Tina Wong

The whole-genome landscape of medulloblastoma subtypes

Current therapies for medulloblastoma, a highly malignant childhood brain tumour, impose debilitating effects on the developing child, and highlight the need for molecularly targeted treatments with reduced toxicity. Previous studies have been unable to identify the full spectrum of driver genes and molecular processes that operate in medulloblastoma subgroups. Here we analyse the somatic landscape across 491 sequenced medulloblastoma samples and the molecular heterogeneity among 1,256 epigenetically analysed cases, and identify subgroup-specific driver alterations that include previously undiscovered actionable targets. Driver mutations were confidently assigned to most patients belonging to Group 3 and Group 4 medulloblastoma subgroups, greatly enhancing previous knowledge. New molecular subtypes were differentially enriched for specific driver events, including hotspot in-frame insertions that target KBTBD4 and ‘enhancer hijacking’ events that activate PRDM6. Thus, the application of integrative genomics to an extensive cohort of clinical samples derived from a single childhood cancer entity revealed a series of cancer genes and biologically relevant subtype diversity that represent attractive therapeutic targets for the treatment of patients with medulloblastoma.

Genome-Wide Profiles of Extra-cranial Malignant Rhabdoid Tumors Reveal Heterogeneity and Dysregulated Developmental Pathways

Malignant rhabdoid tumors (MRTs) are rare lethal tumors of childhood that most commonly occur in the kidney and brain. MRTs are driven by SMARCB1 loss, but the molecular consequences of SMARCB1 loss in extra-cranial tumors have not been comprehensively described and genomic resources for analyses of extra-cranial MRT are limited. To provide such data, we used whole-genome sequencing, whole-genome bisulfite sequencing, whole transcriptome (RNA-seq) and microRNA sequencing (miRNA-seq), and histone modification profiling to characterize extra-cranial MRTs. Our analyses revealed gene expression and methylation subgroups and focused on dysregulated pathways, including those involved in neural crest development.

Spatial heterogeneity in medulloblastoma

Spatial heterogeneity of transcriptional and genetic markers between physically isolated biopsies of a single tumor poses major barriers to the identification of biomarkers and the development of targeted therapies that will be effective against the entire tumor. We analyzed the spatial heterogeneity of multiregional biopsies from 35 patients, using a combination of transcriptomic and genomic profiles. Medulloblastomas (MBs), but not high-grade gliomas (HGGs), demonstrated spatially homogeneous transcriptomes, which allowed for accurate subgrouping of tumors from a single biopsy. Conversely, somatic mutations that affect genes suitable for targeted therapeutics demonstrated high levels of spatial heterogeneity in MB, malignant glioma, and renal cell carcinoma (RCC). Actionable targets found in a single MB biopsy were seldom clonal across the entire tumor, which brings the efficacy of monotherapies against a single target into question. Clinical trials of targeted therapies for MB should first ensure the spatially ubiquitous nature of the target mutation.

The expression level of small non‐coding RNAs derived from the first exon of protein‐coding genes is predictive of cancer status

Small non‐coding RNAs (smRNAs) are known to be significantly enriched near the transcriptional start sites of genes. However, the functional relevance of these smRNAs remains unclear, and they have not been associated with human disease. Within the cancer genome atlas project (TCGA), we have generated small RNA datasets for many tumor types. In prior cancer studies, these RNAs have been regarded as transcriptional “noise,” due to their apparent chaotic distribution. In contrast, we demonstrate their striking potential to distinguish efficiently between cancer and normal tissues and classify patients with cancer to subgroups of distinct survival outcomes. This potential to predict cancer status is restricted to a subset of these smRNAs, which is encoded within the first exon of genes, highly enriched within CpG islands and negatively correlated with DNA methylation levels. Thus, our data show that genome‐wide changes in the expression levels of small non‐coding RNAs within first exons are associated with cancer.