Search Results - EGA European Genome-Phenome Archive

Transcriptome analysis for intrahepatic cholangiocarcinoma

Intrahepatic cholangiocarcinomas (iCCs) are characterized by their rarity, difficulty in diagnosis, and overall poor prognosis. We performed comprehensive transcriptomic characterization of treatment-naive iCC. Whole transcriptome analyses identified two prognostic subtypes, concordant with previous reports.The findings could assist in patient stratification with iCCs and in developing rational therapeutic strategies.

Dataset EGAD00001008544

Myeloid cell programming in patients with non-medullary thyroid carcinoma

This dataset contains single-cell RNA sequencing data from patients with thyroid cancer (n=7), multinodal Goiter (n=3) and healthy individuals (n=5). Mononuclear cells were taken from both the peripheral blood and the bone marrow compartments. We used a pooled single-cell design where multiple individuals were pooled in a single sample for sequencing (NextSeq 500-V2) and later demultiplexed using their genotype data. Associated metadata contains information on the phenotypes per individual, the pooling design and the linkage between the supplied files and sequenced pools. Due to limitations from EGA in uploading single-cell data, the raw fastq files were processed as follows: (i) I1/I2/R1/R2 fast files were concatenated over the different lanes. (ii) Concatenated I1 and I2 files were interleaved, as were the concatenated R1 and R2 files to generate two fastq files per pool containing all the information. To interleave the fastq files, the BBmap tool bbmap/reformat.sh was used, which can also be used to de-interleave the files.

Dataset EGAD00001008108

Somatic mutation and clonal evolution normal breast tissue WGS

Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >70 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumour development. . This dataset contains all the data available for this study on 2023-03-09.

Dataset EGAD00001010123

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

Somatic mutation and clonal evolution normal breast tissue TGS (2020-01-15)

Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >70 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumour development. . This dataset contains all the data available for this study on 2020-01-15.

Dataset EGAD00001005787

Study of Clinical Efficacy of Antimicrobial Therapy Strategy Using Pragmatic Design in Idiopathic Pulmonary Fibrosis (CleanUP IPF-BioLINCC)

Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives To investigate whether the addition of antimicrobial treatments improves outcomes compared to usual care alone among patients with idiopathic pulmonary fibrosis. Background Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease. Lung dysbiosis, characterized by increased bacterial load and/or loss of diversity, has been reported in patients with IPF and may contribute to hospitalization and death. Clinical trials investigating other chronic disorders suggest that antimicrobial therapy favorably alters the lung microbial community. The CleanUP IPF study was initiated to determine if an antimicrobial treatment reduces respiratory hospitalization or death among patients with IPF. Participants A total of 513 participants were enrolled. 254 participants were randomized to receive antimicrobials, of those 128 were randomized to receive co-trimoxazole and 126 were randomized to receive doxycycline. 259 participants were randomized to receive usual care alone. Design CleanUP IPF was a randomized, unblinded, multicenter study. Patients were randomized to receive antimicrobials in addition to usual care or usual care alone. Antimicrobials included co-trimoxazole (trimethoprim 160 mg/sulfamethoxazole 800 mg twice daily plus folic acid 5 mg daily) or doxycycline (100 mg once daily if body weight Data collected included diffusion capacity of lungs for carbon monoxide (DLCO), forced vital capacity (FVC), and occurrence of severe adverse events. Several questionnaires were administered to assess quality of life, including the impacts of shortness of breath, fatigue, and chronic cough on participants. The primary end point was time to first nonelective respiratory hospitalization or all-cause mortality. The study was terminated early due to futility. Conclusions Among adults with idiopathic pulmonary fibrosis, the addition of co-trimoxazole or doxycycline to usual care, compared with usual care alone, did not significantly improve time to nonelective respiratory hospitalization or death. Martinez FJ, Yow E, Flaherty KR, et al. Effect of Antimicrobial Therapy on Respiratory Hospitalization or Death in Adults With Idiopathic Pulmonary Fibrosis: The CleanUP-IPF Randomized Clinical Trial. JAMA. 2021;325(18):1841-1851. doi:10.1001/jama.2021.4956

Study phs004314

Gut metagenome associations with extensive digital health data in a volunteer-based EstMB cohort

Microbiome research is starting to move beyond the exploratory phase towards interventional trials and therefore well-characterized cohorts will be instrumental for generating hypothesis and providing new knowledge. As part of the Estonian Biobank, we established the Estonian Microbiome Cohort which includes stool, oral and plasma samples from 2,509 participants and is supplemented with multi-omic measurements, questionnaires, and regular linkages to national electronic health records. In this study, we analyzed stool data from deep metagenomic sequencing together with rich phenotyping, including 71 diseases, 136 medications, 21 dietary questions, 5 procedures, and 19 other factors. The data revealed numerous relationships with different microbiome features. Additionally, the long-term antibiotic usage, independent from recent administration, has a significant impact on the microbiome composition, partly explaining the common associations between diseases. Overall, this study extends the understanding of microbiome–host interactions and facilitates the development of microbiome-related studies.

Study EGAS00001005900

Multi-omics identify falling LRRC15 as a COVID-19 severity marker and persistent pro-thrombotic signals in convalescence

Patients with end-stage kidney disease (ESKD) are at high risk of severe COVID-19. Here, we perform longitudinal blood sampling of ESKD haemodialysis patients with COVID-19, collecting samples pre-infection, serially during infection, and after clinical recovery. Using plasma proteomics, and RNA-sequencing and flow cytometry of immune cells, we identify transcriptomic and proteomic signatures of COVID-19 severity, and find distinct temporal molecular profiles in patients with severe disease. Supervised learning reveals that the plasma proteome is a superior indicator of clinical severity than the PBMC transcriptome. We show that a decreasing trajectory of plasma LRRC15, a proposed co-receptor for SARS-CoV-2, is associated with a more severe clinical course. Strikingly, we observe that two months after the acute infection, patients still display dysregulated gene expression related to vascular, platelet and coagulation pathways, including PF4 (platelet factor 4), which may explain the prolonged thrombotic risk following COVID-19.

Study EGAS00001006778

Somatic mutation and selection at epidemiological scale - Sanger_NanoSeq_RandD

Bottleneck sequencing of human tissue including neurons, cord blood, sperm 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/. As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 5 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

Dataset EGAD00001015624

Collaborative Study of Genes, Nutrients and Metabolites (CSGNM)

While many genetic and metabolic studies focus on understanding disease states, this genome wide association study (GWAS) was designed to understand the influence of genetic variants on circulating metabolites and factors in normal, healthy individuals. Over 2500 healthy, ethnically Irish college students attending Trinity College Dublin completed a health and diet questionnaire and provided a non-fasting blood sample to be used for genetic and metabolic analysis. The questionnaire was designed to collect information on age, sex, height, weight, medical conditions, smoking, dietary habits, and consumption of alcohol, fortified foods, and supplements. Extracted DNA was genotyped using the Illumina HumanOmni1-Quad Beadchip. Metabolites were measured using a number of methods and focused on those relevant to the folate/vitamin B12 pathway.

