Long non‑coding RNA MEG3 suppresses epithelial‑to‑mesenchymal transition by inhibiting the PSAT1‑dependent GSK‑3β/Snail signaling pathway in esophageal squamous cell carcinoma
- Authors:
- Published online on: September 7, 2020 https://doi.org/10.3892/or.2020.7754
- Pages: 2130-2142
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Copyright: © Li et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
Abstract
Introduction
Esophageal cancer (EC) is a particularly aggressive malignancy with a high mortality rate, which is the ninth most commonly diagnosed type of cancer and the sixth leading cause of cancer-related mortality worldwide (1). There are two types of EC, namely esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma. In China and other East Asian countries, up to 90% of cases are ESCCs (2). Shantou, in particular, is a high-risk area for ESCC. Due to the lack of early signs or symptoms in ESCC, endoscopic screening in the asymptomatic population is inadequate, and early diagnosis of ESCC is difficult. In the majority of the cases, at the time of endoscopy, the disease has already progressed to an advanced stage. Despite numerous advances over the last several decades, the prognosis of this disease remains poor, with a 5-year survival rate of <40% (3,4). Thus, it is urgent to explore the key protein-signaling networks and relative molecular regulatory mechanisms of ESCC.
Previous evidence indicates that the process of epithelial-to-mesenchymal transition (EMT) is a cellular switch from epithelial to mesenchymal cell properties, which promotes cancer progression (5,6). EMT often occurs at the early stages of tumor metastasis, and involves a disassembly of cell-cell junctions and enhancement of cell motility, accompanied by decreased expression of classic epithelial markers (E-cadherin and β-catenin) and increased expression of mesenchymal markers [N-cadherin, glycogen synthase kinase (GSK)-3β, vimentin and Snail] (7,8).
Recent studies have revealed that lncRNAs play key roles in the carcinogenesis and development of various types of cancer. The lncRNA maternally expressed gene 3 (MEG3) is widely expressed in a variety of normal tissues. MEG3 has been identified as a tumor suppressor and is expressed at lower levels in diverse types of cancer (9–13). However, whether MEG3 is involved in the EMT process of ESCC remains elusive.
The aim of the present study was to determine the expression levels of MEG3 in ESCC tissues and cells, and analyze its clinical significance. A recombinant lentiviral vector expressing MEG3 (Lv-MEG3) was constructed. Microarray technology and bioinformatics analysis were employed to study the differentially expressed genes (DEGs) between the two groups. Based on functional annotation results, the underlying target genes and the effects of ectopic expression of MEG3 on cell growth, migration, invasion and EMT were assessed in vitro and in vivo.
Materials and methods
Patients and human esophageal tissue specimens
A total of 43 cases of ESCC, which had been clinically and histologically diagnosed between 2011 and 2016, were included in the present study. The cohort comprised 25 men and 18 women (median age, 57.41 years; range, 36–75 years). Lymph node metastasis was detected in 28 cases, and 19 patients were diagnosed with grade I or II ESCC. None of the patients underwent radiotherapy or chemotherapy prior to surgery. Tumor masses and adjacent normal tissues, which were located ≥5.0 cm distal to the tumor margins, were divided into two parts. One part was snap-frozen in liquid nitrogen for reverse transcription-quantitative PCR (RT-qPCR) assay, and the other part was fixed in formalin and embedded in paraffin for immunohistochemistry assay. Written informed consent was obtained from each patient and all the procedures were approved by the Second Affiliated Hospital Ethics Committee of Shantou University Medical College (Shantou, China).
Cell culture
ESCC cell lines (EC109, EC-9706 and KYSE-450) and the normal esophageal epithelial cell line Het-1A were obtained from the Institute of Biochemistry and Cell Biology of the Chinese Academy of Sciences. Cells were cultured in DMEM supplemented with 10% (v/v) FBS (Invitrogen; Thermo Fisher Scientific, Inc.), 100 U/ml penicillin and 100 mg/ml streptomycin at 37°C in 5% CO2.
