Abstract

Uveal melanoma (UM) is a malignant eye cancer that has a high mortality rate and is notoriously difficult to diagnose clinically. Identifying prognostic biomarkers and evaluating the tumor immune microenvironment for UM in order to improve diagnosis, treatment decisions and even overall survival for patients. Our study involved a thorough analysis of the transcriptome profiling in the TCGA-UVM project with the aim of identifying biomarkers as well as exploring the relationship between the tumor immune microenvironment and UM. We identified 32 differential expression genes and 25 RNAs related to the overall survival rate (OS) of UM patients. The fusion gene HSPE1-MOB4 was found to have the highest risk ratio, indicating it plays a key role in the survival rate of these individuals. Through similarity analysis of RNAs expression levels in UM, two subtypes were identified, and the survival rate for Type 1 was notably greater compared to Type 2. Using LASSO regression, we developed a risk model to identify five genes as possible biomarkers for diagnosis and prediction of the OS of patients with UM. Additionally, we proposed an association between the risk score and the fraction of immune cells present in the Tumor Immune Microenvironment (TIME). Our observations indicate a notable contrast in both immune score and clustering between the high-risk and low-risk groups. Our findings provide new insight into approaches for immunotherapy, as well as potential therapeutic targets for individual patients with UM.