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• METABRIC

  Solid tumors are complex tissues composed of a mixture of cancer and normal cells, which complicates the interpretation of their molecular profiles. Normal cell contamination can dilute cancer cell information and tissue architecture is generally not reflected in molecular assays. To address these challenges, we developed a computational approach based on standard Haematoxylin and Eosin-stained sections and demonstrated its power in a discovery cohort of 323 breast tumors and an independent validation cohort of 241 tumors. First, to deconvolute cellular heterogeneity and detect subtle genomic aberrations, we introduced an algorithm based on tumor cellularity to increase the comparability of copy-number profiles between samples. Second, we demonstrated that a predictor for survival integrating image-based and molecular features significantly outperforms classifiers based on single data types. Third, we described and validated a novel, independent prognostic factor based on quantitative analysis of spatial patterns between stromal cells, which are not detectable by molecular assays. Our quantitative methods refine and complement molecular assays of tumor samples and could benefit all large-scale cancer studies.First, to deconvolute cellular heterogeneity and detect subtle genomic aberrations, we introduced an algorithm based on tumor cellularity to increase the comparability of copy-number profiles between samples. Second, we demonstrated that a predictor for survival integrating image-based and molecular features significantly outperforms classifiers based on single data types. Third, we described and validated a novel, independent prognostic factor based on quantitative analysis of spatial patterns between stromal cells, which are not detectable by molecular assays. Our quantitative methods refine and complement molecular assays of tumor samples and could benefit all large-scale cancer studies.

  Study EGAS00000000098

• Epiclomal: probabilistic clustering of sparse single-cell DNA methylation data

  We present Epiclomal, a probabilistic clustering method arising from a hierarchical mixture model to simultaneously cluster sparse single-cell DNA methylation data and infer their corresponding hidden methylation profiles. Using synthetic and published single-cell CpG datasets we show that Epiclomal outperforms non-probabilistic methods and is able to handle the inherent missing data feature which dominates single-cell CpG genome sequences. Using a recently published single-cell 5mCpG sequencing method (PBAL), we show that Epiclomal discovers sub-clonal patterns of methylation in aneuploid tumour genomes, thus defining epiclones. We show that epiclones may transcend copy number determined clonal lineages, thus opening this important form of clonal analysis in cancer.

  Study EGAS00001003504

• Genomic and transcriptomic determinants of therapy resistance and immune landscape evolution during anti-EGFR treatment in colorectal cancer

  Genomic and transcriptomic data from a cohort of 35 RAS wild-type colorectal cancers. All 35 cases were DNA sequenced at baseline (BL) before treatment with single agent cetuximab. Progressive disease (PD)-biopsies were taken shortly after radiological progression and successfully exome sequenced from 24/35 cases. mRNA sequencing is available for 25 Baseline and 15 PD samples. ctDNA from 9 cases that progressed after prolonged cetuximab benefit were also deep sequenced.

  Dataset EGAD00001004501

• Metastatic Colorectal Adenocarcinoma Tumor Purity Assessment from Whole Exome Sequencing Data

  As molecular medicine wields greater and greater influence on cancer patient care, including therapeutic selection, it becomes increasingly important to understand the power and deficiencies of computational tools used in decision making processes. Here we use a set of unselected metastatic colorectal tumor samples in a head-to-head comparison between the calculation of stromal content by a board certified pathologist, versus that derived from whole exome sequencing and purity assessment by a variety of common computational methods. We find that in about 1/2 of the samples the computational methods each do a poor job of assessing the percent stromal contamination, and as a result, tumor variant allele frequencies (VAFs) are low or undetected, whereas analysis of organoids derived from the same tumors yielded much higher VAFs in keeping with their lower stromal content. The whole exome sequence of our samples is available via dbGaP, accession phs003059.v1.p1.

  Study phs003059

• Summarized somatic variant calls from CMMRD-associated high-grade gliomas

  This dataset contains summarized somatic variant call data derived from paired tumor–blood whole-exome sequencing of human samples. Access to the dataset is controlled and granted only upon submission and approval of a formal data access request. Requests are reviewed by the Data Access Committee led by the Principal Investigator to ensure compliance with applicable legal, ethical, and data protection requirements. Users must not attempt to re-identify study participants and must comply with all relevant confidentiality and data protection regulations. In accordance with local legal and ethical requirements, individual-level raw sequencing data are not shared.

  Dataset EGAD50000002180

• Targeting AXL Kinase Uniquely Sensitizes Therapy-Insensitive Leukemic Stem and Progenitor Cells to Venetoclax Treatment in Acute Myeloid Leukemia

  The abundance of genetic abnormalities and phenotypic heterogeneities in AML pose significant challenges to developing improved treatments. Here we demonstrated that a key GAS6/AXL axis is highly activated in AML patient cells, particularly in leukemic stem cells. We developed a potent, selective AXL inhibitor that has excellent pharmaceutical properties and efficacy against preclinical patient-derived xenotransplantation models of AML. Importantly, inhibition of AXL sensitized AML stem/progenitor cells to venetoclax treatment, with strong synergistic effects in vitro and in vivo. Mechanistically, single-cell RNA-sequencing and functional validation studies uncovered that AXL inhibition or in combination with venetoclax potentially targets intrinsic metabolic vulnerabilities of AML stem/progenitor cells, which shows a distinct transcriptomic profile and inhibits mitochondrial oxidative phosphorylation. These findings have direct translational impact on the treatment of AML and other cancers with high AXL activity.

