Metabolome Analyses Uncovered a Novel Inhibitory Effect of ......targeted elimination of cancer stem/progenitor cells, such as oval-like cells (7, 8). However, the detailed mechanisms

Research Article

Metabolome Analyses Uncovered a NovelInhibitory Effect of Acyclic Retinoid on AberrantLipogenesis in a Mouse Diethylnitrosamine-Induced Hepatic Tumorigenesis ModelXian-Yang Qin1, Hideki Tatsukawa2, Kiyotaka Hitomi2, Yohei Shirakami3,Naoto Ishibashi4, Masahito Shimizu3, Hisataka Moriwaki3, and Soichi Kojima1

Abstract

Acyclic retinoid (ACR) is a promising drug under clinical trialsfor preventing recurrence of hepatocellular carcinoma. The objec-tive of this study was to gain insights into molecular basis of theantitumorigenic action of ACR from ametabolic point of view. Toachieve this, comprehensive cationic and lipophilic liver meta-bolic profiling was performed in mouse diethylnitrosamine(DEN)-inducedhepatic tumorigenesismodel usingboth capillaryelectrophoresis time-of-flight mass spectrometry and liquid chro-matography time-of-flight mass spectrometry. ACR significantlycounteracted against acceleration of lipogenesis but not glucosemetabolism in DEN-treated mice liver, suggesting an importantrole of lipid metabolic reprogramming in the initiation step ofhepatic tumorigenesis. Knowledge-based pathway analysis sug-

gested that inhibition of linoleic acid metabolites such as arachi-donic acid, a proinflammatory precursor, played a crucial role inthe prevention by ACR of DEN-induced chronic inflammation–mediated tumorigenesis of the liver. As amolecularmechanismofthe ACR's effect to prevent the aberrant lipogenesis, microarrayanalysis identified that a key transcription regulator of bothembryogenesis and tumorigenesis, COUP transcription factor2, also known as NR2F2, was associated with the metabolic effectof ACR in human hepatocellular carcinoma cells. Our studyprovided potential therapeutic targets for the chemopreventionof hepatocellular carcinoma as well as new insights into themechanisms underlying prevention of hepatic tumorigenesis.Cancer Prev Res; 9(3); 205–14. �2016 AACR.

IntroductionHepatocellular carcinoma is the most common type of liver

cancer and a leading cause of cancer-related death worldwide(nearly 600,000 deaths annually; ref. 1). Hepatocellular carcino-ma is recorded with the worst prognosis, according to a popula-tion-based cancer registry data in China, in which the age-stan-dardized 5-year relative survival rates for males and females are10.2% and 10.3%, respectively (2). The high lethality of hepato-cellular carcinoma is partly due to its high recurrence rate basedonthe concept of "field cancerization" (3). Acyclic retinoid (ACR), asynthetic vitamin A–like compound, was originally developedfrom a view of nutritional supplementation to improve thevitamin A content in hepatocellular carcinoma patients (4).Clinical trials revealed that ACR could significantly inhibit the

recurrence of hepatocellular carcinoma after the removal of pri-mary tumors (4, 5). It is hypothesized that this recurrence-pre-ventive effect is associated with clonal deletion (6) throughtargeted elimination of cancer stem/progenitor cells, such asoval-like cells (7, 8). However, the detailed mechanisms under-lying the prevention of hepatic tumorigenesis by ACR still needfurther investigation.

Metabolic alterations of cancer cells such as aerobic glycolysisare essential to generate energy and nutrients required forcancer cell processes (9). It is also believed that de novo lipogenesiscontributes to the synthesis of membranes and signaling mole-cules in proliferating cancer cells (10). For example, serummetabolic profiling study demonstrated that the content of ara-chidonic acid (AA), a polyunsaturated fatty acid present in thephospholipids of cell membranes, was significantly elevated inhepatocellular carcinoma patients compared with the healthycontrols (�91.8-fold; ref. 11). In addition, metabolic reprogram-ming has been revealed to be regulated by proto-oncogenes andtumor suppressor genes, suggesting its primary function in tumor-igenesis (12–14). Although viral hepatitis is the major causate ofhepatocellular carcinoma, there is a growing recognition of theimportance of metabolic syndrome such as obesity for the devel-opment of hepatocellular carcinoma (15). Dietary or geneticobesity can induce alteration of gut microbial metabolites suchas increasing the levels of deoxycholic acid (DHA), which leads tochronic liver injury and facilitates hepatocellular carcinomadevel-opment (16). Interestingly, antibiotic treatments inhibiting DHAsynthesis can prevent obesity-induced hepatocellular carcinomadevelopment, suggesting abnormalmetabolismof cancer cells is a

