Gene Ther Mol Biol Vol 14, 1-8, 2012

 

A DNA-based small interfering RNA targeting Stat3 inhibits the growth of renal carcinoma 786-O cells

Research Article

 

 Zhixia Sun1*, Huijie Jia2*, Baofeng Guo1, Xiangbo Kong1, Hui Wang1*, Ling Zhang 2*

 

1 Department of Surgery, China–Japan Union Hospital of Jilin University, Changchun 130021, China

2 Prostate Diseases Prevention and Treatment Research Centre and Department of Pathophysiology, Norman Bethune College of Medicine, Jilin University, Changchun 130021, China

* These authors contributed equally to this work.

______________________________________________________________

*Correspondence: Hui Wang, PH.D., M.D., Department of Surgery, China–Japan Union Hospital of Jilin University, Changchun 130021, China, Phone: 8613578708800, Fax: 86-0431-84641026; Email: wanghui19620708@yahoo.com.cn,  or Ling Zhang, PH.D., M.D., Department of Pathophysiology, Norman Bethune College of Medicine, Jilin University, Changchun 130021, China, Phone: 86-431-563-2348, Fax: 86-431-563-2348, Email: zhangling3@jlu.edu.cn

Keywords: Renal cell carcinoma, tumor gene therapy, Stat3, RNA interference.

 

 

 

Received: 29 November 2011; Revised: 12 December 2011

Accepted: 24 December 2011; electronically published: 30 December 2011

 

Summary

Renal cell carcinoma (RCC) is one of the most treatment-resistant malignancies. Despite new therapeutic advances, almost all patients display resistance to treatment and the outcome is poor. Signal transducer and activator of transcription 3 (Stat3) plays a key role in tumor cell survival, proliferation and angiogenesis, and it aberrantly activated in several types of cancers, including RCC. We investigated the effect of a DNA-based small interfering RNA (siRNA) targeting Stat3 (pSi-Stat3) on tumor growth, cell proliferation, angiogenesis and apoptosis of the human renal carcinoma cell line 786-O both in vitro and in vivo. In 786-O cells, pSi-Stat3 treatment prevented Stat3 expression, and significantly induced cell apoptosis (P<0.01). Treatment with pSi-Stat3 suppressed the expression of Stat3-downstream genes and induced the morphological features of apoptosis (P<0.05). In vivo, intratumor injection of pSi-Stat3 inhibited tumor growth in 786-O-bearing nude mice and significantly decreased the expression of the Stat3-downstream genes Bcl2 and VEGF in tumor xenografts (P<0.05), that may increase apoptosis and decrease angiogenesis, respectively. There was a significant decrease in the expression of Ki-67 in xenograft tumors of pSi-Stat3-treated mice compared with that in the control groups (P<0.05). Our results suggest that using a DNA vector-based siRNA to inhibit the Stat3 signaling pathway might be a useful therapeutic strategy in RCC and other malignancies.

 

 

I. Introduction

 


Human renal cell carcinoma (RCC) is the most common malignant kidney cancer that arises from renal epithelium, and accounts for approximately 3% of all malignant cancers worldwide (Cohen and McGovern, 2005). An estimated 4.4–11.1 cases per 100,000 people are diagnosed with RCC every year (Gupta et al., 2008). Despite improvements in the management of RCC, its treatment by surgery or systemic therapy is largely unsuccessful. Advanced RCC patients have an exceedingly poor outcome with an estimated survival of less than one year (Campbell et al., 2003). Thus, development of new novel agents with more effective antitumor activity is a high priority in the treatment of RCC. Gene therapy has been proposed as the most promising treatment option for RCC (Brower, 2008).

Signal transducer and activator of transcription 3 (Stat3) mediates cell survival, growth and differentiation (Alemany et al., 1999; Ihle, 2001; Levy and Lee, 2002; Takeda and Akira, 2000). Stat3 has been shown to be associated with many types of human cancer (Bowman et al., 2000; Frame, 2002) including RCC (Guo et al., 2009; Horiguchi et al., 2010), and constitutively activated Stat3 acts an oncogene (Bromberg et al., 1999). Stat3 activated by phosphorylation of Tyr-705, which leads to dimerization (Darnell, 1997). Stat3 responds to numerous cytokines and growth factors (Burke et al., 2001), and activated Stat3 complexes translocate to the nucleus to regulate the expression of downstream genes (Williams, 2000).

