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accession-icon GSE54206
Growth factor independence 1b (Gfi1b) is required for erythroid cell maturation and regulates embryonic globin expression
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Growth factor independence 1b (gfi1b) is important for the maturation of erythroid cells and the regulation of embryonic globin expression.

Sample Metadata Fields

Specimen part

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accession-icon GSE54204
Growth factor independence 1b (Gfi1b) is required for erythroid cell maturation and regulates embryonic globin expression [MoGene-1_0]
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Growth factor independence 1b (Gfi1b) is a DNA binding repressor of transcription with vital functions in hematopoiesis. Gfi1b-null embryos die at midgestation very likely due to defects in erythro- and megakaryopoiesis. To analyze the full functionality of Gfi1b in embryonic erythropoiesis, we used conditionally deficient mice that harbor floxed Gfi1b alleles and one EpoR-Cre knock-in allele.

Publication Title

Growth factor independence 1b (gfi1b) is important for the maturation of erythroid cells and the regulation of embryonic globin expression.

Sample Metadata Fields

Specimen part

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accession-icon GSE54205
Growth factor independence 1b (Gfi1b) is required for erythroid cell maturation and regulates embryonic globin expression [Mouse430_2]
  • organism-icon Mus musculus
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Growth factor independence 1b (Gfi1b) is a DNA binding repressor of transcription with vital functions in hematopoiesis. Gfi1b-null embryos die at midgestation very likely due to defects in erythro- and megakaryopoiesis. To analyze the full functionality of Gfi1b in erythropoiesis, we used conditionally deficient mice that harbor floxed Gfi1b alleles and the Mx-Cre transgene inducible by pIpC treatment.

Publication Title

Growth factor independence 1b (gfi1b) is important for the maturation of erythroid cells and the regulation of embryonic globin expression.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE74243
Genome wide gene expression during lung development in three inbred mouse strains
  • organism-icon Mus musculus
  • sample-icon 214 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

To better understand the temporal dynamics of gene expression during normal murine lung development we characterized global gene expression at 26 time points in three common inbred strains of mice (A/J, C57BL/6J, and C3H/HeJ). The data set provides a unique resource for identifying patterns of gene expression changes during normal lung development and for investigating the developmental origins of respiratory disease.

Publication Title

Temporal dynamics of the developing lung transcriptome in three common inbred strains of laboratory mice reveals multiple stages of postnatal alveolar development.

Sample Metadata Fields

Specimen part

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accession-icon SRP061548
RNA-Seq Analysis of Gfi1b KO Megakaryocytes
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Megakaryocytes isolated from Gfi1b flox/flox mice carrying PF4-Cre or not, and from Gfi1b flox/flox mice carrying ROSA-Cre-ERT with or without tamoxifen injection were analyzed for differential expression by RNA-Seq Overall design: A sample of each Gfi1b wild-type and Knock-Out from each model was analyzed

Publication Title

Gfi1b regulates the level of Wnt/β-catenin signaling in hematopoietic stem cells and megakaryocytes.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE69554
Gene expression profiling of BDC2.5 CD4T cells isolated from NOD mice after in vivo antigen stimulation with either DEC205+ or DCIR2+ DCs.
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

We identified DCIR2+DCs but not DEC205+DCs as able to induce peripheral T cell tolerance in pre-diabetic autoimmune NOD mice. To determine what distinct genetic programs are elicited in the auto-reactive CD4 T cells early after stimulation by these two DC subsets, we utilized adoptive transfer of BDC2.5 CD4 T cells into NOD mice, which were then given chimeric antibody to deliver the beta-cell specific antigen to either DCIR2+DCs or DEC205+DCs, leading to BDC2.5 CD4 T cell specific stimulation in vivo. The analysis shows that the negative transcriptional factor Zbtb32 (ROG) is up-regulated more in BDC2.5 CD4 T cells after stimulated with a antigen via DCIR2+DCs presentation, compared with DEC205+DCs, suggesting the involvement of Zbtb32 in DCIR2+DCs-mediated auto-reactive T cell tolerance in disease ongoing NOD mice.

Publication Title

DCIR2+ cDC2 DCs and Zbtb32 Restore CD4+ T-Cell Tolerance and Inhibit Diabetes.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE62932
Comparison of Nanostring nCounter data on FFPE colon cancer samples and Affymetrix microarray data on matched frozen tissues
  • organism-icon Homo sapiens
  • sample-icon 59 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The prognosis of colorectal cancer (CRC) stage II and III patients is still a challenge due to the difficulties of finding robust biomarkers and assays. The majority of published gene signatures of CRC have been generated on frozen colorectal tissues. Because collection of fresh frozen tissues is not routine and the quantity and quality of RNA derived from formalin-fixed paraffin-embedded (FFPE) tissues is vastly inferior to that derived from fresh frozen tissue, a clinical test for improving staging of colon cancer will need to be designed for FFPE tissues in order to be widely applicable. We have designed a custom Nanostring nCounter assay for quantitative assessment of expression of 414 gene elements consisting of multiple published gene signatures for colon cancer prognosis, and systematically compared the gene expression quantification between nCounter data from FFPE and Affymetrix microarray array data from matched frozen tissues using 414 genes.

