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Williams KS, Secomb TW, El-Kareh AW. An autonomous mathematical model for the mammalian cell cycle. J Theor Biol 2023; 569:111533. [PMID: 37196820 DOI: 10.1016/j.jtbi.2023.111533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 04/04/2023] [Accepted: 05/10/2023] [Indexed: 05/19/2023]
Abstract
A mathematical model for the mammalian cell cycle is developed as a system of 13 coupled nonlinear ordinary differential equations. The variables and interactions included in the model are based on detailed consideration of available experimental data. A novel feature of the model is inclusion of cycle tasks such as origin licensing and initiation, nuclear envelope breakdown and kinetochore attachment, and their interactions with controllers (molecular complexes involved in cycle control). Other key features are that the model is autonomous, except for a dependence on external growth factors; the variables are continuous in time, without instantaneous resets at phase boundaries; mechanisms to prevent rereplication are included; and cycle progression is independent of cell size. Eight variables represent cell cycle controllers: the Cyclin D1-Cdk4/6 complex, APCCdh1, SCFβTrCP, Cdc25A, MPF, NuMA, the securin-separase complex, and separase. Five variables represent task completion, with four for the status of origins and one for kinetochore attachment. The model predicts distinct behaviors corresponding to the main phases of the cell cycle, showing that the principal features of the mammalian cell cycle, including restriction point behavior, can be accounted for in a quantitative mechanistic way based on known interactions among cycle controllers and their coupling to tasks. The model is robust to parameter changes, in that cycling is maintained over at least a five-fold range of each parameter when varied individually. The model is suitable for exploring how extracellular factors affect cell cycle progression, including responses to metabolic conditions and to anti-cancer therapies.
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Affiliation(s)
| | - Timothy W Secomb
- BIO5 Institute, University of Arizona, Tucson, AZ, USA; Department of Physiology, University of Arizona, Tucson, AZ, USA
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Obesity, oxidative DNA damage and vitamin D as predictors of genomic instability in children and adolescents. Int J Obes (Lond) 2021; 45:2095-2107. [PMID: 34158611 PMCID: PMC8380542 DOI: 10.1038/s41366-021-00879-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 05/18/2021] [Accepted: 05/27/2021] [Indexed: 02/05/2023]
Abstract
BACKGROUND/OBJECTIVES Epidemiological evidence indicates obesity in childhood and adolescence to be an independent risk factor for cancer and premature mortality in adulthood. Pathological implications from excess adiposity may begin early in life. Obesity is concurrent with a state of chronic inflammation, a well-known aetiological factor for DNA damage. In addition, obesity has been associated with micro-nutritional deficiencies. Vitamin D has attracted attention for its anti-inflammatory properties and role in genomic integrity and stability. The aim of this study was to determine a novel approach for predicting genomic instability via the combined assessment of adiposity, DNA damage, systemic inflammation, and vitamin D status. SUBJECTS/METHODS We carried out a cross-sectional study with 132 participants, aged 10-18, recruited from schools and paediatric obesity clinics in London. Anthropometric assessments included BMI Z-score, waist and hip circumference, and body fat percentage via bioelectrical impedance. Inflammation and vitamin D levels in saliva were assessed by enzyme-linked immunosorbent assay. Oxidative DNA damage was determined via quantification of 8-hydroxy-2'-deoxyguanosine in urine. Exfoliated cells from the oral cavity were scored for genomic instability via the buccal cytome assay. RESULTS As expected, comparisons between participants with obesity and normal range BMI showed significant differences in anthropometric measures (p < 0.001). Significant differences were also observed in some measures of genomic instability (p < 0.001). When examining relationships between variables for all participants, markers of adiposity positively correlated with acquired oxidative DNA damage (p < 0.01) and genomic instability (p < 0.001), and negatively correlated with vitamin D (p < 0.01). Multiple regression analyses identified obesity (p < 0.001), vitamin D (p < 0.001), and oxidative DNA damage (p < 0.05) as the three significant predictors of genomic instability. CONCLUSIONS Obesity, oxidative DNA damage, and vitamin D deficiency are significant predictors of genomic instability. Non-invasive biomonitoring and predictive modelling of genomic instability in young patients with obesity may contribute to the prioritisation and severity of clinical intervention measures.
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Erenpreisa J, Salmina K, Anatskaya O, Cragg MS. Paradoxes of cancer: Survival at the brink. Semin Cancer Biol 2020; 81:119-131. [PMID: 33340646 DOI: 10.1016/j.semcancer.2020.12.009] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 12/07/2020] [Accepted: 12/09/2020] [Indexed: 12/17/2022]
Abstract
The fundamental understanding of how Cancer initiates, persists and then progresses is evolving. High-resolution technologies, including single-cell mutation and gene expression measurements, are now attainable, providing an ever-increasing insight into the molecular details. However, this higher resolution has shown that somatic mutation theory itself cannot explain the extraordinary resistance of cancer to extinction. There is a need for a more Systems-based framework of understanding cancer complexity, which in particular explains the regulation of gene expression during cell-fate decisions. Cancer displays a series of paradoxes. Here we attempt to approach them from the view-point of adaptive exploration of gene regulatory networks at the edge of order and chaos, where cell-fate is changed by oscillations between alternative regulators of cellular senescence and reprogramming operating through self-organisation. On this background, the role of polyploidy in accessing the phylogenetically pre-programmed "oncofetal attractor" state, related to unicellularity, and the de-selection of unsuitable variants at the brink of cell survival is highlighted. The concepts of the embryological and atavistic theory of cancer, cancer cell "life-cycle", and cancer aneuploidy paradox are dissected under this lense. Finally, we challenge researchers to consider that cancer "defects" are mostly the adaptation tools of survival programs that have arisen during evolution and are intrinsic of cancer. Recognition of these features should help in the development of more successful anti-cancer treatments.
