Mathematical modeling reveals the factors involved in the phenomena of cancer stem cells stabilization
Autoři:
Nikolay Bessonov aff001; Guillaume Pinna aff002; Andrey Minarsky aff003; Annick Harel-Bellan aff002; Nadya Morozova aff002
Působiště autorů:
Institute of Problems of Mechanical Engineering, Russian Academy of Sciences, Saint-Petersburg, Russia
aff001; Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, University Paris‐Sud, University Paris‐Saclay, Gif‐sur‐Yvette, France
aff002; Saint-Petersburg Academic University, Russian Academy of Sciences, Saint-Petersburg, Russia
aff003; Institut des Hautes Etudes Scientiques (IHES), Bures-sur-Yvette, France
aff004
Vyšlo v časopise:
PLoS ONE 14(11)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0224787
Souhrn
Cancer Stem Cells (CSC), a subset of cancer cells resembling normal stem cells with self-renewal and asymmetric division capabilities, are present at various but low proportions in many tumors and are thought to be responsible for tumor relapses following conventional cancer therapies. In vitro, most intriguingly, isolated CSCs rapidly regenerate the original population of stem and non-stem cells (non-CSCs) as shown by various investigators. This phenomenon still remains to be explained. We propose a mathematical model of cancer cell population dynamics, based on the main parameters of cell population growth, including the proliferation rates, the rates of cell death and the frequency of symmetric and asymmetric cell divisions both in CSCs and non-CSCs sub-populations, and taking into account the stabilization phenomenon. The analysis of the model allows determination of time-varying corridors of probabilities for different cell fates, given the particular dynamics of cancer cells populations; and determination of a cell-cell communication factors influencing these time-varying probabilities of cell behavior (division, transition) scenarios. Though the results of the model have to be experimentally confirmed, we can anticipate the development of several fundamental and practical applications based on the theoretical results of the model.
Klíčová slova:
Cell cycle and cell division – Cell death – Mathematical models – Population dynamics – Stem cell therapy – Stem cells – Cancer stem cells – Tumor stem cells
Zdroje
1. Lutz C, Hoang VT, Ho AD. Identifying leukemia stem cells—is it feasible and does it matter? Cancer Lett 2013;338: pp.10–14. doi: 10.1016/j.canlet.2012.07.014 22820159
2. Chen SY, Huang YC, Liu SP, Tsai FJ, Shyu WC, Lin SZ. An overview of concepts. Cell Transplant 2011;20: pp.113–120. doi: 10.3727/096368910X532837 20887682
3. Buss EC, Ho AD. Leukemia stem cells. Int. J. Cancer 2011;129, pp.2328–2336. doi: 10.1002/ijc.26318 21796620
4. Reya T., Morrison S.J., Clarke M.F., Weissman I.L. Stem cells, cancer, and cancer stem cells. Nature, 414 (2001), pp.105–111. doi: 10.1038/35102167 11689955
5. Dean M., Fojo T. and Bates S. Tumour stem cells and drug resistance. Nat. Rev. Cancer, 5(2005), pp. 275–284. doi: 10.1038/nrc1590 15803154
6. Clarke M.F., Dick J.E., Dirks P.B., Eaves C.J., Jamieson C.H., Jones D.L. et al. Cancer stem cells-Perspectives on current status and future directions: AACR workshop on cancer stem cells. Cancer Res., 66(2006), pp.9339–9344. doi: 10.1158/0008-5472.CAN-06-3126 16990346
7. Bao S., Wu Q., McLendon R.E., Hao Y., Shi Q., Hjelmeland A.B. et al. Glioma stem cells promote radioresistance by preferential ac-tivation of the DNA damage response. Nature, 444 (2006), pp. 756–760. doi: 10.1038/nature05236 17051156
8. O’Brien C.A., Pollett A., Gallinger S., Dick J.E. A human colon cancer cell capable of initiating tumour growth in immunodeficient mice. Nature, 445 (2007), pp. 106–110. doi: 10.1038/nature05372 17122772
9. Ricci-Vitiani L., Lombardi D.G., Pilozzi E., Biffoni M., Todaro M., Peschle C. et al. Identification and expansion of human colon-cancer-initiating cells. Nature, 445 (2007), pp. 111–115. doi: 10.1038/nature05384 17122771
10. Li C., Heidt D.G., Dalerba P., Burant C.F., Zhang L., Adsay V. et al. Identification of pancreatic cancer stem cells. Cancer Res., 67 (2007), pp.1030–1037. doi: 10.1158/0008-5472.CAN-06-2030 17283135
11. Charafe-Jauffret E, Ginestier C, Bertucci F, Cabaud O, Wicinski J, Finetti P. et al. ALDH1-positive cancer stem cells predict engraftment of primary breast tumors and are governed by a common stem cell program. Cancer Res. 2013 Dec 15;73(24), pp.7290–7300. doi: 10.1158/0008-5472.CAN-12-4704 24142344
