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
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.
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 ÒGuide 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.
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
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).
.
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
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.
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