Filters
Technology
Platform
GSE44148
Drosophila melanogaster
10 Downloadable Samples
Affymetrix Drosophila Genome 2.0 Array (drosophila2)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Drosophila H1 regulates the genetic activity of heterochromatin by recruitment of Su(var)3-9.
Sample Metadata Fields
Specimen part
View Samples- Drosophila melanogaster
- 10 Downloadable Samples
- Affymetrix Drosophila Genome 2.0 Array (drosophila2)
Description
Indicated cells were subjected to RNAi against linker histone H1, Nautilus (control), or GFP (control). RNA was isolated and subjected to Affymetrix GeneChIP Drosophila Genome 2.0 arrays
Publication Title
Drosophila H1 regulates the genetic activity of heterochromatin by recruitment of Su(var)3-9.
Sample Metadata Fields
Specimen part
View Samples- Drosophila melanogaster
- 4 Downloadable Samples
Illumina Genome Analyzer II
Description
Salivary glands or larval ovaries were isolated from transgenic flies expressing RNAi targeting Nautilus (control) or linker histone H1 using a Tub-Gal4 driver. Overall design: ~200 larvae were used to isolate salivary glands or ovaries, independently. Total RNA was isolated using Trizol reagent following manufacturer''s guidelines. Then 5 µg of total RNA was separated on a polyacrylamide gel, and 18-29 nt small RNAs were isolated for cloning.
Publication Title
Drosophila H1 regulates the genetic activity of heterochromatin by recruitment of Su(var)3-9.
Sample Metadata Fields
Specimen part, Subject
View Samples- Mus musculus
- 4 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
A core erythroid transcriptional network is repressed by a master regulator of myelo-lymphoid differentiation.
Sample Metadata Fields
Specimen part, Cell line
View Samples- Mus musculus
- 4 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
We compared the transcriptomes of differentiating cultures of ES cell derived erythroid progentor cells (ES-EP) and murine erythroleukemia (MEL) cells stably transfected with GATA-1 fused to ER.
Publication Title
A core erythroid transcriptional network is repressed by a master regulator of myelo-lymphoid differentiation.
Sample Metadata Fields
Specimen part, Cell line
View Samples- Mus musculus
- 4 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
A large gene network in immature erythroid cells is controlled by the myeloid and B cell transcriptional regulator PU.1.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 4 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
We compared the transcriptomes of ES cell derived erythroid progentor cells (ES-EP) and murine erythroleukemia (MEL) cells stably transfected with Gata-1 fused to ER.
Publication Title
A large gene network in immature erythroid cells is controlled by the myeloid and B cell transcriptional regulator PU.1.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 24 Downloadable Samples
- Illumina human-6 v2.0 expression beadchip
Description
The new official nomenclature subdivides human monocytes into three subsets, classical (CD14++CD16-), intermediate (CD14++CD16+) and nonclassical (CD14+CD16+). Here, we comprehensively define relationships and unique characteristics of the three human monocyte subsets using microarray and flow cytometry analysis. Our analysis revealed that the intermediate and nonclassical monocyte subsets were most closely related. For the intermediate subset, majority of genes and surface markers were expressed at an intermediary level between the classical and nonclassical subset. There features therefore indicate a close and direct lineage relationship between the intermediate and nonclassical subset. From gene expression profiles, we define unique characteristics for each monocyte subset. Classical monocytes were functionally versatile, due to the expression of a wide range of sensing receptors and several members of the AP-1 transcription factor family. The intermediate subset was distinguished by high expression of MHC class II associated genes. The nonclassical subset were most highly differentiated and defined by genes involved in cytoskeleton rearrangement that explains their highly motile patrolling behavior in vivo. Additionally, we identify unique surface markers, CLEC4D, IL-13RA1 for classical, GFRA2, CLEC10A for intermediate and GPR44 for nonclassical. Our study hence defines the fundamental features of monocyte subsets necessary for future research on monocyte heterogeneity.
Publication Title
Gene expression profiling reveals the defining features of the classical, intermediate, and nonclassical human monocyte subsets.
Sample Metadata Fields
Specimen part, Subject
View Samples- Homo sapiens
- 12 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
Fusion of the EWS gene to FLI1 produces a fusion oncoprotein that drives an aberrant gene expression program responsible for the development of Ewing sarcoma. We used a homogenous proximity assay to screen for compounds that disrupt the binding of EWS-FLI1 to its cognate DNA targets. A number of DNA-binding chemotherapeutic agents were found to non-specifically disrupt protein binding to DNA. In contrast, actinomycin D was found to preferentially disrupt EWS-FLI1 binding by comparison to p53 binding to their respective cognate DNA targets in vitro. In cell-based assays, low concentrations of actinomycin preferentially blocked EWS-FLI1 binding to chromatin, and disrupted EWS-FLI1-mediated gene expression. Higher concentrations of actinomycin globally repressed transcription. These results demonstrate that actinomycin preferentially disrupts EWS-FLI1 binding to DNA at selected concentrations. Although the window between this preferential effect and global suppression is too narrow to exploit in a therapeutic manner, these results suggest that base-preferences may be exploited to find DNA-binding compounds that preferentially disrupt subclasses of transcription factors.
Publication Title
Differential disruption of EWS-FLI1 binding by DNA-binding agents.
Sample Metadata Fields
Cell line, Treatment
View Samples- Homo sapiens
- 51 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Gene Expression Profiling of Breast Cancer Patients with Brain Metastases Brain metastases confer the worst prognosis of breast cancer as no therapy exists that prevents or eliminates the cancer from spreading to the brain. We developed a new computational modeling method to derive specific downstream signaling pathways that reveal unknown target-disease connections and new mechanisms for specific cancer subtypes. The model enables us to reposition drugs based on available gene expression data of patients. We applied this model to repurpose known or shelved drugs for brain, lung, and bone metastases of breast cancer with the hypothesis that cancer subtypes have their own specific signaling mechanisms. To test the hypothesis, we addressed the specific CSBs for each metastasis that satisfy that (1) CSB proteins are activated by the maximal number of enriched signaling pathways specific to this metastasis, and (2) CSB proteins involve in the most differential expressed coding-genes specific to the specific breast cancer metastasis. The identified signaling networks for the three types of metastases contain 31, 15, and 18 proteins, respectively, and are used to reposition 15, 9, and 2 drug candidates for the brain, lung, and bone metastases of breast cancer. We performed in vitro and in vivo preclinical experiments as well as analysis on patient tumor specimens to evaluate the targets and repositioned drugs. Two known drugs, Sunitinib (FDA approved for renal cell carcinoma and imatinib-resistant gastrointestinal stromal tumor) and Dasatinib (FDA approved for chronic myelogenous leukemia (CML) after imatinib treatment and Philadelphia chromosome-positive acute lymphoblastic leukemia), were shown to prohibit the metastatic colonization in brain.
Publication Title
Novel modeling of cancer cell signaling pathways enables systematic drug repositioning for distinct breast cancer metastases.
Sample Metadata Fields
Time
View Samples