miR‑140‑5p inhibits cervical cancer cell phenotypes via downregulating FEN1 to halt the cell cycle
- Authors:
- Published online on: September 30, 2020 https://doi.org/10.3892/mmr.2020.11552
- Pages: 4919-4930
Abstract
Introduction
Cervical cancer (CC) is a malignancy that occurs in cervical cells, and causes high morbidity and mortality among females in China (1,2). It was reported that CC resulted in >300,000 deaths in women, and >50,000,000 women were diagnosed with CC in 2018 (3). Despite advances in screening, diagnosis, vaccination and treatments, the survival rate for patients with CC remains <50% (4–6). The low survival rate of CC may result from the complex mechanisms underlying CC, including multistep genes, complex regulators and complicated biological processes (7–9). Therefore, exploring the key molecular mechanisms underlying CC is important.
Flap structure-specific endonuclease 1 (FEN1) is located on human chromosome 11q12, and participates in DNA synthesis and replication (10–14). In the early 1900s, the function of FEN1 was first identified and reported (15). During the 1900s, research focused on the functions of FEN1 at the DNA level (16). In the late 1990s, it was reported that FEN1 was downregulated during differentiation of the HL-60 cell line (a human leukemia cell line) (17). Also in the late 1900s, FEN1 was identified as a novel cell proliferation marker that could be stimulated by proliferating cell nuclear antigen (PCNA) (18,19). FEN1 upregulation has been identified as crucial for the maintenance of genome stability and for the progression of various malignancies occurring in prostate, lung, breast, brain, stomach and pancreatic tissues (20–27). FEN1 is upregulated in the HeLa cell line, and FEN1 inhibitor enhances ionizing radiation sensitivity of CC in vivo and in vitro (28). Previous studies have investigated the interaction between FEN1 and microRNAs (miRNAs/miRs) in human breast and hepatocellular cancer (29–31). However, the interaction between FEN1 and miRNAs in CC is not completely understood.
miRNAs, small non-coding RNAs that contain ~22 nucleotides, have been reported to serve as crucial players in gene transcription and gene editing during numerous cancer cell phenotype alterations (32–35). In 2006, miR-140-5p was first studied in mouse fibroblasts cells (3T3), which indicated that miR-140-5p targeted its downstream mRNA target, histone deacetylase 4, therefore regulating long bone development (36). In the following decade, the regulatory function of miR-140-5p was extensively explored in different types of cancer, such as gastric cancer, hepatocellular carcinoma and esophageal cancer (37–40). Moreover, several studies reported the possible cervical cancer-suppressive role of miR-140-5p via interaction with insulin like growth factor 2 mRNA binding protein 1, ADAM metallopeptidase domain 10, origin recognition complex subunit 1 and Smad3 (41–44). However, how miR-140-5p interacts with FEN1 in CC has not been previously reported.
The aim of the present study was to explore the mechanism underlying miRNA and its downstream target genes in cervical cancer development. Bioinformatics analysis was performed to identify a core gene that participated in CC cell cycle progression. The relationship between miR-140-5p and FEN1 was explored in CC cells. Cytological experiments were conducted to assess how modulating miR-140-5p and FEN1 expression levels altered CC cell phenotypes, especially the cell cycle profile.
Materials and methods
Differentially expressed genes (DEGs) identification and enrichment analysis
The mRNA expression profiles of GSE63514 (24 normal and 28 cancer; PMID (45), GSE64217 (2 normal and 2 cancer; www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE64217) and GSE63678 (5 normal and 5 cancer) (46) were obtained from the Gene Expression Omnibus (GEO) database (www.ncbi.nlm.nih.gov/gds). DEGs with thresholds of |log2(FC)|>2 and an adjusted P-value <0.05 were selected and uploaded to Venny (version 2.1.0; bioinfogp.cnb.csic.es/tools/venny) for screening common DEGs. Search Tool for the Retrieval of Interacting Genes/Proteins (STRING; string-db.org/cgi/input.pl) and Metascape (metascape.org/gp/index.html#/main/step1), two online tools used for gene annotation and gene list enrichment analysis, were used to construct the protein-protein interaction network and analyze the key biological process. The relative expression of DEGs in cervical squamous cell carcinoma was assessed using the University of Alabama Cancer Database (UALCAN; ualcan.path.uab.edu/index.html). Finally, using data from The Cancer Genome Atlas (www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga), The Encyclopedia of RNA Interactomes (ENCORI; version 2.0; starbase.sysu.edu.cn/panCancer.php) (47) was used to identify the key gene that was closely related to the overall survival outcome of patients with CC.
