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Neoplasia. 2012 October; 14(10): 964–973.
PMCID: PMC3479840

Tumor Angiogenesis Phenotyping by Nanoparticle-facilitated Magnetic Resonance and Near-infrared Fluorescence Molecular Imaging1


One of the challenges of tailored antiangiogenic therapy is the ability to adequately monitor the angiogenic activity of a malignancy in response to treatment. The αvβ3 integrin, highly overexpressed on newly formed tumor vessels, has been successfully used as a target for Arg-Gly-Asp (RGD)-functionalized nanoparticle contrast agents. In the present study, an RGD-functionalized nanocarrier was used to image ongoing angiogenesis in two different xenograft tumor models with varying intensities of angiogenesis (LS174T > EW7). To that end, iron oxide nanocrystals were included in the core of the nanoparticles to provide contrast for T2*-weighted magnetic resonance imaging (MRI), whereas the fluorophore Cy7 was attached to the surface to enable near-infrared fluorescence (NIRF) imaging. The mouse tumor models were used to test the potential of the nanoparticle probe in combination with dual modality imaging for in vivo detection of tumor angiogenesis. Pre-contrast and post-contrast images (4 hours) were acquired at a 9.4-T MRI system and revealed significant differences in the nanoparticle accumulation patterns between the two tumor models. In the case of the highly vascularized LS174T tumors, the accumulation was more confined to the periphery of the tumors, where angiogenesis is predominantly occurring. NIRF imaging revealed significant differences in accumulation kinetics between the models. In conclusion, this technology can serve as an in vivo biomarker for antiangiogenesis treatment and angiogenesis phenotyping.


Angiogenesis is one of the crucial processes in tumor growth and development and is considered to predict short-term survival. Compared to the highly organized morphology of blood vessels in healthy tissues, the tumor vasculature is characterized by a chaotic architecture, tortuous vessel structure, and a leaky endothelium [1]. While many angiogenesis inhibitors are already known for decades [2], it was not until 2004 that the Food and Drug Administration approved the first antiangiogenic drug (bevacizumab) for clinical use [3,4]. Agents targeting different angiogenic pathways were subsequently approved [5] or are currently in different stages of clinical trails [6–8]. The major drawbacks associated with angiostatic drugs are inherent or acquired tumor resistance, increased tumor invasiveness, limited effects on overall survival, and, notably, a lack of reliable and thoroughly validated predictive biomarkers to monitor response to treatment [6,7]. For the latter, imaging is being considered as an approach to noninvasively track response to antiangiogenic therapy [9]. The most common standardized ex vivo measure of angiogenesis of tissue specimens is the determination of the microvessel density (MVD). Quantification of the MVD is performed by counting the (maximal) number of stained blood vessels per defined area on a histologic section [10]. In vivo imaging readouts of MVD include dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) [11], dynamic contrast-enhanced computed tomography [12], ultrasound [13], positron emission tomography [14], and optical methods [15,16]. Among those, DCE-MRI is the most widely explored method for monitoring response to antiangiogenic tumor therapy in both animal models [17] and clinical studies [18,19]. It relies on the fast acquisition of T1-weighted MR images after rapid intravenous (i.v.) injection of gadolinium-based contrast agents [20]. DCE-MRI was used in a recent study to investigate its potential as a biomarker for the treatment of metastatic renal cancer with the receptor tyrosine kinase inhibitor sorafenib, which blocks the vascular endothelial growth factor receptor [21]. Whereas DCE-MRI-derived parameters could be shown as pharmacodynamic biomarkers for this agent, variability was high, and therefore further refinements of the data acquisition and analysis are needed.

