FBW7 (F-box andWDRepeat Domain-Containing7) Negatively Regulates Glucose Metabolism byTargeting the c-Myc/TXNIP (Thioredoxin-BindingProtein) Axis in Pancreatic CancerShunrong Ji1,2,3, Yi Qin1,2,3, Chen Liang1,2,3, Run Huang4, Si Shi1,2,3, Jiang Liu1,2,3,Kaizhou Jin1,2,3, Dingkong Liang1,2,3,Wenyan Xu1,2,3, Bo Zhang1,2,3, Liang Liu1,2,3,Chen Liu1,2,3, Jin Xu1,2,3, Quanxing Ni1,2,3, Paul J. Chiao5, Min Li6, and Xianjun Yu1,2,3
Abstract
Purpose: FBW7 functions as a tumor suppressor by targetingoncoproteins for destruction. We previously reported that theoncogenic mutation of KRAS inhibits the tumor suppressor FBW7via the Ras–Raf–MEK–ERK pathway, which facilitates the prolifer-ation and survival of pancreatic cancer cells. However, the under-lying mechanism by which FBW7 suppresses pancreatic cancerremains unexplored. Here, we sought to elucidate the function ofFBW7 in pancreatic cancer glucose metabolism and malignancy.
Experimental Design: Combining maximum standardizeduptake value (SUVmax), which was obtained preoperatively viaaPET/CT scan,with immunohistochemistry staining,we analyzedthe correlation between SUVmax and FBW7 expression in pancre-atic cancer tissues. The impact of FBW7 on glucose metabolismwas further validated in vitro and in vivo. Finally, gene expressionprofiling was performed to identify core signaling pathways.
Results: The expression level of FBW7 was negatively asso-ciated with SUVmax in pancreatic cancer patients. FBW7 signif-icantly suppressed glucose metabolism in pancreatic cancercells in vitro. Using a xenograft model, MicroPET/CT imagingresults indicated that FBW7 substantially decreased 18F-fluor-odeoxyglucose (18F-FDG) uptake in xenograft tumors. Geneexpression profiling data revealed that TXNIP, a negative reg-ulator of metabolic transformation, was a downstream target ofFBW7. Mechanistically, we demonstrated that TXNIP was a c-Myc target gene and that FBW7 regulated TXNIP expression in ac-Myc–dependent manner.
Conclusions: Our results thus reveal that FBW7 serves as anegative regulator of glucose metabolism through regulation ofthe c-Myc/TXNIP axis in pancreatic cancer. Clin Cancer Res; 22(15);3950–60. �2016 AACR.
IntroductionPancreatic cancer is a devastating disease and is the fourth
leading cause of cancer-related deaths in the United States (1).Pancreatic ductal adenocarcinoma (PDAC) accounts for approx-imately 95% of pancreatic cancer cases (2). Due to late diagnosis,high metastatic potential, and resistance to chemoradiotherapy,there are no effective treatments for refractory pancreatic cancer
(3–5). Hence, there is an urgent need for an increased under-standing of the biologic characteristics and molecular mechan-isms of pancreatic cancer.
F-box and WD repeat domain-containing 7 (FBW7) is thesubstrate recognition component for the Skp1-Cul1-F-box (SCF)ubiquitin ligase complex and targets many oncoproteins fordestruction. Loss of the tumor-suppressive function of FBW7 hasbeen proposed to drive the progression of multiple cancers.Deletion or mutation of FBW7 has been frequently identified inmany cancers, including gastric cancer, colon cancer, and breastcarcinoma (6). Overall, approximately 6% of human tumorsharbor FBW7 mutations. Emerging evidence has shown thatFBW7 is also regulated by multiple upstream genes, such asp53, Pin1, Hes-5, and Numb4, as well as by miRNAs (7). Wepreviously reported that fewer than 2% of pancreatic cancersamples harbored FBW7 mutations, according to sequencinganalysis (8). Furthermore, with mass spectrometry analysis, wedetected that ERK kinase phosphorylated FBW7 at the T205 site,which resulted in destabilization of FBW7 in pancreatic cancer.However, the exact role of FBW7 in pancreatic cancer progressionhas not been investigated.
Pancreatic cancer is characterized by extensive desmoplasia thatis caused by the dense stromal fibroinflammatory reaction offibroblasts, which leads to a reduced nutrient and oxygen supply,resulting in a severe hypoxic tumormicroenvironment (9, 10). Toadapt and survive in this hostile environment, cancer cells must
1Department of Pancreatic Surgery, Fudan University Shanghai Can-cer Center, Shanghai, China. 2Department of Oncology, ShanghaiMedical College, Fudan University, Shanghai, China. 3Pancreatic Can-cer Institute, Fudan University, Shanghai, China. 4Department ofBreast Surgery, Shanghai Jiao Tong University affiliated ShanghaiSixthHospital, Shanghai,China. 5DepartmentofMolecularandCellularOncology, the University of Texas M.D. Anderson Cancer Center,Houston, Texas. 6Department of Surgery, The University of OklahomaHealth Sciences Center, Oklahoma City, Oklahoma.
Note: Supplementary data for this article are available at Clinical CancerResearch Online (http://clincancerres.aacrjournals.org/).
S. Ji, Y. Qin, and C. Liang contributed equally to this article.
Corresponding Author: Xianjun Yu, Pancreatic Cancer Institute, Fudan Univer-sity, 270 Dong An Road, Shanghai 200032, China. Phone: 86-21-64175590; Fax:86-21-64031446; E-mail: yuxianjun@fudanpciorg
rely on their ability to reprogram canonicalmetabolic pathways toensure that their needs for macromolecule synthesis and essentialenergy demands are met (11, 12). Among these metabolic trans-formations, glucose metabolism is the best studied. When cancercells are exposed tohypoxia, they undergo ametabolic response inwhich glucose consumption is elevated and glycolytic pyruvate isredirected to lactate. Such a response in cancer is known as aerobicglycolysis, or the Warburg effect (13–15).
