22938 results for "ega"

in 57.44 milliseconds.

• RNA-sequencing of a representative cohort of 209 AML cases

  Sample libraries were prepped using 500 ng of input RNA according to the KAPA RNA HyperPrep Kit with RiboErase (HMR) (Roche) using Unique Dual Index adapters (Integrated DNA Technologies, Inc.). Amplified sample libraries were paired-end sequenced (2x100 bp) on the Novaseq 6000 platform (Illumina) and aligned against the human genome (hg19) using STAR v2.5.4b2.

  Dataset EGAD00001007581

• scRNAseq of distal colon biopsies from patients with ulcerative colitis and healthy controls

  scRNAseq dataset of colonic epithelium from distal colon biopsies from 4 patients with ulcerative colitis and 4 healthy individuals. Includes 11 samples split into three conditions: healthy, healthy margin and ulcerated. Dataset includes raw Fastq files and processed csv count matrices. Fastq files are divided into 4 lanes and into index (I1) and read (R1, R2) files. Count matrices contain comma-separated values with cell barcodes as column names and gene names as row names. Cell Ranger (v3.0.1) software from 10x Genomics was used to process the output and align the reads. The refdata-cellranger-GRCh38-3.0.0 reference was downloaded from the 10x Genomics website. First, cellranger mkfastq function was used to demultiplex raw base call files into FASTQ files. Then, the FASTQ files were aligned and filtered with cellranger count function.

  Dataset EGAD00001010167

• Genomic characterisation of SDH deficient renal cell carcinoma - WGS

  SDH deficient renal cell carcinomas are a rare and recently defined subtype of kidney cancer, often associated with an inherited mutation in one of the SDH gene subunits. This dataset sought to understand the genomic events that underpin tumour formation, from putative cell of origin, characterisation of the tumour microenvironment, to the genomic evolution of these rare tumours. We performed whole genome and RNA sequencing of 4 patients with SDH deficient renal cell carcinomas, including one patient who had an additional paraganglioma. An addition patient in this cohort had the initial diagnosis revised to a clear cell renal cell carcinoma.

  Dataset EGAD00001008469

• Dataset for other_cancer-EXON

  Rare cancer sequencing data of 137 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008896

• Dataset for neuroendocrine_adrenal_tumor-EXON

  Rare cancer sequencing data of 164 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008891

• Sequence Data from the phase 2 PrE0505 trial of Durvalumab with First Line Platinum-Pemetrexed for Unresectable Pleural Mesothelioma

  Dataset comprises of 84 bam files from exome sequencing data, including 40 tumor-normal pairs and 4 normal files. Each sample is numbered by the patient case ID such as 135, 156 and so on. The filenames are suffixed with "_tumor" and "_normal" to indicate tumor and normal bam files respectively.

  Dataset EGAD00001008016

• IMCISION DNAseq

  Whole-exome sequencing of 32 primary head and neck squamous cell carcinoma samples prior to treatment with neoadjuvant anti-PD-1 (n=6) or anti-PD-1 + anti-CTLA-4 (n=26) immunotherapy. DNA quantity used: 50ng. Library Preparation Kit: Twist Human Core Exome Plus (Twist Bioscience). Sequencing parameters: NovaSeq 6000, 2x 100 bp. File type: fastQ.

  Dataset EGAD00001008139

• WGS of cell-free DNA derived from plasma of CRC patients and healthy controls, and WGS of matched tumor tissue and saliva

  This dataset contains: 1.) Whole-genome sequencing (WGS) data (~6x) of 259 cfDNA samples obtained from 50 colorectal cancer (CRC) patients and 61 healthy controls. Paired-end sequencing was performed with 2x101 bp reads on the NovaSeq 6000 system. Data is provided as mapped .bam files (aligned to GRCh38/hg38). 2.) WGS data (~1x) of 50 tumor biopsy and 45 saliva samples from CRC patients. Paired-end sequencing was performed with 2x101 bp reads on the NovaSeq 6000 system. Data is provided as mapped .bam files (aligned to GRCh38/hg38).

  Dataset EGAD00001009309

• Human and rat skeletal muscle multiomic profiling sequencing data

  Illumina sequencing data (fastq files) representing single-nucleus (sn) ATAC-seq, snRNA-seq, bulk ATAC-seq, and snATACseq+snRNAseq multiomics data from human and rat skeletal muscle samples (19 libraries total). Includes a README file that describes the relationship between libraries, samples, and files.

