Uveal melanoma (UM) is a common health challenge worldwide as a prevalent intraocular malignancy because of its high mortality rate. However, clinical workers do not have an accurate prognostic tool now. Immune function is closely related to tumor development. Interestingly, researchers have identified that long noncoding RNAs (lncRNAs) are tightly associated with biological processes at the cellular level, particularly their involvements in immune response and its regulation of the growth of tumor cells. Hence, lncRNAs may be involved in the progression of uveal melanoma. UM patients\' RNA expression matrices were extracted from TCGA database. The targeted immune genes were filtered by weighted correlation network analysis and the immune-related lncRNAs with a high prognostic relevance were obtained by Cox regression analysis and least absolute shrinkage and selection operator regression analysis. Each sample was scored according to those lncRNA expression and divided into high-risk and low-risk group. We confirmed the sensitivity and independence of our risk model compared to the tumor mutation burden score. Finally, we demonstrated the clinical relevance of our model by examining its sensitivity to different drugs. The risk score based on our risk model was significantly independent of other clinical parameters in either univariate (hazard ratio = 109.852 [15.738-766.749], P value < .001) or multivariate (hazard ratio = 114.075 [15.207-855.735], P value < .001) analyses. The ROC curves of this model imply high predictive accuracy for 1-year, 3-year, and 5-year survival (1-year area under the curve [AUC] = 0.849, 3-years AUC = 0.848, and 5-years AUC = 0.761). Our study revealed that immune-related lncRNAs are significant in the clinical diagnosis, treatment and prognosis of UM patients. We successfully constructed a lncRNA-based prognostic risk model which may serve as a future reference for the diagnosis and prognosis of UM. Based on this model we also validated the sensitivity of some cancer drugs, which has implications for the future immunotherapy and drug development.

UNASSIGNED: Perfusion-weighted imaging (PWI; magnetic resonance imaging [MRI]) has been shown to provide valuable biological tumor information in uveal melanoma (UM). Clinically used semiquantitative methods do not account for tumor pigmentation and eye movement. We hypothesize that a quantitative PWI method that incorporates these, provides a more accurate description of tumor perfusion than the current clinical method. The aim of this study was to test this in patients with UM before and after radiotherapy.
UNASSIGNED: Perfusion-weighted 3T MRIs were retrospectively analyzed in 47 patients with UM before and after radiotherapy. Tofts pharmacokinetic modeling was performed to determine vascular permeability (Ktrans), extracellular extravascular space (ve), and reflux rate (kep). These were compared with semiquantitative clinical parameters including peak intensity and outflow percentage.
UNASSIGNED: The effect of tumor pigmentation on peak intensity and outflow percentage was statistically significant (P < 0.01) and relative peak intensity was significantly different between melanotic and amelanotic tumors (1.5 vs. 1.9, P < 0.01). Before radiotherapy, median tumor Ktrans was 0.63 min-1 (range = 0.06-1.42 min-1), median ve was 0.23 (range = 0.09-0.63), and median kep was 2.3 min-1 (range = 0.6-5.0 min-1). After radiotherapy, 85% showed a decrease in Ktrans and kep (P < 0.01). Changes in tumor pigmentation before and after radiotherapy were small and not significant (median increase in T1 of 33 ms, P = 0.55).
UNASSIGNED: Quantitative PWI parameters decreased significantly after radiotherapy and can therefore can serve as an early biomarker for treatment response assessment. However, due to the nonsignificant changes in tumor pigmentation before and after radiotherapy, the current semiquantitative method appears to be sufficiently sensitive for detection of changes in tumor perfusion.

Uveal melanoma (UM) is the most prevalent type of primary intraocular malignancy and is prone to metastasize, particularly to the liver. However, due to the poor understanding of the pathogenesis of UM, effective therapeutic approaches are lacking. As a phenolic compound extracted from grapes, piceatannol (PIC) exhibits anti‑cancer properties. To the best of our knowledge, however, the effects of PIC on UM have not been well investigated. Therefore, in the present study, considering the impact of pyroptosis on modulating cell viability, the mechanism underlying the effects of PIC on UM cell proliferation was explored. The inhibitory effect of PIC on proliferation of UM cells was detected by cell counting kit‑8 assay. Wound healing was used to investigate the effects of PIC on the migration of UM cells. Activity detecting assays were performed to test the apoptosis and oxidant level in UM cells. Western blotting and RT‑qPCR were used to detect the inflammatory and pyroptotic levels of UM cell after PIC treatment. PIC‑treated UM cells were screened by high‑throughput sequencing to detect the differential expression of RNA and differential genes. Si‑TREM2 transfection was used to verify the important role of TREM2 in the effects of PIC. Immunohistochemical staining was used to observe the expressions of TREM2 and GSDMR of tumor in nude mice after PIC administration. PIC effectively inhibited proliferation ability of C918 and Mum‑2b UM cell lines via enhancing apoptosis, as evidenced by enhanced activities of caspase 3 and caspase 9. In addition, treatment of UM cells with PIC attenuated cell migration in a dose‑dependent manner. PIC increased reactive oxygen species levels and suppressed the activity of the antioxidant enzymes superoxide dismutase, glutathione‑S‑transferase, glutathione peroxidase and catalase. PIC inhibited inflammatory responses in C918 cells. PIC treatment upregulated IL‑1β, IL‑18 and Nod‑like receptor protein 3 and downregulated gasdermin D (GSDMD). RNA sequencing results revealed the activation of an unconventional pyroptosis‑associated signaling pathway, namely caspase 3/GSDME signaling, following PIC treatment, which was mediated by triggering receptor expressed on myeloid cells 2 (TREM2) upregulation. As an agonist of TREM2, COG1410‑mediated TREM2 upregulation inhibited proliferation of C918 cells, displaying similar effects to PIC. Furthermore, PIC inhibited tumor growth via regulating the TREM2/caspase 3/GSDME pathway in a mouse model. Collectively, the present study revealed a novel mechanism underlying the inhibitory effects of PIC on UM, providing a potential treatment approach for UM in clinic.

