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GSE52081
Homo sapiens
9 Downloadable Samples
Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
The physiological function of the immune system and the response to therapeutic immunomodulators may be sensitive to combinatorial cytokine micro-environments that shape the responses of specific immune cells. Previous work shows that paracrine cytokines released by virus-infected human dendritic cells (DC) can dictate the maturation state of nave DCs. To understand the effects of paracrine signaling, we systematically studied the effects of combinations cytokines in this complex mixture in generating an antiviral state. After nave DCs were exposed to either IFN or to paracrine signaling released by DCs infected by Newcastle Disease Virus (NDV), microarray analysis revealed a large number of genes that were differently regulated by the DC-secreted paracrine signaling. In order to identify the cytokine mechanisms involved, we identified 20 cytokines secreted by NDV infected DCs for which the corresponding receptor gene is expressed in nave DCs. By exposing cells to all combinations of 19 cytokines (leave-one-out studies) we identified 5 cytokines (IFN, TNF, IL-1, TNFSF15 and IL28) as candidates for regulating DC maturation markers. Subsequent experiments identified IFN, TNF and IL1 as the major synergistic contributors to this antiviral state. This finding was supported by infection studies in vitro, by T cell activation studies and by in vivo infection studies in mouse. Combination of cytokines can cause response states in DCs that differ from those achieved by the individual cytokines alone. These results suggest that the cytokine microenvironment may act via a combinatorial code to direct the response state of specific immune cells. Further elucidation of this code may provide insight into responses to infection and neoplasia as well as guide the development of combinatorial cytokine immunomodulation for infectious, autoimmune and immunosurveillance-related diseases.
Publication Title
Combinatorial cytokine code generates anti-viral state in dendritic cells.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 6 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
We used microarray to characterize interferon stimulated genes in dendritic cells
Publication Title
Comparative analysis of anti-viral transcriptomics reveals novel effects of influenza immune antagonism.
Sample Metadata Fields
Specimen part
View Samples- Drosophila melanogaster
- 5 Downloadable Samples
- Affymetrix Drosophila Genome 2.0 Array (drosophila2)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
The MOF-containing NSL complex associates globally with housekeeping genes, but activates only a defined subset.
Sample Metadata Fields
Sex, Specimen part, Cell line
View Samples- Drosophila melanogaster
- 5 Downloadable Samples
- Affymetrix Drosophila Genome 2.0 Array (drosophila2)
Description
The MOF-containing NSL complex binds to many but not all promoters of active genes and potentially contributes to their proper gene expression. It is currently unknown what determines whether an active gene is bound or not. Here, we provide evidence that the NSL complex primarily targets active promoters of most housekeeping genes. There, it co-localizes with the chromatin remodeler NURF and the histone methyltransferase Trithorax. Moreover, despite binding to most housekeeping genes, the NSL complex regulates only a subset of them, which are depleted for certain insulator binding-proteins and enriched for the core promoter motif Ohler 5. We suggest that the combination of general chromatin factors and core promoter motifs is predictive for whether a housekeeping gene is transcriptionally regulated by the NSL complex.
Publication Title
The MOF-containing NSL complex associates globally with housekeeping genes, but activates only a defined subset.
Sample Metadata Fields
Cell line
View Samples- Mus musculus
- 38 Downloadable Samples
- Illumina MouseWG-6 v2.0 expression beadchip
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Protein sets define disease states and predict in vivo effects of drug treatment.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Homo sapiens
- 24 Downloadable Samples
- Affymetrix Human Genome U133B Array (hgu133b), Affymetrix Human Genome U133A Array (hgu133a)
Description
Alzheimer's disease (AD) is characterized by massive neurodegeneration and multiple changes in cellular processes, including neurogenesis. Proteolytic processing of the amyloid precursor protein (APP) plays a central role in AD. Due to varying APP processing, several beta-amyloid peptides are generated. In contrast to the form with 40 amino acids, the variant with 42 amino acids is thought to be the pathogenic form triggering the pathophysiological cascade in AD. Here, we studied the transcriptomic response to increased or decreased Abeta42 levels generated in human neuroblastoma cells. Genome-wide expression profiles (Affymetrix)were used to analyze the cellular response to the changed Abeta42 and Abeta40-levels. <br></br><br></br>Human neuroblastoma cell line SH-SY5Y is a thrice cloned (SK-N-SH -> SH-SY -> SH-SY5 -> SH-SY5Y) subline of the neuroblastoma cell line SK-N-SH which was isolated and established in 1970. This cell line has 47 chromosomes. The cells possess a unique marker comprised of a chromosome 1 with a complex insertion of an additional copy of a 1q segment into the long arm, resulting in trisomy of 1q. The cell lines used in this study are SHSY5Y transfected with the constructs pCEP-C99I45F, pCEP-C99V50F, pCEP-C99 wildtype or mock transfected with an empty vector. Independent cell clones of each transfected line were used to provide biological replicates.<br></br> Overexpressed C99 I45F is intracellularly cleaved resulting in high Abeta42, but low Abeta40 levels.<br></br> Overexpressed C99V50F is intracellularly cleaved resulting in low Abeta42, but high Abeta40 levels.<br></br>Overexpressed C99 wildtype is intracellularly cleaved resulting in medium Abeta42 and Abeta40 levels<br></br>Mock is the SHSY5Y cell line transfected with the empty vector pCEP (Invitrogen) as a negative control
Publication Title
New Alzheimer amyloid beta responsive genes identified in human neuroblastoma cells by hierarchical clustering.
