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• Loss of presentation of estimated neoantigens from mutated genes in ctDNA was essential for fostering primary to recurrent tumors in postoperative colorectal cancer cases

  Specific parameters regarding mutations at primary sites for the detection of postoperative recurrence using circulating tumor (ct)DNA liquid biopsy are lacking. In the current retrospective study, we conducted target resequencing of ctDNA using 47 plasma samples and established a cancer panel carrying the commonly mutated genes between primary and recurrent tumors. We found that mutated genes in ctDNA indicated immune-resistance traits with respect to the impaired ability to present neoantigens by loss of expression or binding affinity to HLA in the primary tumor. Compared with the estimated neoantigens from all mutated genes in primary tumors, the neoantigen peptides from commonly mutated genes between primary and recurrent tumors showed abundant and significant expression with no binding affinity to HLA. Therefore, ctDNA mutations can be frequently and postoperatively detected to identify recurrence; however, these mutated genes were derived from immune-tolerated clones owing to the loss of neoantigen presentation in primary CRC tumors.

  Study JGAS000549

• Bulk RNA sequencing of day 2 and day 7 biopsies from the tuberculin skin test in people with latent tuberculosis, and of day 2 biopsies from saline controls

  We used the tuberculin skin test (TST) as human challenge model to study the temporal evolution of the immune response to Mycobacterium tuberculosis (Mtb) antigens in vivo. Study participants comprised healthy HIV seronegative adults, 18-60 years of age. Latent tuberculosis (TB) infection was defined as immune memory for Mtb-specific antigens identified by positive peripheral blood IFNg release assays, but no clinical or radiological evidence of active TB. Two units tuberculin each were injected intradermally into the contralateral forearms of participants. After 2 days (n=216) or 7 days (n=158), 3 mm skin punch biopsies were taken from the injection sites and processed for whole genome transcriptional profiling by bulk RNA sequencing. The time points reflect maximum clinical inflammation (day 2) and maximum T cell infiltration (day 7) of the TST. TST samples were compared to skin biopsies taken two days after control injection of saline in a separate group of individuals (n=33), comprising healthy volunteers as well as patients with active or latent TB, ranging from 18-75 years of age. This dataset includes 407 samples from 256 individuals (n=33 saline, n=223 with Day 2 and/or Day 7 TST). Skin biopsies were collected into RNAlater (Qiagen) for RNA extraction. Total RNA was obtained with the Precellys Evolution homogenizer (Bertin Instruments) and Qiagen RNeasy mini kit. RNA was subjected to DNase treatment to remove contaminating genomic DNA using a TURBO DNA-free kit (Ambion, Life Technologies). The KAPA mRNA HyperPrep Kit (Roche Diagnostics) was used to construct stranded mRNA-Seq libraries from up to 500 ng intact total RNA. Paired-end sequencing was performed on the Illumina Nextseq using the Nextseq 500/550 High Output 75 cycle kit (Illumina). Runs were demultiplexed using bcl2fastq by Illumina.

  Dataset EGAD50000001208

• RaScALL: Rapid (Ra) screening (Sc) of RNA-seq data for prognostically significant genomic alterations in acute lymphoblastic leukaemia (ALL)

  RNA-sequencing (RNA-seq) efforts in acute lymphoblastic leukaemia (ALL) have identified numerous prognostically significant genomic alterations which can guide diagnostic risk stratification and treatment choices when detected early. However, a full RNA-seq Bioinformatics workflow is time-consuming and costly in a clinical setting where rapid detection and accurate reporting of clinically relevant alterations are essential. To accelerate the identification of ALL-specific alterations (including gene fusions, single nucleotide variants and focal gene deletions), we developed the rapid screening tool RaScALL, capable of identifying more than 100 prognostically significant lesions directly from raw sequencing reads. RaScALL uses the k-mer based targeted detection tool km and known ALL variant information to achieve a high degree of accuracy for reporting subtype defining genomic alterations compared to standard alignment-based pipelines. Gene fusions, including difficult to detect fusions involving EPOR and DUX4, were accurately identified in 98% (164 samples) of reported cases in a 180-patient Australian study cohort and 95% (n=63) of samples in a North American validation cohort. Pathogenic sequence variants were correctly identified in 75% of tested samples, including all cases involving subtype defining variants PAX5 p.P80R (n=12) and IKZF1 p.N159Y (n=4). Accurate detection of intragenic IKZF1 deletions resulting in aberrant transcript isoforms was also detectable with 98% accuracy. Importantly, the median analysis time for detection of all targeted alterations averaged 22 minutes per sample, significantly shorter than standard alignment-based approaches, ensuring accelerated risk-stratification and therapeutic triage.

