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• A Phase II Clinical Trial of the PARP Inhibitor Talazoparib in BRCA1 and BRCA2 Wild-Type Patients

  The Talazoparib Beyond BRCA (TBB), a phase II proof-of-concept clinical trial, was designed to test the efficacy of talazoparib, a potent, orally bioavailable PARP inhibitor, with an established Phase II recommended dose, in the treatment of advanced BRCA wildtype (WT), HER2-negative breast cancer and other solid tumors with homologous recombination (HR) deficiency. Eligible patients had advanced HER2-negative breast cancer or other solid tumors with a germline or somatic mutation in a gene linked to the HR pathway. Patients identified as harboring a deleterious or suspected deleterious germline or somatic mutation in the HR pathway were treated with single agent talazoparib until disease progression. Primary and metastatic tumor samples were sequenced with panel sequencing and exome sequencing to detect commonly mutated genes and those associated with DNA repair deficiency. In addition, ctDNA was sequenced at baseline and progression. Fastq files for tumor and ctDNA sequencing are deposited. 

  Study phs002803

• 10x Genomics BCR Sequencing

  BCR sequencing done with 10x Genomics V(D)J kit + platform for the paper: Integrated single cell analysis reveals co-evolution of malignant B cells and tumor micro-environment in transformed follicular lymphoma. Dataset contains paired FASTQ files for 35 samples, each was processed with the 10x Genomics V(D)J kit to obtain the sequence of the B-cell receptor sequence.

  Dataset EGAD50000001373

• Dataset for Multiple Myeloma RNA data

  This dataset contains 371 case and control RNA sequencing samples of patients with multiple myeloma. Sequencing was performed on Illumina NovaSeq 6000 and HiSeq X, HiSeq 4000 and HiSeq 2000 using TruSeq Stranded RNA and TruSeq Stranded total mRNA Kits. The sequencing was always paired.

  Dataset EGAD50000000683

• Dataset for desmoplastic small round cell tumor - RNA

  This dataset contains 32 RNA sequencing samples of patients with desmoplastic small round cell tumor. Sequencing was performed on Illumina HiSeq 2500, Illumina HiSeq 4000, Illumina HiSeq X and NovaSeq 6000 using Illumina TruSeq RNA and TruSeq Stranded RNA Kit. The sequencing was always paired.

  Dataset EGAD50000000912

• WGS - germline - oral squamous cell carcinoma

  We conducted a retrospective, single-center Canadian cohort study of patients who underwent primary surgery for OSCC between 2010 and 2024. Nucleic acid quality was assessed using the 4150 TapeStation System (Agilent) prior to library preparation. WGS was performed on germline DNA, following Genome Analysis Toolkit’s (GATK) Best Practices and procedures, with a target of 30X deduplicated coverage per sample, using an Illumina NovaSeq 6000 instrument.

  Dataset EGAD50000002608

• Mate Pair Sequencing data for Molecular Characterization of ETMRs

  This dataset contains Mate Pair Sequencing data from 15 samples from 13 patients. Mate pair DNA library preparation was carried out using the Illumina MP v.2 reagents and protocol. In brief, fragmentation of genomic DNA was performed using a Hydroshear device to an insert size of 4.5 kb followed by sequencing with Illumina HiSeq 2000 instruments resulting in 30 Fastq files (paired end).

  Dataset EGAD00001006207

• Gene signature for predicting homologous recombination deficiency in triple-negative breast cancer

  We developed a gene expression-based classifier for homologous recombination deficiency (HRD) in breast cancer patients using WES and RNA-seq data obtained from 94 TNBC samples from a Malaysian hospital-based cohort (MyBrCa). This classifier was able to predict for high levels of a mutational signature associated with HRD in an additional MyBrCa TNBC validation cohort (this EGA study) as well as in TNBCs from TCGA. We also validated the classifier on a NanoString platform with both fresh frozen and FFPE tissue.

