Next Article in Journal
Triple-Negative Primary Breast Tumors Induce Supportive Premetastatic Changes in the Extracellular Matrix and Soluble Components of the Lung Microenvironment
Previous Article in Journal
Polymeric Nanoparticles for the Treatment of Malignant Gliomas
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Cancers
Volume 12
Issue 1
10.3390/cancers12010174
cancers-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The MicroRNA-23b/27b/24 Cluster Facilitates Colon Cancer Cell Migration by Targeting FOXP2

by
Kensei Nishida
*,
Yuki Kuwano
and
Kazuhito Rokutan
Department of Pathophysiology, Institute of Biomedical Sciences, Tokushima University Graduate School, 3-18-15 Kuramoto-cho, Tokushima 7708503, Japan
*
Author to whom correspondence should be addressed.
Cancers 2020, 12(1), 174; https://doi.org/10.3390/cancers12010174
Submission received: 6 December 2019 / Revised: 6 January 2020 / Accepted: 9 January 2020 / Published: 10 January 2020
Browse Figures
Versions Notes

Abstract

:
Acquisition of cell migration capacity is an early and essential process in cancer development. The aim of this study was to identify microRNA gene expression networks that induced high migration capacity. Using colon cancer HCT116 cells subcloned by transwell-based migrated cell selection, microRNA array analysis was performed to examine the microRNA expression profile. Promoter activity and microRNA targets were assessed with luciferase reporters. Cell migration capacity was assessed by either the transwell or scratch assay. In isolated subpopulations with high migration capacity, the expression levels of the miR-23b/27b/24 cluster increased in accordance with the increased expression of the short C9orf3 transcript, a host gene of the miR-23b/27b/24 cluster. E2F1-binding sequences were involved in the basic transcription activity of the short C9orf3 expression, and E2F1-small-interfering (si)RNA treatment reduced the expression of both the C9orf3 and miR-23b/27b/24 clusters. Overexpression experiments showed that miR-23b and miR-27b promoted cell migration, but the opposite effect was observed with miR-24. Forkhead box P2 (FOXP2) mRNA and protein levels were reduced by both/either miR-23b and miR-27b. Furthermore, FOXP2 siRNA treatment significantly promoted cell migration. Our findings demonstrated a novel role of the miR-23b/27b/24 cluster in cell migration through targeting FOXP2, with potential implications for the development of microRNA-based therapy targeted at inhibiting cancer migration.

1. Introduction

Cell migration plays a pivotal role in epithelial–mesenchymal transition (EMT), invasion, or metastasis in various types of tumors. Tumors can adapt to microenvironments, resulting in heterogeneous subpopulations with distinct properties of proliferation, migration, invasion, or sensitivity to therapies. As a consequence of cellular adaptation, some tumor cells lose their epithelial characteristics, gain mesenchymal properties, and aggressively migrate to the non-tumorigenic extracellular matrix, and are described as EMT. Cell migration is an essential property of EMT and can be a therapeutic target for inhibiting metastatic progression [1].
MicroRNAs (miRNAs) are small non-coding RNAs (containing 21–22 nucleotides), which promote either mRNA degradation or block their translation through binding to partially complementary sequences of their target mRNAs. A single miRNA has more than 100 target mRNAs, and post-transcriptionally regulates their expression profiles. Therefore, altered expression patterns of even a small number of miRNAs could influence cell phenotype, including tumorigenesis and malignant transformation, through regulation of a wide range of biological processes [2,3]. A miRNA cluster is a set of more than two miRNAs produced from a single primary transcript. miRNAs belonging to clusters coordinately regulate multiple processes through targeting functionally related proteins [4,5,6,7]. The miR-23b/27b/24 cluster is composed of three miRNA genes located within an intron of C9orf3 gene on human chromosome 9q22.32. Although previous studies have investigated the roles of miR-23b/27b/24 miRNAs in tumor progression, conflicting functions of miR-23b/27b/24 miRNAs have been reported during tumor development and metastatic progression [8,9]. Inhibition of miR-23b has been shown to decrease proliferation, migration, and invasion in nasopharyngeal carcinoma by directly targeting E-cadherin [10]. Down-regulation of miR-27b inhibits cell growth and invasion in cervical cancer cells [11]. Both miR-23b and miR-27b cooperatively regulate Nischarin expression, resulting in the promotion of tumorigenic properties in breast cancer cells [12]. Conversely, several studies reported that either miR-23b or miR-27b acts as a tumor suppressor in breast and colorectal cancers [8,9]. Most research on miR-23b/27b/24 miRNAs has focused on the roles of individual miRNAs in regulating specific target genes. However, potential coordinated effects of the miR-23b/27b/24 cluster on tumor progression are not fully understood. Furthermore, based on the knowledge of intronic miRNAs biogenesis, the pri-miR-23b/27b/24 cluster could be transcribed as part of the transcript of the host gene, C9orf3. The precise mechanism of regulation of the miR-23b/27b/24 cluster expression has not been investigated.
In this study, using a subpopulation with high migration capacity isolated from HCT116 cells using transwell apparatus [13], we sought to identify the miR-23b/27b/24 cluster, whose expression was upregulated in a subpopulation with cell migration capacity. The promoter assay of C9orf3, the host gene of the miR-23b/27b/24 cluster, revealed that E2F1 was involved in the regulation of the basic transcription activity of the short C9orf3 transcript. Furthermore, we identified forkhead box P2 (FOXP2) as a novel target for both miR-23b and miR-27b. The miR-23b/27b/24 cluster may promote, at least in part, cell migration by regulating FOXP2 expression.

2. Results

2.1. Identification of miRNAs Responsible for the High Migration Capacity

We have previously succeeded in isolating a subpopulation with accelerated baseline motility (migrated cells [MG] cells) and an immotile one (non-MG cells) from a colon cancer cell line (HCT116 p53 wild type) [13]. The MG cell subpopulation was composed of EMT intermediates with high expression levels of EMT marker genes ZEB1 and VIM [13]. In addition, MG cells expressed surface markers of colorectal cancer stem cells (ALDH1A1, CD24, POU5F1, SOX2, and SOX9) to a greater degree compared with non-MG cells [14] (Figure S1). Using these subpopulation cells, we investigated novel regulatory miRNAs involved in cell migration. To identify miRNAs differentially expressed in the MG cells, we prepared total RNA samples from the MG and the non-MG cells, respectively. These samples were subjected to miRNA microarray analysis, and miRNA expression profiles were compared between MG and non-MG cells. Of the 939 probes, 124 probes were passed over the threshold of the “Flag at Present.” Followed by further filtering of the raw signal intensity of 50 in at least one sample, 56 human miRNAs remained. Using the mean expression change of 1.5-fold criterion, we identified four miRNAs (miR-10a, miR-23b, miR-27b, and miR-1274b) differentially expressed between MG and non-MG cells (Table 1). Because miR-1274b is defined as a dead entry on the miRBase (Release 21), miR-1274b was excluded from further analysis. We validated the miRNA expression of miR-10a, miR-23b, and miR-27b. miR-23b and miR-27b belong to the same miR-cluster, which contains miR-23b, miR-27b, and miR-24. Therefore, we also measured miR-24 expression levels besides miR-23b and miR-27b. The amounts of miR-23b, miR-27b, and miR-24 in MG cells were significantly higher than those in non-MG cells (Figure 1A). However, we could not detect the sufficient expression of miR-10a in both the MG and non-MG cells.

