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accession-icon GSE97350
ZBTB18 is a repressor of mesenchymal genes in Glioblastoma
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Epigenetic Regulation of ZBTB18 Promotes Glioblastoma Progression.

Sample Metadata Fields

Cell line

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accession-icon GSE97349
ZBTB18 is a repressor of mesenchymal genes in Glioblastoma [JX6]
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

The transcriptional repressor ZBTB18 was overexpressed in the brain tumor xenoline JX6 by lentiviral transduction. Three independent transduction were performed (biological replicates) and analyzed by gene expression aray. Gene set enrichemnt analysis (GSEA) showed changes in the expression of mesenchymal signature. A subset of genes was further valiadted by qPCR. These results indicate a role of ZBTB18 as repressor of mesenchymal genes in Glioblastoma.

Publication Title

Epigenetic Regulation of ZBTB18 Promotes Glioblastoma Progression.

Sample Metadata Fields

Cell line

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accession-icon GSE97347
ZBTB18 is a repressor of mesenchymal genes in Glioblastoma [BTSC233]
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

The transcriptional repressor ZBTB18 was overexpressed in the brain tumor stem cell-like BTSC233 by lentiviral transduction. Three independent transduction were performed (biological replicates) and analyzed by gene expression aray. Gene set enrichemnt analysis (GSEA) showed changes in the expression of mesenchymal signature. A subset of genes was further valiadted by qPCR. These results indicate a role of ZBTB18 as repressor of mesenchymal genes in Glioblastoma.

Publication Title

Epigenetic Regulation of ZBTB18 Promotes Glioblastoma Progression.

Sample Metadata Fields

Cell line

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accession-icon GSE60925
Access to follicular dendritic cells is a pivotal step in murine chronic lymphocytic leukemia B cell activation and proliferation
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.1 ST Array (mogene11st)

Description

In human chronic lymphocytic leukemia (CLL) pathogenesis B cell antigen receptor signaling seems important for leukemia B cell ontogeny, whereas the microenvironment influences B cell activation, tumor cell lodging and provision of antigenic stimuli. Using the murine E-Tcl1 CLL model, we demonstrate that CXCR5-controlled access to follicular dendritic cells (FDCs) confers proliferative stimuli to leukemia B cells. Intravital imaging revealed a marginal zone B cell-like leukemia cell trafficking route. Murine and human CLL cells reciprocally stimulated resident mesenchymal stromal cells through lymphotoxin--receptor activation, resulting in CXCL13 secretion and stromal compartment remodeling. Inhibition of lymphotoxin/lymphotoxin--receptor signaling or of CXCR5 signaling retards leukemia progression. Thus, CXCR5 activity links tumor cell homing, shaping a survival niche, and access to localized proliferation stimuli.

Publication Title

Access to follicular dendritic cells is a pivotal step in murine chronic lymphocytic leukemia B-cell activation and proliferation.

Sample Metadata Fields

Specimen part

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accession-icon GSE4611
Breast Cancer Gene Expression Data from Frankfurt Series
  • organism-icon Homo sapiens
  • sample-icon 218 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Pooling of microarray datasets seems to be a reasonable approach to increase sample size when a heterogeneous disease like breast cancer is concerned. Different methods for the adaption of datasets have been used in the literature. We have analyzed influences of these strategies using a pool of 3,030 Affymetrix U133A microarrays from breast cancer samples. We present data on the resulting concordance with biochemical assays of well known parameters and highlight critical pitfalls. We further propose a method for the inference of cutoff values directly from the data without prior knowledge of the true result. The cutoffs derived by this method displayed high specificity and sensitivity. Markers with a bimodal distribution like ER, PgR, and HER2 discriminate different biological subtypes of disease with distinct clinical courses. In contrast, markers displaying a continuous distribution like proliferation markers as Ki67 rather describe the composition of the mixture of cells in the tumor.

Publication Title

Data-driven derivation of cutoffs from a pool of 3,030 Affymetrix arrays to stratify distinct clinical types of breast cancer.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE107999
Stage-specific metabolic features of differentiating neurons: implications for toxicant sensitivity
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Developmental neurotoxicity (DNT) may be induced when chemicals disturb a key neurodevelopmental process, and many tests focus on this type of toxicity. Alternatively, DNT may occur when chemicals are cytotoxic only during a specific neurodevelopmental stage. The toxicant sensitivity is affected by the expression of toxicant targets and by resilience factors. Although cellular metabolism plays an important role, little is known how it changes during human neurogenesis, and how potential alterations affect toxicant sensitivity of mature vs. immature neurons. We used immature (d0) and mature (d6) LUHMES cells (dopaminergic human neurons) to provide initial answers to these questions. Transcriptome profiling and characterization of energy metabolism suggested a switch from predominantly glycolytic energy generation to a more pronounced contribution of the tricarboxylic acid cycle (TCA) during neuronal maturation. Therefore, we used pulsed stable isotope-resolved metabolomics (pSIRM) to determine intracellular metabolite pool sizes (concentrations), and isotopically non-stationary 13C-metabolic flux analysis (INST 13C MFA) to calculate metabolic fluxes. We found that d0 cells mainly use glutamine to fuel the TCA. Furthermore, they rely on extracellular pyruvate to allow continuous growth. This metabolic situation does not allow for mitochondrial or glycolytic spare capacity, i.e. the ability to adapt energy generation to altered needs. Accordingly, neuronal precursor cells displayed a higher sensitivity to several mitochondrial toxicants than mature neurons differentiated from them. In summary, this study shows that precursor cells lose their glutamine dependency during differentiation while they gain flexibility of energy generation and thereby increase their resistance to low concentrations of mitochondrial toxicants.

Publication Title

Stage-specific metabolic features of differentiating neurons: Implications for toxicant sensitivity.

Sample Metadata Fields

Sex, Specimen part, Time

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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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