  Study EGAS00001004663

• COVID-19 Challenge Project Single Cell Profiling

  Single-cell profiling of sero-negative and sero-positive humans that were inoculated with SARS-CoV-2. The cellular response during SARS-CoV-2 is profiled using single-cell transcriptomics, CITE-seq and single cell immune profiling, by sampling PBMCs and nasal swabs before and at multiple time points during SARS-CoV-2 infection. This one-of-a-kind cellular map will give unique temporal resolution of how nasal and immune cells respond to SARS-CoV-2 exposure and infection.

  Dataset EGAD00001012227

• The double-hit signature identifies double-hit diffuse large B-cell lymphoma with genetic events cryptic to FISH​

  High-grade B-cell lymphomas with MYC and BCL2 and/or BCL6 rearrangements (HGBL-DH/THs) include a group of diffuse large B-cell lymphomas (DLBCLs) with inferior outcomes after standard chemoimmunotherapy. We recently described a gene expression signature that identifies 27% of germinal center B-cell DLBCLs (GCB-DLBCLs) as having a double-hit-like expression pattern (DHITsig) and inferior outcomes; however, only half of these cases have both MYC and BCL2 translocations identifiable using standard breakapart fluorescence in situ hybridization (FISH). Here, 20 DHITsig+ GCB-DLBCLs apparently lacking MYC and/or BCL2 rearrangements underwent whole-genome sequencing. This revealed 6 tumors with MYC or BCL2 rearrangements that were cryptic to breakapart FISH. Copy-number analysis identified 3 tumors with MYC and 6 tumors with MIR17HG gains or amplifications, both of which may contribute to dysregulation of MYC and its downstream pathways. Focal deletions of the PVT1 promoter were observed exclusively among DHITsig+ tumors lacking MYC translocations; this may also contribute to MYC overexpression. These results highlight that FISH fails to identify all HGBL-DH/THs, while revealing a range of other genetic mechanisms potentially underlying MYC dysregulation in DHITsig+ DLBCL, suggesting that gene expression profiling is more sensitive for identifying the biology underlying poor outcomes in GCB-DLBCL.

  Study EGAS00001004285

• Integrating Genomic and Transcriptomic Data to Identify Breast Cancer Susceptibility Genes

  Genetic factors play an important role in the etiology of both sporadic and familial breast cancer. Since 2007, common genetic variants in ~200 loci have been identified in genome-wide association studies (GWAS) in relation to breast cancer risk. However, it is often difficult to translate GWAS findings to disease prevention and treatment since causal genes in the large majority of GWAS-identified loci are unknown. Furthermore, a large fraction of breast cancer heritability remains unexplained. Recent studies suggest that nearly 80% of disease heritability can be explained by genetic variants regulating gene expression. Herein, we propose three well-powered transcriptome-wide association studies (TWAS) to systematically investigate the association of breast cancer risk with gene expression across the transcriptome of African, Asian and European descendants. In Aim 1, we will perform RNA sequencing and high-density genotyping assays using normal breast tissue samples, and build race-specific gene expression prediction models using data from 1000 women of African, Asian and European descent. These models will be applied to the GWAS data generated from approximately 320,000 breast cancer patients and controls to impute gene expression for association analyses of predicted gene expression with risk of breast cancer overall, and by estrogen receptor and HER2 status. In Aim 2, we will select the top 50 genes identified in Aim 1 for in vitro functional assays to assess their influence on major cell functions related to cancer biology. In Aim 3, we will evaluate whether TWAS-identified genes may express differently in normal breast tissues and breast cancer tissues collected from African, Asian, and European descendants to assess whether these genes may contribute to racial differences in breast cancer risk by molecular subtypes. With strong methodology and a large sample size, we believe that this proposed study should be able to identify and characterize a large number of novel genes related to breast cancer risk. Uncovering breast cancer susceptibility genes will greatly improve the understanding of the genetic and biological basis for breast cancer and accelerate the translation of genetic findings to disease prevention and patient care.

  Study phs003535

• The mutational landscape of human somatic and germline cells

  During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

  Dataset EGAD00001006641

• ctDNA monitoring using patient-specific sequencing and integration of variant reads - Breast cohort

  Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Detection of ctDNA can be challenging in patients with low-volume or residual disease, where plasma contains very few tumor-derived DNA fragments. We show that sensitivity for ctDNA detection in plasma can be improved by analyzing hundreds to thousands of mutations that are first identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) pipeline, which combines custom error-suppression methods and signal-enrichment approaches based on biological features of ctDNA. With this approach, the detection limit in each sample can be estimated independently based on the number of informative reads sequenced across multiple patient-specific loci. We applied INVAR to custom hybrid-capture sequencing data from 176 plasma samples from 105 patients with melanoma, lung, renal, glioma, and breast cancer across both early and advanced disease. By integrating signal across a median of >105 informative reads, ctDNA was routinely quantified to 1 mutant molecule per 100,000, and in some cases with high tumor mutation burden and/or plasma input material, to individual parts per million. This resulted in median Area Under the Curve (AUC) values of 0.98 in advanced cancers, and 0.80 in early stage and challenging settings for ctDNA detection. We generalized this method to whole-exome and whole-genome sequencing, showing that the INVAR may be applied without requiring personalized sequencing panels, so long as a tumor mutation list is available. As tumor sequencing becomes increasingly performed, such methods for personalized cancer monitoring may enhance the sensitivity of cancer liquid biopsies.

