11754 results for "cancer rna-seq"

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• scRNA primaries

  Single cell RNA-seq for primary samples

  Dataset EGAD00001006135

• PACA-CA RNASeq fastq files

  Fastq files for PACA-CA RNA Seq analysis, for DCC release 27

  Dataset EGAD00001003972

• Covacta RNAseq merged EGA metadata

  Sample metadata for the RNA-seq dataset. This dataset includes subject-level data and longitudinal visit day information for the corresponding samples.

  Dataset EGAD00001011162

• Comprehensive Genomic Characterization of Translocation Renal Cell Carcinoma

  Xp11 translocation renal cell carcinoma (tRCC) is a rare, female-predominant cancer driven by a fusion between the TFE3 gene on chromosome Xp11.2 and a partner gene on either chrX or an autosome. It remains unknown what types of rearrangements underlie TFE3 fusions, whether fusions can arise from both the active (chrXa) and inactive X (chrXi) chromosomes, and whether TFE3 fusions from chrXi translocations account for the female predominance of tRCC. To address these questions, we performed haplotype-specific analyses of chrX rearrangements in tRCC whole genomes. We show that TFE3 fusions universally arise as reciprocal translocations and that oncogenic TFE3 fusions can arise from chrXi:autosomal translocations. Female-specific chrXi:autosomal translocations result in a 2:1 female-to-male ratio of TFE3 fusions involving autosomal partner genes and account for the female predominance of tRCC. Our results highlight how X chromosome genetics uniquely constrains somatic chrX alterations and underlies cancer sex differences.This version of the dbGaP study provides a comprehensive set of whole genome data and tables with clinical information collected for the 16 patients (15 pateints as tRCC and 1 patient as ccRCC) in the study cohort. The data also contains 12 RNA-seq samples used in the study and analyses. We anticipate that this data will considerably advance our molecular and genetic understanding of oncogenic translocations in TFE3-tRCC involving inactive chromosome X and its role in cancer sex bias.

  Study phs003008

• Comprehensive molecular profiling with whole-exome sequencing (WES) and RNA sequencing (RNA-seq) of PDX tumors

  To identify biomarkers of the antitumor efficacy of molecular targeted therapies, patient-derived xenograft (PDX) mouse models established from 52 patients with solid tumors were treated.

  Study JGAS000707

• RNA-seq of iPSC-derived microglia treated with miRNA mimics and inhibitors

  Microglia were derived from iPSCs and treated with mimics and inhibitors of the miRNAs hsa-miR-150-5p, hsa-miR-193a-3p and hsa-miR-19b-3p. RNA-sequencing was then performed to examine the effects of up- and down-regulation of the respective miRNAs.

  Dataset EGAD00001006842

• ATAC-seq data in normal colon mucosa

  This dataset includes ATAC-seq data generated in normal colon mucosa obtained in four healthy volunteers during colonoscopy indicated for colorectal cancer screening. Subjects had no lesions in the colon. Also includes one frozen sw480 colon adenocarcinoma cell line sample for piloting the protocol

  Study EGAS00001005281

• Pancreatic cancer RNA sequencing

  Study EGAS00001004706

• Pediatric HGG WES and RNA-Seq

  Paediatric high-grade glioma (pHGG) is the leading cause of paediatric brain tumour death. Here we performed RNA and whole exome sequencing on pHGG samples to analyse transcriptomic and genetic alterations associated with this devastating disease, and to understand the relationship between them.

  Study EGAS00001005687

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

  RNA-sequencing data of pediatric B-cell precursor acute lymphoblastic leukemia, including 18 high hyperdiploid cases and 9 ETV6/RUNX1-positive cases. Sequencing libraries were constructed using the Human Ribo-Zero rRNA Removal Kit (Illumina, San Diego, CA) and sequenced on an Illumina NextSeq 500. RNA sequencing data were processed using the TCGA mRNA-seq pipeline (https://docs.gdc.cancer.gov/Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline/#mrna-analysis-pipeline).

  Dataset EGAD00001004176

• Single-cell RNA-seq data of bronchoalveolar lavage (BAL) fluid in severe COVID-19 and SARS-CoV-2 stimulated classical blood monocytes

  We performed single-cell RNA-sequencing of cells in the bronchoalveolar lavage (BAL) fluid of severe COVID-19. In addition, we performed single-cell RNA-sequencing of SARS-CoV-2 stimulated classical blood monocytes. This study provides detailed insights into the alveolar macrophage response to SARS-CoV-2 infection and reveals a profibrotic macrophage response in severe COVID-19 patients.

  Dataset EGAD00001006827

• Multiplexed scRNA-Seq Reveals Cellular and Genetic Correlates of SLE

  Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease. Knowledge of circulating immune cell types and cell states associated with SLE remains incomplete. We profiled over 1.2 million PBMCs (160 cases, 98 controls) with multiplexed single-cell RNA-seq (mux-seq). Cases exhibited prominent expression of type-1 interferon-stimulated genes (ISG) in monocytes, reduction of naïve CD4+ T cells that correlated with monocyte ISG expression, and expansion of repertoire-restricted cytotoxic GZMH+ CD8+ T cells. Cell-type-specific expression features accurately predicted case-control status and stratified patients into two molecular subtypes. We integrated dense genotyping data, mapping cell-type-specific cis-eQTLs and linked known and novel SLE-associated variants to cell-type-specific gene expression. These results demonstrate mux-seq as a systematic approach to characterize cellular composition, identify transcriptional signatures, and annotate genetic variants associated with SLE.