Tissue samples and characteristics record
A total of 40 cervical carcinoma tissues and 40 adjacent healthy tissues (distance from tumor margin, >5 cm) were obtained from female patients (mean age, 45 years) that underwent resection at Hanyang Hospital and The Second Affiliated Hospital of Nanchang University between March 2015 and January 2019. Patients were diagnosed with CC by three independent pathologists. The clinical characteristics of the patients are presented in Table I.
Cell lines and cell transfection
Human Uterine Cervical Epithelial Cells (HUCECs; cat. no. BNCC353405) and five human CC cell lines (HeLa, SiHa, CaSki, SW756 and C33A) were purchased from BeNa Culture Collection. Cells were cultured at 37°C with 5% CO2 according to the manufacturer's protocol: SW756 cells were cultured in Leibovitz's L-15 medium (American Type Culture Collection); SiHa and C33A cells were cultured in DMEM (Hyclone; Cytiva); and HUCEC, HeLa and CaSki cells were cultured in RPMI-1640 medium (Hyclone; Cytiva). In addition, the 293T cell line was purchased from Sigma-Aldrich (Merck KGaA) for use in the 3′untranslated region (UTR) assay. 293T cells were cultured in DMEM supplemented with 2 mM glutamine. All media was supplemented with 10% FBS (Gibco; Thermo Fisher Scientific, Inc.).
A small interfering (si)RNA targeted against FEN1 (si-FEN1), miR-140-5p mimic, miR-140-5p inhibitor, si-negative control (NC), miR-140-5p mimic NC and miR-140-5p inhibitor NC were designed and synthesized by Shanghai GenePharma Co., Ltd.. The sequences are presented in Table SI. At 50% confluence, HeLa and CaSki cells were transfected with 50 nM si-FEN1, miR-140-5p mimic, miR-140-5p inhibitor or a mixture of si-NC, miR-140-5p mimic NC and miR-150-5p inhibitor NC (the NC group; Figs. S1 and S2) using Lipofectamine® 3000 (Invitrogen; Thermo Fisher Scientific, Inc.). At 48 h post-transfection, cells were used for subsequent experiments.
Reverse transcription-quantitative PCR (RT-qPCR) and western blotting
Total RNA was extracted from tissues and cells using TRIzol® (Invitrogen; Thermo Fisher Scientific, Inc.). Total RNA (1 µg) was reverse transcribed into cDNA using 4 µl 5X First-Strand Buffer, 2 µl 0.1 M DTT, 1 µl Oligo dT Primer, 1 µl dNTP Mixture, 1 µl Rnase inhibitor, 1 µl M-MLV reverse transcriptase (cat. no. 28025013; Thermo Fisher Scientific, Inc.) and ddH2O to a volume of 20 µl. The following temperature protocol was used for reverse transcription: At 37°C for 50 min followed by 70°C for 15 min. Subsequently, qPCR was performed using an ABI 7300 system (Applied Biosystems; Thermo Fisher Scientific, Inc.) and the SYBR Green PCR kit (Thermo Fisher Scientific, Inc.). The following thermocycling conditions were used for qPCR: 95°C for 10 min; followed by 40 cycles of 95°C for 15 sec and 60°C for 1 min; and 40°C for 1 min. The sequences of the primers used for qPCR are presented in Table II. miRNA and mRNA expression levels quantified using the 2−ΔΔCq method (48) and normalized to the internal reference genes U6 and GAPDH, respectively.