Aberrant metabolism is considered to be one of the hallmarksof cancer. The molecular mechanisms for the transformation ofmetabolism have been linked to the activation of oncogenes orthe loss-of-function of tumor suppressors, which ultimately leadto the stabilization of HIF1a or the increased expression of the c-Myc oncogene. The transcription factors HIF1a and c-Mycincreased the expression of glycolytic genes, thereby enhancingglycolysis and lactate production (16–18). HIF1a and c-Myc arewell-characterized regulators of metabolism and are reported tobe downstream substrates of FBW7 (19–21). This prompted us toinvestigate whether FBW7 is a negative regulator of cancer cellmetabolism in pancreatic cancer.
An important clinical manifestation of the Warburg effect isthe increased uptake of 2-[18F]fluoro-2-deoxy-D-glucose bycancer cells, as determined by PET scans, which is a commonpractice in cancer diagnosis (22, 23). Here, we show that FBW7expression was negatively correlated with PET/CT maximumstandardized uptake value (SUVmax) in pancreatic cancerpatients, indicating that FBW7 might be a negative regulatorof glucose metabolism. Furthermore, in vitro and in vivo experi-ments validated FBW7 as a negative regulator of glucosemetabolism. Mechanistically, thioredoxin-binding protein(TXNIP) is observed to be a FBW7 target, according to a mRNAexpression profiling screen. TXNIP is a tumor suppressor andexerts its tumor-suppressive function by negatively regulatingglucose metabolism. Furthermore, TXNIP is a direct target geneof c-Myc, which is a FBW7 substrate and is regulated by FBW7in a c-Myc–dependent manner. Our study identifies FBW7 as anegative regulator of glucose metabolism via the c-Myc/TXNIPaxis, thereby indicating that FBW7 is an important KRAS
downstream effector. FBW7 may reverse KRAS-driven metabol-ic changes in pancreatic cancer.
Materials and MethodsCells and reagents
The human pancreatic cancer cell lines with KRAS mutations,SW1990 and PANC-1, were obtained from the American TypeCulture Collection. SW1990 cells were cultured in L-15 mediumsupplemented with 10% FBS. PANC-1 cells were cultured inDMEM supplemented with 10% FBS. All of the cell culture mediacontained 100 U/mL penicillin and 100 mg/mL streptomycin.The cell lines were authenticated by DNA fingerprinting in 2015and passaged in our laboratory fewer than 6 months after theirreceipt. Hypoxia mimetic conditions were chemically generatedby treating cells with 200mmol/L cobalt chloride (CoCl2; Sigma)for the indicated times.
Tissue specimensThe clinical tissue samples used in this study were obtained
from patients diagnosed with pancreatic cancer at Fudan Univer-sity Shanghai Cancer Center from 2010 to 2011. Prior patientconsent and approval from the Institutional Research EthicsCommittee were obtained. Clinical information regarding thesamples is presented in Supplementary Table S1. The pathologicgrading was performed by two independent pathologists at ourcenter. The correlation between FBW7 and TXNIP was analyzedusing the c2 test.
Whole-body 18F-FDG PET/CTWhole-body FDG PET/CT was performed as previously
described (24). Briefly, 18F-FDG was automatically made by acyclotron (Siemens CTI RDS Eclipse ST) using an Explora FDG4module. Patients had been fasting for more than 6 hours. Scan-ning started 1 hour after intravenous injection of the tracer (7.4MBq/kg). The images were acquired on a Siemens biograph 16HRPET/CT scanner with a transaxial intrinsic spatial resolution of 4.1mm. CT scanning was first initiated from the proximal thighs tothe head, with 120 kV, 80–250mA, pitch 3.6, and rotation time of0.5 seconds. Image interpretation was carried out on a multi-modality computer platform (Syngo; Siemens). Quantification ofmetabolic activity was acquired using the SUV normalized tobody weight, and the SUVmax for each lesion was calculated.
Animal modelBALB/c-numice (female, 4 to 6weeks of age, 18–20 g; Shanghai
SLAC Laboratory Animal Co., Ltd.) were housed in sterile filter-capped cages. The left and rightflanks of themicewere injected s.c.with 4� 106 cells in 100 mL PBS. Six weeks after implantation, themice were prepared for MicroPET/CT scanning. After scanning,the tumors were surgically dissected. The tumor specimens werefixed in 4% paraformaldehyde. Samples were then processed forhistopathologic examination. All animal experiments were per-formed according to the guidelines for the care and use oflaboratory animals and were approved by the Institutional Ani-mal Care and Use Committee of Fudan University.
MicroPET/CT imagingMicroPET/CT scans and image analyses were performed using
an Inveon MicroPET/CT (Siemens Medical Solution). Eachtumor-bearing mouse was injected with 11.1 MBq (300 mCi) of
Translational Relevance
To assess the potential use of FBW7 in pancreatic cancerdiagnosis and prognosis, we combined molecular imagingtechnology (PET/CT) and immunohistochemistry to evaluatethe correlation between SUVmax and FBW7 expression levels.Our clinical and mechanistic findings indicate that FBW7regulates glucose metabolism through the effector TXNIP,which predicted the poor prognosis of pancreatic cancer bynegatively regulating proliferation and glucose metabolism.Moreover, FBW7 regulated TXNIP expression through the E3ubiquitin ligase substrate c-Myc. Overall, the dysregulation ofthe FBW7/c-Myc/TXNIP pathway is a promising new target fornovel therapeutic inhibitors to treat pancreatic cancer. Fur-thermore, key signature enzymes of the glycolysis cascade,such as GLUT1, GLUT4, HK2, and LDHA, are also candidatetargets for combination treatment regimens. Therefore, ourfindings may have a critical impact on pancreatic cancermanagement and may apply to other aggressive and hetero-geneous cancers.
