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CANCER RESEARCH | TRANSLATIONAL SCIENCE

Inactivation of the AMPK–GATA3–ECHS1 PathwayInduces Fatty Acid Synthesis That Promotes Clear CellRenal Cell Carcinoma Growth A C

Yuan-YuanQu1,2,3, Rui Zhao1, Hai-LiangZhang1,3, Qian Zhou1, Fu-JiangXu1,3, Xuan Zhang2,Wen-HaoXu1,3,Ning Shao1,3, Shu-Xian Zhou1,2, Bo Dai1,3, Yao Zhu1,3, Guo-Hai Shi1,3, Yi-Jun Shen1,3, Yi-Ping Zhu1,3,Cheng-Tao Han1,3, Kun Chang1,3, Yan Lin1,2,4, Wei-Dong Zang5, Wei Xu1,2,4, Ding-Wei Ye1,3,Shi-Min Zhao1,2,4, and Jian-Yuan Zhao1,2,4

ABSTRACT◥

The tumorigenic role and underlying mechanisms of lipid accu-mulation, commonly observed in many cancers, remain insuffi-ciently understood. In this study, we identified an AMP-activatedprotein kinase (AMPK)–GATA-binding protein 3 (GATA3)–enoyl-CoA hydratase short-chain 1 (ECHS1) pathway that induceslipid accumulation and promotes cell proliferation in clear cell renalcell carcinoma (ccRCC). Decreased expression of ECHS1, which isresponsible for inactivation of fatty acid (FA) oxidation and acti-vation of de novo FA synthesis, positively associated with ccRCCprogression and predicted poor patient survival. Mechanistically,ECHS1 downregulation induced FA and branched-chain aminoacid (BCAA) accumulation, which inhibited AMPK-promoted

expression of GATA3, a transcriptional activator of ECHS1. BCAAaccumulation induced activation of mTORC1 and de novo FAsynthesis, and promoted cell proliferation. Furthermore, GATA3expression phenocopied ECHS1 in predicting ccRCC progressionand patient survival. The AMPK–GATA3–ECHS1 pathway mayoffer new therapeutic approaches and prognostic assessment forccRCC in the clinic.

Significance: These findings uncover molecular mechanismsunderlying lipid accumulation in ccRCC, suggesting the AMPK–GATA3–ECHS1 pathway as a potential therapeutic target andprognostic biomarker.

IntroductionRecently, dysregulated fatty acid (FA) metabolism has been

observed in many types of cancers, including renal cell carcinoma,breast cancer, prostate cancer, and lung cancer (1–5). The relevance ofFA metabolism to cancer cell functioning, alongside that of perturbedglucose metabolism—known as the Warburg effect—and alteredamino acid metabolism, which is represented by glutamine metabo-lism, is becoming increasingly recognized.

Clear cell renal cell carcinoma (ccRCC), which accounts for approx-imately 80% of diagnosed RCCs, exhibits intracellular lipid dropletaccumulation and is closely related to aberrant FAmetabolism. In fact,

obesity is a well-established independent risk factor of ccRCC (6–9).Weight gain is also associated with increased ccRCC risk (6), as areincreased body mass index (7) and high dietary intake of saturated fat,animal fat, or oleic acid (10). Excess lipids in cancer cells are stored inlipid droplets, and high levels of lipid droplets are currently considereda hallmark of cancer aggressiveness (11–14). The histologic appear-ance of ccRCC cells, i.e., their clear cytoplasm, is due to lipid accu-mulation (15) and suggests that metabolic reprogramming may occurduring ccRCC development. Furthermore, gene expression profilinghas revealed that the expression of FA synthesis genes, such as acetyl-CoA carboxylase (ACC) and fatty acid synthase (FASN; refs. 3, 16), issignificantly increased in ccRCC, indicating enhanced de novo FAsynthesis in ccRCC. In addition, AMP-activated protein kinase(AMPK), themaster sensor of cellular energy balance (17, 18), inhibitsde novo FA synthesis and lipid accumulation through inhibitoryphosphorylation of ACC, thus maintaining cellular energy homeo-stasis and protecting cells from metabolic stress (19). Loss of AMPKactivity, which is frequently observed in ccRCC (3, 20), is correlatedwith enhanced de novo FA synthesis and lipid accumulation (20).

Although evidence suggests a causative role of FA accumulation inccRCC occurrence and development, the underlying mechanismsremain unclear. Most importantly, besides abnormal FA synthesis,the relevance of FA oxidation (FAO) in FA accumulation and cancercell function is unknown. Aberrant activation of mTORC1, which canbe induced by intracellular elevation of branched-chain amino acids(BCAA), especially leucine, is frequently observed in ccRCC (21–23).Our previous study revealed the existence of cross-talk between BCAAmetabolism and FAO via a reaction catalyzed by enoyl-CoA hydrataseshort-chain 1 (ECHS1; ref. 24). Therefore, dysregulated FAO can affectFA and protein synthesis simultaneously.

In this study, we found that ECHS1 expression is nearly absent inccRCC tumors, and its absence predicted poor patient survival. Inclinical samples, animal models, and cultured cells, we validated that

1Department of Urology, Fudan University Shanghai Cancer Center, the Obstet-rics and Gynecology Hospital of Fudan University, State Key Lab of GeneticEngineering and School of Life Sciences, Fudan University, Shanghai, P.R. China.2Key Laboratory of Reproduction Regulation of NPFPC, Institutes of BiomedicalSciences and Collaborative Innovation Center of Genetics and Development,Fudan University, Shanghai, P.R. China. 3Department of Oncology, ShanghaiMedical College, Fudan University, Shanghai, P.R. China. 4Collaborative Inno-vation Center for Biotherapy,West China Hospital, SichuanUniversity, Chengdu,P.R. China. 5School of Basic Medical Sciences, Zhengzhou University,Zhengzhou, P.R. China.

Note: Supplementary data for this article are available at Cancer ResearchOnline (http://cancerres.aacrjournals.org/).

Y.-Y. Qu, R. Zhao, and H.-L. Zhang contributed equally to this article.

CorrespondingAuthors: Jian-YuanZhao, FudanUniversity, 2005 SonghuRoad,Shanghai 200433, China. Phone: 86-21-31246782; Fax: 86-21-31246782; E-mail:[email protected]; Ding-Wei Ye, [email protected]; and Shi-Min Zhao,[email protected]

Cancer Res 2020;80:319–33

doi: 10.1158/0008-5472.CAN-19-1023

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ECHS1 is regulated by the AMPK–GATA-binding protein 3 (GATA3)pathway, and ECHS1 downregulation could inhibit AMPK via FAaccumulation. Analysis of the pathologicmechanism revealed that lossof ECHS1 results in FAO block BCAA-mediated mTORC1 activationand mTORC1 activation–induced de novo FA synthesis, thus pro-moting cancer cell proliferation.

Materials and MethodsReagents and antibodies

AICAR (#A9978) and rapamycin (#553210) were purchased fromSigma-Aldrich. Palmitic acid (1-13C, 99%, CAS#57677-53-9) andglucose (U-13C6, CAS#110187-42-3) were purchased fromCambridge Isotope Laboratories. Primary antibodies used in this studyinclude b-actin (cat. no. A00702, Genscript), a-ECHS1 (cat. no.H00001892-D01P, Abnova), a-GATA3 (cat. no. #5852, Cell SignalingTechnology), a-AMPKa (cat. no. #2532, Cell Signaling Technology),a-pT172-AMPK (cat. no. #2535, Cell Signaling Technology),a-4E-BP1 (cat. no. #9644, Cell Signaling Technology), a-phospho-4E-BP1 (Thr37/46; cat. no. #2855, Cell Signaling Technology), a-p70S6 kinase (cat. no. #9202, Cell Signaling Technology), a-S6K1(phospho T389þT412; cat. no. ab60948, Abcam), a-SREBP1 (PA1-337, Thermo Fisher), a-ACC (cat. no. ab45174, Abcam), a-FASN(cat. no. ab128870, Abcam), a-ATGL (cat. no. #2138, Cell SignalingTechnology), and a-LCAD (cat. no. ab82853, Abcam). Among them,antibodies of sterol regulatory element-binding protein (SREBP1;Supplementary Fig. S1A), ECHS1 (Supplementary Fig. S1B), andGATA3 (Supplementary Fig. S1C) were validated through IHC inxenograft tumors that grew from either wild-type or candidate geneknockout (KO) cells.

Cell cultureHuman HEK293T (ATCC no. CRL-11268), ACHN (ATCC no.

CRL-1611), and 786-O cells (ATCC no. CRL-1932) were purchasedfrom Shanghai Cell Bank. HEK293T and ACHN cells were cultured inhigh-glucose DMEM (HyClone) supplemented with 10% FBS (Invi-trogen), 100 units/mL penicillin (Invitrogen), and 100 mg/mL strep-tomycin (Invitrogen). 786-O cells were maintained in RPMI 1640medium (Invitrogen) containing 10% FBS. The cells were incubated in5% CO2 at 37�C. Cell transfection was performed using polyethyle-nimine (linear, 25 KDa) or Lipofectamine 2000 (Invitrogen). All celllines were tested negative for mycoplasma contamination, and cellmorphology ismonitored throughout all processes according toATCCrecommendations.