1Micro-Signaling Regulation Technology Unit, RIKEN Center for LifeScience Technologies, Saitama, Japan. 2Department of Basic Medic-inal Sciences, Nagoya University Graduate School of PharmaceuticalSciences, Aichi, Japan. 3Department of Gastroenterology, Gifu Uni-versity School of Medicine, Gifu, Japan. 4Tokyo New Drug ResearchLaboratories, Pharmaceutical Division, KOWA Co. Ltd., Tokyo, Japan.

Note: Supplementary data for this article are available at Cancer PreventionResearch Online (http://cancerprevres.aacrjournals.org/).

Corresponding Author: Soichi Kojima, RIKEN Center for Life Science Technol-ogies, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan. Phone: 81-(48)-467-7938;Fax: 81-(48)-462-4675; E-mail: [email protected]

doi: 10.1158/1940-6207.CAPR-15-0326

�2016 American Association for Cancer Research.

CancerPreventionResearch

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potential therapeutic target for the systemic treatment and pre-vention of hepatocellular carcinoma (16, 17).

Our group and others have observed that ACR may suppresscell growth or inhibit hepatitis C virus replication by alteringenergy production and lipid metabolism in hepatocellular car-cinoma cell lines (18, 19). However, in vitro study in malignantcells provides limited information to understand the mecha-nism of tumorigenesis. We reported that ACR prevented diethyl-nitrosamine (DEN)-induced hepatic tumorigenesis in obese anddiabeticC57BKSL/J-þLeprdb/þLeprdbmice (db/dbmice; ref. 20).ACR treatment reduced the prevalence of DEN-initiated liverprecancerous lesions classified as foci of cellular alteration from70% to 10%. Here, we performed metabolomics approaches toexplore the molecular basis of the preventive effect of ACRon hepatic tumorigenesis from a metabolic point of view. Tothis end, comprehensive cationic and lipophilic metabolic pro-files of liver tissues obtained frommouse DEN–induced hepatictumorigenesis model were detected using capillary electropho-resis time-of-flight mass spectrometry (CE-TOFMS) and liquidchromatography time-of-flightmass spectrometry (LC-TOFMS),respectively (21). Our analyses revealed that ACR maysuppress the enhanced lipogenesis during DEN-induced hepatictumorigenesis.

Materials and MethodsChemicals

ACR(NIK-333)was suppliedbyKowaCo. Ltd. All-trans retinoicacid (atRA), DEN, and AA were purchased from Sigma-Aldrich.

Animal experimentsAll experiments were performed in accordance with protocols

approved by the Institutional Committee of Animal Experimentof Gifu University and RIKEN. Four-week-old male db/db micewere obtained from Japan SLC, Inc. and housed under constanttemperature (22�C� 1�C), with free access to food andwater, 12-hour light/dark cycles, and were fed laboratory pellets. Detailedexperimental procedurehas beendescribedpreviously in ref. (20).Briefly, mice were divided into four groups (n ¼ 6, respectively).Three groups were given tap water containing 40 ppm of DEN forthefirst twoweeks and then fedwithbasal diet alone (DENgroup)and basal diet containing 0.03% ACR (DEN-0.03ACR group) or0.06%ACR (DEN-0.06ACR group) till the end of experiment. Themethod for DEN treatment used in this study has been proved tobe sufficient to develop liver neoplasms in db/dbmice (20, 22, 23).The fourth group fed with basal diet containing 0.06%ACR alonewithoutDEN treatment (0.06ACRgroup)was used as the negativecontrol for changes during DEN-initiated liver tumorigenesis(Fig. 1A). After sacrifice byCO2 asphyxiation, liver tissues contain-ing precancerous lesion but not cancer (approximately 60 mg/mouse)were isolated and stored at�80�Cuntil furthermetabolicanalyses. For histopathologic examination, 4-mmthick sections offormalin-fixed, paraffin-embedded livers were stained routinelywith hematoxylin and eosin (H&E).

