Involvement of MAFB and MAFF in Retinoid-Mediated Suppression of Hepatocellular Carcinoma Invasion

International Journal of Molecular Sciences

Article Involvement of MAFB and MAFF in Retinoid-Mediated Suppression of Hepatocellular Carcinoma Invasion

Hiroyuki Tsuchiya 1,* ID and Seiya Oura 2 1 Graduate School of Medicine, Tottori University, Tottori 680-8550, Japan 2 Graduate School of Pharmaceutical Sciences, Osaka University, Osaka 565-0871, Japan; [email protected] * Correspondence: [email protected]; Tel.: +81-859-38-6435

Received: 19 March 2018; Accepted: 10 May 2018; Published: 13 May 2018

Abstract: Retinoids exert antitumor effects through the retinoic acid receptor α (RARα). In the present study, we sought to identify the factors involved in the RARα-mediated transcriptional regulation of the tumor suppressor gene and the tissue factor pathway inhibitor 2 (TFPI2) in hepatocellular carcinoma (HCC). All-trans-retinoic acid (ATRA) was used in the in vitro experiments. Cell invasiveness was measured using trans-well invasion assay. ATRA significantly increased TFPI2 expression through RARα in a human HCC cell line known as HuH7. TFPI2 was vital in the ATRA-mediated suppression of HuH7 cell invasion. The musculo-aponeurotic fibrosarcoma oncogene homolog B (MAFB) significantly enhanced the activation of the TFPI2 promoter via RARα while MAFF inhibited it. The knockdown of RARα or MAFB counteracted the ATRA-mediated suppression of HuH7 cell invasion while the knockdown of MAFF inhibited the invasion. TFPI2 expression in HCC tissues was significantly downregulated possibly due to the decreased expression of RARβ and MAFB. Patients with HCC expressing low MAFB and high MAFF levels showed the shortest disease-free survival time. These results suggest that MAFB and MAFF play critical roles in the antitumor effects of retinoids by regulating the expression of retinoid target genes such as TFPI2 and can be promising for developing therapies to combat HCC invasion.

Keywords: retinoids; RARα; TFPI2; MAFB; MAFF; hepatocellular carcinoma; invasion

1. Introduction Preclinical studies have shown that retinoids possess anticancer effects against different cancer cell lines in vitro [1–3]. Moreover, it was also demonstrated that retinoids reduced cancer risk by 70% in animal models [4,5]. The retinoic acid receptor α (RARα) is a central mediator of pleiotropic actions of retinoids. Many other factors also take part in retinoid action by modulating the transactivating functions of RARα. For example, a nuclear receptor co-repressor and a short heterodimer partner bind to RARα and suppress its function [6,7] while SP1 and the B-cell translocation gene 1 activate RARα via direct interaction [8,9]. Since retinoids produce severe side effects including tetracarcinogenesis, mucocutaneous cytotoxicity, and hypertriglyceridemia [10], elucidating the mechanism underlying retinoid-facilitated transcriptional regulation is crucial in developing next-generation retinoid-acting drugs with an improved speciﬁcity. The tissue factor pathway inhibitor 2 (TFPI2) is a serine protease inhibitor that targets the factor VIIa–tissue factor complex as well as trypsin and plasmin [11,12]. TFPI2 indirectly inhibits the activation of the matrix metalloprotease (MMP), which needs trypsin and plasmin and suppresses cancer invasion [13–16]. This antitumor effect is supported by the fact that TFPI2 is silenced in various tumors including hepatocellular carcinoma (HCC) [15,16]. Therefore, agents with the ability to restore TFPI2 expression in tumors could be promising for developing novel antitumor drugs. Moreover,

Int. J. Mol. Sci. 2018, 19, 1450; doi:10.3390/ijms19051450 www.mdpi.com/journal/ijms Int. J.Int. Mol. J. Mol. Sci. 2018Sci. 2018, 19, 19 1450, x 2 of 162 of 16

tumors including hepatocellular carcinoma (HCC) [15,16]. Therefore, agents with the ability to clarifyingrestore the TFPI2 mechanism expression underlying in tumors TFPI2 could transcriptional be promising for regulation developing may novel be helpfulantitumor in drugs.furthering our understandingMoreover, clarifying of tumor the mechanism development underlying and progression. TFPI2 transcriptional regulation may be helpful in furtheringIn the present our understanding study, we aimed of tumor to investigatedevelopment the and effect progression. of retinoids on TFPI2 expression and its regulatoryIn the present mechanism. study, we In addition,aimed to investigate we asked the whether effect of TFPI2retinoids is on involved TFPI2 expression in retinoid-induced and its suppressionregulatory of mechanism. cancer cell invasion. In addition, Finally, we asked it was whether addressed TFPI2 whether is involved TFPI2 andin retinoid factors-induced involved in TFPI2suppression expression of affectcancer the cell prognosis invasion. Finally, of patients it was with addressed HCC. whether TFPI2 and factors involved in TFPI2 expression affect the prognosis of patients with HCC. 2. Results 2. Results 2.1. TFPI2 Is Transcriptionally Regulated by ATRA 2.1. TFPI2 is Transcriptionally Regulated by ATRA Both HuH7 and HepG2 cell lines are derived from highly differentiated human HCC and are Both HuH7 and HepG2 cell lines are derived from highly differentiated human HCC and are functionally similar in many aspects [17]. The mRNA levels of RARβ, which is a typical retinoid target functionally similar in many aspects [17]. The mRNA levels of RARβ, which is a typical retinoid target gene,gene, increased increased owing owing to ATRA to ATRA in both in both the cell the lines cell lines in a time-dependent in a time-dependent and dose-dependentand dose-dependent manner (see Figuremanner1 A,B).(see Figure However, 1A,B ATRA). However, increased ATRA TFPI2 increased mRNA TFPI2 levels mRNA only levels in HuH7 only cells in HuH7 and notcells in and HepG2 cellsnot (see in Figure HepG21 A,C).cells ( Notesee Figure that the1A,CTFPI2). Notegene that the expresses TFPI2 gene three expresses transcript three variants. transcript The variants. primers for TFPI2The were primers designed for TFPI2 to detect were designed all three to variants. detect all three variants.

FigureFigure 1. ATRA-induced 1. ATRA-induced TFPI2 TFPI2 expression expression inin HuH7HuH7 cells cells.. (A (A) )Dose Dose-dependent-dependent expression expression of TFPI2 of TFPI2 (red)(red) and RARand RARββ (blue) (blue) mRNA mRNA in HuH7 in HuH7 (left ()left and) and HepG2 HepG2 (right (right) cells) cells following following incubation incubation with with ATRA for 12ATRA h (n for= 4). 12 *hp (n< = 0.05 4). *(vs. p < 0.05 0 µ M(vs. ATRA; 0 µM ATRA; Dunnett’s Dunnett’s test), test (B,C), )(B Time,C) Time courses courses of RAR of RARββ (B )(B and) and TFPI2 (C) mRNATFPI2 (C expression) mRNA expression in HuH7 in (left) HuH7 and (left) HepG2 and HepG2 (right) (right) cells followingcells following incubation incubation with with EtOH EtOH (blue) (blue) and 2 µM ATRA (red) for the indicated periods of time (n = 4). and 2 µM ATRA (red) for the indicated periods of time (n = 4).

The RNA polymerase inhibitor actinomycin D (ActD) was added to the cells with ATRA to investigate whether ATRA increased the stability of TFPI2 mRNA. TFPI2 mRNA was more stable than Int. J. Mol. Sci. 2018, 19, x 3 of 16 Int. J. Mol. Sci. 2018, 19, 1450 3 of 16 The RNA polymerase inhibitor actinomycin D (ActD) was added to the cells with ATRA to investigate whether ATRA increased the stability of TFPI2 mRNA. TFPI2 mRNA was more stable RARthanβ mRNA RARβ inmRNA both ofin both the HCC of the cell HCC lines cell (see lines Figure (see Figure2A,B). 2 However,A,B). However, the increase the increase in TFPI2 in TFPI2 mRNA levelsmRNA due tolevels ATRA due in to HuH7 ATRA cells in HuH7 was abolishedcells was abolished by ActD by (see ActD Figure (see2 A),Figure which 2A), suggests which suggests that ATRA transcriptionallythat ATRA transcriptionally regulates TFPI2 regulates expression. TFPI2 expression.

FigureFigure 2. Transcriptional 2. Transcriptional regulation regulation of of TFPI2 TFPI2 expression expression by ATRA by ATRA in HuH7 in HuH7 cells. (A,B cells.) HuH7 (A,B ()A HuH7) and (A) andHepG2 HepG2 (B (B) )cells cells pre pre-treated-treated with with ActD ActD incubated incubated with EtOH with EtOH(blue) (blue)and 2 µM and ATRA 2 µM (red) ATRA for (red)the for the indicatedindicated times. times. Left, Left, RARβ RAR, βright,, right, TFPI2 TFPI2 (n = (4n);= (C 4);) HuH7 (C) HuH7 and HepG2 and HepG2 cells pre cells-treated pre-treated with N- with N-hydroxy-hydroxy-NN0′-phenyloctanediamide-phenyloctanediamide (SAHA (SAHA)) (blue) (blue) and and AzC AzC (red) (red) incubated incubated with with EtOH EtOH and 2 and µM 2 µM ATRA for 12 h. RARβ (Left), TFPI2 (right) (n = 4). * p < 0.05 (vs. non-treatment control), # p < 0.05 ATRA for 12 h. RARβ (Left), TFPI2 (right)(n = 4). * p < 0.05 (vs. non-treatment control), # p < 0.05 (EtOH vs. 2 µM ATRA in the presence of SAHA or AzC) (Tukey–Kramer’s test). (EtOH vs. 2 µM ATRA in the presence of SAHA or AzC) (Tukey–Kramer’s test). 5-Aza-2′-deoxycytidine (AzC) and N-hydroxy-N′-phenyloctanediamide (SAHA) are inhibitors of5-Aza-2 DNA 0-deoxycytidine methyltransferase (AzC) and histoneand N-hydroxy- deacetylase,N0 -phenyloctanediamide respectively. These reagents (SAHA) signific are inhibitorsantly of DNAupregulated methyltransferase RARβ expression and in histoneboth HuH7 deacetylase, and HepG2 respectively.cells, which was These further reagents boosted by significantly ATRA upregulated(see Figure RAR 2C).β AzCexpression instead inof bothSAHA HuH7 induced and TFPI2 HepG2 expression cells, which in HepG2, was furtherwhich suggested boosted bythat ATRA (seeepigenetic Figure2C). suppression AzC instead by DNA of SAHA methylation induced was TFPI2 released expression in the cells. in Despite HepG2, that, which ATRA suggested failed to that epigeneticinfluence suppression TFPI2 expression by DNA (see methylation Figure 2C) was. These released results in suggestthe cells. that Despite ATRA that,-induced ATRA TFPI2 failed to expression is independent of the epigenetic mechanisms. influence TFPI2 expression (see Figure2C). These results suggest that ATRA-induced TFPI2 expression is independent2.2. Through ofTFPI2, the epigeneticATRA Suppresses mechanisms. HuH7 Cell Invasion 2.2. ThroughTo investigate TFPI2, ATRA the biological Suppresses significance HuH7 Cell of Invasion ATRA-induced TFPI2 expression, TFPI2 was stably knocked down in HuH7 cells using expression vectors of short hairpin RNA (shRNA) targeting TFPI2 To investigate the biological significance of ATRA-induced TFPI2 expression, TFPI2 was stably knocked down in HuH7 cells using expression vectors of short hairpin RNA (shRNA) targeting TFPI2 (shTFPI2-1 and shTFPI2-2). We also created a control clone transfected with non-targeting shRNA (shNT). These cells were referred to as T2KD-1, T2KD-2, and NT cells, respectively. Although Int. J.Int. Mol. J. Mol. Sci. 2018Sci. 2018, 19,, 145019, x 4 of 164 of 16

(shTFPI2-1 and shTFPI2-2). We also created a control clone transfected with non-targeting shRNA ATRA-induced(shNT). These TFPI2 cells were expression referred wasto as observedT2KD-1, T2KD in T2KD-1-2, and NT and cells, T2KD-2 respectively. cells, Although it was decreased ATRA- by approximatelyinduced TFPI2 50% expression and 15%, was respectively, observed when in T2KD compared-1 and T2KD with- that2 cells, in NT it was cells decrea (seesed Figure by3 A). The expressionapproximately of the50% TFPI2 and 15%, protein respectively, in T2KD-2 when cells compared was also with decreased that in NT when cells compared (see Figure with 3A). NTThe cells andexpression it is upregulated of the TFPI2 by ATRA, protein which in T2KD was-2 observedcells was also in NT decreased cells. This when was compared completely with abolishedNT cells in T2KD-2and cellsit is upregulated (see Figure 3byB). ATRA, Treatment which with was ATRAobserved for in 48 NT h cells significantly. This was suppressed completely abolished the invasion in of T2KD-2 cells (see Figure 3B). Treatment with ATRA for 48 h significantly suppressed the invasion of NT cells in a dose-dependent manner while this suppression with respect to T2KD-1 and T2KD-2 cells NT cells in a dose-dependent manner while this suppression with respect to T2KD-1 and T2KD-2 was significantly impaired, which correlated with the knockdown efficiency (see Figure3C). Although cells was significantly impaired, which correlated with the knockdown efficiency (see Figure 3C). TFPI2Although is responsible TFPI2 is for responsible the ATRA-mediated for the ATRA inhibition-mediated ofinhibition HuH7 cellof HuH7 invasion, cell invasion, ATRA also ATRA suppressed also HepG2suppressed cell invasion HepG2 without cell invasion inducing without TFPI2 inducing (see FiguresTFPI2 (see1A Figure and S1),s 1A which and S1), suggested which suggested that ATRA employsthat ATRA several employs mechanisms several tomechanisms suppress cancerto suppress invasion cancer in invasion the context in the of context cell lines. of cell lines.