Human samplesClinical specimens were collected from patients with ccRCC who

underwent radical nephrectomy at Fudan University Shanghai CancerCenter from January 2007 to December 2012. Fresh ccRCC andpatient-matched normal tissues frozen at �80�C were subjected toWestern blotting, Oil Red O staining, and BCAA concentrationanalyses. RNA was extracted from human ccRCC and patient-matched normal tissue samples preserved in RNAlater (Qiagen).Formalin-fixed, paraffin-embedded tissue blocks containing ccRCCand normal tissues were used for IHC.

AnimalsAll animal procedures were approved by the Animal Care

Committee at Fudan University. All mice were housed with a12:12-hour light:dark cycle at 25�C. Experiments were carried outusing 6- to 8-month-old littermates. Mice were randomized into

each of the groups. The heterozygous Echs1 KO mice were gener-ated using the CRISPR-Cas 9 system, and their genotype wasconfirmed by PCR. Kidneys were removed, and whole-cell homo-genates were generated with 0.5% NP-40 buffer for Western blottingand homogenated with 80% methanol for BCAA analyses. Forma-lin-fixed, paraffin-embedded tissue blocks were created using kid-ney tissues from wild-type and Echs1 KO mice, respectively, forIHC. For Oil Red O staining, kidney tissues were placed in optimalcutting temperature (OCT) compound (Tissue Tek 4583) in a peel-away mold and frozen at �80�C for further analysis. Samples wereprocessed blindly during the experiments and outcome assessment.

RNA extraction and quantitative real-time PCRTotal RNAwas extracted from human ccRCC and patient-matched

normal tissue samples preserved in RNAlater and then converted tocDNA using random hexamers, oligo (dT) primers, and Moloneymurine leukemia virus reverse transcriptase (TaKaRa). The ECHS1,GATA3, andAMPKmRNA levels were measured by quantitative real-time PCR using the ABI Prism 7900 sequence detection system(Applied Biosystems), with actin as an internal reference gene. Eachreaction was performed in triplicate. The primers used were listed inSupplementary Table S1.

RNA sequencingTotal RNAwas extracted from human ccRCC and patient-matched

normal tissues with TRIzol/CHCl3 (Life Technologies) according tothe manufacturer's protocol. RNA quality was examined by gelelectrophoresis, and only paired RNA of high quality was used forRNA sequencing. RNA sequencing libraries were prepared accordingto the manufacturer's instructions and then sequenced with theIllumina HiSeq 2000 at Genergy Inc.

Western blot analysesCultured cells or cells extracted from human ccRCC and patient-

matched normal tissues were lysed with 0.5%NP-40 buffer containing50 mmol/L Tris-HCl (pH 7.5), 150 mmol/L NaCl, 0.5% Nonidet P-40,and a mixture of protease inhibitors (Sigma-Aldrich). After centrifu-gation at 12,000 rpm and 4�C for 15 minutes, the supernatant of thelysates was collected for Western blotting according to standardprocedures. Detection was performed by measuring chemilumines-cence on a Typhoon FLA 9500 (GE Healthcare).

ImmunohistochemistrySections of ccRCC tissues, adjacent normal tissues, Echs1 wild-type

mouse kidney tissues, and Echs1 heterozygous KO mouse kidneytissues were obtained from the formalin-fixed, paraffin-embeddedtissue blocks. The detailed procedures of immunostaining were per-formed as mentioned in previous studies (25, 26). Sections werestained using the respective antibodies and the Envision detection kit(Dako). The immunostaining was measured based on the quantity ofimmunoreactive cells (quantity score) and the intensity of immunestaining (intensity score), as previously described (25).

Oil Red O stainingFor Oil Red O staining, fresh tissues were placed in OCT

compound (Tissue Tek 4583) in a peel-away mold and frozen at�80�C for further analysis. Oil Red O staining was performed aspreviously reported (27). Briefly, the slides were brought to roomtemperature and washed in running water to remove the OCTcompound. Slides were placed in 50% isopropanol for 3 minutesand in 100% isopropanol for 3 minutes and stained with 0.5% Oil

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Red O (O-0625, Sigma-Aldrich) in 100% isopropanol for 2 hours.Slides were then differentiated in 85% isopropanol for 3 minutesthree times, washed with running water, and stained with Mayer'shematoxylin for 15 seconds followed by bluing in running water for10 minutes. Slides were mounted with Glycerol Jelly MountingMedium (Beyotime) before being analyzed.

Total free FA and BCAA analysesTotal free FA (FFA) levels were determined using the Free Fatty

Acid Quantification Colorimetric/Fluorometric Kit (BioVision)according to the manufacturer's instructions. The levels of palmiticacid, stearic acid, and arachidic acid were determined using the gaschromatography–flame ionization detector (GC-FID)/MS methoddescribed by An and colleagues (28).

BCAA levels were measured using the Agilent 6890-5973 GC-MSsystem. In brief, cells or whole-cell homogenates of tissues wereharvested in prechilled 80% methanol, and 1 mmol/L Ribitol wasadded to the lysates as an internal standard. After 12 hours of vacuumdrying, the samples were derivatized consecutively with 1% methox-yamine hydrochloride/pyridine (70�C for 1 hour) and 20% N-tert-butyldimethylsilyl-N-methyltrifluoro-acetamide/pyridine (37�C for30 minutes), and then assayed using the Agilent 6890-5973 GC-MSsystem.

GC-FID/MS analysis of palmitic acid, stearic acid, and arachidicacid

CcRCC and patient-matched normal tissues (�50 mg) werehomogenized in 600 mL of precooled methanol using a tissue lyser(TissueLyser II, Qiagen). Supernatants were collected after 10 minutesof centrifugation (12,000 x g, 4�C). Twenty microliters of internalstandards in hexane (1 mg/mL methyl heptadecanoate, 0.5 mg/mLmethyl tricosanoate, and 28 mg/mL butylated hydroxytoluene) wasadded to a Pyrex tube, followed by addition of 100 mL of the abovesupernatant and 1 mL of methanol–hexane mixture (4:1, v/v). Thetubes were cooled in liquid nitrogen for 15 minutes. Then, 100 mL ofprecooled acetyl chloride was added, and the mixture was flushedbriefly with nitrogen gas. Tubes were screw-capped and kept at roomtemperature in the dark for 24 hours. Then, the tubes were cooled in anice bath for 10 minutes followed by gradual addition of 2.5 mL of 6%K2CO3 solution (with shaking) for neutralization. After the tubes wereleft to stand for 30 minutes, 200 mL of hexane was added to extractmethylated FAs. The mixture was left to stand for 10 minutes, and theupper layer was transferred into a glass sample vial. This extractionprocess was repeated twice, and the combined supernatants wereevaporated to dryness. The residues were dissolved in 100 mL ofhexane and subjected to GC-FID/MS analysis. For tissues, approxi-mately 10mg of sample was homogenized in 500mL ofmethanol usinga TissueLyser at 20 Hz for 90 seconds. One hundred microliters ofhomogenatemixture was transferred into a Pyrex tube formethylationas described above.

Methylated FAsweremeasured on a ShimadzuGCMS-QP2010Plusspectrometer (Shimadzu Scientific Instruments) equipped with amassspectrometer with an electron impact (EI) ion source and an FID. Onemicroliter of sample was injected into an Agilent DB-225 capillary GCcolumn (10 m, 0.1 mm ID, 0.1 mm film thickness) equipped with asplitter (1:60). Helium gas was used as the carrier andmakeup gas. Theinjection port and detector temperatures were set at 230�C. Thecolumn temperature was set at 55�C for 1 minute, increased to 205�Cat a rate of 30�C/min, kept at 205�C for 3 minutes, and increased to230�C (5�C/min). MS spectra were acquired with an EI voltage of70 eV and an m/z range of 45–450. Methylated FAs were identified by

comparison with a chromatogram from a mixture of 37 knownstandards and confirmed on the basis of mass spectral data. Each FAwas quantified with FID data from its signal integrals and internalstandards.

Stable isotope–labeled metabolites detectionFor the 13C labeling palmitic acid detection, 5 mmol/L D-glucose

(U-13C6) and 20mmol/L nonlabeled glucosewere used to treat cells for12 hours. The cells were washed twice with PBS and harvested forGC-FID/MS detection of palmitate. Because FA is elongated by twocarbons each reaction, we summed [Mþ2] and [Mþ4] palmitate astotal 13C-labeled palmitate. The levels of Mþ2 and Mþ4 palmitatewere analyzed according to m/z ratio. For the 13C labeling acetyl-CoAdetection, 2 mmol/L palmitic acid (1-13C) were used to treat cells for12 hours. Acetyl-CoA and 13C-labeled acetyl-CoA derived from 13Cpalmitate was detected using an LC-MS/MS method as previouslydescribed (29). MS/MS parameters of acetyl-CoA were as follows:Precursor ion [MþH]þ, Precursor ion(m/z): 810 for acetyl-CoA and811 for 13C-acetyl-CoA; Quantifier ion(m/z): 303 for acetyl-CoA and304 for 13C-acetyl-CoA; Qualifier ion (m/z) 428; Fragmentor voltage120V; Collision energy 30eV. Each measurement was obtained at leastin triplicate.

NMR analysis of lipidsCcRCC and patient-matched normal tissues (�50 mg) were

extracted in 1 mL of precooled methanol using the TissueLyser II.Supernatants were collected after 10 minutes of centrifugation(12,000 � g, 4�C). The extraction was repeated twice, and the super-natants were combined and centrifuged (12,000 � g, 4�C) for 10minutes. The supernatants were lyophilized after vacuum removal ofmethanol. The extracts were then individually reconstituted in 600 mLof phosphate buffer (0.15 mol/L, pH 7.43), vortex-mixed, and cen-trifuged (16,099� g at 4�C) for 10minutes. The supernatants (550 mL)were transferred into 5-mm NMR tubes for NMR analysis of lipids aspreviously reported by An and colleagues (28).

Gene silencingFor ECHS1, FASN, and LCAD silencing, stable shRNA-knockdown

(KD) cells were generated by cotransfecting cells with pCMV-VSV-G,pCMV-Gag-Pol, and shRNA plasmids using the calcium phosphatemethod. Transfected cells were cultured in DMEM containing 10%FBS for 6 hours. Twenty-four hours after transfection, culturemediumsupernatant was collected and used for retrovirus preparation to infectcells at 10% confluency in 90-mm-diameter dishes. Cells were rein-fected 48 hours after the initial infection and selected using 5 mg/mLpuromycin (Amresco).

Synthetic oligos were used for siRNA-mediated silencing of ECHS1,GATA3, AMPKa1, paired box 2 (PAX2), doublesex- and mab-3-related transcription factor 2 (DMRT2), forkhead box I1 (FOXI1),PBX homeobox 1 (PBX1), and homeobox D8 (HOXB5), and scramblesiRNA was used as the control. Cells were transfected with siRNAsusing Lipofectamine 2000 according to the manufacturer's protocol.KD efficiency was verified by qRT-PCR or Western blotting. Thesequences within genes that shRNA targeted and DNA sequences ofsiRNA were listed in Supplementary Table S1.

Gene knockoutGATA3-KO and ECHS1-KO cells were generated by the

CRISPR-Cas9 genome editing method, using the following guidesequences: GATA3: 50-ACCACGTCCCGCCCTACTA-30; ECHS1:50-CGCCAGGCGGGACAGCGAAC-30.

AMPK–GATA3–ECHS1 Pathway Inactivation Promotes ccRCC Growth

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Electrophoretic mobility shift assayElectrophoretic mobility shift assay (EMSA) was conducted as

previously described (30). Three pairs of 6-carboxy-fluorescein(FAM)–labeled double-stranded DNA probes containing a putativeGATA3-binding site were generated by annealing their respectivecomplementary oligonucleotides. The sequences of the oligonucleo-tides used were listed in Supplementary Table S1.

Nuclear extract from HEK293T cells was prepared using theNE-PER Nuclear and Cytoplasmic Extraction Kit (Pierce) in accor-dance with the manufacturer's instructions. The FAM-labeled probe(1 pmol) and 20 mg of nuclear extract were incubated in reaction buffercontaining 5mmol/LMgCl2, 2mmol/L EDTA, 50 ng/mL poly (dI-dC),2.5% glycerol, and 0.5mg/mLBSA for 20minutes at 25�C.Omission ofthe nuclear extract served as a negative control. For the supershiftassay, 1mL ofGATA3 antibody (Santa Cruz Biotechnology) was addedinto the reaction mixture and incubated for 30 minutes prior toaddition of the probe. The samples were subjected to 10% nondena-turing polyacrylamide gel electrophoresis and analyzed with theTyphoon FLA 9500 scanner.

Surface plasmon resonanceThe binding kinetics and affinity of ECHS1 promoter probes

(same probes as used in EMSA assay) for GATA3 protein wereanalyzed by SPR using a Biacore T200 instrument (GE Healthcare).Purified soluble GATA3 protein (5 mg/mL) was covalently immo-bilized on a CM5 sensor chip via amine coupling in 10mmol/Lsodium acetate buffer (pH 5.5). To determine the binding affinity ofECHS1 promoter probes for GATA3, probes were diluted to a seriesof concentrations starting at 10 nmol/L. SPR experiments were runat a flow rate of 30mL/min in PBS buffer, following the manu-facturer's instructions.

Chromatin immunoprecipitation assayChromatin immunoprecipitation (ChIP) assay was carried out

using the EZ ChIP Kit (Upstate Biotechnology) as previouslydescribed (31). Briefly, ccRCC and adjacent normal tissue sampleswere cross-linked by 1% (v/v) formaldehyde (Sigma-Aldrich) for 10minutes at 37�C.DNAwas then sonicated to generate 200- to 1,000-bpDNA fragments. The sheared chromatin was immunoprecipitated byincubation with GATA3 antibody or normal rabbit IgG (Santa CruzBiotechnology) overnight at 4�C. The DNA was purified from theeluted solution and subjected to PCR amplification with forwardprimer 50-CTGGTCTCAAACTCCTGACGT-30 and reverse primer50- CCATTTGTGTACTTGCCCGGAT-30 followed by agarose gelelectrophoresis.

Plasmid constructsWhole-length ECHS1 cDNA clones were purchased from Ori-

Gene. After confirming the sequence by Sanger sequencing, ECHS1was cloned into the pcDNA3.1-Flag vector (Invitrogen). The ECHS1promoter reporter plasmid, containing the 1,221-bp ECHS1 corepromoter region fragment, was synthesized by GenScript Corpo-ration and cloned into the pGL3-basic vector (Promega). Toconstruct the GATA3 plasmid, the coding region of GATA3 wasamplified by PCR using XhoI- and EcoRI-tailed primers (Forward:50-ccctcgagATGGAGGTGACGGCGGACCAGCCGC-30; Reverse:50- cggaattcACCCATGGCGGTGACCATGCTGGAG-30) from thecDNA obtained from HEK293T cells. After digestion with XhoI andEcoRI, the amplified products were cloned into the pcDNA3.1-Flagvector.

Dual-luciferase reporter assayFor the ECHS1 promoter luciferase reporter assay, HEK293T,

786-O, and ACHN cells were seeded in a 24-well plate, respectively.The cells were transfected with 1 mg of ECHS1 promoter reporterplasmid and 20 ng of pRL-TK vector (Promega); half of the cells wereadditionally cotransfected with 50 ng of the pcDNA3.1-GATA3expression plasmid or empty pcDNA3.1 vector using Lipofectamine2000. The transfection efficiency was monitored using the Renillaluciferase pRL-TK vector as an internal control. Two days aftertransfection, cell lysates were collected and subjected to luciferaseassay using the Dual-Luciferase Reporter Assay System (Promega)according to the manufacturer's protocol. Three independent trans-fection experiments were conducted, and each luciferase assay wasperformed in triplicate. Normalized data were calculated as the ratio ofthe firefly/Renilla luciferase activities.

Cell proliferation assayCell proliferation was assessed by the Cell Counting Kit-8 (Dojindo

Laboratories). In brief, cells were seeded in a 96-well plate with 4� 103

cells per well and allowed to adhere. Cell Counting Kit-8 solution(10mL)was added to eachwell, and the cells were cultured in 5%CO2 at37�C for 2 hours. Cell proliferation was determined by measuring theabsorbance at 450 nm.

In vivo xenograft studiesFour- to 6-week-old Balb/c nude mice were obtained (Shanghai

SLAC Laboratory Animal Co., Ltd) for in vivo xenografts. Control cellsand cells stably overexpressing ECHS1 from both 786-O and ACHNcell lines were subcutaneously heterotransplanted into the left andright flanks of each mouse. The mice were maintained under condi-tions as specified. Tumor size was measured with a caliper twice perweek from the time of the formation of palpable tumors. Tumorvolumewas calculated as the length�width2� 0.52 (32). At the end ofthe experiment, following euthanasia, tumors were excised, weighed,and imaged. All procedures were performed with approval from theAnimal Care Committee at Fudan University.