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18F-FDG via the tail vein. Scanning started 1 hour after injection.Animals were anesthetized with isoflurane during the scanningperiod. The images were reconstructed using three-dimensionalordered-subset expectationmaximization (OSEM3D)/maximumalgorithm. Inveon Research Workplace was used to obtain thepercentage injected dose per gram (%ID/g) and the SUVs. TheSUVmax was calculated.
PlasmidsThe Flag-tagged coding sequences of human FBW7 and TXNIP
were cloned into the lentiviral vector pCDH-CMV-MCS-EF1-puro(SBI) to generate FBW7 expression plasmids. The pLKO.1 TRCcloning vector (Addgene plasmid 10878) was used to generate c-Myc shRNA constructs. The 21-bp target against c-Myc wasCCTGAGACAGATCAGCAACAA.
Cell cycle and cell viabilityFlow cytometric analysis was conducted to examine cell-cycle
status using propidium iodine (Invitrogen) and ahumanAnnexinV-FITC kit (Invitrogen), respectively, according to the manufac-turer's protocols. Cell viability was determined each day usingCCK-8 (Cell Counting Kit-8; Dojindo Laboratories) according tothemanufacturer's instructions. All observationswere reproducedat least three times in independent experiments.
Colony-formation assayCells were seeded in triplicate in 6-well plates at an initial
density of 500 cells/well. After 10 to 14 days, colonies were clearlyvisible, and the cells were fixed with 4% paraformaldehyde for 15minutes at room temperature and stainedwith 4mg/mL of crystalviolet (Sigma). The colonies containing more than 50 cells werecounted using light microscopy. The average number of colonieswas determined from three independent experiments.
Quantitative real-time PCRTotal RNA was extracted using TRIzol reagent (Invitrogen).
cDNA was synthesized by reverse transcription using a TaKaRaPrimeScript RT reagent kit. The expression status of candidategenes and b-actin were determined by quantitative real-time PCRusing an ABI 7900HT Real-Time PCR system (Applied Biosys-tems). All of the reactions were run in triplicate. Primer sequencesare listed in Supplementary Table S2.
RNA extraction, ss-cDNA synthesis, and microarray analysisTotal RNA from wild-type and FBW7-overexpressing SW1990
cells was extractedwith TRIzol/chloroform and then purifiedwithmagnetic beads from Agencourt Ampure (APN 000132; BeckmanCoulter). Target preparation formicroarray processingwas carriedout according to the GeneChip WT PLUS Reagent Kit. A total of500 ng of RNA was used for a double-round of cDNA synthesis.After fragmentation of second-cycle single-stranded cDNA (ss-cDNA), the sample was labeled with biotin by terminal deox-ynucleotidyl transferase (TdT). Then, the sample was hybridizedto theAffymetrixHumanHTA2.0Array for 16 to 18hours at 45�C.Following the hybridization, the microarrays were washed andstainedwith streptavidin phycoerythrin on theAffymetrix FluidicsStation 450. The microarrays were scanned by using the Affyme-trix GeneChip Command Console (AGCC), which was installedin the GeneChip Scanner3000 7G. The data were analyzed withthe Robust Multichip Analysis (RMA) algorithm using the default
analysis settings and global scaling as normalization method byPartek Genomics Suite 6.6. Values presented are log2 RMA signalintensity. The normalized data were further analyzed using one-wayANOVA to screenout the differentially expressed genes. Then,the Database for Annotation, Visualization and Integrated Dis-covery (DAVID)was used to determine pathways andprocesses ofmajor biologic significance and importance based on the GeneOntology annotation function and Kyoto Encyclopedia of GenesandGenomes pathway function. Themicroarray datawere depos-ited in GEO under accession numbers GSE76443.
Western blotWestern blotting was carried out as previously described (8).
Briefly, whole-cell protein lysates were extracted. An antibodyagainst FBW7 was purchased from Bethyl. The PGC-1a anti-body was purchased from Santa Cruz Biotechnology. The c-Mycand HIF1a antibodies were obtained from Abcam. The TXNIPantibody was produced by Proteintech. b-Actin was used as aloading control.
Glycolysis analysisGlucose Uptake Colorimetric Assay Kits (Biovision) and Lac-
tate Colorimetric Assay Kits (Biovision) were purchased to exam-ine the glycolysis process in pancreatic cancer cells, according tothe manufacturer's protocols.
Oxygen consumption rate and extracellular acidification rateCellular mitochondrial function was measured using the
Seahorse XF Cell Mito stress test Kit and the Bioscience XF96Extracellular Flux Analyzer, according to the manufacturer'sinstructions. The glycolytic capacity was determined using theGlycolysis Stress Test Kit as per the manufacturer's instructions.Briefly, 4 � 104 cells were seeded onto 96-well plates andincubated overnight. After washing the cells with Seahorsebuffer (DMEM with phenol red containing 25 mmol/L glucose,2 mmol/L sodium pyruvate, and 2 mmol/L glutamine), 175 mLof Seahorse buffer plus 25 mL each of 1 mmol/L oligomycin, 1mmol/L FCCP, and 1 mmol/L rotenone was automaticallyinjected to measure the oxygen consumption rate (OCR). Then,25 mL each of 10 mmol/L glucose, 1 mmol/L oligomycin, and100 mmol/L 2-deoxy-glucose were added to measure the extra-cellular acidification rate (ECAR). The OCR and ECAR valueswere calculated after normalization to the cell number and areplotted as the mean � SD.
