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GSE25913
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
- 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- Mus musculus
- 3 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
Brain development requires a massive increase in brain lipogenesis and accretion of the essential omega-3 fatty acid docosahexaenoic acid (DHA). Brain acquisition of DHA is primarily mediated by the transporter Major Facilitator Superfamily Domain containing 2a (Mfsd2a) expressed in the endothelium of the blood-brain barrier. Mfsd2a transports DHA and other polyunsaturated fatty acids esterified to lysophosphatidylcholine (LPC-DHA). However, the function of Mfsd2a and DHA in brain development is incompletely understood. Using vascular endothelial-specific (2aECKO) and inducible vascular endothelial-specific (2aiECKO) deletion of Mfsd2a in mice, we found Mfsd2a to be uniquely required postnatally at the blood-brain barrier for normal brain growth and DHA accretion, with DHA deficiency preceding the onset of microcephaly. Gene expression profiling analysis of these DHA deficient brains indicated that Srebp-1 and Srebp-2 pathways were highly elevated.
Publication Title
The lysolipid transporter Mfsd2a regulates lipogenesis in the developing brain.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 12 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
Gene regulation at the maternal-embryonic transition in the pre-implantation mouse embryo is not well understood. We knock down Ccna2 to establish proof-of-concept that antisense morpholino oligonucleotides can be used to target specific genes. We applied this strategy to study Oct4 and discovered that Oct4 is required prior to blastocyst development. Specifically, gene expression is altered as early as the 2-cell stage in Oct4-knockdown embryos.
Publication Title
A novel and critical role for Oct4 as a regulator of the maternal-embryonic transition.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus, Homo sapiens
- 6 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Orchestrated intron retention regulates normal granulocyte differentiation.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 6 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
Using mRNA-seq, we determined intron retaining genes that were differentially regulated in FACS purified cells at three progressive stages of mouse granulopoiesis; CD34+Kit+Gr-1low promyelocytes, CD34-Kit-Gr-1mid myelocytes and CD34-Kit-Gr-1high granulocytes. We found that IR affects 86 genes, including those specific to granulocyte (Lyz2 and MMP8) and nuclear architecture (Lmnb1 and Lbr). IR was associated with the decrease in protein levels measured by mass spectrometry (P=0.0015, binomial test). Inhibition of NMD in granulocytes resulted in marked accumulation of 39/86 intron retaining mRNAs (P<0.05, RUV procedure with Holm-Bonferroni correction), indicating that IR triggers NMD to downregulate mRNA and protein expression.
Publication Title
Orchestrated intron retention regulates normal granulocyte differentiation.
Sample Metadata Fields
Specimen part
View Samples- Danio rerio
- 16 Downloadable Samples
IlluminaGenomeAnalyzerIIx
Description
Zebrafish is a model system being used in a variety of basic research and biomedical studies. Understanding the neurotranscriptomic architecture will greatly facilitate and enhance interpretation of research projects. Studies have reported that there are strain and sex-specific behavioral variation particulary in response to stress and anxiety-inducing scenarios. Capitalizing on previously documented behavioral variation by strains and sex of zebrafish, this study seeks to understand the neurotranscriptomic mechanisms potentially underlying this variation. Through RNA-sequencing (4 biological replicates per strain further subdivided into 2 biological replicates per sex) we analyzed the whole-brain transcriptomic profiles of four strains of zebrafish and relate transcriptional differences to phenotypic differences (e.g. behavioral or morphological) of the strains. Using a balanced block design, all 16 samples were multiplexed and run across 16 lanes on an Illumina GAIIx. Resulting reads (approximately 52 million reads per biological replicate) were aligned to the Zv9 genome build. We subsequently performed differential gene expression analysis and weighted gene coexpression network analysis to identify genes and gene networks associated with a phenotype. The goal of the study is to identify neurotranscriptomic mechanisms underlying phenotypic (e.g. morphological, behavioral) variation in zebrafish. Overall design: Through RNA-sequencing we quantified whole-brain transcriptome levels of protein-coding genes for four strains of zebrafish (AB, Scientific Hatcheries, High Stationary Behavior, and Low Stationary Behavior). Each line has 4 biological replicates (2 biological replicates for each sex). Each biological replicate is comprised of a pool of 10 same-sex and age-matched individuals. Using a balanced block design, the samples were mulitplexed and run across 16 lanes on an Illumina GAIIx. Reads that passed default quality control filters were aligned using GSNAP and quantified with HTSEQ. We used edgeR and WGCNA for subsequent differential gene expression and network analyses. qRT–PCR validation was performed using SYBR Green assays
Publication Title
Neurotranscriptome profiles of multiple zebrafish strains.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 68 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
A gene signature predictive for outcome in advanced ovarian cancer identifies a survival factor: microfibril-associated glycoprotein 2.
Sample Metadata Fields
Specimen part, Disease stage, Cell line, Treatment
View Samples- Homo sapiens
- 56 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
To demonstrate the use of a whole-genome oligonucleotide array to perform expression profiling on a series of microdissected late-stage, high-grade papillary serous ovarian adenocarcinomas to establish a prognostic gene signature correlating with survival and to identify novel survival factors in ovarian cancer.
Publication Title
A gene signature predictive for outcome in advanced ovarian cancer identifies a survival factor: microfibril-associated glycoprotein 2.
Sample Metadata Fields
Specimen part, Disease stage
View Samples- Homo sapiens
- 12 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Identification of signaling events contributing to the effect of recombinant MAGP2 on HUVECs and OVCA429. We used microarrays to identify the signaling events and up-regulated genes associated with MAGP2.
Publication Title
A gene signature predictive for outcome in advanced ovarian cancer identifies a survival factor: microfibril-associated glycoprotein 2.
Sample Metadata Fields
Cell line, Treatment
View Samples