Growth and in vivo stresses traced through tumor mechanics enriched with predator-prey cells dynamics

Carotenuto, Angelo Rosario; Cutolo, A.; Petrillo, Antonella; Fusco, Roberta; Arra, Claudio; Sansone, Mario; Larobina, Domenico; Cardoso, Luís; Fraldi, Massimiliano

doi:10.1016/j.jmbbm.2018.06.011

Cited by 24 publications

(33 citation statements)

References 51 publications

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“…Here, this is explicitly coupled with the dynamics of GPCRs and MRPs activation, apt to describe the growth of active domains on the membrane surface by means of flow rules that include the receptor-transporter interplay. This dynamics is modelled according to a theory of interspecific growth mechanics recently proposed by Fraldi and Carotenuto (2018) , Carotenuto et al (2018) and applied to model the growth of solid tumors. Here, the same framework is adapted to model the kinetics and diffusion of transmembrane proteins triggered by ligand-binding and mediated by the membrane elasticity.…”

Section: The Biomechanical Modelmentioning

confidence: 99%

Mechanobiology predicts raft formations triggered by ligand-receptor activity across the cell membrane

Carotenuto¹,

Lunghi

Piccolo

et al. 2020

Journal of the Mechanics and Physics of Solids

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Section: The Biomechanical Modelmentioning

confidence: 99%

Mechanobiology predicts raft formations triggered by ligand-receptor activity across the cell membrane

Carotenuto¹,

Lunghi

Piccolo

et al. 2020

Journal of the Mechanics and Physics of Solids

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“…At the level of cell aggregates, statistical mechanics arguments have been used to demonstrate that cells interactions represent a functional constraint to the macroscopic tumor growth law [47] and the use of evolutionary models, in the framework of population ecology, has represented a particularly successful strategy to study the dynamics of cells' collective interactions through competitive/cooperative mechanisms, in which however the feedback from the environmental on cell behaviours seems to be still absent [48][49][50][51][52][53][54]. In the light of these considerations, the full coupling of population dynamics with the tissue biomechanical response and stress-driven factors in modelling tumor growth has been the crucial point developed in very recent works by some of the present authors [27,55]. Therein, the theoretical prediction of cell interspecific behaviour and the cells-extracellular matrix interaction have been described by means of a Volterra-Lotka (VL)-like model following a predator-prey logic, by assuming that cancer and healthy cells compete for the shared space and the available resources.…”

Section: Introductionmentioning

confidence: 99%

Lyapunov stability of competitive cells dynamics in tumor mechanobiology

et al. 2021

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Poromechanics plays a key role in modelling hard and soft tissue behaviours, by providing a thermodynamic framework in which chemo-mechanical mutual interactions among fluid and solid constituents can be consistently rooted, at different scale levels. In this context, how different biological species (including cells, extra-cellular components and chemical metabolites) interplay within complex environments is studied for characterizing the mechanobiology of tumor growth, governed by intratumoral residual stresses that initiate mechanotransductive processes deregulating normal tissue homeostasis and leading to tissue remodelling. Despite the coupling between tumor poroelasticity and interspecific competitive dynamics has recently highlighted how microscopic cells and environment interactions influence growth-associated stresses and tumor pathophysiology, the nonlinear interlacing among biochemical factors and mechanics somehow hindered the possibility of gaining qualitative insights into cells dynamics. Motivated by this, in the present work we recover the linear poroelasticity in order to benefit of a reduced complexity, so first deriving the well-known Lyapunov stability criterion from the thermodynamic dissipation principle and then analysing the stability of the mechanical competition among cells fighting for common space and resources during cancer growth and invasion. At the end, the linear poroelastic model enriched by interspecific dynamics is also exploited to show how growth anisotropy can alter the stress field in spherical tumor masses, by thus indirectly affecting cell mechano-sensing. GraphicAbstract

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“…Multi-parameter models are based on mixture theory (Cowin and Cardoso 2012) where the relevant balance equations are written directly at the level of interest and the thermodynamic consistency is satisfied at the same level. The evolution of phases and species within multi-parameter models is obtained either by use of phase field approach (Hawkins-Daarud et al 2013; Lima et al 2016; Lima et al 2015; Oden et al 2016; Oden et al 2013; Oden et al 2010; Rahman et al 2017; Rocha et al 2018; Vilanova et al 2018) or of Volterra-Lotta (predator/prey like) equations (Carotenuto et al 2018; Fraldi and Carotenuto 2018). Recent multiphase models (Kremheller et al 2018; Sciumè et al 2014a; Sciumè et al 2013) are based on the Thermodynamically Constrained Averaging Theory (TCAT) (Gray and Miller 2014) where the model derivation proceeds systematically from known microscale relations to mathematically and physically consistent larger scale relations.…”

Section: Introductionmentioning

confidence: 99%

Coupling tumor growth and bio distribution models

Santagiuliana

Milošević

Milićević

et al. 2019

Biomed Microdevices

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We couple a tumor growth model embedded in a microenvironment, with a bio distribution model able to simulate a whole organ. The growth model yields the evolution of tumor cell population, of the differential pressure between cell populations, of porosity of ECM, of consumption of nutrients due to tumor growth, of angiogenesis, and related growth factors as function of the locally available nutrient. The bio distribution model on the other hand operates on a frozen geometry but yields a much refined distribution of nutrient and other molecules. The combination of both models will enable simulating the growth of a tumor in a whole organ, including a realistic distribution of therapeutic agents and allow hence to evaluate the efficacy of these agents.

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Growth and in vivo stresses traced through tumor mechanics enriched with predator-prey cells dynamics

Cited by 24 publications

References 51 publications

Mechanobiology predicts raft formations triggered by ligand-receptor activity across the cell membrane

Mechanobiology predicts raft formations triggered by ligand-receptor activity across the cell membrane

Lyapunov stability of competitive cells dynamics in tumor mechanobiology

Coupling tumor growth and bio distribution models

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