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e r 0.2 0 1 2 NT T2KD Figure 3. Abrogation of the suppressive effect of ATRA on HuH7 cell invasion by TFPI2 knockdown. Figure 3. Abrogation of the suppressive effect of ATRA on HuH7 cell invasion by TFPI2 knockdown. (A) TFPI2 mRNA expression in HuH7 cells stably transfected with shNT, shTFPI2-1, and shTFPI2-2 (A) TFPI2(NT, T2KD mRNA-1, and expression T2KD-2 incells, HuH7 respectively). cells stably The transfected cells were treated with shNT, with EtOH shTFPI2-1, (blue) andand shTFPI2-22 µM (NT,ATRA T2KD-1, (red) and for T2KD-2 12 h (n = cells, 4). * p respectively). < 0.05 (EtOH vs. The 2 cellsµM ATRA were), treated # p < 0.05 with (vs. EtOH shNT) (blue) (Tukey and–Kramer’s 2 µM ATRA (red)test for); 12(B) h TFPI2 (n = 4).expression * p < 0.05 in (EtOHNT and vs.T2KD 2 µ-M2 cells. ATRA), The cells # p < were 0.05 treated (vs. shNT) with (Tukey–Kramer’sEtOH (E) and 2 µM test); (B) TFPI2ATRA expression(A) for 48 h. inGlyceraldehyde NT and T2KD-2-3-phosphate cells. The dehydrogenase cells were treated (GAPDH with) was EtOH shown (E) as and the 2loadingµM ATRA (A) forcontrol 48 h. (C Glyceraldehyde-3-phosphate) Invasion capability of NT, T2KD dehydrogenase-1, and T2KD (GAPDH)-2 cells. The was cells shown were treated as the loadingwith 0 µM control (C) Invasion(blue), 1 µM capability (light red), of NT, 2 µM T2KD-1, (red), and and 4 T2KD-2µM (dark cells. red) of The ATRA cells for were 48 h treated (n = 6). with* p < 0.05 0 µM (EtOH (blue), vs. 1 µM (light2 red),µM ATRA 2 µM),(red), # p < 0.05 and (vs. 4 µ shNT)M (dark (Tukey red)– ofKramer’s ATRA fortest). 48 h (n = 6). * p < 0.05 (EtOH vs. 2 µM ATRA), # p < 0.05 (vs. shNT) (Tukey–Kramer’s test). We then performed the microarray analysis to assess the expression profiles of NT and T2KD-2 cells in the presence or absence of 2 µM ATRA for 12 and 36 h. In total, 2061 probes and 961 probes withWe then 1.5-fold performed or more the changes microarray in shTFPI2 analysis-2 at 12 to and assess 36 theh, respectively, expression wereproﬁles clustered of NT into and two T2KD-2 cellsgroups in the presence(Cluster A, or shNT absence > shTFPI2 of 2 µ-2M at ATRA12 h, Cluster for 12 B, and shNT 36 < h. shTFPI2 In total,-2 at 2061 12 h probes, Cluster and C, shNT 961 probes > withshTFPI2 1.5-fold-2, or 36 more h, Cluster changes D, shNT in shTFPI2-2 < shTFPI2 at-2, 12 36 and h) (see 36 h,Figure respectively, S2). This werecluster clustered analysis also into showed two groups (Clusterthat A, changes shNT > in shTFPI2-2 gene expression at 12 h, induced Cluster B, by shNT ATRA < shTFPI2-2were not markedly at 12 h, Cluster different C, shNTfor shNT > shTFPI2-2, and 36 h,s ClusterhTFPI2-2, D, which shNT

Int.TFPI2 J. Mol. may Sci. 2018 be , involved19, 1450 in the pathways related to cellular motility (hsa04151, hsa04360,5 ofand 16 hsa04510), coagulation (hsa04610), nutritional metabolism (hsa00430, hsa01230, hsa01100, hsa00010, nutritionalhsa00051, hsa01230, metabolism and (hsa00430, hsa03320), hsa01230, and xenometabolism hsa01100, hsa00010, (hsa00980, hsa00051, hsa00860, hsa01230, hsa00983, and hsa03320),hsa05034, and xenometabolismhsa05204) (see Figure (hsa00980, S2). hsa00860, hsa00983, hsa05034, and hsa05204) (see Figure S2).

2.3. M MAFBAFB and MAFF Modulate the Transactivation ActivityActivity ofof RARRARαα onon HumanHuman TFPI2TFPI2 PromoterPromoter Genome-wideGenome-wide binding analysis of musculoaponeurotic fibrosarcomaﬁbrosarcoma (MAF) F and MAFK in HepG2 cells from the ENCODE project [18] showed their binding sites in the region around the transcriptional start site of the human TFPI2 ( (seesee Figure S3A). This region was inserted upstream of the luciferase gene for reporter assays. RARα, RARα, RXRα, RXRα, MAF, MAF, MAFA, MAFB, and MAFG significantly signiﬁcantly increased the the promoter promoter activity activity while while MAFF MAFF and and MAFK MAFK showed showed no effect no effect (see Figure (see Figure4A). Only 4A). RAR Onlyα showedRARα showed enhanced enhanced transactivation transactivation activity inactivity response in response to ATRA to (see ATRA Figure (4seeA). Figure Co-transfection 4A). Co- withtransfection RXRα, MAF,with RXRα, MAFA, MAF, and MAFBMAFA, enhanced and MAFB the enhanced transactivation the transactivation activity of RAR activityα while of MAFFRARα waswhile suppressed MAFF was (seesuppressed Figure4 B).(see Only Figure MAFB 4B). Only maintained MAFB maintained the responsiveness the responsiveness of RAR α toof ATRARARα whileto ATRA the while remaining the remaining transcription transcription factors abrogated factors abrogated it (see Figure it (see4B). Figure Therefore, 4B). Therefore, we chose we to focuschose onto focus investigating on investigating the effects the effects of MAFB of MAFB and MAFFand MAFF on TFPI2on TFPI2 promoter promoter activity. activity. MAFB MAFB enhanced the transactiva transactivationtion activity activity of of RXRα RXRα onlyonly in inthe the presence presence of ATRA of ATRA while while MAFF MAFF showed showed no effect no effect (see (seeFigure Figure S4A). S4A). The effects The effects of MAFB of MAFB and MAFF and MAFF on the on RXRα/RARα the RXRα/RAR heterodimerα heterodimer were similar were similar to those to thoseon RARα on RAR(see αFigure(see FigureS4A). Co S4A).-transfecting Co-transfecting MAFB MAFBand MAFF and showed MAFF showed that the thattransac thetivation transactivation activity activityof MAFB of remained MAFB remained unaffected unaffected by MAFF by (see MAFF Figure (see S4B). Figure S4B).

Figure 4. Regulation of of human TFPI2 promoter by by RARα,RARα, MAFB, MAFB, and and MAFF MAFF.. (A,B) A A luciferase luciferase reporter vector driven by the human TFPI2TFPI2 promoterpromoter was transfectedtransfected along with pDNA expressing the indicated indicated transcription transcription factor factor genes genes with with (B ()B and) and without without (A) ( ARARα) RAR-pDNAα-pDNA into into HuH7 HuH7 cells cells(n = (4).n = Twenty 4). Twenty-four-four hours hours after transfection, after transfection, EtOH (blue) EtOH and (blue) 2 µM and ATRA 2 µM (red) ATRA were (red) added were to addedthe cells, to theand cells,further and incubated further incubatedfor 24 h, which for 24 was h, which followed was by followed dual luciferase by dual assay. luciferase * p < assay.0.05 (EtOH * p < vs. 0.05 2 (EtOHµM ATRA vs. 2), µ#M p ATRA),< 0.05 (vs.# p empty)< 0.05 (vs. (Tukey empty)–Kramer’s (Tukey–Kramer’s test), (C) Luciferase test), (C) Luciferasereporter vectors reporter driven vectors by drivenwild-type by wild-type(WT) and (WT)mutant and half mutant-site (mutR4) half-site (mutR4)TFPI2 promoters TFPI2 promoters were transfected were transfected with empty with empty(blue) (blue)and RARα and RAR-expressingα-expressing (red) (red)pDNAs pDNAs into intoHuH7 HuH7 cells cells (n (=n 4).= 4).Twenty Twenty-four-four hours hours after after transfection, transfection, EtOH and 2 µµMM ATRA werewere addedadded toto thethe cellscells andand furtherfurther incubatedincubated for 24 h, whichwhich waswas followed by the dual luciferase assay.assay. (D) Reporter vectors driven byby WT or mutant putative MAF bindingbinding site (mutM1) TFPI2 promoters were transfected with pDNAs expressing RARRARαα (blue), RARRARαα and MAFB (red), oror RARRARαα and MAFF (yellow)(yellow) intointo HuH7HuH7 cellscells ((nn == 4).

