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Review

Click Chemistry as a Tool for Cell Engineering and Drug Delivery

Laboratory of Biopharmaceutics, Faculty of Pharmaceutical Sciences, Tokyo University of Science, 2641 Yamazaki, Noda, Chiba 278-8510, Japan
*
Author to whom correspondence should be addressed.
Molecules 2019, 24(1), 172; https://doi.org/10.3390/molecules24010172
Submission received: 30 November 2018 / Revised: 24 December 2018 / Accepted: 29 December 2018 / Published: 4 January 2019

Abstract

:
Click chemistry has great potential for use in binding between nucleic acids, lipids, proteins, and other molecules, and has been used in many research fields because of its beneficial characteristics, including high yield, high specificity, and simplicity. The recent development of copper-free and less cytotoxic click chemistry reactions has allowed for the application of click chemistry to the field of medicine. Moreover, metabolic glycoengineering allows for the direct modification of living cells with substrates for click chemistry either in vitro or in vivo. As such, click chemistry has become a powerful tool for cell transplantation and drug delivery. In this review, we describe some applications of click chemistry for cell engineering in cell transplantation and for drug delivery in the diagnosis and treatment of diseases.

1. Introduction

Click chemistry is a term that was first proposed by Sharpless et al. in 2001. The characteristics of click chemistry include a high yield, a wide scope, less cytotoxic byproducts, a high stereospecificity, and a simple reaction [1]. Click chemistry reactions can occur under physiological conditions and the resulting chemical bonds are irreversible. Therefore, click chemistry is widely used for the modification of biomolecules, such as nucleic acids, lipids, and proteins with various compounds. Among the click chemistry reactions, the copper (I)-catalyzed azide-alkyne 1,3-dipolar cycloaddition (CuAAC) reaction has been used as a bioorthogonal reaction in the life science research fields (Scheme 1A) [2,3]. Moreover, the strain-promoted [3 + 2] azide-alkyne cycloaddition (SPAAC) reaction, which is a new type copper-free click chemistry developed by Bertozzi et al. in 2004, has brought about the successful application of click reactions to living cells without copper-induced cytotoxicity. They also reported that cyclooctyne (OCT) reacted with azide under physiological conditions without copper catalysis (Scheme 1B) [4,5]. However, the disadvantage of SPAAC reaction using OCT is that a long reaction time is required. The second-order rate constant of the reaction is 0.0024 M−1 s−1, which means that it takes over 120 min to sufficiently label azide-modified cells with OCT under physiological conditions [4]. To solve this problem, researchers have developed modified OCTs, including azadibenzocyclooctyne (ADIBO/DIBAC/DBCO) [6,7], biarylazacyclooctynone [8], bicyclo[6.1.0]nonyne (BCN) [9], dibenzocyclooctyne [10], and difluorinated cyclooctyne (DIFO) [11]. The second-order rates of these modified OCTs are about 24- to 400-fold greater than that of OCT and faster than that of the Staudinger reaction, a bioorthogonal reaction, under physiological conditions [5,12]. Furthermore, BCN and DBCO have a high solubility in water and a low affinity for serum proteins such as albumin. Therefore, copper-free click chemistry using modified OCTs is quicker, has a lower toxicity, and is widely recognized as a useful cell engineering method, in turn increasing the potential biological applications of click chemistry. In another study, Blackman et al. successfully developed the inverse electron demand Diels-Alder (iEDDA) reaction between the cycloaddition of s-tetrazine and trans-cyclooctene (TCO) derivatives, resulting in a faster copper-free click chemistry than SPAAC reactions (Scheme 1C) [13]. The second-order rate of 3,6-di-(2-pyridyl)-s-tetrazine with TCO is 2000 M−1 s−1 (in 9:1 methanol/water at 25 °C) and the reaction can take place in both water and cell culture media. Moreover, other researchers have developed bioorthogonal chemical reporters of the iEDDA reaction, including norbornene [14], cyclopropene [15,16], N-acylazetine [17], or vinylboronic acid [18], which react with tetrazines (Tz) under physiological conditions, and have demonstrated their usefulness for cell labeling with fluorophore and functional molecules. Importantly, these reagents hardly show toxicity to cells or animals at normal concentrations (we summarized in Table 1 and Table 2). Therefore, these rapid bioorthogonal iEDDA reactions are expected to be applied for cell engineering in biological field.
Metabolic engineering is a click chemistry tool that allows for the modification of living cells with chemical tags. Since biocomponents such as sugars, amino acids, or lipids are used and metabolized in living cells, using biomolecules with chemical tags can introduce chemical tags into proteins [19], glycans [20,21], and lipids [22] in living cells. Metabolic glycoengineering using sugar analogs is particularly useful for the introduction of SPAAC and iEDDA chemical substrates into living cells [21,23,24]. For example, monosaccharides with chemical tags can be incorporated into glycans in cells through a biosynthesis pathway to present chemical tags, including azide, alkene, and alkyne, on the surface of cells [21,25]. In metabolic glycoengineering, N-azidoacetyl-mannosamine (Ac4ManNAz) is widely used for engineering of the cell surface. Ac4ManNAz is metabolized into N-azidoacetyl neuraminic acid and is incorporated into glycans, such that azide groups are expressed in the glycans on the surface of living cells (Figure 1). Furthermore, Ac4ManNAz is not affected by the characteristics of culture cells (attachment, differentiation, migration, and mitochondria functions) with a lower toxicity in animal tissues [20,26,27,28,29]. Table 1 and Table 2 summarize the non-toxic dose ranges of the reagents reported in in vitro and in vivo studies using click chemistry and metabolic glycoengineering. Azide groups on cell surfaces after metabolic glycoengineering gradually disappear due to the hydrolysis of glycans by neuraminidase in cells after internalization [25,30]. However, it has been reported that azide groups were detected on the cell surface for at least 14 days [31], suggesting that metabolic glycoengineering is a suitable tool for cell labeling or functionalization through click chemistry.
In this review, we describe the applications of click chemistry for cell engineering and drug delivery systems for the diagnosis and treatment of diseases.

2. Click Chemistry as a Tool for Cell Engineering in Cell Transplantation

Cell transplantation or cell-based therapy is a powerful therapeutic method for the treatment of various diseases including intractable diseases. Recently, clinical trials of cell-based therapy using stem cells such as mesenchymal stem cells (MSCs) have been conducted [46,47]. However, in most cases, the optimal therapeutic effect of transplanted cells has not been achieved due to low engraftment rates and short survival durations after transplantation [48,49,50]. Recently, many researchers have attempted to improve these therapeutic effects by functionalizing these cells. In addition, the biodistribution and fate of transplanted cells are unclear due to a lack of in vivo cell tracking methods. It is important to understand the biodistribution and biological fate of transplanted cells in order to develop a therapeutic strategy for cell-based therapies. Cell tracking techniques provide information about the in vivo behavior of transplanted cells, including migration, translocation, proliferation, cell death, and differentiation [51,52,53]. Researchers have also attempted to develop a cell tracking method. In this section, we summarize some applications of click chemistry for cell engineering in cell transplantation.

2.1. Click Chemistry as a Tracking Tool for Transplanted Cells

Non-invasive cell tracking methods are widely used to monitor transplanted cells in real time [50,54,55]. They are classified into two categories, defined by the use of either reporter proteins or imageable probes. The cell tracking method using reporter proteins, such as fluorescent or luminescent proteins, is suitable for the imaging of living cells [56,57,58]. In addition, this tracking method is beneficial for the long-term tracking of cells that stably express the proteins. However, this method requires genetic engineering before transplantation, which may lead to changes in cellular characteristics. On the other hand, the cell tracking method using imageable probes can label cells with a variety of probes, including fluorescence dyes, reporter proteins, and radiotracers. As such, the labeled cells can be monitored not only by fluorescence and bioluminescence imaging but also by positron emission tomography (PET), computed tomography (CT), and magnetic resonance (MR) imaging after transplantation [59,60,61,62]. MR imaging is able to detect a small number of transplanted cells in deep tissues [63]. Furthermore, the cell tracking method involves a short reaction time and label cells with high efficacy. However, the detectable duration of this method is limited because of the instability of the labels [51,64]. In addition, imageable probes such as lipophilic dyes and radiotracers often cause cytotoxicity [50,64]. Recently, a new cell labeling method with imageable probes has been developed involving the application of metabolic glycoengineering and copper-free click chemistry (Figure 2A). The combination of metabolic glycoengineering and copper-free click chemistry allows for the stable labeling of cells with various molecules without affecting the characteristics of the cells. Therefore, this method is expected to overcome the problems associated with the direct cell labeling method. The applications of copper-free click reactions for cell tracking are summarized in Table 3.
The first application of click chemistry to track transplanted cells was performed using Ac4ManNAz and DBCO-fluorophore [38]. Cells of human lung adenocarcinoma cell line A549 were incubated with Ac4ManNAz to generate azide groups on the surface of A549 cells and were transplanted to the liver of mice. DBCO-Cy5 was then administered into the mouse tail vein after transplantation of azide-labeled A549 cells. These experiments showed that A549 cells with DBCO-Cy5 were detected in the liver using ex vivo analysis. Although this method allows for the reduction of false signals derived from cell fragments that are phagocytosed by macrophages, the differences of in vivo distribution between azide-labeled cells and DBCO-Cy5 may affect the detectability or labeling efficacy. Then, Yoon et al. found that the combination of metabolic glycoengineering and SPAAC reaction was useful for detecting transplanted cells in vivo [29]. This method allows for the detection of transplanted cells over a longer time than a conventional lipophilic tracer without the impairment of cellular functions. They labeled chondrocytes with near-infrared (NIR) fluorescence dye by using Ac4ManNAz and dibenzylcyclooctyne-SETA 650 (DBCO-650), and subcutaneously transplanted DBCO-650-labeled chondrocytes into mice. Transplanted chondrocytes could be detected for 4 weeks using in vivo imaging analysis, and this labeling was found to have a minimal effect on the cartilage formation of chondrocytes. Lee et al. also demonstrated that metabolic glycoengineering and the SPAAC reaction was useful for tracking transplanted stem cells [31]. Since MSCs are able to home to inflammation sites and tumor tissues in response to chemokines released from inflammation sites or tumors [46,65,66], the migration of MSCs was traced. Lee et al. labeled adipose-derived mesenchymal stem cells (ASCs) with Cy5, a fluorescence dye, using Ac4ManNAz and DBCO-Cy5 and confirmed the fluorescence signal from Cy5-labeled ASCs for 14 days, both in vitro and in vivo.
In addition, they demonstrated that the migration potency of Cy5-labeled ASCs toward ischemic lesions was maintained. Furthermore, Layek et al. intravenously administered Cy5.5-labeled MSCs prepared by using the combination of metabolic glycoengineering and the SPAAC reaction into tumor-bearing mice and normal mice [33]. Although the MSC-derived fluorescence signal was hardly detected in normal mice, the signal was detected in the tumors of tumor-bearing mice. In addition, labeling with Ac4ManNAz and DBCO-fluorophore had a minimal effect on the differentiation ability of MSCs into adipocytes and osteocytes.

