15041 results for "cancer studies using rna-seq"

in 47.02 milliseconds.

• Mechanism of Decitabine response in MDS/AML patients

  The dataset includes single cell RNA sequencing data from 17 AML/MDS patients undergoing a decitabine clinical trial. In total 47 samples were interrogated using 10X genomics ChromiumTM 140 Single Cell 5' Reagent Kit. The dataset includes bam files for each sample generated using CellRanger with default parameters.

  Dataset EGAD50000001354

• Single-cell RNA-seq data of bronchoalveolar lavage (BAL) fluid in late severe COVID-19

  We performed single-cell RNA-sequencing of cells in the bronchoalveolar lavage (BAL) fluid of late severe COVID-19. This study provides detailed insights into the alveolar macrophage response to SARS-CoV-2 infection and reveals a profibrotic macrophage response in severe COVID-19 patients.

  Dataset EGAD00001008161

• Whole-genome and transcriptome sequencing files obtained in monozygotic twins discordant for Mayer-Rokitansky-Küster-Hauser syndrome

  Raw, unfiltered, paired-end fastq files obtained through whole-genome and RNA-sequencing, respectively. RNA-seq of affected individuals in three twin pairs. WGS of blood in five twin pairs as well as uterine rudiment tissue of selected affected individuals.

  Dataset EGAD00001008992

• Whole exome and RNA sequencing data from the OXIRI phase 1b clinical trial in Asian pancreatic ductal adenocarcinoma (PDAC) patients

  This dataset contains 8 samples, each of which has paired-end WXS fastq files for Tumour and Normal samples, as well as RNA-Seq fastq file.

  Dataset EGAD00001008632

• RNA-seq of PBX1 knock-down or overexpressing cell lines

  The whole study comprises of two patient cohorts. Screening cohort: 40 patients of Germany; validation cohort: 40 patients from Asia. Further, bile duct and CCA cell lines have been analyzed. This dataset contains 44 samples derived from RNA-sequencing data of bile duct and CCA cell lines. Data was generated on Illumina NovaSeq 6000 device in paired-end mode and is stored in compressed FASTQ file format.

  Dataset EGAD00001011325

• RNA sequencing of follicular T cell lymphoma

  Study EGAS00001004646

• Identification of molecule relationship between intravenous leiomyomatosis and uterus myoma

  Up to now, there are two hypothesis about the pathogenesis of the relationship of intravenous leiomyomatosis and uterine myoma. One theory suggests that the IVL comes from the smooth muscle cell in the vessel wall.The other theory indicates that the IVL derives from the uterine myometrium. However, limited to the technology, few studies have been deeply explore the underlying relation. In this study, we employ the RNA sequencing to explore the molecule relationship between IVL and uterus myoma. In order to identify the molecule relationship between IVl and uterine myoma we conducted transcriptome sequencing and bioinformaitc analysis

  Dataset EGAD00001003356

• Megabase-scale Haplotyped Genomic Analysis of Normal and Cancer Genomes

  We experimentally determined Mb-scale haplotypes from germline and cancer genome sequencing. Using a microfluidic process that partitions long DNA fragments into hundreds of thousands of barcoded reactions, we determined haplotype blocks from matched colorectal cancer samples in the delineation of haplotypes of allelic imbalances and other genomic instability events.

  Study phs000898

• Targeted_Pulldown_Validation_of_mutations_found_in_whole_genome_sequencing

  This experiment is to inform us of the validity of using pre-made library material to perform a bespoke pulldown experiment to validate the mutations found between the whole genome sequencing of the DNA from the same individuals cancer and normal material. This is to identify the valid and informative mutations in cancer genomes.

  Study EGAS00001000260

• The Sea Islands Genetic Network (SIGNET): Identifying genetic contributors to diabetes and dyslipidemia in African Americans

  Recent genome-wide association studies (GWAS) have successfully identified genetic variants that influence diabetes risk in European populations, however most do not have a major impact on diabetes risk in populations of African descent. The African American (AA) population from the Sea Islands of coastal South Carolina and Georgia has high rates of type 2 diabetes, low levels of admixture, and in general, consume a diet rich in saturated fats. We postulate that this unique combination of ancestral and environmental factors results in a more consistent penetrance of diabetes risk alleles, as well as enrichment of risk alleles of African origin. The existing DNA samples and rich phenotypic data from the Sea Island Families Project comprise a unique resource for genetic studies of type 2 diabetes and related metabolic traits such as dyslipidemia. Our central hypothesis is that the increased risk for T2DM in AA compared with European American (EA) is due, in part, to susceptibility alleles of African origin, and that these alleles can be identified using a GWAS. The Specific Aims are to: 1) Identify genetic risk factors for type 2 diabetes utilizing DNA samples and data from the Sea Island Families Project, Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study recruited from SC, GA, NC, and AL; and a GWAS approach; 2) Identify genetic contributors to lipoprotein subclasses in African Americans using the lipoprotein subclass profile (particle size and concentration for multiple subclasses of VLDL, LDL, and HDL) assessed by NMR at LipoScience, Inc., and the GWAS data from Aim 1. The rationale for this project is that identification and validation of novel pathophysiological pathways and informed selection of candidate genes for diabetes risk will inform development of new, targeted prevention and treatment strategies in this underserved, high risk population.

  Study phs000433

• RNA sequencing of periprostatic fat after a 6 month deep androgen deprivation therapy

  Androgen deprivation therapy treated patients (n=11) were recruited from an open label neoadjuvant phase II study in which patients with high-risk disease received a ‘supercastration’ regimen consisting of degarelix 240/80 mg subcutaneously every four weeks; abiraterone acetate 500 mg orally daily titrating upwards every two weeks by 250 mg to a final dose of 1000 mg daily; bicalutamide 50 mg orally daily; and prednisolone 5 mg orally twice daily for a total of 6 months (Australian New Zealand Clinical Trials Registry 12612000772842). Untreated patients with similar pre-treatment characteristics were obtained from a prospective prostatectomy biorepository22,23. Prior to ligation of the dorsal venous complex and prostate pedicles, the anterior prostate was defatted and the specimen was removed immediately, placed in a sterile container and transferred on ice for long-term storage in the vapour phase of liquid nitrogen. A total of 50–100 µg of adipose tissue was separated from fresh frozen samples stored at −160°C. RNA was isolated using the Qiagen RNeasy Lipid Tissue Mini Kit and eluted in 35 µL nuclease-free water. 0.5–1 µg of total RNA was used as the input for cDNA library synthesis using TruSeq RNA Sample Prep Kit v2 (Illumina), and libraries were constructed according to manufacturer’s instructions. Samples were sequenced on a HiSeq 2500 (Illumina) using 101 base paired-end chemistry, aiming for 50 million mapped paired-end reads per sample.

  Dataset EGAD00001004971

• University of Pennsylvania CAR T Cell Responding and Non-responding Patients

  The adoptive transfer of autologous T cells genetically modified to express a CD19-specific, 4-1BB/CD3zeta-signaling chimeric antigen receptor (CAR; CTL019) has shown remarkable activity in patients with B acute lymphoblastic leukemia. Similar therapy can induce long-term remissions for relapsed/refractory chronic lymphocytic leukemia (CLL) patients, but in only a small subset of subjects. The determinants of response and resistance to CTL019 therapy of CLL are not fully understood. We employed next generation sequencing of RNA (RNA-seq) to identify predictive indicators of response to CTL019 treatment. We performed RNA-seq on leukapheresis and manufactured infusion product T cells from patients with heavily pre-treated and high-risk disease. To characterize potency, we also performed RNA-seq on the cellular infusion product after CAR-specific stimulation. Our findings indicate that durable remission in CLL is associated with gene expression signatures of early memory T cell differentiation (e.g., STAT3), while T cells from poorly- or non-responding patients exhibited elevated expression of key regulators of late memory as well as effector T cell differentiation, apoptosis, aerobic glycolysis, hypoxia and exhaustion. These gene expression signatures, along with additional immunological biomarkers, may be used to identify which patients are most likely to respond to cellular therapies and suggest manufacturing modifications that might potentiate the generation of maximally efficacious infusion products. In a follow-up study, we report multiplex CRISPR-Cas9 gene editing on T cells in humans to test the hypothesis that disrupting genes encoding the endogenous T cell receptor (TCR), TCRα (TRAC) and TCRβ (TRBC), as well as PD-1 (PDCD1) would enhance the efficacy of autologous T cells engineered to express a transgenic NY-ESO TCR. We used single cell RNA-seq to comprehensively characterize the transcriptomic phenotype of this T cell product and its evolution over time in a patient with sarcoma. Notably, this patient's transferred T cells that persisted in vivo demonstrated increases in expression of genes associated with a central memory state (IL7R, TCF7). These findings may guide future trials involving administration of genetically redirected, genome -edited T cells.In this follow-up study, we investigated whether CRISPR-Cas9-mediated disruption of PDCD1 and/or CTLA-4 could restore CART dysfunction in healthy donors and/or CLL patients. We show that depletion of CTLA-4 rescues the function of T cells from leukemia patients that previously failed CART cell treatment. We performed single-cell RNA sequencing and characterized the transcriptomic landscape of CTLA-4 KO CART19 cells that showed higher proliferation and anti-tumor efficacy by permitting unopposed CD28 signaling and maintenance of CAR expression on the T cell surface under stress-test conditions of chronic antigen exposure. Our findings reveal that selective disruption of CTLA-4 invigorates dysfunctional patient T cells, providing a strategy for increasing patient responses to CART cell therapy.