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Affiliation(s)
| | - Kristine Salmina
- Latvian Biomedical Research and Study Centre, Riga, LV-1067, Latvia
| | | | - Mark S Cragg
- Centre for Cancer Immunology, Faculty of Medicine, University of Southampton, Southampton, SO16 6YD, UK
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Nishimura K, Watanabe S, Kaku T, Sugishima S. Serum starvation induces abnormal spindle location, RhoA delocalization, and extension of intercellular bridge with the midbody. Biosci Biotechnol Biochem 2018; 82:1-6. [PMID: 29499630 DOI: 10.1080/09168451.2018.1443791] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2017] [Accepted: 02/10/2018] [Indexed: 10/17/2022]
Abstract
Serum starvation induces binucleation in HeLa cells, but the effects of serum starvation on mitosis and the significance of binucleation remain unknown. We investigated the effect of serum starvation on mitosis and analyzed the growth of binucleated cells. The frequency of binucleation caused by cytokinesis failure in DMEM without FBS (0% medium) was higher than that in DMEM with FBS (10% medium). In 0% medium, the metaphase spindle location was off-center, and RhoA localization significantly lacked symmetry. The frequency of the extension of intercellular bridge with the midbody in 0% medium was significantly higher than that in 10% medium. Moreover, all mononucleated mitotic cells caused bipolar mitosis and produced only mononucleated daughter cells, but binucleated cells produced various nucleated cells by multipolar mitosis in 0% medium. These results suggest that serum starvation may have various effects on mitosis, and binucleated cells may be related to formation of aneuploidy.
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Affiliation(s)
- Kazunori Nishimura
- a Department of Health Sciences, Graduate School of Medical Sciences , Kyushu University , Fukuoka City , Japan
| | - Sumiko Watanabe
- b Faculty of Medical Sciences, Department of Health Sciences , Kyushu University , Fukuoka City , Japan
| | - Tsunehisa Kaku
- b Faculty of Medical Sciences, Department of Health Sciences , Kyushu University , Fukuoka City , Japan
| | - Setsuo Sugishima
- b Faculty of Medical Sciences, Department of Health Sciences , Kyushu University , Fukuoka City , Japan
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Liu F, Wang J, Yang X, Li B, Wu H, Qi S, Chen C, Liu X, Yu K, Wang W, Zhao Z, Wang A, Chen Y, Wang L, Gray NS, Liu J, Zhang X, Liu Q. Discovery of a Highly Selective STK16 Kinase Inhibitor. ACS Chem Biol 2016; 11:1537-43. [PMID: 27082499 DOI: 10.1021/acschembio.6b00250] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
STK16, a serine/threonine protein kinase, is ubiquitously expressed and is conserved among all eukaryotes. STK16 has been implicated to function in a variety of cellular processes such as VEGF and cargo secretion, but the pathways through which these effects are mediated remain to be elucidated. Through screening of our focused library of kinase inhibitors, we discovered a highly selective ATP competitive inhibitor, STK16-IN-1, which exhibits potent inhibitory activity against STK16 kinase (IC50: 0.295 μM) with excellent selectivity across the kinome as assessed using the KinomeScan profiling assay (S score (1) = 0.0). In MCF-7 cells, treatment with STK16-IN-1 results in a reduction in cell number and accumulation of binucleated cells, which can be recapitulated by RNAi knockdown of STK16. Co-treatment of STK16-IN-1 with chemotherapeutics such as cisplatin, doxorubicin, colchicine, and paclitaxel results in a slight potentiation of the antiproliferative effects of the chemotherapeutics. STK16-IN-1 provides a useful tool compound for further elucidating the biological functions of STK16.
