Background
Ovarian cancer (OvCa), one of the most common gynecological malignancies in women worldwide [
1], has a high incidence and high mortality rate and is especially difficult to discover during the early stages. This difficulty to discover at the early stages is due to an absence of specific signs or symptoms, as well as a lack of effective or sensitive clinical screening methods for early OvCa [
2]. A high rate of recurrence and poor prognosis due to the metastasis of this devastating disease are common and serious problems to be conquered in OvCa [
3]. High-grade serous ovarian cancer, the most prevalent type of OvCa, is an aggressive disease with a high rate of relapse and metastasis into the abdominal cavity at later stages [
4]. Therefore, more extensive research and a better understanding of the molecular changes that induce the metastasis of tumor cells in serous OvCa is urgently needed.
A growing body of evidence has reported that epithelial-mesenchymal transition (EMT) plays a critical role in cancer cell metastatic dissemination events by endowing cancer cells with a more motile and invasive phenotype [
5‐
7]. Emerging evidence suggests that the acquisition of invasive properties by OvCa cells is accompanied by a loss of epithelial features and a gain of mesenchymal features [
7]. In addition to the transforming growth factor-β signaling pathway (TGF-β), which is a major inducer of EMT, the activation of several transcription factors including ZEB1, ZEB2, SNAI1, SNAI2, TWIST1 and TWIST2, either directly or indirectly repress the E-cadherin (CDH1) promoter. Loss of CDH1 expression is considered to be a typical hallmark of EMT [
8], however, the molecular events that drive the EMT process during OvCa progression are largely unknown [
9].
To date, a large set of non-coding RNAs (ncRNAs) have been recognized as controlling almost every level of gene expression and pathway activation, including the activation and repression of the EMT process [
6,
10]. Among them, a surprisingly prominent layer of regulatory macro ncRNAs, long non-coding RNAs (lncRNAs), have been implicated in various types of gene regulation including epigenetic, transcription or post-transcriptional regulation, which contribute to the development of carcinoma and other diseases [
11]. Furthermore, accumulating evidence has shown that lncRNAs play a critical role in tumor occurrence, invasion, metastasis and drug resistance by acting as a competitive RNA (ceRNA) for microRNAs (miRNAs) [
12,
13]. For example, H19 acts as a molecular sponge for the let-7 family, which are well-characterized tumor suppressors [
14‐
16]. This decrease in let-7 leads to the increased expression of a let-7 target called LIN28, which eventually promotes breast cancer stem cell maintenance [
17]. LncRNA ABHD11-AS
1 promoted ovarian cancer cell proliferation, invasion and metastasis, and inhibited ovarian cancer cell apoptosis by targeting RhoC and its downstream molecules [
18]. Li et al. found that lncRNA XIST promoted EMT by regulating ZEB2 via acting as a ceRNA of miR-367/141 in non-small-cell lung cancer [
19]
. However, the role and mechanism of lncRNAs in EMT and their influences on cell invasion and metastasis in OvCa, are still not well understood.
In the present study, we constructed a ceRNA regulatory network for mesenchymal OvCa and identified a lncRNA AP000695.4, which we named pro-transition associated RNA (PTAR), which is up-regulated in mesenchymal OvCa samples. In addition, we found that PTAR down-regulation inhibits OvCa metastasis by up-regulating miR-101, a potential tumor suppressor in OvCa. In conclusion, we hypothesized that PTAR may serve as a competing, endogenous lncRNA by sponging miR-101, which mediates its role in both TGF-β-induced EMT and the invasion-metastasis cascade of OvCa.
Methods
Data set
The level 3 gene expression profile and miRNA expression profile for OvCa were downloaded from TCGA (
http://gdac.broadinstitute.org/runs/stddata__2016_01_28/data/OV/20160128//), which had integrated epithelial (iE) and integrated mesenchymal (iM) subtype labels [
20]. The processed, sequenced, expression profiles of lncRNAs in the TCGA OvCa dataset were obtained in The Atlas of Non-coding RNAs in Cancer (TANRIC) database [
21]. The miRNA-mRNA interactions and miRNA-lncRNA interactions were collected from the database at
http://www.medsysbio.org/EMTRegulome, which systematically collects the regulations among transcription factors, miRNA, lncRNA and EMT genes and records diverse regulatory motifs involved in the EMT process.
