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• Medulloblastoma exome sequence analysis

  Medulloblastomas are the most common malignant brain tumors in children. Identifying and understanding the genetic events that drive these tumors is critical for the development of more effective diagnostic, prognostic and therapeutic strategies. Recently, our group and others described distinct molecular subtypes of medulloblastoma based on transcriptional and copy number profiles. Here, we utilized whole exome hybrid capture and Illumina sequencing to identify somatic mutations across the coding regions of 92 primary medulloblastoma/normal pairs. Overall, medulloblastomas exhibit low mutation rates consistent with other pediatric tumors, with a median of 0.35 non-silent mutations per megabase. We identified twelve genes mutated at statistically significant frequencies, including previously known mutated genes in medulloblastoma such as CTNNB1, PTCH1, MLL2, SMARCA4 and TP53. Recurrent somatic mutations were identified in an RNA helicase gene, DDX3X, often concurrent with CTNNB1 mutations, and in the nuclear co-repressor (N-CoR) complex genes GPS2, BCOR, and LDB1, to our knowledge novel findings in medulloblastoma and all cancer. We show that mutant DDX3X potentiates transactivation of a TCF promoter and enhances cell viability in combination with mutant but not wild type beta-catenin. Together, our study reveals the alteration of Wnt, Hedgehog, histone methyltransferase and now N-CoR pathways across medulloblastomas and nominates the RNA helicase DDX3X as a component of pathogenic beta-catenin signaling in medulloblastoma. "Reprinted from 'MEDULLOBLASTOMA EXOME SEQUENCING UNCOVERS SUBTYPE-SPECIFIC SOMATIC MUTATION', with permission from Nature"

  Study phs000504

• Multi-omic analysis of SDHB-related PCPG

  Hereditary SDHB-mutant pheochromocytomas (PC) and paragangliomas (PG) are rare tumours with a high propensity to metastasize although their clinical behaviour is unpredictable. To characterize the genomic landscape of these tumours and identify metastasis biomarkers, we performed multi-omic analysis on 94 tumours from 79 patients using six molecular methods including: whole-genome sequencing (WGS) of tumour and matched blood (n=94), whole transcriptome sequencing (RNA-seq) (n=91), small-RNA seq (n=90), DNA methylation profiling (n=93). Droplet-based (10x) single nuclei (sn)RNA-seq and snATAC-seq was applied to 9 and 7 cases, respectively. Additionally snATAC-seq was applied to one sample of normal adrenal medulla.

  Study EGAS50000000346

• Multiple Sclerosis risk variants regulate gene expression in innate and adaptive immune cells

  Each of at least 200 single nucleotide polymorphisms (SNPs) have been confirmed to be associated with individually small increases in the risk of Multiple Sclerosis (MS). A key function that could mediate SNP encoded MS risk is their regulatory effects on gene expression or splicing. Transcriptomic profiling was performed using Affymetrix gene-expression microarrays, using RNA extracted from purified human peripheral blood monocytes, CD4 and CD8 positive lymphocyte cells, B-lymphocyte cells and Natural Killer cells from 73 untreated MS cases and 97 healthy controls. Cis expression quantitative trait locus (eQTL) mapping studies were performed in each cell type separately to characterize MS risk loci associated with gene expression change.

  Study EGAS00001004087

• International Multi-Center ADHD Gene Project (IMAGE) II Case Sample

  This sample represents a collection of cases across a range of sites. All of these samples were ascertained for ADHD with most meeting criteria for combined type ADHD. The collection sites span Europe and America. Further details on the source and inclusion and exclusion information can be found in Neale et al. "Case-Control Genome-Wide Association of Attention-Deficit / Hyperactivity Disorder" J Am Acad Child Adolesc Psychiatry. 2010 September; 49(9): 906-920 PMID20732627. For online access to this manuscript see: PMC2928577.

