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accession-icon GSE89332
Expression data for various immune cells
  • organism-icon Mus musculus
  • sample-icon 35 Downloadable Samples
  • Technology Badge Icon

Description

Segregated nucleus atypical monocyte (SatM) is novel monocyte cell type. Complehensive Gene expression pattern was examined not only in SatM but also its related cell type.

Publication Title

No associated publication

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE25252
Comparison of expression profiles of Foxp3(+)epigenetics(-) T cells, Foxp3(-)epigenetics(+) T cells, and Foxp3(+)epigenetics(+) T cells
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon

Description

Analysis of Foxp3(+)epigenetics(-) T cells, Foxp3(-)epigenetics(+) T cells, and Foxp3(+)epigenetics(+) T cells. Results indicate regulatory T cell (Treg) ontogenesis requires two independent processes, expression of the transcription factor Foxp3 and establishment of Treg epigenetic programs induced by T cell receptor (TCR) stimulation.

Publication Title

T cell receptor stimulation-induced epigenetic changes and Foxp3 expression are independent and complementary events required for Treg cell development.

Sample Metadata Fields

Specimen part

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accession-icon GSE22448
Gene expression data from wild-type and Nlrc5 knockout GM-CSF induced bone marrow dendritic cells infected with Newcastle Disease virus.
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
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Description

Nlrc5 is encoding a Nod-like receptor protein NLRC5/NOD27. To check the involvement of Nlrc5 in antiviral response, we examined gene expression profile in wild-type and Nlrc5 knockout GM-CSF bone marrow macrophage with using microarrays.

Publication Title

NLRC5 deficiency does not influence cytokine induction by virus and bacteria infections.

Sample Metadata Fields

Specimen part, Time

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accession-icon GSE17112
Visualization of cancer initiating cell in the vascular niche utilized with transcriptional activity of PSF1
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon

Description

Identification of cancer stem/initiating cells (CSCs/CICs) by a specific marker is useful for diagnosis and therapy of cancer. We have determined that PSF1 which plays a role in DNA replication in lower species is strongly expressed in wide range of normal stem cell population. Here, utilizing the transcriptional activity of PSF1 promoter in tumor cell xenograft model, we show that PSF1high cancer cells display malignant features including high proliferating activity, serial transplantation potential, and metastatic ability those are used for criteria of CSCs/CICs. PSF1high cancer cells localize in perivascular region and genetically display ES cell like signature. Silencing of PSF1 by RNAi inhibited growth of cancer cells mediated by disruption of DNA synthesis and chromosomal segregation. These suggested that PSF1 is a possible maker and a molecular target of CSCs/CICs.

Publication Title

No associated publication

Sample Metadata Fields

Cell line

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accession-icon GSE72088
Exploiting microRNA and mRNA profiles generated in vitro from carcinogen-exposed primary mouse hepatocytes for predicting in vivo genotoxicity and carcinogenicity
  • organism-icon Mus musculus
  • sample-icon 54 Downloadable Samples
  • Technology Badge Icon

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Exploiting microRNA and mRNA profiles generated in vitro from carcinogen-exposed primary mouse hepatocytes for predicting in vivo genotoxicity and carcinogenicity.

Sample Metadata Fields

Specimen part, Compound

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accession-icon GSE27567
Integrating Factor Analysis and a Transgenic Mouse Model to Reveal a Peripheral Blood Predictor of Breast Tumors
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 94 Downloadable Samples
  • Technology Badge Icon

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Integrating factor analysis and a transgenic mouse model to reveal a peripheral blood predictor of breast tumors.

Sample Metadata Fields

Specimen part

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accession-icon GSE17538
Experimentally Derived Metastasis Gene Expression Profile Predicts Recurrence and Death in Colon Cancer Patients
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 231 Downloadable Samples
  • Technology Badge Icon

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Experimentally derived metastasis gene expression profile predicts recurrence and death in patients with colon cancer.

