Single-cell characterization of macrophages in uveal melanoma uncovers transcriptionally heterogeneous subsets conferring poor prognosis and aggressive behavior

Uveal melanoma (UM) is the most frequent primary intraocular malignancy with high metastatic potential and poor prognosis. Macrophages represent one of the most abundant infiltrating immune cells with diverse functions in cancers. However, the cellular heterogeneity and functional diversity of macrophages in UM remain largely unexplored. In this study, we analyzed 63,264 single-cell transcriptomes from 11 UM patients and identified four transcriptionally distinct macrophage subsets (termed M phi-C1 to M phi-C4). Among them, we found that M phi-C4 exhibited relatively low expression of both M1 and M2 signature genes, loss of inflammatory pathways and antigen presentation, instead demonstrating enhanced signaling for proliferation, mitochondrial functions and metabolism. We quantified the infiltration abundance of M phi-C4 from single-cell and bulk transcriptomes across five cohorts and found that increased M phi-C4 infiltration was relevant to aggressive behaviors and may serve as an independent prognostic indicator for poor outcomes. We propose a novel subtyping scheme based on macrophages by integrating the transcriptional signatures of M phi-C4 and machine learning to stratify patients into M phi-C4-enriched or M phi-C4-depleted subtypes. These two subtypes showed significantly different clinical outcomes and were validated through bulk RNA sequencing and immunofluorescence assays in both public multicenter cohorts and our in-house cohort. Following further translational investigation, our findings highlight a potential therapeutic strategy of targeting macrophage subsets to control metastatic disease and consistently improve the outcome of patients with UM. A recent study utilized single-cell transcriptome data to explore the cellular heterogeneity of macrophages within the uveal melanoma (UM) tumor microenvironment, revealing four distinct macrophage subsets. One subset, M phi-C4, was found to be associated with aggressive tumor behavior and poor survival outcomes. The study also developed a machine-learning-based subtyping system to classify UM subtypes and predict prognosis based on M phi-C4-specific core metagenes. This research deepens our understanding of cellular heterogeneity in UM and highlights the potential therapeutic benefits of targeting macrophages in UM treatment.

Automated summary

A recent study utilized single-cell transcriptome data to explore the cellular heterogeneity of macrophages within the uveal melanoma (UM) tumor microenvironment, revealing four distinct macrophage subsets. One subset, M phi-C4, was found to be associated with aggressive tumor behavior and poor survival outcomes. The study also developed a machine-learning-based subtyping system to classify UM subtypes and predict prognosis based on M phi-C4-specific core metagenes. This research deepens our understanding of cellular heterogeneity in UM and highlights the potential therapeutic benefits of targeting macrophages in UM treatment.