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Systems modeling of oncogenic G-protein and oncogenic GPCR signaling reveals unexpected differences in downstream signaling pathway activation [CY_GQ_experiment]

ABSTRACT: Mathematical models of biochemical reaction networks are an important and emerging tool for the study of cell signaling networks involved in disease processes. One promising potential application of such mathematical models is the study of how disease causing mutations to one or more proteins in the network promote the signaling phenotype that contributes to the disease. It is commonly assumed that one must have a thorough characterization of the network readily available for mathematical modeling to be useful, but we hypothesized that mathematical modeling could be useful when there is incomplete knowledge and that it could be a tool for discovery that opens new areas for further exploration. In the present study, we first develop a mechanistic mathematical model of a G-protein coupled receptor signaling network that is mutated in almost all cases of uveal melanoma and use model-driven explorations to uncover and explore multiple new areas for investigating this disease. Modeling the two major, mutually-exclusive, oncogenic mutations (Gαq/11 and CysLT2R) revealed the potential for previously unknown qualitative differences between seemingly interchangeable disease-promoting mutations, and our experiments confirmed oncogenic CysLT2R was impaired at activating the FAK/YAP/TAZ pathway relative to Gαq/11. This led us to hypothesize that CYSLT2R mutations in UM must co-occur with other mutations to activate FAK/YAP/TAZ signaling, and our bioinformatic analysis uncovers a role for co-occurring mutations involving the plexin/semaphorin pathway, which has been shown capable of activating this pathway. Overall, this work highlights the power of mechanism-based computational systems biology as a discovery tool that can leverage available information to open new research areas.

ORGANISM(S): Homo sapiens

PROVIDER: GSE267152 | GEO | 2024/05/10

REPOSITORIES: GEO

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Project description:Uveal melanoma (UM) is the most prevalent cancer of the eye in adults, with a highly aggressive form of metastasis that is refractory to current therapies. UM is driven by aberrant activation of the Gαq pathway by hotspot activating mutation of GNAQ/GNA11, with few additional genetic aberrations. Despite this, there are limited effective targeted therapies currently available against the treatment of UM and mUM. Here, we performed a high-throughput chemogenetic drug screen in GNAQ-mutant UM contrasted with that of BRAF-mutant skin cutaneous melanoma, as a network chemical biology-based approach to identify therapeutic agents that target the mechanistic underpinnings driving UM. We observed strong genotype-driven drug sensitivities, and identified several drug classes with preferential activity against UM using a method termed Drug Set Enrichment Analysis (DSEA). Among them, we found an enrichment for PKC inhibitors, and identified one compound LXS-196, with the highest preferential activity against UM. Our investigation into the mechanism of action of LXS-196 revealed that in addition to inhibiting the Gq-ERK pathway, unlike other PKC inhibitors, this drug also reduced FAK activity, a recently identified mediator of non-canonical Gαq-driven oncogenic signaling. Kinome profiling revealed that LXS-196 acts as a multi-targeted kinase inhibitor, with high preference for PKC as well as PKN/PRK, the latter a poorly investigated AGC kinase that is activated directly by RhoA. This primes LXS-196 to target cell-essential pathways that drive tumor growth in UM by targeting both PKC, in addition to FAK. Moreover, we find that PKN is activated by GNAQ downstream from RhoA, thereby contributing to FAK stimulation. These findings expose a signaling vulnerability that can be targeted pharmacologically. Ultimately, dual PKC and PKN inhibition by LXS-196 acts synergistically with FAK inhibitors (FAKi) to halt UM growth and promote cytotoxic cell death in vitro and in preclinical metastatic mouse models, thus providing a highly translatable therapeutic multimodal precision strategy against mUM.

Project description:Uncontrolled Transforming growth factor-beta (TGFβ) signaling promotes aggressive metastatic properties in late-stage breast cancers. However, how TGFβ-mediated cues are directed to induce late-stage tumorigenic events is poorly understood, particularly given that TGFβ has clear tumor suppressing activity in other contexts. Here we demonstrate that the transcriptional regulators TAZ and YAP (TAZ/YAP), key effectors of the Hippo pathway, are necessary to promote and maintain TGFβ-induced tumorigenic phenotypes in breast cancer cells. Interactions between TAZ/YAP, TGFβ-activated SMAD2/3, and TEAD transcription factors reveal convergent roles for these factors in the nucleus. Genome-wide expression analyses indicate that TAZ/YAP, TEADs and TGFβ-induced signals coordinate a specific pro-tumorigenic transcriptional program. Importantly, genes cooperatively regulated by TAZ/YAP, TEAD, and TGFβ, such as the novel targets NEGR1 and UCA1, are necessary for maintaining tumorigenic activity in metastatic breast cancer cells. Nuclear TAZ/YAP also cooperate with TGFβ signaling to promote phenotypic and transcriptional changes in non-tumorigenic cells to overcome TGFβ repressive effects. Our work thus identifies crosstalk between nuclear TAZ/YAP and TGFβ signaling in breast cancer cells, revealing novel insight into late-stage disease-driving mechanisms. Expression profiling was conducted following the repression of the transcriptional regulators TAZ and YAP (TAZ/YAP), the TEAD family of transcription factors (TEAD1/2/3/4), or the TGFb signaling pathway (with SB-431542, an inhibitor of the TBRI recpeptor) in human MDA-MB-231-LM2 breast cancer cells treated with TGFβ1. Human MDA-MB-231-LM2-4 breast cancer cells were transfected with control siRNA, or siRNAs targeting TAZ/YAP or all four TEADs and were treated 24 hours later with 500pM TGFβ1 or 5mM SB-431542 for an additional 24 hours. Total RNA was isolated and twelve microarrays in total were performed, with each condition carried out three times on separate days. The Boston University Microarray Core generated the data using the Affymetrix Human Gene 1.0 St Array.

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Systems modeling of oncogenic G-protein and oncogenic GPCR signaling reveals unexpected differences in downstream signaling pathway activation [CY_GQ_experiment]

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