Targeting the Metabolic Response to Statin-Mediated ... · Giovanny Rodriguez Blanco1, Gillian Mackay1, Colin Nixon1, Alexei Vazquez1,2, Owen J. Sansom1,2, and Jurre J. Kamphorst1,2,3

CANCER RESEARCH | METABOLISM AND CHEMICAL BIOLOGY

Targeting the Metabolic Response to Statin-MediatedOxidative Stress Produces a Synergistic AntitumorResponse A C

Grace H. McGregor1,2, Andrew D. Campbell1, Sigrid K. Fey1,2, Sergey Tumanov1,2, David Sumpton1,Giovanny Rodriguez Blanco1, Gillian Mackay1, Colin Nixon1, Alexei Vazquez1,2, Owen J. Sansom1,2, andJurre J. Kamphorst1,2,3

ABSTRACT◥

Statins are widely prescribed inhibitors of the mevalonate path-way, acting to lower systemic cholesterol levels. The mevalonatepathway is critical for tumorigenesis and is frequently upregulatedin cancer. Nonetheless, reported effects of statins on tumor pro-gression are ambiguous, making it unclear whether statins, alone orin combination, can be used for chemotherapy. Here, usingadvanced mass spectrometry and isotope tracing, we showed thatstatins only modestly affected cancer cholesterol homeostasis.Instead, they significantly reduced synthesis and levels of anotherdownstream product, the mitochondrial electron carrier coenzymeQ, both in cultured cancer cells and tumors. This compromisedoxidative phosphorylation, causing severe oxidative stress. To

compensate, cancer cells upregulated antioxidant metabolic path-ways, including reductive carboxylation, proline synthesis, andcystine import. Targeting cystine import with an xCT transporter–loweringMEK inhibitor, in combinationwith statins, causedprofoundtumor cell death. Thus, statin-induced ROS production in cancer cellscan be exploited in a combinatorial regimen.

Significance: Cancer cells induce specific metabolic pathways toalleviate the increased oxidative stress caused by statin treatment, andtargeting one of these pathways synergizes with statins to produce arobust antitumor response.

See related commentary by Cordes and Metallo, p. 151

IntroductionThe mevalonate pathway plays an important role in cellular

and systemic physiology, with downstream pathways contributingto the proper functioning of a diverse set of biological processes.Synthesis of mevalonate occurs by concatenating 3 acetyl-CoAmolecules, followed by a reduction step by the enzyme HMG-CoAreductase. Mevalonate is then subject to further phosphorylationand decarboxylation steps, together catalyzing the production of5-carbon isoprenoid molecules, three of which are used to syn-thesize a 15-carbon farnesyl pyrophosphate (FPP) molecule(Fig. 1A). Isoprenoids and FPP feed into separate downstreampathways to produce a variety of biomolecules. These are (i)dolichols, which are made up of varying numbers of isopreneunits and act as anchors for glycosylation structures, (ii) prenylunits for protein prenylation, enabling their anchoring into

membranes (1), (iii) coenzyme Q (CoQ), or ubiquinone, anessential electron carrier in the electron transport chain (2), and(iv) cholesterol. Cholesterol is arguably the best studied productof the mevalonate pathway, and is an important lipid that acts as astructural component of mammalian cell membranes and aprecursor for the synthesis of steroid hormones, bile acid, andvitamin D (3).

Although cholesterol contributes to a variety of important physi-ologic processes, excess levels (hypercholesterolemia) are oftenobserved in individuals with metabolic syndrome, and it is stronglylinked to cardiovascular disease (4). This has spurred significantinterest into potential pharmacologic interventions, leading to thedevelopment of statins. These are a class of drugs that inhibit the rate-limiting enzyme producing mevalonate, HMG-CoA reductase(HMGCR), and are thought to exert their beneficial effect by normal-izing systemic cholesterol levels. Because of their favorable efficacy andsafety profiles, statins are now among the most widely prescribedmedicines in the clinic (5).

In recent years there have been many reports linking upregu-lated activity of the mevalonate and downstream metabolic path-ways to cancer development and progression (6, 7). For example, inbreast cancer, it was found that high HMGCR and additionalmevalonate pathway gene transcript levels correlated with poorprognosis (6). Likewise, comparison of pancreatic ductal adeno-carcinoma (PDAC) and normal pancreas tissue revealed stronglyderegulated cholesterol metabolism (8). In addition, it was recentlyshown that p53 represses the mevalonate pathway and this is onemechanism by which it suppresses tumor development (9). Finally,a commonly occurring driver oncogene, Ras, is prenylated tofacilitate its localization to the inside of the plasma membrane.This has been shown to cooperate with increased HMGCR levels topromote transformation (6).

1Cancer Research UK Beatson Institute, Glasgow, United Kingdom. 2Institute ofCancer Sciences, University of Glasgow, Glasgow, United Kingdom. 3RheosMedicines Inc, Cambridge, Massachusetts.

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

O.J. Sansom and J.J. Kamphorst are the co-senior authors of this article.

Corresponding Authors: Jurre J. Kamphorst and Owen J. Sansom, CancerResearch UK Beatson Institute, Garscube Estate, Switchback Road, Bearsden,Glasgow G61 1BD, United Kingdom. Phone: 44-141-330-3966; E-mail:[email protected]; Owen J. Sansom, Phone: 44-141-330-3953;E-mail: [email protected]

Cancer Res 2020;80:175–88

doi: 10.1158/0008-5472.CAN-19-0644

�2019 American Association for Cancer Research.

AACRJournals.org | 175

on March 2, 2021. © 2020 American Association for Cancer Research. cancerres.aacrjournals.org Downloaded from

Published OnlineFirst September 27, 2019; DOI: 10.1158/0008-5472.CAN-19-0644

http://crossmark.crossref.org/dialog/?doi=10.1158/0008-5472.CAN-19-0644&domain=pdf&date_stamp=2019-12-30

http://crossmark.crossref.org/dialog/?doi=10.1158/0008-5472.CAN-19-0644&domain=pdf&date_stamp=2019-12-30

http://cancerres.aacrjournals.org/

Despite the clear dysregulation of the mevalonate pathway in avariety of cancer types, robust evidence for a therapeutic benefit ofstatin treatment remains limited to only a subset of cancer types.Statin use in combination with androgen deprivation therapy

increased time to progression in prostate cancer (10). Similarly, inbreast cancer, statin use postdiagnosis led to a reduced risk ofrecurrence, although the largest increase was observed when statinuse was combined with angiotensin receptor blocker treatment (11).

