14977 results for "cancer studies using rna-seq"

in 15.71 milliseconds.

• Coding and non-coding drivers of mantle cell lymphoma identified through exome and genome sequencing

  Mantle cell lymphoma (MCL) is an uncommon B-cell non-Hodgkin lymphoma (NHL) that is incurable with standard therapies. The genetic drivers of this cancer have not been firmly established and the features that contribute to differences in clinical course remain limited. To extend our understanding of the biological pathways involved in this malignancy, we performed a large-scale genomic analysis of MCL using data from 51 exomes and 34 genomes alongside previously published exome cohorts. To confirm our findings, we re-sequenced the genes identified in the exome cohort in 191 MCL tumors, each having clinical follow-up data. We confirmed the prognostic association of TP53 and NOTCH1 mutations. Our sequencing revealed novel recurrent non-coding mutations surrounding a single exon of the HNRNPH1 gene. In RNA-seq data from 103 of these cases, MCL tumors with these mutations had a distinct imbalance of HNRNPH1 isoforms. This altered splicing of HNRNPH1 was associated with inferior outcomes in MCL and showed a significant increase in protein expression by immunohistochemistry. We describe a functional role for these recurrent non-coding mutations in disrupting an auto-regulatory feedback mechanism, thereby deregulating HNRNPH1 protein expression. Taken together, these data strongly implicate a role for aberrant regulation of mRNA processing in MCL pathobiology.

  Study EGAS00001004289

• Contribution of specific cell types to the development of Barrett’s esophagus and carcinoma via germline genetic risk

  This study was designed to elucidate how individual cell types in Barrett’s esophagus (BE) and esophageal adenocarcinoma (EAC) contribute to disease development via germline genetic risk. We performed single cell RNA-sequencing (scRNA-seq) of BE, EAC and paired normal esophagus and gastric fundus tissue samples. After analyzing individual cell types, we integrated the scRNA-seq data and data of a genome-wide association study (GWAS) on BE/EAC to determine cell type-specific genetic risk. Raw data from the RNA-sequencing is provided here.

  Study EGAS50000000530

• Chromatin accessibility profiling of primary human hepatocytes

  The chromatin accessibility profiling of primary human hepatocytes using Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq).

  Study EGAS50000001230

• DAC_RNA-seq of murine osteosarcoma cell line genetically modified for CYR61

  Data access committee for RNA-seq of murine osteosarcoma cell line genetically modified for CYR61

  Dac EGAC50000000352

• Genome-Wide Association Study of Lung Cancer Susceptibility in Never-Smoking Women in Asia

  To learn about the etiology of lung cancer among never-smoking women in Asia, we formed the Female Lung Cancer Consortium in Asia (FLCCA), which includes studies of lung cancer in Eastern Asia and conducted a GWAS. We analyzed a total of 5510 lung cancer cases and 4544 controls and identified 3 novel loci (Lan et al., 2012). Of these study subjects, 4922 lung cancer cases and 3959 controls are available for posting. Lan et al.., Genome-wide association analysis identifies new lung cancer susceptibility loci in never-smoking women in Asia. Nat Genet. 2012 Dec;44(12):1330-5. doi: 10.1038/ng.2456. Epub 2012 Nov 11. PubMed PMID: 23143601.

  Study phs000716

• Genomics_of_acral_lentiginous_melanoma___RNAseq

  Melanoma is the most aggressive type of skin cancer, causing about 75% of dermatological cancer deaths. Acral lentiginous melanoma (ALM) is the most common subtype of melanoma in admixed Latin American populations, but very few tumour genomes and exomes, all from European-descent individuals, have been analysed across several studies. Because of this, the genomic landscape of ALM is mostly unknown. Our aim in this project is to define this landscape and identify driver somatic alterations by whole-exome sequencing a collection of ALM germline/tumour paired FFPE samples from the National Cancer Institute of Mexico.

