Search Results - EGA European Genome-Phenome Archive

Genome-wide genetic and epigenetic dataset of pancreatic acinar cell carcinomas

Pancreatic acinar cell carcinoma (ACC) is an aggressive exocrine tumor with largely unknown biology. To identify potential targets for personalized treatment, integrative genome- and epigenome-wide analyses were performed. The results show frequently aberrant DNA methylation, abundant chromosomal amplifications and deletions, and mutational signatures suggesting defective DNA repair. In contrast to pancreatic ductal adenocarcinoma, no recurrent point mutations are known. The tumor suppressors ID3, ARID1A, APC, and CDKN2A are frequently impaired also on the protein level and thus potentially affect ACC tumorigenesis. Consequently, this work identifies potential novel therapeutic targets in ACC for drugs recently approved for precision cancer therapy.

Study EGAS00001002533

Exome-wide somatic mutation characterization of small bowel adenocarcinoma

Small intestinal adenocarcinoma (SIA) is a rare and aggressive form of cancer with limited treatment options. To further characterize the somatic mutation landscape of this tumor type, exome sequencing was conducted on a population-based set of SIA samples from all three parts of the small intestine. Archival tissue from 106 tumors with comprehensive clinical patient information entered exome sequencing from a patient series consisting of SIA cases diagnosed in Finland between the years 2003-2011. Paired-end exome sequencing was performed using Illumina HiSeq 4000, and OncodriveFML was used to identify significantly mutated genes from the exome data. Also mutational signature and pathway enrichment analyses were performed.

Study EGAS00001002559

Genome Landscape of Primary Pancreatic Ductal Adenocarcinoma

The purpose of the Australian ICGC Pancreatic Cancer Genome Sequencing Initiativestudy is to identify the common driving mutations underlying the initiation anddevelopment of Pancreatic Adenocarcinoma in a large cohort of pancreatic cancerpatients (n=350). Matched genome sequences will be generated from normal tissue(duodenum) and resected primary tumour tissue in each patient using exome andwhole genome sequencing. The complete repertoire of somatic mutations will bedetermined (substitutions, indels, copy number changes and structural changes).Where possible, matched transcriptome sequencing will also be carried out todetermine locus activity, which mutations are actively expressed and whichrearrangements give rise to gene-fusion transcripts.

Study EGAS00001000154

HSC_population_dynamics___CB001_samples

My research project aims to use the clonal dynamics of spontaneously occurring somatic mutations to answer fundamental questions about human haematopoietic stem cell (HSC) biology. The four major questions I will address are: 1. How do age and aging affect normal human HSC dynamics in vivo? 2. How do in vivo perturbations, particularly chemotherapy and increased levels of reactive oxygen species, affect HSC population dynamics? 3. Is response to in vitro perturbation heritable and/or correlated with other features such as age of individual and contribution of the lineage to peripheral blood? 4. How are HSC dynamics altered in people with early driver mutations (clonal haematopoiesis)?

Study EGAS00001003397

Molecular phenotyping of MCA/ID patients to improve diagnosis

De novo structural variants are frequently identified in individuals with neurodevelopmental disorders, but the genes driving their phenotypes are often unknown. In this study we performed Whole Genome Sequencing, RNA-sequencing and ATAC-sequencing on samples of 51 patients with intellectual disability and/or multiple congenital anomalies and their biological parents (when available). The goals of the study were to gain more insights in the molecular consequences of (complex) genomic rearrangements and to improve the genetic diagnosis of patients carrying such rearrangements. Data is divided in four separate datasets based on type of source material and data access restrictions due to consent.

Study EGAS00001003489

Predicting brain tumor recurrence: development and validation of a DNA-methylation based nomogram in meningioma

Our work is the first to demonstrate the transformative utility of integrating clinical and molecular factors for use beyond simple classification into the realm of individualized prognostication for any brain tumor. Using our developed and validated tools that are publicly available, clinicians will be able combine clinical and molecular factors to determine an individualized probability of recurrence for patients with meningiomas. This represents a major advance in the field of personalized medicine for neuro-oncology, and the use of this tool can help clinicians overcome one of the most challenging limitations we face when treating patients with meningiomas.

