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• BLUEPRINT release August 2016, RNA-Seq for monocyte, on genome GRCh38

  RNA-Seq data for 2 monocyte sample(s). 2 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002375

• BLUEPRINT release August 2015, ChIP-Seq for Acute promyelocytic leukemia, on genome GRCh38

  ChIP-Seq data for 6 Acute promyelocytic leukemia sample(s). 29 run(s), 27 experiment(s), 27 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 EGAD00001001490

• BLUEPRINT release August 2015, RNA-Seq for band form neutrophil, on genome GRCh38

  RNA-Seq data for 3 band form neutrophil sample(s). 3 run(s), 3 experiment(s), 3 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_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001504

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

  ChIP-Seq data for 2 erythroblast sample(s). 12 run(s), 12 experiment(s), 12 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 EGAD00001001574

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

  RNA-Seq data for 1 mature eosinophil 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_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001525

• BLUEPRINT release August 2016, RNA-Seq for Acute Promyelocytic Leukemia - MC2392, on genome GRCh38

  RNA-Seq data for 1 Acute Promyelocytic Leukemia - MC2392 sample(s). 1 run(s), 1 experiment(s), 1 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002359

• BLUEPRINT release August 2015, RNA-Seq for Acute promyelocytic leukemia, on genome GRCh38

  RNA-Seq data for 7 Acute promyelocytic leukemia sample(s). 7 run(s), 7 experiment(s), 7 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_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001555

• BLUEPRINT release August 2015, Bisulfite-Seq for central memory CD8-positive, alpha-beta T cell, on genome GRCh38

  Bisulfite-Seq data for 1 central memory CD8-positive, alpha-beta T cell sample(s). 13 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 EGAD00001001553

• BLUEPRINT release January 2015, ChIP-Seq for mature eosinophil

  ChIP-Seq data for 2 mature eosinophil sample(s). 12 run(s), 12 experiment(s), 12 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 EGAD00001001168

• BLUEPRINT release August 2015, Bisulfite-Seq for effector memory CD4-positive, alpha-beta T cell, on genome GRCh38

  Bisulfite-Seq data for 1 effector memory CD4-positive, alpha-beta 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 EGAD00001001567

• BLUEPRINT release January 2015, RNA-Seq for macrophage

  RNA-Seq data for 18 macrophage sample(s). 19 run(s), 18 experiment(s), 18 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_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001199

• BLUEPRINT release August 2015, RNA-Seq for neutrophilic myelocyte, on genome GRCh38

  RNA-Seq data for 3 neutrophilic myelocyte sample(s). 3 run(s), 3 experiment(s), 3 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_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001477

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

  ChIP-Seq data for 4 Acute Myeloid Leukemia - CTR sample(s). 21 run(s), 21 experiment(s), 21 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 EGAD00001001533

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

  ChIP-Seq data for 2 mature eosinophil sample(s). 12 run(s), 12 experiment(s), 12 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 EGAD00001001539

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

  ChIP-Seq data for 2 monocyte sample(s). 6 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001580

• BLUEPRINT release August 2015, Bisulfite-Seq for central memory CD4-positive, alpha-beta T cell, on genome GRCh38

  Bisulfite-Seq data for 1 central memory CD4-positive, alpha-beta 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 EGAD00001001563

• BLUEPRINT release January 2015, ChIP-Seq for inflammatory macrophage

  ChIP-Seq data for 6 inflammatory macrophage sample(s). 35 run(s), 35 experiment(s), 35 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 EGAD00001001204

• BLUEPRINT release January 2015, RNA-Seq for conventional dendritic cell

  RNA-Seq data for 1 conventional dendritic cell sample(s). 1 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_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001170

• BLUEPRINT release January 2015, RNA-Seq for inflammatory macrophage

  RNA-Seq data for 3 inflammatory macrophage sample(s). 3 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_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001132

• BLUEPRINT release August 2015, Bisulfite-Seq for effector memory CD8-positive, alpha-beta T cell, on genome GRCh38

  Bisulfite-Seq data for 1 effector memory CD8-positive, alpha-beta T cell sample(s). 11 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 EGAD00001001583

• Sequencing data on patients with Sezary Syndrome

  This dataset consists of sequencing data on 15 patients with Sezary syndrome. On 12 of these patients, we have exome sequencing data while on 10 patients, we have RNA sequencing data. In total for seven patients, we have both exome as well as RNA sequencing data. We looked for gene mutations and fusion events in these patients to identify genes that could be involved in the pathogenesis of the disease.

  Dataset EGAD00001001998

• BLUEPRINT release August 2016, Bisulfite-Seq for immature conventional dendritic cell - GM-CSF_IL4_T=6_days, on genome GRCh38

  Bisulfite-Seq data for 3 immature conventional dendritic cell - GM-CSF_IL4_T=6_days sample(s). 61 run(s), 4 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 EGAD00001002284

• Merged analysis-ready bam files: HiSeq sequencing of matched tumour/normal DNA samples from Pancreatic Ductal Adenocarcinoma cases

  Additional sequencing data for 173 donors in EGAS00001000154, a study of Pancreatic Ductal Adenocarcinoma. WGS libraries were used for high-cellularity cases, WXS sequencing to high depth on low-cellularity cases. HiSeq 2xxx platform was used in all cases. The analysis files associated with this dataset are merged, de-duplicated bams aligned against GRCh37, one tumour and one normal bam per donor.

  Dataset EGAD00001002192

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

  RNA-Seq data for 3 inflammatory macrophage sample(s). 3 run(s), 3 experiment(s), 3 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_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001480

• BLUEPRINT release August 2015, ChIP-Seq for Acute lymphocytic leukemia - CTR, on genome GRCh38

  ChIP-Seq data for 1 Acute lymphocytic leukemia - CTR sample(s). 7 run(s), 7 experiment(s), 7 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 EGAD00001001569

• BLUEPRINT release January 2015, RNA-Seq for alternatively activated macrophage

  RNA-Seq data for 4 alternatively activated macrophage sample(s). 6 run(s), 4 experiment(s), 4 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_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001202

• BLUEPRINT release August 2015, Bisulfite-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh38

  Bisulfite-Seq data for 7 CD14-positive, CD16-negative classical monocyte sample(s). 101 run(s), 7 experiment(s), 7 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 EGAD00001001591

• BLUEPRINT release August 2014, ChIP-Seq for mature neutrophil

  ChIP-Seq data for 7 mature neutrophil sample(s). 68 run(s), 50 experiment(s), 50 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_chipseq_analysis_ebi_20140811

  Dataset EGAD00001000930

• BLUEPRINT release August 2016, RNA-Seq for T-cell Acute Lymphocytic Leukemia, on genome GRCh38

  RNA-Seq data for 1 T-cell Acute Lymphocytic Leukemia sample(s). 1 run(s), 1 experiment(s), 1 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002287

• BLUEPRINT release August 2016, RNA-Seq for Acute Promyelocytic Leukemia - ATRA, on genome GRCh38

  RNA-Seq data for 3 Acute Promyelocytic Leukemia - ATRA sample(s). 3 run(s), 3 experiment(s), 3 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002356

• BLUEPRINT release August 2015, Bisulfite-Seq for CD4-positive, alpha-beta T cell, on genome GRCh38

  Bisulfite-Seq data for 3 CD4-positive, alpha-beta T cell sample(s). 61 run(s), 3 experiment(s), 3 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 EGAD00001001516

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

  ChIP-Seq data for 4 neutrophilic myelocyte sample(s). 14 run(s), 14 experiment(s), 14 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 EGAD00001001517

• BLUEPRINT release August 2015, Bisulfite-Seq for CD8-positive, alpha-beta T cell, on genome GRCh38

  Bisulfite-Seq data for 4 CD8-positive, alpha-beta T cell sample(s). 56 run(s), 4 experiment(s), 4 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 EGAD00001001571

• BLUEPRINT release August 2015, Bisulfite-Seq for CD38-negative naive B cell, on genome GRCh38

  Bisulfite-Seq data for 4 CD38-negative naive B cell sample(s). 44 run(s), 4 experiment(s), 4 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 EGAD00001001590

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - dcc_release_24_dataset

  WGS sequencing for cases from the ICGC ESAD-UK project Tumours 50x Normals 30x HiSeq X BAM files These samples are all available in ICGC release 24

  Dataset EGAD00001003292

• Gene Characterization in Carbohydrate metabolic alterations (neonatel diabetes & congenital hyperinsulinemic) in early childhood (2018-03-14)

  Whole Exome Sequencing of trios (proband + parents) or probands only with Neonatal Diabetes Mellitus (NDM) or Congenital Hyperinsulinism of Infancy (CHI) of unknown genetic origin. 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/ . This dataset contains all the data available for this study on 2018-03-14.

