11925 results for "cancer rna-seq"

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• RNA-seq dataset for two NUP98-Rearranged Acute Myeloid Leukemia PDX samples

  This dataset includes RNA-seq of two patient-derived xenograft (PDX) samples with NUP98-Rearranged Acute Myeloid Leukemia. Bam files are provided for each sample.

  Dataset EGAD50000001564

• Single cell transcriptome analysis of breast invasive carcinoma

  We performed single-cell RNA-seq of breast invasive ductal carcinoma to identify the expressional heterogeneity in Luminal subtype and HER2-positive subtype.

  Study JGAS000309

• RNA-seq for 8 samples

  This dataset contains RNA-seq data from 8 acute leukemia cases (diagnosis or relapse) belonging to a newly identified subtype, termed FOXF1/FENDRR ALL. All the 8 samples are in bam file type.

  Dataset EGAD50000001789

• WES and RNA-seq raw sequence data for HIFI project

  WES sequence data from 15 samples, RNA-seq sequence data from 19 samples, all sequence data are raw pair-end sequence data in fastq format, sequenced by Illumina platform.

  Dataset EGAD00001004799

• DESIGN-VUMC RNA-seq

  RNA-Seq data of 55 HPV-negative HNSCC specimens from patients treated at the VU medical Centre, Amsterdam, The Netherlands. HNSCC biopsy samples obtained prior to treatment (chemo-radiotherapy) were used for polyA mRNA sequencing.

  Dataset EGAD00001005716

• DESIGN-MAASTRO RNA-seq

  RNA-Seq data of 17 HPV-negative HNSCC specimens from patients treated at the MAASTRO clinic, Maastricht, The Netherlands. HNSCC biopsy samples obtained prior to treatment (chemo-radiotherapy) were used for polyA mRNA sequencing.

  Dataset EGAD00001005717

• WGS and RNA-Seq data from a GBM patient PT-MB9777

  WGS and RNA-Seq data from a GBM patient PT-MB9777

  Dataset EGAD00001004253

• RNA-seq analysis of megakaryocytes and granulocytes in Quebec platelet disorder

  RNA-seq was performed on cultured megakaryocytes and peripheral-blood derived granulocytes from individuals with QPD and a unaffected controls. Each group consisted of n=3 biological replicates.

  Dataset EGAD00001006053

• RNA-Seq files for SJHGG study

  RNA-Seq files accompanying the paper titled "Somatic Histone H3 Mutations in Diffuse Intrinsic Pontine Gliomas and Non-Brainstem Paediatric Glioblastomas".

  Dataset EGAD00001003905

• WGS and RNA-Seq data from a GBM patient PT-SS3647

  WGS and RNA-Seq data from a GBM patient PT-SS3647

  Dataset EGAD00001008530

• WGS and RNA-Seq data from a GBM patient PT-SJ5453

  WGS and RNA-Seq data from a GBM patient PT-SJ5453

  Dataset EGAD00001008529

• RNA-Seq data for manuscript titled: CBL0137 impairs homologous recombination repair and sensitizes high-grade serous ovarian carcinoma to PARP inhibitors Sequencing

  RNA-Seq data for manuscript titled: CBL0137 impairs homologous recombination repair and sensitizes high-grade serous ovarian carcinoma to PARP inhibitors Sequencing

  Dataset EGAD00001009799

• Intellance-2: rRNA-minus RNA-seq

  Intellance-2: rRNA-minus RNA-seq

  Dataset EGAD00001007943

• NiCOL Study RNA-seq dataset

  15 samples sequenced in RNA-seq. This dataset contains their raw FASTQ data and the raw count table and the TPM count table.

  Dataset EGAD00001010912

• Human tumor single-cell RNA-seq

  We profiled 16 patient tumor samples by single-cell or single-nuclei RNA-seq using 10X Chromium 3'. It includes 4 low-grade gliomas and 12 ependymomas. The raw fastqs are provided.

  Dataset EGAD00001011315

• Meso RNA-seq data (SSA cell line study)

  RNA-seq data for mesothelioma cell lines after spliceostatin (SSA) or control (DMSO) treatment.

  Dataset EGAD00001001914

• Longitudinal RNA-seq in a twin cohort

  The dataset consists of 232 RNA-seq samples (whole blood) obtained from healthy female from the TwinsUK adult registry cohort. The samples were obtained at two time points separated on average by 22 months.

