Targeting glucose uptake with siRNA-based nanomedicine for cancer therapy

Biomaterials 51 (2015) 1e11

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Targeting glucose uptake with siRNA-based nanomedicine for cancer therapy Cong-Fei Xu a, Yang Liu b, Song Shen b, Yan-Hua Zhu b, Jun Wang a, b, * a

Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei 230027, Anhui, China The CAS Key Laboratory of Innate Immunity and Chronic Disease, School of Life Sciences and Medical Center, University of Science and Technology of China, Hefei 230027, Anhui, China

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a r t i c l e i n f o

a b s t r a c t

Article history: Received 10 November 2014 Accepted 25 January 2015 Available online

Targeting cancer metabolism is emerging as a successful strategy for cancer therapy. However, most of the marketed anti-metabolism drugs in cancer therapy do not distinguish normal cells from cancer cells, leading to severe side effects. In this study, we report an effective strategy for cancer therapy through targeting glucose transporter 3 (GLUT3) with siRNA-based nanomedicine to simultaneously inhibit the self-renewal of glioma stem cells and bulk glioma cells in a glucose restricted tumor micro-environment. We have demonstrated that cationic lipid-assisted poly(ethylene glycol)-b-poly(d,L-lactide) (PEG-PLA) nanoparticles can efficiently deliver siRNA into U87MG and U251 glioma stem cells and bulk glioma cells. Nanoparticles carrying specific siRNA targeting GLUT3 (NPsiGLUT3) were able to significantly reduce the expression of GLUT3 in glioma stem cells and bulk glioma cells, while GLUT3 knockdown results in obvious cell metabolism and proliferation inhibition, and further glioma stem cells percentage downregulation. Moreover, systemic delivery of NPsiGLUT3, via intravenous injection, significantly inhibited tumor growth in a U87MG xenograft model, due to the reduced expression of GLUT3 and downregulated stemness of glioma cells. © 2015 Elsevier Ltd. All rights reserved.

Keywords: Nanomedicine Cancer therapy Glucose transporter 3 Glioma stem cells siRNA delivery

1. Introduction Significant metabolic disorders are the main features of rapid proliferating cancer cells [1e5]. A few metabolism-associated molecules, including GLUT1, HKII, phosphoglycerate dehydrogenase (PHGDH), and LDH-A, which are overexpressed in certain cancer types, have been proven to be potential therapeutic targets [6e9]. Nevertheless, the development of successful cancer therapies still remains a challenge due to the same metabolic requirements of cancer cells and normal proliferating cells [10]. According to the classic theory of cancer metabolism which is known as “the Warburg effect”, cancer cells prefer glucoseintensive glycolysis rather than oxygen-dependent mitochondrial oxidative phosphorylation to produce enough ATP and biological macromolecular precursors (proteins, nucleic acids, lipids) [11,12].

* Corresponding author. School of Life Sciences and Medical Center, University of Science and Technology of China, Hefei 230027, Anhui, China. Tel.: þ86 551 63600335; fax: þ86 551 63600402. E-mail address: [email protected] (J. Wang). http://dx.doi.org/10.1016/j.biomaterials.2015.01.068 0142-9612/© 2015 Elsevier Ltd. All rights reserved.

However, the ATP production efficiency of glycolysis is much lower than oxidative phosphorylation; cancer cells require much higher glucose flux than normal cells to meet their metabolic requirements [13,14]. It has been proven that glucose uptake in tumors is much higher than adjacent normal tissue [13,14]. However, glucose requires specific transport proteins to assist it into the cytosol [15]. The transportation of glucose into cancer cells is mainly mediated by facilitative glucose transporters (GLUT) [15,16]. GLUT1 is the most studied glucose transporter and thought to primarily be a driver of cancer glucose uptake [12,17]. However, GLUT1 is extensively expressed in many normal tissues, especially erythrocytes; therefore, targeting GLUT1 would cause serious side effects [18e20]. Another tumor highly expressed glucose transporter, GLUT3, is usually ignored. It has a five-fold higher affinity for glucose than the ubiquitous GLUT1 [21,22]. As the concentration of glucose is generally lower in tumors, GLUT3 is expected to be more important for tumor progression. Besides, GLUT3 expression is restricted to neurons, sperm and embryo cells, which are both in a high glucose demand and a glucose-poor micro-environment; therefore, targeting GLUT3 is expected to cause much fewer side effects [12,22].

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According to the high-profile cancer stem cell hypothesis, drug resistance and the relapse of cancer is caused by cancer stem cells [23,24]. A therapy which can kill cancer stem cells is thought to be an effective way of curing cancer permanently. Recently, it was reported that GLUT3 is highly expressed in brain tumor cells, especially in brain tumor stem cells [12,25]. Knockdown of GLUT3 through shRNA resulted in a six-fold or greater decrease in the frequency of brain tumor stem cells in vitro and reduced glioblastoma propagation in vivo [12]. In addition, GLUT3 expression correlated with poor survival in a broad range of tumor types, including those of the breast [26], colon [27] and lung [28]. It is suggested that targeting GLUT3 is likely to be an effective anticancer therapy, which can inhibit the proliferation of cancer cells and cancer stem cells at the same time. However, because GLUT3 has long been ignored for cancer treatment, no GLUT3-specific inhibitors have been developed. Therefore, a bypass strategy with siRNA-based nanomedicine is necessary for GLUT3 inhibition for cancer treatment. Small interfering RNA (siRNA) has emerged as a promising strategy for the treatment of multiple diseases, such as neurodegenerative disorders, eye diseases, infectious diseases, cancer and so on [29e34]. To overcome the obstacles of siRNA delivery in vivo, a lot of siRNA delivery systems have been developed, such as a virus-associated system [35,36], lipid-based particles [37e39], polymer-based systems [40,41], hybrid nanoparticles [42], singlechain fragment variable antibody fusion protein systems [43] and so on. We have previously reported micelleplex and anti-Her2 single-chain antibody-mediated siRNA delivery for cancer therapy [44,45]. In this study, we report a systemically injectable siRNAbased nanomedicine which targets GLUT3 and down-regulates glucose uptake of glioma stem cells and bulk glioma cells for cancer therapy. As shown in Scheme 1, by using a cationic lipid-assisted PEG-PLA nanoparticle system previously developed by us [46e48], we studied GLUT3 expression knockdown by GLUT3 siRNA (siGLUT3) in U87MG and U251 glioma cells and the inhibitory

