Fig. 1.

Overview of IRAPS a 857 solid-tumor cancer cells were stochastically and iteratively sampled for pharmaceutical agent sensitivity or insensitivity determination. Differential expression for the combination of two therapeutic agents per target was calculated. This process was repeated 1000 times for the generation of 1000 different lists of differentially expressed genes. Optimization of the final signature included maximization of accuracy on the tissue of interest by selecting optimal thresholds of P-values and fold changes that were represented in a given fraction of the iterations. b Receiver-operating characteristic (ROC) curves for the prediction of training sets with the HER2 inhibitor Afatinib in breast cancer cell lines with inset accuracy and inset with area under the curve (AUC) values. A ROC AUC value of 1 represents perfect prediction and 0.5 represents random chance. c ROC curve for predicting HER2/Erbb2 patients based on the HER2i sensitivity score