A 4-gene signature associated with clinical outcome in high-grade XXXX .

@entity1 @entity72333 @entity5 @entity1627 @entity11 @entity8724 @entity818 @entity9318 @entity60665
PURPOSE: Gene expression studies provide molecular insights improving the classification of @entity1 with high-grade @entity11 . We have developed a risk estimation strategy based on a combined analysis of gene expression data to search for robust biomarkers associated with outcome in these @entity5 . EXPERIMENTAL DESIGN: We performed a meta-analysis using 3 publicly available @entity11 microarray data sets (267 @entity1 ) to define the genes related to both @entity11 and @entity1 outcome. These biomarkers were used to construct a risk-score equation based on a Cox proportional hazards model on a subset of 144 @entity1 . External validations were performed on microarray data (59 @entity1 ) and on RT-qPCR data (194 @entity1 ). The risk-score model performances (discrimination and calibration) were evaluated and compared with that of clinical risk factors, @entity8724 promoter methylation status, and @entity818 mutational status. RESULTS: This interstudy cross-validation approach allowed the identification of a 4-gene signature highly correlated to survival ( @entity9318 , @entity72333 , @entity1627 , and @entity60665 ), from which an optimal survival model was built (P < 0.001 in training and validation sets). Multivariate analysis showed that the 4-gene risk score was strongly and independently associated with survival (hazard ratio = 0.46; 95% CI, 0.26-0.81; P = 0.007). Performance estimations indicated that this score added beyond standard clinical parameters and beyond both the @entity8724 methylation status and the @entity818 mutational status in terms of discrimination (C statistics, 0.827 versus 0.835; P < 0.001). CONCLUSION: The 4-gene signature provides an independent risk score strongly associated with outcome of @entity1 with high-grade @entity11 .
