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• Breast Cancer Single-Cell RNA-Seq Dataset

  Single-cell RNA-Sequencing of 26 primary breast cancers from Wu et al. (2021) study. Data was generated using the Chromium controller (10X Genomics) and sequenced on the NextSeq 500 platform.

  Dataset EGAD00001007495

• HERBY trial WES

  Whole exome sequencing of non-brainstem paediatric high grade glioma from the HERBY phase II randomised trial. DNA from 86 cases was subjected to Illumina paired end whole exome sequencing using a customised SureSelect Human All Exon V6 capture set. Germline DNA from whole blood was sequenced for 83 cases. 26 cases were sequenced from both fresh frozen tissue and FFPE material, 10 were sequenced from only fresh frozen material and 50 from only FFPE. Data is provided as bwa aligned BAM files

  Dataset EGAD00001004036

• WES of melanoma tumours prior to combined immune checkpoint blockade treatment.

  Paired melanoma tumor and normal (PBMC) WES data from a cohort of 26 patients subsequently treated with combined immune checkpoint blockade.

  Dataset EGAD00001005941

• Duplex sequencing of 26 genes

  Buccal samples and paired esophageal epithelium were obtained using the three sizes of swabs and endoscopic biopsy, respectively. Forty samples from 10 subjects were analyzed via duplex sequencing. This dataset contains bam files that were mapped to the GRCh37 reference genome.

  Dataset EGAD50000000998

• RNA-seq samples

  Raw FASTQ files obtained by RNA sequencing of tumor samples from patients (age 12-29) with newly diagnosed, recurrent intermediate or high-grade sarcoma.

  Dataset EGAD00001008393

• Functional Variant rs9344 at 11q13.3 Regulates CCND1 Expression in Multiple Myeloma with t(11;14)

  Multiple myeloma (MM) is a plasma cell (PC) malignancy characterized by cytogenetic abnormalities, such as t(11;14)(q13;q32), resulting in CCND1 overexpression. The rs9344 G allele within CCND1 is the most significant susceptibility allele for t(11;14). We have found the G risk allele is enriched in both healthy individuals of African ancestry and African American individuals with MM. The overall aim of this study was to identify the mechanism behind why the G allele is enriched in t(11;14) MM. To reach this goal, we performed ATAC-seq from 100,000 CD138+ tumor cells from 26 patients with MM. In addition, we performed ChIP-seq using antibodies against H3K4me1, H3K27ac and H3K4me3 from 100,000 CD138+ tumor cells from 8 patients with MM. We used these data to evaluate whether the G allele of rs9344 is associated with elevated chromatin accessibility, H3K27ac and H3K4me3 in t(11;14) MM.

  Study phs003997

• 'IL-17A-Producing ILC3s and Duodenal Adenoma in FAP'

  Familial Adenomatous Polyposis (FAP) is a hereditary tumor syndrome that significantly enhances the risk of duodenal adenomas, with variations observed even among carriers of the same genetic variant. In this study, intestinal ILCs were isolated from 82 FAP and 26 non-FAP patients and analyzed through flow cytometry, qRT-PCR, and bulkRNA-sequencing. The data revealed a heightened frequency of ILC3s in FAP patients, and increased IL-17A production of duodenal NKp44(-)ILC3s was associated with FAP. Significant elevations in IL1B, IL23A, and DLL4 mRNA expression levels were found in FAP duodenal adenoma tissue, along with enhanced expression of DUOX2 and DUOXA2. The results suggest the involvement of IL-17A-producing NKp44(-)ILC3s in duodenal adenoma formation in FAP.

  Study EGAS00001007347

• Chromatin accessibility in human monocyte differentiation

  This dataset consists of ATAC-seq data from human monocytes, monocyte-derived dendritic cells or monocyte-derived macrophages as well as monocyte-derived cells that were subjected to siRNA treatment targeting TET2, IRF4 and EGR2. In total, it includes 26 samples.

  Dataset EGAD00001006601

• ICGC PCAWG Dataset: ORCA-IN_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: ORCA-IN.

  Dataset EGAD00001002120

• Data files for PCGP SJACT RNASEQ

  This dataset contains RNA-Seq files for the SJACT cohort associated with the paper "Genetic landscape of pediatric Adrenocortical Tumor". In this paper, we analyse 37 adrenocortical tumours (ACTs) by whole-genome, whole-exome and/or transcriptome sequencing.

  Dataset EGAD00001002680

• Small‑scale mutations are infrequent as mechanisms of resistance in post‑PARP inhibitor tumour samples in high grade serous ovarian cancer

  Targeted DNA sequencing of high-grade serous ovarian cancer (HGSC) tumour and normal samples from 26 patients. Following target hybrid capture of 63 genes involved in DNA repair and response to treatment with an Agilent SureSelect XT panel, sequencing libraries were generated using the SureSelect XT Low Input Target Enrichment System (Agilent) as per the manufacturer's protocol. Libraries were sequenced on an Illumina NextSeq 500 at the Peter MacCallum Cancer Centre (Melbourne, Australia).

  Study EGAS50000000146

• RNA sequencing from High-grade B-cell lymphoma, not otherwise specified: an LLMPP study

  RNA-seq for 26 newly added samples in High-grade B-cell lymphoma, not otherwise specified: an LLMPP study, and 32 samples from a previously uploaded dataset.

  Dataset EGAD50000001365

• Neuroblastoma_MP-PCR_MultiplexPCR_TargetedSequencing_BAMs

  This dataset contains raw sequencing data (BAM/BAI files) generated from human neuroblastoma patient samples. The data were produced using targeted high-throughput next-generation sequencing and are intended to support genomic analyses of tumor-associated alterations. All files are provided under controlled access in accordance with EGA data protection requirements.

  Dataset EGAD50000002260

• Mutation analysis of 17 genes in plasma DNA of CRC patients using the AVENIO ctDNA Targeted Kit

  Mutation analysis of 17 genes (ALK, APC, BRAF, BRCA1, BRCA2, DPYD, EGFR, ERBB2, KIT, KRAS, MET, NRAS, PDGFRA, RET, ROS1, TP53, UGT1A1) in plasma DNA of CRC patients using the AVENIO ctDNA Targeted Kit.

  Dataset EGAD00001006103

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 8a)

  Whole genome sequencing data of 26 high-grade serous carcinoma (HGSC) patients (87 samples) sequenced with MGISEQ-2000 and HiSeq X Ten.

  Dataset EGAD00001011304

• Verification of BCR reconstruction from single-cell RNA-seq using BraCeR

  This dataset was made to verify the computational reconstruction of B cell reseptors from single-cell RNA-seq using BraCeR. The dataset contains BCR-derived reads from single-cell RNA-seq from 13 cells using the Smart-seq2 protocol, as well as targeted BCR-sequencing data from the same cells.

  Dataset EGAD00001004199

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

  All libraries were sequenced on Illumina NextSeq or NovaSeq6000 until sufficient saturation was reached.

  Dataset EGAD00001008585

• Clinical utility of combined low-pass whole genome and targeted sequencing in liquid biopsies for diagnosis and monitoring of pediatric solid tumors

  Low-pass whole genome sequencing samples from pediatric solid tumor patients who are deceased

  Dataset EGAD00001009972

• Whole Genome Sequencing of a Triple Negative Breast Cancer Patient: Matched Primary Tumor, Normal, Metastasis and Xenograft samples

  Breast Cancer Subject Participant ID 700064 (Source Sample names: 6888 and 206). We used massively parallel DNA sequencing technologies to screen entire genomes, in an unbiased manner, for genetic changes associated with tumor growth and metastasis. We describe the complete genome sequence analysis of four DNA samples from a 44-year old African-American patient with basal-like breast cancer: peripheral blood, the primary tumor, a brain metastasis that developed within a year of initial therapy, and a first-passage xenograft derived from the primary tumor. A total of 50 validated mutations were discovered within coding, RNA, or splice site sequences. Of these, 20 mutations were abundantly present in all three tumors, including mutations in CSMD1 and JAK2. These two genes subsequently were found to be mutated in other breast tumors. The metastasis contained two de novo mutations not present in the primary tumor, and was significantly enriched for 20 shared mutations, suggesting that they may be involved in the metastatic process. The xenograft contained no unique coding, RNA, or splice site mutations and retained all primary tumor mutations, albeit at different frequencies. However, a significant increase in copy number alterations was observed in the xenograft as compared to the primary tumor. We validated 28 large deletions and six inversions, as well as seven translocations in at least one of the three tumor samples. Among them, a 26 kb deletion in MECR was solely identified, assembled, and validated in the brain metastasis and two overlapping large deletions on chromosome 5 encompassing CTNNA1, a potential tumor suppressor gene, were identified in all three tumors. The differential mutation frequencies and structural variation patterns between primary and metastatic tumors suggest that metastatic tumors may arise from minor subpopulations of cells within the primary. Namely, the metastatic and xenografting processes apparently select for cells harboring a distinct subset of the primary tumor mutation repertoire.

  Study phs000245

• fragmentomic features of individuals with different cfDNA concentrations

  The uploaded data includes sequencing data of 862 individuals from the nasopharyngeal carcinoma (NPC) screening study. Samples from this cohort were sequenced using targeted sequencing methods for the Epstein Barr Virus (EBV) and selected autosomal DNA, but only ‘off-target’ reads were used for fragmentomic analyses. We have also performed genome-wide (non-targeted sequencing) for 1) Individuals with the highest and lowest cell-free DNA concentration (40 individuals); 2) A subsequent collection of the subjects with the highest and lowest DNA concentrations after six years (26 individuals); 3) 30 cases of pregnancy and 4) 20 patients with hepatocellular carcinoma. All sequencing data are of extracted plasma cfDNA from human subjects. The targeted sequencing samples from 862 individuals were sequenced on the NextSeq500 System (Illumina) and aligned to the EBV genome (AJ507799.2) and the human genome (hg19). The alignments were provided in bam format. The original fastq files of the remaining non-target sequencing samples were provided.

  Dataset EGAD50000000970

• Characterization of the molecular signature of human monocytes in aging and myelodysplastic syndrome

  Deep immunophenotypic profiling of peripheral blood immune cells from young and older control subjects as well as patients with MDS was initially performed, using mass cytometry to identify monocyte subpopulations. Abundance of monocyte subpopulations separated the samples from patients with MDS from elderly control subjects was identified. Therefore, targeted immunophenotyping of monocytes was also performed with flow cytometry and RNA sequencing from isolated CD14+ peripheral blood longitudinally in 26 subjects, six young healthy individuals, nine older healthy individuals and eleven patients with MDS.

