ZFP36L2 promotes cancer cell aggressiveness and is regulated by antitumor microRNA-375 in pancreatic ductal adenocarcinoma.

Due to its aggressive nature, pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal and hard-to-treat malignancies. Recently developed targeted molecular strategies have contributed to remarkable improvements in the treatment of several cancers. However, such therapies have not been applied to PDAC. Therefore, new treatment options are needed for PDAC based on current genomic approaches. Expression of microRNA-375 (miR-375) was significantly reduced in miRNA expression signatures of several types of cancers, including PDAC. The aim of the present study was to investigate the functional roles of miR-375 in PDAC cells and to identify miR-375-regulated molecular networks involved in PDAC aggressiveness. The expression levels of miR-375 were markedly downregulated in PDAC clinical specimens and cell lines (PANC-1 and SW1990). Ectopic expression of miR-375 significantly suppressed cancer cell proliferation, migration and invasion. Our in silico and gene expression analyses and luciferase reporter assay showed that zinc finger protein 36 ring finger protein-like 2 (ZFP36L2) was a direct target of miR-375 in PDAC cells. Silencing ZFP36L2 inhibited cancer cell aggressiveness in PDAC cell lines, and overexpression of ZFP36L2 was confirmed in PDAC clinical specimens. Interestingly, Kaplan-Meier survival curves showed that high expression of ZFP36L2 predicted shorter survival in patients with PDAC. Moreover, we investigated the downstream molecular networks of the miR-375/ZFP36L2 axis in PDAC cells. Elucidation of tumor-suppressive miR-375-mediated PDAC molecular networks may provide new insights into the potential mechanisms of PDAC pathogenesis.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies; despite recently developed treatments, the 5‐year survival rate after diagnosis is only 5%.1, 2 PDAC cells are extremely aggressive and more than 50% of patients develop local recurrence or distant metastasis after curative resection.1, 3 PDAC frequently metastasizes to liver, peritoneum and lung.4, 5 Controlling recurrence and metastasis of PDAC improves disease prognosis. Therefore, understanding molecular mechanisms of PDAC aggressiveness through current genomic approaches is needed.

In the post‐genome sequencing era, the discovery of non‐coding RNA in the human genome provided new directions for the study of human cancer pathogenesis. MicroRNA (miRNA) belong to a family of small non‐coding RNA and regulate expression of protein coding and non‐coding RNA by repressing translation or cleaving RNA transcripts in a sequence‐specific manner.6 A unique characteristic of miRNA is that a single miRNA regulates a large number of RNA transcripts in human cells.7 Thus, dysregulated miRNA expression disrupts tightly regulated RNA networks in cancer cells.8 Currently, numerous studies have indicated that miRNA are aberrantly expressed in several cancers, including PDAC.9, 10 Using miRNA expression signatures, we have previously identified tumor‐suppressive miRNA and the novel cancer networks controlled by these miRNA.11, 12, 13

We recently used the same method, miRNA expression signature, to identify aberrantly expressed miRNA in PDAC cells.14 According to these miRNA signatures, microRNA‐375 (miRNA‐375) was significantly reduced in cancer cells. The tumor‐suppressive function of miR‐375 has been reported in several types of cancer.15, 16, 17, 18 Recent studies of PDAC cells showed that the anti‐tumor function of miR‐375 is exerted by targeting several oncogenes, such as PDK1 and HOXB3.19, 20 However, the RNA networks mediated by miR‐375 in PDAC are still obscure.

In this study, we focused on the functional significance of miR‐375 in PDAC cells by identifying the pathologic targets of miR‐375 and the RNA networks that contribute to PDAC aggressiveness. Our current study demonstrated that zinc finger protein 36 ring finger protein‐like 2 (ZFP36L2) is directly regulated by tumor‐suppressive miR‐375 in PDAC cells. ZFP36‐family proteins bind to adenylate‐uridylate (AU)‐rich elements of mRNA, and control gene expression by degrading or inhibiting translation of the mRNA.21, 22 Interestingly, survival analysis showed that high expression of ZFP36L2 predicted a significantly shorter survival of patients with PDAC. Elucidation of miR‐375‐mediated molecular networks in PDAC may provide new insights into the potential mechanisms of PDAC pathogenesis.

