Negatively Regulates Glucose Metabolism by Targeting the C-Myc

Published OnlineFirst March 16, 2016; DOI: 10.1158/1078-0432.CCR-15-2380

Biology of Human Tumors Clinical Cancer Research FBW7 (F-box and WD Repeat Domain-Containing 7) Negatively Regulates Glucose Metabolism by Targeting the c-Myc/TXNIP (Thioredoxin-Binding Protein) Axis in Pancreatic Cancer Shunrong 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 targeting Results: The expression level of FBW7 was negatively asso- oncoproteins for destruction. We previously reported that the ciated with SUVmax in pancreatic cancer patients. FBW7 signif- oncogenic mutation of KRAS inhibits the tumor suppressor FBW7 icantly suppressed glucose metabolism in pancreatic cancer via the Ras–Raf–MEK–ERK pathway, which facilitates the prolifer- cells in vitro. Using a xenograft model, MicroPET/CT imaging ation and survival of pancreatic cancer cells. However, the under- results indicated that FBW7 substantially decreased 18F-fluor- lying mechanism by which FBW7 suppresses pancreatic cancer odeoxyglucose (18F-FDG) uptake in xenograft tumors. Gene remains unexplored. Here, we sought to elucidate the function of expression profiling data revealed that TXNIP, a negative reg- FBW7 in pancreatic cancer glucose metabolism and malignancy. ulator of metabolic transformation, was a downstream target of Experimental Design: Combining maximum standardized FBW7. Mechanistically, we demonstrated that TXNIP was a c- uptake value (SUVmax), which was obtained preoperatively via Myc target gene and that FBW7 regulated TXNIP expression in a a PET/CT scan, with immunohistochemistry staining, we analyzed c-Myc–dependent manner. the correlation between SUVmax and FBW7 expression in pancre- Conclusions: Our results thus reveal that FBW7 serves as a atic cancer tissues. The impact of FBW7 on glucose metabolism negative regulator of glucose metabolism through regulation of was further validated in vitro and in vivo. Finally, gene expression the c-Myc/TXNIP axis in pancreatic cancer. Clin Cancer Res; 1–11. profiling was performed to identify core signaling pathways. 2016 AACR.

Introduction (3–5). Hence, there is an urgent need for an increased understanding of the biologic characteristics and molecular mechan- Pancreatic cancer is a devastating disease and is the fourth isms of pancreatic cancer. leading cause of cancer-related deaths in the United States (1). F-box and WD repeat domain-containing 7 (FBW7) is the Pancreatic ductal adenocarcinoma (PDAC) accounts for approx- substrate recognition component for the Skp1-Cul1-F-box (SCF) imately 95% of pancreatic cancer cases (2). Due to late diagnosis, ubiquitin ligase complex and targets many oncoproteins for high metastatic potential, and resistance to chemoradiotherapy, destruction. Loss of the tumor-suppressive function of FBW7 has there are no effective treatments for refractory pancreatic cancer been proposed to drive the progression of multiple cancers. Deletion or mutation of FBW7 has been frequently identified in many cancers, including gastric cancer, colon cancer, and breast 1Department of Pancreatic Surgery, Fudan University Shanghai Can- carcinoma (6). Overall, approximately 6% of human tumors cer Center, Shanghai, China. 2Department of Oncology, Shanghai harbor FBW7 mutations. Emerging evidence has shown that 3 Medical College, Fudan University, Shanghai, China. Pancreatic Can- FBW7 is also regulated by multiple upstream genes, such as cer Institute, Fudan University, Shanghai, China. 4Department of Breast Surgery, Shanghai Jiao Tong University affiliated Shanghai p53, Pin1, Hes-5, and Numb4, as well as by miRNAs (7). We Sixth Hospital, Shanghai,China. 5Department of Molecularand Cellular previously reported that fewer than 2% of pancreatic cancer Oncology, the University of Texas M.D. Anderson Cancer Center, samples harbored FBW7 mutations, according to sequencing Houston, Texas. 6Department of Surgery, The University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma. analysis (8). Furthermore, with mass spectrometry analysis, we detected that ERK kinase phosphorylated FBW7 at the T205 site, Note: Supplementary data for this article are available at Clinical Cancer Research Online (http://clincancerres.aacrjournals.org/). which resulted in destabilization of FBW7 in pancreatic cancer. However, the exact role of FBW7 in pancreatic cancer progression S. Ji, Y. Qin, and C. Liang contributed equally to this article. has not been investigated. Corresponding Author: Xianjun Yu, Pancreatic Cancer Institute, Fudan Univer- Pancreatic cancer is characterized by extensive desmoplasia that sity, 270 Dong An Road, Shanghai 200032, China. Phone: 86-21-64175590; Fax: is caused by the dense stromal fibroinflammatory reaction of 86-21-64031446; E-mail: yuxianjun@fudanpciorg fibroblasts, which leads to a reduced nutrient and oxygen supply, doi: 10.1158/1078-0432.CCR-15-2380 resulting in a severe hypoxic tumor microenvironment (9, 10). To 2016 American Association for Cancer Research. adapt and survive in this hostile environment, cancer cells must