  Study phs001707

• Broad utility of ultrasensitive analysis of ctDNA dynamics across solid tumors treated with immunotherapy

  Prior studies have suggested the biomarker potential of plasma circulating tumor DNA (ctDNA) in cancer patients treated with immune checkpoint inhibitors (ICIs). In order to characterize the potential role of ultrasensitive ctDNA detection in the management of these patients we have performed tumor whole-genome-informed, ultrasensitive ctDNA analysis—tracking approximately 1,800 tumor-specific mutations per patient—in a retrospective cohort (n=136) and a prospective validation cohort (n=66) across 24 cancer types treated with ICIs alone or in combination with bispecific antibodies or immune cell engagers. Analyzing 1,455 longitudinal samples, we found that ctDNA molecular response measured as early as 3 weeks after treatment initiation correlated with improved progression-free and overall survival, while ctDNA clearance at any time strongly correlated with radiological response and prolonged survival. Additionally, ctDNA dynamics distinguished true progression from pseudoprogression and predicted outcomes in patients receiving continued immunotherapy beyond initial progression. This study highlights the broader applicability of ultrasensitive ctDNA as a biomarker across cancer types and immunotherapy modalities.

  Study EGAS50000001333

• Somatic mutation analysis based on Whole exome Sequencing (WES) of multiple tumor biopsies, patient-derived spheroids and leukocyte DNA from colorectal cancer patients (vcf files)

  Somatic mutations were called using whole exome Sequencing (WES) data from colorectal cancer samples (dataset EGAD00001003821) using MuTect2, with matched constitutional WES-data obtained from leukocytes samples as reference.

  Dataset EGAD00001003823

• Uncovering tumor intrinsic and extrinsic factors that regulate hepatocellular carcinoma growth using patient derived xenograft assays

  Exome Sequencing and RNA Sequencing Data for PDX Samples

  Dataset EGAD00001005734

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__Oesophageal_adenocarcinoma

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001003702

• Differential Gene Expression in Cryptorchid Testes

  Differential Gene Expression in Cryptorchid Testes Study uses whole-genome RNA profiling of testicular biopsies to determine a potential causative role of isolated congenital cryptorchidism in azoospermia and/or infertility in the context of our previously published GeneChip data. Cryptorchid patients, aged 7 months to 5 years and otherwise healthy, were enrolled in this prospective study. During surgery, testicular tissue biopsies were obtained for histological examination and RNA-sequencing (RNA-seq). Fifteen patients were selected based on the histological results and were divided into two groups. Seven were classified as belonging to the high infertility risk (HIR) and eight to the low infertility risk (LIR) group. Cryptorchid boys in the high infertility risk group lacked transformation of gonocytes into Ad spermatogonia due to impaired mini puberty. This group of patients will be infertile despite successful surgery.

  Study phs001275

• PCA Atlas Chromium scRNA-seq and demultiplexing support (FASTQs, BAMs, capture-level VCFs and mapping tables)

  This dataset contains Chromium single-cell RNA-seq data and demultiplexing support for the PCA Atlas study EGAS00001008332. Included data objects: - 16 Chromium scRNA-seq FASTQ runs (EGAR accessions) for captures PCa1–PCa16. - 16 aligned BAM analyses (one Cell Ranger possorted_genome_bam.bam per capture). - 16 capture-level genotype VCF analyses derived from the Axiom UK Biobank array, used as demultiplexing panels. - demux_map.csv (EGAZ00001945520): donor–capture–sample mapping for genotype-based demultiplexing. - chromium.csv (EGAZ00001945537): run-level mapping linking captures, EGA samples, runs (EGAR), experiments (EGAX) and BAM analyses. Together these objects provide a complete view of the Chromium scRNA-seq data and the genotype-based demultiplexing support needed to reproduce donor assignment and downstream analyses.See also https://zenodo.org/records/17372603

  Dataset EGAD00001015795

• Genome-wide cell-free DNA termini in patients with cancer

  The structure, fragmentation pattern, length and terminal sequence of cell-free DNA (cfDNA) is under the influence of nucleases present in the blood. We hypothesized that differences in the diversity of bases at the end of cfDNA fragments can be leveraged on a genome-wide scale to enhance the sensitivity for detecting the presence of tumor signals in plasma. We surveyed the cfDNA termini in 72 plasma samples from 319 patients with 18 different cancer types using low-coverage whole genome sequencing. The fragment-end sequence and diversity were altered in all cancer types in comparison to 76 healthy controls. We converted the fragment end sequences into a quantitative metric and observed that this correlates with circulating tumor DNA tumor fraction (R = 0.58, p < 0.001, Spearman). Using these metrics, we were able to classify cancer samples from control at a low tumor content (AUROC of 91% at 1% tumor fraction) and shallow sequencing coverage (mean AUROC = 0.99 at >1M fragments). Combining fragment-end sequences and diversity using machine learning, we classified cancer from healthy controls (mean AUROC = 0.99, SD = 0.01). Using unsupervised clustering we showed that early-stage lung cancer can be classified from control or later stages based on fragment-end sequences. We observed that fragment-end sequences can be used for prognostication (hazard ratio: 0.49) and residual disease detection inresectable esophageal adenocarcinoma patients, moving fragmentomics toward a greater clinical implementation.

  Study EGAS00001005738

• Genome-wide cell-free DNA termini in patients with cancer

  The structure, fragmentation pattern, length and terminal sequence of cell-free DNA (cfDNA) is under the influence of nucleases present in the blood. We hypothesized that differences in the diversity of bases at the end of cfDNA fragments can be leveraged on a genome-wide scale to enhance the sensitivity for detecting the presence of tumor signals in plasma. We surveyed the cfDNA termini in 72 plasma samples from 319 patients with 18 different cancer types using low-coverage whole genome sequencing. The fragment-end sequence and diversity were altered in all cancer types in comparison to 76 healthy controls. We converted the fragment end sequences into a quantitative metric and observed that this correlates with circulating tumor DNA tumor fraction (R = 0.58, p < 0.001, Spearman). Using these metrics, we were able to classify cancer samples from control at a low tumor content (AUROC of 91% at 1% tumor fraction) and shallow sequencing coverage (mean AUROC = 0.99 at >1M fragments). Combining fragment-end sequences and diversity using machine learning, we classified cancer from healthy controls (mean AUROC = 0.99, SD = 0.01). Using unsupervised clustering we showed that early-stage lung cancer can be classified from control or later stages based on fragment-end sequences. We observed that fragment-end sequences can be used for prognostication (hazard ratio: 0.49) and residual disease detection inresectable esophageal adenocarcinoma patients, moving fragmentomics toward a greater clinical implementation.

  Study EGAS00001005747

• miRNASeq profiles from Indian HFrEF Cohort

  The dataset contains miRNA profiling from a cohort of 49 HFrEF patients. The myocardium samples were collected from these patients during heart transplant of LVAD implantation procedure. The RNA samples were collected in RNAlater. Small RNA libraries were prepared using QIAseq miRNA Library Kit, Qiagen and sequenced on Illumina HiSeq4000.

  Dataset EGAD50000001194

• Dicer and/or ADAR1 depleted HEK293-LGP2 cells

  This dataset includes bulk RNA-sequencing data from HEK293-L cells subjected to siRNA-mediated knockdown of Dicer and/or ADAR1. In total, 12 samples are included, representing four experimental groups with triplicate biological replicates. RNA was extracted using TRIzol according to standard protocols and sequenced on an Illumina NovaSeq 6000.

  Dataset EGAD50000002044

• Single-cell RNA sequencing of acute myeloid leukemia patients

  Single-cell RNA sequencing was performed on bone marrow mononuclear cells from 8 acute myeloid leukemia patients at diagnosis. The profiling was performed using 10x Genomics 3' (5 samples) and 5' (3 samples) platforms. The raw data are available as fastq files.

  Dataset EGAD00001006173

• Single cell RNA-sequencing of treatment naïve PDAC patient samples

  Single cell RNA-sequencing of treatment naïve PDAC patient samples. We have 10 samples, sequenced using the 10X genomics chromium platform with 3 prime chemistry. We are submitting FASTQ files representing the index files (I1), Read1 (R1) and Read2 (R2).

  Dataset EGAD00001008961

• Small molecule screen reveals synergy of cell cycle checkpoint kinase inhibitors with DNA-damaging chemotherapies in medulloblastoma (methylation dataset)

  human medulloblastoma xenograft isolated from mouse brain was frozen and genomic DNA or RNA was extracted. Bisulfite converted DNA was processed and hybridised to illumina EPIC or 450K arrays using standard protocols. RNAseq was performed on total RNA.

