Transcriptome profiling studies suggest that a large fraction of the genome is transcribed and many transcripts function independent of their protein coding potential. The relevance of noncoding RNAs (ncRNAs) in normal physiological processes and in tumorigenesis is increasingly recognized. Here, we describe consistent and significant differences in the distribution of sense and antisense transcripts between normal and neoplastic breast tissues. Many of the differentially expressed antisense transcripts likely represent long ncRNAs. A subset of genes that mainly generate antisense transcripts in normal but not cancer cells is involved in essential metabolic processes. These findings suggest fundamental differences in global RNA regulation between normal and cancer cells that might play a role in tumorigenesis. Overall design: Global strand-specific transcriptome profilings of 2 samples in cancer and 1 sample in normal from clinical breast tissue using asymmetrical strand-specific analysis of gene expression (ASSAGE).
Altered antisense-to-sense transcript ratios in breast cancer.
No sample metadata fields
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 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.
Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.
Sex, Age
View SamplesThe 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.
Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.
Sex, Specimen part, Compound
View SamplesThe 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.
Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.
Age, Specimen part, Race
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 SamplesTo examine irreversible changes in the developing brain following seizures, juvenile inbred mice were intraperitoneally injected with kainate and nicotine.
Increased expression of the lysosomal protease cathepsin S in hippocampal microglia following kainate-induced seizures.
No sample metadata fields
View SamplesThe Shumiya cataract rat (SCR) is a model for hereditary cataract. Two-third of these rats develop lens opacity within 10-11-weeks. Onset of cataract is attributed to the synergetic effect of lanosterol synthase (Lss) and farnesyl-diphosphate farnesyltransferase 1 (Fdft1) mutant alleles that lead to cholesterol deficiency in the lenses, which in turn adversely affects lens biology including the growth and differentiation of lens epithelial cells (LECs). Nevertheless, the molecular events and changes in gene expression associated with the onset of lens opacity in SCR is poorly understood.
Identification of Differential Gene Expression Pattern in Lens Epithelial Cells Derived from Cataractous and Noncataractous Lenses of Shumiya Cataract Rat.
Specimen part, Disease
View SamplesTo assess RNA regulation in FALS for gene expression and alternative processing of RNA in the motor neuron precurssors (MPCs)
Establishment of In Vitro FUS-Associated Familial Amyotrophic Lateral Sclerosis Model Using Human Induced Pluripotent Stem Cells.
Specimen part
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Identification of NUCKS1 as a colorectal cancer prognostic marker through integrated expression and copy number analysis.
Specimen part
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