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accession-icon GSE50741
Transcriptional analysis of sweet orange in response to TAL effector-dependent infection
  • organism-icon Citrus sinensis
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Citrus Genome Array (citrus)

Description

We used this microarray data to survey the differentially expressed genes in sweet orange by comparing leaves challenged with X. citri ssp. citri (Xcc) strain 306 with the pthA4 gene and leaves challenged with mutant Xcc306pthA4 without the pthA4 gene 120 hours after inoculation. The deletion of the pthA4 gene reduced the virulence of Xcc306, and eliminated pustule formation. The gene expression changes after inoculation of these two strains represent PthA4-mediated molecular events in a susceptible reaction.

Publication Title

Lateral organ boundaries 1 is a disease susceptibility gene for citrus bacterial canker disease.

Sample Metadata Fields

Specimen part, Treatment, Time

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accession-icon GSE54280
Comparative gene array analysis of progenitor cells from deep neck and subcutaneous adipose tissue
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Expression profiling of progenitor cells from human supraclavicular and subcutaneous adipose tissue. Studies in animal models revealed that brown and white adipocytes derive from different progenitor cells. Molecular characteristics of these cells have not been investigated in detail in humans.

Publication Title

Comparative gene array analysis of progenitor cells from human paired deep neck and subcutaneous adipose tissue.

Sample Metadata Fields

Sex, Age

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accession-icon GSE57463
SOX9 overexpression in melanoma
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

SOX9 is generally not expressed in melanomas with a high proliferative capacity but is expressed in melanomas with a high invasive capacity. Here we overexpress full length SOX9 in M010817, a melanoma cell culture with high proliferative capacity but low invasive capacity.

Publication Title

Methylation-dependent SOX9 expression mediates invasion in human melanoma cells and is a negative prognostic factor in advanced melanoma.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE6291
Transcriptome Analysis Multipotent Adult Progenitor Cells (Affy)
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

We compare the transcriptome of two different clones of multipotent adult progenitor cells (MAPCs) using Affymetrix arrays.

Publication Title

Hematopoietic reconstitution by multipotent adult progenitor cells: precursors to long-term hematopoietic stem cells.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE4671
Microarray Analysis of the Delipidation of White Adipose Tissue of Mice Fed Conjugated Linoleic Acid
  • organism-icon Mus musculus
  • sample-icon 28 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The white adipose tissue (WAT) rapidly loses mass when mice are fed a diet containing trans-10, cis-12 conjugated linoleic acid (t10c12 CLA). A microarray analysis of WAT due to CLA feeding was performed to better define the processes and genes involved. WAT weight decreased by ca. 80% over 17 days of feeding a 0.5% t10c12 CLA diet. The lipid volume decreased by 90% and the number of adipocytes and total cells were reduced by15% and 47%, respectively. Microarray profiling of replicated pools of control and treated mice (n=140) at seven time points over the 17day feeding indicated between 2798 to 4318 genes showed mRNA changes of 2-fold or more. Transcript levels for genes of glucose and fatty acid import or biosynthesis were significantly reduced. A prolific inflammation response was indicated by the 2 to100-fold induction of many cytokine transcripts, including those for IL-6, IL1?, TNF ligands, and CXC family members

Publication Title

Trans-10, cis-12 conjugated linoleic acid causes inflammation and delipidation of white adipose tissue in mice: a microarray and histological analysis.

Sample Metadata Fields

Age

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accession-icon GSE14888
Conjugated linoleic acid activates AMPK and reduces adiposity more effectively when used with metformin
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Trans-10, cis-12 conjugated linoleic acid (t10c12 CLA) causes dramatic reductions in white adipose tissue in mice but has had limited effectiveness in humans. Determination of the signaling pathways involved may lead to better regulation of adiposity. T10c12 CLA was found to activate AMP-activating protein kinase (AMPK), a central regulator of cell metabolism. Compound C, a potent inhibitor of AMPK, prevents many of the typical responses to treatments with t10c12 CLA including the integrated stress response (ISR), the inflammatory response, the reduction in key lipogenic transcription factors, and delipidation. Treatment of adipocytes or mice with t10c12 CLA in conjunction with AMPK activator metformin results in more delipidation than treatment with the individual chemicals. Additionally, the combination showed a reduced inflammatory response relative to a t10c12 CLA treatment alone. The combination of t10c12 CLA and metformin, widely used to treat insulin resistance and Type II diabetes, has potential as a treatment for reducing adiposity in humans.

Publication Title

Conjugated linoleic acid activates AMP-activated protein kinase and reduces adiposity more effectively when used with metformin in mice.

Sample Metadata Fields

Cell line

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accession-icon GSE44327
The hypoxia-inducible transcription factor ZNF395 is controlled by I-kappaB kinase and activates genes involved in the innate immune response and cancer
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Activation of the hypoxia inducible transcription factor HIF-alpha and the NF-kappaB pathway promotes inflammation mediated tumor progression.

Publication Title

The hypoxia-inducible transcription factor ZNF395 is controlled by IĸB kinase-signaling and activates genes involved in the innate immune response and cancer.

Sample Metadata Fields

Cell line, Treatment

View Samples
accession-icon GSE57141
Defining key signaling nodes and therapeutic biomarkers in NF1-mutant cancers
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The NF1 tumor suppressor encodes a RAS GTPase-Activating Protein (RasGAP). Accordingly, deregulated RAS signaling underlies the pathogenesis of NF1-mutant cancers. However, while various RAS effector pathways have been shown to function in these tumors, it is currently unclear which specific proteins within these broad signaling pathways represent optimal therapeutic targets. Here we identify mTORC1 as the key PI3K pathway component in NF1-mutant nervous system malignancies and conversely show that mTORC2 and AKT are dispensable. We also report that combined mTORC1/MEK inhibition is required to promote tumor regression in animal models, but only when the inhibition of both pathways is sustained. Transcriptional profiling studies were also used to establish a predictive signature of effective mTORC1/MEK inhibition in vivo. Within this signature, we unexpectedly found that the glucose transporter gene, GLUT1, was potently suppressed but only when both pathways were effectively inhibited. Moreover, unlike VHL and LKB1 mutant cancers, reduction of 18F-FDG uptake measured by FDG-PET required the effective suppression of both mTORC1 and MEK. Together these studies identify optimal and sub-optimal therapeutic targets in NF1-mutant malignancies and define a non-invasive means of measuring combined mTORC1/MEK inhibition in vivo, which can be readily incorporated into clinical trials.

Publication Title

Defining key signaling nodes and therapeutic biomarkers in NF1-mutant cancers.

Sample Metadata Fields

Specimen part

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accession-icon SRP148597
Single-cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment 3'' RNA Sequencing
  • organism-icon Homo sapiens
  • sample-icon 168 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 4000, Illumina HiSeq 2500

Description

Knowledge of immune cell phenotypes in the tumor microenvironment is essential for understanding mechanisms of cancer progression and immunotherapy response. We created an immune map of breast cancer using single-cell RNA-seq data from 45,000 immune cells from eight breast carcinomas, as well as matched normal breast tissue, blood, and lymph node. We developed a preprocessing pipeline, SEQC, and a Bayesian clustering and normalization method, Biscuit, to address computational challenges inherent to single-cell data. Despite significant similarity between normal and tumor tissue-resident immune cells, we observed continuous phenotypic expansions specific to the tumor microenvironment. Analysis of paired single-cell RNA and T cell receptor (TCR) sequencing data from 27,000 additional T cells revealed the combinatorial impact of TCR utilization on phenotypic diversity. Our results support a model of continuous activation in T cells and do not comport with the macrophage polarization model in cancer, with important implications for characterizing tumor-infiltrating immune cells.  Overall design: Single-cell RNA sequencing was performed on eight donors using the InDrop v2 protocol. For each donor populations of CD45+ immune cells were assayed for trancriptome-wide RNA-sequence. At least one replicate was taken for each donor.

Publication Title

Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP148594
Single-cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment - 5'' RNA sequencing and TCR sequencing
  • organism-icon Homo sapiens
  • sample-icon 29 Downloadable Samples
  • Technology Badge IconNextSeq 500, Illumina HiSeq 2500

Description

Knowledge of immune cell phenotypes in the tumor microenvironment is essential for understanding mechanisms of cancer progression and immunotherapy response. We created an immune map of breast cancer using single-cell RNA-seq data from 45,000 immune cells from eight breast carcinomas, as well as matched normal breast tissue, blood, and lymph node. We developed a preprocessing pipeline, SEQC, and a Bayesian clustering and normalization method, Biscuit, to address computational challenges inherent to single-cell data. Despite significant similarity between normal and tumor tissue-resident immune cells, we observed continuous phenotypic expansions specific to the tumor microenvironment. Analysis of paired single-cell RNA and T cell receptor (TCR) sequencing data from 27,000 additional T cells revealed the combinatorial impact of TCR utilization on phenotypic diversity. Our results support a model of continuous activation in T cells and do not comport with the macrophage polarization model in cancer, with important implications for characterizing tumor-infiltrating immune cells.  Overall design: Single-cell RNA sequencing was performed on three patients using the 10x genomics TCR profiling kits. For each patient, populations of T-cells were assayed for both TCR sequence and trancriptome-wide RNA-sequence. Two donors have a replicate experiment.

Publication Title

Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment.

Sample Metadata Fields

Specimen part, Subject

View Samples
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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Developed by the Childhood Cancer Data Lab

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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