  Dataset EGAD00001002068

• Cam_121 RNA-Seq data

  This dataset contains RNA-Seq data from 204 primary melanomas and 177 regional lymph nodes. More details can be found in the manuscript: "Tumour gene expression signature in primary melanoma predicts long-term outcomes: A prospective multicentre study"

  Dataset EGAD00001006401

• Transcriptional and DNA binding profiling of CEBPE in REH acute lymphoblastic leukaemia cells using shRNA RNA-Seq and ChIP-Seq

  ChIP-Seq - CEBPE - REH. The ETV6/RUNX1 translocated acute lymphoblastic leukaemia cell line. REH was used to perform ChIP-Seq using a CEBPE antibody. Cells were fixed in 1% formaldehyde for 10mins, prior to preparation of chromatin using Active Motif Express ChIP-IT. 2ug of antibody (anti CEBPE Atlas Antibodies HPA002928)was added to 25ug of chromatin O/N at 4C with rotation. Duplicate reactions were pooled and purified. 10ng of ChIP’d and input DNA used for Illumina NGS preparation (NEBNext ChIP-Seq Library kit; New England Biolabs), CEBPE and Input DNA ChIP samples were sequenced on a MiSeq using 150bp Kit v3 paired end and a HiSeq 2500 using 2x101 version 4 paired end (Illumina) respectively. Reactions performed in duplicate. shCEBPE RNA-Seq - REH. REH cells were lentivirally transduced with a pTRIPZ shRNA vector for transcriptional profiling of CEBPE. Two controls (empty and non-targeting) and two CEBPE shRNAs (V3THS_150517(A13), V3THS_404312(G3) Dharmacon, GE) were transduced into REH cells. Cells were treated with 1ug/ml doxycyclin for 144hrs and total RNA purified using Qiagen RNeasy. Knock down of CEBPE was validated by qRT. RNA integrity >7.7 for all samples. Libraries were prepared using NEBNext Ultra II Directional RNA Library Prep Kit and sequenced on an Illuimna HiSeq 2500 using 2x101 version 4 paired end chemistry. 3 biological replicates of each samples were prepared.

  Dataset EGAD00001004084

• Reference Epigenomes and Regulatory Landscape of CLL

  Analysis of the reference epigenomes and regulatory landscape of CLL as a whole and its major clinico-biological subtypes (with mutated and unmutated IGHV) in the light of the normal B-cell differentiation. We have extensively characterized the reference epigenomes of seven primary chronic lymphocytic leukemia samples (CLLs) with mutated (n=5) and unmutated IGHV (n=2) as well as several mature B-cell subpopulations (naive B cells from blood and tonsil, germinal center B cells, memory B cells and plasma cells from tonsil) using genome-wide maps of six histone marks (H3K4me3, H3K4me1, H3K27ac, H3K36me3, H3K9me3 and H3K27me3), DNA accessibility (ATAC-seq), DNA methylation (whole-genome bisulfite sequencing) and gene expression (RNA-seq). Furthermore, we have mapped the regulatory chromatin landscape of 100 additional CLL cases using chIP-seq of H3K27ac and ATAC-seq and linked these data to additional layers of information (whole-genome and/or whole-exome sequencing (WGS/WES), RNA-seq and DNA methylation microarrays) studied in the context of the International Cancer Genome Consortium (ICGC).

  Dataset EGAD00001004046

• Longitudinal RNA-seq datasets from patients after abdominal surgery

  This dataset consists of RNA-seq data of 126 whole-blood samples derived from patients after abdominal surgery. Total-RNA collected preoperatively and at 3-time points postoperatively (2-6, 24 and 48hrs) were analysed using RNA-sequencing. RNA was collected in PAXGene (Qiagen) tubes and extracted using the PAXGene RNA extraction kit, with a DNase step to remove contaminating DNA. Globin and ribosomal RNA were removed via a Ribo-zero kit (Illumina) and library preparation was carried out using the TruSeq Stranded Total RNA Library Prep Kit (Illumina). Next generation sequencing was performed on the NovaSeq sequencing platform (Illumina) at the Wellcome Centre for Human Genetics (WCHG) in Oxford.

