Molecular Pathogenesis of Pancreatic Ductal Adenocarcinoma: Impact of Mir-30C-5P and Mir-30C-2-3P Regulation on Oncogenic Genes

cancers

Article Molecular Pathogenesis of Pancreatic Ductal Adenocarcinoma: Impact of miR-30c-5p and miR-30c-2-3p Regulation on Oncogenic Genes

Takako Tanaka 1 , Reona Okada 2, Yuto Hozaka 1 , Masumi Wada 1, Shogo Moriya 3, Souichi Satake 1, Tetsuya Idichi 1, Hiroshi Kurahara 1, Takao Ohtsuka 1 and Naohiko Seki 2,*

1 Department of Digestive Surgery, Breast and Thyroid Surgery, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima 890-8520, Japan; [email protected] (T.T.); [email protected] (Y.H.); [email protected] (M.W.); [email protected] (S.S.); [email protected] (T.I.); [email protected] (H.K.); [email protected] (T.O.) 2 Department of Functional Genomics, Chiba University Graduate School of Medicine, Chiba 260-8670, Japan; [email protected] 3 Department of Biochemistry and Genetics, Chiba University Graduate School of Medicine, Chiba 260-8670, Japan; [email protected] * Correspondence: [email protected]; Tel.: +81-43-226-2971; Fax: +81-43-227-3442

Received: 4 August 2020; Accepted: 21 September 2020; Published: 23 September 2020

Simple Summary: A total of 10 genes (YWHAZ, F3, TMOD3, NFE2L3, ENDOD1, ITGA3, RRAS, PRSS23, TOP2A, and LRRFIP1) were identiﬁed as tumor suppressive miR-30c-5p and miR-30c-2-3p targets in pancreatic ductal adenocarcinoma (PDAC), and expression of these genes were independent prognostic factors for patient survival. Furthermore, aberrant expression of TOP2A and its transcriptional activators (SP1 and HMGB2) enhanced malignant transformation of PDAC cells.

Abstract: Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive types of cancer, and its prognosis is abysmal; only 25% of patients survive one year, and 5% live for five years. MicroRNA (miRNA) signature analysis of PDAC revealed that both strands of pre-miR-30c (miR-30c-5p, guide strand; miR-30c-2-3p, passenger strand) were significantly downregulated, suggesting they function as tumor-suppressors in PDAC cells. Ectopic expression assays demonstrated that these miRNAs attenuated the aggressiveness of PDAC cells, e.g., cell proliferation, migration, and invasiveness. Through a combination of in silico analyses and gene expression data, we identified 216 genes as putative oncogenic targets of miR-30c-5p and miR-30c-2-3p regulation in PDAC cells. Among these, the expression of 18 genes significantly predicted the 5-year survival rates of PDAC patients (p < 0.01). Importantly, the expression levels of 10 genes (YWHAZ, F3, TMOD3, NFE2L3, ENDOD1, ITGA3, RRAS, PRSS23, TOP2A, and LRRFIP1) were found to be independent prognostic factors for patient survival (p < 0.01). We focused on TOP2A (DNA Topoisomerase II Alpha) and investigated its potential as a therapeutic target for PDAC. The overexpression of TOP2A and its transcriptional activators (SP1 and HMGB2) was detected in PDAC clinical specimens. Moreover, the knockdown of TOP2A enhanced the sensitivity of PDAC cells to anticancer drugs. Our analyses of the PDAC miRNA signature and tumor-suppressive miRNAs provide important insights into the molecular pathogenesis of PDAC.

Keywords: pancreatic ductal adenocarcinoma; microRNA; tumor-suppressor; miR-30c-5p; miR-30c-2-3p; TOP2A

Cancers 2020, 12, 2731; doi:10.3390/cancers12102731 www.mdpi.com/journal/cancers Cancers 2020, 12, 2731 2 of 22

1. Introduction Pancreatic ductal adenocarcinoma (PDAC), which accounts for the majority of pancreatic cancer (approximately 90%), is one of the most malignant tumors in the world and the third leading cause of cancer death, characterized by frequent metastases and profound chemotherapy resistance [1,2]. The 5-year relative survival rate for pancreatic cancer is the lowest among cancers—only 9% across all stages, and the death rates for pancreatic cancers have risen over the past decade [3]. The current standard treatments for pancreatic cancers continue to rely on surgical resection and cytotoxic therapies; however, only less than 20% of patients are eligible to complete surgical resection, and many will relapse and die within one year [3–6]. To make matters worse, owing to the asymptomatic nature of the early stage of the disease and the absence of efficient diagnostic methods, most patients with PDAC present with the locally advanced and inoperable disease at diagnosis [3–6]. Thus, it is essential to search for new diagnostic markers and develop new therapeutic strategies based on the latest genomic analyses of PDAC. Sequencing through the human genome project has revealed that a vast number of non-coding RNAs are transcribed from the human genome and act as pivotal players in various cellular pathways in physiological and pathological conditions [7]. MicroRNAs (miRNAs) are members of endogenous non-coding RNAs. They are single-stranded RNA, 19 to 23 nucleotides in length, and their functions include fine-tuning of RNA expressions by degradation or translational inhibition of the target RNA transcripts [8,9]. A unique feature of miRNAs is that a single miRNA can control a vast number of RNA transcripts (protein-coding genes and non-coding genes), and, conversely, one mRNA can be the target of numerous miRNAs in diseased and normal cells [8,9]. Bioinformatic studies have shown that more than half of the genes expressed in cells are under the control of miRNAs [10,11]. Given this nearly ubiquitous expression, aberrantly expressed miRNAs can cause perturbations of RNA networks within cells, and these factors are among those that can transform normal cells into cancer cells. Consistently, many studies have shown that aberrant expressions of miRNAs are closely involved in oncogenesis [12–14]. Over the last decade, by applying the latest genomics analysis methods, the search for miRNAs whose expressions are altered in PDAC cells has been energetically carried out [15–17]. A vast number of studies in PDAC cells have revealed that dysregulated miRNAs are deeply involved in the malignant transformation of cancer cells, e.g., cell cycle runaway, suppression of apoptosis, promotion of cell invasion and metastasis, and acquisition of drug resistance [15–17]. Our recent studies have shown that some miRNA passenger strands derived from the pre-miRNA-duplex act as tumor-suppressive miRNAs and their target genes are closely involved in oncogenesis [18–22]. The involvement of miRNA passenger strands in oncogenesis is a new concept in cancer research. Thus, the analysis of both miRNA strands is essential in searching for the molecular pathogenesis of human cancers [23]. Using RNA-sequencing technology, we constructed the miRNA expression signature of PDAC [24]. Analysis of our PDAC signature revealed that both miRNA strands derived from pre-miR-30c (miR-30c-5p, the guide strand; miR-30c-2-3p, the passenger strand) were significantly downregulated in PDAC tissues. The miR-30-family is located on three chromosomal regions (chromosome 1: miR-30c-1 and miR-30e; chromosome 6: miR-30c-2 and miR-30a; chromosome 8: miR-30b and miR-30d) and consists of 12 different mature miRNAs [25]. The seed sequences of the guide strands of the miR-30 family are identical (GUAAACA). In contrast, there are variations in the seed sequences of the passenger strands of the miR-30 family. However, the mature sequences of miR-30c-1-3p (CUGGGAGAGGGUUGUUUACUCC) and miR-30c-2-3p (CUGGGAGAAGGCUGUUUACUCU) are almost identical. Accumulating evidence suggests that guide strands of the miR-30 family act as critical players (tumor-suppressor or oncogenic) in a wide range of human cancers [26–29]. In contrast, there have been almost no reports on the role of miR-30 family passenger strands in PDAC research. In this study, we focused on both strands of the pre-miR-30c (miR-30c-5p, the guide strand; miR-30c-2-3p, the passenger strand) and sought to identify their target genes, which are intimately involved in the molecular Cancers 2020, 12, 2731 3 of 22 pathogenesisCancers 2020, 12 of, x PDAC. FOR FREE A REVIEW total of 10 genes (YWHAZ, F3, TMOD3, NFE2L3, ENDOD1, ITGA3, RRAS3 of, 23 PRSS23, TOP2A, and LRRFIP1) were identified as being significantly predictive of worse prognosis worse prognosis (5-year survival rate) in patients with PDAC. Furthermore, we discussed the (5-year survival rate) in patients with PDAC. Furthermore, we discussed the functional significance of functional significance of TOP2A in PDAC cells. TOP2A in PDAC cells.