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downstream effector. FBW7 may reverse KRAS-driven metabol- Translational Relevance ic changes in pancreatic cancer. To assess the potential use of FBW7 in pancreatic cancer diagnosis and prognosis, we combined molecular imaging Materials and Methods technology (PET/CT) and immunohistochemistry to evaluate Cells and reagents the correlation between SUV and FBW7 expression levels. max The human pancreatic cancer cell lines with KRAS mutations, Our clinical and mechanistic findings indicate that FBW7 SW1990 and PANC-1, were obtained from the American Type regulates glucose metabolism through the effector TXNIP, Culture Collection. SW1990 cells were cultured in L-15 medium which predicted the poor prognosis of pancreatic cancer by supplemented with 10% FBS. PANC-1 cells were cultured in negatively regulating proliferation and glucose metabolism. DMEM supplemented with 10% FBS. All of the cell culture media Moreover, FBW7 regulated TXNIP expression through the E3 contained 100 U/mL penicillin and 100 mg/mL streptomycin. ubiquitin ligase substrate c-Myc. Overall, the dysregulation of The cell lines were authenticated by DNA fingerprinting in 2015 the FBW7/c-Myc/TXNIP pathway is a promising new target for and passaged in our laboratory fewer than 6 months after their novel therapeutic inhibitors to treat pancreatic cancer. Fur- receipt. Hypoxia mimetic conditions were chemically generated thermore, key signature enzymes of the glycolysis cascade, by treating cells with 200 mmol/L cobalt chloride (CoCl ; Sigma) such as GLUT1, GLUT4, HK2, and LDHA, are also candidate 2 for the indicated times. targets for combination treatment regimens. Therefore, our findings may have a critical impact on pancreatic cancer management and may apply to other aggressive and hetero- Tissue specimens geneous cancers. The 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 patient consent and approval from the Institutional Research Ethics rely on their ability to reprogram canonical metabolic pathways to Committee were obtained. Clinical information regarding the ensure that their needs for macromolecule synthesis and essential samples is presented in Supplementary Table S1. The pathologic energy demands are met (11, 12). Among these metabolic trans- grading was performed by two independent pathologists at our formations, glucose metabolism is the best studied. When cancer center. The correlation between FBW7 and TXNIP was analyzed c2 cells are exposed to hypoxia, they undergo a metabolic response in using the test. which glucose consumption is elevated and glycolytic pyruvate is 18 redirected to lactate. Such a response in cancer is known as aerobic Whole-body F-FDG PET/CT glycolysis, or the Warburg effect (13–15). Whole-body FDG PET/CT was performed as previously 18 Aberrant metabolism is considered to be one of the hallmarks described (24). Briefly, F-FDG was automatically made by a of cancer. The molecular mechanisms for the transformation of cyclotron (Siemens CTI RDS Eclipse ST) using an Explora FDG4 metabolism have been linked to the activation of oncogenes or module. Patients had been fasting for more than 6 hours. Scan- the loss-of-function of tumor suppressors, which ultimately lead ning started 1 hour after intravenous injection of the tracer (7.4 to the stabilization of HIF1a or the increased expression of the c- MBq/kg). The images were acquired on a Siemens biograph 16HR Myc oncogene. The transcription factors HIF1a and c-Myc PET/CT scanner with a transaxial intrinsic spatial resolution of 4.1 increased the expression of glycolytic genes, thereby enhancing mm. CT scanning was first initiated from the proximal thighs to glycolysis and lactate production (16–18). HIF1a and c-Myc are the head, with 120 kV, 80–250 mA, pitch 3.6, and rotation time of well-characterized regulators of metabolism and are reported to 0.5 seconds. Image interpretation was carried out on a multi- be downstream substrates of FBW7 (19–21). This prompted us to modality computer platform (Syngo; Siemens). Quantification of investigate whether FBW7 is a negative regulator of cancer cell metabolic activity was acquired using the SUV normalized to metabolism in pancreatic cancer. body weight, and the SUVmax for each lesion was calculated. An important clinical manifestation of the Warburg effect is the increased uptake of 2-[18F]fluoro-2-deoxy-D-glucose by Animal model cancer cells, as determined by PET scans, which is a common BALB/c-nu mice (female, 4 to 6 weeks of age, 18–20 g; Shanghai practice in cancer diagnosis (22, 23). Here, we show that FBW7 SLAC Laboratory Animal Co., Ltd.) were housed in sterile filter- expression was negatively correlated with PET/CT maximum capped cages. The left and right flanks of the mice were injected s.c. 6 m standardized uptake value (SUVmax)inpancreaticcancer with 4 10 cells in 100 L PBS. Six weeks after implantation, the patients, indicating that FBW7 might be a negative regulator mice were prepared for MicroPET/CT scanning. After scanning, of glucose metabolism. Furthermore, in vitro and in vivo experi- the tumors were surgically dissected. The tumor specimens were ments validated FBW7 as a negative regulator of glucose fixed in 4% paraformaldehyde. Samples were then processed for metabolism. Mechanistically, thioredoxin-binding protein histopathologic examination. All animal experiments were per- (TXNIP)isobservedtobeaFBW7target,accordingtoamRNA formed according to the guidelines for the care and use of expression profiling screen. TXNIP is a tumor suppressor and laboratory animals and were approved by the Institutional Ani- exerts its tumor-suppressive function by negatively regulating mal Care and Use Committee of Fudan University. glucose metabolism. Furthermore, TXNIP is a direct target gene of c-Myc, which is a FBW7 substrate and is regulated by FBW7 MicroPET/CT imaging in a c-Myc–dependent manner. Our study identifies FBW7 as a MicroPET/CT scans and image analyses were performed using negative regulator of glucose metabolism via the c-Myc/TXNIP an Inveon MicroPET/CT (Siemens Medical Solution). Each axis, thereby indicating that FBW7 is an important KRAS tumor-bearing mouse was injected with 11.1 MBq (300 mCi) of

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FBW7 Inhibits Glucose Metabolism in Pancreatic Cancer