Study phs000789

Multimodal Profiling of 500,000 Memory T Cells from a Tuberculosis Cohort Identifies Cell State Associations with Demographics, Environment, and Disease

We conducted CITE-seq to measure whole transcriptome gene expression and surface expression of 31 proteins. We assayed >500K memory T cells from 259 donors from a tuberculosis progression cohort (128 cases: former progressors and 131 controls: non-progresssors/latent infection) >4 years post-infection after returning to immune steady state. We defined 31 memory T cell states influenced by age, sex, genetic ancestry, and season. After correcting for these covariates, we found that one cell state (C-12), resembling the T helper cells Th17s, were depleted in cases compared to controls. When sorted ex vivo, this state responds to polyclonal or Mycobacterium tuberculosis (Mtb) peptide antigen stimulation with interleukin-17 (IL-17) or interferon gamma (IFNg).

Study phs002467

Cross-site Concordance Evaluation of Tumor DNA and RNA Sequencing Platforms of CIMAC-CIDC Network

The Cancer Immune Monitoring and Analysis Centers (CIMACs) and the Cancer Immunologic Data Commons (CIDC)  has engaged in efforts to harmonize Whole-exome (WES) and RNA-sequencing (RNA-seq) data from three different experimental platforms (MD Anderson, NCI MoCha lab, and Broad Institute) and are using a series of developed pipelines to process the early trial samples. To evaluate the consistency of tumor WES and RNA-seq profiling platforms across different centers, the CIMACs-CIDC conducted a systematic harmonization study. DNA and RNA were centrally extracted from fresh frozen (FF) and formalin-fixed paraffin-embedded (FFPE) non-small cell lung carcinoma (NSCLC) tumors and distributed to three centers for WES and RNA-seq profiling

Study phs002295

Transcriptome analysis of human longitudinal whole blood samples from PCR-positive and PCR-negative adults following controlled inoculation with Influenza A (H3N2) virus.

Transcriptome analysis of influenza A (H3N2) human challenge samples. Understanding of the transcriptomic profile of individuals in early influenza infection is limited. To investigate this, longitudinal whole-blood samples (n=178) were taken from adult participants following controlled inoculation with Influenza A H3N2 virus (sampling at baseline (0) and days 1, 2, 3, 7, 10 and 14 post-challenge). Most participants became influenza PCR-positive; a minority remained PCR-negative. Total RNA was extracted from PAXgene tubes before undergoing globin and rRNA depletion. DNA libraries were constructed using the NEBNext® Ultra™ II Directional RNA Library Prep Kit for Illumina. All samples were then sequenced using Illumina NovaSeq 6000.

Study EGAS50000000679

The PRIME-AIR Study: Positive End-Expiratory Pressure, Recruitment, Incentive Spirometry, Muscle Relaxant Optimization, Preoperative Education, Postoperative Early Ambulation, Individualized, and Reinforced

Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions.The PRIME-AIR study ("Positive end-expiratory pressure, Recruitment, Incentive spirometry, Muscle relaxant optimization, preoperative Education, postoperative early Ambulation, Individualized, and Reinforced") was a prospective multi-center randomized controlled pragmatic trial, with a blinded assessor, to compare post-operative pulmonary complications (PPCs) in patients with an individualized anesthetic-centered intervention (including individualized mechanical ventilation positive end-expiratory pressure (PEEP) management to maximize respiratory system compliance and minimize driving pressures, a neuromuscular agent and subsequent reversal, and post-operative lung expansion and early mobilization) versus usual care.

Study phs003926

The acute effects of morning bright light on the human white adipose tissue transcriptome: exploratory post hoc analysis

The circadian rhythm of the central brain clock in the suprachiasmatic nucleus (SCN) is synchronized by light. White adipose tissue (WAT) is one of the metabolic endocrine organs containing a molecular clock, and it is synchronized by the SCN; excess WAT is a risk factor for health issues including type 2 diabetes mellitus (DM2). We hypothesized that bright-light exposure would affect the human WAT transcriptome. Therefore, we analyzed WAT biopsies from two previously performed randomized cross-over trials (trial 1: lean healthy men, and trial 2: men with obesity and DM2). RNA sequencing results showed major group differences between men with obesity and DM2 and lean healthy men, as well as a differential effect of bright light exposure.

Study EGAS50000001206

Integrated genomic analysis identifies recurrent mutations and evolution patterns driving the initiation and progression of follicular lymphoma.

follicular lymphoma (FL), the most common indolent non-Hodgkin’s lymphoma, remains incurable. A well-recognized complication of FL is its transformation to a diffuse large B-cell lymphoma (DLBCL)-morphology in a subset of patients, for which the clinical outcomes are poor. Recent genetic profiling and single case studies of donor-derived FL following stem cell transplantation had alluded to the putative existence of a ‘long lived’ tumor-initiating progenitor cell compartment from which successive disease events occurred. To chronicle the genetic changes associated with progression to transformation, we conducted whole-genome sequencing (WGS) of FL-tFL pairs and matched germline (GL) samples from six patients, a total of 20 genomes.

Study EGAS00001000399

RNA-seq study of longitudinal blood cell samples from children at risk of type 1 diabetes

The appearance of type 1 diabetes (T1D)-associated autoantibodies is the first and only measurable parameter to predict progression toward T1D in genetically susceptible individuals. However, autoantibodies indicate an active autoimmune reaction, wherein the immune tolerance is already broken. Therefore, there is a clear and urgent need for new biomarkers that predict the onset of the autoimmune reaction preceding auto-antibody positivity or reflect progressive b-cell destruction. Here we report the mRNA sequencing–based analysis of 306 samples including fractionated samples of CD4+ and CD8+ T cells as well as CD4, CD8 cell fractions and unfractionated PBMC samples longitudinally collected from seven children who developed beta-cell autoimmunity (Case subjects) at a young age and matched control subjects.

Study EGAS00001004071

RNA sequencing on intestinal biopsies from inflammatory bowel disease patients treated with vehicle control, MEK inhibitor, or infliximab

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 ex vivo, we obtained biopsies from patients with active IBD and cultured these biopsies with a selective, non-ATP competitive MEK inhibitor (PD-0325901), infliximab (positive control), or DMSO (vehicle control) for 18 hours, then performed RNA sequencing.