2.2. Click Chemistry as a Tool for Cell-Based Drug Delivery

Since MSCs are able to home to tumor tissues, as described above, they have been applied as a drug delivery vehicle in cancer therapy [67,68]. Researchers have attempted to use MSCs as anti-cancer vehicles by loading them with anti-cancer drug-containing nanoparticles via endocytosis [69,70,71]. Systemically injected drug-loaded MSCs are reported to migrate to tumor tissues and release drugs by drug efflux transporters or external stimulus. However, drug loading with MSCs via endocytosis requires a long preparation (over 24 h). In addition, the drug loading capacity of MSCs is limited because of the small occupation of endosomes in the cytoplasm [72]. To overcome these limitations, cell surface modification using metabolic glycoengineering and copper-free click chemistry could be used for the functionalization of MSCs with nanoparticles (Figure 3B).
In 2017, Lee et al. developed a simple cell surface modification method using a combination of metabolic glycoengineering and the SPAAC reaction [35]. First, they prepared BCN-modified imageable chitosan nanoparticles (BCN-CNPs). CNPs can easily encapsulate various drugs with high biocompatibility and are widely used for drug delivery [73]. They encapsulated Cy5.5, iron oxide nanoparticles, and gold nanoparticles into the BCN-CNPs for optical imaging, MR imaging, and CT imaging. Next, BCN-CNPs were added to azide-labeled MSCs prepared using Ac4ManNAz to obtain BCN-CNPs-Cy5.5-labeled MSCs. In this method, BCN-CNPs were modified to the cell surface of MSCs for less than 1 h. Although the fluorescence signal from BCN-CNPs-Cy5.5-labeled MSCs was detected for 5 days under in vitro culture conditions, the fluorescence signal gradually decreased with time. On the other hand, the fluorescence signals from BCN-CNPs-Cy5.5 labeled MSCs were detected for 15 days after subcutaneous transplantation into nude mice. In this paper, the authors demonstrated that the combination of metabolic glycoengineering and the SPAAC reaction allowed for the modification of MSCs with CNPs in a short reaction time, and that CNP-modified MSCs could be tracked over the long-term. On the other hand, these results indicate that the combination of metabolic glycoengineering and the SPAAC reaction may be a good tool to add anti-cancer functions to MSCs by modifying MSCs with anticancer agent-loaded CNPs. Therefore, the use of MSCs with CNPs that are stably loaded could be beneficial for drug delivery.
As such, metabolic glycoengineering can generate bioorthogonal chemical receptors on the surface of cells and therefore provides a binding site for nanoparticles. Copper-free click chemistry allows to modify cells with nanoparticles containing a variety of compounds in a short amount of time.

2.3. Applications of Click Chemistry for the Formation of Cell Complexes

The combination of metabolic glycoengineering and click chemistry is a powerful tool for cell surface modification. This cell surface modification method can be used for cell functionalization in cell-based sciences and engineering [23]. Koo et al. developed the cell gluing technique based on the iEDDA reaction (Figure 2C) [34]. Non-adherent human Jurkat T lymphocytes were treated with Ac4ManNAz followed by the addition of Tz-DBCO or TCO-DBCO. After incubation for 10 min, about 46% of the Tz- and TCO-modified Jurkat cells formed two- or multiple-cell pairs. The chemically glued cells were able to withstand a shear stress of over 20 dyn/cm2, which was higher than the typical vessel-wall shear stress levels of 1–6 dyn/cm2 in veins and 15 dyn/cm2 in arteries. Furthermore, after the intravenous injection of the glued cells, the cells survived and maintained their structures of two- or multiple-cell pairs in the bloodstream. The results showed that iEDDA reactions could be used to successfully carry out stable cell-cell adhesion in a short amount of time. Although there are few studies on the application of iEDDA reactions for cell engineering, the use of the iEDDA reaction has many benefits in cell engineering due to its fast reaction rate.

3. Applications of Click Chemistry for Drug Delivery in the Diagnosis and Treatment of Diseases

Recently, copper-free click chemistry has been applied for drug delivery in the diagnosis and treatment of diseases as an effective tissue-targeting method due to its high specificity, quick reaction rate, and stability. Some researchers have demonstrated that the labeling method using metabolic glycoengineering and copper-free click chemistry is useful for the visualization of glycans in vivo [26,74]. These studies showed that copper-free click chemistry could be a useful application tool for in vivo molecule imaging, cell tracking, and tissue engineering. Furthermore, copper-free click chemistry has been used for tissue-targeted delivery of imaging agents and anti-cancer agents. In cancer therapy, tumor tissue or cancer cell-specific drug delivery is highly desirable in order to improve therapeutic efficacy and avoid adverse effects [75]. Furthermore, cancer-specific drug delivery is needed for detecting cancer cells in order to determine tumor size and metastasis [76]. Although many tumor tissue- or cancer cell-specific delivery systems have been developed, cancer-specific drug delivery is yet to be fully achieved. This is due to the fact that current drug delivery systems do not show sufficient specificity to cancer and have non-specific biodistributions. Antibody-based drug delivery systems using monoclonal antibodies (mAb) binding to cancer-specific antigens are one of the most suitable and successful strategies for cancer-targeting therapy. For example, mAb-drug conjugates (ADCs) and mAb-coated nanoparticles successfully contribute to improving accumulation and cellular uptake in cancer cells [77,78] through the enhanced permeability and retention (EPR) effect [79,80]. However, antibody-based drug delivery systems have some limitations, including their heterogeneity and the downregulation of antigens in cancer cells due to long-term chemotherapy or chronic drug exposure [81]. Metabolic glycoengineering can artificially generate bioorthogonal chemical receptors, such as azide, on the surface of various types of cells, including cancer cells [20,24,40]. If bioorthogonal chemical receptors can be selectively introduced onto the surface of cancer cells, click chemistry with metabolic glycoengineering could overcome these limitations. Recently, researchers have attempted to develop a strategy which enables cancer cell-specific labeling with substrates for click chemistry, in an attempt to apply click chemistry and metabolic glycoengineering to cancer therapy and diagnosis. The application of metabolic glycoengineering and copper-free click chemistry for tumor targeting delivery and imaging are summarized in Table 4. In this section, we describe recent applications of click chemistry for drug delivery in the diagnosis and treatment of diseases.

3.1. Tumor-Specific Labeling with Azide Groups

The combination of metabolic glycoengineering and click chemistry is a powerful tool for the labeling and targeting of cancer cells [24,40]. Ac4ManNAz is widely used for the introduction of azide groups onto the surface of cancer cells because it can easily introduce azide groups both in vitro and in vivo without any apparent toxicity [28,74,82]. However, if systemically injected, Ac4ManNAz is distributed into many tissues, such that azide groups are introduced not only into the targeted tumor tissue but also into normal tissue [39,83]. Since non-specific azide labeling can have undesirable effects, it is important to selectively introduce azide groups into target cells for successful cancer-specific drug delivery, which can be achieved by using metabolic glycoengineering and click chemistry.
Koo et al. carried out successful tumor-targeting drug delivery using bioorthogonal chemical receptors and the SPAAC reaction [40]. They introduced azide groups into tumor cells in subcutaneous tumor-bearing mice by intratumorally injecting Ac4ManNAz. The amount of azide groups in the tumor tissues was found to increase in a dose-dependent manner. Furthermore, the accumulation of DBCO-modified liposomes in azide-expressing tumor tissue increased significantly after intravenous administration compared with untreated tumor tissues.
This result shows that azide-expressing tumor cells can be targeted by DBCO-modified drugs via the SPAAC reaction. However, the intratumoral injection of Ac4ManNAz poses a disadvantage since it has limitations in clinical application [103]. To specifically introduce azide groups into cancer cells, Ac4ManNAz analogs have been developed (Figure 3A).
Chang et al. demonstrated that the cancer cell-specific azide labeling method using a cancer overexpressing enzyme-cleavable Ac3ManNAz analog and the SPAAC reaction was useful for drug delivery for cancer cell-specific imaging [104]. They synthesized an Ac3ManNAz conjugated to a substrate of the prostate-specific antigen (PSA), a serine protease that was highly secreted by prostate cancer [105]. This Ac3ManNAz analog is metabolized to 1,3,4-tri-O-acetyl-N-azidoacetylmannosamine (Ac3ManNAz) by PSA protease, and the azide groups are introduced into the glycans of the target cells after cellular uptake of Ac3ManNAz. They succeeded in effectively introducing azide groups into PSA-positive prostate cancer cell line PC-3 cells by using this Ac3ManNAz analog, and azide-labeled cells were imaged using DIFO-biotin and avidin-fluorophore. Shim et al. also successfully applied a cancer cell-specific azide labeling method using a cathepsin B-cleavable Ac3ManNAz analog (RR-S-Ac3ManNAz) [84]. First, they conjugated Ac3ManNAz with a cathepsin B-cleavable peptide (Lys-Gly-Arg-Arg, KGRR) using a self-immolative linker p-aminobenzyloxycarbonyl (S). The authors hypothesized that the designed RR-S-Ac3ManNAz would be specifically degraded by cathepsin B in the cytoplasm of the target cells and changed to S-Ac3ManNAz, which would produce Ac3ManNAz after hydrolysis. Cathepsin B is a cysteine protease overexpressed in various human tumors [106]. By the addition of RR-S-Ac3ManNAz, azide groups were specifically introduced into the surface of cathepsin B positive cancer cell lines, including human colon adenocarcinoma cell line HT29 cells, human breast cancer cell line MDA-MB-231 cells, PC-3 cells, and human glioma cell line U-87 MG cells. Moreover, the intravenous injection of RR-S-Ac3ManNAz introduced azide groups into cathepsin B-overexpressing tumor-bearing mice, and the tumor tissue was detected in the fluorescence imaging by intravenously injecting DBCO-Cy5.5. This study showed that a tumor targeting strategy based on metabolic glycoengineering and the SPAAC reaction was successful via intravenous injection. Wang et al. successfully applied a cancer cell-specific azide labeling method using a cancer-over expressing enzyme-cleavable Ac3ManNAz analog and the SPAAC reaction [41]. They synthesized an Ac3ManNAz analog which could be readily degraded by cancer-overexpressing protease, histone deacetylase and cathepsin L (DCL-AAM). Intravenous injection of DCL-AAM to tumor-bearing mice introduced azide groups into the tumor tissue at the same level as with tumor-bearing mice after intravenous injection of Ac4ManNAz at the same dose. On the other hand, the azide expression levels in normal tissues of DCL-AAM-treated mice were lower than those in Ac4ManNAz-treated mice. These results showed that the cancer cell-specific cleavable Ac3ManNAz analog reduced the expressing chemical receptors in normal tissues and improved the targeting efficacy of drugs via click chemistry.
As described above, Ac4ManNAz and its analogs are distributed not only to targeted tumor tissues but also to normal tissues after systemic injection. To achieve tumor-specific labeling with azide groups, researchers have attempted to control the pharmacokinetics of Ac4ManNAz. Here, we describe recent reports regarding the tumor tissue-specific delivery of Ac4ManNAz using nanomaterials (Figure 3B). Lee et al. synthesized Ac4ManNAz-loaded CNPs to improve the accumulation of Ac4ManNAz in tumor tissues [83]. The intravenous injection of Ac4ManNAz-loaded NPs to tumor-bearing mice specifically introduced azide groups into tumor tissues. Furthermore, the expression levels of azide groups in tumor tissues after injection of Ac4ManNAz-loaded CNPs were about 2-fold higher than those of Ac4ManNAz solution-treated groups. This is because most nanoparticles, including Ac4ManNAz-loaded CNPs, accumulate easily in tumor tissues as a result of the EPR effect. This study showed that intravenous injection of Ac4ManNAz-CNPs effectively and specifically generated azide groups in tumor tissues. Xie et al. also demonstrated that azide sugar-loaded folate-modified liposomes were useful for labeling cell-surface glycans of folate receptor-overexpressing cancer cells with azide groups [107]. Folate receptors are overexpressed in various cancer cells and have been widely used as target molecules for drug delivery in cancer therapy [108]. In this study, azide sugar-loaded folate modified-liposomes were effectively taken up by folate receptor-overexpressing HeLa cells via endocytosis, and could deliver sufficient amounts of azide sugars into the cytosol to introduce azide groups onto the surface of HeLa cells. Du et al. also demonstrated that Ac4ManNAz-loaded lipid nanomicelles generated azide groups into tumor tissues [43]. Moreover, Lee et al. developed nano-sized metabolic precursors (Nano-MPs) with a combined structure of generation 4 poly(amidoamine) dendrimer back bone and triacetylated N-azidoacetyl-d-mannosamine. The intravenous injection of Nano-MPs in tumor-bearing mice showed the localization of azide groups in tumor tissues, indicating that Ac4ManNAz was specifically delivered to tumor tissues within which azide groups were successfully generated [37]. As such, nano-sized carriers loaded or conjugated with Ac4ManNAz have been demonstrated to introduce sufficient amounts of azide groups into tumor cells to improve the accumulation of click chemistry chemical-drug conjugates. This method could be useful to specifically generate bioorthogonal chemical receptors in tumor tissue.