  Dataset EGAD00001008323

• Transcriptomic analyses of a large cohort of adult B cell acute lyphoblastic leukemia

  Total mononuclear cells (MNC) were isolated from peripheral blood (PB) or bone marrow (BM) samples of 105 Ph-/-/- (B-cell acute lymphoblastic leukemia [B-ALL] triple negative) and 31 Ph+ B-ALL adult patients using Lymphosep (Biowest, Nuaillé, France). A total of 15 samples from healthy subjects were processed including hematopoietic stem-progenitor cells (CD34+) from bone marrow specimens (n = 3), and bone marrow mononuclear cell samples (n = 3) from STEMCELL Technologies (Vancouver, Canada). PB MNC samples (n=5) and cord blood samples (n = 4). CD34+ cells were enriched from cord blood samples by immunomagnetic separation (CD34 MicroBead Kit, Miltenyi Biotec, Bergisch Gladbach, Germany).Libraries were prepared using the TruSight RNA Pan-Cancer Panel Kit (Illumina, San Diego, California, USA), following the manufacturer’s protocol. Sequencing was performed using the Illumina MiSeq instrument.

  Dataset EGAD00001010837

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 7a)

  Whole genome sequencing data of 36 high-grade serous carcinoma (HGSC) patients (89 samples) sequenced with HiSeq X Ten.

  Dataset EGAD00001010845

• Shallow whole genome sequencing

  This dataset contains a collection of tumour samples from high grade serous ovarian carcinoma patients with recurrent disease collected near the point of diagnosis as well as tumour samples collected after patient relapse upon or some time after study entry. The majority of diagnosis samples were preserved in neutral buffered formalin whereas the majority of post-relapse samples were preserved in universal molecular fixative (UMFIX, Sakura Finetek USA, Inc). DNA was extracted and whole genome sequencing libraries were prepared either using the TruSeq DNA Nano kit (Illumina) or the ThruPLEX DNA-Seq Kit (Takara Bio), which were respectively sequenced at low depth (~0.1-0.5X) on illumina HiSeq 2500 and HiSeq 4000 sequencing platforms. Sequenced reads were aligned to the GRCh37 reference genome (release hs37d5).

  Dataset EGAD00001011049

• A non-canonical lymphoblast in refractory childhood T cell leukaemia

  Refractory cancers may arise either through the acquisition of resistance mechanisms by cancer cells or represent distinct diseases. The origin of childhood T-cell acute lymphoblastic leukaemia (T-ALL) that does not respond to initial treatment, i.e. refractory disease, is unknown. Refractory T-ALL carries a poor prognosis and cannot be predicted at diagnosis. Here, we performed single cell mRNA sequencing of T-ALL from children who did or did not respond to initial treatment. We identified a transcriptionally distinctive blast population, exhibiting features of innate-like lymphocytes, as the major source of refractory disease. Evidence of such blasts at diagnosis heralded refractory disease across independent datasets and was associated with survival in a large, contemporary trial cohort. Our findings portray refractory T-ALL as a distinct disease. They may have immediate clinical utility.

  Dataset EGAD00001015381

• Single cell resolution landscape of hypomutated childhood cancers

  A paradigm of childhood cancers is that they have a low mutation burden, with some ostensibly bearing fewer mutations than the normal tissues from which they derive. We set out to resolve this paradox by examining paediatric renal cancers with exceptionally few mutations using high resolution, high depth sequencing approaches. We found that apparent hypomutation was the result of unusual clonal architecture due to a normal tissue-like mode of tumour evolution, raising the possibility that the mutation burden of some cancers has been systematically misjudged.

  Dataset EGAD00001015406

• Exploring the driver events of eccrine poromas and porocarcinomas: A retrospective, cross-institutional study of 90 cases

  Eccrine poroma (EP) and porocarcinoma (EPC) are rare benign and malignant adnexal neoplasms of the terminal sweat gland duct, respectively. Both can arise de novo, however, EPCs can also arise from a pre-existing EP. To-date, genetic investigation of these tumors has involved studies with small sample sizes and/or limited analyses. To comprehensively compare the driver events and mutational landscape of these tumors, we performed a retrospective multi-institutional whole-exome sequencing and RNA sequencing study on the largest cohort of EPs and EPCs to-date (n=90). We uncovered novel events and delineated different pathways of tumorigenesis underlying these tumors, with EPs driven largely by fusion genes, and EPCs driven largely by somatic mutations, with rare YAP1 and frequent PAK gene novel fusions.

