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GSE74079
Mus musculus
23 Downloadable Samples
Affymetrix Mouse Gene 2.1 ST Array (mogene21st)
Description
Gerstmann Strausller Scheinker (GSS) human prion disease homogenate is i.c. inoculated into mice exhibiting a proline to leucine alteration at codon 101 of the murine prion protein gene (101LL). This results in a disease with an incubation period of approximately 291 days. Normal brain homogenate i.c. inoculated into 101LL mice which are aged matched are used as controls.
Publication Title
Distribution of Misfolded Prion Protein Seeding Activity Alone Does Not Predict Regions of Neurodegeneration.
Sample Metadata Fields
Sex, Specimen part
View Samples- Homo sapiens
- 53 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Background: We have previously shown that the Gene expression Grade Index (GGI) was able to identify two subtypes of estrogen receptor (ER)-positive tumors that were associated with statistically distinct clinical outcomes in both untreated and tamoxifen-treated patients. Here, we aim to investigate the ability of the GGI to predict relapses in postmenopausal women who were treated with tamoxifen (T) or letrozole (L) within the BIG 1-98 trial.
Publication Title
The Gene expression Grade Index: a potential predictor of relapse for endocrine-treated breast cancer patients in the BIG 1-98 trial.
Sample Metadata Fields
Age, Specimen part, Disease stage, Treatment
View Samples- Rattus norvegicus
- 32 Downloadable Samples
- Affymetrix Rat Gene 2.1 ST Array (ragene21st)
Description
We used microarray to examine changes in gene expression in the absence of Csf1r in the brain and spleen.
Publication Title
Pleiotropic Impacts of Macrophage and Microglial Deficiency on Development in Rats with Targeted Mutation of the <i>Csf1r</i> Locus.
Sample Metadata Fields
Sex
View Samples- Homo sapiens
- 167 Downloadable Samples
- Affymetrix Human Genome U219 Array (hgu219)
Description
Using a dataset of 54 pregnant and 113 age/stage-matched non-pregnant breast cancer patients with complete clinical and survival data; we evaluated the pattern of hot spot somatic mutations and performed transcriptomic profiling using Sequenom and Affymetrix, respectively. Breast cancer molecular subtypes were defined using PAM50 and 3-Gene classifiers. We performed Gene set enrichment analysis (GSEA) to evaluate pathways associated with diagnosis during pregnancy. We investigated the differential expression of cancer-related genes and published gene sets according to pregnancy. We finally investigated genes associated with disease-free survival.
Publication Title
Biology of breast cancer during pregnancy using genomic profiling.
Sample Metadata Fields
Age, Disease stage
View Samples- Mus musculus
- 6 Downloadable Samples
Illumina HiSeq 2000
Description
The goal of this study was to identify genes which are differentiatlly expresesd upon induced inactivation of Rfx6 in beta cell in adult mice Overall design: Rfx6fl/fl; Ins1-CreERT2 (mut) and Rfx6fl/fl (ctrl) 8 weeks old mice were injected subcutaneously with tamoxifen daily during 3 days. Pancreatic islets were isolated 5 days after the first injection and RNA purified.
Publication Title
Rfx6 maintains the functional identity of adult pancreatic β cells.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 203 Downloadable Samples
- Affymetrix Human Genome U219 Array (hgu219)
Description
The FinHER trial is a multicentre phase 3 randomised adjuvant breast cancer trial that enrolled 1010 patients. The women were randomly assigned to receive three cycles of docetaxel or vinorelbine, followed by three cycles of fluorouracil, epirubicin, and cyclophosphamide.
Publication Title
Integrative proteomic and gene expression analysis identify potential biomarkers for adjuvant trastuzumab resistance: analysis from the Fin-her phase III randomized trial.
Sample Metadata Fields
Age, Disease stage
View Samples- Homo sapiens
- 51 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Microarrays have revolutionized breast cancer (BC) research by enabling studies of gene expression on a transcriptome-wide scale. Recently, RNA-Sequencing (RNA-Seq) has emerged as an alternative for precise readouts of the transcriptome. To date, no study has compared the ability of the two technologies to quantify clinically relevant individual genes and microarray-derived gene expression signatures (GES) in a set of BC samples encompassing the known molecular BC's subtypes. To accomplish this, the RNA from 57 BCs representing the four main molecular subtypes (triple negative, HER2 positive, luminal A, luminal B), was profiled with Affymetrix HG-U133 Plus 2.0 chips and sequenced using the Illumina HiSeq 2000 platform. The correlations of three clinically relevant BC genes, six molecular subtype classifiers, and a selection of 21 GES were evaluated.
Publication Title
Transfer of clinically relevant gene expression signatures in breast cancer: from Affymetrix microarray to Illumina RNA-Sequencing technology.
Sample Metadata Fields
Specimen part, Disease stage
View Samples- Homo sapiens
- 737 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Purpose: A number of microarray studies have reported distinct molecular profiles of breast cancers (BC): basal-like, ErbB2-like and two to three luminal-like subtypes. These were associated with different clinical outcomes. However, although the basal and the ErbB2 subtypes are repeatedly recognized, identification of estrogen receptor (ER)-positive subtypes has been inconsistent. Refinement of their molecular definition is therefore needed.
Publication Title
Definition of clinically distinct molecular subtypes in estrogen receptor-positive breast carcinomas through genomic grade.
Sample Metadata Fields
Age, Disease stage
View Samples- Homo sapiens
- 77 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Background: Estrogen receptor positive (ER+) breast cancers (BC) are heterogeneous with regard to their clinical behavior and response to therapies. The ER is currently the best predictor of response to the anti-estrogen agent tamoxifen, yet up to 30-40% of ER+BC will relapse despite tamoxifen treatment. New prognostic biomarkers and further biological understanding of tamoxifen resistance are required. We used gene expression profiling to develop an outcome-based predictor using a training set of 255 ER+ BC samples from women treated with adjuvant tamoxifen monotherapy. We used clusters of highly correlated genes to develop our predictor to facilitate both signature stability and biological interpretation. Independent validation was performed using 362 tamoxifen-treated ER+ BC samples obtained from multiple institutions and treated with tamoxifen only in the adjuvant and metastatic settings.
Publication Title
Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen.
Sample Metadata Fields
Age, Disease stage, Treatment
View Samples- Homo sapiens
- 185 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Background: Histologic grade in breast cancer provides clinically important prognostic information. However, 30%-60% of tumors are classified as histologic grade 2. This grade is associated with an intermediate risk of recurrence and is thus not informative for clinical decision making. We examined whether histologic grade was associated with gene expression profi les of breast cancers and whether such profi les could be used to improve histologic grading.
Publication Title
Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis.
Sample Metadata Fields
Age, Disease stage
View Samples