Department of Ophthalmology, Shengjing Hospital Affiliated to China Medical University, Shenyang, Liaoning, China.
Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia.
Aging (Albany NY). 2023 Oct 13;15(20):11201-11216. doi: 10.18632/aging.205122.
Uveal melanoma (UVM) remains the leading intraocular malignancy in adults, with a poor prognosis for those with metastatic disease. Tryptophan metabolism plays a pivotal role in influencing cancerous properties and modifying the tumor's immune microenvironment. In this study, we explore the relationship between tryptophan metabolism-related gene (TRMG) expression and the various features of UVM, including prognosis and tumor microenvironment. Our analysis included 143 patient samples sourced from public databases. Using K-means clustering, we categorized UVM patients into two distinct clusters. Further, we developed a prognostic model based on five essential genes, effectively distinguishing between low-risk and high-risk patients. This distinction underscores the importance of TRMGs in UVM prognostication. Combining TRMG data with gender to create nomograms demonstrated exceptional accuracy in predicting UVM patient outcomes. Moreover, our analysis reveals correlations between risk assessments and immune cell infiltrations. Notably, the low-risk group displayed a heightened potential response to immune checkpoint inhibitors. In conclusion, our findings underscore the dynamic relationship between TRMG expression and various UVM characteristics, presenting a novel prognostic framework centered on TRMGs. The deep connection between TRMGs and UVM's tumor immune microenvironment emphasizes the crucial role of tryptophan metabolism in shaping the immune landscape. Such understanding paves the way for designing targeted immunotherapy strategies for UVM patients.
葡萄膜黑色素瘤（UVM）仍然是成年人眼内最常见的恶性肿瘤，对于转移性疾病患者预后较差。色氨酸代谢在影响癌症特性和改变肿瘤免疫微环境方面起着关键作用。在这项研究中，我们探讨了色氨酸代谢相关基因（TRMG）表达与 UVM 的各种特征之间的关系，包括预后和肿瘤微环境。我们的分析包括了来自公共数据库的 143 名患者样本。使用 K-means 聚类，我们将 UVM 患者分为两个不同的聚类。此外，我们基于五个关键基因开发了一个预后模型，能够有效区分低风险和高风险患者。这种区分突出了 TRMG 在 UVM 预后预测中的重要性。将 TRMG 数据与性别相结合创建列线图，在预测 UVM 患者结局方面表现出了优异的准确性。此外，我们的分析揭示了风险评估与免疫细胞浸润之间的相关性。值得注意的是，低风险组显示出对免疫检查点抑制剂更高的潜在反应能力。总之，我们的研究结果强调了 TRMG 表达与 UVM 各种特征之间的动态关系，提出了一个以 TRMG 为中心的新的预后框架。TRMGs 与 UVM 肿瘤免疫微环境之间的紧密联系强调了色氨酸代谢在塑造免疫景观中的关键作用。这种理解为设计针对 UVM 患者的靶向免疫治疗策略铺平了道路。
