Figure 6.

The predictive ability of PCI is context-independent. A unique property of ceRNETs is the increase in predictive ability and correlation between expression profiles of targets and their regulators as a function of the number of regulators (given in the x-axis in log2 scale) (51). (A) The predictive significance of PCI interactions as a function of the number of regulators, as estimated using ridge regression analysis, assigning significance by bootstrapping residuals. ceRNA targets with the same number of predicted regulators were binned together, and median P values are reported for each group. (B) Pearson correlation between the expression profiles of each target and the average expression of their regulators. Pearson correlation obtained from shuffled networks shown using dashed lines, P-values estimated using K-S test. As shown, in every context, predictive ability improved with the number of ceRNA regulators. For both (A) and (B), the top, middle, and bottom rows summarize analyses of TCGA datasets used to build the PCI, TCGA datasets for other tumor types, and both cancer and non-cancer datasets from Gene Expression Atlas, respectively.