2.2. Transcription of Short C9orf3 Isoforms in the MG Cells

The miR-23b/27b/24 cluster is located at intron 14 of C9orf3 transcript (ENST00000297979). Because the expression levels of all three members of the miR-23b/27b/24 cluster were upregulated in MG cells, we investigated changes in the gene expression of a host gene of the miR-23b/27b/24 cluster, C9orf3. Using five primer sets designed for amplification of different segments of the C9orf3 transcript, we measured C9orf3 expression levels by real-time reverse transcription polymerase chain reaction (RT-qPCR). Although both MG and non-MG cells expressed similar amounts of amplified products containing exon 1 to 2 or exon 3 to 4 of C9orf3 mRNA, amounts of amplified products containing exon 10 to 12, exon 13 to 15, or exon 14 to 15 of C9orf3 mRNA were significantly increased about 3-fold in the MG cells (Figure 1B). Furthermore, we evaluated the clinical relevance of gene expression differences within the C9orf3 gene. As shown in Figure 1C,D, although the expression levels of C9orf3 exons 1 to 4 were similar irrespective of the presence or absence of lymphatic invasion in colorectal adenocarcinoma, those of C9orf3 exons 12 and 13 were significantly upregulated in samples with lymphatic invasion. Furthermore, patients with high expression levels of C9orf3 exons 12 and 13 exhibited a lower overall survival than patients with lower expression levels. In contrast, the expression levels of C9orf3 exons 1 to 4 did not affect overall survival (Figure 1E,F). These data suggest that the mRNA levels of the latter part of C9orf3 are associated with cell migration or invasion and lead to poor prognosis. The discrepancy in exon expression levels in C9orf3 is consistent with the presence of short C9orf3 transcripts (containing exons 10–15) in MG cells. To confirm this hypothesis, we employed 5′-rapid amplification of cDNA end (RACE) analysis using primers of C9orf3 exon 14 as detailed in Figure S2. Eighteen clones were isolated and sequenced by the Sanger method, and we identified two novel transcriptional start sites (TSSs), TSS1, and TSS2. Of 18 clones, 13 clones corresponded to TSS2 sequence, suggesting that TSS2 was preferentially used as the first exon in MG cells (Figure S2A,B). Indeed, TSS2 expression levels were three times higher than those of TSS1, detected by absolute quantification of gene expression using RT-qPCR (Figure S2C). Therefore, we focused on TSS2-containing short C9orf3 transcript in further analyses.

2.3. Regulation of Short C9orf3 Expression

2.3.1. Effect of DNA Methylation on C9orf3 and miR-23b/27b/24 Expression

Hovestadt et al. performed a comprehensive assessment of the correlation between DNA methylation and gene expression; they predicted the presence of a short C9orf3 transcript in WNT-pathway activated medulloblastoma [15]. They also showed that the expression of either C9orf3 or individual miRNAs of the miR-23b/27b/24 cluster is negatively correlated with CpG island methylation. To evaluate the effect of DNA methylation on the expression of individual miRNAs of the miR-23b/27b/24 cluster, we measured these expression levels after 48 h treatment with 5-azacytidine (5-aza), a DNA methyltransferase inhibitor. The levels of each microRNA of the miR-23b/27b/24 cluster were rather decreased in the non-MG cells. Additionally, the mRNA expression of TSS1 and TSS2 in short C9orf3 was not affected by 5-aza treatment. These data suggested that DNA methylation was neither involved in the transcriptional regulation of short C9orf3 mRNA nor miR-23b/27b/24 miRNA expression in our isolated HCT116 cell lines (Figure S3).

2.3.2. Promoter Array of Short C9orf3 Transcript

Next, we investigated the mechanism underlying the transcriptional regulation of the TSS2-containing short C9orf3 transcript. To determine the minimal promoter region of the short C9orf3 transcript, we generated a luciferase reporter vector having the 5′-flank of the short C9orf3 from −825 to +77 bp, and then serially truncated the fragments that were constructed. As shown in Figure 2A, the basal promoter activity was found to reside in −95 to +77 bp fragment sequence. Potential transcription factor binding sites within the −95 to +1 bp in the short C9orf3 promoter were predicted using ALGGEN PROMO version 3.0.2 [16,17]. The region was a GC-rich sequence (86% GC), and a number of E2F1 binding sites (13 sites) were top-ranked (Figure 2B). Increased E2F1 expression has been reported to be associated with cell migration and tumor development [18,19,20]. Indeed, MG cells expressed E2F1 mRNA and protein to a much greater degree compared with non-MG cells (Figure 2C,D). To reveal whether E2F1 interacted with the promoter region in vivo, chromatin immunoprecipitation (ChIP) assay was employed. Cross-linked chromatin from both the MG cells and non-MG cells was immunoprecipitated using anti-E2F1 antibody or normal rabbit IgG. We designed PCR primers to amplify the section of the promoter region of C9orf3 (−95 to +198 bp), which contained putative E2F1-binding sequences. As a negative control for the ChIP assay of E2F1, we designed a primer set for the C9orf3 promoter region (−1033 to −902 bp), where E2F1-binding sequence does not exist. The PCR products of E2F1-immunoprecipitated chromatin were amplified with a primer set of the promoter region of C9orf3 (−95 to +198 bp), only in the MG cells (Figure 2E). Thus, ChIP assay suggested the preferential binding of E2F1 to the short C9orf3 promoter region in the MG cells.

2.4. Effects of E2F1 on C9orf3 and miR-23b/27b/24 Expression

The results of the promoter assay of C9orf3 and ChIP with anti-E2F1 antibody suggested E2F1 as a potent transcriptional activator of the short C9orf3 transcript. We measured C9orf3 mRNA and miR-23b/27/24 miRNA expression in the MG cells when treated with two small-interfering (si)RNAs, targeting different sites of E2F1 over 48 h. These siRNAs effectively reduced E2F1 protein levels (Figure 3A). Both C9orf3 mRNA levels and miR-23b/27b/24 miRNAs were significantly decreased in these cells (Figure 3B,C). However, the additional inhibitory effect of E2F1 knockdown on miR-23b/27b/24 expression was not observed in non-MG cells expressing E2F1 at relatively low levels (Figure S4).

2.5. Effects of the miR-23b/27b/24 Cluster on Cell Migration

2.5.1. Effect of miR-23b, miR-27b, and miR-24 on Cell Migration

Previous studies showed the pleiotropic functions of each miRNA member of the miR-23b/27b/24 cluster in cancer. They can function as oncogenes or tumor suppressors depending on the context. To reveal the effects of miR-23b/27b/24 cluster on cell migration, we assessed the cell migratory capacity using transwell assay. As shown in Figure 4A and Figure S5A overexpression treatment with mixed miRNAs of miR-23b, miR-27b, and miR-24 in both non-MG cells and MG cells enhanced the cell migration capability. Consistent with this effect, inhibitory treatment with mixed miRNA inhibitors of miR-23b, miR-27b, and miR-24 in MG cells, but not in non-MG cells, significantly reduced the cell migration capability (Figure 4B and Figure S5B). Furthermore, we obtained similar effects of miR-23b, miR-27b, and miR-24 during migration in other colon cancer cells; DLD1, RKO, and HT-29 cells (Figure 4C–E).

2.5.2. Effect of a Single MicroRNA on Cell Migration

We also confirmed that for the effects of individual miRNAs of miR-23b/27b/24 cluster on cell migration, transwell (Figure 5A) and scratch assays (Figure 5B) were employed. As shown in Figure 5A, mimics miR-23b and miR-27b enhanced cell migration, whereas miR-24 attenuated the cell migratory capability. We employed combinational transfections mimicking miR-23b, miR-27b, and/or miR-24. As shown in Figure 4 and Figure 5B, all three mimicking miRNA (miR-23b/27b/24) treatment modalities and the combinational treatment of the mimic miR-23b and/or miR-27b significantly enhanced cell migration. However, a single treatment of mimic miR-24 rather inhibited the cell migration; suggesting that miR-23b and miR-27b, but not miR-24, may be involved in cell migration capacity (Figure 5A,B).

2.6. Identification of Common Target mRNAs of miR-23b and miR-27b

Because miR-23b and miR-27b promoted cell migration capacity, we searched for the possible target mRNAs for these two miRNAs using miRDB. It is known that members of the cluster miRNAs often synergistically regulate the same target mRNA. We therefore focused on mRNAs with putative target sites for both miR-23b and miR-27b. Based on miRDB, we picked up 193 and 152 genes as miR-23b and miR-27b targets, respectively. Among these genes, we selected eight candidate genes: CLCN3, KCNK2, FOXP2, PKIA, SEC24A, TRIL, ZDHHC17, and ZBTB34 (Figure 6A). Validation of the expression of these mRNAs in the non-MG and MG cells by qRT-PCR showed that FOXP2 and ZDHHC17 mRNA expression was significantly downregulated in the MG cells, suggesting that these mRNAs were possible mRNA targets of miR-23b and miR-27b (Figure 6B). It has been reported that FOXP2 is associated with the development of several types of cancers [21,22,23]. FOXP2 protein levels were significantly reduced in the MG cells compared with those in the non-MG cells (Figure 6C). The overexpression of mimic miR-23b and/or miR-27b decreased FOXP2 mRNA and protein levels (Figure 6D,E), suggesting that miR-23b and miR-27b may regulate FOXP2 expression.

