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Two-phase dynamics of p53 in the DNA damage response
Open accessAbstract
The tumor suppressor p53 mainly induces cell cycle arrest/DNA repair or apoptosis in the DNA damage response. How to choose between these two outcomes is not fully understood. We proposed a four-module model of the p53 signaling network and associated the network dynamics with cellular outcomes after ionizing radiation. We found that the cellular response is mediated by both the level and posttranslational modifications of p53 and that p53 is activated in a progressive manner. First, p53 is partially activated by primary modifications such as phosphorylation at Ser-15/20 to induce cell cycle arrest, with its level varying in a series of pulses. If the damage cannot be fixed after a critical number of p53 pulses, then p53 is fully activated by further modifications such as phosphorylation at Ser-46 to trigger apoptosis, with its concentration switching to rather high levels. Thus, p53 undergoes a two-phase response in irreparably damaged cells. Such combinations of pulsatile and switch-like behaviors of p53 may represent a flexible and efficient control mode, avoiding the premature apoptosis and promoting the execution of apoptosis. In our model, p53 pulses are recurrently driven by ataxia telangiectasia mutated (ATM) pulses triggered by DNA damage. The p53-Mdm2 and ATM-p53-Wip1 negative feedback loops are responsible for p53 pulses, whereas the switching behavior occurs when the p53-PTEN-Akt-Mdm2 positive feedback loop becomes dominant. Our results suggest that a sequential predominance of distinct feedback loops may elicit multiple-phase dynamical behaviors. This work provides a new mechanism for p53 dynamics and cell fate decision.
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“TP53 plays a central role in regulating cellular responses to genotoxic stress13–17”
From Role of TP53 mutations in the origin and evolution of therapy-related acute myeloid leukaemia (2015) · cites this paper as [17]
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Citations
Cites
AKT/PKB signaling: navigating downstream
Manning, B. D., & Cantley, L. C. (2007) · Cell · doi:10.1016/j.cell.2007.06.009 · Cited by 6,115
The BCL-2 protein family: opposing activities that mediate cell death
Youle, R. J., & Strasser, A. (2007) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2308 · Cited by 4,806
DNA damage activates ATM through intermolecular autophosphorylation and dimer dissociation
Bakkenist, C. J., & Kastan, M. B. (2003) · Nature · doi:10.1038/nature01368 · Cited by 3,466
Negative regulation of PKB/Akt-dependent cell survival by the tumor suppressor PTEN
Stambolic, V., Suzuki, A., de la Pompa, J. L., Brothers, G. M., Mirtsos, C., Sasaki, T., Ruland, J., Penninger, J. M., Siderovski, D. P., & Mak, T. W. (1998) · Cell · doi:10.1016/s0092-8674(00)81780-8 · Cited by 2,551
Vousden, K. H., & Lane, D. P. (2007) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2147 · Cited by 2,351
The p53-mdm-2 autoregulatory feedback loop.
Wu, X., Bayle, J. H., Olson, D., & Levine, A. J. (1993) · Genes & Development · doi:10.1101/gad.7.7a.1126 · Cited by 1,801
Evidence for a lack of DNA double-strand break repair in human cells exposed to very low x-ray doses
Rothkamm, K., & Löbrich, M. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0830918100 · Cited by 1,645 · cited 15×
“For a population of cells exposed to the same radiation dose of DIR, the initial numbers of DSBs are assumed to obey a Poisson distribution with a mean of 35 ×DIR (18).”
BackgroundInfluentialKruse, J.-P., & Gu, W. (2009) · Cell · doi:10.1016/j.cell.2009.04.050 · Cited by 1,610 · cited 1×
“First, p53 is primarily modified (such as phosphorylation at Ser-15 and Ser-20) and accumulates in pulses to induce protective cell cycle arrest for repairable DNA damage; it is further modified (such as phosphorylation at Ser-46) and fully activated to induce apoptosis for irreparable DNA damage (35).”
