14982 results for "cancer studies using rna-seq"

in 18.60 milliseconds.

• Oxford Nanopore targeted RNA-based amplicon data of 12 classical HLA genes

  The dataset consists of Oxford Nanopore targeted RNA-based amplicon data of 12 classical HLA genes (HLA-A, -B, -C, -DRA, -DRB1, -DRB3, -DRB4, -DRB5, -DQA1, -DQB1, -DPA1, and DPB1) of 50 healthy individuals. The 12 classical genes were sequenced in two separate gene pools on R9.4 flowcells using MinION sequencer. Per individual, gene pool 1 contains HLA-A, -B, -C, -DRB1, -DRB3, -DRB4, -DRB5, and -DPB1 and gene pool 2 HLA-DRA, -DQA1, -DQB1, and -DPA1. The dataset includes 100 fastq files of Oxford Nanopore 2D reads (50 for gene pool 1 and 50 for gene pool 2).

  Dataset EGAD00001006814

• Inhibition of CDK4/6 Promotes CD8 T Cell Memory

  Inhibitors of Cyclin-Dependent Kinase 4 and 6 (CDK4/6) have been recently deployed for the treatment of advanced breast cancer. Despite their success, the mechanism of action of these drugs is unclear. In mice, treatment with a CDK4/6 inhibitor improve T cell memory responses and protect mice against tumor rechallenge. We aimed to identify the correlates of this finding in human subjects. In this study, blood was collected from 5 breast cancer patients before and during treatment with the CDK4/6 inhibitors abemaciclib or palbociclib. Blood was also collected from 2 breast cancer patients who did not receive a CDK4/6 inhibitor. Recently activated CD8 T cells (CD45RO+ CD45RA+) were sorted and subjected to single-cell RNA sequencing.

  Study phs002448

• A capture methyl-seq protocol with improved efficiency and cost-effectiveness using pre-pooling and enzymatic conversion

  The opportunities for sequencing-based methylome analysis of clinical samples are increasing. To reduce its cost and the amount of genomic DNA required for library preparation, we aimed to establish a capture methyl-seq protocol, which adopts pre-pooling of multiple libraries before hybridization capture and TET2/APOBEC-mediated conversion of unmethylated cytosine to thymine. We compared a publicly available dataset generated by the standard Agilent protocol of SureSelect XT Human Methyl-Seq Kit and our dataset obtained by our modified protocol, EMCap, that adopted sample pre-pooling and enzymatic conversion. We confirmed that the quality of DNA methylation data was comparable between the two datasets. As our protocol, EMCap, is more cost-effective and reduces the amount of input genomic DNA, it would serve as a better choice for clinical methylome sequencing.

  Study JGAS000605

• Single-cell RNA sequencing of sorted regulatory T cells

  Single-cell RNA sequencing of flow cytometry enriched CD4+ CD127- CD25+ regulatory T cells from 8 systemic lupus erythematosus patients (SLE_001 to SLE_007, and SLE_009) collected at baseline (day 0, before interleukin-2 immunotherpay) and day 5 (after 1 treatment cycle of interleukin-2 immunotherapy). Sorted immune cells were hash tagged and then stained with TotalSeq Human Universal Cocktail (Biolegend) before further processing for single-cell RNA sequencing using the 10X-Genomics platform (incl. generation of TCR libraries). Samples from patients SLE_001, SLE_002, SLE_004, SLE_006 were collected and processed on the first day of experiment (Day 1), and samples from patients SLE_003, SLE_005, SLE_007, SLE_009 on the second day of experiment (Day 2). On each day, samples were pooled and distributed to four lanes on the chromium controller. Run ID 245269 and ID 245270 identify samples sequenced on separate flow cells. Provided are raw sequencing files.

  Dataset EGAD50000000663

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015713

• CIDR Estrogen Receptor Negative Breast Cancer in African American Women: DNA Methylation, Reproductive Events, and Mammary Epithelial Cell Populations

  We conducted methylation profiling of breast tumor DNA from Formalin-Fixed Paraffin-Embedded (FFPE) samples for 1,550 cases from a cohort of Black women from the Black Women’s Health Study (BWHS), the Women’s Circle of Health Study (WCHS), and from the Pathways Study using the Illumina MethylationEPIC array. We will examine differentially methylated loci (DML) between ER+ and ER- tumors, and by age at onset of breast cancer. Combining these data with previously analyzed samples (n=385), we will consider associations between reproductive risk factors and top DML by age at diagnosis and ER status, examining the complex relationships between methylation, tumor and patient characteristics, and reproductive risk factors using structural equation modeling.

