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• Multiomic Landscape of Multiple Myeloma Precursor and Relapsed Disease

  Multiple myeloma (MM) is a treatable, though incurable, plasma cell malignancy. The molecular mechanisms driving disease onset and the emergence of drug resistance remain elusive. To better characterize the mutational, transcriptional, and epigenetic alterations that accompany MM disease evolution, we accessed molecular data from MM patients treated at Moffitt Cancer Center, with bone marrow biopsies collected between 2011 and 2023.We performed scMultiome (single-cell, paired RNA/ATAC-Seq, 10x Genomics) on 18 CD138+-selected bone marrow aspirate samples, including: 2 healthy donors, 3 patients with monoclonal gammopathy of undetermined significance (MGUS), 4 with smoldering myeloma (SMM), 3 with newly diagnosed MM (NDMM), 1 with early relapse MM (ERMM, 1 to 3 lines of therapy), and 5 with late relapse MM (LRMM, 4 or more lines of therapy). Our dataset includes a sequential sample: a patient with a premalignant condition ("scMultiome_SMM_4") that progressed to active myeloma ("scMultiome_NDMM_3"). These data allow for the assessment of transcriptional and epigenetic dysregulation at the cellular level. Our findings illustrate the dynamic epigenetic and transcriptional landscapes that accompany MM disease progression.We also conducted CUT&Tag analysis on 4 NDMM and 4 LRMM samples to map histone modifications, specifically H3K27ac, to investigate their role in transcriptional reprogramming observed in advanced stages of MM. This analysis revealed sample heterogeneity in terms of super-enhancer-regulated genes associated with active transcription.This cohort also includes samples from the clinical trial NCT04151667, “Daratumumab-Based Response-Adaptive Therapy for Older Adults With Newly Diagnosed Multiple Myeloma.” We performed scRNAseq (single-cell RNA sequencing, 10x Genomics) on 30 CD138+-selected bone marrow aspirate samples and 31 pre-sort samples featuring bone marrow mononuclear cells of various cell types from 5 healthy donors and 11 patients with newly diagnosed MM (NDMM). Our dataset includes sequential samples for all 11 NDMM patients, both prior to induction therapy (denoted by ‘a') with Daratumumab and Dexamethasone, and at cycle 2 day 22 (C2D22, i.e., 60 days after induction therapy start, denoted by ‘b'). For three NDMM patients, we also have samples at relapse (denoted by ‘c'). These data allow for the assessment of transcriptional dysregulation at the single-cell level in both the tumor and immune-tumor microenvironment, associated with Daratumumab treatment in NDMM patients.In addition to the molecular data, demographic, and phenotypic information for all samples is provided.

  Study phs003892

• Population Genetics Analysis Program: Immunity to Vaccines/Infections - Smallpox Vaccination (NIAID/NIH)

  The study examines the role of candidate human immune response gene polymorphisms (and their receptors, expression and function) and variations in immune response, among 1,000 active duty members of the military who were recently vaccinated with ACAM2000 or Dryvax Smallpox vaccine. In addition to the phenotype and genotype data available through dbGaP, extensive clinical data are available through NIAID's ImmPort data portal; information to map the the data available in dbGaP to the data available in ImmPort is provided in the dataset pht005302.v1.p1 of the current study, dbGaP phs001057.v1.p1.

  Study phs001057

• Targeted capture, whole genome sequencing, and RNAseq to identify rearrangements in B-cell lymphomas

  This study contains whole genome and custom targeted capture sequencing of mature B-cell lymphomas (DLBCL, FL, BL, HGBCL-DH-BCL2, HGBCL-DH-BCL6) to identify translocation breakpoints of common oncogene rearrangements (MYC, BCL2, BCL6). It is complemented by RNAseq data where available. Complete details are available in the publication Hilton et al, 2024, Blood. Capture sequencing: 357 samples; 364 unique libraries; cram file format aligned to hg38 Whole genome sequencing: 12 samples; 12 unique libraries; cram file format aligned to grch37 RNAseq: 257 samples; 257 unique libraries; fastq file format

  Study EGAS50000000328

• Single-cell transcriptomic data from tumor samples

  Extramedullary multiple myeloma is an aggressive form of multiple myeloma where the myeloma cells escape BM microenvironment and infiltrate distant tissues.We analyse using single cell techniques, the composition and functional state of major immune cells in EMM tumor microenvironment, T and NK cells. This dataset contains the singlecell RNAseq data used in the publication. It includes scRNAseq data from tumor samples across extramedullary multiple myeloma soft tissue (EMM) (n=5; 3 additional samples in the study are under accession numbers mentioned in the publication), EMM bone marrow (EMM_BM) (n=5), and relapsed/refractory multiple myeloma (RRMM_BM) BM (n=6).

  Study EGAS50000001038

• Breast Cancer - Very young women

  This project will focus on sequencing of breast cancer from young age cancer patients characterized by age at diagnosis under 35. Based on the incidence rate by Korean National Cancer Incidence Database, breast cancer is the most common solid tumors among young adults aged 15-34 excepting thyroid cancer (Cancer statistics in Korea (2012)). This project just started from the mid of 2015. National cancer center in Korea are collecting more than 100 tumor specimens from breast cancer patients aged 20-34. Genetic features of young patients will be investigated with somatic mutation pattern, structural variations, and canonical pathways.