3.2. Tumor-Targeting Delivery by Click Chemistry for Cancer Therapy

To carry out cancer-targeting therapy safely and efficiently, cancer-targeting strategies using click chemistry chemical-drug conjugates and bioorthogonal chemical receptors have been reported. Wang et al. developed a tumor-targeting strategy using metabolic glycoengineering and DBCO-drug conjugate to enhance the accumulation of drugs in tumors (Figure 3C) [41]. First, they synthesized the DBCO-valine-cysteine-doxorubicin conjugate (DBCO-VC-Dox), which was degraded by a cancer-overexpressing cathepsin B protease followed by the release of Dox. DCL-AAM was intravenously injected into tumor-bearing mice daily for 3 days for the introduction of azide groups into the tumor tissue. Then, 24 h after the third injection, DBCO-VC-Dox was intravenously injected into DCL-AAM- or PBS-treated mice. The amount of DBCO-VC-Dox in the DCL-AAM-treated group was higher than that of the PBS group in the tumor tissue, while no significant changes in terms of DBCO-VC-Dox accumulation were observed in the normal tissue. Moreover, the combination of DCL-AAM and DBCO-VC-Dox significantly suppressed tumor growth in mice. This study showed that specific-tumor labeling with azide groups enhanced drug accumulation in targeted tumors and the therapeutic effect of anti-cancer agents via the SPAAC reaction.
Researchers have recently reported that modifying nanoparticles with click chemistry chemicals such as BCN and DBCO improves the affinity between nanoparticles and azide-labeled cancer cells. Lee et al. demonstrated that tumor targeting using two types of nanoparticles improved the accumulation of drug-containing nanoparticles in tumors [37]. First, they synthesized CNPs conjugated with BCN and chlorine e6 (BCN-Ce6-CNPs). Ce6, a photosensitizer, is highly activated by irradiation with NIR light and generates singlet oxygen [109,110]. Next, they intravenously injected Ac4ManNAz-loaded CNPs into tumor-bearing mice to introduce azide groups into the tumor tissue, and then irradiated the subcutaneous tumor tissue in mice with an NIR laser after the intravenous injection of BCN-Ce6-CNPs. After laser irradiation, a black scab was formed on the skin at the irradiation site in Ac4ManNAz-CNPs- and BCN-Ce6-CNPs-treated mice, due to the generation of excessive single oxygen in the tumor tissue. The tumor growth of Ac4ManNAz-CNPs- and BCN-Ce6-CNPs-treated mice was significantly inhibited. Layek et al. demonstrated that the MSCs-based targeting strategy improved the tumor targeting efficacy of drug-loaded nanoparticles [33]. They treated MSCs with Ac4ManNAz to label azide groups and found that azide labeling hardly affected the migration or viability of MSCs. Then, azide-labeled MSCs were intraperitoneally injected into metastatic ovarian tumor-bearing mice, followed by the intraperitoneal injection of paclitaxel-loaded DBCO-modified poly (lactide-co-glycolide) (PLGA) nanoparticles (DBCO-NPs). The administration of azide-labeled MSCs and DBCO-NPs showed significant inhibition of tumor growth and improved the overall survival of mice. These studies have shown that a two-step drug delivery strategy based on generating bioorthogonal chemical receptors and the SPAAC reaction could be useful as a cancer-targeting therapy.

3.3. Application of iEDDA Reaction for Tumor-Specific Delivery

Since the iEDDA reaction has the fastest reaction rate of the bioorthogonal reactions [23], its application in cancer-specific therapy and diagnosis is expected to achieve a more effective targeting and therapeutic efficacy than the SPAAC reaction. In this section, we discuss the application of the iEDDA reaction for cancer therapy and diagnosis. Rossin et al. were the first to apply the iEDDA reaction for cancer diagnosis (Figure 3D) [88]. They synthesized the CC49 (anti-tumor associated glycoprotein 72 monoclonal anti body [TAG72])-TCO conjugate (CC49-TCO) and intravenously injected it into colon cancer xenografts-bearing mice in an attempt to label tumor tissues with TCO, followed by the injection of DOTA-Tz labeled with 111In. The TCO-tagged tumors in the mice were then visualized using single-photon emission computed tomography/computed tomography (SPECT/CT) imaging. Zeglis et al. demonstrated that pretargeted PET imaging of the iEDDA reaction could be used to image tumor tissue with high quality [89]. They synthesized the TCO-modified humanized anti-A33 monoclonal antibody (A33-TCO) and intravenously injected it into subcutaneous A33 antigen-expressing xenografts-bearing mice. Then, 64Cu-NOTA-labeled Tz were intravenously injected into TCO-treated mice for PET imaging. 64Cu-NOTA-labeled Tz rapidly distributed and accumulated in the tumor tissue after injection, and a high tumor-to-background contrast was obtained at early time points. Although the mAb-radionuclide conjugate is conventionally used for cancer cell-specific PET and SPECT imaging, its long biological half-life requires high radiation doses [89,97]. These pretargeted methods based on the iEDDA reaction reduce the radiation dose to nontarget tissues. Furthermore, the efficiency of a pretargeting system based on the iEDDA reaction for cancer diagnosis by PET imaging has been demonstrated. Keinänen et al. showed a two-step tumor imaging method based on the iEDDA reaction [90]. They synthesized TCO-modified cetuximab (anti-epidermal growth factor receptor [EGFR] monoclonal antibody) or trastuzumab (anti-human epidermal growth factor receptor 2 [HER-2] monoclonal antibody; TCO-mAb) and then intravenously injected it into EGFR-positive or HER-2-positive tumor-bearing mice to label cancer cells with TCO, followed by the injection of 18F-radiolabeled Tz tracer ([18F] TAF). The iEDDA reaction has been used for the visualization of both antibodies and tumor tissues by PET imaging. Rossin et al. applied the iEDDA reaction for the selective cleavage of tumor-bound ADCs for cancer therapy [101]. First, they synthesized a CC49 conjugate with doxorubicin (DOX) via TCO linker (CC49-TCO-DOX), which was rapidly degraded by the iEDDA reaction. Next, CC49-TCO-DOX was intravenously injected into TAG72-overexpressing colon carcinoma xenografts-bearing mice, followed by the administration of Tz analog. After administration of Tz analog, CC49-TCO-DOX was cleaved and DOX was released into the tumor tissues. These findings demonstrate that the iEDDA reaction has the potential to improve the targeting efficacy of cancer therapy for its treatment and diagnosis.

4. Conclusions

In this review, we discussed the application of copper-free click chemistry for cell engineering in cell transplantation and drug delivery. Although certain factors remain unclear, including the safety of utilizing copper-free click chemistry and metabolic glycoengineering, these reports suggest that copper-free click chemistry is a powerful tool for cell engineering and drug delivery. As such, high biocompatible and fast copper-free click chemistry and its application in the biological and medical fields can be expected to develop further in the near future.

Author Contributions

writing—original draft preparation, Y.T., K.K., and M.N.; researching the literature, Y.T.; writing—review and editing, K.K. and M.N.

Funding

This work was supported in part by a Grant-in-Aid for Young Scientists B (grant number 15K18850) from Japan Society for the Promotion of Science (JSPS).