  Dataset EGAD00001004040

• Gtag&T single-cell genome and transcriptome data

  This submission contains single-cell genome and transcriptome data that is used for the following manuscript: https://doi.org/10.1101/2023.01.13.521174. All Illumina data deposited here is retrieved from HCC38(BL) cell lines and a melanoma PDX model as described in the paper.

  Study EGAS00001007043

• Systematic analysis of paralogous regions in 41,755 exomes uncovers clinically relevant variation

  As part of the study "Systematic analysis of paralogous regions in 41,755 exomes uncovers clinically relevant variation" we wanted to identiffy the SNVs that are located in STRC and which ones in STRCP1. For this we applied targeted long-read sequencing.

  Study EGAS00001007513

• ERBB2/HER2 transmembrane and juxtamembrane domain mutations in cancer

  In this study, we identified several recurrent activating HER2 somatic mutations in transmembrane and juxtamembrane domain in multiple cancers and demonstrate that patients carryingthese mutations are candidates for anti-HER2 therapy. We have also identified a germline mutation in HER2 transmembrane domain.

  Study EGAS00001003213

• Pre_clinical_evolution_of_haematological_malignancies

  Deep targeted sequencing of 291 peripheral blood samples taken 1-20 years prior diagnosis of a haematological malignancy alongside age- and sex-matched controls. Key objective is to distinguish indolent age-related clonal haematopoiesis from pre-cancer and to derive predictive models for early risk-stratification.

  Study EGAS00001002964

• Isotype_resolved_sequencing_of_B_cell_receptor__in_health_and_disease

  Sequencing of B-cell receptor repertoires in healthy individuals and patients with chronic lymphocytic leukemia. 1) 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 please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002634

• PROJET DREPANOCYTOSE ET PALUDISME

  The goal is to study and specify the response to treatment against Plasmodium falciparum malaria in subjects with sickle cell disease in order to propose to the National Malaria Control Program of Côte d'Ivoire effective prevention and treatment strategies for this population at risk.

  Study EGAS00001006008

• Single cell RNA sequencing of colorectal cancer patients (KUL3/KUL5)

  Libraries for scRNA-seq were generated using the Chromium Single Cell 3′ or 5′ library and Gel Bead & Multiplex Kit from 10x Genomics. Aimed to profile 5000 cells per library (if sufficient cells were retained during dissociation).

  Study EGAS00001006049

• Advanced molecular neuropathology to increase diagnostic accuracy in pediatric neurooncology

  To assess their utility in routine neuropathology, we prospectively integrated DNA methylation-based CNS tumor classification and targeted gene panel sequencing of tumor and constitutional DNA with blinded neuropathological reference diagnostics for a population-based cohort of > 1,200 newly-diagnosed pediatric patients.

  Study EGAS00001006680

• Transcriptomic analysis of TFEB knockdown in LT-HSC.

  Long-term hematopoietic stem cells (LT-HSC) were sorted from human cord blood and cultured overnight before transduction with lentiviral vectors overexpressing an shRNA against Renilla (shCTRL) or TFEB (shTFEB). Six days later, mCherry+ transduced cells were sorted for RNA extraction and sequencing.

  Study EGAS00001004967

• WGS patient 130

  Whole genome sequencing on DNA from snap frozen tumour sample and matched whole blood of patient #130. Analysis used the QIAamp DNA Mini Kit. Libraries were prepared using the Illumina TruSeq Nano library method using 200ng of DNA. Extracted DNA was sheared using the Covaris M220 Focused-ultrasonicator with a target fragment length of 550bp through bead size selection. The libraries were sequenced at depth of 40x for germline DNA and 80-100x for tumour DNA using paired 150bp reads.

  Dataset EGAD00001011271

• Single cell transcriptomics of hESC-derived midbrain dopaminergic neurons generated by a new human development-based protocol

  Single cell RNA-seq from D0,D11,D16,D21,D28 of dopamingeric differentiation from hESCs cell lines H9 and HS980 using current protocols. Different time points along the differentiation for each cell line were multiplexed using BD™ Single-Cell Multiplexing Kit for use with the 10x Chromium™ Single Cell 3’ Reagent Kit v2.

  Dataset EGAD00001008834

• Sequencing data for oesophageal and related samples - Ganguli et al (WGS)

  Data supporting: "TBC" Ganguli et al (WGS for 1298 samples)

  Dataset EGAD00001011191

• RNA-Seq FASTQs for Tang F. et al. Chromatin accessibility profiles of castration-resistant prostate cancers reveal novel subtypes and therapeutic vulnerabilities

  This dataset contains the FASTQ files for a portion of the samples in Tang F. et al. “Chromatin accessibility profiles of castration-resistant prostate cancers reveal novel subtypes and therapeutic vulnerabilities” published in Science. It contains 51 samples sequenced with Illumina HiSeq 2500 or HiSeq 4000. The remaining samples can be found at dbGaP: phs000909.v1.p1

  Dataset EGAD00001008598

• Chronic lymphocytic leukemia IGHV somatic hypermutation detection by targeted capture next-generation sequencing

  FASTQ and BAM files for 46 samples (consisting of 35 samples for patients diagnosed with CLL, 5 samples consisting of a dilution series of patient DNA, and 6 samples of cell lines and dilutions involving the cell lines) from targeted capture next-generation sequencing from the LySeq panel. Libraries were sequenced on either Illumina HiSeq 2500 (LySeq66 PoP, R1-3) or Illumina NovaSeq 6000 (LySeq66 Validation Round).

  Dataset EGAD00001009828

• RRBS data for solid tumors and adjacent normal tissues

  RRBS data for solid tumors and adjacent normal tissues

  Dataset EGAD00001009001

• shallow WGS of cell free DNA

  12.5 ng of cfDNA was used as input for shallow whole-genome sequencing (sWGS), aiming for a coverage of x0.2-0.4-fold. Library preparation was performed using the TruSeq Nano DNA High Throughput Library Prep Kit (Illumina, San Diego, CA, USA) on an automated Hamilton STAR liquid handling system (Hamilton, Germany GmbH, Robotics, Gräfeling, Germany) with dual indexing, and sequencing was performed on the NextSeq500/550 platform (Illumina). The fraction of tumor-derived DNA in cell-free DNA was estimated using the R package ichorCNA.

  Dataset EGAD00001009796

• Processed bam files for the whole exome sequencing of primary lung adenocarcinoma samples

  We performed single cell RNA sequencing (scRNA-seq) for 208,506 cells derived from 58 lung adenocarcinomas from 44 patients, which covers primary tumour, lymph node and brain metastases, and pleural effusion in addition to normal lung tissues and lymph nodes. The extensive single cell profiles depicted a complex cellular atlas and dynamics during lung adenocarcinoma progression which includes cancer, stromal, and immune cells in the surrounding tumor microenvironments.

