Fig. 3

Predictor construction for sub-group classification of patients. a Receiver operating characteristic curve (ROC) of the 11-PPI-Mod predictor in the training dataset. The predicted probability of Cluster 1 is adopted for ROC analysis. The area under the curve (AUC) and its 95% confidence interval (CI) are shown. b Distribution of individuals in the training dataset. The x-axis represents the patient index. Y-axis is the predicted probability of Cluster 1. Each point indicates an individual patient, with different colors labeling for Cluster 1 (blue) and Cluster 2 (red). The dotted line indicates the cut-off (probability = 0.5) of the predictor. c The GSVA profiles (heat map) of the optimized 11 PPI sub-modules in the training dataset. PPI sub-modules are organized by unsupervised hierarchical tree on the left side. Patients are sorted by the predicted probability of Cluster 1 (the upper panel). d Sub-group classification of patients in the validation dataset. The upper panel indicates the predicted probability of Cluster 1 (blue) or Cluster 2 (red) of patients. The middle panel indicates annotations of the patients, with p values estimated by Chi-square test for correlations between each clinical variable and predicted two clusters. The heat map in the bottom panel shows the GSVA profiles of 11-PPI-Mod. PPI sub-modules are organized by unsupervised hierarchical tree on the left side. Patients are sorted by the predicted probability of Cluster 1. Abbreviations: F, female; M, male; yrs., years; Adj.Ther., adjuvant chemotherapy; N, no; Y, yes