Tailoring Renal Clearance and Tumor Targeting ... - Wiley Online Library

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International Edition: DOI: 10.1002/anie.201609043 German Edition: DOI: 10.1002/ange.201609043

Tailoring Renal Clearance and Tumor Targeting of Ultrasmall Metal Nanoparticles with Particle Density Shaoheng Tang, Chuanqi Peng, Jing Xu, Bujie Du, Qingxiao Wang, Rodrigo D. Vinluan III, Mengxiao Yu, Moon J. Kim, and Jie Zheng* Abstract: Identifying key factors that govern the in vivo behavior of nanomaterials is critical to the clinical translation of nanomedicines. Overshadowed by size-, shape-, and surface-chemistry effects, the impact of the particle core density on clearance and tumor targeting of inorganic nanoparticles (NPs) remains largely unknown. By utilizing a class of ultrasmall metal NPs with the same size and surface chemistry but different densities, we found that the renal-clearance efficiency exponentially increased in the early elimination phase while passive tumor targeting linearly decreased with a decrease in particle density. Moreover, lower-density NPs are more easily distributed in the body and have shorter retention times in highly permeable organs than higher-density NPs. The density-dependent in vivo behavior of metal NPs likely results from their distinct margination in laminar blood flow, which opens up a new path for precise control of nanomedicines in vivo.

Unraveling the key factors that are involved in nano–bio

interactions in vivo is of fundamental importance for translating nanomedicines into the clinic.[1] Over the past decades, the size, shape, and surface chemistry of inorganic NPs have been found to significantly affect their in vivo behavior.[2] For example, Chan and co-workers showed that gold nanoparticles (AuNPs) with different sizes have distinct tumor uptakes and penetration depths.[3] Among AuNPs with sizes ranging from 20 to 100 nm, the small 20 nm AuNPs showed lower accumulation but larger penetration depths in tumors than the other AuNPs. Xia et al. investigated the effect of shape on the in vivo behavior of gold nanostructures and found that nanospheres exhibited longer blood circulation times and higher tumor uptake than Au nanostructures with different shapes.[4] Moreover, various surface chemistries have been widely used to manipulate the in vivo behavior of nanomedicines.[5] While our fundamental understanding of nano–bio interactions with inorganic NPs in vivo has greatly advanced over

[*] Dr. S. H. Tang, C. Q. Peng, J. Xu, B. J. Du, R. D. Vinluan III, Dr. M. X. Yu, Prof. Dr. J. Zheng Department of Chemistry The University of Texas at Dallas 800 W. Campbell Rd., Richardson, TX 75080 (USA) E-mail: [email protected] Q. X. Wang, Prof. Dr. M. J. Kim Department of Materials Science and Engineering The University of Texas at Dallas (USA) Supporting information for this article can be found under: http://dx.doi.org/10.1002/anie.201609043. Angew. Chem. Int. Ed. 2016, 55, 16039 –16043

