Characterisation of macrophage infiltration into solid tumours via image analysis and computational modelling

Macrophages are innate immune cells that play a key role in conditions as diverse as wound healing, atherosclerosis and cancer. In cancer, macrophages may be characterised as anti-tumour, promoting a wider immune response and phagocytosing tumour cells, or as pro-tumour, suppressing the immune response and promoting blood vessel growth and metastasis. The spatial distribution of macrophages inside a tumour correlates with patient prognosis and treatment response, and is hypothesised to be predictive of macrophage phenotype. In this thesis, we use a combination of mathematical modelling and image analysis to characterise these distribution patterns and understand the mechanisms by which macrophages may infiltrate solid tumours.
We have developed an image analysis pipeline for the automated analysis of whole slide histology images, a rich source of spatial data for the investigation of immune cell distributions in vivo. Our pipeline automatically identifies macrophages and other cell types using a combination of superpixellation and Support Vector Machines (SVMs), and we develop summary statistics which characterise distinct macrophage distributions across different tumour indications based on detected cell locations. We validate our pipeline against real data and benchmark it against human pathologists. We then demonstrate its flexibility and robustness in a range of applications across a variety of datasets.
We investigate the observed distributions of macrophages further by using the Chaste (Cancer, Heart and Soft Tissue Environment) modelling framework to develop a new agent-based model of macrophage infiltration into solid tumours. We first use our model to simulate in vitro experiments in which inert microbeads infiltrate into multicellular tumour spheroids (MCTSs). This study enables us to investigate the role of passive infiltration caused by spatial variation in cell proliferation and death rates across the MCTS. The interplay between cell proliferation and death drives an advective flow from nutrient-rich, proliferative, regions towards necrotic regions. Our agent-based framework reproduces results from previous continuum models of this process and provides new insight into the observed infiltration patterns that cannot be obtained without resolving the trajectories of individual particles in an agent-based framework. We subsequently extend this model to describe macrophage infiltration into MCTSs via a combination of passive infiltration and chemotaxis in response to colony stimulating factor-1 (CSF-1). This chemoattractant, which is expressed by hypoxic tumour cells, is implicated in metastasis and is a target for immunotherapy treatments currently in Phase I trials at Roche. Finally, we discuss methods of integrating whole slide imaging with our agent-based modelling approaches and compare simulated macrophage distributions with those from in vivo images analysed using our imaging pipeline.

Keywords: Digital Pathology
Mathematics
Mathematical Immunology
Agent-based modelling
Mathematical Oncology
Mathematical Biology
Spatial Statistics
Advisor: Byrne, H
Waters, S
Grau, V
Mech, F
Quaiser, T