Subgroup-specific alternative splicing in medulloblastoma

Abstract

Medulloblastoma comprises four distinct molecular variants: WNT, SHH, Group 3, and Group 4. We analyzed alternative splicing usage in 14 normal cerebellar samples and 103 medulloblastomas of known subgroup. Medulloblastoma samples have a statistically significant increase in alternative splicing as compared to normal fetal cerebella (2.3-times; P < 6.47E-8). Splicing patterns are distinct and specific between molecular subgroups. Unsupervised hierarchical clustering of alternative splicing events accurately assigns medulloblastomas to their correct subgroup. Subgroup-specific splicing and alternative promoter usage was most prevalent in Group 3 (19.4%) and SHH (16.2%) medulloblastomas, while observed less frequently in WNT (3.2%), and Group 4 (9.3%) tumors. Functional annotation of alternatively spliced genes reveals overrepresentation of genes important for neuronal development. Alternative splicing events in medulloblastoma may be regulated in part by the correlative expression of antisense transcripts, suggesting a possible mechanism affecting subgroup-specific alternative splicing. Our results identify additional candidate markers for medulloblastoma subgroup affiliation, further support the existence of distinct subgroups of the disease, and demonstrate an additional level of transcriptional heterogeneity between medulloblastoma subgroups.

Figure 1. Subgroup-Specific Alternative Splicing in Medulloblastoma

(a) Distribution of 9096 alternatively spliced probe sets, identified by Splice Index (SI) and Pattern-Based Correlation (PAC) algorithms, across 103 primary medulloblastoma and 14 normal cerebella samples demonstrates strong enrichment patterns in medulloblastoma (79%) with a minority of alternative splicing events restricted to the normal cerebella (15%). (b) Subgroup association of 7509 probe sets with medulloblastoma-enriched splicing patterns identifies elevated levels of Group 3 (19.4%, 1454 probe sets) and SHH (16.2%, 1216 probe sets) enriched alternative splicing with lower levels present in WNT (3.2%, 241 probe sets) and Group 4 (9.3%, 697 probe sets) tumors. Half of all medulloblastoma-enriched splicing events (51.9%, 3901 probe sets) were identified in medulloblastomas from multiple subgroups. (c) Using Splice Index (SI) and Pattern Based Correlation (PAC) algorithms the number of alternative splicing events per sample was identified, producing similar trends for both algorithms. Subgroup-specific splicing patterns revealed a significant developmental increase in alternative splicing from the fetal to adult normal cerebella with a further increase in splicing observed in medulloblastomas. (d) Distribution of the molecular subgroups of medulloblastoma in hyperspliced (n=26) and non-hyperspliced tumors (n=77) reveals an increased frequency of WNT (+6%) and Group 3 tumors (+16%) in hyperpliced medulloblastomas, and a decreased frequency in Group 4 tumors (−20%). (e) Subgroup-specific distribution of alternative splicing per sample for hyperspliced versus non-hyperspliced tumors. Hyperspliced tumors demonstrate a significant increased number of alternatively spliced exons across each subgroup – ranging from 2.18 (WNT) to 4.97 (Group 3) times higher levels of splicing. (f) Hyperspliced medulloblastomas display a significantly decreased overall survival (P<3.08E-2) relative to non-hyperspliced medulloblastomas. (g) Each molecular subgroup of medulloblastomas demonstrates a trend towards increased mortality for hyperspliced tumors, with an 80% or greater increase in mortality for WNT, SHH and Group 3 medulloblastomas.

Figure 2. Unsupervised Clustering of Splice Indices Identifies Four Subgroups of Medulloblastomas

(a) Unsupervised Hierarchical Clustering (HCL) of the top 1000 probe sets with the highest standard deviation across Splice Index (SI) values generates robust clustering of four core medulloblastoma subgroups with two normal cerebella clusters. (b) Non-Negative Matrix Factorization using the same 1000 probe sets used for HCL clustering produces the highest support (cophenetic correlation) for 7 subgroups. (c) Non-Negative Matrix Factorization demonstrates 7 core subgroups composed of the adult and fetal normal samples, the corresponding four subgroups identified by HCL, and one additional subgroup composed of a small set of SHH medulloblastomas (n=3). (d) Medulloblastoma subgroup-enriched alternative splicing events identified by SI and PAC analysis revealing events present in >50-70% of each subgroup.

Figure 3. Pathway and Gene Ontology analysis of Subgroup-Specific Splicing Events Identifies Recurrent Targeting of Cerebellar Development Pathways in non-WNT medulloblastomas

(a) Ingenuity Pathway Analysis (IPA) of the top ten pathways affected by alternative splicing across each molecular subgroup of medulloblastoma. Known signaling pathways: such as Tight junction signaling (WNT, P<1.49E-2) and CREB signaling (SHH, P<1.70E-4) were identified in our analysis as well as an abundance of neuronal pathways in non-WNT medulloblastomas. (b) Cytoscape BINGO analysis of the significant Gene Ontologies (GO) targeted by alternative splicing in Group 3 tumors, after subtracting events present in the normal cerebella, identifies neuronal pathways targeting axonogenesis and glutamatergic synaptic transmission.

Figure 4. Validation of Subgroup-Specific Hallmark Alternative Splicing Events in Medulloblastoma

(a) Exon array RMA signal intensity plots of highly frequent and subgroup-specific alternative transcripts. Alternative promoter usage generates a WNT-specific 3’ isoform of INADL, while alternative promoter usages in Group 3 and Group 4 tumors produce known isoforms of CHN2 and NBEA, respectively. SNAP25 demonstrates subgroup-specific expression of a known exon cassette with Fetal and non-WNT medulloblastomas expressing elevated levels of SNAP25a and Adult and WNT tumors expressing higher levels of SNAP25b. (b) Primers generated against the 5’ and 3’ gene regions of the full transcript were used to assess the intra-transcript variability. A transcript ratio, based on the 3’:5’ expression, was calculated and normalized to normal fetal cerebella permitting the identification of subgroup specific isoform expression. For each of the reported genes we observe the expected isoform expression restricted to the predicted subgroups.

Figure 5. Sense-Antisense Transcription Correlates with Alternative Splicing in Medulloblastoma

(a) Schematic of sense-antisense (S-AS) transcription depicting overlapping genes on opposing strands with concomitant expression. A switch in the predominant sense-strand isoform occurs in the context of antisense transcription. (b) Analysis of MAB21L1 transcription (antisense gene) and correlated NBEA (sense gene) alternative splicing events. The splice index values of 38 NBEA 5’ exons are inversely correlated with expression of MAB21L1 (i.e. these exons are excluded from the NBEA isoform when MAB21L1 is expressed). Conversely, the 22 3’ exons have splice index values that are positively correlated to MAB21L1 expression (i.e. these exons are included in the NBEA isoform when MAB21L1 is expressed). (c) Examples of S-AS gene pairs demonstrating inverse relationships between sense strand exon inclusion and antisense strand transcription. These correlations demonstrate mixed medulloblastomas (C13ORF3-MRP63) or subgroup-enriched (DDX31-GTF3C4, Group 3 & Group 4) patterns suggesting S-AS events may play a critical role in normal development (SLC26A10-B4GALNT, Normal CB) and the pathogenesis of medulloblastoma.