SUMMARY While molecular subgrouping has revolutionized medulloblastoma classification, the extent of heterogeneity within subgroups is unknown. Similarity network fusion (SNF) applied to genome-wide DNA methylation and gene expression data across 763 primary samples identifies very homogeneous clusters of patients, supporting the presence of medulloblastoma subtypes. After integration of somatic copy-number alterations, and clinical features specific to each cluster, we identify 12 different subtypes of medulloblastoma. Integrative analysis using SNF further delineates group 3 from group 4 medulloblastoma, which is not as readily apparent through analyses of individual data types. Two clear subtypes of infants with Sonic Hedgehog medulloblastoma with disparate outcomes and biology are identified. Medulloblastoma subtypes identified through integrative clustering have important implications for stratification of future clinical trials.
Summary Medulloblastoma, the most common malignant pediatric brain tumour, is currently treated with non-specific cytotoxic therapies including surgery, whole brain radiation, and aggressive chemotherapy. As medulloblastoma exhibits marked intertumoural heterogeneity, with at least four distinct molecular variants, prior attempts to identify targets for therapy have been underpowered due to small samples sizes. Here we report somatic copy number aberrations (SCNAs) in 1087 unique medulloblastomas. SCNAs are common in medulloblastoma, and are predominantly subgroup enriched. The most common region of focal copy number gain is a tandem duplication of the Parkinson’s disease gene SNCAIP, which is exquisitely restricted to Group 4α. Recurrent translocations of PVT1, including PVT1-MYC and PVT1-NDRG1 that arise through chromothripsis are restricted to Group 3. Numerous targetable SCNAs, including recurrent events targeting TGFβ signaling in Group 3, and NF-κB signaling in Group 4 suggest future avenues for rational, targeted therapy.
Grade II and III gliomas are generally slowly progressing brain cancers, many of which eventually transform into more aggressive tumors. Despite recent findings of frequent mutations in IDH1 and other genes, knowledge about their pathogenesis is still incomplete. Here, combining two large sets of high-throughput sequencing data, we delineate the entire picture of genetic alterations and affected pathways in these glioma types, with sensitive detection of driver genes. Grade II and III gliomas comprise three distinct subtypes characterized by discrete sets of mutations and distinct clinical behaviors. Mutations showed significant positive and negative correlations and a chronological hierarchy, as inferred from different allelic burdens among coexisting mutations, suggesting that there is functional interplay between the mutations that drive clonal selection. Extensive serial and multi-regional sampling analyses further supported this finding and also identified a high degree of temporal and spatial heterogeneity generated during tumor expansion and relapse, which is likely shaped by the complex but ordered processes of multiple clonal selection and evolutionary events.
Telomerase is a specialized type of reverse transcriptase which catalyzes the synthesis and extension of telomeric DNA (for review, see ref.1). This enzyme is highly active in most cancer cells, but is inactive in most somatic cells. This striking observation led to the suggestion that telomerase might be important for the continued growth or progression of cancer cells. However, little is known about the molecular mechanism of telomerase activation in cancer cells. Human telomerase reverse transcriptase (hTRT) has recently been identified as a putative human telomerase catalytic subunit. We transfected the gene encoding hTRT into telomerase-negative human normal fibroblast cells and demonstrated that expression of wild-type hTRT induces telomerase activity, whereas hTRT mutants containing mutations in regions conserved among other reverse transcriptases did not. Hepatocellular carcinoma (20 samples) and non-cancerous liver tissues (19 samples) were examined for telomerase activity and expression of hTRT, the human telomerase RNA component (hTR; encoded by TERC) and the human telomerase-associated protein (hTLP1; encoded by TEP1). A significant correlation between hTRT expression and telomerase activity was observed. These results indicate that the hTRT protein is the catalytic subunit of human telomerase, and that it plays a key role in the activation of telomerase in cancer cells.
SUMMARY We recently reported that atypical teratoid rhabdoid tumors (ATRTs) comprise at least two transcriptional subtypes with different clinical outcomes; however, the mechanisms underlying therapeutic heterogeneity remained unclear. In this study, we analyzed 191 primary ATRTs and 10 ATRT cell lines to define the genomic and epigenomic landscape of ATRTs and identify subgroup-specific therapeutic targets. We found ATRTs segregated into three epigenetic subgroups with distinct genomic profiles, SMARCB1 genotypes, and chromatin landscape that correlated with differential cellular responses to a panel of signaling and epigenetic inhibitors. Significantly, we discovered that differential methylation of a PDGFRB-associated enhancer confers specific sensitivity of group 2 ATRT cells to dasatinib and nilotinib, and suggest that these are promising therapies for this highly lethal ATRT subtype.
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