  Study phs000407

• RNAseq Transcriptomic Analyses of European Ancestry Samples in MGS Dataset

  Schizophrenia is a common and severe psychotic disorder. While some common SNPs and rare copy number variants have been identified as being significantly associated with disease risk, the biological mechanisms remain undefined. To identify gene expression abnormalities in schizophrenia, we generated whole-genome gene expression profiles using RNAseq on lymphoblastoid cell lines from schizophrenia cases and controls of European ancestry. Subsets of these data have been used in three studies: (1) gene expression outliers (extreme tails of the distribution of transcript expression values) in 634 cases and 713 controls (PMID: 26022996); (2) baseline differential gene expression by affection status in 529 cases and 660 controls (PMID: 28418402); and (3) baseline versus dopamine stimulated differential gene expression by affection status in 514 cases and 690 controls (PMID: 30115913). Various classes of classes were enriched in the differentially expressed genes, especially brain expressed genes and genes related to immune processes.

  Study phs001932

• Molecular Basis of Neuroendocrine Prostate Cancer (Trento/Cornell/Broad 2015)

  A subset of advanced prostate cancers can progress from an androgen receptor (AR)-driven state to AR independence, often associated with low or absent AR expression and extensive neuroendocrine differentiation. Once neuroendocrine prostate cancer (NEPC) develops, patients typically demonstrate an aggressive clinical course and poor overall survival. Early diagnosis is important but remains challenging as the clinical and pathologic features associate with AR independence and NEPC are poorly defined. We performed whole exome sequencing of 114 metastatic tumors from 81 patients (35 with morphologic features of NEPC). Serial or synchronous samples were included to characterize heterogeneity and the transition from adenocarcinoma to NEPC. Computational analysis of clonality and allele specific quantification were performed using CLONET. Quantitative mRNA assessment including AR signaling genes and DNA methylation were evaluated in the context of genomic changes.

  Study phs000909

• Adipose transcriptome and plasma metabolome responses after a 6-day very-low energy fast in obesity: a single-arm feeding trial (FASTOMICS-6)

  Background: Fasting and ketogenic diets have gained popularity due to potential health benefits, in part via autophagy and other protective processes. However, although the basic physiology of fasting is well-established, we lack a deeper understanding of mechanisms on the tissue level and associated metabolome changes, particularly in humans. Method: 4 males and 9 females with severe obesity underwent a very-low-energy in-hospital feeding study (600 kcal/day). Plasma (n=13) and subcutaneous adipose tissue (sAT) samples (n=12) were collected in the morning before and after 6 days and analysed by GC-MS/MS and RNA-sequencing, respectively. Gene set enrichment analysis (GSEA) and weighted gene co-expression network analysis were used to identify biological pathways and modules of affected genes and their correlation with plasma ketones and metabolites.

  Study EGAS50000001015

• WES data from study: Molecular underpinnings of dedifferentiation and aggressiveness in chromophobe renal cell carcinoma

  The ChRCC study WES dataset contains raw whole exome sequencing data of 17 tumor and 7 adjacent normal samples from 7 UTSW patients, who have consented to depositing their genomic data to public repository. WES was performed using 75bp paired-end fragments at an average read depth > 100x on a HiSeq2500 platform (Illumina, San Diego, CA, USA). The raw data is in fastq format.

  Dataset EGAD50000000415

• Non-ADT METs ICGC Prostate UK

  To characterize the subclonal genomic architecture of non-androgen-deprived metastatic prostate cancer, we performed whole-genome sequencing (WGS) of pelvic lymph node metastases and matching noncancerous blood from 10 patients to an average sequencing depth of 55x. The patients are part of PELICAN (Project to ELIminate Lethal Cancer) study led by G. Steven Bova at Johns Hopkins University (USA) and Tampere University (Finland). As of September 2020, study using these data is: Wedge et al, Nature Genetics 2018 (PMID: 29662167)

  Dataset EGAD00001002002

• Analysis of tumor periphery and center-specific mutations in renal cell carcinoma

  Renal cell carcinoma (RCC) is a genomically heterogeneous tumor. In the present project, the question whether intratumoral heterogeneity follows a zonal pattern indicating spatial niches was addressed. Whole exome sequencing of 16 paired samples from tumor periphery and center revealed a number of region-specific functional SNVs and Indels. Therefore, RCCs are not composed of evenly admixed tumor cells but show topological differences in their clonal composition.

  Dataset EGAD00001002067