Objective
A subset of metastatic pancreatic ductal adenocarcinomas depends quantitatively on oncogenic Kras/Mek/Erk-induced hyperactive mTOR signalling.
No sample metadata fields
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Differential Methylation of H3K79 Reveals DOT1L Target Genes and Function in the Cerebellum In Vivo.
Specimen part
View SamplesDOT1L as methyltransferase of H3K79 is implicated in brian development. Here, we further defined DOT1L function in gene expression during cerebellar development using Microarrays. For that we generated Dot1l knockout mice using a Atoh-Cre driver line resulting in a Dot1l knockout within the cerebellum. The RNA of cerebellar tissue of the Dot1l knockout animals was thereby compared to controls. Additionally we compared the RNA levels of cultured CGNP and CGN samples treated with a DOT1L inhibitor versus DMSO treated cells. The data sets reveals potential new gene expression targets of DOT1L in vivo and in vitro, which ensure a correct development of the cerebellum.
Differential Methylation of H3K79 Reveals DOT1L Target Genes and Function in the Cerebellum In Vivo.
Specimen part
View SamplesActivating Transcription Factor 4 (ATF4) is a transcription factor induced by the integrated stress response (ISR). This experiment is a genome-wide profiling of ATF4-dependent RNA expression in human HAP-1 cells. HAP-1 is a near-haploid human cell line that was derived from KBM-7 cells isolated from a patient with Chronic Myelogenous Leukemia. We analyzed WT and ATF4 KO cells. We induced ATF4 expression by mimicking amino acid starvation with the drug histidinol. Overall design: RNA expression profiles were generated for WT and ATF4 KO HAP1 cells. ATF4 genes were mutated using Cas9 genome editing technology. Amino acid starvation was mimicked by treating WT and ATF4 KO cells with 2 mM histidinol for 24 hours, which increases ATF4 expression.
A forward genetic screen reveals novel independent regulators of ULBP1, an activating ligand for natural killer cells.
No sample metadata fields
View SamplesWe analyzed samples from 770 male human subjects who are part of the METSIM study. Ethics Committee of the Northern Savo Hospital District approved the study. All participants gave written informed consent. The population-based cross-sectional METSIM study included 10 197 men, aged from 45 to 73 years, who were randomly selected from the population register of the Kuopio town in eastern Finland (population 95000). Every participant had a 1-day outpatient visit to the Clinical Research Unit at the University of Kuopio, including an interview on the history of previous diseases and current drug treatment and an evaluation of glucose tolerance and cardiovascular risk factors. After 12 h of fasting, a 2 h oral 75 g glucose tolerance test was performed and the blood samples were drawn at 0, 30 and 120 min. Plasma glucose was measured by enzymatic hexokinase photometric assay (Konelab Systems reagents; Thermo Fischer Scientific, Vantaa, Finland). Insulin was determined by immunoassay (ADVIA Centaur Insulin IRI no. 02230141; Siemens Medical Solutions Diagnostics, Tarrytown, NY, USA). Height and weight were measured to the nearest 0.5 cm and 0.1 kg, respectively. Waist circumference (at the midpoint between the lateral iliac crest and lowest rib) and hip circumference (at the level of the trochanter major) were measured to the nearest 0.5 cm. Body composition was determined by bioelectrical impedance (RJL Systems) in subjects in the supine position.
Genetic Regulation of Adipose Gene Expression and Cardio-Metabolic Traits.
Sex, Age, Specimen part
View SamplesThis SuperSeries is composed of the subseries listed below.
Analysis of independent microarray datasets of renal biopsies identifies a robust transcript signature of acute allograft rejection.
