2017/07/31 by Denis Horváth, Denis Horvath, B. Brutovský +1
Biochemistry, Genetics and Molecular Biology · Mathematics · Medicine · Neuroscience · #Adaptation (eye) #Biology #Computational biology #Epigenetics #Evolution and Genetic Dynamics #Gene #Gene Regulatory Network Analysis #Genetic heterogeneity #Genetics #Mathematical Biology Tumor Growth #Medicine #Neuroscience #Phenotype #Phenotypic plasticity #Phenotypic switching #Population #msc:34B60 #msc:65L05 #msc:92B99 #msc:92D15 #q-bio.PE
paper · pdf · doi:10.1016/j.physleta.2018.03.052
24 pages, 1 table, 8 figures
arxiv created 2018/03/30 · openalex publication_date 2018/04/06 · arxiv updated 2018/05/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Reversibility of state transitions is intensively studied topic in many scientific disciplines over many years. In cell biology, it plays an important role in epigenetic variation of phenotypes, known as phenotypic plasticity. More interestingly, the cell state reversibility is probably crucial in the adaptation of population phenotypic heterogeneity to environmental fluctuations by evolving bet-hedging strategy, which might confer to cancer cells resistance to therapy. In this article, we propose a formalization of the evolution of highly reversible states in the environments of periodic variability. Two interrelated models of heterogeneous cell populations are proposed and their behavior is studied. The first model captures selection dynamics of the cell clones for the respective levels of phenotypic reversibility. The second model focuses on the interplay between reversibility and drug resistance in the particular case of cancer. Overall, our results show that the threshold dependencies are emergent features of the investigated model with eventual therapeutic relevance. Presented examples demonstrate importance of taking into account cell to cell heterogeneity within a system of clones with different reversibility quantified by appropriately chosen genetic and epigenetic entropy measures.