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Translational Cancer Mechanisms and Therapy

Ligand-binding Domain–activating Mutations ofESR1 Rewire Cellular Metabolism of Breast CancerCellsLotem Zinger1,2, Keren Merenbakh-Lamin1,2, Anat Klein1,2, Adi Elazar1,2,Shani Journo1,2, Tomer Boldes1,2, Metsada Pasmanik-Chor3, Avishay Spitzer1,Tami Rubinek1,2, and Ido Wolf1,2

Abstract

Purpose:Mutations in the ligand-binding domain (LBD) ofestrogen receptor a (ER) confer constitutive transcriptionalactivity and resistance to endocrine therapies in patients withbreast cancer. Accumulating clinical data suggest adverse out-come for patients harboring tumors expressing these muta-tions. We aimed to elucidate mechanisms conferring thisaggressive phenotype.

Experimental Design: Cells constitutively expressing phys-iologic levels of ER-harboring activating LBD mutations weregenerated and characterized for viability, invasiveness, andtumor formation in vivo. Gene expression profile was studiedusing microarray and RNAseq technologies. Metabolic prop-erties of the cells were assessed using global metabolite screenand direct measurement of metabolic activity.

Results: Cells expressing mutated ER showed increasedproliferation, migration, and in vivo tumorigenicity comparedwith cells expressing the wild-type ER (WT-ER), even in the

presence of estrogen. Expression of the mutated ER was asso-ciated with upregulation of genes involved in invasion andmetastases, as well as elevation of genes associated with tumorcell metabolism. Indeed, a metabolic examination revealedfour distinct metabolic profiles: WT-ER–expressing cells eitheruntreated or estrogen treated andmutated ER–expressing cellseither untreated or estrogen treated. Pathway analyses indi-cated elevated tricarboxylic acid cycle activity of 537S-ER–expressing cells. Thus, while WT-ER cells were mostly glucose-dependent, 537S-ER were not addicted to glucose and wereable to utilize glutamine as an alternative carbon source.

Conclusions: Taken together, these data indicate estrogen-independent rewiring of breast cancer cell metabolism byLBD-activating mutations. These unique metabolic activitiesmay serve as a potential vulnerability and aid in the develop-ment of novel treatment strategies to overcome endocrineresistance.

IntroductionAbout 75% of all breast cancers express estrogen receptor-a

(ER), and inhibition of ER activity by endocrine treatments is aneffective and safe treatment strategy for patients harboring ERþ

breast cancer. However, some patients with metastatic breastcancer do not respond to any form of endocrine treatment(de novo resistance), and virtually all patients who initiallyrespond eventually develop endocrine resistance (acquired resis-tance). We and others have identifiedmutations in the ER ligand-binding domain (LBD) that lead to a conformational change

mimicking the activated ligand bound receptor and serve as anovel mechanism of resistance to endocrine therapy (1–5). Themost commonmutations of the ER are substitution of Asp-538 toglycine (D538G) and substitution of Tyr-537 to serine (Y537S;refs. 6–8). These and other activating mutations where identifiedin up to 39% of heavily pretreated patients with metastatic breastcancer (6, 7, 9).

Accumulating clinical and laboratory data suggest a uniquephenotype of breast cancers expressing these mutations. Thus,LBD mutations were shown to enhance colony formation bybreast cancer cells (10), we and others noted an associationbetween the presence of D538Gmutation and increased frequen-cy of liver metastases (2), and analysis of the SoFea and PALOMAclinical trials, indicated shortened progression free-survival ofpatients with tumors harboring LBD mutations (6, 11). Thesedata suggest that breast cancers harboring these LBD-activatingmutations may constitute a new subgroup of breast cancers,characterized by increased invasiveness and tissue tropism, trans-lating into a more aggressive clinical behavior.

A possible candidate mediating aggressive behavior of ERþ

breast cancer cells is the PI3K-AKT-mTOR pathway (12). Activat-ing mutations in this pathway occur in over 40% of ERþ breastcancers (6, 7, 9) and activation of this pathway has been linked toendocrine-resistant breast cancer (13, 14). Accordingly, inhibitionof mTOR by everolimus is an effective strategy to overcomeendocrine resistance inpatientswithmetastatic breast cancer (14).

1Institute ofOncology, Tel Aviv SouraskyMedical Center, Tel Aviv, Israel. 2SacklerFaculty of Medicine, Tel Aviv University, Tel Aviv, Israel. 3Bioinformatics Unit,Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.

Note: Supplementary data for this article are available at Clinical CancerResearch Online (http://clincancerres.aacrjournals.org/).

T. Rubinek and I. Wolf contributed equally to this article.

Corresponding Authors: Ido Wolf, Tel Aviv Sourasky Medical Center, 6Weizmann Street, Tel Aviv 64239, Israel. Phone: 9725-2736-0558; Fax: 972-3697-3030; E-mail: [email protected]; and Tami Rubinek, Tel Aviv SouraskyMedical Center, 6 Weizmann Street, Tel Aviv 64239, Israel. Phone: 9725-2746-6151; E-mail: [email protected]

doi: 10.1158/1078-0432.CCR-18-1505

�2019 American Association for Cancer Research.

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Activation of thePI3K-AKT-mTORpathwaymaybe associated notonly with endocrine resistance but also with a more aggressivedisease behavior (13, 14). However, the interaction between thepresence of LBDmutations and activation of the PI3K-AKT-mTORhas not been characterized yet.

One of the hallmarks of cancer is reprogramming of energymetabolism, which provides cancer cells appropriate condi-tions required for enhanced proliferation and survival. The ERpathway may play a role in rewiring breast cancer cells' metab-olism. Thus, ERþ and ER� breast cancer have different meta-bolic signatures, with ERþ tumors showing activation of fattyacid metabolism, transport, (15), increased glucose uptake, andglycolysis (16), as well as an increase in amino acid–associatedmetabolites (17). None the less, to our knowledge, the meta-bolic effects of activating LBD mutations have not been char-acterized yet.

In this study, we sought to characterize the oncogenic proper-ties of breast cancer cells harboring LBD-activating mutations.Our results indicate aggressive behavior of these cells, as well asactivation of PI3K-AKT-mTOR. Transcriptomic andmetabolomicanalyses revealed unique metabolic profile, distinct from thatof activated ER cells, characterized by increased tricarboxylicacid (TCA) cycle and reliance on glutamine. Thus, the dataindicate that LBD-activating mutations rewire breast cancer cellmetabolism.

Materials and MethodsConstructs

The ERE-luciferase reporter construct, kindly provided byD. Harris, (University of California, CA), consists of two repeatsof the upstream region of the vitellogenin ERE promoter.Generation of pcDNA3 ER-WT and 538G-ER constructs wasdescribed previously (2). 537S-ER-pcw107-V5 and HcRed-pcw107-V5 (empty vector) were a gift from David Sabatini & KrisWood (Addgene plasmid catalog nos. 64634 and 64647; ref. 18).WT-ER-pcw107-V5was generated using the In-FusionHDcloning

kit according to the manufacturer's instructions, using 537S-ER-pcw107-V5 plasmid as a template for PCR. Primers used wereas follows: 50-primer: CTCTATGACCTGCTGCTGGAGATGCT; 30-primer: CAGCAGGTCATAGAGGGGCACCACGTT. 538G-ER-pcw107-V5 was generated using the In-Fusion HD cloning kit aswell, using WT-ER-pcw107-V5 plasmid as a template for PCR.Primers used were as follows: 50-primer: CCTCTATGGCCTGCTG-CTGGAGATGCTG; 30-primer: AGCAGGCCATAGAGGGGCAC-CACGTTC. All subcloned constructs were sequenced. pCMV-VSV-G was a gift from Bob Weinberg (Addgene plasmid catalogno. 8454; ref. 19), psPAX2 was a gift fromDidier Trono (Addgeneplasmid catalog no. 12260).