Total protein extraction, protein sample separation and transfer to the membranes were performed as previously described (49). Protein extraction was performed using lysis-M reagent (Roche Diagnostic GmbH). Protein concentration was measured by performing the BCA protein assay (Pierce; Thermo Fisher Scientific, Inc.). Proteins (30 µg) were separated via 10% SDS-PAGE and transferred to nitrocellulose membranes at 0.25A for 2 h at 4°C in transfer buffer (25 mM Tris, 200 mM glycine, 20% methanol). After blocking in 5% non-fat milk for 3 h at room temperature, the membranes were incubated at 4°C for 8 h with primary antibodies targeted against: FEN1 (1:2,000; cat. no. ab109132; Abcam) and GAPDH (1:2,500; cat. no. ab9485; Abcam). Subsequently, the membranes were incubated with a horseradish peroxidase-labelled secondary antibody (1:2,500; cat. no. ab205718; Abcam) for 2 h at room temperature. Protein bands were visualized using ECL (Pierce; Thermo Fisher Scientific, Inc.). Protein expression levels were semi-quantified using ImageJ software (version 1.46; National Institutes of Health) with GAPDH as the loading control.
3′UTR reporter assay
TargetScan Human (version 7.2; www.targetscan.org/vert_72) was used to predict the complementary sequences between FEN1 3′UTR and miR-140-5p. The wild-type (WT) 3′UTR of FEN1 mRNA containing the binding site of miR-140-5p or the mutant (MUT) 3′UTR of FEN1 mRNA containing the mutated binding site were inserted into the psiCHECK2 vector (Promega Corporation) to establish the reporter assay constructs. The WT 3′UTR of FEN1 mRNA was mutated to 5′-CCCGGAUA-3′. 293T cells (1×105 cells/well) were co-transfected with 0.1 mg FEN1-WT or FEN1-MUT and 50 nM miR-140-5p mimic or mimic NC using Lipofectamine 3000. At 48 h post-transfection, a GloMax luminometer (Promega Corporation) and a dual-luciferase kit (GeneCopoeia, Inc.) were used to quantify luciferase activities. The activity of firefly luciferase was normalized to the corresponding Renilla luciferase activity.
EdU staining assay
Cell proliferation was assessed by performing EdU staining assay using the EdU Staining Proliferation kit (cat. no. ab219801; Abcam). HeLa and CaSki cells were seeded (5×104 cells/well) in 96-well plates. At 48 h post-transfection, 100 µl EdU (50 µM) was added to each well for 2 h at 37°C. Cells were fixed with 200 µl 1X fixative solution containing 40% formaldehyde for 15 min at room temperature. Subsequently, cells were permeated with 200 µl 1X permeabilization buffer for 20 min at room temperature. After washing with wash buffer, cells were incubated with 100 µl reaction mix for 20 min at room temperature. DNA content was stained using 100 µl Hoechst 33342 stock solution (5 µg/ml) for 30 min in the dark at room temperature. Stained cells were visualized using a fluorescence microscope (magnification, ×100).
Detection of cell apoptosis and cell cycle
HeLa and CaSki cells were seeded (1×104 cells/well) into 6-well plates. To assess cell apoptosis, at 48 h post-transfection, cells were stained using the Annexin V-FITC/PI cell apoptosis detection kit (Dojindo Molecular Technologies, Inc.) according to the manufacturer's instructions in the dark. To assess the cell cycle distribution, at 48 h post-transfection, cells were fixed and permeabilized with cool 70% ethanol overnight at 4°C. Cells were centrifuged at 1,000 × g for 5 min at 4°C. Subsequently, cells were incubated with 50 mg/ml PI (Sigma-Aldrich; Merck KGaA) and 25 mg/ml RNaseA for 30 min in the dark at 37°C. Following staining, cells were analyzed using a FACScalibur flow cytometer (BD Biosciences) and FlowJo software (version 7.6.1; Tree Star, Inc.) to quantify cell apoptosis and cell cycle distribution.