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

A33-TCOtrans-Cyclooctene-modified humanized anti-a differentiation antigen (A33) monoclonal antibody
Ac4GalNAzN-Azidoacetylgalactosamine tetraacylated
Ac3ManNAz1,3,4-Tri-O-acetyl-N-azidoacetylmannosamine
Ac4ManNAzN-Azidoacetylmannosamine tetraacylated
ADCsMonoclonal antibody-drug conjugates
ADIBOAzadibenzocyclooctyne
ASCsAdipose-derived mesenchymal stem cells
BCNBicyclo[6.1.0]nonyne
BCN-Ce6-CNPsGlycol chitosan nanoparticle conjugated with bicyclo[6.1.0]nonyne and chlorine e6
BCN-CNPsBicyclo[6.1.0]nonyne modified imageable glycol chitosan nanoparticle
CC49Anti-tumor associated glycoprotein 72 monoclonal anti body
CC49-TCO-DOXCC49 conjugate with doxorubicin (DOX) via trans-cyclooctene linker
CEACarcinoembryonic antigen
CTComputed tomography
CuAACCopper (I)-catalyzed azide-alkyne 1,3-dipolar cycloaddition
DBCODibenzyl cyclooctyne-
DBCO-650Dibenzyl cyclooctyne-SETA 650
DBCO-liposomeDibenzyl cyclooctyne conjugated PEGylated liposome
DBCO-NPsDibenzyl cyclooctyne-modified poly (lactide-co-glycolide) nanoparticles
DBCO-VC-DoxDibenzyl cyclooctyne-valine-cysteine-doxorubicin conjugate
DCL-AAMHistone deacetylase/cathepsin l-responsive acetylated azidomannose
DIFODifluorinated cyclooctyne
DOTA1,4,7,10-Tetraazacyclododecane- N,N’,N”,N’”-tetraacetic acid
DOXDoxorubicin
EGFREpidermal growth factor receptor
EPREnhanced permeability and retention
HER-2Human epidermal growth factor receptor 2
iEDDAInverse electron demand Diels-Alder
mAbMonoclonal antibodies
MRMagnetic resonance
MSCsMesenchymal stem cells
Nano-MPsNano-sized metabolic precursors
NIRNear-infrared
NOTA1,4,7-Triazacyclononane-N,N′,N”-triacetic acid
OCTCyclooctyne
PEGPoly(ethylene glycol)
PETPositron emission tomography
PLGAPoly (lactide-co-glycolide)
PSAProstate-specific antigen
RIRadio isotope
RR-S-Ac3ManNAzArg-Arg-p-aminobenzyloxycarbonyl-1,3,4-tri-O-acetyl-N-azidoacetylmannosamine
SPAACStrain-promoted [3 + 2] azide-alkyne cycloaddition
SPECTSingle-photon emission computed tomography
TAG72Tumor associated glycoprotein 72
TCOtrans-Cyclooctene
TCO-anti-VEGFR2trans-Cyclooctene-conjugated anti-vascular endothelial growth factor receptor 2
TzTetrazines

References

  1. Kolb, H.C.; Finn, M.G.; Sharpless, K.B. Click chemistry: Diverse chemical function from a few good reactions. Angew. Chem. Int. Ed. Engl. 2001, 40, 2004–2021. [Google Scholar] [CrossRef]
  2. Yang, M.; Li, J.; Chen, P.R. Transition metal-mediated bioorthogonal protein chemistry in living cells. Chem. Soc. Rev. 2014, 43, 6511–6526. [Google Scholar] [CrossRef] [PubMed]
  3. Li, L.; Zhang, Z. Development and applications of the copper-catalyzed azide-alkyne cycloaddition (CuAAC) as a bioorthogonal reaction. Molecules 2016, 21, 1393. [Google Scholar] [CrossRef]
  4. Agard, N.J.; Prescher, J.A.; Bertozzi, C.R. A strain-promoted [3 + 2] azide-alkyne cycloaddition for covalent modification of biomolecules in living systems. J. Am. Chem. Soc. 2004, 126, 15046–15047. [Google Scholar] [CrossRef] [PubMed]
  5. Sletten, E.M.; Bertozzi, C.R. From mechanism to mouse: A tale of two bioorthogonal reactions. Acc. Chem. Res. 2011, 44, 666–676. [Google Scholar] [CrossRef] [PubMed]
  6. Debets, M.F.; van Berkel, S.S.; Schoffelen, S.; Rutjes, F.P.; van Hest, J.C.; van Delft, F. Aza-dibenzocyclooctynes for fast and efficient enzyme PEGylation via copper-free [3 + 2] cycloaddition. Chem. Commun. 2010, 46, 97–99. [Google Scholar] [CrossRef] [PubMed]
  7. Kuzmin, A.; Poloukhtine, A.; Wolfert, M.A.; Popik, V.V. Surface functionalization using catalyst-free azide-alkyne cycloaddition. Bioconjug. Chem. 2010, 21, 2076–2085. [Google Scholar] [CrossRef] [PubMed]
  8. Jewett, J.C.; Sletten, E.M.; Bertozzi, C.R. Rapid Cu-free click chemistry with readily synthesized biarylazacyclooctynones. J. Am. Chem. Soc. 2010, 132, 3688–3690. [Google Scholar] [CrossRef] [PubMed]
  9. Dommerholt, J.; Schmidt, S.; Temming, R.; Hendriks, L.J.; Rutjes, F.P.; van Hest, J.C.; Lefeber, D.J.; Friedl, P.; van Delft, F.L. Readily accessible bicyclononynes for bioorthogonal labeling and three-dimensional imaging of living cells. Angew. Chem. Int. Ed. Engl. 2010, 49, 9422–9425. [Google Scholar] [CrossRef]
  10. Ning, X.; Guo, J.; Wolfert, M.A.; Boons, G.J. Visualizing metabolically labeled glycoconjugates of living cells by copper-free and fast Huisgen cycloadditions. Angew. Chem. Int. Ed. Engl. 2008, 47, 2253–2255. [Google Scholar] [CrossRef]
  11. Baskin, J.M.; Prescher, J.A.; Laughlin, S.T.; Agard, N.J.; Chang, P.V.; Miller, I.A.; Lo, A.; Codelli, J.A.; Bertozzi, C.R. Copper-free click chemistry for dynamic in vivo imaging. Proc. Natl. Acad. Sci. USA 2007, 104, 16793–16797. [Google Scholar] [CrossRef] [Green Version]
  12. Dadfar, S.M.M.; Sekula-Neuner, S.; Bog, U.; Trouillet, V.; Hirtz, M. Site-specific surface functionalization via microchannel cantilever spotting (µCS): Comparison between azide-alkyne and thiol-alkyne click chemistry reactions. Small 2018, 14, e1800131. [Google Scholar] [CrossRef] [PubMed]
  13. Blackman, M.L.; Royzen, M.; Fox, J.M. Tetrazine ligation: Fast bioconjugation based on inverse-electron-demand Diels-Alder reactivity. J. Am. Chem. Soc. 2008, 130, 13518–13519. [Google Scholar] [CrossRef] [PubMed]
  14. Devaraj, N.K.; Weissleder, R.; Hilderbrand, S.A. Tetrazine-based cycloadditions: Application to pretargeted live cell imaging. Bioconjug. Chem. 2008, 19, 2297–2299. [Google Scholar] [CrossRef] [PubMed]
  15. Patterson, D.M.; Nazarova, L.A.; Xie, B.; Kamber, D.N.; Prescher, J.A. Functionalized cyclopropenes as bioorthogonal chemical reporters. J. Am. Chem. Soc. 2012, 134, 18638–18643. [Google Scholar] [CrossRef] [PubMed]
  16. Yang, J.; Šečkutė, J.; Cole, C.M.; Devaraj, N.K. Live-cell imaging of cyclopropene tags with fluorogenic tetrazine cycloadditions. Angew. Chem. Int. Ed. Engl. 2012, 51, 7476–7479. [Google Scholar] [CrossRef] [PubMed]
  17. Engelsma, S.B.; Willems, L.I.; van Paaschen, C.E.; van Kasteren, S.; van der Marel, G.A.; Overkleeft, H.S.; Filippov, D.V. Acylazetine as a dienophile in bioorthogonal inverse electron-demand Diels-Alder ligation. Org. Lett. 2014, 16, 2744–2747. [Google Scholar] [CrossRef]
  18. Eising, S.; Lelivelt, F.; Bonger, K.M. Vinylboronic acids as fast reacting, synthetically accessible, and stable bioorthogonal reactants in the carboni-lindsey reaction. Angew. Chem. Int. Ed. Engl. 2016, 55, 12243–12247. [Google Scholar] [CrossRef]
  19. Kiick, K.L.; Saxon, E.; Tirrell, D.A.; Bertozzi, C.R. Incorporation of azides into recombinant proteins for chemoselective modification by the Staudinger ligation. Proc. Natl. Acad. Sci. USA 2002, 99, 19–24. [Google Scholar] [CrossRef]
  20. Saxon, E.; Bertozzi, C.R. Cell surface engineering by a modified Staudinger reaction. Science 2000, 287, 2007–2010. [Google Scholar] [CrossRef]
  21. Agard, N.J.; Bertozzi, C.R. Chemical approaches to perturb, profile, and perceive glycans. Acc. Chem. Res. 2009, 42, 788–797. [Google Scholar] [CrossRef] [PubMed]
  22. Ricks, T.J.; Cassilly, C.D.; Carr, A.J.; Alves, D.S.; Alam, S.; Tscherch, K.; Yokley, T.W.; Workman, C.E.; Morrell-Falvey, J.L.; Barrera, F.N.; et al. Labeling of phosphatidylinositol lipid products in cells through metabolic engineering by using a clickable myo-inositol probe. Chembiochem 2018. [Google Scholar] [CrossRef] [PubMed]
  23. Oliveira, B.L.; Guo, Z.; Bernardes, G.J.L. Inverse electron demand Diels-Alder reactions in chemical biology. Chem. Soc. Rev. 2017, 46, 4895–4950. [Google Scholar] [CrossRef] [PubMed]
  24. Späte, A.K.; Bußkamp, H.; Niederwieser, A.; Schart, V.F.; Marx, A.; Wittmann, V. Rapid labeling of metabolically engineered cell-surface glycoconjugates with a carbamate-linked yclopropane reporter. Bioconjug. Chem. 2014, 25, 147–154. [Google Scholar] [CrossRef] [PubMed]
  25. Du, J.; Meledeo, M.A.; Wang, Z.; Khanna, H.S.; Paruchuri, V.D.; Yarema, K.J. Metabolic glycoengineering: sialic acid and beyond. Glycobiology 2009, 19, 1382–1401. [Google Scholar] [CrossRef]
  26. Laughlin, S.T.; Bertozzi, C.R. In vivo imaging of Caenorhabditis elegans glycans. ACS Chem. Biol. 2009, 4, 1068–1072. [Google Scholar] [CrossRef] [PubMed]
  27. Han, S.S.; Lee, D.E.; Shim, H.E.; Lee, S.; Jung, T.; Oh, J.H.; Lee, H.A.; Moon, S.H.; Jeon, J.; Yoon, S.; et al. Physiological effects of Ac4ManNAz and optimization of metabolic labeling for cell tracking. Theranostics 2017, 7, 1164–1176. [Google Scholar] [CrossRef]
  28. Xie, R.; Dong, L.; Huang, R.; Hong, S.; Lei, R.; Chen, X. Targeted imaging and proteomic analysis of tumor-associated glycans in living animals. Angew. Chem. Int. Ed. Engl. 2014, 53, 14082–14086. [Google Scholar] [CrossRef]
  29. Yoon, H.I.; Yhee, J.Y.; Na, J.H.; Lee, S.; Lee, H.; Kang, S.W.; Chang, H.; Ryu, J.H.; Lee, S.; Kwon, I.C.; et al. Bioorthogonal copper free click chemistry for labeling and tracking of chondrocytes in vivo. Bioconjug. Chem. 2016, 27, 927–936. [Google Scholar] [CrossRef]
  30. Yoon, H.Y.; Koo, H.; Kim, K.; Kwon, I.C. Molecular imaging based on metabolic glycoengineering and bioorthogonal click chemistry. Biomaterials 2017, 132, 28–36. [Google Scholar] [CrossRef]
  31. Lee, S.Y.; Lee, S.; Lee, J.; Yhee, J.Y.; Yoon, H.I.; Park, S.J.; Koo, H.; Moon, S.H.; Lee, H.; Cho, Y.W.; et al. Non-invasive stem cell tracking in hindlimb ischemia animal model using bio-orthogonal copper-free click chemistry. Biochem. Biophys. Res. Commun. 2016, 479, 779–786. [Google Scholar] [CrossRef] [PubMed]
  32. Zhang, X.; Li, R.; Chen, Y.; Zhang, S.; Wang, W.; Li, F. Applying DNA rolling circle amplification in fluorescence imaging of cell surface glycans labeled by a metabolic method. Chem. Sci. 2016, 7, 6182–6189. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Layek, B.; Sadhukha, T.; Prabha, S. Glycoengineered mesenchymal stem cells as an enabling platform for two-step targeting of solid tumors. Biomaterials 2016, 88, 97–109. [Google Scholar] [CrossRef] [PubMed]
  34. Koo, H.; Choi, M.; Kim, E.; Hahn, S.K.; Weissleder, R.; Yun, S.H. Bioorthogonal click chemistry-based synthetic cell glue. Small 2015, 11, 6458–6466. [Google Scholar] [CrossRef] [PubMed]
  35. Lee, S.; Yoon, H.I.; Na, J.H.; Jeon, S.; Lim, S.; Koo, H.; Han, S.S.; Kang, S.W.; Park, S.J.; Moon, S.H.; et al. In vivo stem cell tracking with imageable nanoparticles that bind bioorthogonal chemical receptors on the stem cell surface. Biomaterials 2017, 139, 12–29. [Google Scholar] [CrossRef] [PubMed]
  36. Kang, K.; Joo, S.; Choi, J.Y.; Geum, S.; Hong, S.P.; Lee, S.Y.; Kim, Y.H.; Kim, S.M.; Yoon, M.H.; Nam, Y.; et al. Tissue-based metabolic labeling of polysialic acids in living primary hippocampal neurons. Proc. Natl. Acad. Sci. USA 2015, 112, 241–248. [Google Scholar] [CrossRef]
  37. Lee, S.; Jung, S.; Koo, H.; Na, J.H.; Yoon, H.Y.; Shim, M.K.; Park, J.; Kim, J.H.; Lee, S.; Pomper, M.G.; et al. Nano-sized metabolic precursors for heterogeneous tumor-targeting strategy using bioorthogonal click chemistry in vivo. Biomaterials 2017, 148, 1–15. [Google Scholar] [CrossRef]
  38. Kang, S.W.; Lee, S.; Na, J.H.; Yoon, H.I.; Lee, D.E.; Koo, H.; Cho, Y.W.; Kim, S.H.; Jeong, S.Y.; Kwon, I.C.; et al. Cell labeling and tracking method without distorted signals by phagocytosis of macrophages. Theranostics 2014, 4, 420–431. [Google Scholar] [CrossRef]
  39. Prescher, J.A.; Dube, D.H.; Bertozzi, C.R. Chemical remodelling of cell surfaces in living animals. Nature 2004, 430, 873–877. [Google Scholar] [CrossRef]
  40. Koo, H.; Lee, S.; Na, J.H.; Kim, S.H.; Hahn, S.K.; Choi, K.; Kwon, I.C.; Jeong, S.Y.; Kim, K. Bioorthogonal copper-free click chemistry in vivo for tumor-targeted delivery of nanoparticles. Angew. Chem. Int. Ed. Engl. 2012, 51, 11836–11840. [Google Scholar] [CrossRef]
  41. Wang, H.; Wang, R.; Cai, K.; He, H.; Liu, Y.; Yen, J.; Wang, Z.; Xu, M.; Sun, Y.; Zhou, X.; et al. Selective in vivo metabolic cell-labeling-mediated cancer targeting. Nat. Chem. Biol. 2017, 13, 415–424. [Google Scholar] [CrossRef] [Green Version]
  42. Praveschotinunt, P.; Dorval Courchesne, N.M.; den Hartog, I.; Lu, C.; Kim, J.J.; Nguyen, P.Q.; Joshi, N.S. Tracking of engineered bacteria in vivo using nonstandard amino acid incorporation. ACS Synth. Biol. 2018, 7, 1640–1650. [Google Scholar] [CrossRef]
