Stochastic Fluctuations Drive Non-genetic Evolution of Proliferation in Clonal Cancer Cell Populations
2023
Authors:
Ortega-Sabater, CarmenF. Calvo, Gabriel
Dinić, Jelena
Podolski-Renić, Ana
Pešić, Milica
Pérez-García, Víctor
Document Type:
Article (Published version)
,
© 2022, The Author(s), under exclusive licence to Society for Mathematical Biology.
Metadata
Show full item recordAbstract:
Evolutionary dynamics allows us to understand many changes happening in a broad variety of biological systems, ranging from individuals to complete ecosystems. It is also behind a number of remarkable organizational changes that happen during the natural history of cancers. These reflect tumour heterogeneity, which is present at all cellular levels, including the genome, proteome and phenome, shaping its development and interrelation with its environment. An intriguing observation in different cohorts of oncological patients is that tumours exhibit an increased proliferation as the disease progresses, while the timescales involved are apparently too short for the fixation of sufficient driver mutations to promote explosive growth. Here, we discuss how phenotypic plasticity, emerging from a single genotype, may play a key role and provide a ground for a continuous acceleration of the proliferation rate of clonal populations with time. We address this question by combining the analysis of real-time growth of non-small-cell lung carcinoma cells (N-H460) together with stochastic and deterministic mathematical models that capture proliferation trait heterogeneity in clonal populations to elucidate the contribution of phenotypic transitions on tumour growth dynamics.
Keywords:
Cancer; Evolutionary dynamics; Noise expression; Phenotype; StochasticSource:
Bulletin of Mathematical Biology, 2023, 85, 1, 8-
DOI: 10.1007/s11538-022-01113-4
ISSN: 0092-8240
PubMed: 36562835
WoS: 000903456300001
Scopus: 2-s2.0-85144635614
URI
https://link.springer.com/10.1007/s11538-022-01113-4http://radar.ibiss.bg.ac.rs/handle/123456789/5357