2.2. Results Results

2.1.2.1. Downregulation Downregulatio ofn of miR-30c-5p miR-30c-5p and and miR-30c-2-3p miR-30c-2-3p in in PDAC PDAC Clinical Clinical Specimens Specimens and and Cell Cell Lines Lines ToTo confirm confirm the the miRNA miRNA expression expression signature signature of of PDAC, PDAC, we we evaluated evaluated the the expression expression levels levels of of miR-30c-5pmiR-30c-5pand andmiR-30c-2-3p miR-30c-2-3pin in PDAC PDAC clinical clinical specimens. specimens. The The clinical clinical features features of of the the patients patient ares are summarizedsummarized in in Table Table S1. S1. TheThe expression expression levels levels of miR-30c-5p of miR-30cand-5pmiR-30c-2-3p and miR-30cwere-2-3p significantly were significantly downregulated downregulated in PDAC in tumorPDAC tissues tumor compared tissues compared with matched with normal matched tissues normal (p = 0.0045tissues and (p =p 0.0045= 0.0013, and respectively; p = 0.0013, Figurerespectively;1A). TheirFigure expression 1A). Their was alsoexpression confirmed was to also be low confirmed in two PDAC to be celllow lines: in two PANC-1 PDAC and cell SW1990 lines: (FigurePANC-11A). and Furthermore,SW1990 (Figure there 1A). was Furthermore, a positive correlation there was between a positivemiR-30c-5p correlationand betweenmiR-30c-2-3p miR-expression30c-5p and amongmiR-30c- the2- clinical3p expressionF samplesigure 1 among (Spearman’s the clinical rank sample analysis;s (Spearmanr = 0.832,’ps rank< 0.001; analysis; Figure r1 =B). 0.832, p < 0.001; Figure 1B).

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FigureFigure 1. Downregulation 1. Downregulation of miR-30c-5p of miR-30cand-5pmiR-30c-2-3p and miR-30cin- pancreatic2-3p in pancreatic ductal adenocarcinoma ductal adenocarcinoma (PDAC). (A)(PDAC Expression). (A) levels Expression of miR-30c-5p levels ofand miRmiR-30c-2-3p-30c-5p andin miR PDAC-30c- clinical2-3p in specimens PDAC clinical and cell specimens lines (PANC-1 and cell andlines SW1990). (PANC Data-1 and were SW1990). normalized Data were to the normalized expression to of the RNU48. expression (B) Spearman’s of RNU48. rank(B) Spearman’s tests showed rank miR-30c-5p miR-30c-2-3p positivetests showed correlations positive between correlations the expression between levels the of expression levelsand of miR-30c-in5p clinicaland miR specimens.-30c-2-3p in 2.2. Eﬀectsclinical of Ectopic specimens Expression. of miR-30c-5p and miR-30c-2-3p on Cell Proliferation, Migration, and Invasion in PDAC Cells 2.2. Effects of Ectopic Expression of miR-30c-5p and miR-30c-2-3p on Cell Proliferation, Migration, and InvasionThe antitumor in PDAC Cells activities of miR-30c-5p and miR-30c-3p were assessed by transfecting these miRNAs into PANC-1 and SW1990 cells. Speciﬁcally, the suppression of cell proliferation was observed followingThe miR-30c-3p antitumor transfection activities of (FiguremiR-30c2-A).5p Furthermore,and miR-30c-3p ectopic were expression assessed by of transfectingmiR-30c-5p and these miR-30c-3pmiRNAs suppressedinto PANC- cell1 and migration SW1990 and cells. cell invasionSpecifically, (Figure the2 suppressionB,C). of cell proliferation was observed following miR-30c-3p transfection (Figure 2A). Furthermore, ectopic expression of miR-30c- 5p and miR-30c-3p suppressed cell migration and cell invasion (Figures 2B,C).

Cancers 2020, 12Fi,g 2731ure 2 4 of 22 Cancers 2020, 12, x FOR FREE REVIEW 4 of 23

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i i m m FigureFigure 2. Tumor-suppressive 2. Tumor-suppressive roles roles of miR-30c-5p of miR-30c-and5p andmiR-30c-2-3p miR-30c-2-in3p PDACin PDAC cell cell lines. lines (A. )(A Cell) Cell proliferationproliferation was was measured measured by by the the XTT XTT assay. assay. Data Data were were collected collected 7272 hh afterafter miRNA transfection (* p (* p<< 0.0001).0.0001). (B (B) )Cell Cell migration migration was was assessed assessed with with a amembrane membrane culture culture system. system. Data Data were were collected collected 48 h 48 hafter after seeding seeding the the cells cells in intoto chambers chambers (* p (*

Cancers 2020, 12, 2731 5 of 22 tissues compared to normal pancreatic tissues (Figure4). We also validated the gene expression levels of these 18 genes using another expression dataset (GSE28735). The analysis data is shown in Figure S1. Two datasets revealed that the expressions of these genes were upregulated in cancerous tissues.

Table 1. Putative target genes by miR-30c-5p and miR-30c-2-3p regulation in PDAC cells.

Putative Target Genes by miR-30c-5p Regulation in PDAC Cells PANC-1 PANC-1 Total Entrez Gene GEO 1 GEO miR-30c-5p miR-30c-5p Gene Name Binding Gene Symbol FC 2 log FC Transfectant Transfectant 2 Sites FC log2 FC tyrosine 3-monooxygenase/tryptophan 7534 YWHAZ 5-monooxygenase 2.11 1.08 1.80 0.85 1 − − activation protein, zeta polypeptide core-binding factor, beta 865 CBFB 2.23 1.16 2.33 1.22 2 subunit − − Putative Target Genes by miR-30c-2-3p Regulation in PDAC Cells PANC-1 PANC-1 Total Entrez Gene GEO GEO miR-30c-2-3p miR-30c-2-3p Gene Name Binding Gene Symbol FC log FC Transfectant Transfectant 2 Sites FC log2 FC coagulation factor III 2152 F3 (thromboplastin, tissue 2.63 1.39 1.62 0.69 1 − − factor) tropomodulin 3 29766 TMOD3 2.05 1.03 2.80 1.48 2 (ubiquitous) − − nuclear factor, erythroid 9603 NFE2L3 2.85 1.51 2.13 1.09 3 2-like 3 − − endonucleasedomain 23052 ENDOD1 2.26 1.18 1.56 0.64 1 containing 1 − − integrin, alpha 3 (antigen CD49C, alpha 3 3675 ITGA3 2.51 1.33 2.56 1.36 2 subunit of VLA-3 − − receptor) related RAS viral (r-ras) 6237 RRAS 2.21 1.15 1.89 0.92 1 oncogene homolog − − 11098 PRSS23 protease, serine, 23 2.75 1.46 1.92 0.94 1 − − topoisomerase (DNA) II 7153 TOP2A 2.89 1.53 2.28 1.19 1 alpha 170kDa − − basic helix-loop-helix 8553 BHLHE40 3.22 1.69 1.56 0.64 1 family, member e40 − − carbohydrate 50515 CHST11 (chondroitin 4) 2.95 1.56 1.80 0.85 1 − − sulfotransferase 11 interleukin 1 receptor 3556 IL1RAP 2.01 1.01 1.80 0.83 1 accessory protein − − digestive organ 27042 DIEXF expansion factor 2.11 1.08 1.62 0.70 5 − − homolog (zebraﬁsh) coronin, actin binding 23603 CORO1C 2.96 1.57 2.90 1.54 1 protein, 1C − − receptor (chemosensory) 64108 RTP4 2.27 1.18 5.89 2.56 1 transporter protein 4 − − adaptor-related protein 130340 AP1S3 complex 1, sigma 3 2.09 1.06 4.18 2.05 3 − − subunit leucine rich repeat (in 9208 LRRFIP1 2.65 1.40 2.43 1.28 2 FLII) interacting protein 1 − − 1 Gene Expression Omnibus, 2 Fold change. Cancers 2020, 12, 2731 6 of 22 CancersFig 2020ure, 123, x FOR FREE REVIEW 7 of 23

