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accession-icon GSE6344
Gene expression in Stage 1,2 Normal and Tumor kidney cancer
  • organism-icon Homo sapiens
  • sample-icon 40 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Although renal cell carcinoma (RCC) is the sixth-leading cause of cancer death, the molecular events leading to disease onset and progression are not well understood. Genomic profiling of clear cell RCC (cRCC) patients indicated that loss of a negative regulator of the Wnt pathway, secreted frizzled-related protein 1 (sFRP1), occurred in the majority of more than 100 patients tested. To our knowledge, this is the first report of loss of sFRP1 expression in patients diagnosed with cRCC; this loss occurs in early stage cRCC, suggesting that it may be an important early event in renal carcinogenesis. Genomic profiling of patient matched normal and cRCC tissues identified Wnt regulated genes to be aberrantly increased in cRCC tissues suggesting sFRP1 suppresses Wnt signaling in cRCC. In order to test the hypothesis that sFRP1 acts as a tumor suppressor in cRCC, we have stably expressed sFRP1 in cRCC cells. sFRP1 expression in cRCC cells resulted in decreased growth in cell culture, inhibition of anchorage-independent growth, and decreased tumor volume in a nude mouse model. Together these data suggest an important role for sFRP1 as a tumor suppressor in cRCC.

Publication Title

Secreted frizzled-related protein 1 loss contributes to tumor phenotype of clear cell renal cell carcinoma.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE85457
Gene array analysis of anaplastic thyroid carcinoma cell lines versus normal thyroid cell lines
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Currently there is a lack of effective therapies which result in long-term durable response for patients presenting with anaplastic thyroid carcinoma (ATC), a very rare and lethal variant of thyroid cancer. ATC is resistant to chemotherapy, radiation, and targeted therapies currently available.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part

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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 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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accession-icon GSE6477
Expression data from different stages of plasma cell neoplasm
  • organism-icon Homo sapiens
  • sample-icon 160 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Multiple myeloma is a relatively common B-cell malignancy that is currently incurable. Certain recurrent genetic abnormalities characteristics of different genetic subtypes have been described. Hyperdiploid myeloma characterized by recurrent trisomies is the most common genetic subtypes. However little is know about it's biology. Another common genetic abnormality is chromosome 13 deletion which is also associated with inferior prognosis. This abnormality is already present at the pre-malignant MGUS stage and is clonally selected with disease progression. Although it is biologically and clinically important the molecular consequence of chromosome 13 deletion is unknown.

Publication Title

Molecular dissection of hyperdiploid multiple myeloma by gene expression profiling.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE46699
Smoking and Obesity Related Molecular Alterations in Clear Cell Renal Cell Carcinoma
  • organism-icon Homo sapiens
  • sample-icon 124 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Both cigarette smoking and obesity have been implicated in increased risk of clear cell renal cell carcinoma (ccRCC); however, there are limited data regarding the molecular mechanisms that underlie these associations. We used a multi-stage design to identify and validate specific molecular targets that are associated with smoking or obesity-related ccRCC.

Publication Title

ANKS1B is a smoking-related molecular alteration in clear cell renal cell carcinoma.

Sample Metadata Fields

Specimen part, Subject

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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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