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• Comparison of protocols for deriving pancreatic progenitors from hPSCs (ATAC-seq)

  This dataset contains 27 mapped bam files. The samples were generated with 3 different protocols for deriving pancreatic progenitors from hPSC. Three parallel differentiations were performed, all done in a hPSC NKX6.1-GFP reporter line. For each protocol there are three cellular populations: total (presort), GFP+ and GFP- . In summary: 3 differentiations x 3 protocols x 3 cellular populations. We prepared ATAC-seq libraries for the 27 samples, and sequenced them on Illumina HiSeq4000.

  Dataset EGAD00001004824

• Tumour gene expression signature in primary melanoma predicts long-term outcomes: A prospective multicentre study

  Adjuvant systemic therapies are now routinely used following resection of stage III melanoma, however accurate prognostic information is needed to better stratify patients. We used differential expression analyses of primary tumours from 204 RNA-sequenced melanomas within a large adjuvant trial, identifying a 121 metastasis-associated gene signature. This signature strongly associated with progression-free (HR=1.63, p=5.24x10-5) and overall survival (HR=1.61, p=1.67x10-4), and validated in 177 regional lymph nodes metastasis as well as two externally ascertained datasets. The machine learning classification models trained using the signature genes performed significantly better in predicting metastases than models trained with clinical covariates (pAUROC=0.02), or published prognostic signatures. The signature score negatively correlated with measures of immune cell infiltration (ρ=-0.75, p<2.2x10-16), with a higher score representing reduced lymphocyte infiltration and a higher 5-year risk of death in stage II melanoma. Our expression signature identifies melanoma patients at higher risk of metastases and warrants further evaluation in adjuvant clinical trials.

  Study EGAS00001004664

• Genomic Evolution of Breast Cancer Metastasis and Relapse

  Recurrent breast cancer is almost universally fatal. We characterize 170 patients locally relapsed or distant metastatic cancers using massively parallel sequencing. We identify that the relapse-seeding clone disseminates late from the primary tumor. TP53 and AKT1 appear to be enriched in ER-positive cancers predisposed to relapse. Mutation acquisition continues at relapse as the same mutation signatures continue to operate and new signatures, such as that caused by radiotherapy appear de novo. In 49% of cases we identify drivers mutations private to the relapse and these are sampled from a wider range of cancer genes, including SWI-SNF complex and JAK-STAT signaling.

  Dataset EGAD00001002696

• Res1_HT29_exp2_MC_03.03.22

  1 sample is pure plasmid DNA and 10 samples are cell pellets for genomic DNA extraction. CRISPR PCR1 and PCR2 indexing - Please use standard Kozuke primers.

  Dataset EGAD00001012231

• Res1_HT29_exp1_MC_02.03.22

  1 sample is pure plasmid DNA and 10 samples are cell pellets for genomic DNA extraction. CRISPR PCR1 and PCR2 indexing - Please use standard Kozuke primers.

  Dataset EGAD00001012230

• Res1_H23_exp1_MC_04.03.22

  1 sample is pure plasmid DNA and 8 samples are cell pellets for genomic DNA extraction. CRISPR PCR1 and PCR2 indexing - Please use standard Kozuke primers.

  Dataset EGAD00001012229

• Clonal dynamics of normal hepatocyte expansions in homeostatic human livers and their association with the biliary epithelium

  BAM files containing paired-end mtDNA sequencing data from morphologically normal human liver. CCO-proficient hepatocytes acquired from livers in which clonal CCO-deficient hepatocyte patches had been previously identified. Individual BAM files are named according to their patch, line and sample location, where PT denotes tissue near to the portal triad (PT), central hepatic vein (CV) and midway between these two structures (Mid). "Stroma" control samples were used for identifying germ-line variants. Sequenced on NextSeq 500 platform.

  Study EGAS00001006962

• Next Generation Mendelian Genetics: Muscle Hypertrophy

  The NHGRI Next Generation Mendelian Genetics project uses exome resequencing to identify variants in unsolved Mendelian diseases. Samples were collected from a single, multi-generational family with the same phenotype of exaggerated muscular development (muscular hypertrophy) and strength characterized by reduced fat pad thickness under the skin. All family members deny "body building" activities, and are so far negative for known gene mutation that have been identified as associated with excessive muscle development. All family members have examples of demonstrating extraordinary strength occurring both in childhood and old age. No negative associated phenotype traits with the muscle hypertrophy phenotype have been identified.