BackgroundCell-signalling dynamics in time and space
Kholodenko, B. N. (2006) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm1838 · Cited by 1,347
Mayo, L. D., & Donner, D. B. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.181181198 · Cited by 1,230
Cited by
Sorted by citations
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Gupta, S., Silveira, D. A., Barbé‐Tuana, F. M., & Mombach, J. C. M. (2020) · Scientific Reports · doi:10.1038/s41598-020-59339-y · Cited by 21
Eliaš, J., & Clairambault, J. (2014) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2014.05.007 · Cited by 20
Müller, I., Beissert, S., & Kulms, D. (2014) · Journal of Investigative Dermatology · doi:10.1038/jid.2014.481 · Cited by 20
Nordick, B., & Hong, T. (2021) · BMC Bioinformatics · doi:10.1186/s12859-021-04405-z · Cited by 18
PTEN enhances G2/M arrest in etoposide-treated MCF-7 cells through activation of the ATM pathway
ZHANG, R., Zhu, L., Zhang, L., Xu, A., Li, Z., Xu, Y., He, P. T., Wu, M., Wei, F., & WANG, C. (2016) · Oncology Reports · doi:10.3892/or.2016.4674 · Cited by 20
RetractedHu, G., Xu, S., & Wang, J. (2015) · Chemical Biology & Drug Design · doi:10.1111/cbdd.12598 · Cited by 19
Roles of cellular heterogeneity, intrinsic and extrinsic noise in variability of p53 oscillation
Wang, D.-G., Wang, S., Huang, B. Y., & Liu, F. (2019) · Scientific Reports · doi:10.1038/s41598-019-41904-9 · Cited by 20
Self-citationCoordination of miR-192 and miR-22 in p53-Mediated Cell Fate Decision
Sun, C., Zhang, X., & Wang, W. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20194768 · Cited by 19
Self-citationShi, W., Lü, J., Li, J., Qiu, M., Lü, Y., Gu, J., Kong, X., & Sun, W. (2021) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2020.625215 · Cited by 19
MicroRNAs and the DNA damage response: How is cell fate determined?
Visser, H., & Thomas, A. D. (2021) · DNA repair · doi:10.1016/j.dnarep.2021.103245 · Cited by 20
Coordination between p21 and DDB2 in the Cellular Response to UV Radiation
Li, H., Zhang, X., & Liu, F. (2013) · PLoS ONE · doi:10.1371/journal.pone.0080111 · Cited by 21
Self-citationNon-Gaussian noise-weakened stability in a foraging colony system with time delay
Dong, X., Zeng, C., Yang, F., Guan, L., Xie, Q., & Duan, W.-L. (2017) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2017.11.015 · Cited by 18
Eskandari, M. R., Shi, Y., Liu, J., Albanese, J. M., Goel, S., Verma, A. K., & Wang, Y. (2020) · Leukemia & lymphoma/Leukemia and lymphoma · doi:10.1080/10428194.2020.1817441 · Cited by 19
Modeling and controlling the two-phase dynamics of the p53 network: a Boolean network approach
Lin, G., Ao, B., Chen, J., Wang, W., & Di, Z. (2014) · New Journal of Physics · doi:10.1088/1367-2630/16/12/125010 · Cited by 18
Self-citationEffect of age on the sensitivity of the rat thyroid gland to ionizing radiation
Matsuu‐Matsuyama, M., Shichijo, K., Okaichi, K., Kurashige, T., Kondo, H., Miura, S., & Nakashima, M. (2015) · Journal of Radiation Research · doi:10.1093/jrr/rrv003 · Cited by 18
Interplay between Mdm2 and HIPK2 in the DNA damage response
Zhang, X., Liu, F., & Wang, W. (2014) · Journal of The Royal Society Interface · doi:10.1098/rsif.2014.0319 · Cited by 19
Self-citationp53 Orchestrates Cancer Metabolism: Unveiling Strategies to Reverse the Warburg Effect
