Ocular melanoma, including uveal melanoma (UM) and conjunctival melanoma (CM), is the most common ocular cancer among adults with a high rate of recurrence and poor prognosis. Loss of epigenetic homeostasis disturbed gene expression patterns, resulting in oncogenesis. Herein, we comprehensively analyzed the DNA methylation, transcriptome profiles, and corresponding clinical information of UM patients through multiple machine-learning algorithms, finding that a methylation-driven gene RBMS1 was correlated with poor clinical outcomes of UM patients. RNA-seq and single-cell RNA-seq analyses revealed that RBMS1 reflected diverse tumor microenvironments, where high RBMS1 expression marked an immune active TME. Furthermore, we found that tumor cells were identified to have the higher communication probability in RBMS1 + state. The functional enrichment analysis revealed that RBMS1 was associated with pigment granule and melanosome, participating in cell proliferation as well as apoptotic signaling pathway. Biological experiments were performed and demonstrated that the silencing of RBMS1 inhibited ocular melanoma proliferation and promoted apoptosis. Our study highlighted that RBMS1 reflects a distinct microenvironment and promotes tumor progression in ocular melanoma, contributing to the therapeutic customization and clinical decision-making.
Keyphrases
- rna seq
- single cell
- poor prognosis
- dna methylation
- gene expression
- machine learning
- end stage renal disease
- signaling pathway
- long non coding rna
- cell proliferation
- genome wide
- ejection fraction
- newly diagnosed
- chronic kidney disease
- skin cancer
- high throughput
- oxidative stress
- cell death
- basal cell carcinoma
- peritoneal dialysis
- healthcare
- prognostic factors
- artificial intelligence
- patient reported outcomes
- deep learning
- optic nerve
- cell cycle
- squamous cell