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Korean Society of Life Science (한국생명과학회)
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Effects of Sasa quelpaertensis Extract on mRNA and microRNA Profiles of SNU-16 Human Gastric Cancer Cells

SNU-16 위암 세포의 mRNA 및 miRNA 프로파일에 미치는 제주조릿대 추출물의 영향

  • Jang, Mi Gyeong (Department of Biology, Jeju National University) ;
  • Ko, Hee Chul (Biotech Regional Innovation Center, Jeju National University) ;
  • Kim, Se-Jae (Department of Biology, Jeju National University)
  • Received : 2020.03.29
  • Accepted : 2020.04.20
  • Published : 2020.06.30
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Abstract

Sasa quelpaertensis Nakai leaf has been used as a folk medicine for the treatment of gastric ulcer, dipsosis, and hematemesis based on its anti-inflammatory, antipyretic, and diuretic characteristics. We have previously reported the procedure for deriving a phytochemical-rich extract (PRE) from S. quelpaertensis and how PRE and its ethyl acetate fraction (EPRE) exhibits an anticancer effect by inducing apoptosis in various gastric cancer cells. To explore the molecular targets involved in this apoptosis, we investigated the mRNA and microRNA profiles of EPRE-treated SNU-16 human gastric cancer cells. In total, 2,875 differentially expressed genes were identified by RNA sequencing, and gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that the EPRE-modulated genes are associated with apoptosis, mitogen-activated protein kinase, inflammatory response, tumor necrosis factor signaling, and cancer pathways. Subsequently, protein-protein interaction network analysis confirmed interactions among genes associated with cell death and apoptosis, and 27 differentially expressed microRNAs were identified by further sequencing. Here, GO and KEGG pathway analysis revealed that EPRE modified the expression of microRNAs associated with the cell cycle and cell death, as well as signaling of tropomyosin-receptor-kinase receptor, transforming growth factor-b, nuclear factor kB, and cancer pathways. Taken together, these results provide insight into the mechanisms underlying the anticancer effect of EPRE.

제주조릿대 잎은 항염, 해열 및 이뇨작용을 가지고 있어 위궤양, 목마름 및 토혈 치료를 위한 민간의약으로 사용되어 왔다. 본 저자들은 제주조리대 잎에서 분리한 피토케미칼 풍부 추출물(PRE)과 그 에틸아세테이트 분획물(EPRE)은 여러 위암 세포주에서 세포사멸을 유도하는 항암 효과가 있다고 보고한 바 있다. 본 연구는 EPRE의 세포사멸 유도 기전에 관여하는 분자표적들을 탐색하기 위하여 EPRE을 처리한 SNU-16 세포에서 mRNA와 microRNA (miRNA)의 프로파일 변화를 분석하였다. RNA sequencing 분석을 통해 총 2,875개의 차등적으로 발현되는 유전자들(DEGs)을 동정하였다. 유전자 온톨로지(GO)와 KEGG 경로 분석 결과, EPRE는 세포사멸, 유사 분열-활성화 단백질 키나제(MAPK) 및 염증 반응, 종양 괴사 인자(TNF) 신호 전달 및 암 경로에 관여하는 유전자들의 발현을 조절하는 것으로 나타났다. 단백질-단백질 상호 작용(PPI) 네트워크 분석으로 세포사멸 및 세포죽음과 관련된 유전자들 간의 상호작용들을 확인할 수 있었다. 그리고, miRNA sequencing 분석을 통해 총 27개의 차별적으로 발현되는 miRNAs (DEMs)를 동정하였다. GO와 KEGG 경로 분석 결과, EPRE는 세포주기, 세포사멸 및 tropomyosin-receptor-kinase (TRK) 수용체 신호 전달, 성장인자-β(TGF-β), 핵인자 κB (NF-κB) 및 암 경로에 관여하는 miRNAs의 발현을 조정하였다. 본 연구결과는 EPRE의 항암 효과의 근본적인 메커니즘에 대한 통찰력을 제공한다.

Keywords

Introduction

Gastric cancer is the fourth most common malignancy and the second leading cause of cancer-related death worldwide[29]. Currently, the most effective treatment for gastric cancer is surgery combined with chemotherapy and radiotherapy;however, these therapies have side effects and can lead to antitherapeutic resistance [33, 39, 40]. Certain plant extracts can ameliorate these side effects, prolong survival, and improve the quality of life by enhancing anticancer activity[5, 17, 34, 36]. Therefore, there is demand for new natural products proven to be safe for the prevention and treatment of gastric cancer.

