Background
Enhancing the radiosensitivity of resistant tumor cells is a common emphasis in the application of clinical radiotherapy [
1]. Tumor suppressor genes that regulate cell cycle can alter the radiosensitivity of cancer cells. For example, down-regulation of RB1 correlates with increased apoptosis induced by radiation in human breast cancer cells [
2,
3]; the mutations in the p53 tumor suppressor gene enhances the radiosensitivity in oral cavity carcinoma cells [
4]; and
P21 deficiency is associated with a radiosensitive phenotype in colorectal carcinoma cells [
5]. The
RB1,
p53 and
p21 are tumor suppressor genes and play cruical roles in controlling the progression of cell cycle [
6,
7]. These findings indicate that cell cycle regulation genes may be intimately related to radiosensitization, therefore, could potentially be exploited in tumor radiotherapy. In this study, the human renal carcinoma cell, which has traditionally been considered to be radioresistant [
8], was used as experimental model.
B cell translocation gene 1 (
BTG1) is another tumor suppressor gene [
9,
10]. The
BTG1 protein, together with five additional proteins (BTG2/PC3/Tis21, BTG3/ANA, BTG4/PC3B, Tob1/Tob, and Tob2), comprise the
BTG/TOB family of anti-proliferative genes involved in the regulation of cell growth [
11]. Expression of
BTG1 not only inhibits the proliferation of cells but also leads to G1 phase cell cycle arrest in multiple types of cells [
12‐
14]. Some studies have shown that BTG1 is involved in the general processes of cell cycle control and in cellular responses to stress [
15], though a specific role for BTG1 in renal cell carcinoma has not been determined. In consideration of the common physiological function of tumor suppressor genes in controlling cell cycle, we propose that
BTG1 may have a similar impact as
RB1,
p53, and
p21 on the radiosensitivity of renal carcinoma tumor cells.
Certain members of the
BTG/TOB family are known to be regulated by microRNAs (miRNAs) [
16], which are small non-coding RNA molecules that suppress gene expression via sequence-specific interactions with the 3′-untranslated region (3′-UTR) of their target transcripts [
17]. For example,
BTG2 was shown to be suppressed by miR-21 [
18]; over-expression of miR-142-5p leads to down-regulation of
BTG3[
19]; and
TOB2 was shown to be a target gene of miR-322 [
20]. However, miRNA candidates that target
BTG1 have not been identified.
The strategy of using miRNAs as therapeutic targets to enhance cellular radiosensitivity has been discussed before [
21]. miRNAs can efficiently modulate tumor radiosensitivity at four aspects containing DNA damage repair, radio-related signal transduction pathways, tumor microenvironment and apoptosis [
22,
23]. Recent reports show that miRNAs can effectively influence tumor radiosensitivity by impeding cell cycle progression, resulting in enhancement of radiotherapy efficacy [
24]. For example, miR-21 can improve tumor radiosensitivity and promote apoptosis through negatively regulating the
CDC25A expression and cell cycle progression [
25]. Up-regulation of miR-504 can reduce
p53 protein level and affect cell cycle arrest and radiosensitivity mediated by p53 [
26]. With these precedents, we tested whether the
BTG1 could be regulated by miRNAs upon irradiation and how the cellular radiosensitivity in renal carcinoma cells could be affected by the changes of miRNAs targeting
BTG1.
Methods
Cell culture and irradiation
Human renal carcinoma 786-O cells were cultured in RPMI-1640 media (GIBCO, NY, USA) supplemented with 10% fetal bovine serum (Hyclone, MA, USA) at 37°C and 5% CO
2. Irradiation was carried out by laboratory X-ray source (RX-650, Faxitron Bioptics, USA) [
27]. The dose rate was 0.8 Gy/min (100 keV, 5 mA). Cells were seeded into 12-well plates and grown to <70% confluence at the time of irradiation.
Cell cycle assay
Cells were harvested and fixed as described previously [
28]. Prior to analysis, fixed cells were washed twice with PBS, treated with 100 μg/mL RNase A and 50 μg/mL propidium iodide (BD Biosciences, California, USA) for 20 min, and analyzed using FACS Calibur flow cytometry (Becton Dickinson, NJ, USA). Cell cycle distribution was analyzed with the FlowJo software package. DNA content of samples was measured with CellQuest (Becton Dickinson).