CE-TOFMS measurementFrozen liver tissues were immersed into 50% acetonitrile solu-

tion containing internal standards in crushing tubes and

Figure 1.Liver metabolic profiles in mouse DEN–induced hepatic tumorigenesis model. A, schematic overview of the experimental procedures. Mice were dividedinto four groups (n ¼ 6, respectively). Three groups were given tap water containing 40 ppm of DEN for the first two weeks and fed with basal diet alone(DEN group) and basal diet containing 0.03% ACR (DEN-0.03ACR group) or 0.06% ACR (DEN-0.06ACR group) till the end of experiment. The fourth groupfed with basal diet containing 0.06% ACR alone without DEN treatment (0.06ACR group) was used as the negative control for changes during DEN-initiatedliver tumorigenesis. B, representative H&E staining of the liver precancerous lesions (top) and hepatocellular carcinoma (HCC; bottom) observed inDEN group. Scale bar 200 mm. To obtain a global view of the metabolic basis of the preventive effect of ACR on DEN-initiated tumorigenesis, unsupervisedPCA analysis was applied on the quantification data measured by CE-TOFMS (C), LC-TOFMS (D), and the combined data (E). The score plot revealed cleardiscrimination in the metabolic profiles between DEN- and ACR-treated groups with the first component (PC1) representing 34.7%, 39.6%, and 30.1%of the total variance, respectively. FCA, foci of cellular alteration.

Qin et al.

Cancer Prev Res; 9(3) March 2016 Cancer Prevention Research206




centrifuged (2,300 � g, 4�C, 5 minutes) using a desk-modelcrusher BMS-M10N21 (BMS Co., Ltd). After that, top layer wascentrifugally filtered (9,100 g, 4�C, 120 minutes) using an Ultra-freeMC-PLHCC 5-kDa cut-off filter (Human Metabolome Tech-nologies Inc). The filtrates were dried and resuspended in 50 mL ofMilli-Qwater for CE-TOFMS analysis using an Agilent CE-TOFMSSystem (Agilent Technologies) as previously described (21, 24).

LC-TOFMS measurementFrozen liver tissues were immersed into acetonitrile solution

with 1% formic acid containing internal standards in crushingtubes and centrifuged (1,500 rpm, 4�C, 120 seconds) for threetimes using a desk-model crusher BMS-M10N21 (BMS Co., Ltd)following another centrifugation (1,500 rpm, 4�C, 120 seconds)after adding 167 mL of Milli-Q water. After that, supernatant wascollected by centrifugation (5,000 � g, 4�C, 5 minutes). Mean-while, the flow-through was mixed with 500 mL of acetonitrilesolution with 1% formic acid and 167 mL of Milli-Q water, andsupernatant was collected again by centrifugation. The super-natants were then mixed and centrifugally filtered (9,100 � g,4�C, 120 minutes) using Pall Nanosep 3K Omega filters (PallCorporation). The filtrate was dried and resuspended in 100 mL ofisopropanol/Milli-Q water solution (1:1) for LC-TOFMS analysisusing an Agilent 1200 series RRLC system SL equipped with anAgilent LC/MSD TOF system (Agilent Technologies).

Metabolites identification and quantificationRaw data obtained were analyzed with KEIO MasterHands

software version2.13 as previously described (25).Quantificationof the major metabolites was performed as described previously(18, 25).

Cell cultureHepatocellular carcinoma cell line, JHH7 cells were kindly

supplied by Dr. Matsuura (Jikei University School of Medicine,Tokyo, Japan) in June 2012 (26). The cells were maintained inDMEM (Wako Industries) containing 10% FBS (Mediatech), 100U/mL penicillin/streptomycin, and 2 mmol/L L-glutamine (Med-iatech) and grown at 37�C in a 5%CO2 humidified incubator. Noauthentication for the cells was done by the authors.