The genus Sasa (Poaceae) is composed of perennial plants commonly known as dwarf bamboo; various Sasa species are distributed in Asian countries, including China, Japan, Korea, and Russia. Their leaves have been used in traditional medicine for the treatment of gastric ulcer, dipsosis, and hematemesis because of their anti-inflammatory, antipyretic,and diuretic activities [2]. Extracts of the leaves of various Sasa species have anticancer effects. For example, S. albomarginata leaf extract has been used to treat hypertension,cardiovascular disease, and cancer [26,28]. Two polysaccharide preparations from S. kurilensis were found to suppress the growth of sarcoma-180 implanted in mice [22]. An alkaline extract from S. senanensis leaves (containing polysaccharides,chlorophyllin, lignin, and flavonoids) reportedly prevented spontaneous mammary tumorigenesis and Her2/NeuN mammary tumorigenesis [23].

S. quelpaertensis Nakai is a dwarf bamboo grass that growson Mt. Halla on Jeju Island, Republic of Korea. Its leaf extracts have antiobesity, antidepressant, antifatigue, and anticancer activities [12-14, 24]. In addition, we previously reported the preparation method for phytochemical-rich extract(PRE) for efficient utilization of its leaf [15]. PRE and its ethyl acetate fraction (EPRE) have been shown to inhibit the proliferation of human gastric cancer cells (MKN-74, MKN-45, SNU-1, and SNU-16) by inducing apoptosis [11]. The present study was performed to investigate the mRNA and microRNA (miRNA) profiles in EPRE-treated SNU-16 cells to explore the underlying mechanism of this antiproliferative activity.

Materials and Methods

Plant material and extraction

S. quelpaertensis leaves were collected from Mt. Halla on Jeju Island, Republic of Korea. The leaves were washed and dried in a hot air dryer at 60℃ for 24 hr. The resulting powder was extracted for 4 hr with hot water (90℃). The hot water extract was removed, and the residue was used to prepare PRE and EPRE, in accordance with the method described by Lee et al. [15]. PRE is a mixture of such phytonutrients as polysaccharides, amino acids, and polyphenols, including the tricin (5.35 mg/g) and p-coumaric acid (44.10mg/g) as indicator components [16].

Cell culture and cell viability assay

SNU-16 human gastric cancer cells were obtained from the Korean Cell Line Bank (Seoul, Korea). The cells were cultured in Roswell Park Memorial Institute-1640 medium supplemented with 10% fetal bovine serum and 1% penicillin-streptomycin (Gibco, Grand Island, NY, USA) in a 37℃ incubator with a humidified atmosphere containing 5% CO2. To evaluate the cell viability, the cells plated in 96-well plates(2.0×105–3.0×105 cells/ml) were cultured overnight, treated with EPRE and then incubated for an additional 48 hr. Each well was supplemented with 50 μl of MTT and incubated for 4 hr at 37℃. The formazan crystals formed were subsequently dissolved in 150 μl DMSO, and the optical density of the resultant reaction solution was read at 540 nm using a microplate reader (Bio-Tek, VT, USA).

Western blot analysis

The harvested cells were lysed in ice-cold RIPA lysis buffer(Merck, Darmstadt, Germany) according to the manufacturer’s protocol. Protein concentration was quantified using the Bio-Rad Protein Assay reagent (Bio-Rad Laboratories, CA, USA). Proteins were separated on 8% to 12% polyacrylamide gel and then transferred for PVDF membranes. The membranes were blocked for 1hr with 5% skim milk in 0.1% Tween-20 and Tris-buffer saline (TTBS). They were incubated for overnight at 4℃ with the following primaryantibodies; B-cell lymphoma 2 (BCL2), bcl-2-associated X protein (BAX), procaspase-3, poly (ADP-ribose) polymerase(PARP) (Santa Cruz, CA, USA) and cleaved caspase-3 (Cell Signaling Technology, Beverly, MA). The membranes werewashed with TTBS, and incubated with horseradish peroxidase-conjugated secondary antibodies (Jackson Immuno Research, West Grove, PA, USA) for 1 hr at room temperature.Immunodetection was carried out using enhanced chemiluminescence (ECL) western blotting detection reagent(Cyanagen, Bologna, Italy).

