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GSE18600
Mus musculus
6 Downloadable Samples
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
FAD-dependent lysine-specific demethylase-1 regulates cellular energy expenditure.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 4 Downloadable Samples
Description
Analysis of differentiating LSD1-KD C2C12 myoblasts. We found LSD1 is an important regulator of oxidative phenotypes in skeletal muscle cells.
Publication Title
LSD1 mediates metabolic reprogramming by glucocorticoids during myogenic differentiation.
Sample Metadata Fields
Specimen part, Cell line
View Samples- Mus musculus
- 4 Downloadable Samples
Description
Sall4 is a mouse homolog of a causative gene of the autosomal dominant disorder known as Okihiro syndrome. We previously showed that Sall4 absence leads to lethality during peri-implantation and that Sall4-null embryonic stem (ES) cells proliferate poorly with intact pluripotency when cultured on feeder cells. However, a subsequent report indicated that shRNA-mediated Sall4 inhibition in ES cells led to a severe reduction in Oct3/4 and a secondary increase in Cdx2, which resulted in complete differentiation into the trophectoderm when cultured in the feeder-free condition. So we profiled gene expression changes when Sall4 is deleted in ES cells in the presence or absence of feeder cells.
Publication Title
No associated publication
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 4 Downloadable Samples
Description
Adipogenic differentiation and metabolic adaptation are initiated through transcriptional and epigenetic reprogramming. In particular, dynamic changes in histone modifications may play central roles in the rearrangement of gene expression patterns. LSD1 (KDM1) protein, encoded by aof2 gene, is a histone demethylase, which is involved in transcriptional regulation. Since the enzymatic activity of LSD1 is FAD (flavin adenine dinucleotide)-dependent, its effects on gene expression may be influenced by FAD availability.
Publication Title
FAD-dependent lysine-specific demethylase-1 regulates cellular energy expenditure.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 2 Downloadable Samples
Description
Osteoclast differentiation is a dynamic differentiation process, which is accompanied by dramatic changes in metabolic status as well as in gene expression. Recent findings have revealed an essential connection between metabolic reprogramming and dynamic gene expression changes during osteoclast differentiation. However, the upstream regulatory mechanisms that drive these metabolic changes in osteoclastogenesis remain to be elucidated. We demonstrate that induced deletion of a tumor suppressor gene, Folliculin (Flcn), in mouse osteoclast precursors causes severe osteoporosis in 3 weeks through excess osteoclastogenesis. Flcn deficient osteoclast precursors (Raw264.7 cells) reveal cell autonomous accelerated osteoclastogenesis. For the purpose of elucidating the molecular mechanism of accelerated osteoclastogenesis in Flcn deficient Raw264.7 cells, we performed DNA microarray analysis.
Publication Title
No associated publication
Sample Metadata Fields
Cell line, Treatment
View Samples- Mus musculus
- 2 Downloadable Samples
Description
Adipogenic differentiation and metabolic adaptation are initiated through transcriptional and epigenetic reprogramming. In particular, dynamic changes in histone modifications may play central roles in the rearrangement of gene expression patterns. BHC80 protein, encoded by phf21a gene, is a part of LSD1 histone demethylase complex and is essential for the demethylation activity.
Publication Title
FAD-dependent lysine-specific demethylase-1 regulates cellular energy expenditure.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 54 Downloadable Samples
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Exploiting microRNA and mRNA profiles generated in vitro from carcinogen-exposed primary mouse hepatocytes for predicting in vivo genotoxicity and carcinogenicity.
Sample Metadata Fields
Specimen part, Compound
View Samples- Mus musculus, Homo sapiens
- 94 Downloadable Samples
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Integrating factor analysis and a transgenic mouse model to reveal a peripheral blood predictor of breast tumors.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus, Homo sapiens
- 231 Downloadable Samples
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Experimentally derived metastasis gene expression profile predicts recurrence and death in patients with colon cancer.
Sample Metadata Fields
Sex, Age, Disease stage, Race
View Samples- Mus musculus
- 54 Downloadable Samples
Description
The well-defined battery of in vitro systems applied within chemical cancer risk assessment is often characterised by a high false-positive rate, thus repeatedly failing to correctly predict the in vivo genotoxic and carcinogenic properties of test compounds. Toxicogenomics, i.e. mRNA-profiling, has been proven successful in improving the prediction of genotoxicity in vivo and the understanding of underlying mechanisms. Recently, microRNAs have been discovered as post-transcriptional regulators of mRNAs. It is thus hypothesised that using microRNA response-patterns may further improve current prediction methods. This study aimed at predicting genotoxicity and non-genotoxic carcinogenicity in vivo, by comparing microRNA- and mRNA-based profiles, using a frequently applied in vitro liver model and exposing this to a range of well-chosen prototypical carcinogens. Primary mouse hepatocytes (PMH) were treated for 24 and 48h with 21 chemical compounds [genotoxins (GTX) vs. non-genotoxins (NGTX) and non-genotoxic carcinogens (NGTX-C) versus non-carcinogens (NC)]. MicroRNA and mRNA expression changes were analysed by means of Exiqon and Affymetrix microarray-platforms, respectively. Classification was performed by using Prediction Analysis for Microarrays (PAM). Compounds were randomly assigned to training and validation sets (repeated 10 times). Before prediction analysis, pre-selection of microRNAs and mRNAs was performed by using a leave-one-out t-test. No microRNAs could be identified that accurately predicted genotoxicity or non-genotoxic carcinogenicity in vivo. However, mRNAs could be detected which appeared reliable in predicting genotoxicity in vivo after 24h (7 genes) and 48h (2 genes) of exposure (accuracy: 90% and 93%, sensitivity: 65% and 75%, specificity: 100% and 100%). Tributylinoxide and para-Cresidine were misclassified. Also, mRNAs were identified capable of classifying NGTX-C after 24h (5 genes) as well as after 48h (3 genes) of treatment (accuracy: 78% and 88%, sensitivity: 83% and 83%, specificity: 75% and 93%). Wy-14,643, phenobarbital and ampicillin trihydrate were misclassified. We conclude that genotoxicity and non-genotoxic carcinogenicity probably cannot be accurately predicted based on microRNA profiles. Overall, transcript-based prediction analyses appeared to clearly outperform microRNA-based analyses.
Publication Title
Exploiting microRNA and mRNA profiles generated in vitro from carcinogen-exposed primary mouse hepatocytes for predicting in vivo genotoxicity and carcinogenicity.
Sample Metadata Fields
Specimen part, Compound
View Samples