  Study EGAS00001001908

• Single cell T cell Landscape and T Cell Receptor Repertoire Profiling of AML in Context of PD-1 Blockade Therapy

  Eight pretreatment and 14 posttreatment bone marrow (BM) aspirates from 8 patients with R/R AML treated with azacitidine and nivolumab along with 2 control BM from healthy donors were profiled with scRNA sequencing with matching scTCR -, scBCR - and scATAC sequencing. Additionally, the targeted DNA sequencing in at least 1 time point per patient (total evaluated 17/22 samples, two samples were performed using CLIA-certified molecular diagnostic assay and data is not available) was performed. The Fastq files and/or bam files are available in this dataset.

  Study EGAS00001004894

• STAMPEED: Myocardial Infarction Genetics Consortium (MIGen)

  Myocardial infarction (MI) is a common complex disease and the leading cause of death and disability worldwide. The genetic basis of this disease is largely unknown. It has been thought that early-onset MI events would have a substantially greater heritability, thus making DNA collections with younger individuals desirable. More recently, genome-wide association studies have become feasible through the development of whole genome arrays and a large catalogue of common variants reported in the International HapMap database. This study aims to use Affymetrix genotyping platform to do a whole genome scan in 3000 early-onset MI cases and 3000 matched controls from 6 study collection sites.

  Study phs000294

• Genomic Profiling of Thyroid Cancer Reveals a Role for Thyroglobulin in Metastasis -Part II

  Papillary thyroid carcinoma (PTC) has a wide geographic variation in incidence, being highest in Saudi Arabia where it is only second to breast cancer as the most common cancer among females. Genomic profiling of PTC from Saudi Arabia has not been attempted previously. We performed whole-exome sequencing of 101 PTC samples and the corresponding genomic DNA to identify genes with recurrent somatic mutations, followed by sequencing of these genes using a next-generation gene panel approach in further 785 samples. In addition to BRAF, N-RAS and H-RAS, which have previously been shown to be recurrently mutated in PTC, our analysis highlights additional genes, including thyroglobulin (TG), which harbored somatic mutations in 3% of the entire cohort. Surprisingly, although TG mutations were not exclusive to mutations in the RAS-MAP kinase pathway, their presence was associated with a significantly worse clinical outcome, which suggests a pathogenic role beyond driving initial oncogenesis. Analysis of metastatic PTC tissue revealed significant enrichment for TG mutations (p<0.001), including events of apparent clonal expansion. Our results suggest a previously unknown role of TG somatic mutations in the pathogenesis of PTC and its malignant evolution.

  Study EGAS00001003357

• Genomic Profiling of Thyroid Cancer Reveals a Role for Thyroglobulin in Metastasis

  Papillary thyroid carcinoma (PTC) has a wide geographic variation in incidence, being highest in Saudi Arabia where it is only second to breast cancer as the most common cancer among females. Genomic profiling of PTC from Saudi Arabia has not been attempted previously. We performed whole-exome sequencing of 101 PTC samples and the corresponding genomic DNA to identify genes with recurrent somatic mutations, followed by sequencing of these genes using a next-generation gene panel approach in further 785 samples. In addition to BRAF, N-RAS and H-RAS, which have previously been shown to be recurrently mutated in PTC, our analysis highlights additional genes, including thyroglobulin (TG), which harbored somatic mutations in 3% of the entire cohort. Surprisingly, although TG mutations were not exclusive to mutations in the RAS-MAP kinase pathway, their presence was associated with a significantly worse clinical outcome, which suggests a pathogenic role beyond driving initial oncogenesis. Analysis of metastatic PTC tissue revealed significant enrichment for TG mutations (p<0.001), including events of apparent clonal expansion. Our results suggest a previously unknown role of TG somatic mutations in the pathogenesis of PTC and its malignant evolution.

  Study EGAS00001001788

• Whole exome sequencing of a cold agglutinin disease patient

  We performed whole exome sequencing of bone marrow monoclear cells derived from a cold agglutinin disease patient. Aim of our study is to elucidate the pathogenesis of hemolytic anemia.

  Study JGAS000612

• Whole exome sequencing of a cold agglutinin disease patient

  We performed whole exome sequencing of bone marrow monoclear cells derived from a cold agglutinin disease patient. Aim of our study is to elucidate the pathogenesis of hemolytic anemia.

  Study JGAS000583

• SNP Array data for: Three-dimensional patient-derived models of glioblastoma retain intra-tumoral heterogeneity

  4 sets of matched patient-derived-organoids (PDOs),  -neurospheres (PDNs), and parent glioblastoma tissue (12 samples total) underwent SNP array analysis. 200ng of each sample DNA extracted via a commercial kit (Qiagen) and loaded onto the Global Screening Array v2.0 array. Data is provided as raw red and green .idat files.

  Dataset EGAD00010002744

• Profiling the Microbiome of Pediatric Gut with Metagenomic Short-Read Sequencing

  This dataset contains short-read metagenomic sequencing of stool, as well as intestinal tissue and tissue washes, from preterm infants. 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 EGAD00001016052

• Predictor_ChemoNEAR_TNBC (2019-08-14)

  In this study a collection of core biopsies from breast cancer patients receiving neoadjuvant chemotherapy as part of the ChemoNEAR trial will be investigated. The study is intended to detect early acquired resistance in women with diagnosed breast carcinoma. Samples will undergo whole genome sequencing and analysis, including use of HR Predict. . This dataset contains all the data available for this study on 2019-08-14.