  Dataset EGAD00001009087

• Identification of the Global miR-130a Targetome Reveals a Novel Role for TBL1XR1 in Hematopoietic Stem Cell Self-Renewal and t(8;21) AML

  In this study, we identified miR-130a as a regulator of HSC self-renewal and differentiation. To characterize gene expression changes following enforced expression of miR-130a OE, we performed RNA-seq in CD34+ cord blood (CB) cells transduced with control and miR-130a OE lentiviruses. To capture miRNA targets in an unbiased, transcriptome-wide manner, we perfomed enhanced CLIPseq procol in 2 replicates of CD34+ CB cells and Kasumi-1 cell line, which represent a model system for t(8;21) AML. We chose this cell line, as we found miR-130a to be highly expressed in this AML subtype where it is critical for maintaining the oncogenic molecular program mediated by AML1-ETO. Chimeric Ago2 eCLIPseq in CD34+ CB cells combined with Mass Spectrometry data analysis identified TBL1XR1 as a principal target of miR-130a. To elucidate gene expression changes associated with TBL1XR1 loss of function, we performed RNA-seq in CD34+CD38- CB cells transduced with control and shRNA targeted against TBL1XR1. To determine the functional significance of high miR-130a expression levels in Kasumi-1 cells on the molecular network controlled by AML1-ETO, we performed CUT&RUN assay and RNA-seq in Kasumi-1 cells following miR-130a knock-down (KD). Collectively, our findings reveal a unique role of miR-130a in regulating normal hematopoietic stem cell self-renewal and how elevated levels of miR-130a in t(8;21) AML contribute to the leukemogenesis of this AML subtype.

  Dataset EGAD00001008412

• Diagnostic utility of whole genome sequencing in adults with B-other acute lymphoblastic leukemia

  Genomic profiling at diagnosis of B-cell precursor Acute Lymphoblastic Leukemia (BCP-ALL) in adults is used to guide disease classification, risk stratification and treatment decisions. Patients for which diagnostic screening fails to identify disease defining or risk stratifying lesions are classified as B-other ALL. We screened a cohort of 652 BCP-ALL cases enrolled in UKALL14 to identify and perform whole genome sequencing (WGS) on paired tumor-normal samples. For 52 B-other patients we compared WGS findings to data from clinical and research cytogenetics. WGS identifies a cancer associated event in 51/52 cases, this includes an established subtype defining genetic alteration in 5/52 that were previously missed by standard-of-care genetics. Of the 47 true B-other ALL we identified a recurrent driver in 87% (41).  Complex karyotype by cytogenetics emerges as a heterogeneous group, underlied by distinct genetic alterations associated with either favorable (DUX4-r) or poor outcomes (MEF2D-r, IGK::BCL2). For a subset of 31 cases, we integrate findings from RNA-sequencing (RNA-seq) analysis to include fusion gene detection, and classification by gene expression. Compared to RNA-seq, WGS was sufficient to detect and resolve recurrent genetic subtypes, however RNA-seq can provide orthogonal validation of findings. In conclusion, we demonstrate that WGS can identify clinically relevant genetic abnormalities missed by standard-of-care testing and identify leukemia driver events in virtually all cases of B-other ALL.

  Dataset EGAD00001009304

• Natural history of clonal haematopoiesis (2017-09-04)

  The incidence of acute myeloid leukemia (AML) increases with age and mortality exceeds 90% when diagnosed after age 60. Only 10-15% of cases evolve from a pre-existing myeloproliferative or myelodysplastic disorder; the remaining cases arise de novo without a detectable prodrome and are diagnosed upon development of bone marrow failure. Analysis of diagnostic blood samples has demonstrated that de novo AML is preceded by the accumulation of somatic mutations in pre-leukemic hematopoietic stem and progenitor cells (preL-HSPCs) that subsequently undergo clonal expansion. If individuals in this pre-leukemic phase could be identified, methods for determination of risk and monitoring for progression to overt AML could be developed. However recurrent AML mutations also accumulate during aging in healthy individuals who never develop AML, referred to as age related clonal hematopoiesis (ARCH). To distinguish individuals with preL-HSPCs at high risk of developing AML from those with ARCH, we undertook deep targeted sequencing of genes recurrently mutated in AML in blood samples from 133 individuals in the European Prospective Investigation into Cancer and Nutrition (EPIC) study taken on average 6 years before they developed AML (pre-AML group), together with 683 matched healthy individuals (Control group). Pre-AML cases displayed accelerated age-correlated accumulation of somatic mutations.The identity, number and variant allele frequency (VAF) of mutations differed between the two groups, and were incorporated into a computational model of AML risk prediction that accurately distinguished pre-AML cases from controls on average 7 years prior to AML development. Our findings provide proof of concept that early prediction of AML development is feasible in high-risk populations, paving the way for early disease detection, monitoring, and potentially prevention.