Study EGAS00001007534

Molecular characterization of NASH-HCC

We collected 80 NASH-HCCs formalin fixed paraffin-embedded (FFPE) samples from 5 different institutions. NASH was diagnosed in FFPE samples by at least two expert pathologists following a described histological algorithm (Bedossa et al., Hepatology, 2012). All NASH patients included in the study were HBV- and HCV-negative. Patients reporting alcohol consumption ≥ 20 g/day for women and 30 g/day for men, as well as patients with a known liver disease superimposed to NASH were excluded. Tumour and paired non-tumour gDNA of NASH-HCC FFPE samples was submitted to Whole Exome Sequencing (WES). Exome capture and sequencing library preparation were performed using the SureSelect Human All Exon V5, no UTR hybridization capture kit from Agilent (Target Size 50 Mb). Libraries were sequenced on an Illumina HiSeq 4000 instrument with 100-bp paired-end reads.

Dataset EGAD00001007524

MutWP1: CRUK Grand Challenge Mutographs of Cancer: pancreas (2019-04-03)

The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (Illumina HiSeqX, 40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. . This dataset contains all the data available for this study on 2019-04-03.

Dataset EGAD00001004893

MutWP1: CRUK Grand Challenge Mutographs of Cancer: Colorectal_LCM (2020-02-20)

The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. . This dataset contains all the data available for this study on 2020-02-20.

Dataset EGAD00001005994

Test dataset: Sequence and variant data from public 1000 Genomes Project

This is a test dataset derived from public data of the 1000 Genomes Project. Its purpose is not to allow for any inference about cohort data or results, but to aid bioinformaticians in the technical development and testing of tools, as well as data consumers in learning how to access information. This dataset consists of 2508 samples from the 1000 Genomes Project (https://www.nature.com/articles/nature15393). Samples' (e.g. NA18534) data can be accessed through the IGSR portal (e.g. https://www.internationalgenome.org/data-portal/sample/NA18534) or their corresponding folder at the 1000 Genomes' FTP site (e.g. http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1000_genomes_project/data/CHB/NA18534/exome_alignment/). There are several different types of data this dataset encompasses: Variant Calling Format (VCF, or its binary counterparts BCF) files, both joint (e.g. ALL_chr22_20130502_2504Individuals.vcf.gz) and split (HG01775.chrY.vcf.gz); exome sequencing CRAM files (e.g. NA18534.GRCh38DH.exome.cram); whole genome sequencing CRAM/BAM files (e.g. NA19239.cram). Additionally, there are multiple files that were sliced to create shorter files, which allows for a quick download, formated as "{FILE-INFO}__{NUMBER-OF-READS}r__{CHR}.{START-COORDINATE}-{END-COORDINATE}.{FILETYPE}" (e.g. "HG01500.GRCh38DH__90r__3.10000-10500__4.10000-10500.cram"). These files can be downloaded directly through the EGA-download-client PyEGA3 (https://github.com/EGA-archive/ega-download-client).

Dataset EGAD00001003338

Exome trios in patients with gastroschisis (2019-04-08)

Gastroschisis (MIM 230750) is a herniation of the intestines through a defect of the abdominal wall lateral to the umbilicus (usually on the right side), and it is not covered by a membrane [Ledbetter, 2012]. Gastroschisis is a congenital anomaly with increasing incidence, easy prenatal diagnosis and extremely variable postnatal outcomes. On the basis of clinical manifestations, epidemiologic charateristics, and the presence and type of additional malformations, gastroschisis could be considered a heterogeneous condition with no gene/s discovered yet. This congenital anomaly affects approximately 1-3 infancts per 10,000 live births [Calzolari et al.1995;Parker et al.,2010] Current knowledge about causative mutations/variants. To date, no single gene has been linked to gastroschisis. Some publications have tried to link this malformation to variants in genes (such as AEBP1 (adipocyte enhancer binding protein) gene [Feldkamp et al,. 2012] or the VEGF-NOS3 pathway [Lammer et al., 2008]. Previously, a Scribble mutant mouse model (circletail) was reported to exhibit gastroschisis, however recent studies demonstrated that the Scribble knockout fetus exhibits exomphalos phenotype of gastroschisis [Carnagham et al., 2013]. 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/ . This dataset contains all the data available for this study on 2019-04-08.

Dataset EGAD00001004942

E5103 Correlative Studies

ECOG-ACRIN E5103 (E5103) was a phase III adjuvant breast cancer trial that randomized 4994 patients with node-positive or high-risk node-negative breast cancer to intravenous doxorubicin and cyclophosphamide every 2 or 3 weeks (at the discretion of treating physician), for four cycles of adriamycin and cyclophosphamide (AC) followed by 12 weeks of weekly paclitaxel (80 mg/m2) alone (Arm A), or to the same chemotherapy with either concurrent bevacizumab (Arm B), or concurrent plus sequential bevacizumab (Arm C). To develop predictive genetic biomarkers for chemotherapy efficacy and toxicities, we have successfully performed genome-wide genotyping and whole exome sequencing in the germline (blood) DNA of 3215 and 672 patients, respectively, from the E5103 trial to investigate the association of genetic variants with chemotherapy efficacy and toxicities. Case and control studies were performed with genome-wide analyses (GWAS) and whole exome analyses (WES) across all arms of E5103 to identify genotypes at single-nucleotide polymorphisms (SNPs) and deleterious gene mutations that were associated with paclitaxel-induced peripheral neuropathy (TIPN). Through GWAS, we have identified a SNP, rs3125923, and through WES, Cytochrome P450 oxidoreductase (POR), that was significantly associated with grade 3-4 TIPN.

Study phs003201

MAITS in HCC

Hepatocellular Carcinoma (HCC) is a leading cause of cancer-related death and can be considered a prototype of inflammation-derived cancer arising from chronic liver injury. The cell composition of the HCC tumor immune microenvironment (TiME) has a major impact on cancer biology as the TiME can have divergent capacities on tumor initiation, progress, and response to therapy. Recent development of multi-omics and single-cell technologies help us to comprehensively quantify the cellular heterogeneity and spatial organization of the TiME and to further our understanding of antitumor immunity. We investigated the cellular composition of liver cancer patient samples (n=8) using single-cell RNA-seq. For this purpose, mononuclear cells were isolated from human liver cancer samples. Three locations within the tumor-bearing liver were used: adjacent liver, rim and tumor core. Then, cells were FACS sorted (either CD45+ cells or MAIT cells) and subjected to 10X Chromium-based scRNA-seq. We investigated immune cell changes and the cellular heterogeneity of the HCC TiME with a focus on MAIT cells. Annotated H5 files are provided. Clinical metadata including TMN stage, sex, gender, ethnicity, pretreatment, and histopathological reports are available for all patient samples. Further details on the study can be obtained in our paper once it’s published.A complementary dataset derived from ultrahighplex CO-Detection by indEXing (CODEX) from paired patient samples can be accessed through The Cancer Imaging Archives (TCIA) under DOI: https://doi.org/10.7937/bh0r-y074.