Microarray analysisTotal RNA was isolated from JHH7 cells before (0 hour) and

after treatment with 1 mmol/L atRA or 10 mmol/L ACR for 1 and 4hours using a RNeasy Kit (Qiagen). The amount and purity of theisolated RNA were evaluated using a NanoDrop Spectrophotom-eter (NanoDrop Products). Then, oligonucleotide microarrayexperiment was performed using Affymetrix HG-U133 Plus 2.0Array (Affymetrix). The arrays were scanned using a GenePix4000B Microarray Scanner (Axon Instruments). Data normaliza-tion and analysis were performed with GeneSpring GX13.0 (Agi-lent Technologies) as previously described (27). All data areMIAME compliant, and the raw data were deposited in the GeneExpression Omnibus (www.ncbi.nlm.nih.gov/geo; accession no.GSE71856).

Real-time RT-PCRJHH7 cells were treated with ethanol, 1 mmol/L atRA, or 10

mmol/L ACR for 4 hours, and then total RNA was isolated andquantified as described above. cDNA was synthesized using a

PrimeScript RT Master Mix Kit (TaKaRa Bio). Oligonucleotideprimers were designed using OligoPerfect Designer software(Invitrogen). The sequences of the primers (50 to 30) are as follows:GAPDH forward (CGACCACTTTGTCAAGCTCA) and reverse(AGGGGTCTACATGGCAACTG); CUOP transcription factor 2(COUP-TFII, also known as NR2F2) forward (TGCCTGTG-GTCTCTCTGATG) and reverse (ATATCCCGGATGAGGGTTTC).PCR reactions were performed on the Thermal Cycler Dice RealTime System (TP8000; TaKaRa Bio) with SsoAdvanced SYBRGreen Supermix (Bio-Rad Laboratories).

Cell viability assayCells were seeded in 96-well plates 24 hours before treatment

with AA in the presence and absence of 10 mmol/L ACR in DMEMcontaining 5% FBS. After 48 hours, cell viability was determinedusing the Cell Counting Kit-8 (Dojindo Molecular Technologies)in a plate reader (ARVO MX, PerkinElmer Inc).

ELISACells were seeded in 10-cm dishes and allowed to grow to

confluency. Cells were treated with 15 mmol/L ACR in FBS-freeDMEM for 24 hours. The cell lysates were isolated and thecontents of AA were measured using an ELISA kit (CEB098Ge,Cloud-Clone Corp.) according to the manufacturer's protocol.

Network generation and pathway analysisMetaboAnalyst software (http://www.metaboanalyst.ca) was

used to identify metabolites with significantly different levelsacross experimental conditions andapply the enrichment analysisof associated metabolic pathways (28). The Ingenuity PathwayAnalysis (IPA) program (Ingenuity Systems) was used toidentify networks and canonical pathways associated with differ-entially expressed genes following ACR treatment as previouslydescribed (27).

Statistical and multivariate analysisThe statistical significance of differences between values was

assessed using ANOVA with post hoc Tukey HSD test or two-tailedStudent t test. Values of P < 0.05 were considered to indicatestatistical significance. Unsupervised principal component anal-ysis (PCA) was run in SIMCA-Pþ (version 12.0, Umetrics).Heatmap visualization of the metabolic data was generated usingPeakStat version 3.18 (Human Metabolome Technologies Inc).Metabolic map was visualized in the network context usingVisualization and Analysis of Networks containing ExperimentalData (29). Hierarchical clustering analysis of the microarray datawas applied using GeneSpring GX13.0 (Agilent Technologies).

ResultsLivermetabolic profiles inDEN-induced hepatic tumorigenesismouse model

A total of 24 liver tissues (n¼ 6 per group) were obtained frommouse DEN–induced hepatic tumorigenesis model treated withor without ACR (Fig. 1A). Representative H&E staining images ofthe liver precancerous lesions and hepatocellular carcinomaobserved in DEN group were presented in Fig. 1B. Peaks of254 cationic metabolites (Supplementary Table S1) and 102lipophilic metabolites (Supplementary Table S2) were detectedusing CE-TOFMS and LC-TOFMS, respectively. Metabolomicscomparison using PCA analysis on CE-TOFMS data (Fig. 1C),

ACR Inhibits Lipogenesis to Prevent Hepatocellular Carcinoma

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Figure 2.Principal metabolic maps illustrated using Visualization and Analysis of Networks containing Experimental Data. The relative quantities of the detected metabolitesare represented as bar graphs (from left to right: DEN group, DEN-0.03ACR group, DEN-0.06 group, and 0.06ACR group). N.D., not detected.

