3450 results for "*geneti*"

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• Sequencing probands and families with severe insulin resistance syndromes

  This is an ongoing project and continuation to all the sequencing we have been doing over the last few years. We have some additional families and probands with syndromes of insulin resistance not previously sequenced within uk10k or other core funded projects. We would like to complete the sequencing in all of the good quality families and probands we have, this would require another ~50 samples to be WES sequenced. This cohort has already proven to be a rich source of interesting findings with papers in Science and Nature genetics.

  Dataset EGAD00001000694

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

  Discovery of resistance mechanisms to the BRAF inhibitor vemurafenib in metastatic BRAF mutant melanoma by massively-parallel sequencing of tumour samples. Comparison of genomic characteristics of pretreatment 'sensitive' to recurrence 'resistant' tumours to identify the genetics of drug resistance.

  Dataset EGAD00001000707

• Whole genome sequencing of Italian genetic isolates -Friuli Venezia Giulia

  Low coverage whole genome sequencing of samples from individuals from Friuli Venezia Giulia, an Italian genetic isolate population.

  Dataset EGAD00001000728

• High-powered complex trait association mapping through whole genome sequencing of a selected subpopulation of the INGI-Val Borbera genetic isolate

  The VBSEQ project aims to combine available extensive genetic and phenotypic data to the latest high-throughput genome sequencing technology and ad hoc statistical analysis to identify new rare genetic variants underlying complex traits. Up to 100 Val Borbera samples will be sequenced to a 6x depth.

  Dataset EGAD00001000730

• Whole Genome sequencing of individuals from Val Borbera, Italy

  This study includes Phase 2 whole-genome sequencing data (at 4x depth)of 100 individuals from an Italian genetic isolate population (Val Borbera, abbreviated VBI) of the Italian Network of Genetic Isolates (INGI). The INGI-VBI_SEQ2 project aims to combine available extensive genetic and phenotypic data to the latest high-throughput genome sequencing technology and ad hoc statistical analysis to identify new rare genetic variants underlying complex traits.

  Dataset EGAD00001000731

• RRBS data of 48 individuals of the Dutch Hunger Winter Families Study

  The dataset entails 48 RRBS libraries of 24 siblings. 24 individuals are conceived during the Dutch Famine, a severe 6 month famine at the end of World War 2. A same sex sibling was added as a control, allowing partial matching for (early) familial environment and genetics.

  Dataset EGAD00001000733

• Integrated genomic characterization of adrenocortical carcinoma

  Adrenocortical carcinomas (ACC) are aggressive cancers originating in the cortex of the adrenal glands. Despite the overall poor prognosis, ACC outcome is heterogeneous. CTNNB1 and TP53 mutations are frequent in these tumors, but the complete spectrum of genetic changes remains undefined. Exome sequencing and SNP array analysis of 45 ACC revealed recurrent alterations in known drivers (CTNNB1, TP53, CDKN2A, RB1, MEN1) and genes not previously reported to be altered in ACC (ZNRF3, DAXX, TERT and MED12), which were validated in an independent cohort of 77 ACC. The cell-surface transmembrane E3 ubiquitin ligase ZNRF36 was the gene the most frequently altered (21%), and appears as a potential novel tumor suppressor gene related to the ß-catenin pathway.Our integrated genomic analyses led to the identification of two distinct molecular subgroups with opposite outcome. The C1A group of poor outcome ACC was characterized by numerous mutations and DNA methylation alterations, whereas the C1B group with good prognosis displayed a specific deregulation of two miRNA clusters. Thus, aggressive and indolent ACC correspond to two distinct molecular entities, driven by different oncogenic alterations.

  Dataset EGAD00001000764

• Whole Genome sequencing of individuals from Carlantino, Italy

  This study includes whole-genome sequencing data (at 4x depth) of 100 individuals from an Italian genetic isolate population (Carlantino, abbreviated CARL) of the Italian Network of Genetic Isolates (INGI). The INGI-CARL_SEQ project aims to combine available extensive genetic and phenotypic data to the latest high-throughput genome sequencing technology and ad hoc statistical analysis to identify new rare genetic variants underlying complex traits.

  Dataset EGAD00001000774

• Bone Cancer - Rare Types Whole Genome

  We propose to definitively characterise the somatic genetics of a selection of rare bone cancers through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing.

  Dataset EGAD00001000785

• Assessment of genetic and epigenetic variation in human IPS cells

  In order to progress human induced pluripotent stem cells (hiPSCs) towards the clinic, several outstanding questions must be addressed. It is possible to reprogram different somatic cell types into hiPSCs but it is unclear whether some cell types carry through fewer mutations through reprogramming (either due to mutations present in the primary cells, or mutations accumulated during reprogramming). Through in depth analysis of hiPSCs generated from different somatic cells, it will be possible to assess the variation in genetic stability of different cell types.

