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GSE12093
Homo sapiens
136 Downloadable Samples
Affymetrix Human Genome U133A Array (hgu133a)
Description
Classification of tamixifen-treated breast cancer patients into high and low risk groups using the 76-gene signature
Publication Title
The 76-gene signature defines high-risk patients that benefit from adjuvant tamoxifen therapy.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 130 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Gene signatures were derived to separate high risk patients from low risk ones..
Publication Title
Gene expression signatures for predicting prognosis of squamous cell and adenocarcinomas of the lung.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 104 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
A number of breast or colon specific genes predictive of the relapse status were used in comparing the outcome from matched fresh frozen and stored in RNAlater preservative.
Publication Title
Prognostic gene expression signatures can be measured in tissues collected in RNAlater preservative.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 58 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Gene signatures were derived to separate responders from nonresponders by tipifarnib treatment.
Publication Title
Identification of molecular predictors of response in a study of tipifarnib treatment in relapsed and refractory acute myelogenous leukemia.
Sample Metadata Fields
Sex, Age
View Samples- Homo sapiens
- 33 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Currently there is no method available to predict response to farnesyltransferase inhibitors (FTI). We analyzed gene expression profiles from the bone marrow of patients from a phase 2 study of the FTI tipifarnib, in older adults with previously untreated acute myeloid leukemia (AML). The RASGRP1:APTX gene expression ratio was found to predict response to tipifarnib with the greatest accuracy. This two-gene ratio was validated by quantitative PCR (QPCR) in the newly diagnosed AML cohort. We further demonstrated that this classifier could predict response to tipifarnib in an independent set of 54 samples from relapsed or refractory AML, with a negative predictive value (NPV) and positive predictive value (PPV) of 92% and 28%, respectively (odds ratio of 4.4). The classifier also predicted for improved overall survival (154 vs 56 days, p = 0.0001), which was shown to be independent of other prognostic factors including a previously described gene expression classifier predictive of overall survival. Therefore, these data indicate that a two-gene expression assay may have utility in categorizing a population of AML patients who are more likely to respond to tipifarnib.
Publication Title
A 2-gene classifier for predicting response to the farnesyltransferase inhibitor tipifarnib in acute myeloid leukemia.
Sample Metadata Fields
Sex, Age, Disease
View Samples- Homo sapiens
- 285 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
This series represents 180 lymph-node negative relapse free patients and 106 lymph-node negate patients that developed a distant metastasis.
Publication Title
Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 360 Downloadable Samples
- Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
No associated publication
Sample Metadata Fields
Specimen part, Cell line
View Samples- Homo sapiens
- 116 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
The plasma cell signature in autoimmune disease.
Sample Metadata Fields
Specimen part, Treatment, Time
View Samples- Mus musculus
- 130 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
Toll-like receptor (TLR)4 agonists are known potent immunostimulatory compounds. These compounds can be formulated as part of novel adjuvants to enhance vaccine medicated immune responses. However, the contribution of the formulation to the innate in vivo activity of TLR4 agonist compounds is not well understood.
Publication Title
No associated publication
Sample Metadata Fields
Specimen part, Time
View Samples- Homo sapiens
- 105 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Objective: Production of pathogenic autoantibodies by self-reactive plasma cells (PC) is a hallmark of autoimmune diseases. Investigating the prevalence of PC in autoimmune disease and their relationship with known pathogenic pathways may increase our understanding of the role of PC in disease progression and treatment response. Methods: We developed a sensitive gene expression based method to overcome the challenges of measuring PC using flow cytometry. Whole genome microarray analysis of sorted cellular fractions identified a panel of genes, IGHA, IGJ, IGKC, IGKV, and TNFRSF17, expressed predominantly in PC. The sensitivity of the PC signature score created from the combined expression levels of these genes was assessed through ex vivo experiments with sorted cells. This PC gene expression signature was used for monitoring changes in PC levels following anti-CD19 therapy; evaluating the relationship between PC and other autoimmune disease-related genes; and estimating PC levels in affected blood and tissue from multiple autoimmune diseases. Results: The PC signature was highly sensitive and capable of detecting as few as 300 PCs. The PC signature was reduced over 90% in scleroderma patients following anti-CD19 treatment and this reduction was highly correlated (r = 0.77) with inhibition of collagen gene expression. Evaluation of multiple autoimmune diseases revealed 30-35% of lupus, rheumatoid arthritis, and scleroderma patients with increased PC levels. Conclusion: This newly developed PC signature provides a robust and accurate method to measure PC levels in the clinic. Our results highlight subsets of patients across multiple autoimmune diseases that may benefit from PC depleting therapy.
Publication Title
The plasma cell signature in autoimmune disease.
Sample Metadata Fields
Specimen part, Treatment, Time
View Samples