12. Kreso A., Dick J.E. Evolution of the cancer stem cell model. Cell Stem Cell, 14 (2014), pp. 275–291. doi: 10.1016/j.stem.2014.02.006 24607403
13. Visvader J.E., Lindeman G.J. Cancer stem cells: current status and evolving complexities. Cell Stem Cell, 10 (2012), pp. 717–728. doi: 10.1016/j.stem.2012.05.007 22704512
14. Liu S., Wicha M.S. Targeting breast cancer stem cells. J. Clin. Oncol., 28 (2010), pp. 4006–4012. doi: 10.1200/JCO.2009.27.5388 20498387
15. Mani S.A., Guo W., Liao M.J., Eaton E.N., Ayyanan A., Zhou A.Y. et al. The epithelial-mesenchymal transition generates cells with properties of stem cells.Cell, 133 (2008), 704–715p. doi: 10.1016/j.cell.2008.03.027 18485877
16. Ginestier C., Wicha M.S. Mammary stem cell number as a determinate of breast cancer risk. Breast Cancer Res., 9 (2007), 109–126. doi: 10.1186/bcr1741 17688678
17. Cicalese A., Bonizzi G., Pasi C.E., Faretta M., Ronzoni S., Giulini B. et al. The Tumor Suppressor p53 Regulates Polarity of Self-Renewing Divisions in Mammary Stem Cells. Cell, V. 138, Iss.6, 2009, pp.1083–1095. doi: 10.1016/j.cell.2009.06.048 19766563
18. Zhang S., Balch C., Chan M.W., Lai H.C., Matei D., Schilder J.M. et al. Identification and characterization of ovarian cancer-initiating cells from human tumors. Cancer Res., 68 (2008), pp.4311–4320. doi: 10.1158/0008-5472.CAN-08-0364 18519691
19. Maitland N.J. Collins A.T. Prostate cancer stem cells: a new target for therapy. J. Clin.Oncol., 26 (2008), pp.2862–2870. doi: 10.1200/JCO.2007.15.1472 18539965
20. Gupta P.B., Onder T.T., Jiang G., Tao K., Kuperwasser C., Weinberg R.A. et al. Identification of selective inhibitors of cancer stem cells by high-throughput screening. Cell,138 (2009), pp.645–659. doi: 10.1016/j.cell.2009.06.034 19682730
21. El Helou R, Pinna G, Cabaud O, Wicinski J, Bhajun R, Guyon L, et al. miR-600 Acts as a Bimodal Switch that Regulates Breast Cancer Stem Cell Fate through WNT Signaling. Cell Rep. 2017 Feb 28;18(9), pp.2256–2268. doi: 10.1016/j.celrep.2017.02.016 28249169
22. Polytarchou C., Iliopoulos D., Struhl K. An integrated transcriptional regulatory circuit that reinforces the breast cancer stem cell state. Proc. Natl. Acad. Sci. USA, 109 (2012), pp. 14470–14475. doi: 10.1073/pnas.1212811109 22908280
23. Song S.J., Ito K., Ala U., Kats L., Webster K., Sun S.M., et al. The oncogenic microRNA miR-22 targets the TET2 tumor suppressor to promote hematopoietic stem cell self-renewal and transformation. Cell Stem Cell, 13 (2013), pp. 87–101. doi: 10.1016/j.stem.2013.06.003 23827711
24. Bu P., Chen K.Y., Chen J.H., Wang L., Walters J., Shin Y.J., et al J.P. A microRNA miR-34a-regulated bimodal switch targets Notch in colon cancer stem cells. Cell Stem Cell, 12 (2013), pp. 602–615. doi: 10.1016/j.stem.2013.03.002 23642368
25. Hwang W.L., Jiang J.K., Yang S.H., Huang T.S., Lan H.Y., Teng H.W., et al. MicroRNA-146a directs the symmetric division of Snail-dominant colorectal cancer stem cells. Nat. Cell Biol., 16 (2014), pp. 268–280. doi: 10.1038/ncb2910 24561623
26. Liu C., Kelnar K., Liu B., Chen X., Calhoun-Davis T., Li H., et al. The microRNA miR-34a inhibits prostate cancer stem cells and metastasis by directly repressing CD44. Nat. Med., 17 (2011), pp. 211–215. doi: 10.1038/nm.2284 21240262
27. Wang H., Sun T., Hu J., Zhang R., Rao Y., Wang S., et al R. miR-33a promotes glioma-initiating cell self-renewal via PKA and NOTCH pathways. J. Clin. Invest., 124 (2014), pp. 4489–4502. doi: 10.1172/JCI75284 25202981
28. Taube J.H., Malouf G.G., Lu E., Sphyris N., Vijay V., Ramachandran P.P., et al. Epigenetic silencing of microRNA-203 is required for EMT and cancer stem cell properties. Sci. Rep., 3 (2013), p. 2687. doi: 10.1038/srep02687 24045437
29. Diehn M., Clarke M.F. Cancer stem cells and radiotherapy: new insights into tumor radioresistance. J. Natl. Cancer Inst., 98 (2006), pp.1755–1757. doi: 10.1093/jnci/djj505 17179471
30. Goldman A, Majumder B, Dhawan A, Ravi S, Goldman D, Kohandel M, et al. Temporally sequenced anticancer drugs overcome adaptive resistance by targeting a vulnerable chemotherapy-induced phenotypic transition. Nature communications, 2015, 6:6139. doi: 10.1038/ncomms7139 25669750
31. Stiehl T, Baran N, Ho AD, Marciniak-Czochra A. Clonal selection and therapy resistance in acute leukaemias: mathematical modelling explains different proliferation patterns at diagnosis and relapse. Journal of The Royal Society Interface 11 (94), (2014), p.79.
