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accession-icon GSE71620
The effects of aging on circadian patterns of gene expression in the human prefrontal cortex
  • organism-icon Homo sapiens
  • sample-icon 419 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.1 ST Array (hugene11st)

Description

With aging, significant changes in circadian rhythms occur, including a shift in phase toward a morning chronotype and a loss of rhythmicity in circulating hormones. However, the effects of aging on molecular rhythms in the human brain have remained elusive. Here we employed a previously-described time-of-death analyses to identify transcripts throughout the genome that have a significant circadian rhythm in expression in the human prefrontal cortex (Brodmanns areas (BA) 11 and 47). Expression levels were determined by microarray analysis in 146 individuals. Rhythmicity in expression was found in ~10% of detected transcripts (p<0.05). Using a meta-analysis across the two brain areas, we identified a core set of 235 genes (q<0.05) with significant circadian rhythms of expression. These 235 genes showed 92% concordance in the phase of expression between the two areas. In addition to the canonical core circadian genes, a number of other genes were found to exhibit rhythmic expression in the brain. Notably, we identified more than one thousand genes (1186 in BA11; 1591 in BA47) that exhibited age-dependent rhythmicity or alterations in rhythmicity patterns with aging. Interestingly, a set of transcripts gained rhythmicity in older individuals, which may represent a compensatory mechanism due to a loss of canonical clock function. Thus, we confirm that rhythmic gene expression can be reliably measured in human brain and identified for the first time significant changes in molecular rhythms with aging that may contribute to altered cognition, sleep and mood in later life.

Publication Title

Effects of aging on circadian patterns of gene expression in the human prefrontal cortex.

Sample Metadata Fields

Sex, Age, Specimen part, Race

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accession-icon GSE87610
Gene expression of L3 and L5 pyramidal neurons in the DLPFC comparing schizophrenia from bipolar major depressive disorders and unaffected subjects.
  • organism-icon Homo sapiens
  • sample-icon 286 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U219 Array (hgu219)

Description

Impairments in certain cognitive processes (e.g., working memory) are typically most pronounced in schizophrenia (SZ), intermediate in bipolar disorder (BP) and least in major depressive disorder (MDD).

Publication Title

Transcriptome Alterations in Prefrontal Pyramidal Cells Distinguish Schizophrenia From Bipolar and Major Depressive Disorders.

Sample Metadata Fields

Specimen part

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accession-icon GSE93987
Distinctive transcriptome alterations of prefrontal pyramidal neurons in schizophrenia and schizoaffective disorder
  • organism-icon Homo sapiens
  • sample-icon 207 Downloadable Samples
  • Technology Badge Icon Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)

Description

Schizophrenia is associated with alterations in working memory that reflect dysfunction of dorsolateral prefrontal cortex (DLPFC) circuitry. Working memory depends on the activity of excitatory pyramidal cells in DLPFC layer 3, and to a lesser extent in layer 5.

Publication Title

Distinctive transcriptome alterations of prefrontal pyramidal neurons in schizophrenia and schizoaffective disorder.

Sample Metadata Fields

Specimen part

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accession-icon GSE93577
Gene expression of L3 parvalbumin neurons in the DLPFC comparing schizophrenia with unaffected subjects
  • organism-icon Homo sapiens
  • sample-icon 141 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U219 Array (hgu219)

Description

Schizophrenia is associated with dysfunction of the dorsolateral prefrontal cortex (DLPFC). This dysfunction is manifest as cognitive deficits that appear to arise from disturbances in gamma frequency oscillations.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part

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accession-icon GSE17025
Gene Expression Analysis of Stage I Endometrial Cancers
  • organism-icon Homo sapiens
  • sample-icon 103 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Global gene expression patterns associated with early stage endometrial cancer have been reported, but changes in molecular expression associated with tumor grade, depth of myometrial invasion, and non-endometrioid histology have not been previously elucidated. Our group hypothesized there are unique genetic events underlying early endometrial carcinogenesis. Ninety-two samples of pathologically reviewed stage I endometrial cancers (80 endometrioid and 12 serous) with a heterogeneous distribution of grade and depth of myometrial invasion (i.e. 9 IAG1, 14 IAG2, 7 IAG3, 14 IBG1, 12 IBG2, 13 IBG3, 7 ICG1, 10 ICG2, and 6 ICG3) were examined in relation to 12 samples of atrophic endometrium from postmenopausal women. Specimens were analyzed using oligonucleotide microarray analysis and a subset of the differentially expressed transcripts was validated using quantitative PCR. Comparison of early stage cancers with normal endometrium samples by the univariate t-test with 10,000 permutations identified 900 genes that were differentially regulated by at least 4-fold at a p value of <0.001. Unsupervised analysis revealed that when compared to normal endometrium, serous and endometrioid stage I cancers appeared to have similar expression patterns. However, when compared in the absence of normal controls, they were distinct. Differential expression analysis revealed a number of transcripts that were common as well as unique to both histologic types. This data uncovers previously unrecognized, novel pathways involved in early stage endometrial cancers and identifys targets for prevention strategies that are inclusive of both endometrioid and serous histologic subtypes.

Publication Title

Identifier mapping performance for integrating transcriptomics and proteomics experimental results.

Sample Metadata Fields

Age, Disease stage, Race

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accession-icon GSE157738
Monocyte-derived DC Expression Data from Advanced Staged Melanoma Patients
  • organism-icon Homo sapiens
  • sample-icon 102 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

The metastatic form of Melanoma has a reported ten-year survival rate of approximately 15%. Clinical trials have shown modest success in a subset of patients. Particularly, combinational therapy using checkpoint blockade has shown the most success, but many patients do not respond. The patients that do respond to treatments often have a pre-existing antitumor immunity.

Publication Title

Dysregulated NF-κB-Dependent ICOSL Expression in Human Dendritic Cell Vaccines Impairs T-cell Responses in Patients with Melanoma.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE81612
Active estrogen receptor-alpha signaling in ovarian cancer
  • organism-icon Homo sapiens
  • sample-icon 56 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

High-grade serous ovarian cancer (HGSOC) is an aggressive disease with few available targeted therapies. Despite high expression of estrogen receptor-alpha (ER) in ~80% of HGSOC and some small but promising clinical trials of endocrine therapy, ER has been understudied as a target in this disease. Results: Proliferation is ER-regulated in HGSOC cells in vitro and in vivo, and is in part dependent on 3-D context. Transcriptomic studies identified genes shared by cell lines and PDX explants as ER targets. The selective ER down-regulator (SERD) fulvestrant is more effective than tamoxifen in blocking ER action. ER H-score was predictive of efficacy of endocrine therapy, and this prediction could be further improved by inclusion of target gene expression, especially that of IGFBP3. Conclusion: Laboratory models corroborate intertumor heterogeneity of endocrine response in HGSOC but identify features associated with functional ER and endocrine responsiveness. Assessing ER function (e.g. IGFBP3 expression) in conjunction with ERH-score may help select patients who would benefit from endocrine therapy. Our preclinical data suggest that SERDs might be more effective than tamoxifen.

Publication Title

No associated publication

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE67089
Analysis of mRNA profiles distinguishes proneural (PN) glioma stem cells (GSC) from mesenchymal (Mes) GSCs
  • organism-icon Homo sapiens
  • sample-icon 48 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U219 Array (hgu219)

Description

Tumor heterogeneity of high-grade glioma (HGG) is recognized by four clinically relevant subtypes based on core gene signatures. However, molecular signaling in glioma stem cells (GSCs) in individual HGG subtypes is poorly characterized. Here we identified and characterized two mutually exclusive GSC subtypes with distinct dysregulated signaling pathways. Analysis of mRNA profiles distinguished proneural (PN) from mesenchymal (Mes) GSCs and revealed a pronounced correlation with the corresponding PN or Mes HGGs. Mes GSCs displayed more aggressive phenotypes in vitro and as intracranial xenografts in mice. Further, Mes GSCs were markedly resistant to radiation compared with PN GSCs. The glycolytic pathway, comprising aldehyde dehydrogenase (ALDH) family genes and in particular ALDH1A3, were enriched in Mes GSCs. Glycolytic activity and ALDH activity were significantly elevated in Mes GSCs but not in PN GSCs. Expression of ALDH1A3 was also increased in clinical HGG compared with low-grade glioma or normal brain tissue. Moreover, inhibition of ALDH1A3 attenuated the growth of Mes but not PN GSCs. Last, radiation treatment of PN GSCs up-regulated Mes-associated markers and downregulated PN-associated markers, whereas inhibition of ALDH1A3 attenuated an irradiation-induced gain of Mes identity in PN GSCs. Taken together, our data suggest that two subtypes of GSCs, harboring distinct metabolic signaling pathways, represent intertumoral glioma heterogeneity and highlight previously unidentified roles of ALDH1A3-associated signaling that promotes aberrant proliferation of Mes HGGs and GSCs. Inhibition of ALDH1A3- mediated pathways therefore might provide a promising therapeutic approach for a subset of HGGs with the Mes signature.

Publication Title

Mesenchymal glioma stem cells are maintained by activated glycolytic metabolism involving aldehyde dehydrogenase 1A3.

Sample Metadata Fields

Specimen part

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accession-icon GSE18121
Gene expression regulation in response to heat stress in different yeast strains
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 42 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome S98 Array (ygs98)

Description

Different yeast strains were subjected to heat stresss; samples were collected at 0, 5, 10, 15, 20, 25 and 30 minutes after heat stress; microarray analysis were performed using the Affymetrix Y-GS98 microarray.

Publication Title

Revealing a signaling role of phytosphingosine-1-phosphate in yeast.

Sample Metadata Fields

Time

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accession-icon GSE50695
Endocrine response in invasive lobular carcinoma is characterized by unique estrogen-mediated gene expression and de novo tamoxifen resistance
  • organism-icon Homo sapiens
  • sample-icon 37 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Invasive lobular carcinoma cell lines are characterized by unique estrogen-mediated gene expression patterns and altered tamoxifen response.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Time

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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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