effects of NPsiGLUT3 (nanoparticle carrying siGLUT3) administration on tumor growth using a U87MG xenograft murine model. 2. Materials and methods 2.1. Materials The diblock copolymer of poly(ethylene glycol) (MW 5000) with poly(d,L-lactide) (MW 11,000) (mPEG5KePLA11K) and cationic lipid BHEM-Chol (N,N-bis(2hydroxyethyl)-N-methyl-N-(2-cholesteryloxycarbonyl aminoethyl) ammonium bromide) were synthesized as previously reported [46]. Lipofectamine RNAi MAX reagent (Invitrogen, Carlsbad, USA) was used as suggested by the manufacturer. FAM-labeled siRNA (FAM-siRNA), negative control siRNA with a scrambled sequence (siNC, antisense strand, 50 -ACGUGACACGUUCGGAGAAdTdT-30 ), siRNA targeting GLUT3 mRNA (siGLUT3, antisense strand, 50 -UAGCCAAAUUGGAAAGAGCTT-30 ) were synthesized by GenePharma Co. Ltd. (Suzhou, China). 2.2. Preparation and characterization of nanoparticles with siRNA encapsulation (NPsiRNA) NPsiRNA was prepared according to a previously reported method [46]. As a typical example, an aqueous solution of siRNA (0.2 mg) in 25 mL of RNase-free water was emulsified by sonication at 80 W for 1 min over an ice bath in 0.5 mL of chloroform containing 1.0 mg of BHEM-Chol and 25 mg of PEG5K-PLA11K. Then, 5 mL of water was added to the primary emulsion before being further emulsified by sonication at 80 W for 2 min over an ice bath to form a water-in-oil-in-water emulsion; the organic solvent was removed using a rotary evaporator. Zeta potentials and particle size of NPsiRNA were characterized at 25  C by a Malvern Zetasizer Nano ZS90, as previously reported [49]. Morphology was examined by JEOL-2010 transmission electron microscopy (TEM) at an accelerating voltage of 200 kV. The encapsulation efficiency of siRNA into the nanoparticles was determined by highperformance liquid chromatography (HPLC) analyses, according to the literature [46]. 2.3. Cell culture The glioma cell lines U87MG and U251 were from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China). Cells were maintained in L-glutamine containing DMEM (Gibco, Grand Island, NY) supplemented with 10% fetal bovine serum (ExCell Bio, Shanghai, China) and 1% penicillin/streptomycin (SigmaeAldrich, St. Louis, MO) at 37  C in a 5% CO2 atmosphere. U87MG and U251 used in the following experiments were maintained in low glucose DMEM (0.45 g/L) supplemented with 10% FBS and other supplements mentioned above.

Scheme 1. Schematic illustration of the preparation of NPsiGLUT3 and the mechanism of NPsiGLUT3 mediated tumor growth inhibition in U87MG xenograft model. After intravenous injection, NPsiGLUT3 mediated GLUT3 knockdown caused glucose deprivation in glioma stem cells and bulk glioma cells, which inhibited the glucose metabolism and the growth of tumor.