Cells and transfectionsCell lines were originally obtained from the ATCC and authen-

ticated with the DNA markers used by ATCC. MCF-7 andT47D cells were grown in DMEM containing 10% FBS. Forparticular experiments, cells were grown with DMEM withoutglutamine or glucose, and in these experiments glucose and/orglutamine (both from Life Technologies) were added separately.For all E2 (obtained from Sigma) and rapamycin (obtained fromCayman Chemical) studies, cells were cultured in phenol-freemedia using 10% charcoal-treated serum for 2 days before treat-ment. All transfections, except for lentiviral system, used jetPEI(Polyplus-transfection SA).

Generation of stably expressing 537S-ER and 538G-ER cells537S-ER-pcw107-V5, 538G-ER-pcw107-V5, WT-ER-pcw107-

V5, or empty pcw107-V5 vectors were transfected along withpCMV-VSV-G and psPax2 (2mg: 2mg: 2mg) into HEK-293T cellsusing the calcium phosphate coprecipitation method. In brief,HEK-293T cells were seeded in 6-well plate and grown to 80%confluency. Plasmid DNA (6 mg) was mixed with 250 mL of0.25mol/LCaCl2, incubated for 20minutes at room temperature,and then mixed with 250 mL of sterile HBSx2 (NaCl 0.28 mol/L,HEPES 0.05 mol/L, and Na2HPO4 1.5 mmol/L; pH ¼ 7.05). Themixed solution was added to cells for 24 hours. Conditionedmedium was harvested twice, 48 hours and 72 hours after trans-fection, and conditioned media containing viral particles wasfiltered through 0.45-mm filters. For virus infection, MCF7 orT47D cells were incubated with conditioned media containingvirus particles supplemented with polybrene (8 mg/mL) for8 hours. Stably infected cells were selected by puromycin(0.5 mg/mL). Two weeks later, single colonies were generated byseeding half-cell per well into 96-well plate, and genomic DNAof the clones was sequenced to confirm insertion of themutation.Two clones of each wild-type (WT), 538G-ER, or 537S-ER werecultured routinely separately and the clones of each genotypeweremixed prior to each experiment.

MTT assayViability and proliferation were assessed using the 3-(4,

5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide(MTT) assay as described previously (20). For the assay, cells(WT, 538G-ER, or 537S-ER–expressing cells) were plated in96-well plate (3,000 cells/well). After 24 hours, 10 wells of eachcell type (WT and mutant) served as day 0. Experiment plate wastreated with E2 or control vehicle for 72 hours, MTT was addedfor 1.5 hours,mediumwas aspirated, andMTTwas dissolvedwith50 mL DMSO. Absorbance was determined at 570 nm using amultichannel plate spectrophotometer. Data were subsequently

Translational Relevance

Resistance to endocrine therapy occurs in virtually allpatientswith estrogen receptor ER-a-positive metastatic breastcancer. Activating mutations in the ligand-binding domain(LDB) of the ER appear in up to 40% of these patients,conferring endocrine resistance and constitutive transcription-al activity. Clinical data suggest an association between thesemutations and adverse clinical outcome. We show here thatbreast cancer cells expressing mutated ER possess distinctcharacteristics from those expressing wild-type ER, even in thepresence of estrogen. These cells have a unique aggressive-related gene signature, translated into amore aggressive in vitroand in vivo behavior. Moreover, this phenotype is supportedby rewired metabolic pathways characterized by glucose-independent tumorigenic activity. These results suggest thattumors harboring LBD mutations comprise a novel distinctsubgroup of breast cancer, with unique metabolic require-ments. These requirements may serve as a potential vulner-ability and be exploited to the development of novel treat-ment strategies to overcome endocrine resistance.

ESR1 Mutations Rewire Breast Cancer Cell Metabolism

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analyzed by comparing live cell counts on day 0 with live cellcounts on day 3. Each condition was assessed from 15 replicatesand three independent experiments were conducted.

Methylene blue assayCells were plated in 96-well plates at a density of 3,000 cells per

well, 15 wells per treatment. A day later, cells were treated with E2or control vehicle and incubated at 37�C, 5% CO2 for 24 hours.Glutaraldehyde (2.5%) was diluted 1:5 into cells for 10 minutesand then cells were washed three times with ddH2O. Cells wereincubated with 100 mL of methylene blue stain [1% methyleneblue in borate buffer (pH 8.5)] for 1 hour at room temperature.After removing the methylene blue stain, cells were washed fourtimes with dH2O and 100mL of 0.1 mol/L HCl was added intoeach well. The absorbance was read with a microplate reader at650 nm.

Migration assayMigration was assessed using the wound-healing ("scratch")

assay as described previously (2). For the assay, MCF-7 cells weretransfectedwith the indicated constructs and grown to confluencyin a 6-well plate in phenol-free media with 10% charcoal-treatedserum. In some experiments MCF-7 cells stably expressing WT or537S-ER were grown to confluency. The cell monolayer was thenscraped in a straight line with a 200-mL tip and photographed atindicated time.

Soft agar assayThe assay was conducted as described previously (21). Briefly,

2 � 104 cells/well were seeded in noble agar (Sigma) at a finalconcentration of 0.3%, on top of 0.5% base agar in completemediawith phenol red. Cells were refed twice aweekwith phenol-free media with 10% charcoal-treated serum. Triplicates wereperformed for each condition and cells were incubated for 2–4weeks at 37�C in 5% CO2 atmosphere. Colonies were thencounted and photographed.

Western blot assayCells were harvested, lysed, and the total protein was extracted

with RIPA buffer (50 mmol/L Tris–HCl pH 7.4, 150 mmol/LNaCl, 1% NP-40, 0.25% Na-deoxycholate, 1 mmol/L EDTA, and1mmol/L NaF), together with a protease and phosphatase inhib-itor cocktails (Sigma). Lysates were resolved on 10% SDS-PAGEand immunoblotted with the indicated antibodies. ERa (SantaCruz Biotechnology, sc-8002), b-actin (Sigma, A5441), and anti-mTOR, anti-p-AKT, and anti-p70s6k (Cell Signaling Technology,catalog nos. 9234, 9271, and 9234).

Seahorse analysisOxygen consumption rate (OCR) and extracellular acidifica-

tion rate (ECAR) measurements were performed with a SeahorseXF 96 Analyzer from Seahorse Bioscience (Agilent) according tothe manufacturer's instructions. Cells expressing WT, Y537S, orD538Gmutationwere plated at a density of 1� 104 cells per well,treated with ethanol (0.003%) as control or E2 (10 nmol/L), 10replicates for each treatment. On the day of analysis, media waschanged to Seahorse XF Base Medium supplemented with1 mmol/L glutamine for the glycolysis stress test, or 1 mmol/Lpyruvate, 2 mmol/L glutamine, and 10 mmol/L glucose for themito stress test followed by incubation at 37�C in a non-CO2

incubator for 1 hour.

Mitochondrial respiration (OCR) was measured by theXF-96 Extracellular Flux Analyzer using Cell Mito Stress Test Kitfrom Seahorse Biosciences under basal conditions followedby the sequential addition of oligomycin (2 mmol/L), FCCP(0.5 mmol/L), rotenone (0.5 mmol/L), and antimycin A(0.5 mmol/L). Glycolysis activity (ECAR) was measured usingglycolysis test kit following sequential addition of glucose(10 mmol/L), oligomycin (1 mmol/L), and 2-deoxyglucose (2-DG;50 mmol/L). After each injection, four time points were recordedwith approximately 35minutes between each injection. The OCRand ECAR were automatically recorded and calculated by theSeahorse XF-96 Software. OCR and ECARwere normalized to cellnumber. Each experiment was repeated at least three times, and arepresentative experiment is shown. The basal respiration, protonleak, and ATP production are calculated by the Seahorse softwareas described in the Seahorse Report Generator manual (https://www.agilent.com/cs/library/usermanuals/public/Report_Generator_User_Guide_Seahorse_XF_Cell_Mito_Stress_Test_Single_File.pdf).

Gene expression analysisMicroarray studies. MCF-7 cells were seeded in 6-well plates(2 � 105 cells/well). Cells were transfected with either WT-ER or538G-ER for 48 hours. The experiment was performed in fullmedium containing 10%FBS. Forty-eight hours after transfection,RNA was extracted using TRizol reagent according to the manu-facturer's instructions. Gene expression analysis was conductedusing Affymetrix GeneChip Human Gene 1.0 ST arrays. UsingPartek Genomics Suite, a list of genes differentially expressedby 538G-ER compared with WT-ER was generated (>1.25 or<-1.25-fold change, P <0.05). Web-based applications and publicdatabases (DAVID, WebGestalt, GeneAnalytics, and String;refs. 22–25) were used to functionally categorize the genes andtheir regulation by the ER pathway.

RNAseq. MCF-7 cells stably expressing WT-ER or 537S-ER weregrown in triplicates with 7 mmol/L glucose and/or 8 mmol/Lglutamine treated with E2 (10 nmol/L) for 24 hours. Total RNAwas extracted using the High Pure RNA Isolation Kit (Roche).RNAseq and bioinformatics were conducted at the INCPM (TheMantoux Bioinformatics Institute of the Nancy and StephenGrandIsrael National Center for Personalized Medicine and WeizmannInstituteof Science, Rehovot, Israel). For sequencing, briefly, 500ngof total RNA was fragmented followed by reverse transcription andsecond strand cDNA synthesis. The double-strand cDNA wassubjected to end repair, A-base addition, adapter ligation, andPCR amplification to create barcoded libraries. Libraries wereevaluated by Qubit and TapeStation. Sequencing was conductedwith NextSeq SR75 v2 (Illumina) at 75 cycles, single read kit. Theoutput was approximately 21 million reads per sample.

Bioinformatics: Poly-A/T stretches and Illumina adapters weretrimmed from the reads using cutadapt (26); resulting readsshorter than 30 bp were discarded. Reads were mapped to theHomo Sapiens GRCm38 reference genome using STAR (ref. 27;with EndToEnd option and outFilterMismatchNoverLmax ¼0.04), supplied with gene annotations downloaded fromEnsembl release 88. Expression levels for each gene were quan-tified using HTSeq-count (28), using the Ensembl annotations.Differentially expressed genes were identified using limma-voom (29). Pipeline was run using snakemake (30). Pathwayand function enrichment and heatmaps of genes associated withspecific pathways were generated.

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Chromatin immunoprecipitation assayChromatin immunoprecipitation (ChIP) assay was carried out

with the ChIP Assay Kit (Millipore Temecula) as described else-where (31) using anti-ERa antibody (Millipore Temecula). ER-bound DNA was amplified by qRT-PCR with primers spanningAP1 motif on the promoters of SNAI, SNAI2, and MMP1, orspanning ERE site at GREB1 promoter (32):

GREB1 Forward: GTGGCAACTGGGTCATTCTGA

Reverse: CGACCCACAGAAATGAAAAGG

SNAI1 Forward: TCCTACTTTGGCTAGGGTGAReverse: GGTAGTGTACAGAGACAATTTAAACAC

SNAI2 Forward: GCTCTCCAGCTAGAACCAGReverse: CAACCTGAAGGGCAGAACTA

MMP1 Forward: GGAGTCACCATTTCTAATGATTGCReverse: TATAGAGTCCTTGCCCTTCCA

qRT-PCRTwo days after transfection with the various constructs, total

RNAwas prepared using theHigh Pure RNA IsolationKit (Roche).Total RNA (1 mg) was reverse transcribed using qScript cDNASynthesis Kit (Quanta Biosciences). qRT-PCR was used to deter-mine mRNA level. Primers were designed using Primer Express(Applied Biosystems) and synthesized by Integrated DNA Tech-nologies and are listed below. Amplification reactions were per-formedwith PlatinumqPCRSuperMix in triplicate using StepOnePlus (Applied Biosystems). PCR conditions: 50�C for 2 minutes,95�C for 2minutes, followed by 40 cycles of 95�C for 15 seconds,60�C for 45 seconds.

The following primers were used:

SERPINB9 (human) Forward: GACTAGGTGGCAGGCCCReverse: ACACGTTGTGCGAAGGGTTA

MGP (human) Forward: TGTGTTATGAATCACATGAAAGCAReverse: GTGGACAGGCTTAGAGCGTT

IL17RB (human) Forward: ATTTCACCTCACCAGGCTGCReverse: CCAGGGGAGTGGTTGTGAAG

TMOD1 (human) Forward: GCGTCCGGGTATTACTCAGCReverse: TTCCAGGGTCCTCAGCTCTT

SNAI1 (human) Forward: CCAGTGCCTCGACCACTATGReverse: CTGCTGGAAGGTAAACTCTGGA

SNAI2 (human) Forward: TCGGACCCACACATTACCTTGReverse: AAAAGGCTTCTCCCCCGTGT

CPM (human) Forward: CCTGGGACCTGAACATGGACReverse: AACGCTTCCATCCCTTCCTG

CST1 (human) Forward: GGTACTAAGAGCCAGGCAACAReverse: GAGCACAACTGTTTCTTCTGC

MMP1 (human) Forward: AGTCCAGAAATACCTGGAAAAATACReverse: TTTTTCAACCACTGGGCCAC

MMP13 (human) Forward: GGAATTAAGGAGCATGGCGACReverse: GCCCAGGAGGAAAAGCATGA

PDK4 (human) Forward: ACAGAGGAGGTGGTGTTCCCReverse: AAACCAGCCAAAGGAGCATTC

PGLYRP (human) Forward: CGCTGGGATTCTTGTACGTGReverse: AGCCCACCACGAAACTGTAG

TFF2 (human) Forward: ATGGGACGGCGAGACGCCCAReverse: TTAGTAATGGCAGTCTTCCACAG

ACSS1 (human) Forward: GTATGATCGCTCCTCCCTGCReverse: ACCTGTTTCTGTCTGCCACC

Metabolom assayWT-ER- and 537S-ER–expressing cells (in quadruplicates) were

grown in phenol-freemediawith 10%charcoal-treated serumandtreated with E2 (10 nmol/L) for 24 hours. Frozen cells (100 mg)were submitted to Metabolon, Inc for sample extraction andanalysis. In brief, samples were prepared using the automatedMicroLab STAR System from Hamilton Company. Several recov-ery standards were added prior to the first step in the extractionprocess for QC purposes. To remove protein and to recoverchemically diverse metabolites, proteins were precipitated withmethanol under vigorous shaking for 2 minutes followed bycentrifugation. The resulting extractwasdivided intofive fractions:two for analysis by two separate reverse-phase (RP)/UPLC-MS/MSmethods with positive ion mode electrospray ionization (ESI),one for analysis by RP/UPLC-MS/MSwith negative ionmode ESI,one for analysis by HILIC/UPLC-MS/MS with negative ion modeESI, andone samplewas reserved for backup. Sampleswere placedbriefly on a TurboVap (Zymark) to remove the organic solvent.The sample extracts were stored overnight under nitrogen beforepreparation for analysis. The sample extract was dried, and thenreconstituted in solvents compatible to each of the four methods.Each reconstitution solvent contained a series of standards atfixedconcentrations to ensure injection and chromatographic consis-tency. One aliquot was analyzed using acidic positive ion condi-tions, chromatographically optimized for more hydrophilic com-pounds while another aliquot was optimized for more hydro-phobic compounds. Another aliquot was analyzed using basicnegative ion optimized conditions using a separate dedicatedC18column. The basic extracts were gradient eluted from the columnusing methanol and water. The fourth aliquot was analyzed vianegative ionization following elution from a HILIC column(Waters UPLC BEH Amide 2.1 � 150 mm, 1.7 mm) using agradient consisting of water and acetonitrile with 10 mmol/Lammonium formate. Mass spectrometry (MS) analysis alternatedbetweenMS and data-dependentMSn scans using dynamic exclu-sion. The scan range varied slighted betweenmethods but covered70–1000 m/z. Statistical analysis of log-transformed data wasconducted using "R" (http://cran.r-project.org/) or JMP.

Mice tumor xenograft studiesMice maintenance and experiments were carried out under

institutional guidelines of the Sourasky Medical Center (Tel Aviv,Israel) in accordance with current regulations and standards ofthe institution Animal Care and Use Committee. We used anorthotopic model to test the tumorigenic properties of MCF-7cells stably expressing WT-ER, 537S-ER, or 538G-ER. Femaleathymic nude mice (Balb/c background), 4–6 weeks of age werepurchased from Envigo RMS. The mice were housed and main-tained in laminar flow cabinets under specific pathogen-freeconditions. Tumors were induced by injecting 0.5 � 106 cells/100mLDMEMwith5%FCS intomammary fat pad, 7mice per cellline. Local tumors were measured twice a week using a caliper.Tumor volume was evaluated by the ellipsoid volume calculationformula 0.5 � (length � width2).

Statistical analysisResults are presented as mean � SD. Tumor volume graph is

presented as mean � SEM. Continuous variables were comparedusing t test. All significance testswere two-tailed and a P<0.05wasconsidered as statistically significant. In the Metabolom studyWelch two-sample t test was used. The random forests were





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created using a cross-validationmethod where each tree is createdleaving out a subset of samples. To validate the tree, each samplereceives votes for group placement for each tree that was excludedfrom the creation of. On the basis of those votes, each sample is"predicted" to be in one of the groups. The predictive accuracy isbased on the comparison of these predictions from the validationwith the actual groups that the samples are in.

ResultsLBD mutations confer a more aggressive phenotype to cancercells

We have previously shown, using overexpression studies, that538G-ER enhances proliferation and migration of breast cancercells (2). Here we aimed to test the effects of mutated ER expressedat physiologic levels on breast cancer cells. For this purpose, wegenerated MCF-7 cells stably expressing either WT-ER, 537S-ER, or538G-ER, under PGK promoter (18), allowing expression of ER atnear physiologic levels at protein level and mRNA level (Supple-mentary Fig. S1A and S1B). Several single-cell clones were gener-ated for each ER and two with typical activity (SupplementaryFig. S1C and S1D), were verified for exogenous ER expression, wereselected, grown separately, and mixed prior to each experiment.

The viability of 537S-ER, 538G-ER, and of WT-ER MCF-7 wasassessed usingMTT (Fig. 1A) andmethylene blue assays (Fig. 1B).For MTT, cells were grown in full serum and medium containingphenol red for 48 or 72 hours. Both 537S-ER- and 538G-ER–expressing cells exhibited significantly enhanced proliferationcompared with WT-ER–expressing cells (P < 0.05 for allcomparisons; Fig. 1A). Formethylene blue assay, cells were grownin estrogen-depleted medium and treated with either a vehicle orE2 for 72 hours. Both 537S-ER- and 538G-ER–expressing cellsexhibited significantly enhanced proliferation, either with orwithout E2 treatment (P < 0.05 for all comparisons; Fig. 1B).

Anchorage-independent growth is a hallmark of the neoplasticphenotype. To assess the effects of mutated ER expression onanchorage-independent growth, growth of these cells in soft agarwas examined in the presence or absence of E2. In the absence ofE2, WT-ER cells did not form colonies whereas 537S-ER cellssuccessfully growunder these conditions (P<0.05; Fig. 1C).Uponaddition of E2, expression of 537S-ERwas associatedwith a 300%increase of colony formation and growth compared with WT-ER(P < 0.05; Fig. 1C). Similar results were observed with 538G-ERcells (��, P < 0.01; ��, P < 0.005; Fig. 1D).

Next we aimed to determine the tumorigenicity profile ofmutated ER–expressing cells compared with WT-ER cells, to formtumors in nude mice. Nude mice were inoculated into themammary fat pad with WT-ER, 537S-ER, or 538G-ER MCF-7

cells, 7 mice per group. Tumor volume was measured twice aweek (Fig. 1E). Twenty days postinoculation, the tumors formedby the 538G mutant were 3-fold larger than those formed by theWT(P<0.05; Fig. 1E),while the 537Swere 5-fold larger than thoseformed by the WT (P < 0.05; Fig. 1E).

