11769 results for "cancer rna-seq"

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• 41 fibroblast RNAseq samples of pediatric patients with childhood epilepsy and developmental delay

  We used RNA sequencing of patient fibroblasts to find a genetic diagnosis in patients with exome-negative childhood epilepsy. RNA extracted from 41 individuals' cultured fibroblasts (passage 3-6) was collected and sequenced at a depth of 90-110 paired reads per sample.

  Study EGAS50000000792

• Primary_DIPG_expression_profiles

  In this study, we used RNA-sequencing gene expression profiling in order to characterize specific phenotypic traits in DIPG. Seventeen primary tumor samples stereotactically biopsied at diagnosis by neurosurgeons in the Necker-Enfants Malades hospital (Paris, France) and snap-frozen for RNA extraction and subsequent poly-A mRNA purification.

  Study EGAS00001007181

• SiMSen‑Seq

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

  Dataset EGAD50000001668

• Identification of High-Risk PHF19 Expressing Cells in Myeloma Single-Cell Multiomics

  The aim of this study is to identify novel subsets of cells that are associated with progression and response to treatment. In this project, we study the tumor fraction from 49 myeloma patients across stages of progression. Samples were collected from 10 smoldering multiple myeloma (SMM), 22 newly diagnosed multiple myeloma (NDMM), and 17 relapsed refractory multiple myeloma (RRMM) patients. These samples were then sorted using magnetic-activated cell sorting (MACS) for CD138+ cells that represent the tumor fraction of each sample. The CD138+ fraction then underwent whole genome sequencing (WGS), where possible, and single-cell multiomics. Single-cell multiomics can now measure scRNA-seq and scATAC-seq simultaneously, which we use in this project. Using single-cell multiomics, we will study subclonal changes in gene expression, chromatin accessibility, and identify novel regulatory relationships within myeloma tumors. Furthermore, we will apply state of the art single-cell and single-cell multiomic techniques to better identify the more high-risk components of myeloma.

  Study phs003220

• Cell-type eQTLs for single-cell Mendelian Randomisation

  The following study mapped eQTLs in the post-mortem human brain from snRNA-seq generated on 391 individuals. Following eQTL discovery and identification of state-specific eQTLs (dynamic associations interacting with disease), colocalisation and MR was performed integrating GWAS from 42 traits, for the identification of putatively causal genes with cell-type specific context. This study contains raw sequencing data and genotype for two datasets used in this work; - The MRC 60 dataset, which contains snRNA-seq generated on post-mortem brain from 60 control individuals (104 samples total, split across prefrontal cortex and hippocampus). Samples were pooled into 27 distinct pools, each of which was split across 4 lanes. Following sequencing and mapping using cellranger, demultiplexing was done using Demuxlet using the pool-specific genotype data (which contain sample IDs). - The Roche PD dataset, which is 10X multiome data generated on on 70 PD and 22 control individuals.

  Study EGAS50000000687

• Functional Variant rs9344 at 11q13.3 Regulates CCND1 Expression in Multiple Myeloma with t(11;14)

  Multiple myeloma (MM) is a plasma cell (PC) malignancy characterized by cytogenetic abnormalities, such as t(11;14)(q13;q32), resulting in CCND1 overexpression. The rs9344 G allele within CCND1 is the most significant susceptibility allele for t(11;14). We have found the G risk allele is enriched in both healthy individuals of African ancestry and African American individuals with MM. The overall aim of this study was to identify the mechanism behind why the G allele is enriched in t(11;14) MM. To reach this goal, we performed ATAC-seq from 100,000 CD138+ tumor cells from 26 patients with MM. In addition, we performed ChIP-seq using antibodies against H3K4me1, H3K27ac and H3K4me3 from 100,000 CD138+ tumor cells from 8 patients with MM. We used these data to evaluate whether the G allele of rs9344 is associated with elevated chromatin accessibility, H3K27ac and H3K4me3 in t(11;14) MM.