  Study EGAS00001006518

• Autoimmune-wide landscape of circulating CD4+ T cells unveils disease-specific heritability and phenotypic changes

  While CD4+ T cells are involved in autoimmunity, how they contribute to the pathogenesis is unclear due to their cellular heterogeneity. Here, to analyze the heterogeneity, we utilized decomposition-based transcriptome characterization for evaluating non-discrete subsets of CD4+ T cells in addition to canonical clustering strategies. This approach identified 12 independent transcriptional gene programs governing whole CD4+ T cell heterogeneity, which can explain the ambiguity of the canonical clustering.

  Study JGAS000578

• Korean Young Age Diffuse Gastric Cancers

  The incidence of diffuse gastric cancers (DGC) remains steadily high, but relatively small numbers of DGCs have been evaluated with whole exome sequencing (WES). Clinicopathological features of DGC vary according to age, but the molecular basis for these variations is unclear. To identify genomic alteration in this unique subset of gastric cancers, whole exome and SNP6 analyses were performed using frozen cancer tissue. The same analyses were also performed using blood of the same patients.

  Study EGAS00001001711

• Transcriptional data of human isogenic iPSCs

  This dataset contains bulk RNA-seq data from 12 autosomally isogenic human iPSCs. Three biological replicas from XXY (sample ID 419295-7), XX (sample ID 419298-419300), XY (sample ID 419302, 419305-6), and XO (sample ID 419308, 419310, 419312) hiPSC. RNA for this dataset was collected using Trizol method, and polyA library type was implemented. The libraries were sequenced using Illumina device. The sample reads are deposited as fastq files. Analysis have been done using reference alignment to GRCh38 reference genome.

  Dataset EGAD50000001361

• Molecular profiling of EBV associated diffuse large B-cell lymphoma

  We describe distinct molecular mechanisms leading to recurrent activation of JAK-STAT signaling, perturbation of epigenetic regulators as well as other direct targetable alterations such as PD-L1 amplification and overexpression contributing to immune evasion of lymphoma cells. Using the LymphGen 2.0 classifier, we combine data of recurrent mutations, somatic copy number alterations, and structural variants in an integrative analysis . For the first time, we reveal that less than 20% of primary EBV+ DLBCLs can be attributed to established molecular clusters of DLBCL NOS emphasizing the unique molecular character of this disease.

  Study EGAS00001006400

• early-stage ESCC sequencing study

  We performed a comprehensive multi-omics analysis of 786 trace-tumor-samples from 154 esophageal squamous cell carcinoma phase (ESCC) patients, covering 9 histopathological stages in 3 phases as nontumor phase (NT phase), intraepithelial neoplasia phase (IEN phase), and ESCC phase. Proteogenomics elucidated the stage-specific molecular characterization and defined the cancer-driving waves along with the mutation accumulation in EC progression. The integrated multi-omics uncovered the chromosome 3q gain was the key event in the transmit from the NT to IEN phase, disclosed the top mutation of TP53 enhanced cell cycle and DNA replication in the IEN phase, and revealed the ESCC phase mutations of AKAP9 and MCAF1 elevated glycolysis and Wnt signaling, respectively. Furthermore, the trajectory analysis identified 6 major tracks related to different clinical features during ESCC progression. Growingly enhanced and hyperphosphorylated phosphoglycerate kinase 1 (PGK1, S203) was detected and considered as a drug target in ESCC progression. Collectively, this study provides insight into the understanding of ESCC molecular mechanism and a valuable resource for the development of therapeutic targets.

  Study EGAS00001006126

• scRNA-seq dataset for AD and Pso patients

  This dataset contains scRNA-seq fastq files to the paper entitled "Single-cell profiles reveal distinctive immune response in atopic dermatitis in contrast to psoriasis". The details of experiment setup was described in the paper.

