ABSTRACT
PURPOSE: This study mainly aimed to identify and assess the performance of a microarray-based prognosis predictor (PP) for stage II colon cancer. A previously suggested 23-gene prognosis signature (PS) was also evaluated. PATIENTS AND METHODS: Tumor mRNA samples from 50 patients were profiled using oligonucleotide microarrays. PPs were built and assessed by random divisions of patients into training and validation sets (TSs and VSs, respectively). For each TS/VS split, a 30-gene PP, identified on the TS by selecting the 30 most differentially expressed genes and applying diagonal linear discriminant analysis, was used to predict the prognoses of VS patients. Two schemes were considered: single-split validation, based on a single random split of patients into two groups of equal size (group 1 and group 2), and Monte Carlo cross validation (MCCV), whereby patients were repeatedly and randomly divided into TS and VS of various sizes. RESULTS: The 30-gene PP, identified from group 1 patients, yielded an 80% prognosis prediction accuracy on group 2 patients. MCCV yielded the following average prognosis prediction performance measures: 76.3% accuracy, 85.1% sensitivity, and 67.5% specificity. Improvements in prognosis prediction were observed with increasing TS size. The 30-gene PS were found to be highly-variable across TS/VS splits. Assessed on the same random splits of patients, the previously suggested 23-gene PS yielded a 67.7% mean prognosis prediction accuracy. CONCLUSION: Microarray gene expression profiling is able to predict the prognosis of stage II colon cancer patients. The present study also illustrates the usefulness of resampling techniques for honest performance assessment of microarray-based PPs.
Subject(s)
Colonic Neoplasms/genetics , Colonic Neoplasms/pathology , Gene Expression Profiling , Aged , Disease-Free Survival , Female , Humans , Male , Monte Carlo Method , Neoplasm Staging , Oligonucleotide Array Sequence Analysis , Predictive Value of Tests , Prognosis , Random Allocation , Sensitivity and SpecificityABSTRACT
Ischemia triggers an inflammatory response that precipitates cell death during reperfusion. Several studies have shown that tissues are protected by ischemic preconditioning (IP) consisting of 10 min of ischemia followed by 10 min of reperfusion just before ischemia. The molecular basis of this protective effect is poorly understood. We used cDNA arrays (20K) to compare global gene expression in liver biopsies from living human liver donors who underwent IP (n=7) or not (n=7) just before liver devascularization. Microarray data were analyzed using pairedt test with a type I error rate fixed at alpha = 2.5 10(6) (Bonferroni correction). We found that 60 genes were differentially expressed (36 over- and 24 underexpressed in preconditioning group). After IP, the most significantly overexpressed gene was IL-1Ra. This was confirmed by immunoblotting. Differentially expressed were genes involved in apoptosis (NOD2, ephrin-A1, and calpain) and in the carbohydrate metabolism. A significant increase in the amount of the anti-apoptotic protein Bcl-2 in preconditioned livers but no change in the cleavage of procaspase-3, -8, and -9 was observed. We also observed an increase in the amount in the inducible nitric oxide synthase. Therefore, the benefits of IP may be associated with the overproduction of IL-1Ra, Bcl-2, and NO countering the proinflammatory and proapoptotic effects generated during ischemia-reperfusion.
