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accession-icon GSE99324
Transcriptome-based network analysis reveals renal cell type-specific dysregulation of hypoxia-associated transcripts [HK2]
  • organism-icon Homo sapiens
  • sample-icon 25 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Accumulating evidence suggests that dysregulation of hypoxia-regulated transcriptional mechanisms is involved in development of chronic kidney diseases (CKD). However, it remains unclear how hypoxia-induced transcription factors (HIFs) and subsequent biological processes contribute to CKD development and progression. In our study, genome-wide expression profiles of more than 200 renal biopsies from patients with different CKD stages revealed significant correlation of HIF-target genes with eGFR in glomeruli and tubulointerstitium. These correlations were positive and negative and in part compartment-specific. Microarrays of proximal tubular cells and podocytes with stable HIF1 and/or HIF2 suppression displayed cell type-specific HIF1/HIF2-dependencies as well as dysregulation of several pathways. WGCNA analysis identified gene sets that were highly coregulated within modules. Characterization of the modules revealed common as well as cell group- and condition-specific pathways, GO-Terms and transcription factors. Gene expression analysis of the hypoxia-interconnected pathways in patients with different CKD stages revealed an increased dysregulation with loss of renal function. In conclusion, our data clearly point to a compartment- and cell type-specific dysregulation of hypoxia-associated gene transcripts and might help to improve the understanding of hypoxia, HIF dysregulation, and transcriptional program response in CKD.

Publication Title

Transcriptome-based network analysis reveals renal cell type-specific dysregulation of hypoxia-associated transcripts.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE99323
Transcriptome-based network analysis reveals renal cell type-specific dysregulation of hypoxia-associated transcripts [AB81]
  • organism-icon Homo sapiens
  • sample-icon 21 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Accumulating evidence suggests that dysregulation of hypoxia-regulated transcriptional mechanisms is involved in development of chronic kidney diseases (CKD). However, it remains unclear how hypoxia-induced transcription factors (HIFs) and subsequent biological processes contribute to CKD development and progression. In our study, genome-wide expression profiles of more than 200 renal biopsies from patients with different CKD stages revealed significant correlation of HIF-target genes with eGFR in glomeruli and tubulointerstitium. These correlations were positive and negative and in part compartment-specific. Microarrays of proximal tubular cells and podocytes with stable HIF1 and/or HIF2 suppression displayed cell type-specific HIF1/HIF2-dependencies as well as dysregulation of several pathways. WGCNA analysis identified gene sets that were highly coregulated within modules. Characterization of the modules revealed common as well as cell group- and condition-specific pathways, GO-Terms and transcription factors. Gene expression analysis of the hypoxia-interconnected pathways in patients with different CKD stages revealed an increased dysregulation with loss of renal function. In conclusion, our data clearly point to a compartment- and cell type-specific dysregulation of hypoxia-associated gene transcripts and might help to improve the understanding of hypoxia, HIF dysregulation, and transcriptional program response in CKD.

Publication Title

Transcriptome-based network analysis reveals renal cell type-specific dysregulation of hypoxia-associated transcripts.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE43106
Phenotypic comparison of common mouse strains developing high-fat diet-induced hepatosteatosis
  • organism-icon Mus musculus
  • sample-icon 72 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Genetic predisposition and environmental components contribute to an individuals non-alcoholic fatty liver disease (NAFLD) susceptibility. Therefore, we compared phenotypic variations of mouse strains extensively used in biomedical research during induction of high-fat diet (HFD)-mediated NAFLD and assessed transcriptional alterations in livers. In a time-resolved fashion we determined a wide spectrum of physiological parameters in C3HeB/FeJ (C3H), C57BL/6NTac, C57BL/6J, and 129P2/OlaHsd (129) males during a 7, 14, or 21 days HFD challenge and performed gene transcription analyses in steatotic livers.

Publication Title

Phenotypic comparison of common mouse strains developing high-fat diet-induced hepatosteatosis.

Sample Metadata Fields

Sex, Age, Treatment

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accession-icon GSE48615
High fat diet-induced modifications in membrane lipid and mitochondrial-membrane protein signatures precede the development of hepatic insulin resistance in mice
  • organism-icon Mus musculus
  • sample-icon 42 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

In this survey we effectively combined transcriptomics, proteomics and targeted-metabolomics to analyse the temporal relationship of alterations in liver preceding and accompanying the development of HFD-mediated hepatic insulin resistance. To assess HFD-mediated alterations in physiological parameters, insulin sensitivity, and molecular adaptations in liver male C3HeB/FeJ mice treated with a high-fat diet (HFD) for 7, 14, or 21 days and compared to age- matched controls fed low-fat diet (LFD).

Publication Title

High fat diet-induced modifications in membrane lipid and mitochondrial-membrane protein signatures precede the development of hepatic insulin resistance in mice.

Sample Metadata Fields

Sex, Age, Treatment, Time

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accession-icon GSE104818
Expression data from APA+ and APA- progenitors and SSEA5+ human pluripotent stem cells
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

Human embryonic stem cells (hESC) can be differentiated into progenitors resembling trophoblast upon exposure to BMP4. Putative trophpblast progenitors express APA cell surface marker

Publication Title

No associated publication

Sample Metadata Fields

Cell line

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accession-icon GSE23704
Gene expression profiling on bronchoalveolar lavage (BAL) cells treated with all-trans-retinoic acid (ATRA)
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

All-trans retinoic acid (ATRA) is a potent retinoid, which has been used successfully in different clinical settings as a potential drug to treat COPD and emphysema. In alveolar macrophages, ATRA selectively down-regulates MMP-9 and up-regulates TIMP-1 expression.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part

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accession-icon GSE12417
Prognostic gene signature for normal karyotype AML
  • organism-icon Homo sapiens
  • sample-icon 404 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Patients with cytogenetically normal acute myeloid leukemia (CN-AML) show heterogeneous treatment outcomes. We used gene expression profiling to develop a gene signature that predicts overall survival (OS) in CN-AML. Based on data from 163 patients treated in the German AMLCG 1999 trial and analyzed on oligonucleotide microarrays, we used supervised principal component analysis to identify 86 probe sets (representing 66 different genes) which correlated with OS, and defined a prognostic score based on this signature. When applied to an independent cohort of 79 CN-AML patients, this continuous score remained a significant predictor for OS (hazard ratio [HR], 1.85; P=0.002), EFS (HR, 1.73; P=0.001), and RFS (HR, 1.76; P=0.025). It kept its prognostic value in multivariate analyses adjusting for age, FLT3 ITD and NPM1 status. In a validation cohort of 64 CN-AML patients treated on CALGB study 9621, the score also predicted OS (HR, 4.11; P<0.001), EFS (HR, 2.90; P<0.001), and RFS (HR, 3.14, P<0.001) and retained its significance in a multivariate model for OS. In summary, we present a novel gene expression signature that offers additional prognostic information for patients with CN-AML.

Publication Title

An 86-probe-set gene-expression signature predicts survival in cytogenetically normal acute myeloid leukemia.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE15210
Gene expression profiles of mono- and biallelic CEBPA mutations in cytogenetically normal AML
  • organism-icon Homo sapiens
  • sample-icon 61 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Purpose: CEBPA mutations are found as either biallelic (biCEBPA) or monoallelic (moCEBPA). We set out to explore whether the kind of CEBPA mutation is of prognostic relevance in cytogenetically normal AML (CN-AML).

Publication Title

Acute myeloid leukemia with biallelic CEBPA gene mutations and normal karyotype represents a distinct genetic entity associated with a favorable clinical outcome.

Sample Metadata Fields

Specimen part

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accession-icon GSE24634
Expression data from developing regulatory T cells
  • organism-icon Homo sapiens
  • sample-icon 38 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

CD25+ regulatory T cells develop in the thymus (nTregs), but may also be generated in the periphery upon stimulation of naive CD4 T cells under appropriate conditions (iTregs). The mechanisms that regulate the generation of peripheral iTregs are largely unknown.

Publication Title

Analysis of the transcriptional program of developing induced regulatory T cells.

Sample Metadata Fields

Specimen part, Treatment, Subject, Time

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accession-icon GSE85260
Different effects of IL-13 and IL-4 on M in the presence of IL-10
  • organism-icon Homo sapiens
  • sample-icon 13 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Tumor-associated macrophages (TAM) represent an abundant cell population of the immune infiltrate in solid tumors and have been shown to orchestrate escape from immune surveillance. Macrophages display a very plastic phenotype which is recapitulated in vitro by classifying certain subsets according to exposure with defined, individual cytokines. The tumor-promoting M2 macrophages are polarized in vitro by differentiating human monocyte-derived macrophages with the T helper cell type 2 (Th2) response cytokines interleukin-4 and interleukin-13 or the immunosuppressive cytokine interleukin-10. Notably, only the latter macrophage subset undergoes apoptosis when treated with the colony stimulating factor 1 receptor (CSF1R) blocking antibody emactuzumab. However, under physiologic conditions the phenotype of TAM is shaped by a combination of cytokines. Hence, we evaluated if the addition of IL-10 to IL-4 or IL-13 differentiated macrophages is able to override IL-4/-13 mediated signaling and to restore susceptibility to emactuzumab. Though addition of IL-10 did not restore emactuzumab susceptibility, we surprisingly detected that only IL-4 differentiated macrophages sustained their specific marker expression while IL-10 skewed the IL-13 differentiated macrophage profile towards the IL-10 regulated phenotype. In-depth characterization by gene expression profiling revealed unique signatures of IL-4+IL-10 and IL-13+IL-10 differentiated macrophage subsets characterized by upregulation of the canonical NFB signaling or Wnt/-catenin signaling pathways, respectively. In silico-based analysis of a large cohort of cancer patients revealed distinct interleukin-4 or interleukin-13 overexpression patterns in a subset of patients with partial co-expression of IL-10 but almost absent IL-4/IL-13 co-expression. These patients may have less TAM depletion under therapy with CSF1R inhibitors.

Publication Title

No associated publication

Sample Metadata Fields

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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