  Dataset EGAD00001006583

• Integrative understanding of human immune system by functional genomics and development of intervention strategies for the prevention of autoimmune diseases

  To elucidate the feature of age-associated helper T (ThA) cells and its contribution to autoimmune diseases, CD4+ T cell subsets from 19 rheumatoid arthritis (RA), 62 systemic lupus erythematosus (SLE), 40 idiopathic inflammatory myopathy (IIM) and 64 healthy controls (HC) were collected (Naive_CD4, Th1, Th2, Th17, Tfh, Fr._I_nTreg, Fr._II_eTreg, Fr._III_T, ThA). RNA-seq was performed with each CD4+ T cell subset samples.

  Study JGAS000626

• Whole Transcriptome Sequencing of NXF1 or CRM1 depleted Cell

  mRNA exporters, NXF1 and CRM1 are known to function in mRNA export. However, since each target mRNA has not been identified genome-widely, it is not clear whether they export exclusive mRNA subsets. To reveal this point, we prepared the nuclear and the cytoplasmic RNAs under either exporter inhibited condition and carried out RNA-seq. In these experiments, we also focused in the export machinery of aberrant transcripts that usually retained and decayed in the nucleus.

  Study JGAS000294

• The genomic landscape of follicular and diffuse large B-cell lymphoma

  As part of the ICGC, the ICGC MMML-Seq project performed whole genome sequencing and RNA sequencing of follicular and diffuse large B-cell lymphoma. Follicular and diffuse large B-cell lymphomas are the most common B-cell lymphomas in adulthood. Analyses were performed in concordance with the guidelines of the ICGC. The results define the genomic landscape of structural variants, somatic single nucleotide variants and mutational signatures in these lymphomas

  Study EGAS00001002199

• GINS3 fibroblast RNAseq

  The eukaryotic CDC45/MCM2-7/GINS (CMG) DNA helicase unwinds the DNA double helix during DNA replication. We report the identification of individuals presenting with a Meier-Gorlin syndrome (MGS) like phenotype, secondary to hypomorphic variants in the GINS3 gene.  To verify whether the GINS3 variant affected the transcriptome, RNA-seq was performed from 3 fibroblast cultures derived from a patient with compound heterozygous GINS3 variants, and 1 replicate of fibroblasts derived from each of the two parents.

  Study EGAS00001006038

• 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

• minION fastq files of 10 different tumor samples from the Master program (H021)

  Nanopore RNA Sequencing was done for 10 tumor samples. Direct cDNA sequencing was performed using the SQK-DCS109 kit (Oxford Nanopore Technologies). For analysis of a single sample on a MinION flow cell (version R9.4.1), 5 μg RNA was used as input. For multiplexing on a MinION flow cell, 2.5 μg RNA per sample was used as input, and the native barcoding expansion kit EXP-NBD104 was employed in conjunction with SQK-DCS109. After reverse transcription with Maxima H Minus Reverse Transcriptase (Thermo Scientific), second-strand synthesis was performed using the 2x LongAmp Taq Master Mix (New England Biolabs). The resulting double-stranded cDNA was subjected to end-repair and dA-tailing using the NEBNext Ultra End Repair/dA-Tailing Module (New England Biolabs). For multiplexed libraries, this step was followed by barcode ligation and library pooling. Next, libraries were quantified with a Qubit Fluorometer 3.0 (Life Technologies). Finally, sequencing adapters were added to the library preparations and ligated with Blunt/TA Ligase Master Mix (New England Biolabs), followed by further quality control using a Qubit. Samples ACC1 and ACC2 were analyzed on individual MinION flow cells, while the remaining eight samples were sequenced as multiplexed libraries on two MinION flow cells by pooling four samples for each run. Five ACC samples were also analyzed individually on Flongle flow cells

  Dataset EGAD00001008970

• RNASeq profiles of ROBUST clinical trial and processed WGS mutation calls output

  The dataset contains RNAseq profiles of 1040 patients from the ROBUST clinical trial (NCT02285062). The Allprep DNA/RNA FFPE kit was used to simultaneously purify genomic DNA and total RNA from formalin-fixed, paraffin embedded (FFPE) tissue sections. RNAseq libraries (75PE, 50M) were constructed using Illumina TruSeq RNA Access method. Fastq files are included. Also includes processed WGS mutation calls output.

  Dataset EGAD50000000482

• RNA Sequencing of Control and Myotonic Dystrophy Type 1 Cells During Myogenic Differentiation

  To investigate gene expression dynamics during myogenic differentiation in myotonic dystrophy type 1, RNA was collected from immortalized control, patient-derived, and CRISPR/Cas9-corrected myoblasts at proliferation (day -2) and at days 1 and 5 of differentiation. High-quality RNA was isolated and sequenced using poly(A)-enriched or rRNA-depleted protocols, yielding 100 bp paired-end reads with high coverage. A subset of samples at day 1 underwent deeper sequencing to enhance transcriptome resolution.

  Dataset EGAD50000001647

• Using RNA-sequencing to characterize the resistance to lirafugratinib

  In addition to Exome-sequencing, we used RNA-sequencing to also characterize resistance to lirafugratinib with whole exome sequencing in patients with FGFR2-driven cancers, treated in the phase 1/2 ReFocus trial (NCT04526106) and enrolled in the UNLOCK program at Gustave Roussy

  Study EGAS50000001370

• Single-cell RNA sequencing of erythroid and megakaryocytic acute myeloid leukemia patient cells

  Single-cell RNA sequencing was performed on bone marrow mononuclear cells of a patient with acute myeloid leukemia with erythroid differentiation of the blasts and on peripheral blood mononuclear cells of a patient with acute myeloid leukemia with megakaryocytic differentiation of the blasts. The dataset contains raw fastq files of these two samples with single-cell RNA sequencing performed using the 10x Genomics platform.

  Dataset EGAD00001009865

• Single-cell characterization of human GBM reveals regional differences in tumor-infiltrating leukocyte activation

  Raw sequencing files from scRNA-seq dataset used in Schmassmann et al. 2023. Single-cell characterization of human GBM reveals regional differences in tumor-infiltrating leukocyte activation. Elife 12 (https://elifesciences.org/articles/92678) Dataset content: 14 samples from 5 donors File type: paired-end fastq files Technology: Illumina sequencing Experimentation used: scRNA-seq using the 10X technology

  Dataset EGAD50000000434

• Mapping genetic effects on cell type-specific chromatin accessibility using single nucleus ATAC-seq

  Gene regulation is highly cell type-specific and understanding the function of non-coding genetic variants associated with complex traits requires molecular phenotyping at cell type resolution. In this study we performed single nucleus ATAC-seq (snATAC-seq) and genotyping in peripheral blood mononuclear cells from 13 individuals. We mapped chromatin accessibility QTLs (caQTLs) in each immune cell type and sub-type in a subset of 10 samples of European genetic ancestry.

  Study EGAS00001006184

• GTestimate: Improving relative gene expression estimation in scRNA-seq using the Good-Turing estimator

  This study introduces a novel scRNA-seq normalization method, which takes unobserved genes into account. To validate GTestimate we designed a cell targeted amplification strategy, enabling us to sequence a small set of cells twice, once at a "typical" sequencing depth and once at a "ultra-deep" sequencing depth.

  Study EGAS50000000915

• Tumor Profiler Melanoma Study

  The Tumor Profiler Study is an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease. Technologies used are digital pathology, targeted NGS, single-cell RNA, single-cell DNA, bulk RNA, bulk proteotyping, single-cell CyTOF, imaging mass cytometry, pharmacoscopy, 4i Drug Response Profiling, and cell-free DNA. These technologies were applied to 240 tumor samples collected over 3 years across three cancer indications: metastatic melanoma, metastatic epithelial ovarian cancer, and acute myeloid leukemia (AML). Here, we publish the scRNA, scDNA, and bkRNA data of the melanoma cohort.

  Study EGAS50000000599

• Targeted NGS panel

  The mutational status of 121 genes recurrently altered in B-cell lymphoma was examined in 55 of 56 diagnostic and 10 of 12 relapse samples using a custom targeted NGS panel. Libraries were generated from 150 ng of DNA using molecular-barcoded library adapters (ThruPLEX Tag- seq kit; Takara) coupled with a custom hybridization capture-based method (SureSelectXT Target Enrichment System Capture strategy, Agilent Technologies). The quality of the libraries was determined using the Bioanalyzer high sensitivity DNA kit (Agilent) and quantified by PCR using the KAPA library quantification kit (KAPA Biosystems). Finally, the libraries were pooled and sequenced in the MiSeq instrument (Illumina).

  Dataset EGAD00001010842

• Rapid Acceleration of Diagnostics - Digital Health Technologies' (RADx-DHT) Collection of General Research Use Datasets

  This individual-level collection of datasets contains all the RADx Digital Health Technologies (RADx-DHT) studies in dbGaP for General Research Use (GRU). Access to studies in this collection is on the RAPIDS platform. To request access to this study collection, select phs003666 in the dbGaP when submitting a data access request.