RNA interference (RNAi) is a sequence-specific, post-transcriptional gene-silencing mechanism that has been proposed as a novel treatment for cancer (Gaither and Iourgenko, 2007). Chemically synthesized small interfering RNAs (siRNAs) and DNA vector-based short hairpin RNAs (shRNAs) are effective in the specific suppression of gene expression in various cell systems (Sui et al., 2002). The therapeutic potential of the RNAi method has been proven in both cultured cell lines and animal models (Czauderna et al., 2003; Matsukura et al., 2003; Sui et al., 2002), and many examples demonstrate the utility of vector-based siRNAs in suppressing target gene expression (Kobayashi et al., 2004; Yu et al., 2002).

In the present study, we examined the inhibitory effect of a DNA vector-based siRNA targeting Stat3 to knock down the expression of this gene in human RCC cells in vitro and in a mouse model of RCC in vivo.

 

II. Materials and Methods

A. Cell lines, plasmids and transfection

The human RCC cell line, 786-O was purchased from the Institute of Cell Biology (Shanghai, China). 786-O cells were grown in high-glucose DulbeccoÕs modified EagleÕs medium (DMEM; Invitrogen, Carlsbad, CA) containing 10% fetal calf serum (FCS; Gibco, USA) and incubated at 37”C in a humidified atmosphere containing 5% CO2. Cells were regularly passaged to maintain exponential growth. A siRNA target located in the SH2 domain of Stat3 (Genbank accession no. NM00315; nucleotides 2144–2162) was chosen based on a previous study (Zhang et al., 2007). A scrambled siRNA was used as a negative control.

Double-stranded DNA oligonucleotides were cloned into the pGCsilencerU6/ Neo/GFP vector that contained a green fluorescent protein gene (Jikai Chemical, Inc.), to generate plasmids pSi-Stat3 and pSi-Scramble. 3×105 786-O cells were seeded in 6-well plates for 24 h and transfected at 90–95% confluence with pSi-Stat3 or pSi-Scramble using Lipofectamine 2000 (Invitrogen, Carlsbad, CA). Cells were harvested and assayed 24 h after transfection. Each experiment was repeated three times.

 

B. Western blotting

Cells were harvested, washed three times with ice-cold phosphate-buffered saline (PBS), and were incubated in ice-cold RIPA buffer. Protein concentrations were determined using a Protein Assay Kit (Bio-Rad, Hercules, CA). Equal amounts of protein were separated by 12% SDS-polyacrylamide gel electrophoresis and transferred onto nitrocellulose membranes (Millipore, Bedford, MA). After blocking with 5% skimmed milk in Tris-buffered saline at room temperature for 1 h, the membranes were incubated at 4”C overnight with primary antibodies against β-actin, Stat3, phosphorylated Stat3 (p-Stat3), Bcl2, or vascular endothelial growth factor (VEGF). After incubation with the appropriate secondary antibody, immune complexes were detected using the diaminobenzidine (DAB; Sigma, St. Louis, MO) coloration method. All antibodies were obtained from Santa Cruz Biotechnology (Santa Cruz, CA). Immunoreactive bands were quantified using a GIS Gelatum imaging system (Tanon, Shanghai, China). Values were corrected to the absorbance of the internal control.

 

C. RNA extraction and semi-quantitative RT-PCR

Total RNA from tissues and 786-O cells were extracted using Trizol (Invitrogen) according to the manufacturerÕs protocol. First-strand cDNA was synthesized by reverse transcription of 2μg of total RNA using Moloney murine leukemia virus reverse transcriptase (Promega, Madison, WI). Transcript levels were normalized to those of β-actin. The primers used in PCR were as follows: β-actin sense 5′- TCGTGATGGACTCCGGTGAC -3′, antisense 5′- TCGTGGATGCCACAGGACTC -3′; Bcl2 sense 5′- GAGGATTGTGGCGTTCTTT-3Õ, antisense 5′- CCCAGCCTCCGTTATCCT -3′; VEGF sense 5′- TTGCCTTGCTGCTCTACCTC -3′, antisense 5′- TCATCTCTCCTATGTGCTGGC -3′. The cycling conditions were 30 cycles of denaturation (94”C, 30 s), annealing (β-actin, 56”C, 30s; Bcl2, 53”C, 30s; VEGF, 53”C, 30s) and extension (72”C, 30 s). The PCR products were electrophoresed on 1% agarose gels containing ethidium bromide and visualized using a GIS Gelatum imaging system (Tanon).

