11754 results for "cancer rna-seq"

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• The paired FF/FFPE colon set, RNA-Seq

  Dataset EGAD00001000831

• RNA-seq of CML074 Tumor tissue; Timpepoint 1

  Dataset EGAD00001001259

• RNA-seq of CML074 Tumor tissue; Timpepoint 2

  Dataset EGAD00001001260

• Molecular_risk_stratification_in_patients_with_T1_colorectal_cancer_WES

  The introduction of bowel cancer screening has led to a significant increase in the proportion of patients being diagnosed with asymptomatic, early-stage colorectal cancer (CRC). Although the majority of these patients are successfully treated with surgery alone, a small proportion of patients have ‘born-to-be-bad’ aggressive lesions with early dissemination leading to distant metastases. Current standard of care histological assessment is unable to distinguish between these aggressive versus non-aggressive early lesions which is essential to provide appropriate clinical management decisions. This study aims to carry out molecular and histological profiling of approximately 300 T1 CRCs in order to develop a molecular stratifier based on the risk of relapse in early-invasive CRC. This novel T1 cohort will represent the world’s largest molecularly characterised T1 cohort of samples, with digital pathology assessment alongside whole exome sequencing, copy number variation analysis and 3’ RNA-seq. This data will be used to generate a robust panel of molecular and/or histological markers applicable to formalin-fixed paraffin embedded (FFPE) archival tissue which discriminates between T1 lesions based on risk of relapse, which will ultimately be used to inform clinical management of CRC at the earliest stages of the disease.

  Study EGAS00001005734

• bulkRNA seq from fibroblasts stimmulated with bead or CD8 T cell supernatant

  CD8 T cells (5 Samples treated, 5 samples control) form the same donors (5 donors, paired design) was subject to RNA-seq (Illumina stranded mRNA) processing. Single end fastq-files are supplied.

  Dataset EGAD00001010004

• Sequence data of 28 Samples (19 chronic lymphocytic leukemia, 9 control)

  Sequence data of 28 Samples (19 chronic lymphocytic leukemia, 9 control) Including RNA-Seq and ChIP-Seq of following histone modifications: H3, H3K4me1, H3K4me3, H3K9ac, H3K9me3, H3K27ac, H3K27me3, H3K36me3 Project see: http://www.cancerepisys.org/

  Dataset EGAD00001003421

• Impact of Glycolysis Inhibition on the Epigenome of Synovial Fluid T Cells in Juvenile Idiopathic Arthritis

  Juvenile Idiopathic Arthritis (JIA) encompasses a group of childhood-onset autoimmune conditions characterized by joint inflammation and mononuclear cell infiltration, especially of activated CD4+ memory/effector T (Tmem/Teff) cells in synovial fluid (SF). JIA CD4+ T cells exhibit a distinct inflammation-associated epigenomic profile, though the underlying molecular mechanisms remain unclear. This study investigates the role of glycolysis in shaping the epigenomic landscape of JIA SF CD4+ T cells, with a focus on H3K27ac histone modifications. Using an ex vivo model of antigen stimulation, CD4+ T cells were isolated from peripheral blood (PB) of healthy controls (HC) and synovial fluid from JIA patients. Cells were activated in vitro with anti-CD3/CD28 for 24 hours, and changes in H3K27ac were assessed by chromatin immunoprecipitation followed by sequencing (ChIP-seq). To explore the specific role of glycolysis, cells were also treated with 2-deoxyglucose (2DG), an inhibitor of glucose-6-phosphate production. This inhibition impacted both H3K27ac acetylation patterns and gene expression associated with the activated epigenomic regions. Additionally, HC CD4+ T cells were activated in vitro in the presence of 30% SF or 30% plasma from JIA patients. RNA sequencing (RNA-seq) was performed to examine SF-induced transcriptional changes, providing insight into the metabolic dysregulation and epigenomic alterations observed in JIA SF CD4+ T cells. This dataset includes ChIP-seq and RNA-seq data that collectively advance our understanding of how glycolysis and the SF environment contribute to the epigenetic and transcriptional regulation in JIA CD4+ T cells.

  Study EGAS50000000808

• RNA-seq bulk

  This dataset gather all RNA-sequencing data in MM.1S cell line in control and Dex condition; both in 3 biological replicates

  Dataset EGAD00001011137

• RNA sequencing of osteoarthritis patients in subchondral bone

  This dataset contains RNA-seq (Illumina Hiseq 4000) from macroscopically preserved and lesioned OA subchondral bone of patients that underwent joint replacement surgery due to OA (N=48).

  Dataset EGAD00001006197

• RNA sequencing of PTCL-NOS

  This dataset contains raw .fastq files of a paired-end RNA-seq experiment on 15 PTCL-NOS samples. Samples were prepared with Truseq stranded mRNA library kit.