Melatonin, noted for its anti-cancer properties in various malignancies, including cutaneous melanoma, shows promise in Uveal melanoma (UM) treatment. This study aimed to evaluate melatonin receptor expression in primary UM and its association with UM-related mortality and prognostic factors. Immunohistochemical analysis of 47 primary UM tissues showed low expression of melatonin receptor 1A (MTNR1A) and melatonin receptor 1B (MTNR1B), with MTNR1A significantly higher in patients who succumbed to UM. Analysis of TCGA data from 80 UM patients revealed RNA expression for MTNR1A, retinoic acid-related orphan receptor alpha (RORα), and N-ribosyldihydronicotinamide:quinone oxidoreductase (NQO2), but not MTNR1B or G protein-coupled receptor 50 (GPR50). Higher MTNR1A RNA levels were observed in patients with a BRCA1 Associated Protein 1 (BAP1) mutation, and higher NQO2 RNA levels were noted in patients with the epithelioid tumor cell type. However, Kaplan-Meier analysis did not show distinct survival probabilities based on receptor expression. This study concludes that UM clinical samples express melatonin receptors, suggesting a potential mechanism for melatonin\'s anti-cancer effects. Despite finding higher MTNR1A expression in patients who died of UM, no survival differences were observed.

OBJECTIVE: Uveal melanoma (UM) represents a prevailing primary intraocular malignancy, with a limited median overall survival among metastatic patients, and most tumors lack RAF/RAS mutations. The pan-RAF inhibitor LY3009120 has demonstrated valuable anti-tumor effects in a wide range of RAF/RASmut and wild-type (WT) tumor models. This study aimed to evaluate the antitumor effect of LY3009120 on 92-1 UM cell line.
METHODS: The effect of the pan-RAF inhibitor LY3009120 on cell proliferation, metabolic activity, biomass, early and late apoptosis/necrosis, and morphology was characterized in vitro (0.1-5 μM for 48 h/72 h). Furthermore, targeted panel sequencing was used to characterize the mutational landscape of the human 92-1 UM cell line.
RESULTS: LY3009120 showed a significant concentration-dependent anti-proliferative effect on 92-1 cells. Cell proliferation and viability were significantly reduced at the lowest effective concentration of 0.5 μM (at 48 and 72 h, p<0.001). Furthermore, LY3009120 caused significant early apoptosis and late apoptosis/necrosis in 92-1 cells at 5 μM. Except for TP53, NGS showed that all 49 additional analysed genes (Oncomine myeloid panel) of 92-1 were wild-type, including BRAF, NRAS, and KRAS.
CONCLUSIONS: The pan-RAF inhibitor LY3009120 demonstrated a significant anti-tumor effect on human UM cell line 92-1 independent of the molecular BRAF and RAS mutational status.

Uveal melanoma (UM) is the most common primary intraocular tumor in adults, with no standardized treatment for advanced disease. Based on preliminary bioinformatical analyses DTYMK and PARP1 were selected as potential therapeutic targets. High levels of both proteins were detected in uveal melanoma cells and correlated with increased tumor growth and poor prognosis. In vitro tests on MP41 (BAP1 positive) and MP46 (BAP1 negative) cancer cell lines using inhibitors pamiparib (PARP1) and Ymu1 (DTYMK) demonstrated significant cytotoxic effects. Combined treatment had synergistic effects in MP41 and additive in MP46 cell lines, reducing cell proliferation and inhibiting the mTOR signaling pathway. Furthermore, the applied inhibitors in combination decreased cell motility and migration speed, especially for BAP1-negative cell lines. Our hypothesis of the double hit into tumoral DNA metabolism as a possible therapeutic option in uveal melanoma was confirmed since combined targeting of DTYMK and PARP1 affected all tested cytophysiological parameters with the highest efficiency. Our in vitro findings provide insights into novel therapeutic avenues for managing uveal melanoma, warranting further exploration in preclinical and clinical settings.