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LC-TOFMS data (Fig. 1D), and the combined data (Fig. 1E)revealed notable variations in the abundance of hepatic metabo-lites according differential ACR/DEN treatments. Notably, LC-TOFMS metabolomics data revealed the clearest distinction,suggesting an important role of lipid metabolism in the preven-tive effect of ACR on DEN-induced hepatic tumorigenesis. Toprovide a general view of the metabolic profiles, principlemetabolic pathways of the detected metabolites were illustratedin Fig. 2 and Supplementary Fig. S1. Furthermore, a recentCE-TOFMS–based metabolomics study identified a novel bio-marker pattern of ratio creatine/betaine of DEN-initiatedhepatocellular carcinoma rat model, which could effectively pre-dict the stage of human hepatocellular carcinoma (30). The ratioof creatine/betaine was calculated using the liver metabolomicsdata of our mouse DEN–initiated hepatocellular carcinomamodel (Supplementary Fig. S2). Although no significance wasobserved, the ratio of creatine/betaine tended to increase in theDEN group.

Statistical analysis of significantly changed metabolitesHeatmap analysis of all detectedmetabolites byCE/LC-TOFMS

also revealed strong and reproducible ACR/DEN–inducedchanges of liver metabolic profiles in mouse DEN–inducedhepatic tumorigenesis model under differential experimentalconditions (Fig. 3A). ANOVA analysis with post hoc Tukey HSDtest identified a total of 61metabolites were significantly changedacross differential chemical treatmentswith the threshold P valuesless than 0.05 (Fig. 3B). The top five of the most significantly

changed metabolites were 1H-imidazole-4-propionic acid,cis-4,7,10,13,16,19-docosahexaenoic acid, arachidonic acid, phe-nylalanine, and cis-8,11,14-eicosatrienoic acid (Fig. 3C). Withmore details, 88 metabolites were significantly changed in theDEN alone–treated mice by comparing with the control micetreated with 0.06% ACR alone without DEN treatment (DEN vs.0.06ACR). Meanwhile, 68 and 79 metabolites were significantlydifferential in mice treated with DEN combined with 0.03% and0.06%ACR, respectively, by comparingwith themice treatedwithDEN alone (DEN-0.03ACR vs. DEN and DEN-0.06 ACR vs. DEN,respectively). Moreover, 50 common metabolites were sharedamong all the comparisons, indicating that ACR may specificallytarget the metabolic pathways dysregulated in DEN-inducedtumorigenesis (Fig. 3D).

Biologic process underlying preventive effect of ACR onhepatictumorigenesis

Top metabolic pathways associated with metabolites signifi-cantly changed between DEN and 0.06ACR groups (Fig. 4A),DEN-0.03ACR andDEN groups (Fig. 4B), andDEN-0.06ACR andDEN groups (Fig. 4C) were identified using functional enrich-ment analyses in MetaboAnalyst software. Of interest, the top 2metabolic pathways "Protein biosynthesis" and "Alpha linolenicacid and linoleic acid metabolism" were common in all thecomparisons. Quantification results of the metabolites signifi-cantly inhibited by ACR treatment involved in the "Proteinbiosynthesis" and "a-linolenic acid and linoleic acidmetabolism"were summarized in Fig. 5A and B, respectively. In contrast, no

Figure 3.Identification of metabolic targets involved in the antitumorigenic effect of ACR. A, heatmap visualization of ACR/DEN–induced changes based on all detectedmetabolite data by CE/LC-TOFMS. B, significantly changed metabolites across differential ACR/DEN treatment identified using ANOVA with post hocTukey HSD test. Red dot indicates significantly changed metabolites with P < 0.05. Top five metabolites were highlighted with arrows in B and rankedaccording to their �log10 of P values in C. Among the significantly changed metabolites observed in ANOVA analysis, Venn diagrams (D) show the numberof metabolites that were significantly deregulated by comparing with the indicated chemical treatments. Eighty-eight metabolites were significantlydifferentiated between DEN group and 0.06ACR group. Sixty-eight metabolites were significantly differentiated between DEN-0.03ACR group andDEN group. Seventy-nine metabolites were significantly differentiated between DEN-0.06ACR group and DEN group. Fifty common metaboliteswere shared among all the three comparisons, which might be the candidate metabolic targets of ACR to prevent DEN-induced tumorigenesis.






