MicroRNA‑744‑5p inhibits glioblastoma malignancy by suppressing replication factor C subunit 2
- Authors:
- Published online on: June 15, 2021 https://doi.org/10.3892/ol.2021.12869
- Article Number: 608
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Copyright: © Fan et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
Abstract
Introduction
Glioblastoma (GBM) is a common malignant primary brain tumor that accounts for ~57% of all gliomas and 48% of all malignant primary tumors of the central nervous system in the United States (1). The prevalence of GBM is highest in North America and Australia, as well as Northern and Western Europe (2). Caucasian patients have the poorest survival rates and highest incidence of GBM (3), and treatment strategies such as surgery, radiotherapy and chemotherapy appear to be ineffective. Moreover, poor prognosis and low long-term survival remain challenging issues (4), though precision oncology and targeted gene therapy herald much promise in developing more efficacious treatments for patients with GBM.
MicroRNAs (miRNAs/miRs) are abundant small non-coding RNAs, ~20-24 nucleotides in length, that regulate gene expression by inhibiting translation or degrading messenger RNA (5,6). A cluster of miRNAs has been shown to affect tumor cellular biological processes and to serve as potential diagnostic targets in various human cancers (7,8). For example, miR-744-5p has been associated with numerous cancers and plays an important role in tumor progression characteristics, including cellular proliferation, invasiveness and apoptosis (9–11). Accumulating evidence suggests that miR-744-5p may also be a promising therapeutic target for cancer treatment (12,13), and has also been reported to suppress cellular proliferation and invasiveness in ovarian (14) and lung cancer (15). Further studies have shown that miR-744-5p is abnormally expressed in GBM, regulating its occurrence and development (16,17). Nevertheless, the underlying mechanisms by which miR-744-5p acts on GBM require further investigation.
The replication factor C subunit 2 (RFC2) gene is located on chromosome 7q11.23 and consists of 11 exons, encoding a member of the activator 1 small subunit family. RFC2 plays an important role in the elongation of primed DNA templates by DNA polymerase δ and ε (18). Upregulated RFC2 expression has been associated with a number of cancers, such as nasopharyngeal (19) and esophageal squamous cell carcinoma (20). However, to the best of our knowledge, only a single study has reported the involvement of RFC2 in GBM, in which RFC2 was indicated to enhance temozolomide (TMZ) cytotoxicity (21). Notably, RFC2 was found to be a direct target of miR-744-5p in the progression of colorectal cancer cell tumorigenicity (22). However, little is known about the expression pattern and biological functions of RFC2 in GBM, including its interaction with miR-744-5p. Therefore, it may be beneficial to elucidate the biological role of RFC2 and its potential interaction with miR-744-5p therein.
Thus, the aim of the present study was to explore a novel interactome, miR-744-5p-RFC2, and to determine the effects of miR-744-5p and RFC2 in GBM. We hypothesized that miR-744-5p suppressed GBM by inhibiting RFC2, which may provide novel targets for the clinical treatment of GBM, and improve future patient prognosis.
Materials and methods
Bioinformatics analysis
Gene Expression Profiling Interactive Analysis (GEPIA; http://gepia2.cancer-pku.cn/#index), including gene expression profiling data from The Cancer Genome Atlas project, was performed to screen differentially expressed genes (DEGs, criteria: |log2FC| ≥2 and P<0.01) and survival-related genes (criteria: P<0.01) associated with GBM. Then, the DEGs and survival-associated genes were overlapped using Venny 2.1.0 (https://bioinfogp.cnb.csic.es/tools/venny/), and STRING (https://string-db.org/) was used to predict the protein-protein interactions between the overlapping genes. Finally, the ENCORI starBase (http://starbase.sysu.edu.cn/index.php), TargetScan Human 7.2 (http://www.targetscan.org/vert_71/) and miRDB.org algorithms (http://mirdb.org/) were used to predict the upstream miRNAs of key genes.
Tissue samples
GBM tissues (n=39) and normal adjacent tissues (n=39) were collected from Union Hospital, Tongji Medical College, Huazhong University of Science and Technology (Wuhan, China) between April 2015 and October 2019. Inclusion criteria included: i) Postoperative pathology diagnosed as GBM; and ii) Complete patient information obtained. Exclusion criteria included: i) Patients who underwent radiotherapy and chemotherapy before surgery; ii) Patients with a history of another kind of malignant cancer; and iii) Patients with serious heart, liver, spleen, lung or kidney diseases. The study protocol was approved by the Ethics Committee of Union Hospital on September 12, 2018 [approval. no. (2018) (216)], and all patients provided written informed consent. The clinical characteristics of the GBM subjects are presented in Table I. The patient aged 45–70 years old, with a mean age of 52.6±9.3 years.
 | Table I.Association of RFC2 or miR-744-5p expression with the epidemiologic features of 39 patients with glioblastoma. |
Cell culture and transfection
The human GBM cell lines, U87 (cat. no. HTB-14; GBM of unknown origin) and A172 (cat. no. CRL-1620) were purchased from the American Type Culture Collection. U251 (cat. no. TCHu 58) and SHG44 (cat. no. TCHu 48) cells were purchased from the cell bank of the Chinese Academy of Sciences (Shanghai, China). Normal human astrocyte (NHA) cells (cat. no. 1800) were purchased from ScienCell Research Laboratories, Inc. U251, SHG44, A172 and NHA cells were maintained in DMEM and U87 cells were maintained in MEM, both with 10% fetal bovine serum (FBS) (Invitrogen; Thermo Fisher Scientific, Inc.), at 37°C (5% CO2 and 90% humidity). All cell lines were verified by short tandem repeat authentication.
