Stochastic Fluctuations Drive Non-genetic Evolution of Proliferation in Clonal Cancer Cell Populations.
Carmen Ortega-SabaterGabriel F CalvoJelena DinićAna PodolskiMilica PesicVíctor Pérez-GarcíaPublished in: Bulletin of mathematical biology (2022)
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.
Keyphrases
- signaling pathway
- single cell
- genome wide
- end stage renal disease
- ejection fraction
- newly diagnosed
- chronic kidney disease
- climate change
- prostate cancer
- genetic diversity
- minimally invasive
- prognostic factors
- cell therapy
- stem cells
- gene expression
- peritoneal dialysis
- young adults
- bone marrow
- patient reported outcomes
- radical prostatectomy
- patient reported
- childhood cancer