11976 results for "cancer rna-seq"

in 113.45 milliseconds.

• The Extracellular RNA Quality Control (exRNAQC) study (phase 2)

  Study EGAS00001006499

• The Extracellular RNA Quality Control (exRNAQC) study (phase 1)

  Study EGAS00001005263

• Human Biofluid RNA Atlas Project - raw data

  Study EGAS00001003917

• HiChIP fastq files

  HiChIP experiments with two sequencing libraries each. Illumina HiSeq 4000/2500.

  Dataset EGAD00001006278

• Single-Cell RNA-Sequencing of Bone Marrow and Circulating Tumor Cells from Patients with Multiple Myeloma and its Precursor Conditions

  We performed single-cell RNA and V(D)J-sequencing of tumor cells from bone marrow and peripheral blood specimens and patients with Monoclonal Gammopathy of Undetermined Significance (MGUS), Smoldering Multiple Myeloma (SMM), and Multiple Myeloma (MM), as well as healthy donors. In this study we aimed to shed light on the mechanisms underlying tumor cell circulatory capacity and dissemination.

  Study phs003855

• DNA and RNA sequencing data from Ovarian Carcinosarcoma patients from the Glasgow Cohort.

  In this study, we analysed DNA and RNA sequencing data from Ovarian Carcinosarcoma patients, from isolated carcinoma and sarcoma components and investigated DNA variants as well as gene expression. Genomic analyses from this data and further investigation from preclinical models of ovarian carcinosarcoma support the conversion theory for disease development and indicate that microtubule inhibitors could be used to suppress EMT and stimulate anti-tumour immunity.

  Study EGAS00001006605

• Rapid Idiosyncratic Mechanisms of Clinical Resistance to KRAS G12C Inhibition

  Using deep RNA and whole exome sequencing of pre- and post-treatment autopsy samples, we reveal diverse clonal populations that occurred through altered cell intrinsic, tumor microenvironment and immunologic remodeling mechanisms of resistance.

  Study phs002734

• Targeting Heterochromatin Eliminates Malignant Stem Cells in Chronic Myelomonocytic Leukemia Through Reactivation of Retroelements and Innate Immune pathways

  RNA-sequencing, ATAC-sequencing, CUT&Tag-sequencing, data from CMML patient and aged-matched healthy donor CD34+ cells. RNA-sequencing data from patient CD34+ cells after treatment for 4 days with decitabine or UNC0638 inhibitors, alone or together, or left untreated

  Dataset EGAD50000000542

• RNASeq profiles from Indian HFrEF Cohort

  The dataset contains whole transcriptomics 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. Total transcriptome libraries were prepared using TruSeq Stranded Total RNA Library Prep with Ribo-Zero Gold kit and sequenced on Illumina HiSeq4000.

  Dataset EGAD50000001196

• Multi-omics profiling identifies two epithelioid sarcoma molecular subtypes with distinct signaling and immune characteristics

  Bulk RNA Sequencing of 33 epithelioid sarcomas (EpS) and 3 extracranial extra-renal rhabdoid tumors (EERT) Whole-exome sequencing of 30 EpS and 3 EERT Single-cell RNA Sequencing of 8 EpS Visium Spatial Transcriptomics of 3 EpS

  Dataset EGAD50000001419

• The study on genomic profiling using clinical specimens (tissue, blood, etc.) form patients with lung and thymic tumors

  The objective is to generate a comprehensive immunogenomic profiling in thymoma using RNA sequencing and TCR repertoire analysis and to evaluate the potential of immunotherapy in thymoma from multiple perspectives.

  Study JGAS000552

• 5' single cell RNA sequencing

  Pared-end fastq files of 22 AML and 2 normal bone marrow samples were generated using 10x Genomics 5' single cell RNA sequencing following manufacturer's protocol (CG000086 User Guide RevG) for chemistry version 1.0 and targeting 10000 cells per sample. Libraries were sequenced using Illumina HiSeq 4000 using recommended cycling parameters.

