15147 results for "cancer studies using rna-seq"

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• Exome sequencing data from tumor progression cohort

  This dataset, named Stockholm tumor progression cohort, contains exome-sequencing samples of matched primary and metastasis samples from 20 metastatic breast cancer patients. All patients have one or more sequenced normal samples as well. The total number of samples is 125. The dataset has been used, apart from other studies, to explore tumor evolution patterns in metastatic breast cancer at Karolinska Institute Stockholm.

  Dataset EGAD00001003837

• RNA-seq of CD34+ HSPCs from LRMDS patients

  To profile transcriptional alterations of HSPCs in LR-MDS patients, 7AAD−CD45+Lin-CD235a−CD34+ cells were isolated from healthy donors and LR-MDS patients for RNA sequencing.

  Study EGAS00001008182

• Gene Fusion Discovery through RNA Sequencing of Human Glioblastoma Stem Cell Lines

  We used massively parallel, paired-end sequencing of expressed transcripts (RNA-seq) to detect novel gene fusions in short-term cultures of glioma stem-like cells freshly isolated from nine patients carrying primary glioblastoma multiforme (GBM). The culture of primary GBM tumors under serum-free conditions selects cells that retain phenotypes and genotypes closely mirroring primary tumor profiles as compared to serum-cultured glioma cell lines that have largely lost their developmental identities.

  Study phs000505

• Expression profiling of Gorlin iPSCs in the osteoblast induction culture

  In this study, we utilized human induced pluripotent stem cell (iPSC)-based models of the two diseases, named Gorlin syndrome and McCune Albright synfrome, to understand the roles of Hh signaling in osteogenesis, especially in mineralization. To examine which signaling pathways and genetic networks were affected by Gorlin syndrome-associated PTCH1 mutation in human osteoblastogenesis, we performed RNA sequencing (RNA-seq) analysis in the osteoblast induction culture of WT and Gorlin iPSCs.

  Study JGAS000218

• 10X snRNA-seq data from human FCDII postoperative brain tissues with mTOR pathway mutations

  Focal cortical dysplasia type II (FCDII) is linked to mTOR pathway mutations and drug-resistant epilepsy. Using 10X snRNA-seq on postoperative FCDII brain tissues, we characterized transcriptional alterations across cell types, revealing mTOR-related dysregulation. These findings provide insights into FCDII pathology and potential therapeutic target

  Study EGAS50000000964

• Epigenetic analysis of clear cell renal cell carcinoma using ChIP-seq

  To investigate the epigenetic landscape of clear cell renal cell carcinoma (ccRCC), we performed ChIP-seq data for the CTCF, H3K4me1, H3K4me3, H3K27ac, H3K27me3, H3K36me3, and HIF1A marks in the 786-O, A-498, UM-RC-2 ccRCC cell lines, as well as the HK-2 normal renal epithelium cell line, cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions. Data are provided in raw fastq and narrowPeak formats. Data were processed using the nf-core chipseq pipeline.

  Dataset EGAD50000001886

• NIH Roadmap Epigenomics Program - Broad Institute

  For the NIH Roadmap Epigenomics project, we applied ChlP-Seq, HTBS and WGBS pipelines to generate comprehensive high-resolution maps of chromatin state and DNA methylation for 100 diverse cell types. Cell types were selected for their biological and medical importance, and for their potential to maximize the comprehensiveness of acquired epigenomic data. They include human ES cells, ES-derived cells, mesenchymal stem cells, reprogrammed stem cells and primary tissues. Comprehensive characterization of epigenetic marks ("the epigenome") is a critical step towards a global understanding of the human genome in health and disease. In this study we provide unprecedented views of the human epigenetic landscape and its variation across cell states, which offer fundamental insight into the functions and interrelationships of epigenetic marks, and provide a framework for future studies of normal and diseased epigenomes. The Roadmap Epigenomics Broad cohort is utilized in the following dbGaP sub-study. To view molecular data and derived variables collected in this sub-study, please click on the following sub-study below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000700 the Roadmap Epigenomics Broad cohort. phs000610 RM_Epigenomics_Broad_Alz

  Study phs000700

• Population Architecture using Genomics and Epidemiology (PAGE)