  Study phs003666

• ChiLDReN/BA: Genetic Studies of Biliary Atresia in the Childhood Liver Disease Research Network

  Biliary atresia (BA) is a progressive necroinflammatory process initially involving the extra-hepatic biliary tree. Little is known about the factors that cause BA or the factors that influence disease progression. A variety of genetic, autoimmune, and environmental influences have been hypothesized to be important. Most studies to date have focused on the neonate and young child with BA, yet the older surviving child with BA can provide important information about genetics as well as natural history.The Childhood Liver Disease Research Network (ChiLDReN) conducts two longitudinal and observational studies that include BA patients: Biliary Atresia Study in Infants and Children (BASIC) and A Prospective Database of Infants with Cholestasis (PROBE). Using samples from participants in these two protocols, we have formed the largest known data set of biliary atresia patients in the world. ChiLDReN is performing a series of genomic analyses, with subsequent analyses being released as subsequent versions of this registration, phs003356. Version 1 concerns PKD1L1.About the PKD1L1 Analysis (phs003356.v1): While multiple factors have been implicated in the perinatal biliary injuries that characterize BA, a definitive etiology has not yet been established. This study is part of a larger project to characterize the largest cohort of pediatric BA patients through whole-exome sequencing (WES). In this analysis, we examine the WES of those with various laterality defects to determine whether genetic factors could be identified to explicate the etiopathogenesis of BA in biliary atresia splenic malformation (BASM) syndrome. We specifically explored variations in the PKD1L1 gene, which recently has been identified in mouse models as playing a role in laterality.

  Study phs003356

• Comprehensive Genomic Characterization of Acral Melanoma

  In this study, we performed paired tumor/normal long insert whole genome and exome sequencing and tumor RNA sequencing on primary or metastatic acral melanoma tumors collected from 34 patients. Patients were enrolled from either Vanderbilt University or the Memorial Sloan-Kettering Cancer Center. We report an integrated analysis of DNA and RNA sequencing data to describe genomic and transcriptomic characteristics of acral melanoma.

  Study phs001036

• RNA-seq of whole blood and PBMC samples from immunotherapy treated NSCLC patients

  This dataset contains 228 paired fastq files sequenced with Illumina Novaseq 6000, and the file with the sample and clinical data.

  Dataset EGAD50000000389

• scRNA-seq of bulk and sorted NK

  Here we performed single-cell RNA sequencing to characterize NK cell subsets. Sorted NK cell subsets representing discrete stages of NK cell differentiation as well as bulk NK cells were sequenced.

  Dataset EGAD50000000020

• MDACC Lymphoma & Myeloma The function of LAMP5 in multiple myeloma

  This dataset includes Fastq files from bulk RNA seq from myeloma cell lines (MM.1S and NCI-H929) expressing a DOX-inducible LAMP5 shRNA, S1 (CACTTCAAAGACGCAGTCAGT) or S5 (GCACACAGAATACAACCTCAT), or a scramble control treated with DOX during 48h.

  Dac EGAC50000000495

• DynaTag for efficient profiling of transcription factors in small samples and single cells

  The dataset included Dynatag data for the occupancy of transcription factors and single nuclei RNA-seq data. Corresponding metadata is provided for both experiments.

  Dataset EGAD50000001562

• RNA-Seq soft tissue sarcoma tumoroid biobank

  Dataset EGAD00001008467

• Single cell RNA seq of the developing human embryo brain

  The study aims at identifying the cell types and lineages of the developing human brain.

  Study EGAS00001004107

• preinvasive LUAD

  Whole-exome sequencing coupled with RNA-seq of preinvasive (n=98) and invasive (n=99) lung adenocarcinoma samples.

  Dataset EGAD00001005479

• PDAC organoid genomic heterogeneity

  Two primary tumor-derived PDAC organoids were subjected to SNP array, RNA-seq, and single-cell WGS.

  Dataset EGAD00001009741

• NASH RNA-seq data

  This dataset includes transcriptome sequencing of 17 paired NAFLD-HCC samples and adjacent normal tissues. All the experiments were performed on Illumina HiSeq 2000 platform with raw reads stored in fastq format.

  Dataset EGAD00001004326

• Multi-omic analysis of the tumor microenvironment shows clinical correlations in Ph1 study of atezolizumab +/- SoC in MM

  Multiple myeloma (MM) remains incurable, and treatment of relapsed/refractory (R/R) disease is challenging. There is an unmet need for more targeted therapies in this setting; deep cellular and molecular phenotyping of the tumor and microenvironment in MM could help guide such therapies. This phase 1b study (NCT02431208) evaluated the safety and efficacy of the anti-programmed death-ligand 1 monoclonal antibody atezolizumab (Atezo) alone or in combination with the standard of care (SoC) treatments lenalidomide (Len) or pomalidomide (Pom) and/or daratumumab (Dara) in patients with R/R MM. Study endpoints included incidence of adverse events (AEs) and overall response rate (ORR). A novel unsupervised integrative multi-omic analysis was performed using RNA sequencing, mass cytometry immunophenotyping, and proteomic profiling of baseline and on-treatment bone marrow samples from patients receiving Atezo monotherapy or Atezo+Dara. A similarity network fusion (SNF) algorithm was applied to preprocessed data. Eighty-five patients were enrolled. Treatment-emergent deaths occurred in 2 patients; both deaths were considered unrelated to study treatment. ORRs ranged from 11.1% (Atezo+Len cohorts, n=18) to 83.3% (Atezo+Dara+Pom cohort, n=6). High-dimensional multi-omic profiling of the tumor microenvironment and integrative SNF analysis revealed novel correlations between cellular and molecular features of the tumor and immune microenvironment, patient selection criteria, and clinical outcome. Atezo monotherapy and SoC combinations were safe in this patient population and demonstrated some evidence of clinical efficacy. Integrative analysis of high dimensional genomics and immune data identified novel clinical correlations that may inform patient selection criteria and outcome assessment in future immunotherapy studies for myeloma.

  Study EGAS00001007286

• Precision Interception of Gastric Cancer Precursors Through Molecular and Cellular Risk Stratification

  The GAstric Precancerous conditions Study (GAPS, NCT04191551) is a cross-sectional study of patients undergoing endoscopy who are at increased risk of gastric cancer. Enrolled patients are administered a standardized questionnaire, undergo clinical biopsy collection using the Sydney system, and consent for the collection of saliva, blood, and additional gastric tissue. All patients are scored for intestinal metaplasia using the operative link on gastric intestinal metaplasia (OLGIM) scoring system.

  Study phs003648

• Shot-gun stool metagenomics and colorectal cancer risk.

  This study aims to identify metagenomics biomarkers in colorectal cancer (CRC). The study includes 156 samples of shot-gun stool metagenomics, corresponding to 51 patients with CRC, 54 patients with high-risk adenoma, and 51 healthy controls. The sequencing libraries were prepared with 2 µg of total DNA using the Nextera XT DN Sample Prep Kit (Illumina, San Diego, CA, USA). Sequencing was performed at 150 nucleotides, paired-end, using an Illumina HiSeq 4000 platform.

  Study EGAS00001007025

• Investigation of Brain Nitrogen Metabolism in Partial Ornithine Transcarbamylase Deficiency (OTCD) Using 1H MRS, DTI, and fMRI

  This is a case controlled, observational study. This project studies cognitive and motor dysfunction in adult and pediatric patients who are female carriers of ornithine transcarbamylase deficiency (OTCD) or are males with late onset presentation (outside of the newborn period) of OTCD, utilizing state of the art MRI (magnetic resonance imaging), a non-invasive technique. This project seeks to improve our understanding of the underlying neural mechanisms that contribute to metabolic, cognitive, sensory and motor abnormalities in urea cycle disorders, which although individually rare, collectively constitute a major cause of neonatal encephalopathy, leading to significant morbidity and mortality. As a result of this study, a greater understanding of the anatomic, cognitive, motor, and biochemical underpinnings of neurologic damage attributable to this metabolic disorder will be gained. Experimental approaches will combine sensory, cognitive and motor testing with structural, functional and molecular magnetic resonance imaging to study symptomatic and asymptomatic heterozygous female carriers of X-linked ornithine transcarbamylase deficiency (OTCD), and late onset hemizygous males. Participants to be included in the studies ranged from ages 7-60 years and were compared to an age-matched typically developed (TD) comparison group. For our research, we use anatomic MRI, functional Magnetic Resonance Imaging (fMRI), and magnetic resonance spectroscopy (MRS) to monitor brain activity. The technique of fMRI provides detailed maps of the brain areas underlying human mental activities. By using fMRI, we are able to observe how the brain is functioning while a person is performing a specific task, such as reading. We can not only observe differences in the structure of the brain, but can also measure differences in brain function and activity as well. This information will ultimately be used to provide a basis for designing more effective interventions and methods for early identification of learning disabilities in patients with OTCD and related disorders. We will also use MRS to study various brain chemicals such as glutamine using the non-invasive MRI imaging techniques.

