Literature DB >> 16697424

Modelling the balance between quiescence and cell death in normal and tumour cell populations.

Lorenzo Spinelli1, Alessandro Torricelli, Paolo Ubezio, Britta Basse.   

Abstract

When considering either human adult tissues (in vivo) or cell cultures (in vitro), cell number is regulated by the relationship between quiescent cells, proliferating cells, cell death and other controls of cell cycle duration. By formulating a mathematical description we see that even small alterations of this relationship may cause a non-growing population to start growing with doubling times characteristic of human tumours. Our model consists of two age structured partial differential equations for the proliferating and quiescent cell compartments. Model parameters are death rates from and transition rates between these compartments. The partial differential equations can be solved for the steady-age distributions, giving the distribution of the cells through the cell cycle, dependent on specific model parameter values. Appropriate formulas can then be derived for various population characteristic quantities such as labelling index, proliferation fraction, doubling time and potential doubling time of the cell population. Such characteristic quantities can be estimated experimentally, although with decreasing precision from in vitro, to in vivo experimental systems and to the clinic. The model can be used to investigate the effects of a single alteration of either quiescence or cell death control on the growth of the whole population and the non-trivial dependence of the doubling time and other observable quantities on particular underlying cell cycle scenarios of death and quiescence. The model indicates that tumour evolution in vivo is a sequence of steady-states, each characterised by particular death and quiescence rate functions. We suggest that a key passage of carcinogenesis is a loss of the communication between quiescence, death and cell cycle machineries, causing a defect in their precise, cell cycle dependent relationship.

Entities:  

Mesh:

Year:  2006        PMID: 16697424     DOI: 10.1016/j.mbs.2006.03.016

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  10 in total

1.  Parameter non-identifiability of the Gyllenberg-Webb ODE model.

Authors:  Niklas Hartung
Journal:  J Math Biol       Date:  2013-08-30       Impact factor: 2.259

2.  A checkpoint-oriented cell cycle simulation model.

Authors:  David Bernard; Odile Mondesert; Aurélie Gomes; Yves Duthen; Valérie Lobjois; Sylvain Cussat-Blanc; Bernard Ducommun
Journal:  Cell Cycle       Date:  2019-04-04       Impact factor: 4.534

3.  Global dynamics of hematopoietic stem cells and differentiated cells in a chronic myeloid leukemia model.

Authors:  Bedr'eddine Aïnseba; Chahrazed Benosman
Journal:  J Math Biol       Date:  2010-08-18       Impact factor: 2.259

4.  Primary cell cultures from human renal cortex and renal-cell carcinoma evidence a differential expression of two spliced isoforms of Annexin A3.

Authors:  Cristina Bianchi; Silvia Bombelli; Francesca Raimondo; Barbara Torsello; Valentina Angeloni; Stefano Ferrero; Vitalba Di Stefano; Clizia Chinello; Ingrid Cifola; Lara Invernizzi; Paolo Brambilla; Fulvio Magni; Marina Pitto; Gianpaolo Zanetti; Paolo Mocarelli; Roberto A Perego
Journal:  Am J Pathol       Date:  2010-02-18       Impact factor: 4.307

Review 5.  Nanovehicular intracellular delivery systems.

Authors:  Ales Prokop; Jeffrey M Davidson
Journal:  J Pharm Sci       Date:  2008-09       Impact factor: 3.534

6.  relocating job wise? A mathematical model separates quantitatively the cytostatic and cytotoxic effects of a HER2 tyrosine kinase inhibitor.

Authors:  Peter Hinow; Shizhen Emily Wang; Carlos L Arteaga; Glenn F Webb
Journal:  Theor Biol Med Model       Date:  2007-04-03       Impact factor: 2.432

7.  Modeling Cancer Cell Growth Dynamics In vitro in Response to Antimitotic Drug Treatment.

Authors:  Alexander Lorz; Dana-Adriana Botesteanu; Doron Levy
Journal:  Front Oncol       Date:  2017-08-30       Impact factor: 6.244

8.  Cell killing and resistance in pre-operative breast cancer chemotherapy.

Authors:  Paolo Ubezio; David Cameron
Journal:  BMC Cancer       Date:  2008-07-21       Impact factor: 4.430

9.  Dynamic rendering of the heterogeneous cell response to anticancer treatments.

Authors:  Francesca Falcetta; Monica Lupi; Valentina Colombo; Paolo Ubezio
Journal:  PLoS Comput Biol       Date:  2013-10-17       Impact factor: 4.475

10.  Modeling of non-small cell lung cancer volume changes during CT-based image guided radiotherapy: patterns observed and clinical implications.

Authors:  Hiram A Gay; Quendella Q Taylor; Fumika Kiriyama; Geoffrey T Dieck; Todd Jenkins; Paul Walker; Ron R Allison; Paolo Ubezio
Journal:  Comput Math Methods Med       Date:  2013-10-24       Impact factor: 2.238

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.