Data-driven dynamic modelling identifies polyploidisation as key process in cell cycle progression upon DNA damage
Burgers, E. J.; Heldring, M. M.; Wijaya, L. S.; Danilyuk, T. Y.; Su, J.; Molenaar, S. J.; Bouwman, P.; Le Devedec, S. E.; Van de Water, B.; Beltman, J. B.
Show abstract
Chemotherapeutic agents often cause DNA damage in order to kill fast-dividing cancer cells or disrupt their proliferation. Therefore, understanding the interplay between DNA damage and cell cycle progression is highly relevant for understanding cancer cell behaviour. An important regulator is transcription factor p53, primarily known for its function to maintain genomic stability, regulate transient and permanent cell cycle arrest and apoptosis. Activated p53 transcriptionally regulates the expression of many proteins, among which are MDM2, p21 and BTG2. MDM2 functions as a direct inhibitor of p53 by targeting it for ubiquitination. The proteins p21 and BTG2 are known for their regulatory function in G1 and G2 cell cycle arrest. Using HepG2-FUCCI cells, we showed that exposure to cisplatin or etoposide caused a temporary G2 arrest. To study the link between protein expression and cell cycle arrest, we developed a mathematical model in which we integrated a previously established model for the protein expression dynamics of p53, MDM2, p21 and BTG2 with a cell cycle model. This allowed us to determine the importance of p21 and BTG2 in their stimulation of G1 and G2 cell cycle arrest. We found that the protein dynamics could predict the G2 cell cycle arrest in exposed cells, but only in combination with endoreplication, i.e., the alternation of S and G phases without mitosis, resulting in polyploid cells. Our model predicted that the majority of cells endoreplicate upon exposure to high concentrations of cisplatin and most concentrations of etoposide, which we validated with additional time-lapse imaging data in which we could track individual cells. In conclusion, polyploidisation is a generic response of HepG2 cells after treatment with DNA-damaging compounds.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Reusable rule-based cell cycle model explains compartment-resolved dynamics of 16 observables in RPE-1 cells 95%
- Quantification of long-term doxorubicin response dynamics in breast cancer cell lines to direct treatment schedules 94%
- Dynamics of chromosomal target search by a membrane-integrated one-component receptor 94%
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- An experimental-mathematical approach to predict tumor cell growth as a function of glucose availability in breast cancer cell lines 95%
- High-volume, label-free imaging for quantifying single-cell dynamics in induced pluripotent stem cell colonies 93%
- Extreme value theory as a general framework for understanding mutation frequency distribution in cancer genomes 93%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.