  43. Du, L.; Qin, H.; Ma, T.; Zhang, T.; Xing, D. In vivo imaging-guided photothermal/photoacoustic synergistic therapy with bioorthogonal metabolic glycoengineering-activated tumor targeting nanoparticles. ACS Nano 2017, 11, 8930–8943. [Google Scholar] [CrossRef] [PubMed]
  44. Zhang, G.; Li, J.; Xie, R.; Fan, X.; Liu, Y.; Zheng, S.; Ge, Y.; Chen, P.R. Bioorthogonal chemical activation of kinases in living systems. ACS Cent. Sci. 2016, 325–331. [Google Scholar] [CrossRef] [PubMed]
  45. Zhang, X.; Wang, B.; Zhao, N.; Tian, Z.; Dai, Y.; Nie, Y.; Tian, J.; Wang, Z.; Chen, X. Improved tumor targeting and longer retention time of NIR fluorescent probes using bioorthogonal chemistry. Theranostics 2017, 7, 3794–3802. [Google Scholar] [CrossRef]
  46. Mao, F.; Tu, Q.; Wang, L.; Chu, F.; Li, X.; Li, H.S.; Xu, W. Mesenchymal stem cells and their therapeutic applications in inflammatory bowel disease. Oncotarget 2017, 8, 38008–38021. [Google Scholar] [CrossRef] [PubMed]
  47. Galipeau, J.; Sensébé, L. Mesenchymal stromal cells: Clinical challenges and therapeutic opportunities. Cell Stem Cell 2018, 22, 824–833. [Google Scholar] [CrossRef]
  48. Lee, R.H.; Pulin, A.A.; Seo, M.J.; Kota, D.J.; Ylostalo, J.; Larson, B.L.; Semprun-Prieto, L.; Delafontaine, P.; Prockop, D.J. Intravenous hMSCs improve myocardial infarction in mice because cells embolized in lung are activated to secrete the anti-inflammatory protein TSG-6. Cell Stem Cell 2009, 5, 54–63. [Google Scholar] [CrossRef] [PubMed]
  49. Kerkelä, E.; Hakkarainen, T.; Mäkelä, T.; Raki, M.; Kambur, O.; Kilpinen, L.; Nikkilä, J.; Lehtonen, S.; Ritamo, I.; Pernu, R. Transient proteolytic modification of mesenchymal stromal cells increases lung clearance rate and targeting to injured tissue. Stem Cells Transl. Med. 2013, 2, 510–520. [Google Scholar] [CrossRef] [PubMed]
  50. Kircher, M.F.; Gambhir, S.S.; Grimm, J. Noninvasive cell-tracking methods. Nat. Rev. Clin. Oncol. 2011, 8, 677–688. [Google Scholar] [CrossRef]
  51. Takayama, Y.; Kusamori, K.; Hayashi, M.; Tanabe, N.; Matsuura, S.; Tsujimura, M.; Katsumi, H.; Sakane, T.; Nishikawa, M.; Yamamoto, A. Long-term drug modification to the surface of mesenchymal stem cells by the avidin-biotin complex method. Sci. Rep. 2017, 7, 16953. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  52. Chatterjee, R.; Ghosh, M.; Chowdhury, A.S.; Ray, N. Cell tracking in microscopic video using matching and linking of bipartite graphs. Comput. Methods Programs Biomed. 2013, 112, 422–431. [Google Scholar] [CrossRef] [PubMed]
  53. Yukawa, H.; Watanabe, M.; Kaji, N.; Okamoto, Y.; Tokeshi, M.; Miyamoto, Y.; Noguchi, H.; Baba, Y.; Hayashi, S. Monitoring transplanted adipose tissue-derived stem cells combined with heparin in the liver by fluorescence imaging using quantum dots. Biomaterials 2012, 33, 2177–2186. [Google Scholar] [CrossRef] [PubMed]
  54. Gu, E.; Chen, W.Y.; Gu, J.; Burridge, P.; Wu, J.C. Molecular imaging of stem cells: Tracking survival, biodistribution, tumorigenicity, and immunogenicity. Theranostics 2012, 2, 335–345. [Google Scholar] [CrossRef]
  55. Hakamata, Y.; Murakami, T.; Kobayashi, E. "Firefly rats" as an organ/cellular source for long-term in vivo bioluminescent imaging. Transplantation 2006, 81, 1179–1184. [Google Scholar] [CrossRef]
  56. Li, Z.; Suzuki, Y.; Huang, M.; Cao, F.; Xie, X.; Connolly, A.J.; Yang, P.C.; Wu, J.C. Comparison of reporter gene and iron particle labeling for tracking fate of human embryonic stem cells and differentiated endothelial cells in living subjects. Stem Cells 2008, 26, 864–873. [Google Scholar] [CrossRef]
  57. Patrick, P.S.; Hammersley, J.; Loizou, L.; Kettunen, M.; Rodrigues, T.B.; Hu, D.E.; Tee, S.S.; Hesketh, R.; Lyons, S.K.; Soloviev, D.; et al. Dual-modality gene reporter for in vivo imaging. Proc. Natl. Acad. Sci. USA 2014, 111, 415–420. [Google Scholar] [CrossRef] [PubMed]
  58. Iwano, S.; Sugiyama, M.; Hama, H.; Watakabe, A.; Hasegawa, N.; Kuchimaru, T.; Tanaka, K.Z.; Takahashi, M.; Ishida, Y.; Hata, J.; et al. Single-cell bioluminescence imaging of deep tissue in freely moving animals. Science 2018, 359, 935–939. [Google Scholar] [CrossRef] [PubMed]
  59. Higuchi, Y.; Wu, C.; Chang, K.L.; Irie, K.; Kawakami, S.; Yamashita, F.; Hashida, M. Polyamidoamine dendrimer-conjugated quantum dots for efficient labeling of primary cultured mesenchymal stem cells. Biomaterials 2011, 32, 6676–6682. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  60. Anderson, S.A.; Glod, J.; Arbab, A.S.; Noel, M.; Ashari, P.; Fine, H.A.; Frank, J.A. Noninvasive MR imaging of magnetically labeled stem cells to directly identify neovasculature in a glioma model. Blood 2005, 105, 420–425. [Google Scholar] [CrossRef] [Green Version]
  61. Rodriguez-Porcel, M. In vivo imaging and monitoring of transplanted stem cells: Clinical applications. Curr. Cardiol. Rep. 2010, 12, 51–58. [Google Scholar] [CrossRef]
  62. Kusamori, K.; Takayama, Y.; Nishikawa, M. Stable surface modification of mesenchymal stem cells using the avidin-biotin complex technique. Curr. Protoc. Stem Cell Biol. 2018, 47, e66. [Google Scholar] [CrossRef] [PubMed]
  63. Ogihara, Y.; Yukawa, H.; Kameyama, T.; Nishi, H.; Onoshima, D.; Ishikawa, T.; Torimoto, T.; Baba, Y. Labeling and in vivo visualization of transplanted adipose tissue-derived stem cells with safe cadmium-free aqueous ZnS coating of ZnS-AgInS2 nanoparticles. Sci. Rep. 2017, 7, 40047. [Google Scholar] [CrossRef] [PubMed]
  64. Kim, S.H.; Park, G.; Hyun, H.; Lee, J.H.; Ashitate, Y.; Choi, J.; Hong, G.H.; Owens, E.A.; Henary, M.; Choi, H.S. Near-infrared lipophilic fluorophores for tracking tissue growth. Biomed. Mater. 2013, 8, 014110. [Google Scholar] [CrossRef]
  65. Kidd, S.; Spaeth, E.; Dembinski, J.L.; Dietrich, M.; Watson, K.; Klopp, A.; Battula, V.L.; Weil, M.; Andreeff, M.; Marini, F.C. Direct evidence of mesenchymal stem cell tropism for tumor and wounding microenvironments using in vivo bioluminescent imaging. Stem Cells 2009, 27, 2614–2623. [Google Scholar] [CrossRef] [PubMed]
  66. Nitzsche, F.; Müller, C.; Lukomska, B.; Jolkkonen, J.; Deten, A.; Boltze, J. Concise review: MSC adhesion cascade-insights into homing and transendothelial migration. Stem Cells 2017, 35, 1446–1460. [Google Scholar] [CrossRef] [PubMed]
  67. Studeny, M.; Marini, F.C.; Champlin, R.E.; Zompetta, C.; Fidler, I.J.; Andreeff, M. Bone marrow-derived mesenchymal stem cells as vehicles for interferon-beta delivery into tumors. Cancer Res. 2002, 62, 3603–3608. [Google Scholar]
  68. Studeny, M.; Marini, F.C.; Dembinski, J.L.; Zompetta, C.; Cabreira-Hansen, M.; Bekele, B.N.; Champlin, R.E.; Andreeff, M. Mesenchymal stem cells: Potential precursors for tumor stroma and targeted-delivery vehicles for anticancer agents. J. Natl. Cancer Inst. 2004, 96, 1593–1603. [Google Scholar] [CrossRef]
  69. Sadhukha, T.; O’Brien, T.D.; Prabha, S. Nano-engineered mesenchymal stem cells as targeted therapeutic carriers. J. Control. Release. 2014, 196, 243–251. [Google Scholar] [CrossRef]
  70. Zhao, Y.; Tang, S.; Guo, J.; Alahdal, M.; Cao, S.; Yang, Z.; Zhang, F.; Shen, Y.; Sun, M.; Mo, R.; et al. Targeted delivery of doxorubicin by nano-loaded mesenchymal stem cells for lung melanoma metastases therapy. Sci. Rep. 2017, 7, 44758. [Google Scholar] [CrossRef] [Green Version]
  71. Huang, W.C.; Lu, I.L.; Chiang, W.H.; Lin, Y.W.; Tsai, Y.C.; Chen, H.H.; Chang, C.W.; Chiang, C.S.; Chiu, H.C. Tumortropic adipose-derived stem cells carrying smart nanotherapeutics for targeted delivery and dual-modality therapy of orthotopic glioblastoma. J. Control. Release. 2017, 254, 119–130. [Google Scholar] [CrossRef] [PubMed]
  72. Nold, P.; Hartmann, R.; Feliu, N.; Kantner, K.; Gamal, M.; Pelaz, B.; Hühn, J.; Sun, X.; Jungebluth, P.; Del Pino, P.; et al. Optimizing conditions for labeling of mesenchymal stromal cells (MSCs) with gold nanoparticles: A prerequisite for in vivo tracking of MSCs. J. Nanobiotechnology 2017, 15, 24. [Google Scholar] [CrossRef] [PubMed]
  73. Agnihotri, S.A.; Mallikarjuna, N.N.; Aminabhavi, T.M. Recent advances on chitosan-based micro- and nanoparticles in drug delivery. J. Control. Release. 2004, 100, 5–28. [Google Scholar] [CrossRef] [PubMed]
  74. Chang, P.V.; Prescher, J.A.; Sletten, E.M.; Baskin, J.M.; Miller, I.A.; Agard, N.J.; Lo, A.; Bertozzi, C.R. Copper-free click chemistry in living animals. Proc. Natl. Acad. Sci. USA 2010, 107, 1821–1826. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  75. Jain, V.; Jain, S.; Mahajan, S.C. Nanomedicines based drug delivery systems for anti-cancer targeting and treatment. Curr. Drug Deliv. 2015, 12, 177–191. [Google Scholar] [CrossRef] [PubMed]
  76. England, C.G.; Hernandez, R.; Eddine, S.B.; Cai, W. Molecular imaging of pancreatic cancer with antibodies. Mol. Pharm. 2016, 13, 8–24. [Google Scholar] [CrossRef]
  77. Carter, P. Improving the efficacy of antibody-based cancer therapies. Nat. Rev. Cancer 2001, 1, 118–129. [Google Scholar] [CrossRef]
  78. Guo, J.; Luan, X.; Cong, Z.; Sun, Y.; Wang, L.; McKenna, S.L.; Cahill, M.R.; O’Driscoll, C.M. The potential for clinical translation of antibody-targeted nanoparticles in the treatment of acute myeloid leukaemia. J. Control. Release. 2018, 286, 154–166. [Google Scholar] [CrossRef]
  79. Matsumura, Y.; Maeda, H. A new concept for macromolecular therapeutics in cancer chemotherapy: Mechanism of tumoritropic accumulation of proteins and the antitumor agent smancs. Cancer Res. 1986, 46, 6387–6392. [Google Scholar]
  80. Yasunaga, M.; Manabe, S.; Tsuji, A.; Furuta, M.; Ogata, K.; Koga, Y.; Saga, T.; Matsumura, Y. Development of antibody-drug conjugates using DDS and molecular imaging. Bioengineering 2017, 4, 78. [Google Scholar] [CrossRef]
  81. Loganzo, F.; Sung, M.; Gerber, H.P. Mechanisms of resistance to antibody-drug conjugates. Mol. Cancer Ther. 2016, 15, 2825–2834. [Google Scholar] [CrossRef] [PubMed]