Sample Metadata Fields

Sex, Age, Disease stage, Race

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accession-icon GSE72081
Exploiting microRNA and mRNA profiles generated in vitro from carcinogen-exposed primary mouse hepatocytes for predicting in vivo genotoxicity and carcinogenicity (mRNA)
  • organism-icon Mus musculus
  • sample-icon 54 Downloadable Samples
  • Technology Badge Icon

Description

The well-defined battery of in vitro systems applied within chemical cancer risk assessment is often characterised by a high false-positive rate, thus repeatedly failing to correctly predict the in vivo genotoxic and carcinogenic properties of test compounds. Toxicogenomics, i.e. mRNA-profiling, has been proven successful in improving the prediction of genotoxicity in vivo and the understanding of underlying mechanisms. Recently, microRNAs have been discovered as post-transcriptional regulators of mRNAs. It is thus hypothesised that using microRNA response-patterns may further improve current prediction methods. This study aimed at predicting genotoxicity and non-genotoxic carcinogenicity in vivo, by comparing microRNA- and mRNA-based profiles, using a frequently applied in vitro liver model and exposing this to a range of well-chosen prototypical carcinogens. Primary mouse hepatocytes (PMH) were treated for 24 and 48h with 21 chemical compounds [genotoxins (GTX) vs. non-genotoxins (NGTX) and non-genotoxic carcinogens (NGTX-C) versus non-carcinogens (NC)]. MicroRNA and mRNA expression changes were analysed by means of Exiqon and Affymetrix microarray-platforms, respectively. Classification was performed by using Prediction Analysis for Microarrays (PAM). Compounds were randomly assigned to training and validation sets (repeated 10 times). Before prediction analysis, pre-selection of microRNAs and mRNAs was performed by using a leave-one-out t-test. No microRNAs could be identified that accurately predicted genotoxicity or non-genotoxic carcinogenicity in vivo. However, mRNAs could be detected which appeared reliable in predicting genotoxicity in vivo after 24h (7 genes) and 48h (2 genes) of exposure (accuracy: 90% and 93%, sensitivity: 65% and 75%, specificity: 100% and 100%). Tributylinoxide and para-Cresidine were misclassified. Also, mRNAs were identified capable of classifying NGTX-C after 24h (5 genes) as well as after 48h (3 genes) of treatment (accuracy: 78% and 88%, sensitivity: 83% and 83%, specificity: 75% and 93%). Wy-14,643, phenobarbital and ampicillin trihydrate were misclassified. We conclude that genotoxicity and non-genotoxic carcinogenicity probably cannot be accurately predicted based on microRNA profiles. Overall, transcript-based prediction analyses appeared to clearly outperform microRNA-based analyses.

Publication Title

Exploiting microRNA and mRNA profiles generated in vitro from carcinogen-exposed primary mouse hepatocytes for predicting in vivo genotoxicity and carcinogenicity.

Sample Metadata Fields

Specimen part, Compound

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accession-icon GSE57132
Evaluating mRNA and microRNA profiles reveals discriminative and compound-specific responses following genotoxic or non-genotoxic carcinogen exposure in primary mouse hepatocytes
  • organism-icon Mus musculus
  • sample-icon 57 Downloadable Samples
  • Technology Badge Icon

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Evaluating microRNA profiles reveals discriminative responses following genotoxic or non-genotoxic carcinogen exposure in primary mouse hepatocytes.

Sample Metadata Fields

Specimen part, Compound

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accession-icon GSE11128
Expression data from single cells from mouse primordial germ cell lineage (E6.25-E8.25, wild type and Blimp1KO)
  • organism-icon Mus musculus
  • sample-icon 106 Downloadable Samples
  • Technology Badge Icon

Description

Specification of germ cell fate is fundamental in development. With a highly representative single-cell microarray and rigorous quantitative-PCR analysis, we defined the genome-wide transcription dynamics that create primordial germ cells (PGCs) from the epiblast, a process that exclusively segregates them from their somatic neighbors. We also analyzed the effect of the loss of Blimp1, a key transcriptional regulator, on these dynamics. Our analysis revealed that PGC specification involves complex, yet highly ordered regulation of a large number of genes, proceeding under the strong influence of mesoderm induction with active repression of specific programs such as epithelial-mesenchymal transition, Hox gene activation, cell-cycle progression and DNA methyltransferase machinery. Remarkably, Blimp1 is essential for repressing nearly all the genes normally down-regulated in PGCs relative to their somatic neighbors, whereas it is dispensable for the activation of approximately half of the genes up-regulated in PGCs.

Publication Title

No associated publication

Sample Metadata Fields

No sample metadata fields

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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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