A

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 540.00

0.05

0.10

[U13C]-glucose and [U13C]-glutamine Labeling of CoQ9

Number of 13C

Frac

tion

of a

ll is

otop

es

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 270.0

0.2

0.4

0.6

0.8

1.0[U13C]-glucose and [U13C]-glutamine Labeling of cholesterol

Number of 13C

Frac

tion

of a

ll is

otop

es

High serum (5% dFBS)Low serum (2% dFBS)

Ctl

Simva

0.0

0.5

1.0

KPC

Rel

ativ

e ce

ll nu

mbe

r ns

ns

Ctl

Simva

0.0

0.5

1.0

MIA-PaCa2

Rel

ativ

e ce

ll nu

mbe

r

Low serumHigh serumns

ns

Ctl

Simva

0.0

0.5

1.0

1.5

KPCR

elat

ive

pool

siz

eC

oQ9

/105 c

ells **

Ctl

Simva

0.0

0.5

1.0

KPC

Frac

tion

de n

ovo

synt

hezi

sed

CoQ

9 ****

De novo synthesized CoQ9

Unlabeledcholesterol from uptake

De novo synthesized cholesterol

12C13C

Partially labeledcholesterol

Fully labeledcholesterol from synthesis

TyrosineBenzoquinine

5C Isoprene unit

CoQ6-10

6-10

Farnesyl Pyrophosphate

Trans-Prenyl transferase

Mevalonate pathway

5C Isoprenoid

Glucose/Glutamine

Acetyl-CoA

Mevalonate

HMG-CoA

Farnesyl Pyrophosphate

CholesterolCoQ

HMGCRSta�n

Extracellular cholesterol

Cholesterol synthesis Cholesterol uptake

Dolichols Prenyla�on

B

C D

E

F G

Figure 1.

The cytostatic effect of statins ismediated through a decrease in coenzymeQ.A, Schematic overviewof themevalonate pathway.B,Cholesterol labeling distributionin KPC (Pdx1-Cre; KrasG12D/þ; Trp53R172H/þ) cells incubated with [U13C]-glucose and [U13C]-glutamine fed for 72 hours in either high serum (5% dFBS) or low serum(2% dFBS). Data was corrected for 13C natural abundance. The orange carbons on the cholesterol molecules represent 12C and the purple carbons represent 13C.C, Effect of simvastatin (Simva) on cell proliferation in high and low serum. KPC andMIA-PaCa2 cellswere treatedwith simvastatin in high (5%) or low (2%) serum for48 hours. Numbers are relative to vehicle (DMSO)-treated control. D, Schematic of CoQ biosynthesis using 5C (5 carbon) isoprene units from the mevalonatepathway. E, CoQ labeling pattern from [U13C]-glucose and [U13C]-glutamine fed to KPC cells for 48 hours. F, Fraction newly synthesized CoQ in KPC cells in vehiclecontrol (DMSO) and simvastatin-treated cells after 48 hours.G,CoQpool size in KPC cells treatedwith simvastatin for 48 hours. Values are relative to control. All datashown asmean� SEMof two (B), four (C), three biological replicates (D–G), each performed in triplicate. Statistical significancewas tested by ANOVA (C) and t test(F and G). �� , P < 0.01; �� , P < 0.0001; ns, nonsignificant. See also Supplementary Fig. S1.

McGregor et al.

Cancer Res; 80(2) January 15, 2020 CANCER RESEARCH176




Notably, in the subset of cancers where statins do appear to beeffective, this cannot merely be attributed to their effect on proteinprenylation (12), indicating that other parts of the mevalonate anddownstream pathways contribute to tumorigenesis and could beblocked to achieve clinical benefit.

This discrepancy between upregulated activity of the mevalonateand branching pathways, and the limited clinical effect of statins inmost cancer types, suggested to us that cells may be able to adapttheir metabolism in response to statin treatment. Here, we per-formed a comprehensive stable isotope tracing study with both 13Cand 2H tracers, to determine which branches of mevalonatemetabolism are active in cancer cells and tumors, and how theymay be affected by statin treatment. This led to the finding thatbiosynthesis of coenzyme Q (CoQ) was very pronounced incultured cells and in tumors. CoQ depletion due to statin treatmentcaused reduced oxidative phosphorylation and significantly ele-vated ROS production. Cancer cells in turn boosted redox–activemetabolic pathways to alleviate ROS levels, with increased cystineimport for glutathione production among the strongest responses.While statins on their own had modest cytostatic effects, combi-nation with a MEK inhibitor (AZD6244), which lowers xCT cystinetransporter levels, led to synergistic induction of cancer cell death.Thus, statins cause metabolic vulnerabilities, and targeting these ina combination treatment paradigm elicits powerful antitumoreffects.

Materials and MethodsCell culture

KPC mouse cells originally derived from Pdx1-Cre; KrasG12D/þ;Trp53R172H/þ (KPC) mice (C57BL/6J background), were kindly pro-vided by Dr Jennifer Morton (Cancer Research UK Beatson Institute,UK). MIA PaCa-2 PDAC cells were purchased from the ATCC. ThePC3 prostate cancer cell line was kindly provided by Dr Hing Leung(Cancer Research UK Beatson Institute, UK). All cells were routinelypassaged in DMEM (Sigma) with 25 mmol/L glucose and 2 mmol/L L-glutamine, supplemented with 5% (v/v) serum (FBS; Sigma; basemedium). Cells were split at 80% confluence and checked for Myco-plasma every 6 weeks using a luciferase-based Mycoalert MycoplasmaDetection Assay (Lonza). Cell lines were authenticated by extractinggenomic DNA (Qiagen kit), carrying out Multiplex PCR using GENEPRINT 10 (Promega) and running samples on a 31/30 XL GeneticAnalyzer. Cells were plated for experiments two passages after thawingand each biological replicate was separated by one passage thereafter.Twenty-four hours prior to experiment, cells were plated in 12-wellplates, to reach 80% confluency at endpoint. Experiments wereperformed in DMEM (experiment medium) supplemented with 2%or 5% dialyzed FBS (DFBS, Sigma) and as indicated with the followingnutrients: 10 mmol/L [U13C]-glucose (Cambridge isotopes) and/or 2mmol/L [U13C]-glutamine (Sigma), or unlabeled glucose and gluta-mine at same concentrations. Simvastatin, pitavastatin, and atorvas-tatin (all Sigma) were used at 2 mmol/L concentration, and AZD6244was used at 250 nmol/L. Rescue experiments were performed usingmevalonolactone (Sigma), N-acetyl cysteine (Sigma), mevalonolac-tone-(methyl-13C; Sigma), or 13C9-L-Tyrosine (Sigma) in experimen-tal quantification medium. Cell numbers were determined using aCASY Cell Counter (Roche).

Cellular experimentsCells were first plated in 12-well plates in basemedium for 24 hours,

and thereafter medium was replaced to the indicated experiment

medium and cells cultured for 48 hours for small-molecule metabo-lites, CoQ, and dolichol experiments, and 72 hours for cholesterolexperiments. Cells were cultured in experiment medium for 48 hoursfor cell counting assays and rescue experiments.

MiceAnimal work was performed under Home Office license (70-8645)

with ethical approval from the University of Glasgow Animal andEthical Review Board. Mice were given access to standard diet andwater ad libitum in conventional cages. Allmouse workwas conductedin accordance with Animal Research: Reporting of In Vivo Experi-ments guidelines. KPC mice, described previously (13), were geno-typed byTransnetyx, weremonitored at least three times perweek, andput on indicated treatment when pancreatic malignancy was con-firmed by abdominal palpitation. Mice were sacrificed after 7 days oftreatment. Adult mice of both sexes were randomly assigned tocohorts.