Statistical analysisData are presented as the mean� SEM, and comparisons of groups

are presented as themean� SEMand analyzed using the Student t test.The correlation between BCAA, lipid, or FA level and ECHS1 expres-sion was quantified using Pearson correlation coefficient. Progression-free survival (PFS)was defined from the initiation of surgery to the dateof disease progression or censoring at the time of last follow-up.Overall survival (OS) was defined as the time interval between thedate of surgery and the date of death or last follow-up, whicheveroccurred first. For survival analysis, the relative mRNA expressions ofECHS1 and GATA3 in ccRCC were measured using the ratio ofexpression in ccRCC/matched normal tissues and were classified intothree groups, respectively. “Low ECHS1 or GATA3 expression”denotes the ratio of ECHS1 or GATA3 mRNA expression inccRCC/matched normal tissues of less than 1/3; “middle ECHS1 orGATA3 expression” denotes the ratio of ECHS1 or GATA3 mRNAexpression in ccRCC/matched normal tissues of greater than 1/3 andless than 2/3; “high ECHS1 or GATA3 expression” denotes the ratio ofECHS1 or GATA3 mRNA expression in ccRCC/matched normaltissues of greater than 2/3. PFS and OS were estimated using theKaplan–Meier method, and the differences between the curves wereassessed by the log-rank test. All statistical analyses were performedusing SPSS software version 16.0 (SPSS Inc.). The P value was two-tailed and considered statistically significant at < 0.05.

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Study approvalThe procedures related to human tissues were carried out in

accordance with the ethical standards of Helsinki Declaration II andapproved by the Institution Review Board of Fudan University Shang-hai Cancer Center.Written-informed consent was obtained from eachpatient before, any study-specific investigation was performed.

ResultsECHS1 downregulation in ccRCC contributes to FAO inhibitionand de novo FFA synthesis

We compared lipid and FFA levels in 24 pairs of ccRCC tumor andadjacent noncancer tissues. The levels of lipids (Fig. 1A; Supplemen-tary Fig. S2) as well as FFAs (Fig. 1B), including palmitic acid, stearicacid, arachidic acid, and total FFAs, were higher in the tumor tissuesthan in the noncancer tissues. mRNA levels of adipose triglyceridelipase (ATGL) were downregulated by 55%, and those of FA syntheticenzymes, such ACC and FASN, were upregulated by approximately2.5-fold in tumor tissues compared with nontumor tissues (Fig. 1C).RNA sequencing revealed that the mRNA levels of genes involved inFAO and lipidmetabolism pathways were significantly downregulatedin the ccRCC tumors (Supplementary Fig. S3A). These results collec-tively suggested that decreased lipolysis inhibits FAO and increases denovo FA synthesis in ccRCC.

Remarkably, in line with data in the Cancer Genome Atlas database(Supplementary Fig. S3B), ECHS1, which is involved in both FAO andBCAA oxidation, was downregulated by more than 80% in ccRCCtumor tissues compared with nontumor tissues as indicated by qRT-PCR of 367 pairs of ccRCC tissues (Fig. 1D), IHC of 12 pairs of ccRCCtissues (Fig. 1E; Supplementary Fig. S3C), and Western blotting of 40pairs of ccRCC tissues (Fig. 1F; Supplementary Fig. S4). Therefore, weinvestigated the role of ECHS1 in regulating FA metabolism. Knock-down of ECHS1 in HEK293T and 786-O cells decreased 13C acetyl-CoA formation when these cells were cultured in medium containing13C-labeled palmitic acid (Fig. 1G), whereas overexpression of ECHS1increased the level of 13C acetyl-CoA in bothHEK293T and 786-Ocells(Fig. 1H).

Although homozygous deletion of Echs1 is embryonically lethal,heterogeneous KO of Echs1 using the CRISPR-Cas9 system in micereduced Echs1 expression to approximately 50% of the level in wild-type mice (Fig. 1I) and led to the accumulation of lipids (Fig. 1J;Supplementary Fig. S5A) and total FFAs (Fig. 1K) in the kidneys ofKOmice. Notably, ATGL was decreased and ACC and FASN increased inthe kidneys of Echs1-KO mice, as indicated by IHC (Fig. 1L–N;Supplementary Fig. S5B–S5D) and Western blotting (Fig. 1O).Echs1-KD mice phenocopied the status of FA metabolism in ccRCC,suggesting that Echs1 downregulation may be responsible for thereprogramming of FA metabolism in ccRCC.

GATA3, a transcription factor of ECHS1, is downregulated inccRCC

The downregulation of ECHS1 mRNA in ccRCC prompted us toidentify transcription factors associatedwithECHS1 expression. Usingthe online software TFBIND (http://tfbind.hgc.jp/), we identified sixconsensus-binding motifs in the promoter region within the�2000 toþ100 region of the ECHS1 gene that potentially bind GATA3,DMRT2, PAX2, FOXI1, PBX1, and HOXB5 (SupplementaryFig. S6A). Remarkably, in RNA sequencing data, the expression ofthese transcription factors was significantly decreased in ccRCCtumors compared with matched normal tissues (SupplementaryFig. S6B). We next explored the potential regulatory effects of candi-

date transcription factors on ECHS1 in VHL-mutant ccRCC-derived786-O cells, VHL–wild-type ccRCC-derived ACHN cells, and embry-onic kidney-derived HEK293T cells. In HEK293T, 786-O, and ACHNcells, which exhibited moderate ECHS1 expression (SupplementaryFig. S7A), KD of GATA3, but not the other five transcription factors(Supplementary Fig. S7B), led to decreased ECHS1mRNA and proteinexpression (Fig. 2A and B). Moreover, GATA3 overexpression inHEK293T or 786-O cells enhanced ECHS1 mRNA and proteinexpression (Fig. 2C and D), further indicating that GATA3 is atranscription factor of ECHS1. Luciferase assay results confirmed thatGATA3 could activate ECHS1 transcription in HEK293T, 786-O, andACHN cells (Fig. 2E). Among the three potential GATA3-bindingsites in the ECHS1 promoter (Supplementary Fig. S6), we validatedthat GATA3 could bind the �798/�787 and �537/�528 regions byEMSA (Fig. 2F) and surface plasmon resonance (SPR; Fig. 2G). Theseresults confirmed that GATA3 transcriptionally activates ECHS1expression.

AMPK regulates ECHS1 through GATA3Considering that mRNA levels of GATA3 were downregulated in

367 ccRCC tumors (Fig. 3A), and less ECHS1 promoter DNA could beimmunoprecipitated with a GATA3 antibody from ccRCC tissue thanfrom control tissue (Fig. 3B), we reasoned that GATA3 is down-regulated in ccRCC, as confirmed by IHC analysis (Fig. 3C; Supple-mentary Fig. S8A) and Western blotting (Fig. 1F; SupplementaryFig. S4). Therefore, we evaluated the correlation between AMPK andECHS1, which has been previously reported to regulate GATA3transcription (33) and whose level is decreased in ccRCC (3), asconfirmed in this study by IHC (Fig. 3D; Supplementary Fig. S8B)and Western blotting (Fig. 1F; Supplementary Fig. S4). KD of thecatalytic AMPKa1 subunit led to decreased mRNA and protein levelsof GATA3 and ECHS1 (Fig. 3E and F). Total AMPK activities in cellswere indicated by the phosphorylation levels of ACC and Raptor, twowell-known AMPK substrates (Fig. 3E and F). Conversely, activationof AMPK using AICAR increased GATA3 and ECHS1 mRNA andprotein expression (Fig. 3G andH). KD of b-catenin, which mediatesthe activating effect of AMPK on GATA3, reduced GATA3 andECHS1 expression and abrogated the activating effect of AICAR onGATA3 and ECHS1 (Fig. 3I). Notably, GATA3 deletion in HEK293Tcells reduced the mRNA (Fig. 3J) and protein (Fig. 3K) levels ofECHS1 and rendered ECHS1 expression nonresponsive to bothAMPKa1 KD (Fig. 3J and K) and AICAR treatment (Fig. 3L andM), revealing that AMPK regulates ECHS1 expression throughGATA3.