  Dataset EGAD00001010320

• Enhanced Detection of Landmark Minimal Residual Disease in Lung Cancer using Cell-Free DNA Fragmentomics

  The circulating tumor DNA (ctDNA) mutation-based approach shows limited performance in minimal residual disease (MRD) detection, especially for landmark MRD detection at an early-stage cancer after surgery. Here, A total of 87 NSCLC patients, who received curative surgical resections (23 patients relapsed during follow-up), enrolled in this study. A total of 163 plasma samples, collected at 7 days and 6 months postsurgical, were used for high-throughput sequencing.

  Dataset EGAD00001010300

• Mtb infected and uninfected neutrophils after 1 and 6 hrs

  Fastq.gz files for mRNA sequenced from Mtb infected and uninfected neutrophils after 1 and 6 hrs. Samples were sequenced in 2 batched as indicated per experiment. Batch 1 was SE unstranded, 100bp on an Illumina HiSeq4000 sequencer and batch 2 unstranded, 150bp paired-end on an Illumina NovaSeq6000 sequencer. Phenotypic data for the samples is also included.

  Dataset EGAD00001010893

• BLUEPRINT release August 2014, ChIP-Seq for inflammatory macrophage

  ChIP-Seq data for 3 inflammatory macrophage sample(s). 21 run(s), 21 experiment(s), 21 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_chipseq_analysis_ebi_20140811

  Dataset EGAD00001000940

• BLUEPRINT release January 2015, RNA-Seq for class switched memory B cell

  RNA-Seq data for 1 class switched memory B cell sample(s). 1 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_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001164

• BLUEPRINT release January 2015, ChIP-Seq for macrophage

  ChIP-Seq data for 13 macrophage sample(s). 55 run(s), 55 experiment(s), 55 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 EGAD00001001196

• BLUEPRINT release August 2015, Bisulfite-Seq for cytotoxic CD56-dim natural killer cell, on genome GRCh38

  Bisulfite-Seq data for 2 cytotoxic CD56-dim natural killer cell sample(s). 24 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 EGAD00001001473

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

  ChIP-Seq data for 4 neutrophilic metamyelocyte sample(s). 18 run(s), 12 experiment(s), 12 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 EGAD00001001495

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

  ChIP-Seq data for 2 Multiple myeloma sample(s). 16 run(s), 14 experiment(s), 14 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 EGAD00001001592

• BLUEPRINT release August 2016, RNA-Seq for mature eosinophil, on genome GRCh38

  RNA-Seq data for 2 mature eosinophil sample(s). 3 run(s), 3 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002326

• BLUEPRINT release August 2016, ChIP-Seq for Acute Promyelocytic Leukemia - MC2884 (4h), on genome GRCh38

  ChIP-Seq data for 1 Acute Promyelocytic Leukemia - MC2884 (4h) sample(s). 6 run(s), 6 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002372

• BLUEPRINT release August 2016, ChIP-Seq for Chronic Lymphocytic Leukemia, on genome GRCh38

  ChIP-Seq data for 106 Chronic Lymphocytic Leukemia sample(s). 174 run(s), 163 experiment(s), 162 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 EGAD00001002384

• BLUEPRINT release August 2016, ChIP-Seq for Mantle Cell Lymphoma, on genome GRCh38

  ChIP-Seq data for 5 Mantle Cell Lymphoma sample(s). 35 run(s), 35 experiment(s), 35 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 EGAD00001002397

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

  ChIP-Seq data for 3 monocyte - RPMI_BG_T=24hrs sample(s). 8 run(s), 8 experiment(s), 8 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 EGAD00001002408

• BLUEPRINT release August 2016, ChIP-Seq for Acute Promyelocytic Leukemia - MC3324, on genome GRCh38

  ChIP-Seq data for 1 Acute Promyelocytic Leukemia - MC3324 sample(s). 2 run(s), 1 experiment(s), 1 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 EGAD00001002431

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

  ChIP-Seq data for 4 neutrophilic metamyelocyte sample(s). 32 run(s), 23 experiment(s), 23 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 EGAD00001002435

• BLUEPRINT release August 2016, RNA-Seq for Acute Myeloid Leukemia - CTR, on genome GRCh38

  RNA-Seq data for 7 Acute Myeloid Leukemia - CTR sample(s). 7 run(s), 7 experiment(s), 7 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002443

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

  ChIP-Seq data for 2 mature eosinophil sample(s). 14 run(s), 14 experiment(s), 14 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 EGAD00001002477

• BLUEPRINT release August 2016, RNA-Seq for osteoclast, on genome GRCh38

  RNA-Seq data for 2 osteoclast sample(s). 2 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002479

• BLUEPRINT release August 2016, Bisulfite-Seq for CD38-negative naive B cell, on genome GRCh38

  Bisulfite-Seq data for 4 CD38-negative naive B cell sample(s). 51 run(s), 5 experiment(s), 8 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 EGAD00001002520

• Single-cell expression of Hodgkin lymphoma

  Single-cell gene expression was profiled for 22 Hodgkin lymphoma tumors and 5 reactive lymph nodes (2 replicates were performed for RLN-1). Library preparation was performed with the 10x Chromium platform (3' version 2 assay). Sequencing was performed on an Illumina NextSeq. The BAM files were generated from the raw sequencing data using Cell Ranger (v2.1.0) mkfastq and count commands.

  Dataset EGAD00001005739

• Investigating the impact of MBD4 on the mutability of the germline (2020-01-15)

  We will be testing the hypothesis that MBD4 PTV germline carriers also show an increased number of C toT germline mutations in their offspring. 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/ . This dataset contains all the data available for this study on 2020-01-15.

  Dataset EGAD00001005788

• Clinical data

  Clinical data from IMvigor210, POPLAR, IMmotion150: Clinical data include demographics, tumor type, PD-L1 IHC, tumor mutation burden, objective response rate, overall survival and progression free survival for 611 patients across IMvigor210, POPLAR and IMmotion150. Clinical data from PCD4989g: Clinical data include tumor type, PD-L1 expression and objective response rate for 206 patients from PCD4989g.

  Dataset EGAD00001006630

• A108846B

  Whole genome sequencing for single cells for library A108846B 1636 cells; filetype=bam

  Dataset EGAD00001007092

• A proof-of-concept study of sequential treatment with the HDAC inhibitor vorinostat following BRAF and MEK inhibitors in BRAFV600 mutated melanoma

  "Purpose: Development of resistance limits the clinical benefit of BRAF and MEK inhibitors (BRAFi/MEKi) in BRAFV600 mutated melanoma. It has been shown that short-term treatment (14 days) with vorinostat was able to initiate apoptosis of the resistant tumor cells. We aimed to assess the anti-tumor activity of sequential treatment with vorinostat following BRAFi/MEKi in patients with BRAFV600 melanoma who progressed after initial response to BRAFi/MEKi. Patients and Methods: Patients with BRAFi/MEKi resistant BRAFV600 melanoma were treated with vorinostat 360 mg QD for 14 days followed by BRAFi/MEKi. The primary endpoint was an objective response rate of progressive lesions of at least 30% according to RECIST 1.1. Secondary endpoints included progression-free survival (PFS), overall survival (OS), safety, pharmacokinetics of vorinostat and translational molecular analyses using ctDNA and tumor biopsies. Results: Twenty-six patients with progressive BRAFi/MEKi resistant BRAFV600 mutated melanoma received treatment with vorinostat. Twenty-two patients were evaluable for response. The ORR was 9% (one complete response for 31.2 months and one partial response for 14.9 months. Median PFS and OS were 1.4 and 5.4 months, respectively. Common adverse events were fatigue (23%) and nausea (19%). ctDNA analysis showed emerging secondary mutations in NRAS and MEK in eight patients at time of BRAFi/MEKi resistance. Elimination of these mutations by vorinostat treatment was observed in three patients. Conclusions: Intermittent treatment with vorinostat in patients with resistant BRAFV600 mutated melanoma is well tolerated. Although the primary endpoint of this study was not met, durable anti-tumor responses were observed in a minority of patients (9%). "

