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We explored the dysregulation of G-protein-coupled receptor (GPCR) ligand systems in cancer transcriptomics datasets to uncover new therapeutics opportunities in oncology. We derived an interaction network of receptors with ligands and their biosynthetic enzymes. Multiple GPCRs are differentially regulated together with their upstream partners across cancer subtypes and are associated to specific transcriptional programs and to patient survival patterns. The expression of both receptor-ligand (or enzymes) partners improved patient stratification, suggesting a synergistic role for the activation of GPCR networks in modulating cancer phenotypes. Remarkably, we identified many such axes across several cancer molecular subtypes, including many involving receptor-biosynthetic enzymes for neurotransmitters. We found that GPCRs from these actionable axes, including, e.g., muscarinic, adenosine, 5-hydroxytryptamine, and chemokine receptors, are the targets of multiple drugs displaying anti-growth effects in large-scale, cancer cell drug screens, which we further validated. We have made the results generated in this study freely available through a webapp (gpcrcanceraxes.bioinfolab.sns.it).

Immune checkpoint blockade (ICB) targeting PD-1 and CTLA-4 has revolutionized cancer treatment. However, many cancers do not respond to ICB, prompting the search for additional strategies to achieve durable responses. G-protein-coupled receptors (GPCRs) are the most intensively studied drug targets but are underexplored in immuno-oncology. Here, we cross-integrated large singe-cell RNA-sequencing datasets from CD8+ T cells covering 19 distinct cancer types and identified an enrichment of Gαs-coupled GPCRs on exhausted CD8+ T cells. These include EP2, EP4, A2AR, β1AR and β2AR, all of which promote T cell dysfunction. We also developed transgenic mice expressing a chemogenetic CD8-restricted Gαs-DREADD to activate CD8-restricted Gαs signaling and show that a Gαs-PKA signaling axis promotes CD8+ T cell dysfunction and immunotherapy failure. These data indicate that Gαs-GPCRs are druggable immune checkpoints that might be targeted to enhance the response to ICB immunotherapies.

Little is known about the impact of metabolic stimuli on brain tissue at a molecular level. The ketone body beta-hydroxybutyrate (BHB) can be a signaling molecule regulating gene transcription. Thus, we assessed lysine beta-hydroxybutyrylation (K-bhb) levels in proteins extracted from the cerebral cortex of mice undergoing a ketogenic metabolic challenge (48 h fasting). We found that fasting enhanced K-bhb in a variety of proteins including histone H3. ChIP-seq experiments showed that K9 beta-hydroxybutyrylation of H3 (H3K9-bhb) was significantly enriched by fasting on more than 8000 DNA loci. Transcriptomic analysis showed that H3K9-bhb on enhancers and promoters correlated with active gene expression. One of the most enriched functional annotations both at the epigenetic and transcriptional level was "circadian rhythms''. Indeed, we found that the diurnal oscillation of specific transcripts was modulated by fasting at distinct zeitgeber times both in the cortex and suprachiasmatic nucleus. Moreover, specific changes in locomotor activity daily features were observed during re-feeding after 48-h fasting. Thus, our results suggest that fasting remarkably impinges on the cerebral cortex transcriptional and epigenetic landscape, and BHB acts as a powerful epigenetic molecule in the brain through direct and specific histone marks remodeling in neural tissue cells.

In this study we show that protein language models can encode structural and functional information of GPCR sequences that can be used to predict their signaling and functional repertoire. We used the ESM1b protein embeddings as features and the binding information known from publicly available studies to develop PRECOGx, a machine learning predictor to explore GPCR interactions with G protein and β-arrestin, which we made available through a new webserver (https://precogx.bioinfolab.sns.it/). PRECOGx outperformed its predecessor (e.g. PRECOG) in predicting GPCR-transducer couplings, being also able to consider all GPCR classes. The webserver also provides new functionalities, such as the projection of input sequences on a low-dimensional space describing essential features of the human GPCRome, which is used as a reference to track GPCR variants. Additionally, it allows inspection of the sequence and structural determinants responsible for coupling via the analysis of the most important attention maps used by the models as well as through predicted intramolecular contacts. We demonstrate applications of PRECOGx by predicting the impact of disease variants (ClinVar) and alternative splice forms from healthy tissues (GTEX) of human GPCRs, revealing the power to dissect system biasing mechanisms in both health and disease.

Many of the fundamental concepts of signal transduction and kinase activity are attributed to the discovery and crystallization of cAMP-dependent protein kinase, or protein kinase A. PKA is one of the best-studied kinases in human biology, with emphasis in biochemistry and biophysics, all the way to metabolism, hormone action, and gene expression regulation. It is surprising, however, that our understanding of PKA's role in disease is largely underappreciated. Although genetic mutations in the PKA holoenzyme are known to cause diseases such as Carney complex, Cushing syndrome, and acrodysostosis, the story largely stops there. With the recent explosion of genomic medicine, we can finally appreciate the broader role of the Gαs-PKA pathway in disease, with contributions from aberrant functioning G proteins and G protein-coupled receptors, as well as multiple alterations in other pathway components and negative regulators. Together, these represent a broad family of diseases we term the Gαs-PKA pathway signalopathies. The Gαs-PKA pathway signalopathies encompass diseases caused by germline, postzygotic, and somatic mutations in the Gαs-PKA pathway, with largely endocrine and neoplastic phenotypes. Here, we present a signaling-centric review of Gαs-PKA-driven pathophysiology and integrate computational and structural analysis to identify mutational themes commonly exploited by the Gαs-PKA pathway signalopathies. Major mutational themes include hotspot activating mutations in Gαs, encoded by GNAS, and mutations that destabilize the PKA holoenzyme. With this review, we hope to incite further study and ultimately the development of new therapeutic strategies in the treatment of a wide range of human diseases. SIGNIFICANCE STATEMENT: Little recognition is given to the causative role of Gαs-PKA pathway dysregulation in disease, with effects ranging from infectious disease, endocrine syndromes, and many cancers, yet these disparate diseases can all be understood by common genetic themes and biochemical signaling connections. By highlighting these common pathogenic mechanisms and bridging multiple disciplines, important progress can be made toward therapeutic advances in treating Gαs-PKA pathway-driven disease.

Oncodriver genes are usually identified when mutations recur in multiple tumours. Different drivers often converge in the activation or repression of key cancer-relevant pathways. However, as many pathways contain multiple members of the same gene family, individual mutations might be overlooked, as each family member would necessarily have a lower mutation frequency and thus not identified as significant in any one-gene-at-a-time analysis. Here, we looked for mutated, functional sequence positions in gene families that were mutually exclusive (in patients) with another gene in the same pathway, which identified both known and new candidate oncodrivers. For instance, many inactivating mutations in multiple G-protein (particularly Gi/o) coupled receptors, are mutually exclusive with Gαs oncogenic activating mutations, both of which ultimately enhance cAMP signalling. By integrating transcriptomics and interaction data, we show that the Gs pathway is upregulated in multiple cancer types, even those lacking known GNAS activating mutations. This suggests that cancer cells may develop alternative strategies to activate adenylate cyclase signalling in multiple cancer types. Our study provides a mechanistic interpretation for several rare somatic mutations in multi-gene oncodrivers, and offers possible explanations for known and potential off-label cancer treatments, suggesting new therapeutic opportunities.

G-protein coupled receptors (GPCRs) control multiple physiological states by transducing a multitude of extracellular stimuli into the cell via coupling to intra-cellular heterotrimeric G-proteins. Deciphering which G-proteins couple to each of the hundreds of GPCRs present in a typical eukaryotic organism is therefore critical to understand signalling. Here, we present PRECOG (precog.russelllab.org): a web-server for predicting GPCR coupling, which allows users to: (i) predict coupling probabilities for GPCRs to individual G-proteins instead of subfamilies; (ii) visually inspect the protein sequence and structural features that are responsible for a particular coupling; (iii) suggest mutations to rationally design artificial GPCRs with new coupling properties based on predetermined coupling features.

G protein-coupled receptors (GPCRs) are the largest gene family of cell membrane-associated molecules mediating signal transmission, and their involvement in key physiological functions is well-established. The ability of GPCRs to regulate a vast array of fundamental biological processes, such as cardiovascular functions, immune responses, hormone and enzyme release from endocrine and exocrine glands, neurotransmission, and sensory perception (e.g. vision, odor, and taste), is largely due to the diversity of these receptors and the layers of their downstream signaling circuits. Dysregulated expression and aberrant functions of GPCRs have been linked to some of the most prevalent human diseases, which renders GPCRs one of the top targets for pharmaceutical drug development. However, the study of the role of GPCRs in tumor biology has only just begun to make headway. Recent studies have shown that GPCRs can contribute to the many facets of tumorigenesis, including proliferation, survival, angiogenesis, invasion, metastasis, therapy resistance, and immune evasion. Indeed, GPCRs are widely dysregulated in cancer and yet are underexploited in oncology. We present here a comprehensive analysis of GPCR gene expression, copy number variation, and mutational signatures in 33 cancer types. We also highlight the emerging role of GPCRs as part of oncocrine networks promoting tumor growth, dissemination, and immune evasion, and we stress the potential benefits of targeting GPCRs and their signaling circuits in the new era of precision medicine and cancer immunotherapies.

Heterotrimetic G proteins consist of four subfamilies (Gs, Gi/o, Gq/11, and G12/13) that mediate signaling via G-protein-coupled receptors (GPCRs), principally by receptors binding Gα C termini. G-protein-coupling profiles govern GPCR-induced cellular responses, yet receptor sequence selectivity determinants remain elusive. Here, we systematically quantified ligand-induced interactions between 148 GPCRs and all 11 unique Gα subunit C termini. For each receptor, we probed chimeric Gα subunit activation via a transforming growth factor-α (TGF-α) shedding response in HEK293 cells lacking endogenous Gq/11 and G12/13 proteins, and complemented G-protein-coupling profiles through a NanoBiT-G-protein dissociation assay. Interrogation of the dataset identified sequence-based coupling specificity features, inside and outside the transmembrane domain, which we used to develop a coupling predictor that outperforms previous methods. We used the predictor to engineer designer GPCRs selectively coupled to G12. This dataset of fine-tuned signaling mechanisms for diverse GPCRs is a valuable resource for research in GPCR signaling.

Reducing CO2 emissions is becoming a particularly important goal for motorcycle manufacturers. A fully electric transition still seems far away, given the difficulties in creating an electric motorcycle with an acceptable range and mass. This opens up opportunities for the application of hybrid powertrains in motorcycles. Managing mass, cost, and volume is a challenging issue for motorcycles; therefore, an MHEV architecture represents an interesting opportunity, as it is a low-complexity and low-cost solution. Firstly, in this work, an adequate sizing of the powertrain components is studied for the maximum reduction in fuel consumption. This is performed by analyzing many different system configurations with different hybridization ratios. A 1D simulation of the motorcycle traveling along the homologation cycle (WMTC) is performed, and the powerunit use strategy is optimized for each configuration using the Dynamic Programming technique. The results are analyzed in order to highlight the impact of kinetic energy recovery and engine load-point shifting on fuel consumption reduction. The results show the applicability of MHEV technology to road motorcycles, thus providing a useful tool to analyze the cost/benefit ratio of this technology. The developed methodology is also suitable for different vehicles once a specific test cycle is known. [ABSTRACT FROM AUTHOR]

The autosomal dominant form of retinitis pigmentosa (adRP) is a blindness-causing conformational disease largely linked to mutations of rhodopsin. Molecular simulations coupled to the graph-based protein structure network (PSN) analysis and in vitro experiments were conducted to determine the effects of 33 adRP rhodopsin mutations on the structure and routing of the opsin protein. The integration of atomic and subcellular levels of analysis was accomplished by the linear correlation between indices of mutational impairment in structure network and in routing. The graph-based index of structural perturbation served also to divide the mutants in four clusters, consistent with their differences in subcellular localization and responses to 9-cis retinal. The stability core of opsin inferred from PSN analysis was targeted by virtual screening of over 300,000 anionic compounds leading to the discovery of a reversible orthosteric inhibitor of retinal binding more effective than retinal in improving routing of three adRP mutants.