2.7. miR-23b and miR-27b Directly Target the 3′ UTR of FOXP2

The miRDB program predicted the putative binding sites for miR-23b and miR-27b in the 3′ UTR of FOXP2 at nt 402–409 and nt 87–94, respectively (Figure 7A). To verify the potential binding sequences of miR-23b and miR-27b, we prepared the reporter plasmids (psiCHECK2) that expressed chimeric RNAs containing the sequence for Renilla and 3′ UTR sequence of FOXP2, and evaluated the effects of miRNAs on the chimeric RNAs by the dual luciferase assay system. The co-overexpression of miR-23b and miR-27b significantly reduced the luciferase activity of Renilla_FOPX2-3′UTR (Figure 7B). Two mutant vectors (MT1 and MT2), which harbored the six-point mutations within each binding sites for miR-23b or miR-27b (Figure 7A), slightly, but significantly, rescued each microRNA-reduced luciferase activity, suggesting that FOXP2 may be regulated, at least in part, by miR-23b and/or miR-27b (Figure 7C,D).

2.8. Promotion of Cell Migration in the FOXP2 Knockdown Cells

FOXP2 was initially identified as the genetic factor of speech disorder, and its mutations lead to speech and language disorder. Recently, several lines of evidence have revealed that the down-regulation of FOXP2 may be associated with tumor initiation, development, or metastasis [21,22,23,24]. To investigate the effects of FOXP2 on cell migration, we employed transwell and scratch assays. The non-MG cells were transfected with two different siRNAs (#1 and #2) targeting FOXP2 for 36 h. The two independent siRNAs efficiently reduced FOXP2 protein levels (Figure 8A). The transwell assay showed that inhibition of FOXP2 expression increased the number of migrated cells, and the scratch assay also showed that FOXP2 siRNA treatment significantly facilitated cell migration (Figure 8B,C). These data suggested that FOXP2 may play the role of a migration inhibitory factor in the non-MG cells.

3. Discussion

Extensive genome-wide analyses have elucidated that genetic heterogeneity is observed as a common feature of various tumors. During cancer development, genetic heterogeneity contributes to cancer adaptation to their surrounding microenvironments. Cell migration is an essential step in cancer metastasis. In the present study, we found up-regulation of miR-23b/27b/24 cluster expression in a subpopulation with high migration capacity using the transwell-based migrated cell selection. Further analyses showed that the overexpression of either or both miR-23b and miR-27b may promote cell migration via potentially targeting FOXP2.
Intratumor heterogeneity is a fundamental mechanism to cope with diverse surrounding microenvironments, such as immune cells and stroma cells. Sato et al. reported that even a cell line is composed of highly heterogeneous cells [25]. They showed that certain subpopulation of cultured cells with immortal phenotype could be putative cancer stem cells. We successfully isolated a subpopulation with high migration capacity by transwell-based migrated cell selection. We were interested in molecules, which introduce distinct subpopulations. In this study, we focused on miRNA regulation involved in acquisition of cell migration capacity. Recently, as numerous studies revealed, the altered expression of miRNAs is involved in cancer development and prognosis [26]. We showed here that miR-23b/27b/24 cluster may be involved in the acquisition of migratory phenotype. The miR-23b/27b/24 cluster belongs to the hetero-seed clusters, which have distinct seed sequences [27]. Although several reports have revealed the functions of individual miRNAs belonging to miR-23b/27b/24 cluster, there are few and controversial evidences which mentioned the functions of miR-23b/27b/24 cluster. The expression of the miR-23b/27b/24 cluster is significantly reduced in prostate cancer tissues, and the overexpression of miR-27b and miR-24 inhibits cell invasion and migration in prostate cancer cell lines [28]. In contrast, in breast cancer, the miR-23b/27b/24 functions in tumor progression, and promotes metastasis [12,29]. However, the function of miR-23b/27b/24 cluster in colon cancer cells has not been studied. The present study is the first report about the function of miR-23b/27b/24 cluster in colon cancer cells migration. Interestingly, the overexpression of either or both miR-23b and miR-27b promoted cell migration, but miR-24 had an opposite effect in cell migration, suggesting that the expression balance of individual miRNAs, belonging to miR-23b/27b/24 cluster, may be associated with distinct phenotypes.
Approximately 40% of mammalian miRNAs are located within introns of host genes, and their expression is transcriptionally linked to their host gene expression and processed from the same primary transcript. In the human genome, most intronic miRNAs show correlated expression with their host genes, and intronic miRNAs often support the function of their host genes by synergistic mediating and antagonistic regulatory effects [30]. We found increased levels of miR-23b, miR-27b, and miR-24 expression consistent with the mRNA levels of C9orf3 (a host gene in the miR-23b/27b/24 cluster), which encodes aminopeptidase O (AOPEP), a metallopeptidase [31]. However, the function of AOPEP in cancer development has not been elucidated. It is of interest to uncover the functional relationship between AOPEP and the miR-23b/27b/24 cluster in future investigations. We found that the expression of C9orf3 mRNA harboring exons 10 to 15 was upregulated in MG cells, suggesting that a novel transcriptional start site may exist upstream of exon 10. Strikingly, we demonstrated that E2F1 biding sites are essential sequences for the promoter activity of a short C9orf3 transcript using promoter assays and ChIP. E2F1 is a cell cycle-specific transcription factor that binds to promoters of diverse downstream genes. Although E2F1 has pleiotropic roles in tumorigenesis [32,33], several lines of evidence have revealed that E2F1 promotes cell migration and aggressiveness in prostate and colorectal cancer cells [18,20]. C9orf3 may be a novel downstream target of E2F1 associated with cell migration and cancer development.
The clustered miRNAs are often conserved evolutionarily and are likely to cooperatively regulate functionally related target genes [27]. For example, BCL2L11 is targeted by multiple miRNAs of the miR-17/92 cluster [34,35]. Because either or both miR-23b and miR-27b promote cell migration, we focused on those target genes that are cooperatively regulated by both miR-23b and miR-27b. Based on miRDB, we found FOXP2 as a common target gene of miR-23b and miR-27b. FOXP2 is a member of the Forkhead family of transcription repressor that regulates speech and learning in humans. Luciferase assay showed that mutation of miR-23b or miR-27b binding site could not fully recover luciferase activity; suggesting that other factors, regulated by miR-23b and miR-27b, may be involved in FOXP2 regulation. The function of FOXP2 was originally investigated in neuronal network development including migration or morphological neuronal cell changes. Recently, FOXP2 was also shown to be involved in cancer development. FOXP2 negatively regulates stem cell-associated factors—such as c-MYC, OCT-4, and CD44—in breast cancer, resulting in a putative tumor/metastasis suppressor [23]. In addition, the expression of FOXP2 is mediated by miR-23a, a member of the miR-23/27/24 family [21]. Furthermore, Abu-Remaileh et al. reported that FOXP2 mRNA levels were significantly decreased in colon cancer samples [36]. We demonstrated that FOXP2 was downregulated in mRNA and protein levels in the MG cells and FOXP2 knockdown enhanced cell migration. These results are consistent with those of previous reports that FOXP2 promotes cell migration. To the best of our knowledge, direct targets of FOXP2 have not been investigated and further studies are needed to elucidate the function of FOXP2 in cancer development or metastases.
In this study, we established the cell selection procedure regarding cell migration. It remains unclear as to whether other processes of EMT or metastasis—such as adhesion, invasion, and attachment—are promoted in the MG cells. Efforts to elucidate the functions of miR-23b/27b/FOXP2 in vivo are currently underway.

4. Materials and Methods

4.1. Cell Culture and Isolation of a Subpopulation with High Cell Migration Capacity

A subpopulation with high migratory capacity, MG cells, were isolated by a transwell-based selection method [13]. In brief, for the isolation of a subpopulation with cell migration capacity, we established the following selection procedures using the transwell migration assay (the modified Boyden Chamber assay [37]). HCT116 cells were seeded in serum-free media on the upper side of a transwell chamber (Becton Dickinson, Franklin Lakes, NJ, USA) and allowed to migrate towards the media containing 10% of fetal bovine serum (FBS). Both cells remaining on the upper membrane (non-MG cells) and cells migrating to the lower side of the membrane (MG cells) were respectively collected. To concentrate the subpopulations, this selection procedure was employed five more times. After this selection procedure, two subpopulations were isolated; one was the non-MG cells remaining on the upper membrane, and another was the MG cells preferentially migrating to the lower membrane. These cells were cultured in DMEM (Nacalai Tesque, Kyoto, Japan) supplemented with 10% (vol/vol) heat-inactivated FBS at 37 °C in 5% CO2.