C.-F. Xu et al. / Biomaterials 51 (2015) 1e11 2.4. Cellular uptake of nanoparticles The cellular uptake of nanoparticles was measured by a Fluorescence Activated Cell Sorter (FACS), Confocal Laser Scanning Microscopy (CLSM) and High Performance Liquid Chromatography (HPLC). In each experiment, the concentration of siRNA with nanoparticles was 150 nM or 300 nM. Lipofectamine RNAi MAX carrying 50 nM FAM-siRNA and free FAM-siRNA (300 nM) were used as controls. For flow cytometric analysis, U87MG and U251 (5  104 cells/well) were seeded in 24-well tissue culture plates (Corning Inc., Corning, NY, USA) 24 h before the experiments. The original medium was replaced with NPFAM-siRNA-containing fresh medium. After 4 h incubation, cells were washed three times with cold phosphatebuffered saline (PBS, 0.01 M, pH 7.4), and then collected by trypsinization. Cells were incubated with AC133-PE antibody (Miltenyi Biotec, Bergisch Gladbach, Germany) for 30 min at 4  C and resuspended in 300 mL cold PBS for analysis with a FACSCalibur flow cytometer (BD Bioscience, Bedford, MA). For microscopic observation, U87MG and U251 cells (5  104 cells) were seeded on coverslips in 24-well plates. After 24 h incubation, the medium was replaced with NPFAM-siRNA-containing fresh medium. After 2 h incubation, cells were washed twice with cold PBS and fixed with 4% formaldehyde (SigmaeAldrich, St. Louis, USA) for 15 min at 4  C. Cells were incubated with AC133-PE antibody for 30 min at 4  C and incubated with 1 mg/mL DAPI (Beyotime, Haimen, China) for 5 min in PBS. Coverslips were mounted on glass microscope slides with a drop of anti-fade mounting medium (SigmaeAldrich, St. Louis, MO) to reduce fluorescence photo-bleaching. The cellular uptake of nanoparticles was visualized by a CLSM (LSM 710, Carl Zeiss Inc., Jena, Germany). For quantitative determination, U87MG and U251 cells (2  106 cells) were seeded in 100 mm tissue culture dish, and 24 h later the medium was replaced with NPFAM-siRNA-containing fresh medium. After 4 h incubation, cells were collected and incubated with AC133-PE antibody for 30 min at 4  C, CD133þ and CD133- cells were sorted by BD FACSaria flow cytometer. The FAM-siRNA endocytosis amount of CD133þ and CD133- cells were determined by HPLC according to the literature [46], using a Waters HPLC system consisting of a Waters 1525 binary pump, a Waters 2475 fluorescence detector, a 1500 column heater and a Symmetry C18 column. 2.5. In vitro gene silencing with GLUT3 siRNA-encapsulated nanoparticles (NPsiGLUT3) U87MG and U251 cells (2  105 cells) were seeded in 6-well plates and 24 h later the cells were transfected with NPsiGLUT3 at two siRNA doses of 150 nM and 300 nM. Lipofectamine RNAi MAX carrying GLUT3 siRNA (Lipo/siGLUT3) at the siRNA dose of 50 nM was used as a positive control, while nanoparticles encapsulating negative control siRNA (NPsiNC) and free GLUT3 siRNA were used as negative controls at the siRNA dose of 300 nM. After 6 h transfection, the medium was replaced with fresh medium. The cells were further incubated for 48 h (for mRNA isolation) or 72 h (for protein extraction) at 37  C, and the cellular levels of GLUT3 mRNA and protein were assessed using quantitative real-time PCR (qRT-PCR) and Western blotting, respectively. Primers used in qRT-PCR for GLUT3 and GAPDH were: GLUT3 forward 50 GCCTTTGGCACTCTCAACCAG-30 , GLUT3 reverse 50 - AGTAGCAGCGGCCATAGCTC-30 , and GAPDH forward 50 -TTCACCACCATGGAGAAGGC-30 , GAPDH reverse 50 -GGCATG GACTGTGGTCATGA-30 . Monoclonal antibody against GLUT3 (Abcam, Shanghai, China) was used at a dilution of 1:5000 in western blotting and goat anti-rabbit immunoglobulin (IgG, 1:10,000, Santa Cruz Biotech., USA) was used as the secondary antibody. The result was visualized using the ImageQuant LAS 4000 mini system (GE Healthcare, London, U.K.) and expression levels of GLUT3 protein were normalized against b-actin protein expression levels.

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2.7. In vitro cell proliferation inhibition and apoptosis analysis post GLUT3 siRNA transfection U87MG and U251 cells were seeded in 96-well plates at 5000 cells per well and 24 h later the cells were transfected with different formulations. After 96 h treatment, the cell proliferation was determined by an MTT assay according to literature, which was normalized to that of cells cultured in the culture medium with PBS treatment. For apoptosis analysis, U87MG and U251 cells were seeded in 6-well plates at 1.0  105 cells per well and transfected with different formulations 24 h later. After 96 h treatment, cells were washed twice with PBS, collected by trypsinization, and resuspended in 500 mL of annexineV binding buffer. Subsequently, 2 mL of fluorescein isothiocyanate (FITC)-conjugated annexin-V and 5 mL of propidium iodide (PI) were added. After 10 min incubation at room temperature in the dark, the samples were immediately analyzed via FACS. 2.8. Determination of glioma stem cells population after NPsiGLUT3 treatment U87MG and U251 cells were seeded in 6-well plates at 1.0  105 cells per well and transfected with different formulations 24 h later. After 96 h, the cells were collected, incubated with AC133-PE antibody for 30 min at 4  C, washed twice with cold PBS and analyzed by FACS. 2.9. Human glioma xenograft tumor model and treatment All animals received care in compliance with the guidelines outlined in the Guide for the Care and Use of Laboratory Animals. All procedures were approved by the University of Science and Technology of China Animal Care and Use Committee. NOD-SCID mice from Beijing HFK Bioscience Co., LTD (Beijing, China) received subcutaneous injection of U87MG cells (2  105) diluted in 100 mL matrigel (BD Biosciences, Franklin Lakes, NJ) in the right flank. The mice were randomly divided into 5 groups when the tumor volume was approximately 70 mm3. Animals were treated with PBS, free siGLUT3, NPsiNC, or NPsiGLUT3 by intravenous injection every other day at a siRNA dose of 1 mg/kg or 2 mg/kg. Tumor growth was monitored by measuring the perpendicular diameter by caliper every other day. The estimated volume was calculated based on the following equation: tumor volume ¼ 1/ 2  length  width2. 2.10. Detection of GLUT3 and stemness-associated genes expression in tumor after treatment Tumor tissues were collected 24 h after the last injection. For mRNA analysis, tumor tissues were lysed in RNAiso Plus (Takara, Otsu, Japan), and total RNA was extracted following the manufacturer's protocol. The cellular levels of mRNA of GLUT3, Oct4, Nanog, Sox2 and CD133 were assessed using qRT-PCR. Primers used in qRT-PCR were: Oct4 forward 50 -TGGCGTGGAGACTTTGCA-30 and Oct4 reverse 50 GAGGTTCCCTCTGAGTTGCTTTC-30 , Nanog forward 50 -GGTTGAAGACTAGCAATGGTCTGA-30 and Nanog reverse 50 -TGCAATGGATGCTGGGATACTC-30 , Sox2 forward 50 -TTGCTGCCTCTTTAAGACTAGGA-30 and Sox2 reverse 50 CTGGGGCTCAAACTTCTCTC-30 , CD133 forward 50 -GGACCCATTGGCATTCTC-30 and CD133 reverse 50 -CAGGACACAGCATAGAATAATC-3’. For GLUT3 protein analysis, tumor tissues were lysed in 100 mL of tissue lysis buffer (50 mM HEPES, pH 7.5, 150 mM NaCl, 1 mM EGTA, 2.5 mM EDTA, 10% glycerol, 0.1% Tween 20, 1 mM dithiothreitol, 10 mM glycerol 2-phosphate, 1 mM NaF, and 0.1 mM Na3VO4) freshly supplemented with Roche's Complete Protease Inhibitor Cocktail Tablets. The lysates were incubated on ice for a total of 30 min, vortexed every 5 min and centrifuged for 15 min at 14,000 g. Proteins were then detected by western blotting as described above. 2.11. Analysis of glioma stem cells population in tumor