Study EGAS00001003490

Molecular response of AML blasts to Aza-treatment.

Azacytidine (Aza) treatment is effective in some patients with acute myeloid leukemia (AML). Clinical observations suggest that DNMT3A-mutant patients represent a subgroup of AML patients that responds particularly well to Aza-treatment. Data coming from a mouse model support this finding and we have already generated molecular data suggesting a molecular pathway involved in Aza-response in DNMT3A-mutant AML patients. We now aim to validate these findings in primary AML-blasts. To this end, we have FACS-sorted blasts from patients with AML prior to and under Aza-treatment and plan to correlate pre-treatment as well as on-treatment methylomes to clinical Aza-response.

Study EGAS00001004825

A GWAS in uveal melanoma identifies risk polymorphisms in the CLPTM1L locus.

Uveal melanoma, a rare malignant tumor of the eye, is predominantly observed in populations of European ancestry. A genome-wide association study of 259 uveal melanoma patients compared to 401 controls all of European ancestry revealed a candidate locus at chromosome 5p15.33 (region rs421284: OR = 1.7, CI 1.43-2.05). This locus was replicated in an independent set of 276 cases and 184 controls. In addition, risk variants from this region were positively associated with higher expression of CLPTM1L. In conclusion, the CLPTM1L region contains risk alleles for uveal melanoma susceptibility, suggesting that CLPTM1L could play a role in uveal melanoma oncogenesis.

Study EGAS00001002334

Chracterising_cellur_pathways_underlying_CD3_CD28_activation_of_human_CD4__cells

We devised an approach to disentangle the TCR and CD28 pathways upon stimulation in naive and memory primary human CD4+ T cells (Tcons) in response to defined stimulatory signals. Sorted Tcons were activated using a titration of anti-CD3 and anti-CD28 in combination as well as individually. As a control we cultured cells in the same conditions but without the stimuli. In total, we defined seven conditions from four individuals for sequencing. 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/

Study EGAS00001002438

'KOREAN' never-smoker female adenocarcinoma RNA-seq

Multi-layered genomic studies such as the TCGA project have greatly advanced our understanding on molecular pathogenesis of lung cancer. For Asian nonsmoker patients, however, majority of studies have been limited to mutational analyses, emphasizing ethnic differences in driver mutations (e.g. more frequent EGFR mutations and ALK fusions). In essence, a comprehensive multi-layered characterization that could lead to molecular etiology and patient stratification scheme to be translated into clinical applications for this patient group is still missing. Here we report molecular profiling of tumor and matched normal tissues from 114 non-small-cell lung adenocarcinoma patients using whole exome sequencing, transcriptome sequencing, and array comparative genomic hybridization (CGH).

Study EGAS00001003789

Detection of Cancer Mutations by Urine Liquid Biopsy in Bladder Cancer Patients

The management of bladder cancer faces multiple challenges concerning the diagnostics and fol-low-up approaches. The standard diagnostic test is invasive cystoscopy. Urine cytology and re-cently proposed urine-based biomarkers still could not replace cystoscopy, thus prompting calls for improvements. Here, we explore urine liquid biopsy to detect cancer mutations for therapeutic and prognostic assessment and subsequently evaluate the utility of urine as a suitable specimen in diagnosing bladder cancer. Our findings show that the analysis of pre-and post-operative urine enables the characterization of specific tumor mutations, which can be used to diagnose and evaluate a patient’s prognosis and therapy response.

Study EGAS00001005758

Hepatitis B virus integrations promote local and distant oncogenic driver alterations in hepatocarcinogenesis

Infection by Hepatitis B Virus (HBV) is the main risk factor for Hepatocellular Carcinoma (HCC) worldwide. HBV can directly drive carcinogenesis through integrations in human genome. This integrative analysis of a French cohort of 190 patients mainly coming from Europe and Africa provides a deep characterization of HBV integrations, in relation with viral and host genomics and clinical features. Clonal HBV integrations directly contribute to HCC development through alterations of cancer driver genes, either at distance when co-localizing with copy number alterations, either locally through viral Enhancers. Together, this analysis gives new insights on HBV-associated driver mechanisms involved in hepato-carcinogenesis.

