No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
Integrated intravital microscopy and mathematical modeling to optimize nanotherapeutics delivery to tumors
1. Franziska Michor, Jan Liphardt, Mauro Ferrari, and Jonathan Widom, “What does physics have to do with cancer?,” Nature reviews 11(9), 657–670 (2011).
5. J. Sinek, H. Frieboes, X. Zheng, and V. Cristini, “Two-dimensional chemotherapy simulations demonstrate fundamental transport and tumor response limitations involving nanoparticles,” Biomed Microdevices 6(4), 297–309 (2004).
6. J. P. Sinek, S. Sanga, X. Zheng, H. B. Frieboes, M. Ferrari, and V. Cristini, “Predicting drug pharmacokinetics and effect in vascularized tumors using computer simulation,” J Math Biol 58(4-5), 485–510 (2009).
7. H. B. Frieboes, M. E. Edgerton, J. P. Fruehauf, F. R. Rose, L. K. Worrall, R. A. Gatenby, M. Ferrari, and V. Cristini, “Prediction of drug response in breast cancer using integrative experimental/computational modeling,” Cancer Res 69(10), 4484–4492 (2009).
8. Helen M. Byrne, “Dissecting cancer through mathematics: from the cell to the animal model,” Nature reviews 10(3), 221–230 (2010).
9. J. S. Lowengrub, H. B. Frieboes, F. Jin, Y. L. Chuang, X. Li, P. Macklin, S. M. Wise, and V. Cristini, “Nonlinear modelling of cancer: bridging the gap between cells and tumours,” Nonlinearity 23(1), R1–R9 (2010).
10. I. M. van Leeuwen, C. M. Edwards, M. Ilyas, and H. M. Byrne, “Towards a multiscale model of colorectal cancer,” World J Gastroenterol 13(9), 1399–1407 (2007).
12. Sergey Astanin and Luigi Preziosi, “Multiphase Models of Tumour Growth: Selected Topics in Cancer Modeling”, (Birkhuser, Boston, 2008), pp. 1–31.
15. T. S. Deisboeck, L. Zhang, J. Yoon, and J. Costa, “In silico cancer modeling: is it ready for prime time?,” Nat Clin Pract Oncol 6(1), 34–42 (2009).
18. S. R. McDougall, A. R. Anderson, M. A. Chaplain, and J. A. Sherratt, “Mathematical modelling of flow through vascular networks: implications for tumour-induced angiogenesis and chemotherapy strategies,” Bull Math Biol 64(4), 673–702 (2002).
19. S. R. McDougall, A. R. Anderson, and M. A. Chaplain, “Mathematical modelling of dynamic adaptive tumour-induced angiogenesis: clinical implications and therapeutic targeting strategies,” J Theor Biol 241(3), 564–589 (2006).
20. A. Stéphanou, S. McDougall, A. Anderson, and M. A. J. Chaplain, “Mathematical modelling of the influence of blood rheological properties upon adaptive tumour-induced angiogenesis,” Math Comput Model 44, 96–123 (2006).
21. M. R. Owen, T. Alarcon, P. K. Maini, and H. M. Byrne, “Angiogenesis and vascular remodelling in normal and cancerous tissues,” J Math Biol 58(4-5), 689–721 (2009).
22. P. Macklin, S. McDougall, A. R. Anderson, M. A. Chaplain, V. Cristini, and J. Lowengrub, “Multiscale modelling and nonlinear simulation of vascular tumour growth,” J Math Biol 58(4-5), 765–798 (2009).
23. T. L. Jackson, “Intracellular accumulation and mechanism of action of doxorubicin in a spatio-temporal tumor model,” J Theor Biol 220(2), 201–213 (2003).
24. E. S. Norris, J. R. King, and H. M. Byrne, “Modelling the response of spatially structured tumours to chemotherapy: drug kinetics,” Math Comput Model 43, 820–837 (2006).
25. H. Enderling, M. A. Chaplain, A. R. Anderson, and J. S. Vaidya, “A mathematical model of breast cancer development, local treatment and recurrence,” J Theor Biol 246(2), 245–259 (2007).
28. H. B. Frieboes, X. Zheng, C. H. Sun, B. Tromberg, R. Gatenby, and V. Cristini, “An integrated computational/experimental model of tumor invasion,” Cancer Res 66(3), 1597–1604 (2006).
30. H. B. Frieboes, F. Jin, Y. L. Chuang, S. M. Wise, J. S. Lowengrub, and V. Cristini, “Three-dimensional multispecies nonlinear tumor growth-II: Tumor invasion and angiogenesis,” J Theor Biol 264(4), 1254–1278 (2010).
31. S. Sanga, J. P. Sinek, H. B. Frieboes, M. Ferrari, J. P. Fruehauf, and V. Cristini, “Mathematical modeling of cancer progression and response to chemotherapy,” Expert Rev Anticancer Ther 6(10), 1361–1376 (2006).
32. A. R. Anderson, A. M. Weaver, P. T. Cummings, and V. Quaranta, “Tumor morphology and phenotypic evolution driven by selective pressure from the microenvironment,” Cell 127(5), 905–915 (2006).
34. X. Zheng, S. M. Wise, and V. Cristini, “Nonlinear simulation of tumor necrosis, neo-vascularization and tissue invasion via an adaptive finite-element/level-set method,” Bull Math Biol 67(2), 211–259 (2005).
35. M. Wu, H. B. Frieboes, S. McDougall, M. A. Chaplain, V. Cristini, and J. Lowengrub, “The effect of interstitial pressure on tumor growth and transport of therapeutic agents: coupling with the blood and lymphatic vascular systems,” (Submitted).
36. A van de Ven, P. Kim, O. Haley, J. Fakhoury, G. Adriani, J. Schmulen, P. Moloney, F. Hussain, M. Ferrari, X. Liu, S. Yun, and P. Decuzzi, “Rapid tumoritropic accumulation of systemically injected plateloid particles and their biodistribution,” JCR, In press. (2011).
37. P. Decuzzi, B. Godin, T. Tanaka, S. Y. Lee, C. Chiappini, X. Liu, and M. Ferrari, “Size and shape effects in the biodistribution of intravascularly injected particles,” J Control Release 141(3), 320–327 (2010).
38. Gu J. , Godin B. , Serda R. E. , Ferrati S. , Liu X. , “Multistage mesoporous silicon-based nanocarriers: biocompatibility and controlled degradation in physiological fluids,” 35th Annual Meeting & Exposition of the Controlled Release Society 575 (New York City, New York) (2008).
39. T. Tanaka, L. S. Mangala, P. E. Vivas-Mejia, R. Nieves-Alicea, A. P. Mann, E. Mora, H. D. Han, M. M. Shahzad, X. Liu, R. Bhavane, J. Gu, J. R. Fakhoury, C. Chiappini, C. Lu, K. Matsuo, B. Godin, R. L. Stone, A. M. Nick, G. Lopez-Berestein, A. K. Sood, and M. Ferrari, “Sustained small interfering RNA delivery by mesoporous silicon particles,” Cancer Res 70(9), 3687–3696 (2010).
40. Huan Meng, Monty Liong, Tian Xia, Zongxi Li, Zhaoxia Ji, Jeffrey I. Zink, and Andre E. Nel, “Engineered Design of Mesoporous Silica Nanoparticles to Deliver Doxorubicin and P-Glycoprotein siRNA to Overcome Drug Resistance in a Cancer Cell Line,” ACS Nano 4(8), 4539–4550 (2010).
41. Ji-Ho Park, Luo Gu, Geoffrey von Maltzahn, Erkki Ruoslahti, Sangeeta N. Bhatia, and Michael J. Sailor, “Biodegradable luminescent porous silicon nanoparticles for in vivo applications,” Nat Mater 8(4), 331–336 (2009).