Materials and Methods

Clinical specimens and cell lines

Clinical tissue specimens (n = 27) and formalin‐fixed, paraffin‐embedded blocks (n = 37) were collected from patients with PDAC who underwent curative surgical resection at Kagoshima University Hospital between 1991 and 2014. Normal pancreatic tissue specimens (n = 14) were obtained from noncancerous tumor‐adjacent tissue. Each surgical specimen was histologically classified according to the TNM classification system.23 All patients in this study provided informed consent and the study protocol was approved by the Institutional Review Board of Kagoshima University. Two human PDAC cell lines were investigated in this study. PANC‐1 cells were obtained from RIKEN Cell Bank (Tsukuba, Ibaraki, Japan) and SW 1990 cells were obtained from the ATCC (Manassas, VA, USA).

Total RNA, including miRNA, was isolated using ISOGEN (NIPPON GENE, Toyama, Japan) according to the manufacturer's protocol.

Quantitative RT‐PCR

Quantification of miRNA was performed using quantitative RT‐PCR (qRT‐PCR) as previously described.24, 25, 26 Briefly, miRNA were quantified using stem‐loop RT‐PCR, TaqMan MicroRNA Assays and Assay‐on‐Demand Gene Expression TaqMan probes and primers as directed by the manufacturer. Probes and primers for miR‐375 (product ID: 000564; Thermo Fisher Scientific, Kanagawa, Japan), ZFP36L2 (product ID: Hs00272828_m1; Thermo Fisher Scientific), CADM1 (product ID: Hs00942508_m1; Thermo Fisher Scientific), TSPYL5 (product ID: Hs00603217_s1; Thermo Fisher Scientific), ELFN2 (product ID: Hs00287464_s1; Thermo Fisher Scientific), SLC7A5 (product ID: Hs01001183_m1; Thermo Fisher Scientific) and HOMER1 (product ID: Hs01029333_m1; Thermo Fisher Scientific) were used. Human GUSB (product ID: Hs99999908_m1; Thermo Fisher Scientific) and RNU48 (product ID: 001006; Thermo Fisher Scientific) were used as internal controls. Expression fold‐changes were determined using the ∆∆Ct method.

Transfection of miRNA mimic, inhibitor and siRNA into pancreatic ductal adenocarcinoma cell lines

Pancreatic ductal adenocarcinoma cell lines were transfected with a miRNA mimic for gain‐of‐function experiments, miRNA inhibitors for loss‐of function experiments, and siRNA for loss‐of‐function experiments. Pre‐miR miRNA precursors for miR‐375 (product ID: PM10327), negative control miRNA (product ID: AM 17111), two ZFP36L2 siRNA (product IDs: HSS101105 and HSS101106) and negative control siRNA (product ID: D‐001810‐10) were purchased from Thermo Fisher Scientific. Two types of miR‐375 inhibitors (product ID: AM10327 and IH‐300682‐07‐0005) were used: Thermo Fisher Scientific and GE Healthcare JAPAN (Tokyo, Japan). The transfection efficiencies of miRNA in PANC‐1 and SW 1990 cells were calculated as described in previous studies.24, 25, 26

Cell proliferation, migration and invasion assays

Pancreatic ductal adenocarcinoma cells were transfected with 10 nmol/L miRNA or si‐RNA by reverse transfection and seeded in 96‐well plates at 5 × 103 cells per well. After 72 h, cell proliferation was evaluated by the XTT assay using a Cell Proliferation Kit II (Roche Molecular Biochemicals, Mannheim, Germany). Cell migration assays were performed with BD Falcon Cell Culture Inserts (BD Biosciences, Franklin Lakes, NJ, USA) that contained uncoated Transwell polycarbonate membrane filters with 8‐μm pores in 24‐well tissue culture plates. Cells were transfected with 10 nm miRNA or siRNA by reverse transfection and seeded in 6‐cm dishes at 2 × 105 cells. After 48 h, the cells were collected and 1 × 105 cells were added to the upper chamber of each migration well and were allowed to migrate for 48 h. After gentle removal of the nonmigratory cells from the filter surface of the upper chamber, the cells that migrated to the lower side were fixed and stained with Diff‐Quick (Sysmex Corporation, Kobe, Japan). The number of cells that migrated to the lower surface was determined microscopically by counting eight areas of constant size per well. Cell invasion assays were performed using modified Boyden chambers containing Transwell membrane filter inserts precoated with Matrigel with 8‐μm pores in 24‐well tissue culture plates (BD Biosciences, Bedford, MA, USA). All experiments were carried out in triplicate.