Within the field of molecular imaging, nanotechnology, in particular, the development of nanoparticle contrast agents, has seen unprecedented growth in the last years [22]. Because of their ability to incorporate high payloads of contrast agents/drugs as well as the possibility to covalently attach targeting molecules to the surface [23], their use to also investigate angiogenic processes has emerged as a very promising tool in cancer research [24,25]. The αvβ3 integrin is known to be significantly upregulated on activated endothelial cells during neoangiogenesis. By binding to the sequence arginine-glycine-aspartate (RGD), it mediates its biologic activity, and therefore, this peptide sequence has been used to functionalize contrast agents/nanoparticles for targeting the tumor neovasculature [26–28].

In the current study, the RGD peptide was attached to the surface of a nanoparticle platform that we described previously [29]. It is based on oil-in-water nanoemulsions with a tunable particle size in a range of 30 to 100 nm and the possibility to include lipophilic contrast agents/drugs in the core as well as amphiphilic ones in the corona.

Here, we focused on iron oxide-enhanced T2*-weighted MRI and near-infrared fluorescence (NIRF) imaging (Cy7 fluorophore), two very complementary imaging modalities of RGD-functionalized nanoparticles. The first modality was used to acquire spatial distribution of angiogenic activity at a given time point, whereas NIRF imaging provided time-resolved information about the nanoparticle binding kinetics in the tumors over a period of 24 hours. Two xenograft tumor models—the highly angiogenic human colorectal LS174T [30] model and the slow growing and low vascular density human EW7 Ewing sarcoma model [31]—were chosen to evaluate our approach with regard to its capability to adequately distinguish different intensity levels of angiogenesis. Moreover, the latter model is known to show abundant vascular mimicry in the outer rim of the tumors, a phenomenon in which tumor cells form tubular structures that contribute to circulation [32], explaining the lower MVD. These fundamental differences between the EW7 and LS174T tumors made us decide that the EW7 group injected with targeted contrast agent served as a control for the LS174T groups examined in this study. Confocal laser scanning microscopy (CLSM) and histologic staining for iron oxide were used to examine the location of the nanoparticles in the tumor tissues and corroborate the in vivo findings.

Materials and Methods


Distearoyl-sn-glycero-3-phosphocholine, distearoyl-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000] ammonium salt (DSPE-PEG), 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[maleimide (polyethylene glycol)-2000] ammonium salt [DSPE-PEG (maleimide)], 1,2-dimyristoyl-sn-glycero-3-phospho-ethanolamine-N-(lissamine rhodamine B sulfonyl), and distearoyl-phosphoethanolamine-N-[amino(polyethylene glycol)-2000] [DSPE-PEG (amino)] were all purchased from Avanti Polar Lipids (Alabaster, AL). Oleic acid-coated magnetite (Fe3O4) particles with an average diameter of 10 nm were obtained as a powder from NN-Labs (Fayetteville, AR). The cyclic 5-mer RGD (c[RGDf(S-acetylthioacetyl]K) was obtained from Peptides International (Louisville, KY). The Cy7 N-hydroxysuccinimide (NHS) ester was purchased from Amersham Biosciences (Piscataway, NJ). Cell culture supplies were purchased from Invitrogen (Carlsbad, CA).

