9337 results for "cancer rna-seq"

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• PACA-CA RNASeq fastq files

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

  Dataset EGAD00001003972

• 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

• 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

• NKI-AvL CRC-OVC DNA-seq

  The dataset “NKI-AvL CRC-OVC DNA-seq" includes 4 normal and 4 tumor BAM files from paired-end whole exome sequencing on Illumina HiSeq2500 and Illumina NovaSeq6000 for 2 colorectal cancer and 2 ovarian cancer patients.

  Dataset EGAD00001004340

• MESA colorectal cancer cfDNA EM-seq dataset

  This dataset contains the methylation sequencing data of 60 nonCancer and 70 colorectal cancer cfDNA samples. The methylation library is constructed by using NEBNext Enzymatic-seq Kit.

  Dataset EGAD00001009165

• Whole-transcriptome characterization of cell-free RNA (cfRNA) in cancer and non-cancer patients

  Whole-transcriptome characterization of cfRNA in cancer (stage III breast [n=46], lung [n=30]) and non-cancer (n=89) participants from the Circulating Cell-free Genome Atlas (NCT02889978). Dataset includes collapsed BAM files for plasma cfRNA from each patient, as well as collapsed BAM files for RNA from matched tumor tissue (when available).

  Dataset EGAD00001006484

• 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

• Transcriptome sequencing of gingivo-buccal oral squamous cell carcinoma for integrative analysis: alterations in expression of genes attributable to methylation changes

  Gingivo-buccal oral squamous cell carcinoma (OSCC-GB) is the most common cancer among men in India and is associated with high mortality. Although OSCC-GB is known to be quite different from tongue cancer in its genomic presentation and its clinical behavior, it is treated identically as tongue cancer. Predictive markers of prognosis and therapy that are specific to OSCC-GB are, therefore, required. To achieve this, we have carried out transcriptome (n=72) profiling of paired tumor-normal tissues collected from OSCC-GB patients from India. RNA sequencing was performed on tumor and paired adjacent normal samples from 72 OSCC-GB patients. From each patient, total RNA was extracted from tumor and normal tissue samples using AllPrep DNA/RNA Mini Kit (QIAGEN). The quality and concentration of isolated total RNA were checked using Agilent 2100 Bioanalyzer and NanoDrop 2000 (Thermo Fisher Scientific). The OD260/OD280 ratio was ≥ 2 and RNA Integrity Number (RIN) was ≥ 7.0 for all sequenced samples. Ribosomal RNA (rRNA) was removed from the RNA samples, using Ribo-Zero Magnetic Kit (Epicentre). Sequencing libraries were prepared from rRNA depleted samples using TrueSeq RNA Sample Preparation Kit (Illumina). Each triplex cDNA library pool was sequenced as 100bp paired-end on HiSeq-2000 or HiSeq-2500 (Illumina). Protocols suggested by the manufacturers were used for all assays.

  Study EGAS00001003893

• Effect of the Placental Transcriptome on Stunting in a Longitudinal African Cohort

  Mammals with placentas and flowering plants evolved genomic imprinting in nutritive tissues, the placenta and endosperm, respectively. In these tissues, the genomes inherited from the mother and father are in conflict over resource allocation to offspring. In imprinted genes, transcription is repressed on the paternal or the maternal allele, resulting in allele specific expression (ASE). We investigated the variation in ASE of imprinted genes in term human placentas in order to detect loss of imprinting (LOI), which leads to partial expression of the repressed allele. We collected the placental tissue from birth to women in our multigenerational, prospective cohort study in Mali, West Africa. We followed the women from their own infancies, early childhood to adulthood (age 18+ years). Contingent on prior informed consent, we collected placental tissue and umbilical cord tissue. We conducted RNA-Seq of the fetal compartment of the placentas and targeted DNA-Seq of the umbilical cord tissue, which is fetal, and of saliva samples from parents. Our sequencing effort produced two datasets. The first dataset is the whole transcriptome RNA-Seq dataset of 111 biopsies (59 placentas) and genotyping of 96 genes. Birth length, weight, and placental weight for the children associated with this dataset are listed in the phenotype file (DOI: 10.1093/molbev/msz226). The second dataset includes targeted RNA-Seq of 262 samples (251 placentas) and targeted DNA-Seq for 766 genes. The genes were selected because they met any one of the following criteria: (1) imprinted and reported in some studies, (2) highly expressed in placenta, or (3) relevant to diseases of interest in this cohort (https://doi.org/10.1093/g3journal/jkab176). This study provides the first systematic analysis of variation in LOI across genes and individuals in a human population, and should shed light on the hypothesis that the modulation of imprinting is an epigenetic mechanism and plays a role in the regulation of offspring growth.