Analysis of ATP productionThe ENLITEN ATP Assay System (Promega; FF2000) was used
according to themanufacturer's instructions. Cells were harvestedby scraping andwere resuspended in PBS. The cell suspensionwasdivided into unequal aliquots. Part of the cell suspension wasmixed with 5% trichloroacetic acid (TCA). The remaining cellswere used for the cell number calculation. Tris-acetate buffer (pH7.75) was then added to neutralize the TCA and to dilute the TCAto a final concentration of 0.1%. The diluted sample (40 mL) wasadded to an equal volume of rL/L reagent (Promega; FF2000).Then, luminescence was measured. The ATP standard (Promega;FF2000) was serially diluted to generate a regression curve forcalculating ATP concentrations in individual samples. The relativeATP concentration was determined and normalized to that of thecontrol cells, which was designated as 1. Three independent
Ji et al.
Clin Cancer Res; 22(15) August 1, 2016 Clinical Cancer Research3952
experiments were performed. The results are presented as themean � SD.
Measurement of mitochondrial membrane potentialThe mitochondrial membrane potential assay Kit with JC-1
(Beyotime Biotechnologies) was used tomeasure the alteration inthemitochondrial membrane potential (Dym). Briefly, cells wereharvested by scraping and were resuspended in 0.5 mL of culturemedium. Next, 0.5mL of JC-1 Staining Solution was added to thecell suspension. Then, the suspension was incubated for 20minutes at 37�C in a CO2 incubator. Next, the cells were collectedby centrifugation at 600� g for 4 minutes. The cells were washedtwice with 1 mL of JC-1 Staining Buffer. Subsequently, 500 mL ofJC-1 Staining Buffer was added to the cell pellet in each tube, andthe cells were thoroughly resuspended. The samples were imme-diately analyzed using flow cytometry. In healthy cells, JC-1 formsmitochondrial aggregates, which emit red fluorescence at 595 nmwhen excited at 525 nm. However, after the loss of Dym, JC-1remains as monomers that emit green fluorescence at 525 nmwhen excited at 485 nm. Mitochondrial depolarization is indi-cated by a decrease in the red/green fluorescence intensity ratio.
Chromatin immunoprecipitation assayChromatin immunoprecipitation (ChIP) assays were per-
formed using the EZ-ChIP Kit from Millipore according to themanufacturer's protocol. Primers to detect TXNIP promoter occu-pancy were: F: 50-CAGAGCGCAACAACCATT-30 and R: 50-AGGCTCGTGCTGCCCTCGTGCAC-30.
siRNA treatmentssiRNA duplexes against c-Myc and FBW7 were transfected
into pancreatic cancer cells using Lipofectamine 2000 (Invitro-gen). The siRNAduplex sense sequenceswere as follows: si-FBW7-1–50-ACCTTCTCTGGAGAGAGAAATGC-30, si-FBW7-2–50-GTGT-GGA ATGCAGAGACTGGAGA-30; si-c-Myc-1–50-CCTGAGACA-GATCAGCAACAA-30, si-c-Myc-2–50-CAGTTGAAACACAAACTT-GAA-30.
Statistical analysisAll data are presented as the mean � SD. Experiments were
repeated at least three times. Two-tailed unpaired Student t testsand one-way analysis of variance were used to evaluate the data.SPSS version 16.0 software (IBM) was used for the data analysis.Differences were considered significant at �, P < 0.05; ��, P < 0.01;and ���, P < 0.001.
ResultsFBW7expression is negatively correlatedwith the 18F-FDGPET/CT SUVmax value
18F-FDG PET/CT, which allows for the visualization of themetabolic activity of viable tumor cells, has been widely used inthemanagement of cancer diagnosis. The SUVmax has beenwidelyused as a surrogate marker for the prognosis of numerous types ofcancer, including pancreatic cancer (23, 25). To explore thepotential relationship between FBW7 and glucose metabolism,we first examined the correlation between the FBW7 IHC stainingand the PET/CT SUVmax value. As expected, patients with pan-creatic cancer with decreased expression of FBW7 exhibited ahigher SUVmax value (Fig. 1A), and the correlation is statisticallysignificant (Fig. 1B). These results indicate that FBW7 plays aninhibitory role in glucose metabolism in pancreatic cancer.
FBW7 inhibits glucose metabolism in pancreatic cancer cellsGlucose metabolism in cancer relies on a series of enzymatic
reactions (Fig. 2A). Clinically, in cancer diagnosis, 18F-FDG PET/CT reflects glucose turnover in the tumor lesion. A higher SUVmax
value implies an increased glucosemetabolic activity in the lesion.To determine the impact of FBW7 expression on cellular metab-olism, we constructed PANC-1 and SW1990 stable cell linesectopically expressing wild-type FBW7 (Fig. 2B). First, we exam-ined glucose uptake and lactate production, two primary indica-tors of the Warburg effect. As expected, FBW7 decreased glucoseuptake and lactate production, indicating its inhibitory role inglycolysis (Fig. 2C and D). The ECAR is another measurement ofglucose metabolism and reflects the lactic acid–induced acidifi-cation of the medium surrounding cancer cells. FBW7 decreasedthe ECAR in PANC-1 and SW1990 cells and may play an inhib-itory role in lactic acid formed during glycolysis (Fig. 2E).
In addition, cellular oxygen consumption reflects mitochon-drial respiration and can be measured by the OCR. PANC-1 andSW1990 cells overexpressing FBW7 exhibited lower OCRs, indi-cating that FBW7 is a negative regulator of basal mitochondrialrespiration (Fig. 2F). Moreover, cancer cells rely on glucosemetabolism for ATP production, which meets the demands ofrapid proliferation and metastasis. We then analyzed the impactof FBW7 on ATP production. Consistently, FBW7 decreased ATPproduction in PANC-1 and SW1990 cells (Fig. 2G). Furthermore,themitochondrial membrane potential, which is used to evaluateearly apoptosis, reflects the mitochondrial integrity and variesaccording to the metabolic state. FBW7 decreased the mitochon-drial potential of PANC-1 andSW1990 cells, indicating that FBW7
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Figure 1.Statistical analysis of the correlationbetween FBW7 expression and the18F-FDG PET/CT SUVmax. A,representative 18F-FDG PET/CTimaging of PDAC patients with low orhigh FBW7 expression (magnificationscale bar, 20 mm). B, analysis of theSUVmax in FBW7low and FBW7high
groups (n ¼ 60; P < 0.001).