  Dataset EGAD00001006293

• Modeling Malignant Progression in Glioma

  Gliomas are the most common primary brain tumor in humans. Low-grade gliomas (WHO grade II) invariably progress to high-grade gliomas (WHO grade III or IV). Although malignant progression may take many years, the survival rate after transformation to a high-grade glioma is poor, often only 12-15 months. In this data set, we have identified low-grade gliomas that have progressed to high-grade gliomas or high-grade gliomas that have progressed from low-grade gliomas. Some cases are matched pairs (meaning we have both the original low-grade tumor and the subsequent high-grade tumor). The samples deposited have been analyzed with bulk-RNA sequencing. They are also de-identified but are clinically annotated. When available, genetic information including IDH mutation status, 1p/19q deletion and histological subtype are also included.

  Study phs002607

• Genomic analysis of pancreatic neuroendocrine tumour with MEN1, ATRX, or DAXX mutations

  This dataset includes 52 samples from 19 individuals with pancreatic neuroendocrine tumours. These samples were analyzed using RNA-sequencing, whole-exome sequencing, shallow (~0.3x) whole-genome sequencing, and a 21-gene panel targeted capture sequencing. Everything was sequenced using the Illumina HiSeq and is provided in BAM or FASTQ format.

  Dataset EGAD00001006001

• Lipomatous tumors with 12q amplification

  The project concerns whole genome sequencing (short-read and long-read) and RNA-sequencing of lipomatous tumors with 12q-amplification. A subset of lipomatous tumors is driven by amplification of genes mapping to chromosome arm 12q, including the MDM2 gene. The goals of the study were to compare expression levels of genes mapping to 12q in tumors with amplification in rod-shaped or circularized chromosomes as well as to assess and compare the structural variants in those tumors. In total, 20 samples were analyzed, and the data were correlated with genomic data on bulk and single cell DNA from the same tumors. The fastq files from the tumors were uploaded to EGA.

  Dataset EGAD50000000087

• Adeno-associated virus in the liver: natural history and consequences in tumor development

  Adeno-associated virus (AAV) is a defective mono-stranded DNA virus, endemic in human population (35-80%). Recurrent clonal AAV2 insertions are associated with the pathogenesis of rare human hepatocellular carcinoma (HCC) developed on normal liver. This study aimed to characterize the natural history of AAV infection in the liver and its consequence in tumor development. In silico analyses using viral capture data explored viral variants and new clonal insertions. Clonal AAV insertions were positive selected during HCC development on non-cirrhotic liver challenging the notion of AAV as a non-pathogenic virus.

  Dataset EGAD00001004484

• Moroccan Genome Project: Sequencing Data from 109 Whole Genomes of Moroccan Individuals

  This study is the first phase of the Moroccan Genome Project, which included the complete sequencing of 109 genomes from the Kingdom of Morocco. The sequencing was performing using the Illumina NovaSeq6000 platform, with a mean coverage of 30X.

  Dac EGAC50000000353

• Molecular and Clinical Analyses of PHF6 Mutant Myeloid Neoplasia Provide Clues as to Their Pathogenesis and Therapeutic Targeting

  PHF6 mutations (PHF6MT) are identified in various myeloid neoplasms (MN). However, little is known about the precise function and consequences of PHF6 in MN. Our comprehensive genomic analyses yielded three main findings. Firstly, we revealed a different pattern of genes correlating with PHF6MT in male and female cases. When analyzing male and female cases separately, in only male cases, RUNX1 and U2AF1 were co-mutated with PHF6. In contrast, female cases revealed co-occurrence of ASXL1 mutations and X-chromosome deletions with PHF6MT. Next, proteomics analysis revealed a direct interaction between PHF6 and the pioneer transcription factor RUNX1. Both proteins co-localize in active enhancer regions that define the context of lineage differentiation. Finally, we demonstrated a negative prognostic role of PHF6MT, especially in association with RUNX1. The negative effects on survival were additive as PHF6MT cases with RUNX1 mutations had worse outcomes when compared to cases carrying single mutation or wild-type.

  Study phs003303

• Analysis of tumor periphery and center-specific mutations in renal cell carcinoma

  Renal cell carcinoma (RCC) is a genomically heterogeneous tumor. In the present project, the question whether intratumoral heterogeneity follows a zonal pattern indicating spatial niches was addressed. Whole exome sequencing of 16 paired samples from tumor periphery and center revealed a number of region-specific functional SNVs and Indels. Therefore, RCCs are not composed of evenly admixed tumor cells but show topological differences in their clonal composition.

  Dataset EGAD00001002067

• WES melanoma biopsies (UV1-hTERT-mm)

  The dataset contains phenotypes of 14 melanoma biopsies sequenced in connection with the study UV1-hTERT-mm, where the thereapeutic cancer vaccine UV1 is combined with ipilimumab in treatment of melanoma patients.

  Dataset EGAD00001007648

• Next Generation Sequencing in an IBD Pedigree Exome Data

  The aim is to find rare variants of intermediate penetrance in those at risk of Crohn's disease

  Dataset EGAD00001000423

• Immune-Related Adverse Events after Immune Checkpoint Blockade-Based Therapy are Associated with Improved Survival in Advanced Sarcoma