Study EGAS00001004629

Single-cell roadmap of immune cell responses in chronic myeloid leukemia

To study the innate and adaptive immune responses in CML, we profiled 25 samples from CML patients including samples at diagnosis (n = 7, N = 9, where n is the number of subjects and N the number of samples if different from n) and before and after TKI-cessation with imatinib (n = 6, N = 15) with paired single-cell RNA and T cell receptor (TCR) αβ chain sequencing (scRNA+TCRαβ-seq) and compared our data to different cancers (n = 29) and healthy donors (n = 7). This dataset contains the samples from before and after TKI-cessation, please see the manuscript for info related to the other datasets.

Study EGAS00001005044

RNA sequencing in primary inflammatory (TPP) macrophages treated with a MEK1/2 inhibitor

By investigating an intergenic haplotype on chr21q22, independently linked to inflammatory bowel disease (IBD), ankylosing spondylitis, primary sclerosing cholangitis and Takayasu’s arteritis, we discover that the causal gene, ETS2, is a master regulator of inflammatory responses in human macrophages and delineate how the risk haplotype increases ETS2 expression. Using a database of cellular signatures, we identified drugs that could modulate this pathway. To validate the anti-inflammatory activity of one class of small molecules in vitro, we treated TPP macrophages with vehicle control or a selective, non-ATP competitive MEK inhibitor (PD-0325901) at 2 doses (100nM and 500nM) and performed RNA sequencing.

Study EGAS00001007552

RNA sequencing data of 257 samples from the CORALLEEN trial

Early-stage Luminal B breast cancer is frequent and is a major cause of breast cancer death due to its poor prognosis. Our proposal aims to study the biology behind the sensitivity and resistance of Luminal B breast cancer to chemotherapy (CHT) or a non-CHT regimen composed of hormone therapy in combination with ribociclib, a CDK4/6 inhibitor. To accomplish this, we first completed the SOLTI-1402 CORALLEEN phase II trial, a study where 106 patients with early-stage Luminal B breast cancer were randomized to standard neoadjuvant CHT for 6 months, or neoadjuvant letrozole and ribociclib for 6 months. After treatment, patients underwent surgery. The primary results of the study, which showed that the response rate to letrozole+ribociclib was similar to CHT, was reported (Prat et al; Lancet Oncol). Tumor biopsies were available at baseline, week 3 and surgery. A total of 257 samples were analyzed using the Illumina TruSeq Stranded Total RNA w/Ribo Zero Gold with MiSeq in TGL (Sequencer NovaSeq S4/PE/100x)

Dataset EGAD00001010121

Understanding Self- Organising Capacity of Stem Cells during Implantation and Early Post-implantation Development in vitro and in vivo: Implications for Human Development (2020-04-20)

The aim of this project is to differentiate human embryonic stem cells to an extra-embryonic fate, specifically the hypoblast. This is of uttermost importance given the current lack of human hypoblast stem cells. We hypothesized that the pluripotent characteristics of the starting human embryonic stem cell population may dictate the competency for extra-embryonic cell fate specification. Based on this hypothesis and using human embryonic stem cells maintained in different naïve-like culture regimes, we have now developed conditions that allow the differentiation of human embryonic stem cells to a stable GATA6+ SOX2- population. This suggests that these cells may be putative human hypoblast stem cells. To validate this finding here we propose to perform RNA sequencing experiments of the differentiated human embryonic stem cells. By comparing their RNA expression profile to the single cell sequencing data of the human embryo that we are currently generating, we will be able to determine the identity of our GATA6+ SOX2- cells, and establish whether they represent the in vivo human hypoblast. This dataset contains all the data available for this study on 2020-04-20.

Dataset EGAD00001006056

Development, maturation and maintenance of human prostate inferred from somatic mutations

Stem cells within prostate epithelium frequently undergo malignant transformation, but there is limited information on their clonal dynamics and mutation burden in healthy human prostates. We sequenced whole genomes from 409 microdissections of prostate epithelium across 8 donors, using phylogenetic reconstruction with spatial mapping in a 59-year-old man’s prostate to provide high-resolution reconstruction of tissue dynamics across the lifespan. Somatic mutation burden increases linearly with age, at ~16 mutations/year/clone, and is higher in peripheral than peri-urethral regions. The 24-30 independent glandular subunits are established as rudimentary ductal structures during fetal development by 5-10 embryonic cells each. Puberty induces formation of further side branches and terminal acini by local stem cells disseminated through the rudimentary ducts during development. During adult tissue maintenance, clonal expansions are small, with limited geographic scope and minimal migration. Driver mutations are rare in normal ageing prostate epithelium, but the one canonical driver we did observe generated a sizable intraepithelial clonal expansion. By resolving unbiased, continuously occurring lineage-marking mutations, we define stem cell dynamics through embryogenesis, puberty and ageing, with relevance for prostate cancer.

Dataset EGAD00001006591

Field effect of healthy and diseased livers (2019-04-08)

Recent work in the Campbell group has revealed somatic mutations present in normal, non-cancerous human skin. A subset of the mutations conferred selective advantages to the host cells, leading to clonal expansions and raising the risk for future cancer development. Capturing such somatic mutations in normal tissue is important to advance our understanding about carcinogenesis and could provide prospective medical insights. In this project, our goal is to detect somatic mutations in normal (pre-cancerous) liver tissue. Using Laser Microdissection technology, we will dissect individual liver lobules from patient samples and submit these to sequencing. For each patient sample, we aim to sequence multiple lobules to characterise the mutagenic burden. Samples will be taken from patients with different liver disease aetiologies, including alcoholism and obesity, with a view on distinguishing the prevalent mutation types occurring in each disease context. We will perform targeted sequencing, initially using the WTSI cancer panel. Later we aim to use a novel bait set that captures both cancer genes as well as genes relevant to the non-cancerous samples (ie. genes implicated in hereditary disorders, immune sequences). . This dataset contains all the data available for this study on 2019-04-08.

Dataset EGAD00001004941

P647 Targeted resequencing project

In collaboration with Dr Robert Semple we have identified a family harbouring an autosomal dominant variant, which leads to severe insulin resistance (SIR), short stature and facial dysmorphism. This family is unique within the SIR cohort in having normal lipid profiles, preserved adiponectin and normal INSR expression and phosphorylation. DNA is available for 7 affected and 7 unaffected family members across 3 generations. All 14 samples have been genotyped using microsatellites and the Affymetrix 6.0 SNP chip. Linkage analysis identified an 18.8Mb haplotype on chromosome 19 as a possible location of the causative variant. However, Exome sequencing of 3 affected and 1 unaffected family members has not identified the causative variant suggesting the possibility of an intronic or intergenic variant in this region or elsewhere in the genome. We propose to conduct whole genome sequencing of 5 members of the pedigree at a depth of 20X. The chosen samples are two sets of parents plus one member of an unaffected branch of the pedigree who shares the risk haplotype on chromosome 19. Sequencing of the two sets of parents will be used along with the genome-wide SNP data to impute 4 affected children giving an effect sample size of 6 affected individuals.

Dataset EGAD00001000383

Evolution and clinical impact of genetic epistasis within EGFR-mutant lung cancers: multi-timepoint exome sequencing of a single patient's disease