Plasmid constructs and lentivirus-mediated MEG3 overexpression in ESCC cells
To construct the MEG3 overexpression lentiviral vector, the full-length coding sequence of the MEG3 gene (GenBank ID: NR_002766) was amplified by PCR and then cloned into the BamHI/EcoRI sites of the pLenti-EF1a-EGFP-F2A-Puro-CMV-MEG3 vector (Obio Technology) using the following primers: Forward, 5′-CGCAAATGGGCGGTAGGCGTG-3′ and reverse, 5′-CATAGCGTAAAAGGAGCAACA-3′. The recombinant eukaryotic expression vector was constructed and confirmed by DNA sequencing, enzymatic digestion and PCR identification. For the production of viral particles, the lentivirus-mediated MEG3 packaging system containing MEG3 was co-transfected with packaging vectors (pLP1 and pLP2) and envelope vector (pLP/VSVG) into 293T cells with OGTR20131002 Transfection Reagent (Obio Technology) according to the manufacturer's instructions. After the recombinant lentiviral vector expressing MEG3 (Lv-MEG3) and the negative control (NC) empty vector (Lv-NC) were constructed, packaging, purification and titer determination were conducted in 293T cells, as described in our previous study (14).
Microarray analysis
EC109 cells were transfected with Lv-MEG3 or Lv-NC. Total RNA was extracted from Lv-MEG3 or Lv-NC cells using TRIzol® RNA isolation reagent (Invitrogen; Thermo Fisher Scientific, Inc.) according to the manufacturer's protocol. The gene expression profiles were performed based on the Affymetrix PrimeView™ Human Gene Expression Array (Affymetrix; Thermo Fisher Scientific, Inc.). Gene expression analysis was performed using GeneSpring software (version 14.8; Agilent Technologies, Inc.), and the data were shown by volcano plots. Cluster, Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted using online tools (http://www.shbio.com/customer.php) to determine the DEGs. P-value and false discovery rate (FDR) were used to define the threshold of significance, and the figures were generated by R language. DEGs were identified by paired test [fold-change (FC) ≥2.0 or ≤0.5, P<0.05 and FDR<0.05]. The microarray data were uploaded in the National Center for Biotechnology Information Gene Expression Omnibus (GEO) database; GEO accession no., GSE142036 (https://www.ncbi.nlm.nih.Gov/geo/query/acc.cgi?acc=GSE142036).
Construction of a protein-protein interaction (PPI) network
The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING; version 10.0; http://string-db.org) was employed to identify the interaction pairs of the overlapped target genes. The predicted and acknowledged interactions were unified and scored. Genes with a connectivity degree of ≥5.0 were considered as hub genes. Interaction pairs in the PPI network were selected when the combined score was >0.4.
Fluorescence in situ hybridization (FISH) and subcellular fractionation analysis
EC109 cells were transfected with Lv-MEG3 or Lv-NC, and immunofluorescence assays were performed as described previously (15). Digoxigenin-labeled MEG3 and FISH Kit (Exon Lab) were used following the manufacturer's instructions. MEG3 was visualized using HRP anti-digoxigenin-antibody (1:50; cat. no. ab6212; Abcam) at room temperature for 1 h, and tyramide signal amplification-FITC technology was used. EC109 cells were co-stained with DAPI and finally observed under a fluorescence microscope at a magnification of ×1,000 (Nikon80i; Nikon Corporation). RNA was isolated as nuclear and cytoplasmic fractions in EC109 cells using the RNA Subcellular Isolation Kit (Norgen Biotek Corp.) according to the manufacturer's guidelines. Cytoplasmic and nuclear fractions were analyzed by RT-qPCR.
Cell proliferation assay
Cell proliferation was analyzed with the Cell Counting Kit-8 (CCK-8) assay (Beyotime Institute of Biotechnology) according to the manufacturer's protocol. A total of 4,000 cells were seeded in triplicate in 96-well plates and transfected with Lv-MEG3 or Lv-NC plasmids for the indicated times. Cell viability was assessed by measuring the absorbance at 450 nm using the FilterMax F5 microplate reader (Molecular Devices, LLC).
Cell cycle analysis
After transfection for 48 h, EC109 cells (1×105 cells/ml) were harvested, washed with ice-cold PBS and fixed with 70% ethanol at 4°C overnight. After fixation, the cells were washed, resuspended in PBS, incubated with ribonuclease at 37°C for 30 min and stained with propidium iodide (Nanjing KeyGen Biotech Co., Ltd.) in the dark at 4°C for 30 min. Then, the cell cycle distribution was analyzed with a flow cytometer (BD Biosciences).
