7188 results for "({!join from=dataset_studies to=id v=$q1}) OR ("transcriptome" OR "RNA-seq" OR "rna sequencing" OR "rna-sequencing")"

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

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

  Dataset EGAD00001004484

• Neonatal and adult recent thymic emigrants produce IL-8 and express complement receptors CR1 and CR2

  By differential gene expression analysis followed by protein expression and functional studies, we define that the naive T cells having divided the least since thymic emigration express complement receptors (CR1 and CR2) known to bind complement C3b- and C3d-decorated microbial products and, following activation, produce IL-8 (CXCL8), a major chemoattractant for neutrophils in bacterial defense. We also observed an IL-8–producing memory T cell subpopulation coexpressing CR1 and CR2 and with a gene expression signature resembling that of RTEs. JCI Insight. 2017;2(16):e93739. https://doi.org/10.1172/jci.insight.93739

  Dataset EGAD00001003793

• 4 subjects, 12 brain regions, UKBEC

  Brain samples for this dataset were provided by the Medical Research Council Sudden Death Brain and Tissue Bank (Edinburgh, UK). All four individuals sampled were of European descent, neurologically normal during life and confirmed to be neuropathologically normal by a consultant neuropathologist using histology performed on sections prepared from paraffin-embedded tissue blocks. Twelve regions of the central nervous system were sampled from each individual. The regions studied were: cerebellar cortex, frontal cortex, temporal cortex, occipital cortex, hippocampus, the inferior olivary nucleus (sub-dissected from the medulla), putamen, substantia nigra, thalamus, hypothalamus, intralobular white matter and cervical spinal cord.

  Dataset EGAD00001001274

• scRNA-Seq & scATAC-Seq Feature-counting Results Derived from 10X Cellrange-arc-count pipeline

  The feature-counting outputs from Cellrange-arc-count pipeline contain information at the single cell level, jointly for both scRNA-Seq and scATAT-Seq on 103 DLBCL samples and 3 normal controls (Please note that sc-40 only has scRNA-Seq data without scATAC-Seq). These files can be used as the input files for further downstream analysis software (e.g. Seurat Package). Moreover, a matrix of single-cell barcodes and associated cell biological types (used in the study) is also provided for users’ reference. This dataset is large and split into two parts to facilitate downloads.

  Dataset EGAD50000002490

• Immune Cell Atlas of Environmental and Ancestral Diversity in Indonesia [TCR]

  This dataset contains single-cell TCR, individually reference-aligned data from 203 individuals representing four Indonesian populations: the general urban population of Denpasar and the traditional community of Pedawa Village in Bali, as well as the traditional community of Yoboi Village (in Lake Sentani) and Sereh Village (individuals from highland Papua residing near Lake Sentani) in Papua. The dataset was produced as part of the Immune Cell Atlas of Environmental and Ancestral Diversity in Indonesia, a study aimed at characterizing how genetic background and environmental context shape immune cell states across diverse Indonesian communities.

  Dataset EGAD50000002383

• Immune Cell Atlas of Environmental and Ancestral Diversity in Indonesia [scRNAseq]

  This dataset contains single-cell RNA, individually reference-aligned data from 203 individuals representing four Indonesian populations: the general urban population of Denpasar and the traditional community of Pedawa Village in Bali, as well as the traditional community of Yoboi Village (in Lake Sentani) and Sereh Village (individuals from highland Papua residing near Lake Sentani) in Papua. The dataset was produced as part of the Immune Cell Atlas of Environmental and Ancestral Diversity in Indonesia, a study aimed at characterizing how genetic background and environmental context shape immune cell states across diverse Indonesian communities.

  Dataset EGAD50000002385

• Whole genome and transcriptome sequencing of lung cancer patients and cell lines at Genentech

  Version 1 Whole genome sequencing was applied to tumor and adjacent normal lung tissue in an individual non-small-cell lung cancer patient. We present an analysis of somatic changes identified throughout the tumor genome, including single-nucleotide variants, copy number variants, and large-scale chromosomal rearrangements. Over 50,000 high-confidence single-nucleotide variants were identified, revealing evidence of substantial smoking-related DNA damage as well as distinct mutational pressures within the tumor resulting in uneven distribution of somatic mutations across the genome. Version 2 Lung cancer is a highly heterogeneous disease in terms of both underlying genetic lesions and response to therapeutic treatments. We performed deep whole genome sequencing and transcriptome sequencing on 19 lung cancer cell lines and 3 lung tumor/normal pairs. Overall, our data show that cell line models exhibit similar mutation spectra to human tumor samples. Smoker and never-smoker cancer samples exhibit distinguishable patterns of mutations. A number of epigenetic regulators are frequently altered by mutations or copy number changes. A systematic survey of splice-site mutations identified over 100 splice site mutations associated with cancer specific aberrant splicing, including mutations in several known cancer-related genes. Differential usages of splice isoforms were also studied. Taken together, these data present a comprehensive genomic landscape of a large number of lung cancer samples and further demonstrate that cancer specific alternative splicing is a widespread phenomenon that has potential utility as therapeutic biomarkers.

  Study phs000299

• Collagen XVII Promotes Pancreatic Cancer Through Regulation of PIK3R5

  Pancreatic ductal adenocarcinoma (PDAC) contains a desmoplastic stroma that promotes the aggressive biology of this disease. While the varied mechanisms by which fibrillar collagens contribute to PDAC have been defined, little is known about the contribution of transmembrane collagens. Among this class of collagens, Collagen XVII uniquely contains an extensive intracellular domain that connects intracellular cytoplasmic components with the extracellular matrix. Collagen XVII is best characterized as the defining component of the type I hemidesmosome, an anchoring complex that attaches epithelial cells to the underlying basement membrane. In this study, we characterize the expression of collagen XVII in PDAC and the mechanisms by which it contributes to PDAC biology. We demonstrate that crosstalk between PDAC cells and cancer associated fibroblasts drive collagen XVII expression in vitro and xenograft tumor models in vivo. Genetic depletion of collagen XVII in low-passage patient derived cell lines diminishes their metastatic potential and ability to form tumors in mice. Whole transcriptome sequencing of tumors formed by cells with diminished collagen XVII levels revealed dramatically lower levels of PIK3R5, a regulatory subunit of class IB phosphatidylinositol-3-kinase (PI3K) that interacts with G protein-coupled receptors. Consistent with this, collagen XVII-deficient tumors exhibited lower levels of phosphorylated AKT, a downstream effector of PI3K. The studies highlight the importance of collagen XVII signaling in PDAC and define a novel mechanism by which collagen XVII mediates activation of PI3K.

  Study phs003641

• Successful Clinical Response in Pneumonia Therapy (SCRIPT)

  The goal of this study is to iteratively identify, validate and refine biomarkers to predict clinical failure, and identify novel targets for therapy, beyond traditional antibiotics, for patients with severe pneumonia requiring intubation, including severe community-acquired pneumonia (CAP), hospital-acquired pneumonia, and ventilator-associated pneumonia (HAP/VAP). We hypothesize that factors within the alveolar microenvironment in many patients with pneumonia prevent the active process of pneumonia resolution.The major emphasis will be on HAP. Mechanically ventilated CAP patients are a very high-risk group for subsequent VAP, and therefore CAP samples will be included to determine baseline bacteria, microbiome, and host defense patterns for those that do or do not develop HAP/VAP. Hospital-acquired pneumonia is the leading cause of death from nosocomial infections. Even in patients receiving pathogen-appropriate therapy, reported clinical failure rates are increasing, approaching 50% in recent clinical trials. Current approaches to improve outcomes in patients with pneumonia almost exclusively focus on the development of antibiotics to address the problem of resistance. However, the prevalence of antibiotic-resistant pathogens is insufficient to explain the high rates of clinical failure. Instead, we hypothesize that factors within the alveolar microenvironment in many patients with pneumonia prevent the active process of pneumonia resolution. These factors include pathogen-specific adaptations to the injured lung that modulate the innate and adaptive immune response, as well as changes to the alveolar microbiome, driven by selective pressure within our modern intensive care units. Understanding this complex adaptive system requires the integration of clinical information with unbiased measures of the host, pathogen, and microbiome changes within the alveolar microenvironment. These measures must be repeated over time to identify factors that distinguish successful from failed therapy for pneumonia sufficiently early during the clinical course to allow for effective interventions. To address this challenge, we have assembled a talented group of investigators in the Successful Clinical Response In Pneumonia Therapy (SCRIPT) Systems Biology Center. We will leverage our routine clinical practice of safe alveolar sampling in mechanically ventilated patients with pneumonia with repeated non-bronchoscopic bronchoalveolar lavage (NBBAL) sampling over the course of pneumonia. From this fluid, we will combine flow cytometry with multi-omic technologies (cell population-specific transcriptomics, epigenomics, shotgun microbiome sequencing, and pathogen-specific sequencing). Our systems scientists will integrate these genomic data with robust clinical -omics with the goal of identifying biomarkers that can be prospectively tested in patients and causally evaluated in humanized mouse models.The addition of a pooled sample artificially increases the number of automatically computed subjects by one.

