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

Get Ready to Sharpen Your Tools: A Short Guide to Heterotrimeric G Protein Activity Biosensors

G protein-coupled receptors (GPCRs) are the largest class of transmembrane receptors encoded in the human genome, and they initiate cellular responses triggered by a plethora of extracellular stimuli ranging from neurotransmitters and hormones to photons. Upon stimulation, GPCRs activate heterotrimeric G proteins (Gαβγ) in the cytoplasm, which then convey signals to their effectors to elicit cellular responses. Given the broad biological and biomedical relevance of GPCRs and G proteins in physiology and disease, there is great interest in developing and optimizing approaches to measure their signaling activity with high accuracy and across experimental systems pertinent to their functions in cellular communication. This review provides a historical perspective on approaches to measure GPCR-G protein signaling, from quantification of second messengers and other indirect readouts of activity to biosensors that directly detect the activity of G proteins. The latter is the focus of a more detailed overview of the evolution of design principles for various optical biosensors of G protein activity with different experimental capabilities. We will highlight advantages and limitations of biosensors that detect different G protein activation hallmarks, like dissociation of Gα and Gβγ or nucleotide exchange on Gα, as well as their suitability to detect signaling mediated by endogenous versus exogenous signaling components or in physiologically relevant systems like primary cells. Overall, this review intends to provide an assessment of the state-of-the-art for biosensors that directly measure G protein activity to allow readers to make informed decisions on the selection and implementation of currently available tools. SIGNIFICANCE STATEMENT: G protein activity biosensors have become essential and widespread tools to assess GPCR signaling and pharmacology. Yet, investigators face the challenge of choosing from a growing list of G protein activity biosensors. This review provides an overview of the features and capabilities of different optical biosensor designs for the direct detection of G protein activity in cells, with the aim of facilitating the rational selection of systems that align with the specific scientific questions and needs of investigators.

Dissecting the molecular basis for the modulation of neurotransmitter GPCR signaling by GINIP

It is well established that G-protein-coupled receptors (GPCRs) stimulated by neurotransmitters are critical for neuromodulation. Much less is known about how heterotrimeric G-protein (Gαβγ) regulation after receptor-mediated activation contributes to neuromodulation. Recent evidence indicates that the neuronal protein GINIP shapes GPCR inhibitory neuromodulation via a unique mechanism of G-protein regulation that controls pain and seizure susceptibility. However, the molecular basis of this mechanism remains ill-defined because the structural determinants of GINIP responsible for binding and regulating G proteins are not known. Here, we combined hydrogen-deuterium exchange mass spectrometry, computational structure predictions, biochemistry, and cell-based biophysical assays to demonstrate an effector-like binding mode of GINIP to Gαi. Specific amino acids of GINIP's PHD domain first loop are essential for G-protein binding and subsequent regulation of Gαi-GTP and Gβγ signaling upon neurotransmitter GPCR stimulation. In summary, these findings shed light onto the molecular basis for a post-receptor mechanism of G-protein regulation that fine-tunes inhibitory neuromodulation.

Characterization of the Prognosis and Tumor Microenvironment of Cellular Senescence-related Genes through scRNA-seq and Bulk RNA-seq Analysis in GC

BACKGROUND

Cellular senescence (CS) is thought to be the primary cause of cancer development and progression. This study aimed to investigate the prognostic role and molecular subtypes of CS-associated genes in gastric cancer (GC).

MATERIALS AND METHODS

The CellAge database was utilized to acquire CS-related genes. Expression data and clinical information of GC patients were obtained from The Cancer Genome Atlas (TCGA) database. Patients were then grouped into distinct subtypes using the "Consesus- ClusterPlus" R package based on CS-related genes. An in-depth analysis was conducted to assess the gene expression, molecular function, prognosis, gene mutation, immune infiltration, and drug resistance of each subtype. In addition, a CS-associated risk model was developed based on Cox regression analysis. The nomogram, constructed on the basis of the risk score and clinical factors, was formulated to improve the clinical application of GC patients. Finally, several candidate drugs were screened based on the Cancer Therapeutics Response Portal (CTRP) and PRISM Repurposing dataset.