  Dataset EGAD00001003703

• Quick Guide for data submission

  Quick Guide This is a quick guide to submit data to the EGA. Please select data type to display the right detailed instructions. Sequence data Array-based data Get your submission account You first need to create your EGA user. Then, once your account has been verified by the Help Desk team, request your submission account and provide details of the data type and platform(s) in your submission. Register Study/DAC Use Submitter Portal to register your study, samples, Data Access Committee (DAC) and Policy. Upload data Encrypt your data files using the and upload it to your inbox using SFTP. Register experiments and runs Associate each data file to a registered sample and study by Linking files to samples. Details of the experimental procedure you followed must be provided. Finalise your submission Group your runs/analysis into datasets and link them to your new or existing DAC and policy using DAC Portal. Data request are done at a dataset level, thus files within a datasets must share release conditions. Release and admin When finalising the submission, set a released date to instruct our Helpdesk to release your study. All registered studies are automatically placed on hold until the named submission or DAC contact instructs our Helpdesk for the study to be released. Get your submission account Fill the submission form and provide details of the data type and platform(s) in your submission. Register Study/DAC Use EGA Programmatic submission to register your study, samples, Data Access Committee (DAC) and Policy. Upload data Encrypt your data files using the EgaCryptor and upload it using default FTP clients or Aspera. Complete the Array-Format (AF) spreadsheet Download the AF spreadsheet and complete all four sections. Return the spreadsheet to the EGA helpdesk. Release and admin Instruct our Helpdesk to release your study. All registered studies are automatically placed on hold until the named submission or DAC contact instructs our Helpdesk for the study to be released.

  Documentation submission/quickguide

• Coverage bias and sensitivity of variant calling for four whole-genome sequencing technologies

  Massively parallel sequencing has revolutionized research in cancer genetics and genomics and enhanced our understanding of natural human genetic variation. Recently, Lam et al. have performed a detailed comparison of two next-generation sequencing technologies with respect to their sensitivity to call single nucleotide variants (SNV) and indels. Here, we sequenced two tumor/normal pairs obtained from two paedriatic medulloblastoma patients with Life Technologies’ SOLiD 4 and 5500xl SOLiD, Illumina’s HiSeq2000, and Complete Genomics’ technology. We then compared their ability to call SNVs with high confidence. As gold standard for SNV calling, we used genotypes determined by an Affymetrix SNP array. Additionally, we performed a detailed analysis of how evenly each technology covers the genome and how the reads are distributed across functional genomic regions. Finally, we studied how a combination of data from different technologies might help to overcome the limitations in SNV calling by any of the four technologies alone.

  Study EGAS00001000274

• A comprehensive characterization of the cell-free transcriptome reveals tissue- and subtype-specific biomarkers for cancer detection

  Cell-free RNA (cfRNA) is a promising analyte for cancer detection. However, a comprehensive assessment of cfRNA in individuals with and without cancer has not been conducted. We performed the first transcriptome-wide characterization of cfRNA in cancer (stage III breast [n=46], lung [n=30]) and non-cancer (n=89) participants from the Circulating Cell-free Genome Atlas (NCT02889978). Of 57,820 annotated genes, 39,564 (68%) were not detected in cfRNA from non-cancer individuals. Within these low-noise regions, we identified tissue- and cancer-specific genes, defined as "dark channel biomarker" (DCB) genes, that were recurrently detected in individuals with cancer. DCB levels in plasma were correlated with tumor shedding rate and RNA expression in matched tissue, suggesting that DCBs with high expression in tumor tissue could enhance cancer detection in patients with low levels of circulating tumor DNA. Overall, cfRNA provides a unique opportunity to detect cancer, predict the tumor tissue of origin, and determine the cancer subtype.

  Study EGAS00001004704

• Evaluation of size selection on cancer specific sequencing libraries

  A couple of previously characterized and sequenced libraries will be repeated using a couple of differing size selection criteria and skim sequenced using an Illumina HiSeq. The resulting sequence will be analyzed to determine the optimal DNA library size for our specific downstream analysis.

  Dataset EGAD00001000301

• Piloting exome resequencing in consanguineous families with homozygosity mapping intervals

  This pilot study aims to generate pilot data to inform future study designs in consanguineous families or inbred populations by resequencing the exome of six individuals from five families with neurodevelopmental diseases. For all of these families a single mapping interval containing the causal variant has previously been identified.

  Dataset EGAD00001000341

• Tcells_CD_scRNAseq

  This set features unfiltered, aligned, UMI-based single cell RNA sequencing count data for 5290 Blood, intraepithelial ileum (IEL) and lamina propria ileum (LPL) T cells from Crohn's disease patients as published in Uniken Venema et al, Gastroenterology 2019

  Dataset EGAD00010001649

• ChIP-seq ERa in primary breast cancer tissues

  ChIP-seq has been perfomed on 5 tumor fresh-frozen primary breast cancer tissues from female patients. Immunoprecipitation has been performed for ERa (SC-543, Santa Cruz). Raw single-end fastq data have been aligned using bwa-mem using Hg19 genome assebly as reference. Unfiltered aligment bam files are provided.