  Dataset EGAD00001000798

• Role of Epigenetic Memory in Human Induced Pluripotent Stem Cells Pilot

  Fibroblasts have been shown to re-program into induced pluripotent stem (hiPS) cells, through over-expression of pluripotency genes. These hiPS cells show similar characteristics to embryonic stem cells including cell surface markers, epigenetic changes and ability to differentiate into the three germ layers. However it is unclear as to the extent of changes in gene expression through the re-programming process.. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001000828

• Osteosarcoma RNAseq

  We propose to definitively characterise the somatic genetics of Osteosarcoma cancer through generation of comprehensive catalogues of somatic mutations by high coverage genome and transcriptome sequencing.

  Dataset EGAD00001000826

• Assessment of epigenetic variation in human iPS cells-Medip

  n order to progress human induced pluripotent stem cells (hiPSCs) towards the clinic, several outstanding questions must be addressed. It is possible to reprogram different somatic cell types into hiPSCs and from studies in the mouse, it appears that an epigenetic memory of the starting cell type is carried over to hiPSCs. However a comprehensive comparative study of the characteristics of these hiPSCs has been missing from the literature. Importantly studies which aimed to address these aspects of hiPSCs have used cells from different patients. In order to avoid this important confounding variable and to keep the genetic background constant, tissue samples were procured from the patients and reprogrammed to iPS cells. The methylation status of these iPS cells will be compared. Protocol: Primary cell cultures were generated and reprogrammed to iPS cells. DNA was extracted and immunoprecipitated using anti-methyl cytosine and anti-hydroxymethyl cytosine antibodies. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001000827

• Combination therapies for personalized cancer medicine

  It is the ambition of the team formed by members of the Netherlands Cancer Institute (NKI) and the Cancer Genome Project at the Wellcome Trust Sanger Institute (WTSI) to unravel the genomic and phenotypic complexity of human cancers in order to identify optimal drug combinations for personalized cancer therapy. Our integrated approach will entail (i) deep sequencing of human tumours and cognate mouse tumours; (ii) drug screens in a 1000+ fully characterized tumour cell line panel; (iii) high-throughput in vitro and in vivo shRNA and cDNA drug resistance and enhancement screens; (iv) computational analysis of the acquired data, leading to significant response predictions; (v) rigorous validation of these predictions in genetically engineered mouse models and patient-derived xenografts. This integrated effort is expected to yield a number of combination therapies and companion-diagnostics biomarkers that will be further explored in our existing clinical trial networks.

  Dataset EGAD00001000869

• FinHer Breast Cancer Study

  The purpose of this study is to sequence 500 known cancer genes in 960 newly diagnosed high risk breast cancer patients treated with current standard of care therapies and trastuzumab, for somatic alteration and copy number changes. We will be using next gen sequencing technology to determine the prognostic relevance of these somatic genetic alterations and of teh low frequency events to determine if they are associated with trastuzumab benefit or HER2 positive breast cancer, i.e. treatment interaction. The samples will be analysed adn correlated with clinical variables including outcome.

  Dataset EGAD00001000871

• RNA-Seq files accompanying Genetic landscape of pediatric Rhabdomyosarcoma

  RNA-Seq files accompanying Genetic landscape of pediatric Rhabdomyosarcoma

  Dataset EGAD00001000878

• Exome sequencing of serially transplanted genetically marked IC-enriched primary PDAC cultures.

  In order to elucidate whether newly acquired genetic alterations during serial transplantation of patient derived primary pancreatic cancer cultures contribute to the observed clonal dynamics in vivo, all coding genes of two patient derived primary cultures and derived genetically marked serial xenografts (1°/2°/3°) were sequenced.

  Dataset EGAD00001000884

• NSCLC WGS

  NSCLC WGS.

  Dataset EGAD00001000888

• Metastatic Breast Cancer Whole Genome

  We propose to definitively characterise the somatic genetics of Metastatic breast cancer through generation of comprehensive catalogues of somatic mutations in Metastatic breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001000899

