Search Results - EGA European Genome-Phenome Archive

Multi-omics data of 1000 Inflammatory Bowel Disease patients

Portal available at https://1000ibd.org Inflammatory bowel disease (IBD) is a chronic complex disease of the gastrointestinal (GI) tract. Patients with IBD can experience a wide range of symptoms, but the pathophysiological mechanisms that cause these individual differences in clinical presentation remain largely unknown. In consequence, IBD is currently classified into subtypes using clinical characteristics. If we are to develop a more targeted treatment approach, molecular subtypes of IBD need to be discovered that can be used as new drug targets. To achieve this, we need multiple layers of molecular data are generated from the same IBD patients.We initiated the 1000IBD project to prospectively follow more than 1000 IBD patients from the Northern provinces of the Netherlands. For these patients, we have collected a uniquely large number of phenotypes and generated multi-omics profiles. To date, 1,215 participants have been enrolled in the project and enrolment is on-going, with 609 patients being present in the first data release. Phenotype data collected for these participants includes information on dietary and environmental factors, drug responses, and adverse drug events. Genome information has been generated using genotyping (ImmunoChip, Global Screening Array and HumanExomeChip) and sequencing (whole exome sequencing and targeted resequencing of IBD susceptibility loci), transcriptome information generated using RNA-sequencing of intestinal biopsies and microbiome information generated using both sequencing of the 16S rRNA gene and whole genome shotgun metagenomic sequencing.All molecular data generated within the 1000IBD project will be shared in multiple data on the European Genome-Phenome Archive (www.ega-archive.org). The first data release, will contain basic phenotypes for 609 participants, genotypes of 314 participants, gut microbiome data generated by tag sequencing the 16S gene of feces from 315 participants and intestinal biopsies from 107 participants, and gut microbiome metagenomic sequencing of feces of 355 participants . Future releases will comprise many more additional phenotypes and -omics data layers. 1000IBD data can be used by other researchers as a replication cohort, a dataset to test new software tools, or a dataset for applying new statistical models.

Study EGAS00001002702

Integrated Single-Cell Genetic and Transcriptional Analysis Suggests Novel Drivers of Chronic Lymphocytic Leukemia

Intratumoral genetic heterogeneity has been characterized across cancers by genome sequencing of bulk tumors, including chronic lymphocytic leukemia (CLL). In order to more accurately identify subclones, define phylogenetic relationships, and probe genotype-phenotype relationships, we developed methods for targeted mutation detection in DNA and RNA isolated from thousands of single cells from five CLL samples. By clearly resolving phylogenic relationships, we uncovered mutated LCP1 and WNK1 as novel CLL drivers, supported by functional evidence demonstrating their impact on CLL pathways. Integrative analysis of somatic mutations with transcriptional states prompts the idea that convergent evolution generates phenotypically similar cells in distinct genetic branches, thus creating a cohesive expression profile in each CLL sample despite the presence of genetic heterogeneity. Our study highlights the potential for single-cell RNA-based targeted analysis to sensitively determine transcriptional and mutational profiles of individual cancer cells leading to increased understanding of driving events in malignancy. Reprinted from Genome Research, with permission from Publisher.

Study phs001372

RNA sequencing of surgically removed lung adenocarcinoma afterwards treated with immune checkpoint inhibitors

Patients with lung adenocarcinoma (LUAD) from The Cancer Genome Atlas (TCGA) database were enrolled in the training cohort to establish a prognostic signature based on the expression of tumor-specific amino acid metabolism related genes. The established signature was further investigated against an original cohort, KCC-ICI, of chemotherapy combined with immune checkpoint inhibitors. The signature consisting of nine genes, KYNU, PSPH, PPAT, MIF, GCLC, ACAD8, TYRP1, ALDH2, and HDC, could effectively stratify the OS in LUAD patients. The KCC-ICI cohort confirmed the predictive ability of the established signature in the clinical response to immune checkpoint blockade therapy, which correlated with the infiltration of immune cells (e.g., T lymphocytes and nature killer cells). We discovered that the high signature risk score patients showed a significantly lower concentration of plasma-free ??-aminobutyric acid (AABA).

Study JGAS000675

Dynamic Evolution of Fibroblasts Revealed by Single Cell RNA Sequencing of Human Pancreatic Cancer

Understanding the constituents of the pancreatic ductal adenocarcinoma (PDAC) microenvironment may illuminate more efficacious targets for treating this aggressive malignancy. However, the compositional changes occurring in untreated and treated PDAC relative to both normal and inflamed pancreas have not been well characterized. To provide a more comprehensive understanding of the PDAC tumor microenvironment relative to the non-cancerous pancreas, we performed single-cell expression profiling (10X Genomics Chromium) on samples of upfront resectable PDAC, FOLFIRINOX-based treated PDAC, chronic pancreatitis, and normal pancreas specimens from 19 patients. Spatial gene expression profiling (10X Genomics Visium) was performed to gain additional insight into cell populations. Our analysis revealed that fibroblasts are central mediators of cell-cell communication in both inflamed and malignant settings and defined unique roles for these cell populations in different disease contexts.

Study phs003751

Microvascular Permeability, Inflammation, and Lesion Physiology in Endometriosis: A Microphysiological Systems Approach

The goal of the study is to identify novel molecular pathways involved in the etiology of endometriosis and to develop in vitro model systems to enable the study of the mechanisms regulating reproductive function. Using a physiomimetic modeling approach, primary tissue samples of the human endometrium derived from patients diagnosed with and without endometriosis and/or endometriotic diseases (e.g. adenomyosis) were used for secondary analysis using multi-omic systems biology analysis and to build tissue engineered models. We performed single cell RNA sequencing (scRNA-Seq, N=6)) to study the cellular and transcriptomic composition of the endometrial tissue microenvironment and proteomics (LC-MS/MS) to study protein-level signaling pathways and the matrisome of the native endometrium. Systems biology analysis of these datasets helped identified a putative dysregulated inflammatory signaling pathway in endometriosis patients compared to controls. Moreover, subsets from these scRNA-Seq and proteomic datasets were used to aid the design of a synthetic extracellular matrix hydrogel as an in vitro platform for the culture of endometrial cells. Tissue-engineered synthetic PEG hydrogel enables the simultaneous co-culture of endometrial epithelial organoids and stromal fibroblasts in a fully defined, 3D, and tunable environment. We demonstrated that the in vitro co-culture model recapitulates key phenotypic processes observed across the human menstrual cycle in response to sex hormone stimulation through both biochemical and transcriptomic (bulk RNA-sequencing) analysis. This model will enable future mechanistic studies that examine origins of endometriotic disease phenotypes. The transcriptomic data generated for this study including the scRNA-Seq data from primary human endometrial tissues and the bulk RNA-Seq datasets from the experimental co-culture models is available through dbGAP.

Study phs003326

A transcriptomic approach to understand patient susceptibility to pneumonia after abdominal surgery

Rationale Nosocomial infections are a major healthcare challenge, developing in over 20% of patients aged 45 or over undergoing major-abdominal surgery, with postoperative pneumonia associated with an almost five-fold increase in 30-day mortality. Objectives To describe immune-pathways and gene-networks altered following major-abdominal surgery and identify transcriptomic patterns associated with postoperative pneumonia. Methods and Measurements From a prospective consecutive cohort (n=150) undergoing major-abdominal surgery whole-blood RNA was collected preoperatively and at three time-points postoperatively (2-6, 24 and 48hrs). Twelve patients diagnosed with postoperative pneumonia and 27 matched patients remaining infection-free were identified for analysis with RNA-sequencing. Main Results Compared to preoperative sampling, 3,639 genes were upregulated and 5,043 downregulated at 2-6hrs. Pathway-analysis demonstrated innate-immune activation with neutrophil-degranulation and Toll-like-receptor signalling upregulation alongside adaptive-immune suppression. Cell-type deconvolution of preoperative RNA-sequencing revealed elevated S100A8/9-high neutrophils alongside reduced naïve CD4 T-cells in those later developing pneumonia. Preoperatively, a gene-signature characteristic of neutrophil-degranulation was associated with postoperative pneumonia acquisition (P=0.00092). A previously reported Sepsis Response Signature (SRSq) score, reflecting neutrophil-dysfunction and a more dysregulated host response, at 48hrs postoperatively, differed between patients subsequently developing pneumonia and those remaining infection-free (P=0.045). Analysis of the novel neutrophil gene-signature and SRSq scores in independent major-abdominal surgery and polytrauma cohorts indicated good predictive performance in identifying patients suffering later infection. Conclusions Major-abdominal surgery acutely upregulates innate-immune pathways while simultaneously suppressing adaptive-immune pathways. This is more prominent in patients developing postoperative pneumonia. Preoperative transcriptomic signatures characteristic of neutrophil-degranulation and postoperative SRSq scores may be useful predictors of subsequent pneumonia risk.

Study EGAS00001007229

H3Africa CAfGEN Exome

Whole Exome Sequencing data from a retrospective paediatric HIV-disease progression cohort defined on the World Health Organization's criteria for paediatric HIV progression. Data comprises of BAM and VCF files for 314 participants from 2 countries: Botswana and Uganda. DNA and RNA samples are linked in bio-repository.

Dataset EGAD00001006224

Lymphoma_primary_patient_drug_perturbed_RNASeq_samples

3'-end low-depth RNA sequencing data from 108 patients with chronic lymphocytic leukemia and 8 patients with lymphoma. Each primary patient sample was treated in vitro with DMSO as a control and with up to ten small-molecule inhibitors (ibrutinib, duvelisib, everolimus, trametinib, nutlin-3a, I-BET-762, MK2206, selinexor, compound 26, and a combination of ibrutinib and compound 26). Sequencing was performed on the Illumina HiSeq4000. The dataset contains FASTQ files.

Dac EGAC50000000578

Integrating molecular imaging and transcriptomic profiling in advanced HER2-positive breast cancer receiving trastuzumab emtansine (T-DM1): an analysis of the ZEPHIR clinical trial

Purpose: The ZEPHIR clinical trial evaluated the role of [89Zr]trastuzumab-PET/CT (HER2-PET/CT) and 2-[18F]fluoro-2-deoxy-D-glucose PET/CT ([18F]FDG-PET/CT) in predicting outcomes in patients with advanced HER2-positive breast cancer treated with trastuzumab emtansine (T-DM1). Here, we combined molecular/metabolic imaging and transcriptomic data to investigate the biological processes associated with [89Zr]trastuzumab and [18F]FDG uptake, and to dissect the mechanisms involved in T-DM1 resistance. Experimental design: RNA was extracted from metastasis biopsies obtained at study inclusion in the ZEPHIR trial. HER2-PET/CT and [18F]FDG-PET/CT imaging data of biopsied lesions were integrated with RNA sequencing data. Lesions were compared based on the level of [89Zr]trastuzumab uptake (dichotomized into high/low classes) as well as on the presence/absence of metabolic response, defined comparing baseline and on-treatment [18F]FDG-PET/CT. Results: We analyzed matched transcriptomic and molecular/metabolic imaging data for 24 metastases (one lesion/patient). Pathways involved in extracellular matrix (ECM) organization, glycosylphosphatidylinositol synthesis, and collagen formation were enriched in lesions presenting low [89Zr]trastuzumab uptake. [18F]FDG uptake at baseline correlated with proliferation and immune-related processes. Hypoxia and ECM-related processes were enriched in lesions that showed no metabolic response to T-DM1. Interestingly, immune-related processes (e.g., Fc gamma receptor activation, complement cascade) were associated with high [89Zr]trastuzumab uptake and metabolic response. Conclusions: To our knowledge, this study represents the first correlative analysis between [89Zr]trastuzumab tumor uptake and gene expression profiling in humans. Our findings point toward a role of ECM in impairing [89Zr]trastuzumab tumor uptake and T-DM1 metabolic response in advanced HER2-positive breast cancer, and highlight the potential of molecular imaging to depict tumor microenvironment features.

Study EGAS50000000470

Glioblastoma epigenome profiling identifies SOX10 as a master regulator of molecular tumour subtype

Glioblastoma in adult patients are classified into four subtypes, IDH, MES, RTK I, and RTK II, based on DNA methylation and RNA expression data. Tumour subtype transitions commonly occur during the treatment of glioblastoma patients, and transitions to the mesenchymal (MES) subtype have been associated with therapy resistance and adverse prognosis. Here, we generate DNA methylome and histone modification data of glioblastoma primary tumours and show that glioblastoma subtypes differ by their enhancer landscapes. Using Core Regulatory Circuitry analysis of H3K27ac data, and independent analysis of RNA-derived gene regulatory networks, we identified 38 subtype master regulators whose cell type-specific activities we mapped in single-cell RNA sequencing data. These analyses identified the chromatin modifier SRY-Box 10 (SOX10) as a master regulator in tumours of the RTK I subtype. In functional studies we demonstrate that SOX10 loss causes a transition of RTK I tumour cells to a mesenchymal cellular state by altering the accessibility of enhancer-rich chromatin regions and their occupancy by Bromodomain Containing 4 (BRD4), a dynamic constituent of super-enhancers. Treatment with the BRD4 inhibitor JQ1 blocked this transition. These data demonstrate the fundamental role of enhancer chromatin remodelling and master regulator activity in the establishment, maintenance and plasticity of glioblastoma cellular states. We also make our data publically browsable at https://dkfz-b060.github.io/gb_browse/

Study EGAS00001003953

3743 results for "RNA AND sequencing OR transcriptome"

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