RNA extraction

The cells were treated with EPRE (100 μg/ml) for 48 hr;total RNA was then extracted using TRIzol reagent (Invitrogen, Carlsbad, CA, USA). RNA quality was assessed using the Agilent 2100 Bioanalyzer and the RNA 6000 Nano Chip(Agilent Technologies, Amstelveen, Netherlands); RNA was quantified using the ND-2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA).

mRNA sequencing and data analysis

For mRNA sequencing, a library was constructed using SMARTer Stranded RNA-Seq Kit (Clontech Laboratories, Inc., Mountain View, CA, USA). Total RNA (2 μg) was incubated with magnetic beads conjugated to oligo-dT; other RNAs were removed by washing. Library production was initiated by random hybridization of starter/stopper heterodimers to the poly(A) RNA bound to the magnetic beads. These starter/stopper heterodimers contained Illumina-compatible linker sequences. A single-tube reverse transcription and ligation reaction extended the starter to the next hybridizedheterodimer, where the newly synthesized cDNA insert was ligated to the stopper. Second strand synthesis was performed to release the library from the beads, and the library was then amplified. Barcodes were introduced when the library had been amplified. High-throughput sequencing was performed as paired-end 100-bp sequencing using a HiSeq 2500 (Illumina, Inc., San Diego, CA, USA). mRNA-seq reads were mapped using TopHat software [32] to obtain alignment files. Differentially expressed genes (DEGs) were determined based on counts from unique and multiple alignments using coverage in Bedtools [21]. Read count data were processed based on the quantile normalization method using EdgeR within R (R Development Core Team, 2016) and Bioconductor [7]. Alignment files were used for assembly of transcripts, estimation of abundances, and detection of differential expression of genes or isoforms using Cufflinks. The fragments per kilobase of exon per million fragments method was used to determine gene expression levels. Gene classification was based on searches performed in DAVID (http://david.abcc.ncifcrf.gov/). The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database was used to provide a comprehensive protein interactome that included known and predicted protein-protein interactions, which were given confidence scores; accessory information (e.g., protein domains and 3D structures) was also searched within this stable and consistent identifier space. Networks were visualized and analyzed using Cytoscape 3.3.0 visualization software (http://www.cytoscape.org/).

miRNA sequencing and data analysis

For miRNA sequencing, a library was constructed using a NEBNext Multiplex Small RNA Library Prep Kit (New England BioLabs, Inc., Ipswich, MA, USA). Total RNA (1μg) was ligated to the adaptors and cDNA was synthesized using reverse transcriptase with adaptor-specific primers. PCR was performed for library amplification and libraries were cleaned-up using the QIAquick PCR Purification Kit(Qiagen, Inc., Hilden, Germany) and AMPure XP beads(Beckman Coulter, Inc., Brea, CA, USA). The yields and size distributions of small RNA libraries were assessed by high-sensitivity DNA assays using the Agilent 2100 Bioanalyzer(Agilent Technologies, Inc.). High-throughput sequences were produced by the NextSeq 500 system for single-end 75 sequencing (Illumina). Sequence reads were mapped by Bowtie2 software to obtain a bam alignment file. A mature miRNA sequence was used as a reference for mapping. Read counts mapped on the mature miRNA sequence were extracted from the alignment file using Bedtools (v.2.25.0) and Bioconductor, which utilizes the R (v. 3.2.2) statistical programming language (R Development Core Team,2011). Read counts were assessed to determine the levels ofmiRNAs. The quantile normalization method was used for comparisons between samples. For miRNA target analyses,miRWalk 2.0 software was used. Functional gene classification was performed using DAVID (http://david.abcc.ncifcrf.gov/). For pathway analysis, genes were selected and input into the KEGG mapper (http://www.genome.jp/kegg/tool/map_pathway2.html). Significant pathways that included selected genes were recorded. CluePedia software,based on the mirTarBase.validated.miRNAs_15.06.2016inCytoscape (v. 3.7.1), was used to investigate interactions between miRNAs and their target genes. The criteria for network interaction formation were analyzed using the default value for each database.

