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Biglycan-driven risk stratification in ZFTA-RELA fusion supratentorial ependymomas through transcriptome profiling
Konstantin Okonechnikov1,2, David R Ghasemi1,2,3,4,5,6, Daniel Schrimpf1,7,8
1Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany.
Acta Neuropathologica Communications
|January 6, 2025
Summary
Biglycan (BGN) expression predicts outcomes in supratentorial ependymomas with ZFTA-RELA fusions. High BGN levels indicate poor survival, suggesting its use in risk stratification for better patient treatment strategies.
Area of Science:
- Neuro-oncology
- Genomics
- Molecular Pathology
Background:
- Intracranial ependymomas are now classified into molecular groups with distinct clinical features.
- Supratentorial ependymomas (ST-EPN) with ZFTA-RELA fusions are typically intermediate risk, but lacked specific molecular prognosticators.
- Understanding molecular drivers within ST-EPN ZFTA-RELA is crucial for refining prognostication.
Purpose of the Study:
- To identify molecular prognosticators within ST-EPN ZFTA-RELA.
- To investigate the clinical significance of DNA methylation and transcriptome profiles.
- To determine if BGN expression can predict patient outcomes.
Main Methods:
- Methylation-based DNA profiling and transcriptome RNA sequencing on 80 ST-EPN ZFTA-RELA samples.
- Multigene analysis to identify survival-associated genes.
- Deconvolution analysis to detect cell subpopulations and assess BGN expression (mRNA and protein) in an independent validation set.
Main Results:
- No significant correlation between ZFTA-RELA fusion breakpoint location and clinical outcomes.
- 1892 survival-associated genes identified, leading to a 100-gene metagene set that defined favorable and unfavorable transcriptome subtypes.
- Biglycan (BGN) emerged as the top survival-associated gene; high BGN expression correlated with poor progression-free survival (PFS) and overall survival (OS).
- BGN immunopositivity was confirmed as a strong prognostic indicator of poor survival in an independent validation cohort.
Conclusions:
- BGN expression (mRNA and protein) is a significant prognostic marker for ST-EPN ZFTA-RELA.
- Integrating BGN into risk stratification models can improve outcome prediction for these tumors.
- BGN analysis may aid in assigning patients to appropriate therapies in clinical trials.
