3743 results for "RNA AND sequencing OR transcriptome"

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• Glioblastoma_CRISPR_Screen

  This is an in vitro genome-wide CRISPR/cas9 screen in human glioblastoma stem cells, screening for genes essential for survival of these cells. These cells express cas9 and have been transfected with a guide RNA library causing gene knockouts. We will analyse the sequencing data for depletion of guide RNAs.

  Study EGAS00001001519

• Genetic dysregulation of gene expression and splicing during a ten-year period of human aging in the PIVUS study

  We performed RNA sequencing in whole-blood from the same individuals from the PIVUS study at ages 70 and 80 to quantify how gene expression, alternative splicing, and their genetic regulation are altered during this 10-year period of advanced aging.

  Study EGAS00001003583

• RSV infection of primary bronchial epithelial cells in asthma

  Primary bronchial epithelial cells derived from healthy donors and asthma patients were differentiated in Air-Liquid-Interface condition and infected with the respiratory syncytial virus. Single-cell RNA sequencing analysis of these cultures was used to study the transcriptomic response of the cells to RSV.

  Study EGAS00001007450

• Symptom Clusters in Oncology Patients Receiving Chemotherapy

  The parent longitudinal study evaluated the symptom experience of oncology outpatients receiving chemotherapy. Patients completed questionnaires in their homes a total of six times (assessments 1 through 6). The questionnaires were timed to evaluate symptoms associated with the receipt of two cycles of chemotherapy that were administered approximately a month apart. Assessments 1 and 4 evaluated symptoms prior to the receipt of chemotherapy. Assessments 2 and 5 evaluated symptoms in the week following the administration of chemotherapy. Assessments 3 and 6 evaluated symptoms two weeks following the administration of chemotherapy. For this analysis, morning and evening fatigue data from the enrollment assessment (i.e., prior to the second or third cycle of chemotherapy) and the assessment that was done approximately 1 week after administration of chemotherapy were evaluated. Patients completed the Lee Fatigue Scale to obtain information on morning and evening fatigue severity. For the morning fatigue assessment, patients were asked to describe how they “felt over the past week when they woke up in the morning”. For the evening fatigue assessment, they were asked to describe how they felt over the past week “before they went to bed at night”. Medical records were reviewed for disease and treatment information. Epigenome assays (microarray) were completed for 1170 patients. Whole transcriptome sequencing (bulk RNA-Seq) was completed for 651 patients.

  Study phs003863

• Phenotypic characterization and prognostic impact of CD103+ tissue-resident memory T cells in diffuse large B cell lymphoma

  Tissue-resident memory T (TRM) cells are a population of memory T cells that stably occupy tissues and play a key role in immunosurveillance, having been linked to favorable survival outcomes in various solid tumors. While TRM cells have been identified in lymph nodes, their phenotype and prognostic significance in B-cell non-Hodgkin lymphoma (B-NHL), including diffuse large B-cell lymphoma (DLBCL), remains poorly characterized. The frequency of CD103 expressing T cells in patient samples with DLCBL was quantified by immunofluorescence (IF) staining of tissue biopsies (n=306) and flow cytometry (n=252) of cell disaggregates, and linked with clinical outcome. The phenotype of TRM cells was characterized by spectral flow cytometry (n=10 DLBCL and 2 reactive lymph node (rLN) samples) and single-cell RNA sequencing (scRNAseq) (n=12 aggressive B cell lymphomas and 4 rLN samples). An additional 51 samples from an external dataset were included to verify the single cell transcriptome findings. The flow cytometry and scRNAseq findings in DLBCL were extrapolated to additional B-NHL entities. Through analysis of these datasets we were able to characterize CD103+ TRM-like cells in DLBCL and other B-NHL entities and identified them to represent a prognostically favorable population with an activated/cytotoxic T cell phenotype.

  Study EGAS50000000943

• Tenk10k Phase 1: Whole Genome Sequencing

  TenK10K Phase 1 is a dataset of matched human whole-genome sequencing (WGS) from 1,925 individuals, and single-cell RNA sequencing (scRNA-seq) from over 5 million peripheral blood mononuclear cells across 28 immune cell types. Single-cell ATAC sequencing was additionally performed on a subset of 922 individuals. This EGA study consists of the WGS data from 1,925 individuals while a separate EGA study comprises the scRNA-seq and scATAC-seq data.

  Study EGAS50000001654

• ChIIP-seq and RNA-seq

  epigenome profiling in tumor tissues and paired normal tissues of LUAD patients and transcriptome profiling in tumor tissues of LUAD patients.

  Dataset EGAD00001007066

• RNA Editing Exome

  Exome sequencing data for tumor and matched normal samples of the EGAS00001000495 project.