Quantitative real-time PCR

For quantification of mRNA, reverse transcription was performed using SuperScript II RTase (Invitrogen). Real-time PCR was performed on the StepOnePlus™ Real-Time PCR System with the SYBR Green PCR Kit (Applied BiosystemsInc., Foster City, CA, USA), using the primers listed in Table 1. Thermal cycling conditions were 95℃ for 10 min, followed by 40 cycles of 95℃ for 15 s and 59℃ for 30 s. Data were analyzed using StepOne software v. 2.2.2 (Applied Biosystems). The expression level of each gene was normalized to the level of the endogenous control (GAPDH) and calculated using the 2−ΔΔCt method. For quantification of miRNA, cDNA synthesis and real-time PCR were performed using the miScript PCR system (Qiagen). cDNA was synthesized from total RNA using the miScript II RT Kit with HiSpecbuffer. cDNA was amplified from miRNA using the following primer pairs: hsa-miR-136-5p, hsa-miR-320d, hsa-miR-132-5p, hsa-miR-1260b, and has-miR-92a-1-5p; hsa-U6 was used as the internal control. Real-time PCR was performed on the StepOnePlus Real-Time PCR System (Applied Biosystems) with QuantiTect SYBR Green PCR Master Mix and miScript Primer Assay (Qiagen). Thermal cycling conditions were 95℃ for 15 min, followed by 40 cycles of 94℃ for 15s, 55℃ for 30 s, and 70℃ for 30 s. Data were analyzed using StepOne software v. 2.2.2 (Applied Biosystems). The expression level of each microRNA was normalized to the level of an endogenous small RNA U6 and calculated using the 2-ΔΔCt method.

Table 1. The primer sequences of the genes used in Real-time PCR analysis

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Statistical analysis

Statistical analysis was performed using SPSS Statistics v.12.0 for Windows (SPSS Inc., Chicago, IL, USA). Data are expressed as means ± standard deviations. Differences between groups were examined by one-way analysis of variance. Differences with p<0.05 were considered statistically significant.

Results and Discussion

The leaves of Sasa species have been used in Eastern Asia as a potential source of natural drug since hundreds of years ago. S. quelpaertensis leaves are considered as one of the useful sources for food, nutraceuticals, and cosmetics because of their therapeutic potential [12-16, 24]. To expend the applicability of S. quelpaertensis leaves as cancer preventive agent, we investigated the effects of EPRE on cell viability, and evaluated the mRNA and miRNA profiles of EPREtreated SNU-16 cells.

Cell viability

The cytotoxicity of PRE solvent fractions was evaluatedin the human gastric cancer cell (SNU-16) and human skin fibroblasts (Hs-68) using the MTT assay. As shown in Fig. 1, EPRE inhibited the most effectively the proliferation ofSNU-16 cells (IC50 = 21.1 μg/ml), but it did not show cytotoxicity to normal HS-68 cells. EPRE decreased the expressions of Bcl-2 and procaspase-3, but increased the expressions of Bax, cleaved caspase-3, and cleaved PARP in a dose-dependent manner. These results suggested that EPRE inhibited cell growth by inducing apoptosis of SNU-16 cells through mitochondrial mediated pathway. Apoptosis can be activated through two main pathways: the mitochondrial-dependent pathway and the death receptor dependent pathway [35]. The Bcl-2 family, which acts on mitochondrial-dependent pathways, includes pro-apoptotic (Bax, Bad, Bak) and anti-apoptotic members (Bcl-2) [6]. Caspase-3 is activated from pro-caspase-3 by the nuclear enzyme PARP, and is known as a major player in apoptosis [30].

SMGHBM_2020_v30n6_501_f0001.png 이미지

Fig. 1. The cell viability and expression of apoptosis-related proteins in EPRE-treated SNU-16 cells. (A) The cells were incubated with different solvent fractions (100 μg/ml). (B) Cells were incubated with different concentration of EPRE. (C) Western blot analysis. (D) HS-68 cells were incubated with different concentration of EPRE. The data expressed means ± standard deviation (SD) of three independent experiments. *p<0.05, **p<0.01, and ***p<0.001 compared to the untreated group. Western blotting results are representative of three independent experiments.

