The process for evaluating chemical safety is inefficient, costly, and animal intensive. There is growing consensus that the current process of safety testing needs to be significantly altered to improve efficiency and reduce the number of untested chemicals. In this study, the use of short-term gene expression profiles was evaluated for predicting the increased incidence of mouse lung tumors. Animals were exposed to a total of 26 diverse chemicals with matched vehicle controls over a period of three years. Upon completion, significant batch-related effects were observed. Adjustment for batch effects significantly improved the ability to predict increased lung tumor incidence. For the best statistical model, the estimated predictive accuracy under honest five-fold cross-validation was 79.3% with a sensitivity and specificity of 71.4 and 86.3%, respectively. A learning curve analysis demonstrated that gains in model performance reached a plateau at 25 chemicals, indicating that the size of the current data set was sufficient to provide a robust classifier. The classification results showed a small subset of chemicals contributed disproportionately to the misclassification rate. For these chemicals, the misclassification was more closely associated with genotoxicity status than efficacy in the original bioassay. Statistical models were also used to predict dose-response increases in tumor incidence for methylene chloride and naphthalene. The average posterior probabilities for the top models matched the results from the bioassay for methylene chloride. For naphthalene, the average posterior probabilities for the top models over-predicted the tumor response, but the variability in predictions were significantly higher. The study provides both a set of gene expression biomarkers for predicting chemically-induced mouse lung tumors as well as a broad assessment of important experimental and analysis criteria for developing microarray-based predictors of safety-related endpoints.
Use of short-term transcriptional profiles to assess the long-term cancer-related safety of environmental and industrial chemicals.
Sex, Age, Specimen part, Disease, Subject
View SamplesThe MAQC-II Project: A comprehensive study of common practices for the development and validation of microarray-based predictive models
Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.
Sex, Age, Specimen part, Race, Compound
View SamplesThe Hamner data set (endpoint A) was provided by The Hamner Institutes for Health Sciences (Research Triangle Park, NC, USA). The study objective was to apply microarray gene expression data from the lung of female B6C3F1 mice exposed to a 13-week treatment of chemicals to predict increased lung tumor incidence in the 2-year rodent cancer bioassays of the National Toxicology Program. If successful, the results may form the basis of a more efficient and economical approach for evaluating the carcinogenic activity of chemicals. Microarray analysis was performed using Affymetrix Mouse Genome 430 2.0 arrays on three to four mice per treatment group, and a total of 70 mice were analyzed and used as the MAQC-II's training set (GEO Series GSE6116). Additional data from another set of 88 mice were collected later and provided as the MAQC-II's external validation set (this Series). The training dataset had already been deposited in GEO by its provider and its accession number is GSE6116.
Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.
Specimen part, Compound
View SamplesEndothelial differentiation occurs during normal vascular development in the developing embryo. Mouse embryonic stem (ES) cells were used to further define the molecular mechanisms of endothelial differentiation. By flow cytometry a population of VEGF-R2 positive cells was identified as early as 2.5 days after differentiation of ES cells, and a subset of VEGF-R2 + cells, that were CD41+ positive at 3.5 days. A separate population of VEGF-R2+ stem cells expressing the endothelial-specific marker CD144 (VE-cadherin) was also identified at this same time point. Microarray analysis of >45,000 transcripts was performed on RNA obtained from cells expressing VEGF-R2, CD41, and CD144.
Gene expression analysis of embryonic stem cells expressing VE-cadherin (CD144) during endothelial differentiation.
No sample metadata fields
View SamplesRenal excretion of water and major electrolytes exhibits a significant circadian rhythm. This functional periodicity is believed to result, at least in part, from circadian changes in secretion/reabsorption capacities of the distal nephron and collecting ducts. Here, we studied the molecular mechanisms underlying circadian rhythms in the distal nephron segments, i.e. distal convoluted tubule (DCT) and connecting tubule (CNT) and, the cortical collecting duct (CCD). Temporal expression analysis performed on microdissected mouse DCT/CNT or CCD revealed a marked circadian rhythmicity in the expression of a large number of genes crucially involved in various homeostatic functions of the kidney. This analysis also revealed that both DCT/CNT and CCD possess an intrinsic circadian timing system characterized by robust oscillations in the expression of circadian core clock genes (clock, bma11, npas2, per, cry, nr1d1) and clock-controlled Par bZip transcriptional factors dbp, hlf and tef. The clock knockout mice or mice devoid of dbp/hlf/tef (triple knockout) exhibit significant changes in renal expression of several key regulators of water or sodium balance (vasopressin V2 receptor, aquaporin-2, aquaporin-4, alphaENaC). Functionally, the loss of clock leads to a complex phenotype characterized by partial diabetes insipidus, dysregulation of sodium excretion rhythms and a significant decrease in blood pressure. Collectively, this study uncovers a major role of molecular clock in renal function.
Molecular clock is involved in predictive circadian adjustment of renal function.
Sex, Specimen part
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Developmentally regulated higher-order chromatin interactions orchestrate B cell fate commitment.
Specimen part
View SamplesOrganization of the genome in 3D nuclear-space is known to play a crucial role in regulation of gene expression. However, the chromatin architecture that impinges on the B cell-fate choice of multi-potent progenitors remains unclear. By employing in situ Hi-C, we have identified distinct sets of genomic loci that undergo a developmental switch between permissive and repressive compartments during B-cell fate commitment. Intriguingly, we show that topologically associating domains (TADs) represent co-regulated subunits of chromatin and display considerable structural alterations as a result of changes in the cis-regulatory interaction landscape. The extensive rewiring of cis-regulatory interactions is closely associated with differential gene expression programs. Further, we demonstrate the regulatory role of Ebf1 and its downstream factor, Pax5, in chromatin reorganization and transcription regulation. Together, our studies reveal that alterations in promoter and cis-regulatory interactions underlie changes in higher-order chromatin architecture, which in turn determines cell-identity and cell-type specific gene expression patterns.
Developmentally regulated higher-order chromatin interactions orchestrate B cell fate commitment.
Specimen part
View SamplesThe adult mammalian brain is composed of distinct regions that have specialized roles. To dissect molecularly this complex structure, we conducted a project, named the BrainStars (B*) project, in which we sampled ~50 small brain regions, including sensory centers and centers for motion, time, memory, fear, and feeding. To avoid confusion from temporal differences in gene expression, we sampled each region every 4 hours for 24 hours, and pooled the sample sets for DNA-microarray assays. Therefore, we focused only on spatial differences in gene expression. We then used informatics to identify candidates for (1) genes with high or low expression in specific regions, (2) switch-like genes with bimodal or multimodal expression patterns, and (3) genes with a uni-modal expression pattern that exhibit stable or variable levels of expression across brain regions. We used our findings to develop an integrated database (http://brainstars.org/) for exploring genome-wide expression in the adult mouse brain.
Quantitative expression profile of distinct functional regions in the adult mouse brain.
Sex, Specimen part
View Samples