Abukwaik, R., Vera-Sigüenza, E., Tennant, D. A., & Spill, F. (2024) · Bulletin of Mathematical Biology · doi:10.1007/s11538-024-01346-5 · Cited by 19
Mathematical Modeling of p53 Pathways
Kim, E., Kim, J.-Y., & Lee, J. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20205179 · Cited by 17
Jiang, M., Shi, L., Li, X., Dong, Q., Sun, H. Q., Du, Y., Zhang, Y., Shao, T., Cheng, H., Chen, W., et al. (2020) · Ecology and Evolution · doi:10.1002/ece3.6462 · Cited by 17
Regulation of epithelial‐to‐mesenchymal transition in hypoxia by the HIF‐1α network
Wang, H., Zhang, X., & Wang, W. (2021) · FEBS Letters · doi:10.1002/1873-3468.14258 · Cited by 17
Self-citationQuadra-Stable Dynamics of p53 and PTEN in the DNA Damage Response
Gupta, S., Panda, P. K., Silveira, D. A., Ahuja, R., & Hashimoto, R. F. (2023) · Cells · doi:10.3390/cells12071085 · Cited by 18
Dynamical Modeling and Analysis of Viscoelastic Properties of Single Cells
Wang, B., Wang, W., Wang, Y., Liu, B., & Liu, L. (2017) · Micromachines · doi:10.3390/mi8060171 · Cited by 17
Self-citationGupta, S., Silveira, D. A., Mombach, J. C. M., & Hashimoto, R. F. (2025) · Proteomes · doi:10.3390/proteomes13010006 · Cited by 16
Practical Understanding of Cancer Model Identifiability in Clinical Applications
Phan, T., Bennett, J., & Patten, T. (2023) · Life · doi:10.3390/life13020410 · Cited by 16
Dynamics of Posttranslational Modifications of p53
Qing-duan, F., Wu, G., & Liu, Z. (2014) · Computational and Mathematical Methods in Medicine · doi:10.1155/2014/245610 · Cited by 16
Realization of tristability in a multiplicatively coupled dual-loop genetic network
Huang, B. Y., Xia, Y., Liu, F., & Wang, W. (2016) · Scientific Reports · doi:10.1038/srep28096 · Cited by 16
Self-citationWang, L.-S., Li, N.-X., Chen, J., Zhang, X., Liu, F., & Wang, W. (2018) · Physical review. E · doi:10.1103/physreve.97.042412 · Cited by 16
Self-citationA plausible model for bimodal p53 switch in DNA damage response
Sun, T., & Cui, J. (2014) · FEBS Letters · doi:10.1016/j.febslet.2014.01.044 · Cited by 16
Aoyama, I., Yaegaki, K., Calenic, B., Ii, H., Ishkitiev, N., & Imai, T. (2012) · Journal of Breath Research · doi:10.1088/1752-7155/6/1/017104 · Cited by 16
CSB modulates the competition between HIF-1 and p53 upon hypoxia
Ye, X.-W., Zhang, X., & Liu, F. (2019) · Mathematical Biosciences & Engineering · doi:10.3934/mbe.2019262 · Cited by 16
Self-citationYan, Y., Yao, S., Jia, Z., Zhao, J., & Wang, L. (2021) · European Journal of Pharmacology · doi:10.1016/j.ejphar.2021.174299 · Cited by 15
CTLA-4 Facilitates DNA Damage–Induced Apoptosis by Interacting With PP2A
Yan, Q., Zhang, B., Ling, X., Zhu, B., Mei, S., Yang, H., Zhang, D., Huo, J., & Zhao, Z. (2022) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2022.728771 · Cited by 14
Ohshima, D., Inoue, J., & Ichikawa, K. (2012) · PLoS ONE · doi:10.1371/journal.pone.0046911 · Cited by 14
Biomolecular Network Controllability With Drug Binding Information
Wu, L., Tang, L., Li, M., Wang, J., & Wu, F. (2017) · IEEE Transactions on NanoBioscience · doi:10.1109/tnb.2017.2705106 · Cited by 14
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Guo, Q., & Wan, F. (2017) · PLoS ONE · doi:10.1371/journal.pone.0188632 · Cited by 14
