11932 results for "cancer rna-seq"

in 29.75 milliseconds.

• BLUEPRINT release August 2016, Bisulfite-Seq for monocyte - RPMI_BG_T=4hrs, on genome GRCh38

  Bisulfite-Seq data for 1 monocyte - RPMI_BG_T=4hrs sample(s). 14 run(s), 1 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002301

• BLUEPRINT release January 2015, Bisulfite-Seq for precursor lymphocyte of B lineage

  Bisulfite-Seq data for 1 precursor lymphocyte of B lineage sample(s). 8 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001134

• BLUEPRINT release August 2014, Bisulfite-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell

  Bisulfite-Seq data for 1 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 14 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000932

• BLUEPRINT release August 2015, Bisulfite-Seq for alternatively activated macrophage, on genome GRCh38

  Bisulfite-Seq data for 5 alternatively activated macrophage sample(s). 79 run(s), 5 experiment(s), 5 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001498

• Chromatin 3D interactions mediate genetic effects on gene expression (ChIP-seq)

  ChIP-seq data for Lymphoblastoid Cell Lines (LCL) and Fibroblasts (FIB) from the Gencord Cohort: - 160 LCLs assayed for H3K27ac, H3K4me1 and H3K4me3, - 78 FIB assayed for H3K4me3 and 79 FIB assayed for H3K27ac and H3K4me1 This dataset was generated as part of the following study: Delaneau et al (2019). Chromatin 3D interactions mediate genetic effects on gene expression.

  Dataset EGAD00001004871

• BLUEPRINT release January 2015, ChIP-Seq for erythroblast

  ChIP-Seq data for 2 erythroblast sample(s). 14 run(s), 14 experiment(s), 14 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001194

• BLUEPRINT release August 2016, Bisulfite-Seq for monocyte - RPMI_LPS_T=1hr, on genome GRCh38

  Bisulfite-Seq data for 1 monocyte - RPMI_LPS_T=1hr sample(s). 14 run(s), 1 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002502

• BLUEPRINT release August 2015, Bisulfite-Seq for inflammatory macrophage, on genome GRCh38

  Bisulfite-Seq data for 6 inflammatory macrophage sample(s). 83 run(s), 6 experiment(s), 6 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001491

• BLUEPRINT release August 2015, Bisulfite-Seq for plasma cell, on genome GRCh38

  Bisulfite-Seq data for 2 plasma cell sample(s). 17 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001522

• BLUEPRINT release August 2015, Bisulfite-Seq for precursor B cell, on genome GRCh38

  Bisulfite-Seq data for 1 precursor B cell sample(s). 6 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001529

• BLUEPRINT release August 2014, Bisulfite-Seq for precursor lymphocyte of B lineage

  Bisulfite-Seq data for 1 precursor lymphocyte of B lineage sample(s). 8 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000910

• BLUEPRINT release August 2016, Bisulfite-Seq for erythroblast, on genome GRCh38

  Bisulfite-Seq data for 2 erythroblast sample(s). 35 run(s), 2 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002423

• BLUEPRINT release January 2015, Bisulfite-Seq for CD38-negative naive B cell

  Bisulfite-Seq data for 3 CD38-negative naive B cell sample(s). 29 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001205

• BLUEPRINT release August 2015, Bisulfite-Seq for naive B cell, on genome GRCh38

  Bisulfite-Seq data for 1 naive B cell sample(s). 5 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001556

• BLUEPRINT release August 2015, Bisulfite-Seq for germinal center B cell, on genome GRCh38

  Bisulfite-Seq data for 1 germinal center B cell sample(s). 6 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001587

• BLUEPRINT release August 2015, Bisulfite-Seq for memory B cells, on genome GRCh38

  Bisulfite-Seq data for 1 memory B cells sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001494

• BLUEPRINT release August 2015, ChIP-Seq for Leukemia, on genome GRCh38

  ChIP-Seq data for 1 Leukemia sample(s). 2 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001528

• BLUEPRINT release August 2015, Bisulfite-Seq for class switched memory B cell, on genome GRCh38

  Bisulfite-Seq data for 2 class switched memory B cell sample(s). 21 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001548

• BLUEPRINT release January 2015, Bisulfite-Seq for cytotoxic CD56-dim natural killer cell

  Bisulfite-Seq data for 3 cytotoxic CD56-dim natural killer cell sample(s). 38 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001128

• BLUEPRINT release January 2015, Bisulfite-Seq for endothelial cell of umbilical vein (proliferating)

  Bisulfite-Seq data for 1 endothelial cell of umbilical vein (proliferating) sample(s). 21 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001151

• BLUEPRINT release January 2015, Bisulfite-Seq for endothelial cell of umbilical vein (resting)

  Bisulfite-Seq data for 2 endothelial cell of umbilical vein (resting) sample(s). 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001135

• BLUEPRINT release January 2015, ChIP-Seq for Acute promyelocytic leukemia

  ChIP-Seq data for 6 Acute promyelocytic leukemia sample(s). 25 run(s), 23 experiment(s), 23 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001138

• BLUEPRINT release January 2015, ChIP-Seq for Chronic lymphocytic leukemia

  ChIP-Seq data for 3 Chronic lymphocytic leukemia sample(s). 6 run(s), 6 experiment(s), 6 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001187

• BLUEPRINT release January 2015, Bisulfite-Seq for effector memory CD8-positive, alpha-beta T cell

  Bisulfite-Seq data for 1 effector memory CD8-positive, alpha-beta T cell sample(s). 11 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001200

• BLUEPRINT release August 2016, Bisulfite-Seq for macrophage, on genome GRCh38

  Bisulfite-Seq data for 6 macrophage sample(s). 88 run(s), 7 experiment(s), 12 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002501

• BLUEPRINT release January 2015, ChIP-Seq for monocyte

  ChIP-Seq data for 2 monocyte sample(s). 7 run(s), 7 experiment(s), 7 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001197

• BLUEPRINT release January 2015, Bisulfite-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell

  Bisulfite-Seq data for 1 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 14 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001150

• BLUEPRINT release August 2016, Bisulfite-Seq for monocyte - RPMI_T=24hrs, on genome GRCh38

  Bisulfite-Seq data for 1 monocyte - RPMI_T=24hrs sample(s). 14 run(s), 1 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002335

• BLUEPRINT release August 2016, Bisulfite-Seq for band form neutrophil, on genome GRCh38

  Bisulfite-Seq data for 3 band form neutrophil sample(s). 34 run(s), 3 experiment(s), 6 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002378

• BLUEPRINT release August 2016, ChIP-Seq for Lymphoma_Follicular, on genome GRCh38

  ChIP-Seq data for 3 Lymphoma_Follicular sample(s). 11 run(s), 11 experiment(s), 11 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002389

• BLUEPRINT release August 2015, Bisulfite-Seq for hematopoietic multipotent progenitor cell, on genome GRCh38

  Bisulfite-Seq data for 1 hematopoietic multipotent progenitor cell sample(s). 5 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001493

• BLUEPRINT September 2016, Bisulfite-Seq Acute Lymphocytic Leukemia for precursor B cell from bone marrow, on Genome GRCh38

  Bisulfite-Seq data for 1 sample(s) Acute Lymphocytic Leukemia for precursor B cell from bone marrow, on Genome GRCh38. 3 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001002969

• FASTQ files of the Exome-Seq data for the study "Genomic landscape of lung adenocarcinoma in East Asians"

  FASTQ files of the Exome-Seq data for both the normal and tumor samples for the study "Genomic landscape of lung adenocarcinoma in East Asians". For mutations and copy number variants called by this study, please download from https://src.gisapps.org/OncoSG_public/study/summary?id=GIS031 by clicking the download icon next to the dataset title.

  Dataset EGAD00001004422

• Genomic landscape of IG-MYC positive Burkitt lymphoma with precursor B-cell immunophenotype.

  As part of the ICGC, the ICGC MMML-Seq project performed whole genome sequencing of a rare Burkitt lymphoma subtype with precursor B-cell immunophenotype. Analysis were performed in concordance with the guidelines of the ICGC.

  Study EGAS00001002968

• Mutational_burden_in_oesophagus__nanoseq_

  We wish to accurately assess mutational burden and signature from patients of different ages using clonal oesophageal epithelium and duplex-seq. We will also attempt to look for differences between smokers and non-smokers and individuals with different levels of alcohol consumption.

  Study EGAS00001007695

• iPSC and iNeuron RNAseq, chip-seq and single cell CRISPR activation

  Dataset includes 1) RNAseq for Bob_Ngn2 cell differentiation from iPSC to iNeuron stage (time point 0, 24, 48 and 96 hours). 2) Bob_Ngn2 cell line chip-seq (H3K4me3, H3K4me1, H3K27me3, H3K9me3, H3K27ac, H3K36me3) for both iPSC and iNeuron stage with 3 replicates at each time point. 3) Single cell CRISPR activation experiment with 96 endogenous genes.

  Dataset EGAD00001010050

• CUT&RUN/ChIP-Seq dataset for Malignant rhabdoid study

  Study describing the dynamics of chromatin organization within malignant rhabdoid tumors. This study describes how this chromatin organization changes upon SMARCB1 rescue within patient-derived organoid models from malignant rhabdoid tumors. Identification of a novel super-enhancer of MYC and identification of patient-specific enhancer utilization to activate MYC expression in these tumors.

  Dataset EGAD00001011821

• BLUEPRINT release January 2015, Bisulfite-Seq for CD4-positive, alpha-beta T cell

  Bisulfite-Seq data for 3 CD4-positive, alpha-beta T cell sample(s). 61 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001157

• BLUEPRINT release August 2015, Bisulfite-Seq for conventional dendritic cell, on genome GRCh38

  Bisulfite-Seq data for 2 conventional dendritic cell sample(s). 30 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001497

• BLUEPRINT release August 2015, Bisulfite-Seq for mature eosinophil, on genome GRCh38

  Bisulfite-Seq data for 1 mature eosinophil sample(s). 15 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001507

• BLUEPRINT release August 2015, Bisulfite-Seq for regulatory T cell, on genome GRCh38

  Bisulfite-Seq data for 1 regulatory T cell sample(s). 15 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001564

• BLUEPRINT release August 2015, Bisulfite-Seq for monocytes - T=0days, on genome GRCh38

  Bisulfite-Seq data for 1 monocytes - T=0days sample(s). 15 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001565

• BLUEPRINT release August 2016, Bisulfite-Seq for monocyte - RPMI_LPS_T=24hrs, on genome GRCh38

  Bisulfite-Seq data for 1 monocyte - RPMI_LPS_T=24hrs sample(s). 22 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002302

• BLUEPRINT release August 2016, Bisulfite-Seq for monocyte - RPMI_BG_T=1hr, on genome GRCh38

  Bisulfite-Seq data for 1 monocyte - RPMI_BG_T=1hr sample(s). 14 run(s), 1 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002327

• BLUEPRINT release August 2016, Bisulfite-Seq for naive B cell, on genome GRCh38

  Bisulfite-Seq data for 3 naive B cell sample(s). 39 run(s), 3 experiment(s), 6 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002361

• Low mutation burden and frequent loss of CDKN2A/B and SMARCA2, but not PRC2, define pre-malignant neurofibromatosis type 1-associated atypical neurofibromas

