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accession-icon GSE66416
Differential gene expression of periostin-overexpressing MC3T3-E1 cells
  • organism-icon Mus musculus
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

Periostin participates in different processes involved in connective tissue homeostasis. It is also involved in repairment of damaged tissues. We used the osteoblast murine cell line MC3T3-E1 cell line to show how overexpresion of periostin is able to increase their adhesion properties while diminishing their migration capacity. By differential gene expression we evaluated putative targets involved in those cellular properties.

Publication Title

Role of Periostin in Adhesion and Migration of Bone Remodeling Cells.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE17825
Murine fracture healing
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Time-point expression analysis of fractures calluses at 1, 3, and 5 days post-fracture in young and old BALB/c mice.

Publication Title

Identification of novel gene expression in healing fracture callus tissue by DNA microarray.

Sample Metadata Fields

Age, Specimen part

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accession-icon GSE14491
TGF/mutant-p53 jointly controlled genes
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

TGF ligands act as tumor suppressors in early stage tumors but are paradoxically diverted into potent prometastatic factors in advanced cancers. The molecular nature of this switch remains enigmatic. We now show that TGF-dependent cell migration, invasion and metastasis are empowered by mutant-p53.

Publication Title

A Mutant-p53/Smad complex opposes p63 to empower TGFbeta-induced metastasis.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP046233
Specific molecular signatures underlie response to decitabine in CMML [RNA-seq]
  • organism-icon Homo sapiens
  • sample-icon 14 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Myelodysplastic syndromes and chronic myelomonocytic leukemia (CMML) are characterized by mutations in epigenetic modifiers and aberrant DNA methylation. DNA methyltransferase inhibitors (DMTis) are used to treat these disorders, but response is highly variable with few means to predict which patients will benefit. To develop a molecular means of predicting response at diagnosis, we examined baseline differences in mutations, DNA methylation, and gene expression in 40 CMML patients responsive and resistant to decitabine (DAC). While somatic mutations did not differentiate responders and non-responders, we were able to identify for the first time 158 differentially methylated regions (DMRs) at baseline between responders and non-responders using next-generation sequencing. These DMRs were primarily localized to non-promoter regions and overlapped with distal regulatory enhancers. Using the methylation profiles, we developed an epigenetic classifier that accurately predicted DAC response at the time of diagnosis. We also found 53 differentially expressed genes between responders and non-responders. Genes up-regulated in responders were enriched in the cell cycle, potentially contributing to effective DAC incorporation. Two chemokines overexpressed in non-responders -- CXCL4 and CXCL7 -- were able to block the effect of DAC on normal CD34+ and primary CMML cells in vitro, suggesting their up-regulation contributes to primary DAC resistance. Overall design: mRNA profiling in bone marrow mononuclear cells (BM MNC) from 14 CMML patients (8 decitabine responders vs. 6 non-responders).

Publication Title

Specific molecular signatures predict decitabine response in chronic myelomonocytic leukemia.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP078441
RNA-seq of primary patient AML samples
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

The goals of this study are to compare transcriptome profiling (RNA-seq) of patients BM with or without ASXL2 mutations. Overall design: Patient bone marrow mRNA profiles with or without ASXL1/2 mutations were generated by deep sequencing

Publication Title

ASXL2 is essential for haematopoiesis and acts as a haploinsufficient tumour suppressor in leukemia.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP078443
RNA-seq of Asxl2 KO LSK cells
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

The goals of this study are to compare transcriptome profiling (RNA-seq) of Asxl2 KO LSK cells to that of Asxl2 wild-type cells. We found substantial number of genes are differentially expressed in Asxl2 KO cells. Overall design: LSK mRNA profiles of Asxl2-/- mice and Asxl2wt/wt (WT) were generated by deep sequencing, in triplicate, using Illumina GAIIx.

Publication Title

ASXL2 is essential for haematopoiesis and acts as a haploinsufficient tumour suppressor in leukemia.

