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accession-icon GSE66175
Imporatance of substantial weight loss for altering gene expression during intensive cardiovascular lifestyle modification
  • organism-icon Homo sapiens
  • sample-icon 479 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

The objective of this study was to examine relationships between weight loss through changes in lifestyle and peripheral blood gene expression profiles. Substantial weight loss (-15.2+3.8%) in lifestyle participants was associated with improvement in selected cardiovascular risk factors and significant changes in peripheral blood gene expression from pre- to post-intervention: 132 unique genes showed significant expression changes related to immune function and inflammatory responses involving endothelial activation.

Publication Title

Importance of substantial weight loss for altering gene expression during cardiovascular lifestyle modification.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE46097
Expression data of Participants of Ornish intervention and Control group
  • organism-icon Homo sapiens
  • sample-icon 377 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Intensive lifestyle modification is believed to mediate cardiovascular disease (CVD) risk through traditional pathways that affect endothelial function and progression of atherosclerosis; however, the extent, persistence, and clinical significance of molecular change during lifestyle modification are not well known. Our study reveals that gene expression signatures are significantly modulated by rigorous lifestyle behaviors and track with CVD risk profiles over time.

Publication Title

Intensive cardiovascular risk reduction induces sustainable changes in expression of genes and pathways important to vascular function.

Sample Metadata Fields

Sex, Age

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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 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 GSE70559
Gene expression patterns associated with histopathology in toxic liver injury
  • organism-icon Rattus norvegicus
  • sample-icon 94 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 2.1 ST Array (ragene21st)

Description

Predicting liver injury after exposure to toxic industrial chemicals is complicated by the large number of potential environmental contaminants, mixtures, and exposure dose and route scenarios. Identifying indicators of end organ injury can complement exposure-based assays and improve predictive power. A multiplexed approach was used to experimentally evaluate a panel of 67 genes predicted to be fibrogenic by computationally mining DrugMatrix, a publicly available repository of gene microarray data. Five-day oral gavage studies in male Sprague-Dawley rats dosed with varying concentrations of three fibrogenic compounds (allyl alcohol, carbon tetrachloride, and 4,4-methylenedianiline) and two non-fibrogenic compounds (bromobenzene and dexamethasone) were conducted. Fibrosis was definitively diagnosed by histopathology. Transcriptomics data matched the predictions made using the DrugMatrix data with greater than 90% accuracy. Microarray data were verified using a 67-plex panel Bioplex assay, confirming that the 67-plex panel constituted a biomolecular signature of hepatic fibrosis (Figure). Necrosis and inflammatory infiltration were comorbid with fibrosis. Interaction analysis identified 24 genes specific for the fibrosis phenotype. The protein product of the gene most strongly correlated with the fibrosis phenotype (Pcolce) was dose-dependently elevated in plasma from animals administered fibrogenic chemicals (p<0.05). PCOLCE is a novel biomarker candidate of fibrotic injury. These results support the development of gene panels for liver injury and may suggest bridging biomarkers for molecular mediators linked to histopathology.

Publication Title

Gene Expression Patterns Associated With Histopathology in Toxic Liver Fibrosis.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE35428
Transcriptional profiling of clinically relevant SERMs and SERM/estradiol complexes in a cellular model of breast cancer
  • organism-icon Homo sapiens
  • sample-icon 106 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

In this study, we have utilized microarray analysis to directly compare a subset of structurally distinct, clinically relevant SERMs in the presence and absence of estradiol, using a high replicate number (10) to ensure detection of modestly regulated genes.

Publication Title

Research resource: Transcriptional profiling in a cellular model of breast cancer reveals functional and mechanistic differences between clinically relevant SERM and between SERM/estrogen complexes.

Sample Metadata Fields

Cell line

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accession-icon GSE4490
Clenbuterol administration in mouse muscle
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430A Array (moe430a)

Description

Background: Beta-adrenergic receptor agonists (BA) induce skeletal muscle hypertrophy, yet specific mechanisms that lead to this effect are not well understood. The objective of this research was to identify novel genes and physiological pathways that potentially facilitate BA induced skeletal muscle growth. We chose to evaluate global changes in gene expression by utilizing the Affymetrix platform to identify gene expression changes in mouse skeletal muscle. Changes in gene expression were evaluated 24 h (1D) and 10 days (10D) after administration of the BA clenbuterol.

Publication Title

Changes in skeletal muscle gene expression following clenbuterol administration.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE56973
Functional and evolutionary significance of human microRNA seed region mutations
  • organism-icon Homo sapiens
  • sample-icon 23 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

Functional and evolutionary significance of human microRNA seed region mutations.

Sample Metadata Fields

Cell line

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accession-icon SRP049815
RNA-seq analysis of differences in gene expression between dorsal and ventral MEC
  • organism-icon Mus musculus
  • sample-icon 16 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Neural circuits in the medial entorhinal cortex (MEC) encode an animal’s position and orientation in space. Within the MEC spatial representations, including grid and directional firing fields, have a laminar and dorsoventral organization that corresponds to a similar topography of neuronal connectivity and cellular properties. Yet, in part due to the challenges of integrating anatomical data at the resolution of cortical layers and borders, we know little about the molecular components underlying this organization. To address this we develop a new computational pipeline for high-throughput analysis and comparison of in situ hybridization (ISH) images at laminar resolution. We apply this pipeline to ISH data for over 16,000 genes in the Allen Brain Atlas and validate our analysis with RNA sequencing of MEC tissue from adult mice. We find that differential gene expression delineates the borders of the MEC with neighboring brain structures and reveals its laminar and dorsoventral organization. Our analysis identifies ion channel-, cell adhesion- and synapse-related genes as candidates for functional differentiation of MEC layers and for encoding of spatial information at different scales along the dorsoventral axis of the MEC. Our results support the hypothesis that differences in gene expression contribute to functional specialization of superficial layers of the MEC and dorsoventral organization of the scale of spatial representations. Overall design: Examination of dorsal and ventral regions from 4 replicate samples each containing pooled data from 3-4 mice

Publication Title

Laminar and dorsoventral molecular organization of the medial entorhinal cortex revealed by large-scale anatomical analysis of gene expression.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP067173
HSB-2 cells stably expressing LDB1 or mutant LDB1 proteins
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

LMO2 is a component of multisubunit DNA-binding transcription factor complexes that regulate gene expression in hematopoietic stem and progenitor cell development. Enforced expression of LMO2 causes leukemia by inducing hematopoietic stem cell-like features in T-cell progenitor cells, but the biochemical mechanisms of LMO2 function have not been fully elucidated. In this study we systematically dissected the LMO2/LDB1 binding interface to investigate the role of this interaction in T-cell leukemia. Alanine scanning mutagenesis of the LIM interaction domain of LDB1 revealed a discrete motif R320LITR required for LMO2 binding. Most strikingly, co-expression of full length, wild type LDB1 increased LMO2 steady state abundance, whereas co-expression of mutant proteins deficient in LMO2 binding compromised LMO2 stability. These mutant LDB1 proteins also exerted dominant negative effects on growth and transcription in diverse leukemic cell lines. Raw gene expression data on HSB-2 cells is presented here. Overall design: RNAseq were performed on HSB cell lines to examine their expression patterns

Publication Title

LMO2 Oncoprotein Stability in T-Cell Leukemia Requires Direct LDB1 Binding.

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)

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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