Integrative transcriptomic and machine learning analysis identifies CDH17 and HOXC13 as robust candidate prognostic biomarkers in uveal melanoma.

BACKGROUND

Uveal melanoma (UM), the most common form of ocular melanoma, represents poor prognosis, with approximately 50% of patients developing metastatic disease that significantly reduces survival rates. There is an crtitical need for accurate prognostic biomarkers to better stratify patients by risk and guide personalized treatment strategies.

METHODS

We employed an integrative, multi-step strategy to analyze UVM transcriptomic data, combining Cox proportional hazards survival analysis, stage-dependent differential expression, and a multi-layer perceptron (MLP) model to identify candidate prognostic genes. Receiver operating characteristic (ROC) analysis and Kaplan-Meier survival analysis were used to evaluate predictive performance, and external validation was performed using the GSE22138 cohort. Functional relevance was assessed through pan-cancer expression, DNA methylation, immune-infiltration, and protein expression analyses.

RESULTS

Integration of Cox regression, stage-dependent differential expression, and MLP modeling identified four robust prognostic biomarkers in UVM: CDH17, HOXC13, FABP5P7, and LINC02188. CDH17, a cadherin involved in cell-cell adhesion, promotes invasion and metastasis via integrin signaling and is oncogenic in gastrointestinal and melanoma tumors. HOXC13, a HOX transcription factor regulating proliferation, differentiation, and EMT, drives metastasis in skin melanoma and other cancers. FABP5P7, a pseudogene of the fatty acid-binding protein family, may act as a ceRNA influencing lipid metabolism and tumor progression. LINC02188, a long noncoding RNA, participates in ceRNA networks and has been linked to proliferation and migration in multiple cancers. Given the established oncogenic roles and protein-coding nature, CDH17 and HOXC13 were further prioritized for in-depth validation, including ROC analysis and pan-cancer characterization. ROC analysis demonstrated discriminative ability for patient outcomes (AUC = 0.76 for CDH17 and 0.65 for HOXC13), and metastasis-free survival trends were validated in the independent cohort. Pan-cancer analysis revealed elevated expression and frequent gene amplification in multiple tumor types, while immune-infiltration and methylation patterns suggested potential mechanistic roles. Both genes have established oncogenic functions in cutaneous melanoma, strengthening their biological plausibility in UM.

CONCLUSIONS

Our integrative approach identifies CDH17 and HOXC13 as biologically relevant, stage-associated prognostic biomarkers in UM. These findings provide a foundation for mechanistic studies and potential translational applications, including therapeutic targeting and risk-stratified patient management.