significant changes of metabolites involved in glucose metabo-lism such as glucose, glucose-6-phosphate, and lactic acid wereobserved (Fig. 5C). Furthermore, we investigated the effect of ACRon AA-induced cell growth of human hepatocellular carcinoma

cells JHH7. ACR inhibited the contents of AA in JHH7 cells(Supplementary Fig. S3) and significantly suppressed the cellgrowth of JHH7 induced by a low dose of AA (1 mmol/L;Supplementary Fig. S4).

Figure 4.Biologic process underlying the antitumorigenic effect of ACR. The list of significantly changed metabolites between DEN group and 0.06ACR group (A),DEN-0.03ACR and DEN group (B), and DEN-0.06ACR group and DEN group (C) were input into the MetaboAnalyst software. Top five associated metabolicpathways were presented and ranked according to their �log10 of P values. Numbers indicate the overlapping ratios of the number of enriched metabolitesand the total number of metabolites involved in the pathways. The dashed lines indicate threshold of significance (P ¼ 0.05).

Figure 5.Quantification of the significantlychanged metabolites. Relativequantitative data of enrichedmetabolites involved in the metabolicpathways "Protein synthesis" (A) and"Alpha linolenic acid and linoleic acidmetabolism" (B) identified usingMetaboAnalyst software and that ofrepresentative metabolites (glucose,glucose-6-phosphate, and lactic acid)involved in glucose metabolism (C).Datawere presented as fold change ascompared with the average of0.06ACR group. Boxplot ofquantitative data displays the fullrange of variation (from minimum tomaximum). �, P < 0.05 compared withthe DEN group identified usingANOVAwith post hoc Tukey HSD test.n.s., not significant.

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Gene expression profiles of hepatocellular carcinoma cells inresponse to ACR

Hierarchical clustering with Ward method of 44,907 genesdetected by microarray analysis demonstrated diverse expressionchanges in hepatocellular carcinoma cells treated with ACR for 4hours (Fig. 6A). A total of 973 differentially expressed genes inresponse to ACR by comparing with atRA for 4-hour treatmentswere identified with a fold change more than 2. Then, networkanalysis was performed on the altered gene expression profilesusing IPA platform. The biologic functions of the top IPA-gener-ated networks were summarized in Fig. 6B. The most highlypopulated networks were associated with the regulation of cellcycle and DNA replication, as ACR is well known to induceapoptosis and suppress cell proliferation in hepatocellular carci-noma cells (31). In addition, networks related to amino acidmetabolism, protein synthesis, and lipid metabolism were alsoobserved. For example, the biologic network entitled "LipidMetabolism, SmallMolecular Biochemistry, Vitamin andMineralMetabolism" was highlighted in Fig. 6C. This network containsgenes that play critical roles in controlling the development oftissues and organs such as the nuclear orphan receptor NR2F2.

Then, the inhibitory effect of ACR on NR2F2 expressions wasvalidated using real-time PCR (Fig. 6D).

Finally, to mine the connection between the metabolic andgenetic actions of ACRobserved in this study, aNR2F2-dependentregulatory network was generated by knowledge-based pathwayanalysis in IPA platform (Fig. 7). A potential mechanism is thatNR2F2 may bind to retinoid X receptor, which is known as amolecular target of ACR (32), and regulate lipid metabolismincluding linoleic acid metabolism through the downstream ofperoxisome proliferator-activated receptor (PPAR) signalingpathways (33).

