GEO series

caArray_beer-00153: Gene-expression profiles predict survival of patients with lung adenocarcinoma

GSE68571 Homo sapiens Expression profiling by array 96 samples Submitted 2015/05/06 Platform GPL80

Summary

Histopathology is insufficient to predict disease progression and clinical outcome in lung adenocarcinoma. Here we show that gene-expression profiles based on microarray analysis can be used to predict patient survival in early-stage lung adenocarcinomas. Genes most related to survival were identified with univariate Cox analysis. Using either two equivalent but independent training and testing sets, or 'leave-one-out' cross-validation analysis with all tumors, a risk index based on the top 50 genes identified low-risk and high-risk stage I lung adenocarcinomas, which differed significantly with respect to survival. This risk index was then validated using an independent sample of lung adenocarcinomas that predicted high- and low-risk groups. This index included genes not previously associated with survival. The identification of a set of genes that predict survival in early-stage lung adenocarcinoma allows delineation of a high-risk group that may benefit from adjuvant therapy.

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Direct links to NCBI, no account and no request form: the whole study as GSE68571_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 96 samples.

Whole study · RAW.tar ↓ Series matrix ↓ All supplementary files ↗

Also filed as BioProject PRJNA283120. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 12118244) ↗

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