Mus musculus strain:NSG/organoids: C57BL/6J
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ABSTRACT:
PROVIDER: PRJDB20422 | ENA |
REPOSITORIES: ENA
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Project description:We have now developed an organoid-based model of gastric cancer from GAstric Neoplasia (GAN) mice, which express Wnt1 and the enzymes COX2 and microsomal prostaglandin E synthase 1 in the stomach. Both p53 knockout (GAN-p53KO) organoids and KRASG12V-expressing GAN-p53KO (GAN-KP) organoids were generated by genetic manipulation of GAN mouse–derived tumor (GAN-WT) organoids. To uncover the molecular mechanism underlying the intratumoral heterogeneity of GAN-KP tumors, we performed spatial transcriptomics analysis with the 10× Genomics Visium platform, which allows characterization of the spatial topography of gene expression.
2021-10-21 | GSE186290 | GEO
Project description:Spatial heterogeneity and plasticity of the mammalian liver is critical for systemic metabolic homeostasis in response to fluctuating nutritional status. Here, we generated a high-resolution transcriptomic landscape of the livers from mice that were either fed chow (fed), fasted for 18 h (fasted), or fasted for 18 h and then refed for 6 h (refed) using spatial transcriptomics (ST) and quantified changes in gene expression. This work provides a critical foundation for future mechanistic studies of liver metabolic heterogeneity and plasticity, and will help to understand the zonated pathology during liver disease progression.
2023-01-12 | GSE222796 | GEO
Project description:Spatial transcriptomic analysis of brain in a mouse model of chronic kidney disease
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Project description:Mouse spatial transcriptomic data
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Project description:BACKGROUND: The transcript levels of many genes exhibit significant variation in tissue samples from inbred laboratory mice. A microarray experiment was designed to separate transcript abundance variation across samples from adipose, heart, kidney, and liver tissues of C57BL/6J mice into within-mouse and between-mouse components. Within-mouse variance captures variation due to heterogeneity of gene expression within tissues, RNA-extraction, and array processing. Between-mouse variance reflects differences in transcript levels between these genetically identical mice. Many biological sources can contribute to heterogeneous transcript levels within a tissue sample including inherent stochasticity of biochemical processes such as intrinsic and extrinsic noise within cells and differences in cell-type composition which can result from heterogeneity of stem and progenitor cell populations. Differences in global signaling patterns between individuals and micro-environmental influences such as interactions with pathogens and cage mates can also contribute to variation, but are likely to contribute more to the between-mouse variance component. RESULTS: The nature and extent of transcript abundance variation differs across tissues. Adipose has the largest total variance and the largest within-mouse variance. Liver has the smallest total variance, but it has the most between-mouse variation. Genes with high variability can be classified into groups with correlated patterns of expression that are enriched for specific biological functions. Variation between mice is associated with circadian rhythm, growth hormone signaling, immune response, androgen regulation, lipid metabolism, and the extracellular matrix. Genes showing correlated patterns of within mouse variation were also associated with biological functions, spatial connectivity of stochastic variation and heterogeneity of cell types within tissues. CONCLUSIONS: Genetically identical mice are individuals and they can experience different outcomes for medically important traits. This is reflected in the stochastic variation in gene expression observed between genetically identical mice. Much of the stochasticity has organismal, tissue, or spatial connectivity. Prior knowledge of the genes and functional classes of genes that are likely to vary in the absence of experimental perturbations, whether these are genetic or environmental, can inform experimental design decisions and the interpretation of gene expression data. Variation in gene expression in genetically identical mice sheds light on the impact of stochastic and micro-environmental factors and their phenotypic consequences.
2010-10-01 | GSE20121 | GEO
Project description:Visium HD Spatial Transcriptomics of E13.5 Wild Type Mouse Head
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Project description:Liver-Specific Retroelement Activation During Mouse Aging
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Project description:The purpose of this experiment was to determine the expression traits in Liver tissue from the Four Core Genotype treated group. Keywords: Sry transgene Four Core Genotype Mouse liver Tissue
2008-12-08 | GSE13264 | GEO
Project description:Spatial transcriptome analysis of gastric cancer which GAN-KP transplanted C57BL/6J mouse
| PRJNA773137 | ENA
Project description:Mouse tumour organoids (MTOs) derived from a compound mutant (LAKTP) intestinal cancer model were orthoptopically transplanted into syngeneic C57BL/6J mice. Tumour-bearing mice were treated with TGF-beta inhibitor Galunisertib or vehicle control. Whole tumour mRNA was extracted from primary tumours and expression profiling was performed with the objective to characterize the tumour microenvironment (TME). As a TGF-beta-activated TME has been associated to a poor prognosis and the CRC consensum molecular subtype CMS4, and the mouse model was found to have such an activated TME, we used the array data to classify these tumours in this mouse model system as CMS4-like. Furthermore, treatment with TGF-beta inhibitor reduced the fibroblast- and T cell-specific TGF-beta response signatures, also associated to poor prognosis in human CRC. This treatment was associated to a strong reduction/prevention of liver metastasis, as well as a reduction of primary tumour (and local carcinomatosis) size.
2018-02-12 | GSE103562 | GEO