  Study phs002688

• H3K27ac ChIP-seq in TMPRSS2:ERG positive and negative prostate cancer tissue samples

  The TMPRSS2:ERG (T2E) structural rearrangements typifies ~50% of prostate tumors and results in overexpression of the ERG transcription factor. Using chromatin data collected in T2E and non-T2E primary prostate tumors, we show a distinct cis-regulatory landscape between T2E and non-T2E, inclusive of Cluster Of Regulatory Elements (COREs). This is mediated by ERG co-option of HOXB13 and FOXA1 implementing a T2E-specific transcriptional profile. We also report a T2E-specific CORE on the structurally rearranged ERG locus arising from spreading of the TMPRSS2 locus pre-existing CORE, assisting in its overexpression. Finally, we show that the T2E-specific cis-regulatory landscape reveals a vulnerability against the NOTCH pathway. Taken together, our work shows that overexpressed ERG co-opts master transcription factors to deploy a unique cis-regulatory landscape inducing a druggable dependency on NOTCH signaling in T2E prostate tumors.

  Study EGAS00001002496

• Long-read-transcriptome-sequencing of CLL and MDS patients uncovers common molecular effects of SF3B1 mutations

  Mutations in SF3B1 occur frequently in patients with chronic lymphocytic leukemia (CLL) and myelodysplastic syndromes (MDS), and a full-length transcriptome approach can expand our current knowledge on SF3B1 mutation effects on RNA splicing. We applied long-read-transcriptome-sequencing (LRTS) to 44 MDS and CLL patients with and without SF3B1 mutations and found a large fraction (>60%) of novel isoforms. Furthermore, we revealed that mutation effects on alternative splicing were largely common in both cancer types and specifically altered the usage of introns as well as 3’-splice-sites. We combined the LRTS with genome-wide SF3B1-RNA binding maps and show multimodal binding at 3’-splice-sites highlighting a window of 12-21nt upstream of the canonical 3’-splice-site in which a dynamic switch in splice site usage is observable in patients carrying SF3B1 mutations. Our work presents the hitherto most complete LRTS study in CLL and MDS and provides a resource for further research on aberrant splicing in cancer.

  Study EGAS50000000053

• Chordoma Sequencing Project RNAseq

  This is a continuation of the Chordoma Sequencing Project. All cancers arise due to somatically acquired abnormalities in DNA sequence. Systematic sequencing of cancer genomes allows acquisition of complete catalogues of all classes of somatic mutation present in cancer. These mutation catalogues will allow identification of the somatically mutated cancer genes that are operative and characterise patterns of somatic mutation that may reflect previous exogenous and endogenous mutagenic exposures. In this application, we aim to perform whole genome sequencing on 10 chordoma matched genome pairs. RNA Sequencing/Methylation and SNP6 and an additional sequencing of three cancer cell lines will be added to this work.

  Dataset EGAD00001000653

• Multi-region RNA sequencing of tumour regions and tumour-adjacent normal lung tissue

  TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC).

  Study EGAS00001006517

• Human Liver Cohort (HLC)

  The Human Liver Cohort (HLC) study aimed to characterize the genetic architecture of gene expression in human liver using genotyping, gene expression profiling, and enzyme activity measurements of Cytochrom P450. The HLC was assembled from a total of 780 liver samples screened. DNA samples were genotyped on the Affymetrix 500K SNP and Illumina 650Y SNP genotyping arrays. Only data from those samples which were collected postmortem are accessible through this submission. These 228 samples represent a subset of the 427 samples included in the Human Liver Cohort Publication (Schadt, Molony et al. 2008, PMID: 18462017). RNA samples were profiled on a custom Agilent 44,000 feature microarray composed of 39,280 oligonucleotide probes targeting transcripts representing 34,266 known and predicted genes, including high-confidence, noncoding RNA sequences. Gene Expression data for the samples from which it could be obtained is available in GEO under accession number GSE9588. Results and networks will be made available for download from Sage Bionetworks.

  Study phs000253

• Functional Genomic Landscape of Acute Myeloid Leukemia

  The implementation of targeted therapies for acute myeloid leukemia has been challenged by complex mutational patterns within and across patients as well as a dearth of pharmacologic agents for most mutational events. The initial findings from the Beat AML program were from a cohort of 672 tumor specimens collected from 562 patients. Additional patients have been added in subsequent versions. We assessed these specimens using whole exome sequencing, RNA-sequencing, and ex vivo drug sensitivity analyses. Our data reveal novel mutational events not previously detected in AML. We show association of drug response with mutational status, including instances of drug sensitivity that are specific to combinatorial mutational events. Integration with RNA-sequencing also revealed gene expression signatures, which predict a role of specific gene networks in drug response. Collectively, this report offers a dataset, accessible by the Beat AML data viewer (www.vizome.org), that can be leveraged to address clinical, genomic, transcriptomic, and functional inquiries into the biology of AML.

