Figure 3
Figure 3. Differential gene expression of the 6-gene signature in patient cases. Heatmaps of the 6-gene signature selected by the iterative BMA algorithm. (A) Heatmap of the gene expression of the 6-gene signature in the training set of CP and BC CML cases using microarray-based gene expression analyses. (B) Heatmap of the gene expression in the test set, also by microarray-based gene expression analyses. This group is made up of AP by cytogenetic criteria only (AP cyto); AP by cytogenetic and blast count criteria (AP); and BC after a return to second CP (BC-rem). Green indicates differentially decreased expression of each gene in each case compared with its expression in a pool of CP patient samples and red indicates differentially increased expression. The more saturated the color, the greater is the degree of differential expression. (C) A graphic depiction of the predicted posterior probability of all patient samples is shown. The samples are represented on the horizontal axis, whereas the predicted probabilities are represented on the vertical axis. For the training data consisting of 72 CP (group 0) and BC (group 1) cases, the average predicted probabilities over 100 cross validation runs are shown. For the test data, composed of 21 patients before allogeneic transplantation, the predicted probabilities of the 6 signature genes averaged over 21 models are shown. This “intermediate phase” test set is composed of group 2 AP by cytogenetic criteria only; group 3 AP by cytogenetic and blast count criteria; and group 4 BC after a return to second CP. For 17 of 21 patients, posttransplantation outcomes were available. Using a posterior probability threshold of 0.3, we found that 7 of 11 patients with predicted posterior probabilities ≥ 0.3 died of relapse or treatment-related mortality after transplantation versus only 1 of 6 with a predicted posterior probability < 0.3 (OR = 9).

Differential gene expression of the 6-gene signature in patient cases. Heatmaps of the 6-gene signature selected by the iterative BMA algorithm. (A) Heatmap of the gene expression of the 6-gene signature in the training set of CP and BC CML cases using microarray-based gene expression analyses. (B) Heatmap of the gene expression in the test set, also by microarray-based gene expression analyses. This group is made up of AP by cytogenetic criteria only (AP cyto); AP by cytogenetic and blast count criteria (AP); and BC after a return to second CP (BC-rem). Green indicates differentially decreased expression of each gene in each case compared with its expression in a pool of CP patient samples and red indicates differentially increased expression. The more saturated the color, the greater is the degree of differential expression. (C) A graphic depiction of the predicted posterior probability of all patient samples is shown. The samples are represented on the horizontal axis, whereas the predicted probabilities are represented on the vertical axis. For the training data consisting of 72 CP (group 0) and BC (group 1) cases, the average predicted probabilities over 100 cross validation runs are shown. For the test data, composed of 21 patients before allogeneic transplantation, the predicted probabilities of the 6 signature genes averaged over 21 models are shown. This “intermediate phase” test set is composed of group 2 AP by cytogenetic criteria only; group 3 AP by cytogenetic and blast count criteria; and group 4 BC after a return to second CP. For 17 of 21 patients, posttransplantation outcomes were available. Using a posterior probability threshold of 0.3, we found that 7 of 11 patients with predicted posterior probabilities ≥ 0.3 died of relapse or treatment-related mortality after transplantation versus only 1 of 6 with a predicted posterior probability < 0.3 (OR = 9).

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