Multimodal Tumor-Targeting Peptides Functionalized with Both a

Sep 2, 2010 - Fijs W B van Leeuwen , Renato Valdés-Olmos , Tessa Buckle , Sergi Vidal-Sicart ... Damien Lhenry , Manuel Larrouy , Claire Bernhard , Vi...
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Bioconjugate Chem. 2010, 21, 1709–1719

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Multimodal Tumor-Targeting Peptides Functionalized with Both a Radioand a Fluorescent Label Joeri Kuil,† Aldrik H. Velders,‡ and Fijs W. B. van Leeuwen*,† Division of Diagnostic Oncology, The Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, 1066 CX Amsterdam, The Netherlands, Supramolecular Chemistry and Technology, MESA + Institute for Nanotechnology, University of Twente, PO Box 217, 7500 AE, Enschede, The Netherlands. Received June 17, 2010; Revised Manuscript Received August 4, 2010

The use of monolabeled tumor-targeting peptides for molecular imaging is widespread. However, it is often desirable to use the same compound for different clinical applications, e.g., combined pre- and intraoperative tumor detection. On the basis of their detection sensitivity, the combination of radioactivity and fluorescence is probably the most valuable in multimodal molecular imaging. In this review, we compare multimodal peptide derivatives and discuss the influence of the diagnostic labels on receptor affinity and biodistribution. On the basis of the described constructs, we propose improvements for the design of future multimodal tumor-targeting peptide derivatives.

INTRODUCTION For molecular imaging several modalities are in use, of which two important ones are radionuclide-based and fluorescencebased imaging (1). To overcome the individual limitations of these modalities, taking advantage of their individual strengths, they can be combined in so-called multimodal imaging approaches (2, 3). For each imaging modality, different molecular labels (also referred to as diagnostic functionalizations) are required. To link the different applications, it is desirable to use one-and-the-same imaging agent (4-6), functionalized with multiple diagnostic labels. A potential application for such multimodal compounds could be an integrated use of preoperative diagnostics and surgical planning (radioactivity-based), with intraoperative surgical image guidance (fluorescence-based) to the predefined lesion location (Figure 1). For preoperative imaging and surgical planning, radionuclidebased imaging technologies, such as single photon emission computed tomography (SPECT) (1) and positron emission tomography (PET) (7), are commonly used. Both modalities have a sensitivity in the nanomolar range (8), but suffer from limited spatial resolution. The total body penetration of the γ-radiation enables whole-body scans in 3D and allows for quantitative analysis of the tracer pharmacokinetics and distribution. To generate anatomical detail, these modalities are often used in combination with computed tomography (CT). Fluorescence-based molecular imaging becomes increasingly important, mainly due to the development of highly sensitive cameras and the very high spatial resolution that can be achieved with fluorescence imaging (9, 10). However, fluorescent signals have a limited tissue penetration making quantitative biodistribution analysis difficult. Despite this potential shortcoming, ‘superficial’ detection during surgical interventions, so-called fluorescence image guidance is a very promising application for fluorescence imaging (11). Indeed, various fluorescent compounds have already been suggested for such (intraoperative) imaging applications (12-15). Peptides have been extensively used in receptor-targeted imaging (16-19) and can be considered intermediate-sized * Corresponding author. E-mail: [email protected]. † The Netherlands Cancer Institute. ‡ University of Twente.

targeting compounds that are somewhat larger than small organic compounds but significantly smaller than antibodies. In peptides, an attachment point for relatively large diagnostic labels can be introduced away from the pharmacophore. This is less feasible for small organic compounds, which cannot easily be functionalized without loss of affinity (19). In addition, the biodistribution of peptides is in general better than that of antibodies, because peptides are much smaller than antibodies. Next to radiolabeled peptides (19), fluorescently and multimodal functionalized peptides have also been studied. In this review, we focus on the latter. For peptide-based receptor imaging, multiple targets are known (19), of which some have been targeted with multimodal peptides, viz., the somatostatin receptor, the gastrin releasing peptide receptor, the interleukin11 receptor R, and Rvβ3 integrin. For these targets, we here discuss multimodal peptides functionalized with a combination of radio- and fluorescent labels, grouped by the receptor target. To establish the influence of the labels on receptor binding and biodistribution of these peptides, the unlabeled and monolabeled peptides are included for comparison.