Western blot analyses

Protein lysates were collected 72 h after transfection and 20 μg of protein was separated using gel electrophoresis on e‐PAGEL 5–20% gels (ATTO, Tokyo, Japan) before transfer to polyvinylidene fluoride membranes. Rabbit anti‐ZFP36L2 antibodies (product ID: 2119; Cell Signaling Technology, Danvers, MA, USA) were diluted 1:1000 for immunoblotting. Anti‐β actin antibodies at a 1:1000 dilution (product ID: A1978; Sigma Aldrich, St. Louis, MO, USA) were used as an internal loading control. A detailed description of the western blotting procedure is published elsewhere.24, 25, 26

Immunohistochemistry

Tissue sections were incubated overnight at room temperature with ZFP36L2 antibodies diluted 1:50 (product ID: HPA047428; Atlas Antibodies AB, Stockholm, Sweden). Following incubation, antibodies were visualized using an avidin–biotin complex (ABC) detection kit (Vector Laboratories, Burlingame, CA, USA) and a diaminobenzidine substrate system according to the manufacturer's protocol. Cytoplasmic staining of ZFP36L2 in at least 1% of cancer cells was classified as high. If no cancer cells were stained, specimens were classified as low for ZFP36L2 staining. The expression of ZFP36L2 was evaluated in 10 fields of 100 cells each using high‐power microscopy (400 × ).

Genome‐wide gene expression and in silico analyses

To identify miR‐375 target genes, a combination of genome‐wide gene expression and in silico analyses was conducted as described previously.24, 25, 26 The microarray data were deposited into the GEO repository under the accession numbers GSE77790 and GSE82108. Next, we selected putative miRNA target genes using the microRNA.org (August 2010 release, http://www.microrna.org/). Figure 1 shows the methodology for selecting target genes.

Figure 1

Flow chart illustrating the analysis strategy for miR‐375 target genes. Expression analysis revealed 45 and 52 downregulated genes in miR‐375‐transfected PANC‐1 and SW1990 pancreatic ductal adenocarcinoma (PDAC) cell lines, respectively. These were selected as putative target genes. Next, we compared the data of selected genes and the microRNA.org database. The analyses showed that 6 putative target genes were common to PANC‐1 and SW 1990 miR‐375 transfectants. We then analyzed gene expression in available GEO datasets (accession number GSE82108).

Plasmid construction and dual luciferase reporter assays

Partial wild‐type sequences of the 3′‐UTR of ZFP36L2 containing the miR‐375 target site (positions 269–275 of ZFP36L2 3′‐UTR, and positions 308‐314 of ZFP36L2 3′‐UTR for miR‐375) or sequences with a deleted miR‐375 target site were inserted between the XhoI and PmeI restriction sites in the 3′‐UTR of the hRluc gene in the psiCHECK‐2 vector (product ID: C8021; Promega, Madison, WI, USA). PANC‐1 and SW 1990 cell lines were transfected with 50 ng of the vector and 10 nM miR‐375 using Lipofectamine 2000 (Thermo Fisher Scientific) in Opti‐MEM (Thermo Fisher Scientific). The activities of firefly and Renilla luciferases were determined in lysates of transfected cells using a dual luciferase reporter assay system according to the manufacturer's recommendations (product ID: E1960; Promega, Madison, WI, USA). Data were normalized to firefly luciferase activity (ratio of Renilla/firefly luciferase activities).

Identification of downstream targets regulated by ZFP36L2 in pancreatic ductal adenocarcinoma

We used genome‐wide gene expression analysis in a PDAC cell line (PANC‐1) transfected with si‐ZFP36L2. Downregulated genes by ZFP36L2 were categorized by KEGG pathways using the GENECODIS program pathways. Microarray results were deposited in the GEO database (accession number GSE82108).

Statistical analysis

Using expression values and the Mann–Whitney U‐test or Bonferroni‐adjusted Mann–Whitney U‐test, relationships between two conditions or variables were analyzed. The correlation between expression of miR‐375 and ZFP36L2 was evaluated using Spearman's rank test. Associations between different categories were assessed using Fisher's exact test and the χ2‐test. Overall survival (OS) after surgery was gauged using Kaplan–Meier curves. Patients were divided into two groups based on ZFP36L2 expression, and differences in survival were estimated using the log‐rank test. Univariate and multivariate analyses were performed using the proportional hazards model. We used Expert StatView software (version 5.0 SAS Institute, Cary, NC, USA) for these analyses.

