We have evaluated the performance characteristics of three quantitative gene expression technologies and correlated their expression measurements to those of five commercial microarray platforms, based on the MicroArray Quality Control (MAQC) data set. The limit of detection, assay range, precision, accuracy and fold-change correlations were assessed for 997 TaqMan Gene Expression Assays, 205 Standardized RT (Sta)RT-PCR assays and 244 QuantiGene assays. TaqMan is a registered trademark of Roche Molecular Systems, Inc. We observed high correlation between quantitative gene expression values and microarray platform results and found few discordant measurements among all platforms. The main cause of variability was differences in probe sequence and thus target location. A second source of variability was the limited and variable sensitivity of the different microarray platforms for detecting weakly expressed genes, which affected interplatform and intersite reproducibility of differentially expressed genes. From this analysis, we conclude that the MAQC microarray data set has been validated by alternative quantitative gene expression platforms thus supporting the use of microarray platforms for the quantitative characterization of gene expression.

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In previous studies, we reported that key antioxidant and DNA repair genes are regulated differently in normal bronchial epithelial cells of lung cancer cases compared with non-lung cancer controls. In an effort to develop a biomarker for lung cancer risk, we evaluated the transcript expressions of 14 antioxidant, DNA repair, and transcription factor genes in normal bronchial epithelial cells (HUGO names CAT, CEBPG, E2F1, ERCC4, ERCC5, GPX1, GPX3, GSTM3, GSTP1, GSTT1, GSTZ1, MGST1, SOD1, and XRCC1). A test comprising these 14 genes accurately identified the lung cancer cases in two case-control studies. The receiver operating characteristicarea under the curve was 0.82 (95% confidence intervals, 0.68-0.91) for the first case-control set (25 lung cancer cases and 24 controls), and 0.87 (95% confidence intervals, 0.73-0.96) for the second set (18 cases and 22 controls). For each gene included in the test, the key difference between cases and controls was altered distribution of transcript expression among cancer cases compared with controls, with more lung cancer cases expressing at both extremes among all genes (Kolmorogov-Smirnov test, D = 0.0795; P = 0.041). A novel statistical approach was used to identify the lower and upper boundaries of transcript expression that optimally classifies cases and controls for each gene. Based on the data presented here, there is an increased prevalence of lung cancer diagnosis among individuals that express a threshold number of key antioxidant, DNA repair, and transcription factor genes at either very high or very low levels in the normal airway epithelium. [Cancer Res 2009;69(22):8629-35]

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