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• WGS of TNBC PDXs

  WGS data relative to 36 triple negative breast cancer PDX models.

  Dataset EGAD00001008535

• Characterisation of the genetic landscape of cutaneous leiomyoma and leiomyosarcoma - Leiomyoma RNA

  Cutaneous leiomyoma (cLM) and leiomyosarcoma (cLMS) are rare benign and malignant soft tissue neoplasms showing smooth muscle differentiation, respectively, that arise from mesenchymal cells in the dermis and subcutis. Through whole exome sequencing of cLM and cLMS cases, we observed distinct differences between the somatic mutational profile of these tumour types. FH was identified as a driver gene in cLM with genetic alterations of FH occurring via somatic point mutation, somatic copy number loss, biallelic inactivation and germline point mutations. TP53 and RB1 were identified as driver genes in the cLMS cohort, with genetic alterations of TP53 occurring via somatic and germline point mutations, copy number loss and biallelic inactivation. Using RNA-sequencing, we identified recurrent gene fusions, including CRTC1/3-MAML2 in cLMS and a novel MYLK-MAP3K2 fusion. Analysis of the cell types present in the tumour microenvironment revealed a significantly increased presence of macrophages and decreased presence of myeloid dendritic cells in the cLMS cohort relative to the cLM cohort. Additionally, we identified common driver genes between cLMS and LMS from other sites. Thus, we provide the first in-depth profile of the genetic landscape of cLM and cLMS.

  Dataset EGAD00001014788

• Characterisation of the genetic landscape of cutaneous leiomyoma and leiomyosarcoma - Leiomyosarcoma RNA

  Cutaneous leiomyoma (cLM) and leiomyosarcoma (cLMS) are rare benign and malignant soft tissue neoplasms showing smooth muscle differentiation, respectively, that arise from mesenchymal cells in the dermis and subcutis. Through whole exome sequencing of cLM and cLMS cases, we observed distinct differences between the somatic mutational profile of these tumour types. FH was identified as a driver gene in cLM with genetic alterations of FH occurring via somatic point mutation, somatic copy number loss, biallelic inactivation and germline point mutations. TP53 and RB1 were identified as driver genes in the cLMS cohort, with genetic alterations of TP53 occurring via somatic and germline point mutations, copy number loss and biallelic inactivation. Using RNA-sequencing, we identified recurrent gene fusions, including CRTC1/3-MAML2 in cLMS and a novel MYLK-MAP3K2 fusion. Analysis of the cell types present in the tumour microenvironment revealed a significantly increased presence of macrophages and decreased presence of myeloid dendritic cells in the cLMS cohort relative to the cLM cohort. Additionally, we identified common driver genes between cLMS and LMS from other sites. Thus, we provide the first in-depth profile of the genetic landscape of cLM and cLMS.

  Dataset EGAD00001014790

• Characterisation of the genetic landscape of cutaneous leiomyoma and leiomyosarcoma - Leiomyoma WES

  Cutaneous leiomyoma (cLM) and leiomyosarcoma (cLMS) are rare benign and malignant soft tissue neoplasms showing smooth muscle differentiation, respectively, that arise from mesenchymal cells in the dermis and subcutis. Through whole exome sequencing of cLM and cLMS cases, we observed distinct differences between the somatic mutational profile of these tumour types. FH was identified as a driver gene in cLM with genetic alterations of FH occurring via somatic point mutation, somatic copy number loss, biallelic inactivation and germline point mutations. TP53 and RB1 were identified as driver genes in the cLMS cohort, with genetic alterations of TP53 occurring via somatic and germline point mutations, copy number loss and biallelic inactivation. Using RNA-sequencing, we identified recurrent gene fusions, including CRTC1/3-MAML2 in cLMS and a novel MYLK-MAP3K2 fusion. Analysis of the cell types present in the tumour microenvironment revealed a significantly increased presence of macrophages and decreased presence of myeloid dendritic cells in the cLMS cohort relative to the cLM cohort. Additionally, we identified common driver genes between cLMS and LMS from other sites. Thus, we provide the first in-depth profile of the genetic landscape of cLM and cLMS.