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Wu, Y., Garmire, L. X., & Fan, R. (2012) · Integrative Biology · doi:10.1039/c2ib20044a · Cited by 14
Dynamics of p53 regulatory network in DNA damage response
Gao, C., & Chen, F. (2020) · Applied Mathematical Modelling · doi:10.1016/j.apm.2020.06.057 · Cited by 14
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Zhang, L., Cheng, Y., & Liew, K. M. (2013) · Applied Mathematics and Computation · doi:10.1016/j.amc.2013.10.025 · Cited by 13
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Gupta, S., Silveira, D. A., & Hashimoto, R. F. (2023) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2023.107926 · Cited by 13
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Hashemi, M., Khoushab, S., Aghmiuni, M. H., Anaraki, S. N., Alimohammadi, M., Taheriazam, A., Farahani, N., & Entezari, M. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e40096 · Cited by 16
Gupta, S., Silveira, D. A., Mombach, J. C. M., & Hashimoto, R. F. (2025) · Journal of The Royal Society Interface · doi:10.1098/rsif.2024.0852 · Cited by 13
Tissue-Specific Chk1 Activation Determines Apoptosis by Regulating the Balance of p53 and p21
van Jaarsveld, M. T. M., Deng, D., Wiemer, E. A. C., & Zi, Z. (2019) · iScience · doi:10.1016/j.isci.2019.01.001 · Cited by 13
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Kurup, S. P., Moioffer, S. J., Pewe, L. L., & Harty, J. T. (2020) · The Journal of Immunology · doi:10.4049/jimmunol.2000654 · Cited by 13
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Wang, P., Wang, H., Gao, X., Zhu, H.-X., Zhang, X., Liu, F., & Wang, W. (2023) · Cells · doi:10.3390/cells12030490 · Cited by 13
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Loriaux, P. M., & Hoffmann, A. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002932 · Cited by 14
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Ye, L., Song, Z., & Li, C. (2021) · The Journal of Chemical Physics · doi:10.1063/5.0030558 · Cited by 13
Bi, Y., Yang, Z., Zhuge, C., & Lei, J. (2015) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/1.4934967 · Cited by 12
Rewiring drug-activated p53-regulatory network from suppressing to promoting tumorigenesis
Song, W., Wang, J., Yang, Y., Jing, N., Zhang, X., Chen, L., & Wu, J. (2012) · Journal of Molecular Cell Biology · doi:10.1093/jmcb/mjs029 · Cited by 12
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Wang, C., Liu, H., & Zhou, J. (2019) · IEEE Transactions on NanoBioscience · doi:10.1109/tnb.2019.2924079 · Cited by 12
Wang, K., Zong, D.-C., Wang, Y., & Wang, P.-X. (2019) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2019.122861 · Cited by 12
Yamamura, Y., Kawamura, Y., Oiwa, Y., Oka, K., Onishi, N., Saya, H., & Miura, K. (2021) · Inflammation and Regeneration · doi:10.1186/s41232-021-00182-7 · Cited by 13
Translational potential of base-editing tools for gene therapy of monogenic diseases
Reshetnikov, V. V., Chirinskaite, A. V., Sopova, J. V., Ivanov, R. A., & Леонова, Е. И. (2022) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2022.942440 · Cited by 13
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Brown, D. W., Beatty, P. H., & Lewis, J. D. (2022) · Cancers · doi:10.3390/cancers14215176 · Cited by 13
Li, Y., Yi, M., & Zou, X. (2013) · Biophysical Journal · doi:10.1016/j.bpj.2013.03.057 · Cited by 11
