11989 results for "cancer rna-seq"

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• Brain Cell Type-Specific Enhancer-Promoter Connectivity Maps and Disease Risk Association

  These studies map the epigenetic landscape of microglia, neurons, astrocytes and oligodendrocytes. The initial study compared acutely isolated microglia to cultured microglia from the same donors, to identify changes that occur when microglia are removed from the brain microenvironment. In collaboration with the Rady Children's Hospital, we obtained brain tissue samples from pediatric patients representing putative normal tissue resected to gain access to brain tumors as well as tissue resected to remove epileptic foci. We assayed microglia isolated from these samples using RNA-seq, ATAC-seq and ChIP-seq for PU.1, H3K4me2, and H3K27ac. For patients from whom a sufficient cell number was obtained, we additionally cultured their microglia for up to 7 days and subjected these to the same suite of assays. In a follow-up study, we obtained brain tissue from a comparable cohort of pediatric epilepsy patients from Rady Children's Hospital. We isolated nuclei from microglia, neurons, astrocytes and oligodendrocytes, and assayed for ATAC-seq, ChIP-seq for H3K4me3, and H3K27ac, and PLAC-seq (Proximity Ligated ChIP-seq). We isolated microglia from human fetal and postnatal sample and assayed for bulk RNA-seq, bulk ATAC-seq, bulk H3K27ac ChIP-seq, single-cell RNA-seq (scRNA-seq) and single-cell ATAC-seq. For these studies, human microglia are defined by signature genes/proteins, such as P2RY12, SALL1, and CX3CR1.

  Study phs001373

• Transcriptome of Ewing sarcoma tumors - RNA-seq (ICGC)

  Transcriptome of Ewing sarcoma tumors (ICGC project). Fastq files of 57 RNA-seq are available (2x101bp).

  Dataset EGAD00001004493

• Single Cell RNA-Seq

  Examination of Sample Multiplexing Reagents for Single Cell RNA-Seq. Nine techniques applied to samples from four PDX models: #105, #177, #233, #264

  Dataset EGAD50000000216

• Single nucleus RNA-seq of human epiglottis and subglottis

  This dataset contains single nucleus RNA-seq of human epiglottis and subglottis tissue performed using the 10X platform

  Dataset EGAD50000001279

• Bulk RNA-seq of Human Epiglottis and Subglottis

  This study contains bulk and single nucleus RNA-seq of human epiglottis and subglottis tissue.

  Dataset EGAD50000001278

• Glioblastoma stem cell lines RNA-seq

  RNA-seq data for three Glioblastoma stem cell (GSC) lines exposed to PRMT5 inhibitor and control samples.

  Dataset EGAD00001006095

• 7 samples RNA-seq raw data

  Dataset comprising raw paired RNA-seq data in fastq.gz format for 7 samples of rosette forming brain tumors

  Dataset EGAD00001009265

• RNA-seq of UTUC samples

  This dataset includes transcription profiling by RNA-seq of 3 upper urinary tract urothelial tumours (UTUC).

  Dataset EGAD00001008138

• Vcf RNA-Seq data

  Variants derived from mapped whole transcriptome RNA-Seq data from 476 human samples of early stage urothelial carcinoma.

  Dataset EGAD00001001941

• Un-mapped RNA-Seq data

  Un-mapped whole transcriptome RNA-Seq data from 476 human samples of early stage urothelial carcinoma.

  Dataset EGAD00001001940

• RNA-seq data from sorted CML and normal samples

  RNA-seq data from sorted populations from 10 CML samples and 4 normal bone marrow samples.

  Dataset EGAD00001004079

• snRNAseq of ATCWGS42

  We performed single nucleus RNA-sequencing (snRNA-seq) on two regions from ATCWGS42 (ATCWGS42_E and ATCWGS42_R).

  Study EGAS50000001491

• DDX50 Cooperates With STAU1 to Effect Stabilization of Pro-Differentiation RNAs

  This study was undertaken to determine the role of DDX50 in epidermal homeostasis. Primary neonatal foreskin keratinocytes were obtained from discarded surgical samples at a California hospital. Samples were anonymous and not selected. DDX50, which was associated with STAU1, was found to promote epidermal differentiation and transcript stability using the methods of RNA-seq, CLIP-seq and DMS-MaP-seq.