18F-FDG via the tail vein. Scanning started 1 hour after injection. analysis settings and global scaling as normalization method by Animals were anesthetized with isoflurane during the scanning Partek Genomics Suite 6.6. Values presented are log2 RMA signal period. The images were reconstructed using three-dimensional intensity. The normalized data were further analyzed using one- ordered-subset expectation maximization (OSEM3D)/maximum way ANOVA to screen out the differentially expressed genes. Then, algorithm. Inveon Research Workplace was used to obtain the the Database for Annotation, Visualization and Integrated Dis- percentage injected dose per gram (%ID/g) and the SUVs. The covery (DAVID) was used to determine pathways and processes of SUVmax was calculated. major biologic significance and importance based on the Gene Ontology annotation function and Kyoto Encyclopedia of Genes Plasmids and Genomes pathway function. The microarray data were depos- The Flag-tagged coding sequences of human FBW7 and TXNIP ited in GEO under accession numbers GSE76443. were cloned into the lentiviral vector pCDH-CMV-MCS-EF1-puro (SBI) to generate FBW7 expression plasmids. The pLKO.1 TRC Western blot cloning vector (Addgene plasmid 10878) was used to generate c- Western blotting was carried out as previously described (8). Myc shRNA constructs. The 21-bp target against c-Myc was Briefly, whole-cell protein lysates were extracted. An antibody CCTGAGACAGATCAGCAACAA. against FBW7 was purchasedfromBethyl.ThePGC-1a antibody was purchased from Santa Cruz Biotechnology. The c-Myc Cell cycle and cell viability and HIF1a antibodies were obtained from Abcam. The TXNIP Flow cytometric analysis was conducted to examine cell-cycle antibody was produced by Proteintech. b-Actinwasusedasa status using propidium iodine (Invitrogen) and a human Annexin loading control. V-FITC kit (Invitrogen), respectively, according to the manufacturer's protocols. Cell viability was determined each day using Glycolysis analysis CCK-8 (Cell Counting Kit-8; Dojindo Laboratories) according to Glucose Uptake Colorimetric Assay Kits (Biovision) and Lac- the manufacturer's instructions. All observations were reproduced tate Colorimetric Assay Kits (Biovision) were purchased to exam- at least three times in independent experiments. ine the glycolysis process in pancreatic cancer cells, according to the manufacturer's protocols. Colony-formation assay Cells were seeded in triplicate in 6-well plates at an initial Oxygen consumption rate and extracellular acidification rate density of 500 cells/well. After 10 to 14 days, colonies were clearly Cellular mitochondrial function was measured using the visible, and the cells were fixed with 4% paraformaldehyde for 15 Seahorse XF Cell Mito stress test Kit and the Bioscience XF96 minutes at room temperature and stained with 4 mg/mL of crystal Extracellular Flux Analyzer, according to the manufacturer's violet (Sigma). The colonies containing more than 50 cells were instructions. The glycolytic capacity was determined using the counted using light microscopy. The average number of colonies Glycolysis Stress Test Kit as per the manufacturer's instructions. was determined from three independent experiments. Briefly, 4 104 cells were seeded onto 96-well plates and incubated overnight. After washing the cells with Seahorse Quantitative real-time PCR buffer (DMEM with phenol red containing 25 mmol/L glucose, Total RNA was extracted using TRIzol reagent (Invitrogen). 2 mmol/L sodium pyruvate, and 2 mmol/L glutamine), 175 mL cDNA was synthesized by reverse transcription using a TaKaRa of Seahorse buffer plus 25 mLeachof1mmol/L oligomycin, 1 PrimeScript RT reagent kit. The expression status of candidate mmol/L FCCP, and 1 mmol/L rotenone was automatically genes and b-actin were determined by quantitative real-time PCR injected to measure the oxygen consumption rate (OCR). Then, using an ABI 7900HT Real-Time PCR system (Applied Biosys- 25 mLeachof10mmol/Lglucose,1mmol/L oligomycin, and tems). All of the reactions were run in triplicate. Primer sequences 100 mmol/L 2-deoxy-glucose were added to measure the extra- are listed in Supplementary Table S2. cellular acidification rate (ECAR). The OCR and ECAR values were calculated after normalization to the cell number and are RNA extraction, ss-cDNA synthesis, and microarray analysis plotted as the mean SD. Total RNA from wild-type and FBW7-overexpressing SW1990 cells was extracted with TRIzol/chloroform and then purified with Analysis of ATP production magnetic beads from Agencourt Ampure (APN 000132; Beckman The ENLITEN ATP Assay System (Promega; FF2000) was used Coulter). Target preparation for microarray processing was carried according to the manufacturer's instructions. Cells were harvested out according to the GeneChip WT PLUS Reagent Kit. A total of by scraping and were resuspended in PBS. The cell suspension was 500 ng of RNA was used for a double-round of cDNA synthesis. divided into unequal aliquots. Part of the cell suspension was After fragmentation of second-cycle single-stranded cDNA (ss- mixed with 5% trichloroacetic acid (TCA). The remaining cells cDNA), the sample was labeled with biotin by terminal deox- were used for the cell number calculation. Tris-acetate buffer (pH ynucleotidyl transferase (TdT). Then, the sample was hybridized 7.75) was then added to neutralize the TCA and to dilute the TCA to the Affymetrix Human HTA2.0 Array for 16 to 18 hours at 45C. to a final concentration of 0.1%. The diluted sample (40 mL) was Following the hybridization, the microarrays were washed and added to an equal volume of rL/L reagent (Promega; FF2000). stained with streptavidin phycoerythrin on the Affymetrix Fluidics Then, luminescence was measured. The ATP standard (Promega; Station 450. The microarrays were scanned by using the Affyme- FF2000) was serially diluted to generate a regression curve for trix GeneChip Command Console (AGCC), which was installed calculating ATP concentrations in individual samples. The relative in the GeneChip Scanner3000 7G. The data were analyzed with ATP concentration was determined and normalized to that of the the Robust Multichip Analysis (RMA) algorithm using the default control cells, which was designated as 1. Three independent

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experiments were performed. The results are presented as the Results mean SD. FBW7 expression is negatively correlated with the 18F-FDG PET/ CT SUVmax value Measurement of mitochondrial membrane potential 18F-FDG PET/CT, which allows for the visualization of the The mitochondrial membrane potential assay Kit with JC-1 metabolic activity of viable tumor cells, has been widely used in (Beyotime Biotechnologies) was used to measure the alteration in the management of cancer diagnosis. The SUV has been widely Dy fl max the mitochondrial membrane potential ( m). Brie y, cells were used as a surrogate marker for the prognosis of numerous types of harvested by scraping and were resuspended in 0.5 mL of culture cancer, including pancreatic cancer (23, 25). To explore the medium. Next, 0.5 mL of JC-1 Staining Solution was added to the potential relationship between FBW7 and glucose metabolism, cell suspension. Then, the suspension was incubated for 20 fi we rst examined the correlation between the FBW7 IHC staining minutes at 37 CinaCO2 incubator. Next, the cells were collected and the PET/CT SUV value. As expected, patients with pan- max by centrifugation at 600 g for 4 minutes. The cells were washed creatic cancer with decreased expression of FBW7 exhibited a twice with 1 mL of JC-1 Staining Buffer. Subsequently, 500 mLof higher SUVmax value (Fig. 1A), and the correlation is statistically JC-1 Staining Buffer was added to the cell pellet in each tube, and significant (Fig. 1B). These results indicate that FBW7 plays an the cells were thoroughly resuspended. The samples were imme- inhibitory role in glucose metabolism in pancreatic cancer. diately analyzed using flow cytometry. In healthy cells, JC-1 forms mitochondrial aggregates, which emit red fluorescence at 595 nm when excited at 525 nm. However, after the loss of Dym, JC-1 FBW7 inhibits glucose metabolism in pancreatic cancer cells remains as monomers that emit green fluorescence at 525 nm Glucose metabolism in cancer relies on a series of enzymatic 18 when excited at 485 nm. Mitochondrial depolarization is indi- reactions (Fig. 2A). Clinically, in cancer diagnosis, F-FDG PET/ fl cated by a decrease in the red/green fluorescence intensity ratio. CT re ects glucose turnover in the tumor lesion. A higher SUVmax value implies an increased glucose metabolic activity in the lesion. To determine the impact of FBW7 expression on cellular metab- Chromatin immunoprecipitation assay olism, we constructed PANC-1 and SW1990 stable cell lines Chromatin immunoprecipitation (ChIP) assays were per- ectopically expressing wild-type FBW7 (Fig. 2B). First, we exam- formed using the EZ-ChIP Kit from Millipore according to the ined glucose uptake and lactate production, two primary indica- manufacturer's protocol. Primers to detect TXNIP promoter occu- tors of the Warburg effect. As expected, FBW7 decreased glucose pancy were: F: 50-CAGAGCGCAACAACCATT-30 and R: 50- uptake and lactate production, indicating its inhibitory role in AGGCTCGTGCTGCCCTCGTGCAC-30. glycolysis (Fig. 2C and D). The ECAR is another measurement of glucose metabolism and reflects the lactic acid–induced acidifi- siRNA treatments cation of the medium surrounding cancer cells. FBW7 decreased siRNA duplexes against c-Myc and FBW7 were transfected the ECAR in PANC-1 and SW1990 cells and may play an inhib- into pancreatic cancer cells using Lipofectamine 2000 (Invitro- itory role in lactic acid formed during glycolysis (Fig. 2E). gen). The siRNA duplex sense sequences were as follows: si-FBW7- In addition, cellular oxygen consumption reflects mitochon- – 0 0 – 0 1 5 -ACCTTCTCTGGAGAGAGAAATGC-3 , si-FBW7-2 5 -GTGT- drial respiration and can be measured by the OCR. PANC-1 and 0 – 0 GGA ATGCAGAGACTGGAGA-3 ; si-c-Myc-1 5 -CCTGAGACA- SW1990 cells overexpressing FBW7 exhibited lower OCRs, indi- GATCAGCAACAA-30, si-c-Myc-2–50-CAGTTGAAACACAAACTT- 0 cating that FBW7 is a negative regulator of basal mitochondrial GAA-3 . respiration (Fig. 2F). Moreover, cancer cells rely on glucose metabolism for ATP production, which meets the demands of Statistical analysis rapid proliferation and metastasis. We then analyzed the impact All data are presented as the mean SD. Experiments were of FBW7 on ATP production. Consistently, FBW7 decreased ATP repeated at least three times. Two-tailed unpaired Student t tests production in PANC-1 and SW1990 cells (Fig. 2G). Furthermore, and one-way analysis of variance were used to evaluate the data. the mitochondrial membrane potential, which is used to evaluate SPSS version 16.0 software (IBM) was used for the data analysis. early apoptosis, reflects the mitochondrial integrity and varies Differences were considered significant at , P < 0.05; , P < 0.01; according to the metabolic state. FBW7 decreased the mitochon- and , P < 0.001. drial potential of PANC-1 and SW1990 cells, indicating that FBW7 A B 15

Figure 1. Statistical analysis of the correlation 10 between FBW7 expression and the 18F-

max FDG PET/CT SUVmax. A, representative 18F-FDG PET/CT imaging of PDAC

SUV patients with low or high FBW7 5 expression (magniﬁcation scale bar, 20 mm). B, analysis of the SUVmax in FBW7low and FBW7high groups (n ¼ 60; P < 0.001). 0

FBW7 Low FBW7 High FBW7 Low FBW7 High

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FBW7 Inhibits Glucose Metabolism in Pancreatic Cancer

A B PANC-1 SW1990 Glucose Lactate ControlFBW7FLAG Control FBW7FLAG FLAG FLAG

Glut 1/4 b-Actin b-Actin

H2O NADPH GSSG

Glucose H2O C Glucose D Lactate ATP NAD+ GSH 120 120 HK2 Control Control ADP FBW7 FBW7 Catalase G6P SOD2 O -HO 2 2 2 80 80

F6P ADP 40 40 TCA Cycle PFKL

ATP Relative activity (%) Relative activity (%) F1,6P Lactate 0 0 NAD+ PANC-1 SW1990 PANC-1 SW1990 GAPDH LDH A/B NADPH E PANC-1 SW1990 GA3P Pyruvate Acetyl-CoA Control + 270 Control 400 NAD FBW7 ATP FBW7 PKM 1/2 Glucose

NADPH cells) Glucose cells) ADP 5 5 300 1,3-BPGA PEP 180

PGK 1 ENO 1/2 200

90 Oligomycin 3-PGA 2-PGA 100 Oligomycin 2-DG 2-DG ADP ATP ECAR (mpH/min/10 0 ECAR (mpH/min/10 0 0204060 80 0 20 40 60 80 Time (min) Time (min)

FCCP Rotenone GH F PANC-1 FCCP SW1990 Rotenone 1,200 Control 1,000 Control 1.2 1.2 Control Control FBW7 FBW7 FBW7 FBW7 cells) cells) 5 750 Oligomycin 5 Oligomycin 800 0.8 0.8 500