This dataset is a time-series of EGFR-mutant NSCLC clinical specimens from an individual patient profiled using tumor-based whole exome sequencing and the data is in BAM format. DNA was extracted from FFPE for primary tumor and frozen tumor tissue samples and matched non-tumor tissue using the Qiagen Allprep DNA/RNA Mini Kit. The library preparation protocol was based on the Agilent SureSelect Library Prep and Capture System. DNA was resuspended in a low TE buffer and sheared (Duty Cycle 5%; Intensity 175; Cycles/Burst: 200; Time: 300s, Corvaris S2 Utrasonicator). Bar-coded exome libraries were prepared using the Agilent Sure Select V5 library kit per manfucaturer’s specifications. The libraries were run on the HiSeq2500. Raw paired end reads (100bp) in FastQ format generated by the Illumina pipeline were aligned to the full hg19 genomic assembly obtained from USCS, gencode 14, using bwa version 0.7.12. Picard tools version 1.117 was used to sort, remove duplicate reads and generate QC statistics. Tumor DNA was sequenced to median depth of 303X (range 114.39-383.41) and the matched germline DNA to average depth of 231.65.

Dataset EGAD00001003769

Timing the landmark events in the evolution of clear cell renal cell cancer

Clear cell renal cancer is characterized by near-universal loss of the short arm of chromosome 3 (3p). This event arises through unknown mechanisms, but critically results in the loss of several tumor suppressor genes. We analyzed whole genomes from 95 biopsies across 33 patients with clear cell renal cancer (ccRCC) recruited into the Renal TRACERx study. We find novel hotspots of point mutations in the 5'-UTR of TERT, targeting a MYC-MAX repressor, that result in telomere lengthening. The most common structural abnormality generates simultaneous 3p loss and 5q gain (36% patients), typically through chromothripsis. Using molecular clocks, we estimate this occurs in childhood or adolescence, generally preceding emergence of the most recent common ancestor by years to decades. Similar genomic changes recent common ancestor by years to decades. Similar genomic changes are seen in inherited kidney cancers. Modeling differences in age-incidence between inherited and sporadic cancers suggests that the number of cells with 3p loss capable of initiating sporadic tumors is no more than a few hundred. Targeting essential genes in deleted regions of chromosome 3p could represent a potential preventative strategy for renal cancer.

Dataset EGAD00001003445

MorphoITH: A Framework for Deconvolving Intra-Tumor Heterogeneity Using Tissue Morphology

This study introduces MorphoITH, a framework for deconvolving intra-tumor heterogeneity (ITH) in clear cell renal cell carcinoma (ccRCC) based on tissue morphology from histopathological slides. The study tested MorphoITH's ability to capture different aspects of morphology and to reflect genetic ITH. The data deposited here is derived from a morphology guided multi-regional sequencing dataset used to study the relationship between morphology and genetic evolution. This dataset consists of whole exome sequencing of tumor from multiple sites and adjacent normal samples which were collected from two patients treated in affiliated hospitals of the University of Texas Southwestern Medical Center (UTSW), including Parkland Hospital.

Study EGAS50000001064

Somatic mutant selection is altered by prior NOTCH1 mutation in ageing esophageal epithelium

Authors: Charlotte King1, Emilie Abbie1, Joanna C. Fowler1, Irina Abnizova1, Roshan K. Sood1, Swee Hoe Ong1, Michael W. J. Hall1,2, Faye Lynch-Williams3, Benjamin A. Hall4, Philip H. Jones1,2,5 Abstract: In cancer evolution, genome alterations often occur in a specific order, implying selection depends on the prior clonal genotype 1-3. It is unknown if similar constraints operate in normal epithelia. Here, we mapped mutations in normal mid-esophagus of aged UK subjects. Mutant NOTCH1 clones colonized most of the epithelium by age 60 and above 70 tissue was saturated with mutants under strong competitive selection. Mutant TP53 was more strongly selected in donors over 60 years of age. Samples predominantly mutant for NOTCH1 showed increased selection of NOTCH2 mutants and weaker selection of mutant TP53 compared with samples that were mostly NOTCH1 wild type. In mouse esophagus lacking Notch1 we observed strong selection of mutant Notch2 and other genes not selected in wild type esophagus. In normal ageing esophagus, the first driver mutation may change the trajectory of subsequent somatic evolution by altering mutant selection.