  Study phs003766

• Human data for chromatin accessibility (ATAC-Seq and scATAC-Seq) and transcriptome (RNA-Seq and scRNA-Seq) in eight B-cell precursors, from HSC to Naive B cells

  We generated paired transcriptomic (RNA-Seq) and chromatin accessibility (ATAC-Seq) profiles from 8 immune cell populations representing the early lymphoid hematopoietic differentiation stages along the B cell lineage: HSC, CLP, pro-B, pre-B, Immature B, Transitional B, Naive B CD5-, Naive B CD5+. Cell populations were isolated from healthy adult human bone marrow precursors and peripheral blood (n=13) following a predefined sorting strategy. For each donor, a subset of different cell type populations was obtained. Additionally, to explore the continuous dynamic of RNA and ATAC, we generated a single-cell sample of human CD34+ B cell precursors.

  Study EGAS00001007296

• RNA sequencing of tumor samples from patients with Waldenstrom macroglobulinemia

  RNA was extracted from flow-sorted CD19+. RNA-Seq was performed on 32 samples of 30 patients (2 replicates per samples). RNA-Seq libraries were subjected to non-stranded paired-end (2 x 75 bp) sequencing on HiSeq 2500 (Illumina). The files are in FASTQ format.

  Dataset EGAD00001005324

• Precise reconstruction of the tumor microenvironment using bulk RNA-seq and a unique machine learning-based algorithm trained on artificial transcriptomes

  Cellular deconvolution algorithms virtually reconstruct tissue composition by analyzing the gene expression of complex tissues. Here, we present the decision tree machine learning algorithm, Kassandra, trained on a broad collection of > 9,400 tissue and blood sorted cell RNA profiles to accurately reconstruct the tumor microenvironment (TME). Bioinformatic correction for technical and biological variability, aberrant cancer cell expression inclusion, and the accurate quantification and normalization of transcript expression increased the stability and robustness of Kassandra. Performance was validated on over 4,000 H&E tissue slides and more than 1,000 normal and tumor tissues by comparison with cytometric, immunohistochemical or single-cell RNA-seq measurements. Kassandra accurately deconvolved stromal and immune elements of blood and tumors, revealing the role of the TME in tumor pathogenesis. Digital TME reconstruction revealed that the presence of PD1-positive CD8+ T cells strongly correlated with immunotherapy response and increased the predictive potential of established biomarkers, indicating that Kassandra could potentially be utilized in future clinical applications.

  Dataset EGAD00001008776

• The Finland-United States Investigation of NIDDM Genetics (FUSION) Study - Islet Expression and Regulation by RNAseq and ATACseq

  This study evaluates gene expression and its regulation in human pancreatic islets, a tissue relevant in the study of genetic risk factors contributing to diabetes. We obtained pancreatic tissue sections and purified pancreatic islets from deceased donors and processed these biological samples to generate various data types. We generated spatial transcriptomic data from pancreatic tissue samples using the 10X Genomics VISIUM technology with sequencing on the Illumina NovaSeq platform. We also generated multiple data types from the purified pancreatic islets using genome-wide SNP chips, bulk RNA-Seq, microRNA (miRNA)-Seq, whole genome sequence, DNA methylation (methyl)-Seq, cap analysis of gene expression (CAGE)-Seq, single cell RNA-seq, and single nuclei ATAC-seq approaches. These data include ATAC-seq of two islet subjects, RNA-seq of 31 additional subjects, genome-wide chip genotypes, and imputed genotypes of the 33 subjects released with phs001188.v1. For genotyping, 500-1000 islet equivalents (IEQ) were cultured as in Gershengorn (Science, 2004, PMID: 15564314); genomic DNA isolated from islet cultures. For RNA analyses, 2500-5000 IEQ from each islet source were used for bulk or single-cell RNA isolation. Messenger RNA was isolated with trizol extraction and 12-plex libraries were generated using the Illumina TruSeq directional mRNA-seq library protocol. Bulk RNA sequencing was performed on HiSeq2000/HiSeq2500/Hiseq4000/NovaSeq6000 sequencers using paired-end reads at the NIH Intramural Sequencing Center (NISC). miRNA libraries were prepared from total RNA from 68 samples, pooled and sequenced 50bp single-end reads on Illumina HiSeq2500. CAGE libraries were prepared from total RNA samples using the nAnT-iCAGE protocol at DNAFORM, Japan. CAGE libraries were sequenced at the NIH Intramural Sequencing Center (NISC) on the HiSeq2000 sequencer. Genotyping on the Illumina Omni2.5M array was performed at the NHGRI Genomics Core facility. Genotypes were imputed using the HRC.r1.1.2016 reference panel. To assess regions of open chromatin in islets, we performed bulk ATAC-seq on HiSeq2000 sequencers using paired-end reads at NISC. Single-nuclei ATAC-seq libraries were prepared using single-cell-combinatorial-indexing (sci-) ATAC-seq protocol and sequenced on Illumina NextSeq using paired-end reads. scRNA-seq libraries were generated using the 10X Genomics platform and sequenced on Illumina HiSeq3000 at the Genomics Technology Core of the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS). Greater than 90% of the loci associated with T2D through genome-wide association studies occur in non-coding regions, suggesting a strong regulatory component to disease susceptibility. Therefore, there is a critical need to understand the full spectrum of genetic variation and regulatory element usage in T2D-relevant tissues. To that end, this study contains multiple genomic and transcriptomic data sets from pancreas tissue sections and pancreatic islets, a resource that will contribute to our efforts to investigate the genetic risk factors for type 2 diabetes.

