Probing the mutational landscape of regulators of G protein signaling proteins in cancer
Author(s) -
Vincent DiGiacomo,
Marcin Maziarz,
Alex Luebbers,
Jillian M. Norris,
Pandu Laksono,
Mikel GarciaMarcos
Publication year - 2020
Publication title -
science signaling
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.659
H-Index - 154
eISSN - 1937-9145
pISSN - 1945-0877
DOI - 10.1126/scisignal.aax8620
Subject(s) - biology , cancer , signal transduction , signaling proteins , microbiology and biotechnology , computational biology , genetics , cancer research
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.
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