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accession-icon GSE77153
Expression data from VND7 induction line
  • organism-icon Arabidopsis thaliana
  • sample-icon 69 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Plants typically contain two different types of cell walls: a primary wall that is being deposited around all growing cells, and a secondary wall that is produced in cells with specialized functions once they have ceased to grow. In Arabidopsis, VND7 is a transcription factor that is sufficient to activate secondary cell wall synthesis. To artificially turn on the secondary cell wall synthesis, VND7 was fused to the activation domain of the herpes virus VP16 protein and the glucocorticoid receptor (GR) domain. Thus, the transgenic plants harbouring the constructs can then be treated with dexamethasone (DEX), a glucocorticoid derivative, to induce the secondary cell wall formation.

Publication Title

A Transcriptional and Metabolic Framework for Secondary Wall Formation in Arabidopsis.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE17933
Transcriptional Biomarkers to Predict Female Mouse Lung Tumors in Rodent Cancer Bioassays - A 26 Chemical Set
  • organism-icon Mus musculus
  • sample-icon 191 Downloadable Samples
  • Technology Badge Icon 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

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accession-icon SRP043162
Fatal Asthma vs. Control Human Airway Smooth Muscle Transcriptome Changes in Response to Vitamin D or Albuterol
  • organism-icon Homo sapiens
  • sample-icon 53 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Rationale: Asthma is a chronic inflammatory airway disease. Children with severe asthma have lower levels of vitamin D than children with moderate asthma, and among children with severe asthma, airway smooth muscle (ASM) mass is inversely related to vitamin D levels. Beta2 agonists are a common asthma medication that act partly by targetting the ASM. We used RNA-Seq to characterize the human ASM transcriptome of fatal and asthma vs. contols at baseline and under two treatment conditions. Methods: The Illumina TruSeq assay was used to prepare 75bp paired-end libraries for ASM cells from white donors, 6 with fatal asthma and 12 control donors under three treatment conditions: 1) no treatment; 2) treatment with a ß2-agonist (i.e. Albuterol, 1µM for 18h); 3) treatment with vitamin D 100 nM for 18h). Llibraries were sequenced with an Illumina Hi-Seq 2000 instrument. The Tuxedo Suite Tools were used to align reads to the hg19 reference genome, assemble transcripts, and perform differential expression analysis using the protocol described in https://github.com/blancahimes/taffeta Overall design: mRNA profiles obtained via RNA-Seq for primary human airway smooth muscle cell lines from fatal asthma or control donors that were treated with vitamin D, albuterol, or were left untreated.

Publication Title

Vitamin D Modulates Expression of the Airway Smooth Muscle Transcriptome in Fatal Asthma.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE16716
MicroArray Quality Control Phase II (MAQC-II) Project
  • organism-icon Mus musculus, Homo sapiens, Rattus norvegicus
  • sample-icon 1314 Downloadable Samples
  • Technology Badge Icon 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

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accession-icon GSE24080
MAQC-II Project: Multiple myeloma (MM) data set
  • organism-icon Homo sapiens
  • sample-icon 549 Downloadable Samples
  • Technology Badge Icon 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

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accession-icon GSE24363
MAQC-II Project: NIEHS data set
  • organism-icon Rattus norvegicus
  • sample-icon 410 Downloadable Samples
  • Technology Badge Icon 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

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accession-icon GSE20194
MAQC-II Project: human breast cancer (BR) data set
  • organism-icon Homo sapiens
  • sample-icon 267 Downloadable Samples
  • Technology Badge Icon 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

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accession-icon GSE24061
MAQC-II Project: Hamner data set
  • organism-icon Mus musculus
  • sample-icon 88 Downloadable Samples
  • Technology Badge Icon 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
accession-icon GSE14801
Expression data from ERG Si treated and Control HUVEC cells
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

ERG (Ets Related Gene) is an ETS transcription factor that was originally described for its role in a number of human cancers. Our preliminary data demonstrate that ERG exhibits a highly EC restricted pattern of expression in cultured primary cells and several adult tissues including the heart, lung, and brain. In response to inflammatory stimuli, such as TNF-alpha, we observed a marked reduction of ERG expression in EC.

Publication Title

Antiinflammatory effects of the ETS factor ERG in endothelial cells are mediated through transcriptional repression of the interleukin-8 gene.

Sample Metadata Fields

Cell line

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accession-icon GSE108868
Expression data of the human colorectal cancer cell line HCT116 in response to MS-275 and hydroxyurea treatment
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

MS-275 and hydroxyurea treatment influences whole gene expression including DNA damage response and cell cycle checkpoint signaling.

Publication Title

HDAC1 and HDAC2 integrate checkpoint kinase phosphorylation and cell fate through the phosphatase-2A subunit PR130.

Sample Metadata Fields

Specimen part, Cell line

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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