RT-qPCR analysis
Total RNA was extracted from freshly frozen ESCC tissues or transfected cells according to the instructions of the TRIzol® kit (Invitrogen; Thermo Fisher Scientific, Inc.). Subsequently, RT-qPCR was performed with a Step-One Plus Real-Time PCR System (Applied Biosystems; Thermo Fisher Scientific, Inc.) using the SYBR Green PCR Master Mix (Promega Corporation). The thermal cycling conditions were as follows: 95°C for 10 min, 95°C for 15 sec, and 58°C for 30 sec for 40 cycles. GAPDH was employed as an endogenous control. All the primer sequences used in this study are listed in the Table I. The relative expression level of mRNAs was calculated by the 2−∆∆Cq method as described in our previous study (16).
Cell invasion assay
After transfection for 48 h, EC109 cells were seeded in a 6-well plate for 48 h and resuspended in serum-free DMEM at a cell density of 3×105 cells/ml. Then, 200 µl cell suspension was added to the apical chamber, while 500 µl DMEM containing 10% FBS was added to the basolateral chamber, and incubated at 37°C in the presence of 5% CO2. After 24 h, the invading cells were fixed at 4°C with methanol for 10 min, washed with PBS 3 times and stained at room temperature with 0.1% crystal violet solution for 10 min. A neutral resin was applied to seal the cells in the apical chamber, and 6 randomly selected fields were observed with an inverted microscope (Axiovert 40 CFL, Carl Zeiss AG) microscope at a magnification of ×100.
Wound healing assay
After transfection with Lv-MEG3 or Lv-NC for 48 h, EC109 cells (1×106 cells/ml) were added to a 6-well plate and incubated for 24 h. After the cells had reached 90–100% confluence, a sterile 1-ml pipette tip was used to create a linear scratch in the cell monolayer. After culturing with FBS-free medium at 37°C for different durations, the cells that migrated to the wounded area were visualized and images were captured with an Axiovert 40 CFL fluorescence microscope (Carl Zeiss AG) at 0, 24, 36 and 48 h. The rate of wound closure was measured using ImageJ software (version 1.46; National Institutes of Health).
Protein extraction and western blotting
EC109 cells transfected with Lv-MEG3 or Lv-NC were harvested at 48 h and washed with ice-cold PBS 3 times. The cell lysates were prepared with RIPA buffer (Beyotime Institute of Biotechnology) containing PMSF. Equal quantities of proteins (50 µg) were separated by 10% SDS-PAGE and transferred to PVDF membranes. After being blocked with 5% non-fat milk for 60 min at room temperature, the membranes were incubated with specific primary antibodies against PSAT1 (1:1,000; cat. no. GTX82102; GeneTex, Inc.), cyclin D1 (CCND1; 1:1,000; cat. no. sc-8396; Santa Cruz Biotechnology, Inc.), phosphorylated (p)-GSK-3β (1:500; cat. no. ab75745; Abcam), GSK-3β (1:500; cat. no. ab32391; Abcam), E-cadherin (1:1,000; cat. no. sc-21791; Santa Cruz Biotechnology, Inc.), Snail (1:1,000; cat. no. sc-271977; Santa Cruz Biotechnology, Inc.), vascular endothelial growth factor (VEGF)A (1:1,000; cat. no. Ag13500; ProteinTech Group, Inc.), vimentin (1:5,000; cat. no. GTX100619; GeneTex, Inc.), β-actin (1:500; cat. no. ab8226; Abcam) or GAPDH (1:5,000; cat. no. sc-166574; Santa Cruz Biotechnology, Inc.) as an internal control in TBS-0.5% Tween-20 (TBST) at 4°C overnight. On the following day, the membranes were washed with TBST 3 times and incubated by anti-rabbit horseradish peroxidase-conjugated secondary antibody (1:10,000; cat. no. sc-2004; Santa Cruz Biotechnology, Inc.) at room temperature in the dark for 60 min. The expression of proteins was measured with the Odyssey Detection System (LI-COR Biosciences) and analyzed using ImageJ software, version 1.46r (National Institutes of Health).
In vivo tumorigenesis assay
The animal protocols in the present study were approved by the Ethics Committee of Shantou University Medical College. A total of 19 male BALB/c nude mice (class SPF, purchased from Beijing Animal Center), aged 6-weeks and weighing 18–24 g, were subcutaneously injected in the right flank with 8×106 EC109 cells transfected with Lv-MEG3 (experimental group) or Lv-NC (control group) in 0.1 ml PBS. Tumor volume (V) was measured with calipers and calculated with the formula V=0.52×LxW2 (where L and W are the long and short axes of the tumor, respectively). After 3–4 weeks, the mice were anesthetized by inhalation of 5% isoflurane and sacrificed by cervical dislocation. Death was confirmed based cessation of convulsions and sustained absence of breathing. The tumors were excised and weighed. The target molecules in the tumor tissues were detected by western blotting.
Immunohistochemical analysis
Formalin-fixed tissues were embedded in paraffin and 4-µm sections were cut from each paraffin block. The paraffin sections were dewaxed in xylene twice for 15 min each and rehydrated through a graded series of alcohol solutions (5 min per step). The slides were then stained with the primary antibody (rabbit anti-PSAT1 antibody; dilution, 1:100; cat. no. sc-133929; Santa Cruz Biotechnology, Inc.) at 4°C overnight. The sections were then washed in PBS and incubated at room temperature for 20 min with biotinylated secondary antibody, followed by incubation at room temperature for 10 min with streptavidin-peroxidase complex (Histostain-Plus Kit, Invitrogen; Thermo Fisher Scientific, Inc.). The chromogen 3,3′-diaminobenzidine was then added, and the sections were subsequently counterstained for 2 min at room temperature with Mayer's hematoxylin. Negative control sections were treated as described above, but the primary antibody was omitted. Two pathologists blinded to the clinical information independently assessed the immunohistochemistry results. In total, 5 visual fields were randomly selected in each section, and 200 tumor cells were counted in each visual field at ×200 magnification. According to the percentage of positive cells marked by yellow particles observed in tissues, the PSAT1 staining index (SI) was scored according to staining intensity (0, negative; 1, weak, light yellow; 2, moderate, yellow brown; and 3, strong, brown) multiplied by a distribution score (1, <10%; 2, 10–50%; and 3, >50% cells stained). An SI score ≥3 was defined as a high expression level of PSAT1, while SI scores 0–2 were considered to reflect a low expression level of PSAT1.
Statistical analysis
Statistical analyses were performed using SPSS software (version 22.0; IBM Corp.). All experiments in the present study were repeated ≥3 times, and the data are presented as the mean ± SD. Differences in mean values between groups were assessed for statistical significance using the Student's t-test. Welch's ANOVA test and Games-Howell post hoc test were applied to compare MEG3 expression among different cell lines. Pearson's correlation coefficient analysis was applied to calculate the correlation between the expression of MEG3 and PSAT1 in ESCC tissues. Survival curves were plotted using the Kaplan-Meier method and were analyzed using the log-rank test. P<0.05 was considered to indicate statistically significant differences.
Results
MEG3 expression is downregulated in ESCC tissues/cells and is associated with poor prognosis
The levels of MEG3 were evaluated in 43 pairs of ESCC tissues and corresponding adjacent normal tissues. The results indicated that MEG3 was significantly downregulated in ESCC tissues compared with its expression in normal controls (Fig. 1A). The expression level of MEG3 was significantly reduced in tumor tissues, as described in our previous study (17). In addition, the association between MEG3 expression and lymph node metastasis in ESCC was investigated. As shown in Fig. 1B, the expression of MEG3 was significantly decreased in ESCC patients with lymph node metastasis compared with that in ESCC patients without lymph node metastasis. Moreover, the expression level of MEG3 was significantly reduced in aggressive ESCC (TNM stage III–IV; Fig. 1C), suggesting that the downregulation of MEG3 is associated with the development of ESCC. Additionally, the level of MEG3 in ESCC cell lines (EC109, EC-9706 and KYSE-450) was significantly lower compared with that in Het-1A cells (Fig. 1D). Among the three ESCC cell lines evaluated, EC109 exhibited the lowest expression of MEG3; thus, this cell line was used for subsequent experiments. Taken together, these findings suggest that MEG3 may play a role as a tumor suppressor gene in the development of ESCC.
Lentivirus-mediated MEG3 stable expression in EC109 cells
To further explore the biological relevance of MEG3 in EC109 cells, the cultured EC109 cells were infected with either Lv-MEG3 or Lv-NC, and then puromycin was employed for selection and enrichment of lentivirus-infected cells (Fig. 2A). The mRNA expression of MEG3 was significantly increased in the Lv-MEG3 group compared with that in the Lv-NC group (Fig. 2B), indicating that Lv-MEG3 was transfected into cells successfully, and a high mRNA expression level of MEG3 was observed in EC109 cells. FISH assay revealed that MEG3 was mainly distributed in the nucleus, and a small portion was distributed in the cytoplasm (Fig. 2C). The results of MEG3 subcellular localization were further confirmed by cytoplasmic and nuclear RNA fractionation analysis in EC109 cells (Fig. 2D).
