The most significant 47 genes found in the correlation analysis separating the lung carcinomas of 14 asbestos-exposed patients from the lung carcinomas of 14 non-exposed patient. Correlation coefficient of gene expression with exposure status (asbestos-exposed vs. non-exposed). Signals of the asbestos-associated tumors were scaled by the median signal of the non-associated tumors and the signals of the non-associated tumors by the median signal of the asbestos-associated tumors. A two-step analysis model was used to detect differentially expressed genes and to identify the smallest set of genes that could distinguish the exposed group from the non-exposed group. As the first step, AUROC (ROC) analysis model (Kettunen et al., 2004) was chosen owing to similar size of the two exposure groups. Genes with ROC values less than 0.4, or higher than 0.6, and with P-value less than 0.4 were included in the subsequent analyses. In the second step, a correlation coefficient for the gene expression and exposure status (asbestos exposed versus non- exposed) was calculated for each gene. As we were primarily interested in the differences between the tumors of asbestos- exposed and non-exposed patients and, minimize the effect of variation in gene expression between individual normal lung tissue samples, the data were rescaled before conducting the correlation analysis. To emphasize the differences between the asbestos-associated and non-associated tumors, the signals of the asbestos-associated tumors were scaled by the median signal of the non-associated tumors and the signals of the non- associated tumors by the median signal of the asbestos- associated tumors. The genes were rank-ordered according to the absolute value of the correlation coefficient. To optimize the number of genes needed for the correct classification of tumors, the genes were added sequentially according to their rank order, and the number of correctly classified patients was determined. A ?leave-one-out? cross-validation method was used to assess the reliability of the classification.