  Study phs000541

• A comprehensive proteogenomic pipeline for neoantigen discovery to advance personalized cancer immunotherapy

  The accurate identification and prioritization of antigenic peptides is crucial for the development of personalized cancer immunotherapies. Publicly available pipelines to predict clinical neoantigens do not allow direct integration of mass spectrometry immunopeptidomics data, which can uncover antigenic peptides derived from various canonical and non-canonical sources. To address this, we present an end-to-end clinical proteogenomic pipeline, called NeoDisc, that combines state-of-the-art publicly available and in-house software for immunopeptidomics, genomics and transcriptomics with in-silico tools for the identification, prediction, and prioritization of tumor-specific and immunogenic antigens from multiple sources, including neoantigens, viral antigens and high-confidence tumor-specific antigens.

  Study EGAS50000000228

• Recurrent CLTC::SYK fusions and CSF1R mutations in juvenile xanthogranuloma of soft tissue

  In this study, the genomic landscape of extracutaneous juvenile xanthogranuloma (JXG) was analyzed. By leveraging the Dutch Nationwide Pathology Databank (Palga), tumor samples were obtained from different academic medical centers in the Netherlands. The study was approved by the Palga Scientific Council and Privacy Committee (LZV-2016-183) and the Institutional Review Board of Leiden University Medical Center (B19.074). In addition, the study was approved by the Biobank and Data Access Committee of the Princess Máxima Center for Pediatric Oncology (PMCLAB2024.0512). Provided are whole transcriptome sequencing (WTS) data of 3 histiocytic tumors with CLTC::SYK fusions. WTS was performed in the routine workflow of the Princess Máxima Center for Pediatric Oncology (as described in Hehir-Kwa, et al. JCO Precis Oncol 2022). RNA was derived from formalin-fixed paraffin-embedded tumor tissue (n=1) or from frozen tumor tissue (n=2).

  Study EGAS50000000584

• The_GENCODE_exome___sequencing_the_complete_human_exome

  We report the design of an extended set of targets for capturing the complete human exome, based on annotation from the GENCODE consortium. The extended set covers an addition 5,594 genes and 10.3 Mb compared to current sets which mainly target the CCDS database. The additional regions include potential disease genes previously inaccessible to exome resequencing studies, such as 43 genes linked to ion channel activity and 70 genes linked to protein kinase activity. In total, the new GENCODE exome set developed covers 47.9Mb and performed well in sequence capture experiments with HapMap and clinical samples. Samples within this study are prepared with either the CCDS or GENCODE exome products.

  Study EGAS00001000016

• Whole Exome Sequencing of 60 tumor/normal matched liver Cancers (HCC)

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 60 whole exome tumor/normal pairs with matched RNA-seq.

  Dataset EGAD00001004180

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

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

  Dac EGAC50000000605

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

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

  Dataset EGAD50000001747

• A Pharmcogenetic Study of Bipolar Disorder in a Taiwanese Han Chinese Population (TWBP)

  Objective: To identify genetic variants associated with response to lithium prophylaxis treatment. Materials: 294 bipolar I (BPI) patients receiving lithium treatment, a subset of 1761 bipolar I (BPI) patients recruited by the Taiwan Bipolar Consortium. Lithium response was assessed based on the Alda Scale. Methods: Responders to lithium treatment were defined if the patients' Alda Scale > 4, 5, 6, and 7. Genome-wide association (GWA) analysis was carried out on the 294 BPI patients for the 4 definitions of responders. The SNPs showing strongest association in the GWAS were then tested for association in a replication sample of 100 patients and further tested in a prospective follow-up series of 24 patients. Results: Two SNPs on GADL1 showed the strongest associations in the four GWA analyses and in the replication set of 100 patients. These two SNPs had a sensitivity of 0.93 for predicting lithium response and differentiated between the good and poor responders in the follow-up cohort. Summary: These genetic variants are associated with response to lithium prophylaxis treatment for BPI.