Publication Title

Comparison of Nanostring nCounter® Data on FFPE Colon Cancer Samples and Affymetrix Microarray Data on Matched Frozen Tissues.

Sample Metadata Fields

Disease

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accession-icon GSE38831
Deciphering genomic alterations in colorectal cancer through transcriptional subtype-based network analysis
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

High-throughput genomic studies have identified thousands of genetic alterations in colorectal cancer (CRC). Distinguishing driver from passenger mutations is critical for developing rational therapeutic strategies. Because only a few transcriptional subtypes exist in previously studied tumor types, we hypothesize that highly heterogeneous genomic alterations may converge to a limited number of distinct mechanisms that drive unique gene expression patterns in different transcriptional subtypes. In this study, we defined transcriptional subtypes for CRC and identified driver networks/pathways for each subtype, respectively. Applying consensus clustering to a patient cohort with 1173 samples identified three transcriptional subtypes, which were validated in an independent cohort with 485 samples. The three subtypes were characterized by different transcriptional programs related to normal adult colon, early colon embryonic development, and epithelial mesenchymal transition, respectively. They also showed statistically different clinical outcomes. For each subtype, we mapped somatic mutation and copy number variation data onto an integrated signaling network and identified subtype-specific driver networks using a random walk-based strategy. We found that genomic alterations in the Wnt signaling pathway were common among all three subtypes; however, unique combinations of pathway alterations including Wnt, VEGF, Notch and TGF-beta drove distinct molecular and clinical phenotypes in different CRC subtypes. Our results provide a coherent and integrated picture of human CRC that links genomic alterations to molecular and clinical consequences, and which provides insights for the development of personalized therapeutic strategies for different CRC subtypes.

Publication Title

Deciphering genomic alterations in colorectal cancer through transcriptional subtype-based network analysis.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE64907
NSCLC Driven by DDR2 Mutation is Sensitive to JQ1 and Dasatinib Combination Therapy
  • organism-icon Mus musculus
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Genetically engineered mouse models of lung cancer have demonstrated an important role in understanding the function of novel lung cancer oncogenes and tumor suppressor genes identified in genomic studies of human lung cancer. Further, these models are important platforms for pre-clinical therapeutic studies. Here, we generated a mouse model of lung adenocarcinoma driven by mutation of the Discoidin Domain Receptor 2 (DDR2) gene combined with loss of TP53. DDR2L63V;TP53L/L mice developed poorly differentiated lung adenocarcinomas in all transgenic animals analyzed with a latency of 40-50 weeks and a median survival of 67.5 weeks. Mice expressing wild-type DDR2 with combined TP53 loss did not form lung cancers. DDR2L63V; TP53L/L tumors displayed robust expression of DDR2 and immunohistochemical markers of lung adenocarcinoma comparable to previously generated models of lung adenocarcinoma though also displayed concomitant expression of the squamous cell markers p63 and SOX2. Tumor-derived cell lines were not solely DDR2 dependent and displayed up-regulation of and partial dependence on MYCN. Combined treatment with the BET inhibitor JQ1 and the mutltitargeted DDR2 inhibitor dasatinib inhibited tumor growth in vitro and in vivo. Together, these results suggest that DDR2 mutation can drive lung cancer initiation in vivo and provide a novel mouse model for lung cancer therapeutics studies.

Publication Title

NSCLC Driven by DDR2 Mutation Is Sensitive to Dasatinib and JQ1 Combination Therapy.

Sample Metadata Fields

Specimen part

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accession-icon SRP051401
Human Schlafen 5 (SLFN5) is a Regulator of Motility and Invasiveness of Renal Cell Carcinoma (RCC) Cells
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

There is some emerging evidence that members of the Schlafen (SLFN) family of proteins mediate antineoplastic responses, but the mechanisms accounting for these effects are not known. We provide evidence that human SLFN5, an interferon (IFN)- inducible member of the family, exhibits key roles in controlling motility and invasiveness of renal cell carcinoma (RCC) cells. Our studies define the mechanism by which this occurs, demonstrating that SLFN5 negatively controls expression of matrix metalloproteinases (MMP)-1 and -13 and several other genes involved in the control of malignant cell motility. Importantly, our data establish that SLFN5 expression correlates with a better overall survival in a large cohort of patients with RCC. The inverse relationship between SLFN5 expression and RCC aggressiveness raises the possibility of developing unique therapeutic approaches in the treatment of RCC, by modulating SLFN5 expression. Overall design: Examination of 2 SLFN5 knockdown cells and 2 controls, in triplicate.

Publication Title

Human Schlafen 5 (SLFN5) Is a Regulator of Motility and Invasiveness of Renal Cell Carcinoma Cells.

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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