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Feng, Y., Liu, F., Du, Z., Zhao, D., Cheng, J., & Guo, W. (2017) · Molecular Medicine Reports · doi:10.3892/mmr.2017.6469 · Cited by 11
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Xiao, H., Xu, Z., Zhu, X., Wang, J., Zheng, Q., Zhang, Q., Xu, C., Tao, W., & Wang, D. (2022) · Science China Life Sciences · doi:10.1007/s11427-021-2051-0 · Cited by 11
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Zeki, S. S., & Fitzgerald, R. C. (2014) · Best Practice & Research Clinical Gastroenterology · doi:10.1016/j.bpg.2014.11.003 · Cited by 11
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Li, Y., & Cucinotta, F. A. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21041214 · Cited by 11
Kellar, R. S., Audet, R. G., Roe, D. F., Rheins, L. A., & Draelos, Z. D. (2013) · Journal of Cosmetic Dermatology · doi:10.1111/jocd.12039 · Cited by 11
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Liu, R., Qian, C., Liu, S., & Jin, Y.-F. (2016) · BMC Systems Biology · doi:10.1186/s12918-016-0314-z · Cited by 11
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Wang, D., Jin, S., Wu, F., & Zou, X. (2015) · Advances in Complex Systems · doi:10.1142/s0219525915500186 · Cited by 10
Oscillations Governed by the Incoherent Dynamics in Necroptotic Signaling
Xu, F., Yin, Z., Zhu, L., Jin, J., He, Q., Li, X., & Shuai, J. (2021) · Frontiers in Physics · doi:10.3389/fphy.2021.726638 · Cited by 10
Yang, X., Liu, D., Wu, H., Kang, H., Pang, H., Huang, D., Sha, X., Wang, E., Wang, Z., & Wei, M. (2012) · Cancer Science · doi:10.1111/j.1349-7006.2012.02312.x · Cited by 10
Liang, M., Li, H., Wang, Z., Cai, L., & Yang, L. (2019) · Journal of the Science of Food and Agriculture · doi:10.1002/jsfa.9888 · Cited by 11
Qi, H., Yin, Y.-S., Yin, Z., Li, X., & Shuai, J. (2023) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2023.111558 · Cited by 10
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Triantafyllidis, C. P., Barberis, A., Hartley, F., Miar, A., Gjerga, E., Charlton, P. V., van Bijsterveldt, L., Sáez-Rodríguez, J., & Buffa, F. M. (2023) · iScience · doi:10.1016/j.isci.2023.108291 · Cited by 9
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Khan, C., Rusan, N. M., & Baker, N. E. (2026) · PLoS Genetics · doi:10.1371/journal.pgen.1012309 · Cited by 11
Chu, Y., Wang, Z., Wang, R., Zhang, N., Li, J., Hu, Y., Teng, M., & Wang, Y. (2017) · Journal of Bioinformatics and Computational Biology · doi:10.1142/s0219720017500214 · Cited by 9
Avcu, N., & Guzelis, C. (2019) · IET Systems Biology · doi:10.1049/iet-syb.2019.0043 · Cited by 9
Dual roles of SIRT1 in the BAX switch through the P53 module: A mathematical modeling study
Liu, N., Yang, H., & Yang, L. (2021) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2021.09.033 · Cited by 9
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Gupta, S., Silveira, D. A., Hashimoto, R. F., & Mombach, J. C. M. (2022) · Biology · doi:10.3390/biology11040480 · Cited by 9
Sun, J., Yi, M., Yang, L., Wei, W., Ding, Y., & Jia, Y. (2014) · Biophysical Journal · doi:10.1016/j.bpj.2014.01.036 · Cited by 8
Quantifying the energy landscape of high-dimensional oscillatory systems by diffusion decomposition