  Immune activation after immune checkpoint blockade (ICB) can lead to a unique group of adverse events (AEs), which have been associated with improved outcome in many carcinomas. The association between immune-related AEs (irAEs) and outcome in patients with sarcoma is not well studied. This study has two components: (1) a retrospective clinical study of irAEs among 131 patients treated with ICB at Memorial Sloan Kettering Cancer Center and (2) an analysis of a subset of these patients who have whole transcriptome sequencing available for analysis. In the clinical study portion, we reviewed a cohort of patients with advanced sarcoma treated on prospective clinical trials utilizing ICB-based therapy between April 2017 and January 2020. The objectives were to pool the safety data from each trial, identify irAEs, and correlate them with best overall response by RECIST 1.1, progression-free survival (PFS) and overall survival (OS). Association of irAEs with response and survival was assessed using a Cox regression model. A total of 131 patients were included. Forty-two (32%) had at least one irAE of any grade and 16 (12%) had at least one Grade ≥ 3 irAE. On Cox analysis adjusting for clinical covariates that were significant in the univariate setting, the hazard ratio (HR) for an irAE (HR 0.662, 95% CI 0.421 - 1.041) approached, but did not reach statistical significance for PFS (P = 0.074), while patients had a significantly lower HR for OS (HR 0.443, 95% CI 0.246 – 0.798; P = 0.007) compared to those without or before an irAE. Tumor samples with available RNA sequencing data were stratified by presence of an irAE to identify patterns of differential gene expression. In total, 71 unique patients had RNA sequencing available for analysis. The transcriptomes of 31 of these patients have been previously uploaded to dbGaP (phs002852), leaving 36 unique transcriptomes that have not been previously publicly shared. Three patients did not agree for their sequencing to be publicly shared. Therefore, 33 unique patient samples will be uploaded to this dbGaP study. Overall, this study found that gene expression profiling on baseline tumor samples from patients who had an irAE had higher numbers of tumor-infiltrating dendritic cells, CD8+ T cells, and regulatory T cells as well as upregulation of immune and inflammatory pathways.

  Study phs003284

• Germline and somatic SMARCA4 mutations characterize small-cell carcinoma of the ovary, hypercalcemic type.

  Small-cell carcinoma of the ovary, hypercalcemic type (SCCOHT) is the most common undifferentiated ovarian malignancy in women under 40 years1. We sequenced the exomes of six individuals from three SCCOHT families. After discovering segregating deleterious germline mutations in SMARCA4 in all three families, we tested DNA from a fourth family, which also possessed a segregating SMARCA4 germline mutation. All familial tumors sequenced harboured either a somatic mutation or loss of the wild-type allele. Immunohistochemical (IHC) analysis of these and additional familial and non-familial cases showed loss of the SMARCA4 protein (BRG1) in 38/40 tumors overall. Sequencing of cases with available DNA revealed at least one germline or somatic deleterious SMARCA4 mutation in 30/32 cases. Additionally, the SCCOHT cell line BIN-67 contained bi-allelic deleterious mutations in SMARCA4. Our findings identify alterations in SMARCA4 as the major cause of SCCOHT, which could lead to genetic counseling and new treatment approaches.

  Study EGAS00001000721

• RNA-seq data in hMPC, MSC_Pat and EWIma

  Ewing sarcoma is characterized by pathognomonic translocations fusing most frequently EWSR1 with FLI1 (EF1). In addition, Ewing sarcoma can also display alterations in STAG2, TP53 and CDKN2A (SPC). Starting from Ewing sarcoma derived human mesenchymal stem cells (MSCpat), we recapitulated this translocation and SPC alterations using a CRISPR/cas9 approach and generated a bona fide Ewing sarcoma model (EWIma1) displaying transcriptomic and epigenetic hallmarks of EwS.

  Study EGAS50000001173

• ChIP-seq data in MSC_Pat and EWIma1 (FLI1 & H3K27ac)

  Ewing sarcoma is characterized by pathognomonic translocations fusing most frequently EWSR1 with FLI1 (EF1). In addition, Ewing sarcoma can also display alterations in STAG2, TP53 and CDKN2A (SPC). Starting from Ewing sarcoma derived human mesenchymal stem cells (MSCpat), we recapitulated this translocation and SPC alterations using a CRISPR/cas9 approach and generated a bona fide Ewing sarcoma model (EWIma1) displaying transcriptomic and epigenetic hallmarks of EwS.

  Study EGAS50000001172

• Single Cell Analysis of Pulmonary Fibrosis

  Pulmonary fibrosis is a heterogenous syndrome in which fibrotic scar replaces normal lung tissue. We performed massively parallel single-cell RNA-Seq on lung tissue from eight lung transplant donors and eight patients with pulmonary fibrosis. Combined with in situ RNA hybridization, with amplification, these data provide a molecular atlas of disease pathobiology. We identified a distinct, novel population of profibrotic alveolar macrophages exclusively in patients with fibrosis. Within epithelial cells, the expression of genes involved in Wnt secretion and response was restricted to non-overlapping cells. We identified rare cell populations including airway stem cells and senescent cells emerging during pulmonary fibrosis. Analysis of a cryobiopsy specimen from a patient with early disease supports the clinical application of single-cell RNA-Seq to develop personalized approaches to therapy.

  Study phs001750

• Identification of G-Quadruplex Clusters by High-Throughput Sequencing of Whole-Genome Amplified Products with a G-Quadruplex Ligand

  G-quadruplex (G4) is a non-canonical DNA structure that has been found in the genome. To identify clusters of G4-forming sequences in the genome, we performed whole genome amplification (WGA) in the presence or absence of a G4 ligand that inhibits DNA polymerase activity on the G4 forming regions, followed by high-throughput sequencing of the WGA products. As the results, 12254 G4 cultures were identified on HeLa genomic DNA.

  Study phs001450

• Screening Cases of Isolated Dystonia for Variants in CIZ1

  Recently, we have identified that variants in CIZ1 gene is associated with dystonia. To identify the prevalence of CIZ1 mutations in dystonia population, we use High resolution melting (HRM) to examine all the coding sequence in 3976 subjects with primary dystonia as well as 1819 subjects of normal controls. Indels in Q rich region of exon 2 in CIZ1 were identified in 21 subjects with dystonia but only 3 controls (P<0.05). Other single nucleotide change variants were also found in some of the patients which include a novel missense mutation (c.787A>G, p.R263G) found in a female patient with apparently familial dystonia. We confirmed that mutations in CIZ1 could be associated with dystonia but in rare cases.

