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• Clinical Outcomes by Tumor Mutational Burden and Inflammatory Gene Expression With Combined Nivolumab and Ipilimumab or Monotherapy in Advanced Melanoma_CM67-RNASeq

  Purpose Exploratory analyses of CheckMate 066 and 067 trials were conducted to investigate associations of tumor mutational burden (TMB), a 4-gene inflammatory gene expression signature, and BRAF mutation status with tumor response, progression-free survival (PFS), and overall survival (OS) in patients with advanced melanoma. Patients and Methods Patients with known programmed death ligand 1 (PD-L1) expression and BRAF mutation status received nivolumab (NIVO) or dacarbazine in CheckMate 066 and either NIVO, ipilimumab (IPI), or NIVO+IPI in CheckMate 067. Whole exome sequencing and RNA sequencing were used to determine TMB and inflammatory gene expression signature scores, respectively. These biomarkers were evaluated in terms of their association with PFS and OS. Results In the NIVO, NIVO+IPI, and IPI arms of CheckMate 067, longer survival was associated with high (> median) versus low (≤ median) TMB with hazard ratios (HRs) (95% confidence interval [CI]) for PFS of 0.45 (0.30–0.65), 0.55 (0.38–0.81), and 0.60 (0.43–0.82), and for OS of 0.46 (0.30–0.71), 0.53 (0.34–0.82), and 0.52 (0.36–0.74), respectively. For NIVO-treated patients, these results were confirmed in CheckMate 066. A survival benefit was observed with high TMB and absence of BRAF mutation. Survival was associated with high versus low inflammatory signature scores with HRs (95% CI) for PFS of 0.56 (0.34–0.94), 0.40 (0.23–0.72), and 0.43 (0.27–0.70), and for OS of 0.37 (0.20–0.66), 0.38 (0.19–0.74), and 0.46 (0.27–0.79), in the NIVO, NIVO+IPI, and IPI arms, respectively. Weak correlations were observed between PD-L1, TMB, and the inflammatory signature. Conclusions Combined assessment of TMB, inflammatory gene expression signature, and BRAF mutation status may be predictive for response to immunotherapy in advanced melanoma.

  Dataset EGAD00001006306

• Molecular diagnosis of albinism (2018-03-14)

  Albinism is genetically heterogeneous rare genetic condition affecting 1:17000 in the Western world (but more frequent in Africa) whose main feature is a profound visual impairment, characterised by foveal hypoplasia, abnormal chiasmatic connections, nystagmus and photofobia. All these features result in severly altered visual acuity (<0,1), absent depth perception and poor night vision. People with albinism are primarily visually handicapped. In addition, for some types of albinism, the visual phenotype can be presented with partial or total hypopigmentation, hence resulting in a secondary phenotype which can lead to skin cancer if skin is not adequately protected. Recently a new syndrome has been described, FHONDA, with the same visual abnormalities of albinism but without pigment alteration. The traditional classification differentiates Oculoculatenous albinism (OCA), where hypopigmentation involves hair, skin and eyes versus Ocular Albinism (OA), where hypopigmentation only affects the eyes. These are non-sydrimic types of albinism. Some syndromic forms (Hermansky-Pudlak=HPS, Chediak-Higashi=CHS) affect cells beyond pigment cells, present in the lungs, immune system, platelets and intestines, resulting in more severe phenotypes that can be fatal. Mutations in at least 19 genes are assocaited with the corresponding types of albinism. Most hospitals will only diagnose the most frequent cases using traditional Sanger, MLPA approaches. Some will use CGH arrays. We aim to diagnose all cases of albinism through the Albinochip proposal, which combines a Sequenom first step of known mutations combined with subsequent NGS approaches. In some cases we fail to find a second mutation, these are good candidates for further full exome analyses. 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 2018-03-14.

  Dataset EGAD00001004039

• Clinical Outcomes by Tumor Mutational Burden and Inflammatory Gene Expression With Combined Nivolumab and Ipilimumab or Monotherapy in Advanced Melanoma - CM066-WES