Ectopic expression of MEG3 suppresses proliferation, migration and invasion in EC109 cells
To further elucidate the role of MEG3 in ESCC cell proliferation and cell cycle progression, Lv-MEG3 was stably transfected into EC109 cells. The results of the CCK-8 assay indicated that the ectopic expression of MEG3 obviously inhibited the proliferation of EC109 cells at 48, 72 and 96 h (Fig. 3B). Consistently with these results, cell cycle analysis demonstrated that the ectopic expression of MEG3 increased the proportion of cells in the G1 phase and decreased the proportion of cells in the S phase of the cell cycle (P<0.05; Fig. 3A). Furthermore, western blotting confirmed that CCND1, a key regulator of G1-to-S phase progression, was significantly decreased in the Lv-MEG3 group (Fig. 3C), which suggested that the ectopic expression of MEG3 inhibited cell proliferation likely through induction of G1 arrest by inhibiting CCND1. Moreover, Transwell migration and wound healing assays revealed that the ectopic expression of MEG3 markedly inhibited cell invasion and migration (Fig. 3D and E). These findings demonstrated that MEG3 suppressed the proliferation and motility of EC109 cells.
Identification of DEGs after overexpression of MEG3
DEGs in EC109 cells were identified after MEG3 was overexpressed through transfection with Lv-MEG3. In total, 177 genes (23 upregulated and 154 downregulated) were found to be differentially expressed in a microarray conducted for 3 pairs of EC109 cells treated with Lv-MEG3 or Lv-NC (the threshold was set as FC >2.0 or <0.5). The 23 upregulated and the top 30 downregulated genes are listed in Table II. Scatter and volcano plots were used to assess gene expression variations between the Lv-MEG3 and Lv-NC groups (Fig. S1A and B). The relative expression levels of mRNAs among the matched samples were determined by hierarchical cluster analysis (Fig. S1C).
 | Table II.All upregulated and top 30 downregulated genes in EC109 cells treated with Lv-NC and Lv-MEG3. |
GO, KEGG pathway and PPI network analysis
Recent findings have identified numerous candidate oncogenes and tumor suppressor genes functioning in the one-carbon metabolism pathway. However, the expression levels of these molecules in ESCC remain unclear. To illustrate the functions of MEG3 in EC109 cells, Cytoscape 3.6 software was used to extract DEGs between the Lv-MEG3 and Lv-NC groups, and the STRING database was utilized to provide PPI information (18).
GO enrichment analysis demonstrated that these genes were significantly enriched in terms of serine family amino acid biosynthetic process, cellular response to glucose starvation and neutral amino acid transmembrane transporter activity (Fig. S2 and Table III). The most significant terms of the KEGG pathway included amino acid biosynthesis, aminoacyl-tRNA biosynthesis, serine and threonine metabolism, vitamin B6 metabolism, aspartate and glutamate metabolism and mitogen-activated protein kinase (MAPK) signaling pathway (Fig. S2; Table IV). The PPI network suggested that PSAT1, PHGDH, ASNS, ASRS, MARS, ATF4 and VEGFA were significant genes, and they were considered as hub genes (Fig. S3).
Validation of DEGs by RT-qPCR analysis and western blotting
Among these hub genes, PSAT1 was considered to be an important regulator of the serine family amino acid biosynthetic process, which contributed to the invasion and migration of ESCC cells (19,20). VEGFA was associated with tumor angiogenesis (21). Hence, these two genes were selected for verification of DEGs. As shown in Fig. 4A-C, RT-qPCR and western blot assays revealed that the ectopic expression of MEG3 significantly downregulated the mRNA and protein expression of PSAT1 and VEGFA in EC109 cells, which was consistent with the results of microarray analysis (FC >2.0 or <0.5; P<0.05; Table II).
