Background
Ovarian cancer is the most lethal gynecological tumor and ranks the fifth in the cause of death for women suffered from tumor. It is estimated that there are 21,290 new ovarian cancer cases and 14,180 deaths in the United States in 2015 [
1]. The poor prognosis of ovarian cancer patients is mainly attributed to cancer metastasis and recurrence. Epithelial-mesenchymal transition (EMT) is a dynamic process mediating ovarian cancer metastasis, among others. Exploration of signaling pathways involved in EMT process will shed light on the molecular mechanisms of metastasis.
EMT refers to the transformation of epithelial cells into fibroblast-like cells in physiological and pathological processes, characterized by loss of epithelial markers, acquisition of mesenchymal molecules and enhancement of cell mobility [
2]. Various cytokines and growth factors, including transforming growth factor β (TGF-β), are key agents for EMT initiation and maintenance. Three isoforms of TGF-β are identified, and TGF-β1 is the most classical and frequently used EMT-inducer [
3,
4].
Increasing evidence shows that aberrations in DNA methylation status are associated with tumor progression and prognosis of patients [
5]. DNA methyltransferases (DNMTs) are major molecules controlling DNA methylation [
6,
7]. Laterly, ten-eleven translocation (TET) family members (TET1-3) which can modify 5-methylcytosine (5-mC) by oxidation to 5-hydroxymethylcytosine (5-hmC) and further 5-formylcytosine (5-fC) and 5-carboxycytosine (5-caC) are identified and expand the understanding about mechanisms of DNA demethylation [
8‐
10]. TETs are dysregulated in multiple malignances including breast cancer [
11], hepatocellular carcinoma [
11], melanoma [
12] and glioma [
13]. For example, decreased TET1 mRNA level is correlated with poor survival of breast cancer patients [
14], and the same goes for TET2 in colorectal cancer [
15].
Aberrant DNA methylation/demethylation is implicated in TGF-β1-induced EMT [
16‐
18]. TGF-β1 triggers
TIP30 (gene coding HIV-1 Tat interactive protein 2) hypermethylation by upregulating DNMT1 and DNMT3A to induce EMT and metastasis in esophageal carcinoma [
19]. However, few researches are performed to elaborate the role of TETs in TGF-β1-induced EMT. Here we report the epigenetic regulation of TET3 on miR-30d in TGF-β1-induced EMT in ovarian cancer cells, highlighting the potentiality of TET3 to be used as a prognostic biomarker or a therapeutic target for ovarian cancer.
Methods
Cell culture and TGF-β1 treatment
Human ovarian cancer cell line SKOV3 was obtained from the Shanghai Cell Bank of Chinese Academy of Sciences (Shanghai, China), and 3AO was from the Shandong Academy of Medical Sciences (Jinan, China). Cells were incubated in RPMI 1640 (GIBCO, Grand Island, NY USA) supplemented with 10 % newborn bovine serum (GIBCO, Grand Island, NY, USA) at 37 °C in 5 % CO2. When treated with 10 ng/ml TGF-β1 (PeproTech, Rocky Hill, USA), cells were maintained in media containing 1 % newborn bovine serum for indicated time before harvested.
Quantitative real-time PCR (qRT-PCR)
Total RNA was extracted from cells using TRIzol reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions. Concentration and quality of total RNA were assessed by absorbance at 260 nm and the ratio of 260/280, respectively, on a UV spectrophotometer (BioRad Inc., Hercules, CA, USA). For mRNA detection, first-strand cDNA was synthesized using a PrimeScript™ RT reagent Kit with gDNA Eraser (Takara, Dalian, China). Quantitative real-time PCR was performed using a SYBR Premix Ex Taq™ II kit (Takara, Dalian, China) on a CFX96 real-time PCR system (Bio- Rad, Hercules, CA, USA). TET1, TET2 and TET3 were normalized to β-actin, while miR-30s were normalized to small nuclear U6. Relative gene expression was calculated automatically using 2
-ΔΔCt. PCR primers for TET1, TET2, TET3 and β-actin were synthesized by Beijing Genomics Institute (Beijing, China), and primer sequences were listed in Table
1. Primers for miR-30a, 30b, 30c, 30d, 30e, and U6 reverse transcription and amplification were designed and synthesized by Ribo-Bio Co., Ltd. (Guangzhou, China).
Table 1
Primer sequences for real-time PCR
TET1 | F: CCCGAATCAAGCGGAAGAATA | 101 |
R: TACTTCAGGTTGCACGGT |
TET2 | F: CTTTCCTCCCTGGAGAACAGCTC | 146 |
R: TGCTGGGACTGCTGCATGACT |
TET3 | F: GTTCCTGGAGCATGTACTTC | 93 |
R: CTTCCTCTTTGGGATTGTCC |
β-actin | F: TCCCTGGAGAAGAGCTACGA | 194 |
R: AGCACTGTGTTGGCGTACAG |
Western blot
Total protein was collected from cells by RIPA lysis buffer containing protease inhibitors (Roche, Indianapolis, IN, USA) and 1 mM PMSF on ice. Protein concentration was measured using the BCA-200 Protein Assay kit (Pierce, Rockford, IL, USA). After heat denaturation at 100 °C for 5 min, proteins were separated by electrophoresis on 10 % SDS–PAGE gels and then transferred onto nitrocellulose membranes (Pall Life Science, Port Washington, NY, USA). The membranes were blocked with 5 % non-fat milk at room temperature for 1 h, and then incubated overnight at 4 °C with rabbit anti-human TET3 (Abcam, 1:1000), E-cadherin (Cell Signaling Technology (CST, 1:1000), Vimentin (CST, 1:500), N-cadherin (CST, 1:1000), Snail (CST, 1:300) and mouse anti-human β-actin (CST, 1:1000). After washing with TBST, the blots were incubated with horse radish peroxidase (HRP)-conjugated goat anti-rabbit or anti-mouse IgG. Blots were visualized using ECL reagents (Pierce, Rockford, IL, USA) by a chemiluminescence imaging system (Bio-Rad, Richmond, CA, USA). The results were quantified by Image J software.
Plasmid transient transfection
The human TET3 expression vector FH-TET3-pEF was obtained from Addgene. SKOV3 and 3AO cells were seeded into 6-well plates until 70 %-80 % confluence and transiently transfected with FH-TET3-pEF or empty vector using the X-treme GENE HP DNA Transfection Reagent (Roche, Indianapolis, IN, USA).
miR transient transfection
miR-30d mimic and negative control were purchased from Ribo-Bio Co. Ltd. (Guangzhou, China). SKOV3 and 3AO cells were seeded into 6-well plates to reach 40 %–50 % confluence after 24 h and then transiently transfected with 100 nM miR-30d mimic or negative control using the X-treme GENE siRNA Transfection Reagent (Roche, Indianapolis, IN, USA). After 24 h of transfection, the cells were treated with 10 ng/ml TGF-β1 for another 48 h.
Cell migration and invasion assay
After transient transfection of FH-TET3-pEF or empty vector and treatment of TGF-β1 for 48 h, cells were trypsinized and counted. A total of 1 × 105 cells (for migration assay) or 4 × 105 cells (for invasion assay) in 100 μl serum-free medium was added into millicells (Millipore Co., Bedford, MA, USA) without (for migration assay) or with (for invasion assay) Matrigel (Becton Dickinson Labware, Bedford, MA, USA) coated. 500 μl of medium containing 20 % newborn bovine serum was added into the bottom chambers as the chemotactic factor. After incubation for 24 h (for migration assay) or 48 h (for invasion assay) at 37 °C in 5 % CO2, cells remaining on the upper surface of the filter were removed using cotton swabs. Then the migrated cells were fixed using methyl alcohol and stained using 0.1 % crystal violet. Migratory (or invasive) cells were counted and averaged from images of five random fields (original magnification × 200) captured using an inverted light microscope. The mean values of three duplicate assays were used for statistical analysis.
DNA bisulfite modification and methylation-specific PCR (MSP)
Cells treated by 10 ng/ml TGF-β1 for 48 h in 24-well plates were resuspended with cold PBS for ~6 × 106/ml. DNA bisulfite modification and purification were performed using an EZ DNA methylation-Direct kit (Zymo Research Corporation, Irvine, California, USA) according to the instruction. Concentration of DNA was evaluated by absorbance at 260 nm on a UV spectrophotometer (BioRad Inc., Hercules, CA, USA). The set of primers for miR-30d gene was flanking the 3 kb region of the 5′ upstream region from the start of pre-miR-30d sequence. The primers for methylation-specific PCR were designed by MethPrimer and the sequences were as follows: methylated (M)-forward (F): 5′-TTGAGATAGGGTTTTATTTTGTCGT-3′; methylated (M)-reverse (R): 5′-TAATACATACGATCCCAACTATTCG-3′;unmethylated (U)- forward (F): 5′-TGAGATAGGGTTTTATTTTGTTGT-3′; unmethylated (U)- reverse (R): 5′-ATACATACAATCCCAACTATTCAAA-3′. DNA amplification was performed with Epi Taq HS (Takara Biotechnology Co. Ltd., Dalian, China) under the following condition: 94 °C for 5 min; 30 cycles of 94 °C for 30 s, 50 °C for 30 s, 72 °C for 30 s; and 72 °C for 10 min. The PCR products were separated by 2.0 % agarose gel electrophoresis and visualized by a chemiluminescence imaging system (Bio-Rad, Richmond, CA, USA).