  Dataset EGAD00001011102

• Evolution of Core Archetypal Phenotypes in High-Grade Serous Ovarian Cancer (HGSOC)

  The evolution of resistance in high-grade serous ovarian cancer (HGSOC) cells in response to chemotherapy is only partially understood. To uncover phenotypic changes associated with chemotherapy resistance, we performed single-cell RNA-sequencing (scRNA-seq) or whole-genome sequencing of 23 total patients, with longitudinal samples collected from 9, treatment-naïve samples from 8 patients, and post-treatment samples from 6 patients. Our study revealed that the HGSOC transcriptome could be described using three core archetypal phenotypes, defined as oncogenic tasks that describe majority of the transcriptional data. We implemented a multi-task learning approach to identify the biological tasks of each archetype and identified metabolism and proliferation, cellular defense response, and DNA repair signaling. The “metabolism and proliferation” archetype evolved during treatment and was enriched in cancer cells from patients that received multiple-lines of treatment and had elevated tumor burden indicated by CA-125 levels. The emergence of archetypes was not consistently linked to specific whole-genome driver mutations. However, archetypes were closely associated with sub-clonal clusters at the single-cell level, indicating that cancer cell sub-populations specialize in particular biological tasks. Our study reveals a defining principle of ovarian tumor evolution using temporal scRNA-seq profiles, identifies the key phenotypic features across patients and links metabolic shifts with a response to chemotherapy.

  Study phs002294

• Aligned FOS RNA sequencing data

  Total RNA-sequencing Paired-End was performed by GenomeScan (Leiden, the Netherlands) on the NovaSeq6000 platform for full-length FOS (FOS FL), truncated FOS (FOSΔ), a FOS isoform with an L376N mutation (FOS mut), untransduced fMSC (unt) and fMSC with empty pLV (pLV) at week 0, 1, 2, and 3 in triplicate (total of 60 samples). Raw RNA-seq data were processed by the RNA-seq BioWDL pipeline pipeline version 5.0.0 developed by the SASC team at LUMC, LUMC, Leiden, the Netherlands).

  Dataset EGAD50000001839

• Human melanoma samples with and without resistance to BRAF inhibitor therapy

  Human melanoma samples were collected pre, on, and progression on BRAF inhibitor therapy. RNA was extracted and run on RNA-seq. This has provided insights into different categories of BRAF inhibitor resistance mechanisms.

  Study EGAS00001000992

• RNA-seq data from primary AML samples with t(3;8)

  RNA-seq was generated to investigate differences in gene expression between t(3;8) AML and other primary AMLs. Briefly, sample libraries were prepared using 500 ng of input RNA according to the KAPA RNA HyperPrep Kit with RiboErase (HMR) (Roche) using Unique Dual Index adapters (Integrated DNA Technologies, Inc.). Amplified sample libraries were paired-end sequenced (2x100 bp) on the Novaseq 6000 platform (Illumina

  Dataset EGAD00001006819

• RNA-seq data from Follicular Lymphoma samples

  Dataset included RNA-seq data (Two Fastq files per sample as paired end sequencing was performed) from ribosomal-depleted total RNA in 28 Follicular Lymphoma (FL) criopreserved samples to analyze long non-coding RNA and coding transcript expression profiles. Sample metadata is referred to histological groups of FL tumors (FL1-3A versus FL3B/DLBCL) either in tumor purified cell samples (N=12) as in unpurified tumor samples including normal cells of the lymph node microenvironment (N=16).

  Dataset EGAD00001004109

• RNA-Seq

  RNA Sequencing

  Dataset EGAD00001001121

• RNA-seq analysis of midbrain dopaminergic neurons following ZFHX4 knockdown.

  We performed RNA-seq analysis on midbrain dopaminergic neurons derived from induced pluripotent stem cells following lentiviral-mediated knockdown of the transcription factor ZFHX4. Transcriptomic analysis enabled the identification of potential ZFHX4 target genes. Enrichment analysis of the differentially expressed genes was conducted to assess the biological pathways regulated by ZFHX4.

  Study EGAS50000001111

• RNA-seq analysis of BMP-stimulated glioma initiating cells

  Bone morphogenetic protein (BMP) signaling has been shown to suppress progression of glioblastoma by promoting astrocytic differentiation; however, roles of BMP signaling in cell proliferation and apoptosis of glioblastoma cells remains to be elucidated. We here performed RNA-seq analysis of glioma initiating cells to identify transcriptional target(s) of BMP.

  Study JGAS000077

• 10x Genomics VDJ single cell sequencing and 10x Genomics sc RNA-Seq (5 individuals/17 VDJ runs,19 scRNA runs))

  single cell RNAseq and TCR sequencing data of 5 individuals. 10x Genomics VDJ single cell sequencing (17 runs) and 10x Genomics sc RNA-Seq (19 runs). The VDJ sequencing was done on a Nextseq 550 using the Chromium Single Cell VDJ Reagent Kit. The RNA-Seq was done either on HiSeq4000 or NovaSeq 6000 using the Chromium Single Cell 5 Reagent Kit.