  Dataset EGAD00001006925

• RNA_Seq_in_Patients_with_Primordial_Dwarfism

  Transcriptome studies in patients with rare genetic diseases can potentially aid in theinterpretation of likely causal genetic variation through identification of altered transcriptabundance and/or structure. RNA-Seq is the most sensitive assay for both investigatingtranscript structure and abundanceThe primary aim of this pilot project is to investigate to what degree integrating exome-Seqand RNA-Seq data on the same individual can accelerate the identification of causal allelesfor rare genetic diseases. There are two main strands to this: (i) identifying which variantsdiscovered in exome-seq appear to be having a functional impact on transcripts, and (ii)identifying transcript outliers, especially among known causal genes, that may not necessarilyhave a causal variant identified from exome sequencing. The latter may identify the presenceof causal variants that lie far from coding regions (e.g. the formation of cryptic splice sitesdeep within introns, or loss of long range regulatory elements), which can be confirmed withfurther targeted genetic assays. Just over 50% of all disease-causing variants recorded in theHuman Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g.nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs).This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients withprimordial dwarfism syndromes, for 10 of these samples we have previously generate exomedata as part of our collaboration with the group of Prof Andrew Jackson. The two remainingsamples are positive controls where the causal mutation is known, and is known to affecttranscript structure and/or abundance.Primordial dwarfism is a prime candidate for these RNA-seq studies because all knowncausal mutations to date have key roles in DNA replication and thus, unsurprisingly, theproducts of the causal genes are typically ubiquitously expressed.Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) persample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001000283

• Circulating immune cell landscape in colorectal cancer patients

  To understand the circulating immune cells in colorectal cancer patients, we performed single-cell RNA sequencing for 14 PBMC samples from 14 colorectal cancer patients.

  Study EGAS50000000590

• ChIP-seq ERa in primary breast cancer tissues

  ChIP-seq has been perfomed on 5 tumor fresh-frozen primary breast cancer tissues from female patients. Immunoprecipitation has been performed for ERa (SC-543, Santa Cruz). Raw single-end fastq data have been aligned using bwa-mem using Hg19 genome assebly as reference. Unfiltered aligment bam files are provided.

  Dataset EGAD50000000014

• ERa ChIP-seq in breast healthy, primary cancer and metastatic tissues

  ChIP-seq has been perfomed on fresh-frozen tissue derived from healthy breast (HB), primary breast cancer (PB), BCa-derived liver metastasis (LM). Immunoprecipitation has been performed for ERa (sc-542, SantaCruz). Raw paired-end fastq.gz files are provided for both immunoprecipitated DNA and input samples.

  Dataset EGAD50000000642

• CITE-seq for peripheral blood samples of 5 breast cancer patients

  We have 5 breast cancer patients who received VEN therapy. We collected their peripheral blood samples before and after long-term Venetoclax treatment. We apply CITE-seq protocol to these samples. This collection contains the all CITE-seq data for patients.

  Dataset EGAD00001008751

• 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

• RNA-seq of hepatocellular carcinoma xenografts established from needle biopsies

  RNA-sequencing of human hepatocellular carcinoma biopsies (n=14), 44 HCC xenografts derived from 11 HCC biopsies and 3 lymphoma xenografts derived from 3 HCC biopsies. RNA-sequencing was performed using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Gold (lllumina). SR126 sequencing was performed on an Illumina HiSeq 2500 using v4 SBS chemistry according to the manufacturer’s guidelines.

  Dataset EGAD00001004541

• Organoid Profiling Identifies Common Responders to Chemotherapy in Pancreatic Cancer

  We generated a collection of patient-derived pancreatic normal and cancer organoids. We performed whole genome sequencing, targeted exome sequencing, and RNA sequencing on organoids as well as matched tumor and normal tissue if available. This dataset is a valuable resource for pancreas cancer researchers, and those looking to compare primary tissue to organoid culture. In our linked publication, we show that pancreatic cancer organoids recapitulate the mutational spectrum of pancreatic cancer. Furthermore, RNA sequencing of organoids demonstrates the presence of both transcriptional subtypes of pancreas cancer.

  Study phs001611

• DSRCT RNA genomic sequencing

  Purpose: To further understand the molecular pathogenesis of desmoplastic small round cell tumor (DSRCT), a rare but often fatal malignancy occurring primarily in young males, we used next-generation RNA sequencing to investigate the gene expression profiles intrinsic to this disease.Experimental Design: RNA from DSRCT tumor samples were obtained from the Cooperative Human Tissue Network biorepository. RNA sequencing was completed using the Illumina HiSeq 2000 system. Presence of the EWSR1-WT1 fusion was verified using both RNA-sequencing and PCR. Validation studies, including WT1 ChIP-seq, RNA sequencing, and EWS-WT1 knockdown experiments, were performed on an established DSRCT cell line, JN-DSRCT-1. Protein expression of clinically relevant genes determined by RNA sequencing was confirmed using immunohistochemistry. A panel of immune signature genes was also evaluated to identify possible immune therapeutic targets. Results: We analyzed the RNA from 14 tumor samples, of which two were confirmed negative for the diagnostic EWSR1-WT1 translocation. Principal component analysis of the sequencing data indicated that fusion-negative and fusion-positive tumors are transcriptionally distinct entities. Overlapping the significant ChIP-seq peaks with genes found to be highly expressed in the RNA sequencing data revealed that IGF2 and FGFR4 were both highly expressed, and targets of the EWS-WT1 fusion gene. This finding has potential clinical relevance for targeted therapeutic intervention. In addition, we identified the immune checkpoints CD200 and CD276 as potentially targetable genes whose expression is independent of the EWS-WT1 fusion gene in vitro.Conclusions: Despite the transcriptional complexity of this disease, we were able to identify IGF2, FGFR4, CD200, and CD276 as potential therapeutic targets for patients suffering from DSRCT.