Bian, S., Zhou, R., Lin, W. J., & Li, C. (2025) · Cell Reports Physical Science · doi:10.1016/j.xcrp.2025.102405 · Cited by 8
Pan, J. H., Cicalo, C., Le, B., Jeon, S., Kim, S., Hwang, K. A., Kong, B. C., Lee, J. H., & Kim, J. K. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21186620 · Cited by 8
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Bian, S., Zhang, Y., & Li, C. (2023) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/5.0128345 · Cited by 8
Scafoglio, C., Smolka, M. B., Zhou, H., Perissi, V., & Rosenfeld, M. G. (2013) · PLoS ONE · doi:10.1371/journal.pone.0059986 · Cited by 8
Shi, X., & Reimers, J. R. (2018) · Scientific Reports · doi:10.1038/s41598-018-20466-2 · Cited by 8
Exploring the influence of microRNA miR-34 on p53 dynamics: a numerical study*
Liu, N., Yang, H., & Yang, L. (2021) · Communications in Theoretical Physics · doi:10.1088/1572-9494/abd84c · Cited by 8
The interplay between DNA damage and autophagy in lung cancer: A mathematical study
Sarmah, D. T., Bairagi, N., & Chatterjee, S. (2021) · Biosystems · doi:10.1016/j.biosystems.2021.104443 · Cited by 8
Codimension-3 Bifurcation in the p53 Regulatory Network Model
Jiang, C., Zhang, Y., & Wang, W. (2021) · International Journal of Bifurcation and Chaos · doi:10.1142/s0218127421501042 · Cited by 8
Self-citationA common pathway to cancer: Oncogenic mutations abolish p53 oscillations
Xiong, L., & Garfinkel, A. (2022) · Progress in Biophysics and Molecular Biology · doi:10.1016/j.pbiomolbio.2022.06.002 · Cited by 9
Cardona-Mendoza, A., Fonseca-Benítez, A. V., Buitrago, D. M., Coy-Barrera, E. D., & Perdomo, S. J. (2023) · Journal of Ethnopharmacology · doi:10.1016/j.jep.2023.117225 · Cited by 8
Sun, T., Mu, D., & Cui, J. (2018) · Cell Cycle · doi:10.1080/15384101.2018.1553342 · Cited by 8
Bi, Y., Liu, Q., Wang, L., Yang, W., & Wu, X. (2020) · International Journal of Bifurcation and Chaos · doi:10.1142/s0218127420501345 · Cited by 8
A Regulatory Network of G2/M Phase Transition for DNA Damage
Zhang, L., & Liew, K. M. (2013) · Applied Mechanics and Materials · doi:10.4028/www.scientific.net/amm.444-445.1182 · Cited by 7
Two‐dimensional polynomial type canonical relaxation oscillator model for p53 dynamics
Demirkıran, G., Demir, G. K., & Guzelis, C. (2018) · IET Systems Biology · doi:10.1049/iet-syb.2017.0077 · Cited by 7
p53/E2F1/miR-25 axis regulates apoptosis induction in glioblastoma cells: a qualitative model
Silveira, D. A., Gupta, S., & Mombach, J. C. M. (2020) · Journal of Physics Complexity · doi:10.1088/2632-072x/aba3bb · Cited by 7
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Wang, C., Liu, H., Miao, Z., & Zhou, J. (2020) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2020.3040368 · Cited by 7
Formal verification confirms the role of p53 protein in cell fate decision mechanism
Mahmoud, E. A., Herajy, M., Ziedan, I., & Shehata, H. I. (2022) · Theory in Biosciences · doi:10.1007/s12064-022-00381-x · Cited by 7
Interplay of p53 and XIAP protein dynamics orchestrates cell fate in response to chemotherapy
Abukwaik, R., Vera-Sigüenza, E., Tennant, D. A., & Spill, F. (2023) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2023.111562 · Cited by 7
Mathematical modeling of p53 pulses in G2 phase with DNA damage
Zhang, L., Cheng, Y., & Liew, K. M. (2014) · Applied Mathematics and Computation · doi:10.1016/j.amc.2014.01.120 · Cited by 7