  Study phs003997

• Mapping the human hematopoietic stem and progenitor cell hierarchy through integrated single-cell proteomics and transcriptomics

  Single-cell transcriptomics (scRNA-seq) has enabled the characterization of cell state heterogeneity and recapitulation of differentiation trajectories. However, since proteins are the main functional entities in cells, the exclusive use of mRNA measurements comes at the risk of missing important biological information. Here we leverage recent technological advances in single-cell proteomics by Mass Spectrometry (scp-MS) to generate the first scp-MS dataset of an in vivo differentiation hierarchy encompassing over 2,500 human CD34+ hematopoietic stem and progenitor cells. Through integration with scRNA-seq, we identify proteins that are important for stem cell quiescence, which were not indicated by their mRNA transcripts, and demonstrate functional expression covariance during differentiation that is only detectable on protein level. Finally, we show that modeling translation dynamics can infer cell progression during differentiation and explain 45% more protein variation from mRNA than linear correlation. Our work serves as a framework for future single-cell multi-omics studies across biological systems.

  Study EGAS00001007930

• Whole-genome-sequencing, Whole-exome-sequencing and RNA-sequencing in Sporadic ALS

  To identify the genetic cause and modifiers of Sporadic ALS, we performed Whole-genome-sequencing, Whole-exome-sequencing and RNA-sequencing of Sporadic ALS patients.

  Study JGAS000393

• ICR_RNASeq_pHGG

  RNA sequencing of paediatric high grade gliomas and diffuse intrinsic pontine gliomas. RNA was sequenced from fresh frozen surgical material or from primary cells cultured under stem cell conditions. RNA was subjected to Illumina whole transcriptome paired end sequencing. Data is provided as paired-end FASTQ files

  Dataset EGAD00001004116

• Single-Cell Multi-Omic Analysis of the Vestibular Schwannoma Ecosystem Uncovers a Nerve Injury-Like State

  Vestibular schwannomas are benign tumors that can lead to significant morbidity, including hearing loss, facial nerve paralysis and obstructive hydrocephalus. The genomic landscape of vestibular schwannomas is relatively bland and the molecular pathophysiology of vestibular schwannomas is poorly understood. Therefore, we performed single cell RNA sequencing on 15 sporadic vestibular schwannomas, with paired single cell ATAC sequencing (n = 6) and whole exome sequencing (n = 12) to perform a detailed characterization of the vestibular schwannoma tumor microenvironment at the transcriptional and epigenetic level. We validated our results by analyzing bulk RNA sequencing data from 22 newly sequenced vestibular schwannomas and 173 previously sequenced bulk RNA sequencing data from 195 vestibular schwannomas. Data available in dbGaP include whole exome sequencing of 12 tumors and matched blood samples. Matching single cell RNA sequencing and single cell ATAC sequencing data is available via NCBI GEO.

  Study phs003318

• 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

• BMP4 and temozolomide synergize in the majority of patient derived glioblastoma cultures

  The poor prognosis of patients with glioblastoma is partly due to resistance to standard treatment, which combines chemoradiation using temozolomide (TMZ). The concept of cancer stem cells provided new insight into tumor resistance and management, and isolated Glioblastoma stem-like cells (GSCs) which contribute to this therapy resistance. Bone morphogenetic protein 4 (BMP4) is a differentiation factor that stimulates astroglial differentiation of such GSCs, thereby reducing their self-renewal. Exposing GSCs to BMP4 could therefore sensitize them to chemotherapy with TMZ, but previous studies with various treatment paradigms have produced contradictory results in this matter. Therefore, we re-defined the optimal treatment paradigm for the combination of TMZ and BMP4 and subsequently re-assessed the inter-tumoral variability in response to co-treatment with TMZ+BMP4 in vitro. First, the simultaneous treatment was found more effective than sequential therapy. Second, after application of our optimized treatment protocol, 70% of a total of 20 patient-derived glioblastoma cultures showed synergy when the treatments were combined. The synergistic effect was a result of increased cellular apoptosis and not of decreased proliferation. Comparative RNA-sequencing suggested that combination treatment results in decreased MAPK signaling. We conclude that addition of BMP4 to standard therapy with TMZ could enlarge the group of patients with good therapeutic response.

