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GSE9631
Mus musculus
16 Downloadable Samples
Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)
Description
Androgens have been postulated to be important modulators of adipose tissue metabolism and fat cell function. In the present study, we investigated the response of male and female mice retroperitoneal adipose tissue to the non-aromatizable androgen dihydrotestosterone (DHT). Adipose tissue samples were obtained in gonadectomized (GDX) animals treated with vehicle (control group), or injected with 0.1mg DHT at 1, 3, 6, 12, 18 and 24h prior to necropsy. Transcripts which were significantly modulated were considered as androgen-responsive genes. Quantitative real-time RT-PCR was used to confirm results from the microarry analysis in a subset of 46 probe sets in male mice and 98 probe sets in female mice. Using both methods and considering peak time versus control, 74.5% and 61.2% of the modulated genes were confirmed by PCR in males and females, respectively. Four genes were significantly stimulated in a similar manner by DHT in both sexes, namely metallothionein 1 (Mt1), growth arrest and DNA-damage-inducible 45 gamma (Gadd45g), cyclin-dependent kinase inhibitor 1A (Cdkn1a), and fk506-binding protein 5 (Fkbp5). All these genes appear to be associated with a down-regulation of adipocyte differentiation/proliferation and adipogenesis. In conclusion, this study which evaluated the transcriptome response of adipose tissue to DHT in male and female mice suggests that DHT consistently modulates genes involved in the regulation of adipogenesis in retroperitoneal adipose tissue of both male and female animals.
Publication Title
Response of the adipose tissue transcriptome to dihydrotestosterone in mice.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 38 Downloadable Samples
Illumina HiSeq 2500
Description
The primary objective of the study was to investigate the uncoupling protein-1 (UCP1) associated features of human epicardial adipose tissue (eAT) using next generation deep sequencing. In addition, paired mediastinal adipose tissue (mAT) and subcutaneous adipose tissue (sAT) samples colleced from patients undergoing cardic surgeries at our center were included in the study. Overall design: Paired biopsies of eAT, mAT and sAT obtained from cardiac surgery patients (n=10), with specific criteria of high- and low- expression of UCP1 in eAT, were subjected to RNA sequencing. While the primary objective was to compare high- vs. low UCP1 expression in eAT, our study design further allowed us to investigate depot- and disease specific transcriptomic shifts in these patients. Specifically, 10 patients provided 30 samples (n = 10 each for eAT, mAT and sAT) that could be compared based on depot specificity (n = 10), obesity (n = 5 lean, n = 5 obese) and coronary artery disease (CAD) (n = 6 CAD, 4 = Non-CAD).
Publication Title
UCP1 expression-associated gene signatures of human epicardial adipose tissue.
Sample Metadata Fields
Disease, Disease stage, Subject
View Samples- Homo sapiens
- 4 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Activation of glycolytic genes by HIF-1 is considered critical for metabolic adaptation to hypoxia. We found that HIF-1 also actively suppresses glucose metabolism through the tricarboxylic acid cycle (TCA) by directly trans-activating the gene encoding pyruvate dehydrogenase kinase 1 (PDK1). PDK1 inactivates the TCA cycle enzyme, pyruvate dehydrogenase (PDH), which converts pyruvate to acetyl-CoA. Forced PDK1 expression in hypoxic HIF-1-null cells increases ATP levels, attenuates hypoxic ROS generation and rescues these cells from hypoxia-induced apoptosis. These studies reveal a novel hypoxia-induced metabolic switch that shunts glucose metabolites from the mitochondria to glycolysis to maintain ATP production and to prevent toxic ROS production.
Publication Title
HIF-1-mediated expression of pyruvate dehydrogenase kinase: a metabolic switch required for cellular adaptation to hypoxia.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 19 Downloadable Samples
Affymetrix Human Genome U95 Version 2 Array (hgu95av2), Affymetrix Human Genome U133A Array (hgu133a)
Description
Reliable clinical tests for predicting cancer chemotherapy response are not available and individual markers failed to correctly predict resistance against anticancer agents. We hypothesized that gene expression patterns attributable to chemotherapy-resistant cells can be used as a classification tool for chemoresistance and provide novel candidate genes involved in anthracycline resistance mechanisms. We contrasted the expression profiles of 4 different human tumor cell lines of gastric, pancreatic, colon and breast origin and of their counterparts resistant to the topoisomerase inhibitors daunorubicin or doxorubicin. We also profiled the sensitive parental cells treated with doxorubicin for 24h. We interrogated Affymetrix HGU133A and U95A arrays independently. We applied two independent methods for data normalization and used Prediction Analysis of Microarrays (PAM) for feature selection. In addition, we established data sets related to drug resistance by using a virtual array composed of features represented on both types of oligonucleotide arrays. We identified 71 candidate genes associated with doxorubicine/daunorubicine resistance. To validate the microarray data, we also analyzed the expression of 12 selected genes by quantitative RT-PCR or immunocytochemistry, respectively. While the comparison of drug-sensitive versus drug-resistant cells yields candidates associated with drug resistance, the 24h treatment of sensitive parental cells produced a distinct transcriptional profile related to short-term drug effects.
Publication Title
PSMB7 is associated with anthracycline resistance and is a prognostic biomarker in breast cancer.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 12 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Reliable clinical tests for predicting cancer chemotherapy response are not available and individual markers failed to correctly predict resistance against anticancer agents. We hypothesized that gene expression patterns attributable to chemotherapy-resistant cells can be used as a classification tool for chemoresistance and provide novel candidate genes involved in anthracycline resistance mechanisms. We contrasted the expression profiles of 4 different human tumor cell lines of gastric, pancreatic, colon and breast origin and of their counterparts resistant to the topoisomerase inhibitors daunorubicin or doxorubicin. We also profiled the sensitive parental cells treated with doxorubicin for 24h. We interrogated Affymetrix HGU133A and U95A arrays independently. We applied two independent methods for data normalization and used Prediction Analysis of Microarrays (PAM) for feature selection. In addition, we established data sets related to drug resistance by using a virtual array composed of features represented on both types of oligonucleotide arrays. We identified 71 candidate genes associated with doxorubicine/daunorubicine resistance. To validate the microarray data, we also analyzed the expression of 12 selected genes by quantitative RT-PCR or immunocytochemistry, respectively. While the comparison of drug-sensitive versus drug-resistant cells yields candidates associated with drug resistance, the 24h treatment of sensitive parental cells produced a distinct transcriptional profile related to short-term drug effects.
Publication Title
PSMB7 is associated with anthracycline resistance and is a prognostic biomarker in breast cancer.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 7 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a), Affymetrix Human Genome U95 Version 2 Array (hgu95av2)
Description
Reliable clinical tests for predicting cancer chemotherapy response are not available and individual markers failed to correctly predict resistance against anticancer agents. We hypothesized that gene expression patterns attributable to chemotherapy-resistant cells can be used as a classification tool for chemoresistance and provide novel candidate genes involved in anthracycline resistance mechanisms. We contrasted the expression profiles of 4 different human tumor cell lines of gastric, pancreatic, colon and breast origin and of their counterparts resistant to the topoisomerase inhibitors daunorubicin or doxorubicin. We also profiled the sensitive parental cells treated with doxorubicin for 24h. We interrogated Affymetrix HGU133A and U95A arrays independently. We applied two independent methods for data normalization and used Prediction Analysis of Microarrays (PAM) for feature selection. In addition, we established data sets related to drug resistance by using a virtual array composed of features represented on both types of oligonucleotide arrays. We identified 71 candidate genes associated with doxorubicine/daunorubicine resistance. To validate the microarray data, we also analyzed the expression of 12 selected genes by quantitative RT-PCR or immunocytochemistry, respectively. While the comparison of drug-sensitive versus drug-resistant cells yields candidates associated with drug resistance, the 24h treatment of sensitive parental cells produced a distinct transcriptional profile related to short-term drug effects.
Publication Title
PSMB7 is associated with anthracycline resistance and is a prognostic biomarker in breast cancer.
Sample Metadata Fields
No sample metadata fields
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- 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
- 10 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Novel fluorescence-activated cell sorting (FACS) strategies to prospectively purify functionally distinct cell populations from the human myofiber-associated (hMFA) cell compartment, including human Skeletal Muscle Precursor cells (hSMPs):
Publication Title
Isolation of progenitors that exhibit myogenic/osteogenic bipotency in vitro by fluorescence-activated cell sorting from human fetal muscle.
Sample Metadata Fields
No sample metadata fields
View Samples