A DNA-structured mathematical model of cell-cycle progression in cyclic hypoxia
Copyright © 2022 Elsevier Ltd. All rights reserved..
New experimental data have shown how the periodic exposure of cells to low oxygen levels (i.e., cyclic hypoxia) impacts their progress through the cell-cycle. Cyclic hypoxia has been detected in tumours and linked to poor prognosis and treatment failure. While fluctuating oxygen environments can be reproduced in vitro, the range of oxygen cycles that can be tested is limited. By contrast, mathematical models can be used to predict the response to a wide range of cyclic dynamics. Accordingly, in this paper we develop a mechanistic model of the cell-cycle that can be combined with in vitro experiments to better understand the link between cyclic hypoxia and cell-cycle dysregulation. A distinguishing feature of our model is the inclusion of impaired DNA synthesis and cell-cycle arrest due to periodic exposure to severely low oxygen levels. Our model decomposes the cell population into five compartments and a time-dependent delay accounts for the variability in the duration of the S phase which increases in severe hypoxia due to reduced rates of DNA synthesis. We calibrate our model against experimental data and show that it recapitulates the observed cell-cycle dynamics. We use the calibrated model to investigate the response of cells to oxygen cycles not yet tested experimentally. When the re-oxygenation phase is sufficiently long, our model predicts that cyclic hypoxia simply slows cell proliferation since cells spend more time in the S phase. On the contrary, cycles with short periods of re-oxygenation are predicted to lead to inhibition of proliferation, with cells arresting from the cell-cycle in the G2 phase. While model predictions on short time scales (about a day) are fairly accurate (i.e, confidence intervals are small), the predictions become more uncertain over longer periods. Hence, we use our model to inform experimental design that can lead to improved model parameter estimates and validate model predictions.
| Errataetall: |
ErratumIn: J Theor Biol. 2023 Aug 21;571:111507. - PMID 37286445 |
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:545 |
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| Enthalten in: |
Journal of theoretical biology - 545(2022) vom: 21. Juli, Seite 111104 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Celora, Giulia L [VerfasserIn] |
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| Links: |
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| Themen: |
9007-49-2 |
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| Anmerkungen: |
Date Completed 03.06.2022 Date Revised 07.06.2023 published: Print-Electronic ErratumIn: J Theor Biol. 2023 Aug 21;571:111507. - PMID 37286445 Citation Status MEDLINE |
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| doi: |
10.1016/j.jtbi.2022.111104 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 500 | |a ErratumIn: J Theor Biol. 2023 Aug 21;571:111507. - PMID 37286445 | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2022 Elsevier Ltd. All rights reserved. | ||
| 520 | |a New experimental data have shown how the periodic exposure of cells to low oxygen levels (i.e., cyclic hypoxia) impacts their progress through the cell-cycle. Cyclic hypoxia has been detected in tumours and linked to poor prognosis and treatment failure. While fluctuating oxygen environments can be reproduced in vitro, the range of oxygen cycles that can be tested is limited. By contrast, mathematical models can be used to predict the response to a wide range of cyclic dynamics. Accordingly, in this paper we develop a mechanistic model of the cell-cycle that can be combined with in vitro experiments to better understand the link between cyclic hypoxia and cell-cycle dysregulation. A distinguishing feature of our model is the inclusion of impaired DNA synthesis and cell-cycle arrest due to periodic exposure to severely low oxygen levels. Our model decomposes the cell population into five compartments and a time-dependent delay accounts for the variability in the duration of the S phase which increases in severe hypoxia due to reduced rates of DNA synthesis. We calibrate our model against experimental data and show that it recapitulates the observed cell-cycle dynamics. We use the calibrated model to investigate the response of cells to oxygen cycles not yet tested experimentally. When the re-oxygenation phase is sufficiently long, our model predicts that cyclic hypoxia simply slows cell proliferation since cells spend more time in the S phase. On the contrary, cycles with short periods of re-oxygenation are predicted to lead to inhibition of proliferation, with cells arresting from the cell-cycle in the G2 phase. While model predictions on short time scales (about a day) are fairly accurate (i.e, confidence intervals are small), the predictions become more uncertain over longer periods. Hence, we use our model to inform experimental design that can lead to improved model parameter estimates and validate model predictions | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a Cancer | |
| 650 | 4 | |a Cell-cycle | |
| 650 | 4 | |a Cyclic hypoxia | |
| 650 | 4 | |a Delay-differential equation | |
| 650 | 4 | |a Model calibration | |
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| 700 | 1 | |a Bader, Samuel B |e verfasserin |4 aut | |
| 700 | 1 | |a Hammond, Ester M |e verfasserin |4 aut | |
| 700 | 1 | |a Maini, Philip K |e verfasserin |4 aut | |
| 700 | 1 | |a Pitt-Francis, Joe M |e verfasserin |4 aut | |
| 700 | 1 | |a Byrne, Helen M |e verfasserin |4 aut | |
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