Study phs003279

Transdisciplinary Studies of Genetic Variation in Colorectal Cancer(CORECT): Meta-analysis

This study is part 2 of 2 for Schumacher et al, Nat Communication. 2015 Jul 7;6:7138. Part 2 is the pooled meta-analysis of 29 different studies of 37,955 European (18,299 Cases/19,656 Controls) participants using eight different genotyping platforms/variations. table, th, td { border: 1px solid black; border-collapse: collapse; } Study Name Participants Platform CFR-1 2976 Illumina 1M, 1M Duo, Omni1 CFR-2 3053 Affymetrix Axiom MECC 1 982 Illumina Omni 2.5 MECC2 1940 Affymetrix Axiom Kentucky 2172 Affymetrix Axiom ACS/CAPII 1086 Affymetrix Axiom Melbourne 1008 Affymetrix Axiom Newfoundland 672 Affymetrix Axiom ASTERKSI 1895 Illumina 300K COLO23 212 Illumina 300K DACHS1 3417 Illumina 300K DACHS2 1173 Illumina OmniExpress DALS1 1416 Illumina 550k/610K DALS2 874 Illumina 300K HPFS1 457 Illumina OmniExpress HPFS2 348 Illumina OmniExpress HPFS AA 658 Illumina OmniExpress MEC 674 Illumina 300K NHS1 1168 Illumina OmniExpress NHS2 340 Illumina OmniExpress NHSAA 1091 Illumina OmniExpress OFCCR 1172 Affymetrix 100k/500K PHS 771 Illumina OmniExpress PMH 402 Illumina 300K PLCO1 2509 Illumina 550k/610K PLCO2 901 Illumina 300K VITAL 573 Illumina 300K WHI1 1999 Illumina 550k/610K WHI2 573 Illumina 300K Since this study is a meta-analysis no corresponding phenotype, pedigree, sample, subjects, or primary molecular data are available. Each contributing study/platform will have fulfilled its own DBGAP submission commitment. This DBGAP entry is for European participants in the the pooled meta-analysis exclusively.

Study phs001499

Genomic Profiling Reveals Spatial Intra-tumour Heterogeneity in Follicular Lymphoma

Follicular lymphoma (FL) is an incurable indolent non-Hodgkin’s lymphoma (NHL) that behaves heterogeneously and is synonymous with the reciprocal translocation t(14;18)(q32;q21), leading to aberrant constitutive over-expression of BCL2 [ref]. High risk groups with poor overall survival include patients that transform to a high grade lymphoma, most commonly diffuse large B cell lymphoma (DLBCL) or progress early (within 2 years) of receiving treatment. Recently several studies have shed light on the diverse genomic landscape of FL, with frequently mutated genes including those involved in chromatin remodelling, (CREBBP, KMT2D, EZH2, EP300), immune modulation (TNFRSF14), JAK-STAT (STAT6, SOCS1), NF-ĸB (CARD11, MYD88, TNFAIP3) and mTORC1 signalling (RRAGC) [ref]. To date, the majority of these studies have either focussed on inter-patient genetic heterogeneity or established the extent of clonal heterogeneity as a patient’s tumour evolves over time. Furthermore, these temporal studies have alluded to the existence of a tumour-repopulating population (referred to as the common progenitor cell (CPC)) that evades treatment and acts as a reservoir, seeding each subsequent relapse and transformation event. Although these previous studies have illuminated the longitudinal clonal dynamics that occur in FL, our understanding of the degree of spatial or intra-tumour heterogeneity (ITH) that exists within an individual patient thus far remains limited. Earlier studies have predominantly focused on differences in cytological grade and immunophenotype between spatially separated lymph nodes and bone marrow, the most common site of extra-nodal involvement in FL, with genomic profiling restricted to examining somatic hypermutation patterns in IgVH genes [ref]. In contrast next generation sequencing has been increasingly utilised in solid organ malignancies to derive comprehensive genomic profiles from spatially separated sites. The seminal study by Gerlinger et al revealed profound differences in the genetic make-up between individual primary and metastatic sites of renal cell carcinoma [ref]. Significant heterogeneity has since been demonstrated both between and within lesions in the same patient in lung, pancreas and breast cancer with presumed driver mutations distributed within the “branches” of the evolutionary phylogenetic tree, suggesting that a single biopsy is incapable of capturing the full genomic heterogeneity of an individual’s malignancy [ref]. This geographical heterogeneity not only adds to the diverse pool of tumour subclones that may contribute to drug resistance mechanisms but importantly, presents a major obstacle for precision-based approaches focussed on targeting specific lesions within a single biopsy. In FL, the exponential increase in clinical trials using novel agents such as EZH2, PI3K and BTK inhibitors reflects this shift in cancer care and along with the development of molecular prognostic scores such as the m7-FLIPI highlights the clinical need to accurately define genomic alterations with clinical relevance. As the majority of FL patients manifest disseminated tumour involvement, we sought to uncover the extent and clinical importance of spatial heterogeneity in FL by comprehensively genetically profiling 22 synchronously removed spatially separated biopsies from 9 patients. Using a combination of whole exome and targeted deep sequencing, our results inferred the complex subclonal architecture within these tumours and the mutational differences between anatomical sites, demonstrating cases with significant intrinsic genetic diversity.

Study EGAS00001002492

The Breast and Prostate Cancer Cohort Consortium (BPC3) GWAS of Aggressive Prostate Cancer and ER- Breast Cancer

The Breast and Prostate Cancer Cohort Consortium (BPC3) was established in 2003 to pool data and biospecimens from nine large prospective cohorts to conduct research on gene-environment interactions in cancer etiology. The BPC3 initially focused on the association of >70 candidate genes in the Steroid Hormone Metabolism and IGF pathways with risk of breast and prostate cancer. The Consortium's work expanded in 2007 to include genome-wide association studies of estrogen receptor negative (ER-) breast cancer and aggressive prostate cancer. ER- breast cancers have specific epidemiologic characteristics and greater lethality, suggesting ER- breast cancer has a different etiology than ER+ breast cancer. Similarly, aggressive forms of prostate cancer, characterized by extraprostatic extension (Stage C/D) or high histologic grade (Gleason score 8+), differ epidemiologically from the vastly more common indolent forms of prostate cancer and are of the greatest clinical importance. By restricting cases to these specific subtypes, the BPC3 GWAS increased power to detect loci associated with ER- and aggressive prostate cancer (Kraft P and Haiman CA, Nature Genetics 2010 Oct;42:819-20, PMID: 20877320 ). The BPC3 GWAS includes the following cohorts: the American Cancer Society Cancer Prevention Study-II (CPS-II); the European Prospective Investigation of Cancer (EPIC); the Physician's Health Study (PHS); the Nurses' Health Studies I and II (NHS and NHSII); the Health Professionals Follow-up Study (HPFS); the Multiethnic Cohort (MEC); the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial; and the Alpha-Tocopherol, Beta-Carotene (ATBC) Study. For the GWAS of ER- cancer, the BPC3 was expanded to include the Polish Breast Cancer Study (PBCS), a population-based case-control study.