  Dataset EGAD00001015377

• Targetable NOTCH1 rearrangements in reninoma

  Reninomas are exceedingly rare renin-secreting kidney tumours that derive from juxtaglomerular cells, specialised smooth muscle cells that reside at the vascular inlet of glomeruli. They are the central component of the juxtaglomerular apparatus which controls systemic blood pressure through the secretion of renin. We assessed somatic changes in reninoma and found structural variants that generate canonical activating rearrangements of NOTCH1, whilst removing its negative regulator, NRARP. Accordingly, in single reninoma nuclei we observed excessive renin and NOTCH1 signalling mRNAs, with a concomitant non-excess of NRARP expression. Re-analysis of previously published reninoma bulk transcriptomes further corroborates our observation of dysregulated Notch pathway signalling in reninoma. Our findings reveal NOTCH1 rearrangements in reninoma, therapeutically targetable through existing NOTCH1 inhibitors, and indicate that unscheduled Notch signalling may be a disease-defining feature of reninoma.

  Dataset EGAD00001010887

• Influence of culture media on airway differentiation at the Air-Liquid Interface

  Single-cell dataset of human airways after in vitro regeneration at the Air-Liquid Interface. Samples from 2 donors were used for the establishment of Human Bronchial Epithelial Cell cultures (HBECs) and were analyzed during proliferation, at the onset of differentiation (ALI0) and after full differentiation (ALI28), in 4 distinct culture media. Single-cell RNAseq was performed with 10x Genomics 3’ v2 RNA-seq using hashtag antibodies for multiplexing, and sequenced on a NextSeq 500. Samples from 3 additional donors were used for the establishment of Human Nasal Epithelial Cell cultures (HNECs) and were analyzed during proliferation in three distinct culture media. Single-cell RNAseq was performed with 10x Genomics 3’ v3 RNA-seq without multiplexing, and sequenced on a NextSeq 2000.

  Dataset EGAD00001011362

• Exploring the driver events of eccrine poromas and porocarcinomas: A retrospective, cross-institutional study of 90 cases

  Eccrine poroma (EP) and porocarcinoma (EPC) are rare benign and malignant adnexal neoplasms of the terminal sweat gland duct, respectively. Both can arise de novo, however, EPCs can also arise from a pre-existing EP. To-date, genetic investigation of these tumors has involved studies with small sample sizes and/or limited analyses. To comprehensively compare the driver events and mutational landscape of these tumors, we performed a retrospective multi-institutional whole-exome sequencing and RNA sequencing study on the largest cohort of EPs and EPCs to-date (n=90). We uncovered novel events and delineated different pathways of tumorigenesis underlying these tumors, with EPs driven largely by fusion genes, and EPCs driven largely by somatic mutations, with rare YAP1 and frequent PAK gene novel fusions.

  Dataset EGAD00001015379

• Direct transcriptional consequences of somatic mutation in breast cancer

  The disordered transcriptomes of cancer encompass direct effects of somatic mutation on transcription; co-ordinated secondary alterations in transcriptional pathways; and increased transcriptional noise. To catalogue the rules governing how somatic mutation Overall, 59% of 6980 exonic substitutions were expressed. Compared to other classes, nonsense mutations showed lower expression levels than expected with patterns characteristic of nonsense-mediated decay. 14% of 4234 genomic rearrangements caused transcriptional abnormalities, including exon skips, exon reusage, fusion transcripts and premature poly-adenylation. We found productive, stable transcription from sense-to-antisense gene fusions and gene-to-intergenic rearrangements, suggesting that these mutation classes may drive more transcriptional disruption than previously suspected. Systematic integration of transcriptome with genome data therefore reveals the rules by which transcriptional machinery interprets somatic mutation.

