Medulloblastomics: the end of the beginning

Abstract

The division of medulloblastoma into different subgroups by microarray expression profiling has dramatically changed our perspective of this malignant childhood brain tumour. Now, the availability of next-generation sequencing and complementary high-density genomic technologies has unmasked novel driver mutations in each medulloblastoma subgroup. The implications of these findings for the management of patients are readily apparent, pinpointing previously unappreciated diagnostic and therapeutic targets. In this Review, we summarize the 'explosion' of data emerging from the application of modern genomics to medulloblastoma, and in particular the recurrent targets of mutation in medulloblastoma subgroups. These data are currently making their way into clinical trials as we seek to integrate conventional and molecularly targeted therapies.

Figure 1. Meta-analysis of medulloblastoma next-generation sequencing studies

(a) Pie chart showing the molecular subgroup distribution within the combined discovery cohort of the three medulloblastoma sequencing studies (n=189)^-. (b) Venn diagram showing the number of mutated genes identified in the three next-generation sequencing studies of medulloblastoma (discovery cohorts, n=189) detailed in the text and the degree of overlap between them. Fifteen genes were commonly mutated in all three studies. (c) Frequency (%) and distribution of top candidate genes subject to recurrent non-synomonous mutation (SNV/indel) in medulloblastoma subgroups. Frequency is expressed as the percentage of affected cases within each subgroup and the denominator was dependent on the total number of cases screened for each individual gene (since not all genes were included in the targeted replication cohorts). Genes highlighted in bold were found to be mutated in each of the three sequencing studies. (d) Oncoprints showing the frequency and sample distribution of the most prevalent somatic mutations (SNVs/indels) and focal SCNAs within the medulloblastoma subgroups as determined in the four genomic studies described in the text^-, .

Figure 2. Novel mutations and genomic targets in medulloblastoma subgroups

Schematic representations of the most frequently targeted, novel candidate genes in medulloblastoma. Mutation positions are based on the three next-generation sequencing studies described in the text^-. Genes are depicted within the subgroup for which they show the greatest enrichment. In Group 3, the zoom box adjacent to MYC depicts the general structure of the recurrent PVT1-MYC fusion genes reported by Northcott et al. In Group 4, the zoom box adjacent to SNCAIP illustrates the general structure of the SNCAIP tandem duplications described by Northcott et al. Abbreviations: DEAD, DEAD domain; LIM, LIM domain; ANK, ankyrin repeat; HLH, helix-loop-helix domain; NIF, NLI interacting factor-like phosphatase; TPR, tetratricopeptide repeat; JmjC, Jumonji C domain; InDel, insertion/deletion.

Figure 3. Convergent deregulation of the histone code in medulloblastoma

Cartoon summarizing a selection of genes recurrently mutated and/or undergoing SCNA in medulloblastoma that are functionally associated with chromatin regulation. Both inactive heterochromatin and active euchromatin and the typical histone marks associated with these chromatin states are illustrated.

Figure 4. Correlation of cytogenetic alterations and somatic mutations within Group 3 and Group 4 medulloblastoma

Distribution of prevalent broad SCNAs and recurrent mutations (SNVs/indels) in Group 3 and 4 medulloblastomas. The majority of both Group 3 and Group 4 medulloblastomas are devoid of somatic mutations in any of the most recurrently mutated genes within these subgroups.