4.2. Cell Counting, Cell Migration Assay and Scratch Assay

Cells were seeded in tissue culture plates, and the numbers of growing cells were counted using a hematocytometer. Migration of colon cancer cells were examined using 8-μm pore size polycarbonate transwell filters (Becton Dickinson). After 48 h serum starvation, cells were seeded in serum-free media on the upper side of a transwell chamber and allowed to migrate towards the media containing 10% FBS for 48 h. After the incubation period, cells on the lower side of the membrane were fixed, stained with Diff-Quick stain (Sysmex, Kobe, Japan) and counted. The migration indices were calculated as the mean number of cells in 5 random fields at 20× magnification. For the scratch assay (wound healing assay), cells were seeded onto 24-well tissue culture plates and maintained at 37 °C and 5% CO2 for 24 h, and then, plasmids or mimic miRNAs were transiently transfected into the cells. To permit the formation of a confluent monolayer, the cells were incubated for 36 h after transfection. These confluent monolayers were then scratched with a cell scratcher (Asahi Techno Glass Co., Ltd., Tokyo, Japan). Culture medium was then immediately replaced with a fresh culture medium (10% FBS) to remove any dislodged cells. Cell migration ability was determined by measuring the migration distance in 5 points per sample at 24 h after the scratch. All scratch assays were performed in quadruplicate.

4.3. Small Interference RNAs (siRNAs)

We used siRNAs (Hs_FOXP2_12 and 13 HP validated siRNAs; Qiagen, Chatsworth, CA, USA) to knock down FOXP2 mRNA. A negative control siRNA (AllStars Negative Control siRNA) was obtained from Qiagen.

4.4. Overexpression of miRNA Mimics and Inhibitors

miRCURY LNA miRNA mimics (has-miR-23b, Product No. 472291-001; has-miR-27b, Product No. 470553-001) and mimic negative control were obtained from Exiqon (Vedbaek, Denmark). mirVana miRNA mimic (has-miR-24-3p; MC10737) was obtained from Ambion (Austin, TX, USA). miRCURY LNA miRNA inhibitors (has-miR-23b, Product No. 4102299; has-miR-27b, Product No. 4103307; has-miR-24-3p, Product No. 4101706; negative control A) were obtained from Exiqon. HCT116, DLD1, RKO, and HT-29 cells were transfected with miRNA mimics or inhibitors at 10 nM using Lipofectamine RNAiMAX (Thermo Fisher Scientific, Waltham, MA, USA).

4.5. Quantitative Real-Time Reverse Transcription-PCR (qPCR)

Total RNAs, including miRNAs, were extracted from cells using RNA iso plus reagent (Takara, Otsu, Japan). For analysis of mRNA expression levels, 1 μg of isolated RNA was reverse-transcribed using ReveTra Ace qPCR RT Master Mix (Toyobo, Osaka, Japan). C9orf3, CLCN3, KCNK2, FOXP2, PKIA, SEC24A, TRIL, and ZDHHC17 mRNA levels were measured using SYBR Green Master Mix and Applied Biosystems 7500 Real-time System (Applied Biosystems, Foster City, CA, USA). The sequences of primer sets are provided in Table S1. mRNA levels were measured by the comparative ΔΔCt method using glyceraldehyde-3-phosphate dehydrogenase (GAPDH) mRNA as a control and expressed as values relative to the indicated control sample. For analysis of miRNA expression levels, isolated RNAs were cleaned using miRNeasy mini kit (Qiagen, Hilden, Germany) and reverse-transcribed using miRNURYLNA Universal RT kit according to the manufacturer’s protocol. Locked nucleic acid (LNA) PCR primer sets (Exiqon) targeting hsa-miR-23b-3p (Product No. 204790), hsa-miR-27b-3p (Product No. 205915), hsa-miR-24-3p (Product No. 204260), and hsa-miR-10a-5p (Product No. 204788) were used to detect miRNA expression. miRNA levels were measured by the comparative ΔΔCt method using RNU48 as a control and expressed as values relative to the indicated control sample.

4.6. Analysis of Global miRNA Expression

Total RNAs were extracted from cells using miRNeasy kit (Qiagen) according to the manufacturer’s protocol. RNA concentration and purity were determined by NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA). Purified RNA quality was assessed by Agilent 2100 Bioanalyzer using an RNA 6000 Nano Labchip kit (Agilent Technologies, Santa Clara, CA, USA), and RNA samples with above 8.5 RNA integrity number (RIN) were used for further study. RNA samples were used to measure miRNA expression profiles using a human miRNA microarray (G4470C; Agilent), containing 939 miRNA probes, as previously described. These data were analyzed using GeneSpring 11.5.1 (Agilent). We selected miRNAs with fluorescence intensities 50 in at least half of the RNA samples, resulting in the detection of 56 miRNAs in the samples. All primary and uniformly processed sequence data generated in this study are available at the NCBI Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo/) under accession number GSE141240.

4.7. miRNA Luciferase Reporter Assay

The fragment of the 3′UTR of FOXP2 was amplified from the cDNA of HCT116 cells using primer sets listed in Table S1. The fragment of FOXP2 3′UTR was subcloned into psiCHECK-2 vector (Promega, Madison, WA, USA) using XhoI and NotI restriction sites. HCT116 cells were cultured on 24-well plates, and then psiCHECK-2 constructs with various site-directed mutations were co-transfected with either miR-23b or miR-27b, or both. Twenty-four hours after the transfection, cells were harvested and the firefly and Renilla luciferase activities were measured using the Dual-Luciferase Reporter Assay System (Promega).

4.8. Western Blotting

Whole-cell lysates were prepared in a RIPA buffer (10 mM Tris-HCl, pH 7.4; 1% Nonidet P-40; 1 mM EDTA; 0.1% SDS; 150 mM NaCl) containing a protease inhibitor (Nacalai Tesque) and phosphatase inhibitor cocktail (Sigma). Rabbit polyclonal anti-E2F1 (1:1000; Cell Signaling Technology, Danvers, MA, USA), rabbit polyclonal anti-FOXP2 (1:1000; #3742, Cell Signaling Technology), or mouse monoclonal anti-GAPDH (1:5000; Santa Cruz Biotechnology) antibody was used. Full-length western blots were shown in Figures S6–S8.

4.9. Promoter Activity Assay

The 5′-flank of the human C9orf3 gene was cloned into the pGL4.21-basic luciferase reporter vector (Promega). In brief, the first PCR was performed using human genomic DNA as a template. The C9orf3 proximal promoter region was amplified using primer sets listed in Table S1. The amplified products were subcloned into the pGL4.21-basic vector using KpnI and HindIII restriction sites. HCT116 cells (1.0 × 105) were cultured on 24-well plates, and then pGL-4.21 luciferase constructs with various site-directed mutation or deletion (100 ng) were cotransfected with pGL4.74 vector (50 ng) using X-tremeGENE HP DNA transfection reagent (Roche, Basel, Switzerland). Twenty-four hours after the transfection, cells were harvested, and the firefly and Renilla luciferase activities were measured using the Dual-Luciferase Reporter Assay System (Promega).

4.10. Chromatin Immunoprecipitation (ChIP) Assay

ChIP assays were performed using the Chromatin Immunoprecipitation Assay Kit (Millipore, Burlington, CA, USA). Briefly, HCT116 cells were fixed with 1% formaldehyde in phosphate-buffered saline (PBS) for 10 min and then washed twice with ice-cold PBS. These cells were resuspended in SDS lysis buffer, incubated for 10 min on ice, and then sonicated. Immunoprecipitation was carried out overnight at 4 °C using 3 μg antibody against E2F1 (Cell Signaling Technology). Normal rabbit IgG was used to assess the non-specific reactions. Immune complexes were collected with protein A agarose/salmon sperm DNA. Cross linking between proteins and DNA was reversed according to the manufacturer’s protocol. Protein-bound DNA was extracted with phenol/chloroform/isoamyl alcohol. The extracted DNA was amplified by PCR (35 cycles; denaturing at 98 °C for 10 s, annealing at 55 °C for 30 s, and extension at 72 °C for 1 min) using the following primers: for the C9orf3 primer set 1 sequence between −209 and +84 bp, 5′-GCGGCCGCTATACCTTTA-3′ and 5′-GCGCGACGCTCCCTCTGCAG-3′; for the C9orf3 primer set2 sequence between −1241 and −1110 bp, 5′-TCCCTCATTTGAGCAGACTTGT-3′ and 5′-ACACAGAGGAGCTTAATGGAGAC-3′. The nuclear chromatin DNA from HCT116 cells (input) was used as a positive control for PCR.

