The tumor immune microenvironment, containing a variety of immune cells with both tumor-promoting and anti-tumoral functions, plays a significant role in tumor immune surveillance and immunological evasion. Characterizing the landscape of the tumor immune microenvironment at the single-cell level is crucial for both cancer diagnosis and treatment strategy design. While current efforts to develop single-cell tumor immune atlases have laid a foundation for understanding the complexity and heterogeneity of the tumor immune microenvironment, existing atlases vary in their data sources, integration and annotation strategies, and the number and definition of cell types, posing challenges in selection. We systematically benchmarked five single-cell tumor immune atlases, comprising two pan-cancer and three cancer-specific ones. We first assessed their similarities and distinct characteristics of major immune cell subpopulations, including T, NK, B, macrophage, and dendritic cells. Next, we utilized each atlas as a reference to perform supervised annotation of six single-cell immuno-transcriptomics datasets, two with expert manual labels and four without. We evaluated annotation performance based on agreement with manual labels, mapping success, accuracy, clusterability, annotatability, and stability. Notably, supervised annotations consistently outperformed unsupervised clustering in identifying cell states related to immunotherapy response. Our study provides insights into the characteristics and quality of existing atlases, demonstrating their utility in delivering harmonized annotations across datasets and uncovering crucial immune components associated with immunotherapy response. It also highlights key requirements and directions for the development of future atlases.
Yang et al. (Tue,) studied this question.