Assessment of cell migration
The wound healing assay was performed to assess HeLa and CaSki cell migration. Briefly, transfected cells were plated into 6-well plates and cultured to 90% confluence. Cells were cultured in serum-free media for 12 h at 37°C. A sterile pipette tip was used to create a linear wound in the middle of the cell monolayer in each well. Following washing with PBS, cells were cultured in fresh serum-free medium for 48 h at 37°C. The wounds were observed in six randomly selected fields of view using a light microscope (magnification, ×100). The migration rates were calculated by comparing the width of the wound at 0 and 48 h.
Statistical analysis
Statistical analyses were performed using GraphPad Prism software (version 7.0; GraphPad Software, Inc.). Data are presented as the mean ± SD of three independent experiments. ENCORI (47) was used to conduct survival analysis. Comparisons among multiple groups were analyzed using one-way ANOVA followed by Dunnett's post hoc test. Comparisons of gene expression levels between tumor tissues and adjacent healthy tissues were analyzed using the Wilcoxon matched-paired signed rank test. Comparisons between two independent groups were analyzed using the paired Student's t-test. P<0.05 was considered to indicate a statistically significant difference.
Results
Identifying genes that are associated with CC
To select key genes, three gene expression profiles (GSE63514, GSE64217 and GSE63678) were downloaded from the GEO database. A total of 64 common DEGs were identified (Fig. 1A). Subsequently, the gene interaction network was constructed using STRING and Metascape algorithms. Both algorithms indicated that the cell cycle was the key biological process including 25 genes from the STRING algorithm and 17 genes from the Metascape algorithm (Fig. 1B and C). For further analysis, 13 genes from both algorithms were selected (Fig. 1D). Among the 13 genes, cyclin B1, cyclin dependent kinase 1, epithelial cell transforming 2, FEN1, nucleolar and spindle associated protein 1 and PCNA displayed high expression levels in cervical squamous cell carcinoma compared with the healthy control, as determined via UALCAN (Fig. 1E). Subsequently, the six upregulated genes were input into ENCORI to perform prognosis analysis, which indicated that FEN1 may serve as a significant prognosis marker in patients with CC (Fig. 2). Previously, FEN1 has been reported to correlate with poor prognosis in non-small-cell lung cancer (50,51) and hepatocellular carcinoma (52). Therefore, FEN1 was selected as the gene of interest in the present study to investigate its underlying mechanism in CC.
FEN1 upregulation and miR-140-5p downregulation in CC
The results indicated that, compared with adjacent healthy tissues, FEN1 mRNA expression levels were 3.15-fold higher (Fig. 3A) and miR-140-5p expression levels were 46.6% lower (Fig. 3B) in CC tissues. Lower miR-140-5p expression levels were associated with a poorer prognosis outcome in patients with CC, especially after 100 months, as determined via ENCORI (Fig. 3C). Consistent with the RT-qPCR results, the protein expression levels of FEN1 were 1.79-fold higher in CC tissues compared with adjacent healthy cervical tissues (Fig. 3D). FEN1 and miR-140-5p expression levels in CC cells displayed similar trends to those in CC tissues (Fig. 3E and F).
miR-140-5p inhibits FEN1 expression
To explore whether FEN1 was the target gene of miR-140-5p, the TargetScan Human algorithm was used to predict the complementary sequences between FEN1 3′UTR and miR-140-5p. The binding site was mutated using the site-directed mutation method and the mutated sequence is presented in Fig. 4A. The direct regulatory association between miR-140-5p and FEN1 mRNA 3′UTR was assessed by performing the 3′UTR reporter assay. The results indicated that luciferase activities were significantly decreased in 293T cells co-transfected with miR-140-5p mimic and FEN1-WT compared with 293T cells co-transfected with mimic NC and FEN1-WT (Fig. 4B). The transfection efficiencies of miR-140-5p inhibitor and miR-140-5p mimic were confirmed. miR-140-5p inhibitor and miR-140-5p mimic significantly decreased (by 70%) and increased (by 2-fold) miR-140-5p expression levels, respectively, compared with the NC group (Fig. 4C). Compared with the NC group, si-FEN1 significantly decreased FEN1 expression levels by 80%, miR-140-5p mimic significantly decreased FEN1 expression levels by ~50% and miR-140-5p inhibitor significantly increased FEN1 expression levels by ~2.5-fold in both cell lines (Fig. 4D). Co-transfection of si-FEN1 and miR-140-5p inhibitor did not significantly alter FEN1 expression levels.
