Reduction of nanoparticle avidity enhances the selectivity of vascular targeting and PET detection of pulmonary inflammation - PubMed (original) (raw)

. 2013 Mar 26;7(3):2461-9.

doi: 10.1021/nn305773f. Epub 2013 Feb 8.

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Reduction of nanoparticle avidity enhances the selectivity of vascular targeting and PET detection of pulmonary inflammation

Blaine J Zern et al. ACS Nano. 2013.

Abstract

Targeting nanoparticles (NPs) loaded with drugs and probes to precise locations in the body may improve the treatment and detection of many diseases. Generally, to achieve targeting, affinity ligands are introduced on the surface of NPs that can bind to molecules present on the cell of interest. Optimization of ligand density is a critical parameter in controlling NP binding to target cells, and a higher ligand density is not always the most effective. In this study, we investigated how NP avidity affects targeting to the pulmonary vasculature, using NPs targeted to ICAM-1. This cell adhesion molecule is expressed by quiescent endothelium at modest levels and is upregulated in a variety of pathological settings. NP avidity was controlled by ligand density, with the expected result that higher avidity NPs demonstrated greater pulmonary uptake than lower avidity NPs in both naive and pathological mice. However, in comparison with high-avidity NPs, low-avidity NPs exhibited several-fold higher selectivity of targeting to pathological endothelium. This finding was translated into a PET imaging platform that was more effective in detecting pulmonary vascular inflammation using low-avidity NPs. Furthermore, computational modeling revealed that elevated expression of ICAM-1 on the endothelium is critical for multivalent anchoring of NPs with low avidity, while high-avidity NPs anchor effectively to both quiescent and activated endothelium. These results provide a paradigm that can be used to optimize NP targeting by manipulating ligand density and may find biomedical utility for increasing detection of pathological vasculature.

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Figures

Figure 1

Figure 1

Model of acute lung injury in mice. (A) Messenger RNA levels of ICAM-1 in LPS-treated mice at a dose of 8 mg/kg. (B) Western blot analysis and quantification of up-regulation of ICAM-1 in this model of inflammation. (C) Anti-ICAM-1Ab localization in the blood and lung in naïve and LPS-challenged mice. Data represented as mean ± S.D.;*, p < 0.05.

Figure 2

Figure 2

Utilization of Ab density to control lung localization. (A) In vivo lung accumulation as a function of anti-ICAM-1 surface density. Data points highlighted in red correspond to ICAM-1 surface densities used to examine tissue selectivity (dashed line denotes control IgG NPs). (B) Using anti-ICAM-1 surface density to increase tissue selectivity in a model of acute lung injury (dashed line denotes control IgG in LPS treated mice). (C) Tissue selectivity of different ICAM-1 formulations. Data represented as mean ± S.D. (n = 4), p < 0.05.

Figure 3

Figure 3

(A) Coronal sections of real-time in vivo CT(left) and PET(right) images acquired after administration of ICAM-1-targeted (200 Ab/NP) [124I]-NP in a naïve mouse to demonstrate organs of interest and anatomical orientation (white dashed-line corresponds to lung space defined from CT images). (B) Different formulations of IgG controls and anti-ICAM-1 (Ab coverage: 50 and 200 Ab/NP) in naïve and LPS-treated mice were examined for lung localization over a period of 1 hour by 124I-PET. Each image represents a summed image of all frames captured within the 1 hour time frame.

Figure 4

Figure 4

(A & B) Lung uptake (%ID/g) in real-time extrapolated from regions-of-interest (ROIs) drawn on lung volumes from PET images over the 1 hour scan time for both ICAM-1 targeted formulations in naïve and LPS-challenged mice. (C) Average lung uptake of anti-ICAM-1 formulations extrapolated from regions-of-interest (ROIs) drawn on lung volumes from PET images at 1 hour p.i. with IgG levels subtracted to account for non-specificity (D) Ratio of LPS-challenged over naïve animals targeted with anti-ICAM-1 formulations extrapolated from ROIs. Data represented as mean ± S.D. (n = 4); *, p < 0.05.

Figure 5

Figure 5

(A) The individual PMF profiles at antibody coverage of _N_ab=200/NP and ICAM-1 density of 2000 ICAM-1/μm2 (left) and 4000 ICAM-1/μm2 (right). (B) The individual PMF profiles at antibody coverage of _N_Ab=50/NP and ICAM density of 2000 ICAM-1/μm2 (left) and 4000 ICAM-1/μm2 (right). Different colors correspond to four independent realizations based on which the statistical error in the binding affinity is computed and reported as one standard deviation. (C) The binding affinities (_K_a) at different antibody coverage and ICAM-1 surface coverages.

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