bioRxivCancer BiologyPreprint
The Immune Landscape of Tumor-Associated Macrophage Reprogramming
Florent DuvaliD, João LourençoiD, Mehdi HichamiD, Gaël BoiviniD, Alan GuichardiD, Celine Wyser-Rmili, Nadine FournieriD, Michele De PalmaiD, Nahal MansouriiD
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Abstract
Tumor-associated macrophages (TAMs) generally acquire immunosuppressive and tumor-promoting phenotypes, which may contribute to tumor resistance to immunotherapy. We previously showed that suppression of microRNA activity through genetic Dicer1 inactivation rewires TAMs transcriptomes and prompts their immunostimulatory activation. This phenotypic switch enhanced recruitment and activation of CD8+ cytotoxic T cells (CTLs) and improved the efficacy of immunotherapy in mouse cancer models. Here, we performed single-cell RNA sequencing of whole tumors grown in either wild-type mice or mice with macrophage-specific Dicer1 deletion. The analysis of multiple cell populations, including several discrete monocyte and macrophage subsets, indicated broad and convergent immunostimulatory programming of the tumor microenvironment, which was dependent on CTL-derived interferon-gamma (IFN{gamma}), in mice with DICER-deficient macrophages. Intriguingly, dynamic inferences on monocyte/macrophage ontogeny and differentiation by pseudotime analysis revealed trajectories associated with progression into cell cycle, monocyte-to-macrophage differentiation, and transition from an immunostimulatory to an immunosuppressive phenotype in tumors with DICER-proficient macrophages. Dicer1 deficiency interfered with this trajectory and stalled TAMs at an intermediate state between immature monocytes and macrophages with T cell-stimulatory capacity, thereby impeding immunosuppressive TAM development. This translated into enhanced response to antiangiogenic immunotherapy in an immunotherapy-resistant model of non-small cell lung cancer. Cycling/M2-like macrophages were conserved in human melanoma and hepatocellular carcinoma and should represent a more promising therapeutic target than the bulk of TAMs.
- organism: mouse
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: trajectory inference
- approach: deep learning
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