4.11. Data Analysis

RNA-seq and clinical data of colorectal adenocarcinoma (CORDREAD) from The Cancer Genome Atlas (TCGA) were analyzed using the UCSC Xena web interface [38].

5. Conclusions

In conclusion, the present study demonstrated a novel role of the miR-23b/27b/24 cluster in cell migration through targeting FOXP2, using the transwell-based separated cells. These data suggest that a novel miR-23b/27b/FOXP2 link may play, at least in part, an important role in the migratory activity in cancer development and might be a potential target for the inhibition of cancer metastases.

Supplementary Materials

The following are available online at https://www.mdpi.com/2072-6694/12/1/174/s1. Table S1: Primer sets used for qPCR and 5′-RACE; Figure S1: mRNA expression of surface markers of colorectal cancer stem cells; Figure S2: Identification of transcriptional start sites by 5′-rapid amplification of cDNA end assay; Figure S3: Effects of DNA methylation on C9orf3 and miR-23b/27b/24 expression; Figure S4: Effects of knockdown of E2F1 in non-MG cells on miR-23b/27/24 expression; Figure S5: Effects of miR-23b/27b/24 on cell migration; Figures S6–S8: Full-length western blots.

Author Contributions

Conceptualization, K.N.; methodology, K.N.; validation, K.N.; formal analysis, K.N.; investigation, K.N.; data curation, K.N.; writing—original draft preparation, K.N.; writing—review and editing, K.N. and K.R.; visualization, K.N.; supervision, Y.K. and K.R.; funding acquisition, K.N. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Takeda Science Foundation (to K.N.) and JSPS KAKENHI, Grant Number 16K09314 to K.N.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Lamouille, S.; Xu, J.; Derynck, R. Molecular mechanisms of epithelial–mesenchymal transition. Nat. Rev. Mol. Cell Biol. 2014, 15, 178–196. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Leva, G.D.; Garofalo, M.; Croce, C.M. microRNAs in cancer. Annu. Rev. Pathol. 2014, 9, 287–314. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Peng, Y.; Croce, C.M. The role of MicroRNAs in human cancer. Signal Transduct. Target. Ther. 2016, 1, 15004. [Google Scholar] [CrossRef] [Green Version]
  4. Dews, M.; Homayouni, A.; Yu, D.; Murphy, D.; Sevignani, C.; Wentzel, E.; Furth, E.E.; Lee, W.M.; Enders, G.H.; Mendell, J.T.; et al. Augmentation of tumor angiogenesis by a Myc-activated microRNA cluster. Nat. Genet. 2006, 38, 1060–1065. [Google Scholar] [CrossRef] [Green Version]
  5. Xu, J.; Wong, C. A computational screen for mouse signaling pathways targeted by microRNA clusters. RNA 2008, 14, 1276–1283. [Google Scholar] [CrossRef] [Green Version]
  6. Guo, L.; Lu, Z. Global expression analysis of miRNA gene cluster and family based on isomiRs from deep sequencing data. Comput. Biol. Chem. 2010, 34, 165–171. [Google Scholar] [CrossRef]
  7. Yu, J.; Wang, F.; Yang, G.-H.; Wang, F.-L.; Ma, Y.-N.; Du, Z.-W.; Zhang, J.-W. Human microRNA clusters: Genomic organization and expression profile in leukemia cell lines. Biochem. Biophys. Res. Commun. 2006, 349, 59–68. [Google Scholar] [CrossRef]
  8. Ding, L.; Ni, J.; Yang, F.; Huang, L.; Deng, H.; Wu, Y.; Ding, X.; Tang, J. Promising therapeutic role of miR-27b in tumor. Tumor Biol. 2017, 39. [Google Scholar] [CrossRef] [Green Version]
  9. Wang, W.; Wang, Y.; Liu, W.; van Wijnen, A.J. Regulation and biological roles of the multifaceted miRNA-23b (MIR23B). Gene 2018, 642, 103–109. [Google Scholar] [CrossRef]
  10. Wang, J.Y.; Li, X.F.; Li, P.Z.; Zhang, X.; Xu, Y.; Jin, X. MicroRNA-23b regulates nasopharyngeal carcinoma cell proliferation and metastasis by targeting E-cadherin. Mol. Med. Rep. 2016, 14, 537–543. [Google Scholar] [CrossRef] [Green Version]
  11. Yao, J.; Deng, B.; Zheng, L.; Dou, L.; Guo, Y.; Guo, K. MiR-27b is upregulated in cervical carcinogenesis and promotes cell growth and invasion by regulating CDH11 and epithelial-mesenchymal transition. Oncol. Rep. 2016, 35, 1645–1651. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Jin, L.; Wessely, O.; Marcusson, E.G.; Ivan, C.; Calin, G.A.; Alahari, S.K. Prooncogenic factors miR-23b and miR-27b are regulated by Her2/Neu, EGF, and TNF-A in breast cancer. Cancer Res. 2013, 73, 2884–2896. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Tanaka, H.; Kuwano, Y.; Nishikawa, T.; Rokutan, K. ZNF350 promoter methylation accelerates colon cancer cell migration. Oncotarget 2018, 9, 36750–36769. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Zhou, Y.; Xia, L.; Wang, H.; Oyang, L.; Su, M.; Liu, Q.; Lin, J.; Tan, S.; Tian, Y.; Liao, Q.; et al. Cancer stem cells in progression of colorectal cancer. Oncotarget 2018, 9, 33403–33415. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Hovestadt, V.; Jones, D.T.W.W.; Picelli, S.; Wang, W.; Kool, M.; Northcott, P.A.; Sultan, M.; Stachurski, K.; Ryzhova, M.; Warnatz, H.-J.J.; et al. Decoding the regulatory landscape of medulloblastoma using DNA methylation sequencing. Nature 2014, 510, 537–541. [Google Scholar] [CrossRef] [Green Version]
  16. Farré, D.; Roset, R.; Huerta, M.; Adsuara, J.E.; Roselló, L.; Albà, M.M.; Messeguer, X. Identification of patterns in biological sequences at the ALGGEN server: PROMO and MALGEN. Nucleic Acids Res. 2003, 31, 3651–3653. [Google Scholar] [CrossRef] [Green Version]
  17. Messeguer, X.; Escudero, R.; Farre, D.; Nunez, O.; Martinez, J.; Alba, M.M. PROMO: Detection of known transcription regulatory elements using species-tailored searches. Bioinformatics 2002, 18, 333–334. [Google Scholar] [CrossRef]
  18. Liang, Y.X.; Lu, J.M.; Mo, R.J.; He, H.C.; Xie, J.; Jiang, F.N.; Lin, Z.Y.; Chen, Y.R.; Wu, Y.D.; Luo, H.W.; et al. E2F1 promotes tumor cell invasion and migration through regulating CD147 in prostate cancer. Int. J. Oncol. 2016, 48, 1650–1658. [Google Scholar] [CrossRef]
  19. Wang, Z.; Sun, X.; Bao, Y.; Mo, J.; Du, H.; Hu, J.; Zhang, X. E2F1 silencing inhibits migration and invasion of osteosarcoma cells via regulating DDR1 expression. Int. J. Oncol. 2017, 51, 1639–1650. [Google Scholar] [CrossRef] [Green Version]
  20. Fang, Z.; Gong, C.; Liu, H.; Zhang, X.; Mei, L.; Song, M.; Qiu, L.; Luo, S.; Zhu, Z.; Zhang, R.; et al. E2F1 promote the aggressiveness of human colorectal cancer by activating the ribonucleotide reductase small subunit M2. Biochem. Biophys. Res. Commun. 2015, 464, 407–415. [Google Scholar] [CrossRef]
  21. Diao, H.; Ye, Z.; Qin, R. miR-23a acts as an oncogene in pancreatic carcinoma by targeting FOXP2. J. Investig. Med. 2017. [Google Scholar] [CrossRef]
  22. Zhong, C.; Liu, J.; Zhang, Y.; Luo, J.; Zheng, J. MicroRNA-139 inhibits the proliferation and migration of osteosarcoma cells via targeting forkhead-box P2. Life Sci. 2017, 191, 68–73. [Google Scholar] [CrossRef] [PubMed]
  23. Cuiffo, B.G.; Campagne, A.; Bell, G.W.; Lembo, A.; Orso, F.; Lien, E.C.; Bhasin, M.K.; Raimo, M.; Hanson, S.E.; Marusyk, A.; et al. MSC-regulated microRNAs converge on the transcription factor FOXP2 and promote breast cancer metastasis. Cell Stem Cell 2014, 15, 762–774. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Jia, W.-Z.; Yu, T.; An, Q.; Yang, H.; Zhang, Z.; Liu, X.; Xiao, G. MicroRNA-190 regulates FOXP2 genes in human gastric cancer. Onco Targets Ther. 2016, 9, 3643–3651. [Google Scholar] [PubMed] [Green Version]
  25. Sato, S.; Rancourt, A.; Sato, Y.; Satoh, M.S. Single-cell lineage tracking analysis reveals that an established cell line comprises putative cancer stem cells and their heterogeneous progeny. Sci. Rep. 2016, 6, 23328. [Google Scholar] [CrossRef] [Green Version]
  26. Mohammadi, A.; Mansoori, B.; Baradaran, B. The role of microRNAs in colorectal cancer. Biomed. Pharmacother. 2016, 84, 705–713. [Google Scholar] [CrossRef]
  27. Wang, Y.; Luo, J.; Zhang, H.; Lu, J. MicroRNAs in the Same Clusters Evolve to Coordinately Regulate Functionally Related Genes. Mol. Biol. Evol. 2016, 33, 2232–2247. [Google Scholar] [CrossRef] [Green Version]
  28. Goto, Y.; Kojima, S.; Nishikawa, R.; Enokida, H.; Chiyomaru, T.; Kinoshita, T.; Nakagawa, M.; Naya, Y.; Ichikawa, T.; Seki, N.; et al. The microRNA-23b/27b/24-1 cluster is a disease progression marker and tumor suppressor in prostate cancer. Oncotarget 2014, 5, 7748–7759. [Google Scholar] [PubMed] [Green Version]
  29. Ell, B.; Qiu, Q.; Wei, Y.; Mercatali, L.; Ibrahim, T.; Amadori, D.; Kang, Y. The microRNA-23b/27b/24 cluster promotes breast cancer lung metastasis by targeting metastasis-suppressive gene prosaposin. J. Biol. Chem. 2014, 289, 21888–21895. [Google Scholar] [CrossRef] [Green Version]
  30. Lutter, D.; Marr, C.; Krumsiek, J.; Lang, E.W.; Theis, F.J. Intronic microRNAs support their host genes by mediating synergistic and antagonistic regulatory effects. BMC Genom. 2010, 11, 224. [Google Scholar] [CrossRef] [Green Version]
  31. Diaz-Perales, A.; Quesada, V.; Sanchez, L.M.; Ugalde, A.P.; Suarez, M.F.; Fueyo, A.; Lopez-Otin, C. Identification of human aminopeptidase O, a novel metalloprotease with structural similarity to aminopeptidase B and leukotriene A4 hydrolase. J. Biol. Chem. 2005, 280, 14310–14317. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Ginsberg, D. E2F1 pathways to apoptosis. FEBS Lett. 2002, 529, 122–125. [Google Scholar] [CrossRef] [Green Version]
  33. Poppy Roworth, A.; Ghari, F.; La Thangue, N.B. To live or let die—Complexity within the E2F1 pathway. Mol. Cell. Oncol. 2015, 2, e970480. [Google Scholar] [CrossRef] [PubMed]
  34. Concepcion, C.P.; Bonetti, C.; Ventura, A. The MicroRNA-17-92 Family of MicroRNA Clusters in Development and Disease. Cancer J. 2012, 18, 262–267. [Google Scholar] [CrossRef]
  35. Ventura, A.; Young, A.G.; Winslow, M.M.; Lintault, L.; Meissner, A.; Erkeland, S.J.; Newman, J.; Bronson, R.T.; Crowley, D.; Stone, J.R.; et al. Targeted Deletion Reveals Essential and Overlapping Functions of the miR-17∼92 Family of miRNA Clusters. Cell 2008, 132, 875–886. [Google Scholar] [CrossRef] [Green Version]
  36. Abu-Remaileh, M.; Bender, S.; Raddatz, G.; Ansari, I.; Cohen, D.; Gutekunst, J.; Musch, T.; Linhart, H.; Breiling, A.; Pikarsky, E.; et al. Chronic inflammation induces a novel epigenetic program that is conserved in intestinal adenomas and in colorectal cancer. Cancer Res. 2015, 75, 2120–2130. [Google Scholar] [CrossRef] [Green Version]
  37. Boyden, S. The chemotactic effect of mixtures of antibody and antigen on polymorphonuclear leucocytes. J. Exp. Med. 1962, 115, 453–466. [Google Scholar] [CrossRef] [Green Version]
  38. Goldman, M.; Craft, B.; Hastie, M.; Repečka, K.; McDade, F.; Kamath, A.; Banerjee, A.; Luo, Y.; Rogers, D.; Brooks, A.N.; et al. The UCSC Xena platform for public and private cancer genomics data visualization and interpretation. BiorXiv 2019. [Google Scholar] [CrossRef] [Green Version]
Cancers 12 00174 g001 550
Figure 1. Up-regulation of the miR-23b/27b/24 cluster expression in migrated (MG) cells. (A) Relative expression levels of miR-23b, miR-27b, and miR-24 in non-MG cells and MG cells were measured by RT-qPCR. RNU48 was used as an endogenous control. (B) mRNA levels of C9orf3, a host gene of miR-23b/27b/24 cluster, were measured by real-time reverse transcription polymerase chain reaction (RT-qPCR) using the indicated primer sets. Data are expressed as the mean fold changes ± standard deviation (SD; n = 4), compared with those in the non-MG cells. * Statistically significant difference versus non-MG cells (unpaired Student’s t-test, p < 0.05). (C,D) Samples from TCGA (Colorectal Adenocarcinoma, COADREAD) were divided into two groups according to the presence or absence of lymphatic invasion. The difference in gene expression of each exon in C9orf3 between the subgroups was tested for significance using Welch’s t-test on log-transformed data. Individual mRNA levels are presented on box-and-whiskers plots using a logarithmic scale for the y-axis. (E,F) Overall survival as a function of C9orf3 expression in TCGA. Patients with C9orf3 expression data from TCGA (COADREAD) were evenly divided into quartiles, and the lowest and highest quartiles were plotted with Kaplan-Meier curves for overall survival using the UCSC Xena browser tool.
Figure 1. Up-regulation of the miR-23b/27b/24 cluster expression in migrated (MG) cells. (A) Relative expression levels of miR-23b, miR-27b, and miR-24 in non-MG cells and MG cells were measured by RT-qPCR. RNU48 was used as an endogenous control. (B) mRNA levels of C9orf3, a host gene of miR-23b/27b/24 cluster, were measured by real-time reverse transcription polymerase chain reaction (RT-qPCR) using the indicated primer sets. Data are expressed as the mean fold changes ± standard deviation (SD; n = 4), compared with those in the non-MG cells. * Statistically significant difference versus non-MG cells (unpaired Student’s t-test, p < 0.05). (C,D) Samples from TCGA (Colorectal Adenocarcinoma, COADREAD) were divided into two groups according to the presence or absence of lymphatic invasion. The difference in gene expression of each exon in C9orf3 between the subgroups was tested for significance using Welch’s t-test on log-transformed data. Individual mRNA levels are presented on box-and-whiskers plots using a logarithmic scale for the y-axis. (E,F) Overall survival as a function of C9orf3 expression in TCGA. Patients with C9orf3 expression data from TCGA (COADREAD) were evenly divided into quartiles, and the lowest and highest quartiles were plotted with Kaplan-Meier curves for overall survival using the UCSC Xena browser tool.
Cancers 12 00174 g001
Cancers 12 00174 g002 550
Figure 2. E2F1 regulates C9orf3 promoter activity. (A) HCT116 cells were transiently transfected with luciferase reporter plasmids driven by the indicated promoter fragments of C9orf3 for 48 h. Luciferase activities in these cells were measured using the Dual-Luciferase Reporter Assay System. * Significant up-regulation in MG cells compared with non-MG cells. Data are expressed as the mean ± standard deviation (SD; n = 4). * Statistically significant difference versus non-MG cells (unpaired Student’s t-test, p < 0.05). (B) Nucleotide sequence of the 5′-flanking region of the C9orf3 gene. Putative binding sites for E2F1 are indicated with bent arrows in red based on the PROME. (C) E2F1 mRNA levels were measured by RT-qPCR using the indicated primer sets. Data are expressed as the mean fold changes ± standard deviation (SD; n = 4), compared with those in the non-MG cells. * Statistically significant difference versus non-MG cells (unpaired Student’s t-test, p < 0.05). (D) Amounts of E2F1 proteins in the non-MG cells and MG cells were measured by western blotting using glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as a loading control. The results of western blotting using anti-E2F1 antibody from three independent experiments were quantified by densitometry as shown in (D). Data are expressed as the mean ± standard deviation (SD; n = 4). * Statistically significant difference versus non-MG cells (unpaired Student’s t-test, p < 0.05). (E,F) HCT116 cells were subjected to chromatin immunoprecipitation (ChIP) assays. Formaldehyde-crosslinked nuclear extracts were immunoprecipitated with an anti-E2F1 antibody or normal rabbit IgG (IgG). PCR was performed using an input nuclear chromatin fraction as a template (input). Specific PCR products corresponding to the region of the C9orf3 promoter containing E2F1-binding sites were amplified and separated by agarose gel electrophoresis followed by ethidium bromide staining. The results of ChIP with an anti-E2F1 antibody from three independent experiments were quantified by densitometry as shown in (F). Data are expressed as the mean ± standard deviation (SD; n = 4). * Statistically significant difference versus control (IgG) (unpaired Student’s t-test, p < 0.05). MW, molecular weight.
