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GSE7116
Homo sapiens
23 Downloadable Samples
Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
BACKGROUND:
Publication Title
Clinical, radiographic, and biochemical characterization of multiple myeloma patients with osteonecrosis of the jaw.
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No sample metadata fields
View Samples- Homo sapiens
- 72 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
We applied a meta-analysis of datasets from seven different microarray studies on lung cancer for differentially expressed genes related to survival time (under 2 y and over 5 y). Systematic bias adjustment in the datasets was performed by distance-weighted discrimination (DWD). We identified a gene expression signature consisting of 64 genes that is highly predictive of which stage I lung cancer patients may benefit from more aggressive therapy.
Publication Title
A gene expression signature predicts survival of patients with stage I non-small cell lung cancer.
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Sex
View Samples- Homo sapiens
- 222 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Here we report a large, training*testing, multi-site, blinded validation study to characterize the performance of several prognostic models based on gene expression for 442 lung adenocarcinomas. The hypotheses proposed examined whether microarray measurements of gene expression either alone or combined with basic clinical covariates (stage, age, sex) could be used to predict overall survival in lung cancer subjects. Several models examined produced risk scores that substantially correlated with actual subject outcome. Most methods performed better with clinical data, supporting the combined use of clinical and molecular information when building prognostic models for early-stage lung cancer. This study also provides the largest available set of microarray data with extensive pathological and clinical annotation for lung adenocarcinomas.
Publication Title
Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study.
Alternate Accession IDs
Sample Metadata Fields
Sex, Age, Specimen part, Disease, Disease stage, Race
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