3796 results for "RNA AND sequencing OR transcriptome"

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• Fecal microbiome predicts treatment response after the initiation of semaglutide or empagliflozin uptake

  To investigate the effect of semaglutide and empagliflozin initiation on the gut microbiome of type 2 diabetes patients. In addition, to analyze whether the pre-treatment gut microbiome can predict the treatment efficacy. Gut microbiome fecal samples donated at four timepoints (Baseline, Month 1, Month 3; Month 12) were studied using 16S ribosomal RNA gene sequencing and analysis.

  Study EGAS50000000531

• CLUSTER consortium RNAseq CD19 B cell dataset of UK JIA patients.

  This study examines B cell transcriptomic profiles in Juvenile Idiopathic Arthritis (JIA) patients to investigate molecular mechanisms underlying disease heterogeneity. CD19+ B cells were isolated from peripheral blood samples and subjected to RNA sequencing to characterise gene expression patterns. The dataset includes patients with documented uveitis status to enable investigation of B cell contributions to the common JIA comorbidity.

  Study EGAS50000001123

• Defective homologous recombination in HCC

  Backgrounds and Aims: We performed an in-depth examination of pathogenic germline (PGVs) and somatic variants in DNA damage response (DDR) genes in hepatocellular carcinoma (HCC) to explore their clinical and genomic impacts. Approach and Results: We used a merged whole exome or RNA sequencing dataset derived from in-house (n=230) and TCGA (n=362) databases of multiethnic HCC samples.

  Study EGAS00001006599

• The Berlin (BLN) panel of glioblastoma cell lines: RNAseq of human gliomasphere cell lines and matched parental tumors

  We generated a panel of nine glioma stem-like cell lines under serum-free cell culture conditions from human glioblastoma samples. In addition to clinical annotation, MR imaging and histological characterization of the parental tumor, as well as xenograft studies of tumorigenecity, transcriptomic profiling of tumor/cell line pairs by RNA sequencing has been performed.

  Study EGAS00001001167

• Molecular profiling of MBD4-deficient acute myeloid leukaemia

  We describe two cases of MBD4-deficient acute myeloid leukaemia (AML). Clinical samples were used for molecular analysis, including genomic profiling (genome and exomes), methylation analysis (RRBS) and transcriptional profiling (RNA-sequencing). An analysis and methodological description has been published: “MBD4 guards against methylation damage and germline deficiency predisposes to clonal hematopoiesis and early-onset AML” [PMID: 30049810]

  Study EGAS00001002581

• Transcriptomic analysis of TFEB overexpression in LT-HSC, ST-HSC and MEP

  Long-term hematopoietic stem cells (LT-HSC), Short-term hematopietic stem cells (ST-HSC) and Megakaryocyte-erythrocyte progenitors (MEP) were sorted from human cord blood and cultured overnight before transduction with lentivirus to overexpress GP91 (CTRL) or TFEB. Three (LT-HSC ans ST-HSC) or six (MEP) days later, BFP+ transduced cells were sorted for RNA extraction and sequencing.

  Study EGAS00001004969

• Multi-omic dataset of neuroendocrine neoplasm organoids

  This dataset corresponds to one of the first biobanks for the understudied neuroendocrine neoplasms from multiple grades and body sites (lung, pancreas, small intestine). It contains whole-genome sequencing data for original tumors, patient-derived tumor organoids at multiple passages, and matched normal tissue, and RNA-seq data for the original tumor and patient-derived tumor organoids.

  Study EGAS00001005752

• Adult B-precursor acute lymphoblastic leukemia transcriptomes

  Bone marrow or peripheral blood samples were collected of adult patients at first diagnosis of B-precursor acute lymphoblastic leukemia. RNA was isolated from mononuclear cells and subjected to mRNA library prep using Poly-A selection and sequencing on a NovaSeq 6000 system. Obtained gene expression profiles and gene fusion calls were used to allocate samples to molecular disease subtypes.

  Study EGAS00001006107

• Integrating Genomic and Transcriptomic Data to Identify Breast Cancer Susceptibility Genes

  Genetic factors play an important role in the etiology of both sporadic and familial breast cancer. Since 2007, common genetic variants in ~200 loci have been identified in genome-wide association studies (GWAS) in relation to breast cancer risk. However, it is often difficult to translate GWAS findings to disease prevention and treatment since causal genes in the large majority of GWAS-identified loci are unknown. Furthermore, a large fraction of breast cancer heritability remains unexplained. Recent studies suggest that nearly 80% of disease heritability can be explained by genetic variants regulating gene expression. Herein, we propose three well-powered transcriptome-wide association studies (TWAS) to systematically investigate the association of breast cancer risk with gene expression across the transcriptome of African, Asian and European descendants. In Aim 1, we will perform RNA sequencing and high-density genotyping assays using normal breast tissue samples, and build race-specific gene expression prediction models using data from 1000 women of African, Asian and European descent. These models will be applied to the GWAS data generated from approximately 320,000 breast cancer patients and controls to impute gene expression for association analyses of predicted gene expression with risk of breast cancer overall, and by estrogen receptor and HER2 status. In Aim 2, we will select the top 50 genes identified in Aim 1 for in vitro functional assays to assess their influence on major cell functions related to cancer biology. In Aim 3, we will evaluate whether TWAS-identified genes may express differently in normal breast tissues and breast cancer tissues collected from African, Asian, and European descendants to assess whether these genes may contribute to racial differences in breast cancer risk by molecular subtypes. With strong methodology and a large sample size, we believe that this proposed study should be able to identify and characterize a large number of novel genes related to breast cancer risk. Uncovering breast cancer susceptibility genes will greatly improve the understanding of the genetic and biological basis for breast cancer and accelerate the translation of genetic findings to disease prevention and patient care.

  Study phs003535

• NIBIT-EPI-MESO study samples

  Multi-omics analysis of pre-immuno checkpoint inhibitors (ICI) therapy lesions from 91 pleural mesothelioma (PM) patients enrolled in the multicenter NIBIT-EPI-MESO study. Neoplastic lesions were characterized using multiple molecular platforms, including RNA sequencing (n=82), Whole Exome Sequencing (WES) (n=87), Reduced Representation Bisulfite Sequencing (RRBS) (n=83) and cell-free methylated immunoprecipitation sequencing (cfMeDIP-seq) (n=18). Tumor samples were collected during the standard diagnostic pleuroscopy or thoracoscopy before ICI therapy. Matched Peripheral Blood Mononuclear Cells (PBMC) were collected from PM patients before ICI therapy.

  Study EGAS50000001478