Purpose:

Uveal melanoma is the most common eye cancer in adults. Approximately 50% of patients with uveal melanoma develop metastatic uveal melanoma (mUM) in the liver, even after successful treatment of the primary lesions. mUM is refractory to current chemo- and immune-therapies, and most mUM patients die within a year. Uveal melanoma is characterized by gain-of-function mutations in GNAQ/GNA11, encoding Gαq proteins. We have recently shown that the Gαq–oncogenic signaling circuitry involves a noncanonical pathway distinct from the classical activation of PLCβ and MEK–ERK. GNAQ promotes the activation of YAP1, a key oncogenic driver, through focal adhesion kinase (FAK), thereby identifying FAK as a druggable signaling hub downstream from GNAQ. However, targeted therapies often activate compensatory resistance mechanisms leading to cancer relapse and treatment failure.

Experimental Design:

We performed a kinome-wide CRISPR-Cas9 sgRNA screen to identify synthetic lethal gene interactions that can be exploited therapeutically. Candidate adaptive resistance mechanisms were investigated by cotargeting strategies in uveal melanoma and mUM in vitro and in vivo experimental systems.

Results:

sgRNAs targeting the PKC and MEK–ERK signaling pathways were significantly depleted after FAK inhibition, with ERK activation representing a predominant resistance mechanism. Pharmacologic inhibition of MEK and FAK showed remarkable synergistic growth-inhibitory effects in uveal melanoma cells and exerted cytotoxic effects, leading to tumor collapse in uveal melanoma xenograft and liver mUM models in vivo.

Conclusions:

Coupling the unique genetic landscape of uveal melanoma with the power of unbiased genetic screens, our studies reveal that FAK and MEK–ERK cotargeting may provide a new network-based precision therapeutic strategy for mUM treatment.

See related commentary by Harbour, p. 2967

Translational Relevance

Most patients with metastatic uveal melanoma (mUM) are refractory to chemotherapies and immune checkpoint blockade, leading to patient death within a year of diagnosis. To date, there are no effective treatment options for mUM, highlighting an urgent need for novel therapeutic strategies. Uveal melanoma is characterized by gain-of-function mutations in GNAQ/GNA11, encoding Gαq proteins. Our recent studies identified focal adhesion kinase (FAK) as an integral component of the oncogenic Gαq signaling circuitry in uveal melanoma, and the clinical benefits of targeting FAK in mUM are already under current investigation. However, single-agent targeted therapies often activate adaptive mechanisms, resulting in drug resistance and treatment failure. Taking advantage of the unique genetic landscape of uveal melanoma and the use of unbiased genetic screens, our studies reveal that horizontal inhibition of FAK and the adaptive activation of MEK–ERK results in uveal melanoma cell death and tumor regression, thereby providing a novel multimodal precision therapy for mUM.

G protein–coupled receptors (GPCR) are the largest family of cell surface proteins with over 800 members (1), and their dysregulation contributes to some of the most prevalent human diseases (2–4). GPCRs represent the largest family of targets for approved drugs. Strikingly, our recent analysis of human cancer genomes revealed that nearly 30% of human cancers present mutations in G proteins and GPCRs (5). In particular, uveal melanoma can be defined as a Gαq-driven malignancy. Indeed, approximately 93% of uveal melanoma lesions harbor activating mutations in GNAQ or GNA11, encoding for the alpha subunits Gαq and Gα11 of the heterotrimeric G protein, respectively (6, 7). An additional 4% harbor mutations in the Gαq-linked receptor CYSLTR2, also acting as a driver oncogene (8).

Uveal melanoma is diagnosed in about 2,500 adults in the United States every year, and is the most common primary cancer of the eye in adults and the second most common melanoma subtype after skin cutaneous melanoma (9). Although the majority of early-stage uveal melanoma lesions can be treated by irradiation or enucleation, approximately 50% of the patients will metastasize, primarily to the liver, within 5 to 10 years after diagnosis (10). Inactivating mutations or copy loss of the BAP1 gene, which is located on chromosome 3p21, are strongly associated with metastasis in patients with uveal melanoma (11), supporting that BAP1 functions as a metastasis suppressor (12). Most patients with metastatic uveal melanoma (mUM) are refractory to current chemotherapies and immune checkpoint blockade (13). Ultimately, the majority of advanced disease patients succumb within a year due to the suboptimal efficacy of these treatments, often combined with severe toxicities, underlying the high unmet medical need for new therapeutic strategies.

Most of the recent clinical research efforts in uveal melanoma have focused on inhibiting the Gαq classical signaling pathway, PLCβ–PKC–ERK. MEK inhibitors (MEKi) selumetinib and trametinib have been extensively evaluated for mUM. Despite encouraging results in preclinical studies, MEK inhibition with these agents has been shown to have nearly no impact on the overall survival of patients with mUM, as single-agent or when combined with chemotherapy (14–16). Our recent findings uncovered a noncanonical Gαq signaling pathway, leading to the Rho-dependent activation of the Hippo/YAP pathway, which contributes to aberrant cancer cell growth (17, 18). By further decoding this oncogenic signaling circuitry, we showed that the nonreceptor focal adhesion kinase (FAK) is an integral node of this noncanonical Gαq pathway (19). Interestingly, FAK overexpression has already been associated with various cancer types including ovarian, head and neck, and breast cancers (20–22). Furthermore, multiple FAK inhibitors (FAKi), defactinib (VS-6063), PF-562271, GSK2256098, and IN10018, have been already tested in clinical trials, showing manageable toxicity profiles (23), and hence can be considered for mUM treatment. However, single-agent targeted therapies often activate compensatory mechanisms resulting in treatment resistance. This prompted us to perform a kinome-wide CRISPR-Cas9 sgRNA screen to identify synthetic lethal gene interactions in the context of FAKi that can be exploited therapeutically (24). Our study demonstrates that dual inhibition of MEK and FAK act synergistically to promote the conversion of cytostatic to cytotoxic inhibition of tumor growth, thereby identifying a new treatment option for mUM.

Reagents

DMEM, RPMI1640, and antibiotic/antimycotic solution were purchased from Sigma-Aldrich. Turbofect, DMEM/F12 Glutamax, basic FGF (bFGF), EGF, B-27, and N2 supplements were purchased from Thermo Fisher Scientific. FBS (lot 18H165) and penicillin/streptomycin are from Sigma Aldrich, Polybrene from Millipore, and AquaBluer from MultiTarget Pharmaceuticals.

VS-4718, VS-6063, and VS-6766 were provided by Verastem Oncology. All inhibitors used in this study were purchased from Selleck Chemicals. Anhydrous DMSO, carboxymethyl cellulose (CMC), polyethylene glycol 400 (PEG400), and Tween 80 were purchased from Sigma-Aldrich. Inhibitors were dissolved in DMSO to a stock concentration of 10 mmol/L, aliquoted, and stored at −80°C for in vitro experiments. For in vivo treatments, trametinib was prepared at a stock concentration 5 mg/mL in DMSO and freshly diluted in PBS containing 5.2% PEG400 + 5.2% Tween 80, and a dose of 1 mg/kg was administered once daily by intraperitoneal injection. VS-4718 was freshly diluted at 5 mg/mL in 0.5% CMC (C5678, Sigma-Aldrich) + 0.1% Tween 80 (P1754, Sigma Aldrich) in sterile water (B. Braun Medical) and a dose of 10 mL/kg was administered by oral gavage twice a day.

FAK, phospho-FAK, ERK, phospho-ERK, cleaved PARP1, cleaved caspase-3, YAP, Cas9, and GAPDH antibodies were purchased from Cell Signaling Technology. BAP1 and PARP1 were purchased from Santa Cruz Biotechnology. Bromodeoxyuridine (BrdUrd) was purchased from Abcam. All antibodies were diluted in 5% BSA at 1:500 to 1:1,000 before use for immunoblotting and in 3% BSA at 1:100 to 1:400 for IHC. pHAGE PGK-GFP-IRES-LUC-W was from Addgene (#46793).

