Challenges for the Optimization of Drug Therapy in the Treatment of Cancer

摘要: Personalized medicine aims at identifying specific targets for treatment considering the gene expression profile of each patient individually. We discuss challenges personalized oncology to take off and present an approach based on hub inhibition that we are developing. That is, subtraction RNA-seq data tumoral non-tumoral surrounding tissues in biopsies allows identification up-regulated genes tumors patients. Targeting connection hubs subnetworks formed by interactions between proteins is a suitable strategy tumor growth metastasis vitro. The most relevant protein may be further analyzed drug repurposing computational biology. allow inference Shannon entropy number inhibited according aggressiveness. There common but many others molecular level. also consider additional measures more sophisticated modeling. This necessary improve rational choice therapeutic description network dynamics. modeling attractors through Hopfield Network ordinary differential equations given here as examples.