YWHAZ expression CBFB expression 100 100 p = 0.001 p = 0.0086

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ENDOD1 expression ITGA3 expression RRAS expression 100 100 100 p = 0.00004 p = 0.00004 p = 0.0010

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PRSS23 expression TOP2A expression BHLHE40 expression 100 100 100 p = 0.0024 p = 0.0027 p = 0.0037

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Figure 3

Cancers 2020, 12, 2731 7 of 22 Cancers 2020, 12, x FOR FREE REVIEW 8 of 23

CHST11 expression IL1RAP expression DIEXF expression 100 100 100 p = 0.0040 p = 0.0055 p = 0.0058

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CORO1C expression RTP4 expression AP1S3 expression 100 100 100 p = 0.0071 p = 0.0083 p = 0.0084

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LRRFIP1 expression 100 p = 0.0096

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FigureFigure 3. 3. ClinicalClinical significance significance of of miRmiR-30c-5p-30c-5p andand miRmiR-30c-2-3p-30c-2-3p targettarget genes genes by by The The Cancer Cancer Genome Genome AtlasAtlas ( (TCGA)TCGA) database database analysis. analysis. Among Among the the putative putative target target genes genes of of miRmiR-30c-5p-30c-5p andand miRmiR-30c-2-3p-30c-2-3p YWHAZ CBFB F3 TMOD3 NFE2L3 regulationregulation in in PDAC PDAC cells, cells, high high expression expression levels levels of of 1 188 genes genes ( (YWHAZ, ,CBFB, ,F3, ,TMOD3, ,NFE2L3, , ENDOD1, ITGA3, RRAS, PRSS23, TOP2A, BHLHE40, CHST11, IL1RAP, DIEXF, CORO1C, RTP4, AP1S3, ENDOD1, ITGA3, RRAS, PRSS23, TOP2A, BHLHE40, CHST11, IL1RAP, DIEXF, CORO1C, RTP4, and LRRFIP1) were found to significantly predict worse prognoses in patients with PDAC (p < 0.01). AP1S3, and LRRFIP1) were found to significantly predict worse prognoses in patients with PDAC (p Kaplan–Meier curves of the 5-year overall survival rate for each gene are presented. < 0.01). Kaplan–Meier curves of the 5-year overall survival rate for each gene are presented. The expression levels of these proteins were verified by “The Human Protein Atlas” database (https://www.proteinatlas.org/). The results of immunostaining for these proteins are summarized in Table S3. Furthermore, in order to predict the functions of these genes, gene ontology (GO) classification was performed using the GeneCodis database. According to the GO classification, it contained significant genes that were classified as protein binding (GO:0005515) and DNA binding (GO:0003677). The analysis data is shown in Table S4.

Cancers 2020, 12, 2731 8 of 22 Cancers 2020, 12, x FOR FREE REVIEW 9 of 23

Figure 4. Cont. Cancers 2020, 12, 2731 9 of 22 Cancers 2020, 12, x FOR FREE REVIEW 10 of 23

FigureFigure 4. Expression 4. Expression levels levels of of 18 1 target8 target genes genes (that (that predictedpredicted 5 5-year-year survival) survival) by by miRmiR-30c-30c regulationregulation in PDACin PDAC clinical clinical specimens specimens by TCGA by TCGA analyses. analyses Expression. Expression levels levels of 18 target target genes genes of ofmiRmiR-30c-30c (Figure(Figure 3) were3) evaluated were evaluated using using TCGA TCGA database database analyses. analyses. AllAll genes were were found found to tobe beupregulated upregulated in PDAC in PDAC tissuestissues (n = (n39) = 39) compared compared to to normal normal tissuestissues ( n == 39).39).

Furthermore,Furthermore, multivariate multivariate analysis analysis identiﬁed identified 10 genes 10 genes (YWHAZ (YWHAZ, F3,, TMOD3F3, TMOD3, NFE2L3, NFE2L3, ENDOD1, , ITGA3ENDOD1, RRAS,, ITGA3PRSS23, RRAS, TOP2A, PRSS23, and, LRRFIP1TOP2A, ) and as independentLRRFIP1) as independent prognostic factors prognostic for patient factors survivalfor (p < patient0.01; Figure survival5). (p For< 0.01; subsequent Figure 5). For analyses, subsequent we analys focusedes, we on focusedTOP2A on asTOP2A an important as an important oncogene basedoncogene on previous based on reports previous [30 reports]. TOP2A [30].is TOP2A an enzyme is an enzyme that can that control can control topological topological state state and and DNA DNA replication by breaking and recombination of DNA strands. It has been reported that aberrant replication by breaking and recombination of DNA strands. It has been reported that aberrant expression of TOP2A is implicated in malignant transformation of cancer cells, e.g., proliferation, expression of TOP2A is implicated in malignant transformation of cancer cells, e.g., proliferation, metastasis, and chemotherapeutic drug resistance [30]. Interestingly, a recent study showed that TOP2A interacted directly with β-catenin, activating the β-catenin pathways. These events promoted Epithelial-Mesenchymal Transition (EMT) pathways and aroused metastasis of PDAC cells [31]. Cancers 2020, 12, x FOR FREE REVIEW 11 of 23

Fmetastasisigure 5 , and chemotherapeutic drug resistance [30]. Interestingly, a recent study showed that TOP2A interacted directly with β-catenin, activating the β-catenin pathways. These events promoted Cancers 2020, 12, 2731 10 of 22 Epithelial-Mesenchymal Transition (EMT) pathways and aroused metastasis of PDAC cells [31].