Western blot analysis
Western blotting was performed as described previously [
29]. Briefly, cells were collected and lysed with RIPA buffer solution (Beyotime, Haimen, China). Supernatants were collected at 10,000 g for 10 min at 4°C. The concentrations of samples were determined using a BCA protein assay kit (Pierce, IL, USA). Equal amounts of protein were loaded onto 10% SDS-polyacrylamide gels for electrophoresis, and proteins were transferred onto PVDF membrane by western blotting. GAPDH was used as loading control. Membranes were then blocked with nonfat milk and incubated overnight at 4°C with the following primary antibodies: anti-GAPDH (1:5,000, Santa Cruz), anti-BTG1 (1:1,000, Abnova, Taipei, Taiwan). Immunological complexes were detected by enhanced electrochemiluminescence (Millipore, Darmstadt, Germany) with either an anti-rabbit peroxidase (1:5000, Santa Cruz, Texas, USA), or an anti-mouse peroxidase (1:4000, Santa Cruz) antibody. The fold changes of protein levels were analyzed by the Image J software.
Transfection
MicroRNA mimic and negative control mimic were synthesized and purified by RiboBio Co. (Guangzhou, China) [
29]. Transfections of the miRNA duplexes were performed with 40–60% confluent cells using Lipofectamine 2000 (Invitrogen, California, USA). The medium was replaced with new culture medium for 5 h after transfection.
Trypan blue dye exclusion assay
Cell viability is calculated as the number of viable cells divided by the total number of cells within the grids on the hemacytometer. Cells which take in trypan blue are considered non-viable. Cells were harvested with trypsin, suspended in PBS and mixed with 0.4% solution of trypan blue stain (Invitrogen) after various treatments. Count at least 500 cells for calculation. The percentage of viable cells = [1.00 - (Number of blue cells/Number of total cells)]*100%.
Caspase-3 activity assay
To evaluate the activity of caspase-3, the caspase-3 activity kit (Beyotime) was used. Cells were collected and lysed with reaction buffer and the total protein concentration is 1-3 mg/mL. In the samples, activated caspase-3 cleaves substrate (Ac-DEVD-pNA) (2 mM) between DEVD and pNA, quantitatively generating pNA that can be detected using an ELISA reader at an absorbance of 405 nm. In the caspase-3 colorimetric calibration, the value of R2 should be greater than 0.999.
The clonogenic assay was conducted as described previously [
30]. Briefly, cells were harvested and an appropriated number of cells were seeded onto each of the 60 mm dishes to produce about 50–120 colonies. After 8–10 days incubation, the colonies were washed with 1 × PBS softly, fixed with 70% ethanol for 5 min and stained with 0.5% crystal violet for 3 min at room temperature. Colonies with more than 50 cells were counted.
Luciferase reporter assay
The 3′-untranslated region (3′-UTR) of human
BTG1 transcript was cloned downstream of the luciferase gene between the Xho I and Sal I sites of the pmirGLO dual-luciferase vector (Promega, WI, USA). A pmirGLO dual-luciferase vector containing one mutated seed sequences of miR-454-3p was constructed. The sequencing of constructed plasmids was verified by Shanghai Sangon Biotechnology Co. (Shanghai, China). 1.5 × 10
5 786-O cells in 12-well plate were co-transfected with 300 ng DNA (pmirGLO-3′ UTR constructs or derived mutants) and 30 nM of either miR-454-3p mimics using transfection reagent Lipofectamine 2000 (Invitrogen). Luciferase activity was measured 48 h later using the Dual Luciferase Reporter Assay System (Promega) [
31] with a Tecan Infinite M200 Pro microplate reader (Tecan, Mannedorf, Switzerland).
Quantitative real-time reverse transcription-PCR
For qRT-PCR, total RNAs were extracted from cultured cells using TRIzol Reagent (Invitrogen) according to the manufacturer’s protocol. Reverse transcription and quantitative RT-PCR were performed according to the protocol of the qRT-PCR Detection Kit (Promega). All of the stem-loop RT primers were purchased from RiboBio Co. (Guangzhou, China) to detect miR-454-3p or U6. U6 was used as an endogenous control for miRNAs and GAPDH for coding genes. Other gene-specific primers were as follows: BTG1, 5′-TCCATAATCCATCCCCAAGA-3′ and 5′-GGATGCAATCCTGGACATTT-3′, SKA2, 5′-CCGCTTTAAACCAGTTGCTG-3′ and 5′-CTCTGCCGCAGTTTTCTCTT-3′, GAPDH, 5′-GTGGACCTGACCTGCCGTCT-3′ and 5′-GGAGGAGTGGGTGTCGCTGT-3′. Gene-specific primers were synthesized from Shanghai Sangon Biotechnology Co. (Shanghai, China).
