Uveal Melanoma Metastasis.
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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:The metastatic risk of uveal melanoma (UM) is defined by a limited number of molecular lesions, somatic mutations (SF3B1 and BAP1), and copy number alterations (CNA): monosomy of chromosome 3 (M3), chr8q gain (8q), chr6p gain (6p), yet the sequence of events is not clear. We analyzed data from three datasets (TCGA-UVM, GSE27831, GSE51880) with information regarding M3, 8q, 6p, SF3B1, and BAP1 status. We confirm that BAP1 mutations are always associated with M3 in high-risk patients. All other features (6p, 8q, M3, SF3B1 mutation) were present independently from each other. Chr8q gain was frequently associated with chr3 disomy. Hierarchical clustering of gene expression data of samples with different binary combinations of aggressivity factors shows that patients with 8q|M3, BAP1|M3 form one cluster enriched in samples that developed metastases. Patients with 6p combined with either 8q or SF3B1 are mainly represented in the other, low-risk cluster. Several gene expression events that show a non-significant association with outcome when considering single features become significant when analyzing combinations of risk features indicating additive action. The independence of risk factors is consistent with a random risk model of UM metastasis without an obligatory sequence.
| S-EPMC10648765 | 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: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:Uveal melanoma (UM) is a highly aggressive disease. There is an urgent need to develop the metastasis prediction markers of UM. This study aims to detect the key role of PALMD in UM metastasis. Transcriptome sequencing results of 2 sets of UM metastatic samples (GSE22138 and GSE156877) were downloaded from the Gene Expression Omnibus (GEO), and 18 overlapping differentially expressed genes were screened out, including PALMD. PALMD was significantly underexpressed in metastatic UM tissue. Low expression of PALMD was associated with poor prognosis in UM patients. The decreased expression of PALMD promoted the invasion and migration of 92-1 and Mel270 cells, while the high expression of PALMD inhibited the invasion and migration of UM cells. Furthermore, the levels of matrix metallopeptidase (MMP) 2 and MMP9 increased after transfection of siRNAs specifically targeting PALMD, whereas the levels of MMP2 and MMP9 were decreased after PALMD overexpression. However, PALMD did not affect the proliferation of UM cells. In addition, ZNF263 promoted the transcription of PALMD through the putative binding sequence using the JASPAR database, luciferase reporter gene analysis and chromatin immunoprecipitation assay. In summary, the expression of PALMD regulated by ZNF263 plays an important role in UM metastasis.
| S-EPMC9043551 | biostudies-literature
Project description:ImportanceAccuracy of the predicted metastasis-free survival (MFS) by a commercially available gene expression profiling (GEP) test is not known.ObjectiveTo compare the predicted MFS with the observed MFS in patients in this cohort and with those in published studies (published MFS, meta-analysis).Design, setting, and participantsThis cohort study included consecutive patients from the University of Iowa and Cleveland Clinic who were diagnosed with uveal melanoma who underwent prognostic fine-needle aspiration biopsy at the time of primary treatment. Patients were recruited from December 2012 to December 2020. The predicted MFS for patients was extracted from the GEP report. The observed MFS was defined as time to metastasis. Cox proportional hazards models were fit to identify tumor variables impacting MFS in patients with class 2 tumors. The overall estimate of the published MFS was obtained by performing meta-analysis of data from published series. Analysis took place in August 2021.Main outcomes and measuresMFS.ResultsThere were 92 patients from the University of Iowa and 255 patients from the Cleveland Clinic. The mean (SD) age at diagnosis was 59.4 (13.0) years. The median (IQR) follow-up interval was 38.0 (19.0-57.0) months. The observed MFS for patients with class 2 tumor in this cohort (3 years: 67% [95% CI, 59%-77%]; 5 years: 47% [95% CI, 37%-61%]) and in published studies (3 years: 62% [95% CI, 57%-66%]; 5 years: 40% [95% CI, 34%-46%]) were better than those predicted (50% and 28% for 3 and 5 years, respectively). Within patients with class 2 tumor, those with metastasis had larger tumors compared with nonmetastatic tumors (mean largest basal diameter difference, 1.7 [95% CI, 0.5-3.0] mm; P = .01; mean thickness ratio, 1.3 [95% CI, 1.04-1.5]; P = .01, respectively). An increasing tumor size was significantly associated with increased hazard ratio (1.16 [95% CI, 1.06-1.27]; P < .001) of metastasis.Conclusions and relevanceThese findings suggest the predicted MFS for metastatic tumors (class 2) appears to be worse than that observed here and reported by others. Incorporation of tumor size in the prediction model may enhance its accuracy. Adjuvant therapy trials may not be able to rely on predicted MFS to calculate efficacy with a high degree of confidence.
| S-EPMC9305597 | biostudies-literature
Project description:PurposeTo 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.MethodsUsing 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.ResultsThe 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).ConclusionsPRiMeUM 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: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