Department of Ophthalmology, Affiliated Hospital of Weifang Medical University, Weifang, China.
Front Immunol. 2022 Mar 2;13:848455. doi: 10.3389/fimmu.2022.848455. eCollection 2022.
Numerous studies indicated that tumor-infiltrated immune cells (TIC) in the microenvironment are substantially linked to immunotherapy response and cancer prognosis. However, systematic studies of infiltrated immune cell characterization in uveal melanoma (UM) for prognosis and immune checkpoint blockade therapy are lacking.
UM datasets were extracted from open access resources (TCGA and GEO databases). The tumor-infiltrated immune cells in the microenvironment were decoded by using the CIBERSORT algorithm, which was further applied to classify UM patients into subgroups using an unsupervised clustering method. The Boruta algorithm and principal component analysis were used to calculate the TIC scores for UM patients. Kaplan-Meier curves were plotted to prove the prognostic value of TIC scores. Besides, the correlations of the TIC score with clinical features, mutated characteristics, and the immune therapeutic response were subsequently investigated.
As a result, we defined three subtypes among 171 UM patients according to the TIC profiles and then calculated the TIC score to characterize the immune patterns for all patients. We discovered that high-TIC score patients with low BAP1 and high EIF1AX mutations have a better prognosis than low-TIC score patients. Activation of immune inflammatory response and increase in immune checkpoint-related genes in high-TIC score patients may account for good prognosis and immunotherapy response. Three melanoma cohorts received immunotherapy, proving that high-TIC score patients have substantial clinical and immune therapeutic improvements. Besides, several potential therapeutic agents were identified in the low-TIC score group.
Our study afforded a comprehensive view of infiltrated immune cell characterization to elucidate different immune patterns of UM. We also established a robust TIC-score signature, which may work as a prognostic biomarker and immune therapeutic predictor.
大量研究表明，微环境中的肿瘤浸润免疫细胞（TIC）与免疫治疗反应和癌症预后密切相关。然而，针对葡萄膜黑色素瘤（UM）浸润免疫细胞特征进行预后和免疫检查点阻断治疗的系统研究仍然缺乏。
从公开访问资源（TCGA 和 GEO 数据库）中提取 UM 数据集。使用 CIBERSORT 算法对微环境中的肿瘤浸润免疫细胞进行解码，进一步应用无监督聚类方法将 UM 患者分为亚组。使用 Boruta 算法和主成分分析计算 UM 患者的 TIC 分数。绘制 Kaplan-Meier 曲线以证明 TIC 分数的预后价值。此外，还研究了 TIC 分数与临床特征、突变特征和免疫治疗反应的相关性。
我们根据 TIC 图谱在 171 名 UM 患者中定义了三种亚型，然后计算 TIC 分数来描述所有患者的免疫模式。我们发现，BAP1 低表达和 EIF1AX 高突变的高 TIC 评分患者比低 TIC 评分患者具有更好的预后。高 TIC 评分患者中免疫炎症反应的激活和免疫检查点相关基因的增加可能是良好预后和免疫治疗反应的原因。三个黑色素瘤队列接受了免疫治疗，证明高 TIC 评分患者具有显著的临床和免疫治疗改善。此外，在低 TIC 评分组中还确定了几种潜在的治疗药物。
本研究全面分析了浸润免疫细胞的特征，阐明了 UM 的不同免疫模式。我们还建立了一个稳健的 TIC 评分特征，可作为预后生物标志物和免疫治疗预测因子。