  Dataset EGAD00001002236

• Massive parallel RNA sequencing of highly purified mesenchymal cells derived from bone marrow specimens of 10 healthy donors

  Highly purified mesenchymal cells (CD45-/7AAD-/CD235a-/CD31-/CD271+/CD105+) were prospectively FACS-isolated from bone marrow specimens of 10 healthy donors (HDs). This data set is used as a baseline control to observe the differences between gene expression profiles (GEPs) of pre-leukemia cases (45 low-risk myelodysplastic syndrome, 4 Shwachman-Diamond and 3 Diamond-Blackfan anemia patients) and gene expression patterns observed in a normal, healthy context. Through differential expression and gene set enrichment analysis we determined that inflammatory signaling pathways are significantly more active in mesenchymal cells of pre-leukemia cases compared to their healthy counterparts. Finally, we determined through statistical modelling of healthy donor's GEPs which pre-leukemia cases have significantly more active inflammatory signaling and demonstrated a strong relation to survival statistics.

  Dataset EGAD00001002659

• MultiOMICS study of a pair of infant monozygotic twins with concordant B-cell ALL (WGBS)

  B-cell acute lymphoblastic leukemia (B-cell ALL) is the most common cancer in childhood. Studying identical twins with B-cell ALL provides a unique and tractable model for deciphering the developmental timing of pre- and post-natal mutations contributing to clonal evolution. To date, this has mainly focused on major cytogenetic subgroups of childhood B-cell ALL, including MLL fusions, ETV6-RUNX1, hyperdiploidy, and BCR-ABL1. However, formal demonstration of the prenatal origin and “backtracking” the natural history of the leukemia remains understudied in “B-other”/Normal Karyotype (NK) B-cell ALL. To characterize the epigenetic landscape of this particular leukemia subtype, we performed DNA bisulfite-sequencing on a pair of 8-month-old monozygotic twins diagnosed with concordant “B-other”/NK B-cell ALL.

  Dataset EGAD00001005018

• The Transcriptional Landscape of SHH Medulloblastoma

  To further understand the biology of Sonic hedgehog medulloblastoma and its molecular subtypes, we studied 250 human Shh-MB using strand-specific RNA sequencing. We identified novel alterations within the cAMP dependent pathway and found that 18% of tumors have genetic events that directly target the abundance and/or stability of MYCN. We also discovered an extensive network of fusions in focally amplified regions, and several loss-of-function fusions in tumor suppressor genes PTCH, SUFU and NCOR1. Molecular convergence on a core of specific genes by nucleotide variants, copy number aberrations, and gene fusions highlights key roles of specific pathways in the pathogenesis of Sonic hedgehog medulloblastoma.

  Dataset EGAD00001006305

• Single-cell antibody-derived tag sequencing data of peripheral blood mononuclear cells obtained from 30 ATL patients, 11 HTLV-1-infected asymptomatic carriers, and 4 healthy donors.

  Single-cell antibody-derived tag sequencing (scADT-seq) data of peripheral blood mononuclear cells (PBMCs) obtained from 30 ATL patients (34 samples including 4 sequential ones), 11 HTLV-1-infected asymptomatic carriers, and 4 healthy donors.

  Dataset EGAD00001007017

• Exploring the driver events of eccrine poromas and porocarcinomas: A retrospective, cross-institutional study of 90 cases

  Eccrine poroma (EP) and porocarcinoma (EPC) are rare benign and malignant adnexal neoplasms of the terminal sweat gland duct, respectively. Both can arise de novo, however, EPCs can also arise from a pre-existing EP. To-date, genetic investigation of these tumors has involved studies with small sample sizes and/or limited analyses. To comprehensively compare the driver events and mutational landscape of these tumors, we performed a retrospective multi-institutional whole-exome sequencing and RNA sequencing study on the largest cohort of EPs and EPCs to-date (n=90). We uncovered novel events and delineated different pathways of tumorigenesis underlying these tumors, with EPs driven largely by fusion genes, and EPCs driven largely by somatic mutations, with rare YAP1 and frequent PAK gene novel fusions.

  Dataset EGAD00001015376

• Follow_up_for_second_tier_signals_from_the_arcOGEN_GWAS

  The arcOGEN UK nationwide consortium has been funded by the arc to undertake a genome-wide association scan in osteoarthritis. GWA genotyping has been carried out at the Sanger on the illumina 610k array. This replication study was desinged to follow-up second-tier signals from the arcOGEN GWS in 25 SNPs (1Sequenom iPLEX) with p<5x10^-6 on 6000 additional UK OA and control samples.

  Study EGAS00001001017

• Genome-wide DNA Methylation Data from Illumina HumanMethylationEPIC arrays for whole blood samples from 403 healthy individuals

  Genome-wide DNA Methylation Data from Illumina HumanMethylationEPIC arrays for whole blood samples from 403 healthy individuals. Additional associated phenotype information is available for all individuals included in this study directly from CIBMTR. Data are available under controlled access release upon reasonable request and execution of a data use agreement. Requests should be submitted to CIBMTR at info-request@mcw.edu and include the study reference IB17-04.

  Study EGAS00001006033

• The Gut Microbiome of liver transplant recipients – Cross-sectional + Longitudinal (renal and liver)

  TransplantLines is designed as a single-center, prospective cohort study and biobank including all different types of solid organ transplant recipients as well as living organ donors. In the TransplantLines gut microbiome study the gut microbiome of solid organ transplant recipients is characterized and linked to clinical phenotypes. This batch contains the cross-sectional data from liver transplant recipients and longitudinal data from renal and liver transplant recipients.

  Study EGAS00001006258

• Privacy Notice for EGA Web user

  Privacy Notice for EGA Public Website This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by dr. Thomas Keane, by: email at: tk2@ebi.ac.uk or post at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: telephone at +49 6221 387-8590, email at dpo@embl.org , or post at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, or post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eu post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. Which is the lawful basis for processing personal data? For providing you access to the website and for offering support whilst using the website, we need your consent under Article 5 (2) of the IP 68 (equivalent to Article 6 (1)(a) of the GDPR). For monitoring your activities on the website, we process your personal data on the grounds of important public interest. Such legal basis is found in Article 5(1)(a) of EMBL Internal Policy No 68 on General Data Protection (hereinafter IP 68), which is equivalent to Article 6 (1)(e) of the EU General Data Protection Regulation (hereinafter GDPR) and upon which personal data are processed for the achievement of the aims laid down in 1973 agreement establishing EMBL, such as the promotion of the cooperation in the fundamental research, in the development of advanced instrumentation and in advanced teaching in molecular biology and dissemination of information. 3. What personal data is collected from users of the service? How do we use this personal data? We collect the following personal data from you: IP addresses Date and time of a visit to the service website Operating system Amount of data transmitted Browser Email address (only when support is requested by the user) The data controller will use your personal data for the following purposes: To provide the user access to the service To better understand the needs of the users and guide future improvements of the service To monitor website activities according to and in compliance with the Terms of Use To better understand the needs of the website visitors and guide future improvements of the service To conduct and monitor website security activities To create anonymous usage statistics 4. Who will have access to your personal data? The personal data will be disclosed to: Authorised staff in the data controller’s institutions acting on data controller`s behalf and instructions. 5. Will your personal data be transferred to third countries (i.e. countries not part of EU/EEA) and/or international organisations? There are no personal data transfers to third countries or international organisations. 6. How long do we keep your personal data? Any personal data directly obtained from you will be retained as long as the service is live. Such duration serves the purpose of enabling scientific research and ensures legal compliance and facilitates internal and external audits if they arise. By contrast, the log files for the data categories related to anonymous usage statistics (raw web service logs) are processed only for 30 days and thereafter erased. 7. The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration. Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period. Request information to understand data processing activities when the results of these activities are applied to you. Object at any time to the processing of your personal data unless we can demonstrate that we have legitimate reasons to process your personal data. Request free of charge and without excessive delay rectification or erasure of your personal data if we have not been processing it respecting the data protection policies of the respective controllers. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. Published at: February 6, 2019

  Documentation data-protection/privacy-notice/ega-website

• ImmunAID

  The ImmunAID study is a multi-center research program aimed at improving the diagnosis and understanding of systemic autoinflammatory diseases. The study integrates immunological, and molecular data from patients across several European cohorts. Its objective is to identify biomarkers and biological pathways that characterize disease mechanisms and help differentiate between inflammatory conditions. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779295. The project has generated genomic datasets, which are available through the European Genome-phenome Archive (EGA). In addition, it has produced several non-genomic datasets, listed below. All datasets have been fully anonymized in accordance with applicable ethical and regulatory frameworks. These non-genomic data are available upon request. To request access to these datasets, please contact: immunaid2024@gmail.com Your request will be studied by the Data Access Committee, and data will be made available upon approval. Non-genomic datasets available: Flow cytometry (general immune phenotype) — Dataset ID: ICKD2021569, size: 23 GB, 342 patients Somascan proteomics data — Dataset ID: ICKD2021570, size: 59 MB, 444 patients ELISA panel (Ferritin, CRP, HO1, IL-1B, IL-6, IL-8, IL-10, IL-12, IL-18, IFN-γ, TNF-α) — Dataset ID: ICKD2021571, size: 295 KB, 439 patients Mass spectrometry (MS/MS) — Dataset ID: ICKD2021572, size: 1.8 TB, 447 patients ELISA (CRP/ SAA) — Dataset ID: ICKD2021573, size: 321 KB, 443 patients Flow cytometry (inflammasome activity) — Dataset ID: ICKD2021574, size: 899 KB, 307 patients Plasma lipidomics — Dataset ID: ICKD2021575, size: 1.1 MB, 427 patients Urine lipidomics — Dataset ID: ICKD2021576, size: 833 KB, 368 patients ELISA (alarmins) — Dataset ID: ICKD2021577, size: 129 KB, 108 patients ELISA (IL-18 / IL-1) — Dataset ID: ICKD2021578, size: 271 KB, 330 patients Flow cytometry (NK cell alterations) — Dataset ID: ICKD2021579, size: 14 GB, 216 patients Chemokine measurements — Dataset ID: ICKD2021580, size: 489 KB, 404 patients Luminex (multiple analyte measurements) — Dataset ID: ICKD2021581, size: 759 KB, 369 patients

  Study EGAS50000001393

• Exploring_the_landscape_of_somatic_mutations_in_normal_tissue___GI___WGS

  The aim of this project is to investiagte somatic mutations, including rates of mutations and signatures, and clonal dynamics in normal (non-cancerous) human tissues from the gastrointestinal tract. The project will involve the studyof normal tissues from healthy individuals and those with specific candidate diseases. We are utilising laser capture microscopy to idnetifiy and isolate specific cell populations which are then subjected to whole genome sequencing to estimate mutational burdens and begin to understand clonal structures across the normal tissues.

  Study EGAS00001003012

• Exploring_the_landscape_of_somatic_mutations_in_normal_tissue___UGI___WGS

  The aim of this project is to investiagte somatic mutations, including rates of mutations and signatures, and clonal dynamics in normal (non-cancerous) human tissues from the gastrointestinal tract. The project will involve the studyof normal tissues from healthy individuals and those with specific candidate diseases. We are utilising laser capture microscopy to idnetifiy and isolate specific cell populations which are then subjected to whole genome sequencing to estimate mutational burdens and begin to understand clonal structures across the normal tissues.

  Study EGAS00001003541

• Whole genome analyses of the childhood cancer neuroblastoma

  Neuroblastomas are tumors of peripheral sympathetic neurons and are the most common solid tumor in children. To determine the genetic basis for neuroblastoma we performed whole-genome sequencing (6 cases), exome sequencing (16 cases), genome-wide rearrangement analyses (32 cases), and targeted analyses of specific genomic loci (40 cases) using massively parallel sequencing. On average each tumor had 19 somatic alterations in coding genes (range, 3-70). Among genes not previously known to be involved in neuroblastoma, chromosomal deletions and sequence alterations of chromatin remodeling genes, ARID1A and ARID1B, were identified in 8 of 71 tumors (11%) and were associated with early treatment failure and decreased survival. Using tumor-specific structural alterations, we developed an approach to identify rearranged DNA fragments in sera, providing personalized biomarkers for minimal residual disease detection and monitoring. These results highlight dysregulation of chromatin remodeling in pediatric tumorigenesis and provide new approaches for the management of neuroblastoma patients.

  Dataset EGAD00001000282

• 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

• EpiMatch_DNA_Methylation_Resource

  Genome-wide DNA Methylation Data from Illumina HumanMethylationEPIC arrays for whole blood samples from 403 healthy individuals. Additional raw data (IDAT files) and associated phenotype information are available for all individuals included in this study (n=570) directly from CIBMTR. Data are available under controlled access release upon reasonable request and execution of a data use agreement. Requests should be submitted to CIBMTR at info-request@mcw.edu and include the study reference IB17-04

  Dataset EGAD00010002283