Mouse treatmentUpon pancreatic malignancy confirmation, mice were randomly

assigned to cohorts. Drug treatment began on the same day asdeuterated water supplementation (see below). Mice were given eithera daily oral gavage of 100 mL simvastatin vehicle (0.5% methylcellulose/5% DMSO), simvastatin (50 mg/kg in 0.5% methyl cellu-lose/5% DMSO) or a twice daily oral gavage of AZD6244 (25 mg/kg0.5% HPMC þ 0.1% Tween-80), or an AZD6244 gavage along with asimvastatin gavage, for 7 days.

2H2O tracing in miceMice were fasted for 6 hours prior to termination. Mice were first

given an intraperitoneal bolus injection of 0.035 mL/g 0.9% NaCl2H2O, made up using 0.9 g NaCl in 100 mL 2H2O, and sterile filtered.Mice were then provided with 8% 2H2O in the drinking water for7 days. A previously performed time-course analysis demonstratedthat steady-state 2H enrichment of approximately 5% of body waterwas achieved after 5 days, in agreement with results published byothers (14).

Analysis of 2H2O enrichment in body waterPlasma was taken at end point and deuterium enrichment in body

water was determined via deuterium acetone exchange as describedpreviously (15, 16).

Tissue homogenizationMouse tissue samples were snap frozen and homogenized in a

Cryocooler (OPS Diagnostics). A mass of 5–10 mg of tissue was thenweighed and vortexed for 15 minutes at 4oC at 3,000 rpm in theappropriate extraction buffer and internal standards (as describedbelow).

Cholesterol extraction and derivatization from cells, medium,and tissues

For cellular extracts, at the time of extraction, cells were first washedthree timeswith 1mL4�CPBS before 700mL 4�Cextraction buffer (1:9v/v water: methanol) was added. Plates were incubated for 5minutes at4�C before being scraped into high-performance liquid chromatog-raphy (HPLC) vials and 20 mL of lathosterol (100 ng/mL) internalstandard added.

For media extracts, samples were centrifuged at 16,100 � g for 5minutes at 4�C to remove cell debris and 500 mL supernatant vortexed

MEK Inhibition Synergizes with Statins for Cancer Treatment

AACRJournals.org Cancer Res; 80(2) January 15, 2020 177




for 15 minutes at 3,000 rpm at 4�C with 500 mL 1:1 v/v chloroform:methanol and 20 mL of lathosterol (100 ng/mL, Sigma) internalstandard. Samples were centrifuged at 16,100 � g for 5 minutes at4�C, the bottom chloroform layer extracted, transferred to an HPLCvial, and dried under N2. Samples were resuspended in 750 mL coldextraction buffer (1:9 v/v water:methanol). For tissue, 700 mL 4�Cextraction buffer and 20 mL of lathosterol (as an internal standard) wasused as detailed in tissue extraction.

All samples (cell extracts, medium, tissue) were saponified byheating for 60 minutes at 80�C with 75 mL of 10 mol/L NaOH toobtain the total cholesterol pool. Upon cooling to room temper-ature, 200 mL water was added, followed by 500 mL n-hexane.Vials were vortexed for 5 minutes at 3,000 rpm, and the upperhexane layer transferred to an autosampler vial. The n-hexaneextraction was repeated and samples dried under N2. Sampleswere reconstituted in 50 mL dry pyridine and 50 mL N-Methyl-N-(trimethylsilyl) trifluoroacetamide (MSTFA, Sigma) silylationagent added. Samples were heated at 60�C for 60 minutes beforecooling and immediate analysis by gas chromatography–massspectroscopy (GC-MS).

Dolichol and CoQ extractionAt time of extraction, cells were placed on ice and washed three

times in 1-mL cold PBS before 750 mL extraction buffer (1:1 v/v PBS:methanol) was added to cells and scraped into 1.5mL Eppendorf tubesand 500 mL chloroform added. Similarly, for tissues following homog-enization as detailed above, 750 mL extraction buffer and then 500 mLchloroform added was added to sample. For all samples, 50 mL1 mg/mL methanolic butylated hydroxytoluene (BHT, Sigma);SPLASH lipidomix internal standard mix (Avanti Polar Lipids) at 1mL per 5 mg tissue/105 cells and 2H9-CoQ10 (Sigma) at 500 ng/mL per5mg tissue/105 cells was added. Sampleswere centrifuged at 10,000� gfor 5 minutes before the lower chloroform layer was extracted anddried under N2. Samples were reconstituted in 1:1 v/v methanol:chloroform at 100 mL/105 cells or 0.2 mL/mg tissue and stored at�20�C until LC-MS analysis.

Metabolite extractionIntracellular metabolite extraction was performed as follows: on

ice, cells were washed three times in 1 mL cold PBS before 500 mL(4�C) extraction buffer (methanol, acetonitrile, and water, (5:3:2) v/v) was added. After 5 minutes, cells were scraped into Eppendorftubes and shaken for 15 minutes at 3,000 rpm at 4�C. Tubes werecentrifuged at 16,100 � g for 5 minutes at 4�C and the supernatantswere transferred into HPLC vials. Vials were stored at �80�C priorto LC-MS analysis.

Media samples were centrifuged at 16,100 � g for 5 minutes at4�C to remove cell debris and the supernatant vortexed for 15minutes at 3,000 rpm at 4�C with cold extraction buffer (methanol,acetonitrile, and water, 50:30:20 v/v). Samples were centrifuged at16,100 � g for 5 minutes at 4�C, and the supernatants weretransferred into HPLC vials. In addition, a pooled sample ofsupernatants was created. A series of standard curves were createdwith pooled samples spiked with increasing concentrations of[U13C]-labeled glucose, lactate, glutamate, and glutamine, whichwere used to determine the concentration of glucose, lactate,glutamate, and glutamine in media samples. For cystine, peak areawas used for a relative concentration to be calculated.

Tissues were reconstituted in extraction buffer (methanol, aceto-nitrile, and water, 50:30:20 v/v) at 5 mg/mL tissue.

Acetone analysis by GC-MSAcetonewas analyzed using anAgilent 7890BGC system coupled to

a 7000 Agilent Triple Quadrupole GC-MS system, with a PhenomenexZB-1701 column (30 mm� 0.25 mm� 0.25 mm). An initial temper-ature of 40�Cwas set to increase at 10�C/minute up to 100�C, and heldfor 0minute. The instrument was operated in split mode (220:1) in theelectron impact mode, 70eV.

Cholesterol analysis by GC-MSCholesterol was analyzed using an Agilent 7890B GC system

coupled to an Agilent 7000 Triple Quadrupole GC-MS system, whichwas operating in a single quadrupole mode, with a Phenomenex ZB-1701 column (30 mm� 0.25 mm� 0.25 mm). An initial temperatureof 200�Cwas set to increase at 20�C/minute up to 280�C, and held for 9minutes. The instrument was operated in splitlessmode in the electronimpact mode, 70eV, for quantification and 50eV for labeling experi-ments. Cholesterol was quantified and isotope labeling pattern ana-lyzed using Mass Hunter B.06.00 software (Agilent). Cholesterol andlathosterol internal standard peak areas were extracted from mass-to-charge ratio (m/z) 458 for both. Cholesterol was normalized to theinternal standard, and a standard curve was used to quantify mgcholesterol per sample.