HR 95%CI p-value HR 95%CI p-value YWHAZ CBFB Gene Expression Gene Expression 1.807 1.173 – 2.822 0.0070 1.531 1.005 – 2.350 0.0472 High vs Low High vs Low Tumor Stage Tumor Stage 1.451 0.750 – 3.104 0.2814 1.547 0.805 – 3.293 0.1992 3/4 vs 1/2 3/4 vs 1/2 LN Stage LN Stage 1.642 0.961 – 2.950 0.0701 1.775 1.048 – 3.166 0.0319 1 vs 0 1 vs 0 Pathological Stage Pathological Stage 1.392 0.810 – 2.150 0.1519 1.341 0.854 – 2.067 0.1978 3/4 vs 1/2 3/4 vs 1/2

1.0 1.0

HR 95%CI p-value HR 95%CI p-value F3 TMOD3 Gene Expression Gene Expression 2.034 1.325 – 3.157 0.0011 2.091 1.338 – 3.323 0.0011 High vs Low High vs Low Tumor Stage Tumor Stage 1.535 0.804 – 3.250 0.2032 1.755 0.905 – 3.760 0.0988 3/4 vs 1/2 3/4 vs 1/2 LN Stage LN Stage 1.846 1.096 – 3.276 0.0202 1.426 0.821 – 2.599 0.2134 1 vs 0 1 vs 0 Pathological Stage Pathological Stage 1.338 0.850 – 2.064 0.2031 1.528 0.967 – 2.367 0.0688 3/4 vs 1/2 3/4 vs 1/2

1.0 1.0

HR 95%CI p-value HR 95%CI p-value NFE2L3 ENDOD1 Gene Expression Gene Expression 1.822 1.185 – 2.847 0.0060 2.247 1.460 – 3.515 0.0002 High vs Low High vs Low Tumor Stage Tumor Stage 1.462 0.768 – 3.095 0.2607 1.614 0.845 – 3.419 0.1538 3/4 vs 1/2 3/4 vs 1/2 LN Stage LN Stage 1.734 1.031 – 3.071 0.0372 2.055 1.216 – 3.656 0.0063 1 vs 0 1 vs 0 Pathological Stage Pathological Stage 1.252 0.792 – 1.936 0.3298 1.364 0.869 – 2.099 0.1727 3/4 vs 1/2 3/4 vs 1/2

1.0 1.0

HR 95%CI p-value HR 95%CI p-value ITGA3 RRAS Gene Expression Gene Expression 1.993 1.295 – 3.110 0.0016 1.838 1.203 – 2.842 0.0047 High vs Low High vs Low Tumor Stage Tumor Stage 1.554 0.817 – 3.281 0.1876 1.549 0.814 – 3.272 0.1916 3/4 vs 1/2 3/4 vs 1/2 LN Stage LN Stage 1.945 1.159 – 3.436 0.0108 1.883 1.120 – 3.332 0.0158 1 vs 0 1 vs 0 Pathological Stage Pathological Stage 1.200 0.761 – 1.856 0.4244 1.234 0.780 – 1.910 0.3611 3/4 vs 1/2 3/4 vs 1/2

1.0 1.0

HR 95%CI p-value HR 95%CI p-value PRSS23 TOP2A Gene Expression Gene Expression 1.803 1.178 – 2.778 0.0065 1.892 1.237 – 2.935 0.0031 High vs Low High vs Low Tumor Stage Tumor Stage 1.490 0.766 – 3.198 0.2513 1.439 0.752 – 3.055 0.2855 3/4 vs 1/2 3/4 vs 1/2 LN Stage LN Stage 1.805 1.060 – 3.239 0.0288 1.912 1.133 – 3.397 0.0142 1 vs 0 1 vs 0 Pathological Stage Pathological Stage 0.917 0.917 – 2.238 0.1100 1.399 0.890 – 2.155 0.1422 3/4 vs 1/2 3/4 vs 1/2

1.0 1.0 Figure 5. Cont.

Figure 5

Cancers 2020, 12, 2731 11 of 22 Cancers 2020, 12, x FOR FREE REVIEW 12 of 23

HR 95%CI p-value HR 95%CI p-value BHLHE40 CHST11 Gene Expression Gene Expression 1.574 1.030 – 2.427 0.0356 1.401 0.904 – 2.196 0.1321 High vs Low High vs Low Tumor Stage Tumor Stage 1.591 0.828 – 3.383 0.1708 1.460 0.747 – 3.142 0.2806 3/4 vs 1/2 3/4 vs 1/2 LN Stage LN Stage 1.697 0.999 – 3.037 0.0500 1.690 0.977 – 3.071 0.0609 1 vs 0 1 vs 0 Pathological Stage Pathological Stage 1.340 0.854 – 2.060 0.1973 1.326 0.845 – 2.042 0.2145 3/4 vs 1/2 3/4 vs 1/2

1.0 1.0

HR 95%CI p-value HR 95%CI p-value IL1RRAP DIEXF Gene Expression Gene Expression 1.700 1.109 – 2.637 0.0146 1.652 1.066 – 2.591 0.0242 High vs Low High vs Low Tumor Stage Tumor Stage 1.632 0.855 – 3.452 0.1436 1.332 0.680 – 2.876 0.4189 3/4 vs 1/2 3/4 vs 1/2 LN Stage LN Stage 1.698 1.006 – 3.023 0.0470 1.931 1.138 – 3.450 0.0137 1 vs 0 1 vs 0 Pathological Stage Pathological Stage 1.394 0.887 – 2.147 0.1466 1.244 0.787 – 1.929 0.3421 3/4 vs 1/2 3/4 vs 1/2

1.0 1.0

HR 95%CI p-value HR 95%CI p-value CORO1C RTP4 Gene Expression Gene Expression 1.576 1.025 – 2.452 0.0379 1.508 0.982 – 2.336 0.0601 High vs Low High vs Low Tumor Stage Tumor Stage 1.436 0.737 – 3.090 0.3006 1.662 0.868 – 3.523 0.1305 3/4 vs 1/2 3/4 vs 1/2 LN Stage LN Stage 1.775 1.048 – 3.168 0.0320 1.730 1.025 – 3.077 0.0394 1 vs 0 1 vs 0 Pathological Stage Pathological Stage 1.392 0.884 – 2.147 0.1494 1.251 0.789 – 1.945 0.3340 3/4 vs 1/2 3/4 vs 1/2

1.0 1.0

HR 95%CI p-value HR 95%CI p-value AP1S3 LREFIP1 Gene Expression Gene Expression 1.607 1.058 – 2.464 0.0257 1.805 1.207 – 2.872 0.0046 High vs Low High vs Low Tumor Stage Tumor Stage 1.542 0.805 – 3.272 0.2010 1.580 0.827 – 3.348 0.1743 3/4 vs 1/2 3/4 vs 1/2 LN Stage LN Stage 1.863 1.104 – 3.313 0.0187 1.893 1.124 – 3.357 0.0153 1 vs 0 1 vs 0 Pathological Stage Pathological Stage 1.332 0.848 – 2.050 0.2084 1.529 0.970 – 2.365 0.0669 3/4 vs 1/2 3/4 vs 1/2

1.0 1.0 Figure 5. ForestForest plot plot of of multivariate multivariate analysis analysis of 1 of8 target 18 target genes genes (that (that predicted predicted 5-year 5-year survival) survival) of miR of- miR-30c.30c. The Themultivariate multivariate analysis analysis determined determined that that the the expression expression levels levels of of 10 10 genes genes ( (YWHAZYWHAZ, , F3,, TMOD3,,NFE2L3 NFE2L3, ENDOD1, ENDOD1, ITGA3, ITGA3, RRAS, RRAS, PRSS23, PRSS23, TOP2A, TOP2A, and LRRFIP1, and LRRFIP1) were independent) were independent prognostic factorsprognostic for 5-year factors overall for 5-yea survivalr overall after survival the adjustment after the for adjustment tumor stage, for lymph tumor node stage, metastasis, lymph node and pathologicalmetastasis, and stage pathological (p < 0.01). stage (p < 0.01).