  Dataset EGAD00001010106

• Estrogen Receptor Positive Breast Cancer: Aromatase Inhibitor Response Study

  Highly variable outcomes are observed in patients with estrogen receptor positive (ER+) breast cancer who undergo preoperative estrogen deprivation therapy with aromatase inhibitors (AI). In this study, 46 baseline tumor and normal genomes and 31 baseline tumor/normal exomes of participants selected from two clinical trials of neoadjuvant AI therapy on ER+ breast cancer were sequenced to identify somatic alterations that correlate with response to AI, to screen for therapeutic targets and to elucidate the genetic landscape of ER+ breast cancer. From the same set of patients we later performed deep genomic characterization of a subset of matched primary tumors after four months of AI therapy, generating comprehensive information about the range of changes that occur when ER+ breast cancers are subjected to estrogen deprivation. This data includes whole genome sequence and transcriptome data. To better understand tumor heterogeneity and the evolution of resistance to estrogen-deprivation therapy, a subset of these tumours, along with 38 additional cases were sequenced to greater depth using targeted capture with a gene panel.

  Study phs000472

• Spatial transcriptomics analysis of triple negative breast cancers

  While triple negative breast cancer (TNBC) is known to be heterogeneous at the genomic and transcriptomic levels, spatial information on tumor organization and cell composition is still lacking. Here, we investigated TNBC tumor architecture including its microenvironment using spatial transcriptomics on a series of 92 patients. We performed an in-depth characterization of tumor and stroma organization and composition using an integrative approach combining histomorphological and spatial transcriptomics. Furthermore, a detailed molecular characterization of tertiary lymphoid structures led to identify a gene signature strongly associated to disease outcome and response to immunotherapy in several tumor types beyond TNBC. A stepwise clustering analysis identified nine TNBC ecotypes, further validated in external datasets. Several ecotypes were associated with disease outcome and characterized by potentially actionable features. In this work, we provideThis is the largest TNBC series providing a comprehensive insight into the complexity of TNBC ecosystem with potential clinical relevance, opening avenues for treatment tailoring including immunotherapy. All the processed data needed to replicate the results from the publication (counts, images, clinical data, etc) are available on Zenodo: https://zenodo.org/records/14204217

  Study EGAS50000000475

• Sequencing_component_for_the_whole_genome_methylation_analysis_in_PBMCs_and_cell_subsets__pilot_study_

  DNA methylation has been shown to play a major role in determining cellular phenotype by regulating gene expression. Moreover, dysregulation of differentially methylated genes has been implicated in disease pathogenesis of various conditions including cancer development as well as autoimmune diseases such as systemic Lupus erythematosus and rheumatoid arthritis. Evidence is rapidly accumulating for a role of DNA methylation in regulating immune responses in health and disease. However, the exact mechanisms remain unknown. The overall aim of the project is to investigate the role of epigenetic mechanisms in regulating immunity and their impact on autoimmune disease pathogenesis.The aim of this pilot study is to perform whole genome methylation analysis in peripheral blood mononuclear cells (PBMCs) and cell subsets (CD4, CD8, CD14, CD19, CD16 and whole PBMCs) obtained from 6 healthy volunteers. Whole genome methylation analysis will be performed using two methodological approaches, the Infinium Methylation Bead Array K450 (Illumina) and MeDIP-seq. mRNA expression arrays will also be performed in order to correlate DNA methylation with gene expression as well as genotyping on the Illumina OmniExpress chip

  Study EGAS00001000490

• GBM-Space: Transcriptomic Profiling of Patient-Derived Glioblastoma Cell Lines (Parse Biosciences - Evercode WT)

  Cancer cells display heterogeneous and dynamic states in glioblastoma, but how these malignant states arise and whether they follow a tractable cellular trajectory across tumours is poorly understood. Here, we generate a deep single cell and spatial multi-region atlas of 12 isocitrate dehydrogenase wild-type (IDH-wt) primary glioblastomas that integrates transcriptomic, epigenomic and genomic analysis to comprehensively characterise their tumour heterogeneity. This dataset comprises sequencing data from single-cell transcriptomic profiles of patient-derived glioblastoma cell lines (Parse Biosciences Evercode WT v3), towards experimentally validating the malignant cell trajectory from developmental-like to gliosis-hypoxia states.

  Dataset EGAD00001016126

• Paediatric_CNS_tumour_autopsy_DNA_WES

  Paediatric gliomas likely have their origins in embryogenesis. This WES extension to the WGS study seeks to estimate the occurrence of driver mutations within the normal tissues of patients which have developed lethal brain tumours and compare the incidence between those that have a germline predisposition and those that don't.