Int. J. Mol. Sci. 2018, 19, 1450 6 of 16 Int. J. Mol. Sci. 2018, 19, x 6 of 16

In general, RARRARαα binds to a tandemtandem repeatrepeat ofof thethe consensusconsensus sequencesequence 550′-RGKTCA-3-RGKTCA-30′, which is termed the half-sitehalf-site [19]. However, the repeat sequence was not found in the promoter sequence of human TFPI2.TFPI2. Instead Instead,, four half half-sites-sites were present (see(see Figure S3A). In addition, two MAF-bindingMAF-binding sites have been predicted by the ORCA toolkit [20].]. Therefore, mutations were introduced into each of the four four half half-sites-sites (mutR1 (mutR1–4)–4) and and two two putative putative MAF MAF-biding-biding sites sites (mutM1 (mutM1–2)–2) (see (seeFigure Figure S3A). S3A). The Theeffects effects of RARα of RAR andα and MAFB/MAFF MAFB/MAFF on onthe theTFPI2 TFPI2 promoter promoter were were,, respectively respectively,, eliminated eliminated by by mutR4 and mutM1 even even in in the the presenc presencee of of ATRA ATRA (see (see Figure Figuress 4C,4C,D 4D, and S4C, S4C,D). and S4D These). These results results helped helped us identifyus identify the the MAF MAF recognition recognition element element (MARE) (MARE) and and retinoic retinoic acid acid response response element element (RARE) (RARE) at +6 at and +6 +66and relative+66 relative to the to the transcription transcription start start site, site, respectively respectively (see (see Figure Figure S3B). S3B). Furthermore, Furthermore, thesethese MARE and RARE were highly conserved among mammalian genomes ( (seesee Figure S3B). Binding of RARRARαα with MAFB or MAFF was not observed under our experimental experimental conditions conditions ( (seesee Figure S5 S5).). Therefore Therefore,, MAFB and MAFF might indirectly interact with RARRARαα onon thethe TFPI2TFPI2 promoter.promoter.

2.4. MAFB, MAFF, and RARRARαα RegulateRegulate TFPI2TFPI2 ExpressionExpression inin HuH7HuH7 CellsCells andand TheirTheir InvasionInvasion HuH7 cells with stably knocked down RARα RARα and MAFB (RaKD and MBKD cells, respectively) showed a decreased expression of TFPI2 while those with knocked down MAFFMAFF (MFKD) showed an increased TFPI2 expression (see(see FiguresFigures5 5AA andand S6A).S6A). Furthermore,Furthermore, HuH7HuH7 cellscells stablystably overexpressingoverexpressing MAFB (MBOE) showed a marked increase in TFPI2 expression while those overexpressing MAFF (MFOE) showed a decrease (see(see Figure S6B). ATRA-mediatedATRA-mediated suppression suppression of cell cell invasion invasion was signiﬁcantlysignificantly impaired impaired by by shRARα shRARα andand shMAFB shMAFB while while MFKD MFKD cells cells showed showed a marked a marked reduction reduction in incell cell invasion invasion irrespective irrespective of ofATRA ATRA (see (see Figure Figure 5B).5B).

Figure 5. Effect of RARα, RARα, MAFB, and MAFF on HuH7 cell invasion through TFPI2.TFPI2. ( A) TFPI2 mRNA expression in HuH7 cells stably transfected with shNT, shRARα, shRARα, shMAFB, or or shMAFF (NT, (NT, RaKD, MBKD, andand MFKDMFKD cells,cells, respectively). respectively). The The cells cells were were treated treated with with EtOH EtOH (blue) (blue) or or 2 µ 2M µM ATRA ATRA (red) (red) for 12for h 12 (n h= ( 4).n = * p4).< * 0.05 p < (EtOH0.05 (EtOH vs. 2 µvs.M ATRA),2 µM ATRA # p <), 0.05 # p (vs. < 0.05 shNT) (vs. (Tukey–Kramer’s shNT) (Tukey–Kramer’s test); (B) Invasiontest); (B) capabilityInvasion capability of HuH7 cellsof HuH7 stably cells transfected stably transfected with shNT, with shRAR shNT,α, shMAFB,shRARα, orshMAFB, shMAFF. or TheshMAFF. cells were The treatedcells were with treated 0 µM with (blue), 0 µM 1 µ (blue),M (light 1 µM red), (light 2 µM red), (red), 2 µM and (red), 4 µM and (dark 4 µM red) (dark of ATRA red) of for ATRA 48 h ( nfor= 48 8). *hp (n< = 0.05 8). * (vs. p < 00.05µM (vs. ATRA), 0 µM # ATRAp < 0.05), # (vs. p < shNT)0.05 (vs. (Tukey–Kramer’s shNT) (Tukey–Kramer’s test). test).

2.5. RAR α and MAFB Contribute to the Downregulation ofof TFPI2TFPI2 inin HCCHCC We checked whether whether the the factors factors involved involved in inTFPI2 TFPI2 transcription transcription plays plays a role a role in human in human HCC. HCC. We Weperformed performed quantitative quantitative PCR PCR with with 44 44 cDNA cDNA samples samples derived derived from from eight eight normal, normal, five five fatty, fatty, three hepatitis, five five cirrhotic, and 23 HCC liver tissues (see(see TableTable S1). S1). TheThe expression of TFPI2, RARRARβ,β, MAFB, and MAFF was significantly significantly lower in HCC than than that that in in normal normal liver liver tissue tissue ( (seesee Figure Figure 66).). MAFB expression was also downregulated in fatty and cirrhotic liver tissues. The role of epigenetic mechanisms aside, the downregula downregulationtion of TFPI2 can be attributable to the decreased expression of RARRARββ andand MAFB MAFB in in HCC. HCC. Correlation Correlation analysis analysis demonstrated demonstrated that that the the mRNA mRNA expression expression of ofTFPI2 TFPI2 in inthe the clinical clinical samples samples was was significantly significantly correlated correlated with with those those of of MAFB MAFB and and MAFF MAFF ( (seesee Figure Figure S7 S7).). Taking intointo accountaccount thethe observation thatthat MAFF did not affect MAFB-inducedMAFB-induced activation of the TFPI2 promoter (see(see Figure S4B),S4B), MAFB may play a more important role in hepatichepatic TFPI2 expression than the other transcription factors. Furthermore, MAFB and RARα expression in HCC was significantly downregulated as the TNM stage and histological grade increased while no correlation between TFPI2 and tumor grades was observed (see Table S2).