Sample Metadata Fields
Cell line, Subject
View Samples- Homo sapiens
- 18 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
In the marrow and lymphatic tissues, chronic lymphocytic leukemia (CLL) cells interact with accessory cells that constitute the leukemia microenvironment. In lymphatic tissues, CLL cells are interspersed with CD68+ nurselike cells (NLC) and T cells. However, the mechanism regulating co-localization of CLL cells and these accessory cells are largely unknown. To dissect the molecular cross-talk between CLL and NLC, we profiled the gene expression of CD19-purified CLL cells before and after co-culture with NLC. NLC co-culture induced high-level expression of B cell maturation antigen (BCMA) and two chemoattractants (CCL3, CCL4) by CLL cells. Supernatants from CLL-NLC co-cultures revealed high CCL3/CCL4 protein levels. B cell receptor triggering also induced a robust induction of CCL3 and CCL4 expression by CLL cells, which was almost completely abrogated by a specific Syc inhibitor, R406. High CCL3 and CCL4 plasma levels in CLL patients suggest that activation of this pathway plays a role in vivo. These studies reveal a novel mechanism of cross-talk between CLL cells and their microenvironment, namely the secretion of two T cell chemokines by CLL-NLC interaction and in response to BCR stimulation. Through these chemokines, CLL cells can recruit accessory cells, and thereby actively create a microenvironment that favors their growth and survival.
Publication Title
High-level expression of the T-cell chemokines CCL3 and CCL4 by chronic lymphocytic leukemia B cells in nurselike cell cocultures and after BCR stimulation.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 15 Downloadable Samples
- Illumina MouseWG-6 v2.0 expression beadchip
Description
Gaining understanding of common complex diseases and their treatments are the main drivers for life sciences. As we show here, comprehensive protein set analyses offer new opportunities to decipher functional molecular networks of diseases and assess the efficacy and side-effects of treatments in vivo. Using mass spectrometry, we quantitatively detected several thousands of proteins and observed significant changes in protein pathways that were (dys-) regulated in diet-induced obesity mice. Analysis of the expression and post-translational modifications of proteins in various peripheral metabolic target tissues including adipose, heart, and liver tissue generated functional insights in the regulation of cell and tissue homeostasis during high-fat diet feeding and medication with two antidiabetic compounds. Protein set analyses singled out pathways for functional characterization, and indicated, for example, early-on potential cardiovascular complication of the diabetes drug rosiglitazone. In vivo protein set detection can provide new avenues for monitoring complex disease processes, and for evaluating preclinical drug candidates.
Publication Title
Protein sets define disease states and predict in vivo effects of drug treatment.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Mus musculus
- 11 Downloadable Samples
- Illumina MouseWG-6 v2.0 expression beadchip
Description
Gaining understanding of common complex diseases and their treatments are the main drivers for life sciences. As we show here, comprehensive protein set analyses offer new opportunities to decipher functional molecular networks of diseases and assess the efficacy and side-effects of treatments in vivo. Using mass spectrometry, we quantitatively detected several thousands of proteins and observed significant changes in protein pathways that were (dys-) regulated in diet-induced obesity mice. Analysis of the expression and post-translational modifications of proteins in various peripheral metabolic target tissues including adipose, heart, and liver tissue generated functional insights in the regulation of cell and tissue homeostasis during high-fat diet feeding and medication with two antidiabetic compounds. Protein set analyses singled out pathways for functional characterization, and indicated, for example, early-on potential cardiovascular complication of the diabetes drug rosiglitazone. In vivo protein set detection can provide new avenues for monitoring complex disease processes, and for evaluating preclinical drug candidates.
Publication Title
Protein sets define disease states and predict in vivo effects of drug treatment.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Mus musculus
- 2 Downloadable Samples
- Illumina MouseWG-6 v2.0 expression beadchip
Description
Gaining understanding of common complex diseases and their treatments are the main drivers for life sciences. As we show here, comprehensive protein set analyses offer new opportunities to decipher functional molecular networks of diseases and assess the efficacy and side-effects of treatments in vivo. Using mass spectrometry, we quantitatively detected several thousands of proteins and observed significant changes in protein pathways that were (dys-) regulated in diet-induced obesity mice. Analysis of the expression and post-translational modifications of proteins in various peripheral metabolic target tissues including adipose, heart, and liver tissue generated functional insights in the regulation of cell and tissue homeostasis during high-fat diet feeding and medication with two antidiabetic compounds. Protein set analyses singled out pathways for functional characterization, and indicated, for example, early-on potential cardiovascular complication of the diabetes drug rosiglitazone. In vivo protein set detection can provide new avenues for monitoring complex disease processes, and for evaluating preclinical drug candidates.
Publication Title
Protein sets define disease states and predict in vivo effects of drug treatment.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples