Figure 2.

Prognostic significance of gene expression–based classification. (A) Bar plot displays the genes that are important contributors to the EMR failure prediction model. The classifier parameters were determined by fivefold cross-validation, yielding a binary classification model that predicts risk of EMR failure based on expression levels of 17 genes. (B) Scatter plot demonstrates the risk score by our predictive model for all 88 patients (EMR achievement or EMR failure) in the independent validation cohort. By default, high risk of EMR failure (HR-GES) was defined as risk score >0.5, and low risk of EMR failure (LR-GES) was defined as risk score ≤0.5. According to this model, 9 (10%) and 79 patients (90%) were classified as HR-GES and LR-GES, respectively. (C) Bar plot of patient samples assigned as HR-GES (n = 9), where 78% failed to achieve EMR compared with 5% of patient samples assigned as LR-GES (n = 79) in the independent validation cohort. Statistical analysis was performed using Fisher’s exact test. (D) Bar plot demonstrating high-risk patient group classified by our predictive model (left) and EMR failure patient group (classified by BCR-ABL1 percentage at 3 months; right). HR-GES indicates a higher BC progression rate compared with low-risk patient group classified by our model or EMR achievement patient group (classified by BCR-ABL1 level at 3 months), respectively.