  Purpose Exploratory analyses of CheckMate 066 and 067 trials were conducted to investigate associations of tumor mutational burden (TMB), a 4-gene inflammatory gene expression signature, and BRAF mutation status with tumor response, progression-free survival (PFS), and overall survival (OS) in patients with advanced melanoma. Patients and Methods Patients with known programmed death ligand 1 (PD-L1) expression and BRAF mutation status received nivolumab (NIVO) or dacarbazine in CheckMate 066 and either NIVO, ipilimumab (IPI), or NIVO+IPI in CheckMate 067. Whole exome sequencing and RNA sequencing were used to determine TMB and inflammatory gene expression signature scores, respectively. These biomarkers were evaluated in terms of their association with PFS and OS. Results In the NIVO, NIVO+IPI, and IPI arms of CheckMate 067, longer survival was associated with high (> median) versus low (≤ median) TMB with hazard ratios (HRs) (95% confidence interval [CI]) for PFS of 0.45 (0.30–0.65), 0.55 (0.38–0.81), and 0.60 (0.43–0.82), and for OS of 0.46 (0.30–0.71), 0.53 (0.34–0.82), and 0.52 (0.36–0.74), respectively. For NIVO-treated patients, these results were confirmed in CheckMate 066. A survival benefit was observed with high TMB and absence of BRAF mutation. Survival was associated with high versus low inflammatory signature scores with HRs (95% CI) for PFS of 0.56 (0.34–0.94), 0.40 (0.23–0.72), and 0.43 (0.27–0.70), and for OS of 0.37 (0.20–0.66), 0.38 (0.19–0.74), and 0.46 (0.27–0.79), in the NIVO, NIVO+IPI, and IPI arms, respectively. Weak correlations were observed between PD-L1, TMB, and the inflammatory signature. Conclusions Combined assessment of TMB, inflammatory gene expression signature, and BRAF mutation status may be predictive for response to immunotherapy in advanced melanoma.

  Dataset EGAD00001006309

• ICGC Benchmarking Exercise

  The main objective of this benchmark is the comparison of the full sequencing pipeline of different ICGC partners, including procedures, methods and performance of library preparation and whole-genome deep-sequencing. A secondary objective will be a follow-up comparison of data analysis pipelines for identification of germline and somatic variants subsequent to the results of the ICGC Somatic Variant Calling Pipeline Benchmark.

  Dataset EGAD00001000625

• Colorectal cancer GWAS on the Spanish population

  Data on Affymetrix 6.0 arrays for Genome-Wide Association Study of colorectal cancer in the Spanish population. Additionally, geographical origin for each sample is provided, which constitutes the largest to-date Spanish genomic sample population

  Dataset EGAD00010001715

• DNA methylation-based classification of sinonasal tumors [Proteomics data]

  This dataset includes raw label-free mass spectrometry proteomics data of different sinonasal tumor entities as well as normal sinonasal tissue. 72 samples were processed on a Q Exactive HF-X instrument coupled to an easy nanoLC 1200 system using one microgram of peptides and an 110 minutes gradient.

  Dataset EGAD00010002381

• RCC_HTA2.0_Buettner2022

  GeneChip HTA 2.0 data of primary renal cell carcinoma (RCC) related to Buettner et al, Genome Med 2022. Microarrays were normalized individually using the SCAN method from the R package SCAN.UPC (version 2.26.0, R version 3.6.1). Probe sets were summarized on the Entrez GeneID level using the annotation provided by BrainArray (version 23).

  Dataset EGAD00010002353

• PDX_HTA2.0_Guergen2022

  GeneChip HTA 2.0 data of primary renal cell carcinoma (RCC) and RCC metastases related to Guergen et al, Front Oncol 12:2022 889789. Microarrays were normalized individually using the SCAN method from the R package SCAN.UPC (version 2.34.0). Probe sets were summarized on the Entrez GeneID level using the annotation provided by BrainArray (version 25).

  Dataset EGAD00010002392

• Heterogeneity and evolution of DNA mutation rates in microsatellite-stable colorectal cancer

  A mutation accumulation experiment in colorectal cancer (CRC) derived tumoroids. A sequential single-cell cloning approach was adopted to measure the mutation rate in eight tumoroids obtained from five patients. WGS was also performed on their matched normal tissue and on standard tumoroids cultures without any cloning step.

  Dataset EGAD50000000411

• Investigating differential diagnostic and prognostic biomarkers in primary cutaneous follicle center lymphoma and follicular lymphoma using low-coverage whole-genome sequencing

  In this study, we analyzed 28 primary cutaneous follicle center lymphoma samples from 20 patients and compared the copy number profiles to a cohort of diagnostic samples of 64 nodal follicular lymphoma patients using low-coverage whole genome sequencing (lcWGS).

  Dataset EGAD50000000199

• BipEx-Landen: Bipolar Exome Sequencing

  This research project was a collaboration between the Karolinska Institute and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 5,876 Bipolar case/control samples from collaborators in Sweden. Genomic DNA from each samples was sequenced to a mean depth of 20x.

