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Cell population growth kinetics in the presence of stochastic heterogeneity of cell phenotype

  • Yue Wang
  • , Joseph X. Zhou
  • , Edoardo Pedrini
  • , Irit Rubin
  • , May Khalil
  • , Roberto Taramelli
  • , Hong Qian
  • , Sui Huang

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Recent studies at individual cell resolution have revealed phenotypic heterogeneity in nominally clonal tumor cell populations. The heterogeneity affects cell growth behaviors, which can result in departure from the idealized uniform exponential growth of the cell population. Here we measured the stochastic time courses of growth of an ensemble of populations of HL60 leukemia cells in cultures, starting with distinct initial cell numbers to capture a departure from the uniform exponential growth model for the initial growth (“take-off”). Despite being derived from the same cell clone, we observed significant variations in the early growth patterns of individual cultures with statistically significant differences in growth dynamics, which could be explained by the presence of inter-converting subpopulations with different growth rates, and which could last for many generations. Based on the hypothesis of existence of multiple subpopulations, we developed a branching process model that was consistent with the experimental observations.

Original languageEnglish
Article number111645
JournalJournal of Theoretical Biology
Volume575
DOIs
StatePublished - Nov 7 2023
Externally publishedYes

Keywords

  • Branching process
  • Growth pattern
  • Heterogeneity
  • Leukemia

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