3884 results for "RNA AND sequencing OR transcriptome"

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• Kidney_tumour_RNA

  This is a bulk DNA and RNA sequencing study of human renal tumours

  Study EGAS00001002487

• RNA sequencing of high hyperdiploid and ETV6/RUNX1-positive pediatric acute lymphoblastic leukemia

  We performed RNA-sequencing of high hyperdiploid and ETV6/RUNX1-positive ALL cases by using the Human Ribo-Zero rRNA Removal Kit to investigate the gene expression in high hyperdiploid ALL.

  Study EGAS00001003079

• RNA-seq of CD34+ HSPCs from LRMDS patients

  To profile transcriptional alterations of HSPCs in LR-MDS patients, 7AAD−CD45+Lin-CD235a−CD34+ cells were isolated from healthy donors and LR-MDS patients for RNA sequencing.

  Study EGAS00001008182

• Genomic Analysis of Diffuse Large B Cell Lymphoma

  Tumors from 383 newly diagnosed diffuse large B cell lymphoma were included in this study. Tumor DNA was extracted from formalin-fixed, paraffin embedded (FFPE) tissue sections, germline DNA was extracted from blood, and whole exome sequencing (WES) of all samples (n=340 tumor normal pairs) was performed using the Agilent SureSelect XT AllExon v5 + UTR kit and sequencing was carried out on an Illumina NovaSeq, 100 x 2 paired end reads. Tumor RNA (n=321) was extracted from formalin-fixed, paraffin embedded (FFPE) tissue sections and RNA sequencing was performed using the Illumina TruSeq RNA Exome Kit (Illumina) for library preparation, sequencing platform HiSeq 4000, 100 x 2 paired end reads.

  Study phs003634

• Control samples, breast cancer clinical samples and matched patient-derived tumour xenografts (PDTXs) to develop and test a computational approach to discriminate human and mouse sequences in PDTXs

  Patient-Derived Tumour Xenografts (PDTXs) have emerged as the pre-clinical models that best represent clinical tumour diversity and intra-tumour heterogeneity. The molecular characterization of PDTXs using High-Throughput Sequencing (HTS) is essential; however, the presence of mouse stroma is challenging for HTS data analysis. Indeed, the high homology between the two genomes results in a proportion of mouse reads being mapped as human. In this study we generated Whole Exome Sequencing (WES) and RNA sequencing (RNA-seq) data from samples with known mixtures of mouse and human DNA or RNA.

  Study EGAS00001002445

• RNA-Seq of Whole Blood from Patients with Intracranial Aneurysms

  Rupture of intracranial aneurysms (IAs) causes intracranial hemorrhaging that leads to high rates of neurological deficits and death. Although rupture rates are low, clinicians must decide whether to treat or monitor these potentially dangerous lesions. In the current clinical practice, the most common metric to measure risk of rupture is aneurysm size. However, clinical data show that small aneurysms can also rupture. As a result, alternative clinical stratification scores have been proposed, including the PHASES (Population, Hypertension, Age, Size, Earlier subarachnoid hemorrhage, and Site) score based on patient demographics and IA characteristics to stratify ruptured and unruptured IAs, and the Rupture Resemblance Score (RRS) that stratifies ruptured and unruptured IAs based on hemodynamic and morphological properties. However, all metrics require imaging on digital subtraction angiography (DSA), which is invasive, expensive, requires the use of X-rays, and is associated with transient or permanent neurological and non-neurological complications. We hypothesize that individuals with dangerous IAs have detectable gene expression differences in their blood that could be used as biomarkers to determine rupture risk. We propose to use whole blood transcriptomes to develop a "one-stop" diagnostic test that can detect the presence of IAs and determine the risk of rupture based on circulating RNA expression biomarkers using our prototype AneuScreenTM platform. We aim to develop and validate biomarkers to predict risk, as calculated by the currently-used metric of aneurysm size, the clinical PHASES score, and the RRS. Here, we collected blood samples from consented individuals who were receiving cerebral imaging at the Gates Vascular Institute (Buffalo, NY) for intracranial aneurysm. RNA extracted from blood samples (n=43) was subjected to RNA-sequencing and added to our existing database (n=44). When combined with our previous data, we had transcriptome data from 68 aneurysms (after additional sample filtering). This dataset was stratified into low- and high-risk according to IA size, PHASES score, and RRS score. Differentially expressed genes were identified and used to construct predictive models. Fastq files and basic demographic information for the 43 newly-sequenced intracranial aneurysm samples on this project will be available through dbGaP.

  Study phs003072

• Whole blood RNAseq from a large ALS case-control study at Univ of Michigan

  This dataset consists of 694 bulk RNA-seq data (sorted aligned BAM files) from whole blood of ALS participants meeting the Gold Coast definition of ALS during their clinical visit (n=422) and healthy controls (n=272) at the University of Michigan (UM). Samples were collected as part of the UM Pranger ALS Clinic between 2011-2021, and prepared either using poly-A selection of rRNA depletion (see Experiments). RNAseq was performed on the NovSeq 6000 S4 at the UM Advanced Genomics Core, resulting in 150bp paired-end reads. Raw reads were trimmed using Cutadapt (v2.3) and aligned to hg38 using STAR (v2.5.3a). Age provided is the age at blood sample collection date.

  Dataset EGAD50000001488

• COVID-19 Multiomics Atlas

  We provide a single-nuclei RNA-sequencing (snRNA-seq) dataset derived from four COVID-19 patients, generated using the 10x Chromium Next GEM Single Cell v3.1 kit. For our study, these were integrated with snRNA-seq data with 12 publicly available sc/snRNA-seq datasets, comprising organ donor lung samples (n=89) and COVID-19 lung tissue samples (n=51). Additionally, we provide a spatial transcriptomic dataset characterizing different histopathological stages of diffuse alveolar damage, across a cohort of 33 COVID-19 patients. This was generated using the Nanostring Whole Transcriptome Assay (WTA) with regions of interest (ROIs) sized 400 µm² each. This integrated multi-omics analysis of snRNA-seq, histology, and spatial transcriptomics data, is available for exploration and download via our web portal: https://covid19-multiomicatlas.cellgeni.sanger.ac.uk/.

  Dataset EGAD00001015404

• Multi-omics profiling of PSCCE

  We performed whole-exome sequencing, RNA sequencing and immunohistochemistry profiling of primary small cell carcinomas of the esophagus.

  Study EGAS00001004889

• HipSci - Monogenic Diabetes - RNA Sequencing - October 2016

  HipSci - Monogenic Diabetes - RNA Sequencing - October 2016

  Dataset EGAD00001003180

• HipSci - Monogenic Diabetes - RNA Sequencing - July 2017

  HipSci - Monogenic Diabetes - RNA Sequencing - July 2017

  Dataset EGAD00001003530

• HipSci - Bleeding and Platelet Disorders - RNA Sequencing - July 2017

  HipSci - Bleeding and Platelet Disorders - RNA Sequencing - July 2017

  Dataset EGAD00001003539

• HipSci - Healthy Normals - RNA Sequencing - May 2014

  HipSci - Healthy Normals - RNA Sequencing - May 2014

  Dataset EGAD00001000897

• Investigating the differences in iPSC-derived intestinal epithelial cell behaviour and composition grown as organoid, in Transwell or Intestine-Chip.

  aim: Investigating the differences in iPSC-derived intestinal epithelial cell behaviour and composition grown as organoid, in Transwell or Intestine-Chip. RNA sequencing data of 21 samples of iPSC-derived intestinal epithelial cells on different model systems. 3 iPSC lines Geni002, Geni007 and Geni012 differentiated into Epcam+ intestinal epithelial cells and grown on the following systems: 6 samples: organoids exposed to EM (3) and DM+D+PD (3) 9 samples: Transwell exposed to EM/EM (3), DM+D+PD/DM+D+PD (3), EM/DM+D+PD (gradient, 3) 6 samples: Emulate Chip exposed to EM/EM (3) and EM/DM+D+PD (3) EM: expansion medium DM+D+PD: differentiation medium including DAPT and PD0325901

  Study EGAS50000001339

• Spatial map of microglia states across CNS diseases

  Microglia are the key immune cells involved in virtually all diseases of the central nervous system (CNS). Here, we generated a novel large-scale single-cell RNA-sequencing-derived taxonomy through the analysis of > 1 million CNS cells enriched for myeloid cells across > 15 different pathologies and conditions. Disease-associated human microglia, together with CNS-associated macrophages and monocytes, were differentiated iteratively into 27 superclusters and 192 clusters. This top-down approach, in combination with targeted and genome-wide subcellular spatial transcriptomics, enabled us to examine and compare the spatial interactome of the identified superclusters and clusters within and across pathologies. Our data provide new insights into the spatial dynamics of the endogenous CNS immune system during development, health and disease in humans.