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also functions as a negative regulator of mitochondrial glucosemetabolism (Fig. 2H). To further explore the role of FBW7 inglucose metabolism, key signature enzymes of the glycolysiscascade were examined. Enzymes related to glucose transporta-tion, such as GLUT1, GLUT4, HK2, LDHA, and LDHB, weredecreased in FBW7-overexpressing PDAC cells (Fig. 2I). In addi-tion, the levels of other glycolytic enzymes decreased in the
presence of FBW7 overexpression (Supplementary Fig. S1A andS1B). Taken together, these results suggest that FBW7 plays a vitalrole in pancreatic cancer cell glucose metabolism.
FBW7 decreases glucose utilization in a xenograft modelTo further confirm the in vitro phenotype of FBW7 in glucose
metabolism, we subcutaneously injected nude mice with FBW7-
Figure 2.FBW7 is a negative regulator of glucose metabolism in pancreatic cancer. A, schematic representation of glucose metabolism in cancer cells. B, overexpressionof FLAG-tagged FBW7 in PANC-1 and SW1990 cells. C, FBW7 inhibits glucose uptake in PANC-1 and SW1990 cancer cells. D, FBW7 reduced lactateproduction via glycolysis in PDAC cells. E, ECAR, an indicator of glycolysis, was reduced in the presence of FBW7 expression. F, OCR, which reflects mitochondrialrespiration, was decreased in FBW7-overexpressing PANC-1 and SW1990 cancer cells. G, FBW7 decreased ATP production. H, mitochondrial potentialdecreased in the presence of FBW7 overexpression. I, FBW7 decreased the expression of rate-limiting glycolytic enzymes.
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Clin Cancer Res; 22(15) August 1, 2016 Clinical Cancer Research3954
overexpressing SW1990 cells. As expected, ectopic FBW7 inhib-ited tumor growth in the xenograft mouse model (Fig. 3A and B).Furthermore, we used a small animal imaging system to evaluatethe role of FBW7 in glucose metabolism (Fig. 3C). The resultsindicated that FBW7 significantly inhibited 18F-FDGuptake in thein vivo xenograft model (Fig. 3D). Subsequent immunohis-tochemistry using antibodies against GLUT1, GLUT4, HK2,LDHA, and LDHB demonstrated that the expression of theseglycolytic enzymes was significantly decreased in tissues fromxenograft tumors (Fig. 3E), which was consistent with previousresults.
TXNIP is a target of FBW7 in PDACNext, to search for a possiblemolecular mechanism underlying
the FBW7-mediated regulation of glucose metabolism, we used ahigh-throughput gene expression profiling array and found that aseries of signaling pathways were altered by FBW7 overexpression(GEO: accession numbers GSE76443). Among the differentiallyexpressed genes, FOXO1 and TXNIP are well-established regula-tors of glucosemetabolism (26–28). Further validation using twocell lines indicated that FBW7 overexpression significantly alteredTXNIP expression (Fig. 4A) but had little impact on FOXO1expression (Supplementary Fig. S1C). We hypothesized thatTXNIP was a potential effector of FBW7 in the regulation ofglucose metabolism. To test this hypothesis, we examined theexpression of TXNIPprotein by immunoblotting after overexpres-sion of FBW7 in two pancreatic cancer cell lines. TXNIP proteinlevels increased following FBW7 overexpression (Fig. 4B). On thecontrary, downregulation of endogenous FBW7 by siRNA con-structs significantly decreased the abundance of TXNIP in thesetwo cells (Fig. 4C and D). Moreover, IHC staining for TXNIP was
elevated in FBW7-overexpressing xenograft tumors (Fig. 4E).Next, we examined the correlation between FBW7 and TXNIPexpression in tissues from PDAC patients and observed a positivecorrelation between FBW7 and TXNIP (Fig. 4F and Supplemen-tary Table S3). Together, these data strongly suggest that TXNIP is apotential FBW7 target in pancreatic cancer.
TXNIP is a negative regulator of glucose metabolismAlthough TXNIP is a negative regulator of glucose metabolism
in many types of cancer cells, its role in pancreatic cancer has notbeen previously investigated. In the present study, we found thatTXNIP expression is inversely correlated with the SUVmax value(Fig. 5A). To determine the impact of FBW7 expression on cellularmetabolism, we generated PANC-1 and SW1990 stable cell linesectopically expressing wild-type TXNIP (Fig. 5B). A subsequentanalysis indicated that TXNIP inhibited glucose uptake and lactateproduction in PANC-1 and SW1990 cells (Fig. 5C and D). TheECAR and OCR results measured using the Seahorse metabolismanalyzers further validated that TXNIP is a negative regulator ofglycolysis and mitochondrial respiration (Fig. 5E and F). ATPproduction also decreased upon TXNIP overexpression (Fig. 5G).Furthermore, it was demonstrated that TXNIP decreased mito-chondrial potential in PDAC cell lines (Fig. 5H). Accordingly, theexpression of glycolytic enzymes related to glucose metabolismdecreased dramatically after TXNIP overexpression (Fig. 5I and J;Supplementary Fig. S2A and S2B). These results confirm thatTXNIP inhibits glucose metabolism in pancreatic cancer.
