14977 results for "cancer studies using rna-seq"

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• A Multiethnic Genome-wide Scan of Prostate Cancer

  Multiple GWA studies of prostate cancer conducted in European White populations are ongoing. These studies will continue to have a dramatic impact on our understanding of the contribution of common genetic variation on inter-individual susceptibility to this common cancer. Important questions that will remain unanswered, however, are whether all common risk alleles for prostate cancer will be revealed in studies limited to populations of European ancestry. A comprehensive examination of common genetic variation in men of Japanese, Latino, and African ancestry will be required to understand population differences in disease risk and to reveal the full spectrum of causal alleles that exist in these populations. Further, genetic and environmental diversity is likely to contribute to ethnic heterogeneity of genetic effects. Elucidating gene x gene and gene x environment interactions is also likely to provide knowledge that may be critical for understanding the contribution of genetic susceptibility to racial/ethnic disparities in prostate cancer incidence and for translating the findings from GWA studies into interventions. In this study we plan to undertake a genome-wide association study (GWAS) of prostate cancer in the Multiethnic Cohort (MEC) Study. We propose the following hypotheses: (a) that inherited DNA variation influences risk of prostate cancer; (b) that many of the causal alleles will be outside known "candidate genes" requiring an agnostic, comprehensive search; and (c) that performing this search in a multi-ethnic cohort is more powerful than a study limited to a single population to reveal the full range of causal alleles relevant to the U.S. population. The version 1 release of this dataset will include genotype data for the Japanese and Latino populations in the study. The version 2 release will include data for the African ancestry population along with the Japanese and Latino subjects. The version 3 release will include fully-cleaned genotype data for all three populations. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to prostate cancer through large-scale genome-wide association studies of a well-characterized multi-ethnic cohort. Genotyping was performed at the Broad Institute of MIT and Harvard, a GENEVA genotyping center and at the University of Southern California. Data cleaning and harmonization were performed at the GEI-funded GENEVA Coordinating Center at the University of Washington. As an add-on to this GWAS we performed a targeted re-sequencing of all known prostate cancer risk loci in the samples from the MEC. Sequencing was performed in Dr. Reich's lab at Harvard Medical School.

  Study phs000306

• Dana-Farber Cancer Institute (DFCI) Brown Lab CLL Sequencing Study

  Chronic Lymphocytic Leukemia (CLL) is a hematological malignancy characterized by accumulation of CD5+CD19+ B cells in peripheral lymphoid organs, bone marrow and blood. In this study we analyze matched whole genome sequencing and RNA-seq data from CLL patients to characterize the mutational processes operative throughout tumor evolution. Source of tumor and normal DNA used is patient PBMC or B cells and saliva respectively.

  Study phs000879

• CD4 T-Cell RNA-Seq

  CD4 T-Cell RNA-Seq

  Dataset EGAD00001002687

• Transcriptomic profiling of lymphedema

  RNA-seq of skin from human subjects with and without lymphedema

  Study EGAS00001004516

• RNA-seq

  RNA-seq data

  Dataset EGAD00001008959

• LGG Epilepsy Cohort RNA-Seq

  LGG Epilepsy Cohort RNA-Seq

  Dataset EGAD00001001666

• Omics data of advanced bladder cancer

  To identify the therapeutic targets in a treatment-refractory cancer patient, we performed single-cell RNA sequencing for 3,115 cells from primary bladder cancer (BC159-T#3) and patient-derived xenografts (BC159-T#3-PDX-vehicle and BC159-T#3-PDX-tipifarnib). Matched time-series bulk tumor tissues were also sequenced using whole exome target probe (WES) and whole transcriptome target probe (WTS).

  Dataset EGAD00001005978

• Bulk RNASeq on CD8+CD69+CD103+ and CD8+CD69+CD103- T cells form breast cancer.

  CD8+CD69+CD103+ and CD8+CD69+CD103- T cells were flow sorted from 1 primary triple negative breast cancer, 1 primary HER2 amplified breast cancer, and 1 triple negative liver metastasis. Prior to flow sorting, fresh tumor samples were digested to produce single cell homogenates on the day of surgery. Following RNA extraction, RNASeq was performed using polyA selection.

  Dataset EGAD00001003964

• Gene Expression Signatures Characterized by Longitudinal Stability and Inter-Individual Variability Delineate Baseline Phenotypic Groups with Distinct Responses to Immune Stimulation

  RNA sequencing (RNAseq) of peripheral blood lymphocytes was used to develop a means to assess immune function in a way that can be used in discovery science and applied to patients individually in clinical settings. The premise is that profiles of RNA present in immune cells is reflective of the combined influence of genetic and environmental variation on immune potential of individuals and that this potential can be tapped to understand human immunity in a variety of biological contexts. CD4+ cells were isolated from fresh whole blood via positive magnetic bead selection and cell lysates were prepared using Qiazol (QIAGEN) and stored at -80ºC for 3 to 8 months. RNA was extracted in batches for cDNA library preparation and RNA-Seq. For this study, we developed standard operating procedures for handling human blood samples and determined: a) the best way to enrich for CD4+ T cells from whole blood and yield high quality RNA, b) the sensitivity of this RNA profiling strategy, and c) the reproducibility of generated immune profiles from healthy subjects. We then developed bioinformatics processes to establish immune response signatures and immune response phenotypes within cohorts of individuals.

  Study phs001512

• scRNA-seq of HGSC tumor and ascites

  Immune regulatory metabolites are key features of the tumor microenvironment (TME), yet with a few notable exceptions, their identities remain largely unknown. We uncovered the immune regulatory metabolic states and metabolomes of sorted tumor and stromal, CD4+, and CD8+ cells from the tumor and ascites of patients with high-grade serous ovarian cancer (HGSC) using high-dimensional flow cytometry and metabolomics supplemented with single cell RNA sequencing. Flow cytometry revealed that tumor cells show a consistently greater uptake of glucose than T cells, but similar mitochondrial activity. Cells within the ascites and tumor had pervasive metabolite differences, with a striking enrichment in 1-methylnicotinamide (MNA) in T cells infiltrating the tumor compared to ascites. Despite the elevated levels of MNA in T cells, the expression of nicotinamide N-methyltransferase, the gene encoding the enzyme that catalyses the transfer of a methyl group from S-adenosylmethionine to nicotinamide, was restricted to fibroblasts and tumor cells. Treatment of T cells with MNA resulted in an increase in T cell-mediated secretion of the tumor promoting cytokine tumor necrosis factor alpha. Thus, the TME-derived metabolite MNA contributes to an alternative and non-cell autonomous mechanism of immune modulation of T cells in HGSC. Collectively, uncovering the tumor-T cell metabolome may reveal metabolic vulnerabilities that can be exploited using T cell-based immunotherapies to treat human cancer.

  Study EGAS00001004829

• Single cell RNA sequencing of human embryonic forebrain after slice culturing for between four weeks and one month

  With the aim of verifying normal tissue development in our Organotypic Timelapse recording with Transcriptomic Readout (OTTR) live tissue imaging method, we performed single cell RNA sequencing in organotypic slice cultures containing labelled cells from virally delivered ubiquitous Enhanced yellow fluorescent protein (EYFP)-expression. Human fetal cortices of PCW 7.5-10.5 were cut into strips along the dorso-ventral axis and directly placed en face, ventricular side down, on PTFE culturing membranes. To assess tissue health with our culturing method, we performed single cell RNA-seq analysis of the cortical explants (using adjacent slices from the same samples subjected to timelapse imaging). We cultured these control slices for four days in vitro (mimicking the start of a live imaging experiment after lentiviral infection and expression of EYFP), 11 days in vitro (corresponding to the end of one week of live imaging), and for two weeks and one month in vitro.

  Study EGAS50000001185

• RNA-seq iNKT, T and C1R cells

  RNA-seq (Ribodepleted Directional -75 PE- Hiseq 4000) data of purified and expanded iNKt and T cells from normal donor, and RNA-seq (poly-A 100-PE Hiseq 2500) data from C1R cell line. Data set consist of 3 pairs of fastq files, one pair per sample

  Dataset EGAD00001004331

• Short-read (RNA-seq)

  The goal of this project was to perform long-read RNA sequencing (LR-seq, PacBio) in combination with short-read RNA-seq for systematic characterization of the isoform diversity in primary breast tumor samples. We sequenced the full-length transcriptomes of 26 breast tumors and 4 normal breast samples.

  Dataset EGAD00001006596

• Analyses of RNAseq data from NEN patient derived tumor organoids (PDTOs) and matched parental tumors

  The dataset includes RNA-seq expression R data, RNA-seq gene counts matrix, and RNA-seq gene FPKM matrix from 21 NEN tumors or metastases and matched PDTOs. The sequencing was done with either a Nextseq 2000 or a NovaSeq 6000 instrument.

  Dataset EGAD00001009994

• Whole genome sequencing of multiple myeloma patient samples.

  Tumor (CD138+ plasma cells) and non-tumor (peripheral blood white cells or stem cell harvest) DNA from patients with a plasma cell dyscrasias were sequenced. Whole genome sequencing using high molecular weight DNA was performed using the 10X Genomics Chromium platform on either a HiSeq4000 or NovaSeq (Illumina) using 100 to 150 bp paired-end reads. The dataset consists of 111 patients, and 223 samples in total (matched tumor and control per patient; one patient had 2 tumor samples sequenced). Diseases consisted of 2 MGUS patients, 8 SMM patients, 91 newly diagnosed myeloma patients, 1 previously treated patient, 4 relapsed MM patients, and 5 PCL patients. Paired RNA-seq data are available for 81 of the samples under study EGAS00001003411.

  Dataset EGAD00001004452

• HipSci_Illumina 450K Methylation analysis_Healthy volunteers

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we performed Methylation analysis using the Infinium HumanMethylation450 BeadChip on iPS cells generated from skin biopsies from healthy volunteers.

  Study EGAS00001000865

• Genetic coupling of enhancer activity and connectivity in gene expression control

  In this study, we investigated whether the genetic effects of eQTLs on enhancer activity and enhancer-promoter contacts (connectivity) are inherently coupled or distinct. To address this, we performed Capture Hi-C targeting ~1100 eQTL loci, along with ATAC-seq and RNA-seq, in monocytes from 34 healthy male donors. Using single-modality and multi-modality Bayesian statistical approaches, we demonstrated that eQTL effects are predominantly shared across enhancer activity, connectivity, and gene expression. However, we also identified a locus where an eQTL disrupts a CTCF binding site at a putative insulator, facilitating contacts between the PCK2 gene promoter and downstream enhancers. To validate these findings, we used 4C-seq to confirm the allelic effects of eQTLs on enhancer-promoter connectivity at the PCK2 locus and another eQTL region associated with THBS1 expression, both of which showed consistent eQTL effects across all three modalities. Additionally, we conducted Hi-C on monocytes from two donors to map reference TADs and performed ChIP-seq to confirm the allelic effects of the PCK2 eQTL on CTCF binding. Together, these data provide comprehensive insights into the genetic coupling of enhancer activity, connectivity, and gene expression.

  Study EGAS50000000756

• Prognostic whole-genome and transcriptome signatures in colorectal cancers

  This dataset consists of RNA-seq CRAM raw-data files of 1063 primary colorectal cancer and 120 adjacent normal tissue samples. The expression profiles for these samples can be found at the ArrayExpress with accession number E-MTAB-12862.

  Dataset EGAD50000000169

• RNA-Seq Dataset of Organoid drug profiling identifies methotrexate as a therapy for SCCOHT, a rare pediatric cancer

  We generated and characterized tumoroids from small cell carcinoma of the ovary, hypercalcemic type. Furthermore, we identified a drug that is selective and effective against SCCOHT tumoroids.

  Dataset EGAD00001015441