Figure 7.

Evidence and Model for Functional Mutations and Tumor-Specific Network Medicine

(A) The functional mutations found in this study are clear examples of single amino acid mutations that can severely perturb signaling networks.

(B) Our study shows how non-recurrent cancer mutations on non-conserved residues can be functionally important and that functional recurrent (orange) and non-recurrent (red) NAMs can converge at the signaling network level. We also identified a case where a functional mutation in a low-abundant protein is accompanied by its overexpression.

(C) The deployment of tools like ReKINect should enable the proposition of more refined signaling mechanisms underlying cellular cancer phenotypes and identification of driver and therapeutically relevant mutations.