Results

Expression levels of miR‐375 in pancreatic ductal adenocarcinoma specimens and cell lines

We evaluated expression levels of miR‐375 in PDAC tissues (n = 27), normal pancreas tissues (n = 14) and two PDAC cell lines (PANC‐1 and SW 1990). Patient backgrounds and clinicopathological characteristics are summarized in Table 1. The expression levels of miR‐375 were significantly lower in tumor tissues and PDAC cell lines compared with normal pancreas tissues (Fig. 2a). However, there were no significant relationships between any of the clinicopathological parameters (i.e. TNM stage, metastasis or survival rate) and the expression of miR‐375 (Fig. S1).

Table 1

Characteristics of the patients

Pancreatic ductal adenocarcinoma
Total number	27
Median age (range), years	67.1 (42–85)
Gender
Male	12
Female	15
T category
pTis	1
pT1	2
pT2	0
pT3	22
pT4	2
N category
0	14
1	13
M category
0	25
1	2
Neoadjuvant chemotherapy
(−)	12
(+)	15
Recurrence
(−)	11
(+)	16
Normal pancreas tissue
Total number	14

Figure 2

Expression levels of miR‐375 and its effects on pancreatic ductal adenocarcinoma (PDAC) cells. (a) Expression levels of miR‐375 in clinical specimens and PDAC cell lines were determined using quantitative RT‐PCR (qRT‐PCR). Data were normalized to expression. (b) Cell growth was determined using XTT assay 72 h after transfection with 10 nM miR‐375. *P < 0.0001. (c) Cell migration activity was determined using BD Falcon Cell Culture Inserts. *P < 0.0001. (d) Cell invasion activity was determined using Matrigel invasion assays. *P < 0.0001.

Effect of miR‐375 expression on cell growth, migration and invasion in pancreatic ductal adenocarcinoma cell lines

To investigate the functional roles of miR‐375, we performed gain‐of‐function studies using transfection. XTT, cell migration and cell invasion assays demonstrated that cell proliferation, migration and invasion were significantly inhibited in miR‐375 transfectants compared with mock or miR‐control transfectants (each P < 0.0001, Fig. 2b–d). Furthermore, we performed loss‐of‐function assays using miR‐375 inhibitors in PDAC cells. Our present data showed that cancer cell proliferation, migration and invasion were significantly enhanced by suppression of miR‐375 in PDAC cells (Fig. S2). These results suggested that miR‐375 could have a tumor‐suppressive function in PDAC cells.

Identification of genes regulated by miR‐375 in pancreatic ductal adenocarcinoma cells

To gain further insight into the molecular mechanisms and pathways regulated by tumor‐suppressive miR‐375 in PDAC cells, we used a combination of in silico and gene expression analyses. Figure 1 presents the strategy for narrowing down the target genes of miR‐375. In gene expression analyses, 45 and 52 genes were downregulated (log2 ratio <−1.0) in PANC‐1 and SW 1990 miR‐375 transfectants, respectively, in comparison with control transfectants (GEO accession number GSE77790). Next, we pared down the list of genes using the microRNA.org database. We found that 9 and 14 genes were putatively targeted by miR‐375 in PANC‐1 and SW 1990 miR‐375 transfectants, respectively. Of those genes, 6 were common to both miR‐375 transfectants. We validated the changes of 6 genes by miR‐375 regulation using miR‐375 transfectant cells (Fig. S3). Among them, we determined that ZFP36L2 was upregulated in clinical PDAC samples using qRT‐PCR (Table 3, Fig. 3a,c). No negative correlations between miR‐375 expression and ZFP36L2 mRNA expression were found using Spearman's rank test (r = −0.240, P = 0.1042, Fig. 3b).