CoQ and dolichol analysis by LC-MSLC-MS analysis was performed as described in ref. 17. CoQ was

analyzed in positive mode using spray voltage 3 kV. Full MS(scan range 300–1,600 m/z) was used at 70,000 resolution with106 automatic gain control and a maximum injection time of 250 ms.For CoQ quantification, XCalibur Software (Thermo Fisher Scien-tific) was used to analyze peak height of CoQ9, CoQ10, and

2H9-CoQ10 internal standard. Similarly, for dolichols, peak height ofdolichol-19 in dolichol internal standard mix (Avanti) was analyzed.Peak heights were normalized against both the internal standard andcell number.

Metabolite analysis by LC-MSThis was performed as described in ref. 18. Peak areas were

determined using Thermo TraceFinder software. Metabolites wereidentified by a combination of exactmasses of ions and retention times.This was validated using commercial standards of all detected meta-bolites run on the system prior to analysis. Peak areas were normalizedto cell number.

Body water 2H2O enrichment calculationsAcetone was quantified and isotope labeling pattern analyzed

using Mass Hunter B.06.00 software (Agilent). Mass isotopologs58 and 59 were integrated and their ratio compared with astandard curve to quantify plasma 2H2O enrichment, as describedpreviously (15, 16).

Cholesterol, CoQ, and dolichol 13C and 2H tracing calculationsFor both [U13C]-glucose/glutamine and 2H2O CoQ and dolichol

tracing,MAVEN software (19) was used. For cholesterol,MassHunterB.06.00 softwarewas used. Peak area for each isotopewas extracted andnatural abundance isotope correction performed using an in-housegenerated algorithm.

For 13C mass isotopolog distributions, calculation of fraction newlysynthesized cholesterol, dolichol, and CoQ was calculated by dividingeach isotopolog by the sum of all isotopologs. Calculation of thefraction newly synthesized cholesterol, dolichol, and CoQ from

McGregor et al.





in vivo 2H2O experiments was performed according to Lee andcolleagues (20, 21).

XF Cell Mito Stress analysisOxygen consumption rate (OCR) was determined using an XFe96

Extracellular Flux Analyzer (Seahorse Agilent Technologies). Mito-chondrial respiratory capacity was determined using XF Cell MitoStress Kit (Agilent Technologies). Twenty-four hours prior to analysis,cells were seeded in 5% dFBS supplemented base medium containing10 mmol/L glucose and 2 mmol/L glutamine and the indicated drugsor DMSO control. One hour prior to assay, media were replaced withSeahorsemedia containing1%dFBS, 10mmol/L glucose, and2mmol/Lglutamine and indicated drugs/DMSO, pH 7.4. During the assay,1 mmol/L oligomycin A, 1 mmol/L FCCP, and 0.5 mmol/L rotenone/antimycin A were sequentially added.

NRF2 knockdownCells were passaged 12 hours prior to transfection with RNAiMAX

(Invitrogen) and siRNA:siGENOME nontargeting control pool(Dharmacon) and NRF2 (Nfe212; Qiagen, SI01326815, SI01326822),according to the manufacturer's protocol. After 48 hours, cells wereplated and treated as described previously.

Synergy assayCells were plated in 24-well plates in base media for 24 hours.

Thereafter, media were replaced with base media plus drug or control(DMSO). Simvastatin was used at 0.5, 1, 2, 4, and 8 mmol/L. AZD6244was used at 0.25, 1, 2, 5, 10, 15, and 20 mmol/L. A combinatorial matrixof these concentrations was then tested. An Incucyte Zoom (EssenBioscience) was used to image wells and confluency after 96 hours wasdetermined using Incucyte Zoom Software (Essen Bioscience). Con-fluency data were normalized to the vehicle (DMSO) condition. Foreach drug alone, usingMicrosoft Excel, the confluency curve was fittedto a cubic equation. The cubic equation was then used to create alookup table of percent inhibition versus drug concentration. The ICX

for a given X was then obtained finding the X value in the percentinhibition column and retrieving the associated drug concentration.For a given X and drug concentrations D1 and D2, the drug combi-nation index (CI) was then calculated as described by Chou–Talalay (22), using the following equation:

CI ¼ DA

ICx;Aþ DB

ICx;B

Where DA and DB are the concentration of simvastatin andAZD6244 used in combination to achieve X % drug effect. ICX,A andICX,B are the concentrations of simvastatin and AZD6244 as singleagents to achieve the same effect. A CI of less than 1 indicates synergy.

Real-time quantitative PCRRNA was extracted using the RNAeasy Kit (Qiagen) and cDNA

synthesized using QuantiTect Reverse Transcription Kit (Qiagen).SYBR Green Master Mix (Bio-Rad) was used to prepare PCR reactionmixtures containing 1mg of cDNA. ACFX96 thermal cycler (Bio-Rad)was used to perform the PCR reaction. Tubulin was used as a referencegene for mouse and actin for human samples.

DCFDA assay20, 70-Dichlorofluorescin diacetate (DCFDA) was used to measure

intracellular ROS using the DCFDACellular ROS Detection Assay Kit(ab113851, Abcam) according to the manufacturer's protocol. Cells

were treated for 24 hours in the indicated conditions prior to assay inbase media containing 5% dFBS, 10 mmol/L glucose, and 2 mmol/Lglutamine and indicated drugs/DMSO with no phenol red. A TecanSPARK plate reader with excitation/emission wavelengths filter: 490/510–570 nm was used to detect fluorescence. Average relative fluo-rescence of control was equated to 100%, with treatment conditionscalculated proportionally. Signal was background corrected andadjusted to cell number.

IHCIHC of formalin-fixed paraffin-embedded tumor and benign

pancreas blocks was obtained from cohort mice treated withvehicle, simvastatin, or simvastatin þ AZD6244. The followingprimary antibodies were used: phospho-histone H2A.X (Ser139;20E3; gH2AX; Cell Signaling Technology) at 1:50 dilution, anti-8-Hydroxy-20-deoxyguanosine (N45.1; 8-hydroxy; Abcam) at 1:200dilution, and caspase-3 (Cell Signaling Technology) at 1:500 dilu-tion. Antigens were retrieved in a PT Module (Agilent) for 25minutes at 98�C in PT Module 1 buffer (Thermo Fisher Scientific).For phospho-Histone H2A.X and caspase-3, endogenous peroxi-dase activity was blocked by incubation with 3% H2O2. This stepwas carried out after anti-8-hydroxy-20-deoxyguanosine staining,so as not to disrupt ROS. Staining was performed on a DakoAutostainer Link48 (for 8-hydroxy and gH2AX) and a Leica BondRX Autostainer (caspase-3) with the primary antibody applied for45 minutes at room temperature and 30 minutes, respectively.Sections were washed with Tris-buffered Tween (TbT) and RabbitEnVision (Agilent) was applied for 30 minutes, before washingwith TbT and then Liquid DAB (Agilent) was applied for 10minutes. Sections were rinsed in water on an autostainer andcounterstained with hematoxylin, nuclei blue'd, before being dehy-drated and cleared through graded alcohols and xylene beforeapplication of a permanent coverslip.

