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accession-icon GSE12333
Retinoic Acid Delivery within Embryoid Bodies Induces an Early Streak Phenotype in vitro
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

During embryogenesis, cell specification and tissue formation is directed by the concentration and temporal presentation of morphogens, and similarly, pluripotent embryonic stem cells differentiate in vitro into various phenotypes in response to morphogen treatment. Embryonic stem cells are commonly differentiated as three dimensional spheroids called embryoid bodies (EBs); however, differentiation within EBs is typically heterogeneous and disordered. Here we show that spatiotemporal control of microenvironmental cues embedded directly within EBs enhances the homogeneity, synchrony and organization of differentiation. Degradable polymer microspheres releasing retinoic acid within EBs induce the formation of cystic spheroids closely resembling the early streak mouse embryo, with an exterior of visceral endoderm enveloping an epiblast layer. These results demonstrate that controlled morphogen presentation to stem cells more efficiently directs cell differentiation and tissue formation, thereby improving developmental biology models and enabling the development of regenerative medicine therapies and cell diagnostics.

Publication Title

Homogeneous and organized differentiation within embryoid bodies induced by microsphere-mediated delivery of small molecules.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE66298
A DNA Hypomethylation Signature Predicts Novel Anti-Tumor Activity of LSD1 Inhibitors in SCLC
  • organism-icon Homo sapiens
  • sample-icon 88 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

A DNA Hypomethylation Signature Predicts Antitumor Activity of LSD1 Inhibitors in SCLC.

Sample Metadata Fields

Specimen part, Cell line, Treatment

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accession-icon GSE66294
A DNA Hypomethylation Signature Predicts Novel Anti-Tumor Activity of LSD1 Inhibitors in SCLC (microarray)
  • organism-icon Homo sapiens
  • sample-icon 88 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Epigenetic dysregulation has emerged as an important mechanism in cancer. Alterations in epigenetic machinery have become a major focus for new targeted therapies. The current report describes the discovery and biological activity of a cyclopropylamine containing inhibitor of Lysine Demethylase 1 (LSD1), GSK2879552. This small molecule is a potent, selective, orally bioavailable, mechanism-based irreversible inhibitor of LSD1. A proliferation screen of cell lines representing a number of tumor types indicated that small cell lung carcinoma (SCLC) is sensitive to LSD1 inhibition. The subset of SCLC lines and primary samples that undergo growth inhibition in response to GSK2879552 exhibit DNA hypomethylation of a signature set of probes suggesting this may be used as a predictive biomarker of activity. The targeted mechanism coupled with a novel predictive biomarker make LSD1 inhibition an exciting potential therapy for SCLC, a highly prevalent, rarely cured, tumor type representing approximately 15% of all lung cancers.

Publication Title

A DNA Hypomethylation Signature Predicts Antitumor Activity of LSD1 Inhibitors in SCLC.

Sample Metadata Fields

Cell line, Treatment

View Samples
accession-icon SRP046331
Global MEF2 target gene analysis in cardiac and skeletal muscle reveals novel regulation of DUSP6 by p38MAPKMEF2 signaling [RNA-seq]
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Identfification of MEF2A target genes using ChIP-exo and RNA-seq in skeletal muscle and primary cardiomyocytes. MEF2 plays a profound role in the regulation of transcription in cardiac and skeletal muscle lineages. To define the overlapping and unique MEF2A genomic targets, we utilized ChIP-exo analysis of cardiomyocytes and skeletal myoblasts. Of the 2783 and 1648 MEF2A binding peaks in skeletal myoblasts and cardiomyocytes, respectively, 294 common binding sites were identified. Genomic targets were compared to differentially expressed genes in RNA-seq analysis of MEF2A depleted myogenic cells. Overall design: The effect of MEF2A gene silencing on gene expression in myoblasts was assessed at 48 hr DM. Up and downregulated genes were then compared to MEF2A target genes identified in ChIP-exo analysis of 48 hr DM C2C12 myoblasts cells and primary cardiomyocytes.

Publication Title

Global MEF2 target gene analysis in cardiac and skeletal muscle reveals novel regulation of DUSP6 by p38MAPK-MEF2 signaling.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE16516
Distinct Self-renewal and Differentiation Phases in the Niche of Infrequently Dividing Hair Follicle Stem Cells
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

In homeostasis of adult vertebrate tissues, stem cells are thought to self-renew by infrequent and asymmetric divisions that generate another stem cell daughter and a progenitor daughter cell committed to differentiate. This model is based largely on in vivo invertebrate or in vitro mammal studies. Here we examine the dynamic behaviour of adult hair follicle stem cells in their normal setting by employing mice with repressible H2B-GFP expression to track cell divisions and Cre inducible mice to perform long-term single cell lineage tracing. We provide direct evidence for the infrequent stem cell division model in intact tissue. Moreover, we find that differentiation of progenitor cells occurs at different times and tissue locations than self-renewal of stem cells. Distinct fates of differentiation or self-renewal are assigned to individual cells in a temporal-spatial manner. We propose that large clusters of tissue stem cells behave as populations, whose maintenance involves unidirectional daughter-cell fate decisions.

