Uveal Melanoma Metastasis.
Ontology highlight
ABSTRACT:
SUBMITTER: Rossi E
PROVIDER: S-EPMC8616038 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Uveal melanoma, the most common intraocular primary cancer in adults, is characterized by striking variability in metastatic tendencies. BAP1 deletion in the primary tumor is associated with uveal melanoma metastasis, but it cannot always be resolved by bulk DNA sequencing of heterogeneous tumors. Here, we show that assessment of BAP1 methylation is an accurate and readily clinically actionable assay to accurately identify high-risk uveal melanoma patients.
| S-EPMC8484429 | biostudies-literature
Project description:Uveal melanoma (UM) is the most frequently found primary intra-ocular tumor in adults. It is a highly aggressive cancer that causes metastasis-related mortality in up to half of the patients. Many independent studies have reported somatic genetic changes associated with high metastatic risk, such as monosomy of chromosome 3 and mutations in BAP1. Still, the mechanisms that drive metastatic spread are largely unknown. This study aimed to elucidate the potential role of microRNAs in the metastasis of UM. Using a next-generation sequencing approach in 26 UM samples we identified thirteen differentially expressed microRNAs between high-risk UM and low/intermediate-risk UM, including the known oncomirs microRNA-17-5p, microRNA-21-5p, and miR-151a-3p. Integration of the differentially expressed microRNAs with expression data of predicted target genes revealed 106 genes likely to be affected by aberrant microRNA expression. These genes were involved in pathways such as cell cycle regulation, EGF signaling and EIF2 signaling. Our findings demonstrate that aberrant microRNA expression in UM may affect the expression of genes in a variety of cancer-related pathways. This implies that some microRNAs can be responsible for UM metastasis and are promising potential targets for future treatment.
| S-EPMC6628189 | biostudies-literature
Project description:PurposeUveal melanoma (UM) can be classified by gene expression profiling (GEP) into Class 1 (low metastatic risk) and Class 2 (high metastatic risk), the latter being strongly associated with mutational inactivation of the tumor suppressor BAP1. Nevertheless, a small percentage of Class 1 tumors give rise to metastatic disease. The purpose of this study was to identify biomarkers of metastasis in Class 1 tumors.Experimental designA total of 389 consecutive patients with UM were assigned to Class 1 or Class 2 using a prospectively validated 12-gene prognostic classifier. Selected tumors were further analyzed using global GEP and single nucleotide polymorphism microarrays. PRAME (preferentially expressed antigen in melanoma) mRNA expression was analyzed in 64 Class 1 tumors by qPCR.ResultsAmong Class 1 UMs, the most significant predictor of metastasis was PRAME mRNA expression (P = 0.0006). The 5-year actuarial rate of metastasis was 0% for Class1(PRAME-), 38% for Class1(PRAME+), and 71% for Class 2 tumors. Median metastasis-free survival for Class1(PRAME+) patients was 88 months, compared to 32 months for Class 2 patients. Findings were validated using three independent datasets, including one using disomy 3 to identify low-risk UM. Chromosome copy number changes associated with Class1(PRAME+) tumors included gain of 1q, 6p, 8q, and 9q and loss of 6q and 11q. PRAME expression was associated with larger tumor diameter (P = 0.05) and SF3B1 mutations (P = 0.003).ConclusionsPRAME is an independent prognostic biomarker in UM, which identifies increased metastatic risk in patients with Class 1 or disomy 3 tumors. This finding may further enhance the accuracy of prognostic testing and precision medicine for UM.
| S-EPMC4780366 | biostudies-literature
Project description:Purpose:To create an interactive web-based tool for the Prediction of Risk of Metastasis in Uveal Melanoma (PRiMeUM) that can provide a personalized risk estimate of developing metastases within 48 months of primary uveal melanoma (UM) treatment. The model utilizes routinely collected clinical and tumor characteristics on 1227 UM, with the option of including chromosome information when available. Methods:Using a cohort of 1227 UM cases, Cox proportional hazard modeling was used to assess significant predictors of metastasis including clinical and chromosomal characteristics. A multivariate model to predict risk of metastasis was evaluated using machine learning methods including logistic regression, decision trees, survival random forest, and survival-based regression models. Based on cross-validation results, a logistic regression classifier was developed to compute an individualized risk of metastasis based on clinical and chromosomal information. Results:The PRiMeUM model provides prognostic information for personalized risk of metastasis in UM. The accuracy of the risk prediction ranged between 80% (using chromosomal features only), 83% using clinical features only (age, sex, tumor location, and size), and 85% (clinical and chromosomal information). Kaplan-Meier analysis showed these risk scores to be highly predictive of metastasis (P < 0.0001). Conclusions:PRiMeUM provides a tool for predicting an individual's personal risk of metastasis based on their individual and tumor characteristics. It will aid physicians with decisions concerning frequency of systemic surveillance and can be used as a criterion for entering clinical trials for adjuvant therapies.