• ICGC Prostate Cancer Whole Genome Sequencing

  To characterize the subclonal genomic architecture of androgen-deprived metastatic prostate cancer, we performed whole-genome sequencing (WGS) of 51 tumours from 10 patients to an average sequencing depth of 55x, including multiple metastases from different anatomic sites in each patient and, in five cases, the prostate tumour. Noncancerous DNA from blood or other tissue is used as reference comparison for each patient. The patients are part of PELICAN (Project to ELIminate Lethal Cancer) rapid autopsy study led by G. Steven Bova at Johns Hopkins University (USA) and Tampere University (Finland). As of September 2020, some of the studies using these data include: Gundem et al, Nature 2015 (PMID: 25830880). Additional EGAD00001000891 sample metadata is contained in Supplementary Information in this report.Tubio et al, Science 2014 (PMID: 25082706) Behjati et al, Nature Comm 2015 (PMID: 27615322) Wedge et al, Nature Genetics 2018 (PMID: 29662167)Pan-Cancer Analysis of Whole Genomes, Nature 2020 (PMID: 32025007)Rodriguez-Martin et al, Nature Genetics 2020 (PMID: 32024998)Woodcock et al, Nature Comm 2020 (In Press)

  Dataset EGAD00001000891

• ICGC Prostate Cancer Whole Genome Sequencing

  Whole Genome Sequencing Illumina HiSeq data from 20 men with prostate cancer. 20 samples were taken from primary tissue obtained at prostatectomy (target sequencing depth 50X) with matched blood control (target sequencing depth 30X). These were submitted for use in the ICGC Pan-Cancer Analysis of Whole Genomes project. Same raw data submitted in EGAD00001001116. As of September 2020, some of the studies using these data include: Wedge et al, Nature Genetics 2018 (PMID: 29662167) Pan-Cancer Analysis of Whole Genomes, Nature 2020 (PMID: 32025007)

  Dataset EGAD00001000892

• Subclonal diversification of primary breast cancer

  Cancers are ecosystems of genetically related clones, competing across space and time for limited resources. To understand the clonal structure of primary breast cancer, we applied genome and targeted sequencing to 295 samples from 49 patients’ tumors. The extent of subclonal diversification varied considerably among patients and encompassed many spatial patterns, including local growth, intraductal dissemination and clonal intermixture. Landmarks of disease progression, such as acquiring invasive or metastatic potential, arose within detectable subclones of antecedent lesions, suggesting that subclonal mutations could be relevant if actionable. No defined temporal order of mutation was evident, with the commonest genes, including PIK3CA, TP53, BRCA2, PTEN and MYC, mutated early in some, late in others, often exhibiting parallel evolution across subclones. Signatures of homologous recombination deficiency correlated with response to neoadjuvant chemotherapy. Thus, the interplay of mutation, growth and competition drives clonal structures of breast cancer that are complex, variable across patients and clinically relevant.

  Dataset EGAD00001000898

• Subclonal diversification of primary breast cancer

  Cancers are ecosystems of genetically related clones, competing across space and time for limited resources. To understand the clonal structure of primary breast cancer, we applied genome and targeted sequencing to 295 samples from 49 patients’ tumors. The extent of subclonal diversification varied considerably among patients and encompassed many spatial patterns, including local growth, intraductal dissemination and clonal intermixture. Landmarks of disease progression, such as acquiring invasive or metastatic potential, arose within detectable subclones of antecedent lesions, suggesting that subclonal mutations could be relevant if actionable. No defined temporal order of mutation was evident, with the commonest genes, including PIK3CA, TP53, BRCA2, PTEN and MYC, mutated early in some, late in others, often exhibiting parallel evolution across subclones. Signatures of homologous recombination deficiency correlated with response to neoadjuvant chemotherapy. Thus, the interplay of mutation, growth and competition drives clonal structures of breast cancer that are complex, variable across patients and clinically relevant.

  Dataset EGAD00001000965

• Harnessing transposons for drug resistance gene discovery in cancer

  This study involves a forward genetic screen to identify common insertion sites in drug resistant clones. We will be utilising piggybac transposon systems in order to generate multiple drug resistant clones in a range of human cancer cell lines.

  Dataset EGAD00001000980

• Multi-omics analysis defines core genomic alterationsin pheochromocytomas and paragangliomas

  Pheochromocytomas and paragangliomas (PCC/PGL) are neural crest derived tumors with a very strong genetic component. We report the first integrated genomic portrayal of a large collection of PCC/PGL. SNP array analysis revealed distinct copy-number patterns associated with genetic background. Whole-exome sequencing showed a low mutation rate of 0.3 mutations per megabase, with few recurrent somatic mutations in genes not previously associated with PCC/PGL. DNA methylation arrays and miRNA sequencing identified DNA methylation changes and miRNA expression clusters strongly associated with mRNA expression profiling. Overexpression of the miRNA cluster 182/96/183 was specific of SDHB-mutated tumors and induced invasive traits, whereas silencing of the imprinted DLK1-MEG3 miRNA cluster appeared as a potential driver in a subgroup of sporadic tumors. Altogether, the complete genomic landscape of PCC/PGL is mainly driven by distinct germline and/or somatic mutations in susceptibility genes and reveals different molecular entities, characterized by a set of unique genomic alterations.

  Dataset EGAD00001000986