Medulloblastoma is the most common brain tumour in children; using whole-genome sequencing of tumour samples the authors show that the clinically challenging Group 3 and 4 tumours can be tetraploid, and reveal the expression of the first medulloblastoma fusion genes identified. Medulloblastoma is the most common malignant brain tumour in children. Four papers published in the 2 August 2012 issue of Nature use whole-genome and other sequencing techniques to produce a detailed picture of the genetics and genomics of this condition. Notable findings include the identification of recurrent mutations in genes not previously implicated in medulloblastoma, with significant genetic differences associated with the four biologically distinct subgroups and clinical outcomes in each. Potential avenues for therapy are suggested by the identification of targetable somatic copy-number alterations, including recurrent events targeting TGFβ signalling in Group 3, and NF-κB signalling in Group 4 medulloblastomas. Medulloblastoma is an aggressively growing tumour, arising in the cerebellum or medulla/brain stem. It is the most common malignant brain tumour in children, and shows tremendous biological and clinical heterogeneity1. Despite recent treatment advances, approximately 40% of children experience tumour recurrence, and 30% will die from their disease. Those who survive often have a significantly reduced quality of life. Four tumour subgroups with distinct clinical, biological and genetic profiles are currently identified2,3. WNT tumours, showing activated wingless pathway signalling, carry a favourable prognosis under current treatment regimens4. SHH tumours show hedgehog pathway activation, and have an intermediate prognosis2. Group 3 and 4 tumours are molecularly less well characterized, and also present the greatest clinical challenges2,3,5. The full repertoire of genetic events driving this distinction, however, remains unclear. Here we describe an integrative deep-sequencing analysis of 125 tumour–normal pairs, conducted as part of the International Cancer Genome Consortium (ICGC) PedBrain Tumor Project. Tetraploidy was identified as a frequent early event in Group 3 and 4 tumours, and a positive correlation between patient age and mutation rate was observed. Several recurrent mutations were identified, both in known medulloblastoma-related genes (CTNNB1, PTCH1, MLL2, SMARCA4) and in genes not previously linked to this tumour (DDX3X, CTDNEP1, KDM6A, TBR1), often in subgroup-specific patterns. RNA sequencing confirmed these alterations, and revealed the expression of what are, to our knowledge, the first medulloblastoma fusion genes identified. Chromatin modifiers were frequently altered across all subgroups. These findings enhance our understanding of the genomic complexity and heterogeneity underlying medulloblastoma, and provide several potential targets for new therapeutics, especially for Group 3 and 4 patients.

Extracellular vesicles (EVs) are reminiscent of their cell of origin and thus represent a valuable source of biomarkers. However, for EVs to be used as biomarkers in clinical practice, simple, comparable, and reproducible analytical methods must be applied. Although progress is being made in EV separation methods for human biofluids, the implementation of EV assays for clinical diagnosis and common guidelines are still lacking. We conducted a comprehensive analysis of established EV separation techniques from human serum and plasma, including ultracentrifugation and size exclusion chromatography (SEC), followed by concentration using (a) ultracentrifugation, (b) ultrafiltration, or (c) precipitation, and immunoaffinity isolation. We analyzed the size, number, protein, and miRNA content of the obtained EVs and assessed the functional delivery of EV cargo. Our results demonstrate that all methods led to an adequate yield of small EVs. While no significant difference in miRNA content was observed for the different separation methods, ultracentrifugation was best for subsequent flow cytometry analysis. Immunoaffinity isolation is not suitable for subsequent protein analyses. SEC + ultracentrifugation showed the best functional delivery of EV cargo. In summary, combining SEC with ultracentrifugation gives the highest yield of pure and functional EVs and allows reliable analysis of both protein and miRNA contents. We propose this combination as the preferred EV isolation method for biomarker studies from human serum or plasma.

Glioblastoma is a devastating disease, for which biomarkers allowing a prediction of prognosis are urgently needed. microRNAs have been described as potentially valuable biomarkers in cancer. Here, we studied a panel of microRNAs in extracellular vesicles (EVs) from the serum of glioblastoma patients and evaluated their correlation with the prognosis of these patients. The levels of 15 microRNAs in EVs that were separated by size-exclusion chromatography were studied by quantitative real-time PCR, followed by CD44 immunoprecipitation (SEC + CD44), and compared with those from the total serum of glioblastoma patients (n = 55) and healthy volunteers (n = 10). Compared to total serum, we found evidence for the enrichment of miR-21-3p and miR-106a-5p and, conversely, lower levels of miR-15b-3p, in SEC + CD44 EVs. miR-15b-3p and miR-21-3p were upregulated in glioblastoma patients compared to healthy subjects. A significant correlation with survival of the patients was found for levels of miR-15b-3p in total serum and miR-15b-3p, miR-21-3p, miR-106a-5p, and miR-328-3p in SEC + CD44 EVs. Combining miR-15b-3p in serum or miR-106a-5p in SEC + CD44 EVs with any one of the other three microRNAs in SEC + CD44 EVs allowed for a prognostic stratification of glioblastoma patients. We have thus identified four microRNAs in glioblastoma patients whose levels, in combination, can predict the prognosis for these patients.