Zhang, L., Cheng, Y., & Liew, K. M. (2014) · Applied Mathematics and Computation · doi:10.1016/j.amc.2014.01.081 · Cited by 7
Guthrie, O. W. (2017) · Experimental Cell Research · doi:10.1016/j.yexcr.2017.08.010 · Cited by 7
Mathematical analysis of a generalised p53-Mdm2 protein gene expression model
Piotrowska, M. J., Bartłomiejczyk, A., & Bodnar, M. (2018) · Applied Mathematics and Computation · doi:10.1016/j.amc.2018.01.014 · Cited by 7
Oscillatory Dynamics of p53-Mdm2 Circuit in Response to DNA Damage Caused by Ionizing Radiation
Zhang, Y., Liu, H., Li, Z., Miao, Z., & Zhou, J. (2019) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2019.2899574 · Cited by 7
Dynamic Behavior of p53 Driven by Delay and a Microrna-34a-Mediated Feedback Loop
Gao, C., Liu, H., & Yan, F. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21041271 · Cited by 7
Potential dynamic analysis of tumor suppressor p53 regulated by Wip1 protein*
Liu, N., Wang, D., Liu, H., Yang, H., & Yang, L. (2020) · Chinese Physics B · doi:10.1088/1674-1056/ab84d1 · Cited by 7
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Wang, D.-G., Zhou, C.-H., & Zhang, X. (2017) · Chinese Physics B · doi:10.1088/1674-1056/26/12/128709 · Cited by 7
Self-citationOscillatory Dynamics and Regulatory Mechanisms of the p53–Per2 Network in DNA-Damaged Cells
Wang, C., Zhang, Y., Cao, J., & Yang, Z. (2024) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2024.3424784 · Cited by 6
Metadata
- Authors
- Zhang, X.-P., Liu, F., & Wang, W.
- Affiliations
- National Laboratory of Solid State Microstructures (CN)
- University of California System (US)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2011-05-16
- Volume
- 108
- Issue
- 22
- Pages
- 8990-8995
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC3107314
- OpenAlex
- W2058631780
- Cited by
- 333
- References
- 55
- Citations by year
- 2026: 8 · 2025: 14 · 2024: 17 · 2023: 27 · 2022: 31 · 2021: 27 · 2020: 25 · 2019: 27 · 2018: 15 · 2017: 24 · 2016: 14 · 2015: 18 · 2014: 35 · 2013: 21 · 2012: 25
- FWCI
- 13.56
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (10834002)
- Government of Jiangsu Province
- Natural Science Foundation of Jiangsu Province (BK2009008)
- Program for New Century Excellent Talents in University (NCET-08, NCET-08-0269)
- National Key Research and Development Program of China (2007CB814806)
- Topics
- Health Sciences › Medicine › Oncology › Cancer-related Molecular Pathways
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Physical Sciences › Mathematics › Modeling and Simulation › Mathematical Biology Tumor Growth
- Keywords
- p53, DNA damage response, ionizing radiation, cell cycle arrest, apoptosis, post-translational modification, p53 phosphorylation, ATM, MDM2, Wip1, negative feedback loop, cell fate determination, mathematical modeling of gene regulation
- MeSH terms
- DNA Damage, DNA Repair, DNA-Binding Proteins, Humans, Models, Theoretical, Neoplasms, Oscillometry, Phosphorylation, Serine, Time Factors, Signal Transduction, Genes, p53, Tumor Suppressor Protein p53, Apoptosis, Protein Serine-Threonine Kinases, Cell Cycle Proteins, Cell Lineage, Tumor Suppressor Proteins, Ataxia Telangiectasia Mutated Proteins
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