  Study phs001782

• Direct Comparative Analysis of 10X Genomics Chromium and Smart-seq2

  Single cell RNA sequencing (scRNA-seq) is widely used for profiling transcriptomes of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently-used scRNA-seq platforms, yet there are only a few thorough and systematic comparisons of their advantages and limitations. Here, by directly comparing the scRNA-seq data by the two platforms from the same samples of CD45- cells, we systematically evaluated their features using a wide spectrum of analysis. Smart-seq2 detected more genes in a cell, especially low abundance transcripts as well as alternatively spliced transcripts, but captured higher proportion of mitochondrial genes. The composite of Smart-seq2 data also resembled bulk RNA-seq data better. For 10X-based data, we observed higher noise for mRNA in the low expression level. Despite the poly(A) enrichment, approximately 10-30% of all detected transcripts by both platforms were from non-coding genes, with lncRNA accounting for a higher proportion in 10X. 10X-based data displayed more severe dropout problem, especially for genes with lower expression levels. However, 10X-data can better detect rare cell types given its ability to cover a large number of cells. In addition, each platform detected different sets of differentially expressed genes between cell clusters, indicating the complementary nature of these technologies. Our comprehensive benchmark analysis offers the basis for selecting the optimal scRNA-seq strategy based on the objectives of each study.

  Study EGAS00001003973

• 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).

  Study phs001373

• Microvascular Permeability, Inflammation, and Lesion Physiology in Endometriosis: A Microphysiological Systems Approach

  The goal of the study is to identify novel molecular pathways involved in the etiology of endometriosis and to develop in vitro model systems to enable the study of the mechanisms regulating reproductive function. Using a physiomimetic modeling approach, primary tissue samples of the human endometrium derived from patients diagnosed with and without endometriosis and/or endometriotic diseases (e.g. adenomyosis) were used for secondary analysis using multi-omic systems biology analysis and to build tissue engineered models. We performed single cell RNA sequencing (scRNA-Seq, N=6)) to study the cellular and transcriptomic composition of the endometrial tissue microenvironment and proteomics (LC-MS/MS) to study protein-level signaling pathways and the matrisome of the native endometrium. Systems biology analysis of these datasets helped identified a putative dysregulated inflammatory signaling pathway in endometriosis patients compared to controls. Moreover, subsets from these scRNA-Seq and proteomic datasets were used to aid the design of a synthetic extracellular matrix hydrogel as an in vitro platform for the culture of endometrial cells. Tissue-engineered synthetic PEG hydrogel enables the simultaneous co-culture of endometrial epithelial organoids and stromal fibroblasts in a fully defined, 3D, and tunable environment. We demonstrated that the in vitro co-culture model recapitulates key phenotypic processes observed across the human menstrual cycle in response to sex hormone stimulation through both biochemical and transcriptomic (bulk RNA-sequencing) analysis. This model will enable future mechanistic studies that examine origins of endometriotic disease phenotypes. The transcriptomic data generated for this study including the scRNA-Seq data from primary human endometrial tissues and the bulk RNA-Seq datasets from the experimental co-culture models is available through dbGAP.

  Study phs003326

• 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

• MPRA-SCZ

  RNA-Seq and ATAC-Seq of iPSC derived neurons under baseline and KCl stimulation conditions from 10 distinct donors, including 5 healthy controls and 5 schizophrenic individuals. scATAC of human post mortem prefrontal cortex from 4 adult individuals including 2 neurotypical individuals and 2 schizophrenic individuals.