SOMATOSTATIN ANALOGUES Somatostatin receptors (especially subtype 2, sst2) can be upregulated in, e.g., neuroendocrine tumors (20), and targeting of this receptor for diagnostic purposes has been extensively studied. Particularly, (derivatives of) the truncated somatostatin cyclic analogues octreotide (D-Phe-cyclo(Cys-Phe-D-Trp-LysThr-Cys)-Threol, 1) and octreotate (D-Phe-cyclo(Cys-Phe-D-TrpLys-Thr-Cys)-Thr-OH, 2) have been used in the clinic for tumor visualization and therapy (Figure 2) (20). These two peptides possess low-nanomolar affinity for sst2 and have higher plasma half-lives than the native ligand somatostatin, i.e., 1.5 h versus a few minutes, respectively (21-23). For radioiodination, the second phenylalanine (Phe3) in octreotide is generally replaced by a tyrosine (Figure 2). The iodine labeled peptide [123I-Tyr3]octreotide, 3, has low-nanomolar affinity for its receptor: the dissociation constant (KD) ) 0.7-5.9 nM for cells obtained from clinical tumors (24, 25). In addition, it has reasonably good in vivo properties (Table 1) (26). Two major drawbacks of this radioiodinated octreotide are the in vivo instability of iodinated tyrosine (27) and the rapid clearance via the liver; i.e., after 24 h, tumor accumulation

10.1021/bc100276j  2010 American Chemical Society Published on Web 09/02/2010

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Figure 1. Schematic overview of the development and potential use of multimodal tumor-targeting peptides. The preoperative SPECT/CT example shows a tumor-bearing mouse, whereby the tumor was visualized with an indium-labeled peptide (In-DTPA-Ac-TZ14011) (79) that binds to the CXCR4 receptor (80). In the fluorescence surgical guidance image, the tumor was visualized with the same Ac-TZ14011 peptide labeled with the CyTE-777 near-infrared label (80, 81). A multimodal version of Ac-TZ14011 would allow both SPECT/CT and fluorescence imaging with the same compound.

Figure 2. Somatostatin receptor targeting peptides 1-11. In all compounds, the labels were attached to the N-terminus of the peptide, and in compound 11, the dye was attached to the C-terminus. For compounds 5 and 8-10, it was not specified which FITC isomer (or isomeric mixture) was used, and therefore, FITC is depicted without specification of isomer. The radiolabels are represented in blue and the fluorescent dyes in red.

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Table 1. Receptor Affinity, Biodistribution, and Imaging Data of the Somatostatin Analogues somatostatin analogue

IC50 (nM)

1 2 3 4 5 6 7 8 9 10 11

0.4 ( 0.07 0.6 ( 0.10 1.8-24.7 22 ( 3.6 9.9 ( 2.1 4.6 ( 0.7 71.3 10.3 ( 1.8 10.3 ( 2.1 45.9 ( 7.2

%ID/ga

tumor-to-muscle ratioa,b

imaging modality

ref

n/a n/a 5.53 ( 1.06 (1 h) 1.5 ( 0.4 (24 h) 0.28 (24 h) 0.287 ( 0.046 (1 h)

n/a n/a 21.3 (1 h) 150 (24 h) 7.0 (24 h) 1.5 (24 h)

n/a n/a radioactivity radioactivity fluorescence fluorescence fluorescence fluorescence

23 23 26 22 23 23 29 23 23 23 30

KD (nM) c

0.7-5.9 11.5 ( 1.8

a Measurement time post injection between parentheses. fluorescence. c Not applicable.

b

Tumor-to-muscle ratios are based on radioactivity data, except for 11, which is based on