  Study EGAS00001005642

• Tissue-specific cell-free DNA degradation quantifies circulating tumor DNA burden

  Profiling of circulating tumor DNA (ctDNA) may offer a non-invasive approach to monitor disease progression. Here, we developed a quantitative method, exploiting local tissue-specific cell-free DNA (cfDNA) degradation patterns, that accurately estimates ctDNA burden independent of genomic aberrations. Nucleosome-dependent cfDNA degradation at promoters and first exon-intron junctions was strongly associated with differential transcriptional activity in tumors and blood. A quantitative model, based on just 6 regulatory regions, could accurately predict ctDNA levels in colorectal cancer patients. Strikingly, a model restricted to blood-specific regulatory regions could predict ctDNA levels across both colorectal and breast cancer patients.

  Study EGAS00001004657

• Clinical relevance of TCGA subtypes for gastric cancer patients

  There is a clinical need for the availability of molecular biomarkers in the tratment of gastric cancer (GC), since survival rates remain poor with a 5-year survival rate of only ~`40% for patients with resectable disease. These markers will elad to a more tailored approach in the treatment of GC, which enhances efficacy and reduces toxicity. Recently, The Cancer Genome Atlas (TCGA) classified GC patients into four molecular subgroups: Epstein Barr Virus positive (EBV+), genomically stable (GS), microsatellite instable (MSI), and chromosomal instable (CIN). For this purpose we aim to collect tumor tissue blocks from patients who participated in the Dutch D1/D2 or the CRITICS trial and who gave informed consent for translational studies. Associations between TCGA subtypes and outcomes to these different therapeutic options will be analyzed.

  Study EGAS50000000779

• WES Profiles from the CheckMate-577 Clinical Trial

  The dataset contains WES profiles of 396 patients from the CheckMate-577 (CA209-577) clinical trial whose ICF allows data deposition into a public repository. The Allprep DNA/RNA FFPE kit was used to simultaneously purify genomic DNA and total RNA from formalin-fixed, paraffin embedded (FFPE) tissue sections. DNA was analyzed by Whole Exome Sequencing using Swift Biosciences Accel-NGS 2S Hyb DNA Library Kit for library preparation and hybridization using Agilent SureSelect All Exon v6, followed by sequencing on the Illumina NovaSeq platform with a 100bp paired-end strategy and a target read depth of 100M per tumor sample. Fastq files are included.

  Dataset EGAD50000002395

• Data access committee for "Detection of brain cancer using genome-wide cell-free DNA fragmentomes"

  The data access committee for “ Detection of brain cancer using genome-wide cell-free DNA fragmentomes”. The DAC is comprised of Drs. Dimitrios Mathios, Jillian Phallen, Victor Velculescu, Robert Scharpf, Noushin Niknafs, and Shashikant Koul, and can be contacted at skoul3@jh.edu.

  Dac EGAC50000000605

• Bulk WES Fastq Files for 103 Samples of Cornell-NCI DLBCL Genomic Project

  Paired-read fastq files were derived from standard Illumina WES NGS sequencing for 103 DLBCL biopsy samples. This is one of three datasets associated with the multi-platform NGS sequencing efforts of the Cornell-NCI DLBCL genomic study.

  Dataset EGAD50000001747

• Oslo University Hospital Data Access Committee for Celiac Disease datasets submitted to FEGA Norway

  This is the Data Access Committee appointed by Oslo University Hospital for governing access to Celiac Disease datasets submitted to FEGA Norway, under the Regional Ethical Committee approval 6544, with main contact Ludvig M. Sollid.

  Dac EGAC50000001032

• Akershus University Hospital Data Access Committee for Immunoglobulin Heavy-Chain locus in Multiple Sclerosis datasets in FEGA Norway

  This is the Data Access Committee appointed by Akershus University Hospital (AHUS) for datasets from Immunoglobulin Heavy-Chain locus in Multiple Sclerosis studies.

  Dac EGAC50000000659