Enrichment of aggressive-related gene expression in mutatedER–expressing cells

As depicted above (Fig. 1) themutated ERs confer an aggressivephenotype to breast cancer cells beyond that of activated WT-ER.We therefore hypothesized that the LBD-mutated ER may showdifferential regulation of gene expression compared with WT-expressing cells, even in the presence of estrogen. To test this, weperformed anmRNA expression screen of MCF-7 cells transfectedwith either 538G-ER or WT-ER and grown in conditions thatWT-ER is also transcriptionally active, that is, full serum (withoutcharcoal stripping) and medium containing phenol red. Hierar-chical clustering showed 72 differentially expressed genes in538G-ER cells compared with WT-ER genes (1.25-fold, P <0.05), of them 59 were upregulated in the mutant comparedwith WT (Fig. 2A) and a list of most upregulated genes associatedwith aggressiveness is detailed (Table 2B). Classic ERE-regulatedtranscripts (e.g., GREB1 and PR) were not upregulated in thisscreen, indicating that the differentially regulated genes are notassociated with classic ER-affected genes but with a unique effectof 538G-ER. Function analysis of these genes using GeneAnalyticsrevealed a significant enrichment of ECM remodeling, ECMdegradation, and matrix metalloproteinases pathways (Fig. 2C;Supplementary Fig. S2A). Importantly, we observed also signalingpathways associated with tumorigenesis like G-protein Rasfamily GTPases and TGFb. Most of the array results were validatedusing qRT-PCR (Fig. 2F and G) and validated genes includedgenes known to be associated with invasion and metastases (e.g.,SERPIN9, SNAI1, SNAI2, MMP1, and MMP13), as well astumor metabolism (e.g., PDK4 and ACSS1). The expression ofthese genes was also studied in T47D, expressing either 538G-ERor 537S-ER or WT-ER. While similar pattern was observed, adifferential expression of certain genes was noted. For example,537S-ER induced a nearly 30-fold increased expression ofMGP inMCF-7 cells, whereas in T47D its effect was much milder.

We next conducted transcriptomic analysis and comparedMCF-7 cells expressing 537S-ER without E2 treatment withWT-ER treated with E2. As noted for 538G-ER–expressing cells,pathway enrichment analysis of untreated 537S-ER cells revealedan increase in genes related to extracellular matrix degradationand to ERK and AKT pathways, even when compared withWT-ER–treated cells (score 31.86, P < 0.0001; Fig. 2D; Supple-mentary Fig. S2B). This analysis demonstrated a clear separation

Figure 1.LBD-ERmutations confer a more aggressive phenotype to breast cancer cells. MCF-7 cells were infected with either 537S-ER, 538G-ER, orWT-ER lentiviralparticles, where ER expression is under PGK promoter. Two clones of each genotype, which were grown separately andmixed prior to each experiment wereused. A, 537S-ER, 538G-ER, andWT-ER MCF-7 cells were seeded in 96-well plates and grown in estrogen-depleted medium. Twenty-four hours later, cells weretreated with E2 and viability was assessed at indicated time points using MTT assay. Each bar represents� SD (�� , P < 0.001). B, 537S-ER, 538G-ER, andWT-ERMCF-7 cells were seeded in 96-well plates and grown in estrogen-depleted medium. Twenty-four hours later, cells were treated with E2 for 72 hours and cellgrowth was assessed using methylene blue. Each bar represents� SD (�� , P < 0.01 and �� , P < 0.001). C,Anchorage-independent growth was studied by soft-agar assay. A 0.6% bottom layer agarose in estrogen-depleted medium� 2 (control, left or with E2, 10 nmol/L, right) was prepared in 6-well culture plates. Ontop, MCF7 cells expressingWT-ER or 537S-ER were seeded, 2� 104 cells/well, on a layer of 0.3% agarose in estrogen-depleted medium� 2. Triplicates wereperformed for every condition and after 4 weeks colonies (above 10 cells) were counted and photographed. A representative experiment out of two is shown.Quantitation represents� SD (� , P < 0.05 and �� , P < 0.001). D, Similar to C, only 538G-ER cells were studied (��, P < 0.01; �� , P < 0.001). E,Mutated ER formslarger tumors compared withWT-ER MCF-7 cells. Athymic nudemice were injected withWT-ER, 537S-ER, and 538G-ER cells (7 mice per group) into themammary fat pad. Tumor volume was measured twice a week. Bar graph, average� SEM (� , P < 0.05).






between E2-regulated genes and genes that are uniquely regulatedby 537S-ER activity (Fig. 2E).

To decipher whether the mutated ERs bind directly to thepromotors of the genes that were upregulated in the mRNAexpression screen, we performed a ChIP assay and assessed

binding of the ER to the promoters of SNAI1, SNAI2, MMP1, orGREB1 as a control for ER binding. The ER can bind apart of EREother motifs like FOXA1 and AP1 (33). As no ERE- or FOXA1-binding sites are present on these promoters (except for GREB1)we assessed binding to AP1 sites. ChIP assay indicated that while

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0.001054670.001900040.0316528

Figure 2.

LBD-ERmutations upregulate genes involved in migration and invasion.A,MCF-7 cells were transfected withWT-ER or 538G-ER and grown in complete media(not E2 depleted) for 48 hours. RNAwas then extracted and gene expression analysis was conducted using AffymetrixGeneChip. Using Partek Genomics Suite aheatmap of differentially expressed genes was generated. B, A list of genes differentially expressed by 538G-ER was generated (>1.25 or <1.25-fold, P < 0.05) andthe genes most upregulated by 538G-ER are shown, among them invasion related genes. C, Pathway enrichment analysis was conducted using GeneAnalytics (25). Results show that 538G-ER overexpression is associated with ECM degradation and activation of protumorigenic pathways. D, Transcriptomeanalysis of 537S-ER compared withWT-ER MCF-7 cells. Cells were grown in estrogen-depleted mediumwith 10% charcoal-treated serum, with 7 mmol/L glucoseand 8mmol/L glutamine, and onlyWT-ER cells were treated with E2 (10 nmol/L) for 24 hours. RNAwas extracted and RNAseq was performed. The resultsrevealed an increase in genes related to extracellular matrix degradation. E, Dissection of genes differentially regulated by 537S-ER compared with WT-ER.There are 906 genes which are differentially expressed between 537S-ER andWT-ERþE2 (fold change of 2 with PFDR < 0.05). These are labeled in red in the plotand represent the unique signature of 537S-ER. F, Validation of RNAmicroarray and RNAseq results. MCF-7 cells transfected with 538G-ER or stably expressing537S-ER were treated as in A. RNA was then extracted andmRNA levels were determined by qRT-PCR. G, T47D cells were transfected with 537S or 538G-ER,treated as inA andmRNA levels were determined as in F. The results shown here are an average of two independent experiments each performed in biologicaltriplicates. Each bar represents� SD. H,WT-ER, 537S-ER, and 538G-ER MCF-7 were seeded in 20 cm plates, treated with vehicle or E2 (10 nmol/L) for 24 hours,and lysed. ChIP assayswere performed using ER-directed antibodies or control IgG (not shown). ER bound DNAwas amplified using primers directed againstERE site in GREB1 promoter and AP1 site in SNAI1, SNAI2, and MMP1 promoters. The figure shows representative results of at least three independentexperiments. Each bar represents� SD (�� , P < 0.01 and �� , P < 0.001).

Zinger et al.





all ERs bind to the GREB1 promoter, neither the WT-ER nor themutated ERs bind directly to SNAI1, SNAI2, or MMP1 promoters(Fig. 2H).

PI3K-AKT-mTORpathway is activated by 538G-ER and 537S-EROne of the hallmarks of cancer is the unique metabolism of

cancer cells (34). As cells expressing the LBD-activatingmutations

Figure 3.