  Study EGAS00001003758

• Brain transcriptome of hereditary cerebral haemorrhage with amyloidosis–Dutch type (HCHWA-D)

  HCHWA-D is an early onset hereditary form of Cerebral Amyloid Angiopathy (CAA) caused by a point mutation resulting in an amino acid change (NP_000475.1:p.Glu693Gln) in the Amyloid Precursor Protein (APP). Post-mortem brain tissue (9 patients and 9 age-related controls; frontal and occipital cortex) was used for next generation sequencing of RNA (RNA-Seq with ribosomal RNA depletion).

  Study EGAS00001002730

• RNA Sequencing of Colorectal Liver Metastases

  Reverse-stranded paired-end 75 base-pair RNA sequencing libraries of 93 metastatic FFPE samples were constructed using Illumina Total RNA Stranded Kits. Ribosomal RNAs (rRNAs) were depleted by using the Ribo-Zero rRNA Removal Kit (Illumina). Libraries were sequenced on a HiSEQ2500 machine. Five samples were re-sequenced using paired-end 50 base-pair libraries due to the smaller insert sizes.

  Dataset EGAD00001004111

• Bulk and RIP-seq transcriptome datasets from skin fibroblasts in PTBP1- and PTBP2-related disorders

  PTBP1- and PTBP2-related disorders are rare human conditions that cause variable neurodevelopmental phenotypes, including intellectual disability and behavioral problems such as autism spectrum disorder, anxiety, aggressiveness, and attention disorders, with or without hyperactivity. PTBP1-related disorder is also associated with skeletal dysplasia. In this study, we generated bulk RNA sequencing and RNA immunoprecipitation sequencing (RIP-seq) data from skin fibroblasts obtained from patients and healthy controls.

  Study EGAS50000001210

• The Library of Integrated Network-Based Cellular Signatures (LINCS) - NeuroLINCS

  The NeuroLINCS Center is part of the NIH Common Fund's Library of Integrated Network-based Cellular Signatures (LINCS) program, which aims to characterize how a variety of human cells, tissues and the entire organism respond to perturbations by drugs and other molecular factors. As Part of the LINCS program, the NeuroLINCS study concentrates on human brain cells, which are far less understood than other cells in the body. Our initial focus is to produce diseased motor neurons from patients by utilizing high-quality induced pluripotent stem cell (iPSC) lines from Amyotrophic Lateral Sclerosis (ALS) and Spinal Muscular Atrophy (SMA) patients in addition to unaffected normal healthy controls. Using state-of-the-art OMICS methods (genomics, epigenomics, transcriptomics, and proteomics), we intend to create a wealth of cellular data that is patient-specific in the context of their baseline genetic perturbations and in the presence of other genetic and environmental perturbagens (e.g. endoplasmic reticulum stress). The primary data will be used to build cell signatures that convey the key features that distinguish the state of a cell and determine its behavior. Ultimately, the analysis of these datasets will lead to the identification of a network of unique signatures relevant to each of these motor neuron diseases. The datasets represented in this study are generated from assays interrogating RNA expression (RNA-seq), chromatin accessibility (ATAC-seq) and whole genome sequencing.

  Study phs001231

• Construction of endoscopic biopsy banking for understanding the intestinal environment in colorectal diseases and exploratory studies using these banking systems.

  Colorectal cancer is the most common type of cancer in Japan. Although some colorectal cancers have a genetic background, most colorectal cancers are sporadic. Known risk factors for colorectal cancer include smoking, obesity, lack of exercise, and red and processed meat. Furthermore, although it has been suggested that changes in the intestinal environment due to changes in diet and lifestyle may be involved in the increased incidence of colorectal cancer in Japan, the molecular mechanism has not yet been fully elucidated. The main objective of this study is to elucidate the changes in the intestinal environment that cause colorectal tumors, and also to contribute to the establishment of colorectal mucosal tissue banking in Japan.

  Study JGAS000655

• Medulloblastoma Illumina RNA-Seq

  Illumina RNA-sequencing of Medulloblastoma primary and relapse tumor.

