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@ARTICLE{Okonechnikov:296134,
author = {K. Okonechnikov$^*$ and D. R. Ghasemi$^*$ and D.
Schrimpf$^*$ and S. Tonn and M. Mynarek and J. Koster and T.
Milde$^*$ and T. Zheng$^*$ and P. Sievers$^*$ and F.
Sahm$^*$ and D. T. W. Jones$^*$ and A. von Deimling$^*$ and
S. M. Pfister$^*$ and M. Kool$^*$ and K. W. Pajtler$^*$ and
A. Korshunov$^*$},
title = {{B}iglycan-driven risk stratification in {ZFTA}-{RELA}
fusion supratentorial ependymomas through transcriptome
profiling.},
journal = {Acta Neuropathologica Communications},
volume = {13},
number = {1},
issn = {2051-5960},
address = {London},
publisher = {Biomed Central},
reportid = {DKFZ-2025-00064},
pages = {4},
year = {2025},
note = {#EA:B062#LA:B300#},
abstract = {Recent genomic studies have allowed the subdivision of
intracranial ependymomas into molecularly distinct groups
with highly specific clinical features and outcomes. The
majority of supratentorial ependymomas (ST-EPN) harbor
ZFTA-RELA fusions which were designated, in general, as an
intermediate risk tumor variant. However, molecular
prognosticators within ST-EPN ZFTA-RELA have not been
determined yet. Here, we performed methylation-based DNA
profiling and transcriptome RNA sequencing analysis of 80
ST-EPN ZFTA-RELA investigating the clinical significance of
various molecular patterns. The principal types of ZFTA-RELA
fusions, based on breakpoint location, demonstrated no
significant correlations with clinical outcomes. Multigene
analysis disclosed 1892 survival-associated genes, and a
metagene set of 100 genes subdivided ST-EPN ZFTA-RELA into
favorable and unfavorable transcriptome subtypes composed of
different cell subpopulations as detected by deconvolution
analysis. BGN (biglycan) was identified as the top-ranked
survival-associated gene and high BGN expression levels were
associated with poor survival (Hazard Ratio 17.85 for PFS
and 45.48 for OS; log-rank; p-value < 0.01). Furthermore,
BGN immunopositivity was identified as a strong prognostic
indicator of poor survival in ST-EPN, and this finding was
confirmed in an independent validation set of 56 samples.
Our results indicate that integrating BGN expression (at
mRNA and/or protein level) into risk stratification models
may improve ST-EPN ZFTA-RELA outcome prediction. Therefore,
gene and/or protein expression analyses for this molecular
marker could be adopted for ST-EPN ZFTA-RELA prognostication
and may help assign patients to optimal therapies in
prospective clinical trials.},
keywords = {Humans / Ependymoma: genetics / Ependymoma: metabolism /
Ependymoma: pathology / Supratentorial Neoplasms: genetics /
Supratentorial Neoplasms: pathology / Supratentorial
Neoplasms: metabolism / Male / Female / Gene Expression
Profiling: methods / Transcription Factor RelA: genetics /
Transcription Factor RelA: metabolism / Adult / Middle Aged
/ Adolescent / Child / Young Adult / Child, Preschool / Aged
/ Prognosis / Risk Assessment: methods / Oncogene Proteins,
Fusion: genetics / Oncogene Proteins, Fusion: metabolism /
BGN (Other) / ZFTA-RELA fusion (Other) / Ependymoma (Other)
/ Expression (Other) / Prognosis (Other) / Transcription
Factor RelA (NLM Chemicals) / RELA protein, human (NLM
Chemicals) / Oncogene Proteins, Fusion (NLM Chemicals)},
cin = {B062 / HD01 / B300 / B310 / B360},
ddc = {610},
cid = {I:(DE-He78)B062-20160331 / I:(DE-He78)HD01-20160331 /
I:(DE-He78)B300-20160331 / I:(DE-He78)B310-20160331 /
I:(DE-He78)B360-20160331},
pnm = {312 - Funktionelle und strukturelle Genomforschung
(POF4-312)},
pid = {G:(DE-HGF)POF4-312},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:39762990},
doi = {10.1186/s40478-024-01921-w},
url = {https://inrepo02.dkfz.de/record/296134},
}