mRNA profile

RNA-seq was performed to identify DEGs in EPRE-treated cells, compared to untreated SNU-16 cells. Among 25,737 genes, 2,875 DEGs (2.7-fold cut-off) were identified; of these,1,200 were upregulated and 1,675 were downregulated. GO analysis revealed that EPRE significantly enriched 280 GO terms in the biological process category, including apoptosis,cell proliferation, and inflammatory response; 37 GO termsin the cellular component category, including extracellularexosome, nucleoplasm, intracellular and perinuclear cytoplasm; and 78 GO terms in the molecular function category, including protein binding, DNA binding, and ATP binding(Fig. 2A). KEGG pathway analysis showed that the cancer,MAPK signaling, and TNF signaling pathways were highly enriched by EPRE (Fig. 2B). Liu et al. [18] reported that activation of the reactive oxygen species(ROS)/ASK1/MAPKpathway induces apoptosis in human lung cancer cells. Certain cancer preventive substances induced apoptosis by activation of p38 MAPK in hepatocellular carcinoma cells[4]. Considering these previous studies, EPRE seems to influence the expression of genes that are closely related to apoptosis in SNU-16 cells.

SMGHBM_2020_v30n6_501_f0002.png 이미지

Fig. 2. The GO and KEGG pathway analysis of differentially expressed genes (DEGs) in EPRE-treated SNU-16 cells. (A) The 280 annotated genes regulated by EPRE were assigned into biological process, cellular component, and molecular function categories based on gene ontology annotations. (B) KEGG pathway analysis.

A protein-protein interaction(PPI) analysis using Cytoscapev. 3.0 (STRING database, cut-off >0.4) showed that the protein-protein interaction network consisted of 154 nodes and 403 edges; moreover, v-myc avian myelocytomatosis viral oncogene homologous (MYC), Fas-associated via death domain (FADD), BCL2-like 14 (BCL2L14), mitogen-activated protein kinase kinase kinase 5 (MAP3K5), and BCL-2-associated X protein (BAX) were located at the major key nodes(Fig. 3). SNU-16 human gastric cancer cells have an abnormal p53 gene and express MYC [20]. MYC controls cell proliferation,differentiation, and apoptosis; inhibition of MYC expression induces brain tumor cell death [41]. BCL2L14 is a member of the Bcl-2 family; it is associated with apoptosis in laryngeal squamous cell carcinoma, prostate cancer, and acute leukemia cancer cells [38]. FADD transmits cell death signals by activation of procaspase-8 [1,19]. MAP3K5 is also known as apoptosis pathway control kinase 1 (ASK1); it is activated by ROS and Fas, as well as other factors [8,31].Downregulation of ASK1 expression reportedly promotes cancer cell apoptosis [9,10]. Therefore, EPRE may exert the anti-cancer effects by modulating the expression of genes that regulate SNU-16 cell apoptosis.

SMGHBM_2020_v30n6_501_f0003.png 이미지

Fig. 3. The protein–protein interaction networks (PPI) among differentially expressed genes (DEGs) in EPRE-treated SNU-16 gastric cancer cells. PPI network was constructed by the String online tool with a confidence score of >0.4. The nodes represent proteins, edges represent interactions between proteins, and the colors of the nodes represent the log2 fold change in the expression level. Red node stands for up-regulated gene and blue node stands for down-regulated gene. The disconnected nodes in the network were hidden.

miRNA profile

MiRNA sequencing was performed to examine the effect of EPRE on the miRNA profile of SNU-16 gastric cancer cells. Compared with untreated control cells, 27 differentially expressed miRNAs (DEMs) were identified in EPRE-treated cells (fold-change >2.7). Among these 27 DEMs, 10 were upregulated and 17 were downregulated (Table 2). GO analysis showed that 222 biological process GO terms were significantly enriched (miRTbase); the top 25 GO terms were related to the cell cycle, cell death, and the tropomyosin-receptor-kinase receptor signaling pathway (Fig. 4A). KEGG pathway analysis revealed 50 significant pathways (p<0.05)(Table S1). Among the top 20 pathways, DEMs were associated with the transforming growth factor-β pathway, nuclear factor-kappaB (NF-κB) pathway, wingless-related integration site (Wnt) signaling pathway, and cancer signaling pathway (Fig. 4B).

Table 2. List of differentially expressed miRNAs in EPRE-treated SNU-16 cells (fold change >2.7, p-value <0.05)

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SMGHBM_2020_v30n6_501_f0004.png 이미지

Fig. 4. GO and KEGG pathway analysis of differentially expressed miRNAs (DEMs) in EPRE-treated SNU-16 cells. The top 20 GO terms (A) and the top 10 KEGG pathway (B) significantly enriched by DEMs.

To evaluate the interactions between 27 DEMs and their target genes, network analysis was performed using Cyto scape v. 3.7.1 (Fig. 5). The network comprised 21 nodes that consisted of 21 DEMs: miR-136-5p, miR-320d, miR-6131, miR-132-5p, miR-92a-1-5p, miR-320e, miR-6073, miR-32-3p, miR-1260b, miR-4483, miR-4301, miR-548aj-5p, miR-1261, miR-181b-3p, miR-1290, miR-25-5p, miR-27a-5p, miR-29b-1-5p, miR-4454, miR-365a-5p, and miR-1246. Potential target genes of the 21 DEMs involved in the network are listed in Table S2.

SMGHBM_2020_v30n6_501_f0005.png 이미지

Fig. 5. Network between differentially expressed miRNAs and potential target genes. The yellow diamond-shapes node indicate target genes, gray circles indicate target miRNAs.

It is well known that various cellular activities like cell growth, proliferation, and differentiation are regulated by miRNAs through their regulatory effects on particular RNA species. In many tumors, up- or down-regulation of different miRNAs has been reported. MiR-136-5p was highly upregulated in EPRE-exposed SNU-16 cells. Expression of miR-136-5p was reportedly reduced in ovarian cancer and glioma cell lines; moreover, it promoted chemotherapy-induced death of glial cells [37,42]. MiR-136-5p suppresses tumor growth and migration, while induces apoptosis [3]. Also, it has been reported that the overexpression of miR-320d has been shown to inhibit proliferation of breast cancer cells and induce apoptosis of these cells [27]. In addition, it was reported that the apoptosis of human acute promyelocytic leukemia cell line (HL-60) can be induced by inhibiting miR-92a [25]. Therefore, it is suggested that the anticancer effect of EPRE may be mediated by modulating key miRNA expressionsin SNU-16 cells.

Validation of RNA-seq data

To validate the mRNA-seq data, qRT-PCR analysis was performed for randomly selected genes. The levels of MYC, MAP3K5, and BCL2L14 mRNAs in EPRE-treated cells were significantly lower, while the level of FADD mRNA tended to be lower comparing to untreated control cells. These qRTPCR results are consistent with the mRNA-seq data (Fig. 6A). Also, to validate the miRNA-seq data, we performed qRT-PCR analysis for five randomly selected miRNAs. We found that miR-136-5p and miR-320d were significantly upregulated in EPRE-treated cells, compared to untreated control cells. In contrast, miR-132-5p, miR-1260b, and miR-92a-1-5p were significantly downregulated in EPRE-treated cells. These qRT-PCR results are consistent with the miRNA-seq data (Fig. 6B).

SMGHBM_2020_v30n6_501_f0006.png 이미지

Fig. 6. Validation of differentially expressed mRNAs and miRNAs using qRT-PCR. (A) Cells were incubated with 100 μg/ml of EPRE for 48 hr. Expression levels of the genes (MAP3K5, MYC, FADD, BCL2L14) were analyzed by quantitative RT-PCR and normalized by GAPDH. (B) Expression levels of miRNAs (miR-136-5p, miR-320d, miR-132-5p, miR-1260b, miR-92a-1-5p) were analyzed by quantitative RT-PCR and normalized by has-U6. The data are expressed as means ± standard deviation(SD) of three determinations. *p<0.05, **p<0.01, and ***p<0.001 compared to untreated SNU-16 cancer cell.

In summary, EPRE inhibited the proliferation of SNU-16cells by activating apoptosis. Total 2,875 DEGs and 27 DEMs were identified in EPRE-treated SNU-16 cells, compared to untreated control cells. Most DEGs and DEMs were associated with biological processes and signaling pathways,such as the cell death, apoptosis, NF-κB, cancer, MAPK, and TNF signaling pathways. The collective findings suggest that EPRE exerts an anticancer effect through regulation of several key genes and miRNAs involved in these pathways. Further research is needed to identify the molecular mechanisms underlying the anticancer effects of EPRE.

Acknowledgment

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education(2017R1D1A3B03029845 and 2019R1A6A10072987).

The Conflict of Interest Statement

The authors declare that they have no conflicts of interest with the contents of this article.

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