537S-ER cells display a unique metabolic profile compared withWT-ER. 537S-ER andWT-ER MCF-7 cells were grown in estrogen-depleted media with 10%charcoal-treated serum and then treated with E2 or control vehicle (veh) for 24 hours. Cells were snap frozen andmetabolic profiling was determined using MS.A, The number of significantly (P < 0.05), and borderline significantly (0.05< P < 0.01) altered metabolite, as a function of treatment or ERmutation, wasanalyzed. B, A Venn diagram of significantly (P < 0.05) altered metabolites in the different groups is depicted (P < 0.05). C, Random Forest classification usingnamedmetabolites ofWT-Veh compared withWT-E2; WT-Veh compared with Y537S-Veh (D); andWT-E2 compared with Y537S-Veh (E).






showamore aggressive phenotype,wehypothesized that theywillalso showdifferentmetabolic activity. To test thiswefirst analyzedactivity of the PI3K-AKT-mTOR pathway, a major regulator ofbreast cancer cell metabolism (13). In accordance with a recentobservation (10), we noted activation of the PI3K-AKT-mTORpathway in MCF-7 cells stably expressing 537S-ER or transientlyexpressing 538G-ER and noted enhanced phosphorylation ofAKT, mTOR and its down-stream target S6K (SupplementaryFig. S4A). We aimed to elucidate whether this pathway underliesthe increased activity of the mutants. Gene expression analysisof CST1 (gene activated only bymutated ER, Fig. 2) andmigrationassay showed that mTORC1 inhibition using rapamycin onlypartially inhibited these activities (Supplementary Fig. S4Band S4C).

537S-ER exhibits distinct metabolic properties compared withactivated WT-ER

To further characterize the effect of 537S-ER on the metabolicactivity of breast cancer cells, we conducted a metabolomicprofiling of MCF-7 cells expressing either WT-ER or 537S-ER(described above, Fig. 1). For the analysis, cells were treated witheither a vehicle control or E2, harvested 24 hours later, and ametabolomic screen was conducted as described under "Mate-rial and Methods". Treatment of WT-ER cells with E2 yielded209 metabolite showing significant change (P < 0.05, eitherup or downregulation), compared with untreated cells (E2-dependent metabolites). However, comparisons of differential-ly regulated metabolites in 537S-ER–expressing cells comparedwith untreated or E2-treated WT-ER–expressing cells revealed370 and 225 metabolites, respectively. This indicates additionalactivity gained by cells expressing the mutated ER. Treatment of537S-ER cells with E2 did not lead to major metabolic changes(Fig. 3A).

To further reveal a metabolic profile of 537S-ER cells, which isdistinct from that of activated WT-ER, the identity of the different

metabolites shared by each of the above groups was analyzed(Fig. 3B). Treatment of WT-ER with E2 resulted in a decrease of183 metabolite, most of them (150/183, 82%) also observed inWT-ER versus 537S-ER. However, these metabolites compriseonly a minority (150/370, 47%) in WT-ER versus 537S-ER com-parison. Likewise, the comparison between 537S-ER andWTþE2yielded a decrease in 164 metabolite, most of them (136/164,83%) observed in WT-ER versus 537S-ER. But, again, these meta-bolites comprise only a minority (178/370, 42%) in WT-ERversus 537S-ER comparison. Importantly, only 65 metaboliteswere downregulated in both groups (WT vs. WTþE2 and 537 vs.WTþE2, 35% and 39%, respectively).

Random Forest classification using named metabolites ofuntreated WT-ER–expressing cells versus E2 treated gave a pre-dictive accuracy of 100% (Fig. 3C). The top-ranking metabolitesand pathways identified were energy, plasma membrane lipids,and amino acid metabolites. These are all considered to be E2-dependent metabolites. Classification of untreated WT-ER versus537S-ER–expressing cells gave a predictive accuracy of 100%(Fig. 3D). The top-ranking metabolites and pathways identifiedwere amino acid metabolites and plasma membrane associatedlipids. This list is expected to include both E2-dependent and-independent metabolites. Classification of E2-treated WT-ER–expressing cells compared with 537S-ER–expressing cells gave apredictive accuracy of 87.5% (Fig. 3E). The top-ranking metabo-lites and pathways in this comparison include plasmamembranelipids, amino acids metabolism, and carbohydrate metabolismand these are expected to be E2 independent. Data generated fromthe metabolomics screen was used for a metabolic pathwayenrichment analysis. The major pathways differentially affectedin 537S-ER–expressing cells were glycolysis and TCA cycle (Fig. 4).Main glycolytic intermediates were found to be reduced by morethan 50% in 537S-ER versus WT-ER–expressing cells (Fig. 4A,both E2-treated, P < 0.05). On the other hand, expression of537S-ER led to an increase in thefirst half of TCA cyclemetabolites

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537S-ER regulates TCA cycle and glycolytic metabolites levels. Glycolysis metabolites levels (A) and TCA cycle (B), driven frommetabolon analysis (Fig. 3), areshown. 537S-ER andWT-ER MCF-7 cells were grown in estrogen-depleted media with 10% charcoal-treated serum and then treated with E2 or control vehicle for24 hours andmetabolite levels were determined using MS. Mut, mutant.

Zinger et al.





Figure 5.

LBD-ERmutations elevate metabolic activity of breast cancer cells. Cellular metabolismwas studied by monitoring ECAR (A and C) and OCR (B and D) usingSeahorse technology. WT-ER, 537S-ER, or 538G-ER cells (described in Fig. 1) were treated with E2 (10 nmol/L) or control, for 24 hours. A and C, Glycolyticactivity was measured using Glycolysis Test Kit (Seahorse Biosciences). The figure depicts a representative graph output of at least three independentexperiments showing the ECAR response to glucose (10 mmol/L), oligomycin (1 mmol/L), and 2-DG (50 mmol/L). B and D,Mitochondrial respiration wasmeasured using cell mito stress test kit under basal conditions followed by the sequential addition of oligomycin (2 mmol/L), FCCP (0.5 mmol/L), rotenone(0.5 mmol/L), and antimycin A (0.5 mmol/L). The figure depicts a representative graph output of at least three independent experiments. Each bar represents�SD (�� , P < 0.01 537S-ER vs. WT-ERþE2; �� , P < 0.001 538G-ER vs. WT-ERþE2).






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Zinger et al.





(i.e., citrate, isocitrate, aconitate, anda-ketoglutarate) and a decreasein the second half (i.e. succinate, fumarate, and malate; Fig. 4B).

Mutated ER increases mitochondrial activity compared withWT-ER cells

Direct analysis of ECAR, indicating glycolytic rate, and OCR,indicating mitochondrial activity, of MCF-7 cells expressingeither WT-ER, 537S-ER, or 538G-ER was conducted using Sea-horse technology and revealed similar glycolytic rate forboth cells (Fig. 5A), but enhanced mitochondrial respirationof 537S-ER–expressing cells compared with WT-ER cells(P < 0.01; Fig. 5B). Similar results were obtained in 538G-ER–expressing cells (Fig. 5C and D). These data indicateE2-independent increased metabolic activity of MCF-7 cellsexpressing LBD-activating mutations. Similar results wereobtained in 537S-ER T47D cells (Supplementary Fig. S5).Interestingly, the mitochondrial activity of 538G-ER T47D cellswas not elevated (Supplementary Fig. S5). Similarly, it wasrecently published that the IGF-1R pathway is more responsivein 537S-ER T47D cells, whereas T47D-expressing 538G-ER cellsdid not exhibit a similar activity (35).