  Study phs000692

• HV31 - Read identifier list for local CCS, CLR, ONT and MGI reads

  This file contains read identifiers for local CCS, CLR, ONT and MGI reads for each of the eight selected genomic regions (HLA, KIR, IGH, IGK, IGL, TRA, TRD, andTRG). We extracted these reads by aligning whole-genome sequencing data to a draft whole-genome de novo assembly, and selecting reads that map to contigs representing each region. These reads were involved in the polishing and validation of the HV31 assembly. Please refer to the relevant manuscript (https://doi.org/10.1101/2021.02.03.429586) for additional details. Read identifiers are stored in JSON format. Along with the full FASTQ files, this file enables convenient re-analysis of the HV31 sequencing data in the eight selected regions.

  Dataset EGAD00001007761

• Rare Diseases Clinical Research Network (RDCRN) Vasculitis Clinical Research Consortium (VCRC) Longitudinal Protocol for Takayasu's Arteritis

  The development and validation of accurate biological markers and predictors of disease activity and outcome for Takayasu's arteritis, a form of idiopathic vasculitis, would have a major positive impact on the clinical care of patients with this rare disease, be an important advance in the design of clinical trials and feasibility of new drug development, and provide important insight into the pathogenesis of this condition. Current measures of disease activity, including erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP), while helpful in selected settings, are mostly considered highly flawed and markers whose poor correlation with disease flares makes them inadequate to help guide therapy. Similarly, ESR and CRP are clearly unhelpful as diagnostic tests for vasculitis. The current state of clinical investigation for vasculitis relies heavily upon determination of disease status solely by clinical presentation and investigator opinion. Thus, discovery and validation of more precise markers that quantifiably measure activity, predict disease course, and correlate with an important biological process, would be of great importance. Knowledge to be gained from this study could potentially be highly important. Discovery of effective biomarkers of vasculitis and assessment of long term disease course and complications by the collection of clinical and diagnostic imaging studies proposed could lead to better care and less toxic treatment regimens. Furthermore, insight into the pathophysiology of vasculitis could be gained and this might lead to better treatments and improved outcomes in terms of reduction of vascular and treatment related complications. Ideally, excellent biomarkers reflect a sophisticated understanding of the pathophysiology of a disease.

  Study phs000589

• SCLC CTC genomic analysis data set

  The data set consists of low-pass whole genome sequence data of single CTCs, pools of CTCs and germline controls for a cohort of 31 SCLC patients at both baseline, and for 5 patients at relapse. In addition 9 CDX models and associated germline controls (where available) are included.

  Dataset EGAD00001002678

• Clinical relevance of TCGA subtypes for gastric cancer patients

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

  Study EGAS50000000779

• Urothelial Cancer - Genomic Analysis to Improve Patient Outcomes and Research (UC-GENOME): a Bladder Cancer Advocacy Network (BCAN)-Led Collaborative Research Pilot Study - for Samples Collected at Johns Hopkins

  UC-GENOME is a real-world cohort of patients with metastatic urothelial carcinoma (UC). The study consisted of two co-equal aims: 1) to provide targeted DNA sequencing for clinical decision making at no cost to patients; and 2) to create a resource for collaborative translational science including a clinically annotated biobank. The submitted data represents the foundational analysis of 218 patients accrued at 7 academic medical centers. The analysis includes 176 patients with both targeted DNA sequencing and RNA sequencing. The genomic data was combined with clinical variables to model response to chemotherapy and immune checkpoint inhibitors (ICI).The larger dataset for this study can be found in dbGaP study phs003066.

  Study phs003094

• Identification of Germline Monoallelic Mutations in IKZF2 in Patients with Immune Dysregulation.