42. Biana Godin, Jianhua Gu, Rita E. Serda, Rohan Bhavane, Ennio Tasciotti, Ciro Chiappini, Xuewu Liu, Takemi Tanaka, Paolo Decuzzi, and Mauro Ferrari, “Tailoring the degradation kinetics of mesoporous silicon structures through PEGylation,” Journal of Biomedical Materials Research Part A 94A(4), 1236–1243 (2010).
43. Joseph J. Casciari, Stratis V. Sotirchos, and Robert M. Sutherland, “Variations in tumor cell growth rates and metabolism with oxygen concentration, glucose concentration, and extracellular pH,” Journal of Cellular Physiology 151(2), 386–394 (1992).
44. D. D. Sumner and J. T. Stevens, “Pharmacokinetic factors influencing risk assessment: saturation of biochemical processes and cofactor depletion,” Environ Health Perspect 102 Suppl 11, 13–22 (1994).
45. R. Ganapathi, H. Schmidt, D. Grabowski, M. Melia, and N. Ratliff, “Modulation in vitro and in vivo of cytotoxicity but not cellular levels of doxorubicin by the calmodulin inhibitor trifluoperazine is dependent on the level of resistance,” British journal of cancer 58(3), 335–340 (1988).
46. C. Chiappini, E. Tasciotti, J. R. Fakhoury, D. Fine, L. Pullan, Y. C. Wang, L. Fu, X. Liu, and M. Ferrari, “Tailored porous silicon microparticles: fabrication and properties,” Chemphyschem 11(5), 1029–1035 (2010).
47. P. Decuzzi, R. Pasqualini, W. Arap, and M. Ferrari, “Intravascular delivery of particulate systems: does geometry really matter?,” Pharm Res 26(1), 235–243 (2009).
48. J. Lankelma, H. Dekker, F. R. Luque, S. Luykx, K. Hoekman, P. van der Valk, P. J. van Diest, and H. M. Pinedo, “Doxorubicin gradients in human breast cancer,” Clin Cancer Res 5(7), 1703–1707 (1999).
49. A. J. Primeau, A. Rendon, D. Hedley, L. Lilge, and I. F. Tannock, “The distribution of the anticancer drug Doxorubicin in relation to blood vessels in solid tumors,” Clin Cancer Res 11(24 Pt 1), 8782–8788 (2005).
51. R. E. Serda, A. Mack, A. L. van de Ven, S. Ferrati, K. Dunner Jr., B. Godin, C. Chiappini, M. Landry, L. Brousseau, X. Liu, A. J. Bean, and M. Ferrari, “Logic-embedded vectors for intracellular partitioning, endosomal escape, and exocytosis of nanoparticles,” Small 6(23), 2691–2700 (2010).
52. M. Gutman, R. K. Singh, S. Yoon, K. Xie, C. D. Bucana, and I. J. Fidler, “Leukocyte-induced angiogenesis and subcutaneous growth of B16 melanoma,” Cancer Biother 9(2), 163–170 (1994).
Article metrics loading...
Inefficient vascularization hinders the optimal transport of cell nutrients, oxygen, and drugs to cancer cells in solid tumors. Gradients of these substances maintain a heterogeneous cell-scale microenvironment through which drugs and their carriers must travel, significantly limiting optimal drug exposure. In this study, we integrate intravital microscopy with a mathematical model of cancer to evaluate the behavior of nanoparticle-based drug delivery systems designed to circumvent biophysical barriers. We simulate the effect of doxorubicin delivered via porous 1000 x 400 nm plateloid silicon particles to a solid tumor characterized by a realistic vasculature, and vary the parameters to determine how much drug per particle and how many particles need to be released within the vasculature in order to achieve remission of the tumor. We envision that this work will contribute to the development of quantitative measures of nanoparticle design and drug loading in order to optimize cancer treatment via nanotherapeutics.
Full text loading...
Most read this month