DiscussionThere are raised efforts to target cancer metabolism as a poten-

tial anticancer strategy (17). However, these therapies have beenpartly elusive due to the poor understanding of metabolic phe-notypes in the tissue-specific tumorigenic process. One majorfinding of our study was that alterations in lipid metabolism, butnot glucose metabolism, were observed in DEN-induced hepatictumorigenesis. ACR can significantly inhibit the DEN-induced

Figure 6.Gene expression profiles of hepatocellular carcinoma cells in response to ACR. JHH7 cells were treated with 1 mmol/L atRA or 10 mmol/L ACR for 0, 1, and 4 hours.Then, total RNA were isolated and applied to microarray analysis. A, hierarchical clustering with Ward method of 44,907 measured genes revealed thatACR treatment for 4 hours had outstanding effect on gene expression profiles of JHH7 cells. The list of differentially expressed genes between ACR treatmentfor 4 hours and atRA treatment for 4 hours were input into the IPA platform. B, the biologic functions of top populated networks generated in IPA wereranked by score, which is the likelihood of a set of genes being found in the network owing to random chance, identified by a Fisher exact test. A representativenetwork related with cancer metabolism entitled "Lipid Metabolism, Small Molecular Biochemistry, Vitamin and Mineral Metabolism" is presented inC. Upregulated metabolites are indicated in red, downregulated metabolites indicated in green, and metabolites that were not annotated in this study butare part of this network are indicated in white. D, reduced levels of NR2F2 expression in JHH7 cells treated with ACR for 4 hours were verified using real-timePCR. Quantitative data were expressed as the means � SD. � , P < 0.05 compared with the ethanol (/EtOH) control identified using two-tailed Student t test.






acceleration of lipogenesis, suggesting lipogenic pathway aspotential cancer targets (Fig. 4). Cancer metabolism has beenlong equated as aerobic glycolysis (known as "Warburg effect";ref. 34), which is mainly based on the hypothesis of mitochon-drial defects in cancer cells.However, this hypothesis is challengedby recent studies that most tumor mitochondria are not defectivein their ability to carry out oxidative phosphorylation (12). Ourprevious in vitro study also raised questions regarding this issuethat no significant difference in the content of lactic acid wasobserved between hepatocellular carcinoma cells, JHH7, andnormal hepatic cells. In addition, the increased gene expressionof pyruvate dehydrogenase kinase 4, which attenuates the flux ofglycolytic carbon into mitochondrial oxidation, was found to beinvolved in the growth suppression action of ACR in JHH7 cells(18). As the JHH7 cells exhibited highly enhanced liver differen-tiation functions and stem cell–like features (35), it was possiblethat lipid metabolic reprogramming might be required in theinitiation step of hepatic tumorigenesis. Consistently, increasedbiosynthesis of macromolecules, particularly lipids, has increas-ingly been recognized as an important component of cancermetabolic reprogramming (36). Limiting fatty acid synthesis cancontrol cancer cell proliferation (10), whereas increased de novofatty acid synthesis has been shown to correlate with breast cancerprogression (37). This study further provided new evidences thatlipid metabolic reprogramming might play a critical role in thedevelopment of hepatocellular carcinoma.

In this study, linoleic acid metabolism was identified as themostly populated metabolic target of ACR (Fig. 3). Decreases inlinoleic acid metabolites such as AA have been suggested as apotential mechanisms from mammary cancer prevention (38).An important issue is the difference between DEN model andhuman hepatocellular carcinoma. DEN is the most widely usedchemical to induce hepatocellular carcinoma in mice, and DENmodel is received as one of the bestmodels to study the pathologyof hepatocellular carcinoma, as it couldmimic the inflammation–fibrosis process (39). The differences between theDENmodel andhuman hepatocellular carcinoma observed by comparing theirgene expression profiles have been reported (40). However,limited focus has been placed on their differences in metabolicprofiles. A recent CE-TOFMS–based metabolomics study sug-

gested that the metabolic profile of DEN model is effective toidentify novel biomarkers for early diagnosis of human hepato-cellular carcinoma (30). Indeed, inhibition of AA metabolicpathway has been recently reported to associate with the chemo-prevention of high fat diet–enhanced colorectal carcinogenesis(41) and the apoptosis of hepatocellular carcinoma cells (42).Furthermore, significantly elevated content of AA was alsoreported in hepatocellular carcinoma patients compared with thehealthy controls (11).

AA is known as a proinflammatory precursor playing etiologicroles in multiple cancers (43). It is possible that through inhibi-tion of AA-regulated signaling pathways, ACR might preventDEN-induced chronic liver inflammation, which finally contri-butes to hepatic tumorigenesis. This is reasonable as we previ-ously showed enhanced inflammatory response and inhibitedserum levels of TNFa and expression levels of TNFa, IL6, and IL1bmRNA in the liver of db/dbmice treated with ACR compared withthose treated with DEN alone (20). Furthermore, in a platelet-derived growth factor–overexpressed mouse model, genome-wide expression profile analysis revealed that the repressive effectof ACR on the development of hepatic fibrosis and tumors wasrelated with inflammatory signaling pathways such as "MIFsignaling" and "IL6 signaling" (44).

