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• POISED (Peanut Oral Immunotherapy: Safety, Efficacy, and Discovery)

  Phase 2 POISED (Peanut Oral Immunotherapy: Safety, Efficacy, Discovery) Study In this randomized, double-blind, placebo-controlled (DBPC) clinical trial, blinded placebo group received oat flour, whereas in active participants, dosage was built-up for over ~ 52 weeks and subsequently maintained on 4000 mg peanut protein, daily for next 52 weeks. 80 (98.77%) per-protocol active participants passed the food challenge at week 104. Subsequently, for 12 weeks, peanut ingestion was avoided in a randomized group of 51 blinded active participants (i.e., peanut avoidance group). 21 (41.2%) participants in the peanut avoidance group passed the 4000 mg double-blind, placebo-controlled food challenge (DBPCFC) without any allergic reaction at week 117, thus demonstrating sustained unresponsiveness. These 21 participants continued oral immunotherapy (OIT) for every three months and afterwards were allowed to continue peanut OIT discontinuation if they passed. 8 participants passed the DBPCFCs, 12 months after peanut discontinuation (week 156), i.e. they achieved long-term sustained unresponsiveness with no allergic reaction in response to food challenge. For detailed description, please refer to Chinthrajah et al., PMID: 31522849.

  Study phs003071

• Gene fusion and transcriptomic landscapes of sarcomas

  Sarcoma represents a highly heterogeneous group of tumors. We report here the first unbiased and systematic search for gene fusions and analysis of transcriptomic profiles in 100 monomorphic sarcomas cases using RNA-sequencing profiling. Fusion genes were detected in two thirds of samples. Similarly to fusion genes such as PAX3/7-FOXO1, EWSR1/FUS-ETS, SS18-SSX, BRD3/4-NUTM1 or EWSR1/FUS/TAF15-NR4A3 characterizing well-defined entities, we show that all sarcomas displaying CIC fusions- whatever their fusion partner (being DUX4, NUTM1 or FOXO4) - form a transcriptionally homogeneous group of tumors. Likewise, tumors with either a BCOR fusion (with CCNB3, MAML3 or ZC3H7B partners) or with a BCOR internal duplication form a single biological entity. We also found that EML4-ALK fusions also characterize a homogeneous infantile fibrosarcoma subgroup. In contrast, fusions like VGLL2-NCOA2/CITED2, TMP3/TRP-NTRK1 or ETV6-NTRK3 are observed in more heterogeneous tumors. Finally, we also describe a new group of bone sarcomas characterized by EWSR1- or FUS-TFCP2 fusions.

  Study EGAS00001002189

• Clonal dynamics after allogeneic haematopoietic cell transplantation using genome-wide somatic mutations - TGS

  Allogeneic haematopoietic cell transplantation (HCT) replaces the stem cells responsible for blood production with those harvested from a donor, and is received by 40,000 patients worldwide each year. To quantify dynamics of long-term stem cell engraftment, we sequenced whole genomes of 2,824 single-cell-derived haematopoietic colonies from blood samples of 10 donor-recipient pairs taken 9-31 years after HLA-matched sibling HCT. With younger donors, 10,000-50,000 stem cells had engrafted and were still contributing to haematopoiesis at time of sampling, but estimates were 10-fold lower with older donors. Engrafted stem cells made multilineage contributions to myeloid, B-lymphoid and T-lymphoid populations, although individual clones often showed biases towards one or other mature cell type. Recipients had lower clonal diversity than matched donors, equivalent to ~10-15 years of additional ageing, arising from up to 25-fold greater expansion of stem cell clones. An HCT-related population bottleneck alone could not explain these differences: instead, phylogenetic trees evinced two distinct modes of HCT-specific selection. In 'pruning selection', cell divisions underpinning recipient-enriched clonal expansions had occurred in the donor, preceding transplant - their selective advantage derived from preferential mobilisation, harvest, survival ex vivo or initial homing. In 'growth selection', cell divisions underpinning clonal expansion occurred through proliferative advantage in the recipient's marrow after homing - clones with multiple driver mutations especially demonstrated this pattern. Uprooting stem cells from their native environment and transplanting them to foreign soil exaggerates selective pressures, distorting and accelerating the loss of clonal diversity compared to the unperturbed haematopoiesis of donors.

  Dataset EGAD00001010874

• Phylogenetic analysis of treatment-naive metastases using whole exome and genome sequencing data

  Metastases are responsible for the majority of cancer related deaths and are often difficult to treat successfully. Even for metastases that occur subsequent to treatment, we do not know whether such relapsing metastases were originally heterogeneous or if the observed heterogeneity is a consequence of therapy. Given that treatment can influence evolutionary dynamics by selecting resistant clones, imposing bottlenecks on cancer cell populations, and even inducing novel somatic mutations, characterizing the prior standing variation among metastases remains an important goal to predict initial therapeutic response. To quantify the heterogeneity at clinical presentation of advanced disease, we surveyed the literature for patients in which at least two treatment-naïve metastases underwent genome/exome-wide sequencing. Across all cancer types surveyed, only 18 subjects were found to fulfill this requirement. Including previously unpublished data from two subjects, we analyzed data of 74 untreated metastases and inferred cancer phylogenies. Putative driver gene mutations were acquired at a 2-fold higher rate on the trunk of all metastases than on branches. Mutations in driver genes along the trunk were strongly enriched for predicted functional consequences. Using a stochastic mathematical model, we find that driver gene heterogeneity among metastases mostly occurs in slowly growing cancers for highly advantageous driver gene mutations. Seeding efficiency only weakly affects the heterogeneity among metastases. These results explain why functional driver gene heterogeneity is uncommon in advanced disease prior to treatment, thus providing optimism for future therapies that depend on mutations across metastases.

  Study EGAS00001002777

• Clonal selection after gene therapy in sickle cell disease

  While gene therapy (GT) provides a potentially curative treatment option for patients with sickle cell disease (SCD), the occurrence of myeloid malignancies in clinical trials has prompted concern. To interrogate potential mechanisms underlying increased cancer risk, we used hematopoietic stem cell (HSC) clonal tracking by whole genome sequencing (WGS) to map the somatic mutation and clonal landscape of 2,592 gene modified as well as unmodified single stem and progenitor cells from six SCD patients undergoing gene therapy (7-26 years old, average 12.7× depth). Pre-GT phylogenetic trees in SCD were highly polyclonal and mutation burdens per cell were elevated in some, but not all, patients. Post-GT, no clonal expansions were identified. However, an increased frequency of driver mutations associated with myeloid neoplasms or clonal hematopoiesis (DNMT3A- and EZH2-mutated clones in particular) were seen in both genetically modified and unmodified cells suggested positive selection of mutant clones during gene therapy. This work sheds light on the mutation landscape and HSC clonal dynamics in gene therapy for SCD and highlights enhanced fitness of some HSCs harboring pre-existing driver mutations following gene therapy. Future studies should define the long-term fate of mutant clones including any contribution to expansions associated with myeloid neoplasms.

  Dataset EGAD00001010913

• DAC for the Study EGAS00001006374: Pathogenic variants damage cell composition and single cell transcription in cardiomyopathies. snRNAseq of 79 (61 CM patients + 18 controls).

  Dac EGAC00001002804

• EGAD00010000286

  All cases and controls (Hap550)

  Dataset EGAD00010000286

• EGAD00010000298

  All cases and controls (Hap300)

  Dataset EGAD00010000298

• EGAD00010000450

  Genome Wide Genotype Data

  Dataset EGAD00010000450

• EGAD00010000496

  Genome-wide SNP genotyping of African rainforest hunter-gatherers and neighbouring agriculturalists

  Dataset EGAD00010000496

• Plasma DNA tissue mapping by genome-wide methylation sequencing for noninvasive prenatal, cancer, and transplantation assessments

  Dataset EGAD00001001602

• 450K_DKFZ_CLL_NB

  CLL and normal B cell samples using 450K

  Dataset EGAD00010000871

• Second generation noninvasive fetal genome analysis reveals de novo mutations, single-base parental inheritance, and preferred DNA ends

  Dataset EGAD00001003778

• WTCCC2 Pre-eclampsia

  Genotype data from the Affymetrix 6.0 platform for 4,375 Colombian pre-eclampsia cases and controls

  Dataset EGAD00010001647

• Whole transcriptome and 850k methylome profiling of human MBM

  Assessment of methylation status of ~850,000 sites

  Dataset EGAD00010002281

• Medulloblastoma Illumina WGS

  Illumina whole genome sequencing of Medulloblastoma Blood, Primary tumor, and Relapse tumor

  Dataset EGAD00001009424

• Medulloblastoma Illumina RNA-Seq

  Illumina RNA-sequencing of Medulloblastoma primary and relapse tumor.

  Dataset EGAD00001009425

• SNParray_CASCADE

  Tumor and matched normal DNA profiling by SNP array

  Dataset EGAD00010002398

• Methylation data

  Methylation data on tumor (n=102) and normal nerve (n=7) DNA samples

  Dataset EGAD00010002441

• Methylation_PBL_UC_Tofacitinib

  Longitudinal whole-genome DNA methylation profiling of PBL obtained from UC patients categorized as responders and non-responders

  Dataset EGAD00010002590

• Whole-exome sequencing of buccal mucosa samples

  40 buccal mucosa samples and a paired blood sample were whole-exome sequenced.

  Dataset EGAD50000000080

• RNAseq for 4 pdx and 1 cell-line

  RNAseq for #1049, #111, #1217, #206, COV362

  Dataset EGAD50000000032

• DLBCL cfDNA seq

  Sequencing dataset of 290 DLBCL and HGBL cfDNA samples of paired end 150bp sequencing runs.

  Dataset EGAD50000000602

• SMPaeds tumour tissue lcWGS

  Low coverage whole genome sequencing (0.5-4X) for both relapse and archival diagnostic tumour tissue.

  Dataset EGAD50000000784

• BREAKFAST trial DAC

  Data Access Committee for BREAKFAST trial datasets, IFOM-ETS The AIRC Institute of Molecular Oncology and INT Istituto nazionale Tumori Milano, Italy.

  Dac EGAC50000000401

• Single cell sequencing reveals expanded cytotoxic CD4+ T cells and two clusters of peripheral helper T cells in synovial fluid of ACPA+ RA patients

  Study EGAS00001005241

• Baulac Lab - Paris Brain Institute

  Raw 10X single-nucleus RNA-seq data from human postoperative brain samples of patients with epilepsy and cortical malformations.

  Dac EGAC50000000546

• CRISPR_perturbations_IRF4_PRDM1_Bcells

  CRISPR perturbations of IRF4, PRDM1, and AAVS1 (within PPP1R12C gene) in activated B cells

  Dataset EGAD50000002113

• Transcriptomic profiling of lymphedema

  RNA-seq of skin from human subjects with and without lymphedema

  Dataset EGAD00001006246

• Exome Sequencing of Gastric Cancer Samples

  We perform whole exome sequencing on 50 pairs of gastric cancer and matched normal samples.

  Dataset EGAD00001006957

• Longitudinal analysis of treatment induced genomic alterations

  Variant call set (vcf) for three (primary and two recurrent) tumors

  Dataset EGAD00001003164

• The UCSF Glioblastoma Genome Project #1

  Dataset contains MeDIP-Seq, MRE-Seq and H3K4me3 ChIP-Seq data on 5 GBM patients.

  Dataset EGAD00001000777

• Whole Genome Sequencing of acral melanoma

  Whole Genome Sequencing of 5 acral melanomas and matched normal samples

  Dataset EGAD00001000944

• High-grade meningioma sequencing data

  Whole genome, whole exome, and custom panel sequencing of high-grade meningioma cohort

  Dataset EGAD00001003220

• Immunopeptidomics of colorectal cancer organoids reveals a sparse HLA class I neoantigen landscape and no increase in neoantigens with interferon or MEK-inhibitor treatment

  Study EGAS00001003886

• 450K_DKFZ_JMML_DBL

  DNA methylation analysis from primary human JMML and normal blood samples using 450K

  Dataset EGAD00010001296

• Nanostring

  Nanostring PanCancer immune profiling data for The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer

  Dataset EGAD00010001515

• WP8_DNA_Methylation_450K_UCL

  BLUEPRINT DNA methylation profiles of monocytes, T cells and B cells in type 1 diabetes-discordant monozygotic twins

  Dataset EGAD00010001025

• ADME_gene_expression

  Gene expression for 303 ADME and ADME related genes (averaged log2 signal intensities using Human-WG6v2 Expression BeadChip)

  Dataset EGAD00010001709

• Methylation_monocytes_female_CD

  Whole-genome DNA methylation profiling of CD14+ monocytes obtained from CD-active, CD-remissive and non-CD individuals

  Dataset EGAD00010001846

• Groupe_case

  Illumina EPIC arrays of human osteoblastomas and their mimics

  Dataset EGAD00010002279

• Illumina_450K

  Primary renal cell carcinoma (RCC), RCC metastases and cell lines by Illumina 450K

  Dataset EGAD00010001001

• Batch1-2_Genotypes_PostQC

  Combined genotypes for Batch 1 and 2 after quality control. All individuals included in analyses.

  Dataset EGAD00010002127

• Hiseq 2000 and GA whole genome sequecing of 14 paired hepatocellular carcinomas

  Dataset EGAD00001001645

• RNA-sequençing of 21 inflammatory hepatocellular adenomas and 1 non-tumoral sample

  Dataset EGAD00001005284

• Stability of gut microbiome after COVID-19 vaccination in healthy and immuno-compromised individuals

  Metagenomic sequencing of human fecal samples

  Dataset EGAD50000000258

• Sample metadata

  Sample metadata for this experiment. Includes treatment and donor derivation information.

  Dataset EGAD50000000827

• Preeclampsia InterPregGen Consortium: GWAS meta-analysis summary statistics for European fetal preeclampsia cases versus controls and GWAS genotype data for European fetal preeclampsia cases

  Study EGAS00001001048

• TCR β-chain repertoire characterization of regulatory and conventional T cells in breast tumors from breast cancer patients.

  Dataset EGAD00001006428

• PanCancer_Phosphoproteomics2024

  Pan-cancer phosphoproteomics profiling data for 1000 retrospective and prospective samples of the MASTER/INFORM cohort,Shotgun proteomics

  Dataset EGAD00010002730