  Study EGAS00001002770

• Mutational Landscape of Plasmablastic Lymphoma

  Plasmablastic lymphoma (PBL) represents a clinically heterogeneous subtype of aggressive B-cell non-Hodgkin lymphoma. Although targeted sequencing studies and a single center whole exome sequencing (WES) study in HIV+ patients recently revealed several genes, associated with PBL pathogenesis, the global mutational landscape and transcriptional profile of PBL remain elusive. To inform on disease-associated mutational drivers, mutational patterns and perturbed pathways in HIV+ and HIV- PBL we performed WES and RNA-sequencing (RNA-seq) of 34 PBL tumors.

  Study EGAS00001004906

• RNA-seq FASTQ files from newborn screening dried blood spot samples

  Paired-end RNA-seq FASTQ files from 21 newborn screening dried blood spot (DBS) samples. These DBS samples were obtained from extremely low gestional age newborns, where 10 of them were affected by a fetal inflammatory response (FIR) before birth, and 11 were unaffected. Total RNA was sequenced using an Illumina NextSeq-500 instrument. The sample preparation protocol included the depletion of rRNA and globin mRNA using the Globin Zero Gold rRNA Removal Kit from Illumina. Libraries were prepared using the NebNext Ultra TM II Directionl RNA LIbrary Prep Kit (New England Biolabs). Each sample was sequenced in 4 lanes, leading to 8 FASTQ files per sample and a total of 21x8=168 FASTQ files. There is an additional number of 8 FASTQ files corresponding to sample BS13, which was downsampled to 1/4 of its original depth (see BS13_README file for details).

  Dataset EGAD00001004991

• Exome-seq, RNA-Seq, SNP array profiling of gastric tumor samples and cell lines.

  Gastric cancer is the second leading cause of worldwide cancer mortality, yet the underlying genomic alterations remain poorly understood. Here we performed exome and transcriptome sequencing and SNP array assays to characterize 51 primary gastric tumors and 32 cell lines. Meta-analysis of the exome data and previously published data sets revealed 24 significantly mutated genes in MSS tumors, and 16 in MSI tumors. More than half of the patients in our collection could potentially benefit from targeted therapies. We identified 55 splice-site mutations accompanied by aberrant splicing products, in addition to mutation-independent differential isoform usage in tumors. The ZAK kinase isoform TV1 is preferentially upregulated in gastric tumors and cell lines relative to normal samples. This pattern is also observed in colorectal, bladder, and breast cancers. Overexpression of this particular isoform activated multiple cancer-related transcription factor reporters, while depletion of ZAK in gastric cell lines inhibited proliferation. These results reveal the spectrum of genomic and transcriptomic alterations in gastric cancer, and identify isoform-specific oncogenic properties of ZAK.

  Study EGAS00001000736

• Genomic, epigenomic and transcriptomic profiling of GCTB

  This dataset contains primary raw data of whole-genome sequencing, whole-genome bisulfite sequencing, ATAC-seq, ChIP-seq (ChIP-mentation) of histone variants and modifications, as well as RNA-seq of giant cell tumor of bone tissue and primary cell line samples.

  Dataset EGAD00001005109

• Exploring the cell-free total RNA transcriptome in diffuse large B-cell lymphoma and primary mediastinal B-cell lymphoma patients as biomarker source in blood plasma liquid biopsies

  The goal of this study was to investigate cell-free RNA (cfRNA) biomarkers in DLBCL and PMBCL patients. Blood plasma samples (n=168) and matched diagnostic formalin-fixed paraffin-embedded (FFPE) tissue samples (n=69) of DLBCL patients, PMBCL patients and healthy controls were collected between 2016-2021. Plasma samples were collected at diagnosis, at interim evaluation, after treatment, and in case of refractory or relapsed disease. RNA was extracted from 200 µl plasma using the miRNeasy serum/plasma kit and from FFPE tissue using the miRNeasy FFPE kit. RNA was subsequently sequenced on a NovaSeq 6000 instrument using the SMARTer Stranded Total RNA-seq pico v3 library preparation kit.

  Study EGAS00001007585

• Short-read RNA-seq of doxycycline-inducible DUX4 human myoblast cell lines

  The dataset includes the short-read RNA sequencing data of DUX4i myoblasts (Clone-5 and Clone-7) with and without 16-hour DOX-treatment (n=1 in each condition).

  Dataset EGAD50000000719