could no longer be detected (25, 28). Both these problems can be overcome by using a chelate-based DTPA label (labeled with 111 In for SPECT): this complex is stable and yields an improved biodistribution profile with reduced liver uptake (25). Since attachment of a hydrophilic glucose unit also improved the tumor accumulation, this improvement in the biodistribution is most likely induced by the hydrophilic nature of DTPA (26). Both octreotide and octreotate have been N-terminally functionalized with a chelating DTPA or DOTA moiety, and both display a low-nanomolar affinity for the somatostatin receptor subtype sst2 (Table 1) (22). The 111In-labeled [DTPA0]octreotide 4 (Figure 2) is widely applied in the clinic (OctreoScan) and can be considered a clinical standard (20). Next to radiolabeling, somatostatin analogues have also been functionalized with various fluorescent dyes. [Tyr3]octreotate has, for example, been N-terminally labeled with fluorescein isothiocyanate (FITC) (5) and a carbocyanine near-infrared (NIR) dye (6) (Figure 2) (23). Although both labels reduced the receptor affinity by approximately a factor of 10 compared to the unlabeled peptide (Table 1), the octreotates 5 and 6 could be used to visualize tumors in vivo. Another interesting derivative is the (NIR) dye-octreotate construct 7 (Figure 2) (29). This compound has been used to visualize subdermal tumors in mice. To determine the biodistribution, Becker et al. labeled compound 7 with 125I, by radioiodination on the aromatic rings of the dye using a similar synthetic procedure as used for tyrosine labeling (29). Analysis 24 h postinjection confirmed that the tumor uptake of 7 was specific (Table 1). Achilefu et al. prepared octreotate peptides 8-10 labeled with both FITC and a DOTA or DTPA chelate (Figure 2 and Table 1) (23). The octreotate peptide 8 possesses an IC50 (50% inhibitory concentration) value of 71.3 nM for the somatostatin receptor. Surprisingly, changing the position of the labels improved the receptor affinity by almost a factor of 7, with peptides 9 and 10 both having an IC50 value of 10.3 nM. The affinity of the unfunctionalized octreotate for the somatostatin receptor is, however, significantly higher under these conditions, i.e., IC50 ) 0.6 nM. In other words, the multimodal label does interfere with receptor binding, but the affinities of 9 and 10 are still reasonably good and comparable with the monolabeled peptides 5 and 6. The biodistribution profile of the multimodal compounds 8-10 was unfortunately not examined in vivo. As a follow-up study, Edwards et al. prepared octreotate 11, which was N- and C-terminal functionalized with DOTA and the NIR dye cypate, respectively (Figure 2) (30). This DOTA-peptide construct was labeled with 64Cu to enable PET studies. Compound 11 with and without copper in the chelate had KD values of 11.5 nM and 2.03 nM, respectively. This indicates that even the binding of a metal ion can significantly alter the receptor affinity. The unfunctionalized octreotate possessed a KD value of 0.427 nM under the same conditions. Compound 11 mainly accumulated in the liver and kidneys, and

the uptake in the tumor was not significantly higher than in healthy tissue. The poor in vivo behavior of the multimodal octreotate 11 appeared to be caused by a lack of internalization into tumor cells (30).

BOMBESIN ANALOGUES By binding to the gastrin releasing peptide receptor (GRPR), the gastrin-releasing peptide and bombesin-like peptides can act as growth factors in many types of cancer, including prostate and (small cell) lung cancer (19, 31). Radiolabeled bombesin analogues have preclinically proven their potential in GRPRtargeted tumor imaging (32, 33). Native bombesin consists of 14 amino acid residues, while the last eight residues are most important for binding (34, 35). This octapeptide, Gln-Trp-AlaVal-Gly-His-Leu-Met (12 in Figure 3), is used in the multimodal bombesin peptides and is defined as bombesin(7-14) is this review. Similar to octreotide, bombesin analogues have also been radioiodinated, e.g., [125I-D-Tyr6,βAla11,Phe13,Nle14]bombesin(6-14) (13) (35, 36). For SPECT and PET imaging, various chelate-containing bombesin peptides have been described (37-39). Direct N-terminal labeling of bombesin(7-14) with 111 In-DOTA (14) decreased the affinity from low-nanomolar (13) to 110.6 nM (Table 2 and Figure 3) (34). However, when a β-alanine (15a), 1-aminopentanoic acid (15b), or 1-aminooctanoic acid (15c) spacer was inserted between the chelate and the peptide, the affinity was restored to the low-nanomolar range (IC50 ) 2.1, 1.7, and 0.6 nM, respectively). An even longer 11-aminoundecanoic acid spacer (15d), however, again reduced the affinity (i.e., IC50 ) 64.0 nM) (34). The tumor uptake of 111 In-DOTA-1-aminooctanoic acid-Gln-Trp-Ala-Val-Gly-HisLeu-Met (15c) was reasonable in PC 3 tumor-bearing SCID mice (34). Another study with bombesin(7-14) peptide 15c by Garrison et al. confirmed this tumor specificity (37). Bombesin(7-14) has also been fluorescently labeled with Alexa Fluor 680 attached to the N-terminus (40). In this compound (16), three glycine residues were placed between bombesin(7-14) and the dye, which is approximately as long as the 1-aminooctanoic acid spacer in 15c (Figure 3). The peptide 16 had an IC50 value of 7.7 nM and showed tumor specific uptake in vivo, although this was not quantified (Table 2). Bombesin analogues have also been dual-labeled with FITC and DTPA or DOTA (compounds 17-19 in Figure 3) (23). For the introduction of the two labels, an extra lysine residue was N-terminally introduced. The attachment of a DTPA chelate to the N-terminus decreased the affinity more than 10-fold. Intriguingly, no negative influence of the DTPA label was observed when DTPA was coupled to the side chain of the N-terminal lysine residue. The same trend was observed for dual-labeled peptides: compound 17, with DTPA attached to the N-terminus and FITC to the side chain of lysine, had a lower

