Literature DB >> 31576418

Investigation of solid tumor progression with account of proliferation/migration dichotomy via Darwinian mathematical model.

Maxim Kuznetsov1, Andrey Kolobov2,3.   

Abstract

A new continuous spatially-distributed model of solid tumor growth and progression is presented. The model explicitly accounts for mutations/epimutations of tumor cells which take place upon their division. The tumor grows in normal tissue and its progression is driven only by competition between populations of malignant cells for limited nutrient supply. Two reasons for the motion of tumor cells in space are taken into consideration, i.e., their intrinsic motility and convective fluxes, which arise due to proliferation of tumor cells. The model is applied to investigation of solid tumor progression under phenotypic alterations that inversely affect cell proliferation rate and cell motility by increasing the value of one of the parameters at the expense of another.It is demonstrated that the crucial feature that gives evolutionary advantage to a cell population is the speed of its intergrowth into surrounding normal tissue. Of note, increase in tumor intergrowth speed in not always associated with increase in motility of tumor cells. Depending on the parameters of functions, that describe phenotypic alterations, tumor cellular composition may evolve towards: (1) maximization of cell proliferation rate, (2) maximization of cell motility, (3) non-extremum values of cell proliferation rate and motility. Scenarios are found, where after initial tendency for maximization of cell proliferation rate, the direction of tumor progression sharply switches to maximization of cell motility, which is accompanied by decrease in total speed of tumor growth.

Entities:  

Keywords:  Intratumoral heterogeneity; Mathematical oncology; Solid tumor growth; Spatially distributed modeling; Tumor cell motility; Tumor progression

Mesh:

Year:  2019        PMID: 31576418     DOI: 10.1007/s00285-019-01434-4

Source DB:  PubMed          Journal:  J Math Biol        ISSN: 0303-6812            Impact factor:   2.259


  54 in total

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8.  Tracking the evolution of cancer cell populations through the mathematical lens of phenotype-structured equations.

Authors:  Tommaso Lorenzi; Rebecca H Chisholm; Jean Clairambault
Journal:  Biol Direct       Date:  2016-08-23       Impact factor: 4.540

Review 9.  The 2007 WHO classification of tumours of the central nervous system.

Authors:  David N Louis; Hiroko Ohgaki; Otmar D Wiestler; Webster K Cavenee; Peter C Burger; Anne Jouvet; Bernd W Scheithauer; Paul Kleihues
Journal:  Acta Neuropathol       Date:  2007-07-06       Impact factor: 17.088

10.  The growth law of primary breast cancer as inferred from mammography screening trials data.

Authors:  D Hart; E Shochat; Z Agur
Journal:  Br J Cancer       Date:  1998-08       Impact factor: 7.640

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