2.6. In vitro glucose uptake, lactate and ROS production U87MG and U251 cells (2  105 cells) were seeded in 6-well plates and 24 h later the cells were transfected with different formulations. The medium was replaced with fresh medium after 6 h transfection and the cells were further incubated at 37  C for 48 h for glucose uptake assay or 72 h for lactate and ROS production assay. For glucose uptake assay, U87MG and U251 cells were incubated for 30 min with 10 mM 2-[N-(7-nitrobenz-2-oxa-1,3-diaxol-4-yl)amino]-2-deoxyglucose (2-NBDG, Invitrogen, Carlsbad, CA) after 2 h of glucose starvation. Cells were collected by trypsinization and directly analyzed via FACS. In another experiment, U87MG and U251 cells were incubated in 0.45 g/L glucose for 30 min after 2 h of glucose starvation, and then collected via trypsinization. Cells were lysed in RIPA buffer (SigmaeAldrich, St. Louis, MO) and a glucose colorimetric detection was performed with Glucose Assay Kit (SigmaeAldrich, St. Louis, MO) according to the manufacturer's protocol. For lactate production assay, U87MG and U251 cell culture supernatants were collected and clarified by centrifugation for 10 min at 13,000 g at 4  C. Cells were collected and lysed in RIPA buffer and the protein was quantified as a loading control via BCA assay. The lactation colorimetric detection was performed with Lactate Assay Kit (SigmaeAldrich, St. Louis, MO) according to the manufacturer's protocol. For ROS production assay, U87MG and U251 cells were collected by trypsinization and washed twice with PBS. Then cells were incubated with 10 mM H2DCF-DA (Invitrogen, Carlsbad, CA) for 30 min at 37  C before analysis via FACS.

Tumor tissues were collected 24 h after the last injection and immediately transferred to a dish and cut into small pieces. The fragments were suspended with 20 mL of DMEM medium and collected by centrifugation for 5 min at 600 rpm. The pellets were resuspended in 10 mL of tumor cell digestion solution (1 mg/mL collagenase Type I in PBS, Invitrogen, Carlsbad, CA) and incubated at 37  C for 3 h with persistent agitation. Tumor cells were collected by centrifuging at 1200 rpm for 5 min at room temperature and washed twice with PBS containing 1% BSA. The tumor cells were filtered twice by a 200-mesh sieve, stained with AC133-PE antibody as described above, and analyzed via FACS. For CD133 and DAPI fluorescent staining, paraffin-embedded sections of tumors from xenografts were deparaffinized in xylene and rehydrated in graded alcohol. Followed antigen enhancement by incubating the sections in citrate buffer pH 6.0, CD133 antibody (Millipore, Bedford, MA) was used at a dilution of 1:100 and incubated for 1 h and PE-labeled secondary antibody (Santa Cruz Biotech., CA) was used at the dilution 1:200 and incubated for 45 min. Nuclei were counterstained with 1 mg/mL DAPI (Beyotime, Haimen, China) for 5 min in PBS and cover-slipped. Sections were examined with Carl Zeiss LSM 710 CLSM. 2.12. Statistical analysis The statistical significance was assessed using Student's t-test (two-tailed); p < 0.05 was considered statistically significant in all analyses (95% confidence level).

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3. Results and discussion 3.1. Preparation and characterization of nanoparticles Cationic lipid-assisted nanoparticles were prepared using the double emulsion method. Scheme 1 illustrates the structure of the biodegradable polymer and the formation of nanoparticles. As previously reported, siRNA could be immobilized in the formed nanoparticles at high encapsulation efficiency (approximately 90%) by incorporating an amphiphilic cationic lipid BHEM-Chol in a solution of mPEG5K-PLA11K matrix [46]. As shown in Fig. 1A, the diameter of siRNA-encapsulating nanoparticles (NPsiRNA) measured by dynamic light scattering (DLS) was 124.7 ± 3.6 nm. Furthermore, the diameter of NPsiRNA was confirmed by transmission electron microscopy (Fig. 1B), which was in accord with the DLS measurements. The Zeta potential of NPsiRNA was 13.1 ± 0.4 mV (Fig. 1C) which was lower than that of blank nanoparticles (NP). The stability of NPsiRNA was studied for 36 h (Fig. 1D) in the same method of our previous work [46], showing NPsiRNA was quite stable in serum due to its PEG blocks. 3.2. Intracellular uptake of NPFAM-siRNA by glioma stem cells and bulk glioma cells Due to the great role of cancer stem cells in sustaining cancer growth and relapse [50e52], the delivery of anti-cancer drugs into cancer cells and cancer stem cells has become increasingly important for cancer treatment. As one of the most lethal and prevalent primary malignant tumors, gliomas also contain a portion of treatment-resistant glioma stem cells. Recent experimental data revealed that solid tumors, especially gliomas, contain a higher portion of cancer stem cells, and the ratio of cancer stem cells increases as a result of low-glucose tumor micro-environment [12]. We simulated the low-glucose tumor micro-environment in vitro according to the literature reported [53e55]; The glucose