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Figure 3. Bombesin derivatives 12-19. In all compounds, the labels were attached to the N-terminus of bombesin(7-14). For compounds 17-19, it was not specified which FITC isomer (or isomeric mixture) was used, and therefore, FITC is depicted without specification of isomer. The radiolabels are represented in blue and the fluorescent dyes in red. Table 2. Receptor Affinity, Biodistribution, and Imaging Data of the Bombesin Derivatives bombesin derivative

IC50 (nM)

KD (nM)

12 13 14 15a 15b 15c 15d 16 17 18 19

28.3 ( 3.7 0.72-1.1 110.6 ( 32.3 2.1 ( 0.3 1.7 ( 0.4 0.6 ( 0.1 64.0 ( 11.2 7.7 ( 1.4 276 20 ( 11.7 15 ( 9

-

a

%ID/ga n/ab

tumor-to-muscle ratioa

1.56 ( 0.45 (24 h) -

n/a 31.2 (24 h) -

imaging modality n/a

radioactivity fluorescence -

ref 23 35 34 34 34 34, 37 34 40 23 23 23

Measurement time post injection between parentheses. b Not applicable.

binding affinity (Table 2). Switching the position of the dye and chelate substantially improved the receptor affinity (IC50 ) 20 nM and 15 nM for compounds 18 and 19, respectively) when compared to the 276 nM of 17. The use of either DTPA or DOTA as a chelate for bombesin(7-14) did not have a significant influence on the binding affinity. A result similar to that was described for octreotate (see above and Tables 1 and 2). Unfortunately, none of these multimodal bombesin(7-14) peptides were studied in vivo.

IL-11 ANALOGUE The 21 kDa cytokine Interleukin-11 (IL-11) and its receptor (IL-11RR) have been related to breast cancer and breast cancer related bone metastasis (41, 42). By means of phage display, the cyclic nonapeptide cyclo(Cys-Gly-Arg-Arg-Ala-Gly-GlySer-Cys) was identified as a selective IL-11RR ligand, but no affinity constant has been provided (43, 44). Wang et al. duallabeled the cyclic peptide ligand 20 with the NIR dye IR-783 and a DTPA chelate (Figure 4) (45). They showed that the multimodal construct could label cells that possessed the IL11RR receptor, and preliminary in vivo results demonstrated

Figure 4. Multimodal labeled IL-11RR receptor ligand 20. The radiolabels are represented in blue and the fluorescent dyes in red.

that the construct has tumor targeting abilities. Accumulation in the kidneys was rather high, but no quantitative biodistribution

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data were presented. Unfortunately, no radioactive nor fluorescent monolabeled peptidic Il-11RR ligands have been reported. The lack of such reference compounds makes it difficult to establish the influence of the multimodal labels on the targeting properties.