 

 

D. Acridine Orange Staining

Acridine orange (AO) staining is a diagnostic technique for apoptotic cell morphology. After transfection for 24 h, cells were stained with 0.5 μg/ml AO (Sigma) in complete medium at 37”C for 15 min. Fluorescence was detected using a fluorescence microplate reader with excitation at 485 nm and emission at 530–640 nm.

 

E. Tumor xenografts in nude mice

Four-week-old male Balb/c athymic nude mice were purchased from the Second Military Medical University, Shanghai, China. All mice in this study were kept under pathogen-free conditions and were maintained in accordance with the National Institutes of Health ŅGuide for the Care and Use of Laboratory AnimalsÓ, and with the approval of the Scientific Investigation Board of Science and Technology of Jilin Province. Briefly, 5×106 786-O RCC cells were injected subcutaneously into the mouseÕs flank.

After 1 weeks, when the tumor reached approximately 5 mm in diameter, the mice were randomly assigned into three groups (n = 5 each): the pSi-Stat3 group; the pSi-Scramble group; and the untreated (Mock) group. The mock group was injected with 100ul PBS into tumors and the mice in the pSi-Stat3 and pSi-Scramble groups received an intra-tumor injection of 20 μg pSi-Stat3 and pSi-Scramble, respectively, diluted in 50 μl PBS per mouse. Immediately after injection, tumors were pulsed with an electroporation generator (ECM 830, BTX). Pulses were delivered at a frequency of 1/s, 150 V/cm, with a length of 50 ms. Mice were received the treatment once a week. Mice were sacrificed on day 40, and tumor sizes were determined. In the Mock group, an equal volume of PBS was injected into the tumor. Tumor size was measured with a caliper every 2 days; tumor volumes were determined using the formula: tumor volume = length × width2 × 0.52.

 

F. Immunohistochemistry

Harvested tumors were fixed in 4% formaldehyde, and then labeled with monoclonal antibodies against Ki-67 and the microvessel marker CD34. Antibody (1:100; Santa Cruz, CA, USA) staining was performed on 4-μm histological sections of formalin-fixed, paraffin-embedded tumor and adjacent normal samples. Serial 4-μm sections were mounted on pretreated glass slides, deparaffinized, rehydrated and microwaved for 15 min at high power in 10 mmol/L sodium citrate buffer (pH 6.0) to unmask the epitopes. Endogenous peroxidase activity was quenched using 3% H2O2 for 10 min; slides were then washed in PBS, pH 7.5, and incubated with 5% bovine serum albumin for 20 min. Sections were incubated overnight at 4”C with a 1:100 dilution of primary antibodies. After washing, the sections were incubated with horseradish peroxidase-conjugated secondary antibodies (1:2000; Santa Cruz, CA, USA) for 1 h at room temperature. After washing, tissues were stained for 5 min with DAB, dehydrated and coverslipped. Each experiment was performed in duplicate.

 

G. TUNEL assays

Terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assays were conducted using the DeadEnd Fluorometric TUNEL kit (Promega). Tumor

tissue sections were fixed in 4% paraformaldehyde as instructed by the manufacturer. The extent of cell apoptosis was analyzed using a FACScan flow cytometer (Becton Dickinson, Franklin Lakes, NJ). The apoptotic index (%) was calculated according to the following formula: number of apoptotic cells / total number of nucleated cells × 100.

 

H. Statistical analysis

Data were expressed as the mean ± SD. Statistical analysis was performed using SPSS statistical software 13.0 (SPSS, Inc.) for multiple comparisons using analysis of variance and StudentÕs t-test. All experiments were repeated three times. A value of P < 0.05 was considered statistically significant.

 

III. Results

A.    In vitro inhibition of Stat3 expression by siRNA treatment

The pSi-Stat3 or pSi-Scrambled plasmids were transfected into 786-O cells and the expression of Stat3 mRNA and protein assessed by western blotting, RT-PCR and real time RT-PCR respectively. The plasmid pSi-Stat3 transfection significantly inhibited the expression of Stat3 mRNA compared with that in the Mock and pSi-Scrambled groups (P < 0.01; Fig. 1A, B). Similarly, transfection of pSi-Stat3 caused a significant reduction in Stat3 protein levels compared with those in the Mock and pSi-Scrambled groups (P < 0.01; Fig. 1C, D).

.