  Study phs001657

• cfDNA dataset from the urine supernatant of ovarian cancer patients and healthy controls

  Background Ovarian cancer is the deadliest gynecological malignancy worldwide, due to frequent diagnosis at advanced stage. Simple and non-invasive methods for earlier and accurate detection are urgently needed. Here, the presence of tumor-derived DNA in home-collected urine, cervicovaginal self-samples and clinician-taken cervical scrapes of ovarian cancer patients was explored by DNA methylation and copy number analysis. Methods A total of 428 samples (urine, cervicovaginal self-samples, and clinician-taken cervical scrapes) of 110 healthy controls and 54 patients with benign (n=25) or malignant (n=29) ovarian masses were analyzed. Different urine fractions were examined (full void urine, urine supernatant, and urine sediment). All samples were tested for 12 methylation markers by quantitative methylation-specific PCR. Shallow whole-genome sequencing was performed to detect copy number aberrations and verify the presence of tumor-derived DNA. Results Full void urine was most discriminatory between healthy controls and ovarian cancer patients (C2CD4D, p=0.008; CDO1, p=0.022; MAL, p=0.008), followed by cervical scrapes (C2CD4D, p=0.001; CDO1, p=0.004). A significant difference between benign and malignant ovarian masses was only observed for GHSR in the urine sediment (p=0.024). Methylation levels in cervicovaginal self-samples did not discriminate between healthy controls, benign and malignant ovarian masses. Copy number changes were identified in 17% of urine supernatant samples and smaller fragment sizes were seen in urine supernatant samples with a high tumor fraction. Conclusions This study demonstrates the presence of ovarian cancer-derived DNA in home-collected urine. Additional studies are warranted to further explore the clinical applicability of this approach.

  Study EGAS00001007238

• Molecular risk stratification in patients with T1 colorectal cancer_WES

  The introduction of bowel cancer screening has led to a significant increase in the proportion of patients being diagnosed with asymptomatic, early-stage colorectal cancer (CRC). Although the majority of these patients are successfully treated with surgery alone, a small proportion of patients have 'born-to-be-bad' aggressive lesions with early dissemination leading to distant metastases. Current standard of care histological assessment is unable to distinguish between these aggressive versus non-aggressive early lesions which is essential to provide appropriate clinical management decisions. This study aims to carry out molecular and histological profiling of approximately 300 T1 CRCs in order to develop a molecular stratifier based on the risk of relapse in early-invasive CRC. This novel T1 cohort will represent the world's largest molecularly characterised T1 cohort of samples, with digital pathology assessment alongside whole exome sequencing, copy number variation analysis and 3' RNA-seq. This data will be used to generate a robust panel of molecular and/or histological markers applicable to formalin-fixed paraffin embedded (FFPE) archival tissue which discriminates between T1 lesions based on risk of relapse, which will ultimately be used to inform clinical management of CRC at the earliest stages of the disease.

  Dataset EGAD00001010890

• An oncogenic enhancer-rearrangement causes concomitant deregulation of EVI1 and GATA2 in leukemia. Targeted resequencing of chromosomal regions centered on 3q21 and 3q26 in conjunction with RNA-Seq from Acute Myeloid Leukemia patients.

  Chromosomal rearrangements without gene-fusions have been implicated in leukemogenesis by causing deregulation of proto-oncogenes via relocation of cryptic regulatory DNA elements. AML with inv(3)/t(3;3) is associated with aberrant expression of the stem-cell regulator EVI1. Applying functional genomics and genome-engineering, we demonstrate that both 3q-rearrangements reposition a distal GATA2 enhancer to ectopically activate EVI1 and simultaneously confer GATA2 functional haploinsufficiency, previously identified as the cause of sporadic familial AML/MDS and MonoMac/Emberger syndromes. Genomic excision of the ectopic enhancer restored EVI1 silencing and led to growth inhibition and differentiation of AML cells, which could be replicated by pharmacologic BET-inhibition. Our data show that structural rearrangements involving chromosomal repositioning of enhancers can cause deregulation of two unrelated distal genes, with cancer as the outcome.

