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accession-icon GSE99340
Transcriptome-based network analysis reveals renal cell type-specific dysregulation of hypoxia-associated transcripts
  • organism-icon Homo sapiens
  • sample-icon 402 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

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

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE99339
Transcriptome-based network analysis reveals renal cell type-specific dysregulation of hypoxia-associated transcripts [glomeruli]
  • organism-icon Homo sapiens
  • sample-icon 187 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

Specimen part

View Samples
accession-icon GSE99325
Transcriptome-based network analysis reveals renal cell type-specific dysregulation of hypoxia-associated transcripts [Tub-FE]
  • organism-icon Homo sapiens
  • sample-icon 169 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

Specimen part

View Samples
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

View Samples
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

View Samples
accession-icon SRP015982
Small RNA analysis of Tu And SJD zebrafish strain and their progeny
  • organism-icon Danio rerio
  • sample-icon 20 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerIIx

Description

Small RNA libraries from total RNA isolated from adult ovaries Overall design: Small RNA libraries were derived from Ovaries of the Founder strain and their offspring and their reciprocal offspring. RNA from 5 individual ovaries was pooled .

Publication Title

piRNA dynamics in divergent zebrafish strains reveal long-lasting maternal influence on zygotic piRNA profiles.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP139927
Transcriptomic analysis of myosin IIa-deficient B cells
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Myosin IIa-deficient follicular B cells have a hyperactivated phenotype. To identify what pathways are regulated by myosin IIa, we performed RNA-seq of coding RNA on flow cytometry sorted follicular B cells from CD23Cre+Myh9fl/fl and CD23Cre+Myh9wt/fl mice. Overall design: B220+AA4.1-CD23+CD21lo follicular B cells were sorted from 3 CD23Cre+Myh9fl/fl and 3 CD23Cre+Myh9wt/fl mice and mRNA was isolated and sequenced.

Publication Title

Myosin IIa Promotes Antibody Responses by Regulating B Cell Activation, Acquisition of Antigen, and Proliferation.

Sample Metadata Fields

Cell line, Subject

View Samples
accession-icon GSE10644
Characteristic Transcriptional Profiling of Rhythmic mRNA Expression in the Murine Distal Colon
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

To identify a cohort of rhythmically expressed genes in the murine Distal Colon,microarrays were used to measure gene expression over a 24-hour light/dark cycle.The rhythmic transcripts were classified according to expression patterns, functions and association with physiological and pathophysiological processes of the colon including motility, colorectal cancer formation and inflammatory bowel disease.

Publication Title

Transcriptional profiling of mRNA expression in the mouse distal colon.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE40885
Data expression in alveolar macrophages induced by lipopolysaccharide in humans
  • organism-icon Homo sapiens
  • sample-icon 14 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Rationale: Lipopolysaccharide (LPS) is ubiquitous in the environment. Inhalation of LPS has been implicated in the pathogenesis and/or severity of several lung diseases, including pneumonia, chronic obstructive pulmonary disease and asthma. Alveolar macrophages are the main resident leukocytes exposed to inhaled antigens. Objectives: To obtain insight into which innate immune pathways become activated within human alveolar macrophages upon exposure to LPS in vivo.

Publication Title

Gene expression profiles in alveolar macrophages induced by lipopolysaccharide in humans.

Sample Metadata Fields

Sex, Specimen part, Treatment, Subject

View Samples
accession-icon GSE53418
Ovarian Cancer Cell line Panel (OCCP): gene expression data.
  • organism-icon Homo sapiens
  • sample-icon 31 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

Epithelial ovarian cancer is a very heterogeneous disease and remains the most lethal gynaecological malignancy in the Western world. Rational therapeutic approaches need to account for interpatient and intratumoral heterogeneity in treatment design. Detailed characterization of in vitro models representing the different histological and molecular subtypes is therefore imperative. Strikingly, from ~100 available ovarian cancer cell lines the origin and which subtype they represent is largely unknown. We have extensively and uniformly characterized 39 ovarian cancer cell lines (with mRNA/microRNA expression, exon sequencing, dose response curves for clinically relevant therapeutics) and obtained all available information on the clinical features and tissue of origin of the original ovarian cancer to refine the putative histological subtypes. From 39 ovarian cell lines, 14 were assigned as high-grade serous, four serous-type, one low-grade serous and 20 non-serous type. Three morphological subtypes (21 Epithelial, 7 Round, 12 Spindle) were identified that showed distinct biological and molecular characteristics, including overexpression of cell movement and migration-associated genes for the Spindle subtype. Clinical validation showed a clear association of the spindle-like tumors with metastasis, advanced stage, suboptimal debulking and poor prognosis. In addition, the morphological subtypes associated with the molecular C1-6 subtypes identified by Tothill et al. [1], Spindle clustered with C1-stromal subtype, Round with C5-mesenchymal and Epithelial with C4 subtype. We provide a uniformly generated data resource for 39 ovarian cancer cell lines, the ovarian cancer cell line panel (OCCP). This should be the basis for selecting models to develop subtype specific treatment approaches, which is very much needed to prolong the survival of ovarian cancer patients.

Publication Title

Ovarian cancer cell line panel (OCCP): clinical importance of in vitro morphological subtypes.

Sample Metadata Fields

Cell line

View Samples
...

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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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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