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Mus musculus
191 Downloadable Samples
Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
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.
Publication Title
Use of short-term transcriptional profiles to assess the long-term cancer-related safety of environmental and industrial chemicals.
Sample Metadata Fields
Sex, Age, Specimen part, Disease, Subject
View Samples- Mus musculus
- 6 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
Obesity increases colorectal cancer despite other disturbances. We have used the AOM/DSS protocol to induce colitis-associated cancer in control and IL-6Ra deficient animals. Tumours were microdissected and globalgene expression was analysed using microarray.
Publication Title
Obesity exacerbates colitis-associated cancer via IL-6-regulated macrophage polarisation and CCL-20/CCR-6-mediated lymphocyte recruitment.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Rattus norvegicus
- 56 Downloadable Samples
- Affymetrix Rat Genome U34 Array (rgu34a)
Description
Not all patients with nerve injury develop neuropathic pain. The extent of nerve damage and age at the time of injury are two of the few risk factors identified to date. In addition, preclinical studies show that neuropathic pain variance is heritable. To define such factors further, we performed a large-scale gene profiling experiment which plotted global expression changes in the rat dorsal root ganglion in three peripheral neuropathic pain models. This resulted in the discovery that the potassium channel alpha subunit KCNS1, involved in neuronal excitability, is constitutively expressed in sensory neurons and markedly downregulated following nerve injury. KCNS1 was then characterized by an unbiased network analysis as a putative pain gene, a result confirmed by single nucleotide polymorphism association studies in humans. A common amino acid changing allele, the 'valine risk allele', was significantly associated with higher pain scores in five of six independent patient cohorts assayed (total of 1359 subjects). Risk allele prevalence is high, with 18-22% of the population homozygous, and an additional 50% heterozygous. At lower levels of nerve damage (lumbar back pain with disc herniation) association with greater pain outcome in homozygote patients is P = 0.003, increasing to P = 0.0001 for higher levels of nerve injury (limb amputation). The combined P-value for pain association in all six cohorts tested is 1.14 E-08. The risk profile of this marker is additive: two copies confer the most, one intermediate and none the least risk. Relative degrees of enhanced risk vary between cohorts, but for patients with lumbar back pain, they range between 2- and 3-fold. Although work still remains to define the potential role of this protein in the pathogenic process, here we present the KCNS1 allele rs734784 as one of the first prognostic indicators of chronic pain risk. Screening for this allele could help define those individuals prone to a transition to persistent pain, and thus requiring therapeutic strategies or lifestyle changes that minimize nerve injury.
Publication Title
Multiple chronic pain states are associated with a common amino acid-changing allele in KCNS1.
Sample Metadata Fields
Age
View Samples- Mus musculus, Homo sapiens, Rattus norvegicus
- 1314 Downloadable Samples
Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2), Affymetrix Rat Genome 230 2.0 Array (rat2302), Affymetrix Human Genome U133A Array (hgu133a), Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
The MAQC-II Project: A comprehensive study of common practices for the development and validation of microarray-based predictive models
Publication Title
Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.
Sample Metadata Fields
Sex, Age, Specimen part, Race, Compound
View Samples- Homo sapiens
- 549 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a), Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
The multiple myeloma (MM) data set (endpoints F, G, H, and I) was contributed by the Myeloma Institute for Research and Therapy at the University of Arkansas for Medical Sciences (UAMS, Little Rock, AR, USA). Gene expression profiling of highly purified bone marrow plasma cells was performed in newly diagnosed patients with MM. The training set consisted of 340 cases enrolled on total therapy 2 (TT2) and the validation set comprised 214 patients enrolled in total therapy 3 (TT3). Plasma cells were enriched by anti-CD138 immunomagnetic bead selection of mononuclear cell fractions of bone marrow aspirates in a central laboratory. All samples applied to the microarray contained more than 85% plasma cells as determined by 2-color flow cytometry (CD38+ and CD45-/dim) performed after selection. Dichotomized overall survival (OS) and eventfree survival (EFS) were determined based on a two-year milestone cutoff. A gene expression model of high-risk multiple myeloma was developed and validated by the data provider and later on validated in three additional independent data sets.