  Dataset EGAD00001014787

• Characterisation of the genetic landscape of cutaneous leiomyoma and leiomyosarcoma - Leiomyosarcoma WES

  Cutaneous leiomyoma (cLM) and leiomyosarcoma (cLMS) are rare benign and malignant soft tissue neoplasms showing smooth muscle differentiation, respectively, that arise from mesenchymal cells in the dermis and subcutis. Through whole exome sequencing of cLM and cLMS cases, we observed distinct differences between the somatic mutational profile of these tumour types. FH was identified as a driver gene in cLM with genetic alterations of FH occurring via somatic point mutation, somatic copy number loss, biallelic inactivation and germline point mutations. TP53 and RB1 were identified as driver genes in the cLMS cohort, with genetic alterations of TP53 occurring via somatic and germline point mutations, copy number loss and biallelic inactivation. Using RNA-sequencing, we identified recurrent gene fusions, including CRTC1/3-MAML2 in cLMS and a novel MYLK-MAP3K2 fusion. Analysis of the cell types present in the tumour microenvironment revealed a significantly increased presence of macrophages and decreased presence of myeloid dendritic cells in the cLMS cohort relative to the cLM cohort. Additionally, we identified common driver genes between cLMS and LMS from other sites. Thus, we provide the first in-depth profile of the genetic landscape of cLM and cLMS.

  Dataset EGAD00001014789

• Single-Nuclei RNA Sequencing and Spatial Transcriptomics of Human Heart Right Atrial Appendage and Pericardial Fluid in Cardiovascular Disease

  This dataset includes single-nuclei RNA sequencing (snRNA-seq) and spatial transcriptomics data from biopsies of the right atrial appendage and pericardial fluid, collected during open-heart surgeries. The samples represent various clinical contexts, including control, ischemic heart disease, heart failure, and myocardial infarction. For each biopsy, nuclei were isolated, and RNA sequencing libraries were prepared using the 10x Genomics Chromium v3 platform. Additionally, spatial transcriptomics was performed on the heart samples. The dataset provides raw sequencing data, which includes fastq files generated from these libraries, offering valuable insights into the cellular composition of heart tissues and associated fluids across different disease states.

  Dataset EGAD50000000927

• Molecular analyses of stage IIIa NSCLC patients treated with neoadjuvant chemmoimmuntherapy

  This dataset comprises molecular and immunogenomic profiles from 60 individual NSCLC patients (30 male, 30 female), with samples collected at multiple timepoints including initial biopsies (IB), resections (RES), and peripheral blood mononuclear cells (PBMC) at different timepoints during treatment. It includes 32 FFPE tumor samples sequenced on Illumina with the FoundationOne panel, 20 FFPE samples sequenced on IonTorrent with the Oncomine Comphrehensive Assay Plus, and 41 samples assessed with IonTorrent via Oncomine Immune Response Research Assay panel for targeted gene expression. T-cell receptor (TCR) repertoire profiling was performed on 62 tumor samples (initial biopsies and resections, Oncomine TCR Beta-SR Assay), and 155 blood-derived samples were sequenced with Oncomine TCR Beta-LR Assay. Data files include processed sequencing results in bam format.

  Dataset EGAD50000001630

• Bulk RNA-seq paired fastq files from i3Ns harbouring a SNCA A53T mutation, with or without RSL3 treatment

  FASTQ files from bulk RNA sequencing of a iPSC-derived rapid neuronal model (i3Ns) harbouring the SNCA A53T mutation in a WTC11 background as a model of synucleinopathy, with or without treatment of 300nM RSL3 for 6 hours. Libraries were prepared using the Watchmaker rRNA and globin depletion kit and sequenced on a NovaSeq X with an average depth of ~27 million paired-end reads with a fragment length of 100 base pairs, per sample. 19 samples are included in this dataset, each with two paired fastq files (R1 and R2). The dataset includes control neurons (WT: dcas9 parental line and C4 CRISPR control) and A53T clones (B7, H8 and L8) across two neuronal inductions (ind1 vs ind2), with or without treatment of RSL3 (UT vs. RSL3).

  Dataset EGAD50000002209

• Whole exome sequencing of SarBC-01- and UroBC-01-related samples.

  This dataset contains raw FASTQ files from DNA of SarBC-01-related samples (SarBC-01 patient Germline, SarBC-01 patient Urothelial tumor, SarBC-01 patient Sarcomatoid tumor, SarBC-01 Passage 6 organoids, SarBC-01 Passage 20 organoids) and UroBC-01 related samples (UroBC-01 patient Germline, UroBC-01 patient Urothelial tumor, UroBC-01 Passage 19 organoids, UroBC-01 Passage 6 organoids). DNA was extracted from FFPE tissue, using RecoverAll RNA/DNA extraction kit (Invitrogen, Carlsbad, CA, USA, AM1975) followed by incubation with Uracil-DNA Glycosylase, and fresh or flash frozen tissue, using Quick-DNA/RNA Miniprep kit (Zymo Research, Irvine, CA, USA, D7001). Twist Human Core Exome + RefSeq + Mito-Panel kit (Twist Bioscience, 102031) was used for the whole exome capturing. Sequencing was performed on Illumina NovaSeq 6000 using paired-end 100-bp reads.