Suppressive effects of miR-140-5p on CC cell phenotypes via targeting FEN1
To further explore the mechanism underlying miR-140-5p in CC, HeLa and CaSki cells were transfected with miR-140-5p inhibitor, miR-140-5p mimic or si-FEN1. Cell proliferation was impaired by transfection with si-FEN1 or miR-140-5p mimic, but enhanced by transfection with miR-140-5p inhibitor compared with blank group. Interestingly, si-FEN1 and miR-140-5p inhibitor co-transfection did not significantly alter cell proliferation compared with the blank group (Fig. 5A). Compared with the blank group, si-FEN1 and miR-140-5p mimic significantly elevated the rate of cell apoptosis by ~1.5-fold, whereas miR-140-5p inhibitor significantly decreased the rate of cell apoptosis by ~80% in HeLa cells. The rate of cell apoptosis in the co-transfection group was similar to the blank group (Fig. 5C and E). Similarly, in CaSki cells, si-FEN1 and miR-140-5p mimic significantly increased the rate of cell apoptosis by 74 and 54%, respectively, whereas miR-140-5p inhibitor significantly decreased cell apoptosis by 58% compared with the blank group (Fig. 6C and E). The cell cycle profiling results indicated that si-FEN1 and miR-140-5p mimic significantly induced cell cycle arrest at the G1 phase, whereas miR-140-5p inhibitor significantly decreased cell cycle arrest at the G1 phase in both cell lines compared with the blank group (Figs. 5B, D, 6B and D). To investigate CC cell migration, the wound healing assay was performed. The results suggested that HeLa cell migration in the miR-140-5p inhibitor group was significantly increased by 1.5-fold at 48 h, whereas cell migration in the si-FEN1 and miR-140-5p mimic groups was significantly decreased by 50 and 40% at 48 h, respectively, compared with the blank group (Fig. 5F). CaSki cell migration in the si-FEN1 and miR-140-5p mimic groups was significantly decreased by 40 and 50%, respectively, but significantly increased in miR-140-5p inhibitor group by 70% compared with the blank group (Fig. 6F). However, cell migration in the co-transfection group was similar to the blank group.
Discussion
The present study identified a novel crosstalk between miR-140-5p and FEN1 in human CC. It was hypothesized that miR-140-5p displayed a CC-suppressing effect, whereas FEN1 displayed the opposite effect. The binding relationship between miR-140-5p and FEN1 predicted by TargetScan Human was also verified. The cell experiment results indicated that FEN1 knockdown inhibited CC cell proliferation, migration and uncontrollable cell cycle progression, whereas miR-140-5p inhibitor promoted CC cell proliferation, migration and cell cycle progression compared with the blank group.
To identify genes that potentially participated in the development of CC, three GEO datasets were analyzed in the present study. The bioinformatics analysis indicated that FEN1, in relation to the cell cycle, was a key gene that served an important role in CC. FEN1 is upregulated in various types of cancer, and FEN1 loss-of-function has been reported to inhibit cancer progression. For instance, He et al (26) reported that FEN1 was upregulated in lung cancer cells, and FEN1 inhibitor effectively inhibited cell proliferation and induced DNA damage in vitro. Also, FEN1 promoted breast cancer cell proliferation by mediating DNA methyltransferase (DNMT)1 and DNMT3a to recover the expression of miR-200a-5p target genes (31). In CC, FEN1 was upregulated in HeLa cells, and FEN1 loss-of-function resulted in significant DNA damage and CC cell proliferation (28). Besides, the combination of FEN1 inhibitor and ionizing radiation displayed an enhanced CC-suppressing effect (28). Another study demonstrated that the antitumor effect of paclitaxel was enhanced in CC cells when paclitaxel was used in combination with FEN1 inhibitor (53). Therefore, it was hypothesized that FEN1 might contribute to the development of CC, and FEN1 knockdown might possess a CC-suppressing effect. The results of the present study indicated that FEN1 was significantly upregulated in CC tissues and cells compared with adjacent healthy tissues and HUCECs. FEN1 knockdown inhibited CC cell phenotypes compared with the blank group, including inhibiting cell mitosis by halting the cell cycle at the G1 phase. Similarly, Zhang et al (45) reported that FEN1 knockdown led to G1/S phase cell cycle arrest in lung cancer cells.