Table 3

Candidate target genes regulated by miR‐375 in pancreatic ductal adenocarcinoma

Entrez gene ID	Gene symbol	Description	Microarray (Log2 ratio) miR‐375			Target site (miRanda)
			Panc‐1	SW1990	Average	miR‐375
23705	CADM1	Cell adhesion molecule 1	−3.86	−5.17	−4.51	(+)
9456	HOMER1	Homer scaffolding protein 1	−1.76	−1.77	−1.76	(+)
8140	SLC7A5	Solute carrier family 7 member 5	−1.51	−1.52	−1.52	(+)
85453	TSPYL5	TSPY‐like 5	−1.38	−1.38	−1.38	(+)
678	ZFP36L2	ZFP36 ring finger protein‐like 2	−1.20	−1.04	−1.12	(+)
114794	ELFN2	Extracellular leucine‐rich repeat and fibronectin type III domain containing 2	−1.00	−1.13	−1.07	(+)

Figure 3

Expression of putative miR‐375 target genes in pancreatic ductal adenocarcinoma (PDAC) clinical specimens and cell lines. (a) Expression levels of in clinical specimens and PDAC cell lines were determined using quantitative RT‐PCR (qRT‐PCR). Data were normalized to expression. (b) Correlation between miR‐375 and expression. (c) Expression levels of other putative miR375 target genes in clinical specimens and PDAC cell lines were determined using qRT‐PCR. Data were normalized to expression.

ZFP36L2 is a direct target of miR‐375 in pancreatic ductal adenocarcinoma cells

We performed qRT‐PCR to validate miR‐375 repression of ZFP36L2 mRNA expression in PDAC cell lines. Our studies revealed that ZFP36L2 mRNA was significantly reduced in miR‐375 transfectants in comparison with mock or miR‐control transfectants (P < 0.0001 and P = 0.0036, Fig. 4a). Protein expression of ZFP36L2 was also repressed in the miR‐375 transfectants (Fig. 4b).

Figure 4

Direct regulation of by miR‐375 in pancreatic ductal adenocarcinoma (PDAC) cells. (a) mRNA expression was evaluated using quantitative RT‐PCR (qRT‐PCR) in PANC‐1 and SW1990 cells 72 h after transfection with miR‐375. was used as an internal control. *P < 0.0001. (b) ZFP36L2 protein expression was evaluated using western blot in PANC‐1 and SW1990 cells 72–96 h after transfection with miR‐375. β‐actin was used as a loading control. (c) miR‐375 binding sites in the 3′‐UTR of mRNA. Dual luciferase reporter assays using vectors encoding putative miR‐375 target sites of the 3′‐UTR (positions 269–275 and 308–314) for both wild‐type and deleted regions. Data were normalized as ratios of Renilla/firefly luciferase activities. *P < 0.0001.

Target prediction databases indicated two putative target sites in the 3′‐UTR of ZFP36L2 (Fig. 4c). To determine whether ZFP36L2 mRNA had a functional target site, we performed a luciferase reporter assay. Compared with the miR‐control, luminescence intensity was significantly reduced by transfection with miR‐375 at the miR‐375 target site, position 308‐314 in the 3′‐UTR of ZFP36L2 (Fig. 4c, lower).

Effects of silencing ZFP36L2 on PDAC cell lines

To investigate the functional role of ZFP36L2 in PDAC cells, we carried out loss‐of‐function studies using si‐ZFP36L2 transfectants. First, we evaluated the knockdown efficiency of si‐ZFP36L2 transfection in PDAC cell lines. In the present study, we used two types of si‐ZFP36L2 (si‐ZFP36L2‐1 and si‐ZFP36L2‐2). According to qRT‐PCR and western blot analyses, both siRNA effectively downregulated ZFP36L2 expression in both cell lines (Fig. 5a,b). XTT, cell migration and cell invasion assays demonstrated that cell proliferation, migration and invasion were inhibited in si‐ZFP36L2 transfectants compared with mock‐control or siRNA‐control‐transfected cells (Fig. 5c–e).

Figure 5

Effects of silencing on pancreatic ductal adenocarcinoma (PDAC) cell lines. (a) mRNA expression was evaluated using quantitative RT‐PCR (qRT‐PCR) in PANC‐1 and SW1990 cells 72 h after transfection with si‐‐1 and si‐‐2. was used as an internal control. (b) ZFP36L2 protein expression was evaluated using western blot in PANC‐1 and SW1990 cells 72 to 96 h after transfection with miR‐375. β‐actin was used as a loading control. (c) Cell proliferation was determined using XTT assay 72 h after transfection with 10 nM si‐‐1 or si‐‐2. *P < 0.0001, **P = 0.0007. (d) Cell migration activity was determined using BD Falcon Cell Culture Inserts. *P < 0.0001. (e) Cell invasion activity was determined using Matrigel invasion assays. *P < 0.0001.