We assessed the effect of rapamycin on cellular metabolism.Interestingly, the results indicated that addition of rapamycinincreased the mitochondrial activity of all the cells, whereas theglycolytic rate was slightly lower upon rapamycin addition,although did not reach statistical significance (SupplementaryFig. S4D and S4E).

Glutamine supports aggressive behavior of mutated-ER–expressing cells

The TCA cycle can be fed by either pyruvate derived fromglucose and glycolysis or alternative sources, among them gluta-mine (36). Thus, glutamine can undergo glutaminolysis byglutamine synthetase to yield glutamate, which can be furtherdeaminated into a-ketoglutarate and enter the TCA cycle.Glutamine and glutamate metabolism correlates with the expres-sion of EMT-associated transcription factors (37) and glutami-nolysis may serve as a driver of invasiveness of breast cancercells (38). To analyze the contribution of glutamine to theaggressive behavior of 537S-ER–expressing cells, MCF-7 cellsexpressing either 537S-ER or WT-ER, were grown in the presenceof E2 under glucose deprivation conditions (described under

"Material and Methods"). Transcriptomic analysis by RNAseqrevealed enrichment in pathways related to extracellular matrixdegradation and ER stress in 537S-ER compared with E2-treatedWT-ER cells (score 21, P < 0.05; Fig. 6A; Supplementary Fig. S6). Aheatmap of the relevant ECM degradation–related genes wasgenerated, and revealed a striking difference between WT and537S-ER cells (two distinct sample clusters). Importantly, itrevealed two gene clusters (MMP1, LOX) and (ITGA5, LRP4) inwhich their expression is upregulated specifically when 537S-ERcells were grown with glutamine as a sole carbon source (Fig. 6B).Interestingly, classic ERE-regulated genes were upregulated byboth E2-treated WT and 537S-ER cells mostly when incubatedwith glucose and not glutamine (Fig. 6B). Of interest, 537S-ERcells grown with glucose form a separate cluster with highestincrease in these genes. This was validated by direct measurementof ECM degradation–associated gene MMP1 and of classic ERE-regulated gene progesterone receptor (PR) under glucose and/orglutamine deprivation (Fig. 6C). Expression of PR was increasedapproximately 20-fold in WT cells treated with E2 and approx-imately 45-fold in 537S-ER, under exposure to glucose. Yet,expression of MMP1, increased only in 537S-ER and in thepresence of glutamine. Similar results were obtained in 538G-ER-expressing cells (Fig. 6D). We aimed to reveal whether theaggressive-related gene expression is reflected also in the aggres-sive behavior of the cells. Cellmigration experiments showed thatwhile WT-ER–expressing cells required glucose for migration,537S-ER–expressing cells were able to migrate in the presenceof either glucose or glutamine (Fig. 6E). Thus, these results suggestthat 537S-ER cells, in opposite to WT-ER cells, can use glutamineas a carbon source to promote their aggressive phenotype (sum-marized in Fig. 6F).

DiscussionThe detection of LBD-activating mutations of ESR1 was

shortly followed by clinical observations suggesting an associ-ation between these mutations and adverse outcome (6). Theseobservations raised the question whether the mutated ER issimply an activated ER or does it harbor a gain-of-functionphenotype. While previous studies focused mostly on ligand-independent activity of the mutated receptor and examined itsactivity under estrogen-deprivation conditions (10, 39), we

Figure 6.The aggressive phenotype of 537S-ER cells is glutamine dependent. A, Transcriptomic analysis was conducted to 537S-ER andWT-ER MCF-7 cells, grown inE2-depleted mediumwithout glutamine or glucose (��), with glutamine (gln, 8 mmol/L), glucose (glc, 7 mmol/L) or both, whereWT-ER cells were treated withE2 (10 nmol/L) for 24 hours. RNAseq analysis was performed as described in Fig. 2. Pathway enrichment analysis conducted revealed pathways related toaggressive phenotype in 537S cells grownwith glutamine. B, Heatmaps of ECM-related genes and ERE-regulated genes were generated. C, 537S-ER andWT-ERcells were grown in E2-depleted medium under deprivation from glucose or glutamine with different concentrations as noted. Cells were then treated withvehicle or 10 nmol/L E2 for 24 hours. RNAwas then extracted and the expression of PR and MMP1 mRNAwas quantified by qRT-PCR. Values were normalized tob-actin levels and plotted relative to the expression ofWT cells (without E2). Results shown are representative results of three independent experiments, eachperformed in triplicates. Each bar represents� SD. D, 538G-ER andWT-ER were grown and treated as in C. RNAwas then extracted and the expression of PR,MMP1, and MMP13 mRNAwas quantified by qRT-PCR. Values were normalized to b-actin levels and plotted relative to the expression ofWT cells (without E2).Results shown are representative results of three independent experiments, each performed in triplicates. Each bar represents� SD. E, 537S-ER aggressivephenotype is supported by glutamine. A scratch assay was conducted to 537S-ER andWT-ER cells. Cells were grown in E2-depleted medium. The monolayerwas scraped, treated with either glucose (7 mmol/L), glutamine (8 mmol/L), their combination, or neither, with or without E2 (10 nmol/L). Cells werephotographed at time 0 and 24 hours. Two independent experiments were performed and a representative experiment is shown. Each bar represents� SD(�� , P < 0.01; �� , P < 0.001). The results show that glucose deprivation inhibits onlyWT-ER cells with no effect on 537S-ER cells, demonstrating that glutamineis sufficient to support 537S-ER aggressive behavior. F, A scheme showing the metabolic routes used by 537S-ER cells. WhileWT-ER cells exploit glucose astheir main carbon source and utilize glycolysis, 537S-ER –expressing cells utilize glutamine which feed the TCA cycle. The differential gene expression inducedby 537S-ER, characterized by ECM degradation (MMP1 gene as an example) employs glutamine and is sufficient to drive the more aggressive phenotype of537S-ER cells.






studied its activity in the presence of estrogen, under conditionsbetter mimicking its activity in patients with breast cancer. Weshow here that harboring LBD-activating mutations leads tometabolic activity associated with aggressiveness and is asso-ciated with higher tumorigenic characteristics of breast cancerscells in vitro and in vivo.

We initially noted activation of the mTORC1 in cells expres-sing the mutated ER. As the mTOR pathway is a major regulatorof cell metabolism, we hypothesized that the metabolic activityof these cells will be different from cells expressing WT-ER. Theresults we present suggest that mTORC1 pathway activationcontributes to the enhanced activity of mutated ERs, althoughother factors play an important role in their enhanced aggres-sive phenotype. Several studies described metabolic alterationsin breast cancer cells. Yet, the metabolic landscape of ERþ breastcancer cells and the metabolic effects of estrogen have not beenelucidated. While a single study noted increased glucose uptakeand glycolysis in MCF-7 cells following E2 treatment (18) ametabolic screen of relatively small number of metabolitescould not verify changes in energy metabolites (19). A meta-bolomic profiling of tumors noted differences between ERþ andER� tumors but did not evaluate the activity of estrogen (40).For this study we used a metabolomic profiling platform thathas been thoroughly validated (41). The metabolic profilingenabled a clear classification and separation between untreatedWT-ER cells, E2-treated WT-ER cells, and 537S-ER cells.

