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accession-icon E-MEXP-1006
Transcription profiling time series of finite life span and immortal non-malignant human mammary epithelial cell lines
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

We analyzed gene expression in 184 (finite life span) and HMT3522 S1 (immortal non-malignant) HMECs on successive days (3, 5, and 7) post-seeding in a laminin-rich extracellular matrix assay. Both HMECs underwent growth arrest in G0/G1 and differentiated into polarized acini between days 5 and 7.

Publication Title

Gene expression signature in organized and growth-arrested mammary acini predicts good outcome in breast cancer.

Sample Metadata Fields

Sex, Specimen part, Cell line, Time

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accession-icon SRP013931
Initial analysis of transcript levels in zebrafish with advancing age
  • organism-icon Danio rerio
  • sample-icon 20 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerIIx

Description

This project aims at an initial characterization of changes in gene expression in zebrafish with advancing age. Transcript levels are determined in several tissues of zebrafish with differing ages using RNA-seq. Differentially expressed genes are determined to pinpoint genes that are differently regulated in young and old zebrafish. Results will be compared with other species to identify common pathways of ageing.

Publication Title

No associated publication

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP039085
Homo sapiens strain:HL-60 Transcriptome or Gene expression
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerIIx

Description

Transcriptome of human HL-60 and HEK-293 cells depending on culture cell density

Publication Title

No associated publication

Sample Metadata Fields

No sample metadata fields

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accession-icon E-MEXP-149
Transcription profiling of blasts from three APL patients expressing PML/RAR before and after treatment with 1 uM retinoic acid (RA) in vitro for four hours
  • organism-icon Homo sapiens
  • sample-icon 40 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133B Array (hgu133b), Affymetrix Human Genome U133A Array (hgu133a)

Description

Gene expression profiles in blasts from three APL patients expressing PML/RAR were assessed before and after treatment with 1 uM retinoic acid (RA) in vitro for four hours. We then studied a U937 clone conditionally expressing PML/RAR (U937-PR), (Grignani et al. 1993) (Alcalay et al. 2003), and compared the gene expression profile prior to and after 4 hours of treatment with 1 uM RA, to that obtained from a cell line bearing an empty vector (U937-MT). For each sample, biotinylated cRNA targets were synthesized starting from 5ug of total RNA, and hybridized to the complete set of HG-U133 Affymetrix oligonucleotide chips, which explores the expression of approximately 45,000 human transcripts. Results were analyzed using MASv5 and further elaborated with the GenePicker software. GeneChip probe sets regulated by RA in each sample were clustered into non-redundant regulated genes according to UniGene release Hs.166.

Publication Title

Molecular signature of retinoic acid treatment in acute promyelocytic leukemia.

Sample Metadata Fields

Specimen part, Disease, Cell line, Subject, Compound

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accession-icon GSE4332
Cell intrinsic alterations underlie hematopoietic stem cell aging
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Loss of immune function and an increased incidence of myeloid leukemia are two of the most clinically significant consequences of aging of the hematopoietic system. To better understand the mechanisms underlying hematopoietic aging, we evaluated the cell intrinsic functional and molecular properties of highly purified long-term hematopoietic stem cells (LT-HSCs) from young and old mice. We found that LT-HSC aging was accompanied by cell autonomous changes, including increased stem cell self-renewal, differential capacity to generate committed myeloid and lymphoid progenitors, and diminished lymphoid potential. Expression profiling revealed that LT-HSC aging was accompanied by the systemic down-regulation of genes mediating lymphoid specification and function and up-regulation of genes involved in specifying myeloid fate and function. Moreover, LT-HSCs from old mice expressed elevated levels of many genes involved in leukemic transformation. These data support a model in which age-dependent alterations in gene expression at the stem cell level presage downstream developmental potential and thereby contribute to age-dependent immune decline, and perhaps also to the increased incidence of leukemia in the elderly.

Publication Title

Cell intrinsic alterations underlie hematopoietic stem cell aging.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE44029
Expression data from SW480 cells with Gankyrin knockdown
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

we performed genome-wide screening using SW480 cells with Gankyrin knockdown on an Affymetrix gene expression array to identify the transcriptional targets of Gankyrin

Publication Title

Gankyrin activates IL-8 to promote hepatic metastasis of colorectal cancer.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE42084
Analysis of Unique and Overlapping Patterns of Gene Expression After Treatment of Zebrafish Embryos with Estradiol and/or Dioxin
  • organism-icon Danio rerio
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Zebrafish Genome Array (zebrafish)

Description

To increase the utility of the zebrafish gene expression bioassay for assessing EDC effects on multiple gene targets and tissue types, and to expand our understanding of genetic overlap between estrogen receptor (ER) and arylhydrocarbon receptor (AhR) mediated signaling pathways, we conducted microarray analysis of zebrafish embryos exposed to estradiol and dioxin alone or in combination. Of >16,000 probe sets on the array, 34 were regulated by estradiol (E2), 86 by dioxin (TCDD) and 109 by E2+TCDD (as chosen by >2-fold change and p<0.1). Of 62 genes selected for verification by QPCR, 14 genes, or 22% were reproducibly up- or down-regulated, offering potential additional target genes for screening of estrogen- and dioxin-like EDC. The majority of these successful hits, 11, were TCDD-responsive. In addition, all of the target genes routinely evaluated in this laboratory (AroB, Vtg1, and Esr1: E2-responsive; Cyp1a: TCDD- responsive; Vtg1: E2+TCDD-responsive) were verified with these arrays, testifying to the power of microarray analysis in finding reliable responsive genes. However, over two-thirds of the novel up- or down- regulated probes were not annotated as zebrafish genes, and many of the identified genes were changed only 2- to 3-fold, an effect often not reproduced by QPCR. Additional responsive genes were identified for each treatment condition, and while low levels of expression and low magnitude fold changes make those for E2 responsiveness or interaction between E2 and TCDD response unlikely to serve as robust biomarkers, their response to EDCs may assist in understanding the regulation of existing biomarkers and zebrafish endocrine systems as a whole. In addition to a source for potential EDC screening biomarkers, these studies provide an entry point to further study physiological effects of ER and AHR ligands and cross-talk between these signaling pathways, in a physiologically relevant in vivo model.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part

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accession-icon DRP001187
Simultaneous RNA-seq of bone marrow derived dendritic cells from Mus Musculus strain C57BL6/J activated with lipopolysaccharide over a period of 24 hours.
  • organism-icon Mus musculus
  • sample-icon 29 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

The innate immune response is primarily mediated by the Toll-like receptors functioning through the Myd88-dependent and TRIF-dependent pathways. Despite being widely studied, it is not yet completely understood and systems-level analyses have been lacking. In this study, we identified a high-probability network of genes activated during the innate immune response using a novel approach to analyze time course gene expression profiles of activated immune cells in combination with a large gene regulatory and protein-protein interaction network. We classified the immune response into three consecutive time-dependent stages and identified the most probable paths between genes showing a significant change in expression at each stage. The resultant network contained several novel and known regulators of the innate immune response, many of which did not show any observable change in expression at the sampled time points. The response network shows the dominance of genes from specific functional classes during different stages of the immune response. It also suggests a role for the protein phosphatase 2a catalytic subunit a in the regulation of the immunoproteasome during the late phase of the response. In order to clarify the differences between the Myd88-dependent and TRIF-dependent pathways in the innate immune response, time course gene expression profiles from Myd88-knockout and TRIF-knockout dendritic cells were analyzed. Their response networks suggest the dominance of the MyD88 dependent pathway in the innate immune response, and an association of the circadian regulators and immunoproteasomal degradation with the TRIF-dependent pathway. The response network presented here provides the most probable associations between genes expressed in the early and the late phases of the immune response, while taking into account the intermediate regulators. We propose that the method described here can also be used in the identification of time-dependent gene subnetworks in other biological systems.

Publication Title

Discovery of Intermediary Genes between Pathways Using Sparse Regression.

Sample Metadata Fields

No sample metadata fields

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accession-icon E-BAIR-7
Transcription profiling of mouse H-2Kb muscle cells treated with metformin (2mM) or insulin (100nM) for 0, 2 or 12 hours
  • organism-icon Mus musculus
  • sample-icon 56 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430B Array (moe430b), Affymetrix Mouse Expression 430A Array (moe430a)

Description

The basic design of the experiment is as described in Fryer et al.(2000)Diabetes 49:1978, and is similar to proto-BAIR (EXP_BAIR_0603_02). H-2Kb muscle cells were treated with metformin (2mM) or insulin (100nM) for 0, 2 or 12 hours.

Publication Title

No associated publication

Sample Metadata Fields

Sex, Age, Specimen part, Cell line, Compound, Time

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accession-icon E-BAIR-3
Transcription profiling of liver tissue in five week old Insulin Receptor Substrate-2 (IRS-2) knock out mice
  • organism-icon Mus musculus
  • sample-icon 32 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430B Array (moe430b), Affymetrix Mouse Expression 430A Array (moe430a)

Description

Mice which lack IRS-2, develop insulin resistance. Comparison between liver tissue from 5 weeks old IRS-2 KO mice and wild type.

Publication Title

Gene expression analysis of liver tissue in five week old Insulin Receptor Substrate-2 (IRS-2) knock out mice.

Sample Metadata Fields

Age, Specimen part

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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)

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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