Immunohistochemistry
Human ovarian cancer tissue microarray was purchased from Shanghai SuperChip Biotech Co. Ltd. (Shanghai, China) and rabbit antibody to TET3 used for immunohistochemistry was purchased from Genetex (Alton PkwyIrvine, CA, USA). The tissue array was dewaxed in xylene, rehydrated in a descending alcohol series. Antigen retrieval was performed by heating the tissue section in 0.01 M citrate buffer (pH 6.0) in a steamer for 90 s. Detection of antigen was carried out through incubation with anti-TET3 antibody (1:250) for 2 h at room temperature, followed by incubation with HRP-labeled secondary antibody at room temperature for 30 min. Signal was generated by incubation with DAB. Slide was counterstained with hematoxylin, dehydrated in an ascending alcohol series, and mounted for analysis. Digital images were acquired using a section microscope scanner (Leica MP SCN400, German). Membrane, cytoplasm or nuclear staining was considered positive for TET3. For statistical analysis, extent (the percentage of positive cells) and intensity of staining were obtained by 2 pathologists. Intensity was semiquantitatively scored as weak (1 point), moderate (2 points), or strong (3 points). For an individual case, the immunohistochemical composite score was calculated based on the extent multiplied by the intensity score.
Statistical analysis
The graphical presentations were performed using GraphPad Prism 5.0. Data were presented as the means ± SD and were analyzed using SPSS 22.0 software (Chicago, IL, USA). Statistical differences were tested by Chi-square test, two-tailed t-test, one-way ANOVA test or Fisher’s Exact test. Differences were considered significant at P <0.05 (*) or highly significant at P <0.001 (**).
Discussion
With the deepening of studies about epigenetics and tumorigenesis, it has been admitted that abnormal DNA methylation/demethylation is a hallmark of cancer [
21]. In addition to DNMTs, TETs are novel regulators of DNA methylation/demethylation status. Growing evidences suggest that deregulation of TETs and TET-mediated DNA demethylation takes part in tumor development and progression [
14,
22‐
25].
In our study, we found that TET3 was decreased in ovarian cancer tissues, as well as in TGF-β1-treated ovarian cancer cells. Loss of TET3 might result in poorer histopathological grade in ovarian cancer patients. It was reported that TET3 was reduced in TGF-β1-activated human hepatic stellate cells (LX-2 cells), which played a critical role in liver fibrosis. Silencing of TET3 inhibited apoptosis, promoted proliferation and induced cell fibrosis in LX-2 cells by downregulating long non-coding RNA (lncRNA) HIF1A-AS1 [
26]. In our experiments, TGF-β1 reduced TET3 in human ovarian cancer cells, and TET3 overexpression blocked TGF-β1-induced EMT via resuming the demethylation status of pre-miR-30d promoter region. As fibrosis was also closely connected to EMT, we speculated that TET3 could be a suppressor of EMT functioning in different tissues and EMT-associated events. In both studies, TET1 and TET2 remained almost unchanged during TGF-β1 stimulation. It might be attributed to tissue or cell specificity. Preview studies indicated that TET1 and TET2 mainly acted in embryonic stem cells (ESCs), induced pluripotent stem cells (iPSCs) and primordial germ cells (PGCs) [
27‐
29], while TET3 was the only member identified in mouse oocytes and one-cell zygotes [
30]. Although the expression pattern of TETs changed during development, differences still existed in diverse tissues and cells.
Our findings indicated that reduction of TET3 could be a result of TGF-β1 stimulation. To date, it was unclear how TGF-β1 decreased TET3. Recent studies showed that TETs were direct targets of multiple microRNAs (miRs), suggesting the proteins to be post-transcriptionally regulated by miRs [
31]. miR-26, implicated in various cancers as an oncogene or tumor suppressor [
32,
33], could decrease expression of all members of the TET family in vertebrates [
34]. Another example was miR-29 that directly targeted TET1 in lung cancer cells [
35], and all TET family members in human dermal fibroblasts and vascular smooth muscle cells [
36]. Interestingly, miR-29 was a critical mediator in TGF-β/Smad signaling [
37]. Thus, we presumed that TET3 reduction in our model could be a result of miR dysregulation. Nevertheless, TET3 could be also controlled by DNA methylation/demethylation, as found in clinical samples [
15]. Illumination of the molecular underpinnings of TGF-β-induced TET3 reduction would contribute to understanding the regulatory network in TGF-β-stimulated EMT.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
ZY and JL performed cell culture and western blot. XH and LW did methylation-specific PCR. HH and HC performed immunohistochemistry. XZ and JL performed qRT-PCR. XL, WC and LZ were involved in the experimental design and data analysis. ZY and LZ wrote the manuscript. All authors read and approved the final manuscript.