Synthesis of the Nanoemulsions

For the synthesis of the nanoemulsions, separate stock solutions of all the lipophilic components were prepared in chloroform. The Cy7-DSPE-PEG lipid was synthesized using the DSPE-PEG (amino) lipid and Cy7 NHS ester as described earlier [29]. The composition of the formulation was 2.7 mg of distearoyl-sn-glycero-3-phosphocholine, 9.1 mg of DSPE-PEG, 38 mg of soybean oil, 19.8 mg of iron oxide particles, 1.06 mg of DSPE-PEG (maleimide), 746 µg of Cy7-DSPE-PEG lipids (= 0.22 µmol Cy7), and 40 µg of 1,2-dimyristoyl-sn-glycero-3-phospho-ethanolamine-N-(lissamine rhodamine B sulfonyl). The components were mixed together and the solvent was evaporated in a rotary evaporator under maximum vacuum in a 70°C water bath. The formed lipid layer was hydrated with 10 ml of Hepes-buffered saline (2.38 g/l Hepes and 8 g/l NaCl, pH 6.7), and the crude emulsion was homogenized by sonication using a sonicator tip (BioLogics, Inc., 3.9 mm). The formulation was sonicated for 20 minutes (level 20%, pulse 70%, device: Biologics, Inc., ultrasonic homogenizer model 150 V/T) while being cooled with room temperature water. Finally, the nanoparticle suspension was concentrated to a final volume of 2 ml by using a Vivaspin 6 centrifugal filter device (membrane cutoff: 100 kDa; Sartorius Corporation, Edgewood, NY) and divided into two batches of 1 ml each. Cyclic RGD was activated by adding 5 µl of deacetylation solution (348 mg of hydroxylamine HCl, 1.19 g of Hepes, 98 mg of EDTA in 10 ml of Millipore water; pH 7.0) to 50 µl of RGD stock solution (2.5 mg/ml) and placed on a shaker at room temperature for 45 minutes. Twenty microliters of activated cyclic RGD solution was added to one of the two batches of nanoemulsions for the coupling reaction to take place overnight at 4°C, while the other served as a control. Both formulations were washed the next day by using Vivaspin 6 columns. To ensure that the formulations of different batches had the same iron oxide content, T1 values of every batch of nanoemulsion were measured (diluted 1:10 with water, 60-MHz Bruker Minispec device operating at 40°C; Bruker Medical GmbH, Ettlingen, Germany).

Dynamic Light Scattering

Hydrodynamic sizes of the nanoparticles were measured by using dynamic light scattering (Brookhaven Instruments, Holtsville, NY) after washing of the particles. Ten microliters of the nanoemulsion formulation was diluted in 1 ml of Millipore water for the measurement.

Cell Culture and Tumor Model

Human EW7 (Ewing's sarcoma, a kind gift of Dr. O. Delattre, Paris, France) cancer cells were cultured in RPMI 1640 medium and human LS174T (colon carcinoma) cells were cultured in Dulbecco's modified Eagle's medium, both supplemented with 10% fetal calf serum. The cells were grown in a 5% CO2, water-saturated atmosphere at 37°C, and subculturing was performed once a week by 1:10 dilution after trypsinization. All animal handling protocols and procedures were approved by the Mount Sinai School of Medicine Institutional Animal Care and Use Committee. Six-week-old male Swiss nude mice were purchased from Taconic (Albany, NY). Subcutaneous tumors were established by injecting 2 million cells of the same cancer type in the lower left and right flanks of the mouse, respectively.

Study Outline

Two complementary imaging methods [22], NIRF imaging and MRI, were used to examine the potential of the targeted nanoparticles to serve as a contrast agent for the phenotyping of tumors with different levels of angiogenesis (Figure 1). To that end, three different mouse groups (six mice per group) were established to determine the time-resolved accumulation by NIRF imaging: (1) LS174T mice injected with RGD-conjugated nanoparticles: LS174T RGD; (2) mice with LS174T tumors injected with unconjugated nanoparticles: LS174T control; and (3) EW7-bearing mice injected with RGD nanoparticles: EW7 RGD. All the groups used for the NIRF imaging experiments were injected with nanoparticles lacking iron oxide nanocrystals. MRI was used to investigate the spatial distribution of the contrast agent within the tumors in dependence of the presence or absence of the targeting molecule RGD on the surface of the particles. The following five groups were used to acquire the MRI data: (4) LS174T RGD, (5) LS174T control, (6) EW7 RGD, (7) LS174T(C) RGD, and (8) LS174T comp. Groups 7 and 8 were chosen for the competition experiment. Group 7 was similar to group 4 but injected with a different batch of RGD-conjugated (iron oxide) nanoparticles and used as control for group 8. In the latter group, mice received two injections: The first injection consisted of RGD nanoparticles lacking iron oxide and the second one was given 1.5 hours afterward and contained RGD nanoparticles carrying iron oxide (same batch as used in group 7). For the first injection, twice as many particles were administered than for the second.