2.4. Direct Regulation of TOP2A by miR-30c-2-3p in PDAC Cells 2.4. Direct Regulation of TOP2A by miR-30c-2-3p in PDAC Cells miR-30c-2-3p TOP2A TOP2A In PDAC cells transfected with miR-30c-2-3p, both TOP2A mRNA expression and TOP2A protein expression were significantlysignificantly suppressedsuppressed (Figure(Figures6A,B). 6A,B). miR-30c-2-3p TOP2A In addition, addition, to to validate validate whether whether miR-30c-2directly-3p directly binds to binds to inTOP2A PDAC in cells, PDAC we performed cells, we dual-luciferaseperformed dual reporter-luciferase assays. reporter We designed assays. We plasmid designed vectors plasmid encoding vectors the partial encoding sequence the partial of the TOP2A miR-30c-2-3p 3sequ0-UTRence of of the 3′-.UTR One of of TOP2A them included. One of them the predictedincluded the predicted miRtarget-30c site-2-3p (“wild-type”), target site (“w andild- thetype other”), and lacked the other the target lacked site the (“deletion-type”; target site (“deletion Figure-type6C).” The; Figure luciferase 6C). The activity luciferase was significantlyactivity was miR-30c-2-3p decreasedsignificantly following decreased co-transfection following co-transfection of of miRand-30c a-2 vector-3p and carrying a vector carrying the wild-type the wild 30-UTR-type TOP2A of3′-UTR of .TOP2A In contrast,. In contrast, no decrease no decrease in luminescence in luminescence was observedwas observed following following transfection transfection of the of miR-30c-2-3p deletion-typethe deletion-type vector vector (Figure (Figure6C). These 6C). These findings findings indicate indicate that that miR-30cdirectly-2-3p directly binds to binds the 3 0to-UTR the TOP2A of3′-UTR of .TOP2A.

Figure 6

Cancers 2020, 12, 2731 12 of 22 Cancers 2020, 12, x FOR FREE REVIEW 13 of 23

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i i m m FigureFigure 6. Direct 6. Direct regulation regulation of ofTOP2A TOP2A byby miRmiR-30c-2-3p-30c-2-3p in inPDAC PDAC cells. cells. (A) Protein (A) Protein expression expression levels of levels of TOP2ATOP2Awere were significantly significantly reduced reduced by bymiRmiR-30c-2-3p-30c-2-3p transfectiontransfection into PANC into-1 PANC-1 and SW1990 and cells SW1990 (72 h cells (72 hafter after transfection). transfection) Images. Images of whole of whole Western Western blot gels blot are gelsshown. are GAPDH shown. was GAPDH used as wasan internal used as an internalcontrol. control. (B) mRNA (B) mRNA expression expression levels levels of TOP2A of TOP2A werewere significantly significantly reduced reduced by miR by-miR-30c-2-3p30c-2-3p transfectiontransfection into into PANC-1 PANC and-1 andSW1990 SW1990 cells cells. (* p < (C0.0001).) TargetScan (C) TargetScan database analysisdatabase showed analysis that showed one that putative binding site of miR-30c-2-3p was annotated in the 3′-UTR region of TOP2A. Dual-luciferase one putative binding site of miR-30c-2-3p was annotated in the 30-UTR region of TOP2A. Dual-luciferase reporter assays showed that luminescence activity was reduced by co-transfection with wild-type reporter assays showed that luminescence activity was reduced by co-transfection with wild-type vector (containing miR-30c-2-3p binding sites) and miR-30c-2-3p in PANC-1 cells. Normalized data vector (containing miR-30c-2-3p binding sites) and miR-30c-2-3p in PANC-1 cells. Normalized data were were calculated as the ratios of Renilla/firefly luciferase activity. calculated as the ratios of Renilla/firefly luciferase activity (* p < 0.0001). 2.5. Incorporation of miR-30c-5p and miR-30c-2-3p into the RNA-Induced Silencing Complex (RISC) in 2.5. Incorporation of miR-30c-5p and miR-30c-2-3p into the RNA-Induced Silencing Complex (RISC) in PDACPDAC Cells Cells Ago2 is an essential component of the RISC, which binds to miRNAs. Whether the transfected Ago2 is an essential component of the RISC, which binds to miRNAs. Whether the transfected miRNAs were incorporated into RISC in PDAC cells was analyzed by immunoprecipitation using miRNAsan Ago were2 antibody. incorporated In miR-30c into-5p RISCtransfected in PDAC cells (PANC cells was-1 and analyzed SW1990), by it immunoprecipitationwas confirmed that a using an Ago2large antibody.amount of miR In miR-30c-5p-30c-5p was incorporatedtransfected into cells RISC (PANC-1 (Figure andS2). Similarly, SW1990), it itwas was confirmed confirmed that that a largemiR amount-30c-2-3p of transfectedmiR-30c-5p intowas PDAC incorporated cells was incorporated into RISC (Figure into RISC S2). (Figure Similarly, S2). From it was these confirmed facts, that miR-30c-2-3pit was showntransfected that the transfected into PDAC miRNAs cells was (miR incorporated-30c-5p and miR into-30c RISC-2-3p) were (Figure indeed S2). functioning From these facts, it wasin shownthe PDAC that cells. the transfected miRNAs (miR-30c-5p and miR-30c-2-3p) were indeed functioning in the PDAC cells. 2.6. Effects of TOP2A Knockdown on Cell Proliferation, Migration, and Invasion in PDAC Cells 2.6. Effects of TOP2A Knockdown on Cell Proliferation, Migration, and Invasion in PDAC Cells To assess the oncogenic functions of TOP2A in PDAC cells, we conducted knockdown assays with small interfering RNAs (siRNAs). The mRNA and protein expressions were effectively suppressed by siTOP2A-1 and siTOP2A-2 transfection into PANC-1 and SW1990 cells (Figure7A). Cancers 2020, 12, x FOR FREE REVIEW 14 of 23

To assess the oncogenic functions of TOP2A in PDAC cells, we conducted knockdown assays with small interfering RNAs (siRNAs). The mRNA and protein expressions were effectively suppressed by siTOP2A-1 and siTOP2A-2 transfection into PANC-1 and SW1990 cells (Figures 7A). Additional functional assays were performed with these siRNAs, and the results showed statistically significant suppression of cell proliferation by siTOP2A transfection in both cell lines (Figure 7B). Moreover, cell migration and invasion activities were significantly downregulated by siTOP2A transfection in PDAC cells (Figures 7C,D). We also investigated if the cisplatin sensitivity of pancreatic cancer cells could be increased by TOP2A knockdown. Co-treatment experiments showed an increased sensitivity to cisplatin in Cancerssi2020TOP2A, 12,- 2731treated cells (Figure 7E). Cisplatin sensitivity significantly increased from 5.259 μM (half13 of 22 maximal inhibitory concentration; IC50) to 3.22 μM (IC50).

FigureFigure 7. Eff 7.ects Effects of TOP2A of TOP2Aknockdown knockdown in in PDAC PDAC cells. ( (AA) )Validation Validation of ofTOP2ATOP2A knockdownknockdown efficiency efficiency in siRNA-transfectedin siRNA-transfected PDAC PDAC cells. cells. The The mRNA mRNA expressionexpression levels levels of of TOP2ATOP2A werewere significantly significantly reduced reduced by miR-30c-2-3pby miR-30c-2transfection-3p transfection into into PANC-1 PANC-1 and and SW1990 SW1990 cells. The The protein protein expression expression levels levels of TOP2A of TOP2A werewere significantly significantly reduced reduced by by transfection transfection of of twotwo siRNAssiRNAs (si (siTOP2ATOP2A-1-1 and and siTOP2A siTOP2A-2) into-2) intoPANC PANC-1-1 and SW1990and SW1990 cells cells (measured (measured 72 72 h afterh after transfection). transfection). Images Images of of whole whole Western Western blot blot gels gelsare shown. are shown. GAPDHGAPDH was was used used as an as internalan internal control. control. ( B(B)) Cell Cell proliferationproliferation was was measured measured by bythe theXTT XTT assay. assay. Data Data werewere collected collected 72 h 72 after h after siRNA siRNA transfection transfection (* (*p p< < 0.0001).0.0001). (C (C) )Cell Cell migration migration was was measured measured using using a a membrane culture system. Data were collected 48 h after seeding the cells into chambers (* p < 0.0001). (D) Cell invasion was determined 48 h after seeding miRNA-transfected cells into chambers using Matrigel invasion assays (* p < 0.0001). (E) In PDAC cells, siTOP2A increased the sensitivity to the

anticancer drug cisplatin. Half maximal inhibitory concentration (IC50) values were worked out by using GraphPad Prism8 software.