  Study phs001188

• Transcriptomic Profiling of an Anti-PD-L1 Treated Cohort of Newly Diagnosed GBM Patients

  Checkpoint inhibitor therapy has limited efficacy in glioblastoma patient outcomes. This study involves RNA sequencing (RNA-seq) of newly diagnosed GBM patients treated with concurrent atezolizumab, radiation therapy, and temozolomide. By analyzing RNA-seq data from 39 tumors, the study aims to explore tumor transcriptomic features, including immune-based transcriptomic programs and immune infiltration, to understand their influence on PD-L1 blockade treatment efficacy and to identify which patients may benefit more from such therapy.

  Study EGAS50000000784

• Dissecting Cell Composition and Drug Sensitivity in Human Adenoid Cystic Carcinomas (ACCs)

  The study reports the results of single-cell RNA sequencing (scRNA-seq), RNA sequencing (RNA-seq), and whole-exome sequencing (WES) experiments performed on malignant cells isolated by flow cytometry from seven patient-derived xenograft (PDX) lines established from human Adenoid Cystic Carcinomas (ACCs). Of these seven lines, five are characterized by well differentiated histology (ACCX5M1, ACCX6, ACCX14, ACCX22, SGTX6) and two by solid histology (ACCX9, ACCX11). Analysis by scRNA-seq of the well-differentiated PDX line ACCX22 led to identification of cell-surface markers (CD49f, KIT) that enabled the differential purification of the two major cellular components contained in well-differentiated ACCs: myoepithelial-like (CD49f-high/KIT-negative) and ductal-like (CD49f-low/KIT-positive) cells. The study reports the analysis by RNA-seq and WES of purified preparations of myoepithelial-like and ductal-like cells from well-differentiated PDX lines (ACCX5M1, ACCX6, ACCX14, ACCX22, SGTX6) and of ductal-like (CD49f-low/KIT-positive) cells from solid PDX lines (ACCX9, ACCX11).

  Study phs002764

• Delineating pediatric brain tumor progression using single-nuclei sequencing

  Pediatric brain cancers are the most common solid tumors in children with varying survival rates depending on molecular features of cancer cells and associated microenvironment. Several studies have used single-cell RNA sequencing to define transcriptional programs active in cancer cells and highlighted supportive roles of non-cancerous cells embedded in these tumors. Although application of single-cell RNA sequencing technology has expanded our understanding of intratumoral heterogeneity and underlying transcriptional mechanisms in brain tumors at diagnosis, mechanisms of disease remains elusive. Therefore, the purpose of this proposal is to characterize cellular and transcriptional states of malignant and non-malignant compartments at primary diagnosis and at relapse. In this study, we performed single-nuclei sequencing of 42 patient samples taken at various disease stages (initial diagnosis, progressive disease, and relapsed disease) from 20 patients with low-grade glioma or Atypical Teratoid Rhabdoid Tumor (ATRT). Bulk whole genome and RNA-seq data for these samples are available from the Children’s Brain Tumor Network and the Gabriella Miller Kids First Data Resource Center. Findings from our study will help define the mechanistic shifts of tumor and non-cancerous cells over course of disease progression. Collectively with the single-cell Pediatric Cancer Atlas funded, this project lays the foundation of an important data set focused on lethal relapsed cancers that can continue to be expanded to identify cancer-intrinsic and extrinsic microenvironmental factors supporting recurrence of pediatric brain tumors.

