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accession-icon GSE41295
Expression data from monocyte-derived macrophages after stimulation with mock, LPS, PolyI:C and P3C.
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

Pre-stimulation of MDMs with LPS (signals via MyD88 and TRIF dependent pathways) and PolyI:C (signals via a TRIF dependent pathway) leads to a reduced viral infection. In contrast, pre-stimulation with P3C (signals via MyD88 dependent pathway) does not lead to a reduced viral infection. This microarray was performed to find genes that are specifically upregulated in LPS and PolyI:C stimulated MDMs but not P3C stimulated MDMs. So to give us leads into the mechanism involved in the reduction of viral infection.

Publication Title

Bacterial lipopolysaccharide inhibits influenza virus infection of human macrophages and the consequent induction of CD8+ T cell immunity.

Sample Metadata Fields

Specimen part, Treatment, Subject

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accession-icon SRP082453
Single cell transcriptome sequencing of mammary stem cells in the pubertal mammary gland
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

The mammary gland is a highly dynamic organ that mainly develops during puberty. Based on morphology and proliferation analysis, mammary stem cells (MaSCs) are thought to be close to or reside in the terminal end buds (TEBs) during pubertal development. However, exclusive stem cell markers are lacking, and therefore the true identity of MaSCs, including their location, multiplicity, dynamics and fate during branching morphogenesis, has yet to be defined. To gain more insights into the molecular identity and heterogeneity of the MaSC pool, we performed single cell transcriptome sequencing of mammary epithelial cells micro-dissected from ducts and TEBs during puberty. These data show that the behaviour of MaSCs cannot be directly linked to a single expression profile. Instead, morphogenesis of the mammary epithelium relies upon a heterogeneous population of MaSCs that functions long-term as a single equipotent pool of stem cells. Overall design: Ducts and terminal end buds were micro-dissected from the 4th and the 5th murine mammary gland at 5 weeks-of-age, dissociated into single cells, and FACS sorted. Single-cell transcriptomics was performed on live cells using an automated version of CEL-seq2 on live, FACS sorted cells. The StemID algorithm was used to identify clusters of cells corresponding to basal and luminal cells types derived from ducts and terminal end buds.

Publication Title

Identity and dynamics of mammary stem cells during branching morphogenesis.

Sample Metadata Fields

Cell line, Subject

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accession-icon GSE41055
A predictive signature gene set for discriminating active from latent TB in Warao Amerindian children
  • organism-icon Homo sapiens
  • sample-icon 27 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

While blood transcriptional profiling has improved diagnosis and understanding of disease pathogenesis of adult tuberculosis (TB), no studies applying gene expression profiling of children with TB have been described so far. In this study, we have compared whole blood gene expression in childhood TB patients, as well as in healthy latently infected (LTBI) and uninfected (HC) children in a cohort of Warao Amerindians in the Delta Amacuro in Venezuela. We identified a 116-gene signature set by means of random forest analysis that showed an average prediction error of 11% for TB vs. LTBI and for TB vs. LTBI vs. HC in our dataset. Furthermore, a minimal set of only 9 genes showed a significant predictive value for all previously published adult studies using whole blood gene expression, with average prediction errors between 17% and 23%. Additionally, a minimal gene set of 42 genes with a comparable predictive value to the 116-gene set in both our dataset and the previously published literature cohorts for the comparsion of TB vs. LTBI vs. HC was identified. In order to identify a robust representative gene set that would hold stand among different ethnic populations, we selected ten genes that were highly discriminative between TB, LTBI and HC in all literature datasets as well as in our dataset. Functional annotation of these ten genes highlights a possible role for genes involved in calcium signaling and calcium metabolism as biomarkers for active TB. These ten genes were validated by quantitative real-time polymerase chain reaction in an additional cohort of 54 Warao Amerindian children with LTBI, HC and non-TB pneumonia. Decision tree analysis indicated that five of the ten genes were sufficient to diagnose 78% of the TB cases correctly with 100% specificity. We conclude that our data justify the further exploration of our signature set as biomarkers to diagnose childhood TB. Furthermore, as the identification of different biomarkers in ethnically distinct cohorts is apparent, it is important to cross-validate newly identified markers in all available cohorts.

Publication Title

A predictive signature gene set for discriminating active from latent tuberculosis in Warao Amerindian children.

Sample Metadata Fields

Sex, Age

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accession-icon GSE66488
Characterization of tumor extracellular vesicle RNA cargo
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Comparative RNA profiling between tumor cells and their secreted extracellular vesicles. Results revealed enrichment in genes involved in cellular migration and metastasis in extracellular vesicles, in agreement with their role as mediators of tumor progression.

Publication Title

In Vivo imaging reveals extracellular vesicle-mediated phenocopying of metastatic behavior.

Sample Metadata Fields

Cell line

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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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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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