  Dataset EGAD00001011157

• The G2 gene expression signature and MYC overexpression are independent poor prognostic factors in childhood high-grade osteosarcoma

  Key objective Are the prognostic transcriptomic G1/G2 gene expression signature, MYC overexpression, and MYC amplification replicable stratifying biomarkers for future clinical trials in high-grade osteosarcoma? Knowledge gathered In an unselected cohort, the G2 gene expression signature and MYC overexpression, but not MYC amplification, were independently associated with poor event-free and overall survival. Relevance Transcriptomic biomarkers may serve as stratifying factors that guide the management of patients with high-grade osteosarcoma. Current data underlines the importance of prospective validation of the G1/G2 signature and MYC overexpression in an international, multicenter, study.

  Dataset EGAD00001015502

• SNV and indel calls from 8086 individuals in the British Autozygosity Populations BioResource dataset

  This includes variant calls (single nucleotide variants and small insertions/deletions) from 8086 (mostly British Pakistani/British Bangladeshi) individuals from the following studies: 1. 3781 British Pakistani/British Bangladeshi adults from East London Genes and Health 2. 2791 British South Asian mothers from Born in Bradford 3. 1428 British South Asian adults from Birmingham 4. 86 individuals (mixed ancestries) from families with rare diseases, from Queen Mary University London All of the Birmingham and most of the Born in Bradford samples were previously sequenced as part of PMID: 26940866. Mapping was done with bwa-mem and variant calling was carried out with GATK HaplotypeCaller. We removed variant sites for which the following was true: SNPs: "QD < 2.0 || FS > 30 || MQ < 40.0 || MQRankSum < -12.5 || ReadPosRankSum < -8.0" Indels: "QD < 2.0 || FS > 30 || ReadPosRankSum < -20.0"

  Dataset EGAD00001004581

• Clonal fitness inferred from timeseries modeling of single cell cancer genomes

  Progress in defining genomic fitness landscapes in cancer by copy number alterations (CNA) has been impeded by lack of single cell and timeseries sampling. We generated 42,000 single cell whole genomes (scWGS) from breast epithelium and primary triple negative breast cancer (TNBC) patient-derived xenografts (PDX) collected during multi-year time series. Using a Wright-Fisher population genetics model, we inferred reproducible CNA-defined clonal fitness dynamics induced by TP53 mutation and cisplatin chemotherapy, with accurate forecasting of experimentally enforced clonal competition dynamics. Drug treatment in three long-term serially passaged TNBC PDX resulted in cisplatin resistant clones that had shown low fitness in the untreated setting. By contrast high fitness clones from treatment naive controls were eradicated reflecting an inversion of the fitness landscape. Upon drug release selective pressure dynamics were reversed indicating a fitness cost of treatment resistance. Taken together, our findings reveal clonal fitness dynamics linked to CNA and therapeutic resistance in polyclonal tumours.

  Study EGAS00001004448

• Dataset for Sarcoma RNA sequencing linked from study EGAS00001004813

  Sequencing data of 410 sarcoma tumor runs, which were uploaded to EGAS00001004813. The sequencing was always paired.

  Dataset EGAD00001010276

• Solve-RD_RND_cohort-1_DF1+2_V1

  Solve-RD data submitted to the ERN-RND cohort for re-analysis (Data freeze 1+2) v1

  Dataset EGAD00001009769

• Single-Cell Transcriptomic Analysis of Kaposi Sarcoma

  Summary: Single-cell transcriptome analysis of skin and blood samples from individuals with Kaposi's sarcoma Aims: Elucidate the cellular composition and gene expression profiles of Kaposi sarcoma herpesvirus (KSHV) infected cells and non-infected tumor infiltrating cells, and peripheral blood samples from the same individuals, with or without specific therapies, such as antiretroviral therapy for HIV, immunotherapies (such as immune checkpoint inhibitors and immune modulator drugs like pomalidomide), or angiogenesis inhibitory agents. Population: Age 18 and older, both genders, including individuals from North America and other areas of the world (including Africa). Individuals with or without HIV are included. Molecular Technologies: Single-cell RNAseq using 10x Genomics Principal Findings: Two distinct populations of endothelial cells were found infected with KSHV, one CD34+ and one CD34-Both clusters include lytic and latent KSHV gene expressionThe KSHV infected cell clusters differ in expression of housekeeping genes, proliferative markers, ribosomal and secretory vesicle genesBiomarkers of KSHV infected cells were identified, including sodium channel SCN9A Changes in cell composition with therapy are noted Clonal amplification of TCR+ T-cells were noted in the skin and blood Data Available through dbGaP: scRNA-seq data

  Study phs003800

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

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

  Study EGAS00001003190

• Integrative understanding of human immune system by functional genomics and development of intervention strategies for the prevention of autoimmune diseases

  Various peripheral blood immune cell subsets from 89 healthy volunteers and 136 systemic lupus erhythematosus (SLE) donors were collected (Naive_CD4, Mem_CD4, Th1, Th2, Th17, Tfh, Fr._I_nTreg, Fr._II_eTreg, Fr._III_T, Naive_CD8, EM_CD8, CM_CD8, TEMRA_CD8, NK, Naive_B, USM_B, SM_B, DN_B, Plasmablast, CL_Mono (or CD16n_Mono), CD16p_Mono, Int_Mono, NC_Mono, mDC, pDC, Neu, LDG). 22 SLE donors were analyzed longitudinally. RNA-seq was performed with each immune cell subset samples. After gene expression quantification samples were filtered.

