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GSE8065
Mus musculus
18 Downloadable Samples
Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
It was the purpose to analyse the changes in gene expression which occur in the mouse small intestine from the pre-weaning to the post-weaning stage. The gene expression was accordingly followed from postnatal day 4 to postnatal day 32.
Publication Title
Cellular cross talk in the small intestinal mucosa: postnatal lymphocytic immigration elicits a specific epithelial transcriptional response.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 82 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Test systems to identify developmental toxicants are urgently needed. A combination of human stem cell technology and transcriptome analysis was used here to provide proof-of-concept that toxicants with a related mode of action can be identified, and grouped for read-across. We chose a test system of developmental toxicity, related to the generation of neuroectoderm from pluripotent stem cells (UKN1), and exposed cells for six days to benchmark concentration (BMC) of histone deacetylase inhibitors (HDACi) valproic acid, trichostatin-A, vorinostat, belinostat, panobinostat and entinostat. To provide insight into their toxic action, we identified HDACi consensus genes, assigned them to superordinate biological processes, and mapped them to a human transcription factor network constructed from hundreds of transcriptome data sets. We also tested a heterogeneous group of mercurials (methylmercury, thimerosal, mercury(II)chloride, mercury(II)bromide, 4-chloromercuribenzoic acid, phenylmercuric acid) (BMCs). Microarray data were compared at the highest non-cytotoxic concentration for all 12 toxicants. A support vector machine (SVM)-based classifier predicted all HDACi correctly. For validation, the classifier was applied to legacy data sets of HDACi, and for each exposure situation, the SVM predictions correlated with the developmental toxicity. Finally, optimization of the classifier based on 100 probe sets showed that eight genes (F2RL2, TFAP2B, EDNRA, FOXD3, SIX3, MT1E, ETS1, LHX2) are sufficient to separate HDACi from mercurials. Our data demonstrate, how human stem cells and transcriptome analysis can be combined for mechanistic grouping and prediction of toxicants. Extension of this concept to mechanisms beyond HDACi would allow prediction of human developmental toxicity hazard of unknown compounds with the UKN1 test system.
Publication Title
A transcriptome-based classifier to identify developmental toxicants by stem cell testing: design, validation and optimization for histone deacetylase inhibitors.
Sample Metadata Fields
Sex, Specimen part
View Samples- Mus musculus
- 113 Downloadable Samples
- Affymetrix Mouse Gene 1.1 ST Array (mogene11st)
Description
Homeodomain interacting protein kinase 2 (Hipk2) has previously been implicated in control of several transcription factors involved in embryonic development, apoptosis, cell proliferation and tumour development13. Analysis of gene expression in tissues from genetically heterogeneous mouse or human populations can reveal motifs associated with the structural or functional components of the tissue, and may predict roles for genes of unknown function4,5. Here we have applied this network strategy to uncover a novel role for the Hipk2 gene in the transcriptional system controlling adipogenesis. Both in vitro and in vivo models were used to show that knockdown or loss of Hipk2 specifically inhibits white adipose cell differentiation and tissue development. In addition, loss of Hipk2 leads to induction of pockets of multilocular brown fat-like cells in remaining white adipose depots. These cells express markers of brown and beige fat such as uncoupling protein 1 (Ucp1) and transmembrane protein 26 (Tmem26), and thermogenic genes including PPAR- coactivator 1a (Ppargc1a), and cell death-inducing DFFA-like effector a (Cidea). These changes are accompanied by increased insulin sensitivity in Hipk2 knock-out mice and reduced high fat diet-induced weight gain, highlighting a potential role for this kinase in diseases such as diabetes and obesity. Our study underscores the versatility and power of a readily available tissue, such as skin, for network modelling of systemic transcriptional programs involved in multiple pathways, including lipid metabolism and adipogenesis.
Publication Title
Identification of Hipk2 as an essential regulator of white fat development.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Mus musculus, Mus musculus x mus spretus, Mus spretus
- 132 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Network analysis of skin tumor progression identifies a rewired genetic architecture affecting inflammation and tumor susceptibility.
Sample Metadata Fields
Sex
View Samples- Mus musculus, Mus musculus x mus spretus, Mus spretus
- 4 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
Gene expression in self-renewing epithelial tissues is controlled by cis- and trans-activating regulatory factors that mediate responses to exogenous agents capable of causing tissue damage, infection, inflammation, or tumorigenesis. We used network construction methods to analyze the genetic architecture of gene expression in normal mouse skin in a cross between tumor-susceptible Mus musculus and tumor-resistant Mus spretus. We demonstrate that gene expression motifs representing different constituent cell types within the skin such as hair follicle cells, haematopoietic cells, and melanocytes are under separate genetic control. Motifs associated with inflammation, epidermal barrier function and proliferation are differentially regulated in mice susceptible or resistant to tumor development. The intestinal stem cell marker Lgr5 is identified as a candidate master regulator of hair follicle gene expression, and the Vitamin D receptor (Vdr) links epidermal barrier function, inflammation, and tumor susceptibility.
Publication Title
Genetic architecture of mouse skin inflammation and tumour susceptibility.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 68 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
Germline polymorphisms influence gene expression networks in normal mammalian tissues. Analysis of this genetic architecture can identify single genes and whole pathways that influence to complex traits including inflammation and cancer susceptibility. Changes in the genetic architecture during the development of benign and malignant tumours have not been investigated. Here, we document major changes in germline control of gene expression during skin tumour development as a consequence of cell selection, somatic genetic events, and changes in tumour microenvironment. Immune response genes such as Interleukin 18 and Granzyme E are under germline control in tumours but not in normal skin. Gene expression networks linked to tumour susceptibility and hair follicle stem cell markers in normal skin undergo significant reorganization during tumour progression. Our data highlight opposing roles of Interleukin-1 signaling networks in tumour susceptibility and tumour progression and have implications for the development of chemopreventive strategies to reduce cancer incidence.
Publication Title
Network analysis of skin tumor progression identifies a rewired genetic architecture affecting inflammation and tumor susceptibility.
Sample Metadata Fields
Sex
View Samples- Mus musculus
- 60 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
Germline polymorphisms influence gene expression networks in normal mammalian tissues. Analysis of this genetic architecture can identify single genes and whole pathways that influence to complex traits including inflammation and cancer susceptibility. Changes in the genetic architecture during the development of benign and malignant tumours have not been investigated. Here, we document major changes in germline control of gene expression during skin tumour development as a consequence of cell selection, somatic genetic events, and changes in tumour microenvironment. Immune response genes such as Interleukin 18 and Granzyme E are under germline control in tumours but not in normal skin. Gene expression networks linked to tumour susceptibility and hair follicle stem cell markers in normal skin undergo significant reorganization during tumour progression. Our data highlight opposing roles of Interleukin-1 signaling networks in tumour susceptibility and tumour progression and have implications for the development of chemopreventive strategies to reduce cancer incidence.
Publication Title
Network analysis of skin tumor progression identifies a rewired genetic architecture affecting inflammation and tumor susceptibility.
Sample Metadata Fields
Sex
View Samples- Mus musculus
- 56 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
We developed a mouse model that captures radiation effects on host biology by transplanting unirradiated Trp53 null mammary tissue to sham or irradiated hosts. Gene expression profiles of tumors that arose in irradiated mice are distinct from those that arose in nave hosts.
Publication Title
Murine microenvironment metaprofiles associate with human cancer etiology and intrinsic subtypes.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 109 Downloadable Samples
- 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
View Samples- Mus musculus
- 307 Downloadable Samples
- 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
View Samples