SMARCB1 (also known as SNF5, INI1, and BAF47), a core subunit of the SWI/SNF (BAF) chromatin-remodeling complex, is inactivated in nearly all pediatric rhabdoid tumors. These aggressive cancers are among the most genomically stable, suggesting an epigenetic mechanism by which SMARCB1 loss drives transformation. Here we show that, despite having indistinguishable mutational landscapes, human rhabdoid tumors exhibit distinct enhancer H3K27ac signatures, which identify remnants of differentiation programs. We show that SMARCB1 is required for the integrity of SWI/SNF complexes and that its loss alters enhancer targeting-markedly impairing SWI/SNF binding to typical enhancers, particularly those required for differentiation, while maintaining SWI/SNF binding at super-enhancers. We show that these retained super-enhancers are essential for rhabdoid tumor survival, including some that are shared by all subtypes, such as SPRY1, and other lineage-specific super-enhancers, such as SOX2 in brain-derived rhabdoid tumors. Taken together, our findings identify a new chromatin-based epigenetic mechanism underlying the tumor-suppressive activity of SMARCB1.

Translocation events are frequent in cancer and may create chimeric fusions or 'regulatory rearrangements' that drive oncogene overexpression. Here we identify super-enhancer translocations that drive overexpression of the oncogenic transcription factor MYB as a recurrent theme in adenoid cystic carcinoma (ACC). Whole-genome sequencing data and chromatin maps highlight distinct chromosomal rearrangements that juxtapose super-enhancers to the MYB locus. Chromosome conformation capture confirms that the translocated enhancers interact with the MYB promoter. Remarkably, MYB protein binds to the translocated enhancers, creating a positive feedback loop that sustains its expression. MYB also binds enhancers that drive different regulatory programs in alternate cell lineages in ACC, cooperating with TP63 in myoepithelial cells and a Notch program in luminal epithelial cells. Bromodomain inhibitors slow tumor growth in ACC primagraft models in vivo. Thus, our study identifies super-enhancer translocations that drive MYB expression and provides insight into downstream MYB functions in alternate ACC lineages.

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.

We introduce an approach to identify disease-relevant tissues and cell types by analyzing gene expression data together with genome-wide association study (GWAS) summary statistics. Our approach uses stratified linkage disequilibrium (LD) score regression to test whether disease heritability is enriched in regions surrounding genes with the highest specific expression in a given tissue. We applied our approach to gene expression data from several sources together with GWAS summary statistics for 48 diseases and traits (average N = 169,331) and found significant tissue-specific enrichments (false discovery rate (FDR) < 5%) for 34 traits. In our analysis of multiple tissues, we detected a broad range of enrichments that recapitulated known biology. In our brain-specific analysis, significant enrichments included an enrichment of inhibitory over excitatory neurons for bipolar disorder, and excitatory over inhibitory neurons for schizophrenia and body mass index. Our results demonstrate that our polygenic approach is a powerful way to leverage gene expression data for interpreting GWAS signals.