  Dataset EGAD00001005255

• Breast cancer women lack normal lifelong immune response after full-term pregnancies

  Immunological tolerance during pregnancy is necessary for women’s bodies to accept the semi-allogenic fetus. Interestingly, “immune evasion”, which consists of some similar immunological changes, was recently proposed as a hallmark of cancer. Looking at these results, it seems paradoxical that increasing number of full-term pregnancies (FTP) reduces the risk of breast cancer in women. Our aim was to use a systems epidemiology approach to investigate this paradox by modelling breast cancer incidence as a function of parity in the Norwegian Women and Cancer (NOWAC) cohort, then testing the mathematical model using gene expression from blood in a subcohort of these women: the NOWAC postgenome cohort. Lastly, we undertook a gene set enrichment analysis for immunological gene sets. A linear trend nicely fitted the dataset showing an 8% decrease in risk for each FTP, independent of stratification on other risk factors and lasting for decades after a woman’s last FTP. However, when we looked at gene expression we found that hundreds of genes showed linear trends in cancer-free controls, but this was not the case in /any/ of the samples from breast cancer cases. In the gene set enrichment analysis, samples consisted of human blood or cord blood and mouse bone marrow or spleen. We found more adaptive gene sets than expected in humans and more innate gene sets than expected in mice. None of the gene sets provided information about the long-term effects of immunological tolerance during pregnancy, but the lack of relevant reductionist experiments hampers our interpretation. We suggest that, after resolution at birth, the immunological tolerance induced by pregnancy augments immune response to cancer development.

  Study EGAS00001002616

• NIH RECOVER: A Multi-Site Pathology Study of Post-Acute Sequelae of SARS-CoV-2 Infection

  The RECOVER tissue pathology study is a cross-sectional study designed to define and characterize the epidemiology, natural history, clinical spectrum, and underlying mechanisms of post-acute effects of SARS-CoV-2 infection in a diverse population representative of the general COVID-19 population in the US. The autopsy study will characterize the pathology of PASC in decedents who die more than 60 days after initial onset or after hospital discharge, whether in-hospital or out-of-hospital at time of death, and who meet the working definition of PASC as defined by the recent World Health Organization publication given in Section 5.4. The autopsy study will also explore the pathology of acute SARS-CoV-2 infection in a smaller subset of decedents who died between15-60 days from symptom onset. This protocol defines the common set of clinical data elements, autopsy procedures for tissue collection, core measures, pathology protocols, shared pathology tissues, data elements, and methodology. Each investigator site is expected to perform autopsies on the decedents to address the pathophysiology of the potential long-term effects of SARS-CoV-2 infection on human health. The Consortium analysis plan aims to address research questions by incorporating: 1) tissue obtained from autopsies performed at each Phase II participant's site; and 2) tissue available from other pathology investigators/autopsy sites within the Consortium.

  Study phs003768

• Elucidating Mechanisms of the Graft versus Leukemia Effect of Hematopoietic Stem Cell Transplant for Acute Myeloid Leukemia

  Donor lymphocyte infusion (DLI) is an established mode of adoptive cellular therapy for treatment of relapsed disease after allogeneic hematopoietic stem cell transplantation (HSCT). For patients with acute myeloid leukemia (AML), the response rate to DLI is only 20%. Here we use next generation sequencing technologies to understand the transcriptomic and immunologic features associated with response or resistance to therapy.

  Study phs003630

• Landscape and significance of multiple mutations in oncogenes.

  This study is a comprehensive pan-cancer study of oncogenic multiple mutations (MMs) which includes long-read whole-genome sequencing data (n = 3).

  Study EGAS00001003763

• Evolution and clinical impact of genetic epistasis within EGFR-mutant lung cancers

  The current understanding of tumorigenesis is largely centered on a monogenic driver oncogene model. This paradigm is incompatible with the prevailing clinical experience in most solid malignancies: monotherapy with a drug directed against an individual oncogenic driver typically results in incomplete clinical responses and eventual tumor progression1-7. By profiling the somatic genetic alterations present in over 2,000 cases of lung cancer, the leading cause of cancer mortality worldwide, we show that combinations of functional genetic alterations, i.e. genetic collectives dominate the landscape of advanced-stage disease. We highlight this polygenic landscape and evolution of advanced-stage non-small cell lung cancer (NSCLC) through the spatial-temporal genomic profiling of 7 distinct tumor biopsy specimens and 6 plasma specimens obtained from an EGFR-mutant NSCLC patient at (1) initial diagnosis of early-stage disease, (2) metastatic progression, (3) sequential treatment and resistance to 2 EGFR inhibitors, (4) death. The comprehensive genomic analysis of this case, coupled with circulating free (cf) tumor DNA profiling of additional advanced-stage EGFR-mutant NSCLC clinical cohorts with associated treatment responses uncovered features of evolutionary selection for multiple concurrent gene alterations: including the presence of EGFR inhibitor-sensitive (EGFRL858R;EGFRexon19del) or inhibitor-resistant (EGFRT790M;EGFRC797S) forms of oncogenic EGFR along with cell cycle gene alterations (e.g. in CDK4/6, CCNE1, RB1) and activating alterations in WNT/β-catenin and PI3K pathway genes, which our data suggest can cooperatively impart non-redundant functions to limit EGFR targeted therapy response and/or promote tumor progression. Moreover, evidence of an unanticipated parallel evolution of both EGFR T790M and two distinct forms of oncogenic PIK3CA was observed. Our study provides a large-scale clinical and genetic dataset of advanced-stage EGFR-mutant NSCLC, a rationale for specific polytherapy strategies such as EGFR and CDK4/6 inhibitor co-treatment to potentially enhance clinical outcomes, and prompts a re-evaluation of the prevailing paradigm of monogenic-based molecular stratification for targeted therapy. Instead, our findings highlight an alternative model of genetic collectives that operate through epistasis to drive lung cancer progression and therapy resistance.