ResultsStatins only modestly affect cholesterol pools, but robustlyblock coenzyme Q synthesis in cancer cells

Cells acquire cholesterol either through uptake of lipoproteins fromthe extracellular environment or by synthesizing it de novo (Fig. 1A;ref. 23). In pancreatic and prostate cancer, cholesterol metabolismgenes in particular have been shown to be deregulated (8, 24). Cho-lesterol synthesis itself has not been measured before in these cancertypes, and therefore we explored cholesterol dynamics as well as theeffect of statins.

We performed a stable isotope tracing experiment with both[U13C]-glucose and [U13C]-glutamine in a cancer cell line derivedfrom the KPC (Pdx1-Cre; KrasG12D/þ; Trp53R172H/þ) geneticallyengineered mouse model of pancreatic ductal adenocarcinoma(PDAC). In the presence of 5% (high) serum, approximately 90% ofthe cholesterol remained unlabeled and very little 13C accumulated inthe 27-carbon molecule (Fig. 1B; Supplementary Fig. S1A), thusindicatingminimal de novo synthesis, but robust uptake of (unlabeled)cholesterol from the medium. As serum is a source of unlabeledcholesterol, we next lowered extracellular cholesterol by reducingserum to 2% (low; Fig. 1B; Supplementary Fig. S1A). While thefraction of unlabeled (M0) cholesterol remained substantial, thepresence of heavily 13C-labeled isotopologs now demonstrated activecholesterol synthesis (Fig. 1B). Of note, we observed partially labeledmolecules that contain both 12C and 13C. This is still indicative ofcomplete de novo cholesterol synthesis, and is caused by partial






labeling of the acetyl-CoA pool, which is also observed for othermacromolecules (17). On the basis of this labeling pattern, uptake (M0)and synthesis (M14 – M27) contributed roughly equally to the cho-lesterol pool (Supplementary Fig. S1A). A similar observation wasmade in the human PDAC cell line MIA-PaCa2 (SupplementaryFig. S1B–S1D). These results demonstrate that cancer cells preferen-tially take up cholesterol from their extracellular environment, but canmaintain cholesterol homeostasis by inducing de novo synthesis whenextracellular availability is limited. This homeostasis is maintainedduring statin treatment (Supplementary Fig. S1D); simvastatin treat-ment in low serum conditions potently abrogated de novo cholesterolsynthesis, but cells were still able to adapt and maintain their choles-terol pool size by increasing cholesterol uptake (SupplementaryFig. S1D–S1F).

By modulating serum availability during treatment of PDAC celllines with simvastatin, we observed potent antiproliferative effectsin both high and low serum conditions (Fig. 1C; SupplementaryFig. S1G). This finding was recapitulated with pitavastatin andatorvastatin, in KPC, MIA-PaCa2, and a human prostate cancercell line, PC3 (Supplementary Fig. S1G). As cholesterol synthesis isactive in low serum but inactive in high serum, this suggests theantiproliferative effect of statins is not mediated through inhibitionof cholesterol metabolism. We therefore started exploring otherbranches of the mevalonate pathway (Fig. 1A). Using LC-MS-basedlipidomics, we were able to directly measure both dolichols andcoenzyme Q (CoQ), also known as ubiquinone. Dolichols arecomposed of multiple concatenated 5-carbon isoprenoid units andfunction to “anchor” glycosylation structures in membranes (25).CoQ is comprised of a benzoquinone ring derived from tyrosine,attached to a 9 (mouse, CoQ9) or 10 (human, CoQ10) isoprenoid-unit tail (Fig. 1D; ref. 26). It functions as an electron carrier in theelectron transport chain (ETC), and hence supports oxidativephosphorylation (2).

Analysis of dolichol labeling from [U13C]-glucose and [U13C]-glutamine revealed relatively little 13C-incorporation, and hence alow rate of de novo synthesis (Supplementary Fig. S1H). Thiscontrasted with CoQ, which showed abundant 13C-incorporationas evidenced by the formation of a multitude of 13C-labeled iso-topologs (Fig. 1E). We confirmed that providing 13C-labeledmevalonolactone, a routinely used cell-permeable mevalonate ana-logue that is rapidly converted upon entry into the cell, andtyrosine, also led to labeled CoQ (Supplementary Fig. S1I–S1K).In all cell lines tested, statin treatment significantly reduced both denovo synthesis of CoQ and consequently CoQ pool size (Fig. 1F andG; Supplementary Fig. S1L and S1M). It took 24 hours for statins tohave a clear effect on CoQ levels, and this effect could be rescuedusing mevalonolactone (Supplementary Fig. S1N). Together, theseresults demonstrate that, in contrast to cholesterol, CoQ is activelyproduced by cancer cells, and that both synthesis and pool size arereduced upon statin treatment.

Decreased CoQ levels cause impaired oxidativephosphorylation and a compensatory shift towardglycolysis

Succinate dehydrogenase (SDH), or complex II, participatesboth in the TCA cycle and the ETC. It couples the oxidation ofsuccinate with the reduction of CoQ (27). To establish whetherdiminished CoQ levels post statin treatment inhibited SDH activ-ity, we determined the levels of its direct substrate succinate(Fig. 2A; Supplementary Fig. S2A). Indeed, statin treatment causedsignificantly higher succinate levels, suggesting inhibition of SDH

activity. We next asked whether reduced SDH activity due tostatin-mediated CoQ depletion more broadly impacted centralcarbon metabolism. We therefore measured OCR after 24 hoursof statin treatment, as CoQ depletion is strongest at this time(Supplementary Fig. S1N). Simvastatin, pitavastatin, and atorvas-tatin all reduced both basal and maximal respiration (Fig. 2B;Supplementary Fig. S2B). Thus, reduced CoQ levels lowered oxi-dative phosphorylation (OXPHOS). Cells can compensate for lossof energy production from the TCA cycle by increasing glycolysis.In accordance with this, we observed increased glucose uptake andlactate secretion (Fig. 2C; Supplementary Fig. S2C). Of note,OXPHOS was restored upon mevalonolactone supplementation(Supplementary Fig. S2D). Thus, cells switch to glycolysis tocompensate for loss of OXPHOS-mediated ATP production dueto statin-mediated CoQ depletion.

Statin-induced reduction inCoQ levels causes elevatedROSandactivation of antioxidant metabolic pathways

Mitochondrial metabolism is intimately linked with ROS main-tenance, and dysfunctional oxidative phosphorylation, as weobserved with statin treatment (Fig. 2), can be a principal causefor excessive ROS generation (28). In addition, the reduced form ofCoQ, also known as ubiquinol, may have antioxidant functions incells beyond oxidative phosphorylation (29). We next mined ourmetabolomics dataset to evaluate whether oxidative stress occurs instatin-treated cells. This revealed a striking shift in the ratio betweenoxidized and reduced glutathione toward the more oxidized form(Fig. 3A; Supplementary Fig. S3A). Thus, it appears that oxidativestress is indeed a major consequence of statin treatment in cancercells.