  Study phs001455

• RNA-sequencing of mechanical stress induced osteoarthritis-like damage in aged human cartilage explants treated with the anti-deiodinase iopanoic acid

  The current study aimed to confirm chondroprotective effects of the D2 inhibitor iopanoic acid (IOP) in an ex vivo aged human osteochondral explant model in which injurious mechanical stress is applied to inflict OA-like damage. This dataset contains RNA-seq (Illumina HiSeq X ten) of osteochondral explant cartilage from aged human patients that underwent a joint replacement surgery due to OA (N=10 donors; n=21 explants).

  Study EGAS00001006242

• Whole-exome sequencing data of ovarian clear cell carcinoma in East Asia

  This is a genomic study to uncover the molecular landscape of ovarian clear cell carcinoma (OCCC) in East Asia. This dataset contains normal-tumor paired samples of 104 patients with OCCC diagnosed in two branches of Chang Gung Memorial Hospital, Taiwan. These are paired-end, whole-exome sequencing data, sequenced by Illumina NovaSeq with target depth of 150X.

  Study EGAS50000000031

• Genetic and transcriptional landscape of plasma cells in POEMS syndrome

  POEMS syndrome is a rare paraneoplastic disease, associated with monoclonal plasma cells whose pathogenic importance remains unclear. We performed comprehensive genetic analyses of plasma cells in 20 patients with POEMS syndrome. Whole exome sequencing and targeted sequencing identified 7 recurrently mutated genes: KLHL6, LTB, EHD1, EML4, HEPHL1, HIPK1, and PCDH10. None of the driver gene mutations frequently found in multiple myeloma (MM) such as NRAS, KRAS, BRAF, and TP53 was detected. Copy number analysis showed chromosomal abnormalities shared with monoclonal gammopathy of undetermined significance (MGUS). RNA sequencing revealed a transcription profile specific to POEMS syndrome, especially in terms of tumorigenesis. Unexpectedly, disease-specific VEGFA expression was not increased in POEMS syndrome. Our study illustrates that the genetic and transcriptional profiles of plasma cells in POEMS syndrome are distinct from MM and MGUS, indicating its unique pathogenesis.

  Study JGAS000150

• RNAseq Iron-Treated iPSC-derived Microglia

  Iron accumulation in microglia has been observed in Alzheimer’s disease and other neurodegenerative disorders and is thought to contribute to disease progression through various mechanisms including neuroinflammation. To study the interaction between iron accumulation and inflammation, we treated human induced pluripotent stem cell-derived microglia (iPSC-MG) with an increasing concentration of iron, in combination with inflammatory stimuli such as interferon gamma and amyloid β, and performed RNA sequencing.

  Dataset EGAD00001008660

• Slim Initiative in Genomic Medicine for the Americas (SIGMA): Diabetes in Mexico Study (DMS)

  The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples (T2D-GENES) Genetics of Type 2 Diabetes (GoT2D) Exome Sequencing Project (ESP) Slim Initiative in Genomic Medicine for the Americas: Type 2 Diabetes (SIGMA T2D) Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP) Progress in Diabetes Genetics in Youth (ProDIGY) This data generated from the SIGMA Diabetes in Mexico Study (DMS) was part of the Slim Initiative in Genomic Medicine for the Americas: Type 2 Diabetes (SIGMA T2D), which is an international research consortium funded by the Carlos Slim Foundation that seeks to identify the genetic risk factors for type 2 diabetes (T2D) in Mexico and Latin America and translate those findings into improved treatment and prevention of diabetes. The SIGMA T2D project has sequenced and genotyped more than 13,000 samples from Mexican and Mexican Americans. The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGaP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGaP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies Ancestry Consortia Study Countries of Origin # Cases # Controls African American T2D-GENES Project 1 Jackson Heart Study US 500 526 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 530 African American ESP Exome Sequencing Project (ESP) US 467 1374 African American T2D-GENES Follow up study BioMe Biobank Program (BioMe) US 1297 1256 East Asian T2D-GENES Project 1 Korea Association Research Project Korea 526 561 East Asian T2D-GENES Project 1& Follow up Study Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 1486 1568 East Asian T2D-GENES Follow up study Korea SNUH South Korea 450 475 East Asian T2D-GENES Follow up study Research Studies in Hong Kong (Hong Kong) Hong Kong 493 485 European T2D-GENES Project 1 Ashkenazi US, Israel 506 355 European T2D-GENES Project 1 Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European GoT2D Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European GoT2D Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European GoT2D UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European GoT2D Malmo-Botnia Study Finland, Sweden 478 443 European LuCamp Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) Denmark 997 997 European ESP Exome Sequencing Project (ESP) US 390 2843 European T2D-GENES Follow up study Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) Scotland, UK 960 966 European T2D-GENES Follow up study Framingham Heart Study (FHS) US 396 596 Hispanic T2D-GENES Project 1 San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 218 Hispanic T2D-GENES Project 1 & SIGMAv2 Starr County, Texas US 1762 1738 Hispanic SIGMAv1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMAv1 & v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMAv1 & v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMAv1 & v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multi ethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multi ethnic ProDIGY SEARCH for Diabetes in Youth (SEARCH) US 553 0 South Asian T2D-GENES Project 1 London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 531 538 South Asian T2D-GENES Project 1 & Follow up study Singapore Indian Eye Study Singapore (Indian Asian) 1640 1478 South Asian T2D-GENES Follow up study Pakistan Genomic Resource (PGR) Pakistan 914 932 The Diabetes in Mexico Study (DMS) study contributed 1,522 cases and 1,546 controls to the 52k T2D exome sequencing study.