Expression of ZFP36L2 in pancreatic ductal adenocarcinoma clinical specimens

We confirmed the expression of ZFP36L2 in PDAC clinical specimens using immunohistochemistry. A total of 37 specimens were evaluated, and 13 samples were classified as having high expression of ZFP36L2 (Fig. 6a–c). Clinicopathological characteristics are summarized in Table 2. Table 4 shows the correlation between ZFP3L2 expression and various clinicopathological factors. High ZFP36L2 expression was significantly associated with increased lymph node metastasis. Furthermore, patients with high ZFP36L2 expression had significantly shorter OS than those with low ZFP36L2 expression (P = 0.0167) (Fig. 6d). In addition, univariate and multivariate analysis showed that ZFP36L2 served as an independent prognostic factor for PDAC (Table 5).

Figure 6

Immunohistochemical staining of ZFP36L2 in pancreatic ductal adenocarcinoma (PDAC) clinical specimens and association of ZFP36L2 with overall survival. Immunohistochemical staining of ZFP36L2 in PDAC clinical specimens. Overexpression of ZFP36L2 was observed in cancer lesions (original magnification ×400). In contrast, negative staining of ZFP36L2 was observed in normal tissues. (a) Positively stained cancer lesion (T3N1M0). (b) Negatively stained cancer lesion (T3N1M0). (c) Negatively stained normal pancreas tissue. (d) Kaplan–Meier survival curves for overall survival rates based on ZFP36L2 expression in 37 patients with PDAC. P‐values were calculated using the log‐rank test.

Table 2

Characteristics of patients included in the immunohistochemistry

Pancreatic ductal adenocarcinoma
Total number	37
Median age (range), years	66.9 (44–85)
Gender
Male	21
Female	16
T category
pTis	0
pT1	0
pT2	2
pT3	26
pT4	9
N category
0	14
1	23
M category
0	37
1	0
Neoadjuvant chemotherapy
(−)	37
(+)	0
Recurrence
(−)	8
(+)	29

Table 4

Correlation between the expression of ZFP36L2 and clinicopathological factors in pancreatic ductal adenocarcinoma (n = 37)

Characteristic	ZFP36L2		P
	Low (n = 24)	High (n = 13)
Age (n)
≥60 (26)	15	11	NS
<60 (11)	9	2
Gender (n)
Male (21)	13	8
Female (16)	11	5	NS
Tumor size (n)
>40 mm (9)	4	5	NS
≤40 mm (28)	20	8
Lymph node metastasis (n)
No (14)	12	2	0.0382
Yes (23)	12	11
TNM Stage (n)
I/II (27)	17	10	NS
III/IV (10)	7	3
Recurrence (n)
No (8)	7	1	NS
Yes (29)	17	12

Table 5

Univariate analysis and multivariate analysis in pancreatic ductal adenocarcinoma

Univariate analysis	Hazard ratio	95% CI	P‐value
Age	0.971	0.490–1.926	0.9333
Gender	0.405	0.206–0.795	0.0086
Tumor size	1.544	0.737–3.236	0.2499
Lymph node metastasis	0.584	0.294–1.161	0.1248
Distant metastasis	0.436	0.176–1.076	0.0716
TNM stage	2.321	1.174–4.587	0.0154
ZFP36L2	0.383	0.186–0.788	0.0091
Multivariate analysis
Gender	0.302	0.147–0.620	0.0011
TNM stage	3.792	1.777–8.091	0.0006
ZFP36L2	0.269	0.123–0.585	0.0009

Investigation of downstream genes regulated by ZFP36L2 in pancreatic ductal adenocarcinoma cells

To identify the downstream genes regulated by ZFP36L2, genome‐wide gene expression and in silico analyses were performed in a PDAC cell line (PANC‐1) transfected with si‐ZFP36L2. A total of 1287 genes were commonly downregulated (log2 ratio < −1.0) in si‐ZFP36L2‐transfected PANC‐1 cells. We also assigned the downregulated genes to KEGG pathways using the GENECODIS program and identified 60 pathways as significantly enriched. The 5 most enriched pathways are presented in Table 6a. Of these 5 pathways, we focused on genes in the ‘cell cycle’ and ‘pathways in cancer’ pathways. The genes composing these 2 pathways are listed in Table 6b,c. Furthermore, we checked the expression status of these genes and pathologic relations of the PDAC by using TCGA‐based large cohort study data (Table 6b,c). We applied the OncoLnc database using 87 pancreatic adenocarcinoma samples (http://www.oncolnc.org/). Clinical outcome for patients with high expression of CCNB1 and CCNB2 or low expression of these genes are displayed as Kaplan–Meier plots with log‐rank tests (Fig. S4).27

