14977 results for "cancer studies using rna-seq"

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• RNA-seq of human astroblastomas

  RNA-seq for fusion gene discovery of human astroblastomas

  Dataset EGAD00001009664

• Genomic Analysis of Fibrolamellar Hepatocellular Carcinoma

  Fibrolamellar hepatocellular carcinoma (FL-HCC) is a very rare and distinct subtype of hepatocellular carcinoma that occurs in the previously healthy livers of adolescents and young adults. The low incidence rate has kept FL-HCC an understudied cancer, thus the list of FL-HCC markers is limited and the genetic alterations driving its growth have remained unknown. In order to gain a better understanding of the molecular mechanisms underlying FL-HCC initiation and progression, we performed an in-depth genomic analyses of one tumor followed by immunohistochemistry validation on seven other tumors. We showed the expression of neuroendocrine markers in FL-HCC. In addition, DNA/RNA sequencing revealed that common cancer pathways are not visibly altered in FL-HCC but identified two novel structural variants, both resulting in fusion transcripts. Through in vitro studies, we demonstrated the oncogenic properties of these fusion transcripts. These experiments further highlight the tumorigenic role of gene fusions in the etiology of pediatric solid tumors and identify both candidate biomarkers and possible therapeutic targets for this lethal pediatric disease.

  Study phs000828

• Transcriptomic analysis of the NA-PHER2 clinical trial

  We performed whole transcriptome RNA sequencing on serial tumour biopsies collected at baseline, Day 14, and after completion of all neoadjuvant therapy from the NA-PHER2 trial. Patients received neoadjuvant treatment with the combined regimen of trastuzumab, pertuzumab, palbociclib with or without addition of fulvestrant. Transcriptomic profiles were generated from 143 samples (Baseline n = 53, Day 14 n = 49, Surgery n = 41) corresponding to 53 of the 58 patients enrolled in NA-PHER2 trial (91.4%). RNA sequencing was performed on total RNA samples derived from formalin-fixed, paraffin-embedded (FFPE) tissue sections. RNA-Seq libraries were produced using NEBNext® Ultra™ II Directional RNA Library Prep Kit. The capture was then performed on cDNA libraries with the Twist Human Core Exome Enrichment System according to supplier recommendations (Twist Bioscience). The obtained eluted-enriched DNA samples was then sequenced on an Illumina NovaSeq as paired-end 100bp reads. FASTQ files are provided.

  Dataset EGAD50000000363

• RNA sequencing from patient-derived intestinal organoids

  RNA from the duodenal organoids was isolated using an RNeasy Kit (Qiagen, Hilden, Germany) following the manufacturer’s instructions. RNA purity and concentration were measured using a NanoDrop One spectrophotometer (NanoDrop Technologies, Wilmington, Delaware, USA). Preparation of the RNA library and transcriptome sequencing was conducted by Novogene Co., LTD (Cambridge, UK). Messenger RNA was purified from total RNA using polyA selection and subjected to library construction. Sequencing was performed on an Illumina platform, and 150 bp paired-end reads were generated.

  Study EGAS50000000338

• 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