For transfection, the RFC2-overexpression (RFC2-OE) vector, pcDNA 3.1 empty vector [used as the RFC2-OE negative control (NC)], si-NC, si-RFC2, miR-744-5p inhibitor, miR-744-5p mimics, mimic-NC and inhibitor-NC were all purchased from Shanghai Tuoran Co., Ltd. A total of 3×105/well U251 and U87 cells were cultured in 24-well plates and transfected with either si-NC, si-RFC2, RFC2-OE, miR-744-5p inhibitor, miR-744-5p mimic or pcDNA 3.1, mimic-NC or inhibitor-NC, at a concentration of 50 nM using Lipofectamine® 3000 (Invitrogen; Thermo Fisher Scientific, Inc.), and maintained at 37°C for 48 h before subsequent experiments were performed. The sequences of RFC2-OE, si-RFC2, miR-744-5p inhibitor, the miR-744-5p mimics and their corresponding NC are presented in Table SI.
RNA extraction and reverse transcription-quantitative (RT-q) PCR
Total RNA from the tissue specimens and cell lines was isolated using TRIzol® reagent following the manufacturer's instructions (Thermo Fisher Scientific, Inc.). Subsequently, total RNA was reverse transcribed into cDNA using the PrimeScript First Strand cDNA Synthesis kit (Takara Biotechnology Co., Ltd.). The targeted reverse transcription of miRNA was performed using the Hairpin-it miRNA qPCR Quantitation Kit (Shanghai GenePharma Co., Ltd.). Then, SYBR Premix Ex Taq (Takara Biotechnology Co., Ltd.) was used for qPCR, performed on an ABI Prism 7900 Detector System (Thermo Fisher Scientific, Inc.). The qPCR conditions were 1 cycle at 95°C for 20 sec, followed by 40 cycles of 1 min each at 95°C, and 20 sec at 60°C. Relative expression levels were normalized to that of U6 and β-actin, corresponding to miRNA and mRNA, respectively. The expression levels were calculated using the 2−ΔΔCq method (23). The primer sequences are listed in Table II.
Western blotting
Total proteins from the U251 and U87 cells were extracted using radioimmunoprecipitation assay lysis buffer (MilliporeSigma), and the total protein content was quantified using a BCA detection kit (Thermo Fisher Scientific, Inc.). Then, the proteins (30 µg per well) were separated by 10% SDS-PAGE and subsequently transferred onto PVDF membranes (EMD Millipore). The membranes were blocked with 5% skim milk for 1 h at 25°C, and then incubated with the following primary antibodies at 4°C for 12 h: Anti-RFC2 (cat. no. ab174271; 1:10,000; Abcam), goat anti-rabbit Bax (cat. no. ab32503; 1:2,000; Abcam), goat anti-rabbit Bcl-2 (cat. no. ab182858; 1:2,000; Abcam) and anti-β-actin (cat. no. ab8226; 1:10,000; Abcam). After washing three times with TBS containing 0.05% Tween 20 (TBST), the membranes were incubated then with the following secondary antibodies: Goat anti-rabbit for RFC2 (cat. no. ab205718; 1:2,000; Abcam) and goat anti-mouse for β-actin (cat. no. ab175783; 1:2,000; Abcam) for 1 h at 25°C. Finally, positive bands were visualized with the Immobilon™ Western Chemiluminescent horseradish peroxidase (HRP) substrate (EMD MilliporeSigma). The densities of the bands was determined using ImageJ software version 1.53 (National Institutes of Health).
Cell Counting Kit 8 (CCK-8) assay
The CCK-8 (Sangon Biotech Co., Ltd.) was used to determine the viability of U251 and U87 cells. Transfected cells (2×103/well) in 96-well plates were incubated for 0, 24, 48 and 72 h. Then, 10 µl CCK-8 reagent was added to each well and the cells were incubated for a further 2 h. The absorbance was measured at an optical density of 450 nm using a multimode microplate reader (Tecan Group, Ltd.).
5-bromo-2-deoxyuridine (BrdU) assay
Cellular proliferation was evaluated using the BrdU Cell Proliferation Assay Kit (Cell Signaling Technology, Inc.) per the manufacturer's instructions. U251 and U87 cells were seeded into 96-well plates (2×104 cells per well) and cultured in FBS-free medium for 24 h to synchronize the cell cycle. Then, the medium was removed and the cells were labeled with 1X BrdU solution (prepared in cell culture medium) for 6 h at 37°C to induce proliferation. The labeling medium was removed, and the cells were fixed and denatured using the supplied fixation/denaturation solution. BrdU mouse mAb was then added and the cells were incubated for 2 h at 37°C. Anti-mouse immunoglobulin G and HRP-linked antibody were used to detect the binding antibody, and HRP substrate (3,3,5,5-tetramethylbenzidine) was added for color development. Finally, the absorbance at 450 nm was determined using a multimode microplate reader (Tecan Group, Ltd.).