400 0.4 0.4 250 OCR (pMol/min/10 Relative ATP production Relative ATP OCR (pMol/min/10

0 0 JC-1 aggregates/monomer 0 20 40 60 80 0 20 40 60 80 0.0 0.0 Time (min) Time (min) PANC-1 SW1990 PANC-1 SW1990

PANC-1 I 1.2 1.2 SW1990 Control Control FBW7 FBW7 0.8 0.8

0.4 0.4 Relative mRNA expression

Relative mRNA expression 0.0 0.0 GLUT1 GLUT4 HK2 LDHA LDHB GLUT1 GLUT4 HK2 LDHA LDHB

Figure 2. FBW7 is a negative regulator of glucose metabolism in pancreatic cancer. A, schematic representation of glucose metabolism in cancer cells. B, overexpression of FLAG-tagged FBW7 in PANC-1 and SW1990 cells. C, FBW7 inhibits glucose uptake in PANC-1 and SW1990 cancer cells. D, FBW7 reduced lactate production via glycolysis in PDAC cells. E, ECAR, an indicator of glycolysis, was reduced in the presence of FBW7 expression. F, OCR, which reﬂects mitochondrial respiration, was decreased in FBW7-overexpressing PANC-1 and SW1990 cancer cells. G, FBW7 decreased ATP production. H, mitochondrial potential decreased in the presence of FBW7 overexpression. I, FBW7 decreased the expression of rate-limiting glycolytic enzymes. also functions as a negative regulator of mitochondrial glucose presence of FBW7 overexpression (Supplementary Fig. S1A and metabolism (Fig. 2H). To further explore the role of FBW7 in S1B). Taken together, these results suggest that FBW7 plays a vital glucose metabolism, key signature enzymes of the glycolysis role in pancreatic cancer cell glucose metabolism. cascade were examined. Enzymes related to glucose transportation, such as GLUT1, GLUT4, HK2, LDHA, and LDHB, were FBW7 decreases glucose utilization in a xenograft model decreased in FBW7-overexpressing PDAC cells (Fig. 2I). In addi- To further conﬁrm the in vitro phenotype of FBW7 in glucose tion, the levels of other glycolytic enzymes decreased in the metabolism, we subcutaneously injected nude mice with FBW7-

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A BCD

) 2,500 Control 1.4 3 2,000 FBW7 1.2 1,500 1.0 0.8 1,000 FBW7 max 0.6 500 Control SUV 0.4 Left - Control 0 Right - FBW7 size (mm Tumor 1 234 5 0.2 Weeks after tumor implantation 0.0 Control FBW7

E FBW7 GLUT1 GLUT4 HK2 LDHA LDHB

Control

FBW7

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/CT imaging 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 FBW7 group 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 formed by FBW7 overexpression in SW1990 cells.

overexpressing SW1990 cells. As expected, ectopic FBW7 inhib- elevated in FBW7-overexpressing xenograft tumors (Fig. 4E). ited tumor growth in the xenograft mouse model (Fig. 3A and B). Next, we examined the correlation between FBW7 and TXNIP Furthermore, we used a small animal imaging system to evaluate expression in tissues from PDAC patients and observed a positive the role of FBW7 in glucose metabolism (Fig. 3C). The results correlation between FBW7 and TXNIP (Fig. 4F and Supplemen- indicated that FBW7 significantly inhibited 18F-FDG uptake in the tary Table S3). Together, these data strongly suggest that TXNIP is a in vivo xenograft model (Fig. 3D). Subsequent immunohis- potential FBW7 target in pancreatic cancer. tochemistry using antibodies against GLUT1, GLUT4, HK2, LDHA, and LDHB demonstrated that the expression of these glycolytic enzymes was significantly decreased in tissues from TXNIP is a negative regulator of glucose metabolism xenograft tumors (Fig. 3E), which was consistent with previous Although TXNIP is a negative regulator of glucose metabolism results. in many types of cancer cells, its role in pancreatic cancer has not been previously investigated. In the present study, we found that TXNIP expression is inversely correlated with the SUVmax value TXNIP is a target of FBW7 in PDAC (Fig. 5A). To determine the impact of FBW7 expression on cellular Next, to search for a possible molecular mechanism underlying metabolism, we generated PANC-1 and SW1990 stable cell lines the FBW7-mediated regulation of glucose metabolism, we used a ectopically expressing wild-type TXNIP (Fig. 5B). A subsequent high-throughput gene expression profiling array and found that a analysis indicated that TXNIP inhibited glucose uptake and lactate series of signaling pathways were altered by FBW7 overexpression production in PANC-1 and SW1990 cells (Fig. 5C and D). The (GEO: accession numbers GSE76443). Among the differentially ECAR and OCR results measured using the Seahorse metabolism expressed genes, FOXO1 and TXNIP are well-established regula- analyzers further validated that TXNIP is a negative regulator of tors of glucose metabolism (26–28). Further validation using two glycolysis and mitochondrial respiration (Fig. 5E and F). ATP cell lines indicated that FBW7 overexpression significantly altered production also decreased upon TXNIP overexpression (Fig. 5G). TXNIP expression (Fig. 4A) but had little impact on FOXO1 Furthermore, it was demonstrated that TXNIP decreased mito- expression (Supplementary Fig. S1C). We hypothesized that chondrial potential in PDAC cell lines (Fig. 5H). Accordingly, the TXNIP was a potential effector of FBW7 in the regulation of expression of glycolytic enzymes related to glucose metabolism glucose metabolism. To test this hypothesis, we examined the decreased dramatically after TXNIP overexpression (Fig. 5I and J; expression of TXNIP protein by immunoblotting after overexpres- Supplementary Fig. S2A and S2B). These results confirm that sion of FBW7 in two pancreatic cancer cell lines. TXNIP protein TXNIP inhibits glucose metabolism in pancreatic cancer. levels increased following FBW7 overexpression (Fig. 4B). On the We then examined the influence of TXNIP on pancreatic cancer contrary, downregulation of endogenous FBW7 by siRNA con- cell proliferation. As expected, a CCK8 proliferation assay indi- structs significantly decreased the abundance of TXNIP in these cated that TXNIP decreased the proliferation rate of PANC-1 and two cells (Fig. 4C and D). Moreover, IHC staining for TXNIP was SW1990 cells (Fig. 5K). A subsequent colony-formation assay

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demonstrated that TXNIP inhibited the colony-forming capacity pancreatic cancer cells (Fig. 6A). The promoter region of TXNIP of PDAC cancer cells (Supplementary Fig. S2C and S2D). Cell- was reported to harbor E-box elements, which consist of the CAC cycle analyses indicated that overexpression of TXNIP inhibited (G/A)TG nucleotide sequence (27; Fig. 6B). We cloned the pro- cell-cycle progression and arrested the cell cycle at the G2–M phase moter region of TXNIP into the pGL3-basic vector and performed (Supplementary Fig. S2E). In clinical specimens, we measured a dual luciferase assay to investigate whether c-Myc influences TXNIP expression using an IHC tissue microarray of PDAC TXNIP promoter activity. The results indicated that cotransfection samples and found that decreased TXNIP expression predicts a with c-Myc inhibited TXNIP promoter activity, whereas cotrans- poor PDAC prognosis (Fig. 5L and Supplementary Fig. S2F and fection with siRNA against c-Myc significantly increased TXNIP S2G). Finally, we silenced TXNIP in FBW7-overexpressing PANC- promoter activity (Fig. 6C). Moreover, c-Myc occupied the E- 1 and SW1990 cells, and we found that TXNIP knockdown could boxes in the TXNIP promoter region, as determined by ChIP reverse the effects of FBW7 overexpressing in vitro, including assay (Fig. 6D). These findings suggest that c-Myc functions as a proliferation and glucose metabolism inhibition (Supplementary promoter of TXNIP transcription, which is consistent with obser- Fig. S3). Thus, we believe that TXNIP is an important downstream vations from the study of triple-negative breast cancer (27). effector of FBW7 in regulating glucose metabolism. To validate whether FBW7 regulated TXNIP expression in a c- Myc–dependent manner, we generated a dominant-negative FBW7 regulates TXNIP expression in a c-Myc–dependent FBW7 mutant, R465H, and designated it FBW7R465H. Compared manner with wild-type FBW7, FBW7R465H only marginally increased FBW7 is an E3 ubiquitin ligase and targets many substrates for TXNIP expression (Fig. 6E and F). Consistent with this observa- proteasomal degradation. Among these substrates, HIF1a, tion, TXNIP promoter activity and protein level both decreased PGC1a, and c-Myc are well-known regulators of metabolism. We with the expression of FBW7R465H (Fig. 6G). Furthermore, ChIP previously reported that the expression of c-Myc decreased dra- assay demonstrated that the introduction of FBW7 decreased c- matically when FBW7 was overexpressed in pancreatic cancer (8). Myc occupancy in the TXNIP promoter region, whereas However, no change in the expression of PGC1a or HIF1a was FBW7R465H had little impact (Fig. 6H). Taken together, these observed upon FBW7 upregulation in pancreatic cancer. There- results demonstrate that FBW7 inhibits glucose reprogramming fore, we investigated the role of c-Myc in pancreatic cancer cell in pancreatic cancer via the c-Myc/TXNIP axis. These results glucose metabolism and confirmed that c-Myc also promoted provide data regarding a novel function of FBW7 in PDAC glucose glucose metabolism in pancreatic cancer (Supplementary Fig. S4). metabolism and indicate that FBW7 is a potential marker for To determine whether FBW7 regulates TXNIP through c-Myc, we pancreatic cancer diagnosis and prognosis and a target for pan- first examined the TXNIP protein level in siRNA-transfected creatic cancer treatment (Fig. 6I).

AB PANC-1 SW1990 PANC-1 SW1990 12 5 Control FBW7 Control FBW7 4 TXNIP TXNIP 8 3 1 3.87 1 2.76 b-Actin b-Actin Figure 4. 2 mRNA 4 mRNA Screening for FBW7 effector proteins

Relative TXNIP Relative TXNIP 1 in glucose metabolism regulation. A, transcription of TXNIP, a major 0 0 Control FBW7 Control FBW7 redox and glucose metabolism regulator, increased with FBW7 CDPANC-1 SW1990 overexpression in cancer cells. B, 1.2 NC FBW7 increased the TXNIP protein NC si-FBW7-1si-FBW7-2 NC si-FBW7-1si-FBW7-2 si-FBW7-1 level. C, PANC-1 and SW1990 cells si-FBW7-2 FBW7 FBW7 0.8 were transfected with indicated siRNA 110.7 0.6 0.60.5 vectors; transcription level of FBW7 TXNIP TXNIP was detected. D, cell lysates were 0.4 collected, and immunoblots were Relative FBW7 mRNA expression b-Actin b-Actin performed with the indicated 0.0 antibodies. FBW7 silencing also PANC-1 SW1990 decreased the TXNIP protein level. E, Low High TXNIP was decreased in xenograft EF mouse tumors formed by FBW7 overexpression (magniﬁcation scale Control FBW7 bar, 40 mm). F, TXNIP and FBW7 expression showed a positive FBW7 correlation in PDAC patient samples (magniﬁcation scale bar, 40 mm). TXNIP TXNIP

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A B 15

PANC-1 SW1990 10 Control TXNIPFLAG Control TXNIPFLAG max FLAG FLAG SUV 5 b-Actin b-Actin

0 TXNIP Low TXNIP High

C DE Glucose Lactate PANC-1 SW1990 120 120 Control Control 270 Control 400 Control TXNIP TXNIP TXNIP TXNIP cells) cells) 5 Glucose 5 Glucose 300 80 80 180 200

40 40 90 Oligomycin 100 2-DG Oligomycin 2-DG Relative activity (%) Relative activity (%) 0 000 ECAR (mpH/min/10 PANC-1 SW1990 PANC-1 SW1990 ECAR (mpH/min/10 0 20 40 60 80 0 20 40 60 80 Time (min) Time (min) F GH PANC-1FCCP SW1990 Rotenone FCCP 1.2 1.2 1,200 Control 1,000 Control Rotenone Control Control TXNIP TXNIP TXNIP TXNIP cells) cells) 5 5 Oligomycin750 Oligomycin 0.8 0.8 800 500 400 0.4 0.4 250

0 0 production Relative ATP 0.0 0.0 OCR (pMol/min/10 OCR (pMol/min/10 0 20 40 60 80 0204060 80 PANC-1 SW1990 JC-1 aggregates/monomer PANC-1 SW1990 Time (min) Time (min) IJ SW1990 1.2 PANC-1 1.2 Control Control TXNIP TXNIP 0.8 0.8

0.4 0.4

0.0 0.0 Relative mRNA expression GLUT1 GLUT4 HK2 LDHA LDHBRelative mRNA expression GLUT1 GLUT4 HK2 LDHA LDHB KL 1.0 4 PANC-1 pCDH 4 SW1990-pCDH High TXNIP PANC-1 TXNIP SW1990-TXNIP 0.8 Low TXNIP 3 3 0.6 2 2 0.4 n = 25 n = 61 1 1 0.2

Overall survival P < 0.001 0 0 0.0 Relative cell viability Relative cell viability 0 1234 01234 0.00 10.00 20.00 30.00 40.00 50.00 Time after passage (days) Time after passage (days) Time (months)

Figure 5. low high TXNIP negatively regulates glucose metabolism and proliferation in pancreatic cancer. A, analysis of the SUVmax in TXNIP and TXNIP groups (n ¼ 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, lactate production was lower in the TXNIP-overexpressing PDAC cells. E, TXNIP negatively regulated the glycolysis rate, reﬂected by the ECAR. F, TXNIP inhibited the OCR. G, TXNIP decreased ATP production in PANC-1 and SW1990 cells. H, mitochondrial potential was decreased upon TXNIP overexpression. I, TXNIP led to changes 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 enzymes of the glycolysis cascade in SW1990 cells. K, TXNIP inhibited cell proliferation as measured by a CCK-8 proliferation kit. L, Kaplan–Meier analysis of the overall survival rate of patients with pancreatic cancer, according to TXNIP expression (n ¼ 86; P < 0.001, log-rank test).

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FBW7 Inhibits Glucose Metabolism in Pancreatic Cancer

A B PANC-1 SW1990 E-Box TS NC si-Myc#1si-Myc#2 NC si-Myc#1si-Myc#2 Luc TXNIP TXNIP –2,000 +1 +220 c-Myc c-Myc TXNIP promoter b-Actin b-Actin

D Input IgG c-Myc C PANC-1 PANC-1 SW1990 2.0 3.5 SW1990

1.5 2.8 2.1 E PANC-1 SW1990 1.0 1.4 3.5 3.5

0.5 0.7 2.8 2.8

0.0 0.0 2.1 2.1 Relative luciferase activity Relative luciferase Relative luciferase activity Relative luciferase pGL3-TXNIP+++ pGL3-TXNIP +++ 1.4 1.4 – + – – + – Myc Myc Relative TXNIP

0.7 Relative TXNIP 0.7 mRNA expression

si-Myc –– + si-Myc –– + mRNA expression 0.0 0.0 WT WT R465H R465H F ControlFBW7FBW7 ControlFBW7FBW7 PANC-1 SW1990

WT R465H WT R465H EV FBW7FBW7 EV FBW7FBW7 H TXNIP TXNIP PANC-1 SW1990 11.8 1.5 1 2.2 1.6 WT R465H WT R465H c-Myc c-Myc EV FBW7 FBW7 EV FBW7 FBW7 FBW7 FBW7 c-Myc c-Myc b b -Actin -Actin IgG IgG Input Input G PANC-1 SW1990 I 2.0 1.8 FBW7 1.5 1.2 1.0 c-Myc 0.6 0.5

TXNIP 0.0 0.0 Relative luciferase activity Relative luciferase activity Relative luciferase pGL3-TXNIP +++ pGL3-TXNIP +++ Warburg Mitochondrial Oncogenesis WT FBW7 – + – FBW7WT – + – effect respiration of PDAC FBW7R465H ––+ FBW7R465H ––+

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 in the 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 a si- 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 ligase activity and was designated as FBW7R465H, had little influence on TXNIP transcription compared with its wild-type counterpart. F, FBW7R465H, which lost the capacity to regulate c-Myc protein levels, exerted no significant impact on TXNIP protein levels, indicating that FBW7 regulated TXNIP expression in a c-Myc–dependent manner. G, FBW7R465H exerted little impact on TXNIP promoter activity compared with its wild-type counterpart. H, FBW7 decreased c-Myc occupancy of the TXNIP promoter, whereas the FBW7 mutant had little influence in PANC-1 and SW1990 cells. I, proposed model of the mechanism of FBW7-mediated regulation of glucose metabolism via the c-Myc/TXNIP axis in pancreatic cancer.

Discussion dent ATP production to fuel mitochondrial respiration, Otto Based on the observation that even in the presence of an oxygen Warburg put forward the notion of the "Warburg effect" in the supply, tumor cells preferentially use glycolysis over mitochon- 1920s (29). Advances in the understanding of the biology of drial oxidative phosphorylation (OXPHOS) for glucose-depen- tumor progression and metastasis have clearly highlighted the

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importance of aberrant tumor metabolism. The manifestation of individual genes. We previously found that c-Myc expression the Warburg effect in today's clinical setting is the use of 18F-FDG decreased dramatically upon FBW7 upregulation, whereas no to detect tumors with an increased glucose uptake. The elevated reduction was observed in PGC-1a expression (8). Here, we again uptake visualized by 18F-FDG PET/CT correlates with a poor measured HIF1a levels and observed no alteration. c-Myc is a prognosis and a higher metabolic burden in many types of tumors multifunctional transcription factor that drives the multiple syn- (23, 30). thetic functions necessary for rapid cell division and simulta- Mounting evidence indicates that the reprogramming of tumor neously inhibits the expression of genes with antiproliferative metabolism is controlled by various oncogenic signals (31, 32). In functions (40). Intriguingly, multiple studies have demonstrated pancreatic cancer, the Ras oncoprotein has been shown to pro- that c-Myc can directly bind to the promoters of thousands of mote metabolic transformation (33–35). Although KRAS muta- genes—up to 30% of all known genes (41). In addition, many of tions were detected in >90% of PDAC patients and were proposed the metabolic changes that occur in transformed cells are driven to be initiators of PDAC, KRAS remains an undruggable target. by c-Myc overexpression (40). Thus, we proposed that FBW7 Elevated oncogenic KRAS activity stimulates many downstream might regulate TXNIP in a c-Myc–dependent manner. To test this, signaling pathways (36–37). Therefore, strategies targeting the we first investigated whether TXNIP expression changed in downstream effectors of KRAS might provide solutions to the response to c-Myc downregulation. We found that c-Myc could inhibition of certain metabolic pathways. Our previous study suppress TXNIP promoter activity and inhibit TXNIP expression. reported that ERK activation caused by KRAS mutation in PDAC These findings were consistent with a previous report that c-Myc resulted in the destabilization of FBW7 (8). However, the specific could function as a promoter of TXNIP transcription. Finally, we role of FBW7 in PDAC remains unclear. validated that FBW7 regulated TXNIP expression in a c-Myc– In the present study, we first provided clinical evidence that dependent fashion by generating a FBW7 mutant that lost its FBW7 expression affects glucose metabolism in PDAC with PET/ E3 ligase activity. CT data. We then used a series of aerobic glycolysis-related In conclusion, we demonstrated a novel role of FBW7 in assays, including the examination of glucose uptake, lactate glucose metabolism in pancreatic cancer. Mechanistically, FBW7 production, OCR, ECAR, and ATP production, and mitochondrial regulates TXNIP expression in a c-Myc–dependent manner. membrane potential. Overexpression of FBW7 dramatically Thus far, therapeutic strategies directly targeting KRAS or c-Myc inhibited glucose metabolism in PDAC cells. We confirmed these have proven to be technically difficult. Therefore, alternative results in an in vivo xenograft model. All the enzymes related to approaches that focus on interfering with c-Myc–mediated down- glucose transportation (GLUT1, GLUT4, HK2, LDHA, and LDHB) stream effectors might provide novel therapeutic avenues for decreased dramatically in the FBW7-overexpressing PDAC cells PDAC. compared with the control cells. Given the important role of fl FBW7 in PDAC glucose metabolism, we further explored the Disclosure of Potential Con icts of Interest fl potential underlying mechanism. No potential con icts of interest were disclosed. FBW7 has been reported to repress synthesis of cholesterol Authors' Contributions and fatty acids lipid homeostasis through modulating SREBPs Conception and design: S. Ji, Y. Qin, J. Xu, Q. Ni, M. Li, X. Yu stability directly (38). However, the role of FBW7 in glucose Development of methodology: S. Ji, Y. Qin, C. Liang, R. Huang, S. Shi, J. Liu, transformation has seldom been studied. To investigate wheth- K. Jin, D. Liang, W. Xu, Q. Ni, X. Yu er FBW7 could affect the downstream expression of glycolysis- Acquisition of data (provided animals, acquired and managed patients, related genes, we performed high-throughput screening to provided facilities, etc.): S. Ji, Y. Qin, R. Huang, S. Shi, J. Liu, K. Jin, D. Liang, identify possible genes necessary for the coordinate regulation W. Xu, L. Liu, C. Liu, X. Yu of FBW7-mediated glucose metabolism. Interestingly, the Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): C. Liang, M. Li, X. Yu expression levels of many glycolysis-related genes were altered Writing, review, and/or revision of the manuscript: S. Ji, Y. Qin, J. Xu, Q. Ni, upon the upregulation of FBW7. Among the altered glycolysis- M. Li, X. Yu related genes in the database, we selected TXNIP as the target Administrative, technical, or material support (i.e., reporting or organizing gene and investigated whether FBW7 regulates glycolysis via data, constructing databases): C. Liang, S. Shi, B. Zhang, J. Xu, X. Yu TXNIP in PDAC. TXNIP has been identified as a tumor sup- Study supervision: X. Yu pressor gene in various solid tumors and hematologic malig- Other (my lab provided some reagents from our unique GEMM): P.J. Chiao nancies (27). Moreover, recent evidence indicates that TXNIP Acknowledgments also functions as a potent negative regulator of glucose uptake The authors thank Huanyu Xia for assistance in collecting the patient data. and aerobic glycolysis. We confirmed these results using q-PCR and Western blot analysis, which demonstrated that the mRNA and protein levels of TXNIP in FBW7-transfected PDAC cells Grant Support fi were signi cantly higher than those in control cells, indicating This work was supported by National Natural Science Foundation that TXNIP was regulated by FBW7, predominantly via tran- (81372651, 81201900, 81172276, and 81101565), Sino-German Center scriptional modifications. (GZ857), Ph.D. Programs Foundation of Ministry of Education of China FBW7 has been reported to function as a tumor suppressor by (20120071120104), and Program of Science and Technology Commission of targeting multiple oncoprotein substrates, such as cyclin E, c-Myc, Shanghai (13431900105 and 13DZ1942802). The costs of publication of this article were defrayed in part by the payment of c-Jun, PGC-1a, HIF1a, and Mcl-1, for degradation (6). Among the a a page charges. This article must therefore be hereby marked advertisement in known substrates of FBW7, HIF1 , PGC-1 , and c-Myc have been accordance with 18 U.S.C. Section 1734 solely to indicate this fact. reported to play critical roles in the regulation of metabolism (16, 39, and 17). These three substrates are also important transcrip- Received October 1, 2015; revised February 17, 2016; accepted March 7, 2016; tion factors responsible for activating or repressing downstream published OnlineFirst March 16, 2016.

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FBW7 (F-box and WD Repeat Domain-Containing 7) Negatively Regulates Glucose Metabolism by Targeting the c-Myc/TXNIP (Thioredoxin-Binding Protein) Axis in Pancreatic Cancer

Shunrong Ji, Yi Qin, Chen Liang, et al.

Clin Cancer Res Published OnlineFirst March 16, 2016.

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