concentrations in interstitial fluid from solid tumors are 0.22e0.87 g/L, which indicates that the ‘restricted’ glucose concentrations used for the studies presented here are representative of physiological conditions. U87MG and U251 glioma cells were cultured in medium containing high glucose (4.5 g/L) or low glucose (0.45 g/L) for 7 days. As glioma stem cells express stem cell markers, we analyzed the expression of a subset of stem cell makers in low glucose cultured U87MG and U251 cells. The qRT-PCR analysis demonstrated several to fifteen-fold elevation of stemness-associated genes, including OCT4, NANOG, SOX2 and CD133 (Fig. S1A and S1B). Flow cytometry analysis also indicated a great increase in the percentage of glioma stem cells (CD133þ) after expose to low glucose. As shown in Fig. S1C and S1D, CD133þ cells in U87MG increased from 0.605% to 18.7% and 0.466%e11.7% for U251. Furthermore, the results of in vitro limiting dilution assays (LDA) also revealed that the frequency of glioma stem cells capable of forming neurospheres increased after culture under glucose restriction (Fig. S1E and S1F). The above results indicated that glioma stem cells were enriched under a glucose restriction environment. There are two mechanisms of glioma stem cells increase with glucose restriction: the first is where glioma stem cells preferentially survive low-glucose conditions and the second is where bulk glioma cells adapt to low glucose by acquiring a more stem cell-like phenotype [12]. To evaluate whether the prepared NPsiRNA could efficiently deliver siRNA into U87MG and U251 glioma stem cells and bulk glioma cells, we used fluorescent FAM-labeled siRNA to examine its internalization. After 4 h of incubation of NPFAM-siRNA with low glucose cultured U87MG and U251 cells, the internalization of NPFAMesiRNA by U87MG and U251 glioma stem cells and bulk glioma cells was examined by flow cytometry. Glioma stem cells were marked with PE-CD133. As shown in Fig. 2A and Fig. 2B, both U87MG and U251 cells incubated with NPFAM-siRNA showed much stronger green fluorescence than NP-treated cells. Moreover, both glioma stem cells (CD133þ) and bulk glioma cells (CD133) of

Fig. 1. Preparation and characterization of nanoparticles. (A) Size distribution. (B) TEM image, (C) Zeta potentials, (D) Serum stability assay.

C.-F. Xu et al. / Biomaterials 51 (2015) 1e11

U87MG and U251 showed similar intracellular fluorescence intensity, implying that glioma stem cells and bulk glioma cells internalized the nanoparticles at a similar level. To further analyze the subcellular localization of NPFAM-siRNA, we observed NPFAM-siRNA incubated U87MG and U251 cells with confocal laser scanning microscopy. Cell nuclei were stained with DAPI and glioma stem cell membranes were stained with PE-CD133. As shown in Fig. 2C and D, NPFAM-siRNA signal was observed in the cytoplasm of U87MG and U251 glioma stem cells and bulk glioma cells, which was consistent with the results of flow cytometric analysis. To more precisely measure the endocytosis of NPFAM-siRNA, we sorted the glioma stem cells (CD133þ) and bulk glioma cells (CD133) with a flow cytometer and analyzed them with HPLC after incubation with NPFAM-siRNA. As Fig. 2E and F indicate, both CD133þ

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and CD133 U87MG and U251 cells took in approximately 2e4 pmol FAM-siRNA per 106 cells. In addition, the endocytosis amount increased according to the dose of NPFAM-siRNA. 3.3. NPsiGLUT3 mediated gene expression knockdown in vitro As one of the most important energy sources of tumors, sufficient glucose supply is crucial for tumor growth. Cellular uptake of glucose occurs through facilitated diffusion using a family of solute carriers, the GLUT family of proteins. There are two main glucose transporters on the glioma cell membrane (GLUT1, GLUT3). We studied the expression of GLUT1 and GLUT3 in U87MG and U251 cells after low glucose treatment; qRT-PCR analysis indicated that GLUT3 expression was significantly higher while GLUT1 expression