  Dataset EGAD50000000307

• Transcriptome atlas of brain organoid developent

  Single-cell Cut&Tag of three histone modifications and chromatin accessibility over a timecourse of brain organoid development from pluripotency. We profiled 5 time points of brain organoid development and 2 time points of retinal organoid development. We used scRNA-seq to profile transcriptome. Library preparation was carried out with the 10x genomics platform.

  Dataset EGAD50000000223

• Hi-C in breast healthy, primary cancer and metastatic tissues

  Hi-C libraries have been prepared by enzymatic digestion with MboI restriction enzyme and sonication (Covaris). Illumina single-indexig primers have been use to amplify ligated fragments. Hi-C experiments have been performed on 10 slices (50um thick) of fresh-frozen tissues or 10x10e6 Pleural Effusion cells. Raw paired-end fastq.gz files are provided.

  Dataset EGAD50000000643

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

  Dataset with eQTL and e2QTL metadata. The analyses were performed using CD8+ T cells from 461 healthy European participants stimulated with high doses of 5 different carcinogens to induce early apoptosis. 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.

  Dataset EGAD50000000941

• Single-cell RNA-sequencing on malignant and benign tissue samples

  Single-cell RNA-sequencing on malignant and benign tissue samples from untreated donors with colorectal adenocarcinoma and liver metastasis was performed in order to deduce tissue adaptive expression patterns of the disease. Matching tissue from five donors with untreated CRC and liver metastasis were sampled.

  Dataset EGAD50000001203

• DAC of "Gene expression adaptation of metastases to their host tissue"

  The DAC consists of Prof. Axel Hillmer, University of Cologne, Faculty of Medicine and University Hospital Cologne, Institute of Pathology, Cologne, Germany, e-mail: ahillmer@uni-koeln.de and Prof. Andreas Beyer, University of Cologne, Faculty of Mathematics and Natural Sciences, Cologne Excellence Cluster for Aging and Aging-Associated Diseases (CECAD), Cologne, Germany, e-mail: andreas.beyer@uni-koeln.de

  Dac EGAC50000000514

• Single-Cell Profiling of the Human Endometrium in Polycystic Ovary Syndrome: Uncovering Disease Signatures and Treatment Responses

  Single-nuclei map of human endometrial biopsies from women with and without PCOS to identify cell-type-specific disease signatures, compositional variations, and transcriptomic reversibility after a 16-week intervention with metformin or lifestyle. Single nuclei were extracted from 27 frozen endometrial biopsies for snRNA-seq using the 10X Genomics protocol.

  Dac EGAC50000000468

• HIV-phyloTSI: PANGEA (PCR amplicon)

  This dataset includes sample numbers TSI_0426 to TSI_0527 for the PANGEA (PCR amplicon) cohort of the study. Samples were generated by pooling four overlapping PCR amplicons (see Gall et al 2012, DOI: 10.1128/JCM.01516-12). The sequencing was conducted using the Illumina NovaSeq system. Each sample has a BAM file, and its associated reference file.

  Dataset EGAD50000001308

• Spatial and temporal transcriptome analysis on human skeletal muscle regeneration

  Skeletal muscle carries a unique ability for adaptation as well as regeneration that highly depends on a supportive cellular microenvironment. Here we show that spatial and single-cell transcriptomic analysis in human skeletal muscle is a unique approach to illuminate cellular interactions in the microenvironment.

  Dataset EGAD50000000263

• Aligned Low pass whole genbome sequencing of cell free and tumour DNA from 5 patients with high grade serous ovarian cancer. Samples have been aligned to hg19 and bam files uploaded

  This is the aligned bam files of 5 patients, with sequential sampltes from patients comprising cfDNA and FFPE extracted tumour DNA

  Dataset EGAD50000001632

• Whone genome DNA methylation profile

  Primary human CD4+ naive T cells were cultured in vitro and sorted based on the defined number of division steps which they have undergone. Of those populations (division 0/div4/div6) EMseq data were generated to assess the whole-genome DNA methylation profile. 2 independent experiments with 2 different donors were conducted

  Dataset EGAD50000001815

• GeoMx digital spatial profiling of NGS mRNA expression in pre-treatment biopsies from patients.

  This DAC is created to define the data controller (the person that determines the purposes for which and the means by which personal data is processed) for the following study: GeoMx digital spatial profiling of NGS mRNA expression in pre-treatment biopsies from patients with metastatic triple-negative breast cancer treated with PARP inhibitors.

  Dac EGAC50000000774

• Dynamic human admixture histories over the past ~1,300 years at the northern Himalayan frontier

  Whole-genome sequencing data from ten present-day individuals from Himachal Pradesh, India. DNA from these ten present-day individuals was converted to double-stranded libraries and sequenced on Illumina NovaSeq 6000 in 150 bp paired-end mode. The dataset consists of raw fastq and bam (hg19) files.

  Dataset EGAD50000001925

• PacBio Revio WGS on 10 carriers of ring and marker chromosomes

  Bam files containing PacBio HiFi reads from carriers of ring and marker chromosomes. The reads where genereated using the PacBio Revio platform. Each individual was sequenced to roughly 30X coverage on one flow cell per individual. The chromosome of interest is indicated in the file name.

  Dataset EGAD50000002111

• Data Access Committee for Maurice Lab - UMC Utrecht

  The Data Access Committee of the Maurice lab at the Center for Molecular Medicine, University Medical Center Utrecht, is responsible for reviewing and approving requests for access to controlled human transcriptomics and genomics data generated by the lab. The DAC ensures that data access requests are consistent with informed consent, ethical approvals, and applicable legal and institutional regulations, including GDPR.

  Dac EGAC50000000876

• MissionBio single cell DNA and protein seq for 2 samples

  This dataset contains MissionBio Targeted single-cell DNA and Protein sequencing data from a primary sample and a patient-derived xenograft (PDX) model, which is used to investigate the clonal evolution in the FOXF1/FENDRR ALL subtype. All the 2 samples are in bam file type.

  Dataset EGAD50000001793

• Chronic lymphocytic leukemia patient-derived xenografts recapitulate clonal evolution to Richter transformation

  Whole-genome sequencing (WGS) and RNA-seq data from patient-derived xenografts (PDXs) obtained from CLL and RT primary samples as described in Playa-Albinyana et al.

  Study EGAS00001006965

• Survival Benefit and Genetic Profile of Pemetrexed as Initial Chemotherapy in Selected Chinese Patients with Advanced Lung Adenocarcinoma

  NGS data of 12 patients enrolled in the Chinese Patient Assistance Program from multiple centers who received pemetrexed alone or combined with platinum as initial chemotherapy and continued pemetrexed maintenance therapy for advanced lung adenocarcinoma from November 2014 to June 2017.

  Dataset EGAD00001006287

• Dataset for melanoma-WHOLE_GENOME

  Rare cancer sequencing data of 22 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008889

• Selected samples from the Boston Children's Hospital Childrens Rare Disease Cohorts initiative

  These are some selected exomes from the first year of the Childrens Rare Disease Cohorts initiative at Boston Children's Hospital. Patients were drawn from the following cohorts: immunodeficiency, epilepsy, IBD, hearing loss, and orphan diseases. Raw sequencing was performed on Illumina NovaSeq 6000 machines, and aligned to hs37d5.

  Dataset EGAD00001006179

• RNA-seq of iPSC-derived microglia treated with miRNA mimics and inhibitors

  Microglia were derived from iPSCs and treated with mimics and inhibitors of the miRNAs hsa-miR-150-5p, hsa-miR-193a-3p and hsa-miR-19b-3p. RNA-sequencing was then performed to examine the effects of up- and down-regulation of the respective miRNAs.

  Dataset EGAD00001006842

• STAT1 AM RNAseq

  The transcriptome of peripheral blood cells (PBMCs) from control or patients with an activation mutation on the STAT1 gene was analyzed. This analysis aimed to identify the major changes in the circulating immune cells of patients with STAT1 mutation and compare this with the result of the perturbation prediction tool huva (human variation, R).

  Dataset EGAD00001006962

• Primary_DIPG_expression_profiles

  In this study, we used RNA-sequencing gene expression profiling in order to characterize specific phenotypic traits in DIPG. Seventeen primary tumor samples stereotactically biopsied at diagnosis by neurosurgeons in the Necker-Enfants Malades hospital (Paris, France) and snap-frozen for RNA extraction and subsequent poly-A mRNA purification.

  Dataset EGAD00001011080

• HDBR exome sequencing data (May 2022)

  Exome sequencing data from seven phenotypically abnormal human fetal samples. Anaysis perfomed using Illumina NovaSeq 6000, Twist Bioscience - Human Comprehensive Exome. Paired end fastq files were aligned to hg38 reference genome using BWA-MEM v0.7.15, followed by sorting using SAMtools sort v1.3.1, and duplicate reads marked using Picard Tools MarkDuplicates v2.18.2

  Dataset EGAD00001008825

• Single-Cell Protein Expression via scTAMseq Cite-seq

  This dataset contains single-cell surface marker expression profiles generated by integrating the Cite-seq protocol with scTAMseq. Samples were stained with an antibody panel targeting 45 (donor A.6 & A.7) and 56 (donors A.1-A.5, B.1-B.5, and X.2 ) surface proteins to enable robust phenotypic characterization.