Publication Title
Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.
Sample Metadata Fields
Sex, Age
View Samples
GSE24363- Rattus norvegicus
- 410 Downloadable Samples
- Affymetrix Rat Genome 230 2.0 Array (rat2302), Affymetrix Human Genome U133A Array (hgu133a)
Description
The NIEHS data set (endpoint C) was provided by the National Institute of Environmental Health Sciences (NIEHS) of the National Institutes of Health (Research Triangle Park, NC, USA). The study objective was to use microarray gene expression data acquired from the liver of rats exposed to hepatotoxicants to build classifiers for prediction of liver necrosis. The gene expression compendium data set was collected from 418 rats exposed to one of eight compounds (1,2-dichlorobenzene, 1,4-dichlorobenzene, bromobenzene, monocrotaline, N-nitrosomorpholine, thioacetamide, galactosamine, and diquat dibromide). All eight compounds were studied using standardized procedures, i.e. a common array platform (Affymetrix Rat 230 2.0 microarray), experimental procedures and data retrieving and analysis processes.
Publication Title
Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.
Sample Metadata Fields
Sex, Specimen part, Compound
View Samples- Homo sapiens
- 267 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
The human breast cancer (BR) data set (endpoints D and E) was contributed by the University of Texas M. D. Anderson Cancer Center (MDACC, Houston, TX, USA). Gene expression data from 230 stage I-III breast cancers were generated from fine needle aspiration specimens of newly diagnosed breast cancers before any therapy. The biopsy specimens were collected sequentially during a prospective pharmacogenomic marker discovery study between 2000 and 2008. These specimens represent 70-90% pure neoplastic cells with minimal stromal contamination. Patients received 6 months of preoperative (neoadjuvant) chemotherapy including paclitaxel, 5-fluorouracil, cyclophosphamide and doxorubicin followed by surgical resection of the cancer. Response to preoperative chemotherapy was categorized as a pathological complete response (pCR = no residual invasive cancer in the breast or lymph nodes) or residual invasive cancer (RD), and used as endpoint D for prediction. Endpoint E is the clinical estrogen-receptor status as established by immunohistochemistry. RNA extraction and gene expression profiling were performed in multiple batches over time using Affymetrix U133A microarrays. Genomic analysis of a subset of this sequentially accrued patient population were reported previously. For each endpoint, the first 130 cases were used as a training set and the next 100 cases were used as an independent validation set.
Publication Title
Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.
Sample Metadata Fields
Age, Specimen part, Race
View Samples GSE24061- Mus musculus
- 88 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
The 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.
Publication Title
Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.
Sample Metadata Fields
Specimen part, Compound
View Samples- Mus musculus
- 24 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
Renal 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.
Publication Title
Molecular clock is involved in predictive circadian adjustment of renal function.
Sample Metadata Fields
Sex, Specimen part
View Samples- Mus musculus
- 6 Downloadable Samples
Illumina HiSeq 2500
Description
Non-proteolytic ubiquitin signaling mediated by K63 ubiquitin chains plays a critical role in multiple pathways converging on NFKB activation that are key to the development and activation of immune cells. However, a complete understanding of how the regulation of ubiquitin signaling affects immune cells development and functionality is still missing. G Protein Suppressor 2 (GPS2) is a multi-functional protein that recently emerged as an important regulator of inflammation and lipid metabolism through inhibition of Ubc13 activity. Here, we have deleted GPS2 in the B cell lineage results and performed RNAseq of WT and KO splenic B cells. Overall design: RNA-seq of WT and_KO of GPS2 in Bcells.
Publication Title
Inhibition of Ubc13-mediated Ubiquitination by GPS2 Regulates Multiple Stages of B Cell Development.
Sample Metadata Fields
Specimen part, Subject
View Samples