  Dataset EGAD50000000014

• University of Bergen Rare Monogenic Autoimmune Syndrome (APS-1) Data Access Committee

  This is the DAC appointed by the University of Bergen for the datasets related to the study of APS-1 in the Department of Clinical Sciences . These data are from single cell transcriptomic analysis of expanded Tregs from patients with the rare monogenic autoimmune syndrome “APS-1” compared to healthy donors.

  Dac EGAC50000000081

• Exome sequencing for heterogeneity and evolution of DNA mutation rates

  Dataset comprising 27 pairs of high-depth (300x) WES results obtained from 54 PDXs derived from primary CRCs resected synchronously with their corresponding metastases. These exoms sequences are part of a larger study on the heterogeneity and evolution of DNA mutation rates in microsatellite-stable colorectal cancer.

  Dataset EGAD50000000208

• Prediction of plasma ctDNA fraction and prognostic implications of liquid biopsy in advanced prostate cancer

  Targeted cfDNA and WBC sequencing data from patients profiled in the study "Prediction of plasma ctDNA fraction and prognostic implications of liquid biopsy in advanced prostate cancer". Note that 'Exome sequencing' is listed under Dataset Type since there is no option for targeted panel sequencing.

  Dataset EGAD50000000303

• RNA sequencing

  For RNA sequencing: All sample numbers starting with 6717 are tumor samples which has been sequenced using transcriptomics (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). RNA sequencing is performed using the Illumina Novaseq 6000 system.

  Dataset EGAD50000000383

• Human Brain Small Extracellular Vesicles Contain Selectively-Packaged, Full-Length mRNA

  sEVs were isolated from postmortem human brain tissue. RNA was extracted from the source brain tissue and the sEVs and prepared for RNA sequencing. cDNA was sequenced on the Illumina HiSeq using a 2x150 paired-end read configuration.

  Dataset EGAD50000000042

• Sputum RNA-Seq from Asthmatic Patients for Microbes and Genes

  RNA-seq files and other data associated with an investigation of the relationship between microbes, genes and immune cells present in the sputum of humans with asthma.

  Study phs002224

• Norwegian Institute of Public Health – Cancer Registry of Norway Data Access Policy for JanusRNA transcriptomics datasets archived in Federated EGA Norway

  JanusRNA transcriptomics datasets are generated from biobank samples from the Janus Serum bank of the Cancer Registry of Norway/National Institute of Public Health. This Data Access Committee has been appointed to govern controlled access to these datasets archived in Federated EGA Norway.

  Dac EGAC50000000192

• ctDNA diva aggregate data

  ctDNA biomarker and relevant clinical data for divarasib phase I GO42144 study, including tumor type, KRAS G12C mutation detectability in plasma at baseline, baseline SLD, sites of metastasis, lines of therapy, best response, confirmed best response, PFS, ctDNA tumor fraction and KRAS G12C VAF at baseline/C1D15/C3D1.

  Dataset EGAD50000000454

• Prognostic whole-genome and transcriptome signatures in colorectal cancers

  This dataset consists of RNA-seq CRAM raw-data files of 1063 primary colorectal cancer and 120 adjacent normal tissue samples. The expression profiles for these samples can be found at the ArrayExpress with accession number E-MTAB-12862.

  Dataset EGAD50000000169

• Dataset for acute myeloid leukemia samples

  This dataset contains RNA, ATAC and WGS sequencing data of 9 acute myeloid leukemia samples. Sequencing was performed on Illumina HiSeq 2000, HiSeq 4000, NovaSeq 6000 and HiSeq X Ten. The sequencing was always paired.

  Dataset EGAD50000000175

• Single-cell/single-nucleus RNA-seq of diffuse hemispheric gliomas, H3G34-mutant.

  9 DHG-H3G34 patient samples were sequenced by paired-end scRNA-sequencing using the Smart-Seq2 protocol on a NextSeq 500 sequencer (Illumina). Illumina bcl2fastq 1.5 was used for demultiplexing. This dataset contains the resulting 9,408 fastq files of 4,704 single cells/nuclei sequenced.

  Dataset EGAD50000000760

• D1D2 trial Whole Exome Sequencing (WES)

  Surgical treatment of gastric cancer: 15-year follow-up results of the randomised nationwide Dutch D1D2 trial. Molecular characterisation of N=80 resectable gastric adenocarcinomas from D1D2 trial, describing mutations obtained by matched (Tumor-Normal) whole exome sequencing (WES). Samples are annotated for TCGA’s molecular classification (MSI, GS and CIN).

  Dataset EGAD50000001144