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accession-icon GSE32540
Identification of novel tissue-specific transcription arising from E-cadherin/CDH1 intron2: a novel protein isoform increases gastric cancer cell invasion and angiogenesis.
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

E-cadherin, a protein encoded by the CDH1 gene is the dominant epithelial cell adhesion molecule playing a crucial role in epithelial tissue polarity and structural integrity. The progression of 90% or more carcinomas is believed to be mediated by disruption of normal E-cadherin expression, subcellular localization or function. Despite the strong correlation between E-cadherin loss and malignancy the mechanism through how this occurs is not known in most sporadic and hereditary epithelial carcinomas. Previous works have shown the importance of CDH1 intron 2 sequences for proper gene and protein expression supporting the possibility of these being cis-modulators of E-cadherin expression/function. but when co-expressed it led to reduced cell-cell adhesiveness, increased invasion and angiogenesis. By expression array analysis, IFITM1 and IFI27 levels were found to be increased upon CDH1a overexpression. Importantly, CDH1a was found to be de novo expressed in gastric cancer cell lines when compared to normal stomach.

Publication Title

Transcription initiation arising from E-cadherin/CDH1 intron2: a novel protein isoform that increases gastric cancer cell invasion and angiogenesis.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE24514
Expression data from human MSI colorectal cancer and normal colonic mucosa
  • organism-icon Homo sapiens
  • sample-icon 49 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Microsatellite instability (MSI), caused by defective mismatch repair, is observed in a subset of colorectal cancers (CRCs). We evaluated somatic mutations in microsatellite repeats of genes chosen based on reduced expression in MSI CRC and existence of a coding mononucleotide repeat.

Publication Title

Candidate driver genes in microsatellite-unstable colorectal cancer.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE53403
Expression data from mouse adipose tissue macrophage
  • organism-icon Mus musculus
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

In mammals, expansion of adipose tissue mass induces accumulation of adipose tissue macrophages (ATMs). We isolated CD11c- (FB) and CD11c+ (FBC) perigonadal ATMs from SVCs of lean (C57BL/6J Lep +/+) and obese leptin-deficient (C57BL/6J Lep ob/ob) mice.

Publication Title

Obesity activates a program of lysosomal-dependent lipid metabolism in adipose tissue macrophages independently of classic activation.

Sample Metadata Fields

Specimen part

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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

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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 GSE71482
Expression data from Caenorhabditis elegans fed with a Lactoferrin-based product
  • organism-icon Caenorhabditis elegans
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix C. elegans Genome Array (celegans)

Description

Lactoferrin is a highly multifunctional protein. Indeed, it is involved in many physiological functions, including regulation of iron absorption and immune responses.

Publication Title

A nutritional supplement containing lactoferrin stimulates the immune system, extends lifespan, and reduces amyloid <i>β</i> peptide toxicity in <i>Caenorhabditis elegans</i>.

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 GSE14359
Expression data from conventional osteosarcoma compared to primary non-neoplastic osteoblast cells
  • organism-icon Homo sapiens
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

In osteosarcoma patients, the development of metastases, often to the lungs, is the most frequent cause of death. To improve this situation, a deeper understanding of the molecular mechanisms governing osteosarcoma development and dissemination and the identification of novel drug targets for an improved treatment are needed. Towards this aim, we characterized osteosarcoma tissue samples compared to primary osteoblast cells using Affymetrix HG U133A microarrays.

Publication Title

De novo expression of EphA2 in osteosarcoma modulates activation of the mitogenic signalling pathway.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP097691
Oncogenic PIK3CA(H1047R) and CTNNB1(stab) in intestinal organoids
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Goals of the study was to compare transcripional and phenotypic response of mouse intestinal organoid cultures to the PIK3CA(H1047R) and CTNNB1(stab) oncogenes. Overall design: Two biological replicates of organoids with transgenic tdTomato-Luciferase, tdTomato-PIK3CAH1047R, tdTomato-CTNNB1stab or td-Tomato-PIK3CAH1047R-CTNNB1stab were analysed by RNA-Seq By comparing 7-10 x 10E7 50bp paired end reads per library we identify transcriptional alterations in the intestinal epithelium following expression of each or both oncogenes,

Publication Title

Oncogenic β-catenin and PIK3CA instruct network states and cancer phenotypes in intestinal organoids.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE46549
Microarray analysis of colon carcinoma cell lines
  • organism-icon Homo sapiens
  • sample-icon 33 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

To investigate potential differences between strong and weak oscillators at the gene expression level we carried out a transcriptome analysis for each cell line. Our results indicate that phenotypic circadian clock differences are reflected by gene expression differences both in genes of the core network, but also in additional genes not directly associated with circadian clock functions.

Publication Title

Ras-mediated deregulation of the circadian clock in cancer.

Sample Metadata Fields

Specimen part, Cell line, Time

View Samples
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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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