Study phs000812

Characterization of Human Transcriptome by Computational and HTS Approaches

We have deeply sequenced total RNA and whole exome of six different post-mortem human snap-frozen tissues (brain, liver, lung, striated muscle, kidney, heart) from three unrelated healthy Caucasian individuals (males, aged 47-54) with the aim to characterize post-transcriptional events due to alternative splicing and RNA editing. In addition, to facilitate the detection of RNA editing sites we have also resequenced the entire genome of each individual. Data are also used to investigate tissue-specific abundance of mitochondrial DNA from exomes and its correlation with mitochondrial transcription, mass and respiratory activity. Tissues were obtained from Cureline (South San Francisco, CA, USA). DNA and RNA were purified using the DNeasy Blood and Tissue Kit (Qiagen, Hilden, Germany) and the RNeasy Plus Mini Kit (Qiagen, Hilden, Germany), respectively. Exome capture was performed using the TruSeq Exome Enrichment Kit (Illumina, San Diego, CA) and the sequencing was carried out at IGA Technology Services in Udine (Italy) on Illumina HiSeq 2000 (generating for each tissue approximately 40 millions of 100bp paired-end reads). Strand-oriented RNA reads (2x100bp) were generated using the TruSeq Stranded Total RNA Sample Prep Kit (Illumina, San Diego, CA, USA) and sequenced at IGA Technology Services in Udine (Italy) on Illumina HiSeq 2000 platform. Whole genome resequencing was performed at Personal Genomics in Italy on an Illumina HiSeq 2000 platform (2x100bp) with a mean coverage of 30X. MiRNA-Seq was instead performed at IBBE Institute (Italy) using the TruSeq Small RNA Sample Prep Kit on Illumina MiSeq platform. Preliminary bioinformatics analyses have been performed to check quality using FASTQC software and inconsistent read regions have been trimmed using trim_galore. All reads were mapped onto the human reference genome (version hg19) using GSNAP.

Study phs000870

National Cancer Institute (NCI) Non-Hodgkin Lymphoma Genome-wide Association Study (GWAS)

Within the framework of the International Lymphoma Epidemiology Consortium (InterLymph) Consortium and NCI-sponsored Cohort Consortium, investigators from 22 studies came together to conduct a genome-wide association study (GWAS) of non-Hodgkin lymphoma (NHL). The goal of the study was to identify common genetic variants associated with the risk of NHL. As described previously (Berndt SI et al., Nature Genetics, 2013, PMID: 23770605 ), cases and controls from 22 studies, including nine prospective cohort studies, eight population-based case-control studies, and five clinic or hospital-based case-control studies were included in this effort. Cases of NHL were ascertained from cancer registries, clinics or hospitals, or through self-report verified by medical and pathology reports. The phenotype information for all NHL cases was reviewed centrally at the InterLymph Data Coordinating Center and harmonized according to the hierarchical classification proposed by the InterLymph Pathology Working Group based on the World Health Organization (WHO) classification (2008). Controls were frequency matched to cases on age and gender by study, and the study was limited to subjects of European ancestry. Participants were genotyped using the Illumina Omni Express. The NCI Non-Hodgkin Lymphoma GWAS is utilized in the following dbGaP sub-studies. To view genotypes and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000801 NCI Non-Hodgkin Lymphoma GWAS. phs000802 NCI Non-Hodgkin Lymphoma GWAS: CLL phs000818 NCI Non-Hodgkin Lymphoma GWAS: Controls phs000889 NCI Non-Hodgkin Lymphoma GWAS: DLBCL phs000890 NCI Non-Hodgkin Lymphoma GWAS: FL phs000891 NCI Non-Hodgkin Lymphoma GWAS: MZL

Study phs000801

The Human Pancreas Analysis Program (HPAP)

The past decade has seen a dramatic improvement in our ability to phenotype and molecularly profile human tissues with unprecedented resolution at the genomic, epigenomic, protein, and functional levels. The Human Pancreas Analysis Program (HPAP), part of the Human Islet Research Network and supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) through multiple NIH grants, is performing deep phenotyping of the human endocrine pancreas to better understand the cellular and molecular events that precede and lead to beta-cell loss and/or dysfunction in type 1 diabetes (T1D) and type 2 diabetes (T2D) as well as to accumulate, analyze, and distribute high-value data sets to the diabetes research community through the HPAP PANC-DB database (and additional details provided at that site). To this end, HPAP employs state-of-the-art technologies to perform comprehensive analyses of pancreas biology as it pertains to organ donors with T1D, autoantibody-positive donors without diabetes, donors with T2D, and control donors. Pancreas procurement and analyses take advantage of the expertise and extensive network of Organ Procurement Organizations (OPOs) and autoantibody screening centers established through the JDRF/The Lenona M. and Harry B. Helmsley Charitable Trust (HCT) – funded nPOD program. In contrast to nPOD, the major product provided by HPAP is not archived biomaterial subject to broad distribution, but rather, the delivery of extensive and high-quality molecular data sets to the diabetes research community in order to facilitate further discovery. Together, nPOD and HPAP are complementary programs that assist the diabetes community and afford the maximal opportunity for advancing knowledge about the pathogenesis of T1D and T2D.

Study phs002465

NHLBI GO-ESP: Family Studies (Hematological Cancers)

The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. Two major goals in the study of human malignancies are (i) to understand the genetic basis that underlies the predisposition of certain individuals to develop cancer and (ii) to identify the full spectrum of acquired mutations that occur in human cancers. There has been some progress in both of these areas with respect to hematologic malignancies but much remains to be discovered. As a result of recent advantages in sequencing technologies it is now feasible to sequence multiple individual whole exomes at reasonable cost. Such technologies provide a unique opportunity to transform our understanding of the biological basis of human cancer and to identify inherited genetic variants that predispose individuals to the development of hematologic malignancies. Myeloproliferative neoplasms (MPN), myelodysplastic syndrome (MDS) and acute leukemia are clonal disorders of hematopoieis. Our study involves performing whole exome sequencing of individuals with these disorders for the purpose of identifying (i) novel inherited genetic variants associated with the risk of developing of MPN/MDS/acute leukemia and (ii) novel acquired mutations associated with the development of MPN/MDS/acute leukemia.

