bioRxivImmunologyPreprint
Spatial immune hubs defined by conserved activated dendritic cells are remodeled by immunotherapy
Tomoyuki MinowaiD, Sunita KeshariiD, Shan HeiD, Akata SahaiD, Alexander S. ShavkunoviD, Josue Estiven PinedaiD, Yao Yu YeoiD, Bokai ZhuiD, Vakul MohantyiD, Sonali JindaliD, Ken CheniD, Kenneth H. HuiD, Linghua WangiD, Garry P. NolaniD, Stephanie S. WatowichiD, Matthew M. GubiniD
Abstract
Dendritic cells (DCs) orchestrate anti-tumor immune responses, yet the full extent of their phenotypic diversity, and spatial dynamics within the tumor microenvironment (TME) remains incompletely understood. Here, we constructed an integrated atlas of tumor-infiltrating DCs by harmonizing single-cell transcriptomic data from 12 murine tumor studies and 28 published human cancer datasets, together with newly generated single-cell-resolved multiplexed tissue imaging across immunotherapy conditions in a murine model. We noted conserved transcriptional states across species, including canonical conventional type 1 DCs (cDC1s), diverse type 2 DC (cDC2) subpopulations, and two activation states characterized by CCR7 expression (CCR7+ DCs) or interferon-stimulated gene expression (ISG DCs). Spatial transcriptomics analyses from human TMEs revealed that CCR7+ DCs and ISG DCs reside in distinct T cell-enriched regions that are embedded within distinct signaling environments. High-dimensional multiplexed proteomic imaging demonstrated that these DC-T cell niches undergo divergent remodeling across multiple immunotherapy conditions. Notably, this spatial reorganization occurred despite minimal detectable changes in DC transcriptional states. This study delineates conserved DC activation states and their spatial organization within tumors and captures the therapy-dependent remodeling, providing a framework for studying therapy-associated remodeling of DC immune programs in cancer.
- organism: mouse
- organism: human
- assay: scRNA-seq
- assay: spatial transcriptomics
- assay: proteomics
- research focus: cell type annotation
- research focus: spatial domain detection
- research focus: cell-cell communication
- approach: statistical model
- Citations
- 0
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