Dataset EGAD00001015261

Childhood Cancer Survivor Study (CCSS)

Background and Rationale for the Childhood Cancer Survivor Study (CCSS) Over the last several decades, advances in treatments for childhood and adolescent cancer have substantially improved survival following diagnosis. These improvements gave rise to the responsibility for investigating long-term treatment-associated morbidity and mortality. Early efforts to describe late effects were largely conducted through single-institution and limited consortia studies. However, by the mid-1980s, it became increasingly clear that these approaches had inherent limitations, including small sample size, convenience sampling, incompletely characterized populations, and limited length of follow-up. To overcome these limitations, the CCSS was proposed and funded by the National Cancer Institute (NCI) as a U01 grant in 1994. Subsequently, the strengths of the CCSS, including an efficient and extensive infrastructure, plus expanding database and biorepository, were recognized and appreciated. Thus, in consultation with the NCI, the CCSS was converted to a U24 (resource grant) funding mechanism to serve the scientific community in 2000. The overarching goal of the CCSS resource is to increase the conduct of innovative and high impact research related to pediatric cancer survivorship. CCSS has been used extensively by researchers from a wide range of disciplines to address a broad spectrum of topics. Strengths of the resource include its large size, comprehensive annotation of treatment exposures, ongoing longitudinal follow-up with characterization of a wide array of participant characteristics and outcomes, and an established biorepository. Design of the Childhood Cancer Survivor Study The Childhood Cancer Survivor Study (CCSS) is a multi-institutional, multi-disciplinary collaborative research resource comprised of a retrospective hospital-based cohort of survivors of childhood cancer and a comparison sibling cohort. Eligible survivors from 31 participating institutions were diagnosed between 1970 and 1999, prior to age 21 years, with selected common pediatric cancers (leukemia, central nervous system tumors, Hodgkin lymphoma, non-Hodgkin lymphoma, kidney tumors, neuroblastoma, soft tissue sarcoma, or bone tumors). All patients who survived five years from the date of diagnosis were eligible, regardless of disease or treatment status. The baseline questionnaire was completed by 24,368 survivors and 5,039 siblings recruited to serve as a comparison group. To date, participants have completed three general follow-up surveys, as well as a number of specialized surveys on specific topics (e.g. health care, insurance, screening practices, men's and women's health issues, adolescent health, sleep and fatigue). In addition, biological samples (buccal cells, saliva and/or blood) have been collected for over 11,000 participants. Full descriptions of the design and characteristics of the CCSS have been previously published (Robison et al; Leisenring et al.), and available data and samples are described at https://ccss.stjude.org/develop-a-study/gwas-data-resource.html. Treatment Data in the Childhood Cancer Survivor Study A key feature of CCSS is the availability of detailed treatment data, which were collected by abstraction of medical records for each individual member of the cohort. Detailed abstraction included dates of therapy, protocol information, and specific details regarding surgery, chemotherapy and radiation. Quantitative dose details were collected for 22 specific chemotherapeutic agents, including alkylating agents, anthracyclines, platinum compounds and epipodophyllotoxins. In addition to individual agent doses, algorithms have been created to calculate cumulative doses of all drugs in a specific class, such as anthracyclines (doxorubicin, daunomycin and idarubicin) or platinum agents (cisplatinum and carboplatinum). Data abstracted for surgeries included dates and both the names and corresponding International Classification of Diseases (9th revision) code. For radiation treatment data, all relevant records were sent to the Radiation Physics Center at M.D. Anderson Cancer Center for detailed abstraction and dosimetry. Initial body region dosimetry was performed for all participants, followed by more detailed dosimetry as needed for specific studies. Genomics Data in the Childhood Cancer Survivor StudyThe NCI's Division of Cancer Epidemiology and Genetics and CCSS investigators collaborated to conduct genomics studies (SNP array genotyping and whole exome sequencing) using samples from the CCSS Biorepository. Studies included all cohort participants with available DNA regardless of sex or ancestry when the genomics studies were initiated. Phenotype Data in the Childhood Cancer Survivor Study Vital status and cause of death for both participants and non-participants is determined via linkage with the National Death Index (NDI). Identification of subsequent neoplasms is based on self-report, followed by validation using medical records, or via NDI. A wide array of additional health outcomes have been ascertained via a comprehensive set of questions on the CCSS questionnaires, covering potential adverse events across a range of organ systems (hearing/vision/speech, urinary, hormonal, heart and circulatory, respiratory, digestive, brain and nervous systems). In addition to health outcomes, longitudinal data have been collected on demographics, health behaviors, family history, screening practices, insurance status, and a range of psychosocial and neurocognitive factors. A full listing of available variables and copies of the CCSS questionnaires are available at http://ccss.stjude.org. Research Areas in the Childhood Cancer Survivor Study Extensive use by the research community has resulted in over 265 published manuscripts on a wide range of topics, including associations between treatment factors and mortality, subsequent neoplasms, chronic health conditions, cardiac events, neurocognitive sequelae, psychosocial factors, fertility, and health status. Additional topics have included health behaviors, screening practices, health care access and utilization, statistical and exposure assessment methodology, and development of risk prediction models. A full listing of published manuscripts using CCSS data is available on the CCSS website at https://ccss.stjude.org/published-research/publications.html. The Childhood Cancer Survivor Study as a Resource for Investigators The CCSS is an NCI-funded resource (U24 CA55727) to promote and facilitate research among long-term survivors of cancer diagnosed during childhood and adolescence. Interested investigators are encouraged to develop research ideas and propose projects within CCSS, whether or not they are from a participating CCSS institution. The CCSS is now accepting proposals to collaborate with CCSS and NCI investigators in the use of genomics data and corresponding outcomes-related data to address innovative research questions relating to potential genetic contributions to risk for treatment-related outcomes. Any researcher, or group of researchers, qualified to conduct genetic research can submit a proposal. There are no restrictions relative to country, institution, or prior involvement in CCSS. A full description of the process for developing a proposal for genetic research in CCSS can be found at https://ccss.stjude.org/develop-a-study/gwas-data-resource.html, along with listings of approved proposals.

Study phs001327

Mutation analysis in human iPS cells

PCR products were obtained from each target loci using genomic DNA from human iPS cells. Subsequently, PCR products are pooled and subjected to Illumina library preparation. The library will be sequenced by MiSeq. 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 EGAD00001000357

DNA sequening

The dataset consist of DNA and RNA sequencing results and metadata of the samples. All sample numbers starting with 6716 are tumor samples which has been sequenced using WES (see BAM files). It concerns biopsies of metastatic lesions from patients with BRAFV600 mutated melanoma, obtained before, during and after the study treatment (see samples metadata) and in some cases blood for germline mutation analysis. Sequencing is performed using the Illumina Novaseq 6000 system.

Dataset EGAD50000000382

Exome sequencing of samples for Corvin_Dublin_BipEx

This research project was a collaboration between Trinity College Dublin, Ireland and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 191 Bipolar case/control samples from collaborators in Ireland. Genomic DNA from each sample was sequenced to a mean depth of 20x. The project used Illumina WXS sequencing of DNA and the file type is cram.

Dataset EGAD50000000392

Adipose tissue macrophage dysfunction is associated with a breach of vascular integrity in NASH

Our study describes for the first time the myeloid cell landscape in human visceral adipose tissue at single-cell level within a cohort of well-characterized patients with non-alcoholic fatty liver disease.

Study EGAS50000000424

SIGi001-A-13 / SAMEA104386250 WGS data

The iPSC line SIGi001-A-13 / SAMEA104386250 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-13 is available for research use at www.EBiSC.org.

Dataset EGAD50000001031

BIONi010-C-8 / SAMEA4454011 WGS data

The iPSC line BIONi010-C-8 / SAMEA4454011 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-8 is available for research use at www.EBiSC.org.

Dataset EGAD50000001028

BIONi010-C-3 / SAMEA4342740 WGS data

The iPSC line BIONi010-C-3 / SAMEA4342740 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-3 is available for research use at www.EBiSC.org.