Study phs000632

McGill Epigenomics Mapping Centre

The McGill Epigenomics Mapping Centre (EMC) and Data Coordination Centre (EDCC) were established in 2012 at the McGill University and Genome Quebec Innovation Centre (Montreal, Canada) to support large-scale human epigenome mapping for a broad spectrum of cell types and diseases. Previous epigenetic studies have provided profiles of specific chromatin marks in relation to basic biological processes, and future studies of molecular mechanisms must build upon these proofs-of-concept by integrating sequence-based variation with multiple levels of epigenetic and transcriptional regulation across the genome of human tissues and animal disease models. This project leverages the high-throughput sequencing infrastructure and expertise in genomics and transcriptomics at the McGill Innovation Centre to carry out this research. Controlled access to the data by collaborators and the greater scientific community is gained via a portal, which takes advantage of Compute Canada high-performance computing cluster resources to manage the large volume of data associated from the generation of reference epigenome maps. McGill University is one of two Canadian mapping and data coordination centres, the other based at the Michael Smith Genome Sciences Centre in Vancouver, British Columbia. The generation of comprehensive epigenome maps at McGill University is part of a larger international effort that is coordinated by the International Human Epigenome Consortium (IHEC), whose overall long-term objective is to determine the extent to which the epigenome shapes human populations over generations and in response to the environment. This project is funded under the Canadian Epigenetics, Environment, and Health Research Consortium (CEEHRC) by the Canadian Institutes of Health Research and by Genome Quebec, with additional support from Genome Canada. The computing and networking infrastructure, and part of the software development, are provided by Compute Canada and CANARIE.

Study EGAS00001000995

Center for Craniofacial and Dental Genetics (CCDG): Genetics of Orofacial Clefts, Sub-types, and Subclinical Phenotypes - CIDR

The purpose of this project is to identify the genetic factors contributing to nonsyndromic orofacial clefts (OFCs), common subtypes, and related subclinical phenotypes. The most common subtypes of OFCs are cleft lip alone (CL), cleft lip with cleft palate (CLP), and cleft palate alone (CP). CL and CLP can be unilateral (left or right) or bilateral. Related subclinical phenotypes include occult lip muscle defects, characteristics of craniofacial morphology, and subtle speech abnormalities, which are distributed within families of affected individuals, and may reflect the underlying genetic susceptibility revealing clues about OFC etiology. The multi-ethnic dataset comprises participants recruited from Pennsylvania, Puerto Rico, Colombia, Philippines, Nigeria, and Ghana, and includes individuals with OFCs (cases), their unaffected relatives, and unrelated healthy controls. The specific aims of this project are to perform genome-wide association (GWAS) scans of (1) OFCs, (2) cleft subtypes (CL, CLP, CP, and laterality subtypes), and (3) cleft-associated subclinical phenotypes to identify variants associated with manifestations across the cleft-risk spectrum. Phenotyping for participants involved characterization of the overt clefts in cases, including affected structures (lip, alveolus, hard and soft palates), visible microforms, completeness, and laterality. Individuals with syndromic forms of OFCs were excluded from participation. Subclinical features were collected for all participants, including unaffected relatives and controls. Orbicularis oris (upper lip muscle) defects were assessed by high-resolution ultrasonography and scored by three independent raters. Lip print patterns were assessed by digital photography and scored for paramedical whorls by three independent raters. Velopharyngeal insufficiency was assessed with perceptual screening by a speech-language pathology expert. This dataset has potential to improve knowledge of the genetic contributors to OFCs, subtypes, and associated subclinical phenotypes by facilitating genetic association discovery, meta-analysis, and replication efforts. Findings may ultimately be useful for predicting OFC risk and recurrence, and may enhance our understanding of OFC biology.

Study phs002815

Blood DNA Methylation in Post-Acute Sequelae of COVID-19 (PASC): a Prospective Cohort Study

Background: DNA methylation integrates environmental signals with transcriptional programs. COVID-19 infection induces changes in the host methylome. While post-acute sequelae of COVID-19 (PASC) is a long-term complication of acute illness, its association with DNA methylation is unknown. No universal blood marker of PASC, superseding single organ dysfunctions, has yet been identified. Methods: In this single center prospective cohort study, PASC, post-COVID without PASC, and healthy participants were enrolled to investigate their symptoms association with peripheral blood DNA methylation data generated with state-of-the-art whole genome sequencing (WGS). PASC-induced quality-of-life deterioration was scored with a validated instrument, SF-36. Analyses were conducted to identify potential functional roles of differentially methylated loci, and machine learning algorithms were used to resolve PASC severity. Findings: 103 patients with PASC (22.3% male, 77.7% female), 15 patients with previous COVID-19 infection but no PASC (40.0% male, 60.0% female), and 27 healthy volunteers (48.1% male, 51.9% female) were enrolled. Whole genome methylation sequencing revealed 39 differentially methylated regions (DMRs) specific to PASC, each harboring an average of 15 consecutive positions, that differentiate patients with PASC from the two control groups. Motif analyses of PASC-regulated DMRs identify binding domains for transcription factors regulating circadian rhythm and others. Some DMRs annotated to protein coding genes were associated with changes of RNA expression. Machine learning support vector algorithm and random forest hierarchical clustering reveal 28 unique differentially methylated positions (DMPs) in the genome discriminating patients with better and worse quality of life.

Study phs003658

Single cell RNA-seq mapping of nasal and tracheobronchial airways in human healthy volunteers

The respiratory tract constitutes an elaborated line of defense based on a unique cellular ecosystem. Single-cell profiling methods enable the investigation of cell population distributions and transcriptional changes along the airways. We have explored cellular heterogeneity of the human airway epithelium in 10 healthy living volunteers by single-cell RNA profiling. 77,969 cells were collected by bronchoscopy at 35 distinct locations, from the nose to the 12th division of the airway tree. The resulting atlas is composed of a high percentage of epithelial cells (89.1%), but also immune (6.2%) and stromal (4.7%) cells with peculiar cellular proportions in different sites of the airways. It reveals differential gene expression between identical cell types (suprabasal, secretory, and multiciliated cells) from the nose (MUC4, PI3, SIX3) and tracheobronchial (SCGB1A1, TFF3) airways. By contrast, cell-type specific gene expression was stable across all tracheobronchial samples. Our atlas improves the description of ionocytes, pulmonary neuro-endocrine (PNEC) and brush cells, which are likely derived from a common population of precursor cells. We also report a population of KRT13 positive cells with a high percentage of dividing cells which are reminiscent of “hillock” cells previously described in mouse. Robust characterization of this unprecedented large single-cell cohort establishes an important resource for future investigations. The precise description of the continuum existing from nasal epithelium to successive divisions of lung airways and the stable gene expression profile of these regions better defines conditions under which relevant tracheobronchial proxies of human respiratory diseases can be developed.