RESULTS

According to the cluster result, patients were categorized into two molecular subtypes (C1 and C2). The two subtypes revealed distinct expression levels, overall survival (OS) and clinical presentations, mutation profiles, tumor microenvironment (TME), and drug resistance. A risk model was developed by selecting eight genes from the differential expression genes (DEGs) between two molecular subtypes. Patients with GC were categorized into two risk groups, with the high-risk group exhibiting a poor prognosis, a higher TME level, and increased expression of immune checkpoints. Function enrichment results suggested that genes were enriched in DNA repaired pathway in the low-risk group. Moreover, the Tumor Immune Dysfunction and Exclusion (TIDE) analysis indicated that immunotherapy is likely to be more beneficial for patients in the low-risk group. Drug analysis results revealed that several drugs, including ML210, ML162, dasatinib, idronoxil, and temsirolimus, may contribute to the treatment of GC patients in the high-risk group. Moreover, the risk model genes presented a distinct expression in single-cell levels in the GSE150290 dataset.

CONCLUSION

The two molecular subtypes, with their own individual OS rate, expression patterns, and immune infiltration, lay the foundation for further exploration into the GC molecular mechanism. The eight gene signatures could effectively predict the GC prognosis and can serve as reliable markers for GC patients.

Functional Assessment of Cancer-Linked Mutations in Sensitive Regions of Regulators of G Protein Signaling Predicted by Three-Dimensional Missense Tolerance Ratio Analysis

Regulators of G protein signaling (RGS) proteins modulate G protein-coupled receptor (GPCR) signaling by acting as negative regulators of G proteins. Genetic variants in RGS proteins are associated with many diseases, including cancers, although the impact of these mutations on protein function is uncertain. Here we analyze the RGS domains of 15 RGS protein family members using a novel bioinformatic tool that measures the missense tolerance ratio (MTR) using a three-dimensional (3D) structure (3DMTR). Subsequent permutation analysis can define the protein regions that are most significantly intolerant (P < 0.05) in each dataset. We further focused on RGS14, RGS10, and RGS4. RGS14 exhibited seven significantly tolerant and seven significantly intolerant residues, RGS10 had six intolerant residues, and RGS4 had eight tolerant and six intolerant residues. Intolerant and tolerant-control residues that overlap with pathogenic cancer mutations reported in the COSMIC cancer database were selected to define the functional phenotype. Using complimentary cellular and biochemical approaches, proteins were tested for effects on GPCR-Gα activation, Gα binding properties, and downstream cAMP levels. Identified intolerant residues with reported cancer-linked mutations RGS14-R173C/H and RGS4-K125Q/E126K, and tolerant RGS14-S127P and RGS10-S64T resulted in a loss-of-function phenotype in GPCR-G protein signaling activity. In downstream cAMP measurement, tolerant RGS14-D137Y and RGS10-S64T and intolerant RGS10-K89M resulted in change of function phenotypes. These findings show that 3DMTR identified intolerant residues that overlap with cancer-linked mutations cause phenotypic changes that negatively impact GPCR-G protein signaling and suggests that 3DMTR is a potentially useful bioinformatics tool for predicting functionally important protein residues. SIGNIFICANCE STATEMENT: Human genetic variant/mutation information has expanded rapidly in recent years, including cancer-linked mutations in regulator of G protein signaling (RGS) proteins. However, experimental testing of the impact of this vast catalogue of mutations on protein function is not feasible. We used the novel bioinformatics tool three-dimensional missense tolerance ratio (3DMTR) to define regions of genetic intolerance in RGS proteins and prioritize which cancer-linked mutants to test. We found that 3DMTR more accurately classifies loss-of-function mutations in RGS proteins than other databases thereby offering a valuable new research tool.

Fatty acid metabolism is related to the immune microenvironment changes of gastric cancer and RGS2 is a new tumor biomarker

Background

Alterations in lipid metabolism promote tumor progression. However, the role of lipid metabolism in the occurrence and development of gastric cancer have not been fully clarified.

Method

Here, genes that are related to fatty acid metabolism and differentially-expressed between normal and gastric cancer tissues were identified in the TCGA-STAD cohort. The intersection of identified differentially-expressed genes with Geneset was determined to obtain 78 fatty acid metabolism-related genes. The ConsensusClusterPlus R package was used to perform differentially-expressed genes, which yielded divided two gastric cancer subtypes termed cluster 1 and cluster 2.

Results

Patients in cluster 2 was found to display poorer prognosis than patients in cluster 1. Using machine learning method to select 8 differentially expressed genes among subtypes to construct fatty acid prognostic risk score model (FARS), which was found to display good prognostic efficacy. We also identified that certain anticancer drugs, such as bortezomib, elesclomol, GW843682X, and nilotinib, showed significant sensitivity in the high FARS score group. RGS2 was selected as the core gene upon an analysis of the gastric cancer single-cell, and Western blotting and immunofluorescence staining results revealed high level of expression of this gene in gastric cancer cells. The results of immunohistochemical staining showed that a large amount of RGS2 was deposited in the stroma in gastric cancer. A pan-cancer analysis also revealed a significant association of RGS2 with TMB, TIDE, and CD8+ T-cell infiltration in other cancer types as well. RGS2 may thus be studied further as a new target for immunotherapy in future studies on gastric cancer.

Conclusion

In summary, the FARS model developed here enhances our understanding of lipid metabolism in the TME in gastric cancer, and provides a theoretical basis for predicting tumor prognosis and clinical treatment.

Self-assembled dipeptide based fluorescent nanoparticles as a platform for developing cellular imaging probes and targeted drug delivery chaperones

Self-assembled peptide-based nanostructures, comprised of naturally occurring amino acids, display excellent biocompatibility, biodegradability, flexible responsiveness, and synthetic feasibility and can be customized for various biomedical applications. However, the lack of inherent optical properties of peptide-based nanoparticles is a limitation on their use as imaging probes or drug delivery vehicles. To overcome this impediment, we generated Boc protected tyrosine-tryptophan dipeptide-based nanoparticles (DPNPs) with structure rigidification by Zn(ii), which shifted the peptide's intrinsic fluorescent properties from the ultraviolet to the visible range. These DPNPs are photostable, biocompatible and have visible fluorescence signals that allow for real-time monitoring of their entry into cells. We further show that two DPNPs (PS1-Zn and PS2-Zn) can encapsulate the chemotherapeutic drug doxorubicin (Dox) and facilitate intracellular drug delivery resulting in cancer cell killing actions comparable to the unencapsulated drug. Finally, we chemically modified our DPNPs with an aptamer directed toward the epithelial cell surface marker EPCAM, which improved Dox delivery to the lung cancer epithelial cell line A549. In contrast, the aptamer conjugated DPNPs failed to deliver Dox into the cardiomyocyte cell line AC16. Theoretically, this strategy could be employed in vivo to specifically deliver Dox to cancer cells while sparing the myocardium, a major source of dose-limiting adverse events in the clinic. Our work represents an important proof-of-concept exercise demonstrating that ultra-short peptide-based fluorescent nanostructures have great promise for the development of new imaging probes and targeted drug delivery vehicles.

An Insight into GPCR and G-Proteins as Cancer Drivers

G-protein-coupled receptors (GPCRs) are the largest family of cell surface signaling receptors known to play a crucial role in various physiological functions, including tumor growth and metastasis. Various molecules such as hormones, lipids, peptides, and neurotransmitters activate GPCRs that enable the coupling of these receptors to highly specialized transducer proteins, called G-proteins, and initiate multiple signaling pathways. Integration of these intricate networks of signaling cascades leads to numerous biochemical responses involved in diverse pathophysiological activities, including cancer development. While several studies indicate the role of GPCRs in controlling various aspects of cancer progression such as tumor growth, invasion, migration, survival, and metastasis through its aberrant overexpression, mutations, or increased release of agonists, the explicit mechanisms of the involvement of GPCRs in cancer progression is still puzzling. This review provides an insight into the various responses mediated by GPCRs in the development of cancers, the molecular mechanisms involved and the novel pharmacological approaches currently preferred for the treatment of cancer. Thus, these findings extend the knowledge of GPCRs in cancer cells and help in the identification of therapeutics for cancer patients.

Residue-level determinants of RGS R4 subfamily GAP activity and specificity towards the Gi subfamily

The structural basis for the GTPase-accelerating activity of regulators of G protein signaling (RGS) proteins, as well as the mechanistic basis for their specificity in interacting with the heterotrimeric (αβγ) G proteins they inactivate, is not sufficiently understood at the family level. Here, we used biochemical assays to compare RGS domains across the RGS family and map those individual residues that favorably contribute to GTPase-accelerating activity, and those residues responsible for attenuating RGS domain interactions with Gα subunits. We show that conserved interactions of RGS residues with both the Gα switch I and II regions are crucial for RGS activity, while the reciprocal effects of "modulatory" and "disruptor" residues selectively modulate RGS activity. Our results quantify how specific interactions between RGS domains and Gα subunits are set by a balance between favorable RGS residue interactions with particular Gα switch regions, and unfavorable interactions with the Gα helical domain.

Exploring absent protein function in yeast: assaying post translational modification and human genetic variation

Yeast is a valuable eukaryotic model organism that has evolved many processes conserved up to humans, yet many protein functions, including certain DNA and protein modifications, are absent. It is this absence of protein function that is fundamental to approaches using yeast as an in vivo test system to investigate human proteins. Functionality of the heterologous expressed proteins is connected to a quantitative, selectable phenotype, enabling the systematic analyses of mechanisms and specificity of DNA modification, post-translational protein modifications as well as the impact of annotated cancer mutations and coding variation on protein activity and interaction. Through continuous improvements of yeast screening systems, this is increasingly carried out on a global scale using deep mutational scanning approaches. Here we discuss the applicability of yeast systems to investigate absent human protein function with a specific focus on the impact of protein variation on protein-protein interaction modulation.

G Protein-Coupled receptors and heterotrimeric G proteins as cancer drivers

G protein-coupled receptors (GPCRs) and heterotrimeric G proteins play central roles in a diverse array of cellular processes. As such, dysregulation of GPCRs and their coupled heterotrimeric G proteins can dramatically alter the signalling landscape and functional state of a cell. Consistent with their fundamental physiological functions, GPCRs and their effector heterotrimeric G proteins are implicated in some of the most prevalent human diseases, including a complex disease such as cancer that causes significant morbidity and mortality worldwide. GPCR/G protein-mediated signalling impacts oncogenesis at multiple levels by regulating tumour angiogenesis, immune evasion, metastasis, and drug resistance. Here, we summarize the growing body of research on GPCRs and their effector heterotrimeric G proteins as drivers of cancer initiation and progression, and as emerging antitumoural therapeutic targets.

Stability Analysis of a Signaling Circuit with Dual Species of GTPase Switches

GTPases are molecular switches that regulate a wide range of cellular processes, such as organelle biogenesis, position, shape, function, vesicular transport between organelles, and signal transduction. These hydrolase enzymes operate by toggling between an active ("ON") guanosine triphosphate (GTP)-bound state and an inactive ("OFF") guanosine diphosphate (GDP)-bound state; such a toggle is regulated by GEFs (guanine nucleotide exchange factors) and GAPs (GTPase activating proteins). Here we propose a model for a network motif between monomeric (m) and trimeric (t) GTPases assembled exclusively in eukaryotic cells of multicellular organisms. We develop a system of ordinary differential equations in which these two classes of GTPases are interlinked conditional to their ON/OFF states within a motif through coupling and feedback loops. We provide explicit formulae for the steady states of the system and perform classical local stability analysis to systematically investigate the role of the different connections between the GTPase switches. Interestingly, a coupling of the active mGTPase to the GEF of the tGTPase was sufficient to provide two locally stable states: one where both active/inactive forms of the mGTPase can be interpreted as having low concentrations and the other where both m- and tGTPase have high concentrations. Moreover, when a feedback loop from the GEF of the tGTPase to the GAP of the mGTPase was added to the coupled system, two other locally stable states emerged. In both states the tGTPase is inactivated and active tGTPase concentrations are low. Finally, the addition of a second feedback loop, from the active tGTPase to the GAP of the mGTPase, gives rise to a family of steady states that can be parametrized by a range of inactive tGTPase concentrations. Our findings reveal that the coupling of these two different GTPase motifs can dramatically change their steady-state behaviors and shed light on how such coupling may impact signaling mechanisms in eukaryotic cells.

Human genetic variants disrupt RGS14 nuclear shuttling and regulation of LTP in hippocampal neurons

The human genome contains vast genetic diversity as naturally occurring coding variants, yet the impact of these variants on protein function and physiology is poorly understood. RGS14 is a multifunctional signaling protein that suppresses synaptic plasticity in dendritic spines of hippocampal neurons. RGS14 also is a nucleocytoplasmic shuttling protein, suggesting that balanced nuclear import/export and dendritic spine localization are essential for RGS14 functions. We identified genetic variants L505R (LR) and R507Q (RQ) located within the nuclear export sequence (NES) of human RGS14. Here we report that RGS14 encoding LR or RQ profoundly impacts protein functions in hippocampal neurons. RGS14 membrane localization is regulated by binding Gαi-GDP, whereas RGS14 nuclear export is regulated by Exportin 1 (XPO1). Remarkably, LR and RQ variants disrupt RGS14 binding to Gαi1-GDP and XPO1, nucleocytoplasmic equilibrium, and capacity to inhibit long-term potentiation (LTP). Variant LR accumulates irreversibly in the nucleus, preventing RGS14 binding to Gαi1, localization to dendritic spines, and inhibitory actions on LTP induction, while variant RQ exhibits a mixed phenotype. When introduced into mice by CRISPR/Cas9, RGS14-LR protein expression was detected predominantly in the nuclei of neurons within hippocampus, central amygdala, piriform cortex, and striatum, brain regions associated with learning and synaptic plasticity. Whereas mice completely lacking RGS14 exhibit enhanced spatial learning, mice carrying variant LR exhibit normal spatial learning, suggesting that RGS14 may have distinct functions in the nucleus independent from those in dendrites and spines. These findings show that naturally occurring genetic variants can profoundly alter normal protein function, impacting physiology in unexpected ways.

Naturally occurring hotspot cancer mutations in Gα13 promote oncogenic signaling

Heterotrimeric G-proteins are signaling switches broadly divided into four families based on the sequence and functional similarity of their Gα subunits: Gs, Gi/o, Gq/11, and G12/13 Artificial mutations that activate Gα subunits of each of these families have long been known to induce oncogenic transformation in experimental systems. With the advent of next-generation sequencing, activating hotspot mutations in Gs, Gi/o, or Gq/11 proteins have also been identified in patient tumor samples. In contrast, patient tumor-associated G12/13 mutations characterized to date lead to inactivation rather than activation. By using bioinformatic pathway analysis and signaling assays, here we identified cancer-associated hotspot mutations in Arg-200 of Gα13 (encoded by GNA13) as potent activators of oncogenic signaling. First, we found that components of a G12/13-dependent signaling cascade that culminates in activation of the Hippo pathway effectors YAP and TAZ is frequently altered in bladder cancer. Up-regulation of this signaling cascade correlates with increased YAP/TAZ activation transcriptional signatures in this cancer type. Among the G12/13 pathway alterations were mutations in Arg-200 of Gα13, which we validated to promote YAP/TAZ-dependent (TEAD) and MRTF-A/B-dependent (SRE.L) transcriptional activity. We further showed that this mechanism relies on the same RhoGEF-RhoGTPase cascade components that are up-regulated in bladder cancers. Moreover, Gα13 Arg-200 mutants induced oncogenic transformation in vitro as determined by focus formation assays. In summary, our findings on Gα13 mutants establish that naturally occurring hotspot mutations in Gα subunits of any of the four families of heterotrimeric G-proteins are putative cancer drivers.

A Global Map of G Protein Signaling Regulation by RGS Proteins

The control over the extent and timing of G protein signaling is provided by the regulator of G protein signaling (RGS) proteins that deactivate G protein α subunits (Gα). Mammalian genomes encode 20 canonical RGS and 16 Gα genes with key roles in physiology and disease. To understand the principles governing the selectivity of Gα regulation by RGS, we examine the catalytic activity of all canonical human RGS proteins and their selectivity for a complete set of Gα substrates using real-time kinetic measurements in living cells. The data reveal rules governing RGS-Gα recognition, the structural basis of its selectivity, and provide principles for engineering RGS proteins with defined selectivity. The study also explores the evolution of RGS-Gα selectivity through ancestral reconstruction and demonstrates how naturally occurring non-synonymous variants in RGS alter signaling. These results provide a blueprint for decoding signaling selectivity and advance our understanding of molecular recognition principles.

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Systematic analysis reveals G protein selectivity of all canonical RGS proteins

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RGS proteins rely on selectivity bar codes for selective G protein recognition

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Transplantation of bar codes across RGS proteins switches their G protein preferences

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Natural variants, mutations, and evolution shape RGS selectivity

Optogenetic activation of heterotrimeric G-proteins by LOV2GIVe, a rationally engineered modular protein

Heterotrimeric G-proteins are signal transducers involved in mediating the action of many natural extracellular stimuli and many therapeutic agents. Non-invasive approaches to manipulate the activity of G-proteins with high precision are crucial to understand their regulation in space and time. Here, we developed LOV2GIVe, an engineered modular protein that allows the activation of heterotrimeric G-proteins with blue light. This optogenetic construct relies on a versatile design that differs from tools previously developed for similar purposes, that is metazoan opsins, which are light-activated G-protein-coupled receptors (GPCRs). Instead, LOV2GIVe consists of the fusion of a G-protein activating peptide derived from a non-GPCR regulator of G-proteins to a small plant protein domain, such that light uncages the G-protein activating module. Targeting LOV2GIVe to cell membranes allowed for light-dependent activation of Gi proteins in different experimental systems. In summary, LOV2GIVe expands the armamentarium and versatility of tools available to manipulate heterotrimeric G-protein activity.

Heterotrimeric Gq proteins as therapeutic targets?

Heterotrimeric G proteins are the core upstream elements that transduce and amplify the cellular signals from G protein-coupled receptors (GPCRs) to intracellular effectors. GPCRs are the largest family of membrane proteins encoded in the human genome and are the targets of about one-third of prescription medicines. However, to date, no single therapeutic agent exerts its effects via perturbing heterotrimeric G protein function, despite a plethora of evidence linking G protein malfunction to human disease. Several recent studies have brought to light that the Gq family-specific inhibitor FR900359 (FR) is unexpectedly efficacious in silencing the signaling of Gq oncoproteins, mutant Gq variants that mostly exist in the active state. These data not only raise the hope that researchers working in drug discovery may be able to potentially strike Gq oncoproteins from the list of undruggable targets, but also raise questions as to how FR achieves its therapeutic effect. Here, we place emphasis on these recent studies and explain why they expand our pharmacological armamentarium for targeting Gq protein oncogenes as well as broaden our mechanistic understanding of Gq protein oncogene function. We also highlight how this novel insight impacts the significance and utility of using G(q) proteins as targets in drug discovery efforts.