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Thermodynamically Constrained Averaging Theory for Cancer Growth 6th IFAC Conference on View metadata,6th IFAC citation Conference and similar on papers at core.ac.uk brought to you by CORE 6thFoundations IFAC Conference of Systems on Biology in Engineering FoundationsOctober 9-12, of 2016. Systems Magdeburg, Biology Germany in EngineeringAvailable online at www.sciencedirect.com OctoberFoundations 9-12, of 2016. Systems Magdeburg, Biology Germany in Engineering provided by Open Repository and Bibliography - Luxembourg October 9-12, 2016. Magdeburg, Germany ScienceDirect IFAC-PapersOnLine 49-26 (2016) 289–294 Thermodynamically constrained averaging Thermodynamically constrained averaging theory for cancer growth modelling theory for cancer growth modelling Marco Albrecht ∗ Giuseppe Scium`e ∗∗ Philippe Lucarelli ∗ Marco Albrecht ∗ Giuseppe Scium`e ∗∗ Philippe Lucarelli ∗ Marco Albrecht ∗ GiuseppeThomas Scium`e Sauter∗∗∗ Philippe Lucarelli ∗ Thomas Sauter ∗ Thomas Sauter ∗ ∗ University of Luxembourg, Belvaux, 4367 Luxembourg ∗ University of Luxembourg, Belvaux, 4367 Luxembourg (e-mail:∗ University [email protected] of Luxembourg, Belvaux, or [email protected]). 4367 Luxembourg (e-mail:∗ University [email protected] of Luxembourg, Belvaux, or [email protected]). 4367 Luxembourg ∗∗ University(e-mail: of [email protected] Bordeaux I2M-TREFLE, or [email protected]). Talence Cedex, 33405 France ∗∗ University of Bordeaux I2M-TREFLE, Talence Cedex, 33405 France ∗∗ University of(e-mail: Bordeaux [email protected]) I2M-TREFLE, Talence Cedex, 33405 France ∗∗ University of(e-mail: Bordeaux [email protected]) I2M-TREFLE, Talence Cedex, 33405 France (e-mail: [email protected]) Abstract: In Systems Biology, network models are often used to describe intracellular mechanismsAbstract: In at Systems the cellular Biology, level. network The obtained models results are often are difficult used to to describe translate intracellular into three mechanismsAbstract: In at Systems the cellular Biology, level. network The obtained models results are often are difficult used to to describe translate intracellular into three mechanismsdimensional atbiological the cellular systems level. of The higher obtained order. results The multiplicity are difficult and to time translate dependency into three of cellulardimensional system biological boundaries, systems mechanical of higher phenomena order. The and multiplicity spatial concentration and time gradients dependency affect of cellulardimensional system biological boundaries, systems mechanical of higher phenomena order. The and multiplicity spatial concentration and time gradients dependency affect of cellularthe intercellular system boundaries, relations and mechanical communication phenomena of biochemical and spatial networks. concentration These gradients environmental affect effectsthe intercellular can be integrated relations with and ourcommunication promising cancer of biochemical modelling networks. environment, These that environmental is based on effectsthe intercellular can be integrated relations with and ourcommunication promising cancer of biochemical modelling networks. environment, These that environmental is based on effectsthermodynamically can be integrated constrained with our averaging promising theory cancer (TCAT). modelling Especially, environment, the TCAT that is parameter based on viscositythermodynamically can be used constrained as critical averaging player in theory tumour (TCAT). evolution. Especially, Strong cell-cell the TCAT contacts parameter and a viscositythermodynamically can be used constrained as critical averaging player in theory tumour (TCAT). evolution. Especially, Strong cell-cell the TCAT contacts parameter and a viscosityhigh degree can of be differentiation used as critical make player cancer in cells tumour viscous evolution. and support Strong compact cell-cell tumourcontacts growth and a withhigh degreehigh tumour of differentiation cell density make and accompanied cancer cells viscous displacement and support of the extracellular compact tumour material. growth In withhigh degreehigh tumour of differentiation cell density make and accompanied cancer cells viscous displacement and support of the extracellular compact tumour material. growth In withcontrast, high dedifferentiation tumour cell density and losing and accompanied of cell-cell contacts displacement make cancer of the cells extracellular more fluid material. and lead Into ancontrast, infiltrating dedifferentiation tumour growth and behaviour losing of cell-cell without contacts resistance make due cancer to the cells ECM. more The fluid fast and expanding lead to ancontrast, infiltrating dedifferentiation tumour growth and behaviour losing of cell-cell without contacts resistance