the past decades, the core density, another intrinsic characteristic of inorganic NPs, has not attracted much attention, and only very limited studies on the effect of density on nano–bio interactions have been reported.[6] For instance, Randall et al. found that approximately 60 nm large polymeric NPs (lowdensity NPs) can move towards the blood vessel walls much more slowly than iron oxide or gold NPs (high-density NPs) of the same size in microfluidic channels even though they have the same diffusion coefficient and the gravitational force is negligible for NPs of such sizes.[6c] This experimental result is also consistent with theoretical modeling on the margination of nanoparticles to blood vessel walls, where relative density differences between NPs and blood play a significant role for the margination time of 50 nm particles: high-density NPs tend to have short margination times, reach the endothelium more quickly, and interact strongly with blood vessel walls.[6a] As a result, light NPs can circulate much faster in the body than heavy NPs.[6a] On an even smaller size scale, however, it is not clear whether density can still significantly affect the in vivo behavior of inorganic NPs with different compositions even though they exhibit distinct clearance efficiencies and tumor targeting.[7] For instance, Choi and co-workers systematically investigated the renal clearance of cysteine-coated CdSe/ZnS quantum dots (QDs) and found that almost all of the 4.36 nm QDs were renally cleared within 24 h after intravenous injection.[8] Similar to these QDs, silica NPs also exhibit very high renal-clearance efficiencies: about 70 % of an injected dose (%ID) of silica NPs had been excreted in urine at 24 h post injection (p.i.).[9] However, the clearance of glutathione (GS) coated AuNPs through the urinary system was relatively slow, as less than 50 %ID of GS-AuNPs were cleared out of the body into the urine at 24 h p.i., and they exhibited much longer blood retention times and higher passive tumor targeting than silica dots and QDs.[10] Other renal-clearable inorganic NPs with different compositions also exhibit distinct renal-clearance and tumor-targeting properties.[11] However, shadowed by differences in size and surface chemistry among these ultrasmall NPs, it is highly challenging to unravel the effect of density on the in vivo behavior of ultrasmall NPs. Herein, we present a quantitative study of the density effect on renal clearance and tumor targeting of ultrasmall metal NPs by synthesizing a class of glutathione-coated noblemetal NPs with the same size and surface chemistry but different densities, including glutathione-coated AuNPs (GSAuNPs), AgNPs (GS-AgNPs), and two kinds of Au/Agalloyed NPs (GS-Au/Ag(1)NPs and GS-Au/Ag(2)NPs). By quantifying their in vivo behavior (renal-clearance efficien-

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Communications cies, pharmacokinetics, kidney filtration, biodistribution, and tumor targeting), we found that as the core density of the NPs increased, their renal-clearance efficiencies in the early elimination stage (2 h p.i.) exponentially decreased while their passive tumor-targeting efficiencies linearly increased. Quantitative analysis of their pharmacokinetic parameters showed that the origin of density-dependent renal clearance and targeting is fundamental because NPs with lower densities are more easily distributed in the body and filtrated through the kidneys; this hypothesis was further supported by noninvasive fluorescence imaging of the kidney clearance of GS-AuNPs and GS-AgNPs. These fundamental insights clearly indicate that the particle density could serve as another key factor to tailor the in vivo behavior of inorganic NPs for different biomedical applications. Four types of ultrasmall noble-metal NPs were synthesized in such a way that they have the same antifouling surface coating (glutathione) and identical sizes. GS-AuNPs and GSAgNPs were prepared according to our previously described thermal reduction method.[12] Briefly, precursor solutions were prepared by dissolving glutathione and HAuCl4 (molar ratio 1:0.8) or AgNO3 (molar ratio 3.4:1) in 40 mL water. Then the mixtures were heated at 95 8C for 0.5 h and 37 h, respectively. After purification, approximately 2.6 nm large near infrared (NIR) emitting GS-AuNPs and GS-AgNPs with a hydrodynamic diameter (HD) of approximately 3.1 nm were obtained (see the Supporting Information, Figure S1). The very small changes in the UV/Vis absorption spectrum of the GS-AgNPs after incubation in phosphate buffered saline (PBS) containing 10 % fetal bovine serum (FBS) at 37 8C for 72 h indicate that the GS-AgNPs are fairly stable in physiological environments (Figure S2). To synthesize more metal NPs with the same size and surface coating but different core densities, we also synthesized Au/Ag-alloy NPs through co-reduction. Briefly, HAuCl4 and AgNO3 solutions were mixed at molar ratios of 1:1.3 or 1:1, which was followed by chemical reduction with freshly prepared NaBH4 solution (0.5 m) in the presence of GS in 4 mL distilled water at room temperature. After purification, glutathione-coated Au/Ag NPs (GS-Au/AgNPs) with a HD of about 3.1 nm were obtained (Figure 1 A, B). Scanning transmission electron microscopy (STEM) imaging coupled with energy-dispersive X-ray spectroscopy (EDS) further confirmed the successful synthesis of the alloyed GS-Au/AgNPs. As shown in Figure 1 C, elemental-mapping analysis indicates that all of the Au and Ag atoms are homogeneously distributed throughout a single nanostructure. The Au/Ag atomic ratios of these NPs were accurately determined by inductively coupled plasma mass spectrometry (ICP-MS), which gave ratios of 1:8.4 and 1:0.64; these values correspond to densities of 11.4 g cm@3 and 15.9 g cm@3 for the GS-Au/ Ag(1)NPs and GS-Au/Ag(2)NPs, respectively. Together with the GS-AuNPs (19.3 g cm@3) and GS-AgNPs (10.5 g cm@3), these ultrasmall metal NPs with the same size and surface chemistry can serve as model systems to quantitatively study how the core density affects renal clearance and tumor targeting of ultrasmall metal NPs. The antifouling properties of glutathione render these ultrasmall metal NPs highly resistant to serum protein

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Figure 1. Characterization of glutathione-coated Au–Ag alloy nanoparticles (GS-Au/AgNPs). A) Typical transmission electron microscopy (TEM) image of GS-Au/AgNPs. B) The GS-Au/AgNPs have a core size of 2.6 : 0.2 nm. Dynamic light scattering analysis gave HD = 3.1 : 0.3 nm in aqueous solution. C) STEM and EOS mapping images of GS-Au/AgNPs with a Au/Ag molar ratio of 1.4. Scale bar = 2 nm.

adsorption and allowed us to unravel density effects without interference from the serum protein in the physiological environment (Figure S3). Four groups of BALB/c mice (n = 3) were intravenously injected with the four types of ultrasmall metal NPs, respectively, and urine samples were collected at various time points and then analyzed by ICPMS (see the Supporting Information for details). As shown in Figure 2 A, these ultrasmall metal NPs exhibited comparable renal-clearance efficiencies at 48 h p.i. of 51.36, 52.99, 48.69, and 45.57 %ID for GS-AgNPs, GS-Au/Ag(1)NPs, GS-Au/ Ag(2)NPs, and GS-AuNPs, respectively. However, their renal-clearance kinetics are quite different and strongly density-dependent: the NPs with the lowest density were excreted most efficiently into urine in the early clearance stage. At 2 h p.i., the highest renal-clearance rate was observed for the GS-AgNPs (45.87 %ID), followed by the GS-Au/Ag(1)NPs (36.90 %ID), GS-Au/Ag(2)NPs (31.22 %ID), and GS-AuNPs (29.19 %ID). Combined with our previous results, where GS-CuNPs (8.9 g cm@3) with 2.7 nm HD exhibited an even higher clearance efficiency (ca. 60 %ID at 2 h p.i.),[13] these results confirm that the amount of NPs excreted into urine at 2 h p.i. exponentially decreases with an increase in the particle density (Figure 2 B). The strong density dependence of the renal clearance is consistent with our pharmacokinetic studies of these metal NPs. Although all of these metal NPs exhibit two-compartment pharmacokinetics with very short distribution half-lives and relatively long elimination half-lives, several key parameters, including the distribution half-life (T1/2a), elimination half-life (T1/2b), volume of distribution (Vd), clearance (CL), and area under the curve (AUC), derived from their pharmacokinetic data are significantly different for these four different types of metal NPs (Figure 2 C and Table S1). It is well known that the parameter Vd reflects how a foreign material is distributed in organs and tissues, and the CL value reflects the capability of an organism to remove a given


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Figure 2. In vivo behavior of ultrasmall glutathione-coated metal NPs. A) Renal clearance of the four different metal NPs within 48 h p.i. B) The exponential relationship between 2 h renal clearance (RC) and particle core density (d), expressed as: RC = 2.5 W 103exp(@d/2.1) + 29.9, R2 = 0.98. C) Pharmacokinetics of the NPs. The pharmacokinetic parameters were determined by fitting the data with a two-compartment model. D–F) Dependence of the three main pharmacokinetic parameters on the density: D) Vd = 4.31 W exp(@d/0.51) + 13.3, R2 = 0.99. E) CL = 6.55 W exp(@d/0.43) + 0.55, R2 = 0.99. F) AUC = 2.7 W 105exp(@d/0.88) + 2.5, R2 = 0.99. G) The relationship between tumor accumulation (TA) and density, which can be expressed as TA = 0.16 [email protected], R2 = 0.99.