  Study phs001388

• Women's Environmental Cancer and Radiation Epidemiology (WECARE) Study

  Study population The WECARE Study is an international multicenter population-based case-control study of cases with asynchronous contralateral breast cancer (CBC) and individually matched controls with unilateral breast cancer (UBC). Recruitment and data collection for the WECARE Study were conducted in two phases, herein referred to as WECARE I (2001–2004) and WECARE II (2009–2012). The study design of the first phase (WECARE I) has been described in detail elsewhere [Bernstein JL, et al 2004, PMID: 15084244]; the second phase (WECARE II) employed a nearly identical approach [Langballe R, et al 2016, PMID: 27400983]. Participants in each phase were identified through eight population-based cancer registries, including six in the United States that contribute to the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) program: Los Angeles County Cancer Surveillance Program; Cancer Surveillance System of the Fred Hutchinson Cancer Center (Seattle region, WA); State Health Registry of Iowa; Cancer Surveillance Program of Orange County/San Diego-Imperial Organization for Cancer Control (Orange County/San Diego, CA); the Greater Bay Area Cancer Registry (San Francisco Bay Area region and Santa Clara region, CA); and the Sacramento and Sierra Center Registry (Sacramento region, CA). Participants were additionally identified using the Ontario Cancer Registry (Canada) and the Danish Breast Cancer Cooperative Group Registry, supplemented by data from the Danish Cancer Registry. The study protocol was approved by the institutional review or regulatory ethics boards at each study site. Data collection Study participants were interviewed by telephone using a structured questionnaire aimed at evaluating known or suspected breast cancer risk factors, including personal demographics, medical history, menstrual and reproductive history, family history of cancer, use of hormones, smoking, and alcohol intake. Risk factor status was assessed during the period prior to first diagnosis, as well as between first diagnosis and reference date (i.e., the at-risk period for CBC). Detailed data on treatment and tumor characteristics were obtained directly from cancer registry records or by abstracting medical records, including pathology and surgical reports, radiation oncology clinic notes, and systemic adjuvant treatment data. Complete medical treatment history information was collected, and for all women who received radiotherapy, the radiation dose to the contralateral breast was reconstructed using radiotherapy records and radiation measurements. Biospecimens were collected from study participants for genotyping: blood collected from WECARE I women; and saliva collected from WECARE II women.

  Study phs003945

• Whole Exome Sequencing of Pancreatic Neuroendocrine Tumors at The Human Genome Sequencing Center, Baylor College of Medicine (HGSC-BCM)

  Pancreatic neuroendocrine tumors (PNETs), often referred to as "islet cell tumors", are neuroendocrine neoplasms that arise from cells of the endocrine and nervous system within the pancreas. These rare tumors which originate from the pancreatic islet are divided into many categories and are often classified by the hormone most strongly secreted. With the collaboration of the Elkins Pancreatic Center, the Human Genome Sequencing Center (HGSC) at Baylor College of Medicine had access to approximately 30 untreated tumor specimens and matched normal blood samples. Since the onset and progression of cancer is driven by extensive mutation of the genome, we are combining enrichment of exonic DNA with next generation sequencing to detect and characterize the somatic mutation profile of patients with pancreatic neuroendocrine cancer. This work was done at the Human Genome Sequencing Center (HGSC) in collaboration with the Elkins Pancreatic Center at Baylor College of Medicine in Houston, TX and was supported by grant number 5U54HG003273 from National Human Genome Research Institute (NHGRI).

  Study phs000871

• Single-cell Kinnex sequencing of Alzheimer's disease isoform profile

  Alzheimer’s disease (AD) is the most common cause of dementia, yet its molecular causes remain incompletely understood. RNA diversity in part arising from dysregulated splicing may contribute to AD pathogenesis; however, the ability to interrogate the resulting full-length isoforms in single brain cells has been technologically limited. Here we report the use of PacBio Kinnex long-read sequencing combined with 10X Genomics single-cell preparations to identify both annotated and unannotated RNA isoforms. Eight AD and seven non-diseased post-mortem human brains yielded ~70,000 single nuclei showing diverse, differentially expressed, and switched transcripts in multiple genes. Cell-type-specific isoform expression and variants with intra-exonic junctions associated with reverse transcriptase-mediated somatic gene recombination were also detected. Novel isoforms, including CHI3L1 and SEPTIN4, were altered in AD. Kinnex sequencing of RNA isoforms from single nuclei detected vast isoform diversity amongst brain cell types, representing an under-explored element in AD and other brain disorders.

  Study EGAS50000001476

• Molecular profiling of metastatic uveal melanoma

  Metastatic uveal melanoma is less well understood than its primary counterpart, has a distinct biology compared to skin melanoma and lacks effective treatments. Here we genomically profile metastatic tumors and infiltrating lymphocytes. BAP1 alterations were overrepresented and occurred in 29/32 of cases. An outlier tumor had high mutational burden associated with UV-damage. CDKN2A deletions also occurred, which are rarely present in primaries. We profiled recurrent copy number alterations associated with metastasis and performed a focused knockdown screen on overexpressed targets. We investigated the role of BAP1 by reintroducing a functional allele into a deficient patient-derived cell line, revealing a broad shift towards a transcriptomic subtype associated with better prognosis. Tumor-infiltrating lymphocytes were in several cases tumor-reactive, but expression of the immune checkpoint receptors TIM-3, TIGIT and LAG3 was abundant. This study represents the largest whole-genome analysis of uveal melanoma to date and presents an updated view of the metastatic disease.

