Agent-Based Modeling of Cancer Stem Cell Driven Solid Tumor Growth

Poleszczuk, Jan; Macklin, Paul; Enderling, Heiko

doi:10.1007/7651_2016_346

Cited by 45 publications

(21 citation statements)

References 69 publications

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“…Some of the model parameters had been estimated in previous studies. Specifically, this applies to the maximum proliferation capacity of nonstem cells (tumor cells and immune cells alike), which we set to 10 analogous to (14). Also, it was previously shown that the maximum number of kills a lymphocyte can deliver can be validly estimated as five (23).…”

Section: Estimation Of Key Parametersmentioning

confidence: 99%

“…Although these models simplify many aspects of reality, they have been shown to be extremely useful in a wide number of circumstances (10)(11)(12). In cancer research, these models are emerging as valuable tools to study emergent behavior in complex ecosystems (13), especially in stem-cell models of tumor growth (14,15) and are used to study the mutational landscape of solid tumors (16,17). Furthermore, they are increasingly used to optimize therapies, for example radiation therapy of solid tumors (18).…”

Section: Introductionmentioning

confidence: 99%

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In Silico Modeling of Immunotherapy and Stroma-Targeting Therapies in Human Colorectal Cancer

et al. 2017

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Despite the fact that the local immunological microenvironment shapes the prognosis of colorectal cancer, immunotherapy has shown no benefit for the vast majority of colorectal cancer patients. A better understanding of the complex immunological interplay within the microenvironment is required. In this study, we utilized wet lab migration experiments and quantitative histological data of human colorectal cancer tissue samples (n ¼ 20) including tumor cells, lymphocytes, stroma, and necrosis to generate a multiagent spatial model. The resulting data accurately reflected a wide range of situations of successful and failed immune surveillance. Validation of simulated tissue outcomes on an independent set of human colorectal cancer specimens (n ¼ 37) revealed the model recapitulated the spatial layout typically found in human tumors. Stroma slowed down tumor growth in a lymphocyte-deprived environment but promoted immune escape in a lymphocyteenriched environment. A subgroup of tumors with less stroma and high numbers of immune cells showed high rates of tumor control. These findings were validated using data from colorectal cancer patients (n ¼ 261). Low-density stroma and high lymphocyte levels showed increased overall survival (hazard ratio 0.322, P ¼ 0.0219) as compared with high stroma and high lymphocyte levels. To guide immunotherapy in colorectal cancer, simulation of immunotherapy in preestablished tumors showed that a complex landscape with optimal stroma permeabilization and immune cell activation is able to markedly increase therapy response in silico. These results can help guide the rational design of complex therapeutic interventions, which target the colorectal cancer microenvironment.

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Section: Estimation Of Key Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

In Silico Modeling of Immunotherapy and Stroma-Targeting Therapies in Human Colorectal Cancer

et al. 2017

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“…This need is actual both in vascular field as several times demonstrated by different group of investigators [9–11], but also more in general in the world of computational models developed to replicate pathophysiological phenomena [12]. …”

Section: Introductionmentioning

confidence: 99%

A Computational Model-Based Framework to Plan Clinical Experiments – An Application to Vascular Adaptation Biology

Casarin

Berceli

Garbey

2018

Lecture Notes in Computer Science

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Several computational models have been developed in order to improve the outcome of Vein Graft Bypasses in response to arterial occlusions and they all share a common property: their accuracy relies on a winning choice of the coefficients’ value related to biological functions that drive them. Our goal is to optimize the retrieval of these unknown coefficients on the base of experimental data and accordingly, as biological experiments are noisy in terms of statistical analysis and the models are typically stochastic and complex, this work wants first to elucidate which experimental measurements might be sufficient to retrieve the targeted coefficients and second how many specimens would constitute a good dataset to guarantee a sufficient level of accuracy. Since experiments are often costly and time consuming, the planning stage is critical to the success of the operation and, on the base of this consideration, the present work shows how, thanks to an ad hoc use of a computational model of vascular adaptation, it is possible to estimate in advance the entity and the quantity of resources needed in order to efficiently reproduce the experimental reality.

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“…So-called in silico trials aimed to predict patient-specific responses to various dose schedules or treatment combinations are becoming an invaluable tool to optimize patient care [11][12][13] . Agent-based tumour growth models are commonly used to describe the behaviour and interaction of individual cells in different environments 14,15 . Among continuous models, the use of ordinary differential equations (ODE) is an useful tool to simulate the evolution of total tumour cell number over time, though it lacks of spatial considerations 16 .…”

Section: Introductionmentioning

confidence: 99%

Microenvironmental influence on microtumour infiltration patterns: 3D-mathematical modelling supported byin vitrostudies

et al. 2018

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Mathematical modelling approaches have become increasingly abundant in cancer research. Tumour infiltration extent and its spatial organization depend both on the tumour type and stage and on the bio-physicochemical characteristics of the microenvironment. This sets a complex scenario that often requires a multidisciplinary and individually adjusted approach. The ultimate goal of this work is to present an experimental/numerical combined method for the development of a three-dimensional mathematical model with the ability to reproduce the growth and infiltration patterns of a given avascular microtumour in response to different microenvironmental conditions. The model is based on a diffusion-convection reaction equation that considers logistic proliferation, volumetric growth, a rim of proliferative cells at the tumour surface, and invasion with diffusive and convective components. The parameter values of the model were fitted to experimental results while radial velocity and diffusion coefficients were made spatially variable in a case-specific way through the introduction of a shape function and a diffusion-limited-aggregation (DLA)-derived fractal matrix, respectively, according to the infiltration pattern observed. The in vitro model consists of multicellular tumour spheroids (MTSs) of an epithelial mammary tumour cell line (LM3) immersed in a collagen I gel matrix with a standard culture medium ("naive" matrix) or a conditioned medium from adipocytes or preadipocytes ("conditioned" matrix). It was experimentally determined that both adipocyte and preadipocyte conditioned media had the ability to change the MTS infiltration pattern from collective and laminar to an individual and atomized one. Numerical simulations were able to adequately reproduce qualitatively and quantitatively both kinds of infiltration patterns, which were determined by area quantification, analysis of fractal dimensions and lacunarity, and Bland-Altman analysis. These results suggest that the combined approach presented here could be established as a new framework with interesting potential applications at both the basic and clinical levels in the oncology area.

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Agent-Based Modeling of Cancer Stem Cell Driven Solid Tumor Growth

Cited by 45 publications

References 69 publications

In Silico Modeling of Immunotherapy and Stroma-Targeting Therapies in Human Colorectal Cancer

In Silico Modeling of Immunotherapy and Stroma-Targeting Therapies in Human Colorectal Cancer

A Computational Model-Based Framework to Plan Clinical Experiments – An Application to Vascular Adaptation Biology

Microenvironmental influence on microtumour infiltration patterns: 3D-mathematical modelling supported byin vitrostudies

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