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GSE99039
Homo sapiens
558 Downloadable Samples
Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Establishing reliable biomarkers for assessing and validating clinical diagnosis at early prodromal stages of Parkinson’s disease is crucial for developing therapies to slow or halt disease progression. Here, we present the largest study to date using whole blood gene expression profiling from over 500 individuals to identify an 87-gene blood-based signature. Our gene signature effectively differentiates between idiopathic PD patients and controls in both a validation cohort and an independent test cohort, and further highlights mitochondrial metabolism and ubiquitination/proteasomal degradation as potential pathways disrupted in Parkinson’s disease.
Publication Title
Analysis of blood-based gene expression in idiopathic Parkinson disease.
Sample Metadata Fields
Sex, Specimen part, Subject
View Samples- Danio rerio
- 3 Downloadable Samples
Description
Microarray data allowed detection of genes that are highly expressed in the pineal gland.
Publication Title
A new cis-acting regulatory element driving gene expression in the zebrafish pineal gland.
Sample Metadata Fields
Sex
View Samples- Danio rerio
- 12 Downloadable Samples
Description
Microarray data allowed detection of genes that have circadian expression pattern in the zebrafish pineal gland Adult (0.5-1.5 years old) transgenic zebrafish, Tg(aanat2:EGFP)Y8, which express enhanced green fluorescent protein (EGFP) in the pineal gland under the control of the aanat2 regulatory regions, were used. Fish were raised under 12-hr light:12-hr dark (LD) cycles, in a temperature controlled room, and transferred to constant darkness (DD) for tissue collection. Fish were anesthetized in 1.5 mM Tricane (Sigma), sacrificed by decapitation, and pineal glands were removed under a fluorescent dissecting microscope. Starting from circadian time (CT) 14, pineal glands were collected at 4-hr intervals for 48 hours (12 time points identified as CT 14, 18, 22, 2, 6, 10, 14b, 18b, 22b, 2b, 6b and 10b). Pools of 12 pineal glands were prepared at each time-point and total RNA was extracted using the RNeasy Lipid Tissue Mini Kit (QIAGEN), according to the manufacturer's instructions.
Publication Title
No associated publication
Sample Metadata Fields
Sex, Specimen part, Subject, Time
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- Mus musculus
- 57 Downloadable Samples
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Evaluating microRNA profiles reveals discriminative responses following genotoxic or non-genotoxic carcinogen exposure in primary mouse hepatocytes.
Sample Metadata Fields
Specimen part, Compound
View Samples- Mus musculus
- 106 Downloadable Samples
Description
Specification of germ cell fate is fundamental in development. With a highly representative single-cell microarray and rigorous quantitative-PCR analysis, we defined the genome-wide transcription dynamics that create primordial germ cells (PGCs) from the epiblast, a process that exclusively segregates them from their somatic neighbors. We also analyzed the effect of the loss of Blimp1, a key transcriptional regulator, on these dynamics. Our analysis revealed that PGC specification involves complex, yet highly ordered regulation of a large number of genes, proceeding under the strong influence of mesoderm induction with active repression of specific programs such as epithelial-mesenchymal transition, Hox gene activation, cell-cycle progression and DNA methyltransferase machinery. Remarkably, Blimp1 is essential for repressing nearly all the genes normally down-regulated in PGCs relative to their somatic neighbors, whereas it is dispensable for the activation of approximately half of the genes up-regulated in PGCs.
Publication Title
No associated publication
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 1 Downloadable Sample
Description
Gene expression profiling using microarray has been limited to profiling of differentially expressed genes at comparison setting since probesets for different genes have different sensitivities. We overcome this limitation by using a very large number of varied microarray datasets as a common reference, so that statistical attributes of each probeset, such as dynamic range or a threshold between low and high expression can be reliably discovered through meta-analysis. This strategy is implemented in web-based platform named Gene Expression Commons (http://gexc.stanford.edu/ ) with datasets of 39 distinct highly purified mouse hematopoietic stem/progenitor/functional cell populations covering almost the entire hematopoietic system. Since the Gene Expression Commons is designed as an open platform, any scientist can explore gene expression of any gene, search by expression pattern of interest, submit their own microarray datasets, and design their own working models.
Publication Title
Gene Expression Commons: an open platform for absolute gene expression profiling.
Sample Metadata Fields
Sex, Age
View Samples