 

B. In vitro inhibition of Stat3-downstream genes and induction of apoptosis by siRNA treatment

In the pSi-Stat3 treatment group, there was a significant decrease in the expression of the Stat3-downstream target genes Bcl2 and VEGF compared with their levels in the pSi-Scramble and Mock groups (P < 0.01; Fig. 2A, B). The same result was observed for the protein levels of these genes (P < 0.01; Fig. 2 C, D).

     We then assessed cellular morphology using AO staining. In the pSi-Scramble group, the cells were intact and budding, whereas in the pSi-Stat3 group, the nuclei were partially or completely disrupted, or condensed into small apoptotic bodies (Fig. 2E and F).

Twenty-four hours after pSi-Stat3 transfection, the features of early apoptosis were observed as intercalated AO (bright green) amongst the fragmented DNA, and the hallmarks of late apoptosis were indicated by orange staining.

 


 

 


Figure 1. Effect of siRNA-Stat3 treatment on Stat3 expression in vitro.

A, Stat3 mRNA expression levels by RT-PCR B, Real time RT-PCR was performed and relative Stat3 mRNA expression was calculated in cells of each group. C, D, Stat3 protein expression levels by western blotting (C) and quantification of the bands (D). * P < 0.05 vs. Mock group; # P < 0.05 vs.p-Si-Scramble group

 

Figure 2. Effect of siRNA-Stat3 treatment on Stat3-downstream genes, and morphological analysis of 786-0 cells in vitro.

A, mRNA expression levels of the Stat3-downstream genes Bcl2 and VEGF using RT-PCR. B, Relative Bcl2 and VEGF mRNA expression by Real time RT-PCR. C, D, Protein levels of Bcl2 and VEGF (C) and quantification of the bands (D). E, F, Fluorescent micrograph of acridine orange staining (×400). * P < 0.05, vs. Mock group; # P < 0.05 vs. p-Si-Scramble group



 

C. In vivo inhibition of Stat3 expression and tumor growth by siRNA-Stat3 treatment

In the pSi-Stat3 group, both tumor weight and volume were sharply decreased compared with those in the Mock and pSi-Scramble groups (P < 0.01; Fig. 3A, B and Table 1). Accordingly, the Stat3 mRNA and protein levels were significantly reduced in the pSi-Stat3 group (P < 0.01; Fig. 3C–F).

 

D. In vivo inhibition of Stat3-downstream genes and induction of apoptosis by siRNA treatment

In the pSi-Stat3 treatment group, there was a significant decrease in the mRNA and protein expression of the Stat3-downstream target genes Bcl2 and VEGF compared with that in the pSi-Scramble and Mock groups (P < 0.01; Fig. 4A–D).

 

E. Morphological changes induced by siRNA-Stat3 treatment in mouse RCC xenografts

 

The expression of p-Stat3 was present in tumor cells in the pSi-Scramble group, whereas it was barely observed in the pSi-Stat3 group (Fig. 5A). We then investigated the effect of pSi-Stat3 on 786-O cell-implanted tumor proliferation, angiogenesis and apoptosis.

 Immunohistochemistry demonstrated that Ki-67, a marker of cell proliferation and cell division, was notably suppressed by pSi-Stat3 compared with its expression in the pSi-Scramble group; moreover, the proliferation index in the pSi-Stat3 group was 9.3±1.5%, significantly lower than that in the pSi-Scramble group (52.7±7.4%) or the Mock group (61.9±9.1%) (Fig. 5B and Table 2). CD34, a

marker of microvessel density, was also markedly decreased by pSi-Stat3 treatment compared with its expression in the pSi-Scramble group (Fig. 5C).

We also performed TUNEL assays on tumor sections to examine apoptosis. The apoptotic index was significantly higher in the pSi-Stat3 group than in the pSi-Scramble or the Mock groups (43.2±7.2% vs. 6.5±1.9% and 5.2±2.2% , respectively) and more apoptotic cells were observed in tumor tissue sections from animals treated with pSi-Stat3 therapy (Fig. 5D and Table 2).



 


 

 


 

Figure 3. Effect of siRNA-Stat3 treatment on the growth of tumor xenografts and the Stat3 expression. A, Relative tumor sizes of tumor xenografts in each treatment group. B, Growth curves of 786-0 tumor xenografts on days 0, 10, 20, 30 and 40 after treatment. C, Stat3 mRNA expression by RT-PCR. D, Relative Stat3 mRNA expression using Real time RT-PCR. E, F, Stat3 protein expression (E) and quantification of the bands (F). * P < 0.05, vs. Mock group; # P < 0.05 vs. pSi-Scramble group.