  Study phs001296

• Childhood Cancer Data Initiative (CCDI): Texas Pediatric Patient Derived Xenograft 

  The DNA/RNA samples of patients for which PDX models were developed were from a population of children, adolescents, and young adults from South Texas. Consent was obtained for collection of malignant and non-malignant tissue samples for genetic analysis and for the development of models to study new ways to treat cancer. For additional details, please refer to these publications: PMID: 37915590; PMID: 37990009.

  Study phs003215

• Small RNA sequencing of untreated and castration resistant prostate cancer

  Small RNA sequencing of 28 untreated prostate cancers, 12 castration resistant prostate cancers, and 3 benign prostatic hyperplasias.

  Dataset EGAD00001000611

• Batch-corrected read-count matrix of the RNAseq Datasets of CLUSTER JIA pre-MTX cohort

  Samples were sequenced with NovaSeq6000 and the sequencing files were processed using the RSSnextflow workflow (https://gitlab.com/b8307038/rssnextflow). The raw read counts from all batches were combined. Analysis-ready batch-corrected read counts were generated using ComBat-seq.

  Dataset EGAD50000002169

• Validated Single-cell RNA sequencing in early breast cancer

  Single-cell RNA and VDJ sequencing of early breast cancer

  Dataset EGAD00001006608

• Whole Exome Sequencing of Parathyroid Cancer Identifies Candidate Driver Mutations and Core Pathways

  Here we performed genomic characterization of twenty-nine sporadic parathyroid cancers using next generation whole exome sequencing. Thirty-three novel candidate driver genes for sporadic parathyroid cancer were proposed, in addition to previously known driver genes CDC73 and MEN1.

  Study phs001765

• Molecular Epidemiology of Colorectal Cancer (MECC) Metastasis Study: A Germline Variant on Chromosome 4q31.1 Associates with Susceptibility to Developing Colon Cancer Metastasis

  This study compared Ashkenazi Jewish individuals with Stage IV metastatic colon cancer to those with non-metastatic Stage I or II colon cancers. A genome-wide association study, using a 2-stage design, identified a significant association with rs60745952.

  Study phs001045

• Multiregion Whole Exome and Smart-Seq3 single cell RNA sequencing of Breast Tumors

  Multiple regions were cut out of each tumor extracted form breast cancer patients and two experiments were run: - Whole exome sequencing on each of the regions plus an adjacent normal tissue sample - Smart-Seq3 Single cell RNA sequencing on EPCAM+ CD45- sorted cells from different tumor regions

  Study EGAS00001006851

• Molecular Biomarkers in Glioma (Mechanisms and Therapeutic Implications of Hypermutation in Gliomas)

  This study seeks to genomically and mechanistically examine the basis for resistance of glioblastoma to chemotherapy, radiation therapy, and targeted therapy including immunotherapies. The study design addresses two Aims. In Aim 1, we will test the hypothesis that treatment with radiation and temozolomide or other therapies leads to consistent genetic changes in human tumors using whole exome sequencing of paired pre- and post-treatment tumor samples to determine large-scale changes in population structures and single cell whole genome sequencing to evaluate the effects of these treatments on microheterogeneity. In Aim 2, we will test the hypothesis that genetic changes identified in post-treatment glioblastomas (GBMs) functionally contribute to various forms of resistance in GBM using patient derived cell lines (PDCL) and patient derived xenografts (PDX). These studies will create a comprehensive understanding of genetic evolution during standard-of-care therapy for GBM. They will inform diagnostic approaches for assignment of targeted therapeutics in the recurrent setting and identify genetic changes driving resistance. Therapeutic targeting of these novel resistance drivers could represent a rational approach to substantially improve our existing standard of care for GBM patients.

  Study phs001967

• Molecular Sub-grouping of CNS-PNET

  In our study we aimed to define CNS-PNET subgroups. We performed Expression, Genotyping and/or Immunohistochemistry on 142 samples from 20 worldwide centers. Using these techniques, we have identified three molecular subgroups with distinct expression and copy number patterns, as well as, unique clinical characteristics. Specifically, these molecular subgroups were distinguished by primitive neural (group 1), oligoneural (group 2), and mesenchymal lineage (group 3) gene-expression signatures with differential expression of cell-lineage markers LIN28 and OLIG2. Our report underscores the importance of concerted, collaborative efforts to study large retrospective cohorts of tumours and patients to accelerate biological and ultimately therapeutic studies of rare tumours. The outcome of such a collaboration allowed us to identify LIN28 and OLIG2 as promising diagnostic and prognostic molecular markers for CNS PNET that warrant further assessment in prospective clinical trials.

  Study EGAS00000000116

• RNAseq Transcriptomic Analyses of European Ancestry Samples in MGS Dataset

  Schizophrenia is a common and severe psychotic disorder. While some common SNPs and rare copy number variants have been identified as being significantly associated with disease risk, the biological mechanisms remain undefined. To identify gene expression abnormalities in schizophrenia, we generated whole-genome gene expression profiles using RNAseq on lymphoblastoid cell lines from schizophrenia cases and controls of European ancestry. Subsets of these data have been used in three studies: (1) gene expression outliers (extreme tails of the distribution of transcript expression values) in 634 cases and 713 controls (PMID: 26022996); (2) baseline differential gene expression by affection status in 529 cases and 660 controls (PMID: 28418402); and (3) baseline versus dopamine stimulated differential gene expression by affection status in 514 cases and 690 controls (PMID: 30115913). Various classes of classes were enriched in the differentially expressed genes, especially brain expressed genes and genes related to immune processes.

  Study phs001932

• CRISPR-Mediated ASD Gene Knockout Reduces Neuronal Activity

  Autism Spectrum Disorder is phenotypically and genetically heterogeneous. We present a CRISPR gene editing strategy to insert a protein tag and premature termination sites creating an induced pluripotent stem cell (iPSC) knockout resource for functional studies of 10 ASD-relevant genes (AFF2/FMR2, ANOS1, ASTN2, ATRX, CACNA1C, CHD8, DLGAP2, KCNQ2, SCN2A, TENM1). Neurogenin 2 (NGN2)-directed induction of iPSCs allowed production of excitatory neurons, and mutant proteins were not detectable. RNAseq revealed convergence of several neuronal networks. Using both patch-clamp and multi-electrode array approaches, the electrophysiological deficits measured were distinct for different mutations. However, they culminated in a consistent reduction in synaptic activity, including reduced spontaneous excitatory post-synaptic current frequencies in AFF2/FMR2-, ASTN2-, ATRX-, KCNQ2- and SCN2A-null neurons. Despite ASD susceptibility genes belonging to different gene ontologies, isogenic stem cell resources can reveal common functional phenotypes, such as reduced functional connectivity.

  Study phs001816

• The Surveillance Monitoring for ART Toxicities (SMARTT) and the Women and Infants Transmission Study (WITS)

  Zidovudine (ZDV) is a nucleoside reverse transcriptase inhibitor (NRTI) which competitively inhibits HIV reverse transcriptase and is incorporated into the viral DNA, resulting in DNA chain termination. It was the first approved antiretroviral medication used for preventing HIV transmission from mother to child. However, in vitro and animal studies have suggested genotoxicity of ZDV and no study has evaluated potential impact of in utero ZDV exposure using genomic sequencing technologies. In this study, we investigate markers of genomic damage detected in peripheral blood mononuclear cell samples obtained from 91 ZDV-exposed and, for comparison, 94 NRTI-unexposed HIV-uninfected children born to HIV-infected mothers during the first week after birth. We utilize high-throughput DNA sequencing (whole exome sequencing) and genotype array methods to comprehensively identify potential clonal somatic single nucleotide variants (SNVs) and large acquired copy number alterations (SCNAs) related to ZDV exposure.

  Study phs002061

• NHLBI TOPMed: Stanford Cardiovascular Institute iPSC Biobank Study (SCVI)

  The proposed Stanford Cardiovascular Institute (SCVI) Biorepository will curate and manage an expanded collection of human induced pluripotent stem cell (iPSC) lines and provide investigators with iPSC materials generated using standardized protocols, with the overall objective of promoting the continued adoption and development of iPSC technology in cardiovascular research. Human iPSCs have revolutionized disease modeling, drug screening, and therapeutic research. However, it is also recognized that the need for specialized technical expertise and the associated cost have largely prevented individual research laboratories from adopting iPSC models in their inquiries, particularly in studies requiring multiple cell lines. To address this bottleneck, the proposed Biorepository will maintain our existing collection of iPSC lines and further expand the collection of iPSCs by recruiting 1,000 healthy, hypertrophic cardiomyopathy (HCM), dilated cardiomyopathy (DCM) donors of both sexes and diverse racial/ethnic backgrounds (African Americans, Asians, Hispanics, and Whites).