Additional functional assays were performed with these siRNAs, and the results showed statistically significant suppression of cell proliferation by siTOP2A transfection in both cell lines (Figure7B). Moreover, cell migration and invasion activities were significantly downregulated by siTOP2A transfection in PDAC cells (Figure7C,D). We also investigated if the cisplatin sensitivity of pancreatic cancer cells could be increased by TOP2A knockdown. Co-treatment experiments showed an increased sensitivity to cisplatin in siTOP2A-treated cells (Figure7E). Cisplatin sensitivity significantly increased from 5.259 µM (half maximal inhibitory concentration; IC50) to 3.22 µM (IC50). Cancers 2020, 12, x FOR FREE REVIEW 15 of 23

membrane culture system. Data were collected 48 h after seeding the cells into chambers (* p < 0.0001). (D) Cell invasion was determined 48 h after seeding miRNA-transfected cells into chambers using Cancers 2020Matrigel, 12, 2731 invasion assays (* p < 0.0001). (E) In PDAC cells, siTOP2A increased the sensitivity to the 14 of 22 anticancer drug cisplatin. Half maximal inhibitory concentration (IC50) values were worked out by using GraphPad Prism8 software. 2.7. Clinical Significance of Transcriptional Regulators of TOP2A in PDAC 2.7. Clinical Significance of Transcriptional Regulators of TOP2A in PDAC Using the GSE15471 and TCGA-Pancreatic adenocarcinoma (PAAD) datasets, we analyzed the clinical importanceUsing the GSE15471 of TOP2A and-associated TCGA-Pancreatic genes (adenocarcinomaHDAC1, HDAC2, (PAAD HMGB1,) datasets HMGB2,, we analyzed NFYA, the NFYB, NFYCclinical, and importanceSP1). These of TOP2A transcriptional-associated regulators genes (HDAC1, of TOP2A HDAC2,have HMGB1, been HMGB2, identified NFYA, in aNFYB, previous studyNFYC [30]., and SP1). These transcriptional regulators of TOP2A have been identified in a previous study [30]. In the GSE15471 dataset, the expression of the genes (except HDAC2) was significantly elevated in In the GSE15471 dataset, the expression of the genes (except HDAC2) was significantly elevated PDAC cancer tissues compared to normal tissues (p < 0.01; Figure8). Furthermore, Kaplan–Meier in PDAC cancer tissues compared to normal tissues (p < 0.01; Figure 8). Furthermore, Kaplan–Meier survivalsurvival analysis analysis of the of the eight eight genes genes revealed revealed that that HMGB2 expressionexpression and and SP1SP1 expressionexpression were were significantlysignificantly predictive predictive of theof the 5-year 5-year survival survival rate rate ofof patients with with PDAC PDAC (p (

FigureFigure 8. Expression 8. Expression levels levels and and clinical clinical significance significance of TOTOP2AP2A transcriptionaltranscriptional regulators regulators by TCGA by TCGA analyses.analyses. The The expression expression levels levels of of 8 8 genes genes ((HDAC1,HDAC1, HDAC2, HDAC2, HMGB1, HMGB1, HMGB2, HMGB2, NFYA, NFYA, NFYB, NFYB, NFYC NFYC, , and SP1) involved in TOP2A transcriptional regulation were evaluated by TCGA database analyses. All genes (except for HDAC2) were upregulated in PDAC tissues (n = 39) compared to normal tissues (n = 39). The overall survival rates were evaluated using the TCGA database. Among the 8 genes identified (HDAC1, HDAC2, HMGB1, HMGB2, NFYA, NFYB, NFYC, and SP1), high expression levels of 2 genes (HMGB2 and SP1) were found to be significantly predictive of worse prognoses in patients with PDAC (p < 0.01). Kaplan–Meier curves of the 5-year overall survival rate for each gene are presented. Cancers 2020, 12, x FOR FREE REVIEW 16 of 23

and SP1) involved in TOP2A transcriptional regulation were evaluated by TCGA database analyses. All genes (except for HDAC2) were upregulated in PDAC tissues (n = 39) compared to normal tissues (n = 39). The overall survival rates were evaluated using the TCGA database. Among the 8 genes identified (HDAC1, HDAC2, HMGB1, HMGB2, NFYA, NFYB, NFYC, and SP1), high expression levels of 2 genes (HMGB2 and SP1) were found to be significantly predictive of worse prognoses in patients

Cancerswith2020 PDAC, 12, 2731 (p < 0.01). Kaplan–Meier curves of the 5-year overall survival rate for each gene are15 of 22 presented.

2.2.8.8. Overexpression of TOP2A TOP2A,, HMGB2,HMGB2, and SP1 in PDAC Clinical Specimens The e expressionsxpressions of TOP2A, HMGB2, and SP1 protein were evaluated in PDAC clinical specimens by immunohistochemistry. The overexpressionoverexpression of the three proteins in the nuclei of cancer cells from PDAC clinical specimens was detected (Figure9 9).). TheThe overexpression overexpression of of these these proteins proteins ( (TOP2A,, HMGB2, and SP1) was not observedobserved in noncancerousnoncancerous tissues. Ki Ki-67-67 was was used as a marker for cell proliferating cells.

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TOP2A SP1 HMGB2 5 0 μ m 5 0 μ m 5 0 μ m Figure 9. TheThe o overexpressionverexpression of TOP2A, HMGB2, and and SP1 inin PDAC PDAC clinical clinical specimens specimens determined determined by immunohistochemical staining. staining. Representative Representative immunohistochemical immunohistochemical images images for for TOP2A,, HMGB2,, and SP1 inin clinical clinical samples samples are are shown. shown. (A (A) H&E) H&E stained stained sections sections of ofhuman human PDAC PDAC tissue. tissue. Areas Areas in the in boxedthe boxed region region at left at are left shown are shown magnified magnified at right. at right.(B) Ki-67 (B )was Ki-67 used was as useda cell asproliferation a cell proliferation marker. (marker.C) Immunohistochemical (C) Immunohistochemical staining staining for TOP2A for TOP2Ashowed showed patchy patchynuclear nuclear signals signals in PDAC. in PDAC. (D,E) (ImmunohistochemicalD,E) Immunohistochemical staining staining for HMGB2 for HMGB2 (D) (andD) and SP1SP1 (E) (wasE) was found found in inthe the nuclei nuclei of of cancer cancer ce cells.lls. The patient numbers are shown in Table S1.S1. 3. Discussion Over the past decade, miRNAs aberrantly expressed in cancer cells have been identified using the latest genomic technologies: microarray, PCR-based array, and RNA-sequencing. As a result, the development of cancer diagnostics and treatment strategies based on miRNA has been accelerating [12–14]. The general concept of miRNA biogenesis involves the degradation of the miRNA passenger strands derived Cancers 2020, 12, 2731 16 of 22 from the pre-miRNA-duplex [8,9]. Contrary to this theory, recent studies have shown that some miRNA passenger strands have tumor-suppressive functions, and their target genes can contribute to cancer progression, metastasis, and drug resistance in several types of cancers [18–23]. Our recent studies of PDAC cells revealed that miR-216a-3p, miR-216b-3p, miR-148a-5p, and miR-130b-5p were significantly downregulated in PDAC tissues using our RNA-sequencing based signature expression patterns [24,32,33]. Ectopic expression assays demonstrated that their expression attenuated the malignant phenotypes of PDAC cells and that the genes they regulate were aberrantly expressed in PDAC clinical specimens. Thus, they function as cancer-promoting genes, such as FOXQ1, PHLDA2, LPCAT2, AP1S3, and EPS8 [24,32,33]. These studies suggest that miRNA analyses that include passenger strands will be crucial to understand the molecular pathogenesis of PDAC. Based on our PDAC miRNA expression signature, we focused on both strands of pre-miR-30c (miR-30c-5p and miR-30c-2-3p). Our ectopic expression assays revealed that both miRNA strands attenuated cancer cell proliferation, migration, and invasion in PDAC cells. Previous studies have shown the downregulation of miR-30c-5p in several types of cancers, and the oncogenes it regulates have been implicated in various cancer pathways, such as cell proliferation, metastasis, and drug resistance [26,27]. For example, the overexpression of DLEU2 (lncRNA) functions as an adsorbed RNA that suppresses miR-30c-5p and subsequently activates the Akt signaling pathway in laryngeal squamous cell carcinomas [34]. In gastric cancer, the expression of miR-30c-5p has been shown to be significantly reduced in cancer tissues, and it also suppresses both metastasis and epithelial-to-mesenchymal transition through targeting MTA1 [35]. Some reports have suggested that miR-30c-2-3p is involved in human cancers. In the human genome, miR-30c-2 and miR-30a are located close to the chromosomal 6q13 region. In clear cell renal cell carcinoma (ccRCC), miR-30c-2-3p and miR-30a-3p are downregulated in von Hippel-Lindau (VHL)-deficient cancer tissues, and both miRNAs specifically bind to hypoxia inducible factor-2α (HIF2A) and inhibit the expression of its transcripts [36]. Moreover, the constitutive expression of HIF2A enhances tumor growth in ccRCC [36]. In breast cancer, the expression levels of miR-30c-2-3p are characterized across patients with different molecular subtypes; lower expressions of miR-30c-2-3p are detected in human epidermal growth factor receptor 2 (HER2)-positive and triple-negative groups compared to estrogen receptor (ER)-positive groups [37]. It has been found that the expression of miR-30c-2-3p negatively regulates nuclear factor kappa B signaling and cell cycle progression in breast cancer cells via targeting TNFRSF1A-associated via death domain (TRADD) and cyclin E1 (CCNE1), respectively [37]. Recent studies have shown that non-coding RNAs, LncRNA-CCAT1, and has-circ-0072995 contribute to the aggressiveness of cancer cells by acting as competing endogenous RNAs for miR-30c-2-3p in hepatocellular carcinoma and breast cancer, respectively [38]. In the present study, we first revealed that both strands of pre-miR-30c-2 (miR-30c-5p and miR-30c-2-3p) acted as tumor-suppressive miRNAs in PDAC cells. Our next goal was to search for novel cancer-promoting genes in PDAC cells controlled by these tumor-suppressive miRNAs. Our miRNA target search strategy successfully identified 18 genes whose expression was significantly predictive of 5-year survival rates of patients with PDAC. Importantly, the expression levels of 10 genes (YWHAZ, F3, TMOD3, NFE2L3, ENDOD1, ITGA3, RRAS, PRSS23, TOP2A, and LRRFIP1) were found to act as independent prognostic factors for short patient survival times. Among these genes, YWHAZ (14-3-3ζ) is a member of the 14-3-3 proteins and has multiple functions in various signal transduction pathways [39]. The overexpression of YWHAZ has been reported in a wide range of cancers, and its aberrant expression contributes to cancer progression and drug resistance [39]. In PDAC cells, tumor-associated macrophages invade cancer tissues after anticancer drug treatment, and the tumor-associated macrophage-secreted YWHAZ is shown to contribute to chemotherapy resistance [40]. Our recent studies identified the overexpression of ITGA3 in PDAC and showed that its expression enhanced cancer cell migration and invasiveness through the activation of several oncogenic pathways [41]. Notably, ITGA3 and ITGB1 expression was directly regulated by tumor-suppressive miR-124-3p in PDAC cells [41]. Further detailed analysis of the genes Cancers 2020, 12, 2731 17 of 22 regulated by miR-30c-2-3p will contribute to our understanding of the molecular networks involved in PDAC. In this study, we focused on TOP2A for further analysis in PDAC cells. The TOP2A enzyme has been implicated in multiple cancers due to its involvement in DNA replication, transcription, and chromatin remodeling [30,42,43]. Etoposide and the anthracycline chemotherapeutic drugs—doxorubicin, daunorubicin, and epirubicin—inhibit TOP2A by obstructing its ability to repair DNA strands after being cleaved [44–46]. A recent study has found that high rates of HER2 amplification are observed in PDAC patients with TOP2A amplification [47]. More recently, Enhertu (fam-trastuzumab deruxtecan-nxki) has become available for the treatment of unresectable or metastatic HER2-positive breast cancer, and this drug attacks both HER2 and topoisomerase in cancer cells [48,49]. In future studies, it will be necessary to investigate the efficacy of these anticancer drug combinations in patients with PDAC highly expressing TOP2A and/or HER2. A previous report indicates that several transcription factors closely control the expression of TOP2A [30]. We further investigated the clinical significance of TOP2A transcriptional regulators—HDAC1, HDAC2, HMGB1, HMGB2, NFYA, NFYB, NFYC, and SP1—in PDAC clinical specimens. The genes (except for HDAC2) were upregulated in PDAC tissues, and the elevated expression of two genes (HMGB2 and SP1) significantly predicted the short-term survival of the patients. High-mobility group proteins (HMGs) are the second most abundant chromatin proteins, and HMG-family proteins contribute to transcriptional fine-tuning in response to rapid environmental changes [50]. Upregulations of high mobility group B (HMGB) members are associated with malignant phenotypes (e.g., uncontrolled cell proliferation, avoidance of apoptosis, and metastasis) in several types of cancers [50]. In PDAC cells, silencing HMGB2 has shown the reduction of the hypoxia-inducible factor 1α (HIF1α) protein and inhibits the HIF1α-mediated glycolytic process [50]. Specific protein 1 (SP1) is a zinc-finger transcription factor that binds to GC-rich motifs of many promoters. Previous studies have shown that the high expression of SP1 is correlated with aggressive behavior in many types of cancers and decreased survival rate of the patients [51]. In PDAC cells, SP1 transcriptionally activates COX-2 expression, and this event promotes the angiogenesis of PDAC [51]. A recent study has shown that SP1 induces the expression of lysyl oxidase-like 2 (LOXL2) and activates the EMT process. As a result, the aberrant expression of SP1 is involved in the acquisition of the invasion and migration abilities of PDAC cells [52]. We confirmed the expression of HMGB2 and SP1 in PDAC clinical specimens by immunohistochemical staining. Our results indicated that the overexpression of several transcriptional regulators coordinately enhanced the expression of TOP2A in PDAC cells. Therefore, the overexpression of these transcription factors might contribute to the malignant transformation of PDAC and might serve as an index of drug resistance.

