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 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: BGN; ZFTA-RELA fusion; Ependymoma; Expression; Prognosis.

Fig. 1

a) Annotation onco-plot describing patient histological and molecular characteristics for target ZFTA-RELA ST-EPN tumors with available RNA sequencing data (n = 80). The following abbreviations were used: RT - radiotherapy, LOC - conformal local, CSP - craniospinal, PFS—progression-free survival, CNV—copy number variants. b) Genomic locations the ZFTA-RELA fusion breakpoints stating the main types of the fusion. c, d) No survival differences were identified between the various ZFTA-RELA fusion types. d) Heatmap of significant differentially expressed genes between ZFTA-RELA fusion type 1 (n = 29) and 2 (n = 16)

Fig. 2

Supervised k-mean clustering of multigene survival data (a) defined a set of 100 genes (metagene set) that subdivided ST-EPN RELA into two transcriptome subtypes (TRS): favorable (n = 52) and unfavorable (n = 28). Two identified TRS were associated with patients’ OS (b) and PFS (c). d) Heatmap of top 20 most confident genes differentially expressed between clinically relevant TRS with BGN on the top of this list

Fig. 3

a) Bar plots of predicted relative proportions of EPN ZFTA cell types in bulk tumor gene expression profiles. Annotation provides favorable (FAV; blue) and unfavorable (UFV; red) status for each tumor sample. (b-e) Boxplots of statistically significant differences between EPN ZFTA favorable and unfavorable in proportions of ST-RELA-Variable (b), ST-Interferon-Response (c), ST-Radial-Glial (d) and ST-Ependymal (e) neoplastic cell subpopulations

Fig. 4

Two variants of BGN protein immunostaining were detected: (a) Negative - expression in the tumor vessels predominantly. (b) Positive - intense dot-like BGN expression in tumor cells. BGN expression levels were significantly higher in immunopositive ST-EPN RELA (c). Survival analysis revealed that BGN immunopositivity is significantly associated with worse clinical outcomes in both the screening (d,e) and validation (f,g) sets of ST-EPN RELA