1. Academic Validation
  2. Integrating multiple key molecules in uveal melanoma to uncover metastatic and immune microenvironment-related gene signatures

Integrating multiple key molecules in uveal melanoma to uncover metastatic and immune microenvironment-related gene signatures

  • Int J Ophthalmol. 2026 Jan 18;19(1):11-24. doi: 10.18240/ijo.2026.01.02.
Yi-Ming Guo 1 Zhan-Pei Bai 2 Jia-Qi Wang 1 Juan Huang 1 Jun-Han Wei 1 Yi-Jin Han 1 Yang Liu 3 Lu Ye 1
Affiliations

Affiliations

  • 1 Shaanxi Eye Hospital, Xi'an People's Hospital (Xi'an Fourth Hospital), Affiliated People's Hospital of Northwest University, Xi'an 710004, Shaanxi Province, China.
  • 2 The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou Medical University, Wenzhou 325000, Zhejiang Province, China.
  • 3 People's Hospital of Ningxia Hui Autonomous Region, Ningxia Medical University, Ningxia Clinical Research Institute, Yinchuan 750000, Ningxia Hui Autonomous Region, China.
Abstract

Aim: To identify metastasis-associated prognostic genes and construct a robust molecular signature for survival prediction in uveal melanoma (UVM) patients.

Methods: Transcriptomic data and clinical information from 80 UVM patients in the Cancer Genome Atlas (TCGA)-UVM cohort and an external Gene Expression Omnibus (GEO) microarray dataset (GSE73652; 8 non-metastatic vs 5 metastatic cases) were analyzed to identify differentially expressed genes (DEGs). Functional enrichment, protein-protein interaction (PPI) network construction, and survival analyses identified seven metastasis- and prognosis-related genes. Their expression was further examined using public single-cell RNA-seq data (GSE139829; 11 tumors). Experimental validation was performed in UVM cell lines (92.1, OMM1, MEL270) and adult retinal pigment epithelial (ARPE-19) cells using quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting to confirm transcriptomic trends. A LASSO COX model was applied to construct a metastasis-related risk Score signature. Tumor immune microenvironment characteristics were evaluated via single-sample gene set enrichment analysis (ssGSEA) and ESTIMATE. Somatic mutation and copy number variation (CNV) profiles were also examined.

Results: Seven key genes (UBE2T, KIF20A, DLGAP5, KLC3, TPX2, UBE2C, AURKA) were significantly associated with overall survival and used to construct a metastasis-related riskScore signature, which effectively stratified patients into high- and low-risk groups and served as an independent prognostic factor. qRT-PCR and Western blot results confirmed that the expression levels of selected key genes in UVM cell lines showed significant differences compared to ARPE-19 cells, which were largely consistent with the transcriptomic findings. The high-risk group exhibited reduced immune infiltration and stromal activity. Single-cell analysis revealed these genes were predominantly expressed in a tumor cell cluster characterized by BAP1 loss and high metastatic potential. Mutation and CNV analyses further supported the relevance of these genes to UVM progression.

Conclusion: This study establishes and validates a seven-gene signature associated with metastasis and prognosis in UVM. The findings provide a framework for understanding molecular determinants of tumor progression and immune microenvironment alterations, and may offer guidance for future mechanistic studies and therapeutic exploration.

Keywords

RNA-seq; immune analysis; single-cell RNA; survival analysis; uveal melanoma.

Figures