Sample Metadata Fields

Specimen part, Cell line, Subject, Compound

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accession-icon GSE51389
THE BILIARY EPITHELIUM GIVES RISE TO LIVER PROGENITOR CELLS BUT MAKES A MINOR CONTRIBUTION TO HEPATOCYTE REGENERATION AFTER LIVER INJURY
  • organism-icon Mus musculus
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

We previously showed that severe liver diseases are characterized by expansion of liver progenitor cells (LPC), which correlates with disease severity. However, the origin and role of LPC in liver physiology and in the hepatic response to injury remains a contentious topic. We have now used genetic lineage tracing of Hnf1-expressing biliary duct cells to assess their contribution to LPC expansion and hepatocyte generation during normal liver homeostasis, and following different types of liver injury. We found that ductular reaction cells in human cirrhotic livers express HNF1. However, HNF1 expression was not present in newly generated EpCAM-positive hepatocytes. Using a tamoxifen-inducible Hnf1CreER/R26RYFP/LacZ mouse, we show that there is no contribution of the biliary epithelium to hepatocyte turnover during liver homeostasis in healthy mice. Moreover, after loss of liver mass, Hnf1+ LPC did not contribute to hepatocyte regeneration. We also assessed the contribution of Hnf1+ cells following acute and repeated liver injury. All animal models showed expansion of LPC, as assessed by immunostaining and gene expression profile of sorted YFP-positive cells. A contribution of Hnf1+ LPC to hepatocyte generation was not detected in animal models of liver injury with preserved hepatocyte regenerative potential such as acute acetaminophen, carbon tetrachloride injury, or chronic diethoxycarbonyl-1,4-dihydro-collidin (DDC)-diet. However, in mice fed with choline-deficient ethionine-supplemented (CDE)-diet, which causes profound hepatocyte damage and arrest, a small number of hepatocytes were derived from Hnf1+ cells. Conclusion: Hnf1+ cells do not participate in hepatocyte turnover in the healthy liver or during liver regeneration after partial hepatectomy. After liver injury, LPC arise from the biliary duct epithelium, which gives rise to a limited number of hepatocytes only when hepatocyte regeneration is compromised.

Publication Title

The biliary epithelium gives rise to liver progenitor cells.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE34268
Expression data from normal and MDS erythroids cell cutlures ex vivo
  • organism-icon Homo sapiens
  • sample-icon 26 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

CD34 positive cells of bone marrow samples from normal and MDS samples were cultured ex vivo into erythroid conditions.

Publication Title

Defective nuclear localization of Hsp70 is associated with dyserythropoiesis and GATA-1 cleavage in myelodysplastic syndromes.

Sample Metadata Fields

Specimen part

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accession-icon GSE48303
Expression data from aldosterone-producing adenomas (APAs) with a somatic mutation in either KCNJ5, CACNA1D, or ATP1A1
  • organism-icon Homo sapiens
  • sample-icon 13 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Analysis of aldosterone-producing adenoma (APA) samples from patients with primary hyperaldosteronism. These APAs have a somatic mutation in either KCNJ5, CACNA1D, or ATP1A1. Results provide insight into the different mechanisms each mutation may cause leading to elevated aldosterone production in APA.

Publication Title

Somatic mutations in ATP1A1 and CACNA1D underlie a common subtype of adrenal hypertension.

Sample Metadata Fields

Specimen part, Disease, Disease stage

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accession-icon GSE59673
Gene expression analysis of ectopic cyclin D1-expressing myeloma cells compared to their non expressing counterparts
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

We analyzed gene expression profiles of myeloma cells belonging to the group of bas prognosis RPMI 8226 and LP1 expressing either the GFP protein or a cyclin D1-GFP fusion protein

Publication Title

Cyclin D1 sensitizes myeloma cells to endoplasmic reticulum stress-mediated apoptosis by activating the unfolded protein response pathway.

Sample Metadata Fields

Specimen part, Cell line

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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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