Construction of gene-expression predictor model for patient outcome with renal cell carcinoma

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Renal cell carcinomas (RCCs) are morphologically and genetically heterogeneous tumors and present diverse clinical courses. We used real-time quantitative PCR to examine the VCAMI and ADFP expression levels of more than 400 clear cell renal carcinomas. We evaluated their significances with respect to patient survival rates using the Cox regression model combined with the split-sample method. We demonstrated that high VCAM1 expression is strongly associated with cancerfine survival for patients with clear cell RCC after curative surgical resection. On the other hand, high ADFPexpression was associated with better cancerspecific survival. Next, We developed a scoring system using levels of gene expression to predict outcome for clear cell RCC patients. We selected differentially expressed genes firom the DNA microarray data of 27clear cell RCCs; 16 were metastasis phenotypes and 11 were not We compared the selected gene set with previously published data and identified 33 overlapping gen … More es closely associated with patient outcome. We selected the 12 top-ranked genes and confirmed the level of expression using quantitative reverse transcriptase PCR Multivariate Cox analysis revealed that three genes-要ascular cell adhesion molecule 1 (VCAM1), endothelin receptor type B (EDNRB), and regulator of G-protein signaling 5 (RGS5)-were the most tightly associated with cancerspecific survival and that higher expression of the three genes correlated with better outcome. A formula for an outcome predictor was generated from integration of the measurements of the expression levels of the three genes. Multivariate Cox models combined with a split-sample cress-validation method in a cohort of 386 clear cell RCC patients demonstrated that the derived score for outcome prediction was an independent predictor in cancerspecific survival tests. The accuracy of the prediction of cancer death after nephrectomy was improved by the inclusion of this score in receiver operating characteristic (ROC) analysis from multivariate logistic regression models, suggesting that a scoring system based on the expression levels of these three genes is useful in the prediction of survival far patients with clear cell RCC. Less