journal contribution
posted on 2023-03-31, 04:24 authored by Luana S. Lenz, Juliano L. Faccioni, Paula A. Bracco, Jephesson A.F. Santos, Luiza C. Pereira, Julieti H. Buss, Mauricio T. Tamborindeguy, Daphne Torgo, Thayana Monteiro, Giovana B. Mantovani, Carolina N. Santo, Julia C. Marcolin, Eloisa Dalsin, Alvaro Vigo, Sidia M. Callegari-Jacques, Andrew O. Silva, Giovana R. Onzi, Karine R. Begnini, Guido Lenz Supplementary Fig. S2 DynaFit implementations. a, data collected from Supplementary Fig. S1c is given as input to the two DynaFit apps. The Python bootstrap app and the R predictive modeling app are based on different analytical strategies. b, Colony Variance Plot formed by the Python app and c, its hypothesis plot. d, Colony Variance Plot formed by the R app and e, its hypothesis plot.
Funding
Ralph Weissleder
Markus Covert
Fundação de Amparo ã Pesquisa do Estado do Rio Grande do Sul
Conselho Nacional de Desenvolvimento Científico e Tecnológico
ICGEB
CAPES
History
ARTICLE ABSTRACT
Several phenotypes that impact the capacity of cancer cells to survive and proliferate are dynamic. Here we used the number of cells in colonies as an assessment of fitness and devised a novel method called Dynamic Fitness Analysis (DynaFit) to measure the dynamics in fitness over the course of colony formation. DynaFit is based on the variance in growth rate of a population of founder cells compared with the variance in growth rate of colonies with different sizes. DynaFit revealed that cell fitness in cancer cell lines, primary cancer cells, and fibroblasts under unhindered growth conditions is dynamic. Key cellular mechanisms such as ERK signaling and cell-cycle synchronization differed significantly among cells in colonies after 2 to 4 generations and became indistinguishable from randomly sampled cells regarding these features. In the presence of cytotoxic agents, colonies reduced their variance in growth rate when compared with their founder cell, indicating a dynamic nature in the capacity to survive and proliferate in the presence of a drug. This finding was supported by measurable differences in DNA damage and induction of senescence among cells of colonies. The presence of epigenetic modulators during the formation of colonies stabilized their fitness for at least four generations. Collectively, these results support the understanding that cancer cell fitness is dynamic and its modulation is a fundamental aspect to be considered in comprehending cancer cell biology and its response to therapeutic interventions.
Cancer cell fitness is dynamic over the course of the formation of colonies. This dynamic behavior is mediated by asymmetric mitosis, ERK activity, cell-cycle duration, and DNA repair capacity in the absence or presence of a drug.