  Study EGAS00001002604

• Origin of second malignancies in children

  Pediatric cancers are rare diseases, and children without known germline predisposing conditions who develop a second malignancy during developmental ages are extremely rare. We present four such clinical cases and through whole-genome and error-correcting ultra-deep duplex sequencing of tumor and normal samples, we explored the origin of the second malignancy in four children, uncovering different routes of development. The exposure to cytotoxic therapies was linked to the emergence of a secondary AML. A common somatic mutation acquired early during embryonic development was the driver of two solid malignancies in another child. In two cases, the two tumors developed from completely independent clones diverging during embryogenesis. Importantly, we demonstrate that platinum-based therapies contributed at least in one order of magnitude more mutations per day of exposure than aging to normal tissues in these children.

  Study EGAS50000000167

• Exploiting evolutionary steering in cancer therapy

  This dataset contains 9 bam files of exome sequencing for an experiment of evolved resistance. Here a barcoded cell line (HCC827 - POT) has been treated under high concentrations of gefitinib (GEF) and trametinib (TRM) until resistance has evolved, as well as under control conditions (DMSO). The dataset contains exome sequencing of confluent cells for three replicates for each anti-cancer drug as well as two replicates of growth under DMSO conditions. The original barcoded cell line (POT) was also exome sequenced and is included in the cohort. Sequencing was performed on the Illumina NovaSeq platform.

  Dataset EGAD00001005782

• Mechanisms of Extreme Genomic Instability at Large Transcribed Genes

  Inhibiting DNA replication leads to copy number variant (CNV) formation throughout the genome, especially at chromosome fragile sites (CFSs). We previously showed that these hotspots for genome instability reside in late-replicating domains associated with large transcribed genes. In this study, we compared aphidicolin (APH)-induced CNV and CFS frequency between wild-type cells and isogenic cells in which FHIT gene transcription was ablated. We further examined the impact of altering RNase H1 expression on CNV or CFS induction frequency and analyzed R-loop formation genome-wide in a human fibroblast cell line. Data sets include Bru-seq nascent RNA transcription, whole genome sequencing for replication timing, SNP microarray analysis, and DRIP-seq. Results suggest that large gene transcription is a determining factor in replication stress-induced genomic instability and that CFSs mainly result from transcription-dependent passage of unreplicated DNA into mitosis with low R-loop levels observed at these loci.

  Study phs002066

• Genomic Profiling of Melanoma

  This study reports on genomic profiling [whole-exome sequencing (WXS), bulk RNA sequencing (RNA-seq), and/or single-cell RNA sequencing (scRNA-seq)] of patient-derived melanoma samples and matched normal samples. The goal is to elucidate the genetic and cellular basis of sun-exposed and sun-shielded melanomas and to relate these findings to survival and regional metastasis. Specimens were collected by the Tissue Resource Core of the Yale SPORE in Skin Cancer with participants' informed signed consent according to Health Insurance Portability and Accountability Act (HIPAA) regulations with a Human Investigative Committee protocol. The melanomas used for sequencing were from fresh or snap-frozen tumors, or from short-term cell cultures. The cell cultures were routinely checked for mycoplasma contamination and were discarded when found positive. Matching normal DNA was from circulating lymphocytes or normal skin. We also include 77 WES-sequenced samples from the Yale Spitzoid neoplasm repository, which collects specimen and data according to a protocol approved by the Yale Human Investigative Committee.

  Study phs000933

• Identification and targeting of extremely high-risk gamma delta T-ALL in children

  Acute lymphoblastic leukemia expressing the gamma delta T cell receptor (γδ T-ALL) is an uncommon, poorly understood disease. We studied 200 pediatric γδ T-ALL enrolled on clinical trials to understand the clinical and genetic features of this disease, which showed variation in outcome according to age and genetic driver. γδ T-ALL diagnosed in children under three years of age was extremely high-risk and enriched for genetic alterations leading to both LMO2 activation and STAG2 inactivation. Using patient samples and isogenic cell lines, we show that inactivation of STAG2 profoundly perturbs chromatin organization by altering enhancer-promoter looping and results in deregulation of gene expression related to T-cell differentiation. High throughput drug screening identified a vulnerability in DNA repair pathways arising from STAG2 inactivation, which was efficaciously targeted by PARP inhibition. These data provide a diagnostic and therapeutic framework for classification and risk stratification of pediatric γδ T-ALL.

  Study EGAS50000000018

• Identifying genetic variants that alter TCR usage in the peripheral repertoire

  The relationship between genetic variation and CD8+ T-cell receptor (TCR) repertoire usage in patients receiving Immune Checkpoint Blockade (ICB) therapy for cancer is unexplored. We have conducted a genome-wide and human leukocyte antigen (HLA)-focused analysis of CD8+ T-cell TCR repertoire to identify genetic determinants of variable gene (V-gene) and CDR3 K-mer usage from samples taken prior to and after ICB (n=250). We identify 11 cis and 10 trans V-gene associations, primarily to the MHC, that meet genome-wide significance. TCR clones containing HLA associated V-genes were less stable across treatment, whilst at the single-cell level, genetically associated clones demonstrate subset enrichment and increased tumor reactivity expression profiles. Notably, patients with HLA-matched TCR clones demonstrate improved overall survival. Our work indicates a complex relationship between genotype and TCR repertoire in the context of ICB treatment, with novel implications for understanding factors relating to therapeutic response and patient outcomes.