  Neurofibromatosis type 1 (NF1) is a tumor-predisposition disorder caused by germline mutations in NF1. NF1 patients have an 8-16% lifetime risk of developing a malignant peripheral nerve sheath tumor (MPNST), a highly aggressive soft-tissue sarcoma, often arising from pre-existing benign plexiform neurofibromas (PN) and atypical neurofibromas (ANF). ANF are distinct from both PN and MPNST, representing an intermediate step in malignant transformation. In the first comprehensive genomic analysis of ANF, we performed tumor/normal exome sequencing (ES) of 16 ANFs. In addition, we conducted ES of three MPNSTs, copy-number meta-analysis of 26 ANF and 28 MPNST, and whole transcriptome RNA-seq analysis of five ANF and five MPNST. We identified low mutation burden (median 1, range 0-5) in the exomes of ANF (only NF1 somatic mutations were recurrent), and frequent deletions of CDKN2A/CDKN2B (69%) and SMARCA2(42%) loci. We determined that polycomb repressor complex 2 (PRC2) genes EED or SUZ12 were frequently mutated, deleted or downregulated in MPNST but not in ANF. Our gene expression study revealed upregulated NRAS, MDM2, CCND1/CCND2/CCND3 and CDK4/CDK6 in both ANF and MPNST, and overexpression of EZH2 in MPNST only. We conclude that the PN-ANF transition is primarily driven by the deletion of CDKN2A/CDKN2B in addition to already present inactivated NF1. Further progression from ANF to MPNST likely involves broad chromosomal rearrangements and frequent inactivation of the PRC2 genes, loss of the DNA repair genes, and copy-number increase of signal transduction, cell cycle and pluripotency self-renewal genes.

  Study phs001993

• Investigating Delayed-Onset Drug Hypersensitivity Reactions Prospectively

  Delayed-type drug hypersensitivity reactions (dtDHR) are significant causes of morbidity and mortality, but the origin, phenotype and function of pathogenic T cells across the spectrum of severity are unknown. Research has been hampered by several barriers. We leveraged recent technical advancements to study skin-resident memory T cells (TRM) versus recruited T cell subsets in the pathogenesis of severe systemic forms of disease, Stevens-Johnson syndrome/toxic epidermal necrolysis (SJS/TEN) and drug reaction with eosinophilia and systemic symptoms (DRESS), and skin-limited disease, morbilliform drug eruption (MDE). As part of the overarching study, we used single cell RNA sequencing (scRNA-seq) with CITE sequencing and TCR sequencing on prospectively collected skin and blood samples from patients with SJS/TEN and MDE patients. We compared this to healthy controls obtained from discarded skin from surgeries and discarded blood collars from a blood donation center. These data are included here in dbGaP database. The overarching study also performed bulk transcriptional profiling and microscopic analysis of clinical skin samples, as well as a mouse model of MDE (PMID: 39042477). Together, the data supported clonal expansion and recruitment of cytotoxic CD8+ T cells (identified using the mean normalized expression of NKG7, GNLY, GZMA, GZMB, and PRF1) from circulation into skin, along with both expanded and non-expanded cytotoxic CD8+ skin TRM in SJS/TEN whereas MDE displayed a cytotoxic T cell profile without expansion or recruitment of cytotoxic CD8+ T cells from circulation implicating TRM as the potential cause of disease. Concurrently, MDE displayed a pro-Treg signature, highlighted by CCR8 and TNFRSF4 (OX40), which promotes Treg survival compared to SJS/TEN.

  Study phs003344

• Exploiting immune cell receptor information to quantify index switching in single cell transcriptome sequencing experiment

  By offering high sequencing speed and ultra-high-throughput at a low price, Illumina next-generation sequencing platforms has been widely adopted in recent years. However, an experiment with multiplexed library could be at risk of molecular recombination, known as “index switching”, which causes certain amount of reads to be assigned to an incorrect library. It is reported that a new advance, exclusion amplification (ExAmp) in conjunction with the patterned flow cell technology introduced on HiSeq 3000/HiSeq 4000/HiSeq X sequencing systems, potentially suffers from a higher rate of index switching than conventional bridge amplification. We took advantage of the diverse but highly cell-unique expression of immune cell receptors to quantify index switching on single cell RNA-seq data that were sequenced on HiSeq 3500 and HiSeq 4000. By utilizing the unique T-cell receptor (TCR) expression, we could quantify the spread-of-signal from many different wells (n=51 from total three batches) due to index switching. We used TraCer to reconstruct full-length TCR from all samples, and then used Kallisto to quantify TCR gene expression. We found index switching in all three batches of experiments investigated. The median percentage of incorrectly detected markers was estimated to be 4.2% (interquartile range (IQR): 2.0%-8.7%). We did not detect any consistent pattern of certain indices to be more prone for switching than others, suggesting that index switching is a stochastic process. We confirm that index switching is a problem that affects all samples run in multiplexed libraries on Illumina HiSeq 3500 and HiSeq 4000 platforms.

  Study EGAS00001002911

• Monocyte and macrophage lipid accumulation results in downregulated type-I interferon responses

  Macrophages are critical components of atherosclerotic lesions and their pro- and anti-inflammatory responses influence atherogenesis. Type-I interferons (IFNs) are cytokines that play an essential role in antiviral responses and inflammatory activation and have been shown to promote atherosclerosis. Although the impact of type-I IFNs on macrophage foam cell formation is well-documented, the effect of lipid accumulation in monocytes and macrophages on type-I IFN responses remains unknown. Here we examined IFN stimulated (ISG) and non-ISG inflammatory gene expression in mouse and human macrophages that were loaded with acetylated LDL (acLDL), as a model for foam cell formation. We found that acLDL loading in mouse and human macrophages specifically suppressed expression of ISGs and IFN-β secretion, but not other pro-inflammatory genes. The downregulation of ISGs could be rescued by exogenous IFN-β supplementation. Activation of the cholesterol-sensing nuclear liver X receptor (LXR) recapitulated the cholesterol-initiated type-I IFN suppression. Additional analyses of murine in vitro and in vivo generated foam cells confirmed the suppressed IFN signalling pathways and suggest that this phenotype is mediated via downregulation of interferon regulatory factor binding at gene promoters. Finally, RNA-seq analysis of monocytes of familial hypercholesterolemia (FH) patients also showed type-I IFN suppression which was restored by lipid-lowering therapy and not present in monocytes of healthy donors. Taken together, we define type-I IFN suppression as an athero-protective characteristic of foamy macrophages. These data provide new insights into the mechanisms that control inflammatory responses in hyperlipidaemic settings and can support future therapeutic approaches focusing on reprogramming of macrophages to reduce atherosclerotic plaque progression and improve stability.