  Study EGAS00001004296

• Amplicon sequencing data from organoids of colorectal cancer patients.

  The dataset includes 13 bam files. Each bam file is a different colorectal cancer patient organoid.

  Dataset EGAD00001004313

• RBWES

  Retinoblastoma is a rare childhood cancer of the retina. We studied retinoblastoma by Whole-Exome-Sequencing.

  Dataset EGAD00001007591

• EORTC-26101 sequencing data

  The dataset contains panel sequencing data of 170 genes from 380 patients of the EORTC-26101 trial. The corresponding methylation data is available via the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/) repository with the accession number GSE237103.

  Dataset EGAD00001011160

• National Cancer Institute (NCI) Study of Lung Cancer and Smoking Phenotypes in African-American Cases and Controls

  This is a two-stage case-control study designed to evaluate the association between common genetic variants and the risk of lung cancer. The stage 1 studies included 1737 cases and 3602 controls from the following studies: MD Anderson Lung Cancer Epidemiology Study, The Multiethnic Cohort Study (MEC), NCI-MD Lung Cancer-Case Control Study, Northern California Lung Cancer Study, Project CHURCH (Creating a Higher Understanding of Cancer Research δ Community Health), Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO), Southern Community Cohort Study (SCCS), and the Karmanos Cancer Institute at Wayne State University (KCI/WSU). The stage 2 studies included an independent set of 866 cases and 796 controls from the following studies: The Black Women's Health Study (BWHS), The Harvard-MGH Lung Cancer Susceptibility Study (HLCS), MD Anderson Lung Cancer Epidemiology Study, MD Anderson/LBJ Hospital Biorepository, NCI-MD Lung Cancer Case-Control Study, Northern California Lung Cancer Study, Philadelphia Lung Cancer Study on Gene Environment Interactions (Plus-Gene), Southern Community Cohort Study (SCCS), and KCI/WSU.

  Study phs001210

• Genomic analysis and evolutionary modeling of breast and larynx cancer, based on specimens from Polish population

  We explore the genomic characteristics of the original dataset of breast and larynx cancer specimens of several cell types from the collection of the Department of Applied Radiology of the Maria Sklodowska-Curie National Research Institute of Oncology, Krakow (Poland) Branch and Institute of Human Genetics Polish Academy of Sciences. DNA from paired tissue samples from primary tumor locations and concurrent metastasis to regional lymph nodes was sequenced and matched to controls. A range of genomic analyses was carried out, such as estimation of variant allele frequencies (VAF) and copy number variation (CNV). They show that subsets of variants from primary tumors are present in metastatic lymph nodes and that the CNV pattern is similar, but not identical to that known in the literature. In addition to that, we fit the VAF data to theoretical site frequency spectra predicted by multiple models found in the literature. Analysis suggests existence of secondary advantageous subclones arising on the clonal background as well as of a number of neutral or slightly deleterious passenger mutations.

  Study EGAS00001006456

• Integrated genetic and epigenetic analysis defines novel molecular clusters in rhabdomyosarcoma

  Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma in childhood. To unravel the genetic/epigenetic basis of RMS, we studied 60 RMS cases using whole exome/transcriptome sequencing, copy number (CN) profiling, and DNA methylome analysis. Based on DNA methylation patterns, RMS was clustered into 4 distinct subtypes, which exhibited remarkable correlation with mutation/CN profiles, histological phenotypes, and clinical behaviors. A1 and A2 subtypes, especially A1, largely corresponded to alveolar histology with frequent PAX3/7 fusions and alterations in cell cycle regulators. In contrast, mostly showing embryonal histology, both E1 and E2 subtypes were characterized by high frequency of CN alterations and/or allelic imbalances, FGFR4/RAS/AKT pathway mutations and PTEN mutations/methylation and in E2, also by p53 inactivation. Despite generally poor prognosis in RMS, patients in E1 cluster exceptionally showed excellent prognosis. Our results highlight the close relationship between DNA methylation status and gene mutations and biological behavior in RMS.

  Study EGAS00001000884

• National Cancer Institute (NCI) Non-Hodgkin Lymphoma Genome-wide Association Study (GWAS)

  Within the framework of the International Lymphoma Epidemiology Consortium (InterLymph) Consortium and NCI-sponsored Cohort Consortium, investigators from 22 studies came together to conduct a genome-wide association study (GWAS) of non-Hodgkin lymphoma (NHL). The goal of the study was to identify common genetic variants associated with the risk of NHL. As described previously (Berndt SI et al., Nature Genetics, 2013, PMID: 23770605 ), cases and controls from 22 studies, including nine prospective cohort studies, eight population-based case-control studies, and five clinic or hospital-based case-control studies were included in this effort. Cases of NHL were ascertained from cancer registries, clinics or hospitals, or through self-report verified by medical and pathology reports. The phenotype information for all NHL cases was reviewed centrally at the InterLymph Data Coordinating Center and harmonized according to the hierarchical classification proposed by the InterLymph Pathology Working Group based on the World Health Organization (WHO) classification (2008). Controls were frequency matched to cases on age and gender by study, and the study was limited to subjects of European ancestry. Participants were genotyped using the Illumina Omni Express. The NCI Non-Hodgkin Lymphoma GWAS is utilized in the following dbGaP sub-studies. To view genotypes and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000801 NCI Non-Hodgkin Lymphoma GWAS. phs000802 NCI Non-Hodgkin Lymphoma GWAS: CLL phs000818 NCI Non-Hodgkin Lymphoma GWAS: Controls phs000889 NCI Non-Hodgkin Lymphoma GWAS: DLBCL phs000890 NCI Non-Hodgkin Lymphoma GWAS: FL phs000891 NCI Non-Hodgkin Lymphoma GWAS: MZL

  Study phs000801

• Psoriatic_arthritis

  This is a pilot single cell mRNA sequencing experiment to study immune cells in psoriatic arthritis.

