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• Complex structural variation patterns in pediatric solid tumors

  In this study, we performed systematic characterization of chromoplexy, chromothripsis and extrachromosomal DNA across five types of pediatric solid tumors: neuroblastoma, Ewing sarcoma, Wilms tumor, hepatoblastoma and rhabdomyosarcoma. Almost half of all tumors had at least one complex SV and we identified candidate pathogenic events that affect genes or chromosomal alterations known to be relevant in these cancer types. In conclusion, complex SVs are prevalent and highly pathogenic in pediatric solid tumors.

  Study EGAS00001007565

• Nanostring – melanoma samples

  This dataset comprises gene expression data generated using the Nanostring nCounter platform from metastatic melanoma samples. RNA extracted from tumour tissues was analysed using targeted gene expression panels, including immune-related and tumour-resident T cell signatures. The dataset includes RCC files and associated normalised counts derived from patients with differing responses to immune checkpoint inhibitor therapy. These data enable targeted profiling of immune and tumour transcriptional programs associated with treatment response and resistance.

  Dataset EGAD50000002477

• Single cell RNA-seq and ATAC-seq of human fetal forebrain tissue, weeks 8 to 11.

  Single cell RNA-seq from 6 and single nuclei ATAC-seq from 3 human fetal tissue samples. Samples from 8 to 11 weeks. Includes a 8.5 weeks samples with matching both ATAC-seq and RNA-seq runs. Data was sequenced using 10X Genomics chromium technology, for scRNA-seq samples belong to v2 and v3.

  Dataset EGAD00001008653

• Sequencing data from a phase II study of nivolumab and ipilimumab in recurrent or refractory cancer of unknown primary (CheCUP trial)

  Sequencing data from a phase II study of nivolumab and ipilimumab in recurrent or refractory cancer of unknown primary (CheCUP trial). Panel sequencing data from baseline FFPE biopsies were used to perform a comprehensive genomic profiling of CUP metastases. Combined targeted next-generation sequencing of patient-specific hotsport mutations and shallow whole genome sequencing of baseline and follow-up liquid biopsy samples were used to analyze ctDNA and to evaluate response to immunei checkpoint inhibitor treatment. In some cases, whole exome sequencing of peripheral blood mononuclear cells was performed to screen for potential CHIP and germline mutations.

  Dataset EGAD00001011130

• FASTQ files of the RNA-Seq data for the study "Genomic landscape of lung adenocarcinoma in East Asians"

  FASTQ files of the RNA-Seq data for both the normal and tumor samples for the study "Genomic landscape of lung adenocarcinoma in East Asians". For raw read count data as well as other metadata, please download from https://src.gisapps.org/OncoSG_public/study/summary?id=GIS031 by clicking the download icon next to the dataset title.

  Dataset EGAD00001004421

• FASTQ files of the Exome-Seq data for the study "Genomic landscape of lung adenocarcinoma in East Asians"

  FASTQ files of the Exome-Seq data for both the normal and tumor samples for the study "Genomic landscape of lung adenocarcinoma in East Asians". For mutations and copy number variants called by this study, please download from https://src.gisapps.org/OncoSG_public/study/summary?id=GIS031 by clicking the download icon next to the dataset title.

  Dataset EGAD00001004422

• The Dutch Microbiome Project Batch 2

  The Dutch Microbiome Project (DMP) data includes shotgun metagenomic sequencing of faecal samples 8,208 Dutch individuals. Paired-end sequencing was performed using Illumina HiSeq 2000 platform. Data is archived in two batches to facilitate easier data access and upload to EGA. Batch 2 of DMP includes ~400 samples.

  Dataset EGAD00001007501

• Other NS tumors

  The dataset represents a total of 18 DNA samples from 6 male and 3 female pediatric patients affected with central or peripheral nervous system tumors not classified as embryonal central nervous system tumors, nor gliomas, glioneuronal, or neuronal tumors. One tumor tissue sample and one peripheral blood sample from each patient were subject to whole genome sequencing (WGS) and were sequenced 2x150 bp paired-end on an Illumina HiSeqX v2.5 instrument. The FASTQ files generated were aligned to the human reference genome sequence GRCh38/hg38 using bwa-mem, with the ALT-aware option turned on. Sorting of reads and marking of PCR duplicates was performed with GATK. Base quality score recalibration and joint realignment of reads around insertions and deletions (indels) were conducted using GATK tools. The dataset consists of 18 files in the CRAM format (lossless compression) with a total file size of ~3,4 TB. Additional genomic and molecular data (FASTQ, BAM, IDAT, and VCF files) and limited clinical data can be requested by ethically approved projects conducting research in the field of pediatric cancer.

