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accession-icon GSE69818
COPD lung tissue expression
  • organism-icon Homo sapiens
  • sample-icon 70 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U219 Array (hgu219)

Description

Comparison of emphysema vs non emphysema COPD lung tissue expression

Publication Title

Network Analysis of Lung Transcriptomics Reveals a Distinct B-Cell Signature in Emphysema.

Sample Metadata Fields

Specimen part

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accession-icon GSE103174
Expression data from lung tissue in mild-moderate COPD
  • organism-icon Homo sapiens
  • sample-icon 53 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U219 Array (hgu219)

Description

Rationale: Chronic Obstructive Pulmonary Disease (COPD) is associated with a complex pulmonary and systemic immune response.

Publication Title

No associated publication

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE33455
Expression data from docetaxel-resistant prostate cancer cell lines
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Docetaxel-based chemotherapy is the standard first-line therapy in metastatic castration-resistant prostate cancer. However, most patients eventually develop resistance to this treatment.

Publication Title

Identification of docetaxel resistance genes in castration-resistant prostate cancer.

Sample Metadata Fields

Disease, Disease stage, Cell line, Treatment

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accession-icon GSE49531
Gene expression data from lymphoblastoid cell lines from participants in the Genetics of Microangiopathic Brain Injury study
  • organism-icon Homo sapiens
  • sample-icon 883 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

European-American individuals of the GENOA cohort participating in the Genetics of Microangiopathic Brain Injury substudy, which investigates the genetic basis of alteration in brain structure detectable by magnetic resonance imaging.

Publication Title

No associated publication

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE23120
Basal gene expression data from Human Variation Panel
  • organism-icon Homo sapiens
  • sample-icon 286 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We used microarrays to identify the variation of basal gene expression level among 287 lymphoblastoid cell lines.

Publication Title

Radiation pharmacogenomics: a genome-wide association approach to identify radiation response biomarkers using human lymphoblastoid cell lines.

Sample Metadata Fields

Specimen part

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accession-icon GSE20161
Networks and miRNAs implicated in aggressive prostate cancer
  • organism-icon Homo sapiens
  • sample-icon 90 Downloadable Samples
  • Technology Badge IconIllumina human-6 v2.0 expression beadchip

Description

Background: Prostate cancer (PC), a complex disease, can be relatively harmless or extremely aggressive. To identify candidate genes involved in causal pathways of aggressive PC, we implemented a systems biology approach by combining differential expression analysis and co-expression network analysis to evaluate transcriptional profiles using lymphoblastoid cell lines from 62 PC patients with aggressive phenotype (Gleason grade > 8) and 63 PC patients with nonaggressive phenotype (Gleason grade < 5). From 13935 mRNA genes and 273 microRNAs tested, we identified significant differences in 1100 mRNAs and 7 microRNAs with false discovery rate < 0.01. We also identified a co-expression module demonstrating significant association with the aggressive phenotype of PC (p=3.67x10-11). The module of interest was characterized by over-representation of cell cycle-related genes (false discovery rate = 3.50x10-50). From this module, we further defined 20 hub genes that were highly connected to other genes. Interestingly, five of the 7 differentially expressed microRNAs have been implicated in cell cycle regulation and two (miR-145 and miR-331-3p) are predicted to target three of the 20 hub genes. Ectopic expression of these two microRNAs reduced expression of target hub genes and subsequently resulted in cell growth inhibition and apoptosis. These results suggest that cell cycle is likely to be a molecular pathway causing aggressive phenotype of PC. Further characterization of cell cycle-related genes (particularly, the hub genes) and miRNAs that regulate these hub genes could facilitate identification of candidate genes responsible for the aggressive phenotype and lead to a better understanding of PC etiology and progression [Cancer Res 2009;69(24):94907].

Publication Title

Gene networks and microRNAs implicated in aggressive prostate cancer.