  Study EGAS00001002104

• Benchmarking_CRISPR_Whole_genome_Drop_out_Screen___B_S

  This study is a benchmarking exercise to explore potential source of variation between different CRISPR drop out libraries.

  Study EGAS00001002931

• Genomic Profiling of Pediatric Tumors by Cell Free DNA Sequencing

  BACKGROUND Analysis of cell-free DNA (cfDNA) from peripheral blood has been studied extensively for detection and monitoring therapy response in adult cancers, but utility in pediatric tumors is unclear. METHODS We studied 233 children with hematologic, solid and brain tumors. cfDNA was extracted from 1 mL of plasma collected at diagnosis. Circulating tumor DNA (ctDNA) in cfDNA was quantified and diverse classes of somatic genomic variants were detected using PeCan-Seq. PeCan-Seq findings were compared with matched tumor whole-genome and whole-exome sequencing data. Minimal residual disease (MRD) status was evaluated by cfDNA PeCan-Seq in 14 patients with B-cell acute lymphoblastic leukemia. RESULTS Plasma cfDNA yields at diagnosis were higher for hematologic malignancies than for solid and brain tumors. Patients with hematologic malignancy were 100% ctDNA-positive, the median ctDNA fraction in cfDNA was 0.77. We detected 97% variants that were present in tumors and covered by the capture panel, and 50 subclonal variants that were present in cfDNA only. Our approach enabled detection of sequence and structural variants in B-ALL ctDNA at varying levels of MRD. Nineteen of 38 patients with solid tumors were ctDNA-positive, with high prevalence in Ewing Sarcoma, liver tumors and osteosarcoma. One of 19 brain tumor patients was ct-DNA positive, indicating lack of utility for plasma-derived cfDNA in this disease. Notably, cfDNA analysis of a single plasma sample identified genomic features in ctDNA derived from B-ALL, concurrent primary neuroblastoma, and a later neuroblastoma relapse, indicating that genomic variations from multiple tumors could be detected simultaneously. CONCLUSIONS Pediatric patients with hematologic malignancy had an abundance of plasma ctDNA at diagnosis. Plasma ctDNA levels varied between different solid tumor types, more studies are needed to determine utility. Panel-based cfDNA sequencing could serve as a non-invasive approach for pediatric cancer diagnosis and disease monitoring.

  Study EGAS50000000072

• Whole genome sequencing of 108 epileptic patients from CENet cohort

  Epileptic patients have been sequenced as part of the CENet cohort which is composed of patients with Genetic Generalized Epilepsy (GGE) or Non-Acquired Focal Epilepsy (NAFE) collected in CHUM Research Center in Montreal. Patients were diagnosed by epileptologists. The clinical epilepsy phenotype was classified according to the current classification by the International League against Epilepsy (ILAE). Libraries preparation and whole-genome sequencing: gDNA was cleaned up using ZR-96 DNA Clean & ConcentratorTM-5 Kit (Zymo) prior to being quantified using the Quant-iTTM PicoGreen dsDNA Assay Kit (Life Technologies) and its integrity assessed on agarose gels. Libraries were generated using the TruSeq DNA PCR-Free Library Preparation Kit (Illumina) according to the manufacturer’s recommendations. Libraries were quantified using the Quant-iTTM PicoGreen dsDNA Assay Kit (Life Technologies) and the Kapa Illumina GA with Revised Primers-SYBR Fast Universal kit (Kapa Biosystems). Average size fragment was determined using a LabChip GX (PerkinElmer) instrument. The libraries were denatured in 0.05N NaOH and diluted to 8pM using HT1 buffer. The clustering was done on a Illumina cBot and the flowcell was ran on a HiSeq 2500 for 2x125 cycles (paired-end mode) using v4 chemistry and following the manufacturer's instructions. A phiX library was used as a control and mixed with libraries at 0.01 level. Bioinformatics: The Illumina control software was HCS 2.2.58, the real-time analysis program was RTA v. 1.18.64. Program bcl2fastq v1.8.4 was used to demultiplex samples and generate fastq reads. The filtered reads were aligned to reference Homo_sapiens assembly b37. Each readset was aligned to create a .cram file.

  Study EGAS00001007507

• Whole genome sequencing of 50 trios, where the child is affected with ID, and the parents are unaffected

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. Each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targetted gene and whole exome screening.

  Study EGAS00001000769

• PGDx elio plasma resolve analytical validation

  This dataset consists of 39 noncancerous donor and 62 cancer patient plasma samples (including 29 patients with CRC across a total of 13 tumor types) that were analyzed with the PGDx elio plasma resolve assay. The PGDx elio plasma resolve assay is a hybrid capture approach targeting 33 genes with sequencing performed using the Illumina NextSeq with 150bp paired-end reads. The bam files provided have been adapter masked and contain duplicate reads.

  Dataset EGAD00001009718

• De novo mutations in cell-free foetal DNA (cffDNA)

  This project is to develop and validate a method to detect de novo mutations in a foetal genome through deep sequencing of cell-free DNA from the plasma of pregnant women. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001000596