  Study EGAS00001000669

• Ultra-Fast Patient-Derived Xenografts Identify Functional and Spatial Tumour Heterogeneities that Drive Therapeutic Resistance

  Treatment of patients with advanced cancers increasingly relies on agents targeting specific molecular or cellular aberrations. These expensive therapies often fail because of pre-existing drug resistance. Intra-tumoural molecular and micro-environmental heterogeneity resistance can create resistance in one or more subclones of a tumour, leading to spatio-functional heterogeneity. We created a rapid approach for quantifying tumour functional phenotypes based on tumour-implantation into the chorioallantoic membrane of chick embryos. We apply this technique to 43 separate biopsies from 6 patients with renal cell carcinoma (RCC) with 36 replicates per biopsy, achieving a 93.6% engraftment rate (1449/1548). Challenging these models with sunitinib, an anti-angiogenic therapy frequently used in RCC allowed us to quantify spatio-functional heterogeneity in individual patients. Prediction of de novo drug resistance in advanced cancer patients would facilitate precision medicine by tailoring systemic therapies and improve clinical trial design outcome measures. We describe a patient-derived xenograft platform where fresh patient tumour samples are implanted into the chorioallantoic membrane (CAM) of chick embryos at high engraftment efficiencies, permitting large scale “tumour avatar” studies to guide the selection of drugs and to predict clinical drug resistance outcomes in renal cell carcinoma (RCC) patients. Applying this “tumour avatar” model in a co-clinical trial on RCC patients, we observe intra-tumoural functional heterogeneity with sunitinib treatment, revealing the presence of drug-resistant clones prior to the initiation of therapy. Multi-regional exome Matched DNA sequencing of the primary tumour and metastases revealed DNA mutational signatures associated with sunitinib resistance at baseline and after treatment. These These studies demonstrate a rapid and affordable method of findings confirm the existence of genetic and surveying functional tumour heterogeneities heterogeneity.

  Study EGAS00001002627

• Genome_Diversity_in_Africa_Project__Benin

  Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene–disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region.The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group).Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformaticsThis data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001001688

• Single-cell RNA sequencing of 22 Hodgkin lymphoma tumors and 5 reactive lymph nodes

  Hodgkin lymphoma (HL) is characterized by an extensively dominant tumor microenvironment (TME) composed of different types of non-cancerous immune cells with rare malignant cells. Characterization of the cellular components and their spatial relationship is crucial to understanding crosstalk and therapeutic targeting in the TME. We performed single-cell RNA sequencing of more than 127,000 cells from 22 HL tissue specimens and 5 reactive lymph nodes, profiling for the first time the phenotype of the HL-specific immune microenvironment at single-cell resolution. Library preparation was performed using the 10x Genomics Chromium system, and Illumina sequencing was used to generate 3' gene expression data for every cell. Downstream analysis was performed in R to identify HL-specific microenvironment patterns and identify novel cell populations.

  Study EGAS00001004085

• L1-Seq and Genome-Wide SNP Genotyping in a Multiethnic Asian Population

  Insertions of the human-specific subfamily of LINE-1 (L1) retrotransposon are highly polymorphic across individuals and can critically influence the human transcriptome. We hypothesized that L1 insertions could represent genetic variants determining important human phenotypic traits, and performed an integrated analysis of L1 elements and single nucleotide polymorphisms (SNPs) in several human populations. We found that a large fraction of L1s were in high linkage disequilibrium (LD) with their surrounding genomic regions and that they were well-tagged by SNPs. However, L1 variants were only partially captured by SNPs on standard SNP arrays, so that their potential phenotypic impact would be frequently missed by SNP array-based genome-wide association studies. We next identified potential phenotypic effects of L1s by looking for signatures of natural selection linked to L1 insertions; significant extended haplotype homozygosity (EHH) was detected around several L1 insertions. This suggests that some of these L1 insertions may have been the target of recent positive selection.

  Study phs000732

• Whole genome sequencing of pancreatic cystic fluid for early detection and diagnosis of pancreatic cancer

  Pancreatic cancer (PC) is a leading cause of cancer-related deaths globally. Accurate PC detection at early or premalignant stage, when surgery is effective, would increase survival rates and prevent unnecessary surgery or surveillance. Molecular diagnostic attempts using PCy fluid (PCyF), as a liquid biopsy, to analyze common mutations associated with PC development are yet to contribute to early diagnosis. Whole genome sequencing (WGS) is utilized in various cancers, PC inclusive, for detecting genetic changes associated with carcinogenesis, but not in PCyF due to technical limitations, including isolated DNA purity. The goal of the study was to achieve high quality of WGS from PCyF from 9 patients to enable development of signatures of malignancy. The WGS was performed using Illumina sequencing. Experimental design was at a 50x depth.