MEG3 inhibits the PSAT1-dependent GSK-3β/Snail signaling pathway
Accumulating evidence has demonstrated that the phenotypic changes of increased motility and invasiveness of cancer cells are associated with EMT. The GSK-3β/Snail signaling pathway plays an important role in the EMT process. GSK-3β has been reported to regulate Snail activity, and Snail triggers the EMT process by repressing E-cadherin expression (22). Sun et al reported that PSAT1 may activate the GSK-3β/Snail signaling pathway (23). To further confirm the role of MEG3-mediated suppression of PSAT1 and its correlation with the GSK-3β/Snail signaling pathway, western blotting was performed. The results revealed that the ectopic expression of MEG3 significantly downregulated the level of the active form of GSK-3β (p-GSK-3β), but did not affect the total GSK-3β level (Fig. 4D and E). Overexpression of MEG3 also significantly downregulated the mean ratio of p-GSK-3β to total GSK-3β compared with the control group (Fig. 4F). In addition, ectopic expression of MEG3 in EC109 cells suppressed the molecular alterations that are characteristic of EMT (downregulation of the mesenchymal markers Snail and vimentin, and upregulation of the epithelial marker E-cadherin; Fig. 4D-H). Since the downregulation of PSAT1 is triggered by the overexpression of MEG3, it was inferred that MEG3 inhibits the PSAT1-dependent GSK-3β/Snail signaling pathway in EC109 cells.
Ectopic expression of MEG3 inhibits xenograft ESCC growth and PSAT1 expression in vivo
To demonstrate the effects of MEG3 on cancer cell dynamics in vivo, a xenograft tumor model in nude mice was constructed. MEG3-overexpressing (Lv-MEG3) and control cells (Lv-NC) were injected into the back flank of nude mice. The results demonstrated that ectopic expression of MEG3 significantly inhibited tumor growth (Fig. 5A-C). The maximum percentage weight loss from start to end point in the experimental group was 10.51%, while in the control group it was 5.58%. Overexpression of MEG3 decreased PSAT1 expression and increased E-cadherin expression (Fig. 5D and E), indicating that MEG3 is involved in the regulation of EMT in vivo.
Expression of MEG3 and PSAT1 in clinical ESCC tissues and association with prognosis
To investigate the clinical relevance of MEG3 and PSAT1 in the progression of ESCC, and to further validate the microarray results, the present study focused on clinical relevance. After the mRNA levels of MEG3 were evaluated in 43 pairs of ESCC, the expression levels of PSAT1 were also examined by immunohistochemical staining. The results demonstrated that the expression levels of PSAT1 were markedly upregulated in ESCC tissues compared with those in adjacent normal tissues (Fig. 5G). Spearman's analysis revealed that the expressions of MEG3 and PSAT1 were negatively correlated in ESCC tissues (Pearson's r=−0.8314; P<0.0001; Fig. 5H). The survival analysis of patients using the Kaplan-Meier plotter website data (http://kmplot.com/analysis/) revealed that higher expression levels of PSAT1 tended to be correlated with a worse OS in Asian ESCC patients (hazard ratio=5.2; P=0.036; Fig. 5I). Taken together, these results indicate that MEG3 inhibits PSAT1 expression, and PSAT1 exerts a carcinogenic effect on ESCC.
Discussion
MEG3 has been proposed to play a biological role in various diseases, particularly cancer. Recent studies demonstrated that MEG3 is involved in the regulation of cancer-related pathways, and contributes to cell proliferation, metabolism, tumor progression and metastasis (9–14). In the present study, the expression and role of MEG3 in ESCC were assessed, and the mechanisms underlying its activity were investigated. The results demonstrated that MEG3 is downregulated in ESCC cell lines and tissues, and a lower level of MEG3 expression was associated with lymph node metastasis, TNM stage and poor prognosis in patients with ESCC. Ectopic expression of MEG3 inhibits cell viability and invasion in vitro and tumor formation by EC109 cells in vivo.
To explore the molecular mechanisms through which MEG3 regulates EMT in ESCC, the microarray results and KEGG pathway analysis were used, which demonstrated that biosynthesis of amino acids, aminoacyl-tRNA biosynthesis, serine and threonine metabolism, MAPK signaling pathway, alanine, and aspartate and glutamate metabolism were markedly enriched. Notably, another study also indicated that some aminoacyl-tRNA synthetases act as secreted cytokines to regulate angiogenesis and play a critical role in the tumor microenvironment (24). Emerging evidence indicates that serine and threonine metabolism, as well as alanine, aspartate and glutamate metabolism, are associated with tumor progression (25,26). The underlying mechanisms likely involve the regulation of the synthesis of proliferation-related proteins (27). Among those, one-carbon metabolism, a system of regulating cellular nutrient status, plays an important role in cancer (28,29). PSAT1, an enzyme that catalyzes the conversion of phosphoserine to serine, is highly expressed in various tumor tissues (19,30–34). Since PSAT1 was a hub gene in the PPI network and was identified as a DEG in the present study, the mechanism of MEG3 regulating EMT through PSAT1 was further investigated in EC109 cells.