  Dataset EGAD00001007672

• Single Cell RNA sequencing of Organoids from TSC2+/- patient IPSCs in H- and L-medium

  This dataset contains single cell RNA sequencing data from Organoids grown in high nutrient (H) and low nutrient (L) medium. Organoids were grown for 110 days. Organoids were grown from a patient IPS cell line with a heterozygous mutation in TSC2 (Patient 1 TSC2+/- iPSCs) and an isogenic control cell line (TSC2+/+).

  Dataset EGAD00001006332

• Dataset on keratinocytic gene expression pattern in Hidradenitis suppurativa

  Human skin samples were obtained from HS patients after informed consent (Ethical vote, University of Würzburg; No. 306/12). Lesional and perilesional were taken and epidermis and dermis separated. Isolated epidermal keratinocytes were further processed for RNA isolation. mRNA was extracted from five pairwise-matched lesional and perilesional epidermal HS pellets and RNA sequencing was performed.

  Dataset EGAD00001008005

• RNA-sequencing data of post-mortem brain tissue taken from individuals with SCA3 and controls

  Spinocerebellar ataxia type 3 (SCA3) is the most common autosomal dominant inherited ataxia worldwide, caused by a CAG repeat expansion in the Ataxin-3 gene resulting in a polyglutamine (polyQ)-expansion in the corresponding protein. Here we have RNA-sequencing data from the cerebellum of individuals with SCA3 and matched controls.

  Dataset EGAD00001009317

• Single-cell RNA sequencing on 5063 single T cells from six hepatocellular carcinoma patients

  T cells isolated from peripheral blood, tumors and adjacent normal tissues from six hepatocellular carcinoma patients. SmartSeq2 and Tang2009 protocol were used to amplify RNA from single T cells. High depth enables simultaneously expression profiling and TCR assembling.

  Dataset EGAD00001003337

• scRNA-seq of human follicular lymphoma and lymph node

  Cryopreserved cells from human nodal follicular lymphoma and lymph node samples were thawed and processed for scRNA-seq analysis. CD3+ CD19− 7-AAD− live T cells (six FL samples from the Original cohort) or 7-AAD− whole live hematopoietic cells (five lymph node and nine FL samples from Validation cohort 1) were sorted using a FACS Aria II or III instrument (BD Biosciences). To generate single-cell emulsions, 6,000–10,000 live cells were loaded into the 10X Genomics Chromium Controller for single-cell partitioning, along with the reverse transcriptase reagent mixture and 3' or 5' gel beads. Sorted T or whole hematopoietic cells were converted to barcoded scRNA-seq libraries using 10X Genomics Chromium single cell 3' reagent kits (v3) for the Validation cohort 1, 5' reagent kits (v1) for the Original cohort, according to the manufacturer’s instructions. The libraries were sequenced on an Illumina HiSeq X Ten or NovaSeq X Plus system, mapped to the human genome (build GRCh38), and demultiplexed using CellRanger pipelines (v3.1.0, 10x Genomics).

  Dataset EGAD50000001143

• Human scMultiome data (GEX and ATAC paired) from CD34+ Bone Marrow (BM) and mobilized peripheral blood (mPB), including CITE-Seq data from mPB CD34+ samples

  We analyzed healthy CD34+ samples from Bone Marrow (BM) and mobilized Peripheral Blood (mPB) in gene therapy experiments within the X-PAND project. BM samples underwent scMultiome analysis, providing paired GEX and ATAC data. For the mPB samples, both scMultiome and CITE-Seq were performed on the same donors, offering additional protein marker information. These datasets allow for an in-depth exploration of chromatin accessibility, gene expression, and surface protein profiling in hematopoietic progenitor cells from healthy donors.

  Study EGAS50000000750

• Genome-wide identification of distinct miRNA-mRNA target regulation pairs in Non-Hodgkin lymphomas: a report from the ICGC MMML-Seq consortium

  We obtained miRNA profiles by miRnome sequencing from ICGC MMML-Seq patients diagnosed with Burkitt lymphoma, diffuse large B-cell lymphoma and follicular lymphoma and provide evidence of subtype-specific miRNA expression differences. We describe differentially expressed, mutated, edited and not previously annotated miRNAs. Addditionally, by performing argonaute-2 photoactivatable ribonucleoside-enhanced cross-linking and immunoprecipitation (PAR-CLIP) experiments, we obtained a set of biochemically-validated miRNA binding sites and identified miRNA-mRNA interaction pairs with a negative correlation in patient RNASeq data.