  Dataset EGAD00001015497

• Low-coverage whole-genome sequencing (lcWGS) data of Genome in a Bottle (GIAB) reference samples

  This dataset contains low-coverage whole-genome sequencing (lcWGS) data generated from three GIAB reference samples (HG001–HG003) for method benchmarking and concordance analysis in FFPE-GWAS workflows. The data were generated using Illumina NovaSeq with paired-end 150bp reads and downsampled to 2x coverage.

  Dataset EGAD00001015533

• HDBR exome sequencing data (November 2022)

  Exome sequencing data from seven phenotypically abnormal human fetal samples. Anaysis perfomed using Illumina NovaSeq 6000, Twist Bioscience - Human Comprehensive Exome. Paired end fastq files were aligned to hg38 reference genome using BWA-MEM v0.7.15, followed by sorting using SAMtools sort v1.3.1, and duplicate reads marked using Picard Tools MarkDuplicates v2.18.2

  Dataset EGAD00001009715

• Mixture of 4

  Mixture of 4 unrelated individuals sequenced by 10x as a scRNA-seq. The dataset was then processed by Cell Ranger and deconvoluted to yield each individuals genetic profile. The clustering of SNPs is submitted as the processed file. The Sequencing fastqs are submitted as unprocessed files.

  Dataset EGAD00001008724

• Mixture of 3

  Mixture of 3 unrelated individuals sequenced by 10x as a scRNA-seq. The dataset was then processed by Cell Ranger and deconvoluted to yield each individuals genetic profile. The clustering of SNPs is submitted as the processed file. The Sequencing fastqs are submitted as unprocessed files.

  Dataset EGAD00001008729

• Pre-neoadjuvant treatment biopsy RNAseq breast cancer dataset

  This dataset contains RNAseq data of n=87 pre-treatment biopsies of triple negative and luminal- type breast cancer patients, all scheduled to receive neoadjuvant chemotherapy. Gene expression data is linked with treatment response and survival.

  Dataset EGAD00001008433

• Dataset for bone_cancer-WHOLE_GENOME

  Rare cancer sequencing data of 48 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008866

• 20190219_EGA_MelanomaOnTreatment

  Illumina platform sequencing data for matched tumour-normal DNA samples from 77 melanoma patients participating in a study investigating response to immunotherapy. Selected cases also have RNA sequencing of the tumour.

  Dataset EGAD00001004869

• Bulk RNA-sequencing of AML blasts pre and post culture

  This dataset contains 18 Fastq files from 9 samples (pre-culture (n=3), post culture in standard (n=4) or niche-llike (n=2) conditions) from 4 patients.They correspond to bulk RNA sequencing on Illumina instrument of libraries prepared using SMARTer Universal Low Input RNA Kit.

  Dataset EGAD00001008773

• Small RNA sequencing from CSF extracellular vesicles - PD/CTR

  The dataset contains FASTQ files referring to the study "Small RNA sequencing from CSF extracellular vesicles - PD/CTR". For this project, RNA was isolated from CSF extracellular vesicles obtained by ultracentrifugation. Libraries were prepared with the TruSeq Small RNA library prep Illumina, and sequencing conducted in the Illumina HiSeq4000.

  Dataset EGAD00001006629

• Dataset for cancer_of_unknown_primary-EXON

  Rare cancer sequencing data of 62 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008870

• Dataset for GIST-WHOLE_GENOME

  Rare cancer sequencing data of 18 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008876

• Dataset for synovial_sarcoma-EXON

  Rare cancer sequencing data of 34 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008898

• Dataset for upper_gastrointestinal_tumor-WHOLE_GENOME

  Rare cancer sequencing data of 28 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008901

• Oropharyngeal Squamous Cell Carcinoma Mutanome

  This dataset comprises genetic variation data (as somatic indels and snvs VCFs) of 38 OPSCC tumors. WES was done using NextSeq 500 System running in 150 cycles (2x 75bp paired-end) mode. Sequence information was converted to FASTQ format using bcl2fastq v2.20.0.422. VCFs were generated using the Strelka package.

  Dataset EGAD00001009167

• RNA sequencing of tumor samples from patients with Waldenstrom macroglobulinemia

  RNA was extracted from flow-sorted CD19+. RNA-Seq was performed on 32 samples of 30 patients (2 replicates per samples). RNA-Seq libraries were subjected to non-stranded paired-end (2 x 75 bp) sequencing on HiSeq 2500 (Illumina). The files are in FASTQ format.

  Dataset EGAD00001005324