E-cadherin mediates cell-cell adhesion, a characteristic that is lost during carcinogenesis. Decreased E-cadherin, and elevated Snail and vimentin expression are the most significant characteristics of EMT (35–38). Several signaling pathways, including MAPK/ERK, PI3K/AKT/GSK-3β and Wnt/β-catenin, are involved in EMT in ESCC (5,6,23,39,40). Liu et al reported that PSAT1 activates the GSK-3β/Snail signaling pathway and promotes the phosphorylation of GSK-3β. The latter further activates Snail and inhibits E-cadherin expression, leading to EMT in ESCC (20,31). In agreement with previous studies, the present study demonstrated that ectopic expression of MEG3 suppressed the migration and invasion of ESCC cells, and also decreased PSAT1 expression. Moreover, overexpression of MEG3 not only inhibited the phosphorylation of GSK-3β, Snail and vimentin expression, but also increased E-cadherin expression in vitro. In addition, the present study demonstrated that ectopic expression of MEG3 suppressed tumor growth, alongside PSAT1 downregulation and E-cadherin upregulation, indicating that MEG3 suppresses EMT by inhibiting the PSAT1-dependent GSK-3β/Snail signaling pathway in ESCC cells.
Based on the results of the in vitro studies, the expression and significance of PAST1 was examined in ESCC tissues to confirm the findings in EC109 cell lines. The immunohistochemical results revealed that PSAT1 expression in tumor tissues was obviously higher compared with that in adjacent normal tissues, and MEG3 expression was significantly negatively correlated with PSAT1. The potential involvement of MEG3 and PSAT1 was confirmed by the Kaplan-Meier plotter website data in ESCC. Survival analysis of patients in the Asian population demonstrated that higher expression levels of PSAT1 were associated with poor prognosis. To the best of our knowledge, the present study was the first to demonstrate that MEG3 negatively regulates PSAT1 expression and the GSK-3β/Snail signaling pathway in vitro and in vivo, which may help improve our understanding of the anticancer mechanism of action of MEG3.
Notably, Dong et al reported that MEG3 inhibited EMT by competitively binding to miR-9 in YES2 cells (13). Xu et al demonstrated that the MEG3/miR-21 axis participates in the regulation of EMT in gastric cancer (41). In the present study, MEG3 inhibited EMT by inhibiting the PSAT1-dependent GSK-3β/Snail signaling pathway, suggesting that the mechanism of MEG3 regulating EMT varies across different cells, and there may be multiple mechanisms involved in the same cell type (7,36–38). The precise mechanism through which MEG3 downregulates PSAT1 and EMT requires further investigation. In addition, only a limited number of samples were examined in the present study. Future studies will include larger sample sizes to validate the correlation analysis.
In conclusion, the findings of the present study validated that MEG3 expression was decreased in human ESCC tissues, and was associated with tumor TNM stage and poor prognosis. The microarray results revealed that ectopic expression of MEG3 led to changes in major biological functions, including compound metabolic process and transcription. Furthermore, MEG3 appears to exert its effects through inhibiting the PSAT1-dependent GSK-3β/Snail signaling pathway in ESCC cells.
Supplementary Material
Supporting Data
Acknowledgements
Not applicable.
Funding
The present study was supported by the Guangdong Provincial Key Laboratory of Infectious Diseases and Molecular Immunopathology and the Department of Education, Guangdong Government, under the Top-tier University Development Scheme for Research and Control of Infectious Diseases.
Availability of data and materials
The datasets used and/or analyzed during the present study are available from the corresponding author on reasonable request.
Authors' contributions
MKL performed the experimental work and contributed to figure preparation and writing of the manuscript. LXL contributed to gene microarray analysis and participated in the experiments. WYZ, HLZ and RPC assisted with the animal and molecular biology experiments. JLF contributed to data analysis. LFW designed and supervised the experiments. All the authors have read and approved the final manuscript.
Ethics approval and consent to participate
The clinical experiments were approved by the Ethics Committee of the Second Affiliated Hospital of Shantou University Medical College. Written informed consent was obtained from all the participants.
Patient consent for publication
Not applicable.
Competing interests
All the authors declare that they have no competing interests.
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