Sex, Age, Subject
View SamplesSpecific early diagnosis of renal allograft rejection is gaining importance in the current trend to minimize and individualize immunosuppression. Gene expression analyses could contribute significantly by defining molecular Banff signatures. Several previous studies have applied transcriptomics to distinguish different classes of kidney biopsies. However, the heterogeneity of microarray platforms, clinical samples and data analysis methods complicates the identification of robust signatures for the different types and grades of rejection. To address these issues, a comparative meta-analysis was performed across five different microarray datasets of heterogeneous sample collections from two published clinical datasets and three own datasets including biopsies for clinical indications, protocol biopsies, as well as comparative samples from non-human primates (NHP). This work identified conserved gene expression signatures that can differentiate groups with different histopathological findings in both human and NHP, regardless of the technical platform used. The marker panels comprise genes that clearly support the biological changes known to be involved in allograft rejection. A characteristic dynamic expression change of genes associated with immune and kidney functions was observed across samples with different grades of CAN. In addition, differences between human and NHP rejection were essentially limited to genes reflecting interstitial fibrosis progression. This data set comprises all renal allograft biopsies for clinical indications from patients at Hpital Tenon, Paris (February 2003 until September 2004) and few respective patients from Hpital Bictre, Paris, Hpital Pellegrin, Bordeaux, and Hpital Dupuytren, Limoges, plus control normal kidney samples from Hpital Tenon, Paris, France (first batch).
Analysis of independent microarray datasets of renal biopsies identifies a robust transcript signature of acute allograft rejection.
Subject
View SamplesSpecific early diagnosis of renal allograft rejection is gaining importance in the current trend to minimize and individualize immunosuppression. Gene expression analyses could contribute significantly by defining molecular Banff signatures. Several previous studies have applied transcriptomics to distinguish different classes of kidney biopsies. However, the heterogeneity of microarray platforms, clinical samples and data analysis methods complicates the identification of robust signatures for the different types and grades of rejection. To address these issues, a comparative meta-analysis was performed across five different microarray datasets of heterogeneous sample collections from two published clinical datasets and three own datasets including biopsies for clinical indications, protocol biopsies, as well as comparative samples from non-human primates (NHP). This work identified conserved gene expression signatures that can differentiate groups with different histopathological findings in both human and NHP, regardless of the technical platform used. The marker panels comprise genes that clearly support the biological changes known to be involved in allograft rejection. A characteristic dynamic expression change of genes associated with immune and kidney functions was observed across samples with different grades of CAN. In addition, differences between human and NHP rejection were essentially limited to genes reflecting interstitial fibrosis progression. This data set comprises all renal allograft biopsies for clinical indications from patients at Hpital Tenon, Paris (February 2003 until September 2004) and few respective patients from Hpital Bictre, Paris, Hpital Pellegrin, Bordeaux, and Hpital Dupuytren, Limoges, plus control normal kidney samples from Hpital Tenon, Paris, France (first batch).
Analysis of independent microarray datasets of renal biopsies identifies a robust transcript signature of acute allograft rejection.
Sex, Age, Subject
View SamplesWe performed an RNA-Seq analysis comparing thymic lymphoma tissues from the p53-null(n=2) and ?Np63?/?;p53-/- (n=3) or ?Np73?/?;p53-/-(n=3). Mice at 10 weeks of age were injected with either Ad-mCherry or Ad-CRE-mCherry to delete ?Np63/?Np73 in the thymic lmyphomas. We aimed to test by deleting the DNp63/DNp73 in these p53-deficient tumors will mediate tumor regression and analyze the expression profile of the genes Overall design: Examination of thymic lymphoma tissues in 3 different genotypes (p53-/- vs ?Np63?/?;p53-/- or ?Np73?/?;p53-/-)
IAPP-driven metabolic reprogramming induces regression of p53-deficient tumours in vivo.
No sample metadata fields
View SamplesElucidating the top of the mammary epithelial cell hierarchy is highly important for understanding its regeneration capabilities and identifying target cells for transformation. Aiming for enriched mammary epithelial stem cell population, CD200highCD200R1high epithelial cells were identified. These cells represent ~50% of the mammary repopulating units (MRUs, CD49fhigh CD24med ) and termed MRUCD200/CD200R1. Gene expression of these cells was compared to all other MRU cells, termed MRUnot CD200/CD200R1, as well as individual CD200+ population (MRU-CD200R1-) and CD200R1+ population (MRU-CD200-). Overall design: Gene expression from mammary epithelial cells carrying sorted by CD200, CD200R1 markers and MRU markers. Four populations were sequenced: MRU-positive CD200 positive and CD200R1 positive; MRU-positive and not CD200 positive CD200R1 positive; not MRU CD200 positive CD200R1 negative; not MRU CD200 negative CD200R1 positive. There are 5 replicates from 5 individual mice.
High Expression of CD200 and CD200R1 Distinguishes Stem and Progenitor Cell Populations within Mammary Repopulating Units.
Sex, Specimen part, Cell line, Subject
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