  Dataset EGAD50000000299

• Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification (H021)

  Systemic pan-tumor analyses may reveal the significance of common features implicated in cancer immunogenicity and patient survival. Here, we provide a comprehensive multi-omics data set for 32 patients across 25 tumor types for proteogenomic-based discovery of neoantigens. By using an optimized computational approach, we discover a large number of tumor-specific and tumor-associated antigens. To create a pipeline for the identification of neoantigens in our cohort, we combine DNA and RNA sequencing with MS-based immunopeptidomics of tumor specimens, followed by the assessment of their immunogenicity and an in-depth validation process. We detect a broad variety of non-canonical HLA-binding peptides in the majority of patients demonstrating partially immunogenicity. Our validation process allows for the selection of 32 potential neoantigen candidates. The majority of neoantigen candidates originates from variants identified in the RNA data set, illustrating the relevance of RNA as a still understudied source of cancer antigens. This study underlines the importance of RNA-centered variant detection for the identification of shared biomarkers and potentially relevant neoantigen candidates.

  Study EGAS00001006706

• ScRNA sequencing and snp-array genotyping of peripheral immune cells in Type 1 diabetes mellitus (T1DM)

  Type 1 diabetes mellitus (T1DM) is a prototypic endocrine autoimmune disease resulting from an immune-mediated destruction of pancreatic insulin-secreting beta-cells. A comprehensive immune cell phenotype evaluation in T1DM has not been performed thus far at the single. In this cross-sectional analysis, we generated a single-cell transcriptomic dataset of peripheral blood mononuclear cells (PBMCs) from 46 manifest T1DM (Stage 3) cases and 31 matched controls.Our study reveals a surprisingly strong systemic dimension at the level of immune cell network in T1DM, defines disease-relevant molecular subtypes and has the potential to guide non-invasive test development and patient stratification.

  Dataset EGAD50000000345

• Single-cell RNA-seq of peripheral blood mononuclear cells in classic Hodgkin lymphoma

  Abstract: Classic Hodgkin lymphoma (cHL) is a largely MHC class I-negative tumor with recurrent 9p24.1/ PD-L1/ PD-L2 copy gains and the highest reported response rates to PD-1 blockade. We utilized scRNA sequencing to characterize the peripheral immune response to PD-1 blockade and more broadly define non-CD8+ dependent mechanisms of immune evasion in cHL. Peripheral blood mononuclear cells were obtained from 20 patients with relapsed/refractory (R/R) cHL treated with PD-1 blockade (nivolumab) on the CheckMate 205 clinical trial (paired samples from cycle 1 day 1 [C1D1] and cycle 4 day 1 [C4D1]), 11 patients with newly diagnosed, previously untreated cHL and 13 healthy donors.

  Dataset EGAD00001011360

• RNA-seq dataset: Single-cell spatial analysis of pediatric high-grade glioma reveals a novel population of immunosuppressive and tumor-promoting SPP1+/GPNMB+ myeloid cells

  Our study utilizes two novel techniques, cyclical immunofluorescence imaging and single-cell spatial transcriptomics, to spatially map the tumor microenvironment of a large sample set of pediatric high-grade gliomas (pHGG). Using these methods, we have identified an abundant immunosuppressive myeloid cell population that has not been described in the context of pediatric high-grade gliomas. We validate our findings using an in vitro assay, spatial analysis on additional pHGG biopsies, independent spatial transcriptomic data, bulk RNA sequencing data of an expanded cohort of in-house patients, and publicly available bulk RNA sequencing data of an even larger cohort of pHGG patients.

  Dataset EGAD00001015450

• Somatic L1 retrotransposition dynamics in high-grade serous ovarian cancer

  Somatic L1 retrotransposition was mapped in high-grade serous carcinoma (HGSC) tumors using LDI-PCR/Nanopore-seq method. This method identifies somatic L1 insertions originating from two active L1 loci at chr22q12.1 and chrXp22.2. Multiple tumors from same patient were utilised to understand L1-mediated intrapatient heterogeneity.