  Study EGAS50000001289

• Dissecting intratumor heterogeneity of nodal B cell lymphoma on the transcriptional, genetic, and drug response level

  Tumor heterogeneity encompasses both the malignant cells and their microenvironment. While heterogeneity between individual patients is well-known to affect the efficacy of anti-cancer, most personalized treatment approaches do not account for intratumor heterogeneity. We addressed this issue by studying the heterogeneity of lymph node-derived B cell non-Hodgkin lymphoma (B-NHL) by single cell RNA-sequencing (scRNA-seq) and transcriptome-informed flow cytometry. We identified transcriptionally distinct malignant subclones and compared their drug response and genomic profiles. Malignant subclones of the same patient responded strikingly different to anti-cancer drugs ex vivo, which recapitulated subclone-specific drug sensitivity during in vivo treatment. Tumor infiltrating T cells represented the majority of non-malignant cells, whose gene expression signatures were similar across all donors, whereas the frequencies of T cell subsets varied significantly between the donors. Our data provide new insights into the heterogeneity of B-NHL and highlight the relevance of intratumor heterogeneity for personalized cancer therapies.

  Study EGAS00001004335

• TGF-β attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells.

  We examined tumours from a large cohort of patients with metastatic urothelial bladder cancer (mUC) treated with an anti–PD-L1 agent (atezolizumab) and identified major determinants of clinical response and immune escape. Whole transcriptome profiles were generated for 368 patients using TruSeq RNA Access technology (Illumina). Somatic mutations were determined via whole exome sequencing for a subset of these patients. - Response was associated with CD8+ T effector cell phenotype and, to an even greater extent, high neoantigen or tumour mutation burden (TMB). On the other hand, lack of response was associated with a transforming growth factor β (TGF-β) signature, particularly in patients with CD8+ T cells preferentially residing in collagen-rich matrix surrounding tumours. Integration of these three independent biological features provided the best basis for understanding outcome in this setting. -

  Study EGAS00001002556

• Multiome sequencing of primary colon tissue and derived organoids

  Multiome (ATAC + RNA) sequencing of primary colon tissue and organoids derived from the same donors.

  Study EGAS00001008110

• Small RNA Sequencing across Diverse Biofluids Identifies Optimal Methods for exRNA Isolation

  We tested the efficiency and reproducibility of 10 RNA isolation methods on 5 different biofluids. Pooled human plasma and serum, bile and urine were used along with cell culture supernatants from human embryonic stem cells (hESC), primary neonatal rat ventricular myocytes (NRVM) and human cholangiocarcinoma cells (KMBC). 4 RNA isolation methods designed to isolate total RNA from bio fluids without enrichment of exRNA carriers were used. 6 methods that preferentially enriched for exRNA carriers were also compared. Small RNA libraries were constructed using the NEBNext small-RNA library prep. The efficiency and reproducibility of the different RNA isolation methods was compared using small-RNA seq.

  Study phs002143

• Genomic and transcriptomic analysis of baseline PDAC patients' tumors from the OXIRI phase 1b clinical trial

  This study was aimed at investigating the genomic and transcriptomic features associated with response to the OXIRI regimen (oxaliplatin, irinotecan, capecitabine) in pancreatic ductal adenocarcinoma (PDAC) tumors. We performed whole-exome sequencing (WES) and RNA sequencing (RNA-seq) on baseline tumor samples obtained from 8 patients recruited in the OXIRI phase 1b clinical trial (NCT02368860).

  Study EGAS00001006073

• HipSci - Bardet-Biedl Syndrome - RNA Sequencing - October 2016

  HipSci - Bardet-Biedl Syndrome - RNA Sequencing - October 2016

  Dataset EGAD00001003181

• HipSci - Bardet-Biedl Syndrome - RNA Sequencing - July 2017

  HipSci - Bardet-Biedl Syndrome - RNA Sequencing - July 2017

  Dataset EGAD00001003531

• Deep RNA sequencing in CLL

  Deep RNA sequencing in CLL

  Dataset EGAD00001000258

• HipSci - Healthy Normals - RNA Sequencing - May 2015

  HipSci - Healthy Normals - RNA Sequencing - May 2015

  Dataset EGAD00001001438

• To_profile_the_landscape_of_sebaceous_tumours___RNA

  Sebaceous tumours are a rare cutaneous cancer with potential for aggressive behaviour. However, limited information is available on these cancers with few published cases. Here we wish to exome sequence these cancers to define the first genomic landscape for this malignancy. We will extract RNA from formalin-fixed, paraffin-embedded (FFPE) cores. Cores may be obtained from lesional and non-lesional tissues of primaries as well as matching metastases. The extracted RNA will be used for RNA sequencing.

  Study EGAS00001007803