11810 results for "cancer rna-seq"

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• DAC for study "Single-nucleus brain transcriptomics reveals microglia dysfunction in Multiple System Atrophy"

  Dataset containing snRNA-seq samples from MSA or PD patients, and healthy controls. We aimed at identifying molecular processes at the single cell level that could identify common and/or disease-specific differences between healthy controls and patient groups. Frozen tissue samples from healthy controls, and multiple system atrophy or Parkinson's disease patients were excised and single nuclei were isolated following the 10x Genomics Chromium workflow.

  Dac EGAC50000000809

• ATAC-Seq of GM adipose tissue samples

  This dataset contains 28 fastq files (11 files for subcutaneous tissue and 17 files for visceral tissue) from nine individuals. All samples were initially sequenced by SEx50 mode (16 files) and some of them were also sequenced by PEx100 mode (12 files). Sequencing was done on the Illumina HiSeq2000 platform.

  Dataset EGAD00001010254

• METABRIC miRNA landscape

  MicroRNAs (miRNAs) are key players in cancer pathogenesis1. They display differential expression across breast cancer subtypes, and play oncogenic and tumor-suppressive roles2-6. A systematic study of the global miRNA landscape in breast cancer and the factors shaping it has not been undertaken. Here we report the results of profiling miRNA expression in 1,302 breast tumors with detailed clinical annotation and long-term follow-up, and for which matching genomic and mRNA expression data were available7. This provides a comprehensive view of the quantity, distribution and variation of the miRNA population and dissects how much genomic, transcriptional and post-transcriptional events contribute to miRNA expression architecture. The key clinical parameters and cellular pathways related to the miRNA landscape are identified, exemplified by context-dependent interaction with cell adhesion and Wnt signaling. Strikingly, in breast cancer miRNAs appear to act as modulators of mRNA-mRNA interactions rather than molecular switches. We demonstrate an important modulatory role for miRNAs in the biology of breast tumors devoid of somatic copy number aberrations, a common subtype where immune response is prominent. Remarkably, prognostic miRNA signatures derived in this subtype are consistently prognostic across several other subtypes and validate in external cohorts. These findings represent a new framework to study the biology of miRNA in human cancer.

  Study EGAS00000000122

• Copy number profiling of putative cancer stem from pleural effusion aspirates from breast cancer patients

  A common symptom during late stage breast cancer disease is pleural effusion, which is related to poor prognosis. In pleural effusions malignant cells can be detected, which indicates a metastatic spread from the primary tumor site. Beside the usefulness for investigation of the metastatic process, it has been a source to isolate cells with putative cancer stem cell (CSC) properties. For this study, pleural effusion aspirate from 25 metastatic breast cancer patients were processed to establish in vitro culture. Patient-derived aspirates were cultured under sphere forming conditions and isolated primary cultures were sorted for cancer stem cell populations ALDH1+ and CD44+CD24-/low and sphere forming efficiency of CSC and non-CSC subpopulation was determined. Unsorted cells had a higher potential to form spheres compared to CSC subpopulations. Subsequently, DNA was isolated from pleural effusions before and after cell sorting, to compare their copy number profiles generated by low-coverage whole genome sequencing to DNA from FFPE primary tumors or bone metastasis. Unbalanced profiles could be detected in four pleural samples before sorting, in two ALDH1+ sorted samples, in one CD44+CD24-/low and in all control samples. Additionally, spheroid culture from one pleural sample could be passaged on and was characterized. Therefore, pleural effusions are an appropriate media for enrichment of putative CSC. However, low-coverage sequencing is difficult due to low quantities of abnormal cells compared to normal cells.

  Study EGAS00001002343

• scRNAseq data of CAP

  Fastq files from scRNAseq data of cancer associated pericytes-like from 3 patients. CAP were isolated from a total of 3 primary BC (surgical residues prior to any treatment) by using BDFACS ARIA III sorter (BD Biosciences). BC were collected directly from the operating room after surgical specimen macroscopic examination and selection of areas of interest by a pathologist. Samples were cut into small pieces (around 1 mm3) and digested in CO2-independent medium (Gibco #18045-054) supplemented with 150 μg/mL liberase (Roche #05401020001) and Dnase I (Roche #11284932001) for 40 min at 37°C with shaking (180 rpm). After digestion, cells were processed and stained as described above (#Flow Cytometry analysis of BC samples). CAP fibroblasts were then gated on the Live/Dead negative fraction and defined as EPCAM- CD45- CD31- CD235a- FAPMed CD29High. CAP scRNA-seq: Upon isolation, CAP cells were directly collected into RNase-free tubes (Thermo Fisher Scientific, #AM12450) precoated with DMEM (GE Life Sciences, #SH30243.01) supplemented with 10% FBS (Biosera, #1003/500). Single-cell capture, lysis, and cDNA library construction were performed using Chromium system from 10X Genomics, with the following kits: Chromium Single Cell 3′ Library & Gel Bead Kit v2 kit (10X Genomics, #120237) and Chromium Single Cell A Chip Kits (10X Genomics, #1000009). Generation of gel beads in Emulsion (GEM), barcoding, post GEM-reverse transcription cleanup and cDNA amplification were performed according to the manufacturer’s instructions. Cells were loaded accordingly on the Chromium Single cell A chips, and 12 cycles were performed for cDNA amplification. cDNA quality and quantity were checked on Agilent 2100 Bioanalyzer using Agilent High Sensitivity DNA Kit (Agilent, #5067-4626) and library construction followed according to 10X Genomics protocol. Libraries were next run on the Illumina HiSeq (for patients P1) and NovaSeq (for patients P2–3) with a depth of sequencing of 50,000 reads per cell.

  Dataset EGAD50000000321

• Scalable ultra-high-throughput multiplexed single-cell chromatin and RNA profiling reveals gene regulatory dynamics during stimulation time courses and CRISPR perturbation screens

  Data for 1) hiPSC-derived macrophages across a polarization time course from the naive M0-state to the M1- and M2-states, 2) Primary T-cells differentiated to helper subtypes, and 3) spontaneous differentiation of hiPSCs upon perturbation of GATA2, NR4A2 or SOX17

  Dac EGAC50000000485

• FLT3 is genetically essential for ITD-mutated leukemic stem cells but dispensable for human HSCs

  bulk RNA sequencing of AML patients It contains 18 samples from primary AML patients. Half of the samples are control samples and half of the samples are FLT3-ITD knock-out (edited for the FLT3-ITD mutation). It is using Illumina high-throughput technology

  Dataset EGAD50000000636

• Waldenström Macroglobulinemia Single-Cell Data Access Committee

  This Data Access Committee (DAC) is responsible for reviewing and approving access requests for controlled-access human single-cell sequencing data, including single-cell RNA sequencing and immune receptor profiling, generated from patients with Waldenström macroglobulinemia. The DAC ensures that all data access requests comply with the informed consent provided by study participants and are consistent with applicable ethical and regulatory requirements.

  Dac EGAC50000000863

• Single cell study of infant leukemias

  We have performed single cell RNA-sequencing for infant and childhood B-cell acute lymphoblastic leukemias as well as infant acute myeloid leukemias at diagnosis. The sequencing was performed with 10X Chromium single cell 3’ and 5’ chemistry.

  Dataset EGAD00001007853

• RNA-sequencing data from vitamin C experiment

  Fasq-files from 3 unaffected TET2 mutation carriers, 2 mutation carriers diagnosed with lymphoma and 3 family members without TET2 mutation. Time series data collected from 0, 6 and 12 months after daily dose of 1g vitamin C.

  Dataset EGAD00001010009