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accession-icon GSE77080
Neuroblastoma cells depend on HDAC11 for mitotic cell cycle progression and survival
  • organism-icon Homo sapiens
  • sample-icon 36 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

The number of long-term survivors of high-risk neuroblastoma remains discouraging, with 10-year survival as low as 20%, despite decades of considerable international efforts to improve outcome. Major obstacles remain and include managing resistance to induction therapy, which causes tumor progression and early death in high-risk patients, and managing chemotherapy-resistant relapses, which can occur years after the initial diagnosis. Identifying and validating novel therapeutic targets is essential to improve treatment. Delineating and deciphering specific functions of single histone deacetylases in neuroblastoma may support development of targeted acetylome-modifying therapeutics for patients with molecularly defined high-risk neuroblastoma profiles. We show here that HDAC11 depletion in MYCN-driven neuroblastoma cell lines strongly induces cell death, mostly mediated by apoptotic programs. Genes necessary for mitotic cell cycle progression and cell division were most prominently enriched in at least two of three time points in whole-genome expression data combined from two cell systems, and all nine genes in these functional categories were strongly repressed, including CENPA, KIF14, KIF23 and RACGAP1. Enforced expression of one selected candidate, RACGAP1, partially rescued the induction of apoptosis caused by HDAC11 depletion. High-level expression of all nine genes in primary neuroblastomas signicantly correlated with unfavorable overall and event-free survival in patients, suggesting a role in mediating the more aggressive biological and clinical phenotype of these tumors. Our study identied a group of cell cycle-promoting genes regulated by HDAC11, being both predictors of unfavorable patient outcome and essential for tumor cell viability. The data indicates a signicant role of HDAC11 for mitotic cell cycle progression and survival of MYCN-amplified neuroblastoma cells, and suggests that HDAC11 could be a valuable drug target.

Publication Title

Neuroblastoma cells depend on HDAC11 for mitotic cell cycle progression and survival.

Sample Metadata Fields

Cell line, Time

View Samples
accession-icon GSE75523
Circadian mRNA expression in skeletal muscle of young and aged mice
  • organism-icon Mus musculus
  • sample-icon 32 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

Aging animals undergo a variety of changes in molecular processes. Among these, the cellular circadian clock has been shown to change as animals age. Moreover, there is evidence that also core circadian clock proteins could influence the ageing behavior of vertebrates.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE49030
Genome-wide profiling of the activity-dependent hippocampal transcriptome
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Activity-dependent gene expression is central for sculpting neuronal connectivity in the brain. Despite the importance for synaptic plasticity, a comprehensive analysis of the temporal changes in the transcriptomic response to neuronal activity is lacking. In a genome wide survey we identified genes that were induced at 1, 4, 8, or 24 hours following neuronal activity in the hippocampus.

Publication Title

Genome-wide profiling of the activity-dependent hippocampal transcriptome.

Sample Metadata Fields

Sex, Age, Specimen part, Time

View Samples
accession-icon GSE38614
Hierarchical regulation in a KRAS pathway-dependent transcriptional network revealed by a reverse-engineering approach
  • organism-icon Rattus norvegicus
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 1.0 ST Array (ragene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Reverse engineering a hierarchical regulatory network downstream of oncogenic KRAS.

Sample Metadata Fields

Cell line, Treatment

View Samples
accession-icon GSE38584
Hierarchical regulation in a KRAS pathway-dependent transcriptional network revealed by a reverse-engineering approach (7TF and control)
  • organism-icon Rattus norvegicus
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 1.0 ST Array (ragene10st)

Description

RAS mutations are highly relevant for progression and therapy response of human tumours, but the genetic network that ultimately executes the oncogenic effects is poorly understood. Here we used a reverse-engineering approach in an ovarian cancer model to reconstruct KRAS oncogene-dependent cytoplasmic and transcriptional networks from perturbation experiments based on gene silencing and pathway inhibitor treatments. We measured mRNA and protein levels in manipulated cells by microarray, RT-PCR and Western Blot analysis, respectively. The reconstructed model revealed complex interactions among the transcriptional and cytoplasmic components, some of which were confirmed by double pertubation experiments. Interestingly, the transcription factors decomposed into two hierarchically arranged groups. To validate the model predictions we analysed growth parameters and transcriptional deregulation in the KRAS-transformed epithelial cells. As predicted by the model, we found two functional groups among the selected transcription factors. The experiments thus confirmed the predicted hierarchical transcription factor regulation and showed that the hierarchy manifests itself in downstream gene expression patterns and phenotype.

Publication Title

Reverse engineering a hierarchical regulatory network downstream of oncogenic KRAS.

Sample Metadata Fields

Cell line, Treatment

View Samples
accession-icon GSE100211
Expression data from primary hepatocytes from mouse
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Retinol Saturase (RetSat) is an oxidoreductase expressed at high levels in the hepatocyte fraction of liver.

Publication Title

Retinol saturase coordinates liver metabolism by regulating ChREBP activity.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE38585
Hierarchical regulation in a KRAS pathway-dependent transcriptional network revealed by a reverse-engineering approach (RAS-ROSE and ROSE with siRNA)
  • organism-icon Rattus norvegicus
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 1.0 ST Array (ragene10st)

Description

RAS mutations are highly relevant for progression and therapy response of human tumours, but the genetic network that ultimately executes the oncogenic effects is poorly understood. Here we used a reverse-engineering approach in an ovarian cancer model to reconstruct KRAS oncogene-dependent cytoplasmic and transcriptional networks from perturbation experiments based on gene silencing and pathway inhibitor treatments. We measured mRNA and protein levels in manipulated cells by microarray, RT-PCR and Western Blot analysis, respectively. The reconstructed model revealed complex interactions among the transcriptional and cytoplasmic components, some of which were confirmed by double pertubation experiments. Interestingly, the transcription factors decomposed into two hierarchically arranged groups. To validate the model predictions we analysed growth parameters and transcriptional deregulation in the KRAS-transformed epithelial cells. As predicted by the model, we found two functional groups among the selected transcription factors. The experiments thus confirmed the predicted hierarchical transcription factor regulation and showed that the hierarchy manifests itself in downstream gene expression patterns and phenotype.

Publication Title

Reverse engineering a hierarchical regulatory network downstream of oncogenic KRAS.

Sample Metadata Fields

Cell line, Treatment

View Samples
accession-icon GSE43409
RORt+ Innate lymphoid cells transcriptomes after aNKp44 and cytokine stimulation
  • organism-icon Homo sapiens
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

RORt+ innate lymphoid cells (ILC) are crucial players of innate immune responses and represent a major source of IL-22, which has an important role in mucosal homeostasis. The signals required by RORt+ ILC to express IL-22 and other cytokines, including TNF, have only partially been elucidated. Here we show that RORt+ ILC can directly sense the environment by the engagement of the activating receptor NKp44. NKp44 triggering in RORt+ ILC selectively activates a coordinated pro-inflammatory program, including TNF, while cytokine stimulation induces preferentially IL-22 expression. However, combined engagement of NKp44 and cytokine receptors results in a strong synergistic effect. These data support the concept that NKp44+ RORt+ ILC can be activated without cytokines and are able to switch between IL-22 or TNF production, depending on the triggering stimulus.

Publication Title

RORγt⁺ innate lymphoid cells acquire a proinflammatory program upon engagement of the activating receptor NKp44.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon GSE26886
Gene expression profiling of Barrett's esophagus, adenocarcinoma, esophageal squamous epithelium and squamous cell carcinoma
  • organism-icon Homo sapiens
  • sample-icon 68 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The aim of this study is to generate and validate biomarkers to stratify patients with Barretts esophagus in terms of risk for developing cancer. We studied gene expression profiling in 69 frozen specimens, consisting of esophageal squamous epithelium from 19 healthy subjects, 20 specimens from patients with Barretts esophagus and 21 cases of esophageal adenocarcinoma, 9 cased of esophageal squamous cell carcinoma by whole genome microarray analysis. Laser capture microdissection technique was applied to procure cells from defined regions of Barretts esophagus metaplasia and esophageal adenocarcinoma. Microarray results were validated by quantitative real-time polymerase chain reaction (qRT-PCR) in an independent cohort consisting of 42 cases. Furthermore, immunohistochemistry was performed using antibodies to two selected target molecules on a third independent cohort of 36 specimens, consisting of 36 cases. A total of 1176 genes were associated significantly with esophageal adenocarcinoma. The expression pattern of a 4 gene signature with the highest discriminant score based on linear discriminant analysis (GeneSpring GX10.2), was identified and validated by qRT-PCR in independent cohort.

Publication Title

Wdr66 is a novel marker for risk stratification and involved in epithelial-mesenchymal transition of esophageal squamous cell carcinoma.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE37307
Aberrant expressed genes in AML
  • organism-icon Homo sapiens
  • sample-icon 48 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Acute myeloid leukemia (AML) is one of the most common and deadly forms of hematopoietic malignancies. We hypothesized that microarray studies could identify aberrantly expressed genes selectively expressed in AML blasts, believing that these genes may be potential therapeutic targets for adoptive T-cell strategies

Publication Title

No associated publication

Sample Metadata Fields

Specimen part, Disease

View Samples
...

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)

fund-icon Fund the CCDL

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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