Literature DB >> 32019900

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

Vincent DiGiacomo1, Marcin Maziarz1, Alex Luebbers1, Jillian M Norris1, Pandu Laksono1, Mikel Garcia-Marcos2.   

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.
Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Entities:  

Year:  2020        PMID: 32019900      PMCID: PMC7079226          DOI: 10.1126/scisignal.aax8620

Source DB:  PubMed          Journal:  Sci Signal        ISSN: 1945-0877            Impact factor:   8.192


  95 in total

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