Dataset EGAD50000001034

BIONi010-C-7 / SAMEA4454010 WGS data

The iPSC line BIONi010-C-7 / SAMEA4454010 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-7 is available for research use at www.EBiSC.org.

Dataset EGAD50000001035

BIONi010-C-6 / SAMEA4454009 WGS data

The iPSC line BIONi010-C-6 / SAMEA4454009 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-6 is available for research use at www.EBiSC.org.

Dataset EGAD50000001037

BIONi010-C-9 / SAMEA4454012 WGS data

The iPSC line BIONi010-C-9 / SAMEA4454012 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-9 is available for research use at www.EBiSC.org.

Dataset EGAD50000001040

SIGi001-A-3 / SAMEA4448571 WGS data

The iPSC line SIGi001-A-3 / SAMEA4448571 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-3 is available for research use at www.EBiSC.org.

Dataset EGAD50000001041

BIONi010-C-4 / SAMEA4452060 WGS data

The iPSC line BIONi010-C-4 / SAMEA4452060 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-4 is available for research use at www.EBiSC.org.

Dataset EGAD50000001043

EDi014-A / SAMEA4459369 WGS data

The iPSC line EDi014-A / SAMEA4459369 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi014-A is available for research use at www.EBiSC.org.

Dataset EGAD50000001051

EDi014-B / SAMEA4459371 WGS data

The iPSC line EDi014-B / SAMEA4459371 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi014-B is available for research use at www.EBiSC.org.

Dataset EGAD50000001053

SIGi001-A-7 / SAMEA4448730 WGS data

The iPSC line SIGi001-A-7 / SAMEA4448730 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-7 is available for research use at www.EBiSC.org.

Dataset EGAD50000001060

BIONi010-C-5 / SAMEA4452061 WGS data

The iPSC line BIONi010-C-5 / SAMEA4452061 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-5 is available for research use at www.EBiSC.org.

Dataset EGAD50000001062

BIONi010-C-2 / SAMEA4342705 WGS data

The iPSC line BIONi010-C-2 / SAMEA4342705 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-2 is available for research use at www.EBiSC.org.

Dataset EGAD50000001068

SIGi001-A-1 / SAMEA4451096 WGS data

The iPSC line SIGi001-A-1 / SAMEA4451096 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-1 is available for research use at www.EBiSC.org.

Dataset EGAD50000001073

SIGi001-A-10 / SAMEA4451117 WGS data

The iPSC line SIGi001-A-10 / SAMEA4451117 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-10 is available for research use at www.EBiSC.org.

Dataset EGAD50000001074

SIGi001-A-11 / SAMEA4451118 WGS data

The iPSC line SIGi001-A-11 / SAMEA4451118 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-11 is available for research use at www.EBiSC.org.

Dataset EGAD50000001075

SIGi001-A-12 / SAMEA104237570 WGS data

The iPSC line SIGi001-A-12 / SAMEA104237570 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-12 is available for research use at www.EBiSC.org.

Dataset EGAD50000001076

SIGi001-A-2 / SAMEA4451116 WGS data

The iPSC line SIGi001-A-2 / SAMEA4451116 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-2 is available for research use at www.EBiSC.org.

Dataset EGAD50000001077

SIGi001-A-6 / SAMEA4447426 WGS data

The iPSC line SIGi001-A-6 / SAMEA4447426 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-6 is available for research use at www.EBiSC.org.

Dataset EGAD50000001078

SIGi001-A-4 / SAMEA4448632 WGS data

The iPSC line SIGi001-A-4 / SAMEA4448632 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-4 is available for research use at www.EBiSC.org.

Dataset EGAD50000001088

SIGi001-A-5 / SAMEA4448708 WGS data

The iPSC line SIGi001-A-5 / SAMEA4448708 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-5 is available for research use at www.EBiSC.org.

Dataset EGAD50000001092

SIGi001-A-8 / SAMEA4448777 WGS data

The iPSC line SIGi001-A-8 / SAMEA4448777 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-8 is available for research use at www.EBiSC.org.

Dataset EGAD50000001093

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