Synthetic dosage lethality in the human metabolic network is highly predictive of tumor growth and cancer patient survival.

ABSTRACT: Synthetic dosage lethality (SDL) denotes a genetic interaction between two genes whereby the underexpression of gene A combined with the overexpression of gene B is lethal. SDLs offer a promising way to kill cancer cells by inhibiting the activity of SDL partners of activated oncogenes in tumors, which are often difficult to target directly. As experimental genome-wide SDL screens are still scarce, here we introduce a network-level computational modeling framework that quantitatively predicts human SDLs in metabolism. For each enzyme pair (A, B) we systematically knock out the flux through A combined with a stepwise flux increase through B and search for pairs that reduce cellular growth more than when either enzyme is perturbed individually. The predictive signal of the emerging network o

SUBMITTER: Megchelenbrink W 

PROVIDER: S-EPMC4593091 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature