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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

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 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 GSE6573
Dysregulation of the circulating and tissue-based renin-angiotensin system in preeclampsia
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Preeclampsia complicates more than 3% of all pregnancies in the United States and Europe. High-risk populations include women with diabetes, dyslipidemia, thrombotic disorders, hyperhomocysteinemia, hypertension, renal diseases, previous preeclampsia, twin pregnancies, and low socioeconomic status. In the latter case, the incidence may increase to 20% to 25%. Preeclampsia is a major cause of maternal and fetal morbidity and mortality. Preeclampsia is defined by systolic blood pressure of more than 140 mm Hg and diastolic blood pressure of more than 90 mm Hg after 20 weeks gestation in a previously normotensive patient, and new-onset proteinuria. Abnormal placentation associated with shallow trophoblast invasion (fetal cells from outer cell layer of the blastocyst) into endometrium (decidua) and improper spiral artery remodeling in the decidua are initial pathological steps.

Publication Title

Dysregulation of the circulating and tissue-based renin-angiotensin system in preeclampsia.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE35489
Expression data from human with IgA nephropathy (IgAN)
  • organism-icon Homo sapiens
  • sample-icon 62 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

A molecular signature of proteinuria in glomerulonephritis.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE35488
Expression data from human with IgA nephropathy (IgAN) [HG-U133A_ENTREZG_10]
  • organism-icon Homo sapiens
  • sample-icon 31 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Proteinuria is the most important predictor of outcome in glomerulonephritis and experimental data suggest that the tubular cell response to proteinuria is an important determinant of progressive fibrosis in the kidney. However, it is unclear whether proteinuria is a marker of disease severity or has a direct effect on tubular cells in the kidneys of patients with glomerulonephritis. Accordingly we studied an in vitro model of proteinuria, and identified 231 albumin-regulated genes differentially expressed by primary human kidney tubular epithelial cells exposed to albumin. We translated these findings to human disease by studying mRNA levels of these genes in the tubulo-interstitial compartment of kidney biopsies from patients with IgA nephropathy using microarrays. Biopsies from patients with IgAN (n=25) could be distinguished from those of control subjects (n=6) based solely upon the expression of these 231 albumin-regulated genes. The expression of an 11-transcript subset related to the degree of proteinuria, and this 11-mRNA subset was also sufficient to distinguish biopsies of subjects with IgAN from control biopsies. We tested if these findings could be extrapolated to other proteinuric diseases beyond IgAN and found that the all forms of primary glomerulonephritis (n=33) can be distinguished from controls (n=21) based solely on the expression levels of these 11 genes derived from our in vitro proteinuria model. Pathway analysis suggests common regulatory elements shared by these 11 transcripts. In conclusion, we have identified an albumin-regulated 11-gene signature shared between all forms of primary glomerulonephritis. Our findings support the hypothesis that albuminuria may directly promote injury in the tubulo-interstitial compartment of the kidney in patients with glomerulonephritis.

Publication Title

A molecular signature of proteinuria in glomerulonephritis.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE35487
Expression data from human with IgA nephropathy (IgAN) [HG-U133A]
  • organism-icon Homo sapiens
  • sample-icon 31 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Proteinuria is the most important predictor of outcome in glomerulonephritis and experimental data suggest that the tubular cell response to proteinuria is an important determinant of progressive fibrosis in the kidney. However, it is unclear whether proteinuria is a marker of disease severity or has a direct effect on tubular cells in the kidneys of patients with glomerulonephritis. Accordingly we studied an in vitro model of proteinuria, and identified 231 albumin-regulated genes differentially expressed by primary human kidney tubular epithelial cells exposed to albumin. We translated these findings to human disease by studying mRNA levels of these genes in the tubulo-interstitial compartment of kidney biopsies from patients with IgA nephropathy using microarrays. Biopsies from patients with IgAN (n=25) could be distinguished from those of control subjects (n=6) based solely upon the expression of these 231 albumin-regulated genes. The expression of an 11-transcript subset related to the degree of proteinuria, and this 11-mRNA subset was also sufficient to distinguish biopsies of subjects with IgAN from control biopsies. We tested if these findings could be extrapolated to other proteinuric diseases beyond IgAN and found that the all forms of primary glomerulonephritis (n=33) can be distinguished from controls (n=21) based solely on the expression levels of these 11 genes derived from our in vitro proteinuria model. Pathway analysis suggests common regulatory elements shared by these 11 transcripts. In conclusion, we have identified an albumin-regulated 11-gene signature shared between all forms of primary glomerulonephritis. Our findings support the hypothesis that albuminuria may directly promote injury in the tubulo-interstitial compartment of the kidney in patients with glomerulonephritis.

Publication Title

A molecular signature of proteinuria in glomerulonephritis.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE50469
The molecular phenotype of endocapillary proliferation in IgA nephropathy and potential modulation by bioactive small molecules
  • organism-icon Homo sapiens
  • sample-icon 22 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Endocapillary proliferation is associated with higher risk of progressive disease in IgAN. To better understand molecular pathways involved in the development of endocapillary proliferation and to identify novel specific therapeutic targets, we evaluated the glomerular transcriptome of microdissected kidney biopsies from 22 patients with IgAN. Endocapillary proliferation was defined according to the Oxford scoring system by 3 nephropathologists. We analyzed mRNA expression using microarrays and identified transcripts differentially expressed in patients with endocapillary proliferation. Next, we employed both transcription factor analysis and in silico drug screening and confirmed that the endocapillary proliferation transcriptome is significantly enriched with pathways modulated by corticosteroid exposure. With this approach we also identified novel therapeutic targets and bioactive small molecules that may be considered for therapeutic trials for treatment of IgAN.

Publication Title

The molecular phenotype of endocapillary proliferation: novel therapeutic targets for IgA nephropathy.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE51257
Functional heterogeneity of cancer-associated fibroblasts from human colon tumors shows specific prognostic gene expression signature
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Tumor growth and metastasis is controlled by paracrine signaling between cells of the tumor microenvironment and malignant cells. Cancer-associated fibroblasts (CAFs), are functionally important components of the tumor microenvironment. Although some steps involved in the cross-talk between these cells are known, there is still a lot that is not clear. Thus, the addition of, the consideration of microenvironment in the development of the disease, to the clinical and pathological procedures (currently admitted as the consistent value cancer treatments) could lay the foundations for the development of new treatment strategies to control the disease.

Publication Title

Functional heterogeneity of cancer-associated fibroblasts from human colon tumors shows specific prognostic gene expression signature.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE3486
Mechanically stimulated fibroblast from different fetal mouse tissues using Affy MOE430 chip set
  • organism-icon Mus musculus
  • sample-icon 36 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430A Array (moe430a)

Description

In order to test the hypothesis that fibroblasts from different tissues are phenotypically distinct from one another, we have subjected tendon, skin and corneal fibroblasts of fetal mouse to mechanical stimulation by fluid flow and analyzed the transcriptional responses of the cells using Affymetrix MOE430 chip set containing two arrays MOE430A and MOE430B.

Publication Title

Phenotypic responses to mechanical stress in fibroblasts from tendon, cornea and skin.

Sample Metadata Fields

No sample metadata fields

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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