In recent years, multiple metabolic adaptations have been shownto have the ability to regulate redox balance (30). These adaptationsinclude (i) the reductive formation of citrate from glutamine forshuttling NADPH into the mitochondria (31), (ii) increased cellularcystine import for glutathione production (32), and (iii) the syn-thesis of proline as an electron sink and ROS scavenger (Fig. 3B;ref. 33). Each of these pathways uses glutamine or derived meta-bolites as a substrate, and we therefore asked whether glutamineuptake by statin-treated cells was changed. Our analysis revealed arobust, roughly 2-fold or higher increase in the rate by whichglutamine is taken up by statin-treated cells, compared withuntreated cells (Fig. 3C; Supplementary Fig. S3B). While glutamaterelease also increased, it did not fully account for the increaseduptake of glutamine, suggesting that statin treatment increases therate by which glutamine-derived carbon feeds into downstreampathways.

We next investigated the effect of statin treatment on the activityof the aforementioned pathways that use glutamine as a substrate.Reductive citrate synthesis can be monitored using the Mþ5 iso-topolog after feeding the cells [U13C]-glutamine. In concordancewith a change in central carbon metabolism and a potential role inredox management, the Mþ5 isotopolog and hence reductive car-boxylation was robustly induced upon statin treatment (Fig. 3D;Supplementary Fig. S3C). In addition, glutamine-derived glutamatecan be exchanged with cystine via the cystine/glutamate antiporterSLC7A11/Slc7a11 (xCT) for glutathione production. Consistentwith this pathway being active, glutamate secretion increased uponstatin treatment, as did cystine uptake and intracellular cystinelevels (Fig. 3E and F; Supplementary Fig. S3D and S3E). Thetranscript levels of xCT transporter also increased (Fig. 3G; Sup-plementary Fig. S3F).

McGregor et al.





Finally, proline synthesis by pyrroline-5-carboxylate reductase(PYCR) from glutamine can also help regulate redox balance byregenerating NADþ, which in turn may promote TCA cycling (34).Accordingly, we found that statin treatment robustly increased prolinesynthesis from glutamine (Fig. 3H; Supplementary Fig. S3G). PYCR1/Pycr1 transcript levels were also elevated (Fig. 3I; SupplementaryFig. S3H). Proline itself can act as a ROS scavenger, reacting withhydroxyl radicals to form hydroxyproline (33, 35). We indeedobserved intracellular hydroxyproline levels to be significantlyincreased upon statin treatment (Fig. 3J; Supplementary Fig. S3I).Thus, proline synthesis from glutamine helps to regenerate NADþ andfacilitate ROS scavenging.

We next asked whether the effects of statin-induced redoxstress could be alleviated by mevalonolactone supplementation

(Fig. 3G and I; Supplementary Fig. S3A, S3C, and S3E–I).Indeed, cell proliferation was rescued by mevalonolactone sup-plementation, as well as by the antioxidant N-acetyl cysteineaddition (Supplementary Fig. S3J). Of note, direct CoQ supple-mentation did not rescue cell growth, but this could have beencaused by the precipitation of CoQ in the culture medium, andwe were unable to confirm uptake or use by the cells. Never-theless, the ability of N-acetyl cysteine to rescue the effect ofsimvastatin is further evidence that the depletion of CoQ andresulting oxidative stress is an important mechanism of statin-induced cell death. Overall, our results indicate that treatingcancer cells with statins leads to pronounced oxidative stress andcells compensate by activating redox-induced metabolic path-ways that mitigate ROS damage.

Ctl

Simva

−6

−4

−2

0

2

4

6

KPC

Rat

e (μ

mol

/107

cell/

h)

Rat

e (μ

mol

/107

cell/

h)

Rat

e (μ

mol

/107

cell/

h)

**

*

Ctl

Simva

−15

−10

−5

0

5

10MIA-PaCa2

*

**

Ctl

Simva

0.0

0.5

1.0

1.5

2.0

2.5

KPC

Rel

ativ

e su

ccin

ate

leve

l(M

S in

tens

ity/c

ell) **

Ctl

Simva

0

1

2

3

4

5

MIA-PaCa2

Rel

ativ

e su

ccin

ate

leve

l(M

S in

tens

ity/c

ell) ****

Ctl

Simva

−15

−10

−5

0

5

PC3

Glucose uptakeLactate secretion

*

**

Ctl

Simva

0.0

0.5

1.0

1.5

2.0

2.5

PC3

Rel

ativ

e su

ccin

ate

leve

l(M

S in

tens

ity/c

ell) **

0 50 100 1500

100

200

300

400

KPC

Time (min)

OC

R (p

mol

/min

/105

cell) Ctl

SimvaOligomycin

FCCP

Rot/AA

0 50 100 1500

50

100

150

200

MIA-PaCa2

Time (min)

OC

R (p

mol

/min

/105

cell)

CtlSimvaOligomycin

FCCP

Rot/AA

A

B

C

Figure 2.

Diminished CoQ levels lead to succinate accumulation, reduced oxidative phosphorylation, and increased glycolysis. A, Effect of statins on succinate pool sizes inKPC, MIA-PaCa2, and PC3 cells. Peak areas were normalized to cell number and shown relative to vehicle control (DMSO). B, Effect of statin treatment on oxidativephosphorylation. Cells were pretreated with vehicle control (DMSO) or simvastatin for 24 hours prior to analysis. C, Glucose uptake and lactate release rates in themedia quantified after 48 hours of simvastatin treatment. All data shown asmean� SEMof three (A) or one (C) representative biological replicates, each experimentperformed in triplicate; three (B) biological replicates, eachwith 10 replicates. Statistical significancewas tested by t test. � , P <0.05; �� , P <0.01; �� , P <0.0001. Seealso Supplementary Fig. S2. Rot/AA, rotenone and antimycin A.






Ctl

Simva

−3

−2

−1

0

1

KPC

Rat

e (μ

mol

/107

cell/

h)

****

*

Ctl

Simva

−3

−2

−1

0

1MIA-PaCa2

Rat

e (μ

mol

/107

cell/

h) Glutamine uptakeGlutamate secretion

****

*

Ctl

Simva

−3

−2

−1

0KPC

Rel

ativ

e cy

stin

e up

take

rate

(am

ount

/h/c

ell)

***

Ctl

Simva

−2.5

−2.0

−1.5

−1.0

−0.5

0.0MIA-PaCa2

Rel

ativ

e cy

stin

e up

take

rate

(am

ount

/h/c

ell)

*

Ctl

Simva

0

5

10

15KPC

Rel

ativ

e G

SS

G/G

SH *

Ctl

Simva

0

2

4

6

8

10MIA-PaCa2

Rel

ativ

e G

SS

G/G

SH **

Ctl

Simva

0

1

2

3KPC

Rel

ativ

e pr

olin

e la

belin

gfro

m [U

13C

]-gln

***

Ctl

Simva

0

1

2

3

4MIA-PaCa2

Rel

ativ

e pr

olin

e la

belin

gfro

m [U

13C

]-gln

M+0M+1M+2M+3M+4M+5

***

Ctl

Simva

Simva

+ Mev

.0.0

0.5

1.0

1.5

2.0KPC

Fold

cha

nge

inxC

T m

RN

A

*** ***

Ctl

Simva

Simva

+ Mev

.0.0

0.5

1.0

1.5

2.0MIA-PaCa2

Fold

cha

nge

inxC

T m

RN

A

**** **

Ctl

Simva

Simva

+ Mev

.0.0

0.5

1.0

1.5

2.0

2.5KPC

Fold

cha

nge

inP

YC

R m

RN

A

* *

Ctl

Simva

Simva

+ Mev

.0

2

4

6

8MIA-PaCa2

Fold

cha

nge

inP

YC

R m

RN

A * *

Ctl

Simva

0

1

2

3

4

5KPC

Rel

ativ

e in

trace

llula

rcy

stin

e (M

S in

tens

ity/c

ell)