Figure 2. E2F1 regulates C9orf3 promoter activity. (A) HCT116 cells were transiently transfected with luciferase reporter plasmids driven by the indicated promoter fragments of C9orf3 for 48 h. Luciferase activities in these cells were measured using the Dual-Luciferase Reporter Assay System. * Significant up-regulation in MG cells compared with non-MG cells. Data are expressed as the mean ± standard deviation (SD; n = 4). * Statistically significant difference versus non-MG cells (unpaired Student’s t-test, p < 0.05). (B) Nucleotide sequence of the 5′-flanking region of the C9orf3 gene. Putative binding sites for E2F1 are indicated with bent arrows in red based on the PROME. (C) E2F1 mRNA levels were measured by RT-qPCR using the indicated primer sets. Data are expressed as the mean fold changes ± standard deviation (SD; n = 4), compared with those in the non-MG cells. * Statistically significant difference versus non-MG cells (unpaired Student’s t-test, p < 0.05). (D) Amounts of E2F1 proteins in the non-MG cells and MG cells were measured by western blotting using glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as a loading control. The results of western blotting using anti-E2F1 antibody from three independent experiments were quantified by densitometry as shown in (D). Data are expressed as the mean ± standard deviation (SD; n = 4). * Statistically significant difference versus non-MG cells (unpaired Student’s t-test, p < 0.05). (E,F) HCT116 cells were subjected to chromatin immunoprecipitation (ChIP) assays. Formaldehyde-crosslinked nuclear extracts were immunoprecipitated with an anti-E2F1 antibody or normal rabbit IgG (IgG). PCR was performed using an input nuclear chromatin fraction as a template (input). Specific PCR products corresponding to the region of the C9orf3 promoter containing E2F1-binding sites were amplified and separated by agarose gel electrophoresis followed by ethidium bromide staining. The results of ChIP with an anti-E2F1 antibody from three independent experiments were quantified by densitometry as shown in (F). Data are expressed as the mean ± standard deviation (SD; n = 4). * Statistically significant difference versus control (IgG) (unpaired Student’s t-test, p < 0.05). MW, molecular weight.
Cancers 12 00174 g002
Cancers 12 00174 g003 550
Figure 3. Knockdown of E2F1 decreased C9orf3 expression levels. (A) Two siRNAs targeted for distinct E2F1 sequences were transfected to the MG cells. Amounts of E2F1 proteins in E2F1 siRNAs-treated cells were measured by western blotting using GAPDH as a loading control. (B,C) Relative expression levels of C9orf3 and miR-23b/27b/24 miRNAs in MG cells after treatment with E2F1-siRNAs were measured by RT-qPCR. GAPDH or RNU48 was used as an endogenous control. Data are expressed as the mean ± standard deviation (SD; n = 4). * Statistically significant difference versus control cells (unpaired Student’s t-test, p < 0.05). MW, molecular weight.
Figure 3. Knockdown of E2F1 decreased C9orf3 expression levels. (A) Two siRNAs targeted for distinct E2F1 sequences were transfected to the MG cells. Amounts of E2F1 proteins in E2F1 siRNAs-treated cells were measured by western blotting using GAPDH as a loading control. (B,C) Relative expression levels of C9orf3 and miR-23b/27b/24 miRNAs in MG cells after treatment with E2F1-siRNAs were measured by RT-qPCR. GAPDH or RNU48 was used as an endogenous control. Data are expressed as the mean ± standard deviation (SD; n = 4). * Statistically significant difference versus control cells (unpaired Student’s t-test, p < 0.05). MW, molecular weight.
Cancers 12 00174 g003
Cancers 12 00174 g004 550
Figure 4. Effects of miR-23b/27b/24 on cell migration. (A,B) Transwell migration (n = 4) assays were performed in mixed mimic or inhibitor of microRNAs (miR-23b, miR-27b and miR-24)-transfected HCT116 cells. Upper panels show representative images of Diff-Quick staining in four experiments of transwell migration assays, and a lower graph shows quantification of cell migration expressed by cell counting. (C–E) Transwell migration assays were performed in mixed mimic of microRNAs (miR-23b, miR-27b, and miR-24)-transfected DLD1, RKO, or HT29 cells. Upper panels and lower graphs are the same as in (aA). Values represent mean ± SD. n = 4. * Statistically significant difference versus control (unpaired Student’s t-test, p < 0.05).
Figure 4. Effects of miR-23b/27b/24 on cell migration. (A,B) Transwell migration (n = 4) assays were performed in mixed mimic or inhibitor of microRNAs (miR-23b, miR-27b and miR-24)-transfected HCT116 cells. Upper panels show representative images of Diff-Quick staining in four experiments of transwell migration assays, and a lower graph shows quantification of cell migration expressed by cell counting. (C–E) Transwell migration assays were performed in mixed mimic of microRNAs (miR-23b, miR-27b, and miR-24)-transfected DLD1, RKO, or HT29 cells. Upper panels and lower graphs are the same as in (aA). Values represent mean ± SD. n = 4. * Statistically significant difference versus control (unpaired Student’s t-test, p < 0.05).
Cancers 12 00174 g004
Cancers 12 00174 g005 550
Figure 5. miR-23b and miR-27b promote cell migration. Transwell assay (A) and Scratch assay (B) were performed in non-MG cells with combinational transfection of mimic miR-23b, miR-27b, and/or miR-24. (A) Upper panels show representative images of Diff-Quick staining in four experiments of transwell migration assays, and a lower graph shows quantification of cell migration expressed by cell counting. Data are expressed as the mean ± standard deviation (SD; n = 4). * Statistically significant difference versus control (unpaired Student’s t-test, p < 0.05). (B) After transfection with mimic miRNAs, cells were scratched. Migration distance was measured at 24 h later. Data are expressed as the mean ± standard deviation (SD; n = 4). * Statistically significant difference versus control (unpaired Student’s t-test, p < 0.05).
Figure 5. miR-23b and miR-27b promote cell migration. Transwell assay (A) and Scratch assay (B) were performed in non-MG cells with combinational transfection of mimic miR-23b, miR-27b, and/or miR-24. (A) Upper panels show representative images of Diff-Quick staining in four experiments of transwell migration assays, and a lower graph shows quantification of cell migration expressed by cell counting. Data are expressed as the mean ± standard deviation (SD; n = 4). * Statistically significant difference versus control (unpaired Student’s t-test, p < 0.05). (B) After transfection with mimic miRNAs, cells were scratched. Migration distance was measured at 24 h later. Data are expressed as the mean ± standard deviation (SD; n = 4). * Statistically significant difference versus control (unpaired Student’s t-test, p < 0.05).