  Study EGAS00001007676

• Datasets of RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial

  RNA-seq analyses were performed on tumor tissue samples of 115 advanced clear cell renal cell carcinoma patients who participated in the NIVOREN GETUG-AFU-26 trial. The samples were obtained prior to treatment initiation. RNA-seq was performed to evaluate previously published gene expression signatures. These included: the IMmotion T effector (CD8A, EOMES, PRF1, IFNG and CD274) and the IMmotion Myeloid (IL-6, CXCL1, CXCL2, CXCL3, CXCL8, and PTGS2) gene signatures represent gene expression patterns associated with T effector cells and myeloid cells, respectively, while JAVELIN Renal 101 Immuno (T-cell receptor signaling: CD3G, CD3E, CD8B, THEMIS, TRAT1, GRAP2, CD247; T-cell activation, proliferation, and differentiation: CD2, CD96, PRF1, CD6, IL7R, ITK, GPR18, EOMES, SIT1, NLRC3; Natural killer cell mediated cytotoxicity: D2, CD96, PRF1, CD244, KLRD1, SH2D1A; Chemokine: CCL5, XCL2; and Other immune response genes: CST7, GFI1, KCNA3, PSTPIP1) represents gene expression patterns associated with both innate and adaptive immune response.

  Dataset EGAD50000001541

• Whole Exome Sequencing of Human Gastro-esophageal Cancer PDXs

  The current study investigates biomarkers of response to anti-EGFR therapies in gastro-esophageal cancer. Whole exome sequencing was performed on 26 tumors to explore potential factors influencing treatment outcomes. As part of the analysis, somatic mutations in EGFR, ERBB2, and key downstream signaling genes (KRAS and PIK3CA) were examined to exclude the presence of known mutations conferring sensitivity/resistance. The study aims to contribute to the identification of patients who may benefit from lower-toxicity regimens, improving treatment personalization and minimizing adverse effects.

  Study EGAS50000000966

• Wilm's tumor sequencing data

  No. of samples: 80 (28 ULP-WGS, 26 WES, 26 RNA-SEQ) File types: FASTQ (28 ULP-WGS, 19 WES, 18 RNA) and BAM (7 WES, 8 RNA) Technology used: Sequencing - Illumina Novoseq 6000; Map/Align - Illumina DRAGEN v3.7.5; Genome assembly - GrCh38p13 Filename nomenclature: - SampleName_Passage_SampleType_TissueType_SequencingType - Passage of: PX = unknown; PZ = from patient; P0 = first passage from patient on plastic; P1 = first passage from plastic/PDX/organoid - SampleType: STN = normal; STT = tumor - SampleType STN: 00 = tissue unknown; 01 = adjacent normal; 02 = fibroblast; 03 = germline blood; 21 = cell line from patient tissue; 22 = cell line from PDX; 23 = cell line from patient fibroblast - SampleType STT: 00 = tissue unknown; 01 = primary tumor; 21 = cell line from patient; 22 = cell line from PDX - TissueType: WT = Wilm's tumor; 00 = kidney unknown; 01 = kidney left; 02 = kidney right - SequencingType: 00 = unknown; 02 = ultra-low pass whole-genome sequencing; 20 = whole-exome; 61 = bulk RNA-sequencing

  Dataset EGAD00001011111

• Cell-free DNA Methylome Analysis Enables Early Preeclampsia Prediction

  This dataset contains in solution target-enrichment bisulfite sequencing of placental tissue, buffy coat and plasma DNA from pregnant women. Blood samples were taken for cell-free DNA (cfDNA) DNA extraction from 64 women at the time of early-onset preeclampsia (PE) diagnosis, or from 38 controls (uncomplicated pregnancies) at a similar gestational age that did not develop preeclampsia subsequently. Among these subjects, plasma samples from 7 PE patients and 6 controls were also subjected to oxidative bisulfite sequencing. Placental tissues from 11 PE and 26 control subjects after delivery, and buffy coat from 16 PE and 16 control subjects at the same time of cfDNA sampling were profiled. A discovery cohort for early PE assessment in the first trimester was collected. In this cohort, cfDNA from 75 pregnancies that went on to develop early-onset PE and from 124 matched controls were collected and methylome sequencing were carried out. An independent validation cohort to validate early PE assessment with methylome profiling was collected as well. This validation cohort includes cfDNA samples from 61 PE and 136 control pregnancies.

  Dataset EGAD00001010159

• Sequencing of pancreatic cancer primary tumors and metastases

  The extent of heterogeneity of driver gene mutations present in naturally occurring metastases is largely unknown, i.e. treatment-naïve metastatic disease. To address this issue, 60x whole genome sequencing of 26 metastases from 4 patients was carried out. We found that the identical driver gene mutations were present in every metastatic lesion of each patient studied. Passenger gene mutations not known or predicted to have functional consequences accounted for all intratumoral heterogeneity. Even with respect to these passenger gene mutations, the genetic similarity among the founding cells of metastases was markedly higher than that expected for any two cells randomly taken from a normal tissue. The uniformity of driver gene mutations among metastases in the same patient has critical, encouraging implications for the success of future targeted therapies in advanced stage disease.

  Study EGAS00001002186

• WES of der(1;7)(q10;p10)

  This dataset contains the BAM files of WES of 26 myeloid neoplasm patients with der(1;7)(q10;p10)(+) cases. The dataset was used to identify key driver genes in patients with der(1;7)(q10;p10). Already known drivers along with novel driver genes were identified through the use of this WES.

  Dataset EGAD50000000986

• Short-read (RNA-seq)

  The goal of this project was to perform long-read RNA sequencing (LR-seq, PacBio) in combination with short-read RNA-seq for systematic characterization of the isoform diversity in primary breast tumor samples. We sequenced the full-length transcriptomes of 26 breast tumors and 4 normal breast samples.

  Dataset EGAD00001006596

• BLUEPRINT: RNA-seq of progenitor cells

  Data supporting the paper Transcriptional diversity during lineage commitment of human blood progenitors

  Dataset EGAD00001000745

• Cancerous Adaptive Dosing Melanoma WGS Dataset

  Illumina NovaSeq 6000 30x WGS of 26 samples, each with up to 5 matched timepoints. Timepoints A,B,C,D,and E correspond to Pretreatment, Week 3, Week 6, Week 9, and Week 12 after treatment, respectively. Additional sample metadata (sample recurrence, treatment course, age, sex, comorbidities, etc.) are present in sample description.

  Dataset EGAD00001010926

• Validation_of_a_Haloplex_platform_for_targeted_re_sequencing_of_the_exons_of_25_genes

  We recently used the Agilent SureSelect platform to re-sequence a set of genes known to bemutated in human AML. The results from 10 AML DNA samples were very satisfactory, butthe effort required was significant.Thus, we decided to re-sequence the same genes using the Haloplax system for targetenrichment in 48 AML samples. We planned to do this using MiSeq and have data from apilot of 3 samples. The data is promising but coverage appears pathcy so far.However, in order to get a better understanding of the data we will need deeper sequencing. Wewill need two lanes of HiSeq to get the same degree coverage as Sureselect.his 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/

  Study EGAS00001000285

• H3Africa H3AChipDesign Phenotype

  Basic phenotypic data (country, ethnicity and sex) for 348 samples of the H3Africa Chip Design Study. Divided into 8 datasets of 41 samples from Zambia, 24 samples from Cameroon, 50 samples from Mali, 26 samples from Cameroon, 49 samples from Nigeria, 48 samples from Botswana, 50 samples from Benin, 60 samples from Burkina Faso and Ghana.

  Dataset EGAD00001005310

• Whole-exome/genome sequencing of childhood acute leukemia in Iraq

  This dataset contains 26 whole-genome sequencing (13 paired tumor and normal), 106 whole-exome sequencing (53 paired tumor and normal), and 43 targeted sequencing data. Sequencing was performed using an Illumina platform. The data are BAM files aligned to the hg19 reference genome.

  Dataset EGAD00001007873

• Young Boost Trial for Breast Cancer patients

  The Young Boost Trial (YBT, YOUNG BOOST / BOOG 2004-01 (Borstkanker) | Kanker.nl investigated the optimal radiation dose for breast cancer patients aged 50 years or younger, treated with breast-conserving therapy (BCT). In this randomized study, participants were assigned to receive either a 26 Gy or a 16 Gy radiation boost, with the primary endpoint being local recurrence. To explore potential predictive biomarkers of treatment response in this patient group, whole exome sequencing (WES) was performed on tumor samples to identify genetic factors that could guide personalized treatment strategies and improve clinical outcomes for these young breast cancer patients.

  Study EGAS50000000797

• Cerebrospinal fluid cfDNA sequencing for classification of central nervous system glioma

  Primary central nervous system (CNS) gliomas can be classified by characteristic genetic alterations. In addition to solid tissue obtained by surgery or biopsy, cell-free DNA (cfDNA) derived from cerebrospinal fluid (CSF) is an alternative source of material for genomic analyses. Experimental design: We performed targeted next-generation sequencing (NGS) of CSF cfDNA in a representative cohort of 85 patients presenting with with suspicion of primary or recurrent glioma at two neurooncological centers. Copy-number variation (CNV) profiles, single nucleotide variants (SNVs), and small insertions/ deletions (indels) were combined into a molecular-guided tumor classification. Comparison with the solid tumor was performed for 38 cases with matching solid tissue available. Results: Cases were stratified into four groups: glioblastoma (n = 32), other glioma (n = 19), non-malignant (n = 17) and no confirmed diagnosis available (n = 17). We introduce a molecular-guided tumor classification, enabling identification of tumor entities and/ or cancer specific alterations in 75.0 % (n = 24) of glioblastoma and 52.6 % (n = 10) of other glioma cases. The overlap between CSF and matching solid tissue was highest for CNVs (26-48 %) and SNVs at pre-defined gene loci (44 %), followed by SNVs/indels identified via uninformed variant calling (8-14 %). A molecular-guided tumor classification was made 23.5 % (n = 4) of cases with no confirmed diagnosis available. Conclusions: We developed a workflow for targeted sequencing of CSF cfDNA as well as a strategy for interpretation and reporting of sequencing results based on a molecular-guided tumor classification in glioma.

  Study EGAS50000000060

• Target sequencing of 27 cancer-predisposing genes and 13 renal cell carcinoma-related genes in Japanese renal cell carcinoma patients

  Identifying causative genes via genetic testing is useful for the screening, prevention, and treatment of cancer. Several hereditary syndromes are known to occur in renal cell carcinoma (RCC). However, these evidences came from the European population; it remains unclear how the RCC-related genes and other cancer-predisposing genes contribute to the development RCC in the Japanese population. A case-control study of 14 RCC-related genes and 26 cancer-predisposing genes was performed using 1,563 Japanese patients with RCC and 6,016 controls. Patients were divided into two major histological subtypes of clear cell RCC (ccRCC) or non-clear cell RCC (nccRCC). Gene-based analysis of germline pathogenic variants in patients with each subtype and cancer-free subjects was performed. Following quality control, 1,532 patients with RCC and 5,996 controls were further analyzed. For ccRCC, 52 of 1,283 (4.05%) patients carried pathogenic variants mainly in the cancer-predisposing genes such as TP53 (P = 1.73 �� 10-4; OR, 5.8; 95% CI, 2.2���15.7). Approximately 80% of patients with pathogenic variants in TP53 had p.Ala189Val that was specific in East Asian population. For nccRCC, 14 of 249 (5.62%) patients carried pathogenic variants mainly in the RCC-related genes such as BAP1 (P = 6.27 �� 10-5; OR, Inf; 95% CI, 10.0���Inf), and FH (P = 6.27 �� 10-5; OR, Inf; 95% CI, 10.0���Inf). Our study showed different and population-specific contributions of risk genes between ccRCC and nccRCC in Japanese for better-personalized medicine.

  Study JGAS000414

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 17)

  The dataset contains whole genome sequencing data of 26 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 86 samples are either fresh frozen tumour samples or blood samples. The files provided are paired fastq files.

  Dataset EGAD50000002409

• Genetics of Glucose Regulation in Gestation and Growth (Gen3G) Cohort - Placenta Transcriptomics RNA Sequencing

  The overarching goals of Genetics of Glucose regulation in Gestation and Growth (Gen3G) are to increase our understanding of biological, environmental, and genetic determinants of glucose regulation during pregnancy and their impact on fetal/child development. Gen3G is a prospective cohort study: we initially recruited 1,024 pregnant women between 2010-2013 at Blood Sampling in Pregnancy Clinic during the first trimester of pregnancy (median 9 weeks of gestation) in Sherbrooke, Québec, Canada. We assessed 898 pregnant women at second trimester (median 26 weeks of gestation), when participants completed a 75g oral glucose tolerance test (OGTT) as clinically indicated for screening of gestational diabetes mellitus (GDM). We collected data for 854 mother-child dyads at delivery (from medical records), in addition to placenta and/or cord blood samples in majority of newborns.The overall goal of the grant that supported data that is included in this dbGaP submission was to discover novel placental factors that regulate glucose metabolism in pregnancy and predict GDM by conducting genome-wide transcriptomics (RNA and miRNA) in carefully collected placenta samples from Gen3G.

  Study phs003151

• Blood-based monitoring of relapsed/refractory cHL patients predict responses to PD-1 blockade treatment

  Hodgkin lymphoma (cHL) patients are uniquely susceptible to treatment with programmed cell death-1 (PD-1) treatment. However, monitoring with FDG-PET/CT, the current response detection standard, is challenging. Here, we address the potential applicability of tissue biomarkers and blood-based biomarkers in PD-1 treated cHL patients. We evaluated 9p24.1/PD-L1/PD-L2 alterations, and expression of PD-L1 and antigen presentation molecules (HLA class I/II) in 9 tissue biopsies of 4 patients. In addition, we assessed circulating tumor DNA (ctDNA), extracellular vesicle associated miRNAs (EV-miRNAs), soluble PD-L1 and serum TARC (sTARC) in 26 longitudinal blood samples of these patients during PD-1 treatment. We found that the predictive power of tissue biomarkers is dependent on the timing of the biopsy . The dynamics of blood-based biomarkers: sTARC, EV-miRNAs and ctDNA corresponded well immunotherapy treatment response. Therefore, blood-based biomarkers are promising monitoring strategies in PD-1 treated cHL patients and should be further explored in clinical trials or observational studies.

  Study EGAS00001005894

• Single-cell RNA-seq of celiac disease-specific plasma cells

  Disease-specific plasma cells (PCs) reactive with transglutaminase 2 (TG2) or deamidated gluten peptides (DGP) are abundant in celiac disease (CeD) gut lesions. Their contribution toward CeD pathogenesis is unclear. We assessed expression of markers associated with PC longevity in 15 untreated and 26 treated CeD patients in addition to 13 non-CeD controls, and performed RNA-sequencing with clonal inference and transcriptomic analysis of 3251 single PCs. We observed antigen-dependent V-gene selection and stereotypic antibodies. Generation of recombinant DGP-specific antibodies revealed a key role of a heavy-chain residue that displays polymorphism, suggesting that immunoglobulin gene polymorphisms may influence CeD-specific antibody responses. We identified transcriptional differences between CeD-specific vs non-disease-specific PCs and between short-lived vs long-lived PCs. The short-lived CD19+CD45+ phenotype dominated in untreated and short-term-treated CeD, in particular among disease-specific PCs but also in the general PC population. Thus, the disease lesion of untreated CeD is characterized by massive accumulation of short-lived PCs that are not only directed against disease-specific antigens.

  Study EGAS00001004623

• Longitudinal sampling in relapsed and refractory Hodgkin lymphoma

  Ultra-deep next-generation panel-sequencing on 59 FFPE-samples (20 LTR, 26 relapsed (rHL: 11 initial-diagnosis, 15 relapse) and 13 primary-refractory (prHL: 8 initial-diagnosis, 5 progression) from 44 cHL-patients applying a hybrid-capture approach. Data was processed as described in the publication and mark duplicated bam files were uploaded.

  Dataset EGAD50000000210

• Whole Exome Sequencing of paired gDNAs and PPGL tumor DNA from patients with cyanotic congenital heart disease

  Fastq files from Whole Exome Sequencing of 12 paired germline DNA (from blood/saliva) and 14 PPGL tumor DNA (from formalin-fixed paraffin-embedded (FFPE) blocks from surgery) from patients with cyanotic congenital heart disease (CCHD) and pheochromocytoma and paraganglioma (PPGL). Sequencing was performed using the Illumina HiSeq4000.

  Dataset EGAD50000001201

• WGS Fastq files from the CPC-Gene project in support of PRAD-CA, DCC Release 26

  This dataset contains fastq files with Whole genome sequencing data for the CPC-Gene Project. Data from each sample was generated using multiple whole genome libraries and sequenced across multiple runs

  Dataset EGAD00001003761

• Contribution of systemic and somatic factors to clinical response and resistance in urothelial cancer: an exploratory multi-omic analysis

  Patients with metastatic urothelial cancer (n=29) were treated with atezolizumab (anti-PD-L1). All 29 patients had T-cell receptor sequencing (TCR-seq) of the pre-treatment blood; 24 also had TCR-seq on at least one post-treatment blood sample. 24 patients had TCR-seq of their pre-treatment tumors. TCR-seq data can be found at http://doi.org/10.5281/zenodo.546110. 26 patients also had RNAseq of their tumors and whole exome sequencing (WES) of their tumors and matched normal blood. WES results for one sample were excluded from our analysis after failing to meet coverage requirements.

  Study phs001743

• COVID-19-Induced Immune Alterations in Infants

  Although previous studies have described some overlap between COVID-19-induced immune alterations in adults and children, no systematic immune profiling studies have been reported in infants. We applied a multidimensional approach to decipher the immune responses to SARS-CoV-2 infected infants (n=26; 10 mild, 11 moderate and 5 severe) and healthy matched controls (n=14). Single-cell RNA-seq profiling (scRNA-seq) of PBMCs revealed alterations in cell composition upon infection, with most cell types demonstrating an interferon-stimulated gene (ISGhi) state. Our findings shed insight into the immune responses to SARS-CoV-2 in the first year of life.

  Study phs002655

• Evolution of Structural Rearrangements in Prostate Cancer Intracranial Metastases

  Intracranial metastases in prostate cancer are uncommon but clinically aggressive. We sought to characterize prostate cancer intracranial metastases in order to improve our understanding of their pathogenesis and to promote the search for new treatment strategies. We evaluated the clinical and molecular characteristics of 36 patients with metastatic prostate cancer to either the dura or brain parenchyma. We performed whole genome sequencing (WGS) on samples from 21 patients. The WGS samples include 10 intracranial prostate cancer metastases, as well as WGS of primary prostate tumors from men who later developed metastatic disease (n=6) and non-brain prostate cancer metastases (n=26).

  Study phs003357

• Next generation sequencing of diffuse intrinsic pontine glioma samples to identify recurrent mutations, variations, and expression patterns to define novel therapies

  Diffuse intrinsic pontine glioma (DIPG) is an extremely rare (~350 cases/year) and universally fatal childhood brain cancer. Standard clinical strategies such as chemotherapy and radiotherapy show only transient improvement in patient condition and result in negligible change in survival, DIPG remains at below 1% survival after 5 years. Prioritization of panobinostat through previous cooperative work resulted in a phase 1 clinical trial. Nonetheless, new therapies for DIPG must be identified to further dramatically change the statistics for DIPG. To identify novel therapy strategies for DIPG, we performed whole exome(16 new samples, 22 previously published samples, 38 in total with 26 matched normal) and RNA deep sequencing (17 new samples, 11 previously published samples) on a cohort of new patient samples. Sequencing results aid in the identification of recurrent mutations/variations and endotypic expression profiling to identify new therapeutic and treatment strategies for DIPG.

  Study phs001526

• Circulating Tumor DNA as a Biomarker in Patients with Stage III and IV Wilms Tumor: Analysis from a Children's Oncology Group Trial, AREN0533

  We evaluated the utility of circulating tumor DNA (ctDNA) as a biomarker in the serum and urine of 50 patients with Stage III or Stage IV Wilms tumor (WT) that were enrolled on Children's Oncology Group (COG) trial AREN0533. 49 out of 50 patients had matched tumor samples available for comparison. We profiled samples with ultra-low pass whole genome sequencing (ULP-WGS) and detected ctDNA in 82% of serum samples and 26% of urine samples. We also identified copy-number changes and single-nucleotide variants in the serum and urine samples, and compared them to the tumor data. Our study highlights the advantages of using ctDNA as non-invasive prognostic biomarker with the potential to detect tumor heterogeneity in patients with WT. We believe that prospective validation of ctDNA as a prognostic biomarker in patients with WT is warranted. The ULP-WGS and targeted next-generation sequencing (OncoPanel) data are available in this study.

  Study phs002847

• International Age-Related Macular Degeneration Genomics Consortium - Exome Chip Experiment

  Advanced age-related macular degeneration (AMD) is the leading cause of blindness in the elderly, with limited therapeutic options. To further our understanding of AMD genetics, we examined the contribution of common and rare genetic variation in the International AMD Genomics Consortium that included ~50,000 samples of 26 AMD case - control cohorts that were jointly genotyped. Analyzing 16,144 patients with late stage AMD and 17,832 controls, we identified 52 independently associated common and rare variants distributed across 34 loci. Besides these single variant signals, we also observed gene-based enrichment of very rare coding variants (frequency < 0.1%) in cases that implicated causal roles for CFH, CFI and TIMP3 in three of the known AMD risk loci. Our results support the hypothesis that rare coding variants can pinpoint causal genes within known genetic loci and illustrate that applying the approach systematically to detect new loci requires extremely large sample sizes.

  Study phs001039

• SeqControl: Process Control for DNA Sequencing

  As next-generation sequencing (NGS) continues to increase in speed and throughput, routine clinical and industrial application draws steadily closer. These “production” uses of NGS will require enhanced quality-monitoring and quality-control to optimize output and reduce costs. We therefore developed a framework called SeqControl for predicting sequencing quality and coverage using a set of 15 metrics describing overall coverage, coverage distribution, base-wise coverage and base-wise quality. Using whole-genome sequences of 27 prostate cancers and 26 normal references we derive multivariate models that predict sequencing quality and depth. SeqControl robustly predicts how much sequencing is required to reach a given coverage depth (AUC = 0.993), accurately classifies clinically relevant formalin-fixed paraffin-embedded samples and makes predictions from as little as 1/8 of a lane of sequencing data (AUC = 0.967). These techniques can be immediately incorporated into existing NGS pipelines to monitor data quality in real-time. SeqControl represents a first step towards statistical process-control for NGS.

