Showing papers by "Stephen W. Fesik published in 2011"

Kinome siRNA-phosphoproteomic screen identifies networks regulating AKT signaling.

Abstract: To identify regulators of intracellular signaling, we targeted 541 kinases and kinase-related molecules with small interfering RNAs (siRNAs), and determined their effects on signaling with a functional proteomics reverse-phase protein array (RPPA) platform assessing 42 phospho and total proteins. The kinome-wide screen demonstrated a strong inverse correlation between phosphorylation of AKT and mitogen-activated protein kinase (MAPK) with 115 genes that, when targeted by siRNAs, demonstrated opposite effects on MAPK and AKT phosphorylation. Network-based analysis identified the MAPK subnetwork of genes along with p70S6K and FRAP1 as the most prominent targets that increased phosphorylation of AKT, a key regulator of cell survival. The regulatory loops induced by the MAPK pathway are dependent on tuberous sclerosis complex 2 but demonstrate a lesser dependence on p70S6K than the previously identified FRAP1 feedback loop. The siRNA screen also revealed novel bi-directionality in the AKT and GSK3 (Glycogen synthase kinase 3) interaction, whereby genetic ablation of GSK3 significantly blocks AKT phosphorylation, an unexpected observation as GSK3 has only been predicted to be downstream of AKT. This method uncovered novel modulators of AKT phosphorylation and facilitated the mapping of regulatory loops.

A robust in vivo positive-readout system for monitoring siRNA delivery to xenograft tumors.

Abstract: Delivering small interfering RNA (siRNA) to tumors is the major technical hurdle that prevents the advancement of siRNA-based cancer therapy. One of the difficulties associated with the development of clinically relevant delivery systems is the lack of reliable tools for monitoring siRNA delivery to tumors in vivo. We describe here a novel, positive-readout system where siRNA-mediated target knockdown elicits a rapid and robust increase of reporter activity. Using the positive-readout system, we created (1) β-galactosidase-based tumor models that allow the detection of target knockdown in 1%–2% of tumor cells and can distinguish between tumor areas where effective target knockdown occurs versus tumor areas that are not accessible to delivery, and (2) luciferase-based tumor models that allow the quantitative assessment of a large number of delivery systems. Using these positive-readout models, we screened a number of literature-described siRNA delivery systems and identified lipid nanoparticles as a promising delivery platform for siRNA-based cancer therapy.