Home > Publications database > Biglycan-driven risk stratification in ZFTA-RELA fusion supratentorial ependymomas through transcriptome profiling. > print

001     296134
005     20250112014723.0
024 7 _ |a 10.1186/s40478-024-01921-w
|2 doi
024 7 _ |a pmid:39762990
|2 pmid
024 7 _ |a altmetric:172787582
|2 altmetric
037 _ _ |a DKFZ-2025-00064
041 _ _ |a English
082 _ _ |a 610
100 1 _ |a Okonechnikov, Konstantin
|0 P:(DE-He78)34b3639de467b2c700920d7cbc3d2110
|b 0
|e First author
|u dkfz
245 _ _ |a Biglycan-driven risk stratification in ZFTA-RELA fusion supratentorial ependymomas through transcriptome profiling.
260 _ _ |a London
|c 2025
|b Biomed Central
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1736322199_24878
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
500 _ _ |a #EA:B062#LA:B300#
520 _ _ |a 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.
536 _ _ |a 312 - Funktionelle und strukturelle Genomforschung (POF4-312)
|0 G:(DE-HGF)POF4-312
|c POF4-312
|f POF IV
|x 0
588 _ _ |a Dataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de
650 _ 7 |a BGN
|2 Other
650 _ 7 |a ZFTA-RELA fusion
|2 Other
650 _ 7 |a Ependymoma
|2 Other
650 _ 7 |a Expression
|2 Other
650 _ 7 |a Prognosis
|2 Other
650 _ 7 |a Transcription Factor RelA
|2 NLM Chemicals
650 _ 7 |a RELA protein, human
|2 NLM Chemicals
650 _ 7 |a Oncogene Proteins, Fusion
|2 NLM Chemicals
650 _ 2 |a Humans
|2 MeSH
650 _ 2 |a Ependymoma: genetics
|2 MeSH
650 _ 2 |a Ependymoma: metabolism
|2 MeSH
650 _ 2 |a Ependymoma: pathology
|2 MeSH
650 _ 2 |a Supratentorial Neoplasms: genetics
|2 MeSH
650 _ 2 |a Supratentorial Neoplasms: pathology
|2 MeSH
650 _ 2 |a Supratentorial Neoplasms: metabolism
|2 MeSH
650 _ 2 |a Male
|2 MeSH
650 _ 2 |a Female
|2 MeSH
650 _ 2 |a Gene Expression Profiling: methods
|2 MeSH
650 _ 2 |a Transcription Factor RelA: genetics
|2 MeSH
650 _ 2 |a Transcription Factor RelA: metabolism
|2 MeSH
650 _ 2 |a Adult
|2 MeSH
650 _ 2 |a Middle Aged
|2 MeSH
650 _ 2 |a Adolescent
|2 MeSH
650 _ 2 |a Child
|2 MeSH
650 _ 2 |a Young Adult
|2 MeSH
650 _ 2 |a Child, Preschool
|2 MeSH
650 _ 2 |a Aged
|2 MeSH
650 _ 2 |a Prognosis
|2 MeSH
650 _ 2 |a Risk Assessment: methods
|2 MeSH
650 _ 2 |a Oncogene Proteins, Fusion: genetics
|2 MeSH
650 _ 2 |a Oncogene Proteins, Fusion: metabolism
|2 MeSH
700 1 _ |a Ghasemi, David R
|0 P:(DE-HGF)0
|b 1
700 1 _ |a Schrimpf, Daniel
|0 P:(DE-He78)e54a1e0999c1d8c95869ef9188b794cc
|b 2
|u dkfz
700 1 _ |a Tonn, Svenja
|b 3
700 1 _ |a Mynarek, Martin
|b 4
700 1 _ |a Koster, Jan
|b 5
700 1 _ |a Milde, Till
|0 P:(DE-He78)0be2f86573954f87e97f8a4dbb05cb0f
|b 6
|u dkfz
700 1 _ |a Zheng, Tuyu
|0 P:(DE-He78)1d5e6252296473fc060b71e61a22256c
|b 7
700 1 _ |a Sievers, Philipp
|0 P:(DE-He78)8aad075b17d93a5636a34942bdbd7ee6
|b 8
|u dkfz
700 1 _ |a Sahm, Felix
|0 P:(DE-He78)a1f4b408b9155beb2a8f7cba4d04fe88
|b 9
|u dkfz
700 1 _ |a Jones, David T W
|0 P:(DE-He78)551bb92841f634070997aa168d818492
|b 10
|u dkfz
700 1 _ |a von Deimling, Andreas
|0 P:(DE-He78)a8a10626a848d31e70cfd96a133cc144
|b 11
|u dkfz
700 1 _ |a Pfister, Stefan M
|0 P:(DE-He78)f746aa965c4e1af518b016de3aaff5d9
|b 12
|u dkfz
700 1 _ |a Kool, Marcel
|0 P:(DE-He78)4c28e2aade5f44d8eca9dd8e97638ec8
|b 13
|u dkfz
700 1 _ |a Pajtler, Kristian W
|0 P:(DE-He78)a7c1bbac024fa232d9c6b78443328d9d
|b 14
|u dkfz
700 1 _ |a Korshunov, Andrey
|0 P:(DE-He78)8d9c904a6cea14d4c99c78ba46e41f93
|b 15
|e Last author
|u dkfz
773 _ _ |a 10.1186/s40478-024-01921-w
|g Vol. 13, no. 1, p. 4
|0 PERI:(DE-600)2715589-4
|n 1
|p 4
|t Acta Neuropathologica Communications
|v 13
|y 2025
|x 2051-5960
909 C O |o oai:inrepo02.dkfz.de:296134
|p VDB
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 0
|6 P:(DE-He78)34b3639de467b2c700920d7cbc3d2110