****

Ctl

Simva

0

1

2

3

4MIA-PaCa2

Rel

ativ

e in

trace

llula

rcy

stin

e (M

S in

tens

ity/c

ell)

****

Ctl

Simva

0

1

2

3

4KPC

Rel

ativ

e hy

drox

ypro

line

(MS

inte

nsity

/cel

l) *

Ctl

Simva

0.0

0.5

1.0

1.5

2.0

2.5MIA-PaCa2

Rel

ativ

e hy

drox

ypro

line

(MS

inte

nsity

/cel

l) ****

M+0

M+1

M+2

M+3

M+4

M+5

M+6

0.0

0.1

0.2

0.3

0.4

0.5

KPC

Rel

ativ

e ci

trate

MS

inte

nsity

/cel

l

CtlSimva

******

Isotopomer

M+0

M+1

M+2

M+3

M+4

M+5

M+6

0.0

0.1

0.2

0.3

0.4

0.5

MIA-PaCa

Rel

ativ

e ci

trate

MS

inte

nsity

/cel

l

CtlSimva

******

Isotopomer

Glutamine Glutamate Redox StressProline

GSH

NAD+NADH

Reduc ve Carboxyla on

Cys ne INxCT

Hydroxy-proline

PYCR .OH

TCA

A B

C D

E F

G H I

J

Figure 3.

Statin treatment causes increased redox stress and metabolic compensation. A, Effect of simvastatin (Simva) on the ratio of oxidized (GSSG) to reduced (GSH)glutathione (48 hours). Relative to vehicle control (DMSO). B, Overview of metabolic pathways mitigating oxidative stress. C, Glutamine uptake and glutamaterelease rates in response to vehicle or simvastatin (2 mmol/L).D, Citrate labeling from [U13C]-glutamine tracing for 48 hours. E, Change in cystine uptake in responseto simvastatin treatment. Rates are relative to vehicle control. F, Effect of simvastatin treatment on intracellular cystine levels (48 hours). Values are relative tocontrol. G, qPCR analysis of xCT following statin treatment and statin plus mevalonolactone (Mev.; 48 hours). H, Proline labeling from [U13C]-glutamine after statintreatment (48 hours). Peak areas were normalized to cell number and expressed relative to control. I, qPCR analysis of PYCR1 after simvastatin treatment and statinplus mevalonolactone (Mev.; 48 hours). J, Intracellular hydroxyproline levels in response to statin treatment. Peak areas were normalized to cell numbers andexpressed relative to control. All data shown asmean� SEM of three biological replicates (A,D, F, and J), each performed in triplicate, one representative biologicalreplicate, each performed in triplicate (C, E, and H), and three biological replicates from six technical repeats (G and I). Statistical significance was tested by ANOVAfor G and I, rest by t test. � , P < 0.05; �� , P < 0.01; �� , P < 0.001; ��, P < 0.0001. See also Supplementary Fig. S3.

McGregor et al.





Statin treatment decreases CoQ synthesis and causes oxidativestress in vivo

We next evaluated mevalonate pathway activity in vivo using 2H2Otracing, which enables persistent labeling of macromolecules (36, 37).Pdx1-Cre; KrasG12D/þ; Trp53R172H/þ (KPC) mice were administered a0.035 mL/g mouse weight 2H2O bolus to mice with palpable tumors,followed by exposure to 8% 2H2O in drinking water for 7 days, whichconsistently led to approximately 5% deuterium enrichment in plasma(Supplementary Fig. S4A).

We assessed 2H-enrichment in cholesterol. A fractional enrich-ment of approximately 0.45 was observed in both liver and plasmaof KPC mice (Supplementary Fig. S4B; Supplementary Fig. S4C).In healthy pancreas and tumors, the fractional enrichment ofcholesterol was comparable with what was observed in plasma(Supplementary Fig. S4D), suggesting that the de novo synthesis ofcholesterol in tumors is minimal, as tumors actively take it upfrom the bloodstream. Statin treatment had no significant impacton cholesterol labeling (Supplementary Fig. S4C) or levels, whichis consistent with reports that statins do not affect circulatingblood cholesterol in mice, in contrast to in humans (38, 39).Analysis of in vivo dolichol labeling revealed a similar labelingpattern to cholesterol, with labeling in tumors somewhat lowerthan in plasma, suggestive of minimal synthesis in the tumor,with no observable effect of simvastatin (Supplementary Fig. S4Eand S4F).

We next proceeded with analysis of CoQ. Notably, CoQ 2Hlabeling in the small intestine was very high (fractional enrichment� 0.9), presumably due to the extremely rapid turnover of theepithelium (Supplementary Fig. S4G). Fractional enrichment ofcirculating CoQ was strikingly similar to cholesterol (Supplemen-tary Fig. S4H). In contrast, while CoQ labeling in healthy pancreaswas lower than circulating CoQ, the inverse was true in KPC PDACtumors, where enrichment was significantly higher (Fig. 4A). As theenrichment is higher than circulating CoQ, this indicates activesynthesis in the tumor. This was significantly reduced upon statintreatment (Fig. 4A). Notably, plasma CoQ9 levels were not signif-icantly altered by statin treatment, indicating a tumor-specific effect(Supplementary Fig. S4I), which appears in contrast to studies inhealthy humans (40). Nevertheless, we conclude that PDAC tumorsactively synthesize CoQ, and this synthesis is reduced by statintreatment.

We next wanted to investigate whether simvastatin treatedtumors also had elevated ROS levels. Indeed, our IHC demon-strated elevated oxidative damage, as there was significantlygreater staining of gH2AX in the simvastatin-treated cohort(Fig. 4B). We used 8-hydroxyguanosine as a DNA damagemarker (41), and found significantly more stained cells in thesimvastatin-treated cohort than vehicle treated (SupplementaryFig. S4J). Consistent with the metabolic compensation observedin vitro, we found that metabolic compensation to mitigateoxidative stress occurred in the PDAC tumors. Specifically, weobserved a significant increase in xCT (Slc7a11) transcript levels(Fig. 4C). Thus, simvastatin treatment leads to increased tumorROS and tumors compensate by attempting to elevate glutathioneproduction via xCT upregulation.