Table 6

(a) Top 5 enriched KEGG pathways downregulated by si‐ZFP36L2; (b) Regulation of genes related to the cell cycle; (c) Regulation of genes related to the pathways in cancer

(a) Number of genes	Pathway name	P‐value
26	Cell cycle	2.25E‐16
20	Oocyte meiosis	1.23E‐11
30	Pathways in cancer	4.32E‐09
14	Small cell lung cancer	4.67E‐08
14	Progesterone‐mediated oocyte maturation	6.36E‐08

NS, not significant. OncoLnc, OncoLnc database.

Discussion

Most patients with PDAC already have advanced or metastasized cancer at the time of first diagnosis. The prognosis for patients with advanced stage PDAC is extremely poor, and there are few effective treatments to date.28 An oncogenic KRAS mutation is frequently observed in patients with PDAC and leads to constitutive activation of KRAS downstream signaling pathways.29 Many studies have failed to directly inhibit activation of KRAS, suggesting that KRAS is a nondruggable target in human cancers.29 To develop new treatment strategies for the disease, it is necessary to elucidate the molecular pathogenesis of PDAC aggressiveness using current genomic approaches.

Substantial evidence has demonstrated that aberrant expression of miRNA is deeply involved in human cancer pathogenesis, including that of PDAC.14, 30 Functionally, miRNA fine‐tune expression of protein‐coding and non‐coding RNA in human cells.31 Therefore, aberrantly expressed miRNA lead to the collapse of tightly regulated RNA networks in cancer cells. Recently, we summarized the aberrant expression of miRNA in PDAC cells.14 Several miRNA were significantly downregulated in PDAC cells, such as miR‐217, miR‐141, miR‐148a, miR‐375 and miR‐29c. Recent studies have also demonstrated that these miRNA function as antitumor miRNA in PDAC.32, 33, 34 For example, expression of miR‐217 was significantly reduced in PDAC tissues and cell lines and directly targeted KRAS mRNA.32 It is well known that miR‐200c/miR‐141 form a miRNA cluster and inhibit epithelial–mesenchymal transition (EMT) in cancer cells.35, 36 In PDAC, miR‐200c and miR‐141 directly bind to the 3′‐UTR of ZEB1 mRNA and TGFb mRNA, respectively, and inhibit cell invasion and migration.33 MiR‐148a has been reported to be associated with DNA methylation in malignant tumors, including PDAC.34

Our previous studies showed that expression of miR‐375 was markedly reduced in several types of cancers and functions as an antitumor miRNA.37, 38, 39 Other studies confirm the antitumor function of miR‐375 in cancer.40, 41 In contrast to these antitumor activities, expression of miR‐375 was upregulated in pediatric acute myeloid leukemia and prostate cancer, suggesting that miR‐375 acts as an oncogenic miRNA in these diseases.42, 43 The dual function of miR‐375 is very unique; thus, it is important to identify miR‐375‐regulated pathways in various cancer types. In this study, we focused on miR‐375 and miR‐375‐mediated oncogenic pathways in PDAC. Previous studies of miR‐375 in PDAC indicated that pyruvate dehydrogenase kinase, isozyme 1 (PDK1) is a regulatory target of miR‐375. PDK1 is a key component in the phosphatidylinositol 3‐kinase‐Akt‐mammalian target of rapamycin (PI3K‐Akt‐mTOR) signaling pathway and has been shown to inhibit proliferation and promote apoptosis in PDAC cells.19, 44

In this study, we showed that ectopic expression of miR‐375 significantly suppressed cancer cell aggressiveness and confirmed the antitumor function of miR‐375 in PDAC cells. Moreover, we identified that ZFP36L2 was directly regulated by antitumor miR‐375 in PDAC cells. ZFP36L2 is zinc finger protein 36, C3H type‐like 2 (also known as Brf2, Erf2 and Tis11D).22 ZFP36L2 directly binds to the AU‐rich element (ARE) in the 3′‐UTR of the target mRNA and regulates the expression of target mRNA.21, 22