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Affiliation(s)
- Feiyang Liu
- High Magnetic Field Laboratory, Chinese Academy of Sciences, 350 Shushanhu Road, P.O. Box 1110, Hefei, Anhui 230031, People’s Republic of China
- University of Science and Technology of China, Hefei, Anhui 230036, People’s Republic of China
| | - Jinhua Wang
- Department of Biological Chemistry & Molecular Pharmacology, Harvard Medical School, 250 Longwood Ave, SGM 628, Boston, Massachusetts 02115, United States
| | - Xingxing Yang
- High Magnetic Field Laboratory, Chinese Academy of Sciences, 350 Shushanhu Road, P.O. Box 1110, Hefei, Anhui 230031, People’s Republic of China
| | - Binhua Li
- High Magnetic Field Laboratory, Chinese Academy of Sciences, 350 Shushanhu Road, P.O. Box 1110, Hefei, Anhui 230031, People’s Republic of China
- CHMFL-HCMTC Target Therapy Joint Laboratory, Shushanhu Road, Hefei, Anhui 230031, People’s Republic of China
| | - Hong Wu
- High Magnetic Field Laboratory, Chinese Academy of Sciences, 350 Shushanhu Road, P.O. Box 1110, Hefei, Anhui 230031, People’s Republic of China
- University of Science and Technology of China, Hefei, Anhui 230036, People’s Republic of China
| | - Shuang Qi
- High Magnetic Field Laboratory, Chinese Academy of Sciences, 350 Shushanhu Road, P.O. Box 1110, Hefei, Anhui 230031, People’s Republic of China
- CHMFL-HCMTC Target Therapy Joint Laboratory, Shushanhu Road, Hefei, Anhui 230031, People’s Republic of China
| | - Cheng Chen
- High Magnetic Field Laboratory, Chinese Academy of Sciences, 350 Shushanhu Road, P.O. Box 1110, Hefei, Anhui 230031, People’s Republic of China
- CHMFL-HCMTC Target Therapy Joint Laboratory, Shushanhu Road, Hefei, Anhui 230031, People’s Republic of China
| | - Xiaochuan Liu
- High Magnetic Field Laboratory, Chinese Academy of Sciences, 350 Shushanhu Road, P.O. Box 1110, Hefei, Anhui 230031, People’s Republic of China
- University of Science and Technology of China, Hefei, Anhui 230036, People’s Republic of China
| | - Kailin Yu
- High Magnetic Field Laboratory, Chinese Academy of Sciences, 350 Shushanhu Road, P.O. Box 1110, Hefei, Anhui 230031, People’s Republic of China
- University of Science and Technology of China, Hefei, Anhui 230036, People’s Republic of China
| | - Wenchao Wang
- High Magnetic Field Laboratory, Chinese Academy of Sciences, 350 Shushanhu Road, P.O. Box 1110, Hefei, Anhui 230031, People’s Republic of China
- CHMFL-HCMTC Target Therapy Joint Laboratory, Shushanhu Road, Hefei, Anhui 230031, People’s Republic of China
| | - Zheng Zhao
- High Magnetic Field Laboratory, Chinese Academy of Sciences, 350 Shushanhu Road, P.O. Box 1110, Hefei, Anhui 230031, People’s Republic of China
- CHMFL-HCMTC Target Therapy Joint Laboratory, Shushanhu Road, Hefei, Anhui 230031, People’s Republic of China
| | - Aoli Wang
- High Magnetic Field Laboratory, Chinese Academy of Sciences, 350 Shushanhu Road, P.O. Box 1110, Hefei, Anhui 230031, People’s Republic of China
- University of Science and Technology of China, Hefei, Anhui 230036, People’s Republic of China
| | - Yongfei Chen
- High Magnetic Field Laboratory, Chinese Academy of Sciences, 350 Shushanhu Road, P.O. Box 1110, Hefei, Anhui 230031, People’s Republic of China
- CHMFL-HCMTC Target Therapy Joint Laboratory, Shushanhu Road, Hefei, Anhui 230031, People’s Republic of China
| | - Li Wang
- High Magnetic Field Laboratory, Chinese Academy of Sciences, 350 Shushanhu Road, P.O. Box 1110, Hefei, Anhui 230031, People’s Republic of China
- CHMFL-HCMTC Target Therapy Joint Laboratory, Shushanhu Road, Hefei, Anhui 230031, People’s Republic of China
| | - Nathanael S. Gray
- Department of Biological Chemistry & Molecular Pharmacology, Harvard Medical School, 250 Longwood Ave, SGM 628, Boston, Massachusetts 02115, United States
| | - Jing Liu
- High Magnetic Field Laboratory, Chinese Academy of Sciences, 350 Shushanhu Road, P.O. Box 1110, Hefei, Anhui 230031, People’s Republic of China
- CHMFL-HCMTC Target Therapy Joint Laboratory, Shushanhu Road, Hefei, Anhui 230031, People’s Republic of China
| | - Xin Zhang
- High Magnetic Field Laboratory, Chinese Academy of Sciences, 350 Shushanhu Road, P.O. Box 1110, Hefei, Anhui 230031, People’s Republic of China
| | - Qingsong Liu
- High Magnetic Field Laboratory, Chinese Academy of Sciences, 350 Shushanhu Road, P.O. Box 1110, Hefei, Anhui 230031, People’s Republic of China
- University of Science and Technology of China, Hefei, Anhui 230036, People’s Republic of China
- CHMFL-HCMTC Target Therapy Joint Laboratory, Shushanhu Road, Hefei, Anhui 230031, People’s Republic of China
- Hefei Science
Center, Chinese Academy of Sciences, Shushanhu Road, Hefei, Anhui 230031, People’s Republic of China
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