  Study EGAS00001007709

• Germ Cell Tumor Molecular Heterogeneity Revealed through Analysis of Primary and Metastasis Pairs

  Purpose: While primary germ cell tumors (GCTs) have been extensively characterized, molecular analysis of metastatic sites has been limited. We performed whole-exome sequencing and targeted next-generation sequencing on paired primary and metastatic GCT samples in a patient cohort enriched for cisplatin-resistant disease. Experimental Design: Tissue sequencing was performed on 100 tumor specimens from 50 patients with metastatic GCT, and sequencing of plasma cell-free DNA (cfDNA) was performed for a subset of patients. Data is being provided for a subset of 10 patients whose samples were analyzed using whole-exome sequencing. Results: The mutational landscape of primary and metastatic pairs from GCT patients was highly discordant (68% of all somatic mutations were discordant). Whereas genome duplication was common and highly concordant between primary and metastatic samples, only 25% of primary-metastasis pairs had =50% concordance at the level of DNA copy number alterations (CNAs). Evolutionary-based analyses revealed that most mutations arose after CNAs at the respective loci in both primary and metastatic samples, with oncogenic mutations enriched in the set of early occurring mutations versus variants of unknown significance (VUS). TP53 pathway alterations were identified in nine cisplatin-resistant cases and had the highest degree of concordance in primary and metastatic specimens, consistent with their association with this treatment-resistant phenotype. Conclusions: Analysis of paired primary and metastatic GCT specimens revealed significant molecular heterogeneity for both CNAs and somatic mutations. Among loci demonstrating serial genetic evolution, most somatic mutations arose after CNAs but oncogenic mutations were enriched in the set of early occurring mutations as compared to VUS. Alterations in TP53 were clonal when present and shared among primary-metastasis pairs. Reprinted from pending publication, with permission from JCO Precision Oncology.

  Study phs002229

• Genetic Progression of Head and Neck Squamous Cell Carcinoma

  These data are tumor/normal-matched exome sequencing results on 45 participants (median age of 58.6 years) treated for squamous cell carcinoma of the oropharynx at Mass Eye and Ear (MEE; Boston, MA, USA). Some tumors had two portions sequenced separately. All research complied with all relevant ethical regulations. Human subject research on patients at MEE was approved by the MEE Human Studies Committee under protocol HSC 11-024H, with informed consent obtained from participants. Participants were not compensated. Clinical data, including HPV status, were abstracted from patient records. Sequencing and clinical data were combined with TCGA data on 486 cases of head and neck squamous cell carcinoma (HNSCC). The PhylogicNDT suite of genomic analysis tools was used to infer the relative timing of genetic events during tumor progression for major molecularly defined classes of HNSCC: HNSCC negative for human papillomavirus (HPV), HPV-associated HNSCC, and HPV-negative HNSCC involving mutations in CASP8, NSD1, and NOTCH1. The timing of the development of whole-genome somatic events leading to tetraploidy or triploidy and to increased measures of intratumor genetic heterogeneity was determined. Associations of heterogeneity measures with clinical outcomes were assessed. The analysis identified genes with early mutations that likely play roles in HPV-tumor initiation (FBXW7, NOTCH1, CASP8, FAT1, NSD1, HRAS, EP300, CREBBP, KMT2D). Genes with mutations at later median relative timing (PK3CA, NFE2L2, HLA-A, SPEN, and KMT2C) were more likely to be important for progressing to later stages of the disease. Gain of chromosome arm 3q and loss of arm 11q were found to occur more frequent in HPV+ HNSCC cases. A high prevalence of 3p and 17p loss were also observed in HPV+ HNSCC cases.

  Study phs003139

• Genomic Studies of Bipolar Disorder in a Large Cohort from The Netherlands

  The transcriptomes of whole blood samples of a large cohort of individuals from the Netherlands were assayed using RNA-seq. These whole blood samples included patients diagnosed with schizophrenia or bipolar disorder, family members of patients, and healthy controls. Within the whole blood dataset, about 600 of the samples were sequenced to an average of 13.9 million mapped reads per sample, while about 2,000 were sequenced to an average of 5.9 million mapped reads per sample, in order to assess changes in power to detect eQTLs based on sample size. We find that expression, defined as the log transcripts per million reads (TPMs), is highly correlated when comparing the moderate (13.9M) and lower (5.9M) coverage datasets. Additionally, a subset of about 150 individuals provided fibroblast cell lines which were assessed for the levels of gene expression using RNA-seq at an average of 50 million mapped reads per sample. We use downsampling techniques to generate synthetic datasets derived from this real fibroblast RNA-Seq data to explore the relationship between coverage and number individuals in an eQTL analysis. Corresponding individual-level genotypes for the samples included in the expression matrix are also made available. The genotypes were derived from multiple other project cohorts, each using different genotyping platforms including OmniExpress Exome, Global Screening Array, Illumina550, and PsychChip. A Plink file set of these cohorts is provided here after merging the separate project file sets and extracting only the individuals who have expression data also provided here; quality control for SNP-missingness is recommended. We demonstrate in this study that given a fixed budget, eQTL discovery power can be increased by lowering the sequencing depth per sample to allow for an a greater number of individuals sequenced. 

  Study phs002856

• Gene-Environment Interactions (GxE) and Complex Traits

  Functional variants associated with complex traits tend to fall in non-coding regions and affect regulatory mechanisms that are not yet well characterized. Furthermore, it is generally difficult to determine in which tissues and conditions they may have a functional impact. This is because the effect of a genetic variant on a molecular pathway, and ultimately on the individual's phenotype, may be modulated by "environmental" factors. We denominate such variants "gene-expression environment-specific quantitative trait nucleotides" GxE-QTNs. Achieving a better understanding of the mechanisms underlying GxE is a critical step in understanding the link between genotype and complex phenotype. It is also crucial to develop computationally efficient and statistically sound methods capable to integrate tissue/condition-specific functional genomics data to predict and validate when a sequence variant is functional. In this study we developed novel experimental and computational approaches to screen, analyze and functionally characterize genetic variants for complex traits modulated by environmental exposures. To identify and characterize genes with GxE, we analyzed allele specific gene expression in a panel of five relevant tissues (e.g. the vascular endothelium for cardiovascular diseases) under 50 controlled environmental conditions (e.g. glucocorticoids treatment, as a proxy for stress exposure). These data should be useful to develop computational tools that integrate different sources of evidence including data collected by ENCODE, RoadMap Epigenome and GTEx projects to functionally annotate GWAS variants. The experimental and computational tools developed by this project have widespread applicability, for example, can be used to tackle the functional basis of complex traits in other environmental contexts (e.g. other types of stress and hormonal levels) and genetic backgrounds. This resource represents the first comprehensive catalog of genetic variants that interact with environmental exposure in determining human complex traits.

  Study phs001176

• Human Gene Expression Patterns Associated with Experimental P. falciparum Infection

  Description: Experimental exposure to malaria parasites can lead to development of protective immunity, providing a foothold for the development of a malaria vaccine. The goal of this study is to investigate immune transcriptional profiles associated with malaria protective immune responses induced by experimental Chemo-Prophylaxis and Sporozoites (CPS) immunization of P. falciparum-naive human volunteers. Samples for this study were obtained from a CPS-immunization study conducted in 2011 (ClinicalTrials.gov Identifier: NCT01218893), where healthy volunteers received CPS-immunization with bites from different numbers of P. falciparum-infected mosquitoes (three times 15 (n=5), 10 (n=9) or 5 (n=10)). Five control subjects received uninfected mosquito bites under chloroquine prophylaxis. Fifteen weeks after discontinuation of chloroquine prophylaxis, all volunteers were challenged by exposure to infected mosquito bites. Study Design: A maximum of 30 volunteers were divided into four groups. All volunteers received weekly chloroquine prophylaxis for a period of 13 weeks (91 days). During these 13 weeks, on days 8, 36 and 64 they were exposed to the bites of 15 mosquitoes. Group 1 (n=5, positive control) received three CPS immunizations by 15 mosquitoes infected with P. falciparum sporozoites. Group 2 (n=10) received three times 10 bites from infected mosquitoes and 5 bites from uninfected mosquitoes. Group 3 (n=10) received three times 5 bites from infected mosquitoes and 10 bites from uninfected mosquitoes. Group 4 (n=5), the negative control, received three placebo immunizations with 15 bites of uninfected mosquitoes. Fifteen weeks after discontinuation of chloroquine prophylaxis, all 30 volunteers were challenged at day 196 by the bites of 5 infectious mosquitoes and followed for 21 days. All subjects were treated with chloroquine 21 days after challenge or whenever they had a positive thick smear during that period.