  Study EGAS50000001198

• WGS of CTCs enriched using high-throughout microfluidic device from entire cancer patient leukopak

  Single-cell low-pass WGS analysis (illumina platform, PE150, 1-2x coverage) was performed on CTCs enriched using high-throughout microfluidic device from entire leukopak from patients with metastatic prostate cancer (GU-1 and GU-2) and metastatic hepatocellular carcinoma (HCC-1 and HCC-2).

  Study EGAS50000000723

• Identification of causal mutation in two patients with Sotos Syndrome Features

  We performed whole exome sequencing (WES) on genomic DNA derived from two patients with Sotos Syndrome Features. Sequencing (100 base pair paired-end) was performed on an Illumina Hiseq 2000 sequencer after enrichment of 62Mb of exonic and adjacent intronic sequences with TruSeq Exome Enrichment Kit (Illumina, San Diego, CA, USA).

  Study EGAS00001000993

• WES and RNA-seq data of 11 cancer patients with multiple cancer types

  This dataset includes WES and RNAseq from 11 patients with metastatic melanoma, lung, kidney, and stomach cancers, enrolled in phase I clinical trials of TIL ACT (NCT03475134 & NCT04643574). WES was performed on matched cancer and healthy samples, whereas RNAseq was performed on cancer tissues, using Illumina HiSeq 2500/4000 and Illumina NextSeq 550 systems. Paired-end reads are provided in fastq format.

  Dataset EGAD00001010169

• CATHeterization GENetics (CATHGEN)

  The CATHGEN biorepository consists of biological samples collected on 9334 sequential consenting individuals undergoing cardiac catheterization at Duke University Medical Center between 2001 and 2010 inclusive. The Institutional Review Board informed consent allowed for 50 mL of blood to be collected from fasting patients through the femoral arterial sheath during the catheterization procedure. Three 7.5 mL EDTA tubes for DNA extraction are stored at -80°C. The Duke Database for Cardiovascular Disease (DDCD) provides the bulk of the clinical data used for analysis. Follow-up includes mortality information gleaned from the National Death Index and Social Security Death Index plus follow-up phone calls and written questionnaires regarding MI, stroke, re-hospitalization, coronary re-vascularization procedures, smoking, exercise, and medication use.

  Study phs000703

• Single-cell RNA-sequencing reveals that glioblastoma recapitulates a normal neurodevetlopmental hierarchy

  10xGenomics single-cell RNA sequencing of glioblastoma patient tumor

  Dataset EGAD00001006206

• Mechanisms_of_patient_response_to_Dabrafenib_in_Melanoma

  Samples will be from the BRF113683 (BREAK-3) study which is a Phase III Randomized, Open-label Study Comparing GSK2118436 to Dacarbazine (DTIC) in Previously Untreated Subjects With BRAF Mutation Positive Advanced (Stage III) or Metastatic (Stage IV) Melanoma (n=250 enrolled)•NGS [Agilent capture (Sanger V2 panel): 360 genes and 20 gene fusions; Illumina HiSEQ Sequencing]•CNV: [via NGS or Affy SNP 6.0 or Illumina Omni (TBD)]Bioinformatics: Analysis will be performed using core Sanger informatics pipelines similar to those previously described (Papaemmanuil E et al. (2013) Blood. 22:3616 -3627). Briefly, copy number analysis will be performed using the ASCAT algorithm, and base substitutions, small insertions and deletions using the CAVEMAN and Pindel algorithms, respectively. Statistical approaches including generalized linear models will be used to predict clinical variables such as maximum clinical response and duration of response using genetic data. Sanger and EBI to conduct analysis; Raw data and correlation with clinical endpoints to be analyzed by both EBI/Sanger and GSK (unique pipeline analyses to increase call confidence)

  Study EGAS00001000946

• Tumour gene expression signature in primary melanoma predicts long-term outcomes: A prospective multicentre study

  Adjuvant systemic therapies are now routinely used following resection of stage III melanoma, however accurate prognostic information is needed to better stratify patients. We used differential expression analyses of primary tumours from 204 RNA-sequenced melanomas within a large adjuvant trial, identifying a 121 metastasis-associated gene signature. This signature strongly associated with progression-free (HR=1.63, p=5.24x10-5) and overall survival (HR=1.61, p=1.67x10-4), and validated in 177 regional lymph nodes metastasis as well as two externally ascertained datasets. The machine learning classification models trained using the signature genes performed significantly better in predicting metastases than models trained with clinical covariates (pAUROC=0.02), or published prognostic signatures. The signature score negatively correlated with measures of immune cell infiltration (ρ=-0.75, p<2.2x10-16), with a higher score representing reduced lymphocyte infiltration and a higher 5-year risk of death in stage II melanoma. Our expression signature identifies melanoma patients at higher risk of metastases and warrants further evaluation in adjuvant clinical trials.