  Dataset EGAD00001009986

• Paired RNA-Seq for Sarcoma tumors

  Paired RNA-Seq of 199 samples of Sarcoma tumors. The sequencing was done mostly on HiSeq 4000 with Illumina TruSeq Stranded mRNA, ist was also done on NovaSeq 6000 using the same kit. Very few samples were sequenced on HiSeq X Ten with Illumina TruSeq RNA or Illumina TruSeq Stranded mRNA.

  Dataset EGAD00001010256

• Transcriptional and DNA binding profiling of CEBPE in REH acute lymphoblastic leukaemia cells using shRNA RNA-Seq and ChIP-Seq

  Dac EGAC00001000891

• Tumorigenic role of Musashi-2 in aggressive mantle cell lymphoma

  SOX11 is overexpressed in the highly aggressive conventional mantle cell lymphoma (MCL) but rarely in the indolent non-nodal MCL subtype. We performed RNA-seq of SOX11+ and SOX11- MCLs to search for SOX11-regulated genes that contributed to MCL clinical evolution, identifying Musashi-2 (MSI2) stem cell-related gene. By performing RNA-seq upon MSI2 knockdown or inhibition in MCL, we identified MSI2 as a potential target to inhibit drug resistance in aggressive MCLs.

  Study EGAS00001006613

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

  Next generation RNA-Sequencing (RNA-seq) is a flexible approach that can be applied to e.g. global quantification of transcript expression, the characterization of RNA structure such as splicing patterns and profiling of expressed mutations. Many RNA-seq protocols require up to microgram levels of total RNA input amounts to generate high quality data, and thus remain impractical for the limited starting material amounts typically obtained from rare cell populations, such as those from early developmental stages or from laser micro-dissected clinical samples. Here, we present an assessment of the contemporary ribosomal RNA depletion-based protocols, and identify those that are suitable for inputs as low as 1-10 ng of intact total RNA and 100-500 ng of partially degraded RNA from formalin-fixed paraffin-embedded tissues.

  Dataset EGAD00001005316

• IBC RNA-seq

  RNA sequencing of IBC patients

  Dataset EGAD00001011649

• Colorectal Microenvironment Spatial Mapping

  In colorectal cancer (CRC), interactions between tumor and immune cells within the tumor microenvironment are critical drivers of tumorigenesis, immune evasion, prognosis, and therapeutic response. Therefore, a deeper understanding of the spatial organization of cancer and immune cells within the CRC microenvironment is urgently needed. In this study, we aimed to characterize distinct cell populations and patterns of spatial gene expression associated with CRC tumorigenesis and immune infiltration. Spatial transcriptomics (ST) was performed on CRC and adjacent normal tissues to investigate the patterns of gene expression. Integrative ST data and publicly available single-cell RNA sequencing (scRNA-seq) data analysis tools were used for data integration, dimension reduction, clustering, and differential expression analysis. This study identified novel immunosuppressive cell populations and immune regulatory factors in CRC. Further functional validation of these findings will be essential to assess their potential as therapeutic targets.

  Study EGAS00001008254

• A Unifying Paradigm for Transcriptional Heterogeneity and Squamous Features in Pancreatic Ductal Adenocarcinoma

  Pancreatic cancer expression profiles largely reflect a classical or basal-like phenotype. The extent to which these profiles vary within a patient is unknown. We integrated evolutionary analysis and expression profiling in multiregion sampled metastatic pancreatic cancers, finding that squamous features are the histologic correlate of an RNA-seq defined basal-like subtype. In patients with coexisting basal/squamous and classical/glandular morphology, phylogenetic studies revealed that squamous morphology represented a subclonal population in an otherwise classical/glandular tumor. Cancers with squamous features were significantly more likely to have clonal mutations in chromatin modifiers, intercellular heterogeneity for MYC amplification, and entosis. These data provide a unifying paradigm for integrating basal-type expression profiles, squamous histology, and somatic mutations in chromatin modifier genes in the context of clonal evolution of pancreatic cancer.  

  Study EGAS00001003974

• Single cell Human Kidney ADPKD

  This ADPKD project has 3 different experiments, 7 different single cell RNA-seq data, 5 different single nuclei RNA-seq data and 6 different bulk ATAC-seq data objects.

