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accession-icon GSE2280
Prediction of lymphatic metastasis from primary squamous cell carcinoma of the oral cavity
  • organism-icon Homo sapiens
  • sample-icon 27 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Metastasis via the lymphatics is a major risk factor in squamous cell carcinoma of the oral cavity (OSCC). We sought to determine whether the presence of metastasis in the regional lymph node could be predicted by a gene expression signature of the primary tumor. A total of 18 OSCCs were characterized for gene expression by hybridizing RNA to Affymetrix U133A gene chips. Genes with differential expression were identified using a permutation technique and verified by quantitative RT-PCR and immunohistochemistry. A predictive rule was built using a support vector machine, and the accuracy of the rule was evaluated using crossvalidation on the original data set and prediction of an independent set of four patients. Metastatic primary tumors could be differentiated from nonmetastatic primary tumors by a signature gene set of 116 genes. This signature gene set correctly predicted the four independent patients as well as associating five lymph node metastases from the original patient set with the metastatic primary tumor group. We concluded that lymph node metastasis could be predicted by gene expression profiles of primary oral cavity squamous cell carcinomas. The presence of a gene expression signature for lymph node metastasis indicates that clinical testing to assess risk for lymph node metastasis should be possible.

Publication Title

Gene expression signature predicts lymphatic metastasis in squamous cell carcinoma of the oral cavity.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE16149
Examining smoking-induced differential gene expression changes in buccal mucosa
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

A tissue like buccal mucosa (from cheek swabs) would be an ideal sample material for rapid, easy collection for testing of biomarkers as an alternative to blood. A limited number of studies, primarily in the smoker/oral cancer literature, address this tissue's efficacy for quantitative PCR or microarray gene expression analysis. In this study both qPCR and microarray analyses were used to evaluate gene expression in buccal cells. An initial study comparing blood and buccal cells from the same individuals looked at relative amounts of four genes. The RNA isolated from buccal cells was degraded but was of sufficient quality to be used with RT-qPCR to detect expression of specific genes. Second, buccal cell RNA was used for microarray-based differential gene expression studies by comparing gene expression between smokers and nonsmokers. The isolation and amplification protocol allowed use of 150-fold less buccal cell RNA than had been reported previously with human microarrays. We report here the finding of a small number of significant gene expression differences between smokers and nonsmokers, using buccal cells as target material. Additionally, Gene Set Enrichment Analysis confirmed that these genes were changing expression in the same pattern as seen in an earlier buccal cell study performed by another group. Our results suggest that in spite of a high degree of RNA degradation, buccal cells from cheek mucosa could be used to detect differential gene expression between smokers and nonsmokers. However the RNA degradation, increase in sample variability and microarray failure rate show that buccal samples should be used with caution as source material in expression studies.

Publication Title

Examining smoking-induced differential gene expression changes in buccal mucosa.

Sample Metadata Fields

Specimen part

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accession-icon GSE50012
Comparison of cellular and transcriptional responses to 1,25-dihydroxyvitamin D3 and glucocorticoids in peripheral blood mononuclear cells
  • organism-icon Homo sapiens
  • sample-icon 72 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Glucocorticoids (GC) and 1,25-dihydroxyvitamin D3 (1,25(OH)2 D3) are steroid hormones with anti-inflammatory properties with enhanced effects when combined. We previously showed that transcriptional response to GCs was correlated with inter-individual and inter-ethnic cellular response. Here, we profiled cellular and transcriptional responses to 1,25(OH)2 D3 from the same donors. We studied cellular response to combined treatment with GCs and 1,25(OH)2 D3 in a subset of individuals least responsive to GCs. We found that combination treatment had significantly greater inhibition of proliferation than with either steroid hormone alone. Overlapping differentially expressed (DE) genes between the two hormones were enriched for adaptive and innate immune processes. Non-overlapping differentially expressed genes with 1,25(OH)2 D3 treatment were enriched for pathways involving the electron transport chain, while with GC treatment, non-overlapping genes were enriched for RNA-related processes. These results suggest that 1,25(OH)2 D3 enhances GC anti-inflammatory properties through a number of shared and non-shared transcriptionally-mediated pathways.

Publication Title

Comparison of cellular and transcriptional responses to 1,25-dihydroxyvitamin d3 and glucocorticoids in peripheral blood mononuclear cells.