UNASSIGNED: Metastatic uveal melanoma (UM) treatment is difficult, and effective treatments are urgently needed. We aimed to explore the role of heme oxygenase 1 (HO-1) in UM and provide new therapeutic strategies for UM.
UNASSIGNED: Bioinformatics was used to analyze the relationship between HMOX1 and immunity in UM and other tumors. Cell Counting Kit-8, Western blot, immunofluorescence staining, wound healing, and Transwell assays were used. A subcutaneous transplanted UM tumor model was used in mice to verify the therapeutic effect.
UNASSIGNED: In UM, the expression level of HMOX1 was strongly correlated with the immune score and the infiltration level of various immune cells. ZnPP can inhibit the growth of UM cells, promote cell apoptosis, and block the cell cycle at G0/G1 phase in vitro. HO-1 knockout can effectively inhibit the proliferation of UM cells. ZnPP effectively inhibited the growth of UM and promoted the infiltration of CD8+ T cells in a subcutaneous tumor transplantation model.
UNASSIGNED: These results indicate that targeting HO-1 in UM has the potential for independent targeted immunotherapy or adjuvant immunotherapy.

OBJECTIVE: To determine the association between gene-expression profiling (GEP), next-generation sequencing (NGS), preferentially expressed antigen in melanoma (PRAME) features, and metastatic risk in patients with uveal melanoma (UM).
METHODS: A retrospective analysis of patients with UM treated by brachytherapy or enucleation by a single ocular oncologist was conducted from November 2020 and July 2022. Clinicopathologic features, patient outcomes, GEP classification, NGS, and PRAME results were recorded.
RESULTS: Comprehensive GEP, PRAME, and NGS testing was performed on 135 UMs. The presence of eukaryotic translation initiation factor 1A, X-chromosomal and splicing factor 3B subunit 1 mutations was significantly associated with GEP class 1A and GEP class 1B, respectively. The presence of BRCA- associated protein-1 mutation was significantly associated with GEP class 2. The average largest basal diameter for tumors with eukaryotic translation initiation factor 1A, X-chromosomal mutations was significantly smaller than those with splicing factor 3B subunit 1 mutations and BRCA1-associated protein-1 mutations. Class 2 tumors metastasized sooner than GEP class 1 tumors. Tumors with splicing factor 3B subunit 1 and/or BRCA1-associated protein-1 mutations metastasized sooner compared with tumors that had either no driver mutation or no mutations at all. Tumors with splicing factor 3B subunit 1 did not have a significantly different time to metastasis compared with tumors with BRCA1-associated protein-1 (P value = 0.97). Forty tumors (30%) were PRAME positive, and the remaining 95 tumors (70%) were PRAME negative. Tumors with PRAME-positive status did not have a significantly different time to metastasis compared with tumors without PRAME-positive status (P value = 0.11).
CONCLUSIONS: GEP, NGS, and PRAME expression analysis help determine different levels of metastatic risk in UM. Although other prognostic tests exist, the following study reports on the use of NGS for metastatic prognostication in UM. However, limitations of NGS exist, especially with small lesions that are technically difficult to biopsy.

UNASSIGNED: Uveal melanoma (UM) is the most common primary intraocular malignancy with a high probability of metastatic disease. Although excellent treatment options 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.
UNASSIGNED: Prognostic relevant primary (N = 4) and metastatic UM (N = 1) cell lines or healthy melanocytes (N = 2) 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.
UNASSIGNED: 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 (SF3B1mut and BAP1mut) 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.
UNASSIGNED: 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.

BACKGROUND: Although there has been some progress in the treatment of primary uveal melanoma (UVM), distant metastasis remains the leading cause of death in patients. Monitoring, staging, and treatment of metastatic disease have not yet reached consensus. Although more than half of metastatic tumors (62%) are diagnosed within five years after primary tumor treatment, the remainder are only detected in the following 25 years. The mechanisms of UVM metastasis and its impact on prognosis are not yet fully understood.
METHODS: scRNA-seq data of UVM samples were obtained and processed, followed by cell type identification and characterization of macrophage subpopulations. High-dimensional weighted gene co-expression network analysis (HdWGCNA) was performed to identify key gene modules associated with metastatic protective macrophages (MPMφ) in primary samples, and functional analyses were conducted. Non-negative matrix factorization (NMF) clustering and immune cell infiltration analyses were performed using the MPMφ gene signatures. Machine learning models were developed using the identified metastatic protective macrophages related genes (MPMRGs) to distinguish primary from metastatic patients. A deep learning convolutional neural network (CNN) model was constructed based on MPMRGs and cell type associations. Lastly, a prognostic model was established using the MPMRGs and validated in independent cohorts.
RESULTS: Single-cell RNA-seq analysis revealed a unique immune microenvironment landscape in primary samples compared to metastatic samples, with an enrichment of macrophage cells. Using HdWGCNA, MPMφ and marker genes were identified. Functional analysis showed an enrichment of genes related to antigen processing progress and immune response. Machine learning and deep learning models based on key genes showed significant effectiveness in distinguishing between primary and metastatic patients. The prognostic model based on key genes demonstrated substantial predictive value for the survival of UVM patients.
CONCLUSIONS: Our study identified key macrophage subpopulations related to metastatic samples, which have a profound impact on shaping the tumor immune microenvironment. A prognostic model based on macrophage cell genes can be used to predict the prognosis of UVM patients.