AMPK–GATA3–ECHS1 pathway downregulation causesaccumulation of FAs and BCAAs

To verify the FAO and BCAA oxidation regulatory function of theAMPK-mediated GATA3 and ECHS1 pathways (AMPK–GATA3–ECHS1 pathway), we examined each of the components in thispathway on the level of FAs and BCAAs. KD ofAMPKa1 in HEK293Tand 786-O cells resulted in accumulation of FAs (Fig. 4A) and theBCAAs leucine, isoleucine, and valine (Fig. 4B), and this effect couldbe reversed by overexpression of eitherGATA3 or ECHS1 in these cells(Fig. 4A and B), confirming that AMPK acts upstream of GATA3 andECHS1 to regulate FA and BCAA levels. Moreover, GATA3 KO inHEK293T cells led to accumulation of total FFAs (Fig. 4C) and BCAAs(Fig. 4D); these increases were reversed by overexpression of ECHS1(Fig. 4C andD), but not AMPK activation by AICAR (Fig. 4C andD),confirming that GATA3 functions downstream of AMPK andupstream of ECHS1 to regulate FA and BCAA levels. Furthermore,





http://tfbind.hgc.jp/


A B

D

C

ATGLHSL

MGLACLY ACC

FASN

ACSS1

ACSS2

ACSS3

CPT1ACPT2

ACADL

EHHADH

ECHS1

HADHA

ACAA20

1

2

3

4 NormalccRCC** **

* *** ns

FAs synthesis FAs oxidation

N = 10

*

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ns

*nsns** nsns

Lipolysis

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Rel

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G H

Mouse kidney

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0.5

1.0

1.5

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N = 6

Echs1+/-

***

Mouse kidney

Qua

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n of

Wes

tern

blo

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I

0.0

0.5

1.0

1.5

2.0

Echs1+/+

N = 6

Echs1+/-

***

Mouse kidney

Qua

ntifi

catio

n of

oil r

ed s

tain

ing

0.0

0.5

1.0

1.5

2.0

Echs1+/+

N = 6

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**

Mouse kidney

Rel

ativ

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tal F

FA le

vels

J K L

M N O

0.0

0.5

1.0

1.5

Echs1+/+

N = 6

Echs1+/-

***

Mouse kidney

Qua

ntifi

catio

n of

ATG

L IH

C

0.0

0.5

1.0

1.5

2.0

Echs1+/+

N = 6

Echs1+/-

***

Mouse kidney

Qua

ntifi

catio

n of

AC

C IH

C

0.0

0.5

1.0

1.5

2.0

Echs1+/+

N = 6

Echs1+/-

***

Mouse kidney

Qua

ntifi

catio

n of

FAS

N IH

C

ACC

FASN

ATGL

Mouse kidney

Actin

Echs1

ECHS1ATGL

ACCFASN

0.0

0.5

1.0

1.5

2.0

2.5Echs1 +/+ Echs1 +/-

** **

** **

N = 6Mouse kidney

Qua

ntifi

catio

n of

Wes

tern

blo

t

E F

0.0

0.5

1.0

1.5

Normal ccRCC

N = 12***

Qua

ntifi

catio

n of

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C

ECHS1GATA3

AMPK

p-4E-BP1p-S6K

SREBP1ACC

FASNATGL 1

p-AMPK0.00.51.01.52.02.53.03.5

Normal ccRCC

*** *** **

** ** ** ** **

*

N = 12N = 40

**

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n of

Wes

tern

blo

t

C palm

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13

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13

0

1

2

3

4

5

Vector ECHS1

**

**

HEK293T

Rel

ativ

e le

vels

C palm

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id

13

C acety

l-CoA

13

0

1

2

3

4

5

**

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Rel

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p-AMPK1

0123456

Nor

mal

ccR

CC

N = 24***

Qua

ntifi

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oilr

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aini

ng

Patie

nt 1

Patie

nt 2

TN

T

N

Palmitic acid

Stearic acid

Arachidic acid

Total FFAs0

1

2

3

4

Normal ccRCC

*** ***

******

Rel

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Normal ccRCC

N = 367***

Rel

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AGAATAGCAG ATCCAGTTGAAGAATAGCAGCGTGGGGCTGATCCAGTTGA

Echs1 exon2

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Echs1+/-

c.138 c.147

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Echs1+/-

Ech

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-Ec

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+

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13 Cpa

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13 Cac

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0

1

2

3

Scrambled shRNA ECHS1 shRNA

**

**

HEK293T

Rel

ativ

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Figure 1.

ECHS1 downregulation in ccRCC contributes to FAO inhibition and de novo FA synthesis. A, Oil Red O staining for lipids in ccRCC specimens and adjacent normaltissues from patients. Scale bars, 200 mm. Representative staining results (left) and a summary of quantification analysis (N¼ 24 pairs; right) are shown. The stainingresults for all samples are shown in Supplementary Fig. S2.B, FFA levels in ccRCC tumors and normal tissues from patients. C,mRNA levels of FAmetabolic enzymesin ccRCC tumors and normal renal tissues as identified by RNA sequencing (N¼ 10). D, Real-time PCR analysis of ECHS1mRNA levels in ccRCC tumors and normalrenal tissues (N¼ 367). E, IHC analysis of ECHS1 protein in ccRCC specimens and adjacent normal tissues. Scale bars, 200 mm. Representative staining results (top)and a summary of quantification analysis (N ¼ 12 pairs; bottom graph are shown. The results for all samples are shown in Supplementary Fig. S3. F, Western blotanalysis of ccRCC tumors and adjacent normal renal tissues. Representative results (left) and a summary of quantification analysis (right) are shown. Results ofpatients #7 to #40 are shown in Supplementary Fig. S4. 1Phosphorylation level of AMPK was normalized by AMPK protein level. G, Knockdown of ECHS1 in cellsblocked 13C-labeled palmitic acid oxidation and decreased 13C acetyl-CoA formation. H, Overexpression of ECHS1 in cells promoted the oxidation of 13C-labeledpalmitic acid. I, Schematic diagram of loss of heterozygosity of 10 bp located at Echs1 exon 2 of C57BL/6mice (top). DNA sequencing confirmation and protein levelquantification are shown in the middle and bottom plots, respectively. J–O, Oil Red O staining for lipids (J). Scale bars, 100 mm. Colorimetric quantification for FFAs(K). IHC for ATGL (L), ACC (M), and FASN (N). Western blots for ECHS1, ATGL, ACC, and FASN (O) in both Echs1þ/� and wild-type mice. Representative stainingresults and a summary of quantification analysis (N ¼ 6 pairs) are shown in J, L, M, and N. Scale bars, 50 mm. The results for all six pairs of samples are shown inSupplementary Fig. S5. �, P < 0.05; �� , P < 0.01; �� , P < 0.001 versus the corresponding control group according to Student t tests; ns, nonsignificant.

Qu et al.





ECHS1 KO in HEK293T and 786-O cells elevated the levels of FAs(Fig. 4E) and BCAAs (Fig. 4F), and overexpression of GATA3 oractivation of AMPK by AICAR had negligible effects on ECHS1expression, as well as FA and BCAA levels (Fig. 4E and F), confirmingthat ECHS1 is under the control of AMPK and GATA3 for regulation

of FAs and BCAAs. To further substantiate this notion, heterozygousEchs1 KO increased levels of FFAs (Fig. 1J and K) and BCAAs(Fig. 4G) in mouse kidneys, and decreased AMPK, GATA3, andECHS1 levels (Fig. 1F) were accompanied with increased levels of FAs(Fig. 1B) and BCAAs (Fig. 4H) in ccRCC tumors comparedwith those

A B C

D E

FNuclear extract

Probe 3Probe 2

GATA3/Probecomplex

GATA3/Probe/GATA3 Ab complex

Anti-GATA3

Probe 1

Free probe

AGTGCTGGGATTACAGGCCT

CTTGTCTAGATATTTAAAAG

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Probe 1 -802 -783

Probe 2

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-543 -524

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pGL3-ECHS1+GATA3

HEK293T 786-O ACHN0

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Probe 2

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****

HEK293T 786-O

** **

Rel

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Ale

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** **

GATA3

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ECHS10

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**

**

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**

**

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**

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HEK293T 786-O

GATA3 siRNA

Scrambled siRNA

ACHN

GATA3

ECHS1

GATA3

ECHS1

GATA3

ECHS1012345

Vector GATA3

*

**

HEK293T 786-O

**

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blo

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*

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GATA3

HEK293T 786-O

GATA3

Vector

ACHN

Figure 2.

GATA3 regulates ECHS1 transcription.A, ECHS1mRNA levels followingGATA3KD in cells.B, ECHS1 protein levels followingGATA3KD in cells. Bottom, quantificationresults of Western blots. C, ECHS1 mRNA expression following GATA3 overexpression in cells. D, ECHS1 protein levels following GATA3 overexpression in cells.Bottom, quantification results ofWestern blots. E,Effect of GATA3on the transcriptional activity of theECHS1promoter in different cell lines as determinedby a dual-luciferase reporter assay. F, EMSA analysis was performed using FAM-labeled probe and nuclear extract from HEK293T cells. Omission of the nuclear extract servedas a negative control. Supershift assaywas performed with the addition of GATA3 antibody in the reactionmixture.G, SPR assay analysis of GATA3 binding with theECHS1 promoter region. � , P < 0.05; �� , P < 0.01; �� , P < 0.001 versus the corresponding control group according to Student t tests.






0.0

0.2

0.4

0.6

0.8

1.0

1.2

Normal ccRCC

N = 367***

Rel

ativ

e G

ATA

3m

RN

A le

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Anti-GATA3

N T N T N T

Input IgG

200 bp500 bp

Normal

ccRCC

0.0

0.5

1.0

1.5

NormalccRCC

***

Rel

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mun

opre

cipi

tate

dD

NA

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A B C

N

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D

0.0

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1.5

Normal ccRCC

N = 12 pairs

***

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GAT

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N = 12 pairs

***

Qua

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AM

PK

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E F G

H

GATA3 ECHS10

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Rel

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Rel

ativ

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Ale

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L M

AMPK GATA3 ECHS10.0

0.5

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1.5 ***ns

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HEK293T

***ns

Rel

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v els

AMPK GATA3 ECHS10.0

0.5

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1.5

ControlScrambled siRNAAMPKa1 siRNA

***ns

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AMPK

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p-Raptor2

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p-ACC1

ACC

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p-Raptor2

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HEK293T

***ns

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tern

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0.5

1.0

1.5

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***ns

***ns

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GATA3 ECHS1 GATA3 ECHS10123456

Control AICAR

******

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Rel

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****** ***

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Figure 3.

AMPK regulates ECHS1 through GATA3. A, Real-time PCR analysis of GATA3mRNA levels in ccRCC tumors and normal renal tissues (N ¼ 367). B, ChIP assay wasperformed in ccRCC specimens and matched normal renal tissues with a GATA3 antibody and rabbit IgG as a control. The presence of the GATA3-binding ECHS1promoter was verified by PCR (left) and qPCR (right). C and D, IHC for GATA3 (C) and AMPK (D) protein in ccRCC specimens and adjacent normal tissues.Representative staining results (top) and a summary of quantification analysis (N ¼ 12 pairs; bottom) are shown. The results for all samples are shown inSupplementary Fig. S8. Scale bars, 200 mm. E and F, Knockdown of AMPKa1 led to decreased mRNA (E) and protein (F) levels of GATA3 and ECHS1. Total AMPKactivities in cells were indicated by the phosphorylation levels of ACC and Raptor, two well-known AMPK substrates. 1Phosphorylation level of ACC was normalizedby ACC protein level. 2Phosphorylation level of Raptor was normalized by Raptor protein level. G and H, Activation of AMPK using AICAR increased mRNA (G) andprotein (H) levels of bothGATA3 and ECHS1. 1Phosphorylation level of ACCwas normalized byACCprotein level. 2Phosphorylation level of Raptorwas normalized byRaptor protein level. I, Knockdown of b-catenin reduced GATA3 and ECHS1 expression and abrogated the activating effect of AICAR on GATA3 and ECHS1. J–M,GATA3 KO abrogated the regulatory effect of AMPK on ECHS1 at the mRNA (J) and protein (K) levels and blocked the regulatory effect of AICAR on ECHS1 at themRNA (L) and protein (M) levels. 1Phosphorylation level of ACC was normalized by ACC protein level. 2Phosphorylation level of Raptor was normalized by Raptorprotein level. �� , P < 0.001 versus the corresponding control group according to Student t tests; ns, nonsignificant.

Qu et al.





A B

C

HEK293T 786-O0

1

2

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4

ControlsiAMPKα1

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siAMPKα1siAMPKα1+GATA3siAMPKα1+ECHS1

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Rel

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Isoleu

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Leuc

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Isoleu

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ive

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IsoleucineValine

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Echs1+/-N = 6

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Rel

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ino

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Leucine

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N = 12

*** **

Rel

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ino

acid

s le

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HEK293T 786-O0

1

2

3

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Rel

ativ

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v els **

****

**** **

E

GATA3

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p-AMPK

Actin

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ECHS1

AICAR

HEK293T 786-O

AMPK

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ine

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cine

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ine

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cine

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Rel

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* * * * * ** * * * * *

* * * * * *

AMPKα1 siRNA

Scrambled siRNA

AMPK

Actin

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ECHS1

GATA3

HEK293T 786-O

ECHS1

ACC

p-ACC1

ECHS1

GATA3 KO

p-AMPK

Actin

GATA3

ECHS1

AICAR

HEK293T 786-O

AMPK

ACC

p-ACC1

Figure 4.

AMPK–GATA3–ECHS1 pathway downregulation leads to accumulation of FAs and BCAAs. A and B, FA (A) and BCAA (B) levels in AMPKa1-KD cells and GATA3- orECHS1-overexpressingAMPKa1-KD cells. Data are shown as themean� SEM of three independent replicates. 1Phosphorylation level of ACCwas normalized by ACCprotein level.C andD,FA (C) andBCAA (D) levels inGATA3KOcells andECHS1-overexpressingorAICAR-treatedGATA3KOcells. Data are shownas themean�SEMof three independent replicates. 1Phosphorylation level of ACC was normalized by ACC protein level. E and F, FA (E) and BCAA (F) levels in ECHS1 KO cells andGATA3-overexpressing or AICAR-treated ECHS1 KO cells. Data are shown as themean� SEM of three independent replicates.G, BCAA concentrations in the kidneyof Echs1þ/� and wild-type mice (N ¼ 6). H, BCAA concentrations in ccRCC tumors and matched normal tissues (N ¼ 12). � , P < 0.05; �� , P < 0.01 versus thecorresponding control group according to Student t tests; ns, nonsignificant.






in adjacent normal tissues. This supported that AMPK–GATA3–ECHS1 pathway downregulation results in FA and BCAA accumu-lation in mice and in humans.

AMPK–GATA3–ECHS1 pathway downregulation activatesmTORC1 and feedback inhibits AMPK

The levels of BCAAs, known potent activators of mTORC1 signal-ing, were negatively correlated with ECHS1 mRNA levels in ccRCC(Fig. 5A and B), suggesting that downregulation of the AMPK–GATA3–ECHS1 pathway activates mTORC1 signaling. Confirmingthis hypothesis, increased phosphorylation of 4E-BP1 and S6K; read-outs of mTORC1 activation; increased expression of the mature formof SREBP1, ACC, and FASN; and downregulated expression of ATGL—all consequences of mTORC1 activation—were observed in ccRCCtumor tissues in which AMPK, GATA3, and ECHS1 were down-regulated according to IHC (Fig. 5C–H; Supplementary Figs. S8A–S8D and S9A–S9D) and western blotting (Fig. 1F; SupplementaryFig. S4). Based on Western blot analysis of human samples, wevalidated that expression levels of SREBP1, ACC, and FASN werecorrelated with decreased AMPK, GATA3, and ECHS1 expression(Supplementary Fig. S10A–S10C). Meanwhile, ATGL levels werecorrelated with increased AMPK, GATA3, and ECHS1 expression(Supplementary Fig. S10A–S10C). Heterozygous Echs1 KO in miceincreased the phosphorylation levels of S6K (Fig. 5I SupplementaryFig. S11A) and 4E-BP1 (Fig. 5J; Supplementary Fig. S11B); increasedSREBP1 (Fig. 5K; Supplementary Fig. S11C), ACC (see Fig. 1M), andFASN (see Fig. 1N) expression; and decreased ATGL expression(see Fig. 1L).

Furthermore, phosphorylation of 4E-BP1 and S6K and expressionof SREBP1, ACC, and FASNwere activated, whereasATGL expressionwas inactivated upon AMPKa1-subunit KD (Fig. 5L), GATA3 KD(Fig. 5M), and ECHS1 KD (Fig. 5N). In contrast, 4E-BP1 and S6Kphosphorylation and SREBP1, ACC, and FASN expression wereinactivated, whereas ATGL expression was activated upon AMPKactivation by AICAR (Fig. 5O), GATA3 overexpression (Fig. 5P), andECHS1 overexpression (Fig. 5Q). Notably, mTORC1 inactivationinduced by AMPK–GATA3–ECHS1 activation could be rescued bysupplemental BCAAs (Fig. 5O–Q; Supplementary Fig. S12A–S12Cshowing BCAA levels in different treatments). Together with the factthat BCAA deficiency blocked mTORC1 activation when AMPKa1,GATA3, and ECHS1 were silenced (Fig. 5R–T), these results collec-tively confirmed that downregulation of the AMPK–GATA3–ECHS1pathway results in activation of mTORC1. Interestingly, as high FAand BCAA levels inhibit AMPK activity (34–37), decreased ECHS1feedback might inhibit AMPK activities. This hypothesis was sup-ported in Echs1 heterozygous KOmice, which showed reduced AMPKphosphorylation (Fig. 5U; Supplementary Fig. S12D), as well as inccRCC tissues, in which relative AMPK phosphorylation was reduced(Fig. 1F). We also observed activated AMPK in ECHS1-overexpres-sing cells (Fig. 5V) and inactivated AMPK in GATA3- or ECHS1-KDcells (Fig. 5M and N). These results indicated that reduced ECHS1feedback could inhibit AMPK activity and thus form a vicious circle ofFA accumulation.