Fig. 2. Intracellular uptake of NPFAM-siRNA by glioma stem cells and bulk glioma cells. (A, B) Flow cytometric analysis of NPFAM-siRNA uptake by U87MG and U251. Glioma stem cells were PE-CD133 (red) positively stained and bulk glioma cells were negative. (C, D) CLSM images of U87MG and U251 with NPFAM-siRNA incubation, glioma stem cells (PE-CD133 positive) are marked with white arrows. (E, F) Quantitative analysis of NPFAM-siRNA uptake by U87MG and U251. RNA were labeled with green fluorescence, DAPI (blue) was used to stain the cell nucleus.(For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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showed no large changes (Fig. S1G and S1H). Because GLUT3 has one-fifth Km and five-fold Kcat of GLUT1 [21], it has a combination of higher affinity and capacity to glucose, which gave low glucosetreated U87MG and U251 cells a survival advantage under a glucose-restricted environment. As GLUT3 is crucial for glioma cells survival under glucose restriction, which was proven in our experiment and a previous report [12], GLUT3 function inhibition is expected to be a quite effective strategy for eliminating the survival advantage of U87MG and U251 glioma stem cells and bulk glioma cells under a glucose restricted environment. We then investigated whether NPsiGLUT3 could down-regulate GLUT3 gene expression in U87MG cells and U251 cells. Different formulations were incubated with the cells; then, GLUT3 expression was determined at both mRNA and protein levels. As shown in Fig. 3A and Fig. 3B, the control NPsiNC carrying scrambled siRNA and free siGLUT3 did not down-regulate GLUT3 expression in either cell. As expected, treatment of the cells with NPsiGLUT3 significantly down-regulated GLUT3 expression. In addition, the gene silencing efficiency of NPsiGLUT3 was dose-dependent. Treatment with NPsiGLUT3 at the siGLUT3 dose of 300 nM led to over 50% knockdown of GLUT3 expression in U87MG and U251 cells. On the protein level, GLUT3 expression was also down-regulated by NPsiGLUT3 in a dosedependent manner in both U87MG and U251 cells. 3.4. NPsiGLUT3 mediated metabolism inhibition in vitro According to the “Warburg effect”, cancer produces ATP and lactate through aerobic glycolysis [1]. Knockdown of GLUT3 in

U87MG and U251 was expected to inhibit glucose uptake and lead to reduced lactate production. To investigate whether treatment with NPsiGLUT3 could significantly inhibit glucose uptake, we incubated U87MG and U251 cells for 48 h with different formulations, and then glucose uptake was measured by the glucose uptake assay. As demonstrated in Fig. 4A and Fig. 4B, NPsiGLUT3 inhibited fluorescent glucose analog (2-NBDG) uptake of U87MG and U251 cells in a dose-dependent manner. Cells treated with NPsiGLUT3 showed an obviously lower 2-NBDG signal. At a dose of 300 nM siGLUT3, NPsiGLUT3 had a similar glucose uptake inhibition efficacy to Lipo/siGLUT3. Then we performed a quantitative glucose uptake assay to measure the exact inhibition efficacy of NPsiGLUT3. As Fig. 4C and D indicate, glucose uptake of U87MG with NPsiGLUT3 treatment was reduced from ~5.0 to ~2.5 pmol/mg cellular protein while U251 was reduced from ~4.2 to 1.5 pmol/mg cellular protein at a dose of 300 nM siGLUT3. To further analyze whether glucose uptake inhibition could interfere with aerobic glycolysis, we detected the lactate production of NPsiGLUT3-treated cells. After 72 h incubation with NPsiGLUT3, cultural supernatants of U87MG and U251 were collected for lactate production assay. As shown in Fig. 4E, lactate production of U87MG fell from ~2.5 to ~0.63 nmol/mg cellular protein after NPsiGLUT3 treatment at a dose of 300 nM siGLUT3. Similarly, U251 showed a reduction from ~1.9 to 0.69 nmol/mg cellular protein at a dose of 300 nM siGLUT3 (Fig. 4F). These results indicated that GLUT3 gene expression knockdown via NPsiGLUT3 could cause significant metabolism inhibition of U87MG and U251 cells in a low glucose environment. In cell metabolism, the important role of reactive oxygen species (ROS) cannot be neglected. High levels of ROS can cause organelle and genome injury, which is a key factor that leads to cell death [56]. Besides, glucose starvation is closely correlated with ROS production [57]. To analyze whether ROS production of U87MG and U251 cells changed after NPsiGLUT3 treatment, we incubated U87MG and U251 cells with different formulations. After 72 h of treatment, U87MG and U251 cells were collected for the ROS production assay. In both U87MG and U251 cells, we found that NPsiGLUT3 treatment could induce a significant increase in the mean fluorescent intensity of the oxidation-dependent fluorogen DCF-DA (Fig. 4G and H). In addition, the increase of DCF-DA mean fluorescent intensity was dose-dependent. Taken together, these data demonstrated that NPsiGLUT3 could inhibit glucose uptake of U87MG and U251 cells in low glucose environment, which led to glucose deprivation and aerobic glycolysis inhibition. Metabolism suppression of U87MG and U251 cells could induce ROS generation and cause further cell injury and death. 3.5. NPsiGLUT3 mediated proliferation inhibition, stemness downregulation and apoptosis in vitro

Fig. 3. NPsiGLUT3 mediated gene expression knockdown in vitro. (A) Real-time PCR analysis of GLUT3 mRNA expression knockdown in U87MG and U251; Data are shown as means ± s.d. (n ¼ 3), **p < 0.01. (B) Western blot analysis of GLUT3 protein expression knockdown in U87MG and U251. Lipo/siGLUT3 represents the transfection with Lipofectamine RNAi MAX at the siGLUT3 dose of 50 nM. The dose of NPsiNC was 300 nM.

Above, we have shown that NPsiGLUT3 can induce significant metabolism inhibition. To investigate whether metabolism inhibition caused by NPsiGLUT3 could result in proliferation inhibition of U87MG and U251, we incubated U87MG and U251 cells with different formulations in a low glucose environment. Cell proliferation was detected 96 h later by the MTT proliferation assay. As demonstrated in Fig. 5A, NPsiGLUT3 inhibited U87MG and U251 proliferation in a similar dose-dependent manner. With the siGLUT3 dose increasing from 150 nM to 300 nM, the viability of U87MG decreased from ~63.1% to ~44.5%, while that of U251 decreased from 68.8% to 52.7%. These results revealed that NPsiGLUT3-induced glucose uptake inhibition could reduce cancer cell proliferation in a glucose-restricted environment. Glioma stem cells acquired a survival advantage in a low glucose environment due to high GLUT3 expression [12]. Knockdown of

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Fig. 4. NPsiGLUT3 mediated metabolism inhibition in vitro. (A, B) Flow cytometric analysis of glucose analog (2-NBDG) uptake inhibition in U87MG and U251 treated with NPsiGLUT3. (C, D) Quantitative analysis of glucose uptake inhibition in U87MG and U251 after NPsiGLUT3 treatment. Data are shown as means ± s.d. (n ¼ 3), *p < 0.05. (E, F) Quantitative analysis of lactate production reduction in U87MG and U251 after NPsiGLUT3 treatment. Data are shown as means ± s.d. (n ¼ 3), **p < 0.01. (G, H) Flow cytometric analysis of ROS production increase in U87MG and U251 treated with NPsiGLUT3. DCF-DA is a kind of oxidation-dependent fluorogen which can indicate intracellular ROS production.

GLUT3 through NPsiGLUT3 makes it possible to reduce the glioma stem cell percentage and improve the curative efficacy of cancer therapy. As mentioned above, CD133 is the marker of glioma stem cells. We determined the percentage of CD133þ cells with flow cytometric analysis. As shown by Fig. 5B, the percentage of CD133þ cells decreased from ~13.7% to 8.85% (for U87MG) and ~10.7%e ~6.18% (for U251) with the treatment of 300 nM siGLUT3 carrying NPsiGLUT3. As revealed by these data, glucose uptake inhibition

caused glucose deprivation, which was capable of reducing the percentage of glioma stem cells in a low glucose environment. This could be an efficient strategy to overcome the chemotherapy- or radiotherapy-resistance of cancer stem cells and improve cancer curative efficacy. As apoptosis is an important indicator for cell damage and glucose-withdrawal induced ROS generation may cause serious cell injury [57]. We detected the apoptosis of NPsiGLUT3 treated-U87MG

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Fig. 5. NPsiGLUT3 mediated proliferation inhibition, stemness down-regulation and apoptosis in vitro. (A) Cell viability of U87MG and U251 with different treatments. Data are shown as means ± s.d. (n ¼ 3), **p < 0.01. (B) The percentage of glioma stem cells (CD133þ) in U87MG and U251 after treatment. Data are shown as means ± s.d. (n ¼ 3), **p < 0.01. (C) Cell apoptosis of U87MG and U251 induced by different treatments.

and U251 with annexin V-FITC and PI apoptosis assay. FACS analysis showed that NPsiGLUT3 treated-U87MG and U251 exhibited elevated extracellular annexin-V binding, as well as increased PI uptake. The percentage of U87MG and U251 cells that underwent apoptosis after treatment with NPsiGLUT3 (at a dose of 300 nM siGLUT3) was >25%, comparable to the ratio of apoptotic cells observed following treatment with Lipo/siGLUT3, whereas both free siGLUT3 alone and NPsiNC did not (Fig. 5C). These results indicated that NPsiGLUT3 is capable of inducing remarkable and specific apoptosis, while ROS could be the main reason for this apoptosis. 3.6. Anti-tumor activity of NPsiGLUT3 following systemic administration The above results have proven that NPsiGLUT3 was able to inhibit U87MG and U251 glioma stem cells and bulk glioma cells metabolism, and cause subsequent anti-cancer effects (proliferation inhibition and apoptosis) in vitro. Next, we investigated whether the anti-cancer activity of NPsiGLUT3 observed in vitro also exists in vivo. Because NPsiGLUT3 showed similar anti-cancer ability in U87MG and U251 cell lines, we chose only one of them as the tumor model in vivo. A tumor xenograft model was generated in NODSCID mice by injection with U87MG cells, and used to assess the tumor growth inhibition efficacy of the systemic administration of NPsiGLUT3 once every other day at an siRNA dose of 1.0 mg/kg or 2.0 mg/kg per injection from 14 days post-xenograft implantation and ten injections in total were performed. Free siGLUT3 and NPsiNC

were used as negative controls. As shown in Fig. 6A and Fig. 6B, intravenous injection of NPsiGLUT3 in tumor-bearing mice showed significant inhibition of tumor growth, especially at the siGLUT3 dose of 2 mg/kg per injection, whereas neither free siGLUT3 nor NPsiNC affected tumor growth in comparison with PBS treatment. The final tumor weights following treatments shown in Fig. S2 also demonstrate the efficacy of NPsiGLUT3. The tumor growth inhibition effect of NPsiGLUT3 in U87MG tumor xenograft model verified the exvivo anti-cancer activity of it in U87MG and U251 cell lines. The body weights of mice were also monitored (Fig. S3); the treatments did not significantly affect the weights of mice, suggesting that this kind of treatment would be potentially safe for cancer therapy. To further evaluate whether the inhibition of tumor growth observed upon treatment with NPsiGLUT3 is related to GLUT3 gene silencing in cancer cells, we examined GLUT3 expression at the mRNA and protein levels in tumors by qRT-PCR and Western blot analyses following the treatment. A tumor mass from each mouse was excised after the last treatment. As Fig. 6C demonstrates, tumors from mice treated with NPsiGLUT3 exhibited significantly lower levels of GLUT3 mRNA than tumors treated with PBS. In contrast, GLUT3 mRNA levels remained unchanged in tumors from mice treated with either free siGLUT3 or NPsiNC. Western blot analysis of total protein from each tumor mass using anti-GLUT3 monoclonal antibody, showed that, following NPsiGLUT3 treatments, there is a clear knockdown of GLUT3 protein expression levels in tumors (Fig. 6D). Such GLUT3 protein expression knockdown was not seen in tumors from mice receiving control treatments.

