Integrative analysis of single-cell and transcriptome RNA sequencing to establish a NAT10-related signature for prognostic prediction of uveal melanoma.

Uveal melanoma (UVM), an intraocular malignant tumor originating from uveal melanocytes, not only induces blindness but also exhibits a high fatality risk. Despite the emergence of numerous local treatment modalities for UM in recent years, such as brachytherapy and proton beam radiotherapy, the prognosis of this disease remains suboptimal. RNA modification, which pertains to diverse chemical modifications on RNA molecules, plays a pivotal role in modulating gene expression and maintaining cell functions. N-acetyltransferase 10 (NAT10), the first reported mRNA acetylation regulator, can be activated in various cancers. However, the function of NAT10 in UVM remains elusive. In the present study, by integrating the gene expression information and clinical data from the TCGA database, we employed Weighted Gene Co-Expression Network Analysis (WGCNA) to screen genes related to NAT10 and subsequently constructed a model thereon. Through Cox proportional hazards model and Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, a signature of NAT10-related genes (NRGs) was generated. This prediction model was established based on four specific NRGs, namely TRIM47, ISG20, CEBPB, and ATG9A. Additionally, via Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA), we identified the disparities in its biological functions and signaling pathways and further investigated the relationship between immune infiltrations. In summary, the findings of this study may facilitate the discovery of novel therapeutic targets and prognostic biomarkers for UVM, thereby laying the foundation for the precision medicine of patients.