  Study EGAS00001005955

• Identification of the dismal subtype of B-ALL with dysregulation of CDX2 and UBTF

  PURPOSE: Advance in the knowledge of genomic basis of B-cell acute lymphoblastic leukemia (B-ALL) has changed the treatment approaches and diagnostic assays and improved their outcome. Despite the recent development of next generation sequencing approaches, there are still some cases that their drivers are unknown. We aimed to define and describe the characteristics of an additional B-ALL subtype by integrating genomic, transcriptomic, and epigenomic approach. METHODS: More than 2,000 B-ALL cases of RNA-seq data from from Eastern Cooperative Oncology Group (ECOG) and the American College of Radiology Imaging Network (ACRIN) (n=764), the Children's Oncology Group (COG), Munich Leukemia Laboratory (MLL) (n=280), and other several collaborators were analyzed to identify the new subtype. Whole genome sequence was performed to detect mutations, stractural variants, and copy number alterations. The tridimentional analysis of chromatin was performed with HiChIP. RESULTS: We identified the new high-risk B-ALL subtype “CDX2/UBTF” that exhibited unique gene expression profiles, which is enriched in female (77.3%), adolescents and young adults (52.6%), and relapse cohort (3.3%). CD10 negativity and IgM positivity are hallmarks of this subtype with NTRK3 expression that can be an effective marker at diagnostic approach and a potential targeted therapy with TRK and mulkinase inbitors, larotrectinib and entrectinib. Genetically, two different alterations define CDX2/UBTF. One is UBTF-ATXN7L3 fusions caused by deletion of 17q21.31, and the other is extopic CDX2 expression through the enhancer hijacking mechanism induced by deletion of 13q12.2. Other genomic features include gain of 1q and PAX5 rearrangement (PAX5-ZCCHC7), might induce upregulation of histone cluster genes and PAX5. CONCLUSION: We described the novel B-ALL subtype “CDX2/UBTF” that has unique clinical and genomic characteristics.

  Study EGAS00001005863

• Epitope-linked Ig-seq of self-reactive plasma cells in celiac disease

  Study EGAS00001003658

• ChIP-seq of plasma cell-free nucleosomes identifies cell-of-origin gene expression programs

  Dac EGAC00001001875

• EGFR Mutant SCLC transformed exome seq

  Dataset EGAD00001001436

• ChIP_PEAKS

  ChIP-seq narrowPeaks. Software: MACS2 v2.1.2

  Dataset EGAD00010001923

• Human Inflammatory Skin Disease scRNA-seq

  Study EGAS00001005271

• ATRT ChIPSeq H3K27ac

  ATRT ChIPSeq H3K27ac

  Dataset EGAD00001004836

• Exome

  Exome Seq for Study EGAS00001001844

  Dataset EGAD00001002159

• Exome

  Exome Seq from EGAS00001001846

  Dataset EGAD00001002162

• Single-cell RNA-seq analysis for COVID19 patients

  While SARS-CoV-2 infection causes mild respiratory disease in most individuals, a small group of patients develops severe COVID-19. Dysfunctional innate immune responses have been identified to contribute to differences in COVID-19 severity, but the key regulators are still unknown. Here, we present an integrative single-cell epigenetics, transcriptomic, and genetics analysis of peripheral blood mononuclear cells from hospitalized and convalescent COVID-19 patients. In classical monocytes, we identified 41.3% of significantly up-regulated genes in hospitalized COVID-19 patients potentially induced by differential chromatin accessibility. Sub-clustering and motif-enrichment analyses of monocytes reveal disease condition-specific regulation by transcription factors, such as C/EBPs and SPI1, and their targets, including a long-noncoding RNA LUCAT1, which further regulates interferon responses and is associated with the need for oxygen supply of COVID-19 patients. The interaction between C/EBPs and LUCAT1 was validated through loss-of-function experiments. Finally, we investigated genetic risk variants that exhibit allele-specific open chromatin (ASoC) in promoters/enhancers of COVID-19 patients. Integrating our data with publicly available expression quantitative trait loci and chromosomal interactions indicates that ASoC SNP rs6800484-C is associated with lower expression of CCR2, which may contributeto higher viral loads in lungs and higher risk of COVID-19 hospitalization. Altogether, our study highlights the diverse genetic and epigenetic regulators that contribute to the innate immune responses of different COVID-19 patients.

  Study EGAS00001006560

• Whole Exome and RNA Sequencing of 22 Patient-Derived Xenografts from Estrogen Receptor-Positive Breast Cancers

  We performed RNA and whole exome sequencing on 22 patient-derived xenografts (PDX) from estrogen receptor-positive (ER+) breast cancers, in the presence and absence of estradiol (E2) supplementation. Exome coverage across more than 3,500 clinically relevant genes that previously were covered below 20X (~2.72Mb) was achieved. On average, 11.2Gb of unique sequence data were generated with 95.3% of the bases in the exome design covered to 20x read depth or greater. RNA sequencing was generated from xenograft tumors. Between 50 and 85M total reads were performed. The average strand-specificity and rRNA rate was 98% and 1.5%, respectively. Transcripts for 17,000 to 27,087 genes were detected in these samples.

  Study phs003324

• scRNA-seq reveals alterations of multiple alveolar macrophage states in chronic obstructive pulmonary disease

  Dac EGAC00001001547

• The paired FF/FFPE colon set, Exome-Seq

  Dataset EGAD00001000834

• AML scRNA-seq

  Dataset EGAD00001006537

• RNA sequecing of primary B cells infected with Epstein-Barr virus (EBV) or stimulated with heat-inactivated EBV

  Naïve (CD27-IgD+) B cells were isolated from buffy coat preparations of healthy donors using CD19 magnetic beads, followed by reals of CD19 beads and incubation with IgD-biotin and anti-biotin magnetic beads. B cells were infected with EBV by spinoculation or stimulated with heat-inactivated EBV and control cells were left uninfected. RNA was extracted immediately after isolation in un-infected B cells. From EBV-infected B cells and B cells stimulated with heat-inactivated virus, RNA was extracted 24 and 96 hours after infection / stimulation.