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 1
|6 P:(DE-HGF)0
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 2
|6 P:(DE-He78)e54a1e0999c1d8c95869ef9188b794cc
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 6
|6 P:(DE-He78)0be2f86573954f87e97f8a4dbb05cb0f
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 7
|6 P:(DE-He78)1d5e6252296473fc060b71e61a22256c
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 8
|6 P:(DE-He78)8aad075b17d93a5636a34942bdbd7ee6
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 9
|6 P:(DE-He78)a1f4b408b9155beb2a8f7cba4d04fe88
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 10
|6 P:(DE-He78)551bb92841f634070997aa168d818492
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 11
|6 P:(DE-He78)a8a10626a848d31e70cfd96a133cc144
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 12
|6 P:(DE-He78)f746aa965c4e1af518b016de3aaff5d9
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 13
|6 P:(DE-He78)4c28e2aade5f44d8eca9dd8e97638ec8
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 14
|6 P:(DE-He78)a7c1bbac024fa232d9c6b78443328d9d
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 15
|6 P:(DE-He78)8d9c904a6cea14d4c99c78ba46e41f93
913 1 _ |a DE-HGF
|b Gesundheit
|l Krebsforschung
|1 G:(DE-HGF)POF4-310
|0 G:(DE-HGF)POF4-312
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-300
|4 G:(DE-HGF)POF
|v Funktionelle und strukturelle Genomforschung
|x 0
914 1 _ |y 2025
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b ACTA NEUROPATHOL COM : 2022
|d 2023-10-26
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2023-10-26
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2023-10-26
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0320
|2 StatID
|b PubMed Central
|d 2023-10-26
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0501
|2 StatID
|b DOAJ Seal
|d 2023-05-02T09:09:14Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0500
|2 StatID
|b DOAJ
|d 2023-05-02T09:09:14Z
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b DOAJ : Anonymous peer review
|d 2023-05-02T09:09:14Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
|d 2023-10-26
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
|d 2023-10-26
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2023-10-26
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
|d 2023-10-26
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2023-10-26
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2023-10-26
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1190
|2 StatID
|b Biological Abstracts
|d 2023-10-26
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2023-10-26
915 _ _ |a IF >= 5
|0 StatID:(DE-HGF)9905
|2 StatID
|b ACTA NEUROPATHOL COM : 2022
|d 2023-10-26
915 _ _ |a Article Processing Charges
|0 StatID:(DE-HGF)0561
|2 StatID
|d 2023-10-26
915 _ _ |a Fees
|0 StatID:(DE-HGF)0700
|2 StatID
|d 2023-10-26
920 2 _ |0 I:(DE-He78)B300-20160331
|k B300
|l KKE Neuropathologie
|x 0
920 1 _ |0 I:(DE-He78)B062-20160331
|k B062
|l B062 Pädiatrische Neuroonkologie
|x 0
920 1 _ |0 I:(DE-He78)HD01-20160331
|k HD01
|l DKTK HD zentral
|x 1
920 1 _ |0 I:(DE-He78)B300-20160331
|k B300
|l KKE Neuropathologie
|x 2
920 1 _ |0 I:(DE-He78)B310-20160331
|k B310
|l KKE Pädiatrische Onkologie
|x 3
920 1 _ |0 I:(DE-He78)B360-20160331
|k B360
|l Pädiatrische Gliomforschung
|x 4
920 0 _ |0 I:(DE-He78)B062-20160331
|k B062
|l B062 Pädiatrische Neuroonkologie
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-He78)B062-20160331
980 _ _ |a I:(DE-He78)HD01-20160331
980 _ _ |a I:(DE-He78)B300-20160331
980 _ _ |a I:(DE-He78)B310-20160331
980 _ _ |a I:(DE-He78)B360-20160331
980 _ _ |a UNRESTRICTED

LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21