Study EGAS00001004082

Biallelic tumor suppressor loss and DNA repair defects in de novo small cell prostate cancer

Small cell prostatic carcinoma (SCPC) is an aggressive pathology that is managed similar to small cell lung cancer. SCPC can evolve from prostatic adenocarcinoma in response to androgen deprivation therapy but in rare cases is present at initial cancer diagnosis. The molecular etiology of de novo SCPC is incompletely understood due to the scarcity of tumor tissue and the brief life expectancy of patients. Through a retrospective search of our regional oncology pharmacy database, we identified 18 patients diagnosed with de novo SCPC between 2004 and 2017. Ten patients had pure SCPC pathology and the remainder had some admixed adenocarcinoma foci, but all were treated with first line platinum-based chemotherapy. Median overall survival was 28 months. We performed targeted DNA sequencing, whole exome sequencing and mRNA profiling on formalin-fixed paraffin embedded archival tumor tissue. We observed frequent biallelic deletion and/or mutation of tumor suppressors TP53, RB1 and PTEN, similar to treatment related SCPC. Indeed, at the RNA level pure de novo SCPC closely resembled treatment-related SCPC. However, five patients had biallelic loss of DNA repair genes including BRCA1, BRCA2, ATM and MSH2/6: potentially underlying the high genomic instability of this rare disease variant. Two patients with pure de novo SCPC harbored ETS gene rearrangements to androgen-driven promoters, consistent with evolution of de novo SCPC from an androgen-driven ancestor. Overall, our results reveal a highly aggressive molecular landscape underlies this unusual pathologic variant, and propose opportunities for targeted therapy strategies in a disease with few treatment options.

Study EGAS00001003007

How are we funded?

How are we funded? The EGA is provided infrastructure, administrative support, advisory input, and other relevant and necessary aspects by: CRG The EGA at the CRG is funded and supported by “La Caixa Foundation”, The Generalitat de Catalunya (Catalan Government), the Spanish Ministerio de Asuntos Económicos y Transformación Digital (Spanish Government) and the Instituto de Salud Carlos III. The Generalitat de Catalunya contributes with funding to the CRG and to the Barcelona Supercomputing Centre (BSC). The Barcelona Supercomputing Center is decisively contributing to EGA by providing the required compute, storage and networking resources, as well as key personnel for shared operations of EGA infrastructure. EMBL-EBI As part of the European Molecular Biology Laboratory (EMBL), the EGA at EMBL’s European Bioinformatics Institute receives funding from the governments of EMBL’s member states. The UK government, via UK Research and Innovation, also continues to support EMBL-EBI technical infrastructure, with EMBL supporting operational costs. A major source of funding for the EGA both at CRG and EMBL-EBI are competitive projects.The EGA resource continues to be funded through strategic engagement in collaborative partnerships and projects. Please see our projects page for more information. Other funders include the European Commission, the US National Institutes of Health, the Wellcome Trust, UK Research Councils, and our Industry Programme partners. Last updated on October, 2024.

Documentation about/projects-and-funders/funders

Integrated Analysis of Multimodal Single-Cell Data

The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single cell genomics and necessitates new computational methods that can define cellular states based on multiple data types. Here, we introduce 'weighted nearest neighbor' analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of hundreds of thousands of human white blood cells alongside a panel of 228 antibodies to construct a multimodal reference atlas of the circulating immune system. We demonstrate that integrative analysis substantially improves our ability to resolve cell states and validate the presence of previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets, and to interpret immune responses to vaccination and COVID-19. Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets, including paired measurements of RNA and chromatin state, and to look beyond the transcriptome towards a unified and multimodal definition of cellular identity. All CITE-seq and ECCITE-seq raw matrices are available in GEO database under the accession number GEO: GSE164378.

Study phs002315

Regulation of T Cell CXCL13 Production

This study evaluated the signals that regulate production of the B cell chemoattractant CXCL13 by human CD4 T cells. Single-cell and bulk RNA-seq datasets evaluated the gene expression changes induced by TGF-beta and the aryl hydrocarbon receptor (AHR), two signals that regulate CXCL13 production. Bulk ATAC-seq data evaluated the epigenetic changes in T cell stimulated with an AHR agonist or antagonist. Ex vivo bulk RNA-seq data of sorted T cell subsets from blood of patients with lupus and control donors interrogated the gene expression differences in sorted T cell subsets. Ex vivo ATAC-seq data allowed comparison of epigenetic profiles of PD-1hi Tph cells from rheumatoid arthritis synovial fluid and PD-1hi T follicular helper (Tfh) cells from tonsil to PD-1low CD4 T cells from the same samples. Single-cell RNA-seq data of T cells from lupus patients before and after treatment with anifrolumab (anti-IFNAR) allowed interrogation of T cell populations that change with anifrolumab treatment. These datasets allowed for genomic interrogation of changes induced by AHR, TGF-beta, and interferon and their relationship to CXCL13 production.

Study phs003582

Chicago Infant Mortality Study

The Chicago Infant Mortality Study (CIMS) was a population-based, prospective, case-control study conducted in metropolitan Chicago, Cook County, Illinois, to examine the risk factors for sudden infant death syndrome (SIDS) among a primarily Black population. Eligible case infants were aged birth to one year where the cause of death was determined to be SIDS while eligible control infants were aged one month to one year who died of other sudden unexpected infant death (SUID) causes. Recruitment occurred between November 1993 and April 1996. The goal of this ancillary multiomics study was to evaluate possible genetic and epigenetic determinates of SIDS and together with metabolomic profiles, identify novel clinical diagnostic tools to enable molecular autopsies and biomarkers to proactively identify and intervene in infants at greater risk of death from SIDS. The multiomics data was generated from medical examiner autopsy specimens and includes: whole exome sequencing genotypes; RNA-seq transcriptome and methylome profiles from autopsy heart tissue; and serum metabolomics profiles. The sample size available varies with the modality of the omics assay, but the total number of unique infants included is about 400.

Study phs003790

RNA sequencing and Illumina 2.5M SNP array data collected from 675 commonly used human cancer cell lines.

Tumor-derived cell lines have served as vital models to advance our understanding of oncogene function and therapeutic response1. Although substantial effort has been directed to defining the genomic constitution of cancer cell line panels2–4, the transcriptome – which represents the active program of a cell – remains understudied. Here, we describe RNA sequencing and SNP array analysis of 675 commonly used human cancer cell lines. We explore numerous transcriptome features including coding and non-coding gene expression, transcribed mutations, gene fusion and expression of non-human sequences. Aside from many known aberrations we find new surprising characteristics, including more than 2200 unique fusion gene pairs representing a vast, testable repertoire of oncogenic fusions, many of which have analogs found in primary human tumors. We show that a combination of multiple genome and transcriptome features in a novel pathway-based approach enhances prediction of response to various targeted therapeutics. Our results provide valuable new insights into these critical pre-clinical models and provide added context for interpreting the numerous studies that employ these widely used cell lines.

Study EGAS00001000610

Clonal Decomposition and DNA Replication States Defined by Scaled Single-Cell Genome Sequencing

Accurate measurement of clonal genotypes, mutational processes, and replication states from individual tumor-cell genomes will facilitate improved understanding of tumor evolution. We have developed DLP+, a scalable single-cell whole-genome sequencing platform implemented using commodity instruments, image-based object recognition, and open source computational methods. Using DLP+, we have generated a resource of 51,926 single-cell genomes and matched cell images from diverse cell types including cell lines, xenografts, and diagnostic samples with limited material. From this resource we have defined variation in mitotic mis-segregation rates across tissue types and genotypes. Analysis of matched genomic and image measurements revealed correlations between cellular morphology and genome ploidy states. Aggregation of cells sharing copy number profiles allowed for calculation of single-nucleotide resolution clonal genotypes and inference of clonal phylogenies and avoided the limitations of bulk deconvolution. Finally, joint analysis over the above features defined clone-specific chromosomal aneuploidy in polyclonal populations.

Study EGAS00001003190

Parallel Genomic Alterations of Antigen and Payload Targets Mediate Polyclonal Acquired Clinical Resistance to the Antibody Drug Conjugate Sacituzumab Govitecan

Sacituzumab Govitecan (SG), a novel antibody drug conjugate (ADC) incorporating the anti-TROP2 antibody hRS7 conjugated to a topoisomerase-1 inhibitor (SN-38) payload, is the first ADC to be approved for advanced triple negative breast cancer (TNBC). However, mechanisms governing therapeutic resistance to SG are not known. We sought to identify mechanisms of de novo and acquired resistance to SG through unbiased whole-exome sequencing (WES) and RNA sequencing analysis of pre-treatment and multi-site post-progression (autopsy) tumor specimens. We examined three metastatic TNBC cases exhibiting (1) de novo progression, (2) stable disease, and (3) a deep response followed by progression, then mapped the temporal and spatial genomic evolution of acquired resistance in the responding patient. We then conducted additional pre-clinical experiments to validate the observed resistance mechanisms. TROP2 RNA and gene copy number were associated with de novo resistance, as case (1) was found to have absent TROP2 expression in all specimens, case (2) expressed TROP2, while case (3) exhibited both expression and focal genomic amplification of the TACSTD2/TROP2 locus. The genomic phylogeny tree inferred from case (3) post-progression specimens revealed one branch harboring an acquired canonical E418K resistance mutation in TOP1 (encoding topoisomerase 1) and a subsequent sub-clonal TOP1 inactivating frameshift mutation, while a distinct branch exhibited acquisition of a novel T256R missense mutation in TACSTD2 (encoding TROP2). Both the TOP1- and TACSTD2-mutant clones seeded multiple distinct metastatic sites. Through reconstitution experiments in TROP2 negative cells we found that TROP2 T256R is a stable protein with defective cell membrane localization and reduced cell surface binding by RS7 compared to wild-type TROP2. Collectively, these findings underscore TROP2 as a determinant of initial response to SG, and they reveal parallel and mutually exclusive polyclonal molecular mechanisms of acquired resistance involving the direct antibody target and drug payload target in distinct metastatic subclones of a single patient. While further research is needed to extend these novel findings, this study highlights the specificity of SG and illustrates how identifying such mechanisms will inform rational therapeutic strategies to overcome ADC resistance.  

Study phs002555

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

A Pilot Study to Evaluate Tissue- and Plasma-based DNA Driver Mutations in a Cohort of Patients with Pancreatic Intraductal Papillary Mucinous Neoplasms

This is a retrospective study aimed at evaluating concordance between intraductal papillary mucinous neoplasm (IPMN) tissue and patient-matched plasma circulating tumor DNA (ctDNA) using a targeted sequencing approach. Archival solid tissue genomic DNA was available for 46 patient FFPE blocks patient-matched plasma ctDNA was available from 15 of those patients. All tissues were obtained pre-treatment from patients with an IPMN diagnosis and subjected to Qiagen custom next generation sequencing panel.

Study phs003043

Characterization of the Gut-Associated Microbiome in Inflammatory Pouch Complications Following Ileal Pouch-Anal Anastomosis

This study involved evaluation of the tissue associated microbiome of the ileal pouch following surgery for ulcerative colitis (UC) or familial adenomatous polyposis (FAP). Individuals were recruited, with biopsies taken from the ileal pouch and the pre-pouch ileum, microbial DNA was extracted and sequenced using 454 pyrosequencing. Total bacterial community structure and abundance were evaluated to determine which changes were characteristic of inflammatory phenotypes including pouchitis (inflammation of the ileal pouch) and a Crohn's disease-like phenotype.

Study phs000659

Expression quantitative trait loci influence DNA damage-induced apoptosis in cancer

The analysis of e2QTL allows for the identification of context-specific eQTL effects (Kim-Hellmuth et al. (2017), PMID: 28814792). To evaluate how inter-individual genetic variability influences the regulation of DNA damage-induced apoptosis, we performed e2QTL analysis of CD8+ T cells from 461 healthy European participants stimulated with high doses of 5 different carcinogens. These include Methyl-methanesulfonate (MMS), tert-butyl-hydroperoxide (TBOOH), benzo(a)pyrene-7,8-diol-9,10-epoxide (BPDE), 4-hydroxycyclophosphamide (HC) and UVC radiation.

Study EGAS50000000666

Multiregional single nuclei RNA-seq and WGS of prostate cancer

This study investigates the clonal evolution and metastatic dissemination of prostate cancer using multiregional single-nuclei RNA sequencing (snRNA-seq) and low-pass whole-genome sequencing (WGS) data from 43 spatially distinct tumor areas in five patients with locally advanced prostate cancer, including both primary and regional lymph node samples. We employed the Chromium Next GEM Single Cell 3’ Kit (v3/3.1, 10x Genomics) for single-nuclei transcriptome profiling and constructed bulk WGS libraries using the NEBNext Ultra II FS DNA Library Prep Kit (New England Biolabs) from the same pool of nuclei extracted from each area. snRNA-seq data were aligned to the human genome (GRCh38-1.2.0_premrna) using 10x Genomics Cell Ranger v5.0.0, while WGS reads were aligned to the human reference genome (GRCh38) with BWA MEM, achieving an average sequencing depth of 0.3X for low-pass WGS and 16X after resequencing.

Dataset EGAD50000001357

Analysis of genomic alterations in dedifferentiated liposarcoma

Multiomics analysis of rare cancers to identify genetic alterations related with pathogenesis and prognosis. To identification of genetics alterations of Dedifferentiated liposarcoma, DNAs and RNAs were extracted from dedifferentiated liposarcoma and paired non-cancer (normal) tissues. NGS libaraies were prepared by using Agilent SureSelect XT Human All Exon V5 + IncRNA kit for whole exome sequencing (WES) and TruSeq Stranded mRNA Prep kit or TruSeq RNA Access Library Prep kit (RNA seq). Sequencing was perfomred by Illumina HiSeq 2500.

Study JGAS000182

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