32. Loeffler M., Roeder I. Conceptual models to understand tissue stem cell organization. Current Opinion in Hematology 2004, 11, pp.81–87. 15257023
33. Roeder I., Herberg M., Horn M. An”Age” structured model of hemapoietic stem cell organization with application to chronic myeloid leukemia. Bull. Math. Biol., 71 (2009), pp. 602–626. doi: 10.1007/s11538-008-9373-7 19101772
34. Yang J, Plikus MV, Komarova NL. The Role of Symmetric Stem Cell Divisions in Tissue Homeostasis. PLoS Comput Biol. 2015 Dec 23;11(12):e1004629. doi: 10.1371/journal.pcbi.1004629 26700130
35. Yang J, Axelrod DE, Komarova NL. Determining the control networks regulating stem cell lineages in colonic crypts. J Theor Biol. 2017 Sep 21;429,pp.190–203. doi: 10.1016/j.jtbi.2017.06.033 28669884
36. Komarova NL. Principles of regulation of self-renewing cell lineages. PLoS One. 2013 Sep 3;8(9):e72847. doi: 10.1371/journal.pone.0072847 24019882
37. D’Onofrio A., Tomlison I.P.M. A nonlinear mathematical model of cell renewal, turnover and tumorigenesys in colon crypts. J. Theor. Biol., 244 (2007), pp. 367–374. doi: 10.1016/j.jtbi.2006.08.022 17049944
38. Gupta PB, Fillmore CM, Jiang G, Shapira SD, Tao K, Kuperwasser C, et al. Stochastic state transitions give rise to phenotypic equilibrium in populations of cancer cells. Cell. (2011) Aug 19;146(4), pp.633–44. doi: 10.1016/j.cell.2011.07.026 21854987
39. Enderling H., Hlatky L., Hahnfeldt P. Cancer Stem Cells: A Minor Cancer Subpopulation that Redefines Global Cancer Features. Front Oncol. 2013; 3: 76. doi: 10.3389/fonc.2013.00076 23596563
40. Stiehl T, Baran N, AD Ho, Marciniak-Czochra A. Cell division patterns in acute myeloid leukemia stem-like cells determine clinical course: a model to predict patient survival. Cancer research 75 (6), (2015), p.940–949. doi: 10.1158/0008-5472.CAN-14-2508 25614516
41. Marciniak-Czochra A, Stiehl T, Ho AD, Jäger W, Wagner W. Modeling of asymmetric cell division in hematopoietic stem cells—regulation of self-renewal is essential for efficient repopulation. Stem cells and development, 2009, 18 (3), pp. 377–386. doi: 10.1089/scd.2008.0143 18752377
42. Stiehl T. and Marciniak-Czochra A. Mathematical Modeling of Leukemogenesis and Cancer Stem Cell Dynamics. Math. Model. Nat. Phenom. Vol. 7, 2012, pp. 166–202.