Int. J. Mol. Sci. 2018, 19, 1450 7 of 16 the other transcription factors. Furthermore, MAFB and RARα expression in HCC was signiﬁcantly downregulated as the TNM stage and histological grade increased while no correlation between TFPI2 Int.and J. tumorMol. Sci. grades2018, 19, wasx observed (see Table S2). 7 of 16

Int. J. Mol. Sci. 2018, 19, x 7 of 16

Figure 6. Gene expression in different types of liver diseases diseases.. Box and whisker plots of relative gene expression levels of TFPI2, RARα, RARβ, MAFB, and MAFF to β-actin in normal (N, n = 8; blue), fatty expressionFigure 6. levels Gene ofexpression TFPI2, RARin differentα, RAR typesβ, MAFB, of liver and diseases MAFF. Box to andβ-actin whisker in normalplots of relative (N, n = gene 8; blue), (FL, n = 5; green), hepatitis (Hs, n = 3; yellow), cirrhotic (Cir, n = 5; orange), and hepatocellular fattyexpression (FL, n = 5; levels green), of TFPI2, hepatitis RARα, (Hs, RARβ,n =3; MAFB, yellow), and cirrhoticMAFF to β (Cir,-actinn in= 5;normal orange), (N, n and = 8; hepatocellularblue), fatty carcinoma(FL, n (Tu,(Tu,= 5; n green),n= = 23;23; red) hepatitisred) liver liver (Hs, tissues. tissues. n = Boxes 3; Boxes yellow), indicate indicate cirrhotic ﬁrst first and (Cir, and thirdn third= 5; quartiles orange), quartiles and and and median hepatocellular median values values and andwhiskers whiskerscarcinoma represent represent(Tu, n 5 = and 23; 5 red) 95and percentiles. liver95 percentiles. tissues. Open Boxes Open circulars indicate circulars first indicate and indicate third outliers. quartilesoutliers. * p < and* 0.05 p

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α β F

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Int. J. Mol. Sci. 2018, 19, x 7 of 16

Figure 6. Gene expression in different types of liver diseases. Box and whisker plots of relative gene expression levels of TFPI2, RARα, RARβ, MAFB, and MAFF to β-actin in normal (N, n = 8; blue), fatty (FL, n = 5; green), hepatitis (Hs, n = 3; yellow), cirrhotic (Cir, n = 5; orange), and hepatocellular carcinoma (Tu, n = 23; red) liver tissues. Boxes indicate first and third quartiles and median values and whiskers represent 5 and 95 percentiles. Open circulars indicate outliers. * p < 0.05 (vs. normal liver tissues) (Dunnett’s test).

2.6. Involvement of MAFB, MAFF, and TFPI2 in the Progression and Prognosis of HCC We further analyzed gene expression in patients with HCC by using the data generated by the TCGA Research [21]. HCC patients with vascular invasion showed significantly low MAFB expression while other genes remained unaffected (see Figure 7A). In addition, the expression of TFPI2 and RARβ was significantly low in patients with metastasis (see Figure 7B). This suggests that these genes may impact the prognosis of HCC patients.

A p = 0.433 p = 0.112 p = 0.126 p = 0.038 p = 0.674 11 13 10 13 13 12 9 12 8 11 11

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l l l l 3 9 8 7 2 1 8 7 -1 7 0 6 5 Int. J. Mol. Sci. 2018, 19, 1450- + - + - + - + - + 8 of 16 Invasion Invasion Invasion Invasion Invasion

B p = 0.000 p = 0.790 p = 0.000 p = 0.404 p = 0.166 11 13 10 14 12

9 12 8 12

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FigureInt. J. Mol. 7. CorrelationSci. 2018, 19, x of gene expression in the livers of patients with HCC with vascular invasion8 of and 16 metastasis from the TCGA cohort. (A) Box and whisker plots of log 2 gene expression levels in HCC liversFigure with (red) 7. Correlation or without of gene (blue) expression vascular in invasion the livers (TFPI2,of patientsn = with 108 HCC vs. 204,with RARvascularα, RAR invasionβ, MAFB, MAFF,andn = metastasis 109 vs. 207). from (theB) BoxTCGA and cohort whisker. (A) Box plots and of whisker log 2 gene plots expression of log 2 gene levels expression in HCC levels livers in with (red) orHCC without livers (blue) with (red) metastasis or without (n = (blue) 4 vs. vascular 267). Boxes invasion indicate (TFPI2, first n = and 108 third vs. 204 quartiles, RARα, and RARβ, median MAFB, MAFF, n = 109 vs. 207). (B) Box and whisker plots of log 2 gene expression levels in HCC livers values and whiskers represent 5 and 95 percentiles. Open circulars indicate outliers. p values shown with (red) or without (blue) metastasis (n = 4 vs. 267). Boxes indicate first and third quartiles and were calculated by the Welch’s t-test. median values and whiskers represent 5 and 95 percentiles. Open circulars indicate outliers. p values shown were calculated by the Welch’s t-test. Kaplan–Meier analysis revealed that the expression of TFPI2, RARα, RARβ, MAFB, and MAFF does not influenceKaplan–Meier the disease-free analysis revealed survival that the (DFS) expression period of (see TFPI2, Figure RARα, S8 [RARβ,22]). However, MAFB, and patients MAFF with does not influence the disease-free survival (DFS) period (see Figure S8, [22]). However, patients with high MAFB expression in TFPI2 high or MAFF high groups showed longer DFS period than those with high MAFB expression in TFPI2 high or MAFF high groups showed longer DFS period than those low MAFBwith l expressionow MAFB expression (see Figures (see8 A,BFigure ands 8A S8B).,B and In contrast,S8B). In contrast, patients patients with high with MAFF high MAFFexpression in TFPI2expression low or in MAFB TFPI2 low or groups MAFB showed low groups poorer showed DFS poorer than DFS those than with those low with MAFF low MAFF expression (see Figuresexpression8C,D (see and Figure S8B).s There8C,D and was S8 noB). significant There wasdifference no significant among difference other groupsamong other including groups RAR α and RARincludingβ (see RARα Figure and S8B RARβ [22]). (see Figure S8B, [22]).

FigureFigure 8. Kaplan–Meier 8. Kaplan–Meier analyses analyses of of disease-free disease-free survival of of HCC HCC patients patients from from the TCGA the TCGA cohort. cohort. (A,B) Disease-free(A,B) Disease- survivalfree survival curves curves of of patients patients withwith lower (blue) (blue) or or higher higher (red) (red) MAFB MAFB expression expression in in HCC withHCC higherwith higher TFPI2 TFPI2 (n = (n 68 = 68 or orn =n = 93, 93, respectively) respectively) ( (AA) )or or higher higher MAFF MAFF (n = ( n83= or 83 70, or respectively) 70, respectively) (B) groups, (C,D) Disease-free survival curves of patients with lower (blue) or higher (red) MAFF (B) groups, (C,D) Disease-free survival curves of patients with lower (blue) or higher (red) MAFF expression in HCC with lower TFPI2 (n = 94 or n = 62, respectively) (C) or lower MAFB (n = 73 or n = n n C n expression83, respectively) in HCC with (D) groups. lower P TFPI2 values ( shown= 94 were or calculated= 62, respectively) by log-rank (test.) or Median lower values MAFB of gene ( = 73 or n = 83,expression respectively) were (usedD) groups. to divideP thevalues patients shown into the were higher calculated or lower bygroups. log-rank test. Median values of gene expression were used to divide the patients into the higher or lower groups. 2.7. Biological Significance of MAFB-Regulated ATRA Target Genes The above findings in human HCC suggest anti-oncogenic properties of MAFB against MAFF. This prompted us to perform a microarray analysis by using the MAFB-knockdown and MAFF- knockdown HuH7 cells (MBKD and MFKD cells, Figure S6A). The genes showing expression that was 1.5-fold or higher due to ATRA in all cell lines were analyzed and clustered into six groups (see Figure S9). Clusters A and D contained genes whose induction ratio was increased and decreased by shMAFF, which implies that retinoid-target genes are regulated by MAFF (see Figure S9A). Clusters B and E, respectively, comprised retinoid-target genes that were positively and negatively regulated

