Uveal melanoma (UM) is the most common primary adult intraocular malignancy. This rare but devastating cancer causes vision loss and confers a poor survival rate due to distant metastases. Identifying clinical and molecular features that portend a metastatic risk is an important part of UM workup and prognostication. Current UM prognostication tools are based on determining the tumor size, gene expression profile, and chromosomal rearrangements. Although we can predict the risk of metastasis fairly accurately, we cannot obtain preclinical evidence of metastasis or identify biomarkers that might form the basis of targeted therapy. These gaps in UM research might be addressed by single-cell research. Indeed, single-cell technologies are being increasingly used to identify circulating tumor cells and profile transcriptomic signatures in single, drug-resistant tumor cells. Such advances have led to the identification of suitable biomarkers for targeted treatment. Here, we review the approaches used in cutaneous melanomas and other cancers to isolate single cells and profile them at the transcriptomic and/or genomic level. We discuss how these approaches might enhance our current approach to UM management and review the emerging data from single-cell analyses in UM.

葡萄膜黑色素瘤（UM）是最常见的原发性成人眼内恶性肿瘤。这种罕见但具有毁灭性的癌症会导致视力丧失，并因远处转移而导致存活率较低。识别预示转移风险的临床和分子特征是 UM 检查和预测的重要组成部分。目前的 UM 预测工具基于确定肿瘤大小、基因表达谱和染色体重排。尽管我们可以相当准确地预测转移风险，但我们无法获得转移的临床前证据或识别可能构成靶向治疗基础的生物标志物。密歇根大学研究中的这些差距可能可以通过单细胞研究来解决。事实上，单细胞技术越来越多地用于识别循环肿瘤细胞并分析单个耐药肿瘤细胞的转录组特征。这些进展导致了针对靶向治疗的合适生物标志物的鉴定。在这里，我们回顾了在皮肤黑色素瘤和其他癌症中分离单细胞并在转录组和/或基因组水平上分析它们的方法。我们讨论这些方法如何增强我们当前的 UM 管理方法，并回顾来自 UM 单细胞分析的新数据。