  Helios, encoded by IKZF2, is a member of the Ikaros family of transcription factors with pivotal roles in T-follicular helper, NK- and T-regulatory cell physiology. Somatic IKZF2 mutations are frequently found in lymphoid malignancies. Although germline mutations in IKZF1 and IKZF3, encoding Ikaros and Aiolos, have recently been identified in patients with phenotypically similar immunodeficiency syndromes, the effect of germline mutations in IKZF2 on human hematopoiesis and immunity remains enigmatic. We identified germline IKZF2 mutations (one nonsense (p.R291X)- and 4 distinct missense variants) in six patients with systemic lupus erythematosus, immune thrombocytopenia or EBV-associated hemophagocytic lymphohistiocytosis. Patients exhibited hypogammaglobulinemia, decreased number of T-follicular helper and NKcells. Single-cell RNA sequencing of PBMCs from the patient carrying the R291X variant revealed upregulation of pro-inflammatory genes associated with T-cell receptor activation and T-cell exhaustion. Functional assays revealed the inability of HeliosR291X to homodimerize and bind target DNA as dimers. Moreover, proteomic analysis by proximity-dependent Biotin Identification revealed aberrant interaction of 3/5 Helios mutants with core components of the NuRD complex conveying HELIOS mediated epigenetic and transcriptional dysregulation.

  Study EGAS00001005874

• This study explored and validated the clinical application of targeted NGS of circulating tumor DNA in identifying tumor-specific mutations and uncovering clinical actionable targets in a variety of solid tumors in large patient cohorts.

  Cancer is a disease of genetic alterations. Comprehensive genetic diagnosis is needed to match each patient to appropriate cancer therapy. However, acquisition of representative tumor samples is invasive and often infeasible. Circulating tumor DNA (ctDNA) is a promising non-invasive biomarker for cancer mutational profiling. Here we implemented targeted next generation sequencing (NGS) with a customized pan-cancer gene panel on 605 clinical ctDNA samples in multiple cancer types. Overall, tumor-specific mutations were identified in 87% of ctDNA samples, with mutation spectra highly concordant with their matched tumor tissues. 71% of patients have at least one clinical actionable mutation with 76% of which have suggested drugs approved or in clinical trials. In particular, our study reveals a unique mutation spectrum in Chinese lung cancer patients, which could be used to guide treatment decision and monitor the appearance of drug-resistant mutations. Taken together, our study demonstrated the clinical utility of target NGS-based ctDNA mutational profiling to guide cancer treatment decision.

  Study EGAS00001002251

• DNA methylation-based prognostic subtypes of chordoma tumors in tissue

  Chordomas are rare malignant bone cancers of the skull-base and spine. Patient survival is variable and not reliably predicted using clinical factors or molecular features. This study identifies prognostic epigenetic chordoma subtypes that are detected noninvasively using plasma methylomes. Methylation profiles of 68 chordoma surgical samples were obtained between 1996 and 2018 across three international centers along with matched plasma methylomes where available. Consensus clustering identified two stable tissue clusters with a disease-specific survival difference that was independent of clinical factors in a multivariate Cox analysis (HR = 14.2, 95%CI: 2.1–94.8, P = 0.0063). Immune-related pathways with genes hypomethylated at promoters and increased immune cell abundance were observed in the poorperforming “Immune-infiltrated” subtype. Cell-to-cell interaction plus extracellular matrix pathway hypomethylation and higher tumor purity were observed in the better-performing “Cellular” subtype. The findings were validated in additional DNA methylation and RNA sequencing datasets as well as with immunohistochemical staining. Plasma methylomes distinguished chordomas from other clinical differential diagnoses by applying fifty chordoma-versusother binomial generalized linear models in random 20% testing sets (mean AUROC = 0.84, 95%CI: 0.52–1.00). Tissue-based and plasma-based methylation signals were highly correlated in both prognostic clusters. Additionally, leave-one-out models accurately classified all tumors into their correct cluster based on plasma methylation data. Here, we show the first identification of prognostic epigenetic chordoma subtypes and first use of plasma methylome based biomarkers to noninvasively diagnose and subtype chordomas. These results may transform patient management by allowing treatment aggressiveness to be balanced with patient risk according to prognosis.

  Study EGAS00001006406

• Khoe-San whole genome sequencing

  High-coverage (>30X) whole genome data (FASTQ) for 25 southern African Khoe-San individuals (from five populations). These are the same individuals as in Schlebusch et al. 2020 (EGAD00001006183), but different data.

  Dataset EGAD50000001559

• Bulk RNA-sequencing data from 9 cHL cell lines

  The dataset contains raw data of 27 bulk RNA-sequencing data from 9 cHL cell lines. Paired-end fastq with polyA capture are available for each cell line.

  Dataset EGAD50000001271