material by excretion or metabolism.[14] As shown in Figure 2 D, E, with a decrease in the particle density from 19.3 g cm@3 (GS-AuNPs) to 10.5 g cm@3 (GS-AgNPs), both Vd and CL increased from 2.98 mL and 0.54 mL h@1 to 8.97 mL and 2.25 mL h@1, respectively, and thus depend exponentially on the particle density. These results indicate that reducing particle density can not only greatly expedite the distribution of NPs in the body but also enhance the renal clearance of NPs. Moreover, because of the differences in renal clearance, the blood retention, measured as the AUC, of these metal NPs with different densities is also distinct, and increases exponentially with an increase in the particle density (Figure 2 F). As passive tumor targeting is mainly governed by the AUCs of NPs in the blood,[3, 15] the GSAuNPs exhibited the highest tumor targeting, and the targeting efficiency of these metal NPs was found to depend linearly on the particle density (Figure 2 G). Angew. Chem. Int. Ed. 2016, 55, 16039 –16043

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To further unravel the details of the excretion mechanism, we took advantage of the strong intrinsic NIR fluorescence of the GS-AuNPs and GS-AgNPs (Figure S4) and noninvasively monitored the luminescence signals from the kidneys and background tissues of BALB/c mice (n = 3) after injection of GS-AuNPs and GS-AgNPs (Movies S1 and S2) to determine the distribution and clearance kinetics. The normalized time fluorescence intensity curves (NTFICs) of the kidneys were obtained through whole-body imaging (Figure 3 A, B), and two key parameters of the NTFICs, namely, the time to reach the maximum fluorescence intensity (TMFI) and the clearance rate (defined as the decline percentage at 60 min = [(peak value@intensity at 60 min p.i.)/peak value] X 100 %), were extracted and compared (Figure S5). For the GSAuNPs, the average fluorescence intensity of the kidney region rapidly increased to the maximum value at about 2 min p.i., which was followed by a rapid decrease in intensity. At 1 h p.i., the kidney fluorescence signal had dropped to about 20 % of the TMFI (Figure 3 C). On the other hand, it took 11.83 : 1.75 min for the fluorescence signal of kidneys of mice injected with GS-AgNPs to reach its maximum. Furthermore, unlike the kidney signals from mice injected with GS-AuNPs, the kidney signals of mice injected with GS-AgNPs maintained a constant intensity with a negligible decrease (1.43 %) even though much more GS-AgNPs were eliminated into the bladder than GS-AuNPs in the early elimination phase. In addition, the clearance of GS-AgNPs from background tissues was also slower than that of GS-AuNPs (Figure 3 D and S6). In combination with the Vd values, the accumulation and clearance kinetics of these two different-density NPs indicate that low-density GS-AgNPs are more easily distributed in the body through the blood and accumulate in both the kidneys and background tissue. Indeed, more detailed fluorescence imaging of the distributions of GS-AgNPs and GS-AuNPs in the kidneys at an early injection time point (7 min p.i.) also confirmed that low-density GS-AgNPs not only accumulate in the cortex region like GS-AuNPs (Figure 3 E) but also penetrated into the medulla regions (Figure 3 F), especially into the region near the renal pelvis, much more than GS-AuNPs (Figure 3 G). To gain more insight into the in vivo clearance of these ultrasmall metal NPs, we quantified their 7 min and 48 h biodistributions and compared the two. As shown in Figures 4 A and S7, at 7 min p.i., these metal NPs mainly accumulated in the highly permeable organs, namely kidney, liver, and intestine; however, the accumulation of GS-AgNPs in these organs is much higher than that of the GS-AuNPs, suggesting that the low-density GS-AgNPs reached the kidneys more quickly than the high-density GS-AuNPs; as a result, more GS-AgNPs were eliminated through the urinary system. Furthermore, head-to-head comparisons of their biodistributions at 48 h p.i. showed that the percentage decreases in these organs are quite different for the GSAuNPs and GS-AgNPs (Figure S8). As shown in Figure 4 B, the amount of GS-AgNPs cleared from the kidney, liver, and intestine was 6.7 : 2.4, 2.6 : 0.6, and 2.4 : 1.6 %ID g@1 greater than that of the GS-AuNPs, further suggesting that lowdensity AgNPs have lower affinities to blood vessels and shorter retention times in the highly vascular organs than the


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Figure 4. Biodistribution of GS-AuNPs and GS-AgNPs. A) Biodistribution of GS-AgNPs and GS-AuNPs in major organs at 7 min p.i. B) The differences in the clearance of GS-AuNPs (DGS-AuNPs) and GSAgNPs (DGS-AgNPs) in various organs at 7 min and 48 h p.i. Kd = kidney, It = intestine, Lv = liver, Hr = heart, Sk = skin, Ms = muscle, St = stomach, Sp = spleen. %ID g@1 = percentage of the injected dose per gram of tissue. *p < 0.005. C) Possible scheme showing the margination of GS-AuNPs (yellow) and GS-AgNPs (green) circulating in the blood stream after tail injection. Because of density-dependent margination, GS-AgNPs reach the kidneys faster than GS-AuNPs.

Figure 3. Noninvasive fluorescence imaging of the kidney clearance kinetics of GS-AuNPs and GS-AgNPs. A, B) Representative whole-body fluorescence images of mice i.v. injected with the GS-AuNPs (A) and the GS-AgNPs (B). Ex/Em filters: 710/830 nm. C, D) Representative TFICs of kidneys (C) and background (D) in the two groups of BALB/c mice (n = 3) intravenously injected with GS-AuNPs and GS-AgNPs, respectively. Two parameters were extracted from the kidney TFICs, namely the time to achieve the maximum fluorescence intensity (TMFI) and the clearance rate (defined as the clearance percentage at 60 min = [(peak value@intensity at 60 min)/peak value] W 100 %). E– G) Kidney penetration study. Bright field (BF) and fluorescence images of kidney slices after intravenous injection of PBS, GS-AuNPs, and GSAgNPs. Three representative regions were selected: cortex (E), medulla regions near the artery (F), and pelvis (G). Scale bars = 200 mm.

high-density AuNPs. These results are consistent with previous theoretical modeling that lower-density about 50 nm large NPs tend to circulate in the blood vessels much faster than higher-density ones because of their long margination time.[6] Based on these experimental results and previous studies on the margination of large NPs (> 50 nm) in blood vessels or microfluidic channels,[6] we hypothesize that even at such small sizes (ca. 3 nm), the density-dependent margination observed at > 50 nm will still be valid. As the densities of AgNPs and AuNPs are much greater than that of blood, both of them marginate in the blood flow (Figure 4 C). As the

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density of gold is nearly two times greater than that of silver, GS-AuNPs marginate to the blood vessel walls faster than GS-AgNPs; as a result, in laminar blood flow, GS-AgNPs circulate faster than GS-AuNPs, resulting in more rapid kidney clearance, shorter blood retention, and lower tumor targeting. In summary, we have systematically investigated the effect of nanoparticle density on renal clearance, kidney filtration, pharmacokinetics, and tumor targeting with a class of ultrasmall metal NPs with the same sizes and surface chemistry but different densities. We have shown that the renal clearance decreases exponentially in the early elimination phase with an increase in particle density and that tumor targeting is linearly dependent on the particle density. The density dependence of the in vivo behavior of ultrasmall metal NPs very likely originates from density-dependent margination, where highdensity gold nanoparticles more quickly marginate to the blood wall. As a result, in laminar blood flow, GS-AuNPs circulate more slowly than GS-AgNPs in the blood vessel, which leads to slower renal clearance, longer blood retention, as well as higher tumor targeting than for the GS-AgNPs. This observation is consistent with previous theoretical modeling studies and experimental measurements of the margination and flow of large NPs (> 50 nm), suggesting that density effects on in vivo behavior that were observed at larger scales might still be valid even for particles with a size of a few nanometers as long as the particle density is much greater than the blood density. Our future work will focus on


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Communications improving our understanding of the margination of these ultrasmall metal NPs in blood vessels. Nevertheless, these quantitative and fundamental studies of particle-density effects on the in vivo behavior of NPs offer a new and generalizable strategy, in addition to size, shape, and surface chemistry effects, for precisely controlling the clearance of nanoparticles and enabling the translation of nanomedicines into the clinic.

Acknowledgements This work was supported by the NIH (R01DK103363), CPRIT (RP120588, RP140544), Louis Beecherl, Jr. endowment funds (M.J.K.), and a start-up fund from The University of Texas at Dallas (J.Z.). Keywords: fluorescence imaging · imaging agents · nanoparticles · renal clearance · tumor targeting How to cite: Angew. Chem. Int. Ed. 2016, 55, 16039 – 16043 Angew. Chem. 2016, 128, 16273 – 16277 [1] S. Wilhelm, A. J. Tavares, Q. Dai, S. Ohta, J. Audet, H. F. Dvorak, W. C. W. Chan, Nat. Rev. Mater. 2016, 5, 16014 – 16026. [2] a) Y. N. Zhang, W. Poon, A. J. Tavares, I. D. McGilvray, W. C. W. Chan, J. Controlled Release 2016, 1, 1 – 17; b) B. D. Chithrani, A. A. Ghazani, W. C. W. Chan, Nano Lett. 2006, 6, 662 – 668; c) L. Y. T. Chou, W. C. W. Chan, Adv. Healthcare Mater. 2012, 1, 714 – 721; d) B. H. Kim, M. J. Hackett, J. Park, T. Hyeon, Chem. Mater. 2014, 26, 59 – 71; e) E. A. Sykes, J. Chen, G. Zheng, W. C. W. Chan, ACS Nano 2014, 8, 5696 – 5706; f) J. Lazarovits, Y. Y. Chen, E. A. Sykes, W. C. W. Chan, Chem. Commun. 2015, 51, 2756 – 2767; g) E. Huynh, M. A. Rajora, G. Zheng, Wiley Interdiscip. Rev. Nanomed. Nanobiotechnol. 2016, 6, 796 – 813. [3] S. D. Perrault, C. Walkey, T. Jennings, H. C. Fischer, W. C. W. Chan, Nano Lett. 2009, 9, 1909 – 1915. [4] K. C. L. Black, Y. Wang, H. P. Luehmann, X. Cai, W. Xing, B. Pang, Y. Zhao, C. S. Cutler, L. V. Wang, Y. Liu, Y. Xia, ACS Nano 2014, 8, 4385 – 4394. [5] a) R. Mo, T. Jiang, Z. Gu, Angew. Chem. Int. Ed. 2014, 53, 5815 – 5820; Angew. Chem. 2014, 126, 5925 – 5930; b) Y. Lu, Q. Hu, Y. Lin, D. B. Pacardo, C. Wang, W. Sun, F. S. Ligler, M. D. Dickey, Z. Gu, Nat. Commun. 2015, 6, 10066; c) W. Sun, W. Ji, J. M. Hall, Q. Hu, C. Wang, C. L. Beisel, Z. Gu, Angew. Chem. Int. Ed. 2015, 54, 12029 – 12033; Angew. Chem. 2015, 127, 12197 – 12201; d) J. Yu, Y. Zhang, Y. Ye, R. DiSanto, W. Sun, D. Ranson, F. S. Ligler, J. B. Buse, Z. Gu, Proc. Natl. Acad. Sci. USA 2015, 112, 8260 – 8265.

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