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accession-icon GSE11292
High-time-resolution dynamic analysis of human regulatory T cell (Treg) / CD4+ T-effector cell (Teff) activation
  • organism-icon Homo sapiens
  • sample-icon 77 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Human FOXP3+CD25+CD4+ regulatory T cells (Tregs) play a dominant role in the maintenance of immune homeostasis. Several genes are known to be important for murine Tregs, but for human Tregs the genes and underlying molecular networks controlling the suppressor function still largely remain unclear. We here performed a high-time-resolution dynamic analysis of the transcriptome during the very early phase of human Treg/ CD4+ T-effector cell activation. After constructing a correlation network specific for Tregs based on these dynamic data, we described a strategy to identify key genes by directly analyzing the constructed undirected correlation network. Six out of the top 10 ranked key hubs are known to be important for Treg function or involved in autoimmune diseases. Surprisingly, PLAU (the plasminogen activator urokinase) was among the 4 new key hubs. We here show that PLAU was critical for expression regulation of FOXP3, EOS and several other important Treg genes and the suppressor function of human Tregs. Moreover, we found Plau inhibits murine Treg development and but promotes the suppressive function. Further analysis unveils that PLAU is particularly important for memory Tregs and that PLAU mediates Treg suppressor function via STAT5 and ERK signaling pathways. Our study shows the potential for identifying novel key genes for complex dynamic biological processes using a network strategy based on high-time-resolution data, and highlights a critical role of PLAU in both human and murine Tregs. The construction of a dynamic correlation network of human Tregs provides a useful resource for the understanding of Treg function and human autoimmune diseases.

Publication Title

PLAU inferred from a correlation network is critical for suppressor function of regulatory T cells.

Sample Metadata Fields

Specimen part

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accession-icon GSE76563
The study of inflammatory responses in mammalian macrophages with LPS stimulation
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st), Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Gene Regulatory Network Inference of Immunoresponsive Gene 1 (IRG1) Identifies Interferon Regulatory Factor 1 (IRF1) as Its Transcriptional Regulator in Mammalian Macrophages.

Sample Metadata Fields

Specimen part

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accession-icon GSE76561
LPS stimulation of human PBMC-derived macrophages
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Immunoresponsive gene 1 (IRG1) is one of the highest induced genes in macrophages under pro-inflammatory conditions and its function has been recently described: it codes for immune-responsive gene 1 protein/cis-aconitic acid decarboxylase (IRG1/CAD), an enzyme catalyzing the production of itaconic acid from cis-aconitic acid, a tricarboxylic acid (TCA) cycle intermediate. Itaconic acid possesses specific antimicrobial properties inhibiting isocitrate lyase, the first enzyme of the glyoxylate shunt, an anaplerotic pathway that bypasses the TCA cycle and enables bacteria to survive on limited carbon conditions. To elucidate the mechanisms underlying itaconic acid production through IRG1 induction in macrophages, we examined the transcriptional regulation of IRG1. Using a combination of literature information, transcription factor prediction models and genome-wide expression arrays, we inferred the regulatory network of IRG1 in mouse and human macrophages.

Publication Title

Gene Regulatory Network Inference of Immunoresponsive Gene 1 (IRG1) Identifies Interferon Regulatory Factor 1 (IRF1) as Its Transcriptional Regulator in Mammalian Macrophages.

Sample Metadata Fields

Specimen part

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accession-icon GSE76562
LPS stimulation of Mouse (RAW 264.7) macrophages
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st), Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Immunoresponsive gene 1 (IRG1) is one of the highest induced genes in macrophages under pro-inflammatory conditions and its function has been recently described: it codes for immune-responsive gene 1 protein/cis-aconitic acid decarboxylase (IRG1/CAD), an enzyme catalyzing the production of itaconic acid from cis-aconitic acid, a tricarboxylic acid (TCA) cycle intermediate. Itaconic acid possesses specific antimicrobial properties inhibiting isocitrate lyase, the first enzyme of the glyoxylate shunt, an anaplerotic pathway that bypasses the TCA cycle and enables bacteria to survive on limited carbon conditions. To elucidate the mechanisms underlying itaconic acid production through IRG1 induction in macrophages, we examined the transcriptional regulation of IRG1. Using a combination of literature information, transcription factor prediction models and genome-wide expression arrays, we inferred the regulatory network of IRG1 in mouse and human macrophages.

Publication Title

Gene Regulatory Network Inference of Immunoresponsive Gene 1 (IRG1) Identifies Interferon Regulatory Factor 1 (IRF1) as Its Transcriptional Regulator in Mammalian Macrophages.

