Ephrin Receptors and Ephrin Ligands in Uveal Melanoma: A Big Data Analysis Using Web Resources
Open Access
- 31 December 2025
- journal article
- research article
- Published by MDPI AG in International Journal of Molecular Sciences
- Vol. 27 (1) , 442
Abstract
Uveal melanoma (UVM) is a rare cancer that represents the second most common melanoma (after the cutaneous) and the most common primary intraocular malignancy in adults. Despite recent advances in the understanding of UVM pathogenesis, its prognosis remains unchanged, with half of patients dying because of liver metastasis. Erythropoietin-producing human hepatocellular receptors (EPHs) constitute the largest known family of tyrosine receptors, and, along with their ligands, EFNs, regulate key physiological processes and are implicated in cancer pathogenesis. In this study, we used open-access web bioinformatics platforms to explore and analyze big datasets provided by The Cancer Genome Atlas (TCGA) UVM cohort of patients. We profiled the genomic alterations present in a subset of UVM patients, highlighting a likely pathogenic deep deletion of EPHA7. Survival analysis showed that overexpression levels of EPHA4, EPHA5, EPHA8, EPHB2, and EFNB2 are significantly associated with poor overall survival. Additionally, high expression levels of EPHA4, EPHA5, EPHA7, EPHA8, EPHB2, EFNA2, and EFNB2 correlate with reduced progression-free interval and disease-free survival. Finally, we identified the EPHs (EPHA2, EPHA4, EPHA8, and EPHB4) and EFNs (EFNA1, EFNA3, EFNA4, and EFNB2) that are significantly overexpressed in the aggressive epithelioid histological subtype and revealed that the majority of EPHs/EFNs are overexpressed in metastatic disease. In conclusion, our results highlight that a subset of EPHs and EFNs may be associated with worse clinical outcomes (EPHA4, EPHA5, EPHA7, EPHA8, EPHB2, EFNA2, and EFNB2), and an aggressive histological subtype (EPHA2, EPHA4, EPHA8, EPHB4, EFNA1, EFNA3, EFNA4, and EFNB2). The potential correlation of these genes with clinicopathological parameters of UVM need to be evaluated and validated with bioinformatic and experimental approaches in well-characterized cohorts of UVM patients.Keywords
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