- Open Access
TET3 inhibits TGF-β1-induced epithelial-mesenchymal transition by demethylating miR-30d precursor gene in ovarian cancer cells
© Ye et al. 2016
- Received: 1 February 2016
- Accepted: 28 April 2016
- Published: 4 May 2016
Abnormal DNA methylation/demethylation is recognized as a hallmark of cancer. TET (ten-eleven translocation) family members are novel DNA demethylation related proteins that dysregulate in multiple malignances. However, their effects on ovarian cancer remain to be elucidated.
The changes of TET family members during TGF-β1-induced epithelial-mesenchymal transition (EMT) in SKOV3 and 3AO ovarian cancer cells were detected. TET3 was ectopically expressed in TGF-β1-treated ovarian cancer cells to examine its effect on TGF-β1-induced EMT phenotype. The downstream target of TET3 was further identified. Finally, the relationships of TET3 expression to clinic-pathological parameters of ovarian cancer were investigated with a tissue microarray using immunohistochemistry.
TET3 was downregulated during TGF-β1-initiatd epithelial-mesenchymal transition (EMT) in SKOV3 and 3AO ovarian cancer cells. Overexpression of TET3 reversed TGF-β1-induced EMT phenotypes including the expression pattern of molecular markers (E-cadherin, Vimentin, N-cadherin, Snail) and migratory and invasive capabilities of ovarian cancer cells. miR-30d was identified as a downstream target of TET3, and TET3 overexpression resumed the demethylation status in the promoter region of miR-30d precursor gene, resulting in restoration of miR-30d (an EMT suppressor of ovarian cancer cells proven in our previous study) level in TGF-β1-induced EMT. We further found that TET3 expression was decreased in ovarian cancer tissues, especially in serous ovarian cancers. The overall positivity of TET3 was inversely correlated with the grade of differentiation status of ovarian cancer.
Our results revealed that TET3 acted as a suppressor of ovarian cancer by demethylating miR-30d precursor gene promoter to block TGF-β1-induced EMT.
- Ovarian cancer
- Epithelial-mesenchymal transition
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 . 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 . 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 . 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 , hepatocellular carcinoma , melanoma  and glioma . For example, decreased TET1 mRNA level is correlated with poor survival of breast cancer patients , and the same goes for TET2 in colorectal cancer .
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 . 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.
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)
Primer sequences for real-time PCR
primer sequences (5′-3′)
Length of PCR product (bp)
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).
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.
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 (**).
TET3 was reduced in TGF-β1-treated ovarian cancer cells
TET3 overexpression reversed TGF-β1-triggered EMT in ovarian cancer cells
TET3 upregulated miR-30d to inhibit TGF-β1-induced EMT in ovarian cancer cells
TET3 was decreased in ovarian cancer tissues and negatively correlated with pathological grade
Positivity and composite scores of TET3 in ovarian cancer tissues
Immunohistochemical composite scores
Subtypes of ovarian cancer
Normal (n = 14)
12 (85.7 %)
Ca (n = 68)
52 (76.5 %)
Serous cancer (n = 37)
29 (78.4 %)
Mucinous cancer (n = 8)
8 (100 %)
Endometrioid cancer (n = 5)
4 (80 %)
Clear cell cancer (n = 5)
5 (100 %)
Germ cell tumor
Dysgerminomas (n = 3)
1 (33.3 %)
Endodermal sinus tumor (n = 1)
Immaure teratomas (n = 2)
1 (50.0 %)
Granulosa cell tumor (n = 3)
2 (66.7 %)
Clinicopathological correlation of TET3 to ovarian cancer
Immunohistochemical composite scores
Clinicopathological parameters of ovarian cancer
< 50 (n = 25)
17 (68 %)
≥ 50 (n = 39)
31 (78.5 %)
NA (n = 4)
G1 (n = 7)
7 (100 %)
G2 (n = 26)
23 (88.5 %)
G3 (n = 29)
18 (62.1 %)
With the deepening of studies about epigenetics and tumorigenesis, it has been admitted that abnormal DNA methylation/demethylation is a hallmark of cancer . 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 . 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 . 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 . 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 . Another example was miR-29 that directly targeted TET1 in lung cancer cells , and all TET family members in human dermal fibroblasts and vascular smooth muscle cells . Interestingly, miR-29 was a critical mediator in TGF-β/Smad signaling . 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 . Illumination of the molecular underpinnings of TGF-β-induced TET3 reduction would contribute to understanding the regulatory network in TGF-β-stimulated EMT.
Our results indicated that TET3 declined in TGF-β1 stimulation and TET3 overexpression inhibited TGF-β1-induced EMT and EMT-mediated metastasis of SKOV3 and 3AO cells by demethylating miR-30d precursor gene, indicating a novel mechanism of epigenetic regulation in ovarian cancer. Targeting the TGF-β1-TET3-miR-30d signaling axis might be a promising therapeutic strategy for ovarian cancer treatment.
This work was financially supported by the National Natural Science Foundation of China (No.30973429).
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