RGD PEPTIDES Since tumor growth depends on sufficient blood supply, tumor cells stimulate the formation of new blood vessels via angiogenesis. Rvβ3 Integrin is a biomarker that is generally overexpressed during (tumor-induced) angiogenesis (46). Several extracellular matrix proteins, e.g., vitronectin, fibrinogen, and laminin, can bind to Rvβ3 by means of the Arg-Gly-Asp (RGD) sequence, present in these proteins (47). On the basis of this RGD sequence, the cyclic pentapeptide cyclo(Arg-Gly-Asp-DPhe-Val) 21 was designed, which has an IC50 in the highnanomolar range (100-4000 nM; Figure 5 and Table 3) (48). The D-phenylalanine residue of RGD was substituted for D-tyrosine to allow radioiodination (125I) for SPECT analysis (49, 50). The radioiodinated peptide cyclo(Arg-Gly-Asp-125ID-Tyr-Val) ([125Tyr4]RGD, 23) had a similar binding affinity for Rvβ3 as cyclo(Arg-Gly-Asp-D-Phe-Val) 21 and cyclo(ArgGly-Asp-D-Tyr-Val) 22 (Figure 5 and Table 3), indicating that substitution for tyrosine and subsequent iodination is welltolerated. Others, however, found that substitution of phenylalanine (21) for tyrosine (22) slightly reduced the affinity, i.e., IC50 ) 65 and 144 nM, respectively (51). For the attachment of a chelate and/or a dye to the RGD peptide, the valine residue is commonly substituted for a lysine (compound 24 in Figure 5), which again does not seem to affect the binding affinity (Table 3) (52). A representative example of such a construct is 111In-DOTA-Glu-cyclo(Arg-Gly-Asp-DPhe-Lys) 25, which has a dissociation constant in the lownanomolar range (KD ) 8.92 nM, IC50 ) 236 nM) (53). The uptake was 2.70%ID/g with a tumor-to-muscle ratio of 14.2 (Table 3) and 25 was rapidly cleared (54). Dye-labeled cyclic RGD peptides have also been widely studied and are exemplified by compound 26 (Figure 5 and Table 3) (55). This construct, which is labeled with the commercial available cyanine dye Cy5.5, has an IC50 value of 42.9 nM. The uptake in tumor bearing mice was approximately 6%ID/g 24 h after injection, the tumor-to-blood ratio was 10, and the tumor-to-muscle ratio 5. These numbers were obtained by measuring the fluorescence in dissected organs. However, the tumor-to-normal tissue ratio in living mice was 2.22 according to a fluorescence whole-body scan. The considerable difference between the numbers obtained with the two fluorescence approaches demonstrates that quantitative biodistribution analysis using fluorescence is less reliable than radioactivitybased (quantitative) biodistribution analysis. Garanger et al. introduced the concept of a reactive multimodal label, which can be used to label any peptide or protein (56). They reasoned that such a label would decrease the chance of interference with receptor binding compared to the use of two separate labels. As an example, they labeled RGD with a label consisting of an NBD fluorescent dye and a DTPA chelate, resulting in compound 27 (Figure 5) (57). The receptor binding and targeting ability of 27 was quantified using SPECT and (fluorescence) immunohistochemistry. Cyclic RGD has also been functionalized with a combination of NIR dye IRDye800 and 111In-DTPA, yielding compound 28 (Figure 5) (58, 59). The IC50 value (3.86 µM) of this multimodal RGD derivative was similar to cyclic RGD itself under the same conditions. This indicates that the multimodal labels did not interfere with receptor binding of RGD (Table 3). Furthermore, biodistribution studies demonstrated that 28 had a tumor uptake of 1.41%ID/g at 24 h with a tumor-to-muscle ratio of 5.0.

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Unfortunately, the tumor uptake was accompanied by a higher degree of nonspecific uptake as compared to peptide 28 without the IRDye800 label. This suggests that the addition of IRDye800 enhances nonspecific background uptake (59). Recently, Edwards et al. published a similar construct as 28: cyclic RGD labeled with a cypate dye and 111In-DOTA (compound 29 in Figure 5) (60). They confirmed that the dual introduction of a chelate and a cypate dye does not reduce the binding affinity for Rvβ3 (IC50 ) 0.046 nM, KD ) 0.029 nM) compared to [Tyr4]RGD (22) (Table 3). The high affinity found for 29, however, differs from other data, e.g., those obtained with 28. This discrepancy can be a result of the smaller hill coefficient (slope) of the inhibition curve. The tumor uptake of this agent was 7.59%ID/g at 24 h and 2.48%ID/g at 72 h. The tumor-to-muscle ratio was 6.36 according to radioactivity data (24 h post injection) and the fluorescence intensity in the individial organs revealed a similar distribution trend. These data seem very promising, although it is difficult to compare 29 with other (multimodal) agents, e.g., compounds 27 and 28, as different control samples were used. Yet another multimodal RGD peptide 30 possesses a cypate dye and desferrioxamine (DFO) as a chelate (Figure 5) (61). DFO is an iron chelator that also binds 67Ga/68Ga, which can be used as isotope for PET imaging. The IC50 value of 30 is 180 nM, which is slightly lower than that of RGD itself under the same conditions (Table 3). The multimodal peptide was rapidly internalized into cells within 1 h after incubation. Unfortunately, no in vivo experiments were conducted. Besides the relatively small multimodal RGD peptides mentioned above, larger peptide structures have also been synthesized. The 33 residue-containing RGD peptide “knottin” was engineered by means of yeast surface display and directed evolution (62). The IC50 value of this knottin peptide was 19 nM in a cell binding assay, and N-terminal labeling with Cy5.5 and a DOTA chelate (31) did not have a large effect on the binding affinity (Figure 5 and Table 3) (63). The addition of a Cy5.5 dye increased the in vivo tumor retention and kidney uptake compared to the DOTA functionalized derivative. The biodistribution of 31 was assessed with PET using a 64Cu radiolabel. The tumor uptake was 4.57%ID/g, and the tumorto-muscle ratio was approximately 12, both determined 24 h post injection (Table 3). The PAMAM dendrimer PAMAM-(Alexa594)0.75-(Gd-DTPA)23-(111In-DTPA)0-4-(cyclo(Arg-Gly-Asp-D-Phe-Lys))2 32 has been used for NIR fluorescence and radioactivity-based imaging in combination with magnetic resonance (MR) imaging (Figure 5) (64). This compound contains a third-generation PAMAM ethylenediamine core dendrimer, consisting of 32 end groups. Because MR imaging requires large quantities of contrast agents, 28 end groups were functionalized with DTPA, of which 23 were labeled with paramagnetic gadolinium (Gd). The remaining four DTPA chelates were partly labeled with 111In (i.e., 0-4 labeled DTPA chelates per dendrimer), and on average, 0.75 end groups in each dendrimer were functionalized with the Alexa594 dye. Only two end groups were functionalized with RGD peptides to bind Rvβ3 expressing cells in vitro. The binding affinity was not determined in this study, which makes comparison with other RGD constructs difficult. Moreover, in vivo studies failed to demonstrate tumor uptake of the dendrimer and almost all of the injected compound accumulated in the kidneys, liver, and spleen. This indicates two possible design flaws: (i) not enough RGD peptides are present in dendrimer 32 and (ii) the macromolecular PAMAM-dendrimer scaffold has a negative influence on the biodistribution and thus the targeting ability of the RGD-peptides. RGD-tagged quantum dots (QDs) have been functionalized with DOTA chelates (DOTA-QD-RGD, 33) to enable PET

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Figure 5. Representation of RGD-peptide based imaging constructs 21-33. In all compounds, except 23 and 31, the labels were attached to the side chain of the lysine residue. For clarity reasons, the large PAMAM-dendrimer and QD scaffold have been schematically represented in a relatively smaller size. The radiolabels are represented in blue and the fluorescent dyes in red.

studies using 64Cu (Figure 5) (65). These QDs had approximately 90 RGD peptides and 28 DOTA chelates per particle and subsequently yielded a 60-fold higher affinity for Rvβ3 than [Tyr4,Lys5]RGD (Table 3). The relatively large QDs, however,

in vivo gave a high degree of nonspecific liver uptake (40-55%). Despite this, RGD tagged 64Cu-DOTA-QD-RGD 33 gave significantly more tumor uptake (4.3%ID/g after 25 h) compared to a nontargeted control 64Cu-DOTA-QD (less than

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Table 3. Receptor Affinity, Biodistribution, and Imaging Data of the RGD Derivatives RGD derivative 21 22 23 24 25 26 27 28 29 30 31 32 33

IC50 (nM) 100-4000 similar to 21 similar to 21 similar to 21 236 42.9 ( 1.2 3860 ( 360 0.046 ( 0.023 180 30 ( 7 3.88

%ID/ga

KD (nM) 8.92 0.029 ( 0.016 -

c

n/a n/a 0.77 ( 0.10 (2 h) 2.70 ( 0.29 (2 h) 6 (24 h) 1.41 ( 0.49 (24 h) 7.59 ( 0.45 (24 h) 4.57 ( 0.70 (24 h) 1.25 ( 0.51 (2 h) 4.3 ( 0.5 (25 h)

tumor-to-muscle ratioa,b n/a n/a 4.5 (2 h) 14.2 (2 h) 5 (24 h) 5.0 (24 h) 6.36 ( 0.04 (24 h) 3.41 ( 0.21 (24 h) 12 (24 h)d 12.5 (24 h)d 3.30 ( 0.03 (2 h)e 4.1 ( 1.1 (5 h)

imaging modality

ref

n/a n/a radioactivity radioactivity fluorescence radioactivity radioactivity, fluorescence radioactivity, fluorescence radioactivity, fluorescence radioactivity

48 49 49, 51 52 53, 54, 78 55 57 58, 59 60 61 63 64 65

a Measurement time post injection between parentheses. b Tumor-to-muscle ratios are based on radioactivity data, except for 5 (26), 3.41 ( 0.21 (29), and 12.5 (31), which are based on fluorescence. c Not applicable. d Tumor-to-background tissue ratio. e Tumor-to-blood ratio.

1%ID/g after 25 h; Table 3). Tissue staining showed a good overlap between CD31 antibody staining of blood vessels and 33 staining, indicating that the vast majority of injected QD 33 did not extravasate from the angiogenic blood vessels. This result is similar to that found for the PAMAM dendrimer 32 (see above) (64).

COMPARISON OF THE MULTIMODAL TUMORTARGETING PEPTIDES The use of multiple diagnostic functionalizations in one imaging agent enables tumor detection with different techniques. As stated in the Introduction, we think that a promising application of such compounds would be the combined use for preoperative and intraoperative imaging (Figure 1). In our opinion, the combined use of radioactive and fluorescent labels is the best option for this application. Such an application, however, has also been suggested for the combination of MR and optical imaging (66-68). Of the four different types of tumor-targeting peptides discussed in this review, RGD has been studied the most in combination with multimodal labels. As all the different peptides target receptors on the cell surface, there is no clear reason why the RGD peptide is more suitable for multimodal functionalization than the others. Most likely, this apparent focus on RGD is caused by the wide applicability of angiogenesis imaging. In addition to the four different tumor-targeting peptides described in this review, this multimodal technology can in theory also be expanded to peptides that target different tumorspecific receptors, e.g., the cholescystokinin-B, the vasoactive intestinal peptide receptor, the melanocortin-1 receptor, the neurotensin receptor, the neuropeptide Y receptor, the gonadotropin releasing hormone receptor, the glucagon-like peptide-1 receptor, and the chemokine receptor 4 (19). Furthermore, the multimodal concept has already been applied in non-receptortargeted peptides, namely, in a caspase-3 substrate and Tat peptides (69-71). A challenge in designing multimodal peptides is to retain the receptor affinity and the biodistribution of the original receptortargeting peptide. Comparing reported multimodal peptides, as has been done in this paper, can facilitate the design of future multimodal peptide-derivatives. Unfortunately, comparison of the different multimodal peptide-derivatives is difficult due to lack of complete data sets for all the individual peptides. An IC50 value has been reported for most peptides (Tables 1-3), but as IC50 values are dependent on experimental settings (e.g., the concentration of competing ligand), it is difficult to compare the data from different studies. A more adequate comparison of the binding affinity found in different experiments can be made based on association or dissociation constants (KA/KD). Nevertheless, these can still differ for cell types. Unfortunately,

only a limited number of KD values have been reported (Tables 1-3). Furthermore, the amount of actual in vivo studies is limited (Tables 1-3) (5), which hinders the analysis of the effect that the multimodal labels have on the biodistribution and the tumor targeting efficacy of the different peptides. All together, this suggests that a standardization of the experiments, including receptor affinity data and in vivo data, is desirable. For future compounds, if possible, we propose a combined report of IC50, KD, in vivo distribution profile, as well as the tumor accumulation. Despite the difficulties in comparing the multimodal peptides, some general observations can be made regarding (i) the position of the labels, (ii) the type of labels, and (iii) the size relation between the targeting moiety and the label. These points are discussed below. Position of the Labels. The binding affinity of peptides is reduced when a diagnostic label is placed close to the pharmacophore. The bombesin(7-14) peptide 14, for example, has a chelate directly attached to the peptide, resulting in a decrease in the peptide’s binding affinity. When a 1-octanoic acid spacer was placed between the peptide and the chelate (peptide 15c), the binding affinity was regained. This effect also appears to be valid for other peptides. Therefore, by choosing the attachment point strategically, far away from the pharmacophore, and by incorporation of the appropriate spacer between the peptide and the labels, multimodal labels should have a minimal effect on the receptor binding affinity. When the diagnostic labels are placed relatively close to the pharmacophore, seemingly minor changes can already result in large differences in the receptor affinity. This is exemplified in octreotate and bombesin derivatives. Both peptide derivatives have been N-terminally functionalized with a lysine residue. On this lysine, one label was attached to the side chain and one to the N-terminus. For octreotate, the chelate had to be attached to the N-terminus and the FITC dye to the side chain, as reversed attachment significantly reduced the receptor affinity (compounds 8-10 in Figure 2 and Table 1). Intriguingly, the opposite trend was observed for bombesin(7-14) with respect to the positions of the dye and the chelate (compounds 17-19 in Figure 3 and Table 2). It is not directly clear what causes this discrepancy between the two peptides. Type of Labels. The choice of dye mainly depends on the spectral properties and the sensitivity of the detection modality used. Besides having different spectral properties, organic dyes can also be structurally and chemically very different (Figures 2-5), something that has an influence on the distribution of the peptide (72). Changing a visual dye to a NIR dye to improve its value in deep tissue imaging (29, 73) will most likely result in an altered biodistribution of the peptide conjugate. Hence, application dictated that dye variations have to be individually studied for their receptor affinity and distribution prior to use.

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merization. Surprisingly, such a multivalent, multimodal derivative has not been reported yet. It is important to note, however, that the above data indicate that structures which are too large have a negative influence on the biodistribution, viz., PAMAM dendrimer 32 and quantum dot 33 cannot extravasate into a tumor. “Shielding” of the diagnostic labels caused by multimerization (Figure 6) is a promising side effect, which may help reduce the influence of the labels. Such dendritic structures allow placement of the multimodal label in the core, while the targeting moieties are placed on the extremities. This design most likely reduces the interactions between the multimodal labels and the biological environment. Therefore, a multimodal core functionalized with multiple peptides has, in our opinion, the highest chance for success and is currently under investigation in our group.

CONCLUSIONS

Figure 6. Tetravalent RGD-functionalized dendrimer 34 with an 111InDOTA chelate (54). The radiolabel is represented in blue.

The attachment of a radiolabel to a peptide should have a minimal (negative) influence on its properties. Here, addition of a single radioactive atom to the peptide via, e.g., direct iodination (123I and 125I for SPECT or 124I for PET) will have the smallest influence on the distribution. The most important drawback of iodination is rapid deiodination of mono- and diiodotyrosine by hepatic deiodases (27). Because of this instability, most multimodal peptides contain stable but relatively large chelate-metal complexes, e.g., DTPA or DOTA with 111In, 64 Cu, or 68Ga. A disadvantage of the predominantly used DTPA and DOTA, however, is that they have a larger influence on the receptor affinity than iodination. A multimodal label consisting of a dye, a chelate, and, optionally, a spacer is generally as large as the peptide to be labeled (Figures 2-5). Clearly, this can influence the biodistribution and nonspecific uptake. The only reported small multimodal peptide with good in vivo properties is RGD peptide 29. However, for the structurally related compound 28 it was found that the dye caused nonspecific tissue uptake compared to the monolabeled derivative, while the extent of such an effect has not been investigated for 29. Size of the Peptides with Respect to the Labels. One approach to reduce the negative influence of the labels on the biodistribution is to use larger peptides. This strategy was successful for “knottin” peptide 31; both the binding affinity for its receptor and the tumor specific biodistribution were not greatly affected by the diagnostic labels. However, it is unclear whether this approach can be employed more widely, since 31 is the only example in the literature. Furthermore, larger peptides tend to be less metabolically stable and can be immunogenic (74). Possible Improvements in the Structural Design of Multimodal Peptide Derivatives. Enhancing the ratio of peptide/ label in the molecule via multimerization is expected to reduce the negative influence of the diagnostic labels. This strategy has already been successfully applied for monolabeled peptides (54, 75-77); e.g., a tetravalent RGD peptide-functionalized dendrimer (34) with a DOTA chelate conjugated to the core of the dendrimer (Figure 6) (54). This tetravalent construct has approximately six times more affinity for Rvβ3 integrin than the monovalent peptide (IC50 ) 19.6 and 120 nM, respectively). Moreover, the tetravalent dendrimer had a significantly better biodistribution than the monovalent peptide. This illustrates the value of enhancing the peptide/label ratio by means of multi-

Targeted multimodal peptides have the potential to be used in various diagnostic applications. For example, multimodal peptides can be employed in an integrated approach for combined pre- and intraoperative imaging of tumor tissue. The receptor affinity and the biodistribution of most reported multimodal peptides are not as good as those found for the unlabeled and/or monolabeled peptides. However, this partial loss of affinity and targeting ability is compensated by the fact that multimodal peptides allow for use in novel diagnostic applications such as the combined pre- and intraoperative imaging paradigm. Furthermore, the use of multimodal labels in multimeric peptide structures may reduce the negative influence of a multimodal label. In such an increasingly optimized structural design, multimodal labeled peptides based on radioactivity and fluorescence should reveal their full potential.

ACKNOWLEDGMENT This research is supported, in part, by the Technology Foundation, applied, science division of NWO, and the technology program of the Ministry of Economic Affairs (Grant No. STW BGT 7528 Veni; FvL), a KWF-translational research award (Grant No. PGF 2009-4344; FvL), and within the framework of CTMM, the Centre for Translational Molecular Medicine (http://www.ctmm.nl), project Breast CARE (grant 030-104; JK).

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