  Study phs002300

• METABRIC

  The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (CNVs, SNPs) and acquired somatic copy number aberrations (CNAs) were associated with expression in 40% of genes, although the landscape was dominated by cis and trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP, and MAP2K4. Unsupervised analysis of paired DNA/RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, ER-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration 0152hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the 0152CNA-devoid sub-group and a Basal-specific chromosome 5 deletion-driven mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic copy number aberrations on the transcriptome.

  Study EGAS00000000083

• Gene expression-based prediction of pazopanib efficacy in sarcoma (HIPO, H021)

  The multi-receptor tyrosine kinase (RTK) inhibitor pazopanib is approved for the treatment of advanced non-adipocytic soft-tissue sarcoma and has also shown activity in other sarcoma subtypes. However, its clinical efficacy is highly variable, and no reliable predictors exist to date to select patients who are most likely to benefit from this drug. We analyzed the molecular profiles and clinical outcomes of pazopanib-treated sarcoma patients enrolled in a prospective observational study by the German Cancer Consortium, DKTK MASTER, that employs whole-genome/exome sequencing (WGS/WES) and transcriptome sequencing to inform the care of adults with advanced cancer across histologies who are younger than 51 and patients with rare tumors, including rare subtypes of more common entities, regardless of age.​ Among a total of 109 patients with available WGS/WES data, there was no correlation between clinical parameters, specific genetic alterations, or mutational signatures and clinical outcome. In contrast, analysis of a subcohort of 62 patients who underwent molecular analysis before pazopanib treatment and had transcriptome sequencing data available showed that mRNA levels of NTRK3 (hazard ratio [HR]=0.53, p=0.021), IGF1R (HR=1.82, p=0.027), and KDR (HR=0.50, p=0.011) were independently associated with progression-free survival (PFS). Based on the expression of these RTK genes, i.e., the features NTRK3-high, IGF1R-low, and KDR-high, we developed a pazopanib efficacy predictor (PEP) that stratified patients into three groups with significantly different PFS (p<0.0001). Application of the PEP to an independent cohort of pazopanib-treated sarcoma patients from DKTK MASTER (n=43) confirmed its potential to separate patient groups with significantly different PFS (p=0.02), whereas no such association was observed in sarcoma patients from DKTK MASTER (n=77) or The Cancer Genome Atlas sarcoma cohort (n=256) who were not treated with pazopanib. A score based on the combined expression of NTRK3, IGF1R, and KDR allows identification of sarcoma patients with good, intermediate, and poor outcome following pazopanib therapy and warrants investigation as a predictive tool in prospective studies to optimize the use of this drug in the clinic.

  Study EGAS00001005836

• Transcriptomic changes in placenta associated with anesthesia, delivery mode and maternal diabetes

  The goal of this study was to analyse the impact of maternal diabetes and other maternal factors such as birth mode and anaesthesia on placental transcriptomics. Placental tissue samples from both, the villous and the decidua were prepared and RNAseq was conducted; samples were from mothers with Type1 Diabetes or gestational diabetes or from control mothers.

  Study EGAS50000000489

• Synchronous patterning of hiPSC-derived CNS progenitors generates comprehensive axial spinal cord organoids (CASCOs) containing diverse motor neuron population

  Dataset includes scRNA-sequencing data of cells isolated by dissociation of ~20 BJ WT day 20 hiPSC-derived MN embryoid bodies generated in ULA 96w plates following the protocol described in Rodriguez-Muela et al., JCI 2018). Droplet-based scRNA-seq was performed using 10X Genomics scRNA-sequencing was performed using 10X Genomics Chromium Single Cell Kit v3. The resulting sequencing reads were processed as described in Buchner et al 2024. Analysis of the count matrices was performed using the R toolkit for single cell genomics, Seurat v5.1.0, with R v3.3.3 “Angel Food Cake.”

  Dataset EGAD50000001301

• Single cell RNAseq and TCRseq data from tumor and blood samples from 4 patients with muscle invasive bladder cancer

  For this dataset we performed single cell RNAseq paired with single cell TCR-seq on tumor and blood samples from 4 patients. This dataset contains 4 tumor samples as well as 4 blood samples. Each sample is made up of 2 sets of paired fastq files. The first pair contains reads corresponding to RNA transcripts (_Transcripts in file name), while the second pair contain reads corresponding to TCRs (_VDJ in file name). Sequenced on the Illumina NovaSeq6000 platform in a paired-end run using an SP flow cell (v1.5, 300 cycles).

  Dataset EGAD50000001381

• PCNSL single cell dataset

  Mononuclear cells were isolated as cell suspensions by dissociation in a BD Horizon™ Dri Tumor & Tissue Dissociation Reagent (BD Biosciences) using a gentleMACS dissociator (Miltenyi Biotec). A totalseq-C antibody cocktail (Biolegend) was used, and the cell suspensions were diluted to a concentration of 1,000 cells/μL. Library sequencing was performed using the DNBSEQ-G400 (MGI Tech), Illumina HiSeq 2000, or Illumina NovaSeq 6000 5 (Illumina). The FASTQ files were aligned to the 10x provided reference genome using 10x Genomics Cell Ranger software v7.1.0 to create unique molecular identifier count tables of gene expression of the samples.

  Dataset EGAD50000000685

• Biomarkers for Noise-Induced Sleep Disruption

  This project aims to investigate gene expression biomarkers for noise-induced sleep disruption and cognitive changes. The project is a sub-study, part of the larger ASCENT COE project 86 designed to test the ability of broadband pink noise to serve as a countermeasure for sleep loss from simulated aircraft noise. Gene expression research was sponsored by the Federal Aviation Administration.

  Study phs003932

• Single-Cell Profiling of the Human Endometrium in Polycystic Ovary Syndrome: Uncovering Disease Signatures and Treatment Responses

  We generated the first single-nuclei map of human endometrial biopsies from women with and without PCOS to identify cell-type-specific disease signatures, compositional variations, and transcriptomic reversibility after a 16-week intervention with metformin or lifestyle. Single nuclei were extracted from 27 frozen endometrial biopsies for snRNA-seq using the 10X Genomics protocol.

  Study EGAS50000000735

• CLUSTER Consortium RNAseq PBMC Dataset of pre-methotrexate UK JIA patients cohort

  This is the RNAseq PBMC dataset (paired FASTQ files, n = 82 paired files) generated from pre-methotrexate treatment JIA patients cohort samples. Total PBMC were isolated from pre-treated blood of JIA patients and clinical metadata is also included in this dataset. Samples were sequenced on the NovaSeq6000 instrument (Illumina, San Diego, US) at 300pM, using a 100bp paired read run with corresponding 8bp dual sample index and 5bp or 8bp unique molecular index reads. Run data were demultiplexed and converted to FASTQ files using Illumina’s BCL Convert Software v3.75.

  Dataset EGAD50000001457

• CLUSTER Consortium RNAseq CD8 Dataset of pre-methotrexate UK JIA patients cohort

  This is the RNAseq CD8 dataset (paired FASTQ files, n = 85 paired files) generated from pre-methotrexate treatment JIA patients cohort samples. CD8 cells were sorted from isolated total PBMC by cell sorter (BD FACSAriaTM III, BD Biosciences). Clinical metadata is also included in this dataset. Samples were sequenced on the NovaSeq6000 instrument (Illumina, San Diego, US) at 300pM, using a 100bp paired read run with corresponding 8bp dual sample index and 5bp or 8bp unique molecular index reads. Run data were demultiplexed and converted to FASTQ files using Illumina’s BCL Convert Software v3.75.

  Dataset EGAD50000001456

• CLUSTER Consortium RNAseq CD4 Dataset of pre-methotrexate UK JIA patients cohort

  This is the RNAseq CD4 dataset (paired FASTQ files, n = 86 paired files) generated from pre-methotrexate treatment JIA patients cohort samples. CD4 cells were sorted from isolated total PBMC by cell sorter (BD FACSAriaTM III, BD Biosciences). Clinical metadata is also included in this dataset. Samples were sequenced on the NovaSeq6000 instrument (Illumina, San Diego, US) at 300pM, using a 100bp paired read run with corresponding 8bp dual sample index and 5bp or 8bp unique molecular index reads. Run data were demultiplexed and converted to FASTQ files using Illumina’s BCL Convert Software v3.75.

  Dataset EGAD50000001455

• CLUSTER Consortium RNAseq CD14 Dataset of pre-methotrexate UK JIA patients cohort

  This is the RNAseq CD14 dataset (paired FASTQ files, n = 80 paired files) generated from pre-methotrexate treatment JIA patients cohort samples. CD14 cells were sorted from isolated total PBMC by cell sorter (BD FACSAriaTM III, BD Biosciences). Clinical metadata is also included in this dataset. Samples were sequenced on the NovaSeq6000 instrument (Illumina, San Diego, US) at 300pM, using a 100bp paired read run with corresponding 8bp dual sample index and 5bp or 8bp unique molecular index reads. Run data were demultiplexed and converted to FASTQ files using Illumina’s BCL Convert Software v3.75.

  Dataset EGAD50000001458

• CLUSTER Consortium RNAseq CD19 Dataset of pre-methotrexate UK JIA patients cohort

  This is the RNAseq CD19 dataset (paired FASTQ files, n = 83 paired files) generated from pre-methotrexate treatment JIA patients cohort samples. CD19 cells were sorted from isolated total PBMC by cell sorter (BD FACSAriaTM III, BD Biosciences). Clinical metadata is also included in this dataset. Samples were sequenced on the NovaSeq6000 instrument (Illumina, San Diego, US) at 300pM, using a 100bp paired read run with corresponding 8bp dual sample index and 5bp or 8bp unique molecular index reads. Run data were demultiplexed and converted to FASTQ files using Illumina’s BCL Convert Software v3.75.

  Dataset EGAD50000001459

• singel cell RNAseq dataset for the study "Composition and functional status of T and NK cells in Extramedullary myeloma tumor microenvironment""

  Dataset contains all newly generated single cell RNAseq data generated for the study. It includes 5 EMM soft tissue samples, 5 EMM bone marrow samples (EMM_BM) and 6 RRMM BM samples without EMM (RRMM_BM). Samples that are sequenced twice are marked by _1 or _2 in the sample name. The sample name mentioned corresponds to the sample name used in the publication. The rest of the EMM single cell RNAseq samples mentioned int the publication, EMM_03_1, EMM_11, EMM_14_1, EMM_14_2, EMM_16, and EMM_15_1 are already uploaded in EGA archive – dataset id EGAD50000000053.

  Dataset EGAD50000001511

• Systematic identification of long non-coding RNAs potentially involved in gastrointestinal carncer

  Recent work has suggested various important functions and molecular mechanisms for long non-coding RNAs (lncRNAs) and they are also thought to play critical roles in cancer. However the importance of lncRNAs in cancer biology is still unclear. In this study, we aim to comprehensively identify novel lncRNAs that are critically involved in tumorigenesis and progression in gastrointestinal cancer.

  Study JGAS000011

• Mechanisms on relapse after allogeneic hematopoietic cell transplantation in CMML

  Disease relapse is a major cause of treatment failure after allogeneic hematopoietic cell transplantation (HCT), and mechanisms on relapse still remain to be elucidated. We experienced a patient with chronic myelomonocytic leukemia (CMML) who underwent haploidentical HCT from his daughter and developed relapse. To understand the mechanisms on relapse after HCT, we analyze blood samples at HCT and at relapse.

  Study JGAS000317