  Study EGAS00001004664

• Mosaic structural variation sample

  Mosaic Normal-Tumor genomes are generated from real normal-tumor pairs with validated somatic variants. In this case, validated variants from the GRIDSS2 paper. Mosaic genomes were generated using GenomeMosaicMaker, an open-source software tool designed and implemented for this specific purpose. The variants provided in the VCF truth file for each mosaic tumor/normal pair were annotated using funnSV for SVs and VEP for SNVs and indels. All CRAM files are aligned to GRCh37. Please see https://github.com/EUCANCan/oncoliner and https://github.com/Computational-Genomics-BSC/GenomeMosaicMaker for more information.

  Study EGAS50000000460

• UNITO_Molpheno_Closed

  This dataset contains Whole Genome Sequencing, RNA-sequencing and ATAC-sequencing data obtained from PBMCs derived from blood samples of one patient with complex genomic rearrangements and the biological parents. The patient has multiple congenital anomalies and delayed development. Data access is closed.

  Dataset EGAD00001004863

• UMCU Molpheno Closed

  This dataset contains Whole Genome Sequencing and, if available, RNA-sequencing and/or ATAC-sequencing data obtained from PBMCs derived from blood samples of two patients with intellectual disability and/or multiple congenital anomalies and eight parents included in the University Medical Center Utrecht (The Netherlands). Data access is closed.

  Dataset EGAD00001004864

• A Study to Evaluate Denosumab in Young Patients With Primary Breast Cancer (D-Beyond)

  This is a prospective, single arm phase IIa trial in which patients with early breast cancer will receive pre-operatively two doses of denosumab 120mg subcutaneously one week apart (maximum 12 days) followed by surgery. Tumor, normal breast tissue and blood samples will be collected at baseline and at surgery. Post-operative treatment will be at the discretion of the investigator.Primary objective: to determine if a short course of RANKL inhibition with denosumab can induce a decrease in tumor proliferation rates as determined by Ki67 immunohistochemistry (IHC) in newly diagnosed, early stage breast cancer in pre-menopausal women.

  Dataset EGAD00001004391

• Transcriptional Response to Hypoxia in iPSC-Derived Endothelial Cells from a High Altitude Adapted Population

  We established lymphoblastoid cell lines from 10 adult individuals of Tibetan ancestry living in the Chicago area. These lines were reprogrammed to induced pluripotent stem cells (iPSC). We validated genetic ancestry by genome-wide SNP array genotyping and population genetic analyses. After being subjected to standard quality control testing iPSCs were differentiated into endothelial cells. Following differentiation, endothelial cells were isolated via a pull down protocol using beads coated with an antibody for a canonical surface cell marker of the vascular endothelium (CD144). Purified vascular endothelial cells were cultured in parallel in normoxia (20% O2) and hypoxia (1% O2) for 48 hours prior to harvesting and processing for bulk RNA-sequencing. We provide imputed genotype data and bulk RNA-sequencing data in normoxia and in hypoxia for each of the 10 individuals. We also provide multiplexed scRNA-sequencing data for the 10 Tibetan individuals pooled with 10 CHB individuals from the 1000 Genome Project. Additionally, we provide scRNAseq data for the cardiomyocytes derived from the same iPSC lines from the Tibetan individuals pooled together with cardiomyocytes derived from iPSC lines of 10 CHB individuals from the 1000 Genome Project. Lymphoblastoid cell lines from the CHB were reprogrammed to iPSCs and differentiated to cardiomyocytes using the same protocols as used for the Tibetans. The batches of 4 lines were balanced by sex and population. These iPSC-derived cardiomyocytes were cultured in hypoxia (1% O2) for 48 hours and subjected to scRNAseq in pooled batches of 3 or 4 lines. The CHB individuals included in this analysis were: NA18528, NA18531, NA18557, NA18596, NA18606, NA18608, NA18614, NA18619, NA18633, and NA18748.

  Study phs003758