This comprehensive analysis shed new light on the metaboliceffect E2 imposes onWT-ER–expressing cells and suggest a role forE2 in regulating energy, plasma membrane lipids, and amino acidmetabolites. Possibly, analysis of specific metabolites (detailedin Fig. 3C) can serve as a novel tool for the evaluation of activityof the ER pathway and aid in the classification of breast cancers.

The metabolic profiling enabled also a clear classificationand separation between E2-activated WT cells and 537S-ER–expressing cells. Our data show significant changes in thelevels of more metabolites in 537S-ER cells compared with WT(370 vs. 209), and most of the differentially regulated metabo-lites were E2-independent. Thus, the unique additional activityof LBD mutations directly affects metabolic activity. Analysisof the top ranking metabolites showing differential levels indi-cated plasma membrane lipids, amino acid metabolites, andcarbohydrates as the most common metabolic pathways affectedby 537S-ER (Fig. 3).These findings further support the transcrip-tomic data regarding the additive effect of the LBD-activatingmutations, even compared with E2 treatment.

As reported previously (40), we noted, by both, Seahorsetechnology and metabolic profiling, increased glycolysisfollowing E2 treatment. Yet, we did not observe increasedglycolysis in 537S-ER cells. On the other hand, we observedincreased mitochondrial activity in 537S-ER cells. Thus, anal-ysis of these cells indicated marked increase in levels of meta-bolites associated with the first half of the TCA cycle (citrate toa-ketoglutarate), along with an increase in mitochondrialactivities as evidenced by Seahorse analysis and increased ATPlevels. Interestingly, 537S-ER led to a decrease in the levelsof metabolites associated with second half of TCA cycle(succinate–malate). Several reasons may lead to this phenom-enon. It is possible that these TCA cycle intermediates areshunted to other pathways, including amino acid or nucleotidebiosynthetic pathways, thus leading to a decrease in their levels.Alternatively, pleurosis takes place in cancer cells when there is

a shortage in certain TCA cycle intermediates and glutamine isan important participant in these reactions (36). It is possiblethat cells expressing 537S-ER engage glutamine in other path-ways, thus not allowing it to participate in the pleurosis reac-tions. The mechanism underlying this needs to be furtherstudied, using labeled glucose and glutamine.

537S-ER and WT-ER cells showed differential dependencyon glucose and glutamine. Thus, while WT-ER cells rely onglucose and cannot utilize glutamine as an alternative carbonsource, 537S-ER cells may use either glucose or glutamineinterchangeably (Fig. 6D). This evidently yields an advantageto cells exposed to different environmental conditions. Ourstudy further implies that the exposure to glutamine in theabsence of glucose can, by itself, mediate aggressive phenotypeacquired by breast cancer cells expressing 537S-ER. Thus, thetranscription of MMP1, a gene strictly regulated by 537S-ERexpression and not WT-ER, was observed under glutamineexposure and glucose starvation, while expression of PR, a geneclassically regulated by E2-stimulated ER, depends mainly onglucose. The aggressive behavior which is supported by gluta-mine was exemplified also by migration assay. Thus, whileWT-ER–expressing cells require glucose to migrate, 537S-ER–expressing cells migrate under either glucose or glutaminedeprivation, it is not clear what role glucose or glutamine playin cell proliferation. This is the subject of our next studies. Theability of cells to thrive under glucose deprivation bestows aselective advantage and also ability to grow under specificmicroenvironment condition where glucose is scarce. Gluta-mine dependency was demonstrated in colorectal cancer cellswere PIK3CA mutations were shown to reprogram glutaminemetabolism. Thus, expression of mutant PIK3CA led to sub-stantially more conversion of glutamine to a-ketoglutarate inorder to replenish the TCA cycle to generate more ATP. Thisresulted in a more aggressive behavior as evidenced in higherproliferation rate and increased tumor growth (42). A correla-tion between glutamine dependency and increased aggres-siveness was also seen in ovarian cancer, where it was shownthat glutamine is required to promote cell proliferation (43). Inaddition, it was demonstrated that certain ovarian cancer celllines are glutamine-dependent while others are glucose depen-dent, and importantly, glutamine dependency correlated withmigration and invasiveness (44).

Interestingly, most of the genes uniquely regulated by themutated ERs do not contain an ERE motif in their promoterregion. Indeed, the ChIP assay results also confirm that themutated ERs do not directly bind these genes' promoters. Theseresults are in agreement with a recently published study thatrevealed a unique transcriptional activity of mutated ER, and thisactivity is mediated by ERE regions (33).

Taken together, this study shows for the first time that LBDmutations possess a more aggressive phenotype, beyond that ofactivated WT-ER, and this phenotype is associated with a uniquegene signature and metabolic pattern. Revealing these uniqueproperties may lead to the discovery of novel therapeutic targetsthat can be exploited to develop specific inhibitors for tumorsexpressing LBD mutations.

Disclosure of Potential Conflicts of InterestI. Wolf reports receiving speakers bureau honoraria and is a consultant/

advisory board member for Roche. No potential conflicts of interest weredisclosed by the other authors.


Zinger et al.




Authors' ContributionsConception and design: L. Zinger, M. Pasmanik-Chor, T. Rubinek, I. WolfDevelopment of methodology: L. Zinger, T. Rubinek, I. WolfAcquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): L. Zinger, K. Merenbakh-Lamin, A. Klein, S. Journo,T. Boldes, T. Rubinek, I. WolfAnalysis and interpretation of data (e.g., statistical analysis,biostatistics, computational analysis): L. Zinger, K. Merenbakh-Lamin,A. Klein, A. Elazar, T. Boldes, M. Pasmanik-Chor, A. Spitzer, T. Rubinek,I. WolfWriting, review, and/or revision of the manuscript: L. Zinger, M. Pasmanik-Chor, T. Rubinek, I. WolfAdministrative, technical, or material support (i.e., reporting or organizingdata, constructing databases): L. Zinger, T. Rubinek, I. WolfStudy supervision: T. Rubinek, I. Wolf

AcknowledgmentsThis work was financially supported by the Israel Science Foundation to

I. Wolf (grant nos. 1320/14 and 2385/15); the Israel Cancer Association toI.Wolf (grant no. 20160053); The Parasol Center forWomen's Cancer Research,The Parasol Foundation; Djerassi-Elias Oncology Institute, CBRC, Tel AvivUniversity, Tel Aviv, Israel to I. Wolf; The Margaret Stultz foundation, theSackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel to I. Wolf.

The costs of publication of this article were defrayed in part by the pay-ment of page charges. This article must therefore be hereby marked advertise-ment in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received June 7, 2018; revised December 18, 2018; accepted January 31,2019; published first February 7, 2019.

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Zinger et al.




2019;25:2900-2914. Published OnlineFirst February 7, 2019.Clin Cancer Res Lotem Zinger, Keren Merenbakh-Lamin, Anat Klein, et al. Cellular Metabolism of Breast Cancer Cells

activating Mutations of ESR1 Rewire−Ligand-binding Domain

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