  Study phs001346

• Single-cell RNA-Seq of human lymphoma reveals malignant B cell diversity and patterns of T cell immune checkpoint co-expression

  Follicular lymphoma (FL) is a generally incurable B-cell malignancy which has the potential to transform into highly aggressive lymphomas. Genomic studies indicate it is often a small subpopulation rather than the dominant population in the FL that gives rise to the more aggressive subtype. To resolve the underlying transcriptional networks of follicular B-cell lymphomas at single molecule and cell resolution, we leveraged droplet-based barcoding technology for highly parallel single cell RNA-Seq. We analyzed the transcriptomes from tens of thousands of cells derived from five primary FL tumors. Simultaneously, we conducted multi-dimensional flow cell sorting to validate our characterizing of cellular lineages and critical expressed proteins. For each tumor, we identified multiple cellular subpopulations, matching known hematopoietic lineages. Comparison of gene expression by matched malignant and normal B cells from the same patient revealed tumor-specific features. Malignant B cells exhibited restricted immunoglobulin light chain expression (either Ig Kappa or Ig Lambda), as well the expected upregulation of the BCL2 gene, but also down-regulation of the FCER2, CD52 and MHC class II genes. By leveraging the single-cell resolution on large numbers of cells per patient, we were able to examine tumor-resident T cells. We identified pairs of immune checkpoint molecules that were co-expressed, providing a potentially useful strategy for selection of patient-tailored combination immunotherapies. In summary, massively parallel measurement of single-cell expression in thousands of tumor cells and tumor-resident lymphocytes can be used to obtain a systems-level view of the tumor microenvironment and identify new avenues for therapeutic development.

  Study phs001378

• Investigating the Role of Neddylation in the Repair of Topoisomerase I-Mediated DNA Damage in Colorectal Cancer

  Colorectal cancer is one of the most lethal cancers worldwide. First-line chemotherapy for metastatic CRC (mCRC) entails a combination of irinotecan with 5-fluorouracil and leucovorin (FOLFIRI). Irinotecan is a prodrug that is converted within the cell to its active metabolite SN38, a potent TOP1 inhibitor. TOP1 relieves DNA torsional strain arising from DNA metabolism by cleaving one strand of the DNA duplex and forming an enzyme-DNA covalent intermediate that can be trapped by inhibitors. The resulting TOP1 DNA-protein crosslinks (TOP1-DPCs) interfere with replication and transcription and induce cell death if left unrepaired. I have established the role of the ubiquitin-proteasome pathway in TOP1-DPC repair, but it remains unknown how ubiquitylation is activated. One possibility is that collision between advancing replication forks and the DPCs triggers a specific ubiquitin ligase to target DPCs for degradation. The DDB1-CUL4 (Cullin 4)-RBX1 (CRL4) ubiquitin ligase complex performs a salient role in both replication and DNA repair upon its activation by auto-NEDD8 modification (neddylation), but it is unknown whether it plays a role for TOP1-DPC repair. We plan to define the role of neddylation for TOP1-DPC repair during replication and examine irinotecan plus pevonedistat (PEV), a NEDD8-activating enzyme inhibitor in multiple clinical trials, in CRC patient-derived preclinical models including 3D organoids. The three in-house organoids, from which samples have been submitted to dbGaP, were sequenced as a means of verifying their identity as colon cancer organoids, to allow us to investigate the combination of TOP1 inhibitors and PEV and the molecular mechanisms underlying this drug combination in these organoids.

  Study phs003257

• Identifying Novel Small RNA Biomarkers Unique to Patients with Gastric Cancer

  The biomarker development study consisted of two parts: discovery and validation. The first part was the discovery and verification phase of biomarkers using two different platforms: transcriptomic and miRNA. The salivary transcriptomes of 63 GC samples and 31 non-GC controls were profiled using Affymetrix HG U133+2.0 microarrays (Affymetrix, Santa Clara, CA). The identified exRNA candidates were verified by quantitative real-time PCR (RT-qPCR) using all 94 of the original samples. In the discovery phase for the miRNA biomarkers, 10 early-stage GC samples and 10 non-GC controls were selected. The salivary miRNAs of these samples (n=20) were profiled using the TaqMan MicroRNA Array (Applied Biosystems, Foster City, CA). MicroRNA candidates were verified using TaqMan miRNA Assay (Thermo Scientific, Grand Island, NY). The second part of the study was to validate these verified exRNA biomarker candidates with exRNA samples extracted from an independent cohort of 100 GC and 100 non-GC saliva samples. The cohort was not balanced for demographics on gender and smoking history but more accurately reflected the diagnostic setting where our proposed final model could be implemented. Reprinted from "Li F, Yoshizawa MJ, Kim K, Kanjanapangka J, Grogan T, Wang X, Elashoff D, Ishikawa S, Chia D, Liao W, Akin D, Yan X, Lee M, Choi R, Kim S, Kang S, Bae J, Sohn T, Lee J, Choi M, Min B, Lee J, Kim J, Kim Y, Kim S, Wong D. (2018) Development and Validation of Salivary Extracellular RNA Biomarkers for Noninvasive Detection of Gastric Cancer. Clin Chem. PMID: 30097497 DOI: 10.1373/clinchem.2018.290569", with permission from American Association for Clinical Chemistry (United States).

  Study phs001767

• Type 1 Diabetes Genetics Consortium (T1DGC): Copy Number Variant (CNV) Study

  Type 1 Diabetes Genetics Consortium (T1DGC) was formed to address issues of limited sample size and consistency of phenotyping that had limited genetic investigations on risk of type 1 diabetes (T1D). The T1DGC first collected affected sib pair (ASP) families from four geographic networks (Asia-Pacific, Europe, North America, United Kingdom). In addition, T1D parent-offspring trios as well as cases and controls were ascertained from existing and de novo collections. For T1D, the genome-wide association study (GWAS) design has been successful at detecting ~50 loci that contribute disease risk. However, in the case of T1D as well as almost all other traits, the sum of these loci does not fully explain the heritability estimated from familial studies. One possibility for the undiscovered contribution to familial aggregation is that additional variants exist but have not yet been found because they have not effectively been targeted by the GWAS design. In this study, we focus on a specific class of large deletions/duplications -- copy number variants (CNVs) - and particularly to the subset of these loci that mutate rapidly, are not tagged by SNPs, and are highly polymorphic. The T1DGC assembled 2,601 T1D ASP families and 69 Parent-T1D offspring trios, that were eligible for this study. All samples included in this series have reported or self-declared European ancestry. All DNA samples were collected after approval from relevant institutional research ethics committees. Importantly, the source of DNA for CNV evaluation was uniform within a family (either all from PBMC or from EBV-transformed cell lines). We use a family based design that was optimized to capture these previously untested variants. We then perform a genome-wide scan to assess their contribution to T1D.

  Study phs000910

• The Role of Germline Mutation and Parental Age in Autism Spectrum Disorders

  <p>We will apply whole genome sequencing of trio families to determine how patterns of germline mutation throughout the genome determine risk for Autism Spectrum Disorder (ASD). We will investigate the nature intrinsic hypermutability and the extrinsic forces, such as paternal age, that influence rates of germline mutation. We will accomplish these goals through the following specific aims: Specific Aim 1 will characterize germline de novo mutations (DNMs) by whole genome sequencing in families. These studies will identify and validate ~8,000 de novo point mutations and structural variants in trios and controls to determine the parent of origin of DNMs. Specific Aim 2 will identify hot spots for germline mutation based on the regional density of DNMs in the genome, and determine the effects of DNA sequence features on rates of mutation. We will determine the association of mutation hotspots with ASD in the discovery sample and in genomic datasets from an independent sample of 2700 cases and 2700 controls. Specific Aim 3 will characterize the effects of extrinsic factors, including parental age and environment, on genome-wide rates of mutation. We will quantify the effect of paternal age on pathogenic and neutral alleles in sperm and investigate whether some DNMs confer a germline selective advantage. The findings of this study will provide fundamental insights into the genetic basis of autism risk and the genetic mechanism of the observed parental age effects in ASD. We will identify genes that confer significant risk for autism, and we will determine how intrinsic properties of the genome interact with extrinsic forces to determining risk for disease in offspring.

  Study phs001164

• Genotyping NIGMS CEPH Samples from the United States, Venezuela, and France

  The Human Genetic Cell Repository (HGCR) is sponsored by the National Institute of General Medical Sciences (NIGMS) with the mission of supplying scientists with the materials for accelerating disease gene discovery and functional studies. The resources available include highly-characterized, contaminant-free fibroblast cell lines, transformed lymphoblastoid cell lines (LCLs), and DNA samples derived from these cultures. While the Repository has a major emphasis on inherited diseases, it also contains large collections of cell lines gathered from populations around the world that are intended for use in facilitating the understanding of human variation. Prominent among these resources is the CEPH Reference Family collection contributed by the Centre d'Etude du Polymorphisme Humain (CEPH), Foundation Jean Dausset, Paris, France. The CEPH collection includes families collected by R. White (Utah), J. Dausset (French), J. Gusella (Venezuelan), and J. Egeland (Amish). There are a total of 809 individuals accounting for 832 pedigree positions in the reference families. Family relationships for the 61 reference families were verified at Coriell and approved by CEPH. In an effort to enhance the value of this cell culture resource available from the Repository, the Coriell Genotyping and Microarray Center used the Affymetrix Genome-Wide Human SNP Array 6.0 platform to genotype 181 samples from the NIGMS HGCR CEPH collection. Included are thirteen families from the United States (Amish Pedigree 884 and Utah Pedigrees 1331, 1356, 1400, 1416, 1424, 1427, 1477, and 1582), France (Pedigrees 35 and 66), and Venezuela (Pedigrees 102 and 104). Twelve of the families consist of 3 generations and one family consists of 2 generations. Pedigree charts and sample descriptions are available on the Repository catalog website (see below).

  Study phs000268

• Genome Studies in Hereditary Spastic Paraplegia

  Next-generation sequencing technology is opening up new opportunities to rethink the way we identify disease causing genetic variation. An early application, whole exome sequencing, has now been established by a small number of research labs, including ours. Exome sequencing allows obtaining a near complete set of protein coding genomic variation in single individuals for less than $5,000. Promising targets for exome sequencing studies are Mendelian diseases, such as hereditary spastic paraplegias (HSP). HSP comprise a genetically very heterogeneous set of neurological disorders with currently 39 different HSP chromosomal loci being reported; yet, the identified genes explain only 60% of the genetic effect at best. Traditional methods of gene identification require linkage analysis of large families, but face increasing difficulties to identify such extended pedigrees for rare HSP forms. However, the innovative approach described in this application will overcome some of these limitations and utilize relatively small pedigrees for highly effective gene identification. We will apply exome sequencing, which will characterize all coding changes and flanking exonic variation in two individuals of a family. We have developed a multi-tiered strategy to reduce the number of identified novel variants to the very causative change in an individual family. We propose to study at least 60 HSP families, which are too small to yield conclusive results with linkage analysis. If the developing technology permits we will consider a larger sample or perform whole genome sequencing. Beyond the important benefit to genetics of HSP, this study will allow us to further establish this new method, which will benefit a large range of additional disease studies.

  Study phs001080

• A Missense SNP in the Tumor Suppressor SETD2 Reduces H3K36me3 and Mitotic Spindle Integrity in Drosophila

  While examining DNA from renal cell carcinoma (RCC) patients we observed a single nucleotide polymorphism (SNP; rs58906143,chr3:47163422 C→G (hg19); E902Q*) within SETD2 that was overrepresented in kidney cancer patients compared to control patients. This original study utilized directed sequencing of 14 genes. In an expanded study using a Taqman assay to study the specific SNP, a G allele was found in 72/493 cases (14.6%) and 24/356 (6.7%) controls. Analysis by ancestry revealed that there was there was a G allele in 50/119 (42.0%) cases and 21/71 (29.6%) controls in patients with African Ancestry while there was a G allele in 19/335 cases (5.7%) and 3/269 (1.1%) controls in patients with European Ancestry. These differences did not reach statistical significance. Concurrently, we studied the functional effect of this SNP in a Drosophila model. The homologous amino acid substitution at E741Q reduces H3K36me3 levels which could be rescued by wild type Set2. Additionally, the mutation resulted in significant defects in spindle morphogenesis, consistent with a role for SETD2 in alpha-tubulin methylation during mitosis. Data available through dbGAP include the 14 gene sequence files of 52 control and 128 RCC patients, the results of Taqman SNP (rs58906143) analysis in text files for 221 controls and 357 RCC patients, and compiled phenotype data including age and assigned race. Due to data use limitations, genotyping data for 8 RCC patients and 83 controls as well as GWAS data for ancestry determination will not be available on dbGaP, but will be made available on request.

  Study phs003474

• Clinical and Molecular Features of Acquired Resistance to Immunotherapy in Non-Small Cell Lung Cancer

  PD-(L)1 blockade has been shown to promote durable responses in non-small cell lung cancer (NSCLC) patients and has been rapidly incorporated into the treatment regimens for many with advanced disease. Despite this, mechanisms of acquired resistance (AR) to PD-(L)1 have not been well understood. To address the clinical and molecular landscape of AR to PD-(L)1 blockade in NSCLC patients, a large clinical cohort of AR to PD-(L)1 blockade in lung cancer was examined. In conjunction, a systematic genomic and transcriptomic analysis in a subset of patients (n = 29) with available tissue samples was conducted. To investigate the molecular mechanisms of AR to PD-1 blockade from pre- and/or post-treatment tumors, microarray-based whole transcriptome expression data for 29 tumor samples, and whole exome sequencing (WES) data from 34 tumor samples was generated from this subset. Microarray data was uploaded to the Gene Expression Omnibus (GEO) database. Most AR tumors showed retained or increased inflammatory characteristics with significant upregulation of IFNγ which was suggestive of persistent albeit insufficient anti-tumor immune response. This finding expounds upon the prior pre-clinical and translational data supporting the intricate role of IFNγ in sensitivity and resistance to immunotherapy. Whereas initial IFNγ exposure may be fundamental to T cell activation (a hallmark of immune response), persistent IFNγ related effects and upregulation may potentially signal immune dysfunction and IFNγ insensitivity in contrast. The inflammatory phenotypes identified have implications for future rational development of new immunotherapy strategies for patients with AR.

  Study phs002834

• Response and Resistance to ER-Directed Therapy in Metastatic Breast Cancer

  Despite the reduction in cancer recurrence and mortality provided by hormonal therapy, estrogen receptor positive (ER+) metastatic breast cancer (MBC) remains the most common cause of breast cancer death, resulting in more than 20,000 deaths in the U.S each year. Although several therapeutic options exist to target the estrogen receptor, resistance to these therapies invariably occurs. Genetic mechanisms of acquired resistance to targeted therapies in ER+ MBC are not well understood. To address this, we developed a prospective biopsy protocol where multiple research biopsies are collected from metastatic samples and used for pathology, ER/PR/HER2, OncoPanel (a CLIA 300 gene sequencing panel), whole exome sequencing (WES), transcriptome sequencing (RNA-Seq), and single-cell RNA-seq (scRNA-seq). In some cases, tissue is used for cell line and xenograft generation. Archival primary biopsies are also obtained when possible for parallel genomic studies. Patients are followed and serial metastatic biopsies are obtained. This data will be used to determine the landscape of genomic alterations in treatment-resistant ER+ MBC, and compared to data generated by TCGA for treatment-naive ER+ primary breast cancer. Comparison of genomic studies from resistant, metastatic specimens with corresponding pre-treatment primary samples will allow us to identify genomic association with resistance to specific therapies. Analysis of the serial metastatic biopsies collected over the course of multiple treatments will also shed light on tumor evolution under selective therapeutic pressure.NoteA subset of the MBC blood biopsies that are included in our study can be accessed and downloaded from the phs001977 accession.Another subset of patients in this study participated in a clinical trial (NCT02871791) and have their data deposited in the current study as well.

  Study phs001285

• MUSIC: Long-TerM OUtcomes after the Multisystem Inflammatory Syndrome In Children

  This study is an observational cohort study that will use routinely-collected clinical and cardiac (EKG, echocardiogram, CMR, exercise testing) data to assess the association between MIS-C (multisystem inflammatory syndrome in children) and cardiac outcomes within the first year after hospital discharge. Research funding will be available for EKGs, echocardiograms and MRIs in protocol windows that are not ordered by primary caregivers. Our principal goal is to determine the spectrum and early time course of coronary artery involvement, LV systolic function, and arrhythmias or conduction system abnormalities, and, using these data, to define associated clinical and laboratory factors. We will include all eligible patients, including retrospective cases beginning January 1, 2020, with follow-up (in-person or telehealth) up to one year and annual medical history forms until up to 5 years have elapsed since illness onset. Because many patients will have been identified by retrospective review, we will obtain consent at different times in their illness course. For this reason, it may be hard to reach some patients and their families. Waiver of consent will be obtained after three attempts have been made to locate the patient and family without success, as well as for the rare child who dies before informed consent can be obtained. We will include a HIPAA-compliant cryptographic algorithm to create a sharable “hashed” identifier from patient information. If blood work for research purposes is added to usual clinically-indicated blood work during follow-up visits, this will be covered by other informed consent forms. Our primary outcomes are the largest proximal Left Anterior Descending Coronary Artery (LAD) or Right Coronary Artery (RCA) z score and lowest Left Ventricular Ejection Fraction (LVEF).

  Study phs002770

• Puerto Rico Heart Health Program (PRHHP-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To investigate morbidity and mortality from Coronary Heart Disease (CHD) in Puerto Rican rural and urban men. The objectives of the study were: (1) to identify factors related to the development of CHD, (2) compare the etiology of disease in rural versus urban men, and (3) determine the prevalence and incidence of CHD and other cardiovascular diseases in Puerto Rican males.Background: As Puerto Rico became more industrialized in the 1940s and 1950s, mortality rates for CHD increased. Since many factors related to CHD can be relatively homogenous within a population, two contrasting subgroups were selected for study in Puerto Rico: a rural population of men from a mountainous community and an urban population selected from San Juan. The NHLBI initiated the Puerto Rico Heart Health Program in May, 1965 as a prospective study of lifestyle, environmental and biological factors in the progression of cardiovascular disease in Puerto Rican men.Participants: A total of 9,824 (2,976 rural, 6,848 urban) men, age 45 to 64 were examined at the baseline exam.Design: The examination consisted of standardized questionnaires to determine education, occupation, smoking habits, and physical activity. Trained interviewers conducted a nutritional survey through a 24 hour diet recall. Subjects were also examined to determine prevalent cardiovascular, cerebrovascular and peripheral vascular abnormalities. The examination included vital capacity, a 12-lead ECG, and laboratory tests for hematocrit, glucose, serum cholesterol, serum glycercides and lipoprotein electrophoresis. A medical history was also obtained. Three additional exams, approximately three years apart, were conducted and morbidity and mortality follow-up concluded in 1980.

  Study phs003930

• High Frequency Ventilation in Premature Infants (HIFI-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To evaluate the hypothesis that high frequency oscillatory ventilation in preterm infants would reduce the incidence of mortality and pulmonary complications compared to conventional mechanical ventilation.Background: With the introduction of mechanical ventilation in preterm infants, mortality and morbidity significantly improved but remained high. The improvement in survival that accompanied the use of mechanical ventilation also brought about an increase in the incidence of pulmonary complications. The principal complication occurs in the form of bronchopulmonary dysplasia. Barotrauma and oxygen toxicity are considered to be in the pathogenesis for this disorder. Considerable interest in high frequency ventilation for preterm infants was generated when animal studies indicated high frequency ventilation to be effective in promoting gas exchange without apparent adverse effects. High Frequency Ventilation (HFV) delivers small tidal volumes at high frequencies of 4 to 15 Hz, and animal studies had indicated that HFV was associated with effective gas exchange, less barotrauma, and lower mean airway pressure. However, the efficacy and safety of HFV in preterm infants had not been studied. The HIFI Planning Phase was initiated in August 1984, and recruitment and intervention began in February, 1986. Follow-up studies continued thru September, 1988.Participants: A total of 673 infants were enrolled.Conclusions: Bronchopulmonary dysplasia incidence was similar in the two groups as was mortality and the need for ventilatory support during the first 28 days. There was a significantly greater rate of pneumoperitoneum of pulmonary origin in the high frequency group as was a greater incidence rate of intracranial hemorrhage. (HIFI Study Group, 1989, PMID: 2643039)

  Study phs004032

• CPTAC Proteogenomic Study

  Recently, significant progress has been made in characterizing and sequencing the genomic alterations in statistically robust numbers of samples from several types of cancer. For example, The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and other similar efforts are identifying genomic alterations associated with specific cancers (e.g., copy number aberrations, rearrangements, point mutations, epigenomic changes, etc.) The availability of these multi-dimensional data to the scientific community sets the stage for the development of new molecularly targeted cancer interventions. Understanding the comprehensive functional changes in cancer proteomes arising from genomic alterations and other factors is the next logical step in the development of high-value candidate protein biomarkers. Hence, proteomics can greatly advance the understanding of molecular mechanisms of disease pathology via the analysis of changes in protein expression, their modifications and variations, as well as protein=protein interaction, signaling pathways and networks responsible for cellular functions such as apoptosis and oncogenesis. Realizing this great potential, the NCI launched the third phase of the CPTC initiative in September 2016. As the Clinical Proteomic Tumor Analysis Consortium, CPTAC continues to define cancer proteomes on genomically-characterized biospecimens. The purpose of this integrative approach was to provide the broad scientific community with knowledge that links genotype to proteotype and ultimately phenotype. In this third phase of CPTAC, the program aims to expand on CPTAC II and genomically and proteomically characterize over 2000 samples from 10 cancer types (Lung Adenocarcinoma, Pancreatic Ductal Adenocarcinoma, Glioblastoma Multiforme, Acute Myeloid Leukemia, Clear cell renal Carcinoma, Head and Neck Squamous Cell Carcinoma, Cutaneous Melanoma, Sarcoma, Lung Squamous Cell Carcinoma, Uterine Corpus Endometrial Carcinoma) .Germline DNA is obtained from blood and Normal control samples for proteomics varied by organ site. All cancer samples were derived from primary and untreated tumor.