Sample Metadata Fields

Cell line

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accession-icon GSE8512
Expression data from mouse bone marrow macrophages from a strain intercross
  • organism-icon Mus musculus
  • sample-icon 207 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Bone marrow macrophages were cultured from 16 week old apoE-deficient F2 mice from an AKRxDBA/2 intercross

Publication Title

Sex specific gene regulation and expression QTLs in mouse macrophages from a strain intercross.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE46480
Peripheral blood mononuclear cell (PBMC) gene expression in healthy adults rapidly transported to high altitude
  • organism-icon Homo sapiens
  • sample-icon 194 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Differential expression analysis comparing healthy volunteers at sea level and after acute exposure to altitude

Publication Title

No associated publication

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE40791
Usp44 binds centrin to regulate centrosome positioning and suppress tumorigenesis
  • organism-icon Homo sapiens
  • sample-icon 192 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Most human tumors have abnormal numbers of chromosomes, a condition known as aneuploidy. The mitotic checkpoint is an important mechanism that prevents aneuploidy through restraining the activity of the anaphase-promoting complex (APC). USP44 was identified as a key regulator of APC activation that maintains the association of MAD2 with the APC co-activator Cdc20. However, the physiological importance of USP44 and its impact on cancer biology are unknown. Here, we show that USP44 is required to prevent tumors in mice and is frequently down-regulated in human lung cancer. USP44 inhibits chromosome segregation errors independently of its role in the mitotic checkpoint by regulating proper centrosome separation, positioning, and mitotic spindle geometry, functions that require direct binding to the centriole protein, centrin. These data reveal a new role for the ubiquitin system in mitotic spindle regulation and underscore the importance of USP44 in the pathogenesis of human cancer.

Publication Title

USP44 regulates centrosome positioning to prevent aneuploidy and suppress tumorigenesis.

Sample Metadata Fields

Sex, Disease, Disease stage

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accession-icon GSE14794
Genome-wide Transcriptional Profiling Reveals MicroRNA-correlated Genes and Pathways in Human Lymphoblastoid Cell Lines
  • organism-icon Homo sapiens
  • sample-icon 90 Downloadable Samples
  • Technology Badge IconIllumina human-6 v2.0 expression beadchip

Description

Background: Expression level of many genes shows abundant natural variation in human populations. The variations in gene expression are believed to contribute to phenotypic differences. Emerging evidence has shown that microRNAs (miRNAs) are one of the key regulators of gene expression. However, past studies have focused on the miRNA target genes and use loss- or gain-of-function approach that may not reflect natural association between miRNA and mRNAs. Methodology/Principal Findings: To examine miRNA regulatory effect on global gene expression under endogenous condition, we performed pair-wise correlation coefficient analysis on expression levels of 366 miRNAs and 14,174 messenger RNAs (mRNAs) in 90 immortalized lymphoblastoid cell lines, and observed significant correlations between the two species of RNA transcripts. We identified a total of 7,207 significantly correlated miRNA-mRNA pairs (false discovery rate q <0.01). Of those, 4,085 pairs showed positive correlations while 3,122 pairs showed negative correlations. Gene ontology analyses on the miRNA-correlated genes revealed significant enrichments in several biological pathways related to cell cycle, cell communication and signal transduction. Individually, each of three miRNAs (miR-331, -98 and -33b) demonstrated significant correlation with the genes in cell cycle-related biological processes, which is consistent with important role of miRNAs in cell cycle regulation. Surprisingly, most miRNA-correlated genes were not direct targets predicted by mRNA target prediction program, TargetScan, suggesting indirect endogenous relationship between miRNAs and their correlated mRNAs. Conclusions/Significance: This study demonstrates feasibility of using naturally expressed transcript profiles to identify endogenous correlation between miRNA and miRNA. By applying this genome-wide approach, we have identified thousands of miRNA-correlated genes and revealed potential role of miRNAs in several important cellular functions. The study results along with accompanying data sets will provide a wealth of high-throughput data to further evaluate the miRNA-regulated genes and eventually in phenotypic variations of human populations.

Publication Title

Genome-wide transcriptional profiling reveals microRNA-correlated genes and biological processes in human lymphoblastoid cell lines.

Sample Metadata Fields

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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