Literature DB >> 7599305

Different growth patterns of a cancer cell population as a function of its starting growth characteristics: analysis by mathematical modelling.

G I Solyanik1, N M Berezetskaya, R I Bulkiewicz, G I Kulik.   

Abstract

The growth kinetics of a cancer cell population as a function of the total number of cells and the proportion of proliferating and resting cells at the beginning of the growth has been analysed by a mathematical model. The model takes into account the processes of cell division, death and transition from proliferation to rest and backwards. It is shown that a single cell population growing under the same environmental conditions has an extremely broad spectrum of growth patterns. The whole multiplicity of possible growth patterns has been determined by the inherent cellular growth characteristics of the population, while the growth pattern actually realized of the variety of growth curves depends on the total number of cells and the proportion of proliferating and resting cells at the initial moment of growth. The model is shown to provide a good prediction of experimentally measured kinetics of regrowth of tumour cells subcultured after various times of the growth in unfed cultures, and the kinetics of tumour cell growth after severe hypoxia. The role of cell transitions between proliferating and resting stages in the problem of growth control is discussed.

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Year:  1995        PMID: 7599305     DOI: 10.1111/j.1365-2184.1995.tb00068.x

Source DB:  PubMed          Journal:  Cell Prolif        ISSN: 0960-7722            Impact factor:   6.831


  5 in total

1.  Implications of a simple mathematical model to cancer cell population dynamics.

Authors:  A L Garner; Y Y Lau; D W Jordan; M D Uhler; R M Gilgenbach
Journal:  Cell Prolif       Date:  2006-02       Impact factor: 6.831

2.  Borna disease virus nucleoprotein interacts with the CDC2-cyclin B1 complex.

Authors:  Oliver Planz; Stephan Pleschka; Katja Oesterle; Friederike Berberich-Siebelt; Christina Ehrhardt; Lothar Stitz; Stephan Ludwig
Journal:  J Virol       Date:  2003-10       Impact factor: 5.103

3.  Dynamic modeling of genes controlling cancer stem cell proliferation.

Authors:  Zhong Wang; Jingyuan Liu; Jianxin Wang; Yaqun Wang; Ningtao Wang; Yao Li; Runze Li; Rongling Wu
Journal:  Front Genet       Date:  2012-05-22       Impact factor: 4.599

4.  Over-diagnosis of potential malignant behavior in MEN 2A-associated pheochromocytomas using the PASS and GAPP algorithms.

Authors:  Adam Stenman; Jan Zedenius; Carl Christofer Juhlin
Journal:  Langenbecks Arch Surg       Date:  2018-05-19       Impact factor: 3.445

5.  Changing Oncology Treatment Paradigms in the COVID-19 Pandemic.

Authors:  Emil Lou; Subbaya Subramanian
Journal:  Clin Colorectal Cancer       Date:  2020-05-14       Impact factor: 4.481

  5 in total

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