According to the previous studies, ZFP36 has antitumor function in several types of cancers.22, 45 Past studies have shown that deletion of ZFP36L2 induced Notch1‐dependent T cell acute lymphoblastic leukemia in mice, and a frameshift mutation in the ZFP36L2 gene was identified in several types of leukemic cells.46 In leukemic cells, a heterozygous frameshift mutation of ZFP36L2/TIS11D gene was detected in a patient with acute myeloid leukemia.47 Moreover, overexpression of wild‐type of ZFP36L2/TIS11D gene inhibited growth of HeLa cells.47 In colorectal cancer, expression of ZFP36 was significantly reduced in cancer tissues and restored ZFP36 expression inhibited epithelial‐to‐mesenchymal transition and induces a higher susceptibility to anoikis.48 These studies indicate that ZFP36L2 acts as a tumor suppressor in human cancers.

In contrast to previous studies, we showed that overexpression of ZFP36L2 was detected in PDAC clinical specimens and knockdown of ZFP36L2 significantly inhibited cancer cell aggressiveness in PDAC cell lines. Furthermore, high expression of ZFP36L2 is significantly associated with lymph node metastasis and poor prognosis of patients with PDAC. Our data demonstrated that ZFP36L2 functions as an oncogene in PDAC cells and is deeply involved in PDAC pathogenesis.

To investigate the oncogenic function of ZFP36L2 in PDAC cells, we identified ZFP36L2‐regulated PDAC pathways using genome‐wide gene expression analysis of si‐ZFP36L2‐transfected cells. Downstream genes modulated by ZFP36L2 were categorized by KEGG pathways. Our data showed that “cell cycle” and “pathways in cancer” pathways were downregulated by ZFP36L2. Recent study showed that ZFP36L1 and ZFP36L2 were critical roles for developing B lymphocytes regulating cell cycle pathways.49 The genes involved in these pathways were critical regulators of cancer cell aggressiveness. Current studies indicated that several cell cycle kinases, such as BUB1 and PLK1, were multi‐functional genes and contributed to cancer cell migration, invasion and metastasis.50, 51 Moreover, overexpression of EGFR, LAMC2, ITGA6 and ITGA3 was observed in several cancers, including PDAC, and these genes were involved in enhancing EMT and cancer cell migration and invasion.52, 53, 54 Furthermore, SLC2A1 is also known as GLUT‐1 and regulates the entry of glucose into cells.55 High expression of SLC2A1 is associated with higher histological grade and larger tumor size.56 Overexpression of SLC2A1 increases MMP‐2 expression and enhances cancer cell invasion.57 These studies have supported our present data of knockdown of ZFP36L2 in PDAC cells.

The primary finding of the present study is the overexpression of ZFP36L2 and several ZFP36L2‐regulated genes that are involved in the pathogenesis of PDAC. A TCGA‐based large cohort study and gene expression data indicated that high expression of 10 genes (CDC45, CDK6, CCNB2, CDK1, BUB1, CCNB1, SLC2A1, ITGA3, STAT1 and FAS) predicted poorer survival of PDAC patients. These findings showed that ZFP36L2‐mediated pathways are deeply involved in PDAC pathogenesis. The identification of the downstream genes regulated by the miR‐375/ZFP36L2 axis may lead to a better understanding of PDAC aggressiveness.

In conclusion, downregulation of miR‐375 was validated in PDAC clinical specimens, and miR‐375 was shown to function as an antitumor miRNA in PDAC cells. To the best of our knowledge, this is the first report demonstrating that ZFP36L2 is directly regulated by antitumor miR‐375 and acts to regulate several oncogenic genes. Expression of ZFP36L2 might be a useful prognostic marker for survival of PDAC patients. The identification of novel molecular pathways and targets regulated by the miR‐375/ZFP36L2 axis may lead to a better understanding of PDAC progression and aggressiveness.

Disclosure Statement

The authors have no conflict of interest to declare.

Fig. S1. The association between the expression levels of miR‐375 with clinicopathological parameters.

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Fig. S2. Effects of miR‐375 inhibition on pancreatic ductal adenocarcinoma (PDAC) cell lines.

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Fig. S3. Regulation of putative target genes by miR‐375 in pancreatic ductal adenocarcinoma (PDAC) cells.

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Fig. S4. The association between the expression level of CCNB1 or CCNB2 and overall survival.

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