miRNAs have been regarded as negative regulators of target genes that also affect the progression of different types of cancer (54–56). miR-140-5p upregulation has been reported to impair the cancerous phenotypes of CC cells (41–43). miR-140-5p overexpression suppressed tumor growth and metastasis in nude mice (44). Interestingly, the effects of FEN1 and its regulator miR-140-5p in other types of cancer have been studied. For instance, overexpression of miR-140-5p and FEN1 in breast cancer resulted in reduced DNA damage and genome instability compared with miR-140-5p overexpression alone in breast cancer cell lines (29), suggesting that FEN1 rescued breast cancer cells from DNA damage and genome instability by compromising miR-140-5p. Similar results were observed in a hepatocellular carcinoma study, which reported that miR-140-5p and FEN1 overexpression reduced cell invasion and tumor growth (30). In the present study, the effects of si-FEN1 were blocked by miR-140-5p inhibitor, indicating a regulatory association between FEN1 and miR-140-5p. Compared with the blank group, miR-140-5p knockdown enhanced the malignant phenotypes of CC cell lines and FEN1 knockdown suppressed CC cell phenotypes. The results also indicated that miR-140-5p directly bound to FEN1 mRNA 3′UTR. Therefore, whether miR-140-5p inhibition could rescue FEN1 knockdown-induced phenotypes was investigated. The results indicated that the cancer-promoting effect of miR-140-5p inhibitor on CC was suppressed by si-FEN1. A potential explanation for the aforementioned effect is that the miR-140-5p inhibitor may have neutralized part of the endogenous miR-140-5p that bound to FEN1 mRNA 3′UTR, which freed some FEN1, compensating for the loss of FEN1 caused by si-FEN1 transfection.
Based on the results of the present study, it was hypothesized that miR-140-5p was an antitumor regulator in CC via suppressing FEN1 expression in vitro. However, whether miR-140-5p and FEN1 serve potential diagnostic and therapeutic benefits for patients with CC requires further investigation in vivo. In addition, whether the interaction between miR-140-5p and FEN1 exists in other CC cell lines should be investigated in future studies to generalize the axis to a wider range of CC cell lines. As a potential participant in the cell cycle signaling pathway, whether FEN1 could regulate the expression of certain cell cycle-related proteins and how FEN1 regulates cell cycle progression also require further investigation.
To the best of our knowledge, the present study suggested for the first time that miR-140-5p binding to FEN1 mRNA 3′UTR suppressed the cancerous phenotypes of HeLa and CaSki cell lines. Moreover, miR-140-5p knockdown prevented cell cycle arrest at the G1 phase by targeting FEN1 in HeLa and CaSki cell lines. Therefore, the present study provided insight into a potential therapeutic target for CC.
Supplementary Material
Supporting Data
Acknowledgements
Not applicable.
Funding
No funding was received.
Availability of data and materials
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Authors' contributions
SL designed the study and prepared the manuscript. YG interpreted the data and supervised the experiments. SL and YG revised the manuscript. Both authors read and approved the final manuscript.
Ethics approval and consent to participate
The present study was approved by the Ethics Committee of Hanyang Hospital (approval no. AB-20.05/07) and The Second Affiliated Hospital of Nanchang University (approval no. NCEFY-04-23). All patients signed written informed consent.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
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