Int. J. Mol. Sci. 2018, 19, 1450 9 of 16

2.7. Biological Significance of MAFB-Regulated ATRA Target Genes The above findings in human HCC suggest anti-oncogenic properties of MAFB against MAFF. This prompted us to perform a microarray analysis by using the MAFB-knockdown and MAFF-knockdown HuH7 cells (MBKD and MFKD cells, Figure S6A). The genes showing expression that was 1.5-fold or higher due to ATRA in all cell lines were analyzed and clustered into six groups (see Figure S9). Clusters A and D contained genes whose induction ratio was increased and decreased by shMAFF, which implies that retinoid-target genes are regulated by MAFF (see Figure S9A). Clusters B and E, respectively, comprised retinoid-target genes that were positively and negatively regulated by MAFB (see Figure S9A). The genes in clusters C and F were, respectively, thought to be positively and negatively regulated by MAFB and MAFF. There was no cluster indicating genes regulated by MAFB and MAFF in an inverse manner (see Figure S9A). The KEGG pathway analysis showed that the enriched pathways common to MAFB and MAFF were retinol metabolism (hsa0083) and the adipocytokine signaling pathway (hsa04920) (see Figure S9B). In addition, MAFB was thought to be involved in coagulation (hsa04610) and MAFF in the inflammatory response (hsa04668, hsa04064, and hsa04670) (see Figure S9B).

3. Discussion MAF transcription factor family members play a vital role in various biological processes. They are divided into two groups based on structural characteristics including large MAFs, which involve c-MAF, MAFA, and MAFB, and small MAFs, which include MAFF, MAFG, and MAFK (see review [23]). Since small MAFs lack the transactivation domain, they can positively and negatively regulate transcription depending on their dimerization partners [24]. In the liver, small MAFs generally form a heterodimer with the Cap’n’Collar proteins to regulate cytoprotective genes related to xenobiotic metabolism, the oxidative stress response, and the redox homeostasis [24]. MAFG was recently revealed as a transcriptional repressor of bile acid synthesis and metabolism [25]. Although mice that lack only one of the small MAFs are viable and show mild phenotypic changes, knockout of all three small MAFs result in embryonic lethality with severe hypoplasia in the fetal liver due to increased apoptosis of hepatocytes and erythrocytes [26]. This suggests that despite being functionally redundant, small MAFs are crucial in proper liver development. MAFB plays a role in the development of erythrocytes, pancreatic β cells, renal podocytes, and macrophages in the fetal liver [27–29]. The anti-oncogenic potential of MAFB is not entirely clear and tends to depend on the cellular context. Additionally, downregulation of MAFB expression is observed in neoplastic liver lesions induced by the activation of γ-aminobutyric acid A receptor in an N-diethylnitrosamine-induced hepatocarcinogenesis model [30]. By contrast, MAFB overexpression in hematopoietic stem/progenitor cells leads to the development of leukemia and myeloma [31]. Although MAFB transforms primary fibroblasts with an efficiency lower than that of c-MAF and MAFA [32], large MAFs do not transform chicken embryonic neuroretina cells but rather induce differentiation of crystallin-producing cells and counteract the proliferation of mutant RAS-transformed neuroretina cells [33]. In addition, MAFB induces the differentiation into macrophages of transformed hematopoietic precursor cells. c-MAF is thought to act as a tumor suppressor gene in prostate cancer [34,35]. We therefore hypothesized that MAFB confers its anti-oncogenic effects by antagonizing MAFF since MAFB-induced activation of the TFPI2 promoter remained unaffected by MAFF (see Figure S4B). Furthermore, the expression of MAFB in HCC tissues was significantly downregulated as the tumor stage increased (see Table S2). By contrast, the apparent difference in MAFB and MAFF expression was not observed in the presence or absence of vascular invasion or metastasis and there were no differences in DFS time based on individual gene expression. This might be attributable to the functional redundancy of large as well as small MAFs. However, HCC patients with lower MAFB and higher MAFF expression (median DFS time: 11.5 months) showed poorer DFS than those with Int. J. Mol. Sci. 2018, 19, 1450 10 of 16 higher expression of both MAFB and MAFF (35.8 months, p = 0.003) and those with lower expression of both MAFB and MAFF (25.3 months, p = 0.017) (see Figures8B,D and S8B). This suggests that MAFF functions as an oncogene in the absence of MAFB. Therefore, the complex interaction of MAFs must be considered when attempting to understand the physiological functions of MAFs in patients with HCC. To our knowledge, this is the first report demonstrating the regulatory function of MAFB and MAFF in HCC cell invasion. TFPI2 is well known as a tumor suppressor gene and inhibits not only the factor VIIa/tissue factor complex but also plasmin, kallikrein, and trypsin [12]. By virtue of this property, TFPI2 also inhibits the activation of MMP1 and 3 by plasmin and trypsin [16]. However, Neaud et al. reported that TFPI2 showed a pro-invasive effect on HCC cell lines, which includes HepG2 and HuH7 cells [36]. They also demonstrated that the neutralization of factor VII with its specific antibody abolished the TFPI2-induced invasion of HCC cell lines [36]. The reason for this discrepancy is not clear at present. Our pathway analysis suggested that knockdown of TFPI2 in HuH7 cells influences the coagulation pathway (see cluster D in Figure S2). In addition, retinoid-target genes regulated by MAFB were also suggested to be classified into the coagulation pathway (clusters B & E in Figure S9). The modulation of clotting factor expression by ATRA may underlie the discrepancy effects of TFPI2 on cancer cell invasion. Furthermore, the expression of TFPI2 is frequently silenced by promoter methylation in many tumor tissues including HCC [15,16,37,38]. Therefore, the restoration of TFPI2 expression suppresses the invasiveness of malignant tumors [16]. In contrast to the silencing mechanism, the transcription factors that are involved in TFPI2 transcription have not been well studied. In the present study, we identified the members belonging to the MAF transcription factor family as novel regulators of RARα transactivation activity in TFPI2 expression. We did not observe ATRA-induced TFPI2 expression in HepG2 cells (see Figure1A). This may be explained by relatively low expression of MAFB in HepG2 cells when compared with HuH7 cells (see Figure S10A). The reporter assay in HepG2 cells demonstrated that RARα as well as MAFB and MAFF did not markedly affected TFPI2 promoter activity even in the presence of ATRA (see Figure S10B). However, when co-transfected MAFB or MAFF with RARα, MAFB significantly activated the promoter while MAFF suppressed it, which was observed in HuH7 cells (see Figure S10B). Therefore, it is implied that MAFB expression in HepG2 cells may not be sufficient for RARα to induce TFPI2 expression. By dividing the HCC patients into groups with higher or lower TFPI2 expression, it was seen that in the higher TFPI2 group, those with higher MAFB expression showed better DFS than those with lower MAFB expression (29.3 months vs. 12.9 months, p = 0.040) while, in the lower TFPI2 group, those with lower MAFF showed better DFS than those with higher MAFF expression (25.3 months vs. 16.5 months, p = 0.033) (see Figure7A,C and Figure S8B). These results suggest that MAFB and MAFF determine TFPI2 expression along with the epigenetic mechanisms. The limitations of our study include the inability to ascertain the correlation between RARα expression and HCC malignancy in combination with the expression of other genes. Low body retinoid stores are frequently observed in patients with chronic liver diseases including those with HCC [39,40]. It has also been shown that retinoid supplementation significantly improves the prognosis of patients with the hepatitis C virus-related HCC [41]. Therefore, it is likely that the activation of RARα by administration of retinoids possibly provides this benefit through TFPI2. To summarize, TFPI2 is an anti-oncogene suppressing HCC invasion whose expression is regulated epigenetically and by retinoids. Moreover, MAFB and MAFF are novel regulators of RARα at least with respect to the transcription of TFPI2 (see Figure S11). This system may be implicated in the pathogenesis and progression of HCC and can be promising as a target for preventing and treating HCC in addition to predicting HCC prognosis. Int. J. Mol. Sci. 2018, 19, 1450 11 of 16