  Study EGAS00001007095

• Identification of Novel Therapeutic Targets for Calcific Aortic Valve Stenosis Using Integrative Genomics

  In order to identify novel therapeutic targets for calcific aortic valve stenosis, we have generated a large transcriptomic dataset from RNA sequencing of human aortic valve tissues from 500 individuals undergoing aortic valve replacement or heart transplant at the Institut universitaire de cardiologie et de pneumologie de Québec – Université Laval (QUEBEC-CAVS-RNA). This dataset represents a unique resource to understand the molecular mechanisms underlying aortic valve diseases.

  Study phs003541

• Complete sequencing dataset of study EGAS00001002795

  Dataset EGAD00001004572

• DAC IBMsnRNAseq

  This DAC manages the data access to our snRNA-seq and spatial transcriptomic data set on healthy and inflamed human skeletal muscle.

  Dac EGAC50000000220

• DLBCL cfDNA seq

  Sequencing dataset of 290 DLBCL and HGBL cfDNA samples of paired end 150bp sequencing runs.

  Dataset EGAD50000000602

• NABEC Exome-Seq

  Exome sequencing of North American Brain Expression Consortium (NABEC) subject.

  Dataset EGAD00001002886

• Centroblast Cohort

  miRNA-seq Cohort of 15 Benign Centroblasts

  Dataset EGAD00001001075

• Evaluation of protocols for rRNA depletion-based RNA sequencing of nanogram inputs of mammalian total RNA

  Study EGAS00001003849

• MuTHER adipose tissue small RNA expression

  MuTHER adipose tissue small RNA expression

  Dataset EGAD00001000105

• Genomic and Transcriptomic sequencing of neuroblastoma cell lines

  Genomic and Transcriptomic sequencing of neuroblastoma HSR and ecDNA cell lines. Data represents five 96-well plates that were processed with G&T sequencing, resulting in genomic and transcriptomic data from the same single cells. Dataset contains 95 bam files containing the DNA sequencing data and 95 bam files containing the RNA sequencing data of CHP212 cells, 380 bam files (190 DNA and 190 RNA) for TR14 cells, 188 bam files (94 DNA and 94 RNA) for Kelly cells and 192 bam files (96 DNA and 96 RNA) for IMR5/75 cells.

  Dataset EGAD50000000729

• 3D-GSC_expression_profiles

  In this study, we used RNA-sequencing gene expression profiling in order to characterize specific phenotypic traits in DIPG-derived glioma stem cell (GSC) models. Twenty-two primary GSC models derived from biopsies collected at diagnosis were cultured in an ECM-mimicking compound before for RNA extraction and subsequent rRNA-depletion and sequencing .

  Study EGAS00001007182

• small RNA-sequencing and RNA-sequencing of human brain tissue with temporal lobe epilepsy

  This data set contains the raw .fastq files from two RNA-sequencing experiments and two small RNA-sequencing experiments. Both control brain tissue and tissue from sufferers of mesial temporal lobe epilepsy were sequenced. Two different brain regions were sequenced; the cortex and the hippocampus. For more details please see: Mills, James D., et al. "Coding and non-coding transcriptome of mesial temporal lobe epilepsy: Critical role of small non-coding RNAs." Neurobiology of disease 134 (2020): 104612.

  Dataset EGAD00001005735

• RNA sequencing

  For RNA sequencing: All sample numbers starting with 6717 are tumor samples which has been sequenced using transcriptomics (see BAM files). It concerns biopsies of metastatic lesions from patients with BRAFV600 mutated melanoma, obtained before, during and after the study treatment (see samples metadata). RNA sequencing is performed using the Illumina Novaseq 6000 system.

  Dataset EGAD50000000383

• Paired RNA sequencing of Thymic epithelial tumors - Additional Dataset

  Paired RNA sequencing of additional samples of Thymic epithelial tumors. Uploaded are the paired fastq files, sequencers were Illumina HiSeq 2500, HiSeq 4000, NovaSeq 6000 and HiSeq X Ten. The kits used were Illumina Truseq RNA and Illumina Truseq stranded mRNA.

  Dataset EGAD50000000324