43. Stiehl T., Baran N., AD Ho and Marciniak-Czochra A. Cell division patterns in acute myeloid leukemia stem-like cells determine clinical course: a model to predict patient survival. Cancer Res. 2015 Mar 15;75(6), pp. 940–949. doi: 10.1158/0008-5472.CAN-14-2508 25614516
44. Werner B, Scott JG, Sottoriva A, Anderson AR, Traulsen A, Altrock PM. The Cancer Stem Cell Fraction in Hierarchically Organized Tumors Can Be Estimated Using Mathematical Modeling and Patient-Specific Treatment Trajectories. Cancer Res. 2016 Apr 1;76(7), pp. 1705–1713. doi: 10.1158/0008-5472.CAN-15-2069 26833122
45. Poleszczuk J, Hahnfeldt P, Enderling H. Evolution and phenotypic selection of cancer stem cells. PLoS Comput Biol. 2015 Mar 5;11(3):e1004025. doi: 10.1371/journal.pcbi.1004025 25742563
46. Craig M, Humphries AR, Mackey MC. A Mathematical Model of Granulopoiesis Incorporating the Negative Feedback Dynamics and Kinetics of G-CSF/Neutrophil Binding and Internalization. Bull Math Biol. 2016 Dec;78(12), pp.2304–2357. doi: 10.1007/s11538-016-0179-8 27324993
47. Stiehl T., AD Ho and Marciniak-Czochra A.. Mathematical modeling of the impact of cytokine response of acute myeloid leukemia cells on patient prognosis., Sci Rep. 2018 Feb 12;8(1):2809. doi: 10.1038/s41598-018-21115-4 29434256
48. Johnston M.D., Edwards C.M., Bodmer W.F., Maini P.K., Chapman S.J. Mathematical modelling of cell population dynamics in the colonic crypt and in colorectal cancer. PNAS,104 (2007), pp. 4008–4013. doi: 10.1073/pnas.0611179104 17360468
49. Theise N.D., d'Inverno M. Understanding cell lineages as complex adaptive systems. Blood Cells Mol Dis. 2004 Jan-Feb;32(1), pp. 17–20. 14757407
50. Theise N.D. Perspective: stem cells react! Cell lineages as complex adaptivesystems. Exp Hematol 2004, 32, pp.25–27. doi: 10.1016/j.exphem.2003.10.012 14725897
51. Michor F., Mathematical models of cancer stem cells. J. Clin. Oncol., 26 (2008), pp.2854–2861. doi: 10.1200/JCO.2007.15.2421 18539964
52. Chaffer C.L., Brueckmann I., Scheel C., Kaestli A.J., Wiggins P.A., Rodrigues L.O., et al. Normal and neoplastic nonstem cells can spontaneously convert to a stem-like state. Proc. Natl. Acad. Sci. 108, (2011) pp.7950–7955. doi: 10.1073/pnas.1102454108 21498687
53. Beretta E, Capasso V, Harel-Bellan A, Morozova N. Mathematical Modelling of Cancer Stem Cells Population Behavior. Math Mod Nat Phen, V. 7, Is. 1, (2012), p.279 – 305.
54. Beretta E, Capasso V, Harel-Bellan A, Morozova N. Some Results on the Population Behavior of Cancer Stem Cells. In: New Challenges for Cancer Systems Biomedicine. d’Onofrio, Cerrai, Gandolfi (eds), Simai Springer Series. 2012.
55. Fathi E, Farahzadi R, Valipour B, Sanaat Z. Cytokines secreted from bone marrow derived mesenchymal stem cells promote apoptosis and change cell cycle distribution of K562 cell line as clinical agent in cell transplantation. PLoS One. 2019 Apr 22;14(4):e0215678. doi: 10.1371/journal.pone.0215678 31009502
56. Akbarian V, Wang W, Audet J. Measurement of generation-dependent proliferation rates and death rates during mouse erythroid progenitor cell differentiation. Cytometry A. 2012 May;81(5), pp.382–389. doi: 10.1002/cyto.a.22031 22407926
57. Zhou F, Rasmussen A, Lee S, Agaisse H. The UPD3 cytokine couples environmental challenge and intestinal stem cell division through modulation of JAK/STAT signaling in the stem cell microenvironment. Dev Biol. 2013 Jan 15;373(2),pp.383–393. doi: 10.1016/j.ydbio.2012.10.023 23110761
58. d’Onofrio A, Caravagna G, Franciscis S. Bounded noise induced first-order phase transitions in a baseline non-spatial model of gene transcription. Physica A, 2018, v.492, pp. 2056–2068.
Článek vyšel v časopise
PLOS One
2019 Číslo 11
- S diagnostikou Parkinsonovy nemoci může nově pomoci AI nástroj pro hodnocení mrkacího reflexu
- Proč při poslechu některé muziky prostě musíme tančit?
- Je libo čepici místo mozkového implantátu?
- Chůze do schodů pomáhá prodloužit život a vyhnout se srdečním chorobám
- Pomůže v budoucnu s triáží na pohotovostech umělá inteligence?
Nejčtenější v tomto čísle
- A daily diary study on maladaptive daydreaming, mind wandering, and sleep disturbances: Examining within-person and between-persons relations
- A 3’ UTR SNP rs885863, a cis-eQTL for the circadian gene VIPR2 and lincRNA 689, is associated with opioid addiction
- A substitution mutation in a conserved domain of mammalian acetate-dependent acetyl CoA synthetase 2 results in destabilized protein and impaired HIF-2 signaling
- Molecular validation of clinical Pantoea isolates identified by MALDI-TOF
Zvyšte si kvalifikaci online z pohodlí domova
Všechny kurzy