A cellular map of human body based on single-cell deconvolution

AbstractA high-resolution map of human tissues and cancers is pivotal to understanding the human immune system and disentangling tumor immune evasion mechanisms, but is still missing now. Here, we apply a single-cell deconvolution strategy and construct a high-resolution cell map of human body based on the big data of Tabula Sapiens, CCLE, GTEx and TCGA across 54 healthy tissue sites and 33 cancer types. The map reveals organ-specific distributions of >1,000 immune cell types/states and ~100 cancerous cell states, and thus enables in silico charting the body distribution of various cell types/states in a user-defined manner akin to cell sorting. Through comparisons of 11,057 tumor-derived samples with 17,382 healthy samples, the map comprehensively depicts cell type-specific immunoediting patterns for different cancers. Additionally, we identified immunotherapy-related immune cell types and genes by in silico cell sorting. The map is also feasible to systematically interrogation of the organ-specific impacts of age and sex on cellular compositions. This map provides an important foundation dataset and deepens our understanding of human immune system from a holistic perspective. Here, we provide an in-house web program bulit by Django for visualizing the the distribution of any intersested cell states that express user-defined gene sets across various healthy or primary tumor tissues as well as other correlation analysis. We also provide windows and linux versions of this web tool for all users.