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GSE53403
Mus musculus
16 Downloadable Samples
Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
In mammals, expansion of adipose tissue mass induces accumulation of adipose tissue macrophages (ATMs). We isolated CD11c- (FB) and CD11c+ (FBC) perigonadal ATMs from SVCs of lean (C57BL/6J Lep +/+) and obese leptin-deficient (C57BL/6J Lep ob/ob) mice.
Publication Title
Obesity activates a program of lysosomal-dependent lipid metabolism in adipose tissue macrophages independently of classic activation.
Sample Metadata Fields
Specimen part
View Samples- Rattus norvegicus
- 18 Downloadable Samples
- Affymetrix Rat Gene 1.0 ST Array (ragene10st)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Reverse engineering a hierarchical regulatory network downstream of oncogenic KRAS.
Sample Metadata Fields
Cell line, Treatment
View Samples- Rattus norvegicus
- 16 Downloadable Samples
- Affymetrix Rat Gene 1.0 ST Array (ragene10st)
Description
RAS mutations are highly relevant for progression and therapy response of human tumours, but the genetic network that ultimately executes the oncogenic effects is poorly understood. Here we used a reverse-engineering approach in an ovarian cancer model to reconstruct KRAS oncogene-dependent cytoplasmic and transcriptional networks from perturbation experiments based on gene silencing and pathway inhibitor treatments. We measured mRNA and protein levels in manipulated cells by microarray, RT-PCR and Western Blot analysis, respectively. The reconstructed model revealed complex interactions among the transcriptional and cytoplasmic components, some of which were confirmed by double pertubation experiments. Interestingly, the transcription factors decomposed into two hierarchically arranged groups. To validate the model predictions we analysed growth parameters and transcriptional deregulation in the KRAS-transformed epithelial cells. As predicted by the model, we found two functional groups among the selected transcription factors. The experiments thus confirmed the predicted hierarchical transcription factor regulation and showed that the hierarchy manifests itself in downstream gene expression patterns and phenotype.
Publication Title
Reverse engineering a hierarchical regulatory network downstream of oncogenic KRAS.
Sample Metadata Fields
Cell line, Treatment
View Samples- Caenorhabditis elegans
- 8 Downloadable Samples
- Affymetrix C. elegans Genome Array (celegans)
Description
Lactoferrin is a highly multifunctional protein. Indeed, it is involved in many physiological functions, including regulation of iron absorption and immune responses.
Publication Title
A nutritional supplement containing lactoferrin stimulates the immune system, extends lifespan, and reduces amyloid <i>β</i> peptide toxicity in <i>Caenorhabditis elegans</i>.
Sample Metadata Fields
No sample metadata fields
View Samples- Rattus norvegicus
- 2 Downloadable Samples
Affymetrix Rat Gene 1.0 ST Array (ragene10st)
Description
RAS mutations are highly relevant for progression and therapy response of human tumours, but the genetic network that ultimately executes the oncogenic effects is poorly understood. Here we used a reverse-engineering approach in an ovarian cancer model to reconstruct KRAS oncogene-dependent cytoplasmic and transcriptional networks from perturbation experiments based on gene silencing and pathway inhibitor treatments. We measured mRNA and protein levels in manipulated cells by microarray, RT-PCR and Western Blot analysis, respectively. The reconstructed model revealed complex interactions among the transcriptional and cytoplasmic components, some of which were confirmed by double pertubation experiments. Interestingly, the transcription factors decomposed into two hierarchically arranged groups. To validate the model predictions we analysed growth parameters and transcriptional deregulation in the KRAS-transformed epithelial cells. As predicted by the model, we found two functional groups among the selected transcription factors. The experiments thus confirmed the predicted hierarchical transcription factor regulation and showed that the hierarchy manifests itself in downstream gene expression patterns and phenotype.
Publication Title
Reverse engineering a hierarchical regulatory network downstream of oncogenic KRAS.
Sample Metadata Fields
Cell line, Treatment
View Samples- Homo sapiens
- 20 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
In osteosarcoma patients, the development of metastases, often to the lungs, is the most frequent cause of death. To improve this situation, a deeper understanding of the molecular mechanisms governing osteosarcoma development and dissemination and the identification of novel drug targets for an improved treatment are needed. Towards this aim, we characterized osteosarcoma tissue samples compared to primary osteoblast cells using Affymetrix HG U133A microarrays.
Publication Title
De novo expression of EphA2 in osteosarcoma modulates activation of the mitogenic signalling pathway.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 8 Downloadable Samples
Illumina HiSeq 2500
Description
Goals of the study was to compare transcripional and phenotypic response of mouse intestinal organoid cultures to the PIK3CA(H1047R) and CTNNB1(stab) oncogenes. Overall design: Two biological replicates of organoids with transgenic tdTomato-Luciferase, tdTomato-PIK3CAH1047R, tdTomato-CTNNB1stab or td-Tomato-PIK3CAH1047R-CTNNB1stab were analysed by RNA-Seq By comparing 7-10 x 10E7 50bp paired end reads per library we identify transcriptional alterations in the intestinal epithelium following expression of each or both oncogenes,
Publication Title
Oncogenic β-catenin and PIK3CA instruct network states and cancer phenotypes in intestinal organoids.
Sample Metadata Fields
Specimen part, Cell line, Subject
View Samples- Homo sapiens
- 195 Downloadable Samples
- Affymetrix Human Genome U219 Array (hgu219)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Combination of Gene Expression Signature and Model for End-Stage Liver Disease Score Predicts Survival of Patients With Severe Alcoholic Hepatitis.
Sample Metadata Fields
Specimen part, Disease
View Samples- Homo sapiens
- 86 Downloadable Samples
- Affymetrix Human Genome U219 Array (hgu219)
Description
Corticosteroids are the current standard of care to improve short-term mortality in severe alcoholic hepatitis (AH), although nearly 40% of the patients do not respond and accurate pre-treatment predictors are lacking. We developed 123-gene prognostic score based on molecular and clinical variables before initiation of corticosteroids. Furthermore, The gene signature was implemented in an FDA-approved platform (NanoString), and verified for technical validity and prognostic capability. Here we demonstrated that a Nanostring-based gene expressoin risk classification is useful to predict mortality in patients with severe alcoholic hepatitis who were treated by corticosteroid
Publication Title
Combination of Gene Expression Signature and Model for End-Stage Liver Disease Score Predicts Survival of Patients With Severe Alcoholic Hepatitis.
Sample Metadata Fields
Specimen part, Disease
View Samples- Homo sapiens
- 71 Downloadable Samples
- Affymetrix Human Genome U219 Array (hgu219)
Description
Corticosteroids are the current standard of care to improve short-term mortality in severe alcoholic hepatitis (AH), although nearly 40% of the patients do not respond and accurate pre-treatment predictors are lacking. We developed 123-gene prognostic score based on molecular and clinical variables before initiation of corticosteroids. Furthermore, The gene signature was implemented in an FDA-approved platform (NanoString), and verified for technical validity and prognostic capability. Here we demonstrated that a Nanostring-based gene expressoin risk classificatoin is useful to predict mortality in patients with severe alcoholic hepatitis who were treated by corticosteroid
Publication Title
Combination of Gene Expression Signature and Model for End-Stage Liver Disease Score Predicts Survival of Patients With Severe Alcoholic Hepatitis.
Sample Metadata Fields
No sample metadata fields
View Samples