Cell lines

HEK 293T cells were cultured in High Glucose DMEM and supplemented with 10% FBS and antibiotic/antimycotic solution (100 U penicillin, 0.1 mg/mL streptomycin, and 0.25 μg/mL amphotericin B). Uveal melanoma cell lines were cultured in RPMI1640 media supplemented with 10% FBS (92.1, OMM1.3, OMM1.5, and OMM1.5Cas9) or 20% FBS (MP41, MP46, MP38, and MM28) and antibiotic/antimycotic solution. Mouse melanoma B2905 cell line was cultured in RPMI1640 medium supplemented with 10% FBS. All cell lines were tested for Mycoplasma and proved to be Mycoplasma free using the MycoAlert PLUS Mycoplasma Detection Kit (Lonza).

Sphere formation assay

Cells were seeded in 96-well ultralow attachment culture dishes (Corning) at 100 cells/well with the indicated concentration of 10 nmol/L trametinib, 1 μmol/L VS-4718, or both. Medium consisted of serum-free DMEM/F12 GlutaMAX supplemented bFGF (20 ng/mL), EGF (20 ng/mL), B-27 (1:50 dilution), and N2 supplement (1:100 dilution). Three weeks after seeding, the number of spheres in each well and their sizes were assessed by bright-field microscopy and quantify using ImageJ (25).

Immunoblotting

Uveal melanoma cells were harvested at the indicated time points posttreatment with 10 nmol/L trametinib and 1 μmol/L VS-4718. Cell lysates were subjected to SDS/PAGE on 10% acrylamide gels and electroblotted to PVDF membranes. Blocking and primary and secondary antibody incubations of immunoblots were performed in Tris-buffered saline/Tween 20 [10 mmol/L Tris (pH 7.4), 150 mmol/L NaCl, and 0.1% Tween 20] supplemented with 5% (w/v) BSA. The primary antibodies were used according to the manufacturers' instructions. HRP-conjugated donkey anti-rabbit and anti-mouse IgGs were used at a dilution of 1:5,000, and immunoreactive bands were detected using enhanced chemiluminescence. Full blots are shown in Supplementary Fig. S4.

Flow cytometry

Apoptosis was determined by detecting phosphatidylserine exposure on cell plasma membranes using the fluorescent dye FITC Annexin V (BD Biosciences) according to the manufacturer's protocol. Briefly, at the end of the treatment period, the cells (including floating cells) were harvested and washed twice with cold PBS. After resuspension in 100 μL 1× binding buffer, 5 μL FITC Annexin V was added and the cells were incubated for 15 minutes at room temperature in the dark. Finally, 400 μL 1× binding buffer was added to the cells and flow cytometric analysis was conducted. The experiments were conducted in triplicate.

IHC

For IHC, all tissue samples were processed and stained as described previously (26). Slides were scanned using a Zeiss Axioscan Z1 slide scanner equipped with a 20×/0.8 NA objective. All image analyses were performed using the QuPath software (27) to perform cell detection and quantify each marker as a percentage of cells stained.

Kinome-wide CRISPR screen

Generation and validation of stable Cas9 lines

For lentivirus-Cas9 production, 293T cells were plated in a poly-D-lysine–coated dish and, 16 hours later, transfected with 12 μg pLenti-CAS9-Blast, 8 μg psPAX2, 4 μg pCMV-VSV-G, using 32 μL TurboFect Transfection Reagent, and media was refreshed 6 hours posttransfection. Forty-eight and 72 hours later, the virus-containing media was collected, filtered through a low protein binding filter unit (PVDF, 0.45 μm, Sigma-Aldrich), and stored at 4°C up to 5 days or at −80°C.

For lentivirus-Cas9 infection, OMM 1.5 cells were plated in a 6-well plate and, 16 hours later, transduced using 1 mL virus-containing media + 1 mL complete media + 10 μg/mL polybrene. The plate was centrifuged for 15 minutes at 1,200 rpm. The same process was repeated after 24 hours, and 48 hours later, the cells were selected with blasticidin (10 μg/mL).

Cas9 editing efficiency was measured by quantifying the editing frequency of the safe-harbor locus AAVS1(TGCCTAACAGGAGGTGGGGGTTAGACCCAATATCAGGAGACTAGGAAGGAGGAGGCCTAAGGATGGGGCTTTTCTGTCACCAATCCTGTCCCTAGTGGCCCCACTGTGGGGTGGAGGGG) by next-generation sequencing (NGS) using two separate sgRNA sequences (sgT1 and sgT2). Briefly, cells were transduced with either AAVS1 sgRNA and, after hygromycin-B selection, genomic DNA was isolated using the Qiagen DNeasy Blood and Tissue Kit (cat # 69504). The AAVS1 region was amplified, DNA gel-purified, and barcoded using the NEBNext Multiplex Oligos for Illumina Kit (E7335) for multi-plex sequencing. Analysis of genome editing was performed using CRISPResso (28).

Pooled CRISPR library details and lentivirus preparation

In total, 3,052 unique sgRNAs targeting 763 human kinome genes for 4 guides per target were used for pooled CRISPR screens [Brunello Human Kinome CRISPR Knockout Library (29); Addgene cat #75312]. Lenti-X 293T cells were seeded in 15-cm plates and transfected the next day with pooled CRISPR library DNA (21 μg), PAX2 (14 μg), and VSV-g (7 μg). Viral media was collected 48- and 72 hours posttransfection, pooled and concentrated using an ultracentrifugation protocol, and stored at −80°C in aliquots.

Infectious virus titer determination and transduction

Several aliquots of concentrated viral stock were used to infect separate 15-cm plates containing 4.8 × 106 OMM1.5-Cas9 cells that were seeded the day before. Noninfected plates for OMM 1.5 parental and Cas9 were also plated as antibiotic selection controls. Forty-eight hours posttransduction, cells were treated with 2 μg/mL puromycin for 72 hours. After puromycin selection, complete cell death was achieved in uninfected control plates. The number of puromycin-resistant cells in each infected plate was counted using the Countess Automated Cell Counter to calculate the functional titer of the viral stock. Cells for screening were infected with a virus dose to achieve a MOI of 0.4 to 0.5 with sufficient cell numbers plated to obtain a screening depth of >1,000 cells per sgRNA.

Screen setup

A total of 4.8 × 106 cells were seeded into 15-cm plates a day before CRISPR library transduction. Forty-eight hours posttransduction, cells were subject to puromycin selection (2 μg/mL; 72 hours). Cells were amplified and seeded into 15-cm plates (4 × 106 cells/plate) divided into two treatment arms: 3 replicate plates for either vehicle/DMSO or VS-4718 treatments. A total of 4 × 106 cells from each individual plate were passaged into a new plate containing DMSO or 0.5 μmol/L VS-4718 every 3 to 4 days for a total of 10 days of treatment. A total of 5 × 106 cells were aliquoted from each plate at the beginning and end of the screen and stored at −80°C for sgRNA quantification.

sgRNA quantification

Genomic DNA was isolated using the Qiagen DNeasy Blood and Tissue Kit (cat # 69504) according to the manufacturer's protocol. DNA concentration was measured using a Qubit assay (Thermo Fisher Scientific; cat #Q33226). Amplification of sgRNAs for NGS was performed according to the Broad Institute's recommended protocol. NGS read counts were processed, aligned, and analyzed using PinAPL-Py (30).

Prescreen evaluation of sgRNAs:

sgRNAs were quantified immediately prior to the start of the screen to evaluate CRISPR library representation: sgRNA representation was 99.5% and gene representation was 100%.

Postscreen evaluation of sgRNAs:

sgRNAs were quantified from each replicate plate at the end of the screen and analyzed to identify sgRNAs depleted in VS-4718–treated cells relative to DMSO-treated cells.

Synergy determination

Dose–response curves and determination of IC50 values

Cells were seeded at a density of 5 × 103 to 1 × 104 cells/well in 96-well white plates. Eight different dilutions of each inhibitor were assayed in technical triplicates for 72 hours in each experiment. Cell viability was measured with the AquaBluer Cell Viability Reagent on a Spark microplate reader (Tecan). Using the GraphPad Prism v8.2.0 software, the half-maximal inhibitor concentration values (GI50) were determined from the curve using the nonlinear log (inhibitor) versus response–variable slope (three parameters) equation. GI50 values were only determined for compounds that inhibited growth by more than 50%.

Synergy determination with the Chou–Talalay method

The Chou–Talalay method (31) was used to determine possible synergistic effects of selected kinase inhibitor combinations. Briefly, cells were seeded at a density of 5 × 103 to 1 × 104 cells/well in 96-well white plates (CulturePlate; PerkinElmer Inc.). Cells were treated with either single inhibitors or combinations thereof using eight different dilutions of each inhibitor and in technical triplicates. Cell viability was measured, after 72-hour treatment, with the AquaBluer Cell Viability Reagent on a Spark microplate reader (Tecan). Combination index (CI) values showing either synergy (<1) or antagonism (>1) were calculated using the following equation:

CI = (D)1/(Dx)1 + (D)2/(Dx)2, where Dx equals the concentration of the tested substance used in the single treatment that was required to decrease the cell viability by x% and D equals the concentration of the tested substance 1 in combination with the concentration of the tested substance 2 that when combined decreased the cell number by x%.

Synergy determination with the Bliss delta score

The Bliss independence model (32) assumes a stochastic process in which two drugs elicit their effects independently, and the expected combination effect was calculated using the following equation: IAB = IA + IB – IA x IB, where IA and IB are the single-agent inhibition levels at fixed concentrations. If the experimentally measured effect of the drug combination was equal to, higher than, or lower than the expected effect (IAB), the combination was considered to be additive (ΔBliss = 0), synergistic (<0), or antagonistic (>0), respectively.

Human xenograft tumor models

All animal studies were approved by the Institutional Animal Care and Use Committee of University of California, San Diego (San Diego, CA) with protocol S15195. Female 4- to 6-week-old NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ (SCID-NOD) mice were purchased from the UCSD in-house breeding program. Mice were injected subcutaneously in both flanks with either 2 × 106 or 2.5 × 106 92.1 or OMM1.3 cells, respectively. Mice were monitored twice weekly for tumor development. Tumor growth analysis was assessed as LW2/2, where L and W represent length and width of the tumor. VS-4718 (5 mg/mL) was prepared in 0.5% CMC (Sigma-Aldrich) and 0.1% Tween 80 (Sigma-Aldrich) in sterile water. Trametinib (0.1 mg/mL) was prepared in 5.2% polyethylene glycol 400 (Sigma-Aldrich) and 5.3% Tween 80 (Sigma-Aldrich) in DPBS. Mice were administered 50 mg/kg VS-4718 (Verastem Oncology) twice daily by oral gavage and 1 mg/kg trametinib once daily by intraperitoneal injection; control group was treated with each vehicle. Mice were euthanized at the indicated time points and tumors were isolated for sequencing, histologic, and IHC evaluation. Results of mice experiments were expressed as mean ± SEM of a total of tumors analyzed.

Human metastasis tumor model

Generation of stable GFP-Luc expressing 92.1

For lentivirus-GFP-Luc production, 293T cells were plated in a poly-D-lysine–coated 15-cm dish and, 16 hours later, transfected with 30 μg pHAGE PGK-GFP-IRES-LUC-W, 3 μg VSV-G, 1.5 μg Tat1b, 1.5 μg Rev1b, and 1.5 μg Gag/Pol using 25.2 μL p3000 buffer and 25.2 μL of Lipofectamine 3000 transfection reagent, and media was refreshed 16 hours posttransfection. Forty-eight and 72 hours later, the virus-containing media was collected, filtered through a low protein binding filter unit (PVDF, 0.45 μm, Sigma-Aldrich), and stored at 4°C up to 5 days or at −80°C.

For lentivirus-Cas9 infection, 92.1 cells were plated in a 6-well plate and, 16 hours later, transduced using 1 mL virus-containing media + 1 mL complete media + 10 μg/mL polybrene. The plate was centrifuged for 15 minutes at 1,200 rpm. GFP expression was validated by fluorescent microscopy.

Splenic injection

Mice were injected with 1 × 106 92.1 GFP-Luc cells in the spleen, followed by removal of the spleen at 2 minutes postinjection. Tumor implantation by bioluminescence was assessed twice weekly by bioluminescence images captured using the In Vivo Imaging System (IVIS) Spectrum (PerkinElmer). To this end, mice received an intraperitoneal injection of 200 mg/kg D-luciferin firefly potassium salt diluted in PBS 15 minutes before imaging (GoldBio). Total bioluminescence was determined upon subtracting the background from the region of interest. Vehicle, trametinib, VS-4718, or trametinib/VS-4718 were administered, starting 7 days postsurgery, with the abovementioned dosing.

Statistical analysis

GraphPad Prism version 8 for Windows (GraphPad Software) was used to perform data analyses, variation estimation, and validation of test assumptions. Statistical analysis was performed using either a paired Student t test or one-way ANOVA.

Identification of conditionally lethal drug targets of FAK inhibition

As the kinome has been the target of most drug discovery efforts, the identification of kinases whose activity are essential for uveal melanoma survival in the context of FAK inhibition may facilitate the discovery of new cotargeting strategies. To perform an efficient loss-of-function screen, we used a two-vector CRISPR system, expressing a Cas9 transgene in representative uveal melanoma cells (OMM1.5, originally derived from metastasis, hereby called OMM1.5Cas9), in which gene editing efficiency was validated (Fig. 1; Supplementary Fig. S1A and S1B). OMM1.5Cas9 cells were infected with the Human Kinome Brunello pooled sgRNAs library (29), targeting 763 kinase genes and containing 3,052 unique sgRNAs along with 100 nontargeting controls, and subjected to puromycin selection. Surviving cells were treated with either selective FAKi (VS-4718) or vehicle for 10 days, followed by the collection of cellular DNA for gRNA analysis by NGS (Fig. 1A). Depleted sgRNAs (dropouts) suggest that inhibition of their gene targets could sensitize cells to FAKi treatment. Our analysis of synthetic lethal interactors of FAKi revealed a significant enrichment of Gαq-PLC and MAPK components of the classical Gαq signaling cascade (Fig. 1B; Supplementary Fig. S1C). Using the pan-PKC inhibitor, Go-6983 (33), we found that inhibition of the canonical PLCβ–PKC–ERK pathway decreased uveal melanoma cell viability and that this inhibitory effect was further enhanced by combining Go-6983 with VS-4718 (Fig. 1C). However, PKC inhibition with Go-6983 was less effective in reducing active ERK (pERK) than the MEKi trametinib (Fig. 1D). This is aligned with prior studies supporting only partial pERK reduction after prolonged PKC inhibition (34), which may explain its very modest clinical activity in mUM (35). Thus, we focused on direct MEK inhibitors for further studies. Interestingly, inhibition of FAK by VS-4718 led to a gradual increase in pERK levels (Fig. 1D and E) and uveal melanoma cells stably expressing the constitutive active MEK mutant (MEK-S218/222D, MEK-DD) were more resistant to VS-4718 (Fig. 1F), suggesting a possible compensatory mechanism that may contribute to drug resistance.

Figure 1.

Kinome-wide CRISPR screen for synthetic lethal interactors of FAKi. A, OMM 1.5 cells expressing Cas9 were infected with the Brunello Human Kinome CRISPR sgRNA KO library at a MOI of 0.3. After selection, cells were treated with vehicle or 0.5 μmol/L VS-4718 (FAKi) for 10 days. B, Left, cell viability represented as fold change in FAKi-treated cells compared with control. Highlighted significant hits represent synthetic lethal genes with FAKi treatment. Right, KEGG pathways analysis for the top depleted sgRNAs (n = 200). C, 92.1 cell viability after 72-hour treatment with vehicle, 1 μmol/L Go-6983 (PKCi), 1 μmol/L VS-4718 or a combination of both. D, Time-course analysis of FAK and ERK phosphorylation in 92.1 cells treated with VS-4718 (1 μmol/L), Go-6983 (1 μmol/L), or trametinib (MEKi, 10 nmol/L). E, Quantification of pFAK/FAK and pERK/ERK ratios in 92.1 cells treated with 1 μmol/L VS-4718 or vehicle for 1 hour. F, Left, cell viability after 72-hour treatment with VS-4718 (1 μmol/L) in 92.1 cells expressing or not MEK-DD (S218/222D). Right, immunoblot showing pERK levels in 92.1 cells expressing or not MEK-DD (S218/222D). C, E, and F, Data shown represent the mean ± SEM of three independent experiments. ***, P < 0.001; **, P < 0.01; n.s., not significant.

Figure 1.

Kinome-wide CRISPR screen for synthetic lethal interactors of FAKi. A, OMM 1.5 cells expressing Cas9 were infected with the Brunello Human Kinome CRISPR sgRNA KO library at a MOI of 0.3. After selection, cells were treated with vehicle or 0.5 μmol/L VS-4718 (FAKi) for 10 days. B, Left, cell viability represented as fold change in FAKi-treated cells compared with control. Highlighted significant hits represent synthetic lethal genes with FAKi treatment. Right, KEGG pathways analysis for the top depleted sgRNAs (n = 200). C, 92.1 cell viability after 72-hour treatment with vehicle, 1 μmol/L Go-6983 (PKCi), 1 μmol/L VS-4718 or a combination of both. D, Time-course analysis of FAK and ERK phosphorylation in 92.1 cells treated with VS-4718 (1 μmol/L), Go-6983 (1 μmol/L), or trametinib (MEKi, 10 nmol/L). E, Quantification of pFAK/FAK and pERK/ERK ratios in 92.1 cells treated with 1 μmol/L VS-4718 or vehicle for 1 hour. F, Left, cell viability after 72-hour treatment with VS-4718 (1 μmol/L) in 92.1 cells expressing or not MEK-DD (S218/222D). Right, immunoblot showing pERK levels in 92.1 cells expressing or not MEK-DD (S218/222D). C, E, and F, Data shown represent the mean ± SEM of three independent experiments. ***, P < 0.001; **, P < 0.01; n.s., not significant.

Close modal

Synergistic antiproliferative effect of MEK and FAK cotargeting in uveal melanoma cells

Cotargeting of MEK and FAK inhibits both canonical and noncanonical Gαq signaling pathways and may provide a suitable drug combination for clinical application in mUM. We used the effect-based ΔBliss model and the dose-effect–based Chou–Talalay CI to assess synergistic, additive, or antagonistic drug interaction in a given combination. We confirmed that trametinib (MEKi) and VS-4718 (FAKi) decrease uveal melanoma cell growth as single agents. CI and ΔBliss scores both converged to demonstrate a synergistic interaction between trametinib and VS-4718 (Fig. 2A). Synergistic antiproliferative effects were observed using multiple clinically relevant MEKi (trametinib, cobimetinib, and selumetinib) as well as the second-generation RAF/MEK inhibitor VS-6766, combined with two different FAKi (VS-4718 and the clinically relevant defactinib). All combinations showed remarkable synergistic activity at relevant doses supporting a general drug–drug class pharmacodynamics interaction (Fig. 2B). Using a panel of GNAQ-mutant uveal melanoma cells lines with different expression levels of the metastasis suppressor protein BAP1 (12), we confirmed similar synergistic profiles in BAP1 wild-type or null cells (Fig. 2C and D), suggesting that this combination may also be active in mUM.

Figure 2.

Synergy between FAKi and MEKi in uveal melanoma and mUM cells. A, Left, 92.1 cell viability 72 hours after treatment. Right, CI values determined using the Chou–Talalay method (CI < 1 synergism, CI = 1 additivity, CI > 1 antagonism, scale from −2 to +2). Bottom, ΔBliss scores (score < 0 synergism, score = 0 additivity, score > 0 antagonism, scale from −1 to +1). B, CI at relevant doses (viability = 50% ± 5%) using various combinations of FAKi/MEKi. C, Immunoblot depicting BAP1 levels in uveal melanoma and mUM patient-derived cells. D, Delta score (ΔBliss), assessing synergism between MEKi (trametinib, 10 nmol/L) and FAKi (VS-4718, 1 μmol/L) in a panel of uveal melanoma and mUM cells with distinct BAP1 status.

Figure 2.

Synergy between FAKi and MEKi in uveal melanoma and mUM cells. A, Left, 92.1 cell viability 72 hours after treatment. Right, CI values determined using the Chou–Talalay method (CI < 1 synergism, CI = 1 additivity, CI > 1 antagonism, scale from −2 to +2). Bottom, ΔBliss scores (score < 0 synergism, score = 0 additivity, score > 0 antagonism, scale from −1 to +1). B, CI at relevant doses (viability = 50% ± 5%) using various combinations of FAKi/MEKi. C, Immunoblot depicting BAP1 levels in uveal melanoma and mUM patient-derived cells. D, Delta score (ΔBliss), assessing synergism between MEKi (trametinib, 10 nmol/L) and FAKi (VS-4718, 1 μmol/L) in a panel of uveal melanoma and mUM cells with distinct BAP1 status.

Close modal

MEKi/FAKi combination increases uveal melanoma apoptotic cell death and reduces melanosphere formation

Several FAKi inhibitors have been evaluated in the clinic and demonstrated primarily a cytostatic effect as single agents (23). Given the high synergistic activity of MEKi and FAKi combination in vitro, we next evaluated the ability of trametinib and VS-4718 to induce cell death. As shown in Fig. 3A, FACS analysis suggests that trametinib induces an increase in the fraction of apoptotic cells (Annexin V+), while VS-4718 has no apoptotic activity as a single agent. Nonetheless, when both drugs were combined, at a ratio of 1:100 based on our isobologram analysis (Supplementary Fig. S2), the apoptotic response was significantly increased.

Figure 3.

MEKi/FAKi combination induces apoptosis and reduces uveal melanoma melanosphere formation. A, FACS analysis of cells positive for Annexin V was used to assess the apoptotic response to trametinib (10 nmol/L), VS-4718 (1 μmol/L), and their combination after 24 hours of treatment. B, Immunoblot showing cleaved-PARP, pFAK (pY-397), and pERK levels upon treatment with vehicle, trametinib (10 nmol/L), VS-4718 (1 μmol/L), or trametinib + VS-4718 for 48 hours in uveal melanoma cells. C, Left, OMM1.3 melanospheres formation after treatment with vehicle (control), trametinib (10 nmol/L), VS-4718 (1 μmol/L), or trametinib + VS-4718 for 3 weeks. Right, representative spheres. A and C, Data shown represent the mean ± SEM of three independent experiments. ***, P < 0.001; **, P < 0.01; n.s., not significant.

Figure 3.

MEKi/FAKi combination induces apoptosis and reduces uveal melanoma melanosphere formation. A, FACS analysis of cells positive for Annexin V was used to assess the apoptotic response to trametinib (10 nmol/L), VS-4718 (1 μmol/L), and their combination after 24 hours of treatment. B, Immunoblot showing cleaved-PARP, pFAK (pY-397), and pERK levels upon treatment with vehicle, trametinib (10 nmol/L), VS-4718 (1 μmol/L), or trametinib + VS-4718 for 48 hours in uveal melanoma cells. C, Left, OMM1.3 melanospheres formation after treatment with vehicle (control), trametinib (10 nmol/L), VS-4718 (1 μmol/L), or trametinib + VS-4718 for 3 weeks. Right, representative spheres. A and C, Data shown represent the mean ± SEM of three independent experiments. ***, P < 0.001; **, P < 0.01; n.s., not significant.

Close modal

One of the most common signaling cascades involved in apoptosis is the activation of a highly specialized family of cysteinyl-aspartate proteases (caspases; ref. 36). Caspase-mediated cell death is achieved through the cleavage of multiple key proteins that are essential to cell survival. PARP-1 is one of the substrates of caspases and a well-established marker for apoptosis (37). Aligned with our prior results, cleaved PARP levels were strongly increased by the combination of FAKi and MEKi (Fig. 3B), while single agents were less active. We then evaluated the ability of VS-4718 and trametinib to induce apoptosis in BAP1-null mUM cells. FAKi alone showed a minimal apoptotic response, and the combination of VS-4718 and trametinib resulted in increased cleaved PARP compared with trametinib alone (Fig. 3B).

Cancer-initiating cells are believed to play a central role in drug resistance and metastasis (38). A typical feature of these cells is their ability to form 3D tumorspheres when cultured in suspension in a stem cell medium. Interestingly, we found that the metastatic-derived OMM1.3 cells, but not 92.1 cells originating from a primary tumor, were able to form melanospheres. Using this model, we found that both VS-4718 and trametinib significantly reduced melanosphere formation as single agents when compared with vehicle (Fig. 3C), and this effect was further enhanced when both drugs were combined. Our results demonstrate that MEKi/FAKi combination acts by inhibiting cancer cell proliferation, including cancer-initiating cells, and enhancing apoptotic cell death. This suggests that this multimodal targeted therapy could be effective on primary and mUM.

Potent antitumoral and cytotoxic effects of MEKi/FAKi combination in uveal melanoma xenograft and liver metastasis models

We used uveal melanoma xenograft models to evaluate the anticancer activity of the MEKi/FAKi combination in vivo. Tumor-bearing mice were randomly divided into four groups: control, trametinib, VS-4718, and trametinib/VS-4718. In this regard, whereas VS-4718 has better pharmacokinetics than defactinib in mice, the latter is better able to inhibit tumor FAK activity with tolerability in patient with cancer (39). Therefore, VS-4718 is used as a surrogate FAKi in murine preclinical models. As shown in Fig. 4A and B, in the 92.1 xenograft model, although trametinib and VS-4718 effectively induced tumor stasis as single agents, only the combination of trametinib with VS-4718 was able to induce tumor regression. No significant difference in body weight was observed between the control and any of the treated groups (Fig. 4C), suggesting that all treatments were well tolerated by the mice. These results were further confirmed using another uveal melanoma cellular system harboring GNAQ mutations, OMM1.3, albeit in this case MEKi alone was quite potent (see Supplementary Fig. S3). We extended these studies in allograft experiments using the recently developed GNAQ-driven B2905 syngeneic mouse melanoma model (40). These cells are highly sensitive to the Gαq inhibitor FR900359, as we reported in a large panel uveal melanoma cells (41), and to the combined inhibition of MEK and FAK (Supplementary Fig. S4). These cells exhibit limited responses to FAKi in vivo, likely reflecting the complexity of genetic alterations of these cells (40). MEKi limited tumor growth, but prolonged inhibition resulted in acquisition of resistance and rapid tumor regrowth, thereby compromising animal survival. Remarkably, the combination therapy was quite effective in promoting tumor regression, and no resistance was observed for the prolonged duration of the mouse experiments (>40 days).

Figure 4.

MEKi/FAKi combination uveal melanoma growth in in vivo xenograft mouse models. A, Changes in 92.1 xenograft tumor volume in mice treated with vehicle (control), trametinib 1 mg/kg, VS-4718 50 mg/kg or trametinib + VS-4718. B, H&E staining of representative xenograft tumor sections after 20 days of treatment. C, Difference in mice body weight between day 0 and day 20 of the indicated treatment in 92.1 xenografts mice. Box and whiskers plot with minimum and maximum whiskers (7 mice/group). D, 92.1 tumor-bearing mice were treated with vehicle (control), trametinib 1 mg/kg, VS-4718 50 mg/kg, or trametinib + VS-4718 for 20 days. Representative IHC staining tumor sections for BrdUrd, cleaved caspase-3 (cl-Casp3), pERK, and YAP. Scale bar is 100 μm and insets are 50 μm wide. E, Quantification of the IHC-stained tumor sections. A and E, Data, mean ± SEM (7 mice/group). *, P < 0.05; **, P < 0.01; ***, P < 0.001; n.s., not significant.

Figure 4.

MEKi/FAKi combination uveal melanoma growth in in vivo xenograft mouse models. A, Changes in 92.1 xenograft tumor volume in mice treated with vehicle (control), trametinib 1 mg/kg, VS-4718 50 mg/kg or trametinib + VS-4718. B, H&E staining of representative xenograft tumor sections after 20 days of treatment. C, Difference in mice body weight between day 0 and day 20 of the indicated treatment in 92.1 xenografts mice. Box and whiskers plot with minimum and maximum whiskers (7 mice/group). D, 92.1 tumor-bearing mice were treated with vehicle (control), trametinib 1 mg/kg, VS-4718 50 mg/kg, or trametinib + VS-4718 for 20 days. Representative IHC staining tumor sections for BrdUrd, cleaved caspase-3 (cl-Casp3), pERK, and YAP. Scale bar is 100 μm and insets are 50 μm wide. E, Quantification of the IHC-stained tumor sections. A and E, Data, mean ± SEM (7 mice/group). *, P < 0.05; **, P < 0.01; ***, P < 0.001; n.s., not significant.

Close modal

We next evaluated MEK/ERK and FAK/YAP pathway activities in the uveal melanoma xenograft tumor specimens by IHC (Fig. 4D and E). As expected, pERK1/2 was strongly decreased only in the trametinib and trametinib/VS-4718–treated groups. We monitored YAP nuclear exclusion as a readout for YAP inactivation upon FAKi treatment (18) and observed decreased nuclear YAP in the VS-4718 and trametinib/VS-4718 treatment groups exclusively. The percentage of proliferating BrdUrd-positive cells was significantly decreased in all treated groups, with the VS-4718 and trametinib/VS-4718 treatment groups showing the most significant inhibition. Using cleaved caspase-3 (cl-Casp3) as a marker for apoptosis, we detected a significant increase of cl-Casp3 in the trametinib/VS-4718 group compared with the single-agent groups, suggesting that the MEKi/FAKi combination induces a switch from cytostatic to cytotoxic activity, consistent with the increased cl-PARP levels observed in vitro.

To assess the efficacy of the MEKi/FAKi combination treatment on a murine system that better represents the advanced disease, we developed a preclinical liver metastasis model. Luciferase/GFP–expressing 92.1 cells (92.1-Luc) were injected into the spleen and allowed hematogenous dissemination followed by complete splenic resection (Fig. 5A). Mice were sacrificed 8 weeks postinjection and necropsies showed macroscopic hepatic metastases with no sign of dissemination to any other organs (Fig. 5B), confirming the strong liver tropism of uveal melanoma cells. Remarkably, when tumor-bearing mice were treated with trametinib, VS-4718, or trametinib/VS-4718, the metastatic burden was reduced by MEKi and FAKi treatment and their combination (Fig. 5C and D). FAKi alone was cytostatic, whereas MEKi and MEKi/FAKi combination induced tumor regression. However, detailed analysis showed that the residual disease in the trametinib alone–treated group represented 24.2% ± 0.6% of the initial tumor compared with 7.5% ± 0.2% in the combination-treated group (P = 0.0002), achieving none versus 40% complete responses, respectively (Fig. 5E ). Resistance to trametinib in patients has led to the failure of this agent in uveal melanoma clinical trials. To further investigate resistance to trametinib as a single agent or as part of a combination with FAKi in our metastatic model, we adjusted the dose of trametinib to reach maximum plasma levels similar to those achieved in humans at the recommended therapeutic dose, 2 mg/day, which is approximately 22 ng/mL upon repeated dosing (42). Mice treated with 0.1 mg/kg trametinib, achieving approximately 20 ng/mL (42), become resistant to treatment with a progressive increase of metastatic burden, whereas tumor burden remains barely undetectable in mice treated with the combination. Taken together, these findings indicate that treatment with trametinib combined with VS-4718 inhibited uveal melanoma tumor growth in subcutaneous and liver metastasis models.

Figure 5.

MEKi/FAKi combination reduces uveal melanoma cells growth in an in vivo liver metastasis model. A, Schematic of the hematogenous dissemination model for uveal melanoma liver metastasis using 92.1 GFP-Luc cells. B, Left, macroscopic view of liver metastasis 8 weeks after splenic injection. Right, H&E staining of liver and lung. C, Hepatic tumor burden tracked by IVIS imaging after injection of 92.1 uveal melanoma cells in SCID/NOD mice treated with vehicle (control), trametinib 1 mg/kg, VS-4718 50 mg/kg, or both. Data, mean ± SEM (6 mice/group). ***, P < 0.001; n.s., not significant. D, Representative mice treated with vehicle (control), trametinib 1 mg/kg, VS-4718 50 mg/kg, or both, at the indicated days of treatment, and representative ex vivo imaging of the liver obtained at day 21. E, Hepatic tumor burden tracked by IVIS imaging after injection of 92.1 uveal melanoma cells in SCID/NOD mice treated with vehicle (control), trametinib 0.1 mg/kg, VS-4718 50 mg/kg, or both. Data, mean ± SEM (5 mice/group). ***, P < 0.001; **, P < 0.01. F, Representative ex vivo imaging of the liver from mice treated for 35 days with trametinib 0.1 mg/kg, VS-4718 50 mg/kg, or both.

Figure 5.

MEKi/FAKi combination reduces uveal melanoma cells growth in an in vivo liver metastasis model. A, Schematic of the hematogenous dissemination model for uveal melanoma liver metastasis using 92.1 GFP-Luc cells. B, Left, macroscopic view of liver metastasis 8 weeks after splenic injection. Right, H&E staining of liver and lung. C, Hepatic tumor burden tracked by IVIS imaging after injection of 92.1 uveal melanoma cells in SCID/NOD mice treated with vehicle (control), trametinib 1 mg/kg, VS-4718 50 mg/kg, or both. Data, mean ± SEM (6 mice/group). ***, P < 0.001; n.s., not significant. D, Representative mice treated with vehicle (control), trametinib 1 mg/kg, VS-4718 50 mg/kg, or both, at the indicated days of treatment, and representative ex vivo imaging of the liver obtained at day 21. E, Hepatic tumor burden tracked by IVIS imaging after injection of 92.1 uveal melanoma cells in SCID/NOD mice treated with vehicle (control), trametinib 0.1 mg/kg, VS-4718 50 mg/kg, or both. Data, mean ± SEM (5 mice/group). ***, P < 0.001; **, P < 0.01. F, Representative ex vivo imaging of the liver from mice treated for 35 days with trametinib 0.1 mg/kg, VS-4718 50 mg/kg, or both.

Close modal

The limited responses of uveal melanoma to immunotherapies (40) and the lack of an FDA-approved standard of care for patients with mUM poses an urgent unmet medical need that necessitates the development of new targeted treatment options. Most clinical studies in uveal melanoma have focused on canonical kinases activated downstream from Gq/G11 with MEK as the major therapeutic target (43). MAPK/ERK pathway inhibitors have been proven to be effective treatments in various cancer types, but their effectiveness is often short-lived, with resistance developing often after the start of treatment (44–47). Uveal melanoma was no exception and despite encouraging results in an initial phase II trial, with the MEK inhibitor selumetinib (AZD6244) showing an improved progression-free survival (PFS) compared with dacarbazine or temozolomide (15), the subsequent phase III double-blind trial failed to show improvement in PFS and overall survival with selumetinib + dacarbazine compared with dacarbazine alone (16). Here, we found that adaptive activation of MEK–ERK represents a compensatory resistance mechanism to FAK inhibition, and that in turn concomitant targeting FAK and MEK–ERK converts the cytostatic effects of FAKi into cytotoxic, resulting in uveal melanoma cell death. These findings suggest that dual inhibition of MEK and FAK may represent a promising therapeutic option for patients with advanced and metastatic uveal melanoma.

Our previous studies revealed that Gαq triggers the activation of the FAK/Hippo–YAP pathway, which represents a major driver in uveal melanoma progression (18, 19). Given that, we aimed at identifying synthetic lethal interactors that could potentiate FAKi efficiency and simultaneously reduce the risk of developing drug resistance (24), which is often observed in single-drug therapy. Our kinome-wide CRISPR/Cas9 screen unveiled potent synthetic lethality between FAKi and the MEK/ERK pathway, uncovering the therapeutic potential of a cotargeting strategy. This idea is reinforced by a recent study demonstrating that treatment of uveal melanoma cells with the MEKi trametinib increased YAP activity and cell proliferation (48), and our findings that FAK/Hippo–YAP pathway inhibition leads to a gradual increase of pERK. These results suggest that both Gαq-activated pathways, FAK/Hippo–YAP and MEK/ERK, can be part of compensatory feedback processes, and that horizontal inhibition of FAK and MEK might be necessary to achieve tumor regression, and prevent treatment resistance and tumor relapse (Fig. 6). In addition, concomitant inhibition of FAK and MEK triggers the activation of apoptotic cell death programs, whose full elucidation may facilitate the identification of mechanistic biomarkers predicting therapeutic response. Of interest, most uveal melanoma and mUM models used in our studies are driven by the GNAQ oncogene. However, based on its high similarity with the GNA11 oncogene, our findings are also expected to be applicable to GNA11-mutant uveal melanoma lesions (6, 7), which should be nonetheless tested experimentally.

Figure 6.

Horizontal inhibition of compensatory pathways in uveal melanoma using MEKi/FAKi combination. The cartoon depicts the proposed pathways by which active GNAQ-mutant controls cell proliferation in uveal melanoma cells. Horizontal inhibition of FAK and MEK likely acts by disabling growth-promoting pathways regulated by YAP while concomitantly targeting parallel converging core survival mechanisms, thereby resulting in mUM regression.

Figure 6.

Horizontal inhibition of compensatory pathways in uveal melanoma using MEKi/FAKi combination. The cartoon depicts the proposed pathways by which active GNAQ-mutant controls cell proliferation in uveal melanoma cells. Horizontal inhibition of FAK and MEK likely acts by disabling growth-promoting pathways regulated by YAP while concomitantly targeting parallel converging core survival mechanisms, thereby resulting in mUM regression.

Close modal

Several potent FAKis have been tested in the clinic in multiple cancer types, showing target inhibition and manageable toxicity profiles. Indeed, based on our findings, a phase I clinical trial using IN10018 as a potent FAKi has been recently initiated in mUM (NCT04109456). The use of FAKis as single agents may act primarily as cytostatic, suggesting the possibility of identifying suitable combination strategies to reach a greater clinical efficacy. Our study supports the clinical potential of cotargeting FAK and its sensitizing pathway, MEK/ERK, as a precision therapy approach in GNAQ-driven uveal melanoma, achieving tumor regression. In this regard, the FAKi defactinib has been recently combined with a RAF/MEKi (VS-6766) in multiple cancer types (NCT03875820). Through the use of an intermittent dosing schedule, the defactinib/VS-6766 combination has shown a manageable safety profile with initial clinical activity in early clinical trial results to date (49). Altogether, we believe our study presents a strong potential for clinical translation as a multimodal signal transduction–based precision therapy for mUM.

J.S. Paradis reports a patent for 16/824639 pending. M. Acosta reports a patent for 16/824639 pending. A. Kishore reports grants from NIH during the conduct of the study, as well as a patent for US20200323863A1 pending. N. Arang reports a patent for US20200323863A1 pending to UCSD. P. Mali is a scientific co-founder of Shape Therapeutics, Boundless Biosciences, Seven Therapeutics, Navega Therapeutics, and Engine Biosciences, which have no commercial interests related to this study. The terms of these arrangements have been reviewed and approved by the University of California, San Diego in accordance with its conflict of interest policies. J.A. Pachter is an employee and shareholder of Verastem Oncology. A.E. Aplin reports ownership interest in patent number 9880150 and a commercial research grant from Pfizer Inc. (2013–2017). J.S. Gutkind reports grants from NIH/NCI and grants from NIH/NCI during the conduct of the study, as well as a patent for 16/824639 pending, and is a consulting member of the scientific advisory board of Oncoceutics, Vividion Therapeutics, and Domain Therapeutics. No disclosures were reported by the other authors.

J.S. Paradis: Conceptualization, formal analysis, funding acquisition, validation, investigation, methodology, writing–original draft. M. Acosta: Formal analysis, validation, investigation, writing–original draft. R. Saddawi-Konefka: Conceptualization, investigation, writing–review and editing. A. Kishore: Conceptualization, formal analysis, writing–review and editing. F. Gomes: Investigation, writing–review and editing. N. Arang: Investigation, writing–review and editing. M. Tiago: Investigation, writing–review and editing. S. Coma: Conceptualization, methodology, writing–review and editing. S. Lubrano: Investigation, writing–review and editing. X. Wu: Conceptualization, writing–review and editing. K. Ford: Conceptualization, writing–review and editing. C.-P. Day: Resources. G. Merlino: Resources. P. Mali: Conceptualization, writing–review and editing. J.A. Pachter: Conceptualization, resources, writing–review and editing. T. Sato: Writing–review and editing. A.E. Aplin: Writing–review and editing. J.S. Gutkind: Conceptualization, resources, supervision, validation, methodology, writing–original draft, project administration, writing–review and editing.

pHAGE PGK-GFP-IRES-LUC-W was a generous gift from Dr. Schoenberger (La Jolla Institute for Immunology). We thank Drs. Alfredo Molinolo for insightful discussion and Helen T. Michael for characterization of mouse melanoma cells. We thank the La Jolla Institute Microscopy and Histology Core Facility for their support with the IHC data presented in this article. We thank the Moores Cancer Center Microscopy Core for the in vivo imaging support. The cartoon was created with BioRender.com. This work was supported, in whole or in part, by NIH Grant R33CA225291 and U54CA209891 to JSG and R01CA196278 and R01CA182635 to AEA. J.S. Paradis was supported by a fellowship from the Canadian Institute for Health Research. K. Ford was supported by the National Science Foundation Graduate Research Fellowship Program (DGE-1650112). S. Lubrano was supported by funding from AIRC and from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 800924. N. Arang was supported by the National Science Foundation Graduate Research Fellowship Program (DGE-1650112). Verastem Oncology provided defactinib, VS-4718, and VS-6766.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1.
Fredriksson
R
,
Lagerström
MC
,
Lundin
LG
,
Schiöth
HB
. 
The G-protein-coupled receptors in the human genome form five main families. Phylogenetic analysis, paralogon groups, and fingerprints
.
Mol Pharmacol
2003
;
63
:
1256
72
.
2.
Schöneberg
T
,
Schulz
A
,
Biebermann
H
,
Hermsdorf
T
,
Römpler
H
,
Sangkuhl
K
. 
Mutant G-protein-coupled receptors as a cause of human diseases
.
Pharmacol Ther
2004
;
104
:
173
206
.
3.
Rosenbaum
DM
,
Rasmussen
SG
,
Kobilka
BK
. 
The structure and function of G-protein-coupled receptors
.
Nature
2009
;
459
:
356
63
.
4.
Simon
MI
,
Strathmann
MP
,
Gautam
N
. 
Diversity of G proteins in signal transduction
.
Science
1991
;
252
:
802
8
.
5.
Wu
V
,
Yeerna
H
,
Nohata
N
,
Chiou
J
,
Harismendy
O
,
Raimondi
F
, et al
Illuminating the Onco-GPCRome: novel G protein-coupled receptor-driven oncocrine networks and targets for cancer immunotherapy
.
J Biol Chem
2019
;
294
:
11062
86
.
6.
Van Raamsdonk
CD
,
Bezrookove
V
,
Green
G
,
Bauer
J
,
Gaugler
L
,
O'Brien
JM
, et al
Frequent somatic mutations of GNAQ in uveal melanoma and blue naevi
.
Nature
2009
;
457
:
599
602
.
7.
Van Raamsdonk
CD
,
Griewank
KG
,
Crosby
MB
,
Garrido
MC
,
Vemula
S
,
Wiesner
T
, et al
Mutations in GNA11 in uveal melanoma
.
N Engl J Med
2010
;
363
:
2191
9
.
8.
Moore
AR
,
Ceraudo
E
,
Sher
JJ
,
Guan
Y
,
Shoushtari
AN
,
Chang
MT
, et al
Recurrent activating mutations of G-protein-coupled receptor CYSLTR2 in uveal melanoma
.
Nat Genet
2016
;
48
:
675
80
.
9.
Aronow
ME
,
Topham
AK
,
Singh
AD
. 
Uveal melanoma: 5-year update on incidence, treatment, and survival (SEER 1973–2013)
.
Ocul Oncol Pathol
2018
;
4
:
145
51
.
10.
Carvajal
RD
,
Schwartz
GK
,
Tezel
T
,
Marr
B
,
Francis
JH
,
Nathan
PD
. 
Metastatic disease from uveal melanoma: treatment options and future prospects
.
Br J Ophthalmol
2017
;
101
:
38
44
.
11.
Shain
AH
,
Bagger
MM
,
Yu
R
,
Chang
D
,
Liu
S
,
Vemula
S
, et al
The genetic evolution of metastatic uveal melanoma
.
Nat Genet
2019
;
51
:
1123
30
.
12.
Afshar
AR
,
Damato
BE
,
Stewart
JM
,
Zablotska
LB
,
Roy
R
,
Olshen
AB
, et al
Next-generation sequencing of uveal melanoma for detection of genetic alterations predicting metastasis
.
Transl Vis Sci Technol
2019
;
8
:
18
.
13.
Komatsubara
KM
,
Carvajal
RD
. 
Immunotherapy for the treatment of uveal melanoma: current status and emerging therapies
.
Curr Oncol Rep
2017
;
19
:
45
.
14.
Chen
X
,
Wu
Q
,
Depeille
P
,
Chen
P
,
Thornton
S
,
Kalirai
H
, et al
RasGRP3 mediates MAPK pathway activation in GNAQ mutant uveal melanoma
.
Cancer Cell
2017
;
31
:
685
96
.
15.
Carvajal
RD
,
Sosman
JA
,
Quevedo
JF
,
Milhem
MM
,
Joshua
AM
,
Kudchadkar
RR
, et al
Effect of selumetinib vs chemotherapy on progression-free survival in uveal melanoma: a randomized clinical trial
.
JAMA
2014
;
311
:
2397
405
.
16.
Carvajal
RD
,
Piperno-Neumann
S
,
Kapiteijn
E
,
Chapman
PB
,
Frank
S
,
Joshua
AM
, et al
Selumetinib in combination with dacarbazine in patients with metastatic uveal melanoma: a phase III, multicenter, randomized trial (SUMIT)
.
J Clin Oncol
2018
;
36
:
1232
9
.
17.
Vaque
JP
,
Dorsam
RT
,
Feng
X
,
Iglesias-Bartolome
R
,
Forsthoefel
DJ
,
Chen
Q
, et al
A genome-wide RNAi screen reveals a Trio-regulated Rho GTPase circuitry transducing mitogenic signals initiated by G protein-coupled receptors
.
Mol Cell
2013
;
49
:
94
108
.
18.
Feng
X
,
Degese
MS
,
Iglesias-Bartolome
R
,
Vaque
JP
,
Molinolo
AA
,
Rodrigues
M
, et al
Hippo-independent activation of YAP by the GNAQ uveal melanoma oncogene through a trio-regulated rho GTPase signaling circuitry
.
Cancer Cell
2014
;
25
:
831
45
.
19.
Feng
X
,
Arang
N
,
Rigiracciolo
DC
,
Lee
JS
,
Yeerna
H
,
Wang
Z
, et al
A platform of synthetic lethal gene interaction networks reveals that the GNAQ uveal melanoma oncogene controls the hippo pathway through FAK
.
Cancer Cell
2019
;
35
:
457
72
.
20.
Sood
AK
,
Coffin
JE
,
Schneider
GB
,
Fletcher
MS
,
DeYoung
BR
,
Gruman
LM
, et al
Biological significance of focal adhesion kinase in ovarian cancer: role in migration and invasion
.
Am J Pathol
2004
;
165
:
1087
95
.
21.
Canel
M
,
Secades
P
,
Rodrigo
JP
,
Cabanillas
R
,
Herrero
A
,
Suarez
C
, et al
Overexpression of focal adhesion kinase in head and neck squamous cell carcinoma is independent of fak gene copy number
.
Clin Cancer Res
2006
;
12
:
3272
9
.
22.
Luo
M
,
Guan
JL
. 
Focal adhesion kinase: a prominent determinant in breast cancer initiation, progression and metastasis
.
Cancer Lett
2010
;
289
:
127
39
.
23.
Mohanty
A
,
Pharaon
RR
,
Nam
A
,
Salgia
S
,
Kulkarni
P
,
Massarelli
E
. 
FAK-targeted and combination therapies for the treatment of cancer: an overview of phase I and II clinical trials
.
Expert Opin Investig Drugs
2020
;
29
:
399
409
.
24.
Lee
JS
,
Das
A
,
Jerby-Arnon
L
,
Arafeh
R
,
Auslander
N
,
Davidson
M
, et al
Harnessing synthetic lethality to predict the response to cancer treatment
.
Nat Commun
2018
;
9
:
2546
.
25.
Schneider
CA
,
Rasband
WS
,
Eliceiri
KW
. 
NIH Image to ImageJ: 25 years of image analysis
.
Nat Methods
2012
;
9
:
671
5
.
26.
Madera
D
,
Vitale-Cross
L
,
Martin
D
,
Schneider
A
,
Molinolo
AA
,
Gangane
N
, et al
Prevention of tumor growth driven by PIK3CA and HPV oncogenes by targeting mTOR signaling with metformin in oral squamous carcinomas expressing OCT3
.
Cancer Prev Res
2015
;
8
:
197
207
.
27.
Bankhead
P
,
Loughrey
MB
,
Fernández
JA
,
Dombrowski
Y
,
McArt
DG
,
Dunne
PD
, et al
QuPath: open source software for digital pathology image analysis
.
Sci Rep
2017
;
7
:
16878
.
28.
Clement
K
,
Rees
H
,
Canver
MC
,
Gehrke
JM
,
Farouni
R
,
Hsu
JY
, et al
CRISPResso2 provides accurate and rapid genome editing sequence analysis
.
Nat Biotechnol
2019
;
37
:
224
6
.
29.
Sanson
KR
,
Hanna
RE
,
Hegde
M
,
Donovan
KF
,
Strand
C
,
Sullender
ME
, et al
Optimized libraries for CRISPR-Cas9 genetic screens with multiple modalities
.
Nat Commun
2018
;
9
:
5416
.
30.
Spahn
PN
,
Bath
T
,
Weiss
RJ
,
Kim
J
,
Esko
JD
,
Lewis
NE
, et al
PinAPL-Py: a comprehensive web-application for the analysis of CRISPR/Cas9 screens
.
Sci Rep
2017
;
7
:
15854
.
31.
Chou
TC
. 
Drug combination studies and their synergy quantification using the Chou-Talalay method
.
Cancer Res
2010
;
70
:
440
6
.
32.
Chou
TC
. 
Theoretical basis, experimental design, and computerized simulation of synergism and antagonism in drug combination studies
.
Pharmacol Rev
2006
;
58
:
621
81
.
33.
Wu-Zhang
AX
,
Newton
AC
. 
Protein kinase C pharmacology: refining the toolbox
.
Biochem J
2013
;
452
:
195
209
.
34.
Chen
X
,
Wu
Q
,
Tan
L
,
Porter
D
,
Jager
MJ
,
Emery
C
, et al
Combined PKC and MEK inhibition in uveal melanoma with GNAQ and GNA11 mutations
.
Oncogene
2014
;
33
:
4724
34
.
35.
Piperno-Neumann
S
,
Larkin
J
,
Carvajal
RD
,
Luke
JJ
,
Schwartz
GK
,
Hodi
FS
, et al
Genomic profiling of metastatic uveal melanoma and clinical results of a phase I study of the protein kinase C inhibitor AEB071
.
Mol Cancer Ther
2020
;
19
:
1031
9
.
36.
Li
J
,
Yuan
J
. 
Caspases in apoptosis and beyond
.
Oncogene
2008
;
27
:
6194
206
.
37.
Chaitanya
GV
,
Steven
AJ
,
Babu
PP.
. 
PARP-1 cleavage fragments: signatures of cell-death proteases in neurodegeneration
.
Cell Commun Signal
2010
;
8
:
31
.
38.
Fang
D
,
Nguyen
TK
,
Leishear
K
,
Finko
R
,
Kulp
AN
,
Hotz
S
, et al
A tumorigenic subpopulation with stem cell properties in melanomas
.
Cancer Res
2005
;
65
:
9328
37
.
39.
Fennell
DA
,
Baas
P
,
Taylor
P
,
Nowak
AK
,
Gilligan
D
,
Nakano
T
, et al
Maintenance defactinib versus placebo after first-line chemotherapy in patients with merlin-stratified pleural mesothelioma: COMMAND-A double-blind, randomized, phase II study
.
J Clin Oncol
2019
;
37
:
790
8
.
40.
Pérez-Guijarro
E
,
Yang
HH
,
Araya
RE
,
El Meskini
R
,
Michael
HT
,
Vodnala
SK
, et al
Multimodel preclinical platform predicts clinical response of melanoma to immunotherapy
.
Nat Med
2020
;
26
:
781
91
.
41.
Annala
S
,
Feng
X
,
Shridhar
N
,
Eryilmaz
F
,
Patt
J
,
Yang
J
, et al
Direct targeting of Galphaq and Galpha11 oncoproteins in cancer cells
.
Sci Signal
2019
;
12
:
eaau5948
.
42.
Drugs@FDA
. 
Trametinib (Mekinist) NDA 20114/0
.
Silver Spring
;
FDA
; 
2013
.
Available from
: https://www.accessdata.fda.gov/drugsatfda_docs/nda/2013/204114Orig1s000ClinPharmR.pdf.
43.
Croce
M
,
Ferrini
S
,
Pfeffer
U
,
Gangemi
R
. 
Targeted therapy of uveal melanoma: recent failures and new perspectives
.
Cancers
2019
;
11
:
846
.
44.
Welsh
SJ
,
Rizos
H
,
Scolyer
RA
,
Long
GV
. 
Resistance to combination BRAF and MEK inhibition in metastatic melanoma: Where to next?
Eur J Cancer
2016
;
62
:
76
85
.
45.
Roth
AD
,
Tejpar
S
,
Delorenzi
M
,
Yan
P
,
Fiocca
R
,
Klingbiel
D
, et al
Prognostic role of KRAS and BRAF in stage II and III resected colon cancer: results of the translational study on the PETACC-3, EORTC 40993, SAKK 60–00 trial
.
J Clin Oncol
2010
;
28
:
466
74
.
46.
Lauchle
JO
,
Kim
D
,
Le
DT
,
Akagi
K
,
Crone
M
,
Krisman
K
, et al
Response and resistance to MEK inhibition in leukaemias initiated by hyperactive Ras
.
Nature
2009
;
461
:
411
4
.
47.
Wagle
N
,
Van Allen
EM
,
Treacy
DJ
,
Frederick
DT
,
Cooper
ZA
,
Taylor-Weiner
A
, et al
MAP kinase pathway alterations in BRAF-mutant melanoma patients with acquired resistance to combined RAF/MEK inhibition
.
Cancer Discov
2014
;
4
:
61
8
.
48.
Faião-Flores
F
,
Emmons
MF
,
Durante
MA
,
Kinose
F
,
Saha
B
,
Fang
B
, et al
HDAC inhibition enhances the in vivo efficacy of MEK inhibitor therapy in uveal melanoma
.
Clin Cancer Res
2019
;
25
:
5686
701
.
49.
Shinde
R
,
Terbuch
A
,
Little
M
,
Caldwell
R
,
Kurup
R
,
Riisnaes
R
, et al
Phase I study of the combination of a RAF-MEK inhibitor CH5126766 and FAK inhibitor defactinib in an intermittent dosing schedule with expansions in KRAS mutant cancers
.
In
:
Proceedings of the Annual Meeting of the American Association for Cancer Research 2020
;
2020 Apr 27–28 and Jun 22–24
.
Philadelphia (PA)
:
AACR
; 
2020
.
Abstract nr CT143
.