  Dataset EGAD00001011335

• Multi-omic analysis of Down Syndrome in thyroid

  Background: Down syndrome (DS) is a chromosomal disorder characterized by trisomy of chromosome 21 and is associated with various health problems. Congenital thyroid dysfunction is a common endocrine abnormality in DS, but its exact cause remains unknown. This work aimed at studying the etiology of congenital thyroid dysfunction in DS. Methods: Thyroid tissue of fetuses with DS (n=4) and fetuses without a genetic/developmental abnormality (n=5) were analyzed using histopathological evaluation, RNA sequencing (RNA-seq), and DNA methylation (DNAm) profiling. Results: Histological examination showed abnormally developed DS thyroid tissue compared to non-DS/healthy tissue. RNA-seq analysis showed numerous differences in gene expression between DS and healthy thyroid tissue, including significant downregulation of thyroid genes FOXE1, IYD and DIO2. Gene set enrichment analysis showed disruption of vital cellular processes and functions in DS fetal thyroid tissue. Analysis of DNAm and expression quantitative trait methylation (eQTM) analysis identified functional and biologically relevant associations, that can be linked to plausible disrupted pathways in DS. Conclusions: Based on these observations, we conclude that congenital non-autoimmune thyroid dysfunction in DS is probably a DS-specific form of thyroid dysfunction, characterized by abnormal thyroid development, altered expression of genes that regulate thyroid development and hormone production, and altered expression and DNAm of genes pertaining to numerous vital pathways leading to significant metabolic disturbances. The disturbances as investigated by multi-omics analyses (RNA-seq, DNAm and eQTM analyses) are widely spread over the genome, and presumably caused by the direct and downstream effects of overexpressed chromosome 21 genes (dosage effect), and (epi)genomic disturbances.

  Study EGAS00001007677

• RNA-seq data of 196 nontumorous human breast tissue

  Transcriptome analysis of nontumorous human breast tissues. 196 cases were included in the dataset.

  Dataset EGAD00001006397

• JMS dataset

  Juntendo Muscle Study (JMS) dataset comprises 23 samples of paired-end RNA-Seq sequences in fastq format.

  Dataset EGAD00001008983

• 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

• Integrated analysis of whole genome and RNA sequencing in 22 HBV-associated HCCs

  RIKEN collection WGS and RNA-seq reads for 66 HBV-associated HCC and matched blood or liver samples from 22 donors.

  Dataset EGAD00001001035

• 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

• Facioscapulohumeral muscular dystrophy (FSHD): RNA-seq of isogenic TIRM+, TIRM- muscle and PBMCs from patients and matched controls

  FASTQ files describing paired-end RNA-sequencing of isogenic TIRM+ and TIRM- muscle biopsies from 24 FSHD patients (48 samples) and vastus lateralis muscle biopsies from 11 matched control individuals. FASTQ files are also provided describing RNA-sequencing of 15 FSHD peripheral blood mononuclear samples and 14 matched controls. For muscle biopsies sequencing was at 21.7-35.5 million reads/sample. RNA was extracted from PBMCs followed by globin depletion with sequencing at 19.7-46.5 million reads/sample.

  Dataset EGAD00001011077

• Breast_cancer_topographs

  Breast cancer topography will be explored using a combination of multi-region whole geome sequencing and in-situ RNA sequencing of fixed tissue specimens.

  Study EGAS00001003698

• Combined Tumor and Immune Signals From Genomes or Transcriptomes Predict Outcomes of Checkpoint Inhibition in Melanoma

  Cancer immunotherapy with checkpoint blockade (CPB) leads to improved outcomes in melanoma and other tumor types, but a majority of patients do not respond. High tumor mutation burden (TMB) and high levels of tumor-infiltrating T cells have been associated with response to immunotherapy, and integrative models using DNA and RNA have improved predictions of clinical benefit. However, identification of immune and tumor-intrinsic features in models using DNA or RNA alone have not been comprehensively explored in melanoma. In this study, we sequenced DNA and RNA of tumors from 67 melanoma patients receiving CPB, and aggregated this cohort with previously published data, yielding whole exome sequencing (WES) data for 189 patients and bulk RNA sequencing data for 178 patients. Using these datasets, we derived genomic and transcriptomic factors that predict overall survival (OS) and response to immunotherapy. Using whole exome DNA data alone, we calculated T cell burden (TCB) and B cell burden (BCB) based on rearranged TCR/Ig DNA sequences, and found that melanoma patients with high TMB and either high TCB or high BCB survived longer and had higher response rates, as compared to patients with low TMB and either low TCB or low BCB. Next, using bulk RNA-Seq data, differential expression analysis identified 83 genes which are associated with high or low OS. By combining pairs of immune-expressed genes with tumor-expressed genes, we identified three gene pairs which are associated with response and survival (Bonferroni P<0.05). All three gene pair models were validated in an independent cohort (n=180) (Bonferroni P<0.05). The best performing gene pair model included the lymphocyte-expressed MAP4K1 (Gene ID: 11184) and the transcription factor TBX3 (Gene ID: 6926) which is overexpressed in poorly differentiated melanomas. We concluded that RNA-based (MAP4K1 and TBX3) or DNA-based (TCB and TMB) models combining with immune and tumor measures improve predictions of outcome after checkpoint blockade in melanoma.

  Study phs002683