Medulloblastoma is a highly malignant paediatric brain tumour, often inflicting devastating consequences on the developing child. Genomic studies have revealed four distinct molecular subgroups with divergent biology and clinical behaviour. An understanding of the regulatory circuitry governing the transcriptional landscapes of medulloblastoma subgroups, and how this relates to their respective developmental origins, is lacking. Here, using H3K27ac and BRD4 chromatin immunoprecipitation followed by sequencing (ChIP-seq) coupled with tissue-matched DNA methylation and transcriptome data, we describe the active cis-regulatory landscape across 28 primary medulloblastoma specimens. Analysis of differentially regulated enhancers and super-enhancers reinforced inter-subgroup heterogeneity and revealed novel, clinically relevant insights into medulloblastoma biology. Computational reconstruction of core regulatory circuitry identified a master set of transcription factors, validated by ChIP-seq, that is responsible for subgroup divergence, and implicates candidate cells of origin for Group 4. Our integrated analysis of enhancer elements in a large series of primary tumour samples reveals insights into cis-regulatory architecture, unrecognized dependencies, and cellular origins.
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http://dx.doi.org/10.1038/nature16546 | DOI Listing |
World J Diabetes
January 2025
National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20810, United States.
Diabetes mellitus (DM) is a debilitating disorder that impacts all systems of the body and has been increasing in prevalence throughout the globe. DM represents a significant clinical challenge to care for individuals and prevent the onset of chronic disability and ultimately death. Underlying cellular mechanisms for the onset and development of DM are multi-factorial in origin and involve pathways associated with the production of reactive oxygen species and the generation of oxidative stress as well as the dysfunction of mitochondrial cellular organelles, programmed cell death, and circadian rhythm impairments.
View Article and Find Full Text PDFNanoscale Adv
January 2025
Université de Lorraine, CNRS, LRGP F-54000 Nancy France
Water-dispersible core/shell CuInZnSe/ZnS (CIZSe/ZnS) quantum dots (QDs) were efficiently synthesized under microwave irradiation using -acetylcysteine (NAC) and sodium citrate as capping agents. The photoluminescence (PL) emission of CIZSe/ZnS QDs can be tuned from 593 to 733 nm with varying the Zn : Cu molar ratio in the CIZSe core. CIZSe/ZnS QDs prepared with a Zn : Cu ratio of 0.
View Article and Find Full Text PDFACS Energy Lett
January 2025
Department of Chemistry and Centre for Processable Electronics, Molecular Sciences Research Hub, Imperial College London, London W12 0BZ, U.K.
Antisolvent treatment is used in the fabrication of perovskite films to control grain growth during spin coating. We study widely incorporated aromatic hydrocarbons and aprotic ethers, discussing the origin of their performance differences in 2D/3D Sn perovskite (PEAFASnI) solar cells. Among the antisolvents that we screen, diisopropyl ether yields the highest power conversion efficiency in solar cells.
View Article and Find Full Text PDFJ Extracell Vesicles
January 2025
IPMC, UMR7275 CNRS-UniCA, INSERM U1323, team certified "Laboratory of Excellence (LABEX) Distalz", Valbonne, France.
Emerging evidence indicates that autophagy is tightly connected to the endocytic pathway. Here, we questioned the role of presenilins (PSENs 1 and 2), previously shown to be involved in autophagy regulation, in the secretion of small endocytic-originating extracellular vesicles known as exosomes. Indeed, while wild-type cells responded to stimuli promoting both multivesicular endosome (MVE) formation and secretion of small extracellular vesicles (sEVs) enriched in canonical exosomal proteins, PSEN-deficient cells were almost unaffected to these stimuli.
View Article and Find Full Text PDFBioData Min
January 2025
The Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, 90069, USA.
Background: With recent advances in single cell technology, high-throughput methods provide unique insight into disease mechanisms and more importantly, cell type origin. Here, we used multi-omics data to understand how genetic variants from genome-wide association studies influence development of disease. We show in principle how to use genetic algorithms with normal, matching pairs of single-nucleus RNA- and ATAC-seq, genome annotations, and protein-protein interaction data to describe the genes and cell types collectively and their contribution to increased risk.
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