  Dataset EGAD50000000305

• Ribosomal profiling on Epstein-Barr virus transformed B-lymphoblastoid cell lines

  Epstein-Barr virus-transformed B-lymphoblastoid cell lines from six individuals (HG00114, HG00282, NA12005, NA12044, NA12717 and NA12751) of the GEUVADIS Project were selected for ribosomal profiling. For each EBV-LCL, 20 million cells were treated with 2 μg/ml harringtonine and 100 μg/ml cycloheximide. After lysing cells in lysis buffer supplemented with 100 μg/ml cycloheximide, ribosome complexes were purified by density purification. Small RNA molecules were isolated using the NucleoSpin miRNA Kit (Bioke, Leiden, Netherlands), followed by RNA PAGE gel separation. Universal linkers were added after dephosphorylation. After reverse transcription, the cDNA was circularized and, after ribosomal RNA depletion, barcoded and sequenced on Illumina NextSeq 500.

  Dac EGAC50000000209

• Single-cell RNA-sequencing of CSF cells and PBMCs from individuals with neurological disorders

  We undertook single-cell RNA sequencing to establish gene expression and lymphocyte receptor sequences of CSF and peripheral blood leukocytes derived from patients with a variety of inflammatory, infectious and non-inflammatory neurological disorders. The aim of the study was the investigation of functional changes of the cells involved in neuroinflammatory responses.

  Study EGAS00001007954

• Spinocerebellar ataxia type 3 RNA-sequencing study

  RNA-Sequencing from human post-mortem Spinocerebellar ataxia type 3 patients. This sequencing experiment was carried out to validate that the transcriptional changes of an Ataxin-3 knock-in mouse model (expressing an expansion of 304 CAG/CAAs either heterozygous or homozygous in the murine Ataxin-3 locus) represent that transcriptional changes seen in the human disease.

  Study EGAS00001004241

• DIPG RNA and exome sequencing

  DIPG is a paediatric high-grade glioma that diffusely infiltrates the brainstem and is the leading cause of paediatric brain tumour death. Here we performed RNA and whole exome sequencing on DIPG and control samples to analyse transcriptomic and genetic alterations associated with this devastating disease, and to understand the relationship between them.

  Study EGAS00001004749

• Melanoma Genome Sequencing Project

  Melanoma is the most prevalent cause of skin cancer morbidity and mortality. In order to characterize the full range of somatic mutations that may drive the growth of melanoma, we are sequencing tumor and normal DNA from a set of roughly 150 melanomas. For the majority of samples (approximately 90% of the cases), mutations in protein coding genes will be assessed in the exonic DNA of tumor-normal pairs using hybrid capture and paired-end DNA sequencing. For a few of DNA samples (approximately 10% of the cases), the entire genomes will be analyzed to assess the possible contribution of complex structural rearrangements contributing to oncogenesis. The sequencing data are supplemented by copy number profiling on the same tumors using high-density SNP arrays. Integration of these approaches will enable the unbiased and comprehensive characterization of both known and novel recurrent DNA alterations that arise in melanoma.Versions 1-4 contain whole exome and bulk RNA sequencing data for patients with melanoma.Version 5 - We compared somatic genomic profiles from matched pre-treatment and post-resistance tumor biopsies in patients with metastatic melanoma who exhibited heterogeneous responses to immune checkpoint inhibitors (ICIs). This version includes whole exome sequencing (WES) data from 14 patients.

  Study phs000452

• The PEMDAC phase 2 study of pembrolizumab and entinostat in patients with metastatic uveal melanoma

  Patients with metastatic uveal melanoma (UM) have an abysmal prognosis. Preclinical studies have suggested that epigenetic therapy could enhance immunogenicity of cancer cells. Here we test if epigenetic therapy would enhance PD-1 immunotherapy in patients with metastatic UM. We report the results of the PEMDAC phase 2 clinical trial (n=29; NCT02697630) where the HDAC inhibitor entinostat was combined with the PD-1 inhibitor pembrolizumab in patients with metastatic UM. The primary endpoint was objective response rate (ORR), and was met with an ORR of 14%. The clinical benefit rate at 18 weeks was 28%, median progression free survival was 2.1 months and the median overall survival was 13.4 months. Toxicities were manageable, and there were no treatment-related deaths. Extensive genomics studies were performed using DNA/RNA and single cell sequencing and flow cytometry. Objective responses and prolonged survival were seen in three patients with BAP1 wildtype tumors, and in one patient with an iris melanoma that exhibited a UV signature. Longer survival also correlated with low baseline ctDNA levels or LDH. In conclusion, HDAC inhibition and anti-PD1 immunotherapy results in durable responses in a subset of patients with metastatic UM. Further exploration of combined immunotherapy and epigenetic therapy in metastatic UM is warranted.

  Study EGAS00001005478

• Ewing and Ewing-like-sarcoma tumoroid biobank reveals distinct drug sensitivities: translocation makes the difference

  Ewing sarcoma (ES) and Ewing-like sarcomas (ELS) are highly aggressive tumors found in soft tissues and bone of mostly children and young adults. Despite being different in many aspects, including genetics, possible cell-of-origin, and pathology, patients with any of these entities all receive the same therapeutic regimen. Currently, there is a lack of preclinical cell models that can predict drug response of these entities in vitro. Here, we describe a pediatric ES and ELS tumor organoid (tumoroid) biobank containing tumoroids with different translocations, including EWSR1::FLI1, EWSR1::ERG, CIC::DUX4, and BCOR-rearrangements. Using histology, whole genome sequencing and RNA sequencing, we demonstrate that these tumoroids retain key properties of their matching patient tumors. In addition, we traced tumor subclones in the tumoroids across patient-matched longitudinal samples, which showed that cellular heterogeneity was maintained. We subsequently performed drug screening on the tumoroid models, which unveiled entity-specific drug sensitivity to various cytotoxic compounds and targeted compounds, including MCL-1 inhibitors for CIC::DUX4 sarcomas. Taken together, this newly established ES and ELS patient-derived tumoroid biobank generates a unique source of material for future basic cancer research and drug-screening.

