Literature DB >> 33731745

Initial cell density encodes proliferative potential in cancer cell populations.

Chiara Enrico Bena1,2, Marco Del Giudice2,3, Alice Grob4,5, Thomas Gueudré2, Mattia Miotto6, Dimitra Gialama7, Matteo Osella8, Emilia Turco9, Francesca Ceroni7,5, Andrea De Martino2,10, Carla Bosia11,12.   

Abstract

Individual cells exhibit specific proliferative responses to changes in microenvironmental conditions. Whether such potential is constrained by the cell density throughout the growth process is however unclear. Here, we identify a theoretical framework that captures how the information encoded in the initial density of cancer cell populations impacts their growth profile. By following the growth of hundreds of populations of cancer cells, we found that the time they need to adapt to the environment decreases as the initial cell density increases. Moreover, the population growth rate shows a maximum at intermediate initial densities. With the support of a mathematical model, we show that the observed interdependence of adaptation time and growth rate is significantly at odds both with standard logistic growth models and with the Monod-like function that governs the dependence of the growth rate on nutrient levels. Our results (i) uncover and quantify a previously unnoticed heterogeneity in the growth dynamics of cancer cell populations; (ii) unveil how population growth may be affected by single-cell adaptation times; (iii) contribute to our understanding of the clinically-observed dependence of the primary and metastatic tumor take rates on the initial density of implanted cancer cells.

Entities:  

Year:  2021        PMID: 33731745      PMCID: PMC7969775          DOI: 10.1038/s41598-021-85406-z

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  30 in total

1.  Robust growth of Escherichia coli.

Authors:  Ping Wang; Lydia Robert; James Pelletier; Wei Lien Dang; Francois Taddei; Andrew Wright; Suckjoon Jun
Journal:  Curr Biol       Date:  2010-05-27       Impact factor: 10.834

2.  Relation between the generation time and the lag time of bacterial growth kinetics.

Authors:  M L Delignette-Muller
Journal:  Int J Food Microbiol       Date:  1998-08-18       Impact factor: 5.277

3.  Stochasticity in colonial growth dynamics of individual bacterial cells.

Authors:  Konstantinos P Koutsoumanis; Alexandra Lianou
Journal:  Appl Environ Microbiol       Date:  2013-01-25       Impact factor: 4.792

4.  Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli.

Authors:  Daniele De Martino; Fabrizio Capuani; Andrea De Martino
Journal:  Phys Biol       Date:  2016-05-27       Impact factor: 2.583

5.  Noise-driven growth rate gain in clonal cellular populations.

Authors:  Mikihiro Hashimoto; Takashi Nozoe; Hidenori Nakaoka; Reiko Okura; Sayo Akiyoshi; Kunihiko Kaneko; Edo Kussell; Yuichi Wakamoto
Journal:  Proc Natl Acad Sci U S A       Date:  2016-03-07       Impact factor: 11.205

Review 6.  Single-Cell Physiology.

Authors:  Sattar Taheri-Araghi; Steven D Brown; John T Sauls; Dustin B McIntosh; Suckjoon Jun
Journal:  Annu Rev Biophys       Date:  2015-02-26       Impact factor: 12.981

7.  Quantifying the entropic cost of cellular growth control.

Authors:  Daniele De Martino; Fabrizio Capuani; Andrea De Martino
Journal:  Phys Rev E       Date:  2017-07-10       Impact factor: 2.529

8.  Prolactin is an autocrine growth factor for the Jurkat human T-leukemic cell line.

Authors:  L Matera; M Cutufia; M Geuna; M Contarini; S Buttiglieri; S Galin; A Fazzari; C Cavaliere
Journal:  J Neuroimmunol       Date:  1997-10       Impact factor: 3.478

9.  Phenotypic bistability in Escherichia coli's central carbon metabolism.

Authors:  Oliver Kotte; Benjamin Volkmer; Jakub L Radzikowski; Matthias Heinemann
Journal:  Mol Syst Biol       Date:  2014-07-01       Impact factor: 11.429

10.  Inoculated Cell Density as a Determinant Factor of the Growth Dynamics and Metastatic Efficiency of a Breast Cancer Murine Model.

Authors:  Ana C Gregório; Nuno A Fonseca; Vera Moura; Manuela Lacerda; Paulo Figueiredo; Sérgio Simões; Sérgio Dias; João Nuno Moreira
Journal:  PLoS One       Date:  2016-11-07       Impact factor: 3.240

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