Predictive Models of Diffusive Nanoparticle Transport in 3-Dimensional Tumor Cell Spheroids
- PDF / 601,551 Bytes
- 16 Pages / 595.276 x 790.866 pts Page_size
- 22 Downloads / 129 Views
Research Article Predictive Models of Diffusive Nanoparticle Transport in 3-Dimensional Tumor Cell Spheroids Yue Gao,1 Mingguang Li,2 Bin Chen,1 Zancong Shen,1 Peng Guo,1 M. Guillaume Wientjes,1,2 and Jessie L.-S. Au1,2,3
Received 4 January 2013; accepted 19 March 2013; published online 20 April 2013 Abstract. The rapidly evolving nanotechnology field highlights the need of better understanding the relationship between nanoparticle (NP) properties and NP transport in solid tumors. The present study tested the hypothesis that the diffusive transport and spatial distribution of NP can be predicted based on the following parameters: interstitial NP diffusivity, NP–cell interaction parameters (cell surface binding capacity, rate constants of association, dissociation, and internalization). We (a) established the models and equations; (b) experimentally measured, in monolayer pharynx FaDu cells, the model parameters for three NP formulations (negatively charged polystyrene beads, near-neutral liposomes, and positively charged liposomes, with respective diameter of 20, 110, and 130 nm); and (c) used the models and parameters to simulate NP diffusion in 3-dimensional (3D) systems. We next measured the NP concentration–depth profiles in tumor cell spheroids, an avascular 3D system, and found good agreement between model-simulated and experimental data in spheroids for the negative and neutral NP (>90% predicted data points at three NP concentrations and three treatment times were within the 95% confidence intervals of experimental data). Model performance was inferior for positive liposomes containing a fusogenic lipid. The present study demonstrated the possibility of using in vitro NP–cell biointerface data in monolayer cultures with in silico studies to predict the NP diffusive transport and concentration–time–depth profiles in 3D systems, as functions of NP concentrations and treatment times. Extending this approach to include convective transport may yield a cost-effective means to predict the NP delivery and residence in solid tumors. KEY WORDS: 3-dimensional tumors; computational models; diffusional transport; nanoparticle; solid tumors.
INTRODUCTION Nanotechnology has emerged as an important tool in cancer translational research. Nanoparticles (NP) offer a Yue Gao and Mingguang Li contributed equally to this work. 1
Division of pharmaceutics, College of Pharmacy, The Ohio State University, Columbus, Ohio 43210, USA. 2 Optimum Therapeutics LLC, 9363 Towne Centre Drive, San Diego, California 92121, USA. 3 To whom correspondence should be addressed. (e-mail: [email protected]) ABBREVIATIONS: 2D and 3D, 2- and 3-Dimensional; AUC, Area under curve; Bmax, Cell surface binding capacity; BS, Binding sites on cell surface; C, Nanoparticle concentration; D, Diffusion coefficient; DAPI, 4′, 6-Diamidino-2-phenylindole dihydrochloride; DOPE, 1,2Dioleoyl-sn-glycero-3-phosphoethanolamine; DOTAP, 1,2-Dioleoyl3-trimethylammonium propane; DPPC, 1,2-Dipalmitoyl-sn-glycero-3phosphocholine; ECM, Extracellular matrix; HPLC, Highperformanc
Data Loading...