  Study EGAS00001001394

• Characterization of Structural Variants in Acute Myeloid Leukemia Patients

  Acute myeloid leukemia (AML) is the most common form of acute leukemia in adults and is expected to increase in frequency as the population ages. Most subtypes of AML are difficult to treat, in part due to a lack of understanding of possible molecular targets. Furthermore, the peak incidence of AML is in the sixth decade, and patients over the age of 65 do not tolerate chemotherapeutic regimens well. Moreover, AML has been highly studied as a model for other cancers. An RNA Biology Program is established aiming to develop comprehensive datasets through the profiling of all different classes of RNA expression, RNA editing, alternative splicing, and non-coding RNAs in CD34+ normal hematopoietic stem cells (HSC), their differentiated progeny, and AML clinical samples that could be utilized to understand leukemia. These datasets will allow us to computationally identify and characterize various RNA species and processes to enable the development of effective therapeutics to AML, leukemia and other types of cancers. Epigenetic factors such as methylation and histone modifications will also be characterized from these clinical samples allowing for integrated dataset analysis to look at the cross-talk between RNA and DNA/epigenomics in leukemia. The following is a subsidiary study of the above study description where whole genome sequencing was performed on two collected AML patients' samples using Illumina and Oxford Nanopore sequencing technologies. The aim is to characterize the roles of structural variants (SV) in RNA biology which are potentially important for AML development using our own established long-read SV characterization tool, NanoVar. The advent of Oxford Nanopore sequencing technologies has opened a new avenue for better SV characterization by having longer sequencing reads. NanoVar is an accurate and rapid SV characterization tool that utilizes low-depth Nanopore sequencing data. NanoVar makes use of split-reads and hard-clipped reads for SV discovery and employs a simulation-trained neural network classifier for true positive enrichment. NanoVar exhibited higher accuracy and faster computational speed amongst other long-read SV detection tools in simulated data. In AML patient data, NanoVar displayed excellent accuracy in SV characterization (16/16 SVs validated in two patients) by using only 4x depth sequencing data. In summary, NanoVar improves the accuracy and speed of SV characterization at a lower sequencing cost, an approach compatible with clinical studies.

  Study phs001847

• SiMSen‑Seq

  High resolution amplicon-bases sequencing o screen for PIK3CA hot spot mutations

  Dataset EGAD50000001668

• RNA sequencing of primary B-cells infected with EBV virus

  Study EGAS00001007187

• Total RNA-Sequencing of patient-derived xenograft models of myxoid liposarcoma

  Study EGAS00001004901

• 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

• High-grade B-cell lymphoma, not otherwise specified: an LLMPP study

  Molecular characterization of high-grade B-cell lymphoma, not otherwise specified (HGBCL-NOS), is hindered by its rarity, evolving definition, and poor diagnostic reproducibility. To address this challenge, we analyzed 92 HGBCL-NOS tumors collected across Lymphoma/Leukemia Molecular Profiling Project sites. These tumors were profiled using whole-genome sequencing (WGS) or whole-exome sequencing (WES) to identify somatic mutations, WGS or low-pass WGS to detect copy number alterations, targeted capture sequencing to assess MYC and BCL2 structural variants, and RNA sequencing. The genetic features of HGBCL-NOS were compared to those of diffuse large B-cell lymphoma (DLBCL-NOS) and EBV-negative adult Burkitt lymphoma (BL). DLBCL-NOS tumors underwent targeted capture sequencing using a panel of 125 genes recurrently mutated in aggressive B-cell lymphomas. BL biopsies were drawn from the Burkitt Lymphoma Genome Sequencing Project and had available WGS (dbGaP Study Accession: phs000527.v18.p6).

  Study EGAS50000000932