  Dataset EGAD00001009425

• RNA-Seq of non-canonical t(7;12) AML

  We performed WGS on AutoMACS-separated BM leukemic blasts (CD34 + CD33+) to characterize the breakpoint and genes involved in the translocation. Additionally, we performed RNA-seq of the bone marrow blast cells to explore the functional consequences of the t(7;12) translocation

  Dataset EGAD50000000268

• Patient-derived conditionally reprogrammed cells (CRCs) were established and characterized to assess their biological properties and to apply these to test the efficacies of drugs.

  RNA seq data was used for the characterization and profiling of the created patient-derived cells and in vivo tissue.

  Study EGAS00001001702

• Chromatin 3D interactions mediate genetic effects on gene expression (RNA-seq)

  RNA-seq data for 168 Lymphoblastoid Cell Lines (LCL) and 78 Fibroblasts (FIB) from the Gencord Cohort. This dataset was generated as part of the following study: Delaneau et al (2019). Chromatin 3D interactions mediate genetic effects on gene expression.

  Dataset EGAD00001004872

• Human tumor bulk RNA-seq

  We profiled 186 patient tumor samples by bulk RNA-seq. These includes 38 embryonal brain tumors, 101 high-grade gliomas, 24 low-grade gliomas, 10 medulloblastoma and 13 matched normals. The raw fastqs are provided.

  Dataset EGAD00001005131

• BLUEPRINT release August 2015, RNA-Seq for Multiple myeloma, on genome GRCh38

  RNA-Seq data for 11 Multiple myeloma sample(s). 11 run(s), 11 experiment(s), 11 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001471

• RNA-seq cohort of normal weight women

  RNA-seq data of non-tumorous breast tissue. There are 32 samples in this cohort.

  Dataset EGAD00001007073

• BLUEPRINT: RNA-seq for monocytes and neutrophils

  RNA-seq for monocytes and neutrophils

  Dataset EGAD00001000675

• RNA-seq data from a variety of pediatric brain tumors

  RNA-seq (n=52) data from a variety of pediatric brain tumors including ependymoma (PFA, PFB, Ste, spinal), medulloblastoma (G3, G4, SHH), high grade glioma (H3K27 and H3-WT), pilocytic astrocytoma, and more. Raw data provided as FASTQ. Data generated on Illumina HiSeq2500.

  Dataset EGAD00001007915

• BLUEPRINT release August 2015, RNA-Seq for monocyte, on genome GRCh38

  RNA-Seq data for 4 monocyte sample(s). 4 run(s), 4 experiment(s), 4 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001572

• Total RNA-seq of intestinal gluten tetramer+ and tetramer- CD4+ T-cells from celiac disease patients

  Total RNA-seq of intestinal gluten tetramer+ and tetramer- CD4+ T-cells from celiac disease patients, as well as intestinal CD4+ T-cells from healthy control individuals (paired-end fastq files).

  Dataset EGAD00001004146

• Combined genetic and transcriptome analysis of patients with Systemic Lupus Erythematosus (SLE)

  A comprehensive profiling of the genomic architecture of Systemic Lupus Erythematosus (SLE) by combining genetic and transscriptomic analysis by RNA-seq.

  Study EGAS00001003662

• subset of 11 samples RRMM (RNA-Seq and WGS) from study EGAS00001005973 used also in study EGAS00001006538

  subset of 11 samples (RNA-Seq and WGS) from study EGAS00001005973, which was published earlier and are linked here to study EGAS00001006538

  Dataset EGAD00001009679

• RNA-seq dataset of Neoantigen Peptides derived from V(D)J-recombined Immunoglobulins Drive Outgrowth of Cytolytic CD8+ T-cells

  RNA-seq dataset of Neoantigen Peptides derived from V(D)J-recombined Immunoglobulins Drive Outgrowth of Cytolytic CD8+ T-cells

  Dataset EGAD00001015647