ECHS1 inactivation promotes cancer cell proliferation throughactivating mTORC1 and de novo FA synthesis

ECHS1 KD in ACHN and 786-O cells promoted their proliferation;however, this proliferation-promoting effect was diminished by rapa-mycin treatment (Fig. 6A and B), suggesting that mTORC1 activationis required. Moreover, rapamycin treatment decreased the FFA level(Fig. 6C), but not lipid accumulation (Fig. 6D), in ECHS1-KD cells,

suggesting that lipid accumulation alone by ECHS1 downregulationdid not contribute to proliferation, and that mTORC1 activation andde novo FA synthesis induced by ECHS1 downregulation may con-tribute to proliferation promotion. Confirming this hypothesis, KD ofLCAD, an FAO enzyme, led to accumulation of lipids (Fig. 6E), butfailed to activate mTORC1 (Fig. 6F) and failed to promote prolifer-ation of 786-O and ACHN cells (Fig. 6A and B). Moreover, thexenograft growth-promoting ability of ECHS1 KD was abolished byrapamycin treatment of mice bearing ACHN (Fig. 6G) or 786-O(Fig. 6H) cells.

Consistent with the observation that ECHS1 downregulation acti-vates FASN and ACC and thus de novo FA synthesis, the formation of13C palmitic acid from 13C glucose–derived 13C acetyl-CoA wasenhanced by ECHS1 KD (Fig. 6I) and inhibited by ECHS1 over-expression (Fig. 6J) inHEK293T and 786-O cells. Notably, ECHS1KDor overexpression had negligible effects on palmitic acid formation(Fig. 6K and L) and proliferation (Fig. 6M andN) in 786-O cells withFASN deletion. Moreover, FASN deletion, which abrogated the effecton lipid accumulation in ECHS1-KD ACHN and 786-O cells(Fig. 6O), rendered the growth of xenografted tumor cells nonre-sponsive to ECHS1 KD (Fig. 6G and H). These results collectivelyshowed that the ECHS1 downregulation–mediated promotion ofde novo FA synthesis accounts for its proliferation-promoting effects.

DecreasedECHS1 levels predict poorprognosis for patientswithccRCC

Finally, we determined the correlation between lipid accumulationand ccRCC progression. In 367 ccRCC and paired adjacent normaltissues (Supplementary Table S2), FA levels were positively correlatedwith ccRCC stage (Fig. 7A) and grade (Fig. 7B). Moreover, highertumor-to-normal lipid ratios were positively correlated with ccRCCstage (Fig. 7C) and grade (Fig. 7D). These results suggested that FAlevels as well as relative lipid levels can predict ccRCC progression.

Relative GATA3 and ECHS1 mRNA levels in the same group ofccRCC samples were inversely correlated with ccRCC stage (Fig. 7E)and grade (Fig. 7F). These results, together with the finding thatccRCC ECHS1 mRNA levels were strongly negatively correlated withthe levels of lipids (Fig. 7G) and FAs (Fig. 7H), are in line with thenotion that GATA3 and ECHS1 inactivation–induced FA and lipidaccumulation predicts the progression of ccRCC.

Cox regression analyses were conducted to assess the prognosticvalue of ECHS1 and GATA3 expression and clinicopathologic para-meters for PFS and OS (Supplementary Tables S3 and S4) for thesepatients with ccRCC. ECHS1 and GATA3 mRNA levels were inde-pendent prognostic factors for both PFS (Fig. 7G and I) and OS(Fig. 7G and J), even after adjustment for known prognostic factorssuch as N stage, M stage, and tumor grade. Survival analyses revealedthat loss of either ECHS1 or GATA3 was associated with inferior PFSand OS. PFS and OS curves according to ECHS1 or GATA3 mRNAexpression in ccRCC tissues were distinctly tiered and statisticallysignificant (P < 0.001; Fig. 7G, I, and J). Taken together, theseobservations suggested that loss of ECHS1 expression contributes toFA accumulation in the kidneys and ccRCC.

DiscussionIntracellular lipid droplet accumulation and activated FA syn-

thesis are hallmarks of ccRCC. Highly proliferative ccRCC cellsshow a strong lipid avidity, which is satisfied by either increasingexogenous (or dietary) lipid and lipoprotein uptake or overactiva-tion of endogenous synthesis. Previous reports have suggested that

Qu et al.





A C D

I J

L N

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Normal ccRCC

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y = 1.27-0.21x P = 0.008

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Ratio of ECHS1 expression inccRCC/Normal

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Figure 5.

AMPK–GATA3–ECHS1 pathway downregulation activates mTORC1, and feedback inhibits AMPK. A and B, Ratio of ECHS1 mRNA expression between tumors andnormal tissueswas negatively correlatedwith the ratio of eachBCAA levels (A) and total BCAAs levels (B) between tumors and normal tissues in patientswith ccRCC.C–H, IHC analysis of p-4E-BP1 (C), p-S6K (D), SREBP1 (E), ACC (F), FASN (G), and ATGL (H) proteins in ccRCC specimens and adjacent normal tissues. Scale bars,200 mm. Representative staining results (top) and a summary of quantification analysis (N ¼ 12 pairs; bottom) are shown. The results for all samples are shown inSupplementary Figs. S8 and S9. I–K, IHC analysis of p-S6K (I), p-4E-BP1 (J), and SREBP1 (K) in either ECHS1þ/� or wild-type mice. Representative stainingresults and a summary of quantification analysis (N ¼ 6 pairs) are shown. The results for all six pairs of samples are shown in Supplementary Fig. S11. Scale bars,100 mm. L–N,Western blot analysis of endogenous ECHS1, p-T389-S6K, S6K, p-T37/46-4E-BP1, 4E-BP1, SREBP1, ACC, FASN, and ATGL protein levels inAMPKa1-KDcells (L), GATA3-KD cells (M), and ECHS1-KD cells (N). O–Q, Western blot analysis of endogenous ECHS1, p-T389-S6K, S6K, p-T37/46-4E-BP1, 4E-BP1, SREBP1,ACC, FASN, and ATGL protein levels in AICAR-treated cells (O), GATA3-overexpressing cells (P), and ECHS1-overexpressing cells (Q) cultured with or withoutBCAAs.R–T,Western blot analysis of endogenous p-T389-S6K, S6K, p-T37/46-4E-BP1, 4E-BP1, SREBP1, ACC, FASN, andATGL protein levels inAMPKa1-KD cells (R),GATA3 KO cells (S), and ECHS1 KO cells (T) cultured with or without BCAAs. U, IHC analysis of p-AMPK in ECHS1þ/� and wild-type mice. Representative stainingresults and a summary of quantification analysis (N¼ 6 pairs) are shown. The results for all six pairs of samples are shown in Supplementary Fig. S11. V,Western blotanalysis of endogenous p-AMPK and AMPK in ECHS1-overexpressing cells. �� , P < 0.001 versus the corresponding control group according to Student t tests.






A

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ECHS1 inactivation promotes cancer cell proliferation through activating mTORC1 and de novo FA synthesis. A and B, Growth curves of LCAD-KD, ECHS1-KD,and rapamycin-treated ECHS1-KD ACHN (A) and 786-O (B) cells. C and D, FFA (C) and lipid (D) levels in ECHS1-KD cells and rapamycin-treated ECHS1-KDcells. E, Lipid levels in LCAD-KD cells. F,Western blots for the pS6K and p4E-BP1 levels in LCAD-KD cells. G and H, Tumor size between the control, ECHS1-KD,rapamycin-treated ECHS1-KD, and ECHS1 and FASN double-KO 786-O cell (G) and ACHN cell (H) xenografts in nude mice. Data are shown as the mean � SEMfor each group of mice (N¼ 10). I, KD of ECHS1 promoted de novo FA synthesis from 13C acetyl-CoA. J,Overexpression of ECHS1 inhibited de novo FA synthesisfrom 13C acetyl-CoA. K and L, Knockdown of FASN abrogated the activation of de novo FA synthesis induced by ECHS1 KD (K) and the inhibitory effect on denovo FA synthesis induced by ECHS1 overexpression (L). M, Proliferation curves of control, ECHS1-KD, and ECHS1 and FASN double-KD 786-O cells.N, Proliferation curves of control, ECHS1-overexpressing, and FASN-KD/ECHS1-overexpressing 786-O cells. O, Lipid levels in control, ECHS1-KD, and ECHS1and FASN double-KD cells. � , P < 0.05; �� , P < 0.01 versus the corresponding control group according to Student t tests; ns, nonsignificant.

Qu et al.





A B

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0.0 0.2 0.4 0.601234567 Palmitic acid

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y = 3.80-4.44x P = 0.002 y = 3.47-3.49x P = 0.007

y = 4.07-4.78x P = 0.002Total FAs

y = 2.91-2.59x P = 0.003

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Figure 7.