  Dataset EGAD50000000869

• Center for Cancer Genomics (CCG) Cancers of Unknown Primary Project (CUPP)

  The Cancers of Unknown Primary Project (CUPP) aims to characterize difficult tumor types with the goal of determining future best treatment practices. NCI will utilize whole exome sequencing, copy-number variation, DNA methylation in conjunction with transcriptome sequencing to provide a comprehensive genomic landscape of Cancers of Unknown Primary (CUP). The samples will be processed and submitted for genomic characterization using pipelines and procedures established within the Center for Cancer Genomics (CCG).

  Study phs001801

• IMMUcan Lung NSCLC2 cohort

  The goal of IMMUcan is to understand how the immune system interacts with tumors and how therapeutic interventions influence this interaction. This cohort includes patients with non-small cell lung cancer who had surgical resection. This is a subcohort of the EORTC SPECTAlung study. Comprehensive profiling data are integrated with longitudinally collected clinical information. Cellular profiling of the same tumor samples was performed using multiplex immunofluorescence imaging, imaging mass cytometry, and H&E staining.

  Study EGAS50000001558

• Myelodysplastic_Syndrome_Follow_Up_Series

  Agilent whole exome hybridisation capture was performed on genomic DNA derived from MDS and matched normal DNA from the same patients. Next Generation sequencing performed on the resulting exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes. Now we aim to discover the prevalence of our findings using bespoke pulldown methods and sequencing the products from a larger set of patient DNA.

  Study EGAS00001000224

• Cryptic Splice Mutation in the Fumarate Hydratase Gene in Patients With Clinical Manifestations of Hereditary Leiomyomatosis and Renal Cell Cancer (HLRCC)

  Four patients with hysterectomy were evaluated for biochemical and molecular evidence of autosomal dominant Fumarate Hydratase (FH) alterations causing Hereditary Leiomyomatosis and Renal Cell Cancer (HLRCC). HLRCC is an autosomal dominant condition characterized by the development of cutaneous and uterine leiomyomas, and risk for development of an aggressive form of papillary renal cell cancer. Enzyme assay, western blot analyses, direct nanopore RNA sequencing, and whole genome sequencing (WGS) were utilized. The study identified a cryptic splice mutation in intron 9 of the FH gene that results in retention of 57 base pairs of intronic sequence in the affected allele of the mature FH mRNA.

  Study phs003381

• UCL Centre for Longitudinal Studies

  Dac EGAC00001001041

• snMultiome Studies of University of Copenhagen

  Dac EGAC50000000924

• Duplex sequencing of selected breast cancer patients

  Investigation of post-zygotic and germline variants using whole exome and ultra-deep duplex sequencing in paired uninvolved margin and primaty tumor samples from 126 breast cancer patients with differing survival outcomes, with skin or blood samples as reference. Pairs of uninvolved margin and blood samples were also collected for 15 reduction mammoplasty patients without personal or familial history of cancer, serving as controls.

  Dataset EGAD50000000769

• WES of breast cancer patients and controls

  Investigation of post-zygotic and germline variants using whole exome and ultra-deep duplex sequencing in paired uninvolved margin and primary tumor samples from 126 breast cancer patients with differing survival outcomes, with skin or blood samples as reference. Pairs of uninvolved margin and blood samples were also collected for 15 reduction mammoplasty patients without personal or familial history of cancer, serving as controls.

  Dataset EGAD50000000770

• RNASeq data from one small cell prostate cancer patient (4 samples from 3 time points)

  RNASeq data from one small cell prostate cancer patient - 4 cancer samples (FFPE) from Patient 1 collected at 3 different time points. mRNA was selected using the Magnetic mRNA Isolation Module (NEB) and sequenced on the Illumina NextSeq 500 as 75bp paired end reads (total read length 150bp).

  Dataset EGAD00001011154

• RNA-Seq Brest Patient-derived Tumor Organoids

  This dataset includes 14 RNASeq samples from 8 patients. For some patients, organoids at different passages have been profiled. They can be identified by their alias, composed of the following structure: <subjectId>_O<organoid_number>_<passage>_RNA. For example, ICSBCS002_O1_1_RNA indicates the earlier passage of organoid 1 for subject ICSBCS002, and ICSBCS002_O1_2_RNA indicates the later passage. Additionally, WCM2137_O1_RNA and WCM2137_O2_RNA indicate two organoids (O1 and O2) derived from different tissues. More information about the passages and tissues can be found in the sample information table.

  Dataset EGAD50000000960