  Dataset EGAD00001009328

• ProstOmics - Spatial Transcriptomics

  Spatial transcriptomics data (ST) from 32 human prostate tissue samples originating from 8 prostate cancer patients (5 patients with post-surgery relapse). The ST data was acquired using the Visium Spatial Gene Expression kit which resulted in over 20 000 spatially defined spots for the 32 tissue samples. The raw transcriptomics data is RNA-seq. The individual samples have information on patient origin and sample type (cancer, cancer-adjacent field-effect normal or normal sample far from cancer). Each ST spot has metadata such as sample origin, histology class (stroma, normal epithelium, cancer of various grading etc), number of cells and estimated cell type fractions. Patient metadata include information of age at surgery, time (months) until reported relapse, total follow-up time, pre-surgery PSA, post-surgery T-stage and metastasis status.

  Dataset EGAD50000000603

• Breast Cancer - immune clusters - RNA-seq

  In this study we use expression data from breast cancer tumors to define immune clusters in breast cancer. Immune clusters have gradual levels of immune infiltration. In the intermediate immune infiltration cluster, we found a worse prognosis which is independent of known clinicopathological features. We also found the immune clusters associated with treatment response. Further using gene expression data and deconvolution algorithms to dissect the immune contexture of the clusters.

  Study EGAS00001003631

• Bulk RNA-seq data of isogenic wild-type RPE1

  Deposited here are time series (6, 24 and 48hrs) bulk RNA-seq data generated from isogenic wild-type (WT) RPE1 untreated or treated with Brequinar (and other dNTP-pool disruptor compounds)

  Dataset EGAD50000001544

• Epigentic sequence data of monocytes and macrophages

  Data for paper: Epigenetic dynamics of monocyte to macrophage differentiation with Chip Seq, NOMe, mRNA, total RNA, noncoding RNA, whole genome bisulfite seq,

  Dataset EGAD00001002201

• RNA-Seq samples from the BELOB clinical trial study to find transcriptome associations with response to Bevacizumab and CCNU in glioblastoma patients

  RNA-Seq samples from the BELOB clinical trial study to find transcriptome associations with response to Bevacizumab and CCNU in glioblastoma patients

  Dataset EGAD00001006329

• Uveal melanoma whole genome sequencing, SNP arrays and RNA-seq

  We conducted whole genome sequencing and DNA SNP array of 12 uveal melanoma genomes and their matched DNA from blood. We also conducted RNA-seq of the 12 tumour samples.

  Dataset EGAD00001000372

• G-SAM: Transcriptional Evolution of Glioblastomas Treated With Standard of Care

  Collection of mostly matching primary and recurrent glioblastoma RNA-seq sample pairs, also matching with an earlier DNA sequencing study

  Study EGAS00001005436

• WGS and RNA-Seq data from a GBM patient PT-PV2594

  WGS and RNA-Seq data from a GBM patient PT-PV2594

  Dataset EGAD00001008526

• RNA-Seq data on multiple myeloma CD138positive bone marrow plasma cells

  RNA-Seq data on multiple myeloma CD138positive bone marrow plasma cells, 11 samples, sequenced on HiSeq 4000 and HiSeq X-Ten, using mostly the TruSeq stranded mRNA Kit.

  Dataset EGAD00001008619

• RNA-Seq data for manuscript titled: A sporadic Alzheimers blood-brain barrier model for developing ultrasound-mediated delivery of Aducanumab and anti-Tau antibodies

  RNA-Seq data for manuscript titled: A sporadic Alzheimers blood-brain barrier model for developing ultrasound-mediated delivery of Aducanumab and anti-Tau antibodies

  Dataset EGAD00001008670

• RNA-seq data of patients with glioblastoma IDH-wt (CNS WHO grade 4) with matched primary and relapse samples.

  Between January 1st, 2016, and December 31th, 2021, patients with glioblastoma IDH-wt (CNS WHO grade 4) were included. RNA-seq was performed in a subset of patients.

  Dataset EGAD00001015683

• Dataset for RNA and Exome sequencing of Glioblastoma samples

  This dataset contains RNA Seq, 10x scRNA Seq and Exome sequencing of glioblastoma samples. Sequencing was performed on a Illumina NovaSeq 6000 and Illumina HiSeq 4000. The sequencing was always paired.

  Dataset EGAD00001012235