  Study JGAS000486

• SNP arrays for chemotherapy response project

  In this study, a total of 300 patients with MIBC receiving chemotherapy were included; 62 received NAC before cystectomy and 245 received first-line chemotherapy upon detection of locally-advanced (T4b) or metastatic disease. Treatment response, defined as pathological downstaging (< pTa,CIS,N0) after NAC or complete or partial response after first-line treatment (RECIST criteria). Illumina SNP arrays (760k markers) were performed using DNA from 49 tumors and associated germline DNA (49x median coverage). Data provided here consist of 98 files.

  Study EGAS00001004519

• Illumina RNA sequencing for HLA expression qauntification

  In this study, we quantified mRNA expression levels of HLA class I and II genes from peripheral blood samples of 50 healthy individuals. The gene- and allele-specific mRNA expression was assessed using unique molecular identifiers, which enabled PCR bias removal and calculation of the number of original mRNA transcripts. We identified differences in mRNA expression between different HLA genes and alleles. Our results suggest that HLA alleles are differentially expressed and these differences in expression levels are quantifiable using RNA sequencing technology.

  Study EGAS00001004931

• Spatial multi-omic map of human myocardial infarction

  We applied an integrative single-cell genomics strategy with single nucleus RNA sequencing (snRNA-seq) and single nucleus Assay for Transposase-Accessible Chromatin sequencing (snATAC-seq) together with spatial transcriptomics from the same tissue mapping human cardiac cells in homeostasis and after myocardial infarction (MI) at unprecedented spatial and molecular resolution. We profiled in total 31 samples from 23 patients including four non-transplanted donor hearts as controls and samples from tissues with necrotic tissue areas (ischemic zone, IZ), border zone (BZ), and the non-affected left ventricular myocardium (remote zone, RZ) of patients with acute MI.

  Dataset EGAD00001008952

• Methylation and nucleosome occupancy studies on cell-free DNA using enzymatic cytosine conversion

  Raw sequencing data (PE, fastq.gz) from NovaSeq 6000 sequencing runs of: 1. Blood-derived cell-free DNA from six healthy controls, enzymatic cytosine conversion (between 1 and 3 replicates each) 2. Urine-derived cell-free DNA from three healthy controls, enzymatic cytosine conversion (between 1 and 3 replicates each) 3. Blood-derived cell-free DNA from six patients with acute or chronic kidney disease with/without other relevant organ dysfunction, enzymatic cytosine conversion (between 1 and 3 replicates each) 4. Urine-derived cell-free DNA from three patients with acute kidney disease, enzymatic cytosine conversion (between 1 and 3 replicates each) 5. Blood-derived cell-free DNA from three healthy controls, bisulfite cytosine conversion (single datasets) 6. Conventional whole-genome sequencing on genomic DNA of two healthy kidney donors for two of the studied patients (single datasets).

  Dataset EGAD00001006072

• cfMethyl-Seq

  cfMethyl-Seq libraries were generated for 479 cfDNA samples and were sequenced with 150 bp paired-end reads.

  Dataset EGAD00001009003

• Leiomyosarcoma Whole Genome Sequencing

  DNA was extracted from fresh frozen LMS material for 29 untreated tumors (24 primary tumors, 5 metastatic 13 relapses) and 13 tumors treated with radiation (7 primaries, 6 metastatic relapses). DNA from matched blood was used as a normal reference. Whole-genome sequencing was performed using established protocols on Illumina instruments.

  Dataset EGAD00001007722

• DNA methylation sequencing profiles of 1538 breast tumors and 244 normal breast tissues

  DNA methylation sequencing profiles of 1538 breast tumors and 244 normal breast tissues. Libraries were prepared using a custom Reduced Representation Bisulfite Sequencing pipeline. Sequencing was performed on the Illumina HiSeq 2500 (v4 chemistry), with single-end reads of 125 bp length. Multiplexing was conducted at the level of 8 samples per lane. FASTQ files are provided for 1538 breast tumors and 244 normal breast tissues. Reference: Batra et al. (2021). DNA methylation landscapes of 1538 breast cancers reveal a replication-linked clock, epigenomic instability and cis-regulation.

  Dataset EGAD00001007976

• 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