4. Materials and Methods

4.1. Materials The HuH7, HepG2, and KMST-6 cells, in addition to the plasmid DNAs (pDNAs) expressing human RXRα and MAFG, were purchased from the RIKEN BRC (Tsukuba, Japan) through the National Bio-Resource Project of the MEXT, Japan. The PDNA-expressing mouse Maf and those expressing mouse MafA or MafB were kindly provided by Hiroshi Nakajima (Graduate School of Medicine, Chiba University, Chiba, Japan) [42] and Satoru Takahashi (Faculty of Medicine, University of Tsukuba, Tsukuba, Japan) [43,44]. PDNAs expressing MAFF, MAFK, and RARα were obtained from NITE Biological Resource Center (Kisarazu, Japan). ShRNA expression vectors targeting TFPI2 (shTFPI2-1, TRCN0000072723; shTFPI2-2, TRCN0000072726), RARα (shRARα, TRCN0000020373), MAFB (shMAFB, TRCN0000017680), and MAFF (shMAFF, TRCN0000016448) along with pLKO.1-puro Non-Target shRNA (shNT) and fetal bovine serum (FBS), which were purchased from Sigma-Aldrich (St. Louis, MO, USA). Dual luciferase assay reagents and luciferase-expressing pDNAs were acquired from Promega (Madison, WI, USA). The cell invasion assay kit (medium basement membrane extract), QuikChange Lightning Site-Directed Mutagenesis Kit, and Viofectin transfection reagent were respectively purchased from Trevigen, Inc. (Gaithersburg, MD, USA), Agilent Technologies (Santa Clara, CA, USA), and Viogene (New Taipei City, Taiwan). ReverTra Ace, Thunderbird SYBR qPCR Mix, and KOD-Plus-Neo were purchased from Toyobo Co., Ltd. (Osaka, Japan). The Anti-Flag antibody and its magnetic agarose beads were purchased from MBL (Nagoya, Japan) and anti-Strep-tag II (ab76949) and anti-TFPI2 (ab186747) antibodies from Abcam (Cambridge, UK). ATRA and anti-GAPDH antibody (sc-365062) was purchased from Santa Cruz Biotechnology (Santa Cruz, CA, USA). Dulbecco’s modiﬁed Eagle’s medium (DMEM), ActD, ethanol (EtOH), puromycin, G418, and Sepasol-RNA I super G were purchased from Nacalai Tesque Inc. (Kyoto, Japan). AzC and SAHA were bought from Tokyo Chemical Industry Co., Ltd. (Tokyo, Japan).

4.2. Cell Culture and ATRA Treatments HuH7 and HepG2 cells were cultured in DMEM supplemented with 10% FBS at 37 ◦C with 5% CO2. Four milliliters of ATRA stock solution was prepared with EtOH. When treating the cells with ATRA, the same volume of EtOH was added to control cells at a concentration of <0.1%.

4.3. Treatment with ActD, AzC, and SAHA To suppress transcription, HuH7 and HepG2 cells were pre-treated with 5 µg/mL ActD for 30 min after which they were separately incubated with EtOH and 2 µM ATRA for 0 to 12 h. To check whether epigenetic mechanisms were involved, HuH7 and HepG2 cells were pre-treated with 2 µM SAHA for 36 h or with 2 µM AzC for 108 h after which the cells were separately incubated with EtOH and 2 µM ATRA for 12 h in the presence of SAHA or AzC.

4.4. Establishment of Transgenic Cell Lines HuH7 cells were transfected with pDNAs of shNT, shTFPI2, shRARα, shMAFB, and shMAFF by Viofectin, which was followed by puromycin selection. HuH7 cells transfected with empty pDNA, pDNA expressing mouse MAFB, or human MAFF were selected by G418. Gene expression in isolated clones was analyzed by using reverse-transcription quantitative PCR.

4.5. Determination of mRNA Levels The cells were lysed with sepazol and total RNA was puriﬁed according to the manufacturer’s instructions. Complementary DNA (cDNA) was synthesized with ReverTra Ace and was analyzed by quantitative PCR with Thunderbird SYBR qPCR Mix. The following PCR primers were used: β-actin, GATGCAGAAGGAGATCACTGC (sense) and TGATCCACATCTGCTGGAAG (anti-sense); TFPI2, Int. J. Mol. Sci. 2018, 19, 1450 12 of 16

GAACCTGTGATGCTTTCACC (sense) and TCCGGATTCTACTGGCAAAG (anti-sense); MAFB, TGAACTTTGCGCGTTAAGCC (sense) and TCCTTTCCTCGTTGCTCTCTTC (anti-sense); mouse MAFB, AGTCGTGCAGGTATAAACGC (sense) and GAGTTTCTCGCACTTGACCTTG (anti-sense); MAFF, ATCCCCTATCCAGCAAAGCTC (sense) and TTGAGCCGTGTCACCTCCTC (anti-sense); RARα, CATTGAGAAGGTGCGCAAAG (sense) and AGACACGTTGTTCTGAGCTG (anti-sense); RARB, GAAAAAGACGACCCAGCAAG (sense) and ATGAGAGGTGGCATTGATCC (anti-sense). Relative mRNA levels were measured using the 2−∆∆Ct method with β-actin as an internal control.

4.6. Cell Invasion Assay Cells pre-cultured in serum-free DMEM for 24 h were seeded in top chambers containing a medium amount of basement membrane extract and were incubated in serum-free DMEM supplemented with 0–4 µM of ATRA for 48 h while the bottom chambers were ﬁlled with DMEM containing 10% FBS as well as the same concentration of ATRA. After the incubation, the cells remaining in the top chambers were discarded and invasive cells were recovered using a dissociation solution provided through the cell invasion assay kit. The recovered cells were stained with calcein AM and calcein ﬂuorescence was measured at an excitation of 485 nm and an emission of 520 nm.

