation profiles. Methylation data and clinical information were correlated, and an integrated model was developed to predict progression-free survival. Patients with EPN-PFA, EPN-ZFTA, and EPN-MYCN tumors showed the worst outcome with 10-year overall survival rates of 56
KW  - Humans
KW  - Ependymoma
KW  - Progression-Free Survival
KW  - Protein Processing, Post-Translational
KW  - DNA methylation (Other)
KW  - Ependymoma (Other)
KW  - Machine learning (Other)
KW  - Molecular types (Other)
KW  - Survival (Other)
LB  - PUB:(DE-HGF)16
C6  - pmid:38265522
DO  - DOI:10.1007/s00401-023-02674-x
UR  - https://inrepo02.dkfz.de/record/287282
ER  -