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accession-icon GSE35643
Expression data from human bronchial airway smooth muscle (ASM) cells
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Interleukin (IL)-17 plays an important and protective role in host defence and has been demonstrated to orchestrate airway inflammation by cooperating with and inducing proinflammatory cytokines. Mircoarrays were used to identify immediate-early/ primary response IL-17A-dependent gene transcripts in primary human bronchial ASM cells from mild asthmatic and healthy individuals.

Publication Title

IL-17A mediates a selective gene expression profile in asthmatic human airway smooth muscle cells.

Sample Metadata Fields

Sex, Age, Specimen part, Treatment, Subject, Time

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accession-icon E-MEXP-304
Transcription profiling of mouse embryonic stem (ES) cells differentiated for 6 days samplesed at 24 hour timepoints (d1-d6) vs undifferentiated cells (d0)
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)

Description

Mouse ES cells were differentiated for 6 days. Undifferentiated cells (d0) were compared to cells harvested at 24 hour timepoints (d1-d6).

Publication Title

Transcriptional profiling of mouse and human ES cells identifies SLAIN1, a novel stem cell gene.

Sample Metadata Fields

Age, Specimen part, Cell line, Time

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accession-icon E-MEXP-303
Transcription profiling of human embryonic stem (ES) cells. Undifferentiated cells of different passage numbers (p19 and p128) were vs cells differentiated in hanging drops for 5 days (d5 embryoid bodies) or expanded on gelatin coated dishes for a further 9 days (d14 embryoid bodies)
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133B Array (hgu133b), Affymetrix Human Genome U133A Array (hgu133a)

Description

Undifferentiated cells of different passage numbers (p19 and p128) were compared to cells differentiated in hanging drops for 5 days (d5 embryoid bodies) or expanded on gelatin coated dishes for a further 9 days (d14 embryoid bodies).

Publication Title

Transcriptional profiling of mouse and human ES cells identifies SLAIN1, a novel stem cell gene.

Sample Metadata Fields

Age, Specimen part, Cell line, Time

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accession-icon GSE63967
Clonal evolution of metastasis revealed by mutational landscapes of chemically induced skin cancers
  • organism-icon Mus musculus
  • sample-icon 109 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.1 ST Array (mogene11st)

Description

Human tumours show a high level of clonal heterogeneity that contributes to malignant progression and metastasis, but the processes that influence the timing of metastatic dissemination of subclones are unknown. Here, we have used whole exome sequencing of 98 matched benign, malignant, and metastatic skin tumours from genetically heterogeneous mice to demonstrate that most metastases disseminate synchronously from the primary tumour, but then evolve separately, acquiring an additional set of mutations during growth at distant sites. Shared mutations between primary carcinomas and their matched metastases have the distinct A>T signature of the initiating carcinogen Dimethylbanzanthracene (DMBA), but non-shared mutations are primarily G>T or C>T substitutions, associated with oxidative stress. We found recurrent point mutations in several hundred genes, including several in the Ras (Hras, Kras, and Pik3ca) pathway. We propose that carcinogen-driven mouse tumour models can aid our understanding of the forces that shape clonal and genetic evolution of human cancers.

Publication Title

Evolution of metastasis revealed by mutational landscapes of chemically induced skin cancers.

Sample Metadata Fields

Sex

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accession-icon GSE52650
Gene expression architecture of mouse dorsal and tail skin reveals functional differences in inflammation and cancer
  • organism-icon Mus musculus
  • sample-icon 307 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.1 ST Array (mogene11st)

Description

Gene expression levels in normal tissues can differ substantially between individuals, due to inherited polymorphisms acting in cis or trans. Analysis of this variation across a population of genetically distinct individuals allows us to visualize a network of co-expressed genes under normal homeostatic conditions, and the consequences of perturbation by tissue damage or disease development. Here, we explore gene expression networks in normal adult skin from 470 genetically unique mice, and demonstrate the dependence of the architecture of signaling pathways on skin tissue location (dorsal or tail skin) and perturbation by induction of inflammation or tumorigenesis. Gene networks related to specific cell types, as well as signaling pathways including Sonic Hedgehog (Shh), Wnt, Lgr family stem cell markers, and keratins differed at these tissue sites, suggesting mechanisms for the differential susceptibility of dorsal and tail skin to development of skin diseases and tumorigenesis. The Pten tumor suppressor gene network is extensively rewired in premalignant tumors compared to normal tissue, but this response to perturbation is lost during malignant progression. We present a software package for eQTL network analysis and demonstrate how network analysis of whole tissues provides insights into interactions between cell compartments and signaling molecules.

Publication Title

Gene Expression Architecture of Mouse Dorsal and Tail Skin Reveals Functional Differences in Inflammation and Cancer.

Sample Metadata Fields

Sex, Age, Specimen part, Treatment

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accession-icon GSE52524
Network Biology of the Skin [1]
  • organism-icon Mus musculus
  • sample-icon 195 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.1 ST Array (mogene11st)

Description

Gene expression levels in normal tissues can differ substantially between individuals, due to inherited polymorphisms acting in cis or trans. Analysis of this variation across a population of genetically distinct individuals allows us to visualize a network of co-expressed genes under normal homeostatic conditions, and the consequences of perturbation by tissue damage or disease development. Here, we explore gene expression networks in normal adult skin from 470 genetically unique mice, and demonstrate the dependence of the architecture of signaling pathways on skin tissue location (dorsal or tail skin) and perturbation by induction of inflammation or tumorigenesis. Gene networks related to specific cell types, as well as signaling pathways including Sonic Hedgehog (Shh), Wnt, Lgr family stem cell markers, and keratins differed at these tissue sites, suggesting mechanisms for the differential susceptibility of dorsal and tail skin to development of skin diseases and tumorigenesis. The Pten tumor suppressor gene network is extensively rewired in premalignant tumors compared to normal tissue, but this response to perturbation is lost during malignant progression. We present a software package for eQTL network analysis and demonstrate how network analysis of whole tissues provides insights into interactions between cell compartments and signaling molecules.

Publication Title

Gene Expression Architecture of Mouse Dorsal and Tail Skin Reveals Functional Differences in Inflammation and Cancer.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon GSE52639
Network Biology of the Skin [2]
  • organism-icon Mus musculus
  • sample-icon 153 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.1 ST Array (mogene11st)

Description

Gene expression levels in normal tissues can differ substantially between individuals, due to inherited polymorphisms acting in cis or trans. Analysis of this variation across a population of genetically distinct individuals allows us to visualize a network of co-expressed genes under normal homeostatic conditions, and the consequences of perturbation by tissue damage or disease development. Here, we explore gene expression networks in normal adult skin from 470 genetically unique mice, and demonstrate the dependence of the architecture of signaling pathways on skin tissue location (dorsal or tail skin) and perturbation by induction of inflammation or tumorigenesis. Gene networks related to specific cell types, as well as signaling pathways including Sonic Hedgehog (Shh), Wnt, Lgr family stem cell markers, and keratins differed at these tissue sites, suggesting mechanisms for the differential susceptibility of dorsal and tail skin to development of skin diseases and tumorigenesis. The Pten tumor suppressor gene network is extensively rewired in premalignant tumors compared to normal tissue, but this response to perturbation is lost during malignant progression. We present a software package for eQTL network analysis and demonstrate how network analysis of whole tissues provides insights into interactions between cell compartments and signaling molecules.

Publication Title

Gene Expression Architecture of Mouse Dorsal and Tail Skin Reveals Functional Differences in Inflammation and Cancer.

Sample Metadata Fields

Sex

View Samples
accession-icon GSE95421
Gene expression architecture of mouse dorsal and tail skin reveals functional differences in inflammation and cancer [telogen/anagen]
  • organism-icon Mus musculus
  • sample-icon 130 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.1 ST Array (mogene11st)

Description

Hair follicles are self-renewing organs within the skin which cycle through periods of growth and destruction, with an intervening period of outward quiescence. The hair follicle cycle is driven by Hedgehog and Wnt signaling and affects epithelial thickness, melanin production, immune function, and tumor susceptibility. We have previously shown that somatic alterations to the genome affect the genetic architecture of the skin. This study examines how the hair follicle cycle affects gene the genetic architecture in vivo by genomic and genetic analysis of 343 genetically heterogeneous mice during the hair follicle growth phase (anagen) and quiescent phase (telogen). We use eQTL analysis and differential correlation to identify changes in metabolic and stem cell activity not detected by differential expression. Germline influence in gene expression is profoundly higher during anagen, but this increase is not a simple factor of higher levels of gene expression. The most strongly induced eQTLs were involved in cellular energy metabolism and melanogenesis rather than hair follicle growth or hedgehog signaling. We demonstrate that hair follicle and circadian rhythm pathways are sexually dimorphic, but do not find evidence for an effect of sex on eQTL networks. We also use eQTL gene network analysis to identify candidate causal relationships between expression of genes in the hair follicle and melanin pathways, identifying Mcoln3 as a candidate for the familial melanoma locus on 1p22. To lower the bioinformatic barriers to eQTL network analysis we produced CARMEN, a free open-source stand-alone software package. This study demonstrates how to perform a systems genetic analysis of a heterogeneous tissue studied in vivo under physiologically relevant growth signals.

Publication Title

Gene Expression Architecture of Mouse Dorsal and Tail Skin Reveals Functional Differences in Inflammation and Cancer.

Sample Metadata Fields

Sex, Age, Specimen part

View Samples
accession-icon GSE82067
Gene expression architecture of mouse dorsal and tail skin reveals functional differences in inflammation and cancer: TPA time course
  • organism-icon Mus musculus
  • sample-icon 68 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.1 ST Array (mogene11st)

Description

Gene expression levels in normal tissues can differ substantially between individuals, due to inherited polymorphisms acting in cis or trans. Analysis of this variation across a population of genetically distinct individuals allows us to visualize a network of co-expressed genes under normal homeostatic conditions, and the consequences of perturbation by tissue damage or disease development. Here, we explore gene expression networks in normal adult skin from 470 genetically unique mice, and demonstrate the dependence of the architecture of signaling pathways on skin tissue location (dorsal or tail skin) and perturbation by induction of inflammation or tumorigenesis. Gene networks related to specific cell types, as well as signaling pathways including Sonic Hedgehog (Shh), Wnt, Lgr family stem cell markers, and keratins differed at these tissue sites, suggesting mechanisms for the differential susceptibility of dorsal and tail skin to development of skin diseases and tumorigenesis. The Pten tumor suppressor gene network is extensively rewired in premalignant tumors compared to normal tissue, but this response to perturbation is lost during malignant progression. We present a software package for eQTL network analysis and demonstrate how network analysis of whole tissues provides insights into interactions between cell compartments and signaling molecules.

Publication Title

Gene Expression Architecture of Mouse Dorsal and Tail Skin Reveals Functional Differences in Inflammation and Cancer.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon GSE67458
The MEF2B Regulatory Network
  • organism-icon Homo sapiens
  • sample-icon 21 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

MEF2B mutations in non-Hodgkin lymphoma dysregulate cell migration by decreasing MEF2B target gene activation.

Sample Metadata Fields

Cell line, Treatment

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)

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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