  PAGE II (2013-2017) seeks to expand understanding gained during PAGE I and similar studies of how ancestry-specific differences in allele frequencies and LD may explain differences in risks of common traits and conditions. Recent studies have identified rare genetic variants that are likely to contribute to common diseases and traits and observed that rare variants likely to be functional, such as those in coding and regulatory regions, tend to be population-specific. PAGE II has genotyped over 50,000 samples using MEGA, an Illumina high density custom exomechip array. The MEGA data is being imputed in PAGE to the 1000 Genomes panel. PAGE also sequenced 1,000 samples representative of 21 populations from the Americas. PAGE has harmonized phenotype data for ~300 trait variables. These datasets will be analyzed to continue emphasis on characterizing population-level disease risks in non-European-descent individuals. Cohorts in PAGE II are: CALiCo (Causal Variants Across the Life Course, a consortium of ARIC, CARDIA, HCHS/SOL, Strong Heart Studies), ISMMS (Mount Sinai BioMe Biobank), MEC (Multiethnic Cohort), WHI (Women's Health Initiative), and Stanford University (PAGE Global Reference Panel). Genotyping services were provided by the Center for Inherited Disease Research (CIDR) and sequence data were provided by the McDonnell Genome Institute at Washington University School of Medicine. PAGE I (2008-2013): The first phase of PAGE examined putative causal genetic variants across approximately 100,000 African Americans, Asian Americans, American Indians, European Americans, Hispanic Americans, and Native Hawaiians from four groups representing nine large U.S.-based cohorts. Two genotyping approaches were employed - targeted genotyping of selected SNPs identified in genome-wide association studies of common disease, and a large-scale effort focused on the Metabochip array, which facilitated trans-ethnic fine mapping of several diseases of public health importance. Cohorts in PAGE I were: CALiCo (Causal Variants Across the Life Course, a consortium of ARIC, CARDIA, CHS, HCHS/SOL, Strong Heart Cohort Study, Strong Heart Family Study), EAGLE (Epidemiologic Architecture for Genes Linked to Environment, based on 3 National Health and Nutrition Examination Surveys (NHANES)), MEC (Multiethnic Cohort) and WHI (Women's Health Initiative). Logistical and scientific support is provided by the PAGE Coordinating Center and the NHGRI Division of Genomic Medicine. PAGE II is funded by the NHGRI and the NIMHD. To access PAGE studies currently available in dbGaP, please click on the links below.Please note that some PAGE studies belong to larger cohorts and have been included as PAGE substudies. For those studies, there is an additional link to the parent study. phs000223 PAGE-ARIC and phs000280 ARIC Cohort phs000236 PAGE-CARDIA and phs000285 CARDIA Cohort phs000301 PAGE-CHS and phs000287 CHS Cohort phs000559 PAGE-EAGLE-BioVu phs000208 PAGE-EAGLE-NHANES phs000555 PAGE-HCHS/SOL and phs000810 HCHS/SOL Cohort phs000220 PAGE-MEC phs000580 PAGE-SHS and SHFS phs001033 PAGE Global Reference Panel phs000227 PAGE-WHI and phs000200 WHI Cohort

  Study phs000356

• Transcriptomic analysis of metastatic colorectal cancer

  Metastatic colorectal cancer (mCRC) is the main cause of CRC mortality, with limited treatment options. Although immunotherapy has benefited some cancer patients, mCRC typically lacks the molecular features that respond to this treatment. However, recent studies indicate that the immune microenvironment of mCRC may be modified to enhance the effect of immune checkpoint inhibitors. This dataset was used to explore the metastatic immune microenvironment by comparing immune cell populations in colorectal liver (CLM), lung (mLu) and peritoneal (PM) metastases.

  Dataset EGAD50000000926

• Transcriptional profiling of tauopathies in human IPS-derived neurons (2019-08-21)

  This project is a pilot study, in collaboration with Maria Grazia Spillantini and Mariangela Iovino (Cambridge Centre for Brain Repair), to investigate the utility of IPS-derived neurons for the study of neurodegenerative disorders. Our aim is to characterise the transcriptional consequences of tauopathies using neurons derived from differentiated IPSCs as a model system. We will use IPS cells derived from six individuals, four with known mutations in the tau protein, 2 without. RNA will be extracted at Day 0 and Day 65 of differentiation by which time the neuronal tauopathy is apparent. RNA will be extracted and the transcriptome of each line characterised using RNAseq. We will then search for genes that are differentially expressed between the transcriptomes of individuals with tau mutations versus those in controls. My lab will analyse the RNAseq data, comparing both affected and controls and both time-points, to establish candidate genes. Darren Logan’s lab, along with our collaborators, will experimentally verify and further investigate these genes in additional lines and animal models. From this analysis we will generate a list of candidate genes that are differentially expressed between cases and controls. This study will not only help us understand the molecular basis of tauopathies, but also identify gene candidates for biomarkers of neurodegenerative disease. It will serve as a proof of principle for future planned studies into generating and transcriptomically analysing an allelic series of Tau mutations in IPSCs with a controlled genetic background. 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/ . This dataset contains all the data available for this study on 2019-08-21.

  Dataset EGAD00001005277