  Study phs001287

• Response to Hepatitis B vaccine

  Approximately 5-10% of individuals, who are vaccinated with a hepatitis B (HB) vaccine designed based on the HBV genotype C, fail to acquire protective levels of antibodies. Host genetic factors behind low immune response to the HB vaccine were investigated by GWAS and HLA association tests. GWAS and HLA association tests were carried out using a total of 1,193 Japanese individuals including 107 low responders (HBsAb ?10 mIU/mL), 351 intermediate responders (10 mIU/mL< HBsAb <100 mIU/mL), and 735 high responders (HBsAb ?100 mIU/mL). Classical HLA class II alleles were statistically imputed using the genome-wide SNP typing data. GWAS identified independent associations of HLA-DRB1-DQB1 haplotypes, HLA-DPB1 alleles and BTNL2 gene with immune response to the HB vaccine designed based on the HBV genotype C. Five HLA-DRB1-DQB1 haplotypes and two DPB1 alleles showed significant associations with response to the HB vaccine in a comparison of three groups of 1,193 HB vaccinated individuals. When frequencies of DRB1-DQB1 haplotypes and DPB1 alleles were compared between low immune responders and HBV patients, significant associations were identified for three DRB1-DQB1 haplotypes, and no association was identified for any of DPB1 alleles. In contrast, no association for DRB1-DQB1 haplotypes and DPB1 alleles was identified in a comparison between high immune responders and healthy individuals. The findings in this study clearly show the importance of HLA-DR-DQ (i.e. recognition of a HB vaccine related HBsAg by specific DR-DQ haplotypes) and BTNL2 molecules (i.e. high immune response to the HB vaccine) for response to a HB vaccine designed based on the HBV genotype C.

  Study JGAS000341

• Targeting the DNA Repair Pathway in Ewing Sarcoma

  Ewing’s Sarcoma is a bone and soft tissue tumor that primarily affects adolescents and young adults. With current therapies, 70% of patients with localized disease survive but survival for metastatic and recurrent disease is poor. Whole genome sequencing of 19 Ewing’s Sarcoma tumors showed that STAG2 was mutated in 10% (2/19) of the tumors and STAG2 protein was absent in 14% (13/106) tumors by immunohistochemical staining. Previous studies have shown that glioblastoma cells lacking STAG2 are more sensitive to poly-ADP ribose polymerase (PARP) inhibitors. We found that Ewing’s Sarcoma cell lines are sensitive to PARP inhibitors irrespective of STAG2 protein expression. Ewing Sarcoma cell lines are defective in double strand DNA break repair. PARP inhibitor cytotoxicity in Ewing’s Sarcoma cells was potentiated 10-1,000 fold by DNA damaging agents (irinotecan and temozolomide). To extend these studies in vivo, we developed an orthotopic Ewing’s Sarcoma mouse model and performed pharmacokinetic and pharmacodynamic studies with three different PARP inhibitors (BMN-673, olaparib and veliparib) in clinical development for pediatric cancer. Those data were used to design preclinical phase I studies to identify tolerable drug combinations for pilot efficacy testing (preclinical phase II). Based on the results of the preclinical phase I/II data, we performed a double blind, randomized, placebo controlled preclinical phase III trial with 274 mice in 15 treatment groups. Irinotecan administered in a low-dose protracted schedule optimized for pediatric patients was an effective DNA damaging agent to combine with olaparib and BMN-673 and was better tolerated than combinations with temozolomide. Combining olaparib or BMN-673 with irinotecan and temozolomide gave complete and durable responses in over 80% of the mice.

  Study EGAS00001000839

• Genome wide association study on coronary heart disease in patients with familial hypercholesterolemia

  Mutations in the low-density lipoprotein receptor (LDLR) gene cause familial hypercholesterolemia (FH), a disorder characterized by coronary heart disease (CHD) at young age. We aimed to apply an extreme sampling method to enhance the statistical power to identify novel genetic risk variants for CHD in individuals with FH. We selected cases and controls with an extreme contrast in CHD risk from 17 000 FH patients from the Netherlands, whose functional LDLR mutation was unequivocally established. The genome-wide association (GWA) study was performed on 249 very young FH cases with CHD and 217 old FH controls without CHD (above 65 years for males and 70 years of age for females) using the Illumina HumanHap 550K chip. In the next stage, two independent samples (one from the Netherlands and one from Italy, Norway, Spain, and the United Kingdom) of FH patients were used as replication samples. In the initial GWA analysis we identified 29 independent single nucleotide polymorphisms (SNPs) with suggestive associations with premature CHD (p&lt;1×10-4). We examined the association of these SNPs with CHD risk in the replication samples. After Bonferroni correction, none of the SNPs either replicated or reached genome-wide significance after combining the discovery and replication samples. Therefore, we conclude that the genetics of CHD risk in FH is complex and even applying an ‘extreme genetics’ approach we did not identify new genetic risk variants. Most likely, this method is not as effective in leveraging effect size as anticipated, and may therefore not lead to significant gains in statistical power. (NB submitten and conditionally accepted at European Journal of Human Genetics-please use abstract only for internal review until submission complete)

  Study EGAS00001000734

• Targeted sequencing of genes recurrently mutated in AML

  Background Massively parallel sequencing technology has transformed cancer genomics. It is now feasible, in a clinically relevant time-frame, for a clinically manageable cost, to screen DNA from patient tumours for mutations essentially genome-wide. The challenge for personalised medicine will be to increase the sample size to thousands or tens of thousands of well-characterised cases in order to attain sufficient statistical power to stratify patients accurately across the complexity and genomic heterogeneity expected for most of the common tumour types. Currently, whole genome sequencing on this scale is not feasible, and targeted sequencing of relevant portions of the genome will be required. Pilot data We have developed protocols for large-scale, multiplexed sequencing of 100-200 genes in thousands of samples. Essentially, using robotic technology, genomic DNA from the cancer specimen is processed into sequencing libraries with unique DNA barcodes, thereby allowing sequencing reads to be attributed to the sample they derive from. Currently, these sequencing libraries can be generated in a 96-well format using fully automated protocols, and we are exploring methods to expand this to a 384-well format. The sequencing libraries are pooled and hybridized to custom sets of RNA baits representing the genomic regions of interest. Sequencing of the pulled-down libraries is done in pools of 48-96 samples per lane of an Illumina Hi-Seq. This protocol is already implemented at the Sanger Institute. We have published proof that somatic mutations in novel cancer genes can be identified from exome-wide sequencing. In unpublished pilot data, we have established the feasibility of robotic library production, custom pull-down, and multiplexed sequencing of barcoded libraries for 100 known myeloid cancer genes across 760 myelodysplasia samples. Highlights of the data thus far analysed reveal that the coverage is remarkably even between samples; when 96 samples are run, average coverage per lane of sequencing is ~250, with 90-95% of targeted exons covered by &gt;25 reads; known mutations can be discovered in the data set; and the protocol is amenable to whole genome amplified DNA. The bioinformatic algorithms for identification of substitutions and indels in pull-down data are well-established; we have pilot data proving that copy number changes, LOH and genomic rearrangements in specific regions of interest can also be identified by tiling of baits across the relevant loci. Proposal We propose to apply this methodology to 10000 samples from patients with AML enrolled in clinical trials over the last 10-20 years. Oncogenic point mutations and potentially genomic rearrangements will be identified, and linked to clinical outcome data, with a view to undertaking the following sorts of analyses: ? Identification of co-occurrence, mutual exclusivity and clusters of driver mutations. ? Correlation of prognosis with driver mutations and potentially gene-gene interactions ? Exploration of genomic markers of drug response Ultimately, we would like to be in a position to release the mutation data together with matched clinical outcome data to genuine medical researchers via a controlled access approach, possibly within the COSMIC framework (www.sanger.ac.uk/genetics/CGP/cosmic/). The vision here is to generate a portal whereby a clinician faced with an AML patient and his / her mutational profile can obtain a ?personalised? prediction of outcome, together with a fair assessment of the uncertainty of the estimate. With a sufficient sample size, there would also be the potential to develop decision support algorithms for therapeutic choices based on such data.

  Dataset EGAD00001000606