| S-EPMC6108308 | biostudies-literature
Project description:Simple Summary This study pursued the proteomic analysis of primary uveal melanoma (pUM) for insights into the mechanisms of metastasis and protein biomarkers. Liquid chromatography tandem mass spectrometry quantitative proteomic technology was used to analyze 53 metastasizing and 47 non-metastasizing pUM. The determined proteome of 3935 proteins was very similar between the metastasizing and non-metastasizing pUM, but included the identification of 402 differentially expressed (DE) proteins. Bioinformatic analyses suggest significant differences in the immune response between metastasizing and non-metastasizing pUM. Immune protein profiling results were consistent with transcriptomic studies, showing the immune-suppressive nature and low abundance of immune checkpoint regulators in pUM, and suggest CDH1, HLA-DPA1, and several DE immune kinases and phosphatases as potential targets for immune therapy checkpoint blockade. Prediction modeling of the proteomic data identified 32 proteins capable of predicting metastasizing versus non-metastasizing pUM with 93% discriminatory accuracy. Abstract Uveal melanoma metastases are lethal and remain incurable. A quantitative proteomic analysis of 53 metastasizing and 47 non-metastasizing primary uveal melanoma (pUM) was pursued for insights into UM metastasis and protein biomarkers. The metastatic status of the pUM specimens was defined based on clinical data, survival histories, prognostic analyses, and liver histopathology. LC MS/MS iTRAQ technology, the Mascot search engine, and the UniProt human database were used to identify and quantify pUM proteins relative to the normal choroid excised from UM donor eyes. The determined proteomes of all 100 tumors were very similar, encompassing a total of 3935 pUM proteins. Proteins differentially expressed (DE) between metastasizing and non-metastasizing pUM (n = 402) were employed in bioinformatic analyses that predicted significant differences in the immune system between metastasizing and non-metastasizing pUM. The immune proteins (n = 778) identified in this study support the immune-suppressive nature and low abundance of immune checkpoint regulators in pUM, and suggest CDH1, HLA-DPA1, and several DE immune kinases and phosphatases as possible candidates for immune therapy checkpoint blockade. Prediction modeling identified 32 proteins capable of predicting metastasizing versus non-metastasizing pUM with 93% discriminatory accuracy, supporting the potential for protein-based prognostic methods for detecting UM metastasis.
| S-EPMC8307952 | biostudies-literature
Project description:PurposeReduced nuclear expression of BRCA1 associated protein 1 (BAP-1) is associated with a high risk for metastasis in uveal melanoma. Manual assessment of the expression level may face issues with interobserver reproducibility. This could be improved with digital image analysis (DIA).MethodsThirty enucleated eyes with uveal melanoma from the Emory Eye Center (Atlanta, GA; years 2009-2017) were included and stained with BAP-1. Retrospective data on patient and tumor characteristics were retrieved. Patients were randomized to a training or validation cohort. Their tumor sections were digitally scanned and scored for percentage of BAP-1-positive cells with the QuPath Bioimage analysis software.ResultsInterobserver concordance was 75% (Cohen's κ 0.52) with manual BAP-1 scoring and 88% to 94% with DIA (Cohen's κ 0.75-0.88). Positive and negative predictive values for metastasis were 90% and 100% with DIA, 80% and 86% with manual scoring, and 78% and 88% with gene expression class 2. In binary logistic regression, manual and DIA of BAP-1 and gene expression class 2 were associated with metastasis, but none retained significance in multiple regression. Metastasis-free survival was significantly shorter with low BAP-1 expression as defined by DIA (log-rank P = 0.02), but not with manual scoring (log-rank P = 0.36) or with gene expression class 2 (log-rank P = 0.17).ConclusionsDIA of BAP-1 is a competitive alternative to manual assessment as well as gene expression profiling in prognostication of enucleated specimens with uveal melanoma.Translational relevanceThe emerging scope for automatization of qualified diagnostic tasks is applied to uveal melanoma.
| S-EPMC6504204 | biostudies-literature
Project description:BACKGROUND:Patients with metastatic uveal melanoma (MUM) in the liver usually die within 1 year. The development of new treatments for MUM has been limited by the lack of diverse MUM cell lines and appropriate animal models. We previously reported that orthotopic xenograft mouse models established by direct injection of MUM cells into the liver were useful for the analysis associated with tumor microenvironment in the liver. However, considering that patients with UM metastasize to the liver hematogenously, direct liver injection model might not be suitable for investigation on various mechanisms of liver metastasis. Here, we aim to establish new orthotopic xenograft models via hematogenous dissemination of tumor cells to the liver, and to compare their characteristics with the hepatic injection model. We also determine if hepatic tumors could be effectively monitored with non-invasive live imaging. METHODS:tdtTomate-labeled, patient-derived MUM cells were injected into the liver, spleen or tail vein of immunodeficient NSG mice. Tumor growth was serially assessed with In Vivo Imaging System (IVIS) images once every week. Established hepatic tumors were evaluated with CT scan and then analyzed histologically. RESULTS:We found that splenic injection could consistently establish hepatic tumors. Non-invasive imaging showed that the splenic injection model had more consistent and stronger fluorescent intensity compared to the hepatic injection model. There were no significant differences in tumor growth between splenic injection with splenectomy and without splenectomy. The splenic injection established hepatic tumors diffusely throughout the liver, while the hepatic injection of tumor cells established a single localized tumor. Long-term monitoring of tumor development showed that tumor growth, tumor distribution in the liver, and overall survival depended on the number of tumor cells injected to the spleen. CONCLUSION:We established a new orthotopic hepatic metastatic xenograft mouse model by splenic injection of MUM cells. The growth of orthotopic hepatic tumors could be monitored with non-invasive IVIS imaging. Moreover, we evaluated the therapeutic effect of a MEK inhibitor by using this model. Our findings suggest that our new orthotopic liver metastatic mouse model may be useful for preclinical drug screening experiments and for the analysis of liver metastasis mechanisms.
| S-EPMC7240939 | biostudies-literature
Project description:Background: Uveal melanoma (UM) is an uncommon melanoma subtype with poor prognosis. Agents that have transformed the management of cutaneous melanoma have made minimal inroads in UM. Methods: We conducted a single-arm phase II study of pembrolizumab in patients with metastatic UM and performed bioinformatics analyses of publicly available datasets to characterize the activity of anti-PD-1 in this setting and to understand the mutational and immunologic profile of this disease. Results: A total of 5 patients received pembrolizumab in this study. Median overall survival was not reached, and median progression-free survival was 11.0 months. One patient experienced a complete response after one dose and 2 others experienced prolonged stable disease (20% response rate, 60% clinical benefit rate); 2 additional patients had rapidly progressing disease. Notably, the patients who benefited had either no liver metastases or small-volume disease, whereas patients with rapidly progressing disease had bulky liver involvement. We performed a bioinformatics analysis of The Cancer Genome Atlas for UM and confirmed a low mutation burden and low rates of T-cell inflammation. Note that the lack of T-cell inflammation strongly correlated with MYC pathway overexpression. Conclusions: Anti-PD-1-based therapy may cause clinical benefit in metastatic UM, seemingly more often in patients without bulky liver metastases. Lack of mutation burden and T-cell infiltration and MYC overexpression may be factors limiting therapeutic responses.ClinicalTrials.gov identifier: NCT02359851.
| S-EPMC8063157 | biostudies-literature
Project description:BackgroundUveal melanoma (UM), the most common adult intraocular tumor, is characterized by high malignancy and poor prognosis in advanced stages. Angiogenesis is critical for UM development, however, not only the role of vascular endothelial dysfunction in UM remains unknown, but also their analysis at the single-cell level has been lacking. A comprehensive analysis is essential to clarify the role of the endothelium in the development of UM.MethodsBy using single-cell RNA transcriptomics data of 11 cases of primary and liver metastasis UM, we analyzed the endothelial cell status. In addition, we analyzed and validated ECs in the in vitro model and collected clinical specimens. Subsequently, we explored the impact of endothelial dysfunction on UM cell migration and explored the mechanisms responsible for the endothelial cell abnormalities and the reasons for their peripheral effects.ResultsUM metastasis has a significantly higher percentage of vascular endothelial cells compared to in situ tumors, and endothelial cells in metastasis show significant senescence. Senescent endothelial cells in metastatic tumors showed significant Krüppel-like factor 4 (KLF4) upregulation, overexpression of KLF4 in normal endothelial cells induced senescence, and knockdown of KLF4 in senescent endothelium inhibited senescence, suggesting that KLF4 is a driver gene for endothelial senescence. KLF4-induced endothelial senescence drove tumor cell migration through a senescence-associated secretory phenotype (SASP), of which the most important component of the effector was CXCL12 (C-X-C motif chemokine ligand 12), and participated in the composition of the immunosuppressive microenvironment.ConclusionThis study provides an undesirable insight of senescent endothelial cells in promoting UM metastasis.
| S-EPMC11218175 | biostudies-literature
Project description:Uveal melanoma (UM) is a major intraocular cancer that is molecularly distinct from cutaneous melanoma. Approximately half of patients with UM eventually develop metastasis. The prognosis of metastatic UM is poor, with a median overall survival (OS) of less than a year. In this study, we sought to identify microRNAs (miRNAs) associated with metastasis and OS in UM. We analyzed the miRNA expression and clinical outcomes data from The Cancer Genome Atlas (TCGA) dataset for UM. Differential expression analyses were conducted for each miRNA with respect ever-development of metastasis. Multiple survival analyses were done, using the Cox proportional hazards model, to evaluate interactions between miRNA expression, metastasis, and OS. A total of 22 miRNAs (3 upregulated and 19 downregulated) were differentially expressed between patients with vs. without metastatic UM. These 22 miRNAs could be grouped into four clusters based on similarities in expression patterns. Of the 22 miRNAs differentially expressed with respect to metastasis, 21 were significantly associated with OS. The expression of multiple miRNAs was significantly associated with metastasis and overall survival in patients with UM. Further investigation of these miRNAs as biomarkers and/or therapeutic targets is warranted in the push to improve outcomes for patients with metastatic UM.
| S-EPMC7185062 | biostudies-literature