  Study EGAS00001008189

• COVID19 Host Genetic Initiative

  The COVID-19 host genetics initiative is a bottom-up collaborative effort that has three main goals: 1. Provide an environment to foster the sharing of resources to facilitate COVID-19 host genetics research (e.g. protocols, questionnaires). 2. Organize analytical activities across studies to identify genetic determinants of COVID-19 susceptibility and severity. 3. Provide a platform to share the results from such activities, as well as the individual-level data where possible, to benefit the broader scientific community. Here, we release the harmonized individual-level data for the subset of individuals who participated in COVID-19 HGI. Please refer to this data dictionary: https://docs.google.com/spreadsheets/d/1whu_MjShXxbdoAJMCYxZ5C-vWOcRivwfWglTcBRNZgQ/edit#gid=470747846 Please cite both Nakanishi, T el al. J Clin Invest 2021 (PMID: 34597274) and COVID-19 Host Genetics Initiative, Nature 2021 (PMID: 34237774) when you use these data for your publications.

  Study EGAS00001005304

• Comprehensive epigenomic profiling reveals the extent of disease-specific chromatin states and informs drug target discovery in ankylosing spondylitis

  Ankylosing spondylitis (AS) is a common, highly heritable inflammatory arthritis characterised by enthesitis of the spine and sacroiliac joints. Genome-wide association studies have revealed >100 genetic associations but their functional effects remain largely unresolved. Here, we present a comprehensive transcriptomic and epigenomic map of disease-relevant blood immune cell subsets from AS patients and healthy controls. We report differential disease signatures for specific genomic regions from individual -omic modalities and multi-omic integration, showing enrichment at genetically associated loci and evidence for altered monocyte function in AS. We link putative functional SNPs with cognate genes using high-resolution Capture-C at 10 loci, including PTGER4 and ETS1. We also show how disease-specific functional genomic data can be integrated with GWAS evidence to enhance therapeutic target discovery. This study combines multiple epigenetic and transcriptional analysis with GWAS to identify cell types, candidate drug target genes and transcriptional regulation of likely pathogenic relevance.

  Study EGAS00001006233

• Comprehensive epigenomic profiling reveals the extent of disease-specific chromatin states and informs drug target discovery in ankylosing spondylitis

  Ankylosing spondylitis (AS) is a common, highly heritable inflammatory arthritis characterised by enthesitis of the spine and sacroiliac joints. Genome-wide association studies have revealed >100 genetic associations but their functional effects remain largely unresolved. Here, we present a comprehensive transcriptomic and epigenomic map of disease-relevant blood immune cell subsets from AS patients and healthy controls. We report differential disease signatures for specific genomic regions from individual -omic modalities and multi-omic integration, showing enrichment at genetically associated loci and evidence for altered monocyte function in AS. We link putative functional SNPs with cognate genes using high-resolution Capture-C at 10 loci, including PTGER4 and ETS1. We also show how disease-specific functional genomic data can be integrated with GWAS evidence to enhance therapeutic target discovery. This study combines multiple epigenetic and transcriptional analysis with GWAS to identify cell types, candidate drug target genes and transcriptional regulation of likely pathogenic relevance.

  Study EGAS00001006945

• scRNA-seq of HSPC treated with gemcitabine and carboplatin

  4 samples of 2000000 HSPCs in 2 ml media each were then prepared and treated for 24 hours: carboplatin-high: 150 µg/ml carboplatin carboplatin-low: 18.75 µg/ml carboplatin gemcitabine: 25 ng/ml gemcitabine control: no drug Single-cells were subsequently extracted using the ddSEQ™ Single-Cell Isolator (Bio-Rad) and later sequenced using the SureCell™ Whole Transcriptome Analysis 3' Library Prep Kit (Illumina) on the NextSeq 500 System (Illumina) using the NextSeq 500/550 High Output Kit v2.5 150 Cycles (Illumina) all following the manufacturer's instructions. The raw FASTQ-files are available as read 1 and read 2 files from 4 lanes for each sample giving a total of 16 FASTQ-files. The FASTQ-files were also processed following the ddSeeker (Romagnoli, D., et al., BMC Genomics 2018, doi:10.1186/s12864-018-5249-x) and Drop-seq (Macosko, E.Z., et al., Cell 2015, doi:10.1016/j.cell.2015.05.002) protocols for processing scRNA-seq data to yield the final digital gene expression (dge) for each cell of each sample. This has resulted in one dge text file and one dge summary text file per sample. These 8 text-files with dge data are found in the zip-compressed analysis data-file.

  Dataset EGAD00001006080

• Integrated Analysis of Multimodal Single-Cell Data

  The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single cell genomics and necessitates new computational methods that can define cellular states based on multiple data types. Here, we introduce 'weighted nearest neighbor' analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of hundreds of thousands of human white blood cells alongside a panel of 228 antibodies to construct a multimodal reference atlas of the circulating immune system. We demonstrate that integrative analysis substantially improves our ability to resolve cell states and validate the presence of previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets, and to interpret immune responses to vaccination and COVID-19. Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets, including paired measurements of RNA and chromatin state, and to look beyond the transcriptome towards a unified and multimodal definition of cellular identity. All CITE-seq and ECCITE-seq raw matrices are available in GEO database under the accession number GEO: GSE164378.

