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Mus musculus
21 Downloadable Samples
Affymetrix Mouse Expression 430A Array (moe430a)
Description
The experiment describes the dynamic transcriptional alterations in brains of ME7- infected, and age-matched, mock-inoculated mice immediatly before inoculation, at two important preclinical time points and at terminal stages.
Publication Title
Transcriptome analysis reveals altered cholesterol metabolism during the neurodegeneration in mouse scrapie model.
Sample Metadata Fields
Sex, Age, Specimen part, Subject, Time
View Samples- Homo sapiens
- 11 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Dilated cardiomyopathy (DCM) is a common cause of heart failure and a leading cause of cardiac transplantation in western countries. The robust predictive expression profile of cardiomyopathic and NF hearts as well as the functional classification can help to identify promising candidates for DCM and may improve the early diagnosis of cardiomyopathy.
Publication Title
Identification of a common gene expression signature in dilated cardiomyopathy across independent microarray studies.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 199 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
In chronic lymphocytic leukemia (CLL), 13q14 and 11q22-23 deletions are found in 2/3 of the cases. 11q22-23 deletions are associated with poor survival, whereas 13q14 deletions as single abnormality are often found in indolent disease forms. The molecular basis for this difference in prognosis is not known.
Publication Title
Expression analysis of genes located in the minimally deleted regions of 13q14 and 11q22-23 in chronic lymphocytic leukemia-unexpected expression pattern of the RHO GTPase activator ARHGAP20.
Sample Metadata Fields
Specimen part, Disease, Disease stage
View Samples- Homo sapiens
- 51 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Background Published multi-gene classifiers suggested outcome prediction for patients with stage UICC II colon cancer based on different gene expression signatures. However, there is currently no translation of these classifiers for application in routine diagnostic. Therefore, we aimed at validating own and published gene expression signatures employing methods which enable RNA and protein detection in routine diagnostic specimens. Results Immunohistochemistry was applied to 68 stage UICC II colon cancers to determine the protein expression of five selected previously published classifier genes (CDH17, LAT, CA2, EMR3, and TNFRSF11A). Correlation of protein expression data with clinical outcome within a 5-year post-surgery course failed to separate patients with a disease-free follow-up [Group DF] and relapse [Group R]). In addition, RNA from macrodissected tumor samples from 53 of these 68 patients was profiled on Affymetrix GeneChips (HG-U133 Plus 2.0). Prognostic signatures were generated by Nearest Shrunken Centroids with cross-validation. Although gene expression profiling allowed the identification of differentially expressed genes between the groups DF and R, a stable classification and prognosis signature was not discernable in our data. Furthermore, the application of previously published gene signatures consisting of 22 and 19 genes, respectively, to our gene expression data set using global tests and leave-one-out cross-validation was unable to predict clinical outcome (prediction rate 75.5% and 64.2%; n.s.). T-stage was the only independent prognostic factor for relapse in multivariate analysis with established clinical and pathological parameters including microsatellite status. Conclusions Our protein and gene expression analyses currently do not support application of molecular classifiers for prediction of clinical outcome in routine diagnostic as a basis for patient-orientated therapy in stage UICC II colon cancer. Further studies are needed to develop prognosis signatures applicable in patient care.
Publication Title
Molecular profiles and clinical outcome of stage UICC II colon cancer patients.
Sample Metadata Fields
Sex
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GSE2665- Homo sapiens
- 19 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Lymph node vs. tonsil
Publication Title
Differential expression of a gene signature for scavenger/lectin receptors by endothelial cells and macrophages in human lymph node sinuses, the primary sites of regional metastasis.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 11 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
p63 mutations have been associated with several human hereditary disorders characterized by ectodermal dysplasia such as EEC syndrome, ADULT syndrome and AEC syndrome . The location and functional effects of the mutations that underlie these syndromes reveal a striking genotype-phenotype correlation. Unlike EEC and ADULT that result from missense mutations in the DNA-binding domain of p63, AEC is solely caused by missense mutations in the SAM domain of p63. We report a study on the TAp63a isoform, the first to be expressed during development of the embryonic epithelia, and on its naturally occurring Q540L mutant derived from an AEC patient. To assess the effects of the Q540L mutation, we generated stable cell lines expressing TAp63a wt, DeltaNp63 alpha or the TAp63 alpha-Q540L mutant protein and used them to systematically compare the cell growth regulatory activity of the mutant and wt p63 proteins and to generate, by microarray analysis, a comprehensive profile of differential gene expression. We found that the Q540L substitution impairs the transcriptional activity of TAp63a and causes misregulation of genes involved in the control of cell growth and epidermal differentiation.
Publication Title
The Hay Wells syndrome-derived TAp63alphaQ540L mutant has impaired transcriptional and cell growth regulatory activity.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 194 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Chronic lymphocytic leukemia (CLL) is a common and heterogeneous disease. An accurate prediction of outcome is highly relevant for the development of personalized treatment strategies. Microarray technology was shown to be a useful tool for the development of prognostic gene expression scores. However, there are no gene expression scores which are able to predict overall survival in CLL based on the expression of few genes that are better than established prognostic markers. We correlated 151 CLL microarray data sets with overall survival using Cox regression and supervised principal component analysis to derive a prognostic score. This score based on the expression levels of eight genes and was validated in an independent group of 149 CLL patients by quantitative real time PCR. The score was predictive for overall survival and time to treatment in univariate Cox regression in the validation data set (both: p<0.001) and in a multivariate analysis after adjustment for 17p and 11q deletions and the IgVH-status. The score achieved superior prognostic accuracy compared to models based on genomic aberrations and IgVH-status and may support personalized therapy.
Publication Title
An eight-gene expression signature for the prediction of survival and time to treatment in chronic lymphocytic leukemia.
Sample Metadata Fields
Specimen part, Disease, Disease stage
View Samples- Rattus norvegicus
- 60 Downloadable Samples
Affymetrix Rat Genome U34 Array (rgu34a), Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)
Description
Ochratoxin A gene expression profiling in liver and kidney, with time points of exposure from 7 days to 12 motnhs
Publication Title
A toxicogenomics approach to identify new plausible epigenetic mechanisms of ochratoxin a carcinogenicity in rat.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 20 Downloadable Samples
- Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)
Description
Photoreceptor disorders are collectively known as retinal degeneration (RD), and include retinitis pigmentosa (RP), cone-rod dystrophy and age related macular degeneration (AMD). These disorders are largely genetic in origin; individual mutations in any one of >200 genes cause RD, making mutation specific therapies prohibitively expensive. A better treatment plan, particularly for late stage disease, may involve stem cell transplants into the photoreceptor or ganglion cell layers of the retina. Stem cells from young mouse retinas can be transplanted, and can form photoreceptors in adult retinas. These cells can be grown in tissue culture, but can no longer form photoreceptors. We have used microarrays to investigate differences in gene expression between cultured retinal progenitor cells (RPCs) that have lost photoreceptor potential, postnatal day 1 (pn1) retinas and the postnatal day 5 (pn5) retinas that contain transplantable photoreceptors. We have also compared FACS sorted Rho-eGFP expressing rod photoreceptors from pn5 retinas with Rho-eGFP negative cells from the same retinas. We have identified over 300 genes upregulated in rod photoreceptor development in multiple comparisons, 37 of which have been previously identified as causative of retinal disease when mutated. It is anticipated that this research should bring us closer to growing photoreceptors in culture and therefore better treatments for RD. This dataset is also a resource for those seeking to identify novel retinopathy genes in RD patients.
Publication Title
Gene expression changes during retinal development and rod specification.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 290 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2), Affymetrix Human Genome U133B Array (hgu133b), Affymetrix Human Genome U133A Array (hgu133a)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Adults with Philadelphia chromosome-like acute lymphoblastic leukemia frequently have IGH-CRLF2 and JAK2 mutations, persistence of minimal residual disease and poor prognosis.
Sample Metadata Fields
Specimen part, Disease, Disease stage
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