  Study EGAS00001000899

• med-pchic-dac

  The data are accessible under the terms of the following Data Access Agreement that needs to be filled in, signed (by yourself and your institution’s official contact) and returned by email to med-pchic-dac@lists.cam.ac.uk

  Dac EGAC00001000523

• WGS data of patient derived organoids (PDO) generated from dMMR colorectal tumor subclones

  The dataset includes bam files from WGS of 26 monoclonal patient derived organoid (PDO) lines isolated from 6 independent tumor subclones of a dMMR colorectal tumor. These organoids were grown as part of an in vitro timecourse experiment for the duration of 9 weeks; bam files represent the mutational load at the start of the timecourse (t0) and the end of the timecourse (t1).

  Dataset EGAD50000000427

• Whole Exome Sequencing of Human Gastro-esophageal Cancer PDXs

  The dataset includes 51 whole exome sequencing datasets generated using Illumina paired-end sequencing technology. These data derive from 26 patient-derived xenograft (PDX) tumors and their matched normal tissues, which consist of either normal gastric mucosa or blood samples. In one case (GTR0607), the matched normal tissue data are unavailable. As a result, the dataset comprises 102 FASTQ files, providing raw sequencing reads for comprehensive genomic analysis.

  Dataset EGAD50000001407

• RNA-seq of atypical 3q26 samples

  RNA was isolated using phenol-chloroform extraction followed by DNase digestion or using the Qiagen Allprep DNA/RNA kit and protocol (Qiagen, #80204). cDNA synthesis was done using the SuperScript II Reverse Transcriptase kit (Invitrogen). Quantitative real-time PCR was performed by using primers as described previously13,21 on the 7500 Fast Real-time PCR System (Applied Biosystems). Relative levels of gene expression were calculated using the ΔΔCt method

  Dataset EGAD00001006106

• Whole Genome Sequencing of Therapy-Related Myeloid Neoplasms

  The dataset consists of: 51 paired tumor/normal WGS samples (26 tumors and 25 normals), and 13 normal targeted samples.

  Dataset EGAD00001010026

• Single_Cell_Sequencing_of_Sperm__scSperm_

  The aim of this project is to genotype and sequence single spermatozoa from two men, one in his twenties and the other in his seventies. The resulting data is used to quantify the mutations that have arisen in the gametes of both individuals in order to better understand the effect of aging on mutation rates and modes.Project Outline. In order to quantify mutations, semen from two individuals are sequenced. 48 single sperm cells are isolated from each individual, and their DNA is extracted. The resulting genomes are amplified using PicoPlex, GenomiPhi MDA, Repli-G MDA, and MALBAC. QC step is applied to check the quality of WGA DNA using standard Sequenom plex (26 SNPs). A subset of 32 amplification products which pass the intiall QC, are genotyped using Affymetrix SNP6 chips. 12 of the genotyped amplification products are also sequenced. In addition, one multi-cell sample per individual is sequenced as a reference and for validation purposes.Altogether, 12 single cell sperm genomes and two multi-cell genomes are sequenced, coming to a total of 14 genomes. Of the single cell sperm genomes, 2 are sequenced to 50x coverage, and the other 10 to 25x coverage. Both multi-cell genomes are sequenced to 25x coverage.

  Study EGAS00001000935

• Metabolic reprogramming towards OXPHOS identifies a novel therapeutic target for mantle cell lymphoma

  Metabolic reprogramming is linked to cancer cell growth and proliferation, metastasis, and therapeutic resistance in a multitude of cancers. Targeting dysregulated metabolic pathways to overcome resistance, an urgent clinical need in all relapsed/refractory cancers, remains difficult. Through genomics analysis of clinical specimens, we show that metabolic reprogramming towards oxidative phosphorylation (OXPHOS) and glutaminolysis is associated with therapeutic resistance to the Bruton’s tyrosine kinase inhibitor ibrutinib in mantle cell lymphoma (MCL), an incurable B-cell lymphoma with poor clinical outcomes. Inhibition of OXPHOS with a novel, clinically applicable small molecule, IACS-010759, which targets complex I of the mitochondrial electron transport chain, results in significant growth inhibition in vitro and in vivo in ibrutinib-resistant patient-derived cancer models. This work suggests that targeting metabolic pathways to subvert therapeutic resistance is a clinically viable approach to treat highly refractory malignancies.

  Dataset EGAD00001004577

• PATL2 is a key actor of oocyte maturation whose invalidation causes infertility in women and mice

  The genetic causes of oocyte meiotic deficiency (OMD), a form of primary infertility characterised by the production of immature oocytes, remain largely unexplored. Using whole exome sequencing, we found that 26% of a cohort of 23 subjects with OMD harboured the same homozygous nonsense pathogenic mutation in PATL2, a gene encoding a putative RNA-binding protein. Using Patl2 knockout mice, we confirmed that PATL2 deficiency disturbs oocyte maturation, since oocytes and zygotes exhibit morphological and developmental defects respectively. PATL2's amphibian orthologue is involved in the regulation of oocyte mRNA as a partner of CPEB. However, Patl2's expression profile throughout oocyte development in mice, alongside colocalisation experiments with Cpeb1, Msy2 and Ddx6 (three oocyte RNA-regulators) suggest an original role for Patl2 in Mammals. Accordingly, transcriptomic analysis of oocytes from WT and Patl2-/- animals demonstrated that in the absence of Patl2, expression levels of a select number of highly relevant genes involved in oocyte maturation and early embryonic development are deregulated. In conclusion, PATL2 is a novel actor of mammalian oocyte maturation whose invalidation causes OMD in humans.

  Study EGAS00001002903

• EGA QuickView

  EGA QuickView Secure and Remote Access to EGA Files What is EGA QuickView? EGA QuickView is a FUSE file system that allows secure and remote access to EGA files. It is a hybrid of sshfs and crypt4ghfs, which means it uses ssh to connect to the EGA distribution servers, downloads data in Crypt4GH format, and transparently decrypts those files. It is compatible with Linux and macOS 12. Why use EGA QuickView? EGA QuickView is a highly useful and convenient tool for anyone who needs to access EGA files remotely and securely. The software offers a quick and convenient way to browse through EGA files without the need for complete downloads, thus saving bandwidth and time. Whether you are a medical professional requiring access to sensitive patient data or a research scientist working on a project that involves EGA files, EGA QuickView provides a highly useful solution. The software boasts advanced security features, ensuring that your data is safe and protected at all times. Get started with EGA QuickView To get started with EGA QuickView, visit the EGA QuickView GitHub repository for more information and installation instructions.

  Documentation access/download/visualisation/ega-quickview

• Exome-wide mutation analysis of cell-free DNA to simultaneously monitor the full spectrum of cancer treatment outcomes

  Purpose: Cell-free DNA (cfDNA) offers a non-invasive approach to monitor cancer. Here we develop a method using whole-exome sequencing (WES) of cfDNA for simultaneously monitoring the full spectrum of cancer treatment outcomes, including MRD, recurrence, evolution, and second primary cancers. Experimental Design: Three simulation datasets were generated from 26 cancer patients to benchmark the detection performance of MRD/recurrence and second primary cancers. For further validation, cfDNA samples (n=76) from cancer patients (n=35) with six different cancer types were used for performance validation during various treatments.Results: We present a cfDNA-based cancer monitoring method, named cfTrack. Taking advantage of the broad genome coverage of WES data, cfTrack can sensitively detect MRD and cancer recurrence by integrating signals across known clonal tumor mutations of a patient. In addition, cfTrack detects tumor evolution and second primary cancers by de novo identifying emerging tumor mutations. A series of machine learning and statistical denoising techniques are applied to enhance the detection power. On the simulation data, cfTrack achieved an average AUC of 99% on the validation dataset and 100% on the independent dataset in detecting recurrence in samples with tumor fraction ≥0.05%. In addition, cfTrack yielded an average AUC of 88% in detecting second primary cancers in samples with tumor fraction ≥0.2%. On real data, cfTrack accurately monitors tumor evolution during treatment, which cannot be accomplished by previous methods.Conclusion: Our results demonstrated that cfTrack can sensitively and specifically monitor the full spectrum of cancer treatment outcomes using exome-wide mutation analysis of cfDNA.

  Study EGAS00001005906

• Identification of putative multiple myeloma (MM) susceptibility genes

  We sought to identify novel MM susceptibility genes using a collection of families with multiple cases of MM/MGUS, including 189 affected individuals from 40 families, and index cases from an additional 88 families, along with 170 early-onset (EO) MM cases (≤ 55 years). We analyzed a total of 347 affected individuals using whole exome (N=321) and whole genome (N=26) sequencing. Samples were identified and collected through nation-wide efforts in France, Sweden and Greece. We focused on rare (MAF<0.5%) germline protein truncating and likely deleterious missense variants in genes harboring variants in at least two families showing variant-disease segregation, and in additional index (≥2) and/or early-onset (≥2) cases.

  Study EGAS50000001259

• Tissue Site

  Tissue site for RNAsequencing data. Tissue site is associated with the clinical biomarker data and be linked to the biomarker data using the SAMPLE and PAT identifiers.

