Biglycan-driven risk stratification in ZFTA-RELA fusion supratentorial ependymomas through transcriptome profiling
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 interme...
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2025-01-01
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Online Access: | https://doi.org/10.1186/s40478-024-01921-w |
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author | Konstantin Okonechnikov David R. Ghasemi Daniel Schrimpf Svenja Tonn Martin Mynarek Jan Koster Till Milde Tuyu Zheng Philipp Sievers Felix Sahm David T.W. Jones Andreas von Deimling Stefan M. Pfister Marcel Kool Kristian W. Pajtler Andrey Korshunov |
author_facet | Konstantin Okonechnikov David R. Ghasemi Daniel Schrimpf Svenja Tonn Martin Mynarek Jan Koster Till Milde Tuyu Zheng Philipp Sievers Felix Sahm David T.W. Jones Andreas von Deimling Stefan M. Pfister Marcel Kool Kristian W. Pajtler Andrey Korshunov |
author_sort | Konstantin Okonechnikov |
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description | 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. |
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institution | Kabale University |
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publishDate | 2025-01-01 |
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spelling | doaj-art-360c3a769ab0461e94964cd13e61bf382025-01-12T12:43:58ZengBMCActa Neuropathologica Communications2051-59602025-01-0113111210.1186/s40478-024-01921-wBiglycan-driven risk stratification in ZFTA-RELA fusion supratentorial ependymomas through transcriptome profilingKonstantin Okonechnikov0David R. Ghasemi1Daniel Schrimpf2Svenja Tonn3Martin Mynarek4Jan Koster5Till Milde6Tuyu Zheng7Philipp Sievers8Felix Sahm9David T.W. Jones10Andreas von Deimling11Stefan M. Pfister12Marcel Kool13Kristian W. Pajtler14Andrey Korshunov15Hopp Children’s Cancer Center Heidelberg (KiTZ)Hopp Children’s Cancer Center Heidelberg (KiTZ)Hopp Children’s Cancer Center Heidelberg (KiTZ)Pediatric Hematology and Oncology, University Medical Center Hamburg-EppendorfPediatric Hematology and Oncology, University Medical Center Hamburg-EppendorfCenter for Experimental and Molecular Medicine, Amsterdam University Medical Centers, University of Amsterdam and Cancer Center AmsterdamHopp Children’s Cancer Center Heidelberg (KiTZ)Hopp Children’s Cancer Center Heidelberg (KiTZ)Clinical Cooperation Unit Neuropathology (B300), German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), National Center for Tumor Diseases (NCT)Hopp Children’s Cancer Center Heidelberg (KiTZ)Hopp Children’s Cancer Center Heidelberg (KiTZ)Hopp Children’s Cancer Center Heidelberg (KiTZ)Hopp Children’s Cancer Center Heidelberg (KiTZ)Hopp Children’s Cancer Center Heidelberg (KiTZ)Hopp Children’s Cancer Center Heidelberg (KiTZ)Hopp Children’s Cancer Center Heidelberg (KiTZ)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.https://doi.org/10.1186/s40478-024-01921-wEpendymomaZFTA-RELA fusionBGNExpressionPrognosis |
spellingShingle | Konstantin Okonechnikov David R. Ghasemi Daniel Schrimpf Svenja Tonn Martin Mynarek Jan Koster Till Milde Tuyu Zheng Philipp Sievers Felix Sahm David T.W. Jones Andreas von Deimling Stefan M. Pfister Marcel Kool Kristian W. Pajtler Andrey Korshunov Biglycan-driven risk stratification in ZFTA-RELA fusion supratentorial ependymomas through transcriptome profiling Acta Neuropathologica Communications Ependymoma ZFTA-RELA fusion BGN Expression Prognosis |
title | Biglycan-driven risk stratification in ZFTA-RELA fusion supratentorial ependymomas through transcriptome profiling |
title_full | Biglycan-driven risk stratification in ZFTA-RELA fusion supratentorial ependymomas through transcriptome profiling |
title_fullStr | Biglycan-driven risk stratification in ZFTA-RELA fusion supratentorial ependymomas through transcriptome profiling |
title_full_unstemmed | Biglycan-driven risk stratification in ZFTA-RELA fusion supratentorial ependymomas through transcriptome profiling |
title_short | Biglycan-driven risk stratification in ZFTA-RELA fusion supratentorial ependymomas through transcriptome profiling |
title_sort | biglycan driven risk stratification in zfta rela fusion supratentorial ependymomas through transcriptome profiling |
topic | Ependymoma ZFTA-RELA fusion BGN Expression Prognosis |
url | https://doi.org/10.1186/s40478-024-01921-w |
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