4.7. Dual Reporter Assay To construct a human TFPI2 promoter reporter vector, PCR cloning was performed with LA Taq with GC buffer I (TaKaRa Bio, Otsu, Japan). In the reaction, genomic DNA isolated from a human immortalized the ﬁbroblast cell line, KMST-6, was used as a template and the following oligoDNAs were used as primers: hTFPI2pro-For, CGTCCTCGAGGTCCACACAAAGCAGCTT; hTFPI2pro-Rev, GTCGAGATCTGGGCAAGGCGTCCGAGAAA. The PCR products were digested with XhoI and BglII, which was followed by ligation into the same restriction sites of pGL4.10 [luc2]. The promoter sequence was conﬁrmed by DNA sequencing. Site-directed mutagenesis was performed according to the manufacturer’s instructions by using the following mutagenic primers: mutR1-For, GTGCG GAGTTCTTGGAAAAGAGCGGAGCGGGATTCG; mutR1-Rev, CGAATCCCGCTCCGCTCTTTTCCA AGAACTCCGCAC; mutR2-For, CCACCTCTTGAAGGCATGAAGAAAAGGTATTTGAAAGGCT GGTGG; mutR2-Rev, CCACCAGCCTTTCAAATACCTTTTCTTCATGCCTTCAAGAGGTGG; mutR3-For, TGGGAAATCTGCAAGCTAGACGGAAAAAGAATGCTAGTGATTGCGCTGTAAAG AAGC; mutR3-Rev, GCTTCTTTACAGCGCAATCACTAGCATTCTTTTTCCGTCTAGCTTGCAGATTT CCCA; mutR4-For, CCCCGCCAAGTTGAAAAGTTTTTCCTGCCTCCCAAACTTTCTC; mutR4-Rev, GAGAAAGTTTGGGAGGCAGGAAAAACTTTTCAACTTGGCGGGG; mutM1-For, CTAGCTTGCAG ATTTCCCATTACTTTCCAAAACGCTCCCTCAGGGCG; mutM1-Rev, CGCCCTGAGGGAGCGTTTT GGAAAGTAATGGGAAATCTGCAAGCTAG; mutM2-For, GCGGGGTGACAGTCCCCGTGCATTTA ATAGCCACCCCTCA; mutM2-Rev, TGAGGGGTGGCTATTAAATGCACGGGGACTGTCACCCCGC. These reporter vectors and pDNAs expressing transcription factors were transfected into HuH7 cells using Viofectin. The dual luciferase assay was performed 48 h after transfection using pGL4.74[hRluc/TK] expressing renilla luciferase with the herpes simplex virus thymidine kinase promoter (Promega) acting as a transfection control.

4.8. Gene Expression Data in Clinical Samples CDNAs derived from various liver tissues (TissueScan Liver Cancer Tissue qPCR Panel I) were purchased from Origene Technologies (Rockville, MD, USA). RNA-seq data of HCC tissues were obtained from the TCGA Research Network [21], which also provides DFS times, and the presence of vascular invasion or metastasis.

4.9. Transcription Profiling MRNAs were recovered from cells treated with EtOH or 2 µM ATRA for 12 h by using sepazol and were purified with the RNeasy Plus Mini Kit (QIAGEN, Redwood City, CA, USA). The expression Int. J. Mol. Sci. 2018, 19, 1450 13 of 16 profile was analyzed by the Human HT-12 v4 Expression BeadChip (Illumina, San Diego, CA, USA) at Macrogen Japan (Kyoto, Japan). The microarray data were deposited in the ArrayExpress database (Accession No. E-MTAB-6447). Cluster analysis was performed using Cluster 3.0 and the results were visualized using Java Tree View. The Database for Annotation, Visualization, and Integrated Discovery online tool was used to enrich the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway.

4.10. Immunoprecipitation-Western Blotting PDNA expressing Strep-tag-fused RARα was constructed as follows. Internal ribosome entry site of pIRES2 DsRed-Express2 (Clontech, Foster City, CA, USA) was amplified by KOD-Plus-Neo with the forward primer, GCGGGTCGACGCCCCTCTCCCTCCCC, and the reverse primer, GCGGGG ATCCTGTGGCCATATTATCATCGT. The PCR product was digested with SalI and BamHI and was then ligated into the same restriction sites of pAcGFP-N1 (Clontech), which produced pIRES2-AcGFP. RARα cDNA was amplified by using pDNA expressing human RARα as a template with the forward primer, GGCGCTCGAGCACTGTTGGCCTACTGG, and the reverse primer, CGCCGAATTCTT ACTTTTCAAACTGCGGATGGCTCCACGGGGAGTGGGTGGCCG, which fuses a Strep tag to the C-terminal of RARα. The PCR product was digested with XhoI and EcoRI and was then ligated into the same restriction sites of pIRES2-AcGFP. This resulted in a pDNA expressing Strep-tag-fused RARα. PDNAs expressing Flag-tag-fused MafB and MAFF were constructed as follows. Mouse MafB and human MAFF cDNAs were amplified by KOD-Plus-Neo with the MafB forward primer, GGCGGCTAGCCACCATGGACTACAAGGATGACGATGACAAGATGGCCGCGGAGCTGAGC, which fuses a Flag tag to the N-terminal of MafB and the MafB reverse primer, CGCCGTCGACTC ACAGAAAGAACTCAGGAGAG, in addition to the MAFF forward primer, GGCGGCTAGCCAC CATGGACTACAAGGATGACGATGACAAGATGTCTGTGGATCCCCTATC, which fuses a Flag tag to the N-terminal of MAFF and the MAFF reverse primer, GGGGGTCGACTAGGAGCAGGAGGCCGGG. The PCR products were digested with NheI and SalI and were then ligated into the same restriction sites of pIRES2 DsRed-Express2, which result in pDNAs expressing Flag-tag-fused MAFB and MAFF. The pDNA expressing Strep-tag-fused RARα was co-transfected into HEK293 cells with either empty pDNA or pDNAs expressing Flag-tag-fused MAFB or MAFF. Forty-two hours after transfection, EtOH and 2 µM ATRA were separately added to the cell mixture. Following a six hour incubation, the cells were lysed with NP40 buffer (1% NP40, 50 mM Tris-HCl [pH 8.0] and 150 mM NaCl). The lysates were incubated overnight with anti-Flag-tag antibody-conjugated magnetic beads at 4 ◦C. The whole-cell lysates and precipitates were separated by using SDS-PAGE and immunoblotting with anti-Strep-tag and anti-Flag-tag antibodies.

4.11. Statistical Analysis Data were expressed as mean ± standard deviation. Statistical analysis was performed using SPSS (version 24, SPSS Inc., Chicago, IL, USA). Probability values less than 0.05 were considered statistically signiﬁcant.

Supplementary Materials: Supplementary materials can be found at http://www.mdpi.com/1422-0067/19/5/ 1450/s1. Author Contributions: H.T. designed and supervised experiments, analyzed and interpreted data, and wrote the manuscript. H.T. and S.O. performed the experiments. Acknowledgments: The authors express gratitude to Hiroshi Nakajima (Graduate School of Medicine, Chiba University, Japan) and Satoru Takahashi (Faculty of Medicine, University of Tsukuba, Japan) for kindly providing us mouse Maf-expressing pDNA and mouse MafA- expressing pDNAs or MafB-expressing pDNAs, respectively. This work was supported by JSPS KAKENHI Grant Number JP16K09359, the Mochida Memorial Foundation for Medical and Pharmaceutical Research, the Kowa Life Science Foundation, and the Takeda Science Foundation (H.T.). Conﬂicts of Interest: The authors have no competing ﬁnancial interest. Int. J. Mol. Sci. 2018, 19, 1450 14 of 16

Abbreviations

RARα retinoic acid receptor α TFPI2 tissue factor pathway inhibitor 2 HCC hepatocellular carcinoma ATRA all-trans-retinoic acid MAFB musculoaponeurotic ﬁbrosarcoma oncogene homolog B MAFF musculoaponeurotic ﬁbrosarcoma oncogene homolog F ActD actinomycin D AzC 5-aza-20-deoxycytidine SAHA N-hydroxy-N0-phenyloctanediamide

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