Biological interactions between cell populations in heterogeneous tumour spheroids

When radiotherapy is prescribed in the clinic, the tumour is assumed to be homogeneous. However, tumours are composed of many distinct cell populations that interact with each other and their environment. It is unclear how this heterogeneity affects tumour growth and response to treatment. Additionally, much of cancer research considers tumour cells in isolation, neglecting the context in which the disease develops. Experimental approaches alone are not suficient to understand the complexity of the interactions occurring in the cancer ecosystem. In this thesis we use a multidisciplinary approach combining in vitro experiments, mathematical modelling and parameter inference methods to explore the impact of cellular heterogeneity on tumour growth and radiation response. Our objectives are: i) to determine if intratumour heterogeneity affects bulk radiation response; ii) to characterise the interactions between co-cultured cell populations; iii) to determine how interactions between different cell populations are affected by radiation. In the first part of the thesis we design a 3D experimental model in which we co-culture pairs of prostate cancer cell lines with distinct phenotypes and derived from the same tumours. We use the experimental model to study the growth and radiation response of heterogeneous tumours (Chapter 2). We then use nonlinear regression and approximate Bayesian computation algorithm to fit the Verhulst logistic and Lotka-Volterra mathematical models to our data to characterise how the cell populations interact when co-cultured in tumour spheroids before and after exposure to ionising radiation (Chapters 3 and 4). Our third piece of work involves the development of a cellular automaton model of avascular tumour growth to allow for spatial variation within the tumour. The cellular automaton model is simulated for a range of parameter values and fitted to the logistic model to determine the relationship between microscale and macroscale parameters describing tumour growth and to study the dynamics between co-cultured cell populations. The work presented in this thesis highlights the benefits of multidisciplinary research for understanding cancer heterogeneity. We show that intratumour heterogeneity affects bulk tumour growth and radiation response. We demonstrate how complex biological interactions can be identified and quantified via mathematical modelling and inference. We also show how experimental design studies can streamline biological experiments. Taken together, this work presents a framework for uncovering the effect of cellular heterogeneity on tumour growth with a particular emphasis on interclonal interactions.