Wound-healing assay
The migratory ability of U251 and U87 cells was evaluated by wound-healing assay. Cells were seeded into 6-well plates (2×105/well), cultured to 80% density and subsequently, 200-µl pipette tips were used to create wounds in the center of each well. After incubation with FBS-free medium for 24 h at 37°C, the wound was photographed using an optical microscope (Olympus Corporation) at ×100 magnification. The wound closure was measured using the following formula: (W0 h-W24 h)/W0 h ×100%, where W is the width.
Cellular adhesion Assay
A 96-well plate was coated with collagen I solution (40 µg/ml; Sigma-Aldrich; Merck KGaA) and stored at 4°C for 12 h. U251 and U87 cells (2×105 cells/ml) were cultured in FBS-free DMEM for 8 h before harvesting by trypsinization. Then, the cells were collected and suspended in 100 µl DMEM with 0.1% BSA in the coated 96-well plate, and incubated at 37°C for 20 min. Subsequently, the cells were incubated with medium containing 10% FBS for 4 h at 37°C. Then, 10 µl MTT substrate (MilliporeSigma) was added to each well and the plate was incubated for a further 2 h at 30°C. The cells were then washed twice with PBS and 100 µl DMSO was added to each well. Absorbance was measured at a wavelength of 570 nm using a multimode microplate reader (Tecan Group, Ltd.).
Caspase activity assay
U251 and U87 cells were seeded into 96-well plates (3×105 cells per well). Caspase-3 assay loading solution (Cell Signaling Technology, Inc.) was prepared by adding the caspase-3 substrate to DL-dithiothreitol reagent according to the manufacturer's instructions. Cells were collected at 80% density and lysed with ice-cold cell lysis buffer for 10 min. Subsequently, loading solution (100 µl/well) was added to each sample and incubated at 37°C for 2 h. The absorbance was then measured at a wavelength of 405 nm using a multimode microplate reader (Tecan Group, Ltd.).
Dual-luciferase reporter assay
The psiCHECK2-RFC2-3′ untranslated region (3′-UTR) wild-type vectors and psiCHECK2 RFC2-3′-UTR mutated vectors were purchased from Weizhen Bio (Shanghai, China). U251 and U87 cells were co-transfected with the vectors and negative control (NC) or miR-744-5p mimics using Lipofectamine® 3000, and cultured in a 24-well plate. After 48 h, the dual-luciferase reporter assay System (Promega Corporation) was used to detect the firefly and Renilla luciferase activities. Relative luciferase activity was normalized to the activity of Renilla luciferase (internal control).
RNA pull-down analysis
The biotin-labeled miR-2355-5p (Bio-miR-2355-5p, 5′-AUCCCCAGAUACAAUGGACAA-biotin-3′), miR-122-5p (Bio-miR-122-5p, 5′-AACGCCAUUAUCACACUAAAUA-biotin-3′) and miR-744-5p (Bio-miR-744-5p, 5′-UGCGGGGCUAGGGCUAACAGCA-biotin-3′), as well as negative controls (Bio-NC, 5′-GUGCACGAAGGCUCAUCAUU-biotin-3′) were purchased from Guangzhou RiboBio Co., Ltd, and were used to transfect both U251 and U87 cells for 48 h at 37°C using Lipofectamine® 3000. Next, the cells were collected and lysed using 0.5 ml lysis buffer, containing 25 mM Tris-HCl (pH 7.5), 70 mM KCl, 2.5 mM EDTA, 0.05% NP-40, protease inhibitor cocktail (Sigma-Aldrich; Merck KGaA) and RNase inhibitors (Thermo Fisher Scientific, Inc.), for 20 min on ice. The mixture was centrifuged at 1,400 × g at 4°C for 20 min, and 0.5 ml supernatant lysate was collected. The streptavidin beads (50 µl; cat. no. 88816; Thermo Fisher Scientific, Inc.) were washed and added to the supernatant lysates, and then incubated at 4°C on a rotating platform for 12 h. The following day, the beads were washed twice with cold lysis buffer, three times with low salt buffer solution, and once with high salt buffer solution; the specifically-bound RNAs were purified using the RNeasy Mini Kit (QIAGEN). Finally, the enrichment of RFC2 was detected by performing RT-qPCR.
Statistical analysis
All analyses were performed using GraphPad Prism 8.0 software (GraphPad Software, Inc.). Paired Student's t-test (two-tailed) was used to compare the differences between two groups, while the differences between three or more groups were determined by one-way ANOVA with Dunnett's (comparisons with one group) or Tukey's (comparisons with more than one group) post hoc test. The correlation between miR-744-5p and RFC2 expression levels was determined by Pearson's correlation analysis. Data are presented as the mean ± standard deviation, and P<0.05 was considered to indicate a statistically significant difference.
Results
Identification of study objects of interest
DEGs and survival-related genes for GBM were acquired from the GEPIA database, which is a gene expression profiling interactome analysis tool that includes gene expression profiling data from The Cancer Genome Atlas project. GEPIA yielded 1,384 DEGs with the criteria of |log2FC| ≥2 and P<0.01, and 547 GBM survival-related genes with the criterial of P<0.01. Among these genes, 47 were both DEGs and GBM survival-related (Fig. 1A). By performing STRING analysis of the 47 genes, 22 were found to be closely related (Fig. 1B). The STRING network indicated that RFC2 had been studied in glioma once, and it was reported to be related to drug cytotoxicity; furthermore, the knockdown of RFC2 led to reduced cell viability (21). Nonetheless, how RFC2 affects other GBM cell phenotypes has not been extensively studied. Therefore, RFC2 was chosen as a gene of interest. The ENCORI starBase, TargetScan Human 7.2 and miRDB.org algorithms were used to predict the upstream miRNAs of RFC2, and three overlapping miRNAs (miR-2355-5p, miR-122-5p and miR-744-5p) were identified (Fig. 1C). After constructing bio-miR-2355-5p, bio-miR-122-5p and bio-744-5p, these plasmids showed high transfection efficiency in U251 and U87 (Fig. S1). After RNA pull-down analysis, it was observed that the association between RFC2 and miR-744-5p was stronger than that with miR-2355-5p or miR-122-5p (Fig. 1D). Therefore, the involvement of RFC2 mRNA and miR-744-5p miRNA in GBM was investigated further.
RFC2 expression is upregulated in GBM tissues and cell lines
To elucidate whether RFC2 is involved in GBM, RFC2 expression was first detected in tumor tissues and corresponding normal tissues from patients with GBM. The results showed that RFC2 expression increased 1.5-fold compared to normal control tissues (Fig. 2A). RFC2 gene expression was also detected in NHAs and GBM cells (U251, U87, SHG44 and A172), and was significantly increased in the GBM cell lines compared to NHA cells. In particular, U251 and U87 cells showed more than a 3-fold increase in RFC2 expression compared with NHA cells. Therefore, U251 and U87 cells were chosen for subsequent experiments due to having the highest expression of RFC2 (Fig. 2B). To further explore the effects of RFC2 in GBM, U251 and U87 cells were transfected with si-NC, OE-NC (pcDNA 3.1 empty vector), Co-NC (si-NC+OE-NC), RFC2-overexpression (OE),or si-RFC2 constructs. Cells transfected with RFC2-OE displayed ~4-fold upregulated RFC2 levels compared with the control cells, while cells transfected with si-RFC2 exhibited an ~70% decrease in RFC2 levels compared with the control cells (Fig. 2C). Furthermore, the protein expression levels of RFC2 increased more than 1.4-fold in cells transfected with RFC2-OE, with an ~60% decrease in protein levels observed in si-RFC2 cells compared with the control cells (Fig. 2D). As the Co-NC exerted no obvious effect on RFC2 expression, Co-NC was used as the NC group in subsequent experiments.
RFC2 promotes cellular proliferation, migration and adhesion, and suppresses apoptosis in GBM
To determine whether RFC2 promotes GBM tumorigenesis, a CCK-8 assay was performed using transfected U251 and U87 cells. Cells transfected with RFC2-OE exhibited higher proliferative capacity, while cells transfected with si-RFC2 proliferated to a lower degree than the control cells (Fig. 3A). Moreover, according to the results of the BrdU assay, cells transfected with RFC2-OE exhibited an ~30% enhancement in proliferation, while cells transfected with si-RFC2 indicated reduced proliferation (~50%) compared with the control cells (Fig. 3B). A wound-healing assay was performed to assess the migratory capacity of the transfected cells. The results showed a 30% increase in the migratory ability of cells transfected with RFC2-OE, and a 50% decrease in the migratory ability of cells transfected with si-RFC2 compared with the control cells (Fig. 3C). Furthermore, adhesion ability was elevated by ~30% in cells transfected with RFC2-OE, while cells transfected with si-RFC2 showed ~30% reduced cell adhesion ability compared with the control cells (Fig. 3D). Additionally, the levels of caspase-3 activity were elevated 6-fold in cells transfected with si-RFC2, while cells transfected with RFC2-OE indicated reduced levels of caspase-3 activity by 70% compared to control cells (Fig. 3E). Furthermore, western blot analysis showed that compared with the control group, Bax protein expression was decreased and Bcl-2 expression was increased in U251 and U87 cells overexpressing RFC2, while the trend was opposite in cells with low expression of RFC2 (Fig. 3F). Therefore, these results demonstrated that RFC2 promoted cell proliferation, migration, and adhesion, and suppressed cell apoptosis in GBM.
RFC2 is a target of miR-744-5p in GBM
The TargetScan Human 7.2 database was used to identify potential miRNAs targeting RFC2. The analysis identified miR-744-5p as a potential miRNA that could interact with the 3′UTR of RFC2 mRNA; the binding sequences are displayed in Fig. 4A. Subsequently, U251 and U87 cells were successfully transfected with miR-744-5p mimics and inhibitor (Fig. S2). The results showed that U251 and U87 cells co-transfected with wild-type RFC2 3′-UTR plasmid and miR-744-5p mimic showed ~50% reduced luciferase activity compared with cells co-transfected with wild-type RFC2 3′-UTR plasmid and miR-NC. However, no change was observed in cells co-transfected with the mutant RFC2 3′-UTR plasmid (Fig. 4B). This suggested that miR-744-5p directly bound to the 3′-UTR of RFC2. RT-qPCR analysis demonstrated that miR-744-5p expression in GBM tissues was ~50% lower than that in normal-adjacent tissues (Fig. 4C). A significant negative correlation was found between miR-744-5p and RFC2 expression in GBM tissues (Fig. 4D). Additionally, the results revealed that miR-744-5p levels were downregulated by ~50% in U87 cells and 25% in U251 cells compared to NHAs (Fig. 4E). Overall, RFC2 acts as a negative downstream target of miR-744-5p in GBM. U251 and U87 cells were transfected with RFC2-OE and miR-744-5p inhibitor, or si-RFC2 together with miR-744-5p inhibitor. RT-qPCR analysis confirmed that cells transfected with RFC2-OE and miR-744-5p inhibitor showed more than 2.5-fold higher expression of RFC2, and 50% lower expression of RFC2 in cells transfected with si-RFC2 than in the control cells. Cells transfected with si-RFC2 and miR-744-5p inhibitor showed the same level as control cells (Fig. 4F). RFC2 protein expression was markedly increased in cells transfected with miR-744-5p inhibitor, and significantly reduced by in si-RFC2 cells, compared with the controls. Cells transfected with si-RFC2 and miR-744-5p inhibitor showed the same levels of RFC2 expression as the control cells (Fig. 4G).
miR-744-5p targets RFC2 to suppress GBM progression
To assess the important role of miR-744-5p and RFC2 in GBM, NC and si-RFC2, miR-744-5p inhibitor, and Si-RFC2 together with miR-744-5p inhibitor were transfected into U251 and U87 cells. CCK-8 assay analysis showed that after 48 h, cells transfected with miR-744-5p inhibitor exhibited significantly enhanced proliferation capacity, whereas cells transfected with si-RFC2 showed significantly reduced capacity, compared with the control cells. Cells transfected with si-RFC2 and miR-744-5p inhibitor showed the same level as control cells (Fig. 5A). Furthermore, proliferation was enhanced by ~50% in cells transfected with miR-744-5p inhibitor but decreased by ~30% in si-RFC2 cells compared to control cells. Cells transfected with si-RFC2 and miR-744-5p inhibitor showed the same level as control cells (Fig. 5B). In addition, cells transfected with miR-744-5p inhibitor showed ~30% enhanced migratory ability, while cells transfected with si-RFC2 showed ~50% decrease in migratory ability compared to control cells as observed by wound healing assay. Cells transfected with si-RFC2 and miR-744-5p inhibitor showed the same level as control cells (Fig. 5C). Moreover, cells transfected with si-RFC2 exhibited a 40% decrease in cell adhesion, while cells transfected with miR-744-5p inhibitor showed a 40% increase in cell adhesion levels compared to control cells. Cells transfected with si-RFC2 and miR-744-5p inhibitor showed the same level as control cells (Fig. 5D). Additionally, cells transfected with si-RFC2 showed >4-fold caspase-3 activity, while cells transfected with miR-744-5p inhibitor showed ~50% reduced caspase-3 activity compared to control cells. Cells transfected with si-RFC2 and miR-744-5p inhibitor showed the same level as control cells (Fig. 5E). Furthermore, western blotting showed that in U251 and U87 cells, with low expression of miR-744-5p, the expression levels of Bax protein, were lower than those in the control group, while the expression levels of Bcl-2 protein was higher than that in the control group (Fig. 5F). Moreover, the protein expression levels of Bax and Bcl-2 in RFC2 and miR-744-5p knockdown cells were the same as that in the control group (Fig. 5F). Collectively, these results revealed that miR-744-5p suppressed cellular proliferation, migration and adhesion, and promoted apoptosis in GBM by inhibiting RFC2.
Discussion
GBM is the most lethal form of primary glioma (24). The standard therapy for GBM consists of surgery followed by radiation therapy with adjuvant chemotherapy (25,26). The highly infiltrative, heterogeneous and mutable nature of GBM frequently contributes to tumor recurrence and treatment failure (27). Therefore, despite advances in multimodal therapies, the 5-year survival rate of patients with GBM is only 5% after diagnosis (28). Hence, it is necessary to investigate the therapeutic methods for GBM at the molecular level. In the present study, the expression of RFC2 was found to be significantly upregulated in GBM tumor tissues and cell lines, while the expression of miR-744-5p was downregulated. In addition, miR-744-5p targeted RFC2 and functionally repressed its expression, thereby suppressing the progression of GBM cells.
Recently, an increasing number of reports has emphasized the molecular mechanism and significance of miR-744-5p expression in different human tumors. Studies have shown that abnormal expression of miRNAs may be one of the primary reasons for the occurrence of GBM, and therefore, miRNAs can be used as predictive biomarkers for the diagnosis of GBM (29,30). The expression of miRNA-744-5p in GBM has also been investigated in recent years. For instance, miRNA-744-5p inhibited tumorigenesis by inhibiting NIN1/RPN12 binding protein 1 homolog (NOB1) in GBM (17). The study demonstrated that miRNA-744-5p expression was significantly reduced in GBM tissues and cell lines, and that it inhibited the proliferation, colony formation, migration and invasiveness, and promoted apoptosis in GBM cells by targeting NOB1. Another study revealed that the expression of miR-744-5p was markedly decreased in GBM specimens and primary GBM cell lines. miR-744-5p inhibited GBM migration by suppressing transforming growth factor β1 and Dishevelled 2, which further functionally downregulated MAP2K4 signaling (17). Consistent with their results, the present study indicated that miR-744-5p was significantly decreased in GBM specimens and cell lines. Downregulation of miR-744-5p enhanced proliferation and repressed apoptosis in GBM cells, as observed by CCK-8, wound-healing, and caspase-3 activity assays.
RFC2, a member of the RFC family, acts as a primer recognition factor for DNA polymerase, and regulates cellular proliferation, migration, invasiveness and metastasis in various cancers (18,22). Previous studies have reported the dysregulation of RFC2 in various human cancer types (19,31). For instance, high expression of RFC2 has been considered as a molecular marker of nasopharyngeal carcinoma (19). Ho et al (21) observed that miR-4749-5p inhibited RFC2 expression, which further enhanced TMZ cytotoxicity in GBM. They further clarified that a higher level of RFC2 was observed in GBM patients with poor survival. Upregulated miR-4749-5p targeting RFC2 decreased cell viability, increased apoptosis and enhanced TMZ cytotoxicity in GBM cells. In the present study, abnormally increased expression of RFC2 was observed in both GBM tissues and cells. Upregulation of RFC2 enhanced cellular proliferation, migration and adhesion, and suppressed apoptosis in GBM. Furthermore, it was also identified that the impact of RFC2 on GBM cell proliferation, migration, adhesion and apoptosis was regulated by miR-744-5p, which directly targets RFC2.
During the advanced stages of cancer, synaptosomal, associated protein of 25 kDa (SNAP-25), a membrane-binding protein in neurons, is thought to promote tumor development through autophagy, and to play a role in the process of tumor pain (32,33). Furthermore, studies have shown that the expression of SNAP-25 alters the characteristics of synaptic transmission, leading to pathological changes in neuronal circuits in psychiatric diseases (34). Therefore, the effect of miR-744-5p/RFC2 on SNAP-25 is a focus of future research. In addition, the detection of apoptosis-related factors in cancer cells is important when exploring the genesis and development of GBM. For example, E3 ubiquitin-protein ligase XIAP, belonging to the inhibitor of apoptosis protein (IAP) family, is highly expressed in various tumor types, such as malignant glioma (35). p53 mutation may not only lead to the development of GBM tumors (as an early event), but also lead to its malignant progression (as a late event) (36). It has been speculated that XIAP or p53 may be highly expressed in GBM and regulated by the miR-744-5p/RFC2 axis, and this hypothesis will be verified in future studies. Various types of cells exist in the microenvironment of primary, invasive and metastatic tumors (37). The expression levels of miR-744-5p and RFC2 in GBM tissues do not fully reflect the true status of cancer cells. Therefore, the effect of the miR-744-5p/RFC2 axis in GBM requires clinical investigation in greater detail. TMZ resistance is a common cause of treatment failure in GBM (38). A previous study revealed that miR-4749-5p inhibited RFC2 expression, which could further enhance TMZ cytotoxicity in GBM (21). Therefore, we hypothesize that miR-744-5p enhances the chemosensitivity of TMZ in GBM by targeting RFC2, which is also a focus of our future research. Besides, Weighted Gene Co-expression Network Analysis (WGCNA) is a tool often used to identify the key biological processes and hub genes in GBM by constructing gene co-expression networks (39–41), which is different from GEPIA used in the present study. Due to the lack of WGCNA technology, we will learn WGCNA to help us identify the biological processes and genomic networks to develop effective treatment strategies for GBM by targeting the miR-744-5p/RFC2 axis. Moreover, this study only observed these tumor characteristics at the cellular level, detected cell apoptosis by western blot assay and detected cell adhesion by spectrophotometry; however, these findings need to be further determined by establishing animal models, performing flow cytometry and using atomic force microscope.
In conclusion, the results of the present study demonstrated that miR-744-5p targeted RFC2 and suppressed the progression of GBM through repressing cell proliferation and migration, and effectively promoting cell apoptosis. Consequently, our study demonstrated that the miR-744-5p/RFC2 interaction could be a potential candidate for the treatment of GBM.
Supplementary Material
Supporting Data
Acknowledgements
Not applicable.
Funding
The present study was supported by the Fundamental Research Funds for the Central Universities (grant. no. 2019kfyXKJC071).
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
FF and DY performed the experiments and data analysis. PY conceived and designed the study. XJ and JH acquired the data, and are responsible for the authenticity of the raw data. FF and DY conducted the analysis and interpretation of data. All authors read and approved the manuscript.
Ethics approval and consent to participate
The present study was approved by the Ethics Committee of the Union Hospital, Tongji Medical College, Huazhong University of Science and Technology. The processing of clinical tissue samples is in strict compliance with the ethical standards of the Declaration of Helsinki. All patients signed written informed consent.
Patient consent for publication
Not applicable
Competing interests
The authors declare that they have no competing interests.
References
|
Wen PY and Kesari S: Malignant gliomas in adults. New Engl J Med. 359:492–507. 2008. View Article : Google Scholar : PubMed/NCBI | |
|
Ostrom QT, Gittleman H, Truitt G, Boscia A, Kruchko C and Barnholtz-Sloan JS: CBTRUS statistical report: Primary brain and other central nervous system tumors diagnosed in the United States in 2011–2015. Neuro Oncol. 20 (Suppl 4):iv1–iv86. 2018. View Article : Google Scholar : PubMed/NCBI | |
|
Patel NP, Lyon KA and Huang JH: The effect of race on the prognosis of the glioblastoma patient: A brief review. Neurol Res. 41:967–971. 2019. View Article : Google Scholar : PubMed/NCBI | |
|
Taphoorn MJ, Sizoo EM and Bottomley A: Review on quality of life issues in patients with primary brain tumors. Oncologist. 15:618–626. 2010. View Article : Google Scholar : PubMed/NCBI | |
|
Bartel DP: MicroRNAs: Target recognition and regulatory functions. Cell. 136:215–233. 2009. View Article : Google Scholar : PubMed/NCBI | |
|
Pasquinelli AE: MicroRNAs and their targets: Recognition, regulation and an emerging reciprocal relationship. Nat Rev Genet. 13:271–282. 2012. View Article : Google Scholar : PubMed/NCBI | |
|
Li XT, Wang HZ, Wu ZW, Yang TQ, Zhao ZH, Chen GL, Xie XS, Li B, Wei YX, Huang YL, et al: miR-494-3p regulates cellular proliferation, invasion, migration, and apoptosis by PTEN/AKT signaling in human glioblastoma cells. Cell Mol Neurobiol. 35:679–687. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Chae DK, Park J, Cho M, Ban E, Jang M, Yoo YS, Kim EE, Baik JH and Song EJ: MiR-195 and miR-497 suppress tumorigenesis in lung cancer by inhibiting SMURF2-induced TGF-β receptor I ubiquitination. Mol Oncol. 13:2663–2678. 2019. View Article : Google Scholar : PubMed/NCBI | |
|
Shen J and Li M: MicroRNA-744 inhibits cellular proliferation and invasion of colorectal cancer by directly targeting oncogene notch1. Oncol Res. 26:1401–1409. 2018. View Article : Google Scholar : PubMed/NCBI | |
|
Chen XF and Liu Y: MicroRNA-744 inhibited cervical cancer growth and progression through apoptosis induction by regulating Bcl-2. Biomed Pharmacother. 81:379–387. 2016. View Article : Google Scholar : PubMed/NCBI | |
|
Wang J, Cai H, Dai Z and Wang G: Down-regulation of lncRNA XIST inhibits cell proliferation via regulating miR-744/RING1 axis in non-small cell lung cancer. Clin Sci (Lond). 133:1567–1579. 2019. View Article : Google Scholar : PubMed/NCBI | |
|
Guo Q, Zhang Q, Lu L and Xu Y: Long noncoding RNA RUSC1-AS1 promotes tumorigenesis in cervical cancer by acting as a competing endogenous RNA of microRNA-744 and consequently increasing Bcl-2 expression. Cell Cycle. 19:1222–1235. 2020. View Article : Google Scholar : PubMed/NCBI | |
|
Miyamae M, Komatsu S, Ichikawa D, Kawaguchi T, Hirajima S, Okajima W, Ohashi T, Imamura T, Konishi H and Shiozaki A: Plasma microRNA profiles: Identification of miR-744 as a novel diagnostic and prognostic biomarker in pancreatic cancer. Br J Cancer. 113:1467–1476. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Kleemann M, Schneider H, Unger K, Sander P, Schneider EM, Fischer-Posovszky P, Handrick R and Otte K: MiR-744-5p inducing cell death by directly targeting HNRNPC and NFIX in ovarian cancer cells. Sci Rep. 8:90202018. View Article : Google Scholar : PubMed/NCBI | |
|
Chen S, Shi F, Zhang W, Zhou Y and Huang J: miR-744-5p inhibits non-small cell lung cancer proliferation and invasion by directly targeting PAX2. Technol Cancer Res Treat. 18:15330338198769132019. View Article : Google Scholar : PubMed/NCBI | |
|
Hübner M, Hinske CL, Effinger D, Wu T, Thon N, Kreth FW and Kreth S: Intronic miR-744 inhibits glioblastoma migration by functionally antagonizing its host gene MAP2K4. Cancers (Basel). 25:4002018. View Article : Google Scholar | |
|
Deng Y, Li Y, Fang Q, Luo H and Zhu G: microRNA-744 is downregulated in glioblastoma and inhibits the aggressive behaviors by directly targeting NOB1. Am J Cancer Res. 8:2238–2253. 2018.PubMed/NCBI | |
|
Li Y, Gan S, Ren L, Yuan L, Liu J, Wang W, Wang X, Zhang Y, Jiang J, Zhang F and Qi X: Multifaceted regulation and functions of replication factor C family in human cancers. Am J Cancer Res. 8:1343–1355. 2018.PubMed/NCBI | |
|
Xiong S, Wang Q, Zheng L, Gao F and Li J: Identification of candidate molecular markers of nasopharyngeal carcinoma by tissue microarray and in situ hybridization. Med Oncol. 28 (Suppl 1):S341–S348. 2011. View Article : Google Scholar : PubMed/NCBI | |
|
Xu J, Wang G, Gong W, Guo S, Li D and Zhan Q: The noncoding function of NELFA mRNA promotes the development of oesophageal squamous cell carcinoma by regulating the Rad17-RFC2-5 complex. Mol Oncol. 14:611–624. 2020. View Article : Google Scholar : PubMed/NCBI | |
|
Ho KH, Kuo TC, Lee YT, Chen PH, Shih CM, Cheng CH, Liu AJ, Lee CC and Chen KC: Xanthohumol regulates miR-4749-5p-inhibited RFC2 signaling in enhancing temozolomide cytotoxicity to glioblastoma. Life Sci. 254:1178072020. View Article : Google Scholar : PubMed/NCBI | |
|
Hu T, Shen H, Li J, Yang P, Gu Q and Fu Z: RFC2, a direct target of miR-744, modulates the cell cycle and promotes the proliferation of CRC cells. J Cell Physiol. 235:8319–8333. 2020. View Article : Google Scholar : PubMed/NCBI | |
|
Livak KJ and Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods. 25:402–408. 2001. View Article : Google Scholar : PubMed/NCBI | |
|
Kato T, Natsume A, Toda H, Iwamizu H, Sugita T, Hachisu R, Watanabe R, Yuki K, Motomura K, Bankiewicz K and Wakabayashi T: Efficient delivery of liposome-mediated MGMT-siRNA reinforces the cytotoxity of temozolomide in GBM-initiating cells. Gene Ther. 17:1363–1371. 2010. View Article : Google Scholar : PubMed/NCBI | |
|
Omuro A and DeAngelis LM: Glioblastoma and other malignant gliomas: A clinical review. Jama. 310:1842–1850. 2013. View Article : Google Scholar : PubMed/NCBI | |
|
Gilbert MR, Wang M, Aldape KD, Stupp R, Hegi ME, Jaeckle KA, Armstrong TS, Wefel JS, Won M, Blumenthal DT, et al: Dose-dense temozolomide for newly diagnosed glioblastoma: A randomized phase III clinical trial. J Clin Oncol. 31:4085–4091. 2013. View Article : Google Scholar : PubMed/NCBI | |
|
Cloughesy TF, Cavenee WK and Mischel PS: Glioblastoma: From molecular pathology to targeted treatment. Ann Rev Pathol. 9:1–25. 2014. View Article : Google Scholar : PubMed/NCBI | |
|
Johnson DR and O'Neill BP: Glioblastoma survival in the United States before and during the temozolomide era. J Neurooncol. 107:359–364. 2012. View Article : Google Scholar : PubMed/NCBI | |
|
Luo JW, Wang X, Yang Y and Mao Q: Role of micro-RNA (miRNA) in pathogenesis of glioblastoma. Eur Rev Med Pharmacol Sci. 19:1630–1639. 2015.PubMed/NCBI | |
|
Saadatpour L, Fadaee E, Fadaei S, Mansour RN, Mohammadi M, Mousavi SM, Goodarzi M, Verdi J and Mirzaei H: Glioblastoma: Exosome and microRNA as novel diagnosis biomarkers. Cancer Gene Ther. 23:415–418. 2016. View Article : Google Scholar : PubMed/NCBI | |
|
Cui JQ, Shi YF and Zhou HJ: Expression of RFC2 and PCNA in different gestational trophoblastic diseases. Ai Zheng. 23:196–200. 2004.(In Chinese). PubMed/NCBI | |
|
Olbrich K, Costard L, Möser CV, Syhr KMJ, King-Himmelreich TS, Wolters MC, Schmidtko A, Geisslinger G and Niederberger E: Cleavage of SNAP-25 ameliorates cancer pain in a mouse model of melanoma. Eur J Pain. 21:101–111. 2017. View Article : Google Scholar : PubMed/NCBI | |
|
Mu Y, Yan X, Li D, Zhao D, Wang L, Wang X, Gao D, Yang J, Zhang H, Li Y, et al: NUPR1 maintains autolysosomal efflux by activating SNAP25 transcription in cancer cells. Autophagy. 14:654–670. 2018. View Article : Google Scholar : PubMed/NCBI | |
|
Antonucci F, Corradini I, Morini R, Fossati G, Menna E, Pozzi D, Pacioni S, Verderio C, Bacci A and Matteoli M: Reduced SNAP-25 alters short-term plasticity at developing glutamatergic synapses. EMBO Rep. 14:645–651. 2013. View Article : Google Scholar : PubMed/NCBI | |
|
Fulda S, Wick W, Weller M and Debatin KM: Smac agonists sensitize for Apo2L/TRAIL- or anticancer drug-induced apoptosis and induce regression of malignant glioma in vivo. Nat Med. 8:808–815. 2002. View Article : Google Scholar : PubMed/NCBI | |
|
Shiraishi S, Tada K, Nakamura H, Makino K, Kochi M, Saya H, Kuratsu Ji and Ushio Y: Influence of p53 mutations on prognosis of patients with glioblastoma. Cancer. 95:249–257. 2002. View Article : Google Scholar : PubMed/NCBI | |
|
Wu T and Dai Y: Tumor microenvironment and therapeutic response. Cancer Lett. 387:61–68. 2017. View Article : Google Scholar : PubMed/NCBI | |
|
She X, Yu Z, Cui Y, Lei Q, Wang Z, Xu G, Xiang J, Wu M and Li G: miR-128 and miR-149 enhance the chemosensitivity of temozolomide by Rap1B-mediated cytoskeletal remodeling in glioblastoma. Oncol Rep. 32:957–964. 2014. View Article : Google Scholar : PubMed/NCBI | |
|
Xu P, Yang J, Liu J, Yang X, Liao J, Yuan F, Xu Y, Liu B and Chen Q: Identification of glioblastoma gene prognosis modules based on weighted gene co-expression network analysis. BMC Med Genomics. 11:962018. View Article : Google Scholar : PubMed/NCBI | |
|
Xiang Y, Zhang CQ and Huang K: Predicting glioblastoma prognosis networks using weighted gene co-expression network analysis on TCGA data. BMC Bioinformatics. 13 (Suppl 2):S122012. View Article : Google Scholar : PubMed/NCBI | |
|
Kong Y, Feng ZC, Zhang YL, Liu XF, Ma Y, Zhao ZM, Huang B, Chen AJ, Zhang D, Thorsen F, et al: Identification of immune-related genes contributing to the development of glioblastoma using weighted gene co-expression network analysis. Front Immunol. 11:12812020. View Article : Google Scholar : PubMed/NCBI |
