15059 results for "cancer studies using rna-seq"

in 15.73 milliseconds.

• snRNAseq of ATCWGS42

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

  Study EGAS50000001491

• NHLBI TOPMed: Genomic Summary Results for the Trans-Omics for Precision Medicine Program

  The NHLBI Trans-Omics for Precision Medicine (TOPMed) program aims to identify the genetic basis of variation in biomedical phenotypes, with emphasis on those related to heart, lung, blood and sleep disorders, as part of a broader Precision Medicine Initiative. The TOPMed program has provided whole genome sequencing (WGS) to over 80 different studies that had previously recruited participants and collected extensive phenotype data. Many TOPMed investigators affiliated with these studies have organized their activities into phenotype-focused Working Groups and have developed genotype-phenotype association projects. These analyses have resulted in valuable cross-study Genomic Summary Results (GSR) that include whole genome association test results of both common and rare variants. Most of the analyses include data from multiple studies, some of which are based on sensitive populations, precluding public sharing of GSR. This dbGaP accession provides a mechanism for sharing sensitive GSR, using the controlled-access mechanisms of dbGaP to provide protections for sensitive populations.

  Study phs001974

• Ex vivo RNA-seq in moderate COVID-19 monocytes

  This dataset was used to compare gene expression profiles of ex vivo isolated classical CD14+ monocytes from patients with moderate COVID-19 to those of healthy individuals. Blood samples were taken from patients with moderate COVID-19 admitted to hospitals in London (Hammersmith Hospital, Charing Cross Hospital, Saint Mary’s Hospital) 3-14 days after disease onset and 0-2 days after hospitalization and positive PCR, and before study treatment initiation. Moderate patients displayed mild or moderate COVID-19 pneumonia, defined as grade 3 or 4 WHO severity. Samples were collected from March 2020 to February 2021. Healthy donors were Imperial College staff with no prior diagnosis of or recent symptoms consistent with COVID-19, and where possible, were matched in age and sex distribution with COVID-19 patients. None of the participants of this study were COVID-19 vaccinated. Peripheral blood mononuclear cells (PBMCs) were isolated by Ficoll Hypaque (GE Healthcare) gradient centrifugation <4 hours after blood collection. CD14+ monocytes were isolated using a positive selection magnetic sorting kit (StemCell Technologies, UK) from total PBMC and stimulated with vehicle, UV-inactivated SARS-CoV-2 (CoV-2). RNA was isolated using the RNeasy Micro Plus Kit (QIAGEN) following the manufacturer’s guidelines. RNA-sequencing was performed by the Oxford Genomics Centre. PolyA-enriched strand- specific libraries were prepared using NEBNext Ultra II Directional RNA Library Prep Kits (Illumina). All samples were pooled together and 150bp PE reads were sequenced on a Novaseq 6000 system.

  Dataset EGAD00001009800

• Single cell RNAseq 7 days - Calprotectin in vitro effects on human early hematopoiesis

  To explore the effects of calprotectin (CAL) on early hematopoiesis, we incubated CD34+ cells from four healthy donors for 7 days in the presence of stem cell factor (SCF), FLT3-ligand and thrombopoietin (TPO) without and with CAL, interleukin-6 (IL6) and the IL6_CAL combination before collecting cells. We performed the same experiment with CD34+ cells collected from three patients with JAK2-V617F-mediated myelofibrosis (MF). A total of 135,545 cells from healthy donors and 111,725 cells from myelofibrosis patients were analyzed by single-cell RNA sequencing (scRNA-seq) using the 10X Chromium droplet-based platform. Single cell RNAseq 7 days - Normal and tumor samples 4 conditons : -Control - Calprotectin - IL-6 - Calprotectin+IL-6

  Study EGAS50000000455

• Bulk ATACseq 7days - Calprotectin in vitro effects on human early hematopoiesis

  To explore the effects of calprotectin (CAL) on early hematopoiesis, we incubated CD34+ cells from four healthy donors for 7 days in the presence of stem cell factor (SCF), FLT3-ligand and thrombopoietin (TPO) without and with CAL, interleukin-6 (IL6) and the IL6_CAL combination before collecting cells. We performed the same experiment with CD34+ cells collected from three patients with JAK2-V617F-mediated myelofibrosis (MF). A total of 135,545 cells from healthy donors and 111,725 cells from myelofibrosis patients were analyzed by single-cell RNA sequencing (scRNA-seq) using the 10X Chromium droplet-based platform. Bulk ATACseq 7days - Normal and tumor samples 4 conditons : -Control - Calprotectin - IL-6 - Calprotectin+IL-6

  Study EGAS50000000456

• 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

• Stem-like peripheral helper T cells seed their effector counterpart in rheumatoid arthritis

  The dynamics of helper T cells in the synovium of rheumatoid arthritis was investigated using scRNA-seq, scTCR-seq, and spatial transcriptome.

  Study JGAS000774

• 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

• MethCORR: DNA Methylation-based Characterization, Classification and Prognostication of Colorectal Cancer using Archival Formalin-fixed, Paraffin-embedded Tissue

  Transcriptional characterization and classification has potential to resolve the inter-tumor heterogeneity of colorectal cancer (CRC) and improve patient management. Yet, robust transcriptional profiling is difficult using formalin-fixed, paraffin-embedded (FFPE) samples, which complicates testing in clinical and archival material. We present MethCORR, an approach that allows uniform molecular characterization and classification of fresh-frozen and FFPE samples. MethCORR identifies genome-wide correlations between RNA expression and DNA methylation in fresh-frozen samples. This information is used to infer gene expression information in FFPE samples from their DNA methylation profiles. MethCORR was applied to methylation profiles from 877 fresh-frozen and FFPE samples and comparative analysis identified the same two major subtypes in four independent cohorts. Furthermore, subtype-specific prognostic biomarkers that better predicted relapse-free survival (HR=2.66, 95% CI [1.67-4.22], P<0.001) than TNM staging and MSI status were identified and validated using DNA methylation-specific PCR assays. The MethCORR approach is general, and may be similarly successful for other cancer types.

  Study EGAS00001004293

• 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

• Single-cell RNA-seq of human kidney tumors

  Fresh nephrectomy samples were collected from a total of 5 untreated ccRCC patients. Out of these 5 patients, 7 samples were obtained. Two samples consisted of fresh versus frozen single cells from the primary tumor site of one patient. Two other samples consisted of matched primary and distant thrombus sites (the vena cava) of a second patient. The three remaining samples came from the primary tumor sites of three distinct ccRCC patients. Single-cells were captured into 10x barcoded gel beads and RNA-sequencing library preparation was done using Chromium Single Cell 3' v2 chemistry. Sequencing was performed on a Illumina HiSeq 4000 sequencer.

  Dataset EGAD00001009306

• Bulk RNA-seq dataset of Single cell RNA sequencing reveals induced bifurcated differentiation after RUNX1::RUNX1T1 depletion in patient-derived leukemic blasts

  In this study, we demonstrate that primary AML cells harboring the chromosomal translocation t(8;21) are critically dependent on the corresponding fusion gene, RUNX1::RUNX1T1, to suppress differentiation and maintain stemness. Silencing RUNX1::RUNX1T1 expression using siRNA-loaded lipid nanoparticles induces significant changes in chromatin accessibility, redirecting the leukemia-associated transcriptional network towards a myeloid differentiation program. Single-cell analyses reveal that this transcriptional reprogramming is associated with the depletion of immature stem and progenitor-like cell populations, accompanied by an expansion of granulocytic and eosinophilic/mast cell-like populations with impaired self-renewal capacity.

  Dataset EGAD00001015508

• RNA-seq of BCR-ABL1 lymphoblastic leukemia

  This dataset is derived from whole-transcriptome sequencing (RNA-seq) of RNA from 57 BCR-ABL1 lymphoblastic leukemias (53 diagnostic, 4 relapse).

  Dataset EGAD00001010307

• RNA-seq colorectal adenomas NKI-AvL TGO series NGS-ProToCol

  The dataset "RNA-seq colorectal adenomas NKI-AvL TGO series NGS-ProToCol" includes 2 x 30 fastq files from paired-end total RNA sequencing on Illumina HiSeq2500 for 30 snap-frozen colorectal adenomas.

  Dataset EGAD00001004055

• RNA-seq colorectal carcinomas NKI-AvL TGO series NGS-ProToCol

  The dataset "RNA-seq colorectal carcinomas NKI-AvL TGO series NGS-ProToCol" includes 2 x 30 fastq files from paired-end total RNA sequencing on Illumina HiSeq2500 for 30 snap-frozen colorectal carcinomas.

  Dataset EGAD00001004056

• RNA-Seq data of VDH15 cells with and without deletion of NSUN3

  paired RNA-Seq data of VDH15 cells with and without deletion of NSUN3. The 11 samples were sequenced on HiSeq 4000 and prepared with SmarTer low input RNA and Chip NEBNext kit.

  Dataset EGAD00001006560

• RNA-seq data for Heterogeneity of IKZF1 genomic alterations and risk of relapse in childhood BALL

  RNA-seq data for 14 samples with B-cell acute lymphoblastic leukemia

  Dataset EGAD50000000151

• Single-cell RNA-seq of Bone marrow samples

  For two donors, we collected CD34 plus and CD34 minus hematopoietic cells for the single-cell RNA-seq analysis.

  Dataset EGAD50000000514

• RNA-seq data for de-methylation of FOXP3-TSDR study

  22 RNA-seq samples of ex-vivo (TN and Treg), cultured Treg, TET1 and untreated mCherry-MOCK

  Dataset EGAD00001006865

• RNA-seq data for HCC patients from Y90+Nivolumab trial

  This dataset includes RNA-seq fastq files of pre-treatment and on-treatment samples from 28 patients

  Dataset EGAD00001010132

• RNA-Seq Illumina GAII dataset

  RNA-Seq Illumina GAII dataset for the TraIT cell-line use case (added reverse and forward reads).

  Dataset EGAD00001001626

• IMpower133 processed RNA-seq data whole transcriptome

  This dataset contains log2(TPM + 1) for 271 tumor samples profiled by RNA-seq for the entire transcriptome.

  Dataset EGAD00001006927