Sample Metadata Fields

Specimen part

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accession-icon SRP063363
Transcriptomes of peripheral blood mononuclear cells from a Guillain-Barre Syndrome patient and her healthy twin sampled at three different points of the disease evolution
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerIIx

Description

Guillain-Barré syndrome (GBS) is an immune-mediated peripheral neuropathy that debilitates the voluntary and autonomous response of the patient. In this study the transcriptome of peripheral blood mononuclear cells from a GBS patient and her healthy twin were compared to discover possible correlates of disease progression and recovery. Overall design: Blood samples were collected simultaneously from the Guillain-Barré patient (A) and from her control healthy twin (B) at three different time points during disease progression from hospitalization in the intensive care unit (T1), passing to intermediate care (T2), and at conclusion of locomotion rehabilitation program when the patient was close to abandon the hospital (T3).

Publication Title

Expression of Early Growth Response Gene-2 and Regulated Cytokines Correlates with Recovery from Guillain-Barré Syndrome.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE67060
Expression data of Wnt3a stimulated K562 cells after CXXC5 overexpression or knockdown
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

CXXC5 inhibits the canonical Wnt signaling pathway

Publication Title

Downregulation of the Wnt inhibitor CXXC5 predicts a better prognosis in acute myeloid leukemia.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon SRP150250
Quiescence modulates stem cell maintenance and regenerative capacity in the aging brain – SMART-seq2
  • organism-icon Mus musculus
  • sample-icon 474 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000, Illumina HiSeq 3000

Description

Single cell RNA-seq of neural stem cell and astrocytes from old mice Overall design: Single cell RNA-seq of neural stem cell and astrocytes from old mice

Publication Title

Quiescence Modulates Stem Cell Maintenance and Regenerative Capacity in the Aging Brain.

Sample Metadata Fields

Sex, Age, Specimen part, Cell line, Subject

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accession-icon SRP049826
Whole-transcriptome analysis of endothelial-to-hematopoietic stem cell transition
  • organism-icon Mus musculus
  • sample-icon 16 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Hematopoietic stem cells (HSCs) are generated via a natural transdifferentiation process known as endothelial-to-hematopoietic cell transition (EHT). Due to small numbers of embryonal arterial cells undergoing EHT and the paucity of markers to enrich for hemogenic endothelial cells, the genetic program driving HSC emergence is largely unknown. Here, we use a highly sensitive RNAseq method to examine the whole transcriptome of small numbers of enriched aortic HSCs (CD31+cKit+Ly6aGFP+), hemogenic endothelial cells (CD31+cKit-Ly6aGFP+) and endothelial cells (CD31+cKit-Ly6aGFP-). Overall design: Comparison of mRNA profiles of endothelial cells, hemogenic endothelial cells, and hematopoietic stem cells generated by deep-sequencing of sorted populations from pool of embryos, in triplicate.

Publication Title

Whole-transcriptome analysis of endothelial to hematopoietic stem cell transition reveals a requirement for Gpr56 in HSC generation.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE115313
Transcriptomics analysis of paired tumor and normal mucosa samples in a cohort of patients with colon cancer, with and without T2DM.
  • organism-icon Homo sapiens
  • sample-icon 27 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

This is a transcriptomics analysis contributing to a bigger project that tries to shed light on the role of type 2 diabetes mellitus (T2DM) as a risk factor for colon cancer (CC). Here we present a gene expression screening of paired tumor and normal colon mucosa samples in a cohort of 42 CC patients, 23 of them with T2DM. Using gene set enrichment, we identified an unexpected overlap of pathways over-represented in diabetics compared to non-diabetics, both in tumor and normal mucosa, including diabetes-related metabolic and signaling processes. An integration with other -omic studies suggests that in diabetics, the local micro-environment in normal colon mucosa may be a factor driving field cancerization which may promote carcinogenesis. Several of these pathways converged on the tumor initiation axis TEAD/YAP-TAZ. Cell culture studies confirmed that high glucose concentrations upregulate this pathway in non-tumor colon cells. In conclusion, diabetes is associated to deregulation of cancer-related processes in normal colon mucosa adjacent to tissue which has undergone a malignant transformation. These data support the existence of the field of cancerization paradigm in diabetes and set a new framework to study link between diabetes and cancer.

Publication Title

Molecular evidence of field cancerization initiated by diabetes in colon cancer patients.

Sample Metadata Fields

Specimen part

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accession-icon GSE115329
Transcriptomics analysis of Colon tumor xenograft model in streptozotocin-induced diabetic mice
  • organism-icon Homo sapiens
  • sample-icon 1 Downloadable Sample
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

This is a transcriptomics analysis contributing to a bigger project that tries to shed light on the role of type 2 diabetes mellitus (T2DM) as a risk factor for colon cancer (CC). Here we present a gene expression screening of 7 colon tumor xenograft samples, 2 with diabetic mice and 5 with normal blood glucose levels. For xenograft model details see: Prieto I, et al. (2017) Colon cancer modulation by a diabetic environment: A single institutional experience. PLoS One 12(3):e0172300

Publication Title

Molecular evidence of field cancerization initiated by diabetes in colon cancer patients.

Sample Metadata Fields

Specimen part

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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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