Publication Title

Distinct self-renewal and differentiation phases in the niche of infrequently dividing hair follicle stem cells.

Sample Metadata Fields

Specimen part

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accession-icon SRP032989
mRNA expression in C-33A cells expressing HPV1 E2
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Profile of RNA expression in a C-33A cell line derived from an HPV negative cervical carcinoma in the presence or absence of HPV1 E2 expression. Overall design: mRNA profiles of C-33A cells in presence or absence of HPV1 E2 expression were generated by deep sequencing using Illumina GAIIx. Two samples (no replicates). One control and one experimental.

Publication Title

The effect of Rho kinase inhibition on long-term keratinocyte proliferation is rapid and conditional.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE53077
High Runx1 levels promote a reversible more differentiated cell-state in hair follicle stem cells during quiescence
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Quiescent hair follicle (HF) bulge stem cells (SCs) differentiate to early progenitor (EP) hair germ (HG) cells, which divide to produce transit-amplifying (TA) matrix cells. EPs can revert to SCs upon injury, but whether this de-differentiation occurs in normal HF homeostasis (hair cycle), and the mechanisms regulating both differentiation and de-differentiation are unclear. Here we use lineage tracing, gain of function, transcriptional profiling, and functional assays to examine the role of observed endogenous Runx1 level changes in the hair cycle. We find that forced Runx1 expression implements hair degeneration (catagen) and simultaneously promotes changes in the quiescent bulge SC transcriptome towards a cell-state resembling the EP HG fate. This cell-state transition is functionally reversible. We propose that SC differentiation and de-differentiation are likely to occur during normal HF degeneration and niche restructuring in response to changes in endogenous Runx1 levels associated with SC location with respect to the niche.

Publication Title

High Runx1 levels promote a reversible, more-differentiated cell state in hair-follicle stem cells during quiescence.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE112798
Machine learning predicts individual cancer patient responses to therapeutic drugs with high accuracy
  • organism-icon Homo sapiens
  • sample-icon 27 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Samples of primary tumors collected from 23 ovarian cancer patients

Publication Title

Machine learning predicts individual cancer patient responses to therapeutic drugs with high accuracy.

Sample Metadata Fields

Sex, Specimen part, Disease

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accession-icon GSE1832
Time and Exercise effects on Human Skeletal Muscle
  • organism-icon Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U95 Version 2 Array (hgu95av2)

Description

Four healthy human volunteers underwent an acute bout of resistance exercise with the right leg at 2 pm. Biopsies were removed from the Vastus Lateralis muscle 6 h (8 pm) and 18 h (8 am) after exericise

Publication Title

Time- and exercise-dependent gene regulation in human skeletal muscle.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE33892
Comparison of TEX and M9-ENL1 cell lines to HL60 and THP1 cell lines
  • organism-icon Homo sapiens
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Gene regulatory networks that govern hematopoietic stem cells (HSC) and leukemiainitiating cells (L-IC) are deeply entangled. Thus, the discovery of compounds that target L-IC while sparing HSC is an attractive but difficult endeavor. Presently, most drug discovery approaches fail to counter-screen compounds against normal hematopoietic stem/progenitor cells (HSPC) to assess therapeutic index. Here, we present a combined in vitro and in vivo strategy to identify compounds specific to L-IC in acute myeloid leukemia (AML). A high-throughput screen of 4000 compounds on novel leukemia cell lines derived from human experimental leukemogenesis models yielded 80 hits, of which most were toxic to normal HSPC. Of the 10 compounds that passed this initial filter, we chose to characterize a single compound, kinetic riboside (KR), on AML L-IC and HSPC. KR demonstrated comparable efficacy to standard therapies against 63 primary AMLs. In vitro, KR effectively targeted the L-IC-enriched CD34+CD38- AML fraction, while sparing normal HSPC enriched fractions, although these effects were mitigated on HSC assayed in vivo, and highlights the importance of in vivo L-IC and HSC assays to measure function. Overall, we provide a novel approach to screen large drug libraries for the discovery of anti-L-IC compounds for human leukemias.

Publication Title

A small molecule screening strategy with validation on human leukemia stem cells uncovers the therapeutic efficacy of kinetin riboside.

Sample Metadata Fields

Cell line, Treatment

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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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