Identification of ceRNAs involved in mesenchymal OvCa
T tests were performed to detect differentially expressed (DE) genes, lncRNAs and miRNAs in the iM subtype compared with the iE subtype of OvCa. The
P values were corrected using the Benjamini-Hochberg method. The Pearson’s correlation test was used to calculate the correlation between the expression of DE miRNAs and DE lncRNAs or DE genes. A hypergeometric distribution model was used to test whether the DE EMT genes shared a significant number of miRNA binding sites with DE lncRNAs. The mesenchymal-related ceRNAs were selected according to the following criteria: (1) The EMT coding-genes, lncRNAs and miRNAs were significantly, differentially expressed in iM OvCa samples compared with iE OvCa samples under the constraint of a false discovery rate (FDR) < 0.1. (2) The expression of DE EMT coding-genes (lncRNAs) and DE miRNAs were significantly correlated (
P < 0.05, Pearson’s correlation test) in iM OvCa samples, while not correlated in iE OvCa samples. The ceRNA network was presented using the Cytoscape web tool (
http://js.cytoscape.org). All analyses were performed in R 3.2.3 (
https://www.r-project.org/).
Cell culture and treatment
The human ovarian cancer cell lines SKOV3, A2780 and OVCAR3 were obtained from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China). The SKOV3 and OVCAR3 cells were cultured in RPMI-1640 medium (Biological Industries, Kibbutz Beit-Haemek, Israel), and A2780 cells were cultured with DMEM (Biological Industries, Kibbutz Beit-Haemek, Israel). All the cells were supplemented with 10% fetal bovine serum (FBS, Biological Industries, Kibbutz Beit-Haemek, Israel), 1% penicillin/streptomycin (Beyotime, Jiangsu, China) and incubated at 37 °C with 5% CO2.
Plasmid construct and transfection
For PTAR overexpression, the full-length PTAR cDNA was amplified and subcloned into pcDNA3.1. An empty vector was used as a negative control. Three shRNAs targeting PTAR were synthesized for PTAR knockdown, and a scrambled shRNA was synthesized for the negative control. All plasmids were isolated using AxyPrep DNA Miniprep Kit (Axygen, Scientific, Union City, CA, USA). A hsa-miR-101 mimic was used in place of miR-101, a chemically modified antisense oligonucleotide (antagomir AMO-101) was used to inhibit miR-101 expression, and a scrambled oligonucleotide (GenePharma) was used as a control. The hsa-miR-101 mimic, inhibitor and stable negative control were purchased from GenePharm (Shanghai, China). For transfection, cells were cultured in six-well plates until 70% confluence. The plasmids were then transfected using Lipofectamine 2000 (Thermo Fisher Scientific, Waltham, MA, USA) based on the manufacturer’s instructions. Six hours after transfection, hsa-miR-101 mimics/inhibitors were added to the cells and incubated for 48 h.
Wound healing assay
The cells were cultured in six-well plates (Nest, Biotechnology, Jiangsu, China) overnight. The cells monolayers were wounded by scratching with plastic 10-μl micropipette tips and washed 2 times with PBS. Fresh growth medium with no FBS was added to the plates. Subsequently, the cells were transfected as described above for 48 h. Images of the different stages of wound healing were photographed via microscopy at 0, 24 and 48 h. Relative cell motility was quantified using Image-Pro Plus.
Transwell migration and invasion
Cells were seeded in the upper chamber of transwell plates (Corning, NY, USA) with serum-free medium. Ten percent FBS medium was added to the lower chamber of the transwell. Next, cells were transfected as described above for 48 h. For the invasion experiments, the upper chamber was covered with RPIM-1640 and matrigel (BD Biosciences, San Jose, CA) mixture. Finally, cells on the top of the chamber were removed with cotton swabs, while cells that went through the membrane were stained with 0.5% crystal violet (Sigma-Aldrich, St. Louis, MO) observed and counted under a microscope at 100 x magnification.