Sample Metadata Fields

Sex, Age, Specimen part, Treatment

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accession-icon GSE20489
Microarray characterization of gene expression changes in blood during acute ethanol exposure
  • organism-icon Homo sapiens
  • sample-icon 51 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

As part of the civil aviation safety program to define the adverse effects of ethanol on flying performance, we present results of our DNA microarray analysis of samples from a timecourse study of individuals given ethanol orally, and then evaluated by breathalyzer to monitor blood alcohol content (BAC). At five blood alcohol levels, T1-T5, blood was drawn such that the samples represented 0%, 0.04%, 0.08% BAC, and return to 0.04%, and 0.02% BAC. Microarray analysis showed that changes in gene expression could be detected across the time-course. We verified these expression changes by quantitative polymerase chain reaction (qPCR). Candidate target genes identified from the microarray analysis were clustered by expression change pattern, examined for shared functions and functional network membership. Five coordinately expressed groups were revealed and functional analysis showed shared transcription factor binding sites and functions for members of the clusters. These functions include protein synthesis and modification, expected for changes in gene expression, hematological and immune functions, expected for a blood sample, and pancreatic and hepatic function, expected as response to ethanol. The results provide a first look at changing gene expression patterns in blood during acute increase of ethanol concentration and its depletion due to metabolism or excretion and demonstrate that it is possible to detect significant changes in gene expression using total RNA isolated from whole blood. The analysis approach for this study can be utilized as part of a workflow to identify target genes by timecourse changes in gene expression that may affect pilot performance.

Publication Title

Microarray characterization of gene expression changes in blood during acute ethanol exposure.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE98582
Exploring gene expression biomarker candidates for neurobehavioral impairment from total sleep deprivation
  • organism-icon Homo sapiens
  • sample-icon 555 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Exploring gene expression biomarker candidates for neurobehavioral impairment from total sleep deprivation.

Sample Metadata Fields

Subject, Time

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accession-icon GSE98564
Gene expression biomarkers for neurobehavioral impairment from total sleep deprivation microarray data [D6]
  • organism-icon Homo sapiens
  • sample-icon 199 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Healthy human adults were recruited to a sleep lab at Washington State University and remained there 7 consecutive days. Six received a well-rested Control condition of 10 h Time-In-Bed (TIB) nightly.

Publication Title

Exploring gene expression biomarker candidates for neurobehavioral impairment from total sleep deprivation.

Sample Metadata Fields

Subject, Time

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accession-icon GSE98565
Gene expression biomarkers for neurobehavioral impairment from total sleep deprivation microarray data [D8]
  • organism-icon Homo sapiens
  • sample-icon 193 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Healthy human adults were recruited to a sleep lab at Washington State University and remained there 7 consecutive days. Six received a well-rested Control condition of 10 h Time-In-Bed (TIB) nightly.

Publication Title

Exploring gene expression biomarker candidates for neurobehavioral impairment from total sleep deprivation.

Sample Metadata Fields

Subject, Time

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accession-icon GSE98566
Gene expression biomarkers for neurobehavioral impairment from total sleep deprivation microarray data [D9]
  • organism-icon Homo sapiens
  • sample-icon 163 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Healthy human adults were recruited to a sleep lab at Washington State University and remained there 7 consecutive days. Six received a well-rested Control condition of 10 h Time-In-Bed (TIB) nightly.

Publication Title

Exploring gene expression biomarker candidates for neurobehavioral impairment from total sleep deprivation.

Sample Metadata Fields

Subject, Time

View Samples
accession-icon GSE58203
Stimulation of RA SFBs with IL1 or PDGF-D
  • organism-icon Homo sapiens
  • sample-icon 59 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Synovial fibroblasts of 6 RA patients were treated with IL1 or PDGF-D. The aim of this study was to outline mechanism of the disease RA by a treatment with one of these cytokines.

Publication Title

Novel application of multi-stimuli network inference to synovial fibroblasts of rheumatoid arthritis patients.

Sample Metadata Fields

Treatment, Subject, Time

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accession-icon GSE56789
Enrichment of inflammatory bowel disease and colorectal cancer risk variants in colon expression quantitative trait loci
  • organism-icon Homo sapiens
  • sample-icon 40 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Genome wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with diseases of the colon including inflammatory bowel diseases (IBD) and colorectal cancer (CRC). However, the functional role of many of these SNPs is largely unknown and tissue-specific resources are lacking. Expression quantitative trait loci (eQTL) mapping identifies target genes of disease-associated SNPs. Here, we comprehensively map eQTLs in the human colon, assess their relevance for GWAS of colonic diseases and provide functional characterization.

Publication Title

Enrichment of inflammatory bowel disease and colorectal cancer risk variants in colon expression quantitative trait loci.

Sample Metadata Fields

Sex, 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)

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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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