  Study EGAS00001007941

• Longitudinal evaluation of serum microRNAs as biomarkers for neuroblastoma burden and therapeutic p53 reactivation

  Accurate assessment of treatment response and residual disease is indispensable for the evaluation of cancer treatment efficacy. However, performing tissue biopsies for longitudinal follow-up poses a major challenge in the management of solid tumours like neuroblastoma. In the present study, we evaluated whether circulating miRNAs are suitable to monitor neuroblastoma tumour burden and whether treatment-induced changes of miRNA abundance in the tumour are detectable in serum. We performed small RNA sequencing on longitudinally collected serum samples from mice carrying orthotopic neuroblastoma xenografts that were exposed to treatment with idasanutlin or temsirolimus. We identified 57 serum miRNAs to be differentially expressed upon xenograft tumour manifestation, out of which 21 were also found specifically expressed in the serum of human high-risk neuroblastoma patients. The murine serum levels of these 57 miRNAs correlated with tumour tissue expression and tumour volume, suggesting potential utility for monitoring tumour burden. In addition, we describe serum miRNAs that dynamically respond to p53 activation following treatment of engrafted mice with idasanutlin. We identified idasanutlin-induced serum miRNA expression changes upon one day and 11 days of treatment. By limiting to miRNAs with a tumour-related induction, we put forward hsa-miR-34a-5p as a potential pharmacodynamic biomarker of p53 activation in serum.

  Study EGAS00001006678

• Stratifying and Targeting Pediatric Medulloblastoma through Genomics

  In this project, genomic analyses of pediatric medulloblastoma samples, obtained through the international medulloblastoma consortium, will be performed. RNA and miRNA expression profiles of 1000 samples, representing all four subgroups (Wnt, Shh, Group C, and D), will be studied to identify novel subtypes within each subgroup. The resulting subtype-specific expression profiles will support the development of reliable and robust biomarkers to more accurately and reliably classify medulloblastomas for treatment in clinical trials. For that purpose, two assays will be developed: an antibody-based immunohistochemical assay and an orthogonal nucleic acid-based hybridization assay. Additional genomic DNA analysis of the 300 high risk subgroup cases will support the discovery of subgroup specific somatic mutations in order to inform current clinical trials of targeted therapies, and to identify genes and pathways already targeted in other diseases. Such therapies could be rapidly transitioned to Phase II trials in medulloblastoma. Furthermore, the discovery of somatic mutations could be used for developing as well as validating specific biomarkers. The project team will also try to identify risk factors that predispose children to this type of cancer.

  Study EGAS00001000273

• ADCC Pilot RNAseq Study on Posterior Cingulate Astrocytes in Alzheimer's Disease

  In this study, RNA sequencing was performed on astrocytes microdissected from the posterior cingulate cortex of Alzheimer's disease subjects and healthy elderly controls.

  Study phs000745

• TCRseq

  T cell receptor sequencing of tumor samples. Briefly, DNAse I treated tumor RNA samples were subjected to library preparation using AmpliSeq Immune Repertoire Panel (Illumina) and sequenced using NextSeq500.

  Study EGAS50000000258

• Transcriptional Reference Map of Human Natural Killler Cells

  Here we performed single-cell RNA sequencing of both bulk NK and sorted NK subsets to establish a transcriptional reference map of human natural killer cells.

  Study EGAS50000000014

• Inherited defects of piRNA biogenesis cause transposon de-repression, impaired spermatogenesis, and human male infertility

  Effect of biallelic variants in genes of the piRNA pathway on biogenesis of pachytene piRNAs. RNA isolated from snap frozen testicular tissue

  Study EGAS50000000397

• Single-cell RNAseq of hematological toxicity following CAR-T cells injection

  Bone marrow aspirations obtained from patients treated with CAR-T cells were analyzed using single cell RNA sequencing (CD3+, CAR T+, CD34+ sorted populations).

  Study EGAS50000000776

• circulating cell-free RNAs, CF-miRNAs, Sequencing with Qiaseq and NextSeq 550

  This dataset includes small RNA sequencing data from circulating cell-free RNAs (CF-miRNAs). miRNA libraries were prepared using the Qiaseq miRNA Library Kit with adaptations for low RNA input and sequenced on the Illumina NextSeq 550 platform

  Dataset EGAD50000001503

• RNA-sequencing of PBMCs from COVID-19 patients experiencing different degrees of the disease (mild and critical), and control patients

  Bulk RNA-sequencing of peripheral blood mononuclear cells collected from mild COVID-19 (n = 4), critical COVID-19 (n = 12) and control (n = 8) patients. Sequencing data is provided as FASTQ files.

  Dataset EGAD50000001405

• p200503_fn1

  RNA-Sequencing data of tumor spheroids (HT-29) incubated with medium conditioned by Fusobacterium nucleatum treated CAFs (patient derived CAF20 and CAF32 as well as the CAF05 cell line).

  Study EGAS50000001120

• Single-cell transcriptomic data of 9 DHG-H3G34 patient tumors.

  We applied single-cell/single-nucleus RNA-sequencing to a patient cohort of 9 fresh and frozen untreated diffuse hemispheric gliomas, H3G34-mutant (DHG-H3G34).

  Study EGAS50000000534

• Ribo-depleted RNA-sequencing of II.3, III.1, and III.3

  This datasets contains the Ribo-depleted RNA-sequencing of patients II.3, III.1, and III.3. Libraries were sequenced to a minimum depth of 195 million read pairs (2x75nts) on an Illumina NextSeq500 Midoutput FC.