  82. Rong, J.; Han, J.; Dong, L.; Tan, Y.; Yang, H.; Feng, L.; Wang, Q.W.; Meng, R.; Zhao, J.; Wang, S.Q.; et al. Glycan imaging in intact rat hearts and glycoproteomic analysis reveal the upregulation of sialylation during cardiac hypertrophy. J. Am. Chem. Soc. 2014, 136, 17468–17476. [Google Scholar] [CrossRef] [PubMed]
  83. Lee, S.; Koo, H.; Na, J.H.; Han, S.; Min, H.S.; Lee, S.J.; Kim, S.H.; Yun, S.H.; Jeong, S.Y.; Kwon, I.C.; et al. Chemical tumor-targeting of nanoparticles based on metabolic glycoengineering and click chemistry. ACS Nano 2014, 8, 2048–2063. [Google Scholar] [CrossRef] [PubMed]
  84. Shim, M.K.; Yoon, H.Y.; Ryu, J.H.; Koo, H.; Lee, S.; Park, J.H.; Kim, J.H.; Lee, S.; Pomper, M.G.; Kwon, I.C.; et al. Cathepsin B-specific metabolic precursor for in vivo tumor-specific fluorescence imaging. Angew. Chem. Int. Ed. Engl. 2016, 55, 14698–14703. [Google Scholar] [CrossRef] [PubMed]
  85. Wang, H.; Gauthier, M.; Kelly, J.R.; Miller, R.J.; Xu, M.; O’Brien, W.D., Jr.; Cheng, J. Targeted ultrasound-assisted cancer-selective chemical labeling and subsequent cancer imaging using click chemistry. Angew. Chem. Int. Ed. Engl. 2016, 55, 5452–5456. [Google Scholar] [CrossRef]
  86. Lee, S.B.; Kim, H.L.; Jeong, H.J.; Lim, S.T.; Sohn, M.H.; Kim, D.W. Mesoporous silica nanoparticle pretargeting for PET imaging based on a rapid bioorthogonal reaction in a living body. Angew. Chem. Int. Ed. Engl. 2013, 52, 10549–10552. [Google Scholar] [CrossRef]
  87. Neves, A.A.; Stöckmann, H.; Wainman, Y.A.; Kuo, J.C.; Fawcett, S.; Leeper, F.J.; Brindle, K.M. Imaging cell surface glycosylation in vivo using "double click" chemistry. Bioconjug. Chem. 2013, 24, 934–941. [Google Scholar] [CrossRef] [PubMed]
  88. Rossin, R.; Verkerk, P.R.; van den Bosch, S.M.; Vulders, R.C.; Verel, I.; Lub, J.; Robillard, M.S. In vivo chemistry for pretargeted tumor imaging in live mice. Angew. Chem. Int. Ed. Engl. 2010, 49, 3375–3378. [Google Scholar] [CrossRef]
  89. Zeglis, B.M.; Sevak, K.K.; Reiner, T.; Mohindra, P.; Carlin, S.D.; Zanzonico, P.; Weissleder, R.; Lewis, J.S. A pretargeted PET imaging strategy based on bioorthogonal Diels-Alder click chemistry. J. Nucl. Med. 2013, 54, 1389–1396. [Google Scholar] [CrossRef] [PubMed]
  90. Keinänen, O.; Fung, K.; Pourat, J.; Jallinoja, V.; Vivier, D.; Pillarsetty, N.K.; Airaksinen, A.J.; Lewis, J.S.; Zeglis, B.M.; Sarparanta, M. Pretargeting of internalizing trastuzumab and cetuximab with a 18F-tetrazine tracer in xenograft models. EJNMMI Res. 2017, 7, 95. [Google Scholar] [CrossRef]
  91. Devaraj, N.K.; Thurber, G.M.; Keliher, E.J.; Marinelli, B.; Weissleder, R. Reactive polymer enables efficient in vivo bioorthogonal chemistry. Proc. Natl. Acad. Sci. USA 2012, 10, 4762–4767. [Google Scholar] [CrossRef] [PubMed]
  92. Rossin, R.; Läppchen, T.; van den Bosch, S.M.; Laforest, R.; Robillard, M.S. Diels-Alder reaction for tumor pretargeting: In vivo chemistry can boost tumor radiation dose compared with directly labeled antibody. J. Nucl. Med. 2013, 54, 1989–1995. [Google Scholar] [CrossRef] [PubMed]
  93. Rossin, R.; van den Bosch, S.M.; Ten Hoeve, W.; Carvelli, M.; Versteegen, R.M.; Lub, J.; Robillard, M.S. Highly reactive trans-cyclooctene tags with improved stability for Diels-Alder chemistry in living systems. Bioconjug. Chem. 2013, 24, 1210–1217. [Google Scholar] [CrossRef] [PubMed]
  94. Rossin, R.; van Duijnhoven, S.M.; Läppchen, T.; van den Bosch, S.M.; Robillard, M.S. Trans-cyclooctene tag with improved properties for tumor pretargeting with the Diels-Alder reaction. Mol. Pharm. 2014, 11, 3090–3096. [Google Scholar] [CrossRef]
  95. Nichols, B.; Qin, Z.; Yang, J.; Vera, D.R.; Devaraj, N.K. 68Ga chelating bioorthogonal tetrazine polymers for the multistep labeling of cancer biomarkers. Chem. Commun. 2014, 50, 5215–5217. [Google Scholar] [CrossRef] [PubMed]
  96. Zlitni, A.; Janzen, N.; Foster, F.S.; Valliant, J.F. Catching bubbles: Targeting ultrasound microbubbles using bioorthogonal inverse-electron-demand Diels-Alder reactions. Angew. Chem. Int. Ed. Engl. 2014, 53, 6459–6463. [Google Scholar] [CrossRef] [PubMed]
  97. Houghton, J.L.; Zeglis, B.M.; Abdel-Atti, D.; Sawada, R.; Scholz, W.W.; Lewis, J.S. Pretargeted immuno-PET of pancreatic cancer: Overcoming circulating antigen and internalized antibody to reduce radiation doses. J. Nucl. Med. 2016, 57, 453–459. [Google Scholar] [CrossRef]
  98. Houghton, J.L.; Membreno, R.; Abdel-Atti, D.; Cunanan, K.M.; Carlin, S.; Scholz, W.W.; Zanzonico, P.B.; Lewis, J.S.; Zeglis, B.M. Establishment of the in vivo efficacy of pretargeted radioimmunotherapy utilizing inverse electron demand Diels-Alder click chemistry. Mol. Cancer Ther. 2017, 16, 124–133. [Google Scholar] [CrossRef]
  99. Rondon, A.; Ty, N.; Bequignat, J.B.; Quintana, M.; Briat, A.; Witkowski, T.; Bouchon, B.; Boucheix, C.; Miot-Noirault, E.; Pouget, J.P.; et al. Antibody PEGylation in bioorthogonal pretargeting with trans-cyclooctene/tetrazine cycloaddition: In vitro and in vivo evaluation in colorectal cancer models. Sci. Rep. 2017, 7, 14918. [Google Scholar] [CrossRef]
  100. Emmetiere, F.; Irwin, C.; Viola-Villegas, N.T.; Longo, V.; Cheal, S.M.; Zanzonico, P.; Pillarsetty, N.; Weber, W.A.; Lewis, J.S.; Reiner, T. 18F-labeled-bioorthogonal liposomes for in vivo targeting. Bioconjug. Chem. 2013, 24, 1784–1789. [Google Scholar] [CrossRef]
  101. Rossin, R.; van Duijnhoven, S.M.; Ten Hoeve, W.; Janssen, H.M.; Kleijn, L.H.; Hoeben, F.J.; Versteegen, R.M.; Robillard, M.S. Triggered drug release from an antibody-drug conjugate using fast “click-to-release” chemistry in mice. Bioconjug. Chem. 2016, 27, 1697–1706. [Google Scholar] [CrossRef] [PubMed]
  102. Rossin, R.; Versteegen, R.M.; Wu, J.; Khasanov, A.; Wessels, H.J.; Steenbergen, E.J.; Ten Hoeve, W.; Janssen, H.M.; van Onzen, A.H.A.M.; Hudson, P.J.; et al. Chemically triggered drug release from an antibody-drug conjugate leads to potent antitumour activity in mice. Nat. Commun. 2018, 9, 1484. [Google Scholar] [CrossRef] [PubMed]
  103. Marabelle, A.; Kohrt, H.; Caux, C.; Levy, R. Intratumoral immunization: A new paradigm for cancer therapy. Clin. Cancer Res. 2014, 20, 1747–1756. [Google Scholar] [CrossRef] [PubMed]
  104. Chang, P.V.; Dube, D.H.; Sletten, E.M.; Bertozzi, C.R. A strategy for the selective imaging of glycans using caged metabolic precursors. J. Am. Chem. Soc. 2010, 132, 9516–9518. [Google Scholar] [CrossRef] [PubMed]
  105. Denmeade, S.R.; Nagy, A.; Gao, J.; Lilja, H.; Schally, A.V.; Isaacs, J.T. Enzymatic activation of a doxorubicin-peptide prodrug by prostate-specific antigen. Cancer Res. 1998, 58, 2537–2540. [Google Scholar] [PubMed]
  106. Aggarwal, N.; Sloane, B.F. Cathepsin B: Multiple roles in cancer. Proteom. Clin. Appl. 2014, 8, 427–437. [Google Scholar] [CrossRef] [Green Version]
  107. Xie, R.; Hong, S.; Feng, L.; Rong, J.; Chen, X. Cell-selective metabolic glycan labeling based on ligand-targeted liposomes. J. Am. Chem. Soc. 2012, 134, 9914–9917. [Google Scholar] [CrossRef] [PubMed]
  108. Low, P.S.; Henne, W.A.; Doorneweerd, D.D. Discovery and development of folic-acid-based receptor targeting for imaging and therapy of cancer and inflammatory diseases. Acc. Chem. Res. 2008, 41, 120–129. [Google Scholar] [CrossRef]
  109. Paszko, E.; Ehrhardt, C.; Senge, M.O.; Kelleher, D.P.; Reynolds, J.V. Nanodrug applications in photodynamic therapy. Photodiagnosis Photodyn. Ther. 2011, 8, 14–29. [Google Scholar] [CrossRef] [Green Version]
  110. Kamimura, M.; Omoto, A.; Chiu, H.-C.; Soga, K. Enhanced red upconversion emission of NaYF4: Yb3+, Er3+, Mn2+ nanoparticles for near-infrared-induced photodynamic therapy and fluorescence imaging. Chem. Lett. 2017, 46, 1076–1078. [Google Scholar] [CrossRef]
Scheme 1. Reaction schemes of various click chemistry reactions. (A) CuAAC reaction with azide and linear alkyne; (B) SPAAC reaction with azide and cyclooctyne; (C) iEDDA reaction with Tz and TCO.
Scheme 1. Reaction schemes of various click chemistry reactions. (A) CuAAC reaction with azide and linear alkyne; (B) SPAAC reaction with azide and cyclooctyne; (C) iEDDA reaction with Tz and TCO.
Molecules 24 00172 sch001
Figure 1. Schematic illustration of cell labeling via metabolic glycoengineering. Ac4ManNAz is taken up by cells and incorporated into membrane proteins, resulting in the metabolic labeling of membrane proteins with azide.
Figure 1. Schematic illustration of cell labeling via metabolic glycoengineering. Ac4ManNAz is taken up by cells and incorporated into membrane proteins, resulting in the metabolic labeling of membrane proteins with azide.
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Figure 2. Schematic illustration of cell engineering using copper-free click chemistry. (A) Azide-modified cells are labeled with DBCO-imageable probes via SPAAC reaction. The modified cells are detected after transplantation; (B) Azide-modified MSCs are labeled with DBCO-coated nanoparticles via SPAAC reaction. The modified MSCs home to tumor tissues after transplantation; (C) Tz-modified cells and TCO-modified cells form two- or multiple-cell pairs via iEDDA reaction.
Figure 2. Schematic illustration of cell engineering using copper-free click chemistry. (A) Azide-modified cells are labeled with DBCO-imageable probes via SPAAC reaction. The modified cells are detected after transplantation; (B) Azide-modified MSCs are labeled with DBCO-coated nanoparticles via SPAAC reaction. The modified MSCs home to tumor tissues after transplantation; (C) Tz-modified cells and TCO-modified cells form two- or multiple-cell pairs via iEDDA reaction.