  Study phs002812

• G&T-seq: parallel sequencing of the genomes and transcriptomes of single cells

  The ability to simultaneously sequence the genome and transcriptome of the same single cell offersa powerful means to dissect functional genetic heterogeneity at the cellular level. Here we describeG&T-seq, a method for separating and sequencing genomic DNA and full-length mRNA from singlecells. By applying G&T-seq to over 220 single cells we reveal cellular properties that cannot beinferred from DNA or RNA sequencing alone, including associations between DNA copy numbervariation and gene expression dosage. We further demonstrate the detection of coding interchromosomalfusions and single nucleotide variants in both the genomes and transcriptomes ofindividual cells. G&T-seq enables the study of genotype-phenotype associations in single cells, andthe investigation of DNA cell lineage trees of healthy and diseased tissues with transcriptome inferredcell types and states.

  Study EGAS00001001204

• Enhanced Adjuvanticity of a Personal Neoantigen Vaccine Generates Potent Neoantigen-Specific Immunity

  Personalized neoantigen-targeting vaccines can induce durable and diverse T cell responses and have been associated with improved outcomes. To augment immunogenicity, we tested a synthetic long peptide vaccine formulated with the adjuvants Montanide and poly-ICLC in 10 patients with melanoma. The vaccines, co-administered locally with ipilimumab and systemically with nivolumab, generated de novo ex vivo T cell responses against the majority of immunizing neoepitopes in all 9 fully vaccinated patients, and ex vivo CD8+ T cell responses in 6 of 9. Hundreds of circulating and intratumoral T cell receptor (TCR) clonotypes emerged following vaccination that were distinct from those arising after PD-1 inhibition. By linking vaccine-specificity and cellular phenotype of TCRs in post-treatment tumors at single cell resolution, we demonstrate remodeling of the intratumoral T cell repertoire following vaccination. These observations demonstrate the impact of multi-pronged immune adjuvanticity on the T cell repertoire in the context of neoantigen-targeting vaccines. We are submitting WES data from whole blood samples and tumor FFPE samples, and RNA-seq data from tumor FFPE samples. We are also submitting RNA-seq data from purified tumor samples. scRNA-seq data will also be submitted for skin samples (pre and post neoantigen vaccine dose #3), and tumor samples before starting treatment, before starting neoantigen vaccine Dose #1, and before neoantigen vaccine dose #4. Bulk TCR-seq data will be submitted for blood samples.

  Study phs003919

• RNA-seq, WGS and WES of Hepatocellular carcinomas, enriched in fibrolamellar carcinomas

  Dataset EGAD00001005308

• RNA-seq of human embryonic heart, lung, and cerebellum

  Characterization of cell types in the human embronic heart, lung, and cerebellum.

  Study EGAS00001004375

• bulkRNA

  Bulk RNA-seq for cALL patient-derived PDX samples

  Dataset EGAD00001006133

• Myeloma XI trial data

  The dataset contains WGS and RNA-seq from Myeloma XI trial

  Dataset EGAD00001005491

• RNAseq data

  RNA-seq data from PAXgene extracted whole blood of patients enrolled in the COVACTA trial. This dataset includes raw FASTQ files.

  Dataset EGAD00001011168

• Gene expression of transduced human primary germinal centre B-cells

  RNA-seq sequencing data of human germinal centre B-cells (42 samples)

  Dataset EGAD00001005281

• Berlin Neuroblastoma Dataset

  Paired tumor/normal WGS and RNA-seq of primary neuroblastoma.

  Dataset EGAD00001005488

• Transcriptome sequencing of cancer cell lines

  This dataset contains RNA sequencing data for 675 cancer cell lines. RNA libraries were made with the TruSeq RNA Sample Preparation kit (Illumina) according to the manufacturer protocol. The libraries were sequenced on an Illumnia HiSeq 2000

  Dataset EGAD00001000725

• Citeseq of human bone marrow

  CITE-seq dataset of human bone marrow from four healthy donors. Single-cell RNA sequencing was performed using the 10x Genomics 3’ v3 platform. Approximately 7,000–10,000 cells were loaded in each 10x channel, after which the single-cell libraries were prepared according to manufacturer’s instructions, except for the added CITE-seq steps. Demultiplexed FASTQ files are provided.

  Dataset EGAD50000001211

• Epigenomics and Single-cell Sequencing Define Cellular Heterogeneity in Langerhans Cell Histiocytosis

  Epigenomic and transcriptomic analysis of Langerhans cell histiocytosis (LCH) biopsies. Single-cell RNA-seq (10x Genomics) of seven LCH biopsies. ATAC-seq data from four sorted cell populations (in duplicate) from one LCH biopsy.

  Dataset EGAD00001005280

• CITE-seq data of primary acute myeloid leukemia patient samples with complex karyotype

  In this study, we aimed to assess RNA expression and surface antigen expression of acute myeloid leukemia with complex karyotype (CK-AML) at the single-cell level. For this purpose, we performed cellular indexing of transcriptomes and epitopes (CITE-seq) of primary leukemia samples from four CK-AML patients.

  Dataset EGAD00001011171