  Study phs002315

• Integrative genome profiling in AML

  AML emerges as a consequence of accumulating independent genetic aberrations that direct regulation and/or dysfunction of genes resulting in aberrant activation of signalling pathways, resistance to apoptosis and uncontrolled proliferation. Given the significant heterogeneity of AML genomes, AML patients demonstrate a highly variable response rate and poor median survival in response to current chemotherapy regimens. For the past 4 years we have conducted gene expression profiling on purified bone marrow populations equating to normal haematopoietic stem and progenitor cells from healthy subjects and patients with de novo AML in order to identify AML signatures of aberrantly expressed genes in cancer versus normal. We are now applying a series of bioinformatic methodologies combined with clinical and conventional diagnostic data to establish novel genomics strategies for improved prognostication of AML. Additionally, we use our AML signatures to unravel oncogenic signalling pathway activities in AML patients and test inhibitory drugs for these pathways inn preclinical therapeutic programmes. We consider that superimposing GEP and clinical data for our AML patient cohort with additional data on their mutational status will significantly improve the prognostic power of the study as well as unravel yet unknown mutations associated with aberrant signalling activities of oncogenic pathways.

  Dataset EGAD00001001873

• A Genome-Wide Association Comparative Analysis of Response of AF Patients to Rate Control Therapy; A Collaboration between the NIH Pharmacogenomics Research Network and the RIKEN Yokohama Institute Center for Genomic Medicine

  The goal of this study was to identify genetic predictors of response to rate control therapy in patients with AF. We conducted a genome-wide association study (GWAS) focusing on subjects with a history of atrial fibrillation. Rate control therapy for AF uses a range of drugs (beta-adrenergic receptor blockers, calcium channel blockers, and digitalis) to depress conduction through the AV node, thereby preventing rapid rates and minimizing symptoms. In large groups of patients, such as the Vanderbilt AF Registry (a clinical and genetic repository with over 1200 patients with ECG-confirmed AF) from which these study subjects were drawn, approximately 5% display failure of aggressive AV nodal-blocking therapy to control ventricular rate. In these patients, interruption of the AV node by ablation and pacemaker implantation are necessary for adequate rate control. Study cases were individuals who underwent AV node ablation and pacemaker implantation after combined therapy with 3 AV nodal-blocking agents was ineffective in rate control. Controls for this study were individuals who met standardized rate-control efficacy criteria (as described in AFFIRM study, Wyse et al, NEJM 2002; PMID: 12466506) for optimal rate control with 2 or fewer AV nodal-blocking agents. Two additional groups were genotyped by RIKEN: An additional group of patients with AF as well as subjects undergoing cardiac surgery in whom AF did not occur post-operatively. All study participants were recruited and treated/evaluated at Vanderbilt University Medical Center. This study was conducted by the Pharmacogenomics of Arrhythmia Therapy subgroup of the Pharmacogenetics Research Network, a nationwide collaboration of scientists studying the genetic contributions to drug response variability. Genotyping was performed by the RIKEN research institute in Japan using the Illumina 610 Quad Beadchip platform.

  Study phs000439

• BRAF_and_MEK_resistant_cell_line_clones

  The Sanger Institute has the largest collection of genetically-characterised cancer cell lines world-wide (we have collected >1000 human cancer cell lines which are being screened against >400 cancer therapeutics (http://www.sanger.ac.uk/genetics/CGP/translation). These lines have been characterized to the level of gene copy number, gene expression and cancer gene mutation sequence data. This has enabled us to select melanoma lines with varying BRAF mutational status and that show sensitivity to a range of BRAF inhibitors. Sensitive lines are being used to generate resistant clones by serial exposure to increasing concentrations of BRAF and MEK inhibitors and these are being characterised by genome-wide copy number analysis as well as by whole exome sequencing.

  Study EGAS00001000172

• Prediction of pigmentation phenotypes by SNP typing in a Northern German population

  Human pigmentation traits are of great interest to many research areas, from ancient DNA analysis to forensic science. We aimed to develop a gene-based predictive model for pigmentation phenotypes in a realistic target population for forensic case work from Northern Germany. Our aim was to determine whether better prediction accuracy can be achieved, or fewer genetic markers may suffice, than in previously studied, genetically more heterogeneous populations. We investigated the association between eye, hair and skin colour, and 12 candidate single nucleotide polymorphisms (SNPs) from six genes. Our study comprised two samples of 300 and 100 individuals from Northern Germany who were carefully characterized with regard to pigmentation phenotypes. The first sample was used to select trait-associated SNPs whereas the second sample served to estimate odds ratios (ORs) and to quantify the predictive capability of the respective SNP genotypes. SNP rs12913832 in HERC2 was found to be strongly associated with blue eye colour (OR=15.6, p<1.2•10-4) and to yield reasonable predictive power (90% sensitivity, 63% specificity). SNP associations with hair and skin colour were weaker and genotypes less predictive. A comparison to two recently published sets of markers to predict eye and hair colour revealed that the consideration of additional SNPs with weak to moderate effect increases the predictive power in Northern Germans for eye colour, but not for hair colour. In addition, fine phenotyping and differentiation of hair colour (light / dark and red tint / no red tint) were found to increase the number of significant genotype-phenotype associations.

  Study EGAS00001001174

• Molecular Phenotyping to Accelerate Genomic Epidemiology (MolPAGE)

  MolPAGE is an integrated EU project that aims to develop methods and tools for discovery of biomarkers associated with diabetes (see www.ocdem.ox.ac.uk for MolOBB and www.twinsuk.ac.uk for MolTWIN).

  Study EGAS00000000102

• SNP array analysis of spondylocostal dysostosis patient iPSCs and gene edited isogenic controls

  This study, "SNP Array Analysis of Gene Edited SDV Patient iPSCs" is part of a larger study where we applied our recently established experimental in vitro model system of the human segmentation clock, for the analysis of human segmentation defects of the vertebrae (SDV) including spondylocostal dysostosis (SCD). To this end we generated patient-derived iPSC lines, identified putative disease-causing mutations and corrected these mutations using CRISPR/Cas9-based genome editing technology. We identified in the patient-sample originally obtained from the NIGMS Human Genetic Cell Repository at the Coriell Institute for Medical Research (#: GM13539) heterozygous compound mutations in MESP2. These mutations were corrected accordingly and the resulting clones were genotyped by SNP array analysis.

  Study phs001975

• RNA sequencing data from patient derived colorectal cancer organoids

  This study aimed to develop NovumRNA, a bioinformatics pipeline designed to predict non-canonical tumor-specific antigens (ncTSAs) from human tumor RNA-sequencing data, potentially broadening the target pool for cancer neo-epitope-based immunotherapies. The pipeline was utilized to analyze RNA-seq data from ten patient-derived colorectal cancer (CRC) organoids, representing seven microsatellite stable (MSS) and three microsatellite instable (MSI) tumors. The goal was to explore the ncTSA landscape in CRC, particularly in MSS cases, which typically exhibit low tumor mutational burden and limited response to current immunotherapies. The study identified comparable ncTSA burdens across MSI and MSS tumors, suggesting new avenues for immunotherapy targeting non-canonical antigens in CRC. NovumRNA is available at: https://github.com/ComputationalBiomedicineGroup/NovumRNA.

  Study EGAS50000000685

• Pilot_experiment_on_functional_genomics_in_osteoarthritis_RNA

  The aim of this work is to apply an integrated systems approach to understand the biological underpinnings of large joint (hip and knee) osteoarthritis which culminates in the need for total joint replacement (TJR). In this pilot we will assess the feasibility of the approach in the relevant tissue. We will obtain diseased and non-diseased tissue (cartilage and endochondral bone) following TJR, coupled with a blood sample, from 12 patients. We will characterise the 12 pairs of diseased and non-diseased tissue samples in terms of transcription (RNASeq) The pilot will help assess the feasibility of isolating sufficient levels of starting material for the different approaches, and will instigate the development of analytical approaches to synthesising the resulting data.

  Study EGAS00001001203

• Acral Melanoma PDXs from the admixed Brazilian Population - Patient Derived Xenograft samples VCF files with somatic SNV and INDELs - Whole exome sequencing data

  Raw, flagged and annotated VCF files with somatic calls made with CavEMan and Pindel for Patient Derived Xenograft samples. Variant effect prediction was run with Ensembl VEP v103. Acral melanoma (AM) is an aggressive melanoma subtype with limited therapeutic options and poor outcomes. In non-European descent and admixed populations, like in Latin America, it can account for a significant proportion of cutaneous melanoma cases. Here, we performed comprehensive genomic and functional profiling of AM from a uniquely diverse Brazilian cohort. Whole-exome and transcriptome sequencing was performed on both tumours and patient-derived xenograft (PDX) samples. The PDX were obtained from a comprehensive collection of patient-derived xenograft (AM-PDX) models that we established which faithfully retained the histopathological and genomic features of the original tumours.

  Dataset EGAD00001015749

• Transcriptome of Chronic Pain and Disease

  The Functional Genomics Section (FGS) is a part of the National Institute of Dental and Craniofacial Research (NIDCR) within the National Institutes of Health (NIH). Research at the FGS focuses on understanding the mechanics involved in nociception through both clinical samples from patients with chronic pain and mouse models of pain. Pain is relayed from the periphery to the central nervous system through specialized sensory neurons known as nociceptors. The cell body of nociceptors resides in neuronal structures that branch off of the spinal cord known as dorsal root ganglia (DRG). The DRG is a heterogenous tissue containing not only sensory neurons like nociceptors, but also glial cells, capillaries, fibroblasts, and resident macrophages. The interaction between the nociceptors and these DRG cell types can have a significant role in affecting neuronal hyperexcitability and downstream pain sensitivity. To better understand the cellular factors involved in producing conditions of chronic pain, DRGs from consenting organ donors were collected from individuals experiencing pain disorders such as painful diabetic neuropathy and rheumatoid arthritis. A multi-omics approach is being used to identify molecular mechanisms that lead to pain hypersensitivity in patients with chronic pain.  

  Study phs002548

• Whole Exome Sequencing in Alopecia Areata Identifies Rare Mutations in KRT82

  Alopecia areata (AA) is an autoimmune disorder, in which the body's own immune cells attack hair follicels resulting in hair loss. It is a complex genetic disease with 14 associated loci previously identified in our genome-wide association study (GWAS). In the study, we performed the whole-exome sequencing (WES) on 849 AA patients with the aim to identify the novel rare variants in genes contributing to AA susceptibility. We performed gene-collapsing analyses and identified keratin 82 (KRT82 Gene ID: 3888) as the highest associated AA gene in the three rare damaging collapsing models with p<6.7E-07 in one of the models. The KRT82 gene is a hair-specific type II keratin expressed in the hair shaft cuticle during the anagen phase of the hair cycle. We reported the lower expression of KRT82 in AA hair follicles, compared to controls, and the KRT82 expression is absent from the bulb region, the site of AA immune attack. This study emphasizes the significance of using WES and gene collapsing analyses to identify rare variation in a functionally relevant risk gene using a moderate sample size.  

  Study phs002632

• Fecal metagenomics and plasma metabolomics

  This dataset contains all fecal shotgun metagenomics and metabolomics of the study which investigated the effects of the probiotic strain Anaerobutyricum soehngenii. Shotgun data is from three different time points, baseline and two follow up. Metabolomics sets are pre and post intervention, both fasted and post prandially. Data on randomization and metformin use can be found in the analysis.

  Dataset EGAD50000000608

• Tumor Profiler Project - OV cell-free DNA data additional samples

  The dataset contains amplicon sequencing data from 7 samples from 7 different patients with ovarian cancers. Cell free DNA was collected from plasma. Sequencing was performed on an Ion Torrent platform and the sequencing data is provided in bam format. These samples are from patients not classified as having high-grade serous adenocarcinoma.

  Dataset EGAD50000001412

• Nimblegen

  The aim of this project is to identify rare variants in the 1q region associated with type 2 diabetes. To this end 651 case samples and 651 control samples from six populations have been pooled (pool sizes range from 27-33 individuals), and are being sequenced. The hybridization solution being used captures the exons and UTRs of genes in the 1q region.

  Dataset EGAD00001000424

• The spatial organization of intratumor heterogeneity and evolutionary trajectories of metastasis in hepatocellular carcinoma

  A dataset consisting of Multi-regional Whole Exome Sequencing (WES) and Whole Genome Sequencing (WGS) data for 54 samples from 9 patients with hepatocellular carcinoma. The dataset includes 45 tumor samples and 9 normal blood samples. Selected somatic variants were validated by Sequenom. Patients covered are: Patient 1, Patient 2, Patient 3, Patient 4, Patient 5, Patient 6, Patient 7, Patient 8, Patient 9 and Patient 10.

  Dataset EGAD00001003138

• Primary ER-positive Breast Cancer Treated with Neoadjuvant Letrozole

  These are tumor biopsies and corresponding normal samples from patients with early stage ER+/HER2- breast cancer who had received the aromatase inhibitor letrozole for 10-21 days prior to surgery.

  Study phs000857

• Somatic variant calls from whole-exome sequencing of three tumor–normal matched cell lines

  This dataset comprises matched tumor–normal cell line samples. Whole-exome sequencing data are available for three matched pairs, and targeted deep sequencing–based somatic variant calls are provided for them as well in the form of VCF files.

  Dataset EGAD50000002392

• Engineering large chromosomal deletions by CRISPR-Cas9

  Arm-level chromosomal deletions are a prevalent and defining feature of cancer. A high degree of tumor-type and subtype specific recurrencies suggest a selective oncogenic advantage. However, due to their large size it has been difficult to pinpoint the oncogenic drivers that confer this advantage. Suitable functional genomics approaches to study the oncogenic driving capacity of arm-level deletions are limited. Here we present an effective technique to engineer arm-level deletions by CRISPR-Cas9 and create isogenic cell line models. We simultaneously induce double-strand breaks (DSBs) at two ends of a chromosomal arm and select the cells that have lost the intermittent region. Using this technique, we induced arm-level deletions on chromosome 11q (65 MB) and chromosome 6q (53 MB) in neuroblastoma cell lines. Such isogenic models enable further research on the role of arm-level deletions in tumor development and growth, and their possible therapeutic potential.

  Study EGAS00001005134

• Whole exome sequencing of long-term, never relapse exceptional responders of trastuzumab-treated HER2+ metastatic breast cancer

  The dataset contains Whole Exome Sequencing data (BAM files) of 22 samples from HER2+ metastatic breast patients. For 9 of the 13 tumours samples there are paired controls available from normal tissue. There are 8 tumours samples that are from treatment-responder patients and 5 tumours samples from non responder patients.

  Dataset EGAD00001006217

• A Functional Network of Gastric-Cancer-Associated Splicing Events Controlled by Dysregulated Splicing Factors

  Except for a few genes known to have oncogenic spliceforms in gastric cancer, the full scope of aberrant splicing in gastric oncogenesis remains unclear. In this study, we elucidated the alternative splicing events associated with gastric carcinogenesis and identified upstream regulators governing these events. We performed RNA-seq on 19 matched tumor/normal pairs and a panel of gastric cancer cell lines, and identified 361 tumor associated (TA) alternative splicing events (ASEs), which included known oncogenic ASEs in genes such as INSR, FGFR2, CD44 and KRAS. We further identified 8 splicing factors dysregulated in gastric tumors, the expression of which are correlated to the splice ratio of the TA ASEs. We thereby constructed a dysregulated splicing network in gastric cancer, consisting of alternative splicing changes correlated to their potential regulators. This network featured three potential regulatory modules centered around the splicing factors ESRP2, MBNL1 and PTPB1. Knockdown of each splicing factor led to the expected changes in splicing of approximately half of the ASEs assayed. Thus, dysregulation of the splicing factors indeed was the cause of many of the TA ASEs. Pathway enrichment analysis showed that genes affected by tumor associated splicing were pre-dominantly involved in cytoskeletal organization. Concordant with this, knockdown of the splicing factors regulating the TA ASEs led to the expected changes in trans-well migration activity. Thus, we have established for the first time a comprehensive splicing network that likely drives gastric tumor progression, based on which novel therapeutic targets can be identified for further evaluation.

  Study EGAS00001002256