An agent-based model of monocyte differentiation into tumour-associated macrophages in chronic lymphocytic leukemia
Monocyte-derived macrophages help maintain tissue homeostasis and defend the organism against pathogens. In tumors, recent studies have uncovered complex macrophage populations, including tumor-associated macrophages, which support tumorigenesis through cancer hallmarks such as immunosuppression, an...
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Veröffentlicht in: | iScience 2023-06, Vol.26 (6), p.106897-106897, Article 106897 |
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Sprache: | eng |
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Zusammenfassung: | Monocyte-derived macrophages help maintain tissue homeostasis and defend the organism against pathogens. In tumors, recent studies have uncovered complex macrophage populations, including tumor-associated macrophages, which support tumorigenesis through cancer hallmarks such as immunosuppression, angiogenesis, or matrix remodeling. In the case of chronic lymphocytic leukemia, these macrophages are known as nurse-like cells (NLCs) and they protect leukemic cells from spontaneous apoptosis, contributing to their chemoresistance. We propose an agent-based model of monocyte differentiation into NLCs upon contact with leukemic B cells in vitro. We performed patient-specific model optimization using cultures of peripheral blood mononuclear cells from patients. Using our model, we were able to reproduce the temporal survival dynamics of cancer cells in a patient-specific manner and to identify patient groups related to distinct macrophage phenotypes. Our results show a potentially important role of phagocytosis in the polarization process of NLCs and in promoting cancer cells’ enhanced survival.
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•Patient blood-derived cultures track tumor-associated macrophage formation in vitro•Agent-based model predicts macrophage polarization and cancer cell survival dynamics•Patient-specific models identify two groups with distinct macrophage phenotypes•Phagocytosis efficiencies and cancer cell heterogeneity drive the observed dynamics
Health sciences; Immunology; Computational bioinformatics; Cancer |
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ISSN: | 2589-0042 2589-0042 |
DOI: | 10.1016/j.isci.2023.106897 |