Probing the mutational landscape of regulators of G protein signaling proteins in cancer

24Citations
Citations of this article
33Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The advent of deep-sequencing techniques has revealed that mutations in G protein–coupled receptor (GPCR) signaling pathways in cancer are more prominent than was previously appreciated. An emergent theme is that cancer-associated mutations tend to cause enhanced GPCR pathway activation to favor oncogenicity. Regulators of G protein signaling (RGS) proteins are critical modulators of GPCR signaling that dampen the activity of heterotrimeric G proteins through their GTPase-accelerating protein (GAP) activity, which is conferred by a conserved domain dubbed the “RGS-box.” Here, we developed an experimental pipeline to systematically assess the mutational landscape of RGS GAPs in cancer. A pan-cancer bioinformatics analysis of the 20 RGS domains with GAP activity revealed hundreds of low-frequency mutations spread throughout the conserved RGS domain structure with a slight enrichment at positions that interface with G proteins. We empirically tested multiple mutations representing all RGS GAP subfamilies and sampling both G protein interface and noninterface positions with a scalable, yeast-based assay. Last, a subset of mutants was validated using G protein activity biosensors in mammalian cells. Our findings reveal that a sizable fraction of RGS protein mutations leads to a loss of function through various mechanisms, including disruption of the G protein–binding interface, loss of protein stability, or allosteric effects on G protein coupling. Moreover, our results also validate a scalable pipeline for the rapid characterization of cancer-associated mutations in RGS proteins.

Cite

CITATION STYLE

APA

DiGiacomo, V., Maziarz, M., Luebbers, A., Norris, J. M., Laksono, P., & Garcia-Marcos, M. (2020). Probing the mutational landscape of regulators of G protein signaling proteins in cancer. Science Signaling, 13(617). https://doi.org/10.1126/scisignal.aax8620

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free