Abstract 1063: CellMap: a comprehensive human single cell gene expression reference for automated cell annotation and cancer cell-of-origin analysis

作者：Yuping Zhang, Gabriel Cruz, Hanbyul Cho, Chandan Kumar‐Sinha, Rahul Mannan, Chen Jin, Xuhong Cao, Saravana M. Dhanasekaran, Arul M. Chinnaiyan · 发表于：Cancer Research · 年份：2025 · DOI：10.1158/1538-7445.am2025-1063 · 被引用次数：1 · 研究领域：Single-cell and spatial transcriptomics、Gene expression and cancer classification

Abstract In single-cell transcriptomic analysis, accurate cell type annotation forms the essential basis for all downstream analysis and data interpretation. While time consuming manual annotation requires extensive prior knowledge, available automated cell annotation tools lack a unified, curated human cell reference to ensure successful identification of all cell types present in any given dataset. To fill in the gap we create “CellMap” a comprehensive single cell gene expression reference database of known cell types across most human tissues by compiling, curating and integrating single cell datasets from multiple sources including Human Protein Atlas, Tabula Sapiens, ArrayExpress and GEO. CellMap contains 151 different celltypes/states including 94 epithelial, 31 brain, 4 from soft tissues, 8 stromal and 15 major immune celltypes from 42 human tissues. Projecting pseudo-bulk profiles of the 151 celltypes into 2-dimensional UMAP revealed major clusters of cells from the nervous system, respiratory system, gastrointestinal tract, proximal digestive system, female tissues and endocrine tissues. Immune cells and stromal cells are generally clustered together regardless of their tissue origin. We also curated about 200 immune cell phenotypes from the ImmGen database for fine-tuning annotation of immune cell subpopulations. Importantly by combining CellMap and the SingleR algorithm, we successfully identified the cell lineage of the tumor and minor cell types originated from t...