  Dataset EGAD50000000931

• Sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC)

  In 2016 we established the Sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC) funded by the Ice Bucket Challenge Grant administered by the Motor Neurone Disease Research Institute of Australia. The goals of the SALSA-SGC are to collect biological samples from clinics across Australia with matched in depth clinical and self-report phenotypes and to generate multiple levels of genetic and genomic data. In this first data generation exercise of the SALSA-SGC the majority of the samples were collected prior to the formal establishment of SALSA-SGC from clinics across Australia.Briefly, the cohort includes the University of Sydney&#8217;s Australian Motor Neuron Disease DNA Bank (MND Bank) cohort recruited April 2000 to June 2011), with study protocol approved by the Sydney South West Area Health Service Human Research Ethics Committee (HREC). Cases were recruited from around Australia via state-based MND associations with diagnosis verified by a neurologist. The remainder of the cases were recruited from clinics across Australia between 2015 and 2017 under HREC approvals from Royal Brisbane and Women&#8217;s Hospital, Macquarie University Multidisciplinary Motor Neurone Disease Clinic,&nbsp; Calvary Health Care Bethlehem in Melbourne , Fiona Stanley Hospital in Perth, and from 2016 under HREC approvals at each site for the sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC). The ALS cases were diagnosed with definite or probable ALS according to the revised El Escorial criteria. Some controls were recruited as either partners or friends of patients, healthy individuals free of neuromuscular diseases. We are providing GWAS and MWAS data in this dataset. Individual level GWAS data were generated using Illumina Infinium CoreExome-24 version 1.1 chips for N= 846 cases and N=665 controls. Individual MWAS data was generated using the Illumina Human methylation 450K array for N=782 cases and N=613 controls. There 1315 individuals where GWAS and MWAS data has been generated and is available. Further information on these data sets can be found: Paper 1: Restuadi, R, Garton, FC, Benyamin, B, Lin, T, et al. Amyotrophic Lateral Sclerosis Genetic Correlation with Cognitive Performance, educational attainment and schizophrenia: evidence from polygenic risk score analysis. (submitted) Paper 2: Nabais, MF, Lin, T, Benyamin, B et al. Significant out-of-sample classification from methylation profile scoring for amyotrophic lateral sclerosis. 2020. NPJ genomic medicine. 5(10). Files provided in this submission include: GWAS: This folder contains QCed genotype for the Australian ALS case-control cohort. Contains PLINK files for genotyping data (not imputed yet). The individuals selected here have: good consistency on phenotype data ethics approval registered as part of sporadic ALS studies unrelated by GRM cut-off 0.05 No ancestry QC yet MWAS: This folder contains the IDAT and post-QC normalized DNAm (beta) for the Australian ALS case-control cohort. 2019_AUS_ALS_PCTG_DNAm.tar.gz - IDATS for 1315 individuals analyzed in the MWAS study normalized_beta_values - Binary files (created with the OSCA software) containing information on the individuals, probes and the DNAm (beta) values obtained after QC phenotype_file - contains all the covariates analysed in the MWAS including: case-control status, coded 0 = Control and 1 = ALS, predicted age, predicted cell-type proportions, predicted smoking scores, slide and chip position and sex Important Notes: The DNAm data were normalized together with samples that were not part of this ALS case/control study and thus, the normalization procedure may not be 100% reproducible using only the IDAT files uploaded here. Summary data has been made publicly available and can be accessed directly: Data collection and sample processing were performed at several clinics across Australia. Genotyping and DNA methylation arrays were performed by the Human Studies Unit, at the Institute for Molecular Bioscience (University of Queensland). Quality control of the genotypic, phenotypic and DNA methylation data was done by the Program of Complex Traits Genomics, at the Institute for Molecular Bioscience (University of Queensland).

  Study phs002068

• Single cell RNA sequencing data of advanced melanoma patients treated with checkpoint inhibitor immunotherapy

  Single cell RNA libraries were prepared using 10x Genomics Chromium Next GEM Single Cell 3’ v2 reagents. The samples were barcoded and each library were pooled with two samples at equimolar concentrations. The pooled libraries (n=4) were sequenced on the NextSeq 500 machine (Illumina) with paired-end sequencing and dual indexing as recommended in the manufacturer’s protocol; 26 and 98 cycles for the respective Read 1 and 2, and 8 cycles for i7 index.

  Dataset EGAD50000000493

• Pancreatic, Small-intestinal and Pulmonary Neuroendocrine Tumors

  Purpose: The primary origin of neuroendocrine tumor metastases can be difficult to determine by histopathology alone, but is critical for therapeutic decision making. DNA methylation-based profiling is now routinely used in the diagnostic workup of brain tumors. This has been enabled by the availability of cost-efficient array-based platforms. We have extended these efforts to augment histopathological diagnosis in neuroendocrine tumors. Experimental Design and Results: We compiled data of 69 small-intestinal, pulmonary, and pancreatic neuroendocrine tumors. These data were used to build a ridge regression calibrated random forest classification algorithm (NEN-ID) that predicts the origin of tumor samples with high accuracy (&amp;gt; 95%). The model was validated during 3x3 nested cross validation and tested in a local (n=26) and external (n=172) cohort. In addition, we show that our diagnostic approach is robust across a range of possible confounding experimental parameters such as tumor purity and array quality. A software infrastructure and online user interface was built to make the model available to the scientific community. Conclusions: This DNA methylation-based prediction model can be used in the workup for patients with neuroendocrine tumors of unknown primary. To facilitate validation and clinical implementation, we provide a user-friendly, publicly available web-based version of NEN-ID.

  Study EGAS00001004878

• The Mutational Landscape of CTCL and Sezary Syndrome

  Sezary syndrome is a leukemic and aggressive form of cutaneous T-cell lymphoma (CTCL) resulting from the malignant transformation of skin-homing central memory CD4+ T cells. To identify new genetic alterations involved in Sezary syndrome and CTCL transformation we performed whole-exome sequencing of tumor-normal sample pairs from 26 Sezary syndrome and 16 CTCL patients. These analyses revealed a distinctive pattern of somatic copy number alterations in Sezary syndrome including highly prevalent recurrent chromosomal deletions involving the TP53, RB1, PTEN, DNMT3A, and CDKN1B tumor suppressor genes. Mutation analysis identified a broad spectrum of somatic mutations involving key genes involved in epigenetic regulation (TET2, CREBBP, MLL3, BRD9, SMARCA4 and CHD3) and signaling, including mutations in MAPK1, BRAF, CARD11 and PRKG1 driving increased MAPK, NFKB and NFAT activity upon T-cell receptor stimulation. Collectively, our findings provide new insights into the genetics of Sezary syndrome and CTCL and support the development of personalized therapies targeting key oncogenically activated signaling pathways for the treatment of these diseases.

  Study phs000994

• Molecular stratification of endometrioid ovarian carcinoma predicts clinical outcome

  Endometrioid ovarian carcinoma (EnOC) is an under-investigated type of ovarian carcinoma. Here, we report the largest genomic study of EnOCs to date, performing whole exome sequencing of 112 cases following rigorous pathological assessment. High frequencies of mutation were detected in CTNNB1(43%), PIK3CA(43%), ARID1A(36%), PTEN(29%), TP53(26%) and SOX8(19%), a novel target of recurrent mutation in EnOC. POLE and mismatch repair protein-encoding genes were mutated at lower frequency (6%, 18%) with significant co-occurrence. A molecular taxonomy was constructed using a novel algorithm (PRISTINE), identifying clinically distinct EnOC subtypes: TP53m cases demonstrated greater genomic complexity, were frequently FIGO stage III/IV at diagnosis (48%) and incompletely debulked (44%), and demonstrated inferior survival; conversely, CTNNB1m cases demonstrated low complexity and excellent clinical outcome, were predominantly stage I/II at diagnosis (89%) and completely resected (87%). Tumour complexity provides further resolution within the TP53wt/CTNNB1wt group. Moreover, we identify the WNT, MAPK/RAS and PI3K pathways as good candidate targets for molecular therapeutics in EnOC.

  Study EGAS00001004366

• A dataset compiled as a resource a for orthogonal assessment of exon CNV calling in NGS data

  The dataset includes high-quality sequencing data from a targeted NGS assay (the TruSight Cancer Panel) together with Multiplex Ligation-dependent Probe Amplification (MLPA) results for 96 independent samples. 66 samples contain at least one validated exon CNV and 30 samples have validated negative results for exon CNVs in 26 genes. The dataset includes 46 exon CNVs in BRCA1, BRCA2, TP53, MLH1, MSH2, MSH6, PMS2, EPCAM and PTEN, giving excellent representation of the cancer predisposition genes most frequently tested in clinical practice. Moreover, the validated exon CNVs include 25 single exon CNVs the most difficult exon CNV to detect. The full dataset includes FASTQ files, target BED file, and MLPA results.

  Study EGAS00001002428

• Mitochondrial DNA sequencing of iPSC, parental cells, and iPSC derived cardiomyocytes

  The aim of this work was to analyze to which extent mitochondrial DNA (mtDNA) variants in human induced pluripotent stem cells (iPSC) originate from their parental cells or from de novo mutagenesis, and whether dynamics in variant heteroplasmy levels during prolonged expansion culture of iPSC are caused by inter- or intra-cellular selection or genetic drift. Hence, mtDNA of 26 early passage iPSC clones from, in total, 10 donors and the corresponding parental cell populations (here endothelial cells) were sequenced. Furthermore, 7 iPSC clones were expanded up to passage 50 and the change in variant heteroplasmy levels was monitored. Lastly, the effect of differentiation on the variant heteroplasmy levels was investigated during directed cardiomyocyte differentiation of 4 iPSC clones.

  Study EGAS00001005560

• Synergy study: "Tissue resident CD8+ T cell clonal expansion in advanced triple negative breast cancer is associated with response to chemoimmunotherapy"

  Dataset of 10x Genomics 5'prime single-cell RNA sequencing of 40 tumor biopsy samples or triple negative breast cancer. Samples are taken before and after immuno checkpoint blockade treatment. Processed according the 10X genomics protocol, sequenced on Immumina NovaSeq6000. Raw sequencing reads are further processed with Cellranger 3.0 to get gene-expression matrices.

  Study EGAS50000000527

• MicroRNAs, Hypertension and End Organ Damage in Humans

  Study 1) Profiling of microRNAs in plasma of patients with hypertension complicated or not by metabolic syndrome or chronic kidney disease Hypertension (HTN) or high blood pressure is associated with subclinical target organ damage such as cardiac, vascular and kidney injury, which may lead to complications and death. In this study, we investigated circulating microRNAs as biomarkers of target organ damage in HTN patients. We profiled circulating microRNAs by RNA sequencing in platelet-poor plasma of normotensive subjects and patients with HTN complicated or not by metabolic syndrome (MetS) or chronic kidney disease (CKD) (n=15 each group). Differentially expressed microRNAs were identified with a threshold of false discovery rate &lt;0.1. Differentially expressed microRNAs were identified uniquely to associate with HTN (8), MetS (1) or CKD (13), and 8 were similarly differentially expressed in different groups. This study identified the association of differentially expressed circulating microRNAs with target organ damage in HTN patients, which could have some pathophysiological and therapeutic implications. Study 2) Profiling of microRNAs in gluteal subcutaneous small arteries of patients with hypertension complicated or not by chronic kidney disease Hypertension (HTN) is associated with vascular damage characterized by endothelial dysfunction and vascular remodeling and stiffening, which contributes to kidney injury leading to chronic kidney disease (CKD). MicroRNAs are short non-coding RNAs which repress/degrade target mRNAs. The microRNA role in vascular injury in HTN remains unclear. In this study, we aimed to identify differentially expressed microRNAs in small arteries of patients with HTN associated or not with CKD, in order to shed light on the pathophysiological molecular mechanisms. Normotensive subjects and HTN patients associated or not with CKD grades 3-4 were studied (n=15-16). Small arteries were isolated from subcutaneous gluteal biopsies, RNAs were extracted, and small and total RNA sequencing was performed by Illumina HiSeq-2500. Differentially expressed genes were identified with a P&lt;0.05 and fold change (FC) &gt;1.3. Differentially expressed microRNAs and mRNAs were identified uniquely to associate with HTN (microRNAs: 10, mRNAs: 68), CKD (microRNAs: 68, mRNAs: 395), and both groups (microRNAs: 2, mRNAs: 32). This study identified differentially expressed microRNAs and mRNAs in small arteries with target organ damage in HTN, which could have some pathophysiological and therapeutic implications.