Statistical analyses
All experiments were repeated at least three times, and data were presented as means ± SE. The statistical significance of the results was determined by Student’s t-tests using Microsoft Excel (Microsoft Campus, Redmond, WA, USA).
Discussion
In the present study, we identified miR-454-3p as regulator of
BTG1 expression based on bioinfomatic software prediction and detailed experimental validation. The expression of
BTG1 and miR-454-3p was shown to inversely correlate in 786-O cells upon exposure to environmental stressors, thus supporting a physiological role for miR-454-3p in regulating BTG1 expression. In addition to miR-454-3p, miR-19b was predicted to have two binding sites on the 3′-UTR of the BTG1 mRNA, one of which occupies the same site as the putative miR-454-3p target. A significant repression of endogenous BTG1 protein by miR-19b expression vector was also observed in 786-O cells (Additional file
2F). Therefore, we speculate that more than one miRNA may target BTG1, and these miRNAs may function antagonistically under specific physiological conditions. Future experimentation to address this possibility may unveil a regulation network of BTG1 regulation by miRNAs.
Our results show that the expression of
SKA2 is regulated coordinately with the expression of miR-454-3p. Interestingly, miR-454-3p and a third putative BTG1 target, miR-301a, are encoded within the first intron of
SKA2, whose depletion affects the cell cycle by inducing a metaphase-like delay [
37]. MiR-301a also down-regulates the expression of an inhibitor of NF-κB, Nkrf [
38]. NF-κB binds directly to the
SKA2 promoter region to activate the transcription of
SKA2 and miR-301a and also enhances persistent NF-κB activation to facilitate tumor growth [
37,
39], thus suggesting a feedback loop to moderate SKA2 function. It is intriguing that miR-454-3p targets BTG1, which has a strong anti-proliferative ability, and suggesting an additional complexity of the growth regulatory function derived from the
SKA2 locus. BTG1 has been suggested to inhibit NF-κB activities [
40]. Therefore, complex regulatory loop appears to regulate cell growth inhibition by BTG1, and it is likely that SKA2, NF-κB and multiple miRNAs are coordinated to control the BTG1 expression.
Little is known about the molecular mechanisms of control of the cell cycle by BTG1, and most of the information comes from interaction studies. BTG1 exerts cellular functions by interacting with PRMT1, HOXB9, and hCAF1, which regulate the expression of a number of genes involved in cell cycle control and progression [
41‐
43]. CCNA2 (cyclinA2) physically associates with BTG1 [
44] and controls S phase by activating CDK2 kinases to initiate DNA synthesis [
45]. Ectopic over-expression of CCNA2 triggers checkpoint response and subsequently increases the S phase population in mammalian cells [
45]. We found that siRNA-mediated silencing of BTG1 led to S phase arrest after IR. Additionally, the S phase arrest can also be mediated by miR-454-3p. Furthermore, miR-454-3p is highly expressed in the S phase. The above negative regulation may suggest the association between CCNA2 and BTG1 in the control of the cell cycle progression of S phase. However, our results also show that over-expression of BTG1 in 786-O cells promotes a G1 arrest. Therefore, the link between miR-454-3p, BTG1 and cell cycle is likely complex and warrants further investigation to unravel the network of cell cycle regulators that are functionally associated with BTG1.
Acknowledgements
This work was supported by the Major State Basic Research Development Program of China (973 Program, No. 2010CB834201), the National Natural Science Foundations of China (No. U1232125, 31270895, 11335011 and 31370846). We thank Qingxiang Gao and Liang Peng for their kind help of technology of flow cytometry; Torsten Juelich, Wenfei Li for critical reading of the manuscript.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
XW, ND, and WH did the most of the experimental work. JH and SX conducted the luciferase reporter assay. HP and JH performed qRT-PCR. JW and XW wrote the paper and designed the experiments. GZ provided intellectual input and helped with experimental design. All authors read and approved the final manuscript.