  Dataset EGAD50000002364

• RNA sequencing data to study therapeutic targeting of ependymoma

  This dataset conatains RNA sequencing data from 24 patients. Up to two lanes per tumour sample have been seqeunced on a Illumina HiSeq2000 instrument in paired-end mode resulting in 58 Fastq files.

  Dataset EGAD00001003966

• FACS-based purification and paired-end RNA sequencing

  We performed a prospective investigation in Sézary syndrome by the application of a standardized multiparameter flow cytometry, FACS-cell sorting, and RNA-sequencing for an in-depth immunophenotypic and transcriptional profiling of Sézary cells.

  Dataset EGAD00001007687

• RNA sequencing of human fetal brain at 7, 9, 12, 15 and 21 gestational weeks

  The dataset contains raw sequences (FASTQ files) from the Illumina 2x150bp paired-end RNA sequencing profiles of 11 fetal human brain samples at 7, 9, 12, 15 and 21 gestational weeks

  Dataset EGAD00001003915

• Sequencing data for CLL patients

  Single-cell RNA-sequencing and other genome-wide approaches were applied to a cohort of CLL patients receiving Venetoclax treatment to study mechanisms of resistance.

  Study EGAS00001005815

• Single cell RNA sequencing of CD34+ CB and BM samples in SLE and healthy controls

  Single cell RNA paired-end sequencing was performed on CD34+ progenitor cells derived from 4 SLE patients, 6 healthy control samples and 2 umbilical cord blood samples using Illumina MiSeq/NextSeq 500.

  Dataset EGAD00001011277

• Whole Transcriptome Sequencing of Human Tumor Cells and Hematopoietic Stem and Progenitor Cells During Aging and Bone Marrow Disorders

  Whole transcriptome sequencing analyses were performed on human hematopoietic stem and progenitor cells during aging and bone marrow disorders. For this purpose, normal and diseased bone marrow or peripheral blood-derived mononuclear cells were FACS-purified into hematopoietic stem (CD34+CD38-Lin-) or hematopoietic progenitor (CD34+CD38+Lin-) populations. Primary human samples from healthy individuals were used along with comparative analyses in some pre-malignant and malignant conditions, including myelodysplastic syndrome (MDS), acute myeloid leukemia (AML) and plasma cell dyscrasias (e.g., multiple myeloma). Studies were also performed on total mononuclear cell fractions from patients with newly-diagnosed or relapsed multiple myeloma, or plasma cell leukemia. Briefly, RNA was extracted from all samples and quality was assessed using a Bioanalyzer instrument. Only samples with RNA integrity (RIN) values >7 were subjected to library preparation for RNA-sequencing. The SMARTer v4 cDNA amplification kit was used along with library construction by the NEB Ultra DNA kit for Illumina. Paired-end sequencing was performed on Illumina NextSeq instruments (Scripps Next Generation Sequencing Core), with all samples run over two separate flow-cells (to generate additional sequencing reads); >95M reads were generated in total for each sample. The RNA-sequencing data are available as FASTQ files.

  Study phs002291

• Genome Sequencing of Circulating Tumor Cells for Minimally Invasive Molecular Characterization of Multiple Myeloma Pathology

  ​​Multiple Myeloma (MM) develops from well-defined precursor stages known as Monoclonal Gammopathy of Undetermined Significance (MGUS) and Smoldering MM (SMM); however, invasive bone marrow (BM) biopsy limits screening and monitoring strategies for patients. In this study, we enumerated circulating tumor cells (CTCs) from patients with precursor and overt diseases, and developed a novel approach, MinimuMM-seq, which enables detection of translocations and copy number abnormalities through whole-genome sequencing of highly pure CTCs. In a cohort of 51 patients, 24 with paired BM, we applied our method MinimuMM-seq and detected 100% of clinically reported BM biopsy events. The next-generation sequencing (NGS) assay could replace molecular cytogenetics by Fluorescence In Situ Hybridization (FISH) for diagnostic yield and risk classification. In 8 patients we could apply MinimuMM-seq on serially collected samples to track and monitor major clones in peripheral blood. We describe clonal evolution and shifting dynamics of subclones over time, as well as in between blood and marrow compartments. All whole-genome sequencing (WGS) data generated in this study will be made accessible through dbGaP.

  Study phs003084

• ChIP_2PEAKS

  Second batch of ChIP-seq narrowPeaks. Software: MACS2 v2.1.2

  Dataset EGAD00010002051

• scRNA-seq analysis Identifies Hepatic IL-13-Producing ILC3-Like Cells Potentially Linked to Liver Fibrosis

  Study EGAS00001007207

• Human oligodendroglial progenitor cells (hGPCs/OPCs) derived from induced pluripotent stem cell (iPS) scCRISPRi/a-seq

  Dac EGAC50000000804

• RNA sequencing, ATACseq, and TCR-seq of Tfh cells and CXCR5- CD4+ T cells in HIV infected lymph nodes

  The high dimensional analyses of CD4+ T cells in human lymph nodes are case-based analyses of the TCR repertoire, transcriptome, and epigenetic signatures of various CD4+ T cells in human lymph nodes. The study aims to determine clonal overlap between phenotypically distinct CD4+ T cells and the similarities between these populations on transcriptional and epigenetic levels. This study performs TCR repertoire sequencing using Molecular Identifier Clustering-based Immune Repertoire Sequencing (MIDCIRS). We found clonal overlap between a population of CXCR5- T cells and follicular helper T (Tfh) cells. We also show epigenetic and transcriptional similarities between CXCR5-PD-1+ T cells and Tfh cells. This study shares an overlapping set of donors with phs001548.

