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• Gut microbiota analysis after 3months probiotic-like bacteria or placebo treatment in subjects with metabolic syndrome

  Background: Probiotic-like bacteria treatment has been described to be associated with gut microbiota modifications. Goal: To decipher if the effects of the tested probiotic-like bacteria are due to the bacteria itself or due to the effects of the bacteria on the gut microbiota. Methodology: In this study, gut microbiota has been analyzed from feces samples of subjects with metabolic syndrome and treated with one of the 2 tested probiotic-like bacteria or with the placebo during 3months.

  Study EGAS00001003585

• We performed an integrative analysis to determine genomic aberrations common to sporadic schwannomas.

  Schwannomas are common peripheral nerve sheath tumors that can cause significant debilitating morbidities. We performed an integrative analysis to determine genomic aberrations common to sporadic schwannomas. Exome sequence analysis with validation by targeted DNA-sequencing of 125 samples uncovered, in addition to expected NF2 disruption additional recurrent mutations. RNA sequencing identified a recurrent in-frame SH3PXD2A-HTRA1 fusion in 12/125 (10%) cases, and genomic analysis demonstrated the mechanism as resulting from a balanced 19Mb chromosomal inversion on chromosome 10q.

  Study EGAS00001001886

• Discovering genetic causes of optic atrophy syndromes through whole exome sequencing

  The genetic defects leading to optic atrophy range from mitochondrial DNA (mtDNA) point mutations in Leber’s hereditary optic neuropathy (LHON), to dominant and recessive mutations affecting a cluster of nuclear genes implicated in mitochondrial dynamics. We performed WES in patients with an optic atrophy spectrum disorder, including retinal macular dystrophy and kidney insufficiency leading to transplantation, associated with mitochondrial DNA (mtDNA) depletion without accumulation of multiple deletions, to identify the genetic causes of this syndrome.

  Study EGAS00001003850

• Transcriptome profiling of three giant cell tumour of bone cell lines

  Transcriptome profiling of three established giant cell tumour of bone (GCTB) cell lines on the BGISEQ-500 platform (PE100). Cell lines consist of neoplastic "stromal" cells harboring a heterozygous H3F3A p.G34W mutation. Data was used in a study (Venneker et al., Histone deacetylase inhibitors as a therapeutic strategy to eliminate neoplastic “stromal” cells from giant cell tumors of bone, 2022) to determine H3F3A-WT/MT expression ratios, to identify pathogenic variants, and to examine the expression levels of epigenetic modifiers and regulators.

  Study EGAS00001006441

• RNAseq - Discovery of resistance mechanisms to the BRAF inhibitor vemurafenib in metastatic BRAF mutant melanoma

  We propose to biopsy 20 consented BRAF mutant melanoma patients at Addenbrooke's Hospital pre-treatment with vemurafenib and also upon the development of resistant disease, with the aim of using exome sequence and SNP6 data to identify novel sequence variants and copy number alterations that can be used to validate observed resistance mechanisms in our cell line models and also to use these models to inform as to likely candidate small molecule inhibitors to overcome resistance and that could be tested in the clinical trial setting.

  Dataset EGAD00001001050

• Discovery of resistance mechanisms to the BRAF inhibitor vemurafenib in metastatic BRAF mutant melanoma

  We propose to biopsy 20 consented BRAF mutant melanoma patients at Addenbrooke's Hospital pre-treatment with vemurafenib and also upon the development of resistant disease, with the aim of using exome sequence and SNP6 data to identify novel sequence variants and copy number alterations that can be used to validate observed resistance mechanisms in our cell line models and also to use these models to inform as to likely candidate small molecule inhibitors to overcome resistance and that could be tested in the clinical trial setting.

  Dataset EGAD00001001046

• Genomic Factors Involved in Chromosome Rearrangements

  Approximately 15-20% of children referred for chromosomal microarray analysis (CMA) testing have a clinically relevant CNV that in many cases explains their phenotype. The goal of this study is to discover the genomic factors that mediate chromosome rearrangements and the phenotypic effects of chromosome rearrangements. We hypothesize that particular DNA sequences are susceptible to breakage and rearrangement. To this end, we fine-map chromosome breakage sites and analyze the DNA motifs that underlie double-strand breaks (DSBs). Our studies will also capture the genomic structure of breakpoint junctions, which will allow us to determine the mechanisms of DNA repair that shape different types of chromosome rearrangements. We also correlate chromosome rearrangements with clinical features to establish genotype-phenotype correlations. Defining critical regions of deletion or duplication is the first step to identifying candidate genes responsible for particular phenotypes.

  Study phs000845

• Genome-Wide Association Study of Relapse of Childhood Acute Lymphoblastic Leukemia

  Using risk-directed therapy for childhood acute lymphoblastic leukemia (ALL), outcome has improved dramatically in the last 40 years. However, a substantial portion of patients experience relapse, many of whom have no known risk factors. Taking a genome-wide approach, we sought to evaluate the relationships between germline SNP genotypes and the risk of relapse in 2,535 children with newly diagnosed ALL after adjusting for genetic ancestry and treatment regimen. We examine prognostic value of selected SNPs in the context of known relapse risk factors (molecular subtypes, minimal residual disease, age and leukocyte count at diagnosis). Associations of relapse-related SNPs with pharmacokinetic and pharmacodynamics of antileukemic drugs offer plausible mechanism by which they are linked to treatment outcome. Finally, we aim to identify SNPs that are related to both genetic ancestry and relapse which are likely to contribute to racial disparities in ALL survival.

  Study phs000638

• Single-cell analysis reveals different age-related somatic mutation profiles between stem and differentiated cells in human liver

  Highly metabolic liver is exposed to many sources of spontaneous mutagenesis resulting in increased genome instability that, potentially, causes age-related functional liver failure. Here we comparatively characterize the somatic mutational landscape in single human liver cells from individuals of various ages. Mutation frequency is very high in normal human hepatocytes, increasing dramatically with age as compared to other tissues and cell types, e.g., B-cells, neurons, and clonal surrogates of various adult stem cells. Moreover, differentiated hepatocytes tend to accumulate more mutations compared to age-matched proliferating liver stem cells (LSCs). Mutation spectra also differ dramatically between different cell types. Elevated oxidative hallmarks are observed in mouse liver and ex vivo cultured LSCs, but not during liver aging. Overall, human liver is prone to high age-dependent genome instability, compared to other tissues, and reveals functional difference between LSCs and hepatocytes.

  Study phs001956

• PDAC Prognosis Biomarkers in Genomic and Transcriptomic Molecular Data

  Our study was designed to identify biomarkers related to the prognosis of Pancreatic Ductal AdenoCarcinoma (PDAC) patients using genomic variants and gene expression in coding regions of the human genome (exome). PDAC is the 7th cause of cancer deaths and is among types of cancer having the poorest prognosis. To improve treatment outcomes of PDAC, biomarkers related to PDAC prognosis are needed. The goals of our study are to find genomic and transcriptomic biomarkers, which can classify prognosis subtype of PDAC patients, and eventually to predict subtypes or prognosis for each patient. In this study, we generated Whole Exome Sequencing (WES) and exome capture RNA sequencing data of 450 tumor and matched normal samples from 150 PDAC patients. Our data may be useful for understanding genomic and transcriptomic features, prognosis prediction, and precision medicine for PDAC.

  Study phs002347