KRAS can bind numerous effector proteins, which activate different downstream signaling events. The best known are RAF, phosphatidylinositide (PI)-3' kinase, and RalGDS families, but many additional direct and indirect effectors have been reported. We have assessed how these effectors contribute to several major phenotypes in a quantitative way, using an arrayed combinatorial siRNA screen in which we knocked down 41 KRAS effectors nodes in 92 cell lines. We show that every cell line has a unique combination of effector dependencies, but in spite of this heterogeneity, we were able to identify two major subtypes of KRAS mutant cancers of the lung, pancreas, and large intestine, which reflect different KRAS effector engagement and opportunities for therapeutic intervention.
RNA interference (RNAi) is a powerful tool for target identification and can lead to novel therapies for pharmacologically intractable targets such as KRAS. RNAi therapy must combine potent siRNA payloads with reliable in vivo delivery for efficient target inhibition. We employed a functional “Sensor” assay to establish a library of potent siRNAs against RAS pathway genes and show they efficiently suppress their targets at low dose. This reduces off-target effects and enables combination gene knockdown. We administered Sensor siRNAs in vitro and in vivo and validated the delivery of KRAS siRNA alone and siRNA targeting the complete RAF effector node (A/B/C-RAF) as promising strategies to treat KRAS-mutant colorectal cancer. We further demonstrate that improved therapeutic efficacy is achieved by formulating siRNA payloads that combine both single-gene siRNA and node-targeted siRNAs (KRAS+PIK3C-A/B). The customizable nature of Sensor siRNA payloads offers a universal platform for combination target identification and development of RNAi therapeutics.
Summary Background Cell-to-cell variability in populations has been widely observed in mammalian cells. This heterogeneity can result from random stochastic events or can be deliberately maintained through regulatory processes. In the latter case, heterogeneity should confer a selective advantage that benefits the entire population. Results Using multicolor flow cytometry, we have uncovered robust heterogeneity in PI3K activity in MCF10A cell populations, which had been previously masked by techniques that only measure population averages. We show that AKT activity is bimodal in response to EGF stimulation and correlates with PI3K protein level, such that only cells with high PI3K protein can activate AKT. We further show that heterogeneity in PI3K protein levels is invariably maintained in cell populations through a degradation/re-synthesis cycle that can be regulated by cell density. Conclusions Given that the PI3K pathway is one of the most frequently upregulated pathways in cancer, we propose that heterogeneity in PI3K activity is beneficial to normal tissues by restricting PI3K activation to only a subset of cells. This may serve to protect the population as a whole from over-activating the pathway, which can lead to cellular senescence or cancer. Consistent with this, we show that oncogenic mutations in p110α (H1047R and E545K) partially evade this negative regulation, resulting in increased AKT activity in the population.
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