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Figure 3. Schematic illustration of the application of copper-free click chemistry for drug delivery system. (A) Cancer overexpressing enzyme-cleavable Ac3ManNAz is metabolized to Ac3ManNAz in tumor cells. Azide group specifically presents on the surface of tumor cells; (B) Ac4ManNAz-loaded nanoparticles specifically accumulate in tumor tissue through the EPR effect and are taken up by tumor cells. Azide group presents on the surface of tumor cells; (C) DBCO-coated nanoparticles accumulate in tumor tissue and is conjugated with azide group in tumor cells via SPAAC reaction; (D) TCO-labeled mAb accumulate in tumor tissue. Tz-RI is conjugated with TCO in tumor cells via iEDDA reaction.
Figure 3. Schematic illustration of the application of copper-free click chemistry for drug delivery system. (A) Cancer overexpressing enzyme-cleavable Ac3ManNAz is metabolized to Ac3ManNAz in tumor cells. Azide group specifically presents on the surface of tumor cells; (B) Ac4ManNAz-loaded nanoparticles specifically accumulate in tumor tissue through the EPR effect and are taken up by tumor cells. Azide group presents on the surface of tumor cells; (C) DBCO-coated nanoparticles accumulate in tumor tissue and is conjugated with azide group in tumor cells via SPAAC reaction; (D) TCO-labeled mAb accumulate in tumor tissue. Tz-RI is conjugated with TCO in tumor cells via iEDDA reaction.
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Table 1. Non-toxic concentration range of the reagents used in click chemistry and glycoengineering in vitro.
Table 1. Non-toxic concentration range of the reagents used in click chemistry and glycoengineering in vitro.
CompoundNon-Toxic ConcentrationIncubation TimeCell TypeReference (Year)
Ac4ManNAz5 μM3 daysB16[32] (2016)
10 μM3 daysA549[27] (2017)
20 μM3 daysMSC (human)[33] (2016)
50 μM3 daysNIH3T3[34] (2015)
50 μM1 dayASC (human)[35] (2017)
3 daysJurkat T lymphocyte[34] (2015)
3 daysChondrocyte (rabbit)[29] (2016)
7 daysMSC (human)[33] (2016)
Ac3ManNAz<5 μM2 daysPrimary hippocampal neurons (rat)[36] (2015)
100 μM2 daysU87[37] (2017)
BCN-CNP-Cy5500 μg/mL1 dayASC (human)[35] (2017)
DBCO-65050 μM1 hChondrocyte (rabbit)[29] (2016)
DBCO-Cy520 μM1 hASC (human)[31] (2016)
100 μM48 hA549[38] (2014)
TCO-DBCO100 μM30 minNIH3T3[34] (2015)
A549
Jurkat T lymphocyte
Tz-DBCO100 μM30 minNIH3T3[34] (2015)
A549
Jurkat T lymphocyte
B16, murine melanoma cell line; A549, human lung adenocarcinoma cell line; NIH3T3, murine embryo fibroblast cell line; ASCs, adipose-derived mesenchymal stem cells; BCN-CNP-Cy5, Cy5-labeled bicyclo[6.1.0]nonyne modified imageable glycol chitosan nanoparticle; Ac3ManNAz, 1,3,4-tri-O-acetyl-N-azidoacetylmannosamine; DBCO-650, dibenzylcyclooctyne-SETA 650; Tz, tetrazines; TCO, trans-cyclooctene.
Table 2. Non-toxic dose range of the reagents used in click chemistry and glycoengineering in vivo.
Table 2. Non-toxic dose range of the reagents used in click chemistry and glycoengineering in vivo.
CompoundNon-Toxic DoseAdministration RouteAnimal TypeReference
Ac4ManNAz300 mg/kg/day daily for 7 daysipMouse[39] (2004)
10 mg/kg/day daily for 3 daysitMouse[40] (2012)
40 mg/kg/day daily for 3 daysivMouse[41] (2017)
10 nmolOralMouse[42] (2018)
Ac4ManNAz-LP40 mg/kg/day of Ac4ManNAz daily for 4 daysivMouse[43] (2017)
BCN-Lipo10 mg/kgivMouse[37] (2017)
DBCO-Cy55 nmolivMouse[38] (2014)
DBCO-Cy5.55 μg (4.25 nmol)ivMouse[33] (2016)
DBCO-lipo10 mg/kgivMouse[40] (2012)
DBCO modified polymeric nanoparticles100 μg/bodyivMouse[33] (2016)
DBCO-ZnPc-LP2.5 mg/kgivMouse[43] (2017)
3,6-dimethyl-1,2,4,5-Tz6 mg/kgivMouse[44] (2016)
Tz-Cy5.58 nmolivMouse[45] (2017)
GEBP11-TCO4 nmolivMouse[45] (2017)
Ac4ManNAz-Lp, Ac4ManNAz-loaded liposome; BCN-Lipo, bicyclo[6.1.0]nonyne-modified liposome; DBCO-lipo, dibenzyl cyclooctyne conjugated PEGylated liposome; DBCO-ZnPc-LP, dibenzyl- cyclooctyne-modified zinc (II)-phthalocyanine-loaded liposome; GEBP11-TCO, a vascular-homing peptide (GEBP11)-trans-cyclooctene.
Table 3. The application of copper-free click chemistry for cell tracking.
Table 3. The application of copper-free click chemistry for cell tracking.
Reaction TypeAzide SugarProbeImagingCell TypeTransplantation RouteType of AnimalsReference
SPAACAc4ManNAzDBCO-Cy5
(administration after cell transplantation)
FLA549
(human)
Injection into liverNude mice[38]
(2014)
SPAACAc4ManNAzDBCO-650FLChondrocyte (rabbit)scNude mice[29]
(2016)
SPAACAc4ManNAzDBCO-Cy5.5FLMSC (human)iv and ipNude mice[33]
(2016)
SPAACAc4ManNAzDBCO-Cy5FLASC (human)Injection into hindlimbNude mice[31]
(2016)
SPAACAc4ManNAzBCN-CNPsFL, MR, CTMSC (human)scNude mice[35]
(2017)
FL, fluorescence; sc, subcutaneous injection; iv, intravenous injection; ip, intraperitoneal injection; MR, magnetic resonance; CT, computed tomography.
Table 4. The application of copper-free click chemistry for tumor targeting delivery and imaging.
Table 4. The application of copper-free click chemistry for tumor targeting delivery and imaging.
Reaction TypeTumor LabelingTargeting AgentTumor ModelPurposeReference
Labeling MethodLabeling AgentAdministration RouteTargeting AgentAdministration Route
SPAACMGEAc4ManNAzitDBCO-liposomeivA549 subcutaneous tumorImaging[40]
(2012)
SPAACMGERR-S-Ac3ManNAzitDBCO-Cy5.5ivHT-29 subcutaneous tumorImaging[84]
(2016)
SPAACMGEDCL-AAMivDBCO-Cy5ivLS174T subcutaneous tumorImaging[41]
(2017)
DBCO-VC-DoxLS174T and MDA-MB-231 subcutaneous tumor and4T1 lung metastatic tumorTherapy
SPAACMGEAc4ManNAz-loaded CNPsivBCN-Ce6-CNPsivA549 subcutaneous tumorImaging and therapy[83]
(2014)
SPAACMGEAc4ManNAz-liposomeivDBCO-ZnPc-liposomeivA549 subcutaneous tumorImaging andtherapy[43]
(2017)
SPAACMGENano-MPsivCy5.5 labeled BCN-liposomeivU87 and MCF7 subcutaneous tumorImaging[37]
(2017)
SPAACMGEAc4ManNAz loaded microbubbleivDBCO-Cy5iv4T1 subcutaneous tumorImaging[85]
(2016)
SPAACAzide-labeling cellsAzide-labeling MSCsitNIR-dye containing DBCO-NPsivA549-Luc subcutaneous tumorImaging[33]
(2016)
ipPaclitaxel-loaded DBCO-NPsipMA148 metastatic ovarian tumorTherapy
SPAACNanoparticlesDBCO-PEG-MSNsiv18F-azideivU87 MG subcutaneous tumorImaging[86]
(2013)
SPAAC, Staudinger ligation and iEDDAMGEAc4GalNAzipTz-DyLightivLL2 subcutaneous tumorImaging[87]
(2013)
TMDIBO-TCO and PHOS-TCOiv
iEDDAAntigen-antibody reactionCD49-TCOiv111 In-TzivColon carcinoma xenograftImaging[88]
(2010)
iEDDAAntigen-antibody reactionA33-TCOiv64Cu-Tz-Bn-NOTAivSW1222 subcutaneous tumorImaging[89]
(2013)
iEDDAAntigen-antibody reactionmAb-TCOiv18F-TzivA431 and BT-474 subcutaneous tumorImaging[90]
(2017)
iEDDAAntigen-antibody reactionA33-TCOivPolymer-modified TzivLS174 subcutaneous tumorImaging[91]
(2012)
iEDDAAntigen-antibody reactionCC49-TCOiv177Lu-TzivLS174T subcutaneous tumorImaging[92]
(2013)
iEDDAAntigen-antibody reactionCC49-TCOiv111In-TzivLS174T subcutaneous tumorImaging[93]
(2013)
iEDDAAntigen-antibody reactionTCO-oxymethylacetamide-tagged CC49iv111In-TzivLS174T subcutaneous tumorImaging[94]
(2014)
iEDDAAntigen-antibody reactionA33-TCOiv68Ga-Tz-DTPA dextranivLS174T subcutaneous tumorImaging[95]
(2014)
iEDDAAntigen-antibody reactionTCO-antiVEGFR2ivMBTZivSKOV-3 subcutaneous tumorImaging[96]
(2014)
iEDDAAntigen-antibody reaction5B1-TCOiv64Cu-NOTA-PEG7-TCOivCapan-2 and BxPC3 subcutaneous tumorImaging[97]
(2016)
iEDDAAntigen-antibody reaction5B1-TCOiv177Lu-DOTA-PEG7-TzivBxPC3 subcutaneous tumorTherapy[98]
(2017)
89Zr-TzImaging
iEDDAAntigen-antibody reactionTs29.2-PEG-TCOivTz-Cy5ivHT29 subcutaneous tumorImaging[99]
(2017)
35A7-PEG-TCOivTz-Cy5ipA431-CEA-Luc peritoneal carcinomatosis tumor
iEDDAMembrane inserted peptidepHLIP-Tzit18F-TCO-liposomeivSKOV-3 subcutaneous tumorImaging[100]
(2013)
iEDDAAptamer (peptide)GEBP11-TCOivCy5.5-TzivSGC-7901 subcutaneous tumorImaging[45]
(2017)
iEDDAAntigen-antibody reactionCC49-TCO-DOXivRadio-labeled Tziv and ipLS174T subcutaneous tumorTherapy[101]
(2016)
iEDDAAntigen-antibody reactionTAG72-TCO-MMAEivTz-DOTAivLS174T and OVCAR 3 subcutaneous tumorTherapy[102]
(2018)
MGE, metabolic glycoengineering; it, intratumoral injection; DBCO-liposome, DBCO conjugated PEGylated liposome (PEG = poly[ethylene glycol]); iv, intravenous injection; LST174T, human colon cancer cell line; DBCO-ZnPc-LP, DBCO-modified zinc (II)-phthalocyanine-loaded liposome; U87, human glioblastoma cell line; MCF7, human breast cancer cell line; ip, intraperitoneal injection; DBCO-PEG-MSNs, DBCO-functionalized PEGylated mesoporous silica nanoparticles; Ac4GalNAz, tetraacetylated N-Azidoacetyl-galactosamine; TMDIBO-TCO, tetramethoxydibenzocyclooctyne-TCO; PHOS-TCO, bifunctional TCO-phosphine; Tz-DyLight, fluorescently labeled Tz; LL2, murine small cell lung cancer cell line; SW1222, human colorectal cancer cell line; A431, human epidermoid carcinoma cell line; BT-474, human breast carcinoma cell line; TCO-anti-VEGFR2, TCO-conjugated anti-vascular endothelial growth factor receptor 2; MBtz, Tz-labeled gas-filled microbubbles; SKOV-3, human ovarian carcinoma cell line; 5B1-TCO, TCO-modified a human anti-CA19.9 monoclonal antibody 5B1; Capan-2, human pancreas adenocarcinoma cell line Cpan-2; BxPC3, human pancreatic cancer cell line; Ts29.2-PEG-TCO, anti-TSPAN8 monoclonal antibody (Ts29.2)-PEG-TCO; 35A7-PEG-TCO, anti-CEA monoclonal antibody (35A7)-PEG-TCO; A431-CEA-Luc, colon carcinoma transfected with constructs encoding both carcinoembryonic antigen and luciferase; pHLIP-Tz, Tz-conjugated pH (low) insertion peptide; GEBP11-TCO, a vascular-homing peptide (GEBP11)-TCO conjugate; SGC-7901, human gastric carcinoma cell line SGC-7901; MMAE, monomethyl auristatin E.

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Takayama, Y.; Kusamori, K.; Nishikawa, M. Click Chemistry as a Tool for Cell Engineering and Drug Delivery. Molecules 2019, 24, 172. https://doi.org/10.3390/molecules24010172

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Takayama Y, Kusamori K, Nishikawa M. Click Chemistry as a Tool for Cell Engineering and Drug Delivery. Molecules. 2019; 24(1):172. https://doi.org/10.3390/molecules24010172

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Takayama, Yukiya, Kosuke Kusamori, and Makiya Nishikawa. 2019. "Click Chemistry as a Tool for Cell Engineering and Drug Delivery" Molecules 24, no. 1: 172. https://doi.org/10.3390/molecules24010172

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