Decreased ECHS1 levels predict poor prognosis of ccRCC. A, Correlation between FFA levels and tumor stage. B, Correlation between FFA levels and tumorgrade. C, Correlation between lipid levels and tumor stage. D, Correlation between lipid levels and tumor grade. E, Ratio of ECHS1 (left) and GATA3 (right)mRNA expression in primary ccRCC specimens/patient-matched normal tissues for all stages of ccRCC. F, Ratio of ECHS1 (left) and GATA3 (right) mRNAexpression in primary ccRCC specimens/patient-matched normal tissues for all grades of ccRCC. G and H, Correlations between ECHS1 expression and lipidlevels (G) or FFA levels (H). I, Kaplan–Meier survival plots for PFS according to ECHS1 (top) and GATA3 (bottom) mRNA expression in primary ccRCCspecimens. “Low ECHS1 expression” denotes a ratio of ECHS1 mRNA expression in primary ccRCC specimens/patient-matched normal tissues of less than 1/3;“Middle ECHS1 expression” denotes a ratio greater than 1/3 and less than 2/3; and “High ECHS1 expression” denotes a ratio greater than 2/3. J, Kaplan–Meiersurvival plots for OS according to ECHS1 (top) and GATA3 (bottom) mRNA expression in primary ccRCC specimens. � , P < 0.05; ��, P < 0.01; �� , P < 0.001versus the corresponding control group according to Student t tests; ns, nonsignificant.






FA accumulation in ccRCC results from enhanced FA synthesis andthat the rate-limiting enzymes in the FA synthesis pathway, ACCand FASN, may represent the main cause of FA accumulation andccRCC pathologic effects (3, 38, 39). Here, we report that AMPK–GATA3–ECHS1 pathway inactivation induces FAO blockage, con-tributing to ccRCC onset through accumulation of lipids andpromotion of de novo FA synthesis.

Oxidized FAs constitute an important energy source for manycell types, including proximal tubular epithelial cells, from whichccRCC is derived (40). Conversely, most cancer cells, includingccRCC, produce energy from glucose through glycolysis rather thanfrom FA through b-oxidation and the tricarboxylic acid cycle. Ourresults revealed that, besides de novo FA synthesis, the FAOpathway was shut down in ccRCC. Isotopic tracing experimentsconfirmed that loss of ECHS1 blocked FAO and decreased acetyl-CoA generation via FAO. This was in accordance with the obser-vation that cancer cells curtail the energy demand from FAs andprovides an explanation for the existing paradox in that increasedFA levels do not lead to enhanced energy export from this enhancedpotential substrate in ccRCC development.

Although enhanced FA synthesis and inhibition of FAO wereobserved simultaneously in ccRCC tumors, we confirmed that FAOinhibition induced by ECHS1 downregulation plays a key role in FAmetabolic reprogramming. Using isotopic tracing, we found that down-regulation of ECHS1 promoted de novo FA synthesis, whereas over-expression of ECHS1 inhibited this. In cultured cells and Echs1 hetero-zygousKOmice,we confirmed that the alteration indenovoFAsynthesiswas caused by activation of ACC and FASN. Our previous findingsrevealed that lossofECHS1 led toBCAAaccumulation andconsequentlyactivation of mTORC1, which governs protein synthesis and is anothersignature of cancer (21–23). Furthermore, we validated that ECHS1silence-inducedmTORC1 activation subsequently increased the expres-sion of SREBP1 and its downstream targets, ACC and FASN, and finallypromoteddenovoFAsynthesis. In cultured cells and an animal xenograftmodel, we found that FAO blockage alone did not provide the cells withproliferative advantage; activated de novo FA synthesis was the keyprocess to enhance cell proliferation and tumor growth.

In addition, we demonstrated that decreased ECHS1 transcriptionresulted from GATA3 downregulation, which in turn resulted from adecrease in AMPK levels. Upon activation, AMPK inhibits anabolicpathways and promotes catabolism in response to an increase in theAMP/ATP ratio by downregulating the activity of key enzymes ofintermediary metabolism (41–43). In its activated state, AMPK phos-phorylates ACC and inhibits its enzymatic activity, resulting indecreased FA synthesis (44). We found that activated AMPK promotedFAO by increasing ECHS1 expression, further indicating that AMPKcould coordinate the synthesis and degradation of FAs andmaintain theintracellular FA balance. It has been previously shown that AMPKprotein levels are significantly decreased in ccRCC, and this contributesto a metabolic shift toward increased FA synthesis (3). Our resultsfurther indicated that AMPK inactivation may result in the loss oftranscription ofGATA3 and downstream ECHS1, thus preventing FAOand enhancing denovoFA synthesis simultaneously by transcriptionallyactivating ACC and FASN—finally leading to FA accumulation duringccRCC development. Furthermore, high levels of BCAAs and saturatedFAs were reported to inhibit AMPK activity (34–37). Thus, AMPKinactivation–induced ECHS1 loss and FA/BCAA accumulation maylead to a positive feedback to downregulate ECHS1.

In patients, ccRCC prognosis is currently determined based onanatomical and histologic factors. However, as ccRCC represents ametabolic disease, previously identified molecular markers, including

those from gene expression profiling and sequencing results, arenot recommended in routine practice. For example, the relationshipbetween body mass index and prognosis remains controversial;some reports have suggested that increased body mass indexindicates poor survival (38), whereas others have associated thiswith improved survival (45). However, FASN expression has con-sistently been reported to be associated with poor prognosis inseveral tumor types, including RCC (46, 47). Thus, developingreliable molecular markers could improve the predictive accuracyof current prognostic systems for ccRCC (48). We investigated thecorrelation between ECHS1 mRNA expression and tumor progres-sion and survival in a cohort of 367 patients with ccRCC. Wedemonstrated that loss of ECHS1 in ccRCC tissues was correlatedwith tumor progression and inferior PFS andOS. Furthermore,ECHS1mRNA expression constituted an independent prognostic factor forboth PFS and OS, even after adjustment for known prognostic factors.Our findings therefore indicate an integral role of ECHS1 in theunderlying biological mechanisms of tumorigenesis and in the prog-nosis of patients with ccRCC.

In summary, our results showed that AMPK–GATA3–ECHS1pathway inactivation causes FA metabolic reprogramming in ccRCC.ECHS1 showed good prognostic ability and, together with in vitro andin vivo findings, indicated that enhanced ECHS1 may slow downtumor cell proliferation. These insights may offer new therapeuticapproaches for the treatment and prognostic assessment of ccRCC inthe clinic.

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

Authors’ ContributionsConception and design: D.-W. Ye, S.-M. Zhao, J.-Y. ZhaoDevelopment of methodology: Y.-Y. Qu, R. Zhao, Y. Lin, W. Xu, S.-M. Zhao,J.-Y. ZhaoAcquisition of data (provided animals, acquired and managed patients, providedfacilities, etc.):R. Zhao, H.-L. Zhang, Q. Zhou, F.-J. Xu, X. Zhang,W.-H. Xu, N. Shao,S.-X. Zhou, C.-T. Han, K. Chang, W.-D. ZangAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): R. Zhao, B. Dai, Y. Zhu, G.-H. Shi, Y.-J. Shen, Y.-P. ZhuWriting, review, and/or revision of the manuscript: S.-M. Zhao, J.-Y. ZhaoAdministrative, technical, or material support (i.e., reporting or organizing data,constructing databases): Y.-Y. Qu, H.-L. Zhang, J.-Y. ZhaoStudy supervision: D.-W. Ye, S.-M. Zhao, J.-Y. Zhao

AcknowledgmentsThisworkwas supported by grants from theNational Science Foundation ofChina

(nos. 31330023 to S.-M. Zhao; 81722021 to J.-Y. Zhao; 31671483 toW. Xu; 81771627to J.-Y. Zhao; 31521003 to J.-Y. Zhao; 31821002 to S.-M. Zhao; 91753207 to S.-M.Zhao; 31930062 to S.-M. Zhao; 81802525 to Y.-Y. Qu; 81672544 to D.-W. Ye;81872099 to D.-W. Ye; and 31871432 to W. Xu), Shanghai Rising-Star Program(no. 18QA1400300 to W. Xu), National Key R&D Program of China (nos.2018YFA0800300 to S.-M. Zhao; 2019YFA0801900 to J.-Y. Zhao; 2018YFA0801300to W. Xu; and 2018YFC1004700 to W. Xu); Science and Technology MunicipalCommission of Shanghai, China (16JC1405301 to S.-M. Zhao; 16JC1405302 toD.-W. Ye; 18511108000 to D.-W. Ye; and 2018ZHYL0201 to D.-W. Ye), ShanghaiSailing Program (no. 17YF1402700 to Y.-Y. Qu), Shanghai Natural Science Foun-dation of China (no. 16ZR1406400), and Shanghai "Rising Stars of Medical Talent"Youth Medical Talents–Specialist Program (Y.-Y. Qu).

The costs of publication of this article were defrayed in part by the payment of pagecharges. This article must therefore be hereby marked advertisement in accordancewith 18 U.S.C. Section 1734 solely to indicate this fact.

Received March 28, 2019; revised August 28, 2019; accepted November 1, 2019;published first November 5, 2019.

Qu et al.





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2020;80:319-333. Published OnlineFirst November 5, 2019.Cancer Res Yuan-Yuan Qu, Rui Zhao, Hai-Liang Zhang, et al. GrowthAcid Synthesis That Promotes Clear Cell Renal Cell Carcinoma

ECHS1 Pathway Induces Fatty−GATA3−Inactivation of the AMPK

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