  Study EGAS50000001288

• Enhancer profiling identifies epigenetic markers of endocrine resistance and reveals therapeutic options for metastatic castration-resistant prostate cancer patients (LuCaP cell line data)

  Androgen Receptor (AR) signaling inhibitors, including enzalutamide, are treatment options for patients with metastatic castration-resistant prostate cancer (mCRPC), but resistance inevitably develops. Using metastatic samples from a prospective phase II clinical trial, we epigenetically profiled enhancer/promoter activities with H3K27ac chromatin immunoprecipitation followed by sequencing, before and after AR-targeted therapy. We identified a distinct subset of H3K27ac-differentially marked regions that associated with treatment responsiveness. These data were successfully validated in mCRPC patient-derived xenograft models (PDX). In silico analyses revealed HDAC3 as a critical factor that can drive resistance to hormonal interventions, which we validated in vitro. Critically, we identified the pan-HDAC inhibitor, vorinostat to be effective in decreasing tumor cell proliferation both in vitro and in vivo. Moreover, we uncovered evidence for HDAC3 working together with Glucocorticoid Receptor (GR) as a potential mechanism for this therapeutic effect. These findings demonstrate rationale for new therapeutic strategies including HDAC inhibitors to improve patient outcome in advanced stages of mCRPC. Project Goal: We identified H3K27ac regions associated with resistance in patient samples. Extensive analysis of these regions suggested that HDAC3 may play a role in resistance. To test this, we analyzed ChIP-seq and RNA-seq from cell lines generated from PDX LuCaP samples (recapitulating resistant and non-resistant) to validate findings in patient samples. ChIP-seq samples were used to verify the signals identified from specific factors, such as H3K27ac, AR, FOXA1, GR and HDAC3, their association with resistance and possible mechanisms of action. RNA-seq samples were analyzed to determine the effect of AR signaling in these samples in specific genes in the H3K27ac resistance-associated regions.

  Study EGAS50000000917

• Adeno-associated virus in the liver: natural history and consequences in tumor development

  Adeno-associated virus (AAV) is a defective mono-stranded DNA virus, endemic in human population (40-80%). AAV infection has long been considered as non-pathogenic1, however few years ago we reported for the first time recurrent clonal AAV2 insertion in the pathogenesis of human hepatocellular carcinoma (HCC) developed on normal liver. These clonal viral insertions target cancer driver genes, including CCNA2, CCNE1, TERT, TNFSF10 and MLL4, leading to their overexpression. The viral inserted sequences involved in almost all the cases the 3’ inverse tandem repeat (ITR) of AAV2, which is important for virus integration in host DNA and exhibits a promoter/enhancer activity. Here, we used RNA sequencing (RNA-seq) to investigate their functional impact on the tissue, such as fusion transcript generation events.

  Study EGAS00001003310

• scRNA Seq of MCSP+ melanoma DCC and bulkRNA Seq of MelDCC lines

  Single cell RNA Seq of: 193 MCSP+ DCC isolated from SLNs of melanoma patients, 9 MCSP+ cells isolated from LNs of non-melanoma patients, 14 melanocytes from a healthy donor. Bulk RNA Seq of 10 samples from 4 DCC-PDX-derived cell lines. Sequencing on NovaSeq6000. Fastq files.

  Dataset EGAD00001009662

• Leiomyosarcoma RNA-Seq

  RNA was extracted from fresh frozen LMS material for 29 untreated tumors (24 primary tumors, 5 metastatic12 relapses) and 13 tumors treated with radiation(7 primaries, 6 metastatic relapses). RNA-Seq sequencing was performed using established protocols on Illumina HiSeq 2500

  Dataset EGAD00001006628

• Single RNA-Seq of fCAB treated tRNAs from VDH01

  Single RNA-seq of fCAB treated tRNAs from vdh01 samples (5 replicates). tRNAs were extracted using Mirvana° Invitrogen kit. The samples were prepped with Il TruSeq Small RNA and sequenced on Illumina NextSeq550.

  Dataset EGAD00001008743