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Fig. 6. Anti-tumor activity of NPsiGLUT3 following systemic administration. (A) Tumor growth curves of U87MG xenograft tumor model after treating with NPsiGLUT3 at different doses. Data are shown as means ± s.d. (n ¼ 5), **p < 0.01. (B) Xenograft tumors at the final time point of treatment. (C) and (D) GLUT3 mRNA and protein expression level in U87MG tumor tissue at the end-point of treatment. Data are shown as means ± s.d. (n ¼ 5), **p < 0.01.

Fig. 7. In vivo stemness down-regulation of U87MG through NPsiGLUT3 treatment. (A) Glioma stem cells (CD133þ) percentage in U87MG tumor tissue at the end-point of treatment. Data are shown as means ± s.d. (n ¼ 5), *p < 0.05. (B) Immunofluorescent assay of glioma stem cells in U87MG tumor tissue. Glioma stem cells (PE-CD133 positive) are marked with white arrows. (C) Real-time PCR analysis of stemness-associated genes mRNA expression level in U87MG tumor tissue at the end-point of treatment. Glioma stem cells were stained with PE-CD133 (red) and DAPI (blue) was used to stain the cell nucleus. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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3.7. In vivo stemness down-regulation of U87MG through NPsiGLUT3

Acknowledgments

NPsiGLUT3 have shown the ability to reduce glioma stem cell percentage in vitro, which makes it possible to improve cancer treatment efficacy. To test whether the in vivo anti-tumor activity of NPsiGLUT3 is correlated with stemness down-regulation, we further detected the population of glioma stem cells (CD133þ) recovered from tumors at the end of the treatment. As shown in Fig. 7A, the percentage of CD133þ glioma stem cells in U87MG tumors treated with NPsiGLUT3 at a dose of 2 mg/kg siGLUT3 was ~4.39%, which was moderately lower than that in the PBS control (~6.88%). A dosedependent manner was also observed in NPsiGLUT3 treatment. It should be mentioned that the in vivo down-regulation of glioma stem cells percentage is less significant than that in vitro observed in this study. Firstly, blood clearance by mononuclear phagocytic system will reduce the amount of nanoparticles reaching glioma stem cells. Secondly, glioma stem cells may tend to reside in hypoxic regions of the tumor, penetration of nanoparticles to glioma stem cells could still be a hurdle that must be overcome in the future. To confirm the down-regulated CD133þ cell percentage analyzed with flow cytometry, we further detected CD133þ cells in tumors with immunofluorescent assay. Fewer PE-CD133 labeled glioma stem cells were seen in tumors from 2 mg/kg dose NPsiGLUT3-treated mice than in PBS control, as revealed by the LSM results (Fig. 7B). OCT4, NANOG, SOX2 and CD133 are the main stemnessassociated genes that are expressed extensively in stem cells and cancer stem cells. As the percentage of glioma stem cells was reduced after NPsiGLUT3 treatment, expression of these stemnessassociated genes should also be influenced. qRT-PCR assays were performed to analyze whether the expression of OCT4, NANOG, SOX2 and CD133 were affected. As Fig. 7C shows, the expression of OCT4, NANOG, SOX2 and CD133 all decreased to a certain extent at the end of NPsiGLUT3 treatment. NANOG, SOX2 showed a >40% reduction, while the reduction of OCT4 and CD133 was more than 25%. In contrast, neither CD133þ cell percentage nor stemnessassociated gene expression were affected by free siGLUT3 or NPsiNC treatments. Taken together, our results provide evidence for the stemness down-regulation ability of NPsiGLUT3 in vitro and in vivo, which indicates that the anti-cancer activity of NPsiGLUT3 is associated with stemness down-regulation.

This work was supported by the National Basic Research Program of China (973 Programs, 2012AA022501, 2015CB932100) and the National Natural Science Foundation of China (51125012, 31470965).

4. Conclusions We have demonstrated that cationic lipid-assisted PEG-PLA nanoparticles can efficiently deliver siRNA into U87MG and U251 glioma stem cells and bulk glioma cells. NPsiGLUT3 were able to significantly reduce the expression of GLUT3 in cell culture. GLUT3 knockdown resulted in significant glucose uptake and metabolism inhibition, which further led to stemness down-regulation and proliferation inhibition of U87MG and U251 cells in a glucose restricted environment. The systemic delivery of NPsiGLUT3 significantly inhibited tumor growth in mice bearing U87MG xenografts, due to reduced GLUT3 expression and down-regulated stemness of glioma cells. This strategy can be applied to multiple types of cancer therapy because GLUT3 expression is correlated with predicted poor survival in multiple tumor types and GLUT3 expression increased in multiple low glucose cultured cancer cells. Importantly, GLUT3 expression is confined to multiple cancers and brain; therefore, targeting GLUT3 with an inhibitor would be useful for treating many aggressive cancers with minimal toxicity. Besides, cancer stem cells are an important factor of therapy resistance and tumor relapse or reoccurrence; the combination GLUT3 inhibition with other cancer treatments possibly improves cancer therapeutic efficacy.

Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.biomaterials.2015.01.068.

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