Monocyte-derived macrophages help maintain tissue homeostasis and defend the organism against pathogens. In tumours, recent studies have uncovered complex macrophage populations, including tumour-associated macrophages, which support tumorigenesis through cancer hallmarks such as immunosuppression, angiogenesis or matrix remodelling. In the case of chronic lymphocytic leukaemia, these macrophages are known as nurse-like cells and they protect leukemic cells from spontaneous apoptosis contributing to their chemoresistance. We propose an agent-based model of monocyte differentiation into nurse-like cells upon contact with leukemic B cells in vitro. We performed patient-specific model calibrations using cultures of peripheral blood mononuclear cells from patients. Using our model, we were able to reproduce 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 nurse-like cells and in promoting cancer cells' enhanced survival

About the speaker

Dr Vera Pancaldi was trained as a physicist and soon found her way in systems and computational biology. Since 2018 she leads a computational biology team at the Cancer Research Center of Toulouse (CRCT) working on modelling cancer and its interactions with the immune system.       
Her main current focus is understanding the relationship between genome architecture and heterogeneity at various levels and relating heterogeneity in the phenotype of tumour infiltrating immune cells to patient's response to immunotherapy.

Who is this course for?

This webinar is part of PerMedCoE webinar series and is open for researchers in the life sciences, biomedical scientists and anyone interested in immuno-oncology as well as in simulation of intercellular interactions.

The goal of PerMedCoE is to provide an efficient and sustainable entry point to the HPC/Exascale-upgraded methodology to translate omics analyses into actionable models of cellular functions of medical relevance.

Outcomes

By the end of this webinar, you will be able to:

• Describe the challenges of data-driven modelling
• Cite simple models of immuno-oncology dynamics in simplified experimental systems

This webinar took place on 25 January 2023. Please click the 'Watch video' button to view the recording