guest ::
| Home > Publications database > Biglycan-driven risk stratification in ZFTA-RELA fusion supratentorial ependymomas through transcriptome profiling. |
| Home > Publications database > Biglycan-driven risk stratification in ZFTA-RELA fusion supratentorial ependymomas through transcriptome profiling. |
| Journal Article | DKFZ-2025-00064 |
; ; ; ; ; ; ; ; ; ; ; ; ; ; ;
2025
Biomed Central
London
This record in other databases: 
Please use a persistent id in citations: doi:10.1186/s40478-024-01921-w
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.
Keyword(s): Humans (MeSH) ; Ependymoma: genetics (MeSH) ; Ependymoma: metabolism (MeSH) ; Ependymoma: pathology (MeSH) ; Supratentorial Neoplasms: genetics (MeSH) ; Supratentorial Neoplasms: pathology (MeSH) ; Supratentorial Neoplasms: metabolism (MeSH) ; Male (MeSH) ; Female (MeSH) ; Gene Expression Profiling: methods (MeSH) ; Transcription Factor RelA: genetics (MeSH) ; Transcription Factor RelA: metabolism (MeSH) ; Adult (MeSH) ; Middle Aged (MeSH) ; Adolescent (MeSH) ; Child (MeSH) ; Young Adult (MeSH) ; Child, Preschool (MeSH) ; Aged (MeSH) ; Prognosis (MeSH) ; Risk Assessment: methods (MeSH) ; Oncogene Proteins, Fusion: genetics (MeSH) ; Oncogene Proteins, Fusion: metabolism (MeSH) ; BGN ; ZFTA-RELA fusion ; Ependymoma ; Expression ; Prognosis ; Transcription Factor RelA ; RELA protein, human ; Oncogene Proteins, Fusion
; 
; Article Processing Charges ; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; DOAJ Seal ; Ebsco Academic Search ; Essential Science Indicators ; Fees ; IF >= 5 ; JCR ; PubMed Central ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
|
The record appears in these collections: |