We then examined the influence of TXNIP on pancreatic cancercell proliferation. As expected, a CCK8 proliferation assay indi-cated that TXNIP decreased the proliferation rate of PANC-1 andSW1990 cells (Fig. 5K). A subsequent colony-formation assay
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Figure 3.FBW7 negatively regulates glucose turnover in a xenograft model. A, SW1990 cells stably expressing FBW7 or empty vector were s.c. injected into nude mice (left,control; right, FBW7). B, at the indicated times, tumors were measured with Vernier calipers (mean � SEM; n ¼ 5). C, representative 18F-FDG MicroPET/CTimaging of tumor-bearing mice. The tumors are indicated with arrows. Mice were fasted for 6 hours before detection. D, the ratios of the tumor SUVmax in the FBW7group and the control group (n ¼ 5; P < 0.05). E, expression of the rate-limiting enzymes GLUT1, GLUT4, HK2, LDHA, and LDHB decreased in tumors formedby FBW7 overexpression in SW1990 cells.
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demonstrated that TXNIP inhibited the colony-forming capacityof PDAC cancer cells (Supplementary Fig. S2C and S2D). Cell-cycle analyses indicated that overexpression of TXNIP inhibitedcell-cycle progression and arrested the cell cycle at theG2–Mphase(Supplementary Fig. S2E). In clinical specimens, we measuredTXNIP expression using an IHC tissue microarray of PDACsamples and found that decreased TXNIP expression predicts apoor PDAC prognosis (Fig. 5L and Supplementary Fig. S2F andS2G). Finally, we silenced TXNIP in FBW7-overexpressing PANC-1 and SW1990 cells, and we found that TXNIP knockdown couldreverse the effects of FBW7 overexpressing in vitro, includingproliferation and glucosemetabolism inhibition (SupplementaryFig. S3). Thus, we believe that TXNIP is an important downstreameffector of FBW7 in regulating glucose metabolism.
FBW7 regulates TXNIP expression in a c-Myc–dependentmanner
FBW7 is an E3 ubiquitin ligase and targets many substrates forproteasomal degradation. Among these substrates, HIF1a,PGC1a, and c-Myc are well-known regulators of metabolism. Wepreviously reported that the expression of c-Myc decreased dra-matically when FBW7was overexpressed in pancreatic cancer (8).However, no change in the expression of PGC1a or HIF1a wasobserved upon FBW7 upregulation in pancreatic cancer. There-fore, we investigated the role of c-Myc in pancreatic cancer cellglucose metabolism and confirmed that c-Myc also promotedglucosemetabolism inpancreatic cancer (Supplementary Fig. S4).To determine whether FBW7 regulates TXNIP through c-Myc, wefirst examined the TXNIP protein level in siRNA-transfected
pancreatic cancer cells (Fig. 6A). The promoter region of TXNIPwas reported to harbor E-box elements, which consist of the CAC(G/A)TG nucleotide sequence (27; Fig. 6B). We cloned the pro-moter region of TXNIP into the pGL3-basic vector and performeda dual luciferase assay to investigate whether c-Myc influencesTXNIP promoter activity. The results indicated that cotransfectionwith c-Myc inhibited TXNIP promoter activity, whereas cotrans-fection with siRNA against c-Myc significantly increased TXNIPpromoter activity (Fig. 6C). Moreover, c-Myc occupied the E-boxes in the TXNIP promoter region, as determined by ChIPassay (Fig. 6D). These findings suggest that c-Myc functions as apromoter of TXNIP transcription, which is consistent with obser-vations from the study of triple-negative breast cancer (27).
To validate whether FBW7 regulated TXNIP expression in a c-Myc–dependent manner, we generated a dominant-negativeFBW7 mutant, R465H, and designated it FBW7R465H. Comparedwith wild-type FBW7, FBW7R465H only marginally increasedTXNIP expression (Fig. 6E and F). Consistent with this observa-tion, TXNIP promoter activity and protein level both decreasedwith the expression of FBW7R465H (Fig. 6G). Furthermore, ChIPassay demonstrated that the introduction of FBW7 decreased c-Myc occupancy in the TXNIP promoter region, whereasFBW7R465H had little impact (Fig. 6H). Taken together, theseresults demonstrate that FBW7 inhibits glucose reprogrammingin pancreatic cancer via the c-Myc/TXNIP axis. These resultsprovide data regarding a novel function of FBW7 in PDACglucosemetabolism and indicate that FBW7 is a potential marker forpancreatic cancer diagnosis and prognosis and a target for pan-creatic cancer treatment (Fig. 6I).
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1 3.87 1 2.76
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NIP
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e F
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Figure 4.Screening for FBW7 effector proteinsin glucose metabolism regulation.A, transcription of TXNIP, a majorredox and glucose metabolismregulator, increased with FBW7overexpression in cancer cells. B,FBW7 increased the TXNIP proteinlevel. C, PANC-1 and SW1990 cellswere transfectedwith indicated siRNAvectors; transcription level of FBW7was detected. D, cell lysates werecollected, and immunoblots wereperformed with the indicatedantibodies. FBW7 silencing alsodecreased the TXNIP protein level.E, TXNIP was decreased in xenograftmouse tumors formed by FBW7overexpression (magnification scalebar, 40 mm). F, TXNIP and FBW7expression showed a positivecorrelation in PDAC patient samples(magnification scale bar, 40 mm).
Ji et al.
Clin Cancer Res; 22(15) August 1, 2016 Clinical Cancer Research3956
Time after passage (days) Time after passage (days)
Ove
rall
surv
ival
Time (months)
GLUT4 HK2 LDHA LDHB GLUT1 GLUT4 HK2 LDHA LDHB
0.4
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%)Control
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I J
K L
G H
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Figure 5.TXNIP negatively regulates glucosemetabolism and proliferation in pancreatic cancer.A, analysis of the SUVmax in TXNIP
low and TXNIPhigh groups (n¼ 60; P <0.05).B, overexpression of FLAG-tagged TXNIP in PANC-1 and SW1990 cells. C, TXNIP overexpression reduced the glucose uptake capacity of PDAC cells. D, lactateproduction was lower in the TXNIP-overexpressing PDAC cells. E, TXNIP negatively regulated the glycolysis rate, reflected by the ECAR. F, TXNIP inhibitedthe OCR. G, TXNIP decreased ATP production in PANC-1 and SW1990 cells. H,mitochondrial potential was decreased upon TXNIP overexpression. I, TXNIP led tochanges in the expression of rate-limiting enzymes of the glycolysis cascade in PANC-1 cells. J, TXNIP led to changes in the expression of rate-limiting enzymesof the glycolysis cascade in SW1990 cells. K, TXNIP inhibited cell proliferation as measured by a CCK-8 proliferation kit. L, Kaplan–Meier analysis of theoverall survival rate of patients with pancreatic cancer, according to TXNIP expression (n ¼ 86; P < 0.001, log-rank test).
FBW7 Inhibits Glucose Metabolism in Pancreatic Cancer
www.aacrjournals.org Clin Cancer Res; 22(15) August 1, 2016 3957
DiscussionBased on the observation that even in the presence of an oxygen
supply, tumor cells preferentially use glycolysis over mitochon-drial oxidative phosphorylation (OXPHOS) for glucose-depen-
dent ATP production to fuel mitochondrial respiration, OttoWarburg put forward the notion of the "Warburg effect" in the1920s (29). Advances in the understanding of the biology oftumor progression and metastasis have clearly highlighted the
PANC-1
PANC-1
PANC-1
PANC-1
PANC-1
PANC-1
PANC-1
c-Myc
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b-Actin
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2.0
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0.5
0.0 0.0
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ControlControl
FBW7WT
FBW7WT
FBW7R465H
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0.7
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pGL3-TXNIP pGL3-TXNIP
Mycsi-Myc
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+ ++
+
+
–
––
–+ +
++
+
–
––
–
Rel
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e lu
cife
rase
act
ivit
y
2.0
1.5
1.0
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0.0
+ ++
+––
– – +
+ ++
+––
– – +
pGL3-TXNIP
FBW7WT
FBW7R465H
pGL3-TXNIP
FBW7WT
FBW7R465H
0.0
0.6
1.2
1.8FBW7
c-Myc
TXNIP
Warburgeffect
Mitochondrialrespiration
Oncogenesisof PDAC
Rel
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rase
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si-Myc#2
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si-Myc#2
SW1990
SW1990
SW1990
SW1990
SW1990
SW1990
SW1990
E-Box
–2,000
Input IgG c-Myc
TXNIP promoter+1 +220
TS
Luc
Figure 6.FBW7 regulates TXNIP expression via c-Myc.A, siRNA-mediated silencing of c-Myc led to an increase in TXNIP protein levels. B, position of the c-Myc–binding site inthe TXNIP promoter. C, relative TXNIP promoter activity in PANC-1 and SW1990 cells cotransfected with the TXNIP promoter and a c-Myc expression plasmid or asi-c-Myc, respectively. D, c-Myc occupies the E-box of the TXNIP promoter region, as measured by ChIP assay. E, An FBW7 mutant, which lost its E3 ligaseactivity andwas designated as FBW7R465H, had little influence on TXNIP transcription comparedwith itswild-type counterpart.F, FBW7R465H,which lost the capacityto regulate c-Myc protein levels, exerted no significant impact on TXNIP protein levels, indicating that FBW7 regulated TXNIP expression in a c-Myc–dependentmanner. G, FBW7R465H exerted little impact on TXNIP promoter activity compared with its wild-type counterpart. H, FBW7 decreased c-Myc occupancy of theTXNIP promoter, whereas the FBW7 mutant had little influence in PANC-1 and SW1990 cells. I, proposed model of the mechanism of FBW7-mediatedregulation of glucose metabolism via the c-Myc/TXNIP axis in pancreatic cancer.
Ji et al.
Clin Cancer Res; 22(15) August 1, 2016 Clinical Cancer Research3958
importance of aberrant tumor metabolism. The manifestation ofthe Warburg effect in today's clinical setting is the use of 18F-FDGto detect tumors with an increased glucose uptake. The elevateduptake visualized by 18F-FDG PET/CT correlates with a poorprognosis and ahighermetabolic burden inmany types of tumors(23, 30).
Mounting evidence indicates that the reprogramming of tumormetabolism is controlled by various oncogenic signals (31, 32). Inpancreatic cancer, the Ras oncoprotein has been shown to pro-mote metabolic transformation (33–35). Although KRAS muta-tions were detected in >90%of PDACpatients andwere proposedto be initiators of PDAC, KRAS remains an undruggable target.Elevated oncogenic KRAS activity stimulates many downstreamsignaling pathways (36–37). Therefore, strategies targeting thedownstream effectors of KRAS might provide solutions to theinhibition of certain metabolic pathways. Our previous studyreported that ERK activation caused by KRAS mutation in PDACresulted in the destabilization of FBW7 (8). However, the specificrole of FBW7 in PDAC remains unclear.
In the present study, we first provided clinical evidence thatFBW7 expression affects glucose metabolism in PDAC with PET/CT data. We then used a series of aerobic glycolysis-relatedassays, including the examination of glucose uptake, lactateproduction,OCR, ECAR, andATPproduction, andmitochondrialmembrane potential. Overexpression of FBW7 dramaticallyinhibited glucose metabolism in PDAC cells. We confirmed theseresults in an in vivo xenograft model. All the enzymes related toglucose transportation (GLUT1, GLUT4, HK2, LDHA, and LDHB)decreased dramatically in the FBW7-overexpressing PDAC cellscompared with the control cells. Given the important role ofFBW7 in PDAC glucose metabolism, we further explored thepotential underlying mechanism.
FBW7 has been reported to repress synthesis of cholesteroland fatty acids lipid homeostasis through modulating SREBPsstability directly (38). However, the role of FBW7 in glucosetransformation has seldom been studied. To investigate wheth-er FBW7 could affect the downstream expression of glycolysis-related genes, we performed high-throughput screening toidentify possible genes necessary for the coordinate regulationof FBW7-mediated glucose metabolism. Interestingly, theexpression levels of many glycolysis-related genes were alteredupon the upregulation of FBW7. Among the altered glycolysis-related genes in the database, we selected TXNIP as the targetgene and investigated whether FBW7 regulates glycolysis viaTXNIP in PDAC. TXNIP has been identified as a tumor sup-pressor gene in various solid tumors and hematologic malig-nancies (27). Moreover, recent evidence indicates that TXNIPalso functions as a potent negative regulator of glucose uptakeand aerobic glycolysis. We confirmed these results using q-PCRand Western blot analysis, which demonstrated that the mRNAand protein levels of TXNIP in FBW7-transfected PDAC cellswere significantly higher than those in control cells, indicatingthat TXNIP was regulated by FBW7, predominantly via tran-scriptional modifications.
FBW7 has been reported to function as a tumor suppressor bytargetingmultiple oncoprotein substrates, such as cyclin E, c-Myc,c-Jun, PGC-1a, HIF1a, andMcl-1, for degradation (6). Among theknown substrates of FBW7,HIF1a, PGC-1a, and c-Myc have beenreported to play critical roles in the regulation ofmetabolism (16,39, and 17). These three substrates are also important transcrip-tion factors responsible for activating or repressing downstream
individual genes. We previously found that c-Myc expressiondecreased dramatically upon FBW7 upregulation, whereas noreduction was observed in PGC-1a expression (8). Here, we againmeasured HIF1a levels and observed no alteration. c-Myc is amultifunctional transcription factor that drives the multiple syn-thetic functions necessary for rapid cell division and simulta-neously inhibits the expression of genes with antiproliferativefunctions (40). Intriguingly, multiple studies have demonstratedthat c-Myc can directly bind to the promoters of thousands ofgenes—up to 30% of all known genes (41). In addition, many ofthe metabolic changes that occur in transformed cells are drivenby c-Myc overexpression (40). Thus, we proposed that FBW7might regulate TXNIP in a c-Myc–dependent manner. To test this,we first investigated whether TXNIP expression changed inresponse to c-Myc downregulation. We found that c-Myc couldsuppress TXNIP promoter activity and inhibit TXNIP expression.These findings were consistent with a previous report that c-Myccould function as a promoter of TXNIP transcription. Finally, wevalidated that FBW7 regulated TXNIP expression in a c-Myc–dependent fashion by generating a FBW7 mutant that lost itsE3 ligase activity.
In conclusion, we demonstrated a novel role of FBW7 inglucose metabolism in pancreatic cancer. Mechanistically, FBW7regulates TXNIP expression in a c-Myc–dependent manner.Thus far, therapeutic strategies directly targeting KRAS or c-Mychave proven to be technically difficult. Therefore, alternativeapproaches that focus on interfering with c-Myc–mediated down-stream effectors might provide novel therapeutic avenues forPDAC.
Disclosure of Potential Conflicts of InterestNo potential conflicts of interest were disclosed.
Authors' ContributionsConception and design: S. Ji, Y. Qin, J. Xu, Q. Ni, M. Li, X. YuDevelopment of methodology: S. Ji, Y. Qin, C. Liang, R. Huang, S. Shi, J. Liu,K. Jin, D. Liang, W. Xu, Q. Ni, X. YuAcquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): S. Ji, Y. Qin, R. Huang, S. Shi, J. Liu, K. Jin, D. Liang,W. Xu, L. Liu, C. Liu, X. YuAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): C. Liang, M. Li, X. YuWriting, review, and/or revision of the manuscript: S. Ji, Y. Qin, J. Xu, Q. Ni,M. Li, X. YuAdministrative, technical, or material support (i.e., reporting or organizingdata, constructing databases): C. Liang, S. Shi, B. Zhang, J. Xu, X. YuStudy supervision: X. YuOther (my lab provided some reagents from our unique GEMM): P.J. Chiao
AcknowledgmentsThe authors thank Huanyu Xia for assistance in collecting the patient data.
Grant SupportThis work was supported by National Natural Science Foundation
(81372651, 81201900, 81172276, and 81101565), Sino-German Center(GZ857), Ph.D. Programs Foundation of Ministry of Education of China(20120071120104), and Program of Science and Technology Commission ofShanghai (13431900105 and 13DZ1942802).
The costs of publication of this articlewere defrayed inpart by the payment ofpage charges. This article must therefore be hereby marked advertisement inaccordance with 18 U.S.C. Section 1734 solely to indicate this fact.
ReceivedOctober 1, 2015; revised February 17, 2016; acceptedMarch 7, 2016;published OnlineFirst March 16, 2016.
FBW7 Inhibits Glucose Metabolism in Pancreatic Cancer
www.aacrjournals.org Clin Cancer Res; 22(15) August 1, 2016 3959
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2016;22:3950-3960. Published OnlineFirst March 16, 2016.Clin Cancer Res Shunrong Ji, Yi Qin, Chen Liang, et al. (Thioredoxin-Binding Protein) Axis in Pancreatic CancerRegulates Glucose Metabolism by Targeting the c-Myc/TXNIP FBW7 (F-box and WD Repeat Domain-Containing 7) Negatively
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