  Study phs002338

• Genetic landscape of inherited retinal dystrophies affected cases in Spain

  Inherited retinal diseases (IRDs), defined by dysfunction or progressive loss of photoreceptors, are disorders characterized by elevated heterogeneity, both at the clinical and genetic levels. Our main goal was to address the genetic landscape of IRD in a Spanish cohort of patients. A retrospective hospital-based cross-sectional study was carried out on IRD affected individuals, referred for genetic testing from all the Spanish autonomous communities. Clinical, demographic and familiar data were collected from each patient, including family pedigree, age of appearance of visual symptoms, presence of any systemic findings and geographical origin. Genetic studies were performed to all families with available DNA using different molecular techniques. Our study provides the general landscape for IRD in Spain and our results have important implications for genetic diagnosis, counselling and new therapeutic strategies to both the Spanish population and other related populations.

  Study EGAS00001005104

• T2D-GENES Consortium: San Antonio Mexican American Family Studies (SAMAFS)

  The Type 2 Diabetes (T2D) Genetic Exploration by Next-generation sequencing in Ethnic Samples (T2D-GENES) Consortium is a collaborative international effort to identify genes influencing susceptibility to type 2 diabetes in multiple ethnic groups using next generation sequencing. To fulfill this objective, T2D-GENES Consortium undertook two large sequencing studies, called T2D-GENES Projects 1 and 2. Project 1 has carried out whole exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 non-diabetic controls, equally divided among five continental ancestry groups: Europeans, East Asians, South Asians, Hispanic Americans, and African Americans. The goal of Project 1 is to identify all genetic variants in the complete coding regions of the genomes (i.e., whole exome) by sequencing, including rare variants. Project 2 (i.e., SAMAFS substudy 2) is a pedigree-based study designed to identify low frequency or rare variants influencing susceptibility to T2D, using whole genome sequence information from approximately 600 individuals in 20 Mexican American T2D-enriched pedigrees from San Antonio, Texas, augmented with family-based imputation into approximately 440 additional family members. The major objectives of Project 2 are to identify low frequency or rare variants in and around known common variant signals for T2D, as well as to find novel low frequency or rare variants influencing susceptibility to T2D. Both T2D-GENES Projects 1 and 2 involve the San Antonio Mexican American Family Studies (SAMAFS), which are composed of four San Antonio, Texas-based family studies: the San Antonio Family Heart Study (SAFHS), San Antonio Family Diabetes/Gallbladder Study (SAFDGS), Veterans Administration Genetic Epidemiology Study (VAGES), and Family Investigation of Nephropathy and Diabetes - San Antonio (FIND-SA) Component and its extension called the Extended FIND [E-FIND]. The SAFHS and SAFDGS began in 1991 and have followed participants with extensive clinical phenotyping related to T2D for over 20 years. The VAGES was initiated in 1994 and a large battery of T2D-related phenotypic data has been obtained from its participants. The FIND-SA began in 2000, a part of the multicenter FIND study which was designed to identify genetic determinants of diabetic kidney disease; data from its participants related to T2D were used for this project. Non-overlapping subsets of SAMAFS participants are part of the T2D-GENES Projects 1 and 2, henceforth referred to as SAMAFS substudies 1 and 2, respectively. The SAMAFS substudies 1 and 2 are part of one of the five awards funded by NIDDK under a cooperative agreement award mechanism, which is governed by the Steering Committee of the T2D-GENES Consortium. Since Project 1 relies on population based subsets of cases and controls, 491 unrelated participants are drawn from the four SAMAFS as part of the T2D-GENES Project 1 Mexican American sample (i.e., SAMAFS substudy 1). The whole exome sequencing was performed at the Broad Institute. For Project 2, 1048 individuals are drawn from two SAMAFS (SAFHS and SAFDGS), representing 20 large families for substudy 2. The substudy 2 strategy is to sequence approximately 600 individuals at an average of 50x coverage across the entire genome, then impute genome wide genotypes for about 440 additional family members. The 600 sequenced individuals are specifically chosen for their value in imputing sequence information into other family members. By studying large pedigrees, we expect to find multiple individuals carrying each genetic variant, even if this variant is very rare in the population at large. Thus, a pedigree-based approach provides an excellent opportunity for identifying rare novel variants influencing risk of T2D and quantitative variation in T2D-related phenotypes. The whole genome sequencing has been done commercially by Complete Genomics, Inc. (CGI). The available sample of 1,048 includes 5 sequenced individuals who do not belong to any of the 20 large pedigrees. The final family data of 1,043 individuals includes whole genome sequence data for 607 individuals. After quality control, 590 sequenced individuals provide data for family based imputation using Merlin linkage analysis software into approximately 440 additional family members for whom chip based genotypes are available to indicate which parental haplotype is transmitted. The complete SAMAFS data including phenotype, genotype, sequence, other T2D-related trait data utilized for Projects 1 and 2 are available. These data can readily be viewed by clicking on the substudy title shown below or in the box: "Substudies", located on the right hand side of this parent or top study page phs000847.v1.p1, titled T2D-GENES Consortium: San Antonio Mexican American Family Studies (SAMAFS). phs000849 T2D-GENES Project 1: San Antonio Mexican American Family Studies (SAMAFS), Substudy 1: Whole Exome Sequencing phs000462 T2D-GENES Project 2: San Antonio Mexican American Family Studies (SAMAFS), Substudy 2: Whole Genome Sequencing in Pedigrees

  Study phs000847

• Common Deleterious Germline Variants Shape the Urothelial Cancer Genome

  Our study used whole-exome, whole-genome, and RNA sequencing to analyze samples from primary tumors, locally recurrent or metastatic urothelial tumors collected over time, and matched normal urothelium. We described the molecular landscape of mutational signatures and structural variants in chemotherapy-resistant urothelial cancer.

  Study phs001087

• CRUK Accelerator: Non-small cell lung cancer whole exome and RNA sequencing

  Whole exome and RNASeq raw sequencing data for a cohort 24 patients with non-small cell lung cancer, 15 adenocarcinoma (8 female, 7 male) and 9 squamous cell carcinoma(5 female, 4 male). Median age at diagnosis was 69. Tumour tissue and PBMCs were used for whole exome sequencing and RNA sequencing. This data was generated as part of a study funded by a Cancer Research UK Centres Network Accelerator Award Grant (A21998).

  Dataset EGAD00001007934

• Iso-seq or Long-read RNAseq Dataset for 7 T-ALL patient samples

  7 Isoform sequencing or Long-read RNAseq mapped bam files. Reads were aligned to HG38 reference using Minimap2.

  Dataset EGAD50000000022

• scRNA-seq for 4 reactive lymph node and 12 high grade B cell lymphoma samples

  Dataset includes count matrices, barcode tsvs, and features tsv for each sample, generated using Cell Ranger.

  Dataset EGAD50000001386

• A Phase Ib/II Study of Regorafenib and Paclitaxel in Beyond First-line Advanced Esophagogastric Carcinoma (REPEAT)

  Regorafenib showed promising results in gastric cancer. We aimed to assess the tolerability of regorafenib and paclitaxel in advanced esophagogastric cancer (EGC) patients refractory to first-line treatment and explore potential biomarkers.. We performed enzyme-linked immunosorbent assay measurements of galectin-1, RNA sequencing, and shallow wholegenome sequencing of metastatic tumor biopsies for biomarker analyses.

  Study EGAS00001006054

• LEF1 knockdown effects on human T cell transcriptome and chromatin accessibility profiles.

  LEF1 (Lymphoid Enhancer-Binding Factor 1) is a key transcription factor in T cell development and function, and its dysregulation has been implicated in various immune-related disorders. This study aimed to comprehensively characterize the transcriptional and epigenetic changes induced by LEF1 knockdown in human T cells. CD3+ T cells isolated from three healthy donors were transfected with either LEF1-specific siRNA or control siRNA, followed by activation with CD3/CD28 Dynabeads and culture in IL-2-containing media. Cells were harvested at 24, 48 and 72 hours post-transfection for multi-omics analysis including bulk RNA-seq, bulk ATAC-seq, single-cell CITE-seq (For CITE-seq, 48 and 72 hours only). This dataset provides insights into LEF1-dependent gene regulatory networks and chromatin accessibility patterns in activated human T cells, contributing to our understanding of T cell biology and potential therapeutic targets. This dataset is part of a comprehensive study investigating functional roles of risk polymorphisms in autoimmune diseases, particularly focusing on the rs58107865 variant at the LEF1 locus.

  Study JGAS000818

• Premalignant SOX2 overexpression in the fallopian tubes of ovarian cancer patients: Discovery and validation studies

  To identify early driver mutations in ovarian cancer cells, we used dense whole genome sequencing of micrometastases and microscopic residual disease collected at three time points from a single patient during treatment for high-grade serous ovarian cancer (HGSOC). Laser capture microdissection of tumour islets was performed on samples prior to chemotherapy, after three cycles of chemotherapy and at recurrence. Long frament read whole genome sequencing was performed and mutations were identified. To our knowledge, this is the first longitudinal study that attempts to investigate spatial and temporal micro-heterogeneity in cancer.

  Study EGAS00001001909

• NIMH Human Middle Temporal Gyrus (MTG) Cell Types

  Elucidating the cellular architecture of the human neocortex is central to understanding our cognitive abilities and susceptibility to disease. In this study, we applied single nucleus RNA sequencing to perform a comprehensive analysis of cell types in the middle temporal gyrus of human cerebral cortex. We identify a highly diverse set of excitatory and inhibitory neuronal types, many of which are relatively sparse. Additionally, we found that excitatory types are less layer-restricted than expected based prior knowledge from cell morphologies and from mouse studies. Comparison to a similar mouse cortex single cell RNA-sequencing dataset revealed a surprisingly well-conserved cellular architecture that enables matching of homologous types and predictions of human cell type properties. Despite this general conservation, we also find extensive differences between homologous cell types in human and mouse, including dramatic alterations in proportions, laminar distributions, gene expression, and morphology. These species-specific features emphasize the importance of directly studying human brain. This study conducted by the Allen Institute for Brain Science was supported by the Allen Institute for Brain Science and by US National Institutes of Health grant U01 MH114812-02 to E.S.L. Collaborators request that publications resulting from these data cite their original publication: Hodge RD, Bakken TE, et al. Conserved cell types with divergent features between human and mouse cortex. bioRxiv. 2018 doi: 10.1101/384826.

  Study phs001790

• Targeted_sequencing_of_genes_recurrently_mutated_in_AML

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

  Study EGAS00001000408

• Strand-specific mRNA-Seq assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  Strand-specific mRNA-Seq assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001227

• Fastq data for stranded mRNA-Seq assays for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Fastq data for stranded mRNA-Seq assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001402

• ChIP-Seq (Input) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (Input) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001235

• Whole genome sequence analysis in patients with primary central nervous system lymphomas

  We performed target amplicon sequencing analysis in 28 patients with primary central nervous system lymphomas using target capture technology (NGS) on Cancer Panel to explore molecular targets.

  Study JGAS000258

• Enzymatic Methyl-Seq Rectal Mucus

  Enzymatic methyl sequencing of rectal mucus samples from patients suspected to have colorectal cancer. This is 1 of 4 sequencing experiments on the same sample type.

  Study EGAS50000001314

• Data for noninvasive lung cancer subtyping study

  This dataset included cfMethyl-Seq data of 15 plasma cfDNA samples from 15 lung cancer patients and RRBS data of 58 lung tumor tissue samples from 58 lung cancer patients. The data were generated following the standard protocols.

  Dataset EGAD00001015344

• A fast, affordable and minimally-invasive diagnostic test for Cancer of Unknown Primary (CUP) using DNA methylation profiling

  CUP diagnosis on FFPE tissue and liquid biopsies (blood, pleural and peritoneal effusions) using cfRRBS (cell-free reduced representation bisulfite sequencing), a technique that allows for identification of the methylation profile starting from minimal amounts of highly fragmented DNA.

  Study EGAS50000000257

• MIBS MGS

  Metagenomic sequencing of the human gut in Maastricht IBS studies, cases and controls.

  Study EGAS00001001924

• Blood Transcriptome Profiling Following Seizures

  The retrospective diagnosis or confirmation of a seizure, after the event, is very challenging. Many times clinicians can only use a patient's self-reported history. To further complicate the diagnosis, it is known that 20-30% of patients reporting a seizure actually suffer from psychogenic non-epileptic seizure (PNES). The patient has the behavior of a seizure, but does not suffer from brain seizure activity. Considerable time and resources are used to monitor PNES, and many patients undergo unnecessary therapy with anti-epileptic drugs. These resources could be more effectively used if we could confirm a seizure after the event (retrospective diagnosis). Here we propose a novel approach to distinguish seizures from PNES after the seizure event has happened.We have developed an accurate blood biomarker technology to diagnose acute brain injury, and assess chronic progression following brain injury. Previous studies support the premise that seizures affect blood RNA expression; here we assess temporal RNA expression pattern changes following seizure. We present preliminary preclinical data showing the discrimination of electric-stimulation evoked animal seizures. Here, we validate this maturing technology to assist with the discrimination of epileptic seizures from psychogenic non-epileptic seizures. We will analyze blood samples from patients undergoing video EEG monitoring in an epilepsy monitoring unit (Emory University Hospital, Atlanta GA). We expect 20% of these patients will have PNES. Once a patient has an EEG verified seizure, we will collect blood at various time points and identify biomarker RNA molecules in the blood. Blood samples will be collected from patients with non-verified seizures as control. These RNA expression values will be used to develop a predictive test for the occurrence of seizures. A biomarker gene panel will be developed from this exploratory project for validation in a larger patient population.

  Study phs003460

• NCI's Collection of Studies for General Cancer Research

  This collection contains all of NCIs authorized individual-level genomic datasets currently in dbGaP that are approved for Cancer Research (DS-CA) use only and limitations outlined in the model Data Use Certification Agreement. Access to this study will include any additional authorized individual-level DS-CA datasets that become available. Renewal of this study is required annually. To request access to this study collection, select phs003967.v1.p1 in the dbGaP Authorized Access System.

  Study phs003967

• Sleep Heart Health Study (SHHS-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Related StudiesParent cohort phenotype data can be accessed through ARIC-BioLINCC, Framingham-BioLINCC, and CHS-BioLINCC. Objectives To determine the cardiovascular and other consequences of sleep-disordered breathing and to test whether sleep-disordered breathing is associated with an increased risk of coronary heart disease, stroke, all-cause mortality and hypertension by examining subjects from well-characterized and established epidemiologic cohorts. Background Obstructive sleep apnea syndrome (OSA) is a potentially debilitating condition characterized by repetitive episodes of apnea while asleep, nocturnal oxygen desaturation, excessive daytime sleepiness, and loud disruptive snoring. Epidemiologic data from middle-aged adults indicate that OSA is common, with prevalence rates of 4% in men and 2% in women. Prior studies implicated OSA as a risk factor for the development of hypertension, ischemic heart disease, congestive heart failure, stroke and consequently premature death. Questions arose as to whether an increased propensity for cardiovascular and cerebrovascular diseases was limited to only those with frank OSA or whether more subtle forms of sleep-disordered breathing (SDB) would also confer elevated risk. Further evidence was also needed to clarify whether, SDB, including OSA, is an independent risk factor for the development of cardiovascular or cerebrovascular disease. Known cardiovascular and cerebrovascular disease risk factors such as obesity and smoking are commonly present in those with SDB; therefore, apparent associations between SDB and cardiovascular and cerebrovascular diseases may have resulted from the effects of these concomitant risk factors. Moreover, there was no understanding as to whether such factors as race, age, gender, and prevalent cardiovascular or cerebrovascular disease might interact with SDB to alter future cardiovascular and cerebrovascular disease risk. Mechanisms underlying any propensity to develop cardiovascular or cerebrovascular disease with SDB had not been firmly established (Quan, et al., 1997, PMID: 9493915). Participants Participants in SHHS were recruited from nine existing NHLBI epidemiological studies in which data on cardiovascular risk factors had been collected previously. The “parent” cohorts included: Two sites of the Atherosclerosis Risk in Communities Study (ARIC) Three sites of the Cardiovascular Health Study (CHS) The Framingham Offspring Cohort The Strong Heart Study (SHS) sites in South Dakota, Oklahoma, and Arizona The New York Hypertension Cohorts The Tucson Epidemiologic Study of Airways Obstructive Diseases and the Health and Environment Study From these parent cohorts, a sample of participants who met the inclusion criteria (age 40 years or older; no history of treatment of sleep apnea; no tracheostomy; no current home oxygen therapy) was invited to participate in the baseline examination of the SHHS, which included an initial polysomnogram (SHHS-1). Several cohorts over-sampled snorers in order to increase the study-wide prevalence of sleep-disordered breathing. In all, 6441 individuals were enrolled between November 1, 1995 and January 31, 1998. During exam cycle 3 (January 2001-June 2003), a second polysomnogram (SHHS-2) was obtained in 3295 of the participants. Due to sovereignty issues, Strong Heart Study participants are not included in the shared SHHS data. Data from a total of 5839 participants (1920 ARIC, 1249 CHS, 997 Framingham Offspring and OMNI 1, and 1673 from other studies), consenting to share data are available. Design The Sleep Heart Health Study added in-home polysomnography to the data collected in each of the parent studies at a baseline SHHS exam and a follow-up approximately 4 years later. Using the Compumedics PS polysomnograph, sleep studies were obtained in an unattended setting, usually in the homes of the participants, by trained and certified technicians. The recording montage consisted of: C3/A2 and C4/A1 EEGs, sampled at 125 Hz right and left electrooculograms (EOGs), sampled at 50 Hz a bipolar submental electromyogram (EMG), sampled at 125 Hz thoracic and abdominal excursions (THOR and ABDO), recorded by inductive plethysmography bands and sampled at 10 Hz "airflow" detected by a nasal-oral thermocouple (Protec, Woodinville, WA), sampled at 10 Hz finger-tip pulse oximetry (Nonin, Minneapolis, MN) sampled at 1 Hz ECG from a bipolar lead, sampled at 125 Hz for most SHHS-1 studies and 250 Hz for SHHS-2 studies Heart rate (PR) derived from the ECG and sampled at 1 Hz body position (using a mercury gauge sensor) ambient light (on/off, by a light sensor secured to the recording garment)This montage provides data on the occurrence of sleep-disordered breathing, sleep stages, heart rate, oximetry and on arousals. Each participant in the parent studies was also asked to complete the Sleep Habits Questionnaire which covers usual sleep pattern, snoring, and sleepiness.

  Study phs003637

• RNA-sequencing from duodenal bipsies of Celiac disease patients

  Samples, in a form of PAXgene fixed and paraffin-embedded biopsies, were collected from the multi-site, double-blind, randomized, placebo-controlled trial, aimed at dose-finding and assessing the efficacy and tolerability of a 6-week treatment with ZED1227 capsules vs. placebo in subjects with well-controlled celiac disease undergoing gluten challenge. Total RNA was extracted from the PaxFPE biopsy specimens (n = 116) using additional cuttings from the samples on which histomorphometry was previously assessed. For the extraction, an RNeasy Kit (Qiagen, Hilden, Germany) was used according to the manufacturer’s instructions. Library preparation and next-generation sequencing (NGS) were performed by the Qiagen NGS Service. A total of 10 ng of purified RNA was converted into cDNA NGS libraries. Library preparation was quality controlled using capillary electrophoresis. Based on the quality of the inserts and the concentration measurements, the libraries were pooled in equimolar ratios and then sequenced on a NextSeq (Illumina Inc., San Diego, USA) sequencing instrument according to the manufacturer’s instructions, with 100 bp read length for read 1 and 27bp for read 2. The raw data were de-multiplexed, and FASTQ files for each sample were generated using bcl2fastq2 software (Illumina Inc., San Diego, USA).

  Dataset EGAD50000000491

• Notch Signaling and Efficacy PD-1/PD-L1 Blockade in Relapsed Small Cell Lung Cancer

  Small cell lung cancer (SCLC) is a highly aggressive neuroendocrine (NE) cancer that accounts for approximately 15% of all lung cancer, with an annual incidence of more than 34,000 in the United States alone. SCLC is characterized by loss of function of p53 and RB and high tumor mutational burden, which suggests that these tumors could be immunogenic and respond to immune checkpoint blockade (ICB). However, the benefit from ICB in an unselected SCLC population is modest. In this study, we evaluated the genomic features associated with clinical outcomes in relapsed SCLC to gain insight into the underlying mechanisms of ICB response. Exome, RNA and TCR sequencing data from a prospective clinical trial of relapsed SCLC treated with durvalumab and olaparib and RNA-sequencing data for second cohort of relapsed SCLC cohort treated with nivolumab are included.   

  Study phs002176

• Childhood Cancer Data Initiative (CCDI): OncoKids - NGS Panel for Pediatric Malignancies

  This study aimed to systematically collect clinical, registry and genomic data on pediatric cancer patients, and to contribute to the CCDI Pediatric Data Ecosystem. Clinical, treatment and outcome data on 1,039 pediatric cancer patients whose molecular profile was characterized on OncoKids gene panel at Children's Hospital Los Angeles was abstracted and harmonized for submission to the NCI’s Cancer Data Service. The OncoKids panel was designed to detect DNA mutations and amplification in almost 200 oncogenes and tumor suppressor genes, a limited number of pharmacogenomic targets and 1,700 disease-associated gene fusions at the RNA level. The panel encompasses the vast majority of FDA’s relevant pediatric molecular target list, as well as additional genes associated with ultra-rare pediatric tumors. The final data elements included DNA/RNA sequence data, OncoKids test results, clinical data on demographics, diagnosis, comorbidity and adverse events and treatment data.

  Study phs002518

• Ongoing_mutagenesis_RNAseq

  One of the key questions to be explored is whether the biological processes generating specific mutational signatures continue to operate in the human cancer cell lines or simply reflect past mutagenic activity which is no longer operative. To address this question, we have extracted mutational signatures from 1,000 cancer cell lines of diverse cancer types. Several cell lines with mutational signatures of interest were selected, subcloned over a defined period of time and their genomes sequenced. The increased load of the mutations representative of a specific mutational signature within the genome of a subclone when compared to its parental clone was informative of the on-going mutational processes. To further study the recent observation that some of the clones belonging to a same cell line acquired differencet numbers of mutations over a set period of time, their RNA will be subjected to RNA-sequencing to study their differences.

  Study EGAS00001002364

• Indonesian RNA-seq data

  Transcription data were collected to study patterns of functional variation across the broad geography of Indonesia. The region has extremely diverse populations, with very different demographic histories and multiple genetic ancestries. This dataset reports high-throughput RNA-sequencing data for individuals from three islands spanning this geographical region: Mentawai, Sumba and West Papua.

  Study EGAS00001003671

• Circulating Tumor DNA in Intermediate Risk Rhabdomyosarcoma

  In this study, we evaluated circulating tumor DNA (ctDNA) as a biomarker in the serum of 124 patients with newly diagnosed intermediate risk rhabdomyosarcoma (IR RMS) from the Children's Oncology Group (COG) biorepository. In addition to pre-treatment serum, we also analyzed matched tumor tissue and germline in a subset of patients. We profiled samples using ultra-low passage whole genome sequencing (ULP-WGS) and a new custom hybrid-capture sequencing assay, Rhabdo-Seq, to detect copy number alterations, rearrangements, and single nucleotide variants. We found that patients with detectable ctDNA at diagnosis had significantly worse outcomes than those without detectable levels of ctDNA. Our study demonstrates that baseline ctDNA detection is feasible and prognostic in IR RMS. The ULP-WGS and targeted next-generation sequencing (Rhabdo-Seq and TranSS-Seq) data are available in this study.  

  Study phs002866

• Neuroblastoma patient Total RNA Seq data

  Tumor Total RNA Seq data of primary neuroblastomas. This is an update of the „Berlin Neuroblastoma Dataset” (EGAS00001004022). This data was used for the analysis of circular RNA expression and regulation in neuroblastoma.

  Dataset EGAD00001008124

• Effects of 2DG, Galactose, or Oligomycin on the epigenome remodeling induce by T cells activation.

  T cell activation is known to require a metabolic shift towards glycolysis, triggered by TCR-engagement . To substantiate the role of glycolysis in transcriptional reprogramming during antigen-driven T cell activation, we utilized a well-established ex-vivo model to recapitulate the process of antigen stimulation without the requirement for additional antigen-presenting cells . We initially explored and validated the conditions for both metabolic and epigenetic reprogramming. Antigen-mediated CD4+ T cells activation initiates context-specific gene-expression programs that drive effector functions and cell fates through changes in the epigenetic landscape . To evaluate global changes in histone modifications, we isolated CD4+ T cells from peripheral blood (PB) of healthy control (HC) human donors and either maintained them in resting conditions or stimulated with anti-CD3/CD28 for 24h. Rapid changes in the CD4+ epigenome and transcriptome were observed within 24h as measured by RNA-sequencing (RNA-seq) and H3K27ac chromatin immunoprecipitation followed by DNA-sequencing (ChIP-seq).To explore the requirement for metabolic reprogramming in regulating transcriptional responses after initial TCR engagement, CD4+ T cells from PB of healthy donors were isolated and activated in either the presence or absence of oligomycin (inhibitor of ATP synthase blocking the production of ATP by OXPHOS), 2-deoxyglucose (2DG; competitively inhibiting production of glucose-6-phosphate from glucose), or replacement of glucose with galactose. Galactose is metabolized through glycolysis, utilizing the Leloir pathway which is energy neutral, forcing cells to use all the pyruvate production to sustain the TCA cycle for OXPHOS and ATP synthesis at the expense of lactate production. Employing ChIP-seq and RNA-seq, inhibition of OXPHOS-mediated ATP production by oligomycin had only a limited effect on H3K27-acetylation or activation-induced transcription during the first 24h of activation. In contrast, inhibition of glycolysis by 2DG treatment compromised both H3K27-acetylation and transcriptional changes. However, under conditions of galactose-metabolism where lactate production is abrogated, activated CD4+ T cells were still able to globally remodel H3K27 acetylation and reprogram the transcriptome.

  Study EGAS00001007115

• Fecal microbiome predicts treatment response after the initiation of semaglutide or empagliflozin uptake

  To investigate the effect of semaglutide and empagliflozin initiation on the gut microbiome of type 2 diabetes patients. In addition, to analyze whether the pre-treatment gut microbiome can predict the treatment efficacy. Gut microbiome fecal samples donated at four timepoints (Baseline, Month 1, Month 3; Month 12) were studied using 16S ribosomal RNA gene sequencing and analysis.

  Study EGAS50000000531