make due cancer to the cells ECM. more The fluid fast and expanding lead to antumour infiltrating front of tumour the invasive growth type behaviour consumes without oxygen resistance and the due limited to the oxygen ECM. The availability fast expanding behind thetumour invasive front front of the results invasive automatically type consumes in a oxygen much smaller and the average limited tumour oxygen availability cell density behind in the thetumour invasive front front of the results invasive automatically type consumes in a oxygen much smaller and the average limited tumour oxygen availability cell density behind in the thetumour invasive core. front The proposed results automatically modelling technique in a much is most smaller suitable average for tumour tumour growth cell density phenomena in the intumour stiff tissues core. The like proposed skin or bone modelling with high technique content is of most extracellular suitable for matrix. tumour growth phenomena intumour stiff tissues core. The like proposed skin or bone modelling with high technique content is of most extracellular suitable for matrix. tumour growth phenomena in stiff tissues like skin or bone with high content of extracellular matrix. © 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. Keywords: TCAT, Systems Biology, cancer growth, multi phase systems, porous media, tissues Keywords: TCAT, Systems Biology, cancer growth, multi phase systems, porous media, tissues Keywords: TCAT, Systems Biology, cancer growth, multi phase systems, porous media, tissues 1. INTRODUCTION to the softness of several cancer cell lines, especially of 1. INTRODUCTION metastaticto the softness cells. of This several soft cancer conformation cell lines, might especially help cells of 1. INTRODUCTION metastaticto the softness cells. of This several soft cancer conformation cell lines, might especially help cells of The biological field experiences an enormous boost of metastaticsqueezing through cells. This the soft tight conformation and small mightchannels help within cells The biological field experiences an enormous boost of squeezing through the tight and small channels within mathematicalThe biological and field quantitative experiences methods. an enormous The field boost of Sys- of squeezingthe ECM. through In melanoma the tight it seems, and small that channels the stiffness within of mathematicalThe biological and field quantitative experiences methods. an enormous The field boost of Sys- of the ECM. In melanoma it seems, that the stiffness of temsmathematical Biology has and emerged quantitative in the methods. interface The of Molecular field of Sys- Bi- the cancer ECM. cells In melanoma changes over it seems, the different that the stages, stiffness always of temsmathematical Biology has and emerged quantitative in the methods. interface The of Molecular field of Sys- Bi- the cancer cells changes over the different stages, always ology,tems Biology Mathematics, has emerged Informatics in the interfaceand Engineering. of Molecular Besides Bi- theusing cancer the most cells appropriate changes over mechanical the different invasion stages, strategy always to ology,tems Biology Mathematics, has emerged Informatics in the interfaceand Engineering. of Molecular Besides Bi- using the most appropriate mechanical invasion strategy to thisology, movement, Mathematics, a cooperation Informatics between and Engineering. mainly clinicians, Besides usingcircumvent the most anatomic appropriate obstacles mechanical (Weder invasion et al. (2014)). strategy This to thisology, movement, Mathematics, a cooperation Informatics between and Engineering. mainly clinicians, Besides circumvent anatomic obstacles (Weder et al. (2014)). This mathematiciansthis movement, a and cooperation civil engineers between pushed mainly forward clinicians, the circumventtumour evolutionary anatomic pattern obstacles has (Weder its equivalent et al. (2014)). phenotype This mathematiciansthis movement, a and cooperation civil engineers between pushed mainly forward clinicians, the tumour evolutionary pattern has its equivalent phenotype fieldmathematicians of Physical Oncology and civil (Frieboes engineers et pushed al. (2011)). forward During the tumouron the transcriptomic evolutionary pattern pattern. has Hoek its et equivalent al. (2008) phenotype state that fieldmathematicians of Physical Oncology and civil (Frieboes engineers et pushed al. (2011)). forward During the on the transcriptomic pattern. Hoek et al. (2008) state that thefield last of Physical five years, Oncology those interdisciplinary(Frieboes et al. (2011)). fields coalesce During onmelanoma the transcriptomic cells oscillate pattern. between Hoek a etproliferative al. (2008) state but non- that thefield last of
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