LAUSR

Uveal melanoma (UM) is the most common primary intraocular malignant tumor in adults and almost fifty percent of patients subsequently develop systemic metastases usually involving the liver. The tumor microenvironment (TME) is crucial to the initiation and progression of tumors. In the present study, we comprehensively evaluated the TME of primary UM samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database by using several bioinformatic algorithms. The prognostic value of immune score and infiltrating immune cells in the TME were evaluated. Differentially expressed genes between the low- and high-immune score groups were also identified. The majority of tumor-infiltrating lymphocytes in UM have been determined to be activated CD8 + T cells. Therefore, weighted gene co-expression network analysis (WGCNA) was performed to identify the co-expression modules and genes significantly associated with the level of infiltrating CD8 + T cells in UM. Survival-related genes involved in the TME were identified by univariate Cox regression analysis. Furthermore, an eight-gene-based prognostic signature was established in the training dataset TCGA-UM via Lasso-penalized and multivariate Cox regression analyses. The predictive value of this signature was validated in two testing datasets. Besides, a nomogram was established to serve clinical practice. Moreover, hub genes involved in the infiltrating CD8 + T cells were identified and a potential targeted therapy for preventing metastasis of UM was proposed based on the results. In summary, our results provided a robust gene-based prognostic signature for predicting prognosis of UM patients and proposed a potential targeted therapy for preventing UM metastasis.