Optimal control nodes in disease-perturbed networks as targets for combination therapy.

ABSTRACT: Most combination therapies are developed based on targets of existing drugs, which only represent a small portion of the human proteome. We introduce a network controllability-based method, OptiCon, for de novo identification of synergistic regulators as candidates for combination therapy. These regulators jointly exert maximal control over deregulated genes but minimal control over unperturbed genes in a disease. Using data from three cancer types, we show that 68% of predicted regulators are either known drug targets or have a critical role in cancer development. Predicted regulators are depleted for known proteins associated with side effects. Predicted synergy is supported by disease-specific and clinically relevant synthetic lethal interactions and experimental validation. A significa

SUBMITTER: Hu Y 

PROVIDER: S-EPMC6522545 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature