Uveal Melanoma zebrafish xenograft models illustrate the mutation status-dependent effect of compound synergism or antagonism

Uveal Melanoma zebrafish xenograft models illustrate the mutation status-dependent effect of compound synergism or antagonism | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Uveal Melanoma zebrafish xenograft models illustrate the mutation status-dependent effect of compound synergism or antagonism Quincy van den Bosch, Emine Kilic, Erwin Brosens This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4292304/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose Uveal melanoma (UM) is the most common primary intraocular malignancy with a high probability of metastatic disease. Although excellent treatment option for primary UM are available, therapy for metastatic disease remain limited. Drug discovery studies using mouse models have thus far failed to provide therapeutic solutions, highlighting the need for novel models. Here, we optimize zebrafish xenografts as a potential model for drug discovery by showcasing the behavior of multiple cell lines and novel findings on mutation-dependent compound synergism/antagonism using Z-Tada; an algorithm to objectively characterize output measurements. Methods Prognostic relevant primary and metastatic UM cell lines or healthy melanocytes were inoculated at three distinct inoculation sites. Standardized quantifications independent of inoculation site were obtained using Z-Tada; an algorithm to measure tumor burden and the number, size and distance of disseminated tumor cells. Sequentially, we utilized this model to validate combinatorial synergism or antagonism seen in vitro. Results Detailed analysis of 691 zebrafish xenografts demonstrated perivitelline space inoculation provided robust data with high probability of cell dissemination. Cell lines with more invasive behavior ( SF3B1 mut and BAP1 mut ) behaved most aggressive in this model. Combinatorial drug treatment illustrated synergism or antagonism is mutation-dependent, which were confirmed in vivo . Combinatorial treatment differed per xenograft-model, as it either inhibited overall tumor burden or cell dissemination. Conclusion Perivitelline space inoculation provides robust zebrafish xenografts with the ability for high-throughput drug screening and robust data acquisition using Z-Tada. This model demonstrates that drug discovery for uveal melanoma must take mutational subclasses into account, especially in combinatorial treatment discoveries. Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Animal models play an important role in our understanding of cancer biology and drug discovery. Traditionally, mouse models dominate the realm of tumor-xenograft investigations[ 1 , 2 ], but since 2010, there has been a steep increase in the number of published zebrafish xenograft models[ 3 ]. Zebrafish have several advantages over mice, as they yield a large number of offspring and are relatively cheap to maintain and time efficient. Additionally, these methods are easy to manipulate; only a small number of tumor cells are needed to generate zebrafish xenografts, and they have the potential for high-throughput drug screening. These aspects have boosted their use in biomedical science and allow for large drug screenings in patient-derived xenografts in a short period of time, potentially improving personalized medicine[ 4 ]. Zebrafish larvae xenografts also allow tumor microenvironment assessments, as these models are not immunocompromised; however, the current knowledge on the interaction between tumor cells and their environment still has drawbacks that need to be improved to produce translatable results[ 5 ]. Zebrafish cancer avatars have been studied in multiple cancers, such as glioblastoma, breast cancer, hepatocellular carcinoma, prostate cancer, pediatric cancer and uveal melanoma[ 6 – 11 ]. Although a promising Bap1 - deficient mouse model was recently developed[ 12 ], mouse models have thus far failed to improve therapies for UM[ 13 ]. Therefore, we are particularly interested in BAP1 mut -based zebrafish xenograft models. To improve drug discoveries in UM research, we argue that zebrafish xenografts could serve as a first-line model before more expensive mammalian studies are carried out. UM is the most common intraocular malignancy, and it has a poor prognosis, as 50% of patients will develop metastasis within 5 years[ 14 ]. UM etiology is characterized by driver mutations involved in the MEK-ERK pathway, where activating mutations in guanine nucleotide-binding protein Q ( GNAQ ), guanine nucleotide-binding protein 11 ( GNA11 ), cysteinlyl leukotreine receptor 2 ( CYSLTR2 ), or phospholipase C beta 4 ( PLCB4 ) induce uncontrolled cell proliferation[ 14 ]. However, UM prognosis prediction relies on secondary mutations in eukaryotic translation initiation factor 1A X-linked (EIF1AX), splicing factor 3b subunit 1 ( SF3B1) or BRCA1-associated protein-1 (BAP1) . Furthermore, chromosomal aberrations also predict patient outcome, as loss of chromosome 3 and gain of 8q are associated with poor prognosis[ 15 ]. Secondary driver mutations are typically mutually exclusive and determine whether patients are at low risk ( EIF1AX mut ), intermediate risk ( SF3B1 mut ) or high risk ( BAP1 mut ) of metastatic disease[ 16 ]. BAP1 mut UMs are clinically the most relevant to study, yet despite the availability of several BAP1 mut cell lines, most mouse and zebrafish models have been generated with EIF1AX mut cells or UM cell lines with unknown driver/secondary mutations[ 13 ]. Microinjection of UM tumor cells in zebrafish to generate xenografts has been accomplished by multiple groups. Unfortunately, inoculation of UM cells in zebrafish larvae is not consistent between laboratories, as UM cell lines have been inoculated at the yolk sac[ 11 , 17 – 21 ], perivitelline space[ 22 , 23 ], intraocular space[ 24 ], or duct of Cuvier[ 25 , 26 ]. Moreover, analyses of zebrafish xenograft larvae are not always consistent. For example, tumor volume can be measured in different ways by multiplying the mean area by the total number of objects[ 21 ] or evaluating tumor size at 3 days post injection versus immediately after transplantation[ 22 ]. In contrast, others use a script in image analysis software to acquire quantifications[ 27 ] To improve UM zebrafish xenograft models, we investigated zebrafish xenografts in detail by using 7 cell lines with representative mutations and chromosomal aberrations found in UM patients. We evaluated the phenotypic behavior of 2 dermal melanocytic cell lines (one hTERT immortalized cell line and one primary melanocyte cell line) and 5 uveal melanoma cell lines, including 2 BAP1 mut primary cell lines and one BAP1 mut metastatic cell line. To our knowledge, previously generated zebrafish models did not utilize BAP1 mut cell lines[ 13 ]. To optimize this model, we evaluated 7 cell lines at 2 common inoculation sites and 1 novel inoculation site (retro-orbital) to identify the most efficient and useful site for obtaining the most robust data. Additionally, we developed publicly available analysis scripts to standardize quantification methods for both tumor volume and dissemination measurements that allow for phenotypic behavior of UM cells in vivo and to evaluate compound efficacy. 2. Methods 2.1 Cell culture conditions Five uveal melanoma cell lines, namely, 92.1 (established at the Leiden University Medical Center, Leiden, The Netherlands[ 28 ]), Mel202 (established at Schepens Eye Research Institute, Boston, USA[ 29 ], MP38, MP46, MM28 (established at Curie Institute, Paris, France[ 30 ]), immortalized dermal melanocytes CRL4059 and neonatal dermal melanocytes GM21808 (both obtained from American Type Culture Collection, Manassas, VA), were used for this study. The chromosomal aberrations and mutation status and Research Resource Identifiers of all the cell lines can be found in Supplementary Table 1. Uveal melanoma cell lines have been authenticated previously by single polymorphism analysis and AmpFLSTR™ Identifiler™ Plus PCR Amplification Kit (Thermo Fisher, Bleiswijk, The Netherlands) followed by sequencing. Additionally, we performed single nucleotide polymorphism analysis on CLR4059 and GM21808 with the Infinium™ Global Screening Array-24 v3.0 BeadChip according to the manufacturer’s protocols and guidelines (Illumina, San Diego, CA, USA) and analysis methods described previously[ 31 ]. (Supplementary Fig. 1). All uveal melanocytes were propagated in RPMI supplemented with 20% heat-inactivated fetal calf serum and 1% penicillin‒streptomycin; MP38 and MM28 media were supplemented with sodium pyruvate. Both dermal melanocyte strains were propagated in Medium 254 supplemented with human melanocyte growth supplements (Thermo Fisher Scientific, The Netherlands). All cell lines were incubated at 37°C in a humidified 5% CO 2 -enriched atmosphere and regularly checked for mycoplasma. 2.2 Drug screening of uveal melanoma cells Dabrafenib, ricolinostat, withaferin A and quisinostat (Selleckchem, Berlin, Germany) were stored in DMSO at a 10 mM stock concentration at -80°C. E7107 (gifted by H3 Biomedicine Inc., Cambridge, MA, USA) was diluted in DMSO at a 10 mM stock concentration and stored at -20°C. To determine the IC50 values, a total of 6000 cells (92.1, Mel202 and MP46) were seeded per well in a 96-well plate. The following day, the medium was removed, the cells were washed once with PBS, and subsequently, 100 µl of medium supplemented with the drug was added at various concentrations (ranging from 50 µM to 1 µM for dabrafenib, ricolinostat and withaferin A or 500 nM to 1 nM for quisinostat and E7107). Identification of synergistic effects was performed after identifying the IC50 of each compound. A 6x6 matrix was used to treat cells at different concentrations based on the IC50 values. After 3 days, the medium was removed, the cells were washed once with PBS and fixed in ice-cold methanol. After fixation, the cells were stained with 0.1% crystal violet for 30 minutes, washed with water and air-dried. Finally, crystal violet was solubilized in methanol, and the absorption was measured at 545 nm. Samples were treated in triplicate and analyzed in GraphPad Prism V9 using nonlinear regression. The data are presented as the means ± SD. Combinatorial treatments were analyzed for synergistic, noninteractive and antagonistic effects using SynergyFinder[ 32 ]. A synergy score less than − 10 was considered antagonistic, a score between − 10 and 10 was considered additive, and a score greater than 10 was considered synergistic. 2.3 Zebrafish husbandry and xenograft injections Wild-type AB zebrafish were maintained under standard conditions with a 14 hr light/10 hr dark cycle. In this study, only larval zebrafish (no older than 120 hours post fertilization) were used. The animal experiments were approved by the Animal Experimentation Committee at Erasmus MC, Rotterdam. Zebrafish embryos were raised in E3 medium supplemented with 0.003% phenylthiourea (PTU) in a Petri dish at 28°C. At 24 hours post fertilization, the medium was refreshed following the dechlorination of the larvae. At 48 hours post fertilization, the zebrafish larvae were anesthetized with 0.016% tricane and used for injections. A total of 2.5x10 6 cells were harvested and stained with 2.5 µM CellTracker CM-Dil dye for 5 minutes at 37°C and subsequently for an additional 15 minutes at 4°C. After staining, CM-Dil dye was removed by centrifugation. The cells were then washed with PBS and resuspended in 2% PVP-40/PBS. A total of ~ 200–300 cells were injected into the yolk, perivitelline space or retro-orbitally. For the retro-orbital injection, every larva was injected into the left eye. Correctly injected larvae were selected 1 hour post injection under a fluorescence stereomicroscope, placed in E3 medium supplemented with PTU and raised at 34°C. At 3 days post injection, xenograft larvae were anesthetized and embedded in 1% low-melting agarose for live-cell imaging. 2.4 Confocal microscopy of zebrafish xenografts Zebrafish xenograft larvae were imaged using a Leica SP5 (Leica Microsystems, Mannheim, Germany) under standard conditions (561 nm, 35% laser power with additional bright field image). Tile scans of 3 images were generated to obtain full-body length images for analysis. The number of disseminated cells, the distance of dissemination and the total tumor volume were calculated in FIJI with an in-house script (details can be found in the Results section and Supplementary Methods). The obtained values were then processed in GraphPad Prism V9. Comparisons of the number of detected spots, distance of dissemination and tumor volume between the different cell lines were statistically tested using ANOVA with Dunnett’s multiple comparison method. The data are presented as the means ± SD. 2.5 Drug screening in zebrafish xenografts For zebrafish toxicity assays, the same range of concentrations used in vitro was used to treat the zebrafish larvae from 2 days post fertilization until 5 days post fertilization. A total of 8–12 larvae per well were sorted in a 12-well plate with E3 medium supplemented with 0.003% phenylthiourea containing DMSO, ricolinostat, withaferin A, quisinostat or E7107 at different concentrations. The medium was refreshed daily. At 1, 2 and 3 days post treatment, larvae were inspected and registered; for each drug, this experiment was performed twice using two different wild-type AB parental zebrafish. The synergistic/antagonistic concentrations used per cell line were determined based on in vitro data where less than 20% of viable cells remained after single-compound inhibition. Drug treatment started at 3 hours post injection, and the media containing the compounds were refreshed daily. At 3 days post injection (dpi), the zebrafish xenografts were imaged and analyzed in the same fashion as described earlier. Zebrafish-xenografts were statistically tested by comparing DMSO to Drug A, Drug B or the combination of both drugs using Welch’s t test. The data are presented as the means ± SD. 3. Results 3.1 Different phenotypes of cell behavior based on inoculation site Gaining insights into the optimal inoculation site could differ depending on the research question or behavior of cells in vivo . Therefore, we used 1 metastatic UM cell line, 5 primary UM cell lines and 2 dermal melanocyte lines to determine the optimal inoculation site. The images shown in Fig. 1 depict zebrafish larvae with 92.1 cells inoculated at different sites and serve as a representative example of zebrafish larvae inoculated with other cell lines. Zebrafish larvae were sorted at 1 hour post injection (1 hpi) for correctly injected cells; e.g. larvae that had cells in the brain, intraocular space or bloodstream were removed. At 3 days post injection (3 dpi), we assessed cell behavior and found vastly different phenotypes. All cell lines grew and disseminated after retro-orbital (RO) and perivitelline space (PS) injections (Fig. 1 A, 1 B). The most commonly used inoculation site, the yolk sac, demonstrated an inconsistent phenotype. The injected cells predominantly stayed within the yolk (Fig. 1 C, 1 E), while a small number of larvae showed disseminated cells throughout the body (Fig. 1 D, 1 E), which phenotypically resembled what was observed in PS injections. 3.2 Z-Tada: Z ebrafish Xenograft T umor Volume a nd D issemination A nalysis To quantify the tumor volume, number of disseminated cells and distance of disseminated cells from the inoculation site, we developed Z-Tada, a system in which 2 scripts are used to analyze the tumor volume, dissemination distance, number of disseminated cells and size of disseminated cell clusters in a uniform manner independent of the inoculation site. By making confocal stack images, a simple yet robust method to measure tumor volume is by using the 3D counter plugin in FIJI. The first script is therefore quite simple because it splits the channels, removes the brightfield image, rotates the figure and runs the 3D counter plugin to obtain the tumor volume in cubic microns (Supplementary methods and Supplementary Fig. 2). This plugin identified spots and measured them in 3D; this allows 3D measurements of disseminated cells per identified object (in voxels) or total tumor volume by subsequently adding all objects together. The second script quantifies the number of disseminated cells and their migration distance using a single script. This script splits the channels, removes the brightfield image, rotates the figure and makes a maximum Z-stack projection. The Z-stack projection is then subjected to thresholding and multiplied by a mask to reduce the background and obtain a binary figure. The user is then asked to hover over the image to identify the X and Y coordinates of the injection site, which can subsequently be entered manually in the pop-up screens. Next, disseminated cells were identified with the Find Maxima function and analyzed with the Analyze Particles function (Supplementary Fig. 2, settings have a maximum particle size limitation to prevent measurement of the inoculation site, which is typically a large spot). For each spot, the X and Y coordinates are obtained and used to calculate a straight-line distance between the detected spot and reference point using the Pythagorean theorem (Supplementary methods and Supplementary Fig. 1). For example, a 92.1-xenograft inoculated retro-orbitally (Fig. 2 A) or in the perivitelline space (Fig. 2 B) illustrates the accuracy of this script independent of the inoculation site using an X-Y plot. Tumor volume analysis revealed vastly different behaviors based on the inoculation site (Fig. 2 C-E). In general, yolk sac inoculation yielded the greatest tumor volume at 3 dpi (Supplementary Fig. 3A-G), with MP38, hTERT-melanocytes and neonatal melanocytes demonstrating the greatest tumor volume (Fig. 2 C). Retro-orbital inoculation yielded the lowest tumor volume of all inoculation sites (Supplementary Fig. 3A-G). MP38 yielded the lowest tumor volume, which was comparable to that of MP46 and Mel202, while 92.1, hTERT-melanocytes and neonatal melanocytes harbored the greatest tumor volumes at 3 dpi (Fig. 2 D). Perivitelline space inoculation resulted in intermediate tumor volumes between inoculation sites but was highly consistent between cell lines, whereas yolk sac inoculation was more dependent on the cell line (Supplementary Fig. 3A-G). Cell line 92.1 thrived in perivitelline inoculations with the highest tumor volume, while Mel202 harbored the lowest tumor volume in perivitelline space injections. All other cell lines yielded similar tumor volumes (Fig. 2 E). Additionally, the size of the detected objects was inspected to investigate whether there were size differences per cell line in perivitelline space-inoculated larvae. An arbitrary threshold of > 200 voxels was used to count the number of disseminated cell clusters that could be considered to be more than 1 cell. In the 92.1 cell line, hTERT-melanocyte and neonatal melanocyte-xenografts yielded a low number of disseminated cells > 200 voxels, while Mel202, MP46, MP38 and MM28 had a greater abundance of large disseminated cell objects (Fig. 2 F). Retro-orbital and perivitelline space inoculation consistently promoted cell dissemination in all the cell lines. The average dissemination distance per larva was similar between cell lines after retro-orbital injection, where MP38, MM28 and neonatal melanocytes tended to disseminate the furthest (Fig. 2 G). The cell dissemination distance after perivitelline space inoculation was highly consistent between the cell lines, with only 92.1 indicating a slightly greater distance (Fig. 2 I). The number of spots was significantly greater in the perivitelline space injection group than in the retro-orbital inoculation group (Supplementary Fig. 3H). Mel202-xenografts had the greatest number of spots in both models, while 92.1 had a slight increase in the perivitelline space model compared to the other cell lines used (Fig. 2 H, 3 J). Due to the consistent tumor volume, high number of disseminated cells, differences in disseminated cell sizes and largest dissemination distance in perivitelline space inoculations, we argue that this site is the most useful site for use in uveal melanoma zebrafish–larva xenograft systems. 3.3 Drug synergism differs among UM subtypes To evaluate the robustness and abilities of zebrafish xenografts as a drug discovery model, we screened compounds previously tested in mouse or zebrafish xenografts. A total of 4 compounds were evaluated: quisinostat, ricolinostat (both tested in zebrafish xenografts[ 23 , 25 ]), withaferin A (tested in mice[ 33 ]) and E7101 (a novel compound). Unlike in previous studies, in this study, compound screening was performed on the EIF1AX mut , SF3B1 mut and BAP1 neg UM cell lines. All the compounds inhibited UM cell lines in vitro (Fig. 3 A-D). As UM typically shares activation of the MEK-ERK pathway due to driver mutations in GNAQ, GNA11, PLCB4 or CYSLTR2 [ 14 ] but differs in prognosis based on secondary mutations[ 16 ], we hypothesize that combinatorial inhibition could improve the inhibitory response dependent on UM subtype. To evaluate this hypothesis, we combined each compound with each other to identify synergistic or antagonistic effects. Surprisingly, we detected synergistic effects of the histone deacetylase inhibitors quisinostat and ricolinostat on EIF1AX mut cells, while this combination had antagonistic effects on BAP1 mut cells (Table 1 , Fig. 3 E, 3 H). On the other hand, we found strong synergistic effects of the combination of the MAPK/PI3K-AKT inhibitor withaferin A and the spliceosome inhibitor E7107 in Mel202 cells (Table 1 , Fig. 3 F). Despite all the compounds being able to inhibit UM cells regardless of secondary mutation status (Fig. 3 A-C), synergism during combinatorial inhibition highly differed among UM subtypes (Table 1 ). Table 1 Synergy scores based on SynergyFinder 92.1 Drug A Drug B ZIP Loewe H SA Bliss E7107 Quisinostat -5,03 -0,41 2,89 -5,43 E7107 Ricolinostat -7,42 -1,29 2,68 -7,45 Ricolinostat Quisinostat 21,96 -3,23 7,09 24,01 Withaferin A E7107 2,03 3,01 7,91 1,97 Withaferin A Quisinostat 1,47 -2,33 5,25 2,21 Withaferin A Ricolinostat 6,38 3,28 12,4 6,92 Mel202 Drug A Drug B ZIP Loewe H SA Bliss E7107 Quisinostat -4,71 9,02 11 -4,35 E7107 Ricolinostat 1,34 -4,15 -5,21 -3,46 Ricolinostat Quisinostat -1,6 -2,43 0,4 -2,5 Withaferin A E7107 13,39 11,95 15,05 16,26 Withaferin A Quisinostat -8,33 4,05 3,12 -8,97 Withaferin A Ricolinostat 4,76 17,04 18,36 4,43 MP46 Drug A Drug B ZIP Loewe H SA Bliss E7107 Quisinostat -1,33 5,39 7,57 -2,38 E7107 Ricolinostat 6,69 -8,35 -9 3,5 Ricolinostat Quisinostat -10,73 4,38 3,02 -11,65 Withaferin A E7107 -1,52 -3,85 2,67 -2,4 Withaferin A Quisinostat -10 2,74 0,02 -8,23 Withaferin A Ricolinostat 9,58 -0,01 -3,85 2,98 Table 1 : A total of 4 tools are used in SynergFinder: ZIP, Loewe, HSA and Bliss. For each combination, the score is given and divided between 92.1, Mel202 and MP46. Synergism or antagonism is highlighted in bold. 3.4 In vivo evaluation of synergistic treatment therapies To evaluate the synergistic effect of compounds, we first investigated the toxicity tolerance of single compounds in zebrafish larvae (Supplementary Fig. 4). None of the compounds exhibited toxicity in wild-type zebrafish larvae, even at the highest concentration tested in vitro. Therefore, we were able to utilize compounds at concentrations at which the in vitro survival of UM cells was < 20% without toxic effects in zebrafish xenografts. Interestingly, compared with DMSO, ricolinostat, quisinostat or combined treatment of 92.1-xenografts did not decrease the overall tumor burden (Fig. 4 A). However, all the compounds inhibited the migration and number of disseminated cells, and dual treatment had the strongest inhibitory effect (Fig. 4 B, C). Treatment of Mel202-xenografts with E7107, withaferin A or their combination significantly inhibited the overall tumor burden in dual-treated xenografts (Fig. 4 D), supporting our synergistic in vitro findings. However, these compounds were unable to inhibit cell dissemination (Fig. 4 E, F). Finally, the overall tumor burden of MP46-xenografts was lower in quisinostat-treated xenografts than in ricolinostat-treated or DMSO-treated xenografts. Notably, combined treatment prevented the inhibitory effect of quisinostat, as these xenografts harbored similar tumor burdens as those of the DMSO controls (Fig. 4 G), supporting our antagonistic in vitro findings. Additionally, neither quisinostat, ricolinostat nor the combination treatment reduced cell dissemination in MP46-xenografts (Fig. 4 H, I). 4. Discussion UM remains a devastating disease with a high propensity for metastasis and limited therapeutic options. To discover novel therapeutics, we optimized our xenograft zebrafish model, developed a robust algorithm to consistently determine model output measures and carried out a detailed analysis of zebrafish xenografts using multiple cell lines, which, to our knowledge, has not been previously investigated in this model. Previous UM-zebrafish xenografts typically utilized cell lines without known secondary mutations (OMM1[ 11 ], OMM2.3[ 11 , 18 , 22 , 23 ], Mel270[ 11 ], and Mel285[ 22 ]) or patient-derived spheroids (spUM-LB008[ 26 ] and spXmm66[ 25 ]). Here, we describe the novel cellular behavior of established cell lines with known secondary mutations in all three clinically relevant molecular subclasses ( EIF1AX , SF3B1 and BAP1 ) in both primary and metastasis-derived cell lines. Notably, all established cell lines were derived from patients who eventually developed metastatic disease, including the 92.1 cell line, which harbors an EIF1AX mutation. Due to the variety of inoculation sites in zebrafish xenografts, we first evaluated which inoculation site would provide robust data that would allow investigation of the cellular behavior and effectiveness of therapeutic compounds. By generating 691 xenografts with primary and metastatic UM cell lines via retro-orbital, perivitelline space or yolk-sac injections, this study revealed that the perivitelline space is the most robust site for UM zebrafish xenografts. The quantification of zebrafish xenografts has varied across laboratories, for which we have developed Z-Tada. This provides a method for standardized analysis of the tumor volume and cell dissemination of zebrafish xenograft larvae, which accurately detects tumor cells and provides migration distances. Although yolk sac inoculation typically yielded the highest tumor burden (Supplementary Fig. 3), this site lacked robust cell dissemination (Fig. 1 ). Retro-orbital inoculation provided robust cell dissemination, yet the number of disseminated cells and overall tumor burden were significantly lower than perivitelline space inoculation (Supplementary Fig. 3). Interestingly, cell lines behave differently depending on the molecular subclass. The cell line 92.1 (primary EIF1AX mut ) typically yielded a high tumor burden, but the size of the disseminated cell clusters was relatively small, whereas MP38 (primary BAP1 mut ) and MM28 (metastatic BAP1 mut ) developed more disseminated cell clusters with a large size (Fig. 2 ). Although this model provides robust data on tumor volume and cell dissemination, healthy and hTERT-immortalized melanocytes were also able to proliferate and disseminate, suggesting that this model is highly prone to cell dissemination regardless of cell type. Nonetheless, molecular subclasses with a greater probability of developing metastatic disease ( SF3B1 mut and BAP1 mut ) behave more aggressively in this model. To evaluate whether this model system can reliably be used for novel drug screening for UM, we investigated previously used compounds that were shown to effectively inhibit tumor growth or cell dissemination in UM cells. A potential therapeutic option for high-risk UM is histone deacetylase (HDAC) inhibitors, which are able to differentiate UM into a more melanocyte-like state[ 34 ]. In mice, the histone deacetylase inhibitors inhibitor quisinostat (targeting HDAC3, 5, 8 and 9) was shown to selectively inhibit BAP1 mut xenografts (MP46 and MM28)[ 35 ]. However, in zebrafish xenografts, quisinostat was also found to effectively inhibit the dissemination of metastatic cell lines (OMM2.3) or spheroids (spXmm66) that do not harbor BAP1 mutations[ 11 , 25 ]. In this study, we confirmed inhibition of overall tumor burden in quisinostat-treated BAP1 mut zebrafish xenografts (MP46). However, quisinostat was also able to inhibit the cell dissemination of 92.1 cells ( EIF1AX mut ) but failed to reduce the overall tumor burden (Fig. 4 ); suggesting quisinostat effectivity is dependent on molecular subclass. Another HDAC inhibitor, ricolinostat (targeting HDAC6), was previously shown to inhibit tumor burden in zebrafish xenografts using the metastatic UM cell line OMM2.3[ 23 ]. Here, we showed that ricolinostat was also able to inhibit other types of UM cells in vitro (Fig. 3 ) but was effective only in 92.1-based xenografts. Ricolinostat was not effective against BAP1 mut -cells (MP46) in vivo. Interestingly, combining HDAC inhibitors was shown to be either synergistic (92.1) or antagonistic (MP46) based on the molecular subclass (Fig. 3 , Table 1 ). Our zebrafish xenografts demonstrated that the synergistic effects of quisinostat and ricolinostat on 92.1 cells strongly inhibited cell dissemination but did not affect overall tumor burden. However, its antagonistic effect seen in vitro was also reproduced in MP46-xenografts, as the inhibitory effect of quisinostat was lost in the combination-treated xenografts (Fig. 4 ). Targeting HDACs is a promising therapy for many cancers and has been combined with several compounds that target other pathways[ 36 ]; however, combining multiple HDACs is not a strategy that has been studied in detail before. Our study suggests combining multiple HDAC inhibitors can be mutation-dependent; and should be investigated pre-clinically in detail to validate efficacy. In addition to HDAC inhibitors, we evaluated withaferin A, a compound tested only in mice. Withaferin A is able to inhibit the MET and MEK1/2 pathways, making this an interesting compound for UM because it acts on the primary driver pathways[ 33 ]. In vitro , withaferin A inhibited the growth of all the tested cell lines. However, withaferin A in combination with the spliceosome inhibitor E7107 had synergistic effects on Mel202 cells, yet failed to illustrate synergistic effects on other cell lines tested (Fig. 3 , Table 1 ). The synergistic effect was reproduced in Mel202-xenografts, suggesting that this combination could provide novel therapeutic options for SF3B1 mut UM patients (Fig. 4 ). Zebrafish xenografts hold potential as a drug screening platform for UM, where synergism and antagonism can be studied in detail. However, this study only treated xenografts for a total of 3 days, which could be too short to see a more defined inhibitory effect. Other important elements in this platform that could affect drug efficiency are the number of fish treated per well and the efficiency of compound uptake by zebrafish larvae. However, an important advantage of this model is functional liver metabolism in zebrafish larvae[ 37 ], which can metabolize compounds and therefore alter their effects. Nonetheless, this platform illustrates that molecular subclasses of UM are important parameters for discovering novel therapeutic compounds. In summary, this study illustrates that optimal inoculation of uveal melanoma cells in the perivitelline space allows for robust tumor burden and cell dissemination analysis in a short time span of 3 days. Using Z-Tada, this model is able to identify differences in cellular behavior depending on genetic background in a standardized fashion. Furthermore, this methodology allows standardized read-out parameters for high-throughput screening of novel compounds and can identify synergistic or antagonistic effects. Using this model, we provide evidence that clinically prognostic subclasses of UM are key to developing effective therapies. Synergistic compound screenings for UM should take this into account, as the same combination can be synergistic in low-risk UM but antagonistic in high-risk UM. Abbreviations UM Uveal melanoma (UM) GNAQ Guanine nucleotide-binding protein Q (GNAQ) GNA11 Guanine nucleotide-binding protein 11 (GNA11) CYSLTR2 Cysteinlyl leukotreine receptor 2 (CYSLTR2) PLCB4 Phospholipase C Beta 4 (PLCB4) EIF1AX Eukaryotic Translation Initiation Factor 1A X-Linked (EIF1AX) SF3B1 Splicing factor 3b subunit 1 (SF3B1) BAP1 BRCA1-associated protein-1 (BAP1) EIF1AX mut EIF1AX-mutated SF3B1 mut SF3B1-mutated BAP1 mut BAP1-mutated hTERT human telomerase reverse transcriptase µM Micromolar nM Nanomolar mM Millimolar PTU Phenylthiourea Dpi days post injection Hpi hour post injection RO retro-orbital PS perivitelline space 3D Three-dimensional Declarations Ethics approval and consent to participate In this study, only larval zebrafish (no older than 120 hours post fertilization) were used. The animal experiments were approved by the Animal Experimentation Committee at Erasmus MC, Rotterdam. Competing interests The authors declare that they have no competing interests. Funding This study was supported by “Rotterdamse Stichting Blindenbelangen” and “Stichting voor Ooglijders”. Authors’ contributions Q.B. and E.B. contributed to the conceptualization, experimental design and interpretation of the data. Q.B. performed the data acquisition, script development and initial analysis. Q.B. drafted the manuscript, followed by reviewing and editing by Q.B. E.B. and E.K. Funding was acquired by E.B. and E.K. Supervision was carried out by E.B. and E.K. Acknowledgments We thank Thomas Huizer, BSc and Nikki Könemann, BSc for their contributions to the data acquisition and technical support. References J.H. Nadeau, J. Auwerx, The virtuous cycle of human genetics and mouse models in drug discovery. Nat. Rev. Drug Discovery. 18 (4), 255–272 (2019) C.R. Ireson et al., The role of mouse tumour models in the discovery and development of anticancer drugs. Br. J. Cancer. 121 (2), 101–108 (2019) A. Groenewoud et al., XePhIR: the zebrafish xenograft phenotype interactive repository. Database, 2022. 2022 M. Fazio et al., Zebrafish patient avatars in cancer biology and precision cancer therapy. Nat. Rev. Cancer. 20 (5), 263–273 (2020) P. Cabezas-Sáinz et al., Modeling Cancer Using Zebrafish Xenografts: Drawbacks for Mimicking the Human Microenvironment. Cells, 2020. 9 (9) A. Pliakopanou et al., Glioblastoma research on zebrafish xenograft models: a systematic review (Clin Transl Oncol, 2023) A. Wawruszak, E. Okoń, K. Dudziak, Advancements in Zebrafish Models for Breast Cancer Research: Unveiling Biomarkers, Targeted Therapies, and Personalized Medicine. Med. Sci. Monit. 29 , e940550 (2023) S. Targen, O. Konu, Zebrafish Xenotransplantation Models for Studying Gene Function and Drug Treatment in Hepatocellular Carcinoma. J. Gastrointest. Cancer. 52 (4), 1248–1265 (2021) H. Amawi et al., The use of zebrafish model in prostate cancer therapeutic development and discovery. Cancer Chemother. Pharmacol. 87 (3), 311–325 (2021) M.J. Casey, R.A. Stewart, Pediatric Cancer Models in Zebrafish. Trends Cancer. 6 (5), 407–418 (2020) van der W. Ent et al., Modeling of Human Uveal Melanoma in Zebrafish Xenograft Embryos. Investig. Ophthalmol. Vis. Sci. 55 (10), 6612–6622 (2014) F. Roula et al., BAP1 deficient human and mouse uveal melanomas up-regulate a shared EMT pathway. bioRxiv, 2023: p. 2023.05.24.542173 van den Q.C.C. Bosch et al., Uveal melanoma modeling in mice and zebrafish. Biochimica et Biophysica Acta (BBA) - Reviews on Cancer, 2024. 1879 (1): p. 189055 M.J. Jager et al., Uveal melanoma. Nat. Reviews Disease Primers. 6 (1), 24 (2020) van den T. Bosch et al., Higher Percentage of FISH-Determined Monosomy 3 and 8q Amplification in Uveal Melanoma Cells relate to Poor Patient Prognosis , vol. 53 (Investigative Ophthalmology & Visual Science, 2012), pp. 2668–2674. 6 S. Yavuzyigitoglu et al., Uveal Melanomas with SF3B1 Mutations: A Distinct Subclass Associated with Late-Onset Metastases. Ophthalmology. 123 (5), 1118–1128 (2016) G. Fornabaio et al., Angiotropism and extravascular migratory metastasis in cutaneous and uveal melanoma progression in a zebrafish model. Sci. Rep. 8 (1), 10448 (2018) van der W. Ent et al., Embryonic Zebrafish: Different Phenotypes after Injection of Human Uveal Melanoma Cells. Ocul Oncol. Pathol. 1 (3), 170–181 (2015) Y. Ding et al., Dose-Dependent Carbon-Dot-Induced ROS Promote Uveal Melanoma Cell Tumorigenicity via Activation of mTOR Signaling and Glutamine Metabolism. Adv. Sci. (Weinh). 8 (8), 2002404 (2021) L. Yu et al., Co-occurrence of BAP1 and SF3B1 mutations in uveal melanoma induces cellular senescence. Mol. Oncol. 16 (3), 607–629 (2022) Y. Li et al., Copper ionophore elesclomol selectively targets GNAQ/11-mutant uveal melanoma. Oncogene. 41 (27), 3539–3553 (2022) K. Slater et al., High Cysteinyl Leukotriene Receptor 1 Expression Correlates with Poor Survival of Uveal Melanoma Patients and Cognate Antagonist Drugs Modulate the Growth, Cancer Secretome, and Metabolism of Uveal Melanoma Cells. Cancers (Basel), 2020. 12 (10) H. Sundaramurthi et al., Uveal Melanoma Cell Line Proliferation Is Inhibited by Ricolinostat, a Histone Deacetylase Inhibitor. Cancers (Basel), 2022. 14 (3) C. Tobia et al., An Orthotopic Model of Uveal Melanoma in Zebrafish Embryo: A Novel Platform for Drug Evaluation. Biomedicines, 2021. 9 (12) A. Groenewoud et al., Patient-derived zebrafish xenografts of uveal melanoma reveal ferroptosis as a drug target. Cell. Death Discov. 9 (1), 183 (2023) J. Yin et al., Zebrafish Patient-Derived Xenograft Model as a Preclinical Platform for Uveal Melanoma Drug Discovery. Pharmaceuticals (Basel), 2023. 16 (4) A. Au - Groenewoud, J. Au -, Yin, and B.E. Au - Snaar-Jagalska, Ortho- and Ectopic Zebrafish Xeno-Engraftment of Ocular Melanoma to Recapitulate Primary Tumor and Experimental Metastasis Development . JoVE, 2021 (175): p. e62356 De I. Waard-Siebinga et al., Establishment and characterization of an uveal-melanoma cell line. Int. J. Cancer. 62 (2), 155–161 (1995) D.J. Verbik et al., Melanomas that develop within the eye inhibit lymphocyte proliferation. Int. J. Cancer. 73 (4), 470–478 (1997) N. Amirouchene-Angelozzi et al., Establishment of novel cell lines recapitulating the genetic landscape of uveal melanoma and preclinical validation of mTOR as a therapeutic target. Mol. Oncol. 8 (8), 1508–1520 (2014) L.E. Kuil et al., Size matters: Large copy number losses in Hirschsprung disease patients reveal genes involved in enteric nervous system development. PLoS Genet. 17 (8), e1009698 (2021) S. Zheng et al., SynergyFinder Plus: Toward Better Interpretation and Annotation of Drug Combination Screening Datasets. Genomics Proteom. Bioinf. 20 (3), 587–596 (2022) A.K. Samadi et al., Natural withanolide withaferin A induces apoptosis in uveal melanoma cells by suppression of Akt and c-MET activation. Tumour Biol. 33 (4), 1179–1189 (2012) S. Landreville et al., Histone deacetylase inhibitors induce growth arrest and differentiation in uveal melanoma. Clin. Cancer Res. 18 (2), 408–416 (2012) J.N. Kuznetsoff et al., Dual Screen for Efficacy and Toxicity Identifies HDAC Inhibitor with Distinctive Activity Spectrum for BAP1-Mutant Uveal Melanoma. Mol. Cancer Res. 19 (2), 215–222 (2021) T. Liang et al., Targeting histone deacetylases for cancer therapy: Trends and challenges. Acta Pharm. Sinica B 13 (6), 2425–2463 (2023) W. Goessling, K.C. Sadler, Zebrafish: an important tool for liver disease research. Gastroenterology. 149 (6), 1361–1377 (2015) Additional Declarations No competing interests reported. Supplementary Files SupplementaryMoleculardependentdrugsynergisminUMV1.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4292304","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":293817838,"identity":"a881eb84-a43b-46e1-ad90-fcb5312257b5","order_by":0,"name":"Quincy van den Bosch","email":"","orcid":"","institution":"Erasmus MC","correspondingAuthor":false,"prefix":"","firstName":"Quincy","middleName":"van den","lastName":"Bosch","suffix":""},{"id":293817839,"identity":"ebbe2b0e-7b1d-47d9-90c0-7814ae8f9d0d","order_by":1,"name":"Emine Kilic","email":"","orcid":"","institution":"Erasmus MC","correspondingAuthor":false,"prefix":"","firstName":"Emine","middleName":"","lastName":"Kilic","suffix":""},{"id":293817840,"identity":"3a9281c0-7a75-4b49-a1d4-295810ead6ae","order_by":2,"name":"Erwin Brosens","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIie3PIQsCMRjG8R0DLTutiohfYXBV9Kv4MrgkIliMS2eyisOwr3DJfDAwCVbhLcpVw4HFMFAPDAadFw37l7088AsjxOf7y9jrrcv3dVqFsOx95VVIa1SRNEm4Kwrbn/RUvitudgt6ZU506iBt2RBKJfGMYyzUMkFIMeZ07SA8YxENpYG0M45IKLE8CGUOMiwJs3fQ6nANrEXQmx+Ek5LUMpBHRp8HgsQfpGUaIlCJgHQfR7SbYFT+xbhIc7E0pLAD0AuTBxeLXb0R55zNvxNCP42ZA/h8Pp+vQg9k6E7Ns+2F0QAAAABJRU5ErkJggg==","orcid":"","institution":"Erasmus MC","correspondingAuthor":true,"prefix":"","firstName":"Erwin","middleName":"","lastName":"Brosens","suffix":""}],"badges":[],"createdAt":"2024-04-19 09:44:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4292304/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4292304/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":55234335,"identity":"a172ce81-b257-492e-a864-ce8dff7e9091","added_by":"auto","created_at":"2024-04-24 13:23:53","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2898703,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eDifferent inoculation sites in zebrafish UM xenografts.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA) Zebrafish xenograft injected behind the eye (retro-orbital) with 92.1 cells at 3 dpi. B) Zebrafish xenograft injected in the perivitelline space with 92.1 cells at 3 dpi. C) Zebrafish xenograft injected in the yolk sac with 92.1 cells that did not show cell dissemination at 3 dpi. D) Zebrafish xenograft injected in yolks-sac with 92.1 cells showing cell dissemination at 3 dpi. E) Amount of dissemination present in xenografts injected in the yolk with 92.1 (n=42), Mel202 (n=31), MP46 (n=40), MP38 (n=34), MM28 (n=28), hTERT-melanocytes (CRL-4059, n=26) and neonatal melanocytes (GM21807, n=35).\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4292304/v1/1482c965e0d3816221bd490c.jpeg"},{"id":55234940,"identity":"27db7244-4984-4fc9-8df1-44802c3eddca","added_by":"auto","created_at":"2024-04-24 13:31:53","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3697351,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eQuantification of UM zebrafish xenografts.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA) Max projected Z-stack of retro-orbital injected zebrafish xenograft at 3 dpi with cells in white followed by an X-Y plot overlaying the corresponding bright field image. B) Max-projected Z-stack of perivitelline space-injected zebrafish xenograft at 3 dpi with cells in white followed by an X-Y plot overlaying the corresponding bright field image. C, D, E) Overview of tumor volume analysis per cell line in the yolk sac (92.1 n=42, Mel202 n=31, MP46 n=40, MP38 n=34, MM28 n=28, hTERT-melanocytes n=26, GM21807 n=35), retro-orbital region (92.1 n=30, Mel202 n=30, MP46 n=38, MP38 n=28, MM28 n=33, hTERT-melanocytes n=32, GM21807 n=31) or perivitelline space injections. (92.1, n=35, Mel202 n=31, MP46 n=33, MP38 n=31, MM28 n=33, hTERT-melanocytes n=38, GM21807 n=33). F) Number of detected objects larger than 200 voxels in perivitelline space-inoculated zebrafish xenografts. G) Cell dissemination distance per cell line in retro-orbital inoculated zebrafish larvae at 3 dpi. H) Number of disseminated cells detected per cell line in retro-orbital inoculated zebrafish larvae at 3 dpi. I) Cell dissemination distance per cell line in perivitelline space-inoculated zebrafish larvae at 3 dpi. J) Number of detected disseminated cells per cell line in perivitelline space-inoculated zebrafish larvae at 3 dpi.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4292304/v1/cb5973d0b1ffbebfad1442b8.jpeg"},{"id":55234331,"identity":"79a56f5a-8b07-4391-b445-86970fa2f968","added_by":"auto","created_at":"2024-04-24 13:23:52","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1992001,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eDose‒response curve and synergy plots for UM cells.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA) Dose‒response curve of withaferin A. B) Dose response curve of quisinostat. C) Dose‒response curve of E7107. D) Dose‒response curve of ricolinostat. Synergy scores are plotted in a 3D graph, with synergy scores on the Z-axis, the concentration of Drug A on the Y-axis and the concentration of Drug B on the X-axis. E) Bliss synergy score plot of ricolinostat and quisinostat in 92.1 cells. F) Bliss synergy score plot of Mel202 cells treated with withaferin A and E7107. H) Bliss synergy score plot of ricolinostat and quisinostat in MP46 cells.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4292304/v1/99ce93dc25e7dd4c9b484ab9.jpeg"},{"id":55234334,"identity":"f2a94eb7-310c-40da-9486-a538c128f907","added_by":"auto","created_at":"2024-04-24 13:23:53","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":3254325,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eIn vivo drug screening of zebrafish xenografts\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eA) Normalized tumor burden of 92.1-xenografts after 3 days of treatment with DMSO (n=21), ricolinostat (n=22), quisinostat (n=25) or their combination (n=33). B) Average cell dissemination distance of treated 92.1-xenografts. C) Number of disseminated cells in treated 92.1-xenografts. D) Normalized tumor burden of Mel202-xenografts after 3 days of treatment with DMSO (n=21), E7107 (n=19), withaferin A (n=20) or the combination of both (n=23). E) Average cell dissemination distance of treated Mel202-xenografts. F) Number of disseminated cells in treated Mel202-xenografts. G) Normalized tumor burden of MP46-xenografts after 3 days of treatment with DMSO (n=19), ricolinostat (n=20), quisinostat (n=20) or their combination (n=20). H) Average cell dissemination distance of treated MP46-xenografts. I) Number of disseminated MP46-xenograft-bearing cells\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4292304/v1/34121da7445c1f38254162a7.jpeg"},{"id":55392134,"identity":"fdee5e12-3871-43d8-b97c-5e8cc9e965b2","added_by":"auto","created_at":"2024-04-26 16:10:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1270963,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4292304/v1/8d7bb49e-6089-4165-9704-9ff877cc86ce.pdf"},{"id":55234336,"identity":"d0f93916-dc4b-4fe0-8253-6938cbba5001","added_by":"auto","created_at":"2024-04-24 13:23:53","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":7245363,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMoleculardependentdrugsynergisminUMV1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4292304/v1/f99fb8e09b515be459117e80.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Uveal Melanoma zebrafish xenograft models illustrate the mutation status-dependent effect of compound synergism or antagonism","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAnimal models play an important role in our understanding of cancer biology and drug discovery. Traditionally, mouse models dominate the realm of tumor-xenograft investigations[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], but since 2010, there has been a steep increase in the number of published zebrafish xenograft models[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Zebrafish have several advantages over mice, as they yield a large number of offspring and are relatively cheap to maintain and time efficient. Additionally, these methods are easy to manipulate; only a small number of tumor cells are needed to generate zebrafish xenografts, and they have the potential for high-throughput drug screening. These aspects have boosted their use in biomedical science and allow for large drug screenings in patient-derived xenografts in a short period of time, potentially improving personalized medicine[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Zebrafish larvae xenografts also allow tumor microenvironment assessments, as these models are not immunocompromised; however, the current knowledge on the interaction between tumor cells and their environment still has drawbacks that need to be improved to produce translatable results[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Zebrafish cancer avatars have been studied in multiple cancers, such as glioblastoma, breast cancer, hepatocellular carcinoma, prostate cancer, pediatric cancer and uveal melanoma[\u003cspan additionalcitationids=\"CR7 CR8 CR9 CR10\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Although a promising \u003cem\u003eBap1\u003c/em\u003e\u003cb\u003e-\u003c/b\u003edeficient mouse model was recently developed[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], mouse models have thus far failed to improve therapies for UM[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Therefore, we are particularly interested in \u003cem\u003eBAP1\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e-based zebrafish xenograft models. To improve drug discoveries in UM research, we argue that zebrafish xenografts could serve as a first-line model before more expensive mammalian studies are carried out.\u003c/p\u003e \u003cp\u003eUM is the most common intraocular malignancy, and it has a poor prognosis, as 50% of patients will develop metastasis within 5 years[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. UM etiology is characterized by driver mutations involved in the MEK-ERK pathway, where activating mutations in guanine nucleotide-binding protein Q (\u003cem\u003eGNAQ\u003c/em\u003e), guanine nucleotide-binding protein 11 (\u003cem\u003eGNA11\u003c/em\u003e), cysteinlyl leukotreine receptor 2 (\u003cem\u003eCYSLTR2\u003c/em\u003e), or phospholipase C beta 4 (\u003cem\u003ePLCB4\u003c/em\u003e) induce uncontrolled cell proliferation[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. However, UM prognosis prediction relies on secondary mutations in eukaryotic translation initiation factor 1A X-linked (EIF1AX), splicing factor 3b subunit 1 (\u003cem\u003eSF3B1)\u003c/em\u003e or BRCA1-associated protein-1 \u003cem\u003e(BAP1)\u003c/em\u003e. Furthermore, chromosomal aberrations also predict patient outcome, as loss of chromosome 3 and gain of 8q are associated with poor prognosis[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Secondary driver mutations are typically mutually exclusive and determine whether patients are at low risk (\u003cem\u003eEIF1AX\u003c/em\u003e\u003csup\u003emut\u003c/sup\u003e), intermediate risk (\u003cem\u003eSF3B1\u003c/em\u003e\u003csup\u003emut\u003c/sup\u003e) or high risk (\u003cem\u003eBAP1\u003c/em\u003e\u003csup\u003emut\u003c/sup\u003e) of metastatic disease[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. \u003cem\u003eBAP1\u003c/em\u003e\u003csup\u003emut\u003c/sup\u003e UMs are clinically the most relevant to study, yet despite the availability of several \u003cem\u003eBAP1\u003c/em\u003e\u003csup\u003emut\u003c/sup\u003e cell lines, most mouse and zebrafish models have been generated with \u003cem\u003eEIF1AX\u003c/em\u003e\u003csup\u003emut\u003c/sup\u003e cells or UM cell lines with unknown driver/secondary mutations[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMicroinjection of UM tumor cells in zebrafish to generate xenografts has been accomplished by multiple groups. Unfortunately, inoculation of UM cells in zebrafish larvae is not consistent between laboratories, as UM cell lines have been inoculated at the yolk sac[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan additionalcitationids=\"CR18 CR19 CR20\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], perivitelline space[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], intraocular space[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], or duct of Cuvier[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Moreover, analyses of zebrafish xenograft larvae are not always consistent. For example, tumor volume can be measured in different ways by multiplying the mean area by the total number of objects[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] or evaluating tumor size at 3 days post injection versus immediately after transplantation[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In contrast, others use a script in image analysis software to acquire quantifications[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eTo improve UM zebrafish xenograft models, we investigated zebrafish xenografts in detail by using 7 cell lines with representative mutations and chromosomal aberrations found in UM patients. We evaluated the phenotypic behavior of 2 dermal melanocytic cell lines (one hTERT immortalized cell line and one primary melanocyte cell line) and 5 uveal melanoma cell lines, including 2 \u003cem\u003eBAP1\u003c/em\u003e\u003csup\u003emut\u003c/sup\u003e primary cell lines and one \u003cem\u003eBAP1\u003c/em\u003e\u003csup\u003emut\u003c/sup\u003e metastatic cell line. To our knowledge, previously generated zebrafish models did not utilize \u003cem\u003eBAP1\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e cell lines[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. To optimize this model, we evaluated 7 cell lines at 2 common inoculation sites and 1 novel inoculation site (retro-orbital) to identify the most efficient and useful site for obtaining the most robust data. Additionally, we developed publicly available analysis scripts to standardize quantification methods for both tumor volume and dissemination measurements that allow for phenotypic behavior of UM cells \u003cem\u003ein vivo\u003c/em\u003e and to evaluate compound efficacy.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Cell culture conditions\u003c/h2\u003e \u003cp\u003eFive uveal melanoma cell lines, namely, 92.1 (established at the Leiden University Medical Center, Leiden, The Netherlands[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]), Mel202 (established at Schepens Eye Research Institute, Boston, USA[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], MP38, MP46, MM28 (established at Curie Institute, Paris, France[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]), immortalized dermal melanocytes CRL4059 and neonatal dermal melanocytes GM21808 (both obtained from American Type Culture Collection, Manassas, VA), were used for this study. The chromosomal aberrations and mutation status and Research Resource Identifiers of all the cell lines can be found in Supplementary Table\u0026nbsp;1. Uveal melanoma cell lines have been authenticated previously by single polymorphism analysis and AmpFLSTR\u0026trade; Identifiler\u0026trade; Plus PCR Amplification Kit (Thermo Fisher, Bleiswijk, The Netherlands) followed by sequencing. Additionally, we performed single nucleotide polymorphism analysis on CLR4059 and GM21808 with the Infinium\u0026trade; Global Screening Array-24 v3.0 BeadChip according to the manufacturer\u0026rsquo;s protocols and guidelines (Illumina, San Diego, CA, USA) and analysis methods described previously[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. (Supplementary Fig.\u0026nbsp;1). All uveal melanocytes were propagated in RPMI supplemented with 20% heat-inactivated fetal calf serum and 1% penicillin‒streptomycin; MP38 and MM28 media were supplemented with sodium pyruvate. Both dermal melanocyte strains were propagated in Medium 254 supplemented with human melanocyte growth supplements (Thermo Fisher Scientific, The Netherlands). All cell lines were incubated at 37\u0026deg;C in a humidified 5% CO\u003csub\u003e2\u003c/sub\u003e-enriched atmosphere and regularly checked for mycoplasma.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Drug screening of uveal melanoma cells\u003c/h2\u003e \u003cp\u003eDabrafenib, ricolinostat, withaferin A and quisinostat (Selleckchem, Berlin, Germany) were stored in DMSO at a 10 mM stock concentration at -80\u0026deg;C. E7107 (gifted by H3 Biomedicine Inc., Cambridge, MA, USA) was diluted in DMSO at a 10 mM stock concentration and stored at -20\u0026deg;C. To determine the IC50 values, a total of 6000 cells (92.1, Mel202 and MP46) were seeded per well in a 96-well plate. The following day, the medium was removed, the cells were washed once with PBS, and subsequently, 100 \u0026micro;l of medium supplemented with the drug was added at various concentrations (ranging from 50 \u0026micro;M to 1 \u0026micro;M for dabrafenib, ricolinostat and withaferin A or 500 nM to 1 nM for quisinostat and E7107). Identification of synergistic effects was performed after identifying the IC50 of each compound. A 6x6 matrix was used to treat cells at different concentrations based on the IC50 values. After 3 days, the medium was removed, the cells were washed once with PBS and fixed in ice-cold methanol. After fixation, the cells were stained with 0.1% crystal violet for 30 minutes, washed with water and air-dried. Finally, crystal violet was solubilized in methanol, and the absorption was measured at 545 nm. Samples were treated in triplicate and analyzed in GraphPad Prism V9 using nonlinear regression. The data are presented as the means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Combinatorial treatments were analyzed for synergistic, noninteractive and antagonistic effects using SynergyFinder[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. A synergy score less than \u0026minus;\u0026thinsp;10 was considered antagonistic, a score between \u0026minus;\u0026thinsp;10 and 10 was considered additive, and a score greater than 10 was considered synergistic.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Zebrafish husbandry and xenograft injections\u003c/h2\u003e \u003cp\u003eWild-type AB zebrafish were maintained under standard conditions with a 14 hr light/10 hr dark cycle. In this study, only larval zebrafish (no older than 120 hours post fertilization) were used. The animal experiments were approved by the Animal Experimentation Committee at Erasmus MC, Rotterdam. Zebrafish embryos were raised in E3 medium supplemented with 0.003% phenylthiourea (PTU) in a Petri dish at 28\u0026deg;C. At 24 hours post fertilization, the medium was refreshed following the dechlorination of the larvae. At 48 hours post fertilization, the zebrafish larvae were anesthetized with 0.016% tricane and used for injections. A total of 2.5x10\u003csup\u003e6\u003c/sup\u003e cells were harvested and stained with 2.5 \u0026micro;M CellTracker CM-Dil dye for 5 minutes at 37\u0026deg;C and subsequently for an additional 15 minutes at 4\u0026deg;C. After staining, CM-Dil dye was removed by centrifugation. The cells were then washed with PBS and resuspended in 2% PVP-40/PBS. A total of ~\u0026thinsp;200\u0026ndash;300 cells were injected into the yolk, perivitelline space or retro-orbitally. For the retro-orbital injection, every larva was injected into the left eye. Correctly injected larvae were selected 1 hour post injection under a fluorescence stereomicroscope, placed in E3 medium supplemented with PTU and raised at 34\u0026deg;C. At 3 days post injection, xenograft larvae were anesthetized and embedded in 1% low-melting agarose for live-cell imaging.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Confocal microscopy of zebrafish xenografts\u003c/h2\u003e \u003cp\u003eZebrafish xenograft larvae were imaged using a Leica SP5 (Leica Microsystems, Mannheim, Germany) under standard conditions (561 nm, 35% laser power with additional bright field image). Tile scans of 3 images were generated to obtain full-body length images for analysis. The number of disseminated cells, the distance of dissemination and the total tumor volume were calculated in FIJI with an in-house script (details can be found in the \u003cspan refid=\"Sec8\" class=\"InternalRef\"\u003eResults\u003c/span\u003e section and Supplementary Methods). The obtained values were then processed in GraphPad Prism V9. Comparisons of the number of detected spots, distance of dissemination and tumor volume between the different cell lines were statistically tested using ANOVA with Dunnett\u0026rsquo;s multiple comparison method. The data are presented as the means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Drug screening in zebrafish xenografts\u003c/h2\u003e \u003cp\u003eFor zebrafish toxicity assays, the same range of concentrations used \u003cem\u003ein vitro\u003c/em\u003e was used to treat the zebrafish larvae from 2 days post fertilization until 5 days post fertilization. A total of 8\u0026ndash;12 larvae per well were sorted in a 12-well plate with E3 medium supplemented with 0.003% phenylthiourea containing DMSO, ricolinostat, withaferin A, quisinostat or E7107 at different concentrations. The medium was refreshed daily. At 1, 2 and 3 days post treatment, larvae were inspected and registered; for each drug, this experiment was performed twice using two different wild-type AB parental zebrafish. The synergistic/antagonistic concentrations used per cell line were determined based on \u003cem\u003ein vitro\u003c/em\u003e data where less than 20% of viable cells remained after single-compound inhibition. Drug treatment started at 3 hours post injection, and the media containing the compounds were refreshed daily. At 3 days post injection (dpi), the zebrafish xenografts were imaged and analyzed in the same fashion as described earlier. Zebrafish-xenografts were statistically tested by comparing DMSO to Drug A, Drug B or the combination of both drugs using Welch\u0026rsquo;s t test. The data are presented as the means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 Different phenotypes of cell behavior based on inoculation site\u003c/h2\u003e\n \u003cp\u003eGaining insights into the optimal inoculation site could differ depending on the research question or behavior of cells \u003cem\u003ein vivo\u003c/em\u003e. Therefore, we used 1 metastatic UM cell line, 5 primary UM cell lines and 2 dermal melanocyte lines to determine the optimal inoculation site. The images shown in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e depict zebrafish larvae with 92.1 cells inoculated at different sites and serve as a representative example of zebrafish larvae inoculated with other cell lines. Zebrafish larvae were sorted at 1 hour post injection (1 hpi) for correctly injected cells; e.g. larvae that had cells in the brain, intraocular space or bloodstream were removed. At 3 days post injection (3 dpi), we assessed cell behavior and found vastly different phenotypes. All cell lines grew and disseminated after retro-orbital (RO) and perivitelline space (PS) injections (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA, \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eB). The most commonly used inoculation site, the yolk sac, demonstrated an inconsistent phenotype. The injected cells predominantly stayed within the yolk (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eC, \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eE), while a small number of larvae showed disseminated cells throughout the body (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eD, \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eE), which phenotypically resembled what was observed in PS injections.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Z-Tada: \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eZ\u003c/span\u003eebrafish Xenograft \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eT\u003c/span\u003eumor Volume \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003ea\u003c/span\u003end \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eD\u003c/span\u003eissemination \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eA\u003c/span\u003enalysis\u003c/h2\u003e\n \u003cp\u003eTo quantify the tumor volume, number of disseminated cells and distance of disseminated cells from the inoculation site, we developed Z-Tada, a system in which 2 scripts are used to analyze the tumor volume, dissemination distance, number of disseminated cells and size of disseminated cell clusters in a uniform manner independent of the inoculation site. By making confocal stack images, a simple yet robust method to measure tumor volume is by using the 3D counter plugin in FIJI. The first script is therefore quite simple because it splits the channels, removes the brightfield image, rotates the figure and runs the 3D counter plugin to obtain the tumor volume in cubic microns (Supplementary methods and Supplementary Fig. 2). This plugin identified spots and measured them in 3D; this allows 3D measurements of disseminated cells per identified object (in voxels) or total tumor volume by subsequently adding all objects together. The second script quantifies the number of disseminated cells and their migration distance using a single script. This script splits the channels, removes the brightfield image, rotates the figure and makes a maximum Z-stack projection. The Z-stack projection is then subjected to thresholding and multiplied by a mask to reduce the background and obtain a binary figure. The user is then asked to hover over the image to identify the X and Y coordinates of the injection site, which can subsequently be entered manually in the pop-up screens. Next, disseminated cells were identified with the Find Maxima function and analyzed with the Analyze Particles function (Supplementary Fig. 2, settings have a maximum particle size limitation to prevent measurement of the inoculation site, which is typically a large spot). For each spot, the X and Y coordinates are obtained and used to calculate a straight-line distance between the detected spot and reference point using the Pythagorean theorem (Supplementary methods and Supplementary Fig. 1). For example, a 92.1-xenograft inoculated retro-orbitally (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA) or in the perivitelline space (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB) illustrates the accuracy of this script independent of the inoculation site using an X-Y plot.\u003c/p\u003e\n \u003cp\u003eTumor volume analysis revealed vastly different behaviors based on the inoculation site (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eC-E). In general, yolk sac inoculation yielded the greatest tumor volume at 3 dpi (Supplementary Fig. 3A-G), with MP38, hTERT-melanocytes and neonatal melanocytes demonstrating the greatest tumor volume (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eC). Retro-orbital inoculation yielded the lowest tumor volume of all inoculation sites (Supplementary Fig. 3A-G). MP38 yielded the lowest tumor volume, which was comparable to that of MP46 and Mel202, while 92.1, hTERT-melanocytes and neonatal melanocytes harbored the greatest tumor volumes at 3 dpi (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eD). Perivitelline space inoculation resulted in intermediate tumor volumes between inoculation sites but was highly consistent between cell lines, whereas yolk sac inoculation was more dependent on the cell line (Supplementary Fig. 3A-G). Cell line 92.1 thrived in perivitelline inoculations with the highest tumor volume, while Mel202 harbored the lowest tumor volume in perivitelline space injections. All other cell lines yielded similar tumor volumes (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eE). Additionally, the size of the detected objects was inspected to investigate whether there were size differences per cell line in perivitelline space-inoculated larvae. An arbitrary threshold of \u0026gt;\u0026thinsp;200 voxels was used to count the number of disseminated cell clusters that could be considered to be more than 1 cell. In the 92.1 cell line, hTERT-melanocyte and neonatal melanocyte-xenografts yielded a low number of disseminated cells\u0026thinsp;\u0026gt;\u0026thinsp;200 voxels, while Mel202, MP46, MP38 and MM28 had a greater abundance of large disseminated cell objects (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eF).\u003c/p\u003e\n \u003cp\u003eRetro-orbital and perivitelline space inoculation consistently promoted cell dissemination in all the cell lines. The average dissemination distance per larva was similar between cell lines after retro-orbital injection, where MP38, MM28 and neonatal melanocytes tended to disseminate the furthest (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eG). The cell dissemination distance after perivitelline space inoculation was highly consistent between the cell lines, with only 92.1 indicating a slightly greater distance (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eI). The number of spots was significantly greater in the perivitelline space injection group than in the retro-orbital inoculation group (Supplementary Fig. 3H). Mel202-xenografts had the greatest number of spots in both models, while 92.1 had a slight increase in the perivitelline space model compared to the other cell lines used (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eH, \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eJ). Due to the consistent tumor volume, high number of disseminated cells, differences in disseminated cell sizes and largest dissemination distance in perivitelline space inoculations, we argue that this site is the most useful site for use in uveal melanoma zebrafish\u0026ndash;larva xenograft systems.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 Drug synergism differs among UM subtypes\u003c/h2\u003e\n \u003cp\u003eTo evaluate the robustness and abilities of zebrafish xenografts as a drug discovery model, we screened compounds previously tested in mouse or zebrafish xenografts. A total of 4 compounds were evaluated: quisinostat, ricolinostat (both tested in zebrafish xenografts[\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e]), withaferin A (tested in mice[\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e]) and E7101 (a novel compound). Unlike in previous studies, in this study, compound screening was performed on the \u003cem\u003eEIF1AX\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eSF3B1\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e and \u003cem\u003eBAP1\u003c/em\u003e\u003csup\u003e\u003cem\u003eneg\u003c/em\u003e\u003c/sup\u003e UM cell lines. All the compounds inhibited UM cell lines \u003cem\u003ein vitro\u003c/em\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA-D). As UM typically shares activation of the MEK-ERK pathway due to driver mutations in \u003cem\u003eGNAQ, GNA11, PLCB4\u003c/em\u003e or \u003cem\u003eCYSLTR2\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e] but differs in prognosis based on secondary mutations[\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e], we hypothesize that combinatorial inhibition could improve the inhibitory response dependent on UM subtype. To evaluate this hypothesis, we combined each compound with each other to identify synergistic or antagonistic effects. Surprisingly, we detected synergistic effects of the histone deacetylase inhibitors quisinostat and ricolinostat on \u003cem\u003eEIF1AX\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e cells, while this combination had antagonistic effects on \u003cem\u003eBAP1\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e cells (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eE, \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eH). On the other hand, we found strong synergistic effects of the combination of the MAPK/PI3K-AKT inhibitor withaferin A and the spliceosome inhibitor E7107 in Mel202 cells (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eF). Despite all the compounds being able to inhibit UM cells regardless of secondary mutation status (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA-C), synergism during combinatorial inhibition highly differed among UM subtypes (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSynergy scores based on SynergyFinder\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003e92.1\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDrug A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrug B\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eZIP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLoewe\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eH SA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBliss\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eE7107\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eQuisinostat\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5,03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0,41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5,43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eE7107\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eRicolinostat\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-7,42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1,29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-7,45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eRicolinostat\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuisinostat\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e21,96\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e-3,23\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e7,09\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e24,01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eWithaferin A\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eE7107\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eWithaferin A\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eQuisinostat\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2,33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eWithaferin A\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eRicolinostat\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eMel202\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDrug A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrug B\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eZIP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLoewe\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eH SA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBliss\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eE7107\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eQuisinostat\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4,71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4,35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eE7107\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eRicolinostat\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4,15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5,21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3,46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eRicolinostat\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eQuisinostat\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2,43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2,5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eWithaferin A\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eE7107\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e13,39\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e11,95\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e15,05\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e16,26\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eWithaferin A\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eQuisinostat\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-8,33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-8,97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eWithaferin A\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eRicolinostat\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17,04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18,36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eMP46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDrug A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrug B\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eZIP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLoewe\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eH SA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBliss\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eE7107\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eQuisinostat\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1,33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2,38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eE7107\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eRicolinostat\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-8,35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eRicolinostat\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuisinostat\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e-10,73\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e4,38\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e3,02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e-11,65\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eWithaferin A\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eE7107\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1,52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3,85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2,4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eWithaferin A\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eQuisinostat\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-8,23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eWithaferin A\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eRicolinostat\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0,01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3,85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e: A total of 4 tools are used in SynergFinder: ZIP, Loewe, HSA and Bliss. For each combination, the score is given and divided between 92.1, Mel202 and MP46. Synergism or antagonism is highlighted in bold.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4 \u003cem\u003eIn vivo\u003c/em\u003e evaluation of synergistic treatment therapies\u003c/h2\u003e\n \u003cp\u003eTo evaluate the synergistic effect of compounds, we first investigated the toxicity tolerance of single compounds in zebrafish larvae (Supplementary Fig. 4). None of the compounds exhibited toxicity in wild-type zebrafish larvae, even at the highest concentration tested \u003cem\u003ein vitro.\u003c/em\u003e Therefore, we were able to utilize compounds at concentrations at which the \u003cem\u003ein vitro\u003c/em\u003e survival of UM cells was \u0026lt;\u0026thinsp;20% without toxic effects in zebrafish xenografts. Interestingly, compared with DMSO, ricolinostat, quisinostat or combined treatment of 92.1-xenografts did not decrease the overall tumor burden (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA). However, all the compounds inhibited the migration and number of disseminated cells, and dual treatment had the strongest inhibitory effect (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eB, C). Treatment of Mel202-xenografts with E7107, withaferin A or their combination significantly inhibited the overall tumor burden in dual-treated xenografts (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eD), supporting our synergistic \u003cem\u003ein vitro\u003c/em\u003e findings. However, these compounds were unable to inhibit cell dissemination (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eE, F). Finally, the overall tumor burden of MP46-xenografts was lower in quisinostat-treated xenografts than in ricolinostat-treated or DMSO-treated xenografts. Notably, combined treatment prevented the inhibitory effect of quisinostat, as these xenografts harbored similar tumor burdens as those of the DMSO controls (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eG), supporting our antagonistic \u003cem\u003ein vitro\u003c/em\u003e findings. Additionally, neither quisinostat, ricolinostat nor the combination treatment reduced cell dissemination in MP46-xenografts (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eH, I).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eUM remains a devastating disease with a high propensity for metastasis and limited therapeutic options. To discover novel therapeutics, we optimized our xenograft zebrafish model, developed a robust algorithm to consistently determine model output measures and carried out a detailed analysis of zebrafish xenografts using multiple cell lines, which, to our knowledge, has not been previously investigated in this model. Previous UM-zebrafish xenografts typically utilized cell lines without known secondary mutations (OMM1[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], OMM2.3[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], Mel270[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], and Mel285[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]) or patient-derived spheroids (spUM-LB008[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] and spXmm66[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]). Here, we describe the novel cellular behavior of established cell lines with known secondary mutations in all three clinically relevant molecular subclasses (\u003cem\u003eEIF1AX\u003c/em\u003e, \u003cem\u003eSF3B1\u003c/em\u003e and \u003cem\u003eBAP1\u003c/em\u003e) in both primary and metastasis-derived cell lines. Notably, all established cell lines were derived from patients who eventually developed metastatic disease, including the 92.1 cell line, which harbors an \u003cem\u003eEIF1AX\u003c/em\u003e mutation.\u003c/p\u003e \u003cp\u003eDue to the variety of inoculation sites in zebrafish xenografts, we first evaluated which inoculation site would provide robust data that would allow investigation of the cellular behavior and effectiveness of therapeutic compounds. By generating 691 xenografts with primary and metastatic UM cell lines via retro-orbital, perivitelline space or yolk-sac injections, this study revealed that the perivitelline space is the most robust site for UM zebrafish xenografts. The quantification of zebrafish xenografts has varied across laboratories, for which we have developed Z-Tada. This provides a method for standardized analysis of the tumor volume and cell dissemination of zebrafish xenograft larvae, which accurately detects tumor cells and provides migration distances. Although yolk sac inoculation typically yielded the highest tumor burden (Supplementary Fig.\u0026nbsp;3), this site lacked robust cell dissemination (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Retro-orbital inoculation provided robust cell dissemination, yet the number of disseminated cells and overall tumor burden were significantly lower than perivitelline space inoculation (Supplementary Fig.\u0026nbsp;3). Interestingly, cell lines behave differently depending on the molecular subclass. The cell line 92.1 (primary \u003cem\u003eEIF1AX\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e) typically yielded a high tumor burden, but the size of the disseminated cell clusters was relatively small, whereas MP38 (primary \u003cem\u003eBAP1\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e) and MM28 (metastatic \u003cem\u003eBAP1\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e) developed more disseminated cell clusters with a large size (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Although this model provides robust data on tumor volume and cell dissemination, healthy and hTERT-immortalized melanocytes were also able to proliferate and disseminate, suggesting that this model is highly prone to cell dissemination regardless of cell type. Nonetheless, molecular subclasses with a greater probability of developing metastatic disease (\u003cem\u003eSF3B1\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e and \u003cem\u003eBAP1\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e)\u003c/em\u003e behave more aggressively in this model.\u003c/p\u003e \u003cp\u003eTo evaluate whether this model system can reliably be used for novel drug screening for UM, we investigated previously used compounds that were shown to effectively inhibit tumor growth or cell dissemination in UM cells. A potential therapeutic option for high-risk UM is histone deacetylase (HDAC) inhibitors, which are able to differentiate UM into a more melanocyte-like state[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In mice, the histone deacetylase inhibitors inhibitor quisinostat (targeting HDAC3, 5, 8 and 9) was shown to selectively inhibit \u003cem\u003eBAP1\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e xenografts (MP46 and MM28)[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. However, in zebrafish xenografts, quisinostat was also found to effectively inhibit the dissemination of metastatic cell lines (OMM2.3) or spheroids (spXmm66) that do not harbor \u003cem\u003eBAP1\u003c/em\u003e mutations[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In this study, we confirmed inhibition of overall tumor burden in quisinostat-treated \u003cem\u003eBAP1\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e zebrafish xenografts (MP46). However, quisinostat was also able to inhibit the cell dissemination of 92.1 cells (\u003cem\u003eEIF1AX\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e) but failed to reduce the overall tumor burden (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e); suggesting quisinostat effectivity is dependent on molecular subclass. Another HDAC inhibitor, ricolinostat (targeting HDAC6), was previously shown to inhibit tumor burden in zebrafish xenografts using the metastatic UM cell line OMM2.3[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Here, we showed that ricolinostat was also able to inhibit other types of UM cells \u003cem\u003ein vitro\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) but was effective only in 92.1-based xenografts. Ricolinostat was not effective against \u003cem\u003eBAP1\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e-cells (MP46) \u003cem\u003ein vivo.\u003c/em\u003e Interestingly, combining HDAC inhibitors was shown to be either synergistic (92.1) or antagonistic (MP46) based on the molecular subclass (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Our zebrafish xenografts demonstrated that the synergistic effects of quisinostat and ricolinostat on 92.1 cells strongly inhibited cell dissemination but did not affect overall tumor burden. However, its antagonistic effect seen \u003cem\u003ein vitro\u003c/em\u003e was also reproduced in MP46-xenografts, as the inhibitory effect of quisinostat was lost in the combination-treated xenografts (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Targeting HDACs is a promising therapy for many cancers and has been combined with several compounds that target other pathways[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]; however, combining multiple HDACs is not a strategy that has been studied in detail before. Our study suggests combining multiple HDAC inhibitors can be mutation-dependent; and should be investigated pre-clinically in detail to validate efficacy. In addition to HDAC inhibitors, we evaluated withaferin A, a compound tested only in mice. Withaferin A is able to inhibit the MET and MEK1/2 pathways, making this an interesting compound for UM because it acts on the primary driver pathways[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. \u003cem\u003eIn vitro\u003c/em\u003e, withaferin A inhibited the growth of all the tested cell lines. However, withaferin A in combination with the spliceosome inhibitor E7107 had synergistic effects on Mel202 cells, yet failed to illustrate synergistic effects on other cell lines tested (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The synergistic effect was reproduced in Mel202-xenografts, suggesting that this combination could provide novel therapeutic options for \u003cem\u003eSF3B1\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e UM patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eZebrafish xenografts hold potential as a drug screening platform for UM, where synergism and antagonism can be studied in detail. However, this study only treated xenografts for a total of 3 days, which could be too short to see a more defined inhibitory effect. Other important elements in this platform that could affect drug efficiency are the number of fish treated per well and the efficiency of compound uptake by zebrafish larvae. However, an important advantage of this model is functional liver metabolism in zebrafish larvae[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], which can metabolize compounds and therefore alter their effects. Nonetheless, this platform illustrates that molecular subclasses of UM are important parameters for discovering novel therapeutic compounds.\u003c/p\u003e \u003cp\u003eIn summary, this study illustrates that optimal inoculation of uveal melanoma cells in the perivitelline space allows for robust tumor burden and cell dissemination analysis in a short time span of 3 days. Using Z-Tada, this model is able to identify differences in cellular behavior depending on genetic background in a standardized fashion. Furthermore, this methodology allows standardized read-out parameters for high-throughput screening of novel compounds and can identify synergistic or antagonistic effects. Using this model, we provide evidence that clinically prognostic subclasses of UM are key to developing effective therapies. Synergistic compound screenings for UM should take this into account, as the same combination can be synergistic in low-risk UM but antagonistic in high-risk UM.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eUM \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Uveal melanoma (UM)\u003c/p\u003e\n\u003cp\u003eGNAQ\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Guanine nucleotide-binding protein Q (GNAQ)\u003c/p\u003e\n\u003cp\u003eGNA11\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Guanine nucleotide-binding protein 11 (GNA11)\u003c/p\u003e\n\u003cp\u003eCYSLTR2\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Cysteinlyl leukotreine receptor 2 (CYSLTR2)\u003c/p\u003e\n\u003cp\u003ePLCB4\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Phospholipase C Beta 4 (PLCB4)\u003c/p\u003e\n\u003cp\u003eEIF1AX\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Eukaryotic Translation Initiation Factor 1A X-Linked (EIF1AX)\u003c/p\u003e\n\u003cp\u003eSF3B1\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Splicing factor 3b subunit 1 (SF3B1)\u003c/p\u003e\n\u003cp\u003eBAP1\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;BRCA1-associated protein-1 (BAP1)\u003c/p\u003e\n\u003cp\u003eEIF1AX\u003csup\u003emut\u003c/sup\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;EIF1AX-mutated\u003c/p\u003e\n\u003cp\u003eSF3B1\u003csup\u003emut\u003c/sup\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;SF3B1-mutated\u003c/p\u003e\n\u003cp\u003eBAP1\u003csup\u003emut\u0026nbsp;\u003c/sup\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;BAP1-mutated\u003c/p\u003e\n\u003cp\u003ehTERT\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;human telomerase reverse transcriptase\u003c/p\u003e\n\u003cp\u003e\u0026micro;M\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Micromolar\u003c/p\u003e\n\u003cp\u003enM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Nanomolar\u003c/p\u003e\n\u003cp\u003emM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Millimolar\u003c/p\u003e\n\u003cp\u003ePTU\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Phenylthiourea\u003c/p\u003e\n\u003cp\u003eDpi\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;days post injection\u003c/p\u003e\n\u003cp\u003eHpi\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;hour post injection\u003c/p\u003e\n\u003cp\u003eRO\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;retro-orbital\u003c/p\u003e\n\u003cp\u003ePS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;perivitelline space\u003c/p\u003e\n\u003cp\u003e3D \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Three-dimensional\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, only larval zebrafish (no older than 120 hours post fertilization) were used. The animal experiments were approved by the Animal Experimentation Committee at Erasmus MC, Rotterdam.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by \u0026ldquo;Rotterdamse Stichting Blindenbelangen\u0026rdquo; and \u0026ldquo;Stichting voor Ooglijders\u0026rdquo;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQ.B. and E.B. contributed to the conceptualization, experimental design and interpretation of the data. Q.B. performed the data acquisition, script development and initial analysis. Q.B. drafted the manuscript, followed by reviewing and editing by Q.B. E.B. and E.K. Funding was acquired by E.B. and E.K. Supervision was carried out by E.B. and E.K.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Thomas Huizer, BSc and Nikki K\u0026ouml;nemann, BSc for their contributions to the data acquisition and technical support.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eJ.H. Nadeau, J. Auwerx, The virtuous cycle of human genetics and mouse models in drug discovery. Nat. Rev. Drug Discovery. \u003cb\u003e18\u003c/b\u003e(4), 255\u0026ndash;272 (2019)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eC.R. Ireson et al., The role of mouse tumour models in the discovery and development of anticancer drugs. Br. J. Cancer. \u003cb\u003e121\u003c/b\u003e(2), 101\u0026ndash;108 (2019)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eA. 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Gastroenterology. \u003cb\u003e149\u003c/b\u003e(6), 1361\u0026ndash;1377 (2015)\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4292304/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4292304/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eUveal melanoma (UM) is the most common primary intraocular malignancy with a high probability of metastatic disease. Although excellent treatment option for primary UM are available, therapy for metastatic disease remain limited. Drug discovery studies using mouse models have thus far failed to provide therapeutic solutions, highlighting the need for novel models. Here, we optimize zebrafish xenografts as a potential model for drug discovery by showcasing the behavior of multiple cell lines and novel findings on mutation-dependent compound synergism/antagonism using Z-Tada; an algorithm to objectively characterize output measurements.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003ePrognostic relevant primary and metastatic UM cell lines or healthy melanocytes were inoculated at three distinct inoculation sites. Standardized quantifications independent of inoculation site were obtained using Z-Tada; an algorithm to measure tumor burden and the number, size and distance of disseminated tumor cells. Sequentially, we utilized this model to validate combinatorial synergism or antagonism seen \u003cem\u003ein vitro.\u003c/em\u003e\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eDetailed analysis of 691 zebrafish xenografts demonstrated perivitelline space inoculation provided robust data with high probability of cell dissemination. Cell lines with more invasive behavior (\u003cem\u003eSF3B1\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e and \u003cem\u003eBAP1\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e)\u003c/em\u003e behaved most aggressive in this model. Combinatorial drug treatment illustrated synergism or antagonism is mutation-dependent, which were confirmed \u003cem\u003ein vivo\u003c/em\u003e. Combinatorial treatment differed per xenograft-model, as it either inhibited overall tumor burden or cell dissemination.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003ePerivitelline space inoculation provides robust zebrafish xenografts with the ability for high-throughput drug screening and robust data acquisition using Z-Tada. This model demonstrates that drug discovery for uveal melanoma must take mutational subclasses into account, especially in combinatorial treatment discoveries.\u003c/p\u003e","manuscriptTitle":"Uveal Melanoma zebrafish xenograft models illustrate the mutation status-dependent effect of compound synergism or antagonism","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-24 13:23:48","doi":"10.21203/rs.3.rs-4292304/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e7a10d28-41b1-46a9-bbb3-8069211d85a3","owner":[],"postedDate":"April 24th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-26T15:37:46+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-24 13:23:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4292304","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4292304","identity":"rs-4292304","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}