  Study phs002389

• DNA methylation database for gynecological cancer detection, classification and assay development

  MeD-seq data (fastq files) from gynecological cancers and associated healthy tissues. In total 292 fastq files generated by MeD-seq are deposited consisting of: healthy tissues (vulva n=11, cervix n=15, endometrium n=13, fallopian tube n=18 and ovary n=13), precursor lesions of cancer (vulva n=23 and cervix n=46) and cancer (vulva n=21, cervix n=45, endometrium n=26, fallopian tube n=8 and ovary n=33)

  Dataset EGAD50000000611

• Regulatory T cell transcriptomic reprogramming characterizes adverse events by checkpoint inhibitors in solid tumors

  Tregs were sorted as CD4+CD25+CD127- cells from peripheral blood of patients with advanced metastatic melanoma, stage III(B-D)-IV, who were receiving treatment with anti-PD1 (n =26); and patients with kidney, non-small cell lung, liver and bladder cancer who were receiving treatment with anti-PD1. RNA was extracted and polyA libraries were prepared using the Illumina Truseq sample preparation kit v.2. Single-end sequencing was performed on NextSeq500.

  Dataset EGAD00001006415

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

  ChIP-Seq data for 4 band form neutrophil sample(s). 26 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 EGAD00001002454

• Mitochondrial DNA sequencing of human iPSC, parental cells, and iPSC derived cardiomyocytes

  Dataset contains whole mitochondrial DNA sequencing data in fastq format (Illumina MiSeq paired-end) of 62 samples, in total. Those samples include sequencing data of the endothelial cell populations of 10 different donors and of 26 early-passage iPSC clones derived thereof. Moreover, the dataset contains the data of 7 of those iPSC clones sequenced additionally in passage 30 and 50, each. Lastly, 4 iPSC clones were sequenced during directed cardiomyocyte differentiation, each at day 0, 5, and 15 of differentiation.

  Dataset EGAD00001008021

• PyEGA3 download client

  PyEGA3 Checks prior to download - Is the dataset available for download? Most datasets are available using the PyEGA3 Download client, except for specific legacy datasets. For these ones, refer to Live Outbox distribution, an alternative way to download these datasets.If the dataset you've been granted access to begins with the ID EGAD5XXXXXXX, please refer to the Live Outbox distribution. If the dataset you have been granted access to contains encrypted data (filename ending in .gpg), contact EGA Helpdesk for detailed information on how to download these files.General Information The PyEGA3 download client is available at its GitHub repository. In its README you will find a step by step guide on how to use it to download files you have been granted access to. PyEGA3 implements the GA4GH-compliant HTSGET protocol supporting requests over genomic ranges. This enables the download of specific regions of interest rather than the entire file. HTSGET is not possible for all the files held by EGA: if the dataset does not contain index files (e.g. filename ending in *.crai), then genomic range requests cannot be performed. The maximum number of connections allowed is 30. If more than 30 connections are used, the download client will encounter 500 errors. The recommended number of connections for maximum output is one. Check out our video tutorial! Frequently Asked Questions General questions How do I download the datasets to which I have been granted access? After setting up your EGA download account, you can proceed to download using the EGA download client – PyEGA3. The pyEGA3 download client is a python-based tool for viewing and downloading files from authorised EGA datasets. This download client is continuously being developed for more user-friendly download experiences. Can I download the dataset’s metadata via the download client? No, the download client cannot be used to download metadata. Registered EGA users can download metadata of an authorised dataset by logging into the EGA webpage and navigating to the dataset of choice. Approximately two thirds down the page you will find the option to download the metadata as a zip file. How do I download large datasets as quickly as possible? The main EGA download client is pyEGA3 download client, a python-based tool for viewing and downloading files from authorised EGA datasets.We could exceptionally consider the option of an Aspera download for users experiencing very slow download rates or facing particular issues.Contact the EGA Helpdesk for further information. Pre-requirement and Installation What are the major requirements for the PyEGA3 download client installation and usage? The PyEGA3 client is compatible with any OS with Python 3.6+ installed. The client requires a connection to the internet, sufficient space on the destination drive, and the EGA download account credentials. Where can I find the PyEGA3 download client installation and download instructions? We strongly recommend checking our video tutorial demonstrating the usage of PyEGA3 from installation to file download. More detailed information is available at PyEGA3 GitHub. What ports are required for the PyEGA3 download client to function? PyEGA3 makes HTTPS calls to the EGA Data API (https://ega.ebi.ac.uk:8443). This port 8443 must be reachable from the location where PyEGA3 is executed to avoid timeouts. PyEGA3 download client How to update the PyEGA3 download client to be on the latest version? Updating the client to the latest version can be achieved by running the following command: pip3 install pyega3 --upgrade I do not have an active EGA account. Can I test the download with the PyEGA3 download client? An EGA download test account (ega-test-data@ebi.ac.uk) has been created for troubleshooting and training purposes. The test account does not require an EGA username and password because it contains publicly accessible files from the 1000 Genomes Project. More information about the use of this account and log in details are available at pyEGA3. I lost my connection while the download was in progress. Does this mean that I have to download the file again from the start? The PyEGA3 download client supports automatic resumption of downloads. To enable quicker download speeds, the API breaks files into up to four segments and downloads them in parallel. With the resume feature, downloads will automatically resume if you encounter any errors or if the connection is interrupted. How can I improve the overall download speed of the PyEGA3 download client? Download speeds can be optimised using the --connections parameter which will parallelise download at the file level. If the --connections parameter is provided, all files >100Mb will be downloaded using the specified number of parallel connections. It is important to note that files are still downloaded sequentially, so using multiple connections does not mean downloading multiple files in parallel. The maximum number of connections allowed is 30. If more than 30 connections are used, the download client will encounter 500 errors. The recommended number of connections for maximum output is one. Why is my file taking a long time to be saved? Please note that when a file is being saved, it goes through two processes. First, the downloaded file "chunks" are pieced back together to reconstruct the original file. Secondly, PyEGA3 calculates the checksum of the file to confirm that the file was downloaded successfully. Larger files will take more time to reconstruct and validate the checksum. Why is the HTSGET protocol not working with my dataset of interest? PyEGA3 implements the GA4GH-compliant htsget protocol for supporting requests over genomic ranges. This exciting new feature means that for data files with accompanying index files (e.g. .crai for CRAM files) users can download specific regions of interest rather than the entire file, saving both time and storage space. Please note that in order for the genomic range requests to work for a BAM, CRAM or VCF file there must be an associated BAI, CRAI or TBI file, respectively. If the dataset does not contain these index files then genomic range requests cannot be performed. After download Do I need to decrypt data files downloaded through the pyEGA3 download client? Files are transferred over secure HTTPS connections and received unencrypted, thus there is no need for decryption after data download. What is the purpose of an MD5 file? After the download completes, file integrity is verified using checksums. The PyEGA3 download client automatically verifies each file’s unencrypted md5 after download to ensure that the file was downloaded correctly from the EGA. Errors Why do I get a “400 Client Error” while trying to access the download client? Ensure that your credentials are formatted correctly. Please contact the EGA Helpdesk if you are unsure about your account’s username (i.e. your email address). Why do I get a “500 Server Error”? It is important to note that files are still downloaded sequentially, so using multiple connections does not mean downloading multiple files in parallel. The maximum number of connections allowed is 30. If more than 30 connections are used, the download client will encounter 500 errors. The recommended number of connections for maximum output is one. Otherwise, 500 server errors are internal server errors from EGA’s end. Retry after some time and, if the 500 error persists: check our homepage or Twitter for any outage information or report it to EGA Helpdesk. Why do I get a “slice error”? This type of error occurs when one slice download was prematurely interrupted. Please re-start the same download. The download client will pick up any partial download and download any missing slices. Why do I get the error “Dataset' EGADXXXXXXXXXXX' is not in the list of your authorised datasets”? Please note that the data access was given to the email (username) provided to the Data Access Committee (DAC) in your official request. Therefore, you shall check that the account that you are using is the same one that you sent to the DAC. Why do I get “ERROR:root:Failed to obtain IP address”? This might mean that the connection ports are blocked. Check that the port 8443 is reachable.In case the port is reachable and the error persists, please try to modify the file pyega3.py on line 44 in the python module installation: Replace endpoint = 'https://ipinfo.io/json' with endpoint = 'https://api.myip.com' Why do I get the error “Invalid username, password or secret key - please check and retry”? Make sure that you are using the correct credentials (username and password) and there is no typo. Contact EGA Helpdesk if the problem persists.

  Documentation access/download/files/pyega3

• Single Cell Sequencing of Sperm (scSperm)

  The aim of this project is to genotype and sequence single spermatozoa from two men, one in his twenties and the other in his seventies. The resulting data is used to quantify the mutations that have arisen in the gametes of both individuals in order to better understand the effect of aging on mutation rates and modes.Project Outline. In order to quantify mutations, semen from two individuals are sequenced. 48 single sperm cells are isolated from each individual, and their DNA is extracted. The resulting genomes are amplified using PicoPlex, GenomiPhi MDA, Repli-G MDA, and MALBAC. QC step is applied to check the quality of WGA DNA using standard Sequenom plex (26 SNPs). A subset of 32 amplification products which pass the intiall QC, are genotyped using Affymetrix SNP6 chips. 12 of the genotyped amplification products are also sequenced. In addition, one multi-cell sample per individual is sequenced as a reference and for validation purposes.Altogether, 12 single cell sperm genomes and two multi-cell genomes are sequenced, coming to a total of 14 genomes. Of the single cell sperm genomes, 2 are sequenced to 50x coverage, and the other 10 to 25x coverage. Both multi-cell genomes are sequenced to 25x coverage.

  Dataset EGAD00001001216

• Integrating molecular imaging and transcriptomic profiling in advanced HER2-positive breast cancer receiving trastuzumab emtansine (T-DM1): an analysis of the ZEPHIR clinical trial

  Purpose: The ZEPHIR clinical trial evaluated the role of [89Zr]trastuzumab-PET/CT (HER2-PET/CT) and 2-[18F]fluoro-2-deoxy-D-glucose PET/CT ([18F]FDG-PET/CT) in predicting outcomes in patients with advanced HER2-positive breast cancer treated with trastuzumab emtansine (T-DM1). Here, we combined molecular/metabolic imaging and transcriptomic data to investigate the biological processes associated with [89Zr]trastuzumab and [18F]FDG uptake, and to dissect the mechanisms involved in T-DM1 resistance. Experimental design: RNA was extracted from metastasis biopsies obtained at study inclusion in the ZEPHIR trial. HER2-PET/CT and [18F]FDG-PET/CT imaging data of biopsied lesions were integrated with RNA sequencing data. Lesions were compared based on the level of [89Zr]trastuzumab uptake (dichotomized into high/low classes) as well as on the presence/absence of metabolic response, defined comparing baseline and on-treatment [18F]FDG-PET/CT. Results: We analyzed matched transcriptomic and molecular/metabolic imaging data for 24 metastases (one lesion/patient). Pathways involved in extracellular matrix (ECM) organization, glycosylphosphatidylinositol synthesis, and collagen formation were enriched in lesions presenting low [89Zr]trastuzumab uptake. [18F]FDG uptake at baseline correlated with proliferation and immune-related processes. Hypoxia and ECM-related processes were enriched in lesions that showed no metabolic response to T-DM1. Interestingly, immune-related processes (e.g., Fc gamma receptor activation, complement cascade) were associated with high [89Zr]trastuzumab uptake and metabolic response. Conclusions: To our knowledge, this study represents the first correlative analysis between [89Zr]trastuzumab tumor uptake and gene expression profiling in humans. Our findings point toward a role of ECM in impairing [89Zr]trastuzumab tumor uptake and T-DM1 metabolic response in advanced HER2-positive breast cancer, and highlight the potential of molecular imaging to depict tumor microenvironment features.

  Study EGAS50000000470

• 86 paired-end MiSeq 16S rRNA sequencing samples

  We compared bacterial communities in breast milk from teen (≤19 yr, n = 26) vs. adult (&gt;19 yr, n = 56) mothers, normal weight (BMI 18.5-24.9, n = 63) vs. overweight (BMI ≥ 25, n = 19) mothers, primiparous (parity = 1, n = 41) vs. multiparous (parity &gt; 1, n = 44), early (5-46d postpartum, n = 39) vs. established lactation (4-6 mo postpartum, n = 45), breastfeeding (EBF: PBF, n = 72) vs. mixed feeding (n = 11) and mothers with (Na/K ratio &lt; 0.6, n = 75) and without SCM (Na/K ration ≥ 0.6, n = 10).

  Dataset EGAD00001004160

• Pediatric Whole Genome Sequencing Diagnostic Utility

  The standard of care for first-tier clinical investigation of the etiology of congenital malformations and neurodevelopmental disorders is chromosome microarray analysis (CMA) for copy number variations (CNVs), often followed by gene(s)-specific sequencing searching for smaller insertion-deletions (indels) and single nucleotide variant (SNV) mutations. We compared diagnostic rate of WGS to CMA and targeted gene testing of 100 patients referred to The Hospital for Sick Children Genetics clinic in 2014. WGS identified genetic variants meeting clinical diagnostic criteria in 34% of cases, representing a 4-fold increase in diagnostic rate over CMA (8%) (p-value = 1.42e-05) alone and &gt;2-fold increase in CMA plus targeted gene sequencing (13%) (p-value = 0.0009). WGS identified all rare clinically significant CNVs that were detected by CMA. In an additional 26 patients, WGS revealed indel and missense mutations presenting in a dominant (63%) or a recessive (37%) manner. We found four subjects with mutations in at least two genes associated with distinct genetic disorders, including two cases harboring a pathogenic CNV and SNV. When considering medically actionable secondary findings in addition to primary WGS findings, 38% of patients would benefit from genetic counselling.

  Study EGAS00001001623

• OpACIN-neo – A Multicenter Phase 2 Study to identify the Optimal neo-Adjuvant Combination scheme of Ipilimumab and Nivolumab – Whole exome sequencing

  The outcome of patients with macroscopic stage III melanoma is poor. Neoadjuvant treatment with ipilimumab plus nivolumab at the standard dosing schedule induced pathological responses in a high proportion of patients in two small independent early-phase trials. However, toxicity of the standard ipilimumab plus nivolumab dosing schedule was high, preventing its broader clinical use. The aim of the OpACIN-neo study (NCT02977052) to identify a dosing schedule of ipilimumab plus nivolumab that is less toxic but equally effective. 86 patients with macroscopic stage III melanoma were randomised to one of three dosing schedules: arm A, two cycles of ipilimumab 3 mg/kg plus nivolumab 1 mg/kg once every 3 weeks; arm B, two cycles of ipilimumab 1 mg/kg plus nivolumab 3 mg/kg once every 3 weeks; or arm C, two cycles of ipilimumab 3 mg/kg once every 3 weeks directly followed by two cycles of nivolumab 3mg/kg once every 2 weeks. Within the first 12 weeks, grade 3–4 immune-related adverse events were observed in 12 (40%) of 30 patients in group A, six (20%) of 30 in group B, and 13 (50%) of 26 in group C. Pathological responses occurred in 24 (80%) patients in group A, 23 (77%) in group B, and 17 (65%) in group C. The 2-year estimated relapse-free survival was 84% for all patients, 97% for patients achieving a pathologic response and 36% for nonresponders (p&lt;0.001). High tumor mutational burden (TMB) and high interferon-gamma-related gene expression signature score (IFN-γ score) were associated with pathologic response and low risk of relapse; pathologic response rate (pRR) was 100% in patients with high IFN-γ score/high TMB, patients with high IFN-γ score/low TMB or low IFN-γ score/high TMB had pRRs of 91% and 88%; while patients with low IFN-γ score/low TMB had a pRR of only 39%. These data demonstrate long-term benefit in patients with a pathologic response and show the predictive potential of TMB and IFN-γ score.

  Study EGAS00001004832

• OpACIN-neo – A Multicenter Phase 2 Study to identify the Optimal neo-Adjuvant Combination scheme of Ipilimumab and Nivolumab – RNA sequencing

  The outcome of patients with macroscopic stage III melanoma is poor. Neoadjuvant treatment with ipilimumab plus nivolumab at the standard dosing schedule induced pathological responses in a high proportion of patients in two small independent early-phase trials. However, toxicity of the standard ipilimumab plus nivolumab dosing schedule was high, preventing its broader clinical use. The aim of the OpACIN-neo study (NCT02977052) to identify a dosing schedule of ipilimumab plus nivolumab that is less toxic but equally effective. 86 patients with macroscopic stage III melanoma were randomised to one of three dosing schedules: arm A, two cycles of ipilimumab 3 mg/kg plus nivolumab 1 mg/kg once every 3 weeks; arm B, two cycles of ipilimumab 1 mg/kg plus nivolumab 3 mg/kg once every 3 weeks; or arm C, two cycles of ipilimumab 3 mg/kg once every 3 weeks directly followed by two cycles of nivolumab 3mg/kg once every 2 weeks. Within the first 12 weeks, grade 3–4 immune-related adverse events were observed in 12 (40%) of 30 patients in group A, six (20%) of 30 in group B, and 13 (50%) of 26 in group C. Pathological responses occurred in 24 (80%) patients in group A, 23 (77%) in group B, and 17 (65%) in group C. The 2-year estimated relapse-free survival was 84% for all patients, 97% for patients achieving a pathologic response and 36% for nonresponders (p&lt;0.001). High tumor mutational burden (TMB) and high interferon-gamma-related gene expression signature score (IFN-γ score) were associated with pathologic response and low risk of relapse; pathologic response rate (pRR) was 100% in patients with high IFN-γ score/high TMB, patients with high IFN-γ score/low TMB or low IFN-γ score/high TMB had pRRs of 91% and 88%; while patients with low IFN-γ score/low TMB had a pRR of only 39%. These data demonstrate long-term benefit in patients with a pathologic response and show the predictive potential of TMB and IFN-γ score.

  Study EGAS00001004833

• Circumventing intratumoral heterogeneity to identify potential therapeutic targets in hepatocellular carcinoma. Details please contact lifuqiang@genomics and zhaoxin@genomics.cn.

  Background and aims: Intratumoral heterogeneity (ITH) challenges identifying mutations with target therapy potential whereas circulating cell-free DNAs (cfDNAs) could reflect nearly the entire mutation spectrum in given tumors. We investigated how to minimize the limit of ITH for profiling hepatocellular carcinoma (HCC).Methods: Thirty-two multi-regional HCC samples from five patients were subjected to whole exome sequencing (WES) and targeted deep sequencing (TDS). ITH extent was measured by the average percentage of non-ubiquitous mutations (present in parts of tumor regions). Matched cfDNAs were also analyzed by WES and TDS. Profiling efficiencies of single tumor specimen and cfDNA were compared and the one better depicted mutational landscape was selected to screen therapeutic targets.Results: We found variable extents of ITH in HCCs and observed branched and parallel evolution patterns. ITH level decreased at higher sequencing depth of TDS than that measured by WES (28.1% vs 34.9%, P &lt; 0.01) but it remained unchanged upon additional samples analyzed. TDS of single tumor specimen detected an average of 70% the total mutations in HCC. Although more mutations were detected in cfDNA under TDS than WES, an average of 47.2% total HCC mutations uncovered by cfDNA suggested tissue outperform cfDNA and the latter may serve as alternative in profiling HCC genome. Consequently, TDS of single tumor tissue in 66 patients and cfDNAs in four unresectable HCCs identified 38.6% (26/66 and 1/4) patients bearing therapeutic targets.Conclusions: TDS of single tumor specimen could largely circumvent ITH to uncover mutations indicative of target therapy in HCC.

  Study EGAS00001002207

• Validation of a Haloplex platform for targeted re-sequencing of the exons of 25 genes

  We recently used the Agilent SureSelect platform to re-sequence a set of genes known to be mutated in human AML. The results from 10 AML DNA samples were very satisfactory, but the effort required was significant. Thus, we decided to re-sequence the same genes using the Haloplax system for target enrichment in 48 AML samples. We planned to do this using MiSeq and have data from a pilot of 3 samples. The data is promising but coverage appears pathcy so far. However, in order to get a better understanding of the data we will need deeper sequencing. We will need two lanes of HiSeq to get the same degree coverage as Sureselect. his 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 EGAD00001000603

• single cell RNA-seq of peripheral blood from analysis in infants with MLL-rearranged Acute Lymphoblastic Leukemia

  This dataset contains two experiments. 1) Single cell RNA-seq of peripheral blood diagnostic samples from patients with MLL-rearranged infant ALL that underwent relapse or not (samples ending in R relapsed, samples ending in N did not), sequenced with SORT-seq (see cell systems, 2016, doi:10.1016/j.cels.2016.09.002). For some of the patients, multiple indipendent plates were produced (each plate is a sample). Barcode-well correspondence can be found here: https://bitbucket.org/princessmaximacenter/sharq/src/master/data/celseq2_bc384-v4.csv . 2) Single cell RNA-seq of peripheral blood diagnostic samples from patients with MLL-rearranged infant ALL that underwent relapse or not (samples ending in R relapsed, samples ending in N did not), sequenced with10x Genomics Version 2.

  Dataset EGAD00001007752

• Germline RUNX1 Variation and Predisposition to Childhood Acute Lymphoblastic

  Somatic mutations of RUNX1, which encodes the myeloid and lymphoid transcriptional factor RUNX1, are common in both B- and T- acute lymphoid leukemia (ALL) and are associated with poor prognosis of T-ALL. However, there has been no comprehensive investigation of the pattern or prevalence of RUNX1 germline mutation in both B- and T-ALL. Here we report germline RUNX1 variants in 1.23% of B-ALL and 2.11% of T-ALL, identifying 31 unique variants in 62 B-ALL and 18 unique variants in 26 T-ALL children. The majority of frameshift and nonsense variants affected RUNX1 function in transcriptional regulation, hematopoiesis, and cellular proliferation. We identified JAK3 as the most frequent somatic mutation in T-ALL with RUNX1 variants. These results not only identify RUNX1 as a leukemia predisposition gene but also further underline the importance of germline genetic variants to the development of ALL

  Study EGAS00001005403

• Test Study for EGA using data from 1000 Genomes Project - Phase 3

  The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes &gt;99% of SNP variants with a frequency of &gt;1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies...

  Study EGAS00001005042

• CSF and PBMC scRNAseq RRMS patients at diagnostic n=5

  To get insights about immune cells infiltrating cells the CSF of RRMS patients (n=5), we proceed to 10X scRNAseq of paired CSF and blood circulating cells (about 20000 cells each) sampled at diagnostic.

  Study EGAS50000000308

• ucfDNA workflows for molecular profiling of malignant disease

  Urinary cell-free DNA (ucfDNA) is a promising liquid biopsy analyte obtained by a non-invasive sampling method, particularly valuable in urological cancers due to the proximity of biofluids to the tumor site. However, extremely high fragmentation and low abundance of ucfDNA pose significant analytical challenges. Improper handling and storage can severely affect ucfDNA quality, necessitating optimized pre-analytical workflows for clinical applications. We evaluated multiple pre-analytical workflows, including urine stabilization approaches against unstabilized urine samples. Our results demonstrated that without stabilization, ucfDNA degraded rapidly and minimal quantities remaining after 72 hours. In contrast, urine stabilization preserved ucfDNA integrity, enabling successful downstream analyses, including digital PCR and next-generation sequencing, for mutation detection in cancer-related genes and genome wide copy number profiling. These findings underscore the critical role of stabilization for a reliable ucfDNA analysis and highlight its potential in molecular diagnostics as a complementary tool to plasma-based liquid biopsies.

  Study EGAS50000001093

• JMML targeted sequencing (2013)

  Juvenile myelomonocytic leukemia (JMML) is a rare myelodysplastic myeloproliferative neoplasm of early childhood initiated by germline or somatic RAS-activating mutations (Chang, Dvorak et al. 2014). Clinical evolution is heterogeneous, with acute myeloid leukemia (AML) transformation in 1/3 of cases and frequent relapses after hematopoietic-stem-cell transplantation (HSCT), although some patients experience spontaneous remission (Locatelli, Nollke et al. 2005; Matsuda, Shimada et al. 2007; Takagi, Piao et al. 2013; Locatelli and Niemeyer 2015). The initiating lesion incompletely predicts outcome, suggesting the involvement of additional mutations. Genetic profiling of a large JMML cohort (n=118), including whole-exome sequencing (WES) in 30 cases, uncovered additional genetic abnormalities in 56 cases (47%). Somatic events were rare (0.38/case/Mb) and restricted to sporadic (47/78; 60%) or NF1-associated (8/8; 100%) JMML. Multiple concomitant genetic hits were identified targeting the RAS pathway in 13/78 (17%), RAC2D63V, which activates the PI3K/PDK1/AKT and the mTORC2 pathways, and a novel pathway for JMML, the polycomb repressive complex 2 (PRC2), in 26/78 (33%) of the sporadic JMML cases. Interestingly, PRC2 imbalance was recently shown to synergize with RAS activation (De Raedt, Beert et al. 2014). JMML outcome was associated to the mutational profile, suggesting a dose-dependent effect for RAS-pathway activation, distinguishing very aggressive JMML rapidly progressing to AML.

  Study EGAS00001001324

• Small cell number RNA-seq (400 cells per sample)

  Transcriptional profiles for stemB and proB cells harvested from either primary or secondary xenografts. This dataset contains six types of samples: - diagnostic stemB cells harvested from primary xenografts - diagnostic proB cells harvested from primary xenografts - relapse stemB cells harvested from secondary xenografts injected with stemB cells from primary xenografts - relapse proB cells harvested from secondary xenografts injected with stemB cells from primary xenografts - relapse stemB cells harvested from secondary xenografts injected with proB cells from primary xenografts - relapse proB cells harvested from secondary xenografts injected with proB cells from primary xenografts

  Dataset EGAD50000001830

• Paired-end Whole Exome-seq analysis of the 3D evolution of glioma cell populations. Part 2.

  Dataset contains paired-end Whole Exome sequencing data from 257 glioma samples from 28 patients. 26 normal blood samples are also included.

  Dataset EGAD00001009496

• Genome-wide evaluation of the maturation of the immune response to the tuberculin skin test from day 2 to day 7

  The tuberculin skin test (TST) is a standardised human challenge model to evaluate the immune response to Mycobacterium tuberculosis (Mtb) antigens in vivo. To study the temporal evolution of the TST, we recruited healthy volunteers with evidence of peripheral blood Mtb reactive T cells, to undergo a TST in each arm that was sampled on day 2 at one site and on day 7 at the contralateral site on day 7. Genome-wide TST transcriptomes at day 2 and day 7 were defined by differential gene expression compared to transcriptomes from the site of control saline injections performed in a separate subset of volunteers.

  Study EGAS50000000822

• Genetic Aberrations and Subclonal Structure Impact Chronic Lymphocytic Leukemia

  Large-scale whole-exome sequencing (WES) of primary tumor samples enables the unbiased discovery of recurrent putative driver events and patterns of clonal evolution. We report the identification of 44 recurrently mutated genes and 11 recurrent CNVs through the WES of 538 chronic lymphocytic leukemia (CLL) and matched germline DNAs. These include previously unrecognized cancer drivers (e.g., RPS15, IKZF3), and collectively identify nuclear export, MYC activity and MAPK signaling as central pathways affected by somatic mutation in CLL. A clonality analysis of this large dataset further enabled the reconstruction of temporal relationships between these driver events. Several drivers were associated with shorter progression-free survival (PFS) in 280 samples that were collected prior to uniform treatment with front line chemo-immunotherapy, with mature follow up of greater than 10 years. Direct comparison between matched pretreatment and relapse CLL from 59 samples demonstrated marked clonal evolution occurring in more than 95% of these patients. Distinct patterns of clonal evolution in relationship to specific gene alteration were observed, suggesting a hierarchy of fitness amongst mutations. Thus, large WES datasets of clinically informative samples enable the discovery of novel driver genes as well as the network of relationships between the drivers and their impact on disease relapse and clinical outcome.Additionally, we performed RNA-seq for 268 CLL samples (including 26 follow-up samples) and used them to identify expression subtypes of CLL. RRBS for 30 of these samples was also generated. In an integrative analysis of genetic, transcriptomic, and epigenetic data, incorporating known and newly identified subtypes of CLL, we built new models to improve patient prognostication.

  Study phs000922

• Spatiotemporal Genomic Profiling of Intestinal Metaplasia Reveals Clonal Dynamics of Gastric Cancer Progression

  Intestinal metaplasia (IM) is a pre-malignant condition of the gastric mucosa associated with increased gastric cancer (GC) risk. We analyzed 1256 gastric samples (1152 IMs) from 692 subjects from a 10-year prospective study. We identified 26 IM driver genes in diverse pathways including chromatin regulation (ARID1A) and intestinal homeostasis (SOX9), largely occurring as subclonal events. Analysis of clonal dynamics between and within subjects, and also longitudinally across time, revealed that IM clones are likely transient but increase in size upon progression to dysplasia, with eventual transmission of genetic events to paired GCs. Single-cell and spatial profiling highlighted changes in tissue ecology and lineage heterogeneity in IM, including an intestinal stem-cell dominant cellular compartment linked to early malignancy. Expanded transcriptome profiling revealed expression-based molecular subtypes of IM, including a body-resident “pseudoantralized” subtype associated with incomplete histology, antral/intestinal cell types, ARID1A mutations, inflammation, and microbial communities normally associated with the healthy oral tract. We demonstrate that combined clinical-genomic models outperform clinical-only models in predicting IMs likely to progress. Our results raise opportunities for GC precision prevention and interception by highlighting strategies for accurately identifying IM patients at high GC risk and a role for microbial dysbiosis in IM progression.

  Study EGAS00001007067

• Dataset for NSCLC-RNA

  Rare cancer sequencing data of 45 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008846

• Dataset for liposarcoma-RNA

  Rare cancer sequencing data of 40 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008854

• EGA FUSE Client

  EGA FUSE Client What is EGA FUSE Client? The EGA FUSE Client is a Java Native Runtime (JNR) based Filesystem in Userspace (FUSE) client that allows users to access authorised EGA files by presenting them in a virtual directory. This means that users can use authorised EGA files like regular files without having to download them first. The EGA FUSE Client is a useful tool for researchers who need to access and work with large amounts of EGA data. Why use EGA FUSE Client? The EGA FUSE Client provides several benefits for researchers working with EGA data: Efficient use of storage space: With the EGA FUSE Client, users can access authorised EGA files without having to download them first. This means that users can save storage space on their local machines. Faster access to data: Since users can access authorised EGA files directly through the EGA FUSE Client, they can work with the data more quickly than if they had to download the files first. Simplified workflow: The EGA FUSE Client presents authorised EGA files in a virtual directory, allowing users to work with the files like regular files. This simplifies the workflow for researchers who need to access and work with large amounts of EGA data. Get started with EGA FUSE Client To get started with EGA FUSE Client visit the EGA FUSE Client GitHub repository for more information and installation instructions.

  Documentation access/download/visualisation/fuse-client

• Examination of Engineered LINE-1 Integration Events in HeLa Cells

  Long Interspsesed Element-1 (LINE1 or L1) encodes two proteins (ORF1p and ORF2p) required for its mobilization (i.e. retrotransposition) in the human genome. Human ORF2p, a 150kDa protein, has endonuclease (EN) and reverse transcriptase (RT) activities. L1 EN is classified as apurinic/apyrimidin-like endonuclease (APE) and is responsible for initiating target-site primer reverse transcription (TPRT) during the L1 retrotransposition cycle. During canonical TPRT, the L1 EN activity makes a single-strand endonucleolytic nick at a double-strand DNA target sequence in genomic DNA. The endonucleolytic nick is typically made at an L1 EN degnerate consensus cleavage sequence (5'-TTTT/A-3') exposing a free 3' hydroxy group that can be used as a primer by the ORF2p L1 RT activity to reverse transcribe the associated L1 RNA. Here, we characterized over 21,000 de novo engineered L1 retrotransposition events in HeLa cells to determine if L1 exhibits overt integration preferences in the human genome. Bru-seq of HeLa cells to determine actively transcribed regions of the genome was also performed. This Bru-seq data was used to determine if engineered L1 integration events preferentially integrate into transcribed regions of the genome, and to determine which strand during transcription may present itself as preferential during L1 retrotransposition.

  Study phs001669

• Genetic heterogeneity and dynamics of transcriptional subtypes in matched primary and recurrent head and neck squamous cell carcinomas

  To get a better understanding of different HNSCC subtypes, whole-exome (matched tumor-normal paits) and whole transcriptome sequencing to to elucidate underlying molecular processes. Here, we present the matched whole-exome sequencing data from 28 patients (normal tissue, tumor tissue, relapse).

  Study EGAS00001005005