Comparison of transcriptome profiles between medulloblastoma primary and recurrent tumors uncovers novel variance effects in relapses

Abstract

Nowadays medulloblastoma (MB) tumors can be treated with risk-stratified approaches with up to 80% success rate. However, disease relapses occur in approximately 30% of patients and successful salvage treatment strategies at relapse remain scarce. Acquired copy number changes or TP53 mutations are known to occur frequently in relapses, while methylation profiles usually remain highly similar to those of the matching primary tumors, indicating that in general molecular subgrouping does not change during the course of the disease. In the current study, we have used RNA sequencing data to analyze the transcriptome profiles of 43 primary-relapse MB pairs in order to identify specific molecular features of relapses within various tumor groups. Gene variance analysis between primary and relapse samples demonstrated the impact of age in SHH-MB: the changes in gene expression relapse profiles were more pronounced in the younger patients (< 10 years old), which were also associated with increased DNA aberrations and somatic mutations at relapse probably driving this effect. For Group 3/4 MB transcriptome data analysis uncovered clear sets of genes either active or decreased at relapse that are significantly associated with survival, thus could be potential predictive markers. In addition, deconvolution analysis of bulk transcriptome data identified progression-associated differences in cell type enrichment. The proportion of undifferentiated progenitors increased in SHH-MB relapses with a concomitant decrease of differentiated neuron-like cells, while in Group 3/4 MB relapses cell cycle activity increases and differentiated neuron-like cells proportion decreases as well. Thus, our findings uncovered significant transcriptome changes in the molecular signatures of relapsed MB and could be potentially useful for further clinical purposes.

Keywords: Medulloblastoma; Prognosis; Relapses; Transcriptomics.

Fig. 1

a Annotation onco-plot describing patient histological and molecular characteristics for target primary-relapse tumor pairs with available RNA sequencing data (n = 43). The following abbreviations were used: SHH_INF—infant SHH, CH_AD—child–adult SHH, DNMB—desmoplastic/nodular, LCA—large cell/anaplastic, PFS—progression-free survival, CNV—copy number variants. b Principal component analysis of full MB gene expression primary-relapse dataset based on the top 500 most highly variable genes. Tumor profiles from the same patient connected via dot lines, target component variance percentage (VP) is shown in axis labels. c Boxplot demonstrating the transcriptome variance between primary and relapse tumors among MB groups (SHH-MB—24, Group 3 MB—5, Group 4 MB—14 cases)

Fig. 2

a Principal component analysis of SHH-MB gene expression primary-relapse dataset based on the top 500 most highly variable genes. Primary and relapse tumor profiles from the same patient connected via dot lines, target component variance percentage (VP) is shown in axis labels. b Association of transcriptome variance between primary and relapse SHH-MB with age of the patients. c Boxplot demonstrating the transcriptome variance between primary and relapse tumors among SHH-MB with (n = 11) and without (n = 13) novel CNVs. d Copy number profiles derived from methylation data of primary (top) and relapse (bottom) tumors from the same SHH-MB infant patient. e Boxplot demonstrating the transcriptome variance between primary and relapse MB SHH among relapse types (local: 12, metastatic: 4, combined: 8 cases)

Fig. 3

a Principal component analysis of Group 3/4 MB gene expression primary-relapse dataset based on top 500 most highly variable genes, target component variance percentage (VP) is shown in axis labels. Primary and relapse tumor profiles from the same patient are connected via dot lines. b Association of transcriptome variance between primary and relapse Group 3/4 MB with age of the patients. c Boxplot demonstrating the transcriptome variance between primary and relapse Group 3/4 MB among relapse patterns (metastases: 11, combined: 9 cases). d Heatmap of top most confident genes differentially expressed between primary and relapse Group 3/4 MB, either down-regulated (first block, n = 20) or up-regulated (second block, n = 20) in relapses respectively. e, f Boxplots of differentially expressed genes either up-regulated (e, PDIA6) or down-regulated (f, SNORD115-23) in Group 3/4 MB relapses vs primaries

Fig. 4

a, b Kaplan–Meyer overall survival probability curves for cases from DKFZ RNA-seq dataset with high and low expression of PDIA6 in entire (a) and relapsed (b) Group 3/4 MB cohorts disclosed unfavorable OS for tumors with elevated gene expression (log rank; p < 0.01). c, d Kaplan–Meyer survival probability curves for cases with high and low expression of SNORD115-23 in entire (c) and relapsed (d) Group 3/4 MB cohorts disclosed unfavorable OS for tumors with low levels of gene expression (log rank; p < 0.01). For relapsed cohort (b,d) survival time was calculated from re-operation to the last event

Fig. 5

a Barplot demonstrating predicted relative proportions of MB cell types in bulk primary and relapse tumor gene expression profiles. Thick black lines delimitated each primary-relapse pair. b, c Boxplots of difference between MB SHH primary and relapse tumors in proportions of undifferentiated progenitors B1 (b) and differentiated neuron-like cells C1 (c). d, e Boxplots of difference between MB G4 primary and relapse tumors in proportions of cell cycle enriched A1 (d) and differentiated neuron-like cells C1 (e)