Cancers 12 00174 g005
Cancers 12 00174 g006 550
Figure 6. FOXP2 as a potential target of miR-23b and miR-27b. (A) The number of candidate target mRNAs of miR-23b or miR-27b based on miRDB is shown in a Venn diagram. (B) mRNA levels of CLCN3, KCNK2, FOXP2, PKIA, SEC24A, TRIL, ZDHHC17, and ZBTB34 were determined using RT-qPCR in non-MG cells and MG cells. Expression of ZBTB34 mRNA was not detected by RT-qPCR. (C) Amounts of FOXP2 protein in non-MG cells and MG cells were determined using western blotting with GAPDH as a loading control. (D) FOXP2 mRNA levels were determined in non-MG cells with mimic miR-23b and/or miR-27b transfection and RT-qPCR. (E) Amounts of FOXP2 protein in non-MG cells with mimic miR-23b and/or miR-27b transfection were determined using western blotting with GAPDH as a loading control. The results of western blotting with an anti-FOXP2 antibody were quantified by densitometry, and the ratio of FOXP2 to GAPDH is shown in (E). MW, molecular weight.
Figure 6. FOXP2 as a potential target of miR-23b and miR-27b. (A) The number of candidate target mRNAs of miR-23b or miR-27b based on miRDB is shown in a Venn diagram. (B) mRNA levels of CLCN3, KCNK2, FOXP2, PKIA, SEC24A, TRIL, ZDHHC17, and ZBTB34 were determined using RT-qPCR in non-MG cells and MG cells. Expression of ZBTB34 mRNA was not detected by RT-qPCR. (C) Amounts of FOXP2 protein in non-MG cells and MG cells were determined using western blotting with GAPDH as a loading control. (D) FOXP2 mRNA levels were determined in non-MG cells with mimic miR-23b and/or miR-27b transfection and RT-qPCR. (E) Amounts of FOXP2 protein in non-MG cells with mimic miR-23b and/or miR-27b transfection were determined using western blotting with GAPDH as a loading control. The results of western blotting with an anti-FOXP2 antibody were quantified by densitometry, and the ratio of FOXP2 to GAPDH is shown in (E). MW, molecular weight.
Cancers 12 00174 g006
Cancers 12 00174 g007 550
Figure 7. FOXP2 is directly targeted by both miR-23b and miR-27b. (A) miRDB predicted a putative binding site of miR-23b (nt 402–409) and of miR-27b (nt 87–94) in the FOXP2 3’ UTR region. The mutated (MT) sequences of the putative binding sites are shown as FOXP2 3′UTR_MT1 or MT2. (B) psiCHECK2 vector containing the full length of 3′ UTR in FOXP2 or empty vector was co-transfected with both miR-23b and miR-27b. Renilla luciferase activity was normalized to firefly luciferase. Fold-change values were normalized to empty vector. (C,D) psiCHECK2 vector containing the full length of 3′ UTR in FOXP2 (psiCHECK2 FOXP2-3′UTR WT) or the mutated binding sequences (psiCHECK2 FOXP2-3′UTR MT1 or MT2) were co-transfected with either mimic miR-23b or miR-27b. Renilla luciferase activity was normalized to firefly luciferase. Fold-change values were normalized to empty vector. Fold-change values were then normalized to mimic control-treated cells. Data are expressed as the mean ± standard deviation (SD; n = 4). * Statistically significant difference versus control (B–D) or WT (C,D) (unpaired Student’s t-test, p < 0.05).
Figure 7. FOXP2 is directly targeted by both miR-23b and miR-27b. (A) miRDB predicted a putative binding site of miR-23b (nt 402–409) and of miR-27b (nt 87–94) in the FOXP2 3’ UTR region. The mutated (MT) sequences of the putative binding sites are shown as FOXP2 3′UTR_MT1 or MT2. (B) psiCHECK2 vector containing the full length of 3′ UTR in FOXP2 or empty vector was co-transfected with both miR-23b and miR-27b. Renilla luciferase activity was normalized to firefly luciferase. Fold-change values were normalized to empty vector. (C,D) psiCHECK2 vector containing the full length of 3′ UTR in FOXP2 (psiCHECK2 FOXP2-3′UTR WT) or the mutated binding sequences (psiCHECK2 FOXP2-3′UTR MT1 or MT2) were co-transfected with either mimic miR-23b or miR-27b. Renilla luciferase activity was normalized to firefly luciferase. Fold-change values were normalized to empty vector. Fold-change values were then normalized to mimic control-treated cells. Data are expressed as the mean ± standard deviation (SD; n = 4). * Statistically significant difference versus control (B–D) or WT (C,D) (unpaired Student’s t-test, p < 0.05).
Cancers 12 00174 g007
Cancers 12 00174 g008 550
Figure 8. Promotion of cell migration in FOXP2 knockdown cells. (A) Amounts of FOXP2 protein in non-MG cells treated with two siRNAs targeted to distinct FOXP2 sequences were measured using western blotting with GAPDH as a loading control. (B) Upper panels show representative images of Diff-Quick staining in four experiments of transwell migration assays, and a lower graph shows quantification of cell migration expressed by cell counting. Data are expressed as the mean ± standard deviation (SD; n = 4). * Statistically significant difference versus control (unpaired Student’s t-test, p < 0.05). (C) Scratch assay was performed in non-MG cells with FOXP2-siRNA treatment. Migration distance was measured 24 h after cells were scratched. Representative images were shown in lower panels. Data are expressed as the mean ± standard deviation (SD; n = 4). * Statistically significant difference versus control (unpaired Student’s t-test, p < 0.05). MW, molecular weight.
Figure 8. Promotion of cell migration in FOXP2 knockdown cells. (A) Amounts of FOXP2 protein in non-MG cells treated with two siRNAs targeted to distinct FOXP2 sequences were measured using western blotting with GAPDH as a loading control. (B) Upper panels show representative images of Diff-Quick staining in four experiments of transwell migration assays, and a lower graph shows quantification of cell migration expressed by cell counting. Data are expressed as the mean ± standard deviation (SD; n = 4). * Statistically significant difference versus control (unpaired Student’s t-test, p < 0.05). (C) Scratch assay was performed in non-MG cells with FOXP2-siRNA treatment. Migration distance was measured 24 h after cells were scratched. Representative images were shown in lower panels. Data are expressed as the mean ± standard deviation (SD; n = 4). * Statistically significant difference versus control (unpaired Student’s t-test, p < 0.05). MW, molecular weight.
Cancers 12 00174 g008
Table
Table 1. MicroRNAs (miRNAs) with >1.5-fold significant expression change in the migrated cells (MG cells).
Table 1. MicroRNAs (miRNAs) with >1.5-fold significant expression change in the migrated cells (MG cells).
miRNAChange Relative to Upper Cells (1)
(Fold-Change)		mirBase Accession No.
hsa-miR-10a2.119MIMAT0000415
hsa-miR-23b2.610MIMAT0000418
hsa-miR-27b1.837MIMAT0000419
has-miR-1274b(2)1.511MIMAT0005938
(1) Values are expressed as fold changes compared with the values in the non-MG cells. (2) These miRNAs were removed as dead entries on the miRBase (Release 21).

Share and Cite

MDPI and ACS Style

Nishida, K.; Kuwano, Y.; Rokutan, K. The MicroRNA-23b/27b/24 Cluster Facilitates Colon Cancer Cell Migration by Targeting FOXP2. Cancers 2020, 12, 174. https://doi.org/10.3390/cancers12010174

AMA Style

Nishida K, Kuwano Y, Rokutan K. The MicroRNA-23b/27b/24 Cluster Facilitates Colon Cancer Cell Migration by Targeting FOXP2. Cancers. 2020; 12(1):174. https://doi.org/10.3390/cancers12010174

Chicago/Turabian Style

Nishida, Kensei, Yuki Kuwano, and Kazuhito Rokutan. 2020. "The MicroRNA-23b/27b/24 Cluster Facilitates Colon Cancer Cell Migration by Targeting FOXP2" Cancers 12, no. 1: 174. https://doi.org/10.3390/cancers12010174

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop