NetCF: A Network Control-based Framework to Reveal the Molecular Mechanism of Phenotype Switching in Lung Cancer

While targeted therapies are widely used in cancer treatment with specific biomarkers, they still encounter critical challenges such as intrinsic drug resistance. Discovery of combination targets to overcome such resistance is crucial. However, due to intricate molecular regulations, identifying a combination target against targeted therapies remains problematic. To systematically tackle this problem, we present a network control strategy for identifying a core switching circuit in cell state transition through feedback analysis (NetCF). This framework identifies a combination target and unravels the underlying mechanism based on data-driven Boolean network modeling and complex network analysis. NetCF explores a core switching circuit, composed of coupled positive feedback loops, that drives a phenotype change when the identified combination target is regulated. By applying this framework to lung cancer cells, we suggest PIN1 as an effective combination target to overcome resistance to MEK inhibitor. Our framework identifies potential therapeutic interventions for cancer in the form of combination targets and their system-level mechanisms that enable them to overcome drug resistance. NetCF is available at https://github.com/namheee/NetCF.