As a central regulatory hub, protein kinase A (PKA) coordinates numerous biological processes, including discrete effects on metabolic enzymes all the way to global effects on organism growth and development. Given the diversity of roles PKA can play in normal physiology it is not surprising that dysregulation of PKA leads to diverse pathophysiology and disease. While PKA is one of the most studied kinases, its role in diseases has remained largely unknown. With this dissertation, I aim to map the contributions of the Gαs-PKA pathway in disease from multiple perspectives. First, I aim to unify the view of PKA-driven pathophysiology by utilizing mutational data from hereditary diseases and cancer databases to define a family of diseases known as the Gαs-PKA pathway signalopathies. Further I utilize evidence from the scientific literature to bring functional understanding to these diverse disease states. Second, I leverage our genetic understanding of PKA pathway mutations to develop several transgenic mouse models of cancer, providing evidence of the role of GNAS in cancer initiation and tools for application in multiple tissue contexts. Finally, I take advantage of affinity purification mass spectrometry (AP-MS) approaches to identify novel PKA interactors. I uncover several functional themes and ultimately focus on specific RNA binding proteins interactions that mediate new mechanisms of posttranscriptional regulation. In total, this dissertation makes important progress towards the understanding of PKA-driven disease, providing a framework for the advancement of the field and ultimately unique opportunities for identifying therapeutic interventions.

G-protein coupled receptors (GPCRs) are the most intensively studied drug targets since they play key roles in many physiological processes, and they have remained longstanding favorable pharmacological targets. GPCRs have become one of the top targets for pharmaceutical drug development, largely due to their known dysregulated expression and aberrant functions in some of the most prevalent human diseases. However, the study of the role of GPCRs in tumor biology has only just begun to make headway. Though recent advances have enriched our understanding of the contribution of GPCRs to tumorigenesis, angiogenesis, and immune evasion, drug development for GPCRs in oncology is still underexploited. Adding to his, although checkpoint blockade immunotherapies (CBI) inhibiting programmed death-1 (PD-1) and cytotoxic T-lymphocyte antigen-4 (CTLA-4) have revolutionized cancer treatment, the limited response rates in most cancers suggest that new approaches, targets, and animal models that more faithfully recapitulate human cancers are clearly needed to fully elucidate the underlying biology of resistance to cancer immunotherapies. Here, we first developed a full, comprehensive analysis of GPCRs across multiple tumor types to highlight GPCRs that may be important to target on the global tumor level. Next, we explored whether a carcinogen-induced mouse model of oral cancer can better model mutational signatures and response to immunotherapies of human head and neck cancers. With these novel tools and analyses, we aimed to uncover new GPCR targets for immune oncology with cutting edge chemogenetic approaches to investigate the role of downstream Gas-signaling in CD8 T cells that infiltrate tumors. Altogether, our work here provides a platform to identify emerging GPCR targets that when blocked concomitant with PD-1 and CTLA-4, can enable achieving a higher response rate and more durable responses (cure). Ultimately, our studies provide novel therapeutic interventions as part of multimodal precision immunotherapies for oncology

Cancer immunotherapy has brought about a paradigm shift in the standard of care for cancer patients; however, the limited response rates in cancer patients underscores the persistent challenge in translating preclinical findings to effective clinical interventions. Here, we explore the imperative of 1) refining and developing preclinical animal models to better mirror human cancer and 2) identifying G protein-coupled receptors (GPCRs) as a promising avenue to improving responses to immunotherapy. Clinical success in the discovery and development of anti-cancer drugs have relied on the use of preclinical animal models, namely mice, to recapitulate tumor growth kinetics and tumor-intrinsic elements of human disease. However, many of the most commonly used syngeneic models for cancer immunotherapy do not properly resemble the disease state for which they were designed, and this discrepancy has been associated with a high attrition rate of preclinical and early-stage drug candidates failing to gain Food and Drug Administration (FDA) approval. This underscores the need to validate pre-existing models for disease relevance as well as to develop new pre-clinical models that can translate to human responses. Using new and pre-existing preclinical models, our research has identified GPCRs as critical regulators of the immune response within the tumor microenvironment (TME). GPCRs are the most intensively studied drug targets since they play key roles in many physiological processes, and they have remained longstanding favorable pharmacological targets. Here, we target GPCRs that have been identified on dysfunctional T cells using RNA-seq to relieve the immunosuppressive tumor microenvironment. Preliminary data shows an upregulation of Gαs-coupled receptors, PTGER2, PTGER4, and ADRB2, on activated and exhausted T cells in HNSC patients, suggesting that these GPCRs that are coupled to the G protein Gαs, and their downstream signaling cascades may be dampening anti-tumor cytotoxicity of CD8 T cells, leading to T cell dysfunction and exhaustion.

Tumors evolve from normal cells due to aberrant activation or repression of cell signaling. Our understanding of how these signaling pathways affect the phenotype of the malignant cells themselves, as well as the surrounding microenvironment, is lacking. As the era of precision medicine approaches, a more holistic understanding of cancer intrinsic signaling and its effect on the epigenome of tumor cells, as well as how these tumor cells interact with surrounding normal cells, is key to unlocking novel therapeutic targets and biomarkers. Through three examples of cancer evolution and signaling I will show the value of integrative data modeling to better understand the biology of this disease.First, in the context of breast cancer progression, I developed a microenvironment modeling approach to identify several novel intercellular signaling pathways that are altered in the transition from in situ to invasive disease. Second, in uveal melanoma, a cancer caused by aberrant GNAQ signaling, I generated and integrated transcriptional and protein level datasets together to nominate p53, and other pathways, as novel downstream targets of GNAQ. And third, in the context of head and neck cancer progression, I characterized the role of YAP activation in malignant transformation and cell signaling through EGFR and mTOR.

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