Emma Leschiera

@article{leschiera_2660,

title = {An individual-based model to explore the impact of psychological stress on immune infiltration into tumour spheroids},

author = {Emma Leschiera and Gheed Al-Hity and Melanie Flint and Chandrasekhar Venkataraman and Tommaso Lorenzi and Luis Almeida and Chloé Audebert},

url = {10.1088/1478-3975/ad221a},

year  = {2024},

date = {2024-02-01},

journal = {Physical Biology},

volume = {2},

pages = {5;21},

abstract = {In recent in vitro experiments on co-culture between breast tumour spheroids and activated immune cells, it was observed that the introduction of the stress hormone cortisol

resulted in a decreased immune cell infiltration into the spheroids. Moreover, the presence of cortisol deregulated the normal levels of the pro- and anti-inflammatory cytokines IFN-?

and IL-10. We present an individual-based model to explore the interaction dynamics between tumour and immune cells under psychological stress conditions. With our model,

we explore the processes underlying the emergence of different levels of immune infiltration,

with particular focus on the biological mechanisms regulated by IFN-? and IL-10. The set-up of numerical simulations is defined to mimic the scenarios considered in the experimental

study. Similarly to the experimental quantitative analysis, we compute a score that quantifies the level of immune cell infiltration into the tumour. The results of numerical simulations indicate that the motility of immune cells, their capability to infiltrate through

tumour cells, their growth rate and the interplay between these cell parameters can affect the level of immune cell infiltration in different ways. Ultimately, numerical simulations

of this model support a deeper understanding of the impact of biological stress-induced mechanisms on immune infiltration.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{almeida_2658,

title = {Discrete and continuum models for the coevolutionary dynamics between CD8+ cytotoxic T lymphocytes and tumour cells},

author = {Luis Almeida and Chloé Audebert and Emma Leschiera and Tommaso Lorenzi},

url = {https://academic.oup.com/imammb/article-abstract/40/2/141/6873764},

year  = {2023},

date = {2023-06-01},

journal = {Mathematical Medicine And Biology-A Journal Of The Ima},

volume = {40},

number = {2},

pages = {141-174},

abstract = {We present an individual-based model for the coevolutionary dynamics between CD8+ cytotoxic T lymphocytes (CTLs) and tumour cells. In this model, every cell is viewed as an individual agent whose phenotypic state is modelled by a discrete variable. For tumour cells, this variable represents a parameterization of the antigen expression profiles, while for CTLs it represents a parameterization of the target antigens of T-cell receptors (TCRs). We formally derive the deterministic continuum limit of this individual-based model, which comprises a non-local partial differential equation for the phenotype distribution of tumour cells coupled with an integro-differential equation for the phenotype distribution of CTLs. The biologically relevant homogeneous steady-state solutions of the continuum model equations are found. The linear-stability analysis of these steady-state solutions is then carried out in order to identify possible conditions on the model parameters that may lead to different outcomes of immune competition and to the emergence of patterns of phenotypic coevolution between tumour cells and CTLs. We report on computational results of the individual-based model, and show that there is a good agreement between them and analytical and numerical results of the continuum model. These results shed light on the way in which different parameters affect the coevolutionary dynamics between tumour cells and CTLs. Moreover, they support the idea that TCR-tumour antigen binding affinity may be a good intervention target for immunotherapy and offer a theoretical basis for the development of anti-cancer therapy aiming at engineering TCRs so as to shape their affinity for cancer targets.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{almeida_2659,

title = {A Hybrid Discrete-Continuum Modelling Approach to Explore the Impact of T-Cell Infiltration on Anti-tumour Immune Response},

author = {Luis Almeida and Chloé Audebert and Emma Leschiera and Tommaso Lorenzi},

url = {https://pubmed.ncbi.nlm.nih.gov/36315362/},

year  = {2022},

date = {2022-10-01},

journal = {Bulletin Of Mathematical Biology},

volume = {84},

number = {141},

pages = {1-37},

abstract = {We present a spatial hybrid discrete-continuum modelling framework for the interaction dynamics between tumour cells and cytotoxic T cells, which play a pivotal role in the immune response against tumours. In this framework, tumour cells and T cells are modelled as individual agents while chemokines that drive the chemotactic movement of T cells towards the tumour are modelled as a continuum. We formally derive the continuum counterpart of this model, which is given by a coupled system that comprises an integro-differential equation for the density of tumour cells, a partial differential equation for the density of T cells and a partial differential equation for the concentration of chemokines. We report on computational results of the hybrid model and show that there is an excellent quantitative agreement between them and numerical solutions of the corresponding continuum model. These results shed light on the mechanisms that underlie the emergence of different levels of infiltration of T cells into the tumour and elucidate how T-cell infiltration shapes anti-tumour immune response. Moreover, to present a proof of concept for the idea that, exploiting the computational efficiency of the continuum model, extensive numerical simulations could be carried out, we investigate the impact of T-cell infiltration on the response of tumour cells to different types of anti-cancer immunotherapy.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{leschiera_2627,

title = {A mathematical model to study the impact of intra-tumour heterogeneity on anti-tumour CD8+ T cell immune response},

author = {Emma Leschiera and Tommaso Lorenzi and Shensi Shen and Luis Almeida and Chloé Audebert},

url = {https://www.sciencedirect.com/science/article/pii/S0022519322000261?via%3Dihub},

year  = {2022},

date = {2022-04-01},

journal = {Journal Of Theoretical Biology},

volume = {538},

number = {2022},

pages = {111028},

abstract = {Intra-tumour heterogeneity (ITH) has a strong impact on the efficacy of the immune response against solid tumours. The number of sub-populations of cancer cells expressing different antigens and the percentage of immunogenic cells (i.e. tumour cells that are effectively targeted by immune cells) in a tumour are both expressions of ITH. Here, we present a spatially explicit stochastic individual-based model of the

interaction dynamics between tumour cells and CD8+ T cells, which makes it possible to dissect out the specific impact of these two expressions of ITH on anti-tumour immune response. The set-up of numerical simulations of the model is defined so as to mimic scenarios considered in previous experimental studies. Moreover, the ability of the model to qualitatively reproduce experimental observations of successful and unsuccessful immune surveillance is demonstrated. First, the results of numerical simulations of this model indicate that the presence of a larger number of sub-populations of tumour cells that express different antigens is associated with a reduced ability of CD8+ T cells to mount an effective anti-tumour immune response. Secondly, the presence of a larger percentage of tumour cells that are not effectively targeted by CD8+ T cells may reduce the effectiveness of anti-tumour immunity.

Ultimately, the mathematical model presented in this paper may provide a framework to help biologists and clinicians to better understand the mechanisms that are responsible for the emergence of different outcomes of immunotherapy.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}