  Study phs001849

• Identification of cardiovascular biomarkers through an integrative omics approach

  Recent GWAS studies have made extensive use of large eQTL data sets to functionally annotate index SNPs. With a large number of association signals located outside coding regions there has been an intense search among sequence variants affecting gene expression at the transcriptional level. However, little progress has been made in mapping regulatory variants that affect protein levels at the translational or post-translational level. It is now possible to undertake a protein QTL scan for focused sets of e.g. oxidized proteins by mass spectrometry. We have established a collaboration with a longitudinal, family-based study in France, the Stanislas cohort, which comprises circa 1000 nuclear families (4,295 individuals) and has follow up data for 10 years (three visits). We have undertaken a pilot study in a focus set of 257 subjects from 79 families with the aim to integrate GWAS, transcriptomic and DNA methylation data with proteomic data on a set of 100 proteins measured in PBMCs. We have already generated GWAS data using Illumina's core-exome chip as well as DNA methylation profiles with the 450K array. We propose to use RNA seq to generate transcriptomic data of the corresponding PBMCs. 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/

  Dataset EGAD00001002197

• RNA-seq study of longitudinal blood cell samples from children at risk of type 1 diabetes

  The appearance of type 1 diabetes (T1D)-associated autoantibodies is the first and only measurable parameter to predict progression toward T1D in genetically susceptible individuals. However, autoantibodies indicate an active autoimmune reaction, wherein the immune tolerance is already broken. Therefore, there is a clear and urgent need for new biomarkers that predict the onset of the autoimmune reaction preceding auto-antibody positivity or reflect progressive b-cell destruction. Here we report the mRNA sequencing–based analysis of 306 samples including fractionated samples of CD4+ and CD8+ T cells as well as CD4, CD8 cell fractions and unfractionated PBMC samples longitudinally collected from seven children who developed beta-cell autoimmunity (Case subjects) at a young age and matched control subjects.

  Study EGAS00001004071

• RNA-seq data

  RNAseq FASTq files of 181 bulk pre-treatment and 14 post-treatment tumors from GO30140 Ph1b group A and F and 177 bulk pre-treatment tumors of IMbrave150 PhIII

  Dataset EGAD00001008128

• TRACERx NSCLC, multiregion sequencing of the first 100 tumors

  BACKGROUND 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). METHODS Multiregion high-depth whole-exome sequencing (M-seq) was performed on 100 early stage NSCLC tumors resected prior to systemic therapy. A total of 327 tumor regions were sequenced and analyzed to define evolutionary histories, obtain a census of clonal and subclonal events, and assess the relationship between ITH and recurrence-free survival (RFS). RESULTS Widespread ITH was observed for both somatic copy number alterations (median 48% [0.03-88%]) and mutations (median 30% [0.5-93%]). Driver mutations in EGFR, MET, BRAF and TP53 were almost always clonal. However, heterogeneous driver alterations occurring later in evolution were found in over 75% of tumors and were common in PIK3CA, NF1 and genes involved in chromatin modification and DNA response and repair. Genome doubling and ongoing dynamic chromosomal instability (CIN), illustrated by mirrored subclonal allelic imbalance, were identified as causes of ITH resulting in parallel evolution of driver copy number events, including amplifications of CDK4, FOXA1, and BCL11A. Elevated copy number heterogeneity was associated with shorter RFS (HR=4.9, P=0.00044), which remained significant in a multivariate analysis. CONCLUSIONS ITH mediated through CIN, rather than point mutational heterogeneity, was associated with increased risk of relapse, supporting its value as a prognostic predictor, and the need to target this high-risk phenotype.

  Dataset EGAD00001003206

• ChIP-seq of plasma cell-free nucleosomes identifies gene expression programs of the cells-of-origin

  Cell-free DNA in human plasma provides access to molecular information about the pathological processes in the organs or tumors from which it originates. These DNA fragments are derived from fragmented chromatin in dying cells, and retain some of the cell of origin histone modifications. Here, we apply chromatin immunoprecipitation of cell-free nucleosomes carrying active chromatin modifications followed by sequencing (cfChIP-seq) to 268 human samples. In healthy donors, we identified bone marrow megakaryocytes, but not erythroblasts, as major contributors to the cfDNA pool. In patients with a range of liver diseases, we show that we can identify pathology-related changes in hepatocyte transcriptional programs. In metastatic colorectal carcinoma patients, we detected clinically relevant, and patient-specific information, including transcriptionally active HER2 amplifications. Altogether, cfChIP-seq using low sequencing depth, provides systemic and genome-wide information, can inform diagnosis, and facilitate interrogation of physiological and pathological processes using blood samples.

  Study EGAS00001004913

• Whole-genome and transcriptome versus panel sequencing in precision oncology: A translational-clinical comparison

  Precision oncology offers new cancer treatment options. While the use of whole-genome (WGS) and transcriptome (TS) sequencing remains often confined to specific clinical programs, molecular analysis with gene panels is more common clinical practice. Methods: Twenty patients with rare or advanced tumors sequenced by WGS/TS within the DKFZ/NCT/DKTK-MASTER program from 2015 to 2020 (MASTER 1) were additionally sequenced with the TSO500 DNA and TST170 RNA Assay by Illumina. Original Molecular Tumor Board (MTB) therapy recommendations (TR) were juxtaposed with TR from NGS panel data analysis (comparison 1). To mitigate temporal differences between the two sequencings, WGS/TS was bioinformatically reanalyzed (MASTER 2), and new TR were again compared (comparison 2). Results: In comparison 1, 47.1% of the MASTER 1’s TR and 62.8% of the panel’s TR were identical, as were 45.9% of the TR of MASTER 2 and 54.9% of the panel in comparison 2. In both MASTER 1 and MASTER 2, 26.5% and 36.1% of TR, respectively, relied on Biomarkers (BM) which were not covered by the panel. Eight of the ten MTB-derived therapy implementations were also supported in the panel, the two remaining ones being based on BM absent from the panel. Conclusions: About half of the TR in WGS/TS and panel sequencing were identical. Around a third of TR issued by WGS/TS were based on BM which are not covered by the panel, leading to therapy implementations. The presented data underscores the clinical value of comprehensive molecular analyses in individuals with advanced cancers.

  Study EGAS50000000431