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accession-icon GSE6055
Gene Expression Profiling Reveals Unique Pathways Associated with Differential Severity of Lyme Arthritis
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430A Array (moe430a)

Description

The murine model of Lyme disease provides a unique opportunity to study the localized host response to similar stimulus, B. burgdorferi, in the joints of mice destined to develop severe arthritis (C3H) or mild disease (C57BL/6). Pathways associated with the response to infection and the development of Lyme arthritis were identified by global gene expression patterns using oligonucleotide microarrays. A robust induction of IFN responsive genes was observed in severely arthritic C3H mice at one week of infection, which was absent from mildly arthritic C57BL/6 mice. In contrast, infected C57BL/6 mice displayed a novel expression profile characterized by genes involved in epidermal differentiation and wound repair, which were decreased in the joints of C3H mice. These expression patterns were associated with disease state rather than inherent differences between C3H and C57BL/6 mice, as C57BL/6-IL10-/- mice infected with B. burgdorferi develop more severe arthritis that C57BL/6 mice and displayed an early gene expression profile similar to C3H mice. Gene expression profiles at two and four weeks post infection revealed a common response of all strains that was likely to be important for the host defense to B. burgdorferi and mediated by NF-kB-dependent signaling. The gene expression profiles identified in this study add to the current understanding of the host response to B. burgdorferi and identify two novel pathways that may be involved in regulating the severity of Lyme arthritis.

Publication Title

Gene expression profiling reveals unique pathways associated with differential severity of lyme arthritis.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE16195
Expression profiling of joint tissue from C3H and interval specific congenic mouse lines post- B. burgdorferi infection
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Gene expression profile of joint tissue from C3H and interval specific congenic mouse lines (ISCL) following infection with Borrelia burgdorferi

Publication Title

Interval-specific congenic lines reveal quantitative trait Loci with penetrant lyme arthritis phenotypes on chromosomes 5, 11, and 12.

Sample Metadata Fields

Specimen part

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accession-icon GSE19511
Equivalent mutations in the eight subunits of the chaperonin CCT produce dramatically different cell phenotypes.
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome 2.0 Array (yeast2)

Description

The eukaryotic cytoplasmic chaperonin-containing TCP-1 (CCT) is a complex formed by two back-to-back stacked hetero-octameric rings that assists the folding of actins, tubulins and other proteins in an ATP-dependent manner. Here, we decided to test the significance of the hetero-oligomeric nature of CCT for its function by introducing, in each of the eight subunits in turn, an identical mutation at a position involved in ATP binding and conserved in all the subunits, in order to establish the extent of individuality of the various subunits. Our results show that these identical mutations lead to dramatically different phenotypes. For example, cells with the mutation in CCT2 have an excess of actin patches and are the only pseudo-diploid strain. By contrast, cells with the mutation in CCT7 are the only ones to accumulate juxta-nuclear protein aggregates that may reflect the absence of stress response in this strain. System-level analysis of the strains using RNA microarrays reveals connections between CCT and several cellular networks including ribosome biogenesis and TOR2 that help to explain the phenotypic variability observed

Publication Title

Equivalent mutations in the eight subunits of the chaperonin CCT produce dramatically different cellular and gene expression phenotypes.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP065478
Snai2 and Snai3 transcriptionally regulate cellular fitness and functionality of T cell lineages through distinct gene programs
  • organism-icon Mus musculus
  • sample-icon 23 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

T lymphocytes are essential contributors to the adaptive immune system and consist of multiple lineages that serve various effector and regulatory roles. As such, precise control of gene expression is essential to the proper development and function of these cells. Previously, we identified Snai2 and Snai3 as being essential regulators of immune tolerance partly due to the impaired function of CD4+ regulatory T cells in Snai2/3 conditional double knockout mice. Here we extend those previous findings using a bone marrow transplantation model to provide an environmentally unbiased view of the molecular changes imparted onto various T lymphocyte populations once Snai2 and Snai3 are deleted. The data presented here demonstrate that Snai2 and Snai3 transcriptionally regulate the cellular fitness and functionality of not only CD4+ regulatory T cells but effector CD8a+ and CD4+ conventional T cells as well. This is achieved through the modulation of gene sets unique to each cell type and includes transcriptional targets relevant to the survival and function of each T cell lineage. As such, Snai2 and Snai3 are essential regulators of T cell immunobiology. Overall design: GFP- CD3e+ CD8a+ CD4-, GFP- CD3e+ CD8a- CD4+ CD25- and GFP- CD3e+ CD8a- CD4+ CD25+ T cells were isolated from spleens of UBC-GFP mice transplanted with WT or cDKO lineage-depleted donor bone marrow following lethal irradiation of recipient mice. RNA-seq was performed on 3-4 biological replicates from each genotype for all T cell populations analyzed.