Figure 1
Conceptual scheme of the study characterizing the different mouse groups selected for the in vivo NIRF imaging and the MRI experiments (six mice per group, two tumors per mouse). Nanoparticles used for the MRI contained iron oxide, whereas those for the ...

The purpose of the MRI competition experiment was to demonstrate that the previously acquired specific accumulation (signal loss) pattern of the RGD-targeted particles in LS174T tumors (group 4) was caused by binding to the αvβ3 integrins rather than nonspecific accumulation. This was performed by monitoring changes in the signal attenuation pattern after saturating αvβ3 integrins by nonlabeled nanoparticles in the tumors before injection of the targeted nanoparticles carrying the iron oxide label. To achieve saturation, we chose the injection of the first dose of unlabeled nanoparticles to be twice that of the labeled nanoparticles.

Near-infrared Fluorescence Imaging and Data Analysis

NIRF imaging was performed with a custom-made imaging system [33,34] using a 760-nm excitation filter, an 800-nm emission filter, and an exposure time of 700 ms. The camera of the device was operated with the LabView software (National Instruments, Austin, TX, [35]). Swiss nude mice were anesthetized with a 4% isoflurane/oxygen gas mixture (400 ml/min initial dose) and maintained by using 1.5% isoflurane/oxygen gas (100 ml/min) delivered through a nose cone. The mice were injected i.v. with the nanoparticles through the tail vein. For the time-resolved accumulation, images were acquired 5 minutes, 15 minutes, 30 minutes, 1 hour, 2 hours, 4 hours, 6 hours, and 24 hours after i.v. injection. The mice were perfused with phosphate-buffered saline containing 20 U heparin/ml directly afterward while being under isoflurane anesthesia. In three mice of each group, Alexa Fluor 488-labeled isolectin GS-IB4 (a general stain for vascular endothelium; Invitrogen) was administered i.v. 15 minutes before perfusion. Tumors as well as organs were excised and imaged simultaneously with an exposure time of 500 ms. Subsequently, the tumors were embedded in Tissue-Tek (Sakura, Torrance, CA) and stored at -80°C.

For the data analysis of the fluorescence images (24-hour kinetics), region-of-interests (ROIs) outlining the tumors as well as parts of the skin, respectively, were drawn using ImageJ software. By using the following equation, the signal intensity of the tumor was normalized to the signal intensity of the skin: NER = (Itumor - Iskin)/Iskin x 100% (NER, normalized enhancement ratio; Itumor, signal intensity of tumor ROI at certain time point; Iskin, signal intensity of skin ROI at equal time point). All calculated values were subtracted by the value determined at the 5-minute time point to correct for the blood pool signal. To evaluate statistical significance, a two-way analysis of variance was used and P values < .05 were considered as significant.

The biodistribution of the nanoparticles was evaluated by drawing ROIs along the outlines of the excised tumors and organs. Subsequently, all relative fluorescence intensities I [I = (ROI area) x (mean signal intensity of ROI)] corresponding to the different ROIs per mouse were added up to create a 100% value (Io) to which all the individuals values (I) of the organs or tumors were normalized. The determined values (I/Io) were averaged within the mouse groups (Figure 6D). To assess the accumulation of the nanoparticles in the tumors compared to the liver, the averaged tumor fluorescence intensities were normalized to the liver intensity per mouse (Itumor/Iliver x100%) and averaged again within the three different mouse groups.

Figure 6
Fluorescence images (Cy7) of excised tumors and organs (A–C) of one representative mouse from each group, 24 hours after injection of the nanoparticles. The relative fluorescence counts of each organ or tumor were normalized to the sum total of ...

Immunohistochemistry, Confocal, and Perls Staining

To determine the MVD of the tumors, we cut 5-µm cryosections, followed by fixation in acetone for 5 minutes at -20°C. After blocking unspecific sites by using 4% rabbit serum in phosphate-buffered saline for 10 minutes, sections were incubated with rat anti-mouse CD31 primary antibody (BD Pharmingen, Franklin Lakes, NJ) in a dilution of 1:100 with 4% rabbit serum. A rabbit anti-rat secondary antibody and the alkaline phosphatase method served for the staining (Vector ABC Kit; Vector Laboratories, Burlingame CA). Four tumors of the EW7 RGD group and five tumors of the LS174T RGD group were analyzed with one to two sections per tumor. Several digital images of the tumor sections were photographed in bright field by using the Axioplan 2IE microscope with a 20x objective and stitched together by using the Axiovision 4.6.3 SP1 software to one image displaying the entire tumor section. The CD31+ color (red) selection was performed by using the gimp 2 software and converted to grayscale images. These images showing only positive CD31 areas were inverted to white (signal) on black (background) images. ROIs were drawn along the outlines of the tumors and the area fraction in percent was determined by using ImageJ software (Figure 8).

Figure 8
Histologic CD31 staining was performed for EW7 and LS174T tumors to determine the microvessel density. One entire tumor section was captured with an automated bright-field microscope (20x objective) generating multiple images that were stitched together ...

MRI and Data Analysis

Nude mice bearing EW7 or LS174T subcutaneous tumors were scanned under isoflurane anesthesia using a 9.4-T MRI system (400.106 MHz; Bruker Instruments), operated by ParaVision software 4.0. MRI was performed by using a gradient echo sequence (T2*) with a repetition time (TR) of 120 ms, echo time (TE) of 3 ms, flip angle of 30°, field of view of 2.6 x 2.6 cm, matrix size of 128 x 128, 10 slices with a slice thickness of 1 mm, and 16 averages, which amounted to a total scan time of 2.5 minutes. After the pre-scans, mice were injected i.v. with the nanoemulsion (equivalent of 36.7 mg/kg iron oxide) and scanned up to 4 hours after injection in 30-minute steps, while the position of the mouse remained unchanged.

The data analysis of the T2* images was performed by using a custom-made program written in MATLAB (MathWorks, Natick, MA). An ROI was manually drawn along the outline of the selected tumor slice. The program used this outer outline to automatically subdivide the tumor section into five concentric sub-ROIs of equal area from the periphery to the core (ROIs 1–5; Figure 3C). For the pixel-by-pixel analysis per ROI, a threshold of 4 x SD of the noise was set to define a pixel of the 4-hour post-image to be “reduced” (hypointense because of contrast agent accumulation) compared to the one of the pre-scanned image. Two slices were analyzed per tumor, and the percentage of reduced pixels per total number of pixels in the equal area ROI of two slices was averaged in each mouse group and plotted against the corresponding ROI. For the statistical analysis, a paired t test of the values for the reduced pixels (%) of ROI 1 (periphery) versus ROI 5 (core) was performed for each mouse group. P values < .05 were considered as statistically significant.

Figure 3
For the evaluation of the MR images, the tumor area was divided into five ROIs (C) and the percentage of reduced pixels (pre vs post) per ROI was plotted against the corresponding ROI (A, B, D). A very high grade of reproducibility could be achieved when ...


In Vivo MRI

The distribution pattern of iron oxide nanoemulsions (mean particle size range, 75–85 nm) with and without the conjugation of RGD in tumors was investigated by T2*-weighted MRI, which is sensitive to the presence of iron. Five groups of mice were chosen to compare the two different tumor models (LS174T vs EW7) with distinct MVD and to perform a competition experiment (Figure 1; for details, see Materials and Methods section). To minimize the error for the pre-post quantification owing to movement or reposition of the mouse after application of the contrast agent, we fixed and kept the mice in the same position in the coil during the entire scan series. In the pre-contrast images, the tumors appear isointense with their surrounding muscle tissue (Figure 2, A–D). The mice were scanned immediately after the administration of the nanoemulsion (equivalent of 36.7 mg/kg iron oxide) and an intense homogeneous darkening of the tumor area served as proof for a proper i.v. injection. On the basis of the half-lives previously determined for the untargeted version of the nanoemulsions [29], 4-hour post-administration was considered to be sufficient for the necessary clearance of the particles from the blood pool. Hypointense (dark) regions could be discerned within the tumor area of the post-contrast images (4 hours) owing to the accumulation of iron oxide. Importantly, the spatial distribution of signal loss in the LS174T RGD group (Figure 2E) differed from all the other investigated groups (Figure 2, F–H). While in the latter groups the nanoparticles seemed to be distributed rather homogenously, in the case of the LS174T tumors injected with the RGD-functionalized nanoemulsions, the contrast agent was prevailingly confined to the periphery of the tumors.

Figure 2
T2*-weighted gradient echo pre-injection (A–D) and post-injection (E–H; 4 hours, 36.7 mg/kg Fe) MR images of subcutaneous LS174T and EW7 tumors in Swiss nude mice (position unchanged in coil). The tumors of the LS174T RGD group, i.v. injected ...

The statistical analysis of the acquired T2*-weighted tumor images (for details, see Materials and Methods section) revealed a very high reproducibility of the performed experiments (Figure 3A). As seen in the chart showing the percentage of reduced pixels per ROI plotted against the corresponding ROI, two different groups of mice injected with different batches of the RGD-conjugated contrast agent yielded an almost identical signal loss pattern across the tumor (*P < .01 between ROI 1 and ROI 5). In comparison to the high statistically significant difference of pixels with reduced intensity between the tumor periphery and the core (P = .008) in the targeted LS174T RGD model, the analysis of the EW7 RGD as well as the LS174T control group revealed no difference (EW7 RGD: P = .88, LS174T control: P = .204; Figure 3B). The evaluation of the competition group that was injected first with twice the amount of targeted nanoparticles lacking iron oxide, followed by a second injection with targeted nanoparticles carrying iron oxide, resulted in a distribution with a trend toward the control (Figure 3D).

In Vivo NIRF Imaging

Representative examples of mice for the different groups display the results of the time-resolved accumulation of the nanoemulsions in the tumors by using in vivo fluorescence imaging within a period of 24 hours (Figure 4). The NER of the Cy7 fluorescence in percent was plotted against time and revealed a statistically significant difference (P < .05) between all three investigated groups for the time points 1, 2, 4, and 6 hours (Figure 5). The LS174T RGD group was the one with the fastest accumulation kinetics. The analysis demonstrated that the difference in tumor fluorescence intensity between the two different cancer models was higher than the LS174T RGD compared to the LS174 control for those time points. The mice were sacrificed 24 hours after injection and perfused, and the organs as well as tumors were imaged (Figure 6). The analysis of the fluorescence intensities revealed a high-dose percentage of the contrast agent in the tumors normalized to the liver for the LS174T RGD mice (35%) compared to the EW7 RGD (17%) and the LS174T control (19%; for details, see Materials and Methods section). The result of the analysis of the organ fluorescence (I) normalized to the sum total of the fluorescence of the organs and the tumors (Io) is depicted in Figure 6D.

Figure 4
Fluorescence images (Cy7) of representatives of the two mouse groups injected with RGD-targeted nanoemulsions (LS174T RGD: A–F, EW7 RGD: M–R) as well as of the group injected with untargeted nanoemulsions (LS174T control: G–L), ...
Figure 5
Time-dependent tumor fluorescence signal of the three mouse groups normalized to the skin and corrected for the blood pool effect after injection. The analysis of the kinetics revealed a statistically significant difference (P < .05) between the ...

Histologic Analysis

Perls staining was performed on fixed tumor sections to confirm the presence of iron oxide delivered by the nanocarrier 24 hours after i.v. administration. The results depicted in Figure 7, A–C, demonstrate the association of the particles with tumor vessels in the example of LS174T RGD, whereas, for the LS174T control tumors, the distribution was rather within the tissue (Figure 7D).

Figure 7
Ex vivo Perls staining for iron oxide showed accumulation of the nanoparticles in the tumor vessel endothelium (A–C) compared to the rather homogenous distribution within the tumor tissue in the control (D). CLSM corroborated these results, where ...

CLSM imaging corroborated the co-localization of the targeted nanoparticles (rhodamine B fluorescence) with microvessels (isolectin-Alexa Fluor 488 stained; Figure 7, E–H), whereas control particles were again spread within the tumor tissue (Figure 7, I–L).

The MVD of the two different tumor models was determined by using CD31 staining. Tumor areas of one slide were photographed sequentially with a system using a 20x objective and then auto-stitched to display an entire section (CD31+: red; Figure 8A). These high-resolution images were transformed by using appropriate software into a corresponding black and white image with white representing positive CD31 signal (Figure 8B). The result of the percentage area analysis confirmed the statistically significant higher MVD of the LS174T tumors compared to the EW7 (Figure 8C).


In the present study, we demonstrated that our previously developed nanoparticle platform can be functionalized with RGD to serve as a contrast agent that allows the detection of ongoing angiogenesis and the distinction between angiogenesis intensities of different tumor models by two complementary and noninvasive imaging modalities, i.e., MRI and NIRF. The combination of both modalities provided spatiotemporal information about the accumulation and fate of the probe. Analysis of the MR images revealed a significant difference in distribution of the RGD-targeted nanoemulsions in the fast growing and highly vascularized human colorectal LS174T model compared to the EW7 model, characterized by slow growth (50% of LS174T), highly elevated vascular mimicry in the tumor rim [32], and lower MVD [31]. In the case of the EW7 model with a lower angiogenesis level and vascular mimicry, the majority of the RGD nanoparticle uptake occurred nonspecifically and might explain the relatively homogeneous nanoparticle distribution pattern, which was similar to the LS174T control group injected with the untargeted nanoparticles. In this way, the EW7 RGD group served as a control for both, i.e., the targeted as well as untargeted LS174T groups. On the contrary, in the LS174T RGD nanoparticle tumors, the high expression of the αvβ3 integrin, predominantly observed at the periphery of the tumor, caused a shift away from the homogenous accumulation pattern toward a pattern corresponding prevalently to documented expression of the integrin [36]. Because αvβ3 integrin expressed at endothelial cells is directly accessible from the circulation, targeting of RGD-functionalized nanoparticles is faster than the passive accumulation owing to the EPR effect. Therefore, the first one of these two competing processes dominates the second in the case of a high receptor expression at the tumor vasculature [37,38].

Whereas MRI served to show the accumulation pattern within the tumors 4 hours after injection, NIRF imaging provided time-resolved information about the fate of the particles on the whole tumor level for a period of 24 hours. The statistically significant difference in accumulation kinetics between the three investigated groups for the time points up to 6 hours was given as follows: LS174T RGD > LS174T control > EW7 RGD.

Histologic examination served to corroborate the accumulation of nanoparticles in the tumor tissue. Perls staining, used to visualize iron oxide deposits in tissue, demonstrated the co-localization of the targeted particles with the vessel walls, whereas untargeted nanoemulsions were found extravasated and diffusely spread throughout the tissue. CLSM of rhodamine B-labeled nanoparticles corroborated the Perls staining results. The biodistribution, assessed by measuring the Cy7 fluorescence counts of the whole organs and the tumors after excision, revealed a high-dose percentage of the targeted contrast agent in the LS174T tumors (normalized to the liver: 35%), a highly desirable property of a contrast agent.

The MVD of the two used tumor models was assessed using CD31 staining and revealed LS174T tumors to have a much higher angiogenesis level than the EW7 counterpart. It is important to stress that such an assessment of MVD alone does not provide information about the proliferating fraction of endothelial cells within a tumor at a given time point. However, in most mouse models—unlike human tumors—high MVD is associated to intense ongoing angiogenesis [39]. Usually, the degree of MVD increases with tumor types that have higher rates of nutrient or oxygen consumption compared to others with a lower level metabolic requirement. Whereas MVD has often been shown to be a prognostic indicator in many tumor studies, its measurement for monitoring of antiangiogenic therapy has not been demonstrated to be reliable. A decrease in MVD following antiangiogenic therapy is certainly a confirmation of its efficacy, but an unchanged MVD is not necessarily a proof for its inefficacy [10]. In cases of equal tumor cell and endothelial cell dropout, no changes in MVD are detectable, as, e.g., shown in a case of multiple myeloma treatment with thalidomide, where not all tumor regressions were associated with an MVD decrease [40].

In light of this, because our nanoparticles were shown to be able to distinguish between different levels of angiogenesis in two distinct tumor models by directly targeting the αvβ3 receptor as visualized by NIRF and MRI, it is imaginable that they could be not only used as a noninvasive contrast agent for angiogenic phenotyping but also to reliably monitor response to antiangiogenic therapy, like we have shown with paramagnetic liposomes [41]. The efficacy of the latter then would be expressed as a change in nanoparticle kinetics monitored by NIRF imaging and/or differences in T2* signal loss pattern using MRI after injection over time. Moreover, we found in a very recent parallel study that our nanoparticle platform could be modified by implementation of cholesterol to form a stable nanocarrier with a PEG content that could be judiciously varied in a range of 5 to 50 mol%. Lower PEG contents proved to even highly increase its targeting capabilities to the αvβ3 receptors of newly forming vessels [37]. An improved modification of our nanoemulsion of this sort might result in a much higher sensitivity for detecting changes in neoangiogenesis during the course of treatment. Furthermore, by using this modified version of our nanoemulsion formulation, it could be convincingly shown that RGD-targeted nanoparticles began to accumulate as early as 10 to 30 minutes after i.v. injection and gave a clear binding pattern 2 hours after administration. In contrast, untargeted control particles showed almost no accumulation within the first 30 minutes and a very heterogeneous pattern after 2 to 4 hours. Only 8 hours after injection, all the particles extravasated into the tumor tissue. These data corroborate our finding that RGD-targeted nanoparticles show a higher accumulation compared to the untargeted control within the first hours after i.v. administration, as presented in the 24-hour kinetics herein. Another recent study using RGD-targeted, superparamagnetic polymeric micelle nanoprobes, combined with T2*-weighted time-resolved MRI, demonstrated an increased accumulation of the probe over the control in subcutaneous tumor animal models during the first 30 minutes after i.v. injection, showing an onset already within the first 5 minutes [38].

In a recently published study with a smaller, 50-nm version of the RGD nanoemulsion presented here, which also had hydrophobic glucocorticoids incorporated, we achieved significant tumor growth inhibition, demonstrating the versatility of this nanocarrier and its use for theranostics [42].

In conclusion, the RGD-conjugated nanoparticle contrast agent presented in this study can be used to noninvasively investigate differences in angiogenic activity in tumors and for angiogenesis phenotyping of tumors. Its biodegradability, flexibility, and capability of encapsulating hydrophobic materials/drugs make this platform suitable for theranostics and the tailored antiangiogenesis combination therapy with highly potent but water-insoluble cytotoxic agents.


The authors thank Rolando Nolasco of the Mount Sinai Pathology for the histologic cutting and staining.


confocal laser scanning microscopy
dynamic contrast-enhanced magnetic resonance imaging
magnetic resonance imaging
micro-vessel density
near-infrared fluorescence
polyethylene glycol


1This work was supported by the National Heart, Lung, and Blood Institute, National Institutes of Health, as a Program of Excellence in Nanotechnology Award, Contract No. HHSN268201000045C, by the Dutch Foundation “De Drie Lichten” (L.H.D.), by the Netherlands Organization for Scientific Research (NWO; VIDI 917.76.347), and R01 CA155432 (W.J.M.M.).


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