Further microarray analysis identified that inhibited NR2F2expression in human hepatocellular carcinoma cells was associ-ated with the metabolic effect of ACR through PPAR-dependentsignaling pathways (Figs. 5 and 6). Deletion of NR2F2 led toembryonic lethality with defects in angiogenesis and heart devel-opment, suggesting an essential role of NR2F2 in embryogenesisand organization (45). It was known that aggressive tumor cellsshared many characteristics with embryonic progenitors. Thediscovery of cancer stem cells further increased the interest in theinteractions between cancer progression and embryologic devel-opment (46). Indeed, biologic function of NR2F2 has beenproven in prostate carcinogenesis (47), suggesting NR2F2 as apotential drug target for preventing tumor progression.

In summary, to investigate the metabolic effect of ACR againstDEN-inducedhepatic tumorigenesis, comprehensive cationic andlipophilic metabolic analyses were performed using CE/LC-TOFMS. Significant preventive effect of ACR was observed onaccelerated lipogenesis elicited by DEN, but not glucose metab-olism. Pathway analysis suggested a crucial role of linoleic acidmetabolism, such as the AA metabolic pathway, in the antitu-morigenic action of ACR. Gene expression analysis identifiedNR2F2, a key transcription regulator of embryogenesis andtumorigenesis, was associated with the metabolic effect of ACRin human hepatocellular carcinoma cells. Our study providedpotential therapeutic targets for the chemoprevention of hepato-cellular carcinoma, as well as new insights into the mechanismsunderlying hepatic tumorigenesis.

Disclosure of Potential Conflicts of InterestNo potential conflicts of interest were disclosed.

Authors' ContributionsConception and design: X.-Y. Qin, S. KojimaDevelopment of methodology: X.-Y. Qin, S. KojimaAcquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): X.-Y. Qin, H. Tatsukawa, Y. Shirakami, M. Shimizu,H. MoriwakiAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): X.-Y. Qin, H. Moriwaki

Figure 7.A schematic model of NR2F2-dependent regulatory network underlying theantitumorigenic actions of ACR generated using IPA platform. PDK4,pyruvate dehydrogenase kinase 4; RXR, retinoid X receptor


Qin et al.




Writing, review, and/or revision of the manuscript: X.-Y. Qin, K. Hitomi,N. Ishibashi, H. Moriwaki, S. KojimaAdministrative, technical, or material support (i.e., reporting or organizingdata, constructing databases): N. Ishibashi, H. Moriwaki, S. KojimaStudy supervision: H. Moriwaki, S. Kojima

Grant SupportThis study was partly supported by the HMT Research Grant for Young

Leaders in Metabolomics 2012 from Human Metabolome TechnologiesInc. (to X.-Y. Qin), a Grant-in-Aid for Scientific Research on InnovativeAreas "Chemical Biology of Natural Products" from the Ministry of Edu-cation, Culture, Sports, Science and Technology of Japan (to S. Kojima),

and the Research on the Innovative Development and the Practical Appli-cation of New Drugs for Hepatitis B (H24-B Drug Discovery HepatitisGeneral 003) from the Ministry of Health, Labor and Welfare of Japan(to S. Kojima).

The costs of publication of this article were defrayed in part by thepayment of page charges. This article must therefore be hereby markedadvertisement in accordance with 18 U.S.C. Section 1734 solely to indicatethis fact.

Received August 25, 2015; revised December 15, 2015; accepted December31, 2015; published OnlineFirst January 7, 2016.

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Qin et al.




2016;9:205-214. Published OnlineFirst January 7, 2016.Cancer Prev Res Xian-Yang Qin, Hideki Tatsukawa, Kiyotaka Hitomi, et al. Diethylnitrosamine-Induced Hepatic Tumorigenesis ModelAcyclic Retinoid on Aberrant Lipogenesis in a Mouse Metabolome Analyses Uncovered a Novel Inhibitory Effect of

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