4. Materials and Methods

4.1. Collection of Human Clinical PDAC Specimens, Pancreatic Tissue Specimens, and PDAC Cell Lines The present study was approved by the Bioethics Committee of Kagoshima University (Kagoshima, Japan; approval no. 160038 28-65, 4 September 2016). Written prior informed consent and approval were obtained from all patients. In this study, 27 clinical samples were collected from PDAC patients who underwent resection at Kagoshima University Hospital from 1997 to 2016. Sixteen normal pancreatic tissue specimens were collected from noncancerous regions. The clinical samples were staged according to the American Joint Committee on Cancer/Union Internationale Contre le Cancer (UICC) TNM classification. The total RNA of clinical samples were extracted from frozen specimens. Immunohistochemistry about PDAC was prepared from formalin-fixed and paraffin-embedded. The clinical features of the PDAC specimens are shown in Table S1. We used two PDAC cell lines: SW1990, purchased from the American Type Culture Collection (Manassas, VA, USA), and PANC-1, purchased from RIKEN Cell Bank (Tsukuba, Ibaraki, Japan). Cancers 2020, 12, 2731 18 of 22

4.2. RNA Extraction and Quantitative Real-Time Reverse Transcription Polymerase Chain Reaction (qRT-PCR) The methods for RNA extraction from clinical specimens and cell lines and for qRT-PCR have been described previously [32,33,41]. The TaqMan probes and primers used in this study are listed in Table S5.

4.3. Transfection of miRNAs, siRNAs, and Plasmid Vectors into PDAC Cells The transfection procedures of miRNAs, siRNAs, and plasmid vectors into PDAC cells by using Opti-MEM and Lipofectamine RNAiMAX transfection regent have been described previously [32,33,41]. The reagents used in this study are listed in Table S5.

4.4. Incorporation of miRNAs (miR-30c-5p and miR-30c-2-3p) into RNA-Induced Silencing Complex (RISC) by Agonaute-2 (AGO2) Immunoprecipitation For the measurement of incorporated miRNAs into RISC in PDAC cells, we applied Ago2 immunoprecipitation by using a microRNA Isolation Kit, Human Ago2 (Wako Pure Chemical Industries, Ltd., Osaka, Japan). The number of Ago2-conjugated miRNAs were assessed by qRT-PCR assay. The experimental procedure has been described in previous studies [32,33,41].

4.5. Functional Assays in PDAC Cells (Cell Proliferation, Migration, and Invasion Assays) The procedures for the functional assays in cancer cells (proliferation, migration, and invasion) are described in our previous publications [32,33,41]. PANC-1 and SW1990 cells were transfected with 10 nM miRNA or siRNA. For cell proliferation assays, cells were transfected in 96-well plates. PANC-1 cells were plated at 4 103 cells per well, and SW1990 cells were plated at 6 103 cells per well. After 72 h, cell proliferation × × was evaluated using XTT assays. Migration assays were performed with uncoated transwell polycarbonate membrane ﬁlters, and the invasion assays were performed in modiﬁed Boyden chambers without any other proteins about the extracellular matrix. For migration and invasion assays, PANC-1 cells at 2 105 and SW1990 × cells at 3 105 were transfected in 6-well plates. After 72 h, PANC-1 and SW1990 cells were adjusted × to 2.5 105 and were added into each chamber. After 48 h, the cells of the lower surface were counted × for analysis. All experiments were performed in triplicate.

4.6. Identiﬁcation of miR-30c-5p and miR-30c-2-3p Targets in PDAC Cells We selected putative target genes having binding sites for miR-30c-5p and miR-30c-2-3p using TargetScanHuman ver.7.2 (http://www.targetscan.org/vert_72/; data was downloaded on 13 July 2018). Our microarray data (from miR-30c-5p or miR-30c-2-3p transfected cells) were deposited in the GEO repository under accession number GSE106791. To determine the genes upregulated in the PDAC clinical specimens, we obtained expression data from the Gene Expression Omnibus (GEO) database (GSE15471). The expression data of 39 pairs of specimens are stored in this dataset.

4.7. Clinical Database Analysis of miRNA Target Genes in PDAC Clinical Specimens For the analysis of gene expression between normal and cancerous tissues, we utilized the GSE15471 datasets obtained from the GEO database. In brief, GSE15471 contained mRNA array data from 36 PDAC tumors and matching normal pancreatic tissue samples, which were obtained using Aﬀymetrix U133 Plus 2.0 whole-genome chips. The expression levels were shown as signal intensity, and for each gene with multiple probes, the mean value was used. For the Kaplan–Meier survival analysis, we downloaded TCGA clinical data (TCGA, Firehose Legacy) from cBioportal (https://www.cbioportal.org). Gene expression grouping data for each gene were collected from OncoLnc (http://www.oncolnc.org). R version 4.0.2 was used for statistical analyses. Cancers 2020, 12, 2731 19 of 22

4.8. Plasmid Construction and Dual-Luciferase Reporter Assays

Plasmid vectors containing wild-type sequences of miR-30c-2-3p binding sites in the 30-UTR of TOP2A or deletion sequences of miR-30c-2-3p binding sites in the 30-UTR of TOP2A were prepared. The detailed procedures for transfection and dual-luciferase reporter assays have been described in our previous studies [32,33,41]. The reagents used in this study are listed in Table S5.

4.9. Western Blotting and Immunohistochemistry The procedures for Western blotting and immunohistochemistry have been described in our previous publications [32,33,41]. The antibodies used in the present study are listed in Table S5.

4.10. Statistical Analyses Mann-Whitney U tests were applied for comparisons between two groups. For multiple groups, one-way analysis of variance and Dunnett’s test were applied. These analyses were performed with JMP Pro 14 (SAS Institute Inc., Cary, NC, USA).

5. Conclusions We demonstrated that both strands of pre-30c (miR-30c-3p and miR-30c-2-3p) acted as tumor-suppressive miRNAs in PDAC cells. A total of 10 genes (YWHAZ, F3, TMOD3, NFE2L3, ENDOD1, ITGA3, RRAS, PRSS23, TOP2A, and LRRFIP1) were found to be regulated by these miRNAs, and high expression levels were signiﬁcantly predictive of short survival times in patients with PDAC. We further investigated the expression control of TOP2A in PDAC cells. The overexpression of several transcriptional factors and downregulation of miR-30c-2-3p contributed to the upregulation of TOP2A in PDAC cells. Our miRNA-based strategy thus provides novel insight, contributing to our overall understanding of the molecular pathogenesis of PDAC.

Supplementary Materials: The following are available online at http://www.mdpi.com/2072-6694/12/10/2731/s1, Table S1: Clinical samples’ patient characteristics, Table S2A: Putative target genes by miR-30c-5p regulation in PDAC cells, Table S2B: Putative target genes by miR- 30c-2-3p regulation in PDAC cells, Table S3: The expression levels of protein, Table S4: Gene ontology classification, Table S5: Reagents used in this study, Figure S1: Expression levels of 18 target genes using GSE28735, Figure S2: Incorporation of miR-30c-5p and miR-30c-2-3p into the RISC in PDAC cells. Author Contributions: Conceptualization, N.S.; methodology, N.S.; validation, R.O. and Y.H.; formal analysis, T.T., R.O., Y.H., and M.W.; investigation, T.T., R.O., Y.H., M.W., and S.M.; resources, S.S., T.I., H.K., and T.O.; data curation, T.T., R.O., and Y.H.; writing—original draft preparation, N.S. and R.O.; writing—review and editing, R.O., T.T., Y.H., and S.M.; visualization, T.T., R.O., and N.S.; supervision, N.S.; project administration, N.S.; funding acquisition, M.W., T.I., H.K., N.S., and T.O. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by JSPS KAKENHI; grant numbers 17H04285, 18K08626, 18K09338, 18K16322, 19K09077. Conflicts of Interest: The authors declare no conflict of interest.

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