Publication Title

Snai2 and Snai3 transcriptionally regulate cellular fitness and functionality of T cell lineages through distinct gene programs.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE43022
ZFX controls the propagation and cell-of-origin characteristics of acute leukemia
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 28 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

ZFX controls propagation and prevents differentiation of acute T-lymphoblastic and myeloid leukemia.

Sample Metadata Fields

Specimen part, Cell line, Treatment

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accession-icon GSE36921
Effect of genetic Zfx deletion on gene expression in c-Kit + MLL-AF9 AML cells
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Acute myeloid leukemia (AML) propagates as a cellular hierarchy which is maintained by a rare subpopulation of self-renewing leukemia-initiating cells (LICs). These LICs phenotypically resemble HSCs and early myeloid progenitors, and they are functionally defined by their ability to reconstitute AML in xenografted mice.

Publication Title

ZFX controls propagation and prevents differentiation of acute T-lymphoblastic and myeloid leukemia.

Sample Metadata Fields

Cell line, Treatment

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accession-icon GSE43020
Effect of genetic Zfx deletion on gene expression in Notch induced T-ALL
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Acute myeloid leukemia (AML) and acute T-lymphoblastic leukemia (T-ALL) maintain the undifferentiated phenotype and proliferative capacity of their respective cells of origin, hematopoietic stem/progenitor cells and immature thymocytes. The mechanisms that maintain these progenitor-like characteristics are poorly understood. We report that the transcription factor Zfx is required for the development and propagation of experimental AML caused by MLL-AF9 fusion, and of T-ALL caused by Notch1 activation. In both leukemia types, Zfx activated progenitor-associated gene expression programs and prevented differentiation. Key Zfx target genes included mitochondrial enzymes Ptpmt1 and Idh2, whose overexpression partially rescued the propagation of Zfx-deficient AML. These studies identify a common mechanism that controls the cell-of-origin characteristics of acute leukemias derived from disparate lineages and transformation mechanisms.

Publication Title

ZFX controls propagation and prevents differentiation of acute T-lymphoblastic and myeloid leukemia.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE20540
Gene expression profiles of myeloma cells interacting with bone marrow stromal cells in vitro
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Conventional anti-cancer drug screening is typically performed in the absence of accessory cells (e.g. stromal cells) of the tumor microenvironment, which can profoundly alter anti-tumor drug activity. To address this major limitation, we have developed assays (e.g. the tumor cell-specific in vitro bioluminescence imaging (CS-BLI) assay) to selectively quantify tumor cell viability, in presence vs. absence of non-malignant stromal cells or drug treatment. These assays have allowed us to identify that neoplastic cells from diverse malignancies exhibit stroma-induced resistance to different anti-tumor agents. In this analysis, we evaluated the molecular changes triggered in myeloma cells by their in vitro interaction with stromal cells. The transcriptional profile of 3 human multiple myeloma (MM) cell lines (MM.1S, MM.1R, INA-6) co-cultured with stromal cells vs. when cultured alone was characterized by oligonucleotide microarray analysis, using the human U133 plus 2.0 Affymetrix GeneChip.

Publication Title

Tumor cell-specific bioluminescence platform to identify stroma-induced changes to anticancer drug activity.

Sample Metadata Fields

Cell line

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accession-icon SRP047065
Ribosome profiling upon inhibition of eIF4A
  • organism-icon Homo sapiens
  • sample-icon 13 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Ribosome profiling of MDA-MB-231 cells treated with Silvestrol to monitor transcriptome wide, eIF4A-dependent changes in translation efficiency Overall design: Translation efficiency (TE) of mRNAs dervied from ribosome footprints was monitored in the presence or absence of 25 nM Silvestrol, an inhibitor of eukaryotic translation initiation factor 4A (eIF4A). Transcripts with reduced TE in the presence of Silvestrol were compare to transcripts with reduced TE in the presence of INK128, a catalytic mTOR inhbitor.

Publication Title

Transcriptome-wide characterization of the eIF4A signature highlights plasticity in translation regulation.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE30747
AML mouse models
  • organism-icon Mus musculus
  • sample-icon 28 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

An integrated approach to dissecting oncogene addiction implicates a Myb-coordinated self-renewal program as essential for leukemia maintenance.

Sample Metadata Fields

Specimen part, Treatment

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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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