  Dataset EGAD00001000626

• National Cancer Institute Cancer Genome Characterization Initiative (CGCI)

  The Office of Cancer Genomics at the National Cancer Institute sponsored a series of studies as part of the Cancer Genome Characterization Initiative (CGCI) to assess novel emerging sequencing technologies in cancer. The CGCI program included comprehensive characterization of the genetic aberrations found in different pediatric and/or adult tumors. CGCI characterized a number of B-cell non-Hodgkin lymphomas (including diffuse large B-cell lymphoma (DLBCL) from patients with and without HIV+ infection, follicular lymphoma (FL), as well as adult and pediatric Burkitt lymphomas), and additional HIV-associated tumors (including DLBCL, lung, and cervical cancers). All data from these projects is available at the NCI Genomic Data Commons. Individual project descriptions are available by disease on the substudy pages (links are included at the top of this page). Brief summaries are as follows: Non-Hodgkin Lymphoma (NHL) - CGCI investigators probed genomic alterations more deeply than had previously been possible by using state-of-the-art RNA sequencing (mRNA-seq) and whole genome shotgun sequencing (WGS) coupled with leading edge bioinformatics, data management and analysis approaches. The project sequenced tumor DNA and/or RNA from 117 NHL tumor samples and 10 cell lines. This included the genomes or exomes of 1 Follicular Lymphoma (FL) and 13 diffuse large B-cell lymphoma (DLBCL) cases, all with matched constitutional DNA sequenced to comparable depths, RNA-sequencing (mRNA-seq) of 92 DLBCL, 12 FL and 8 B-cell NHL cases with other histologies and 10 DLBCL-derived cell lines. The DLBCL cases and cell-lines are from the two major subtypes of DLBCL: germinal center B-cell (GCB) and activated B-cell (ABC). HIV+ Tumor Molecular Characterization Project (HTMCP) - This project was a joint effort of the Office of Cancer Genomics (OCG) and the Office of HIV and AIDS Malignancy (OHAM). Its goals were to characterize HIV-associated cancers (obtained from HIV-infected patients) and compare them to the same types of cancers from patients without HIV infection. Investigators performed 30X genome sequencing of 100 cases of paired tumor and germline DNA, along with transcriptome sequencing in each of 3 types of HIV+ tumors (DLBCL, lung and cervical cancers). These platforms allow discovery of mutations both in coding and non-coding genomic regions, gene expression and genomic alterations (including translocations, insertions and deletions). Comparing tumors of cancer patients both with and without HIV-infection provides insight into the potential function of this virus in certain cancers. Burkitt Lymphoma Genome Sequencing Project (BLGSP) - This project was a collaborative effort between the National Cancer Institute and the Foundation for Burkitt Lymphoma Research to develop a databank of the many alterations found in Burkitt lymphoma (BL), an uncommon type of Non-Hodgkin lymphoma that occurs most often in children and young adults. The goal of the BLGSP was to explore potential genetic changes in patients with BL that could lead to better prevention, detection and treatment of the cancer. The project characterized the alterations of the tumors' genomes (with matched normal as control) and transcriptomes by sequencing the DNA and RNA of each case. Using the data generated, the ultimate goals of the project was to discover the molecular changes that are present in BL patients and then determine how those changes correlate with treatment regimen and outcome. CGCI data is accessible at the NCI's Genomic Data Commons (GDC) via the GDC's Data Portal and from each of the CGCI Publication Pages at the GDC (Please see the "Supplemental Links" section of any CGCI publication's "Publication Information and Associated Data Files page" at the GDC.). Available datasets include raw sequencing data, datasets generated by the original CGCI research teams (fully annotated clinical information and higher-level/analyzed molecular characterization data), as well as higher level data generated by the GDC. Please see the CGCI Use and Publication Guidelines for updated details on the sharing of any CGCI substudy data, including how to cite CGCI.To learn more about the CGCI studies, please visit the CGCI Program website.

  Study phs000235

• Single-Cell RNA-Sequencing Analysis of Responses to Pembrolizumab in Sezary Syndrome

  This phase 2 single arm clinical trial assessed the efficacy of pembrolizumab in patients with previously treated mycosis fungoides or Sezary syndrome. Pembrolizumab was found to have a 38% overall response rate, and a 27% overall response rate in subjects with Sezary syndrome. We performed single-cell RNA-sequencing on samples collected before the first treatment and after 3 weeks of pembrolizumab treatment. Sequencing was performed on cryopreserved peripheral blood T-lymphocytes isolated from 6 trial participants, including 3 patients who responded to pembrolizumab treatment and 3 patients who did not respond. A total of 118,961 peripheral blood T-cells are included in this data set.

  Study phs002933