Real-time quantitative reverse transcription PCR (qRT-PCR)
Total RNA was extracted from tumor tissues that were collected from nude mice and SKOV3/A2780 cells using a Trizol reagent (Thermo Fisher Scientific). The cDNA was synthesized using a cDNA Reverse Transcription Kit (Applied Biological Materials Inc., Canada). The expression levels of mRNAs and miRNAs were quantified using a 7500 Fast Real-Time PCR System with a SYBR green PCR Master Mix. The relative mRNA levels were determined using the comparative Ct method with GAPDH or U6 as the reference gene, and the formula 2-ΔΔCt.
Western blot analysis
For western blot analysis, total protein samples were extracted from SKOV3, A2780 or OVCAR3 cells and tumor tissues collected from nude mice using RIPA lysis buffer with a protease inhibitor (Beyotime, Jiangsu, China). An equal amount of protein (60 μg/lane) was loaded on 8% SDS-polyacrylamide gels and then transferred to a Pure Nitrocellulose Blotting membrane (Pall Life Science, AZ, USA). Next, the membrane was blocked in 5% non-fat milk for 1.5 h and then probed with primary antibodies against ZEB1 (1:1000, Abcam, Cambridge, USA), E-cadherin (1:500, Proteintech, Rosemont, IL, USA), vimentin (1:1000, Cell Signaling Technology, Beverly, MA), fibronectin 1 (FN1, 1:500, Proteintech, Rosemont, IL, USA), and GAPDH (1:2000, Kangchen, Shanghai, China) overnight at 4 °C. Then, the membranes were incubated with anti-mouse or anti-rabbit secondary antibodies (1:8000; LI-COR Biosciences). Finally, immunoreactivity was detected using the Odyssey Infrared Imaging System (Gene Company Limited, Hong Kong, China).
Lentiviral vector construct and tumor xenografts in mice
The lentiviral constructs of PTAR shRNA were constructed by Biowit Technology (Shenzhen, China). The nude mice were infected with the constructed lentiviral vectors at day 7 following tumor xenografts. 106 SKOV3 cells were injected into 4-week old, female, athymic BALB/c nude mice which were obtained from SLRC Laboratory Animals (Shanghai, China), intraperitoneally. The nude mice were housed under specific pathogen-free conditions and sacrificed after 28 days. Then, the xenograft tumor tissues were harvested, weighed, formalin-fixed and paraffin-embedded for subsequent immunohistochemical staining. The remaining tumor tissues were stored in a − 80 °C refrigerator for analysis of protein and RNA levels. The procedures were in accordance with the regulations of the Ethics Committee of Harbin Medical University and the Guide for the Care and Use of Laboratory Animals published by the US National Institutes of Health (NIH Publication No. 85–23, 2011).
Immunohistochemistry (IHC) analysis
Cancer tissue sections were de-paraffinized in a xylene series and rehydrated through a series of descending ethanol concentrations. After washing with double-distilled H2O, the sections were treated with 3% H2O2 in methanol for 30 min and blocked with normal goat serum for 1 h. Then, the sections were incubated with anti-E-cadherin (Proteintech, Wuhan, China), anti-FN1 (Proteintech, Wuhan, China), anti-ZEB1 (Abcam, USA), and anti-vimentin (Cell Signaling Technology, MA) overnight at 4 °C and then washed in PBS and incubated with secondary antibodies for 30 min at room temperature. Next, the sections were stained with a DAB staining solution and counterstained with hematoxylin for 2 min. Images were taken under an Olympus IX73 microscope (Olympus, Valley, PA).
Statistical analysis
All data were expressed as the mean ± SEM. Statistical analyses were performed using Student’s t-test for two group comparisons. One-way analysis of variance ANOVA followed by Dunnett’s post hoc test were used for multiple comparisons. GraphPad Prism 5.0 was used for statistical analyses. A value P < 0.05 was considered statistically significant.
Discussion
In the current study, we showed that the lncRNA PTAR is a key regulator of EMT and promotes the OvCa invasion-metastasis cascade. We determined this using evidence from systems-based miRNA, lncRNA and mRNA analyses of large-scale OvCa data sets, along with in vivo (nude mice) and in vitro (cell lines) experiments. The up-regulation of PTAR led to an elevated expression of ZEB1, which is a transcriptional repressor of E-cadherin, by competitively binding to miR-101. This binding of PTAR to miR-101 resulted in the promotion of OvCa cell EMT and invasion. We demonstrated that miR-101 inhibits the mesenchymal phenotype, as well as the TGF-β1-induced EMT, at least in part, via directly targeting ZEB1. We established the importance of PTAR-miR-101-ZEB1 in the EMT process by showing a positive correlation between PTAR and ZEB1 expression and inverse correlations between miR-101 and PTAR expression and miR-101 and ZEB1 expression in iM OvCa samples (Fig.
7f). Our findings not only suggest an important role of lncRNAs acting as miRNA sponges during the regulation of EMT progression in OvCa but also highlight the potential of lncRNA PTAR to act as a target for EMT inhibition in OvCa.
To date, a variety of miRNAs have been reported to be involved in the pathogenesis of ovarian carcinoma [
24‐
26]. Yang et al. reported that miR-506 targeted the regulation of SNA12, which led to the inhibition of tumor growth by promoting E-cadherin expression [
20]. In addition, colleagues from their labs also found that high expression of miR-506 was associated with longer progression-free periods and overall survival. miR-506 could also be a potential marker for patients’ response to chemotherapy in serous ovarian cancers [
27]. In a previous study, miR-101 had been shown to suppress EMT by targeting ZEB1 and ZEB2 in ovarian carcinoma [
23]. Consistently, we also confirmed a tumor suppressing function of miR-101, as indicated by reduced EMT progression, cell invasion and metastatic ability. However, the up-stream regulators for the dysregulation of these miRNAs in OvCa are not well understood.
Increasingly more studies have reported that interactions between lncRNAs and miRNAs play a critical role in cancer progression and metastasis. For instance, in colorectal cancer, lncRNA UICLM acts as a ceRNA for miR-215 to regulate ZEB2 expression and promote colorectal cancer metastasis [
28]. lncRNA-PAGBC promotes tumor growth and metastasis of gallbladder cancer cells by competitively binding to the tumor suppressive microRNAs, miR-133b and miR-511 [
29]. Long non-coding RNA linc00673 regulated non-small cell lung cancer proliferation, migration, invasion and epithelial mesenchymal transition by inhibiting miR-150-5p and modulate ZEB1 expression [
30]. In a recent study, MALAT1 was found to compete with endogenous RNA to regulate ZEB2 expression by sponging with miR-200 s in kidney carcinoma [
31]. In the current study, we tried to examine the role and mechanism of lncRNAs in OvCa metastasis by constructing a ceRNA network for mesenchymal OvCa. Here, through bioinformatics analysis, we identified an inverse relationship between miR-101 and PTAR expression levels in ovarian cancer tissues and cell lines. Additionally, dual-luciferase reporter assays confirmed the interaction between miR-101 and PTAR. Therefore, we hypothesized that miR-101 is at least partially required for PTAR’s oncogenic effects. As expected, functional studies verified that PTAR promoted EMT and migration of OvCa cells, which was blocked by miR-101 application. Moreover, PTAR knockdown attenuated TGF-β1-induced EMT and metastasis, while an miR-101 inhibitor reversed this effect. Surprisingly, a positive relationship between PTAR and ZEB1 was observed in high-throughput data sets, and it was concluded that PTAR could regulate ZEB1 expression via the modulation of miR-101.
Notably, we also revealed another key ceRNA relationship, which is the lncRNA AC004988.1 and FN1. Both AC004988.1 and FN1 have binding sites with miR-101 and showed a negative correlation of expression levels in TCGA data sets. These results indicate that miR-101 regulates the EMT process not only by targeting ZEB1, but also FN1. Other lncRNAs, such as lncRNA AC004988.1, but not lncRNA PTAR, may also act as sponges for miR-101. Thus, the newly identified AC004988.1-miR-101-FN1 axis may have a potential role in the iM subtype of OvCa, which warrants additional detailed studies.