 

Figure 4. Expression of the Stat3-downstream targets Bcl2 and VEGF in RCC xenografts in vivo. A, B, Bcl2 and VEGF mRNA expression by RT-PCR (A) and Real time RT-PCR(B) respectively. C, D, Bcl2 and VEGF protein expression (C) and quantification of the bands (D). * P < 0.05, vs. Mock group; # P < 0.05 vs. p-Si-Scramble group.

 

Figure 5. Immunohistochemical staining on RCC xenograft sections. Sections were stained with anti-p-Stat3 (A), Ki-67 (B) or CD34 (C). Panels A–C were shown at ×200 magnification. D, TUNEL assay (×10,000). TUNEL-positive cells are indicated by green fluorescence.

 

 


 

IV. Discussion

Gene therapy offers a novel and promising therapeutic opportunity against RCC. In fact, several research achievements have already been translated into clinical practice, with significant therapeutic effect (Saylor and Michaelson, 2009). RNAi therapy has been used successfully to suppress the abnormally up-regulated expression of specific oncogenes (Cuevas et al., 2009; Dykxhoorn, 2009).

In this study, we investigated the antitumor activity and mechanism of action of pSi-Stat3 both in vitro in the renal cancer cell line 786-O and in vivo in murine xenografts. We used an RCC xenograft mouse model to investigate the potential therapeutic effect of a vector-based siRNA targeting the Stat3 gene. Injection of the pSi-Stat3 plasmid into xenograft tumors caused no evident discomfort or infection, and we believe this method to be safe, non-toxic, and without side effects. The plasmid-based siRNA correctly and efficiently targeted the Stat3 gene and down-regulated its expression in vitro and in vivo, as shown by semi-quantitative RT-PCR and western blotting.

siRNA-mediated targeting of Stat3 must affect its downstream signal transduction pathway, because cells and tumors in the pSi-Stat3 group demonstrated significant decreases in the mRNA and protein level expression of the Stat3-targeted genes Bcl2, an anti-apoptosis factor, and VEGF, an angiogenesis factor. AO staining of 786-O cells revealed that transfection of pSi-Stat3 caused the morphological features of apoptosis in many cells.

We also examined the effect of pSi-Stat3 treatment on tumor xenograft growth in nude mice, and investigated the underlying mechanism. Treatment with pSi-Stat3 significantly inhibited tumor growth, and increased expression of the markers of cell proliferation and angiogenesis Ki-67 and CD34, respectively. pSi-Stat3 treatment also induced apoptosis, as demonstrated by TUNEL assay.

Stat3 has been shown to be persistently activated in RCC and play a central role in carcinogenesis (Guo et al., 2009). Stat3 is a key regulator of tumor proliferation, angiogenesis, apoptosis and tumor immune evasion (Avizienyte et al., 2005; Gritsko et al., 2006; Yu et al., 2009). Therefore, blocking the Stat3 signal transduction pathway in tumors by gene therapy may be a useful therapeutic approach (Fratto et al., 2010; Horiguchi et al., 2010). This method can be classified as a tumor suppressor gene therapy as well as a cancer immunotherapy. Stat3 plays a significant role in tumor immune evasion probably by increasing expression of immune-suppressing factors, blocking the secretion of various proinflammatory mediators and regulation various immune cells. Future studies should be aimed at studying the mice survival rate and the immune-markers to explain the superexcellent effect of Si-Stat3.

 

 

 

In summary, down-regulation of Stat3 by a DNA vector-based siRNA resulted in cell apoptosis in vitro and tumor growth inhibition in a RCC xenograft mouse model. The possible reason was pSi-Stat3 reduced the expression of Stat3 and inhibited its downstream cellular proliferation factors, increased apoptosis and decreased angiogenesis. We suggest that silencing of the Stat3 gene is worthy of further investigation for cancers and may be useful for clinical application.

 

 

Acknowledgments

This work was supported by the National Natural Science Foundation of China (grant no. 30801354 and 30970791) the Ph.D. Programs Foundation of Ministry of Education of China (grant no. 200801831077) and the Jilin Provincial Science & Technology Department (grant no. 20080154).

 

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        Hui Wang   Ph.D                        Ling Zhang Ph.D