Combined statin and MEK inhibitor treatment synergize toaccumulate ROS and cause apoptosis

Our findings revealed that statins reduce CoQ levels, causingoxidative stress, and metabolic compensation occurs to mitigatethe effects of ROS damage. We next asked whether disrupting these

metabolic adaptations, together with statin treatment, wouldsynergize to induce tumor cell death. The most pronouncedmetabolic adaptation we observed in vivo was upregulation of thexCT transporter (Fig. 4C). It was previously shown that the MEKinhibitor AZD6244 can promote ROS by reducing NRF2 induc-tion (42). In line with this, we found simvastatin treatmentincreased NRF2 transcript levels, while AZD6244 treatmentreduced NRF2 transcript levels, as expected (SupplementaryFig. S5A). As xCT is a NRF2 target (43) and NRF2 itself is regulatedby MEK (44), we sought to determine whether the ROS-promotingeffect of AZD6244 was through lowered expression of xCT. Indeed,AZD6244 was able to reduce xCT transporter levels in culturedcancer cells (Fig. 5A). We further validated this by testing MEKtargets and found them to be reduced (Supplementary Fig. S5B).Specifically, our previous results showed simvastatin elevates xCTmRNA levels, but in combination with AZD6244 this was pre-vented and the expression even reduced below the vehicle condi-tion (Fig. 5A). This resulted in reduced cystine uptake (Supple-mentary Fig. S5C), indicating that cells were not able to compen-sate for the elevated ROS from simvastatin treatment throughincreased cystine uptake for glutathione synthesis. In accordance,ROS levels were significantly increased using the combinationtreatment (Fig. 5B). There was also a trend toward increasedglutathione oxidation after combination treatment (Supplementa-ry Fig. S5D). Overall the combination treatment exacerbates ROSlevels. Importantly, proliferation was substantially reduced uponcombination treatment and NRF2 knockdown (KD; Fig. 5C; Sup-plementary Fig. S5E and S5F). NRF2 KD reduced NRF2 targettranscript levels, and most notably xCT levels (SupplementaryFig. S5G). Combined, these results suggest AZD6244 may besynergizing with simvastatin.

To explore the potential synergy of AZD6244 and simvastatinfurther, the effect upon cell proliferation of the two drugs as singleagents and in combination was analyzed (see Supplementary Fig. S5Hand S5I for example graphs). Using a matrix of all drug concentrationcombinations, the combination index (CI), as described by Chou–Talalay, was calculated (Supplementary Fig. S5J and S5K). Thisdemonstrated that the two drugs synergized at all except the veryhighest concentrations.

These results obtained in vitro led us to investigate the potencyof a dual treatment of AZD6244 and simvastatin in vivo. We foundthe combination treatment reduced in vivo xCT transcript levels towell below the simvastatin treatment alone, and was comparablewith the AZD6244 single-arm treatment (Fig. 5D). This showsAZD6244 is able to counter the elevated xCT levels induced bystatin treatment in the tumor setting (Fig. 5E). Strikingly, our IHCrevealed caspase-3 induction and associated apoptotic body num-bers were significantly higher in the combination treatment com-pared with vehicle, AZD6244, or simvastatin alone (Fig. 5F and G).Combined, these results indicate that a combined treatment withstatin and a MEK inhibitor may be an effective cancer treatmentparadigm.

DiscussionOur rationale for studying the mevalonate and downstream path-

ways in cancer was 2-fold. First, while the mevalonate pathway isknown tobeupregulated in anumber of different cancer types (6, 8, 10),and to be critical for tumorigenesis (9), what downstream products aresynthesized and how they contribute to tumorigenesis, thus farremained largely unexplored. Second, despite the importance of the






mevalonate pathway in cancer, the chemotherapeutic potential of theubiquitously prescribed statins, either as a single agent or in acombination strategy, remained uncertain. We combined bothGC-MS and LC-MS modalities with innovative stable isotope tracingapproaches to determine the metabolic activity of this branch ofmetabolism, as well as the compensatory mechanisms that occur uponpharmacologic inhibition.

It is well established that statins lower circulating cholesterol levelsin humans, yet few studies have looked at cholesterol metabolismdirectly in cancers (8, 45). Using tracers, we directly measuredcholesterol metabolism, both in vitro and in vivo, to reveal that cancer

cells preferentially take up cholesterol, rather than synthesizing it.Cholesterol uptake occurs via the LDL receptor and its increasedexpression has been reported in a variety of tumor types, includingpancreatic cancer (8).

Although our labeling studies clearly demonstrated that choles-terol synthesis is minimal in tumor cells, statin treatment stillelicited a robust antiproliferative response. Through further explo-ration using an innovative combination of stable isotope tracing andlipidomics, we discovered that CoQ is actively synthesized by cancercells. This contrasted with the synthesis of dolichols, which showedsubstantially less pronounced labeling. The principal function of

Panc V

eh

Panc S

imva

Tum V

eh

Tum S

imva

0.0

0.2

0.4

0.6

0.8

CoQ9 Synthesis

Frac

tion

new

ly s

ynth

esiz

ed*

ns

***

Vehicl

eSim

va0

5

10

15KPC Tumor

Fold

cha

nge

inxC

T m

RN

A *

Vehicl

eSim

va0

50

100

150

200

γH2AX

Med

ian

scor

e

*

Vehicle Simvasta�n

A

B

C

Figure 4.

Statin-treated KPCmice have reduced tumor CoQ synthesis and pronounced oxidative stress. A, Fraction newly synthesized CoQ9 in KPC PDAC tumors and benignadjacent pancreas.B, IHC and scoring ofDNAdamage response by gH2AX in tumor. Scale bar in larger image, 50mm; smaller image, 20mm.C,qPCR analysis of xCT inPDAC tumors from KPCmice. Data shown asmean� SEM for n¼ 4mice per group (A and C). Note one vehicle mouse had no benign pancreas. For B, quantificationis shown as median score� SEM from 30 frames for n¼ 4mice per group. Statistical significance was tested by Student t test for A and C and Mann-Whitney for B.� , P < 0.05; ��, P < 0.001. See also Supplementary Fig. S4. ns, nonsignificant; Panc, pancreas; Veh, vehicle.

McGregor et al.





Ctl

Simva

AZD6244

AZD6244

+ Simva

0.0

0.5

1.0

1.5

2.0

KPC

Fold

cha

nge

inxC

T m

RN

A

****

**** ****

Ctl

Simva

AZD6244

AZD6244

+ Simva

0.0

0.5

1.0

1.5

2.0

MIA-PaCa2

Fold

cha

nge

inxC

Tm

RN

A

****

********

Ctl

Simva

AZD6244

AZD6244

+ Simva

0.0

0.5

1.0

1.5

KPC

Rel

ativ

e ce

ll nu

mbe

r

***

Ctl

Simva

AZD6244

AZD6244

+ Simva

0.0

0.5

1.0

1.5

2.0

MIA-PaCa2

Rel

ativ

e ce

ll nu

mbe

r

*****

Ctl

Simva

AZD6244

AZD6244

+ Simva

0

50

100

150

200

250KPC ROS level

Fluo

resc

ence

(% C

tl no

rmto

are

a co

vere

d)

********

Ctl

Simva

AZD6244

AZD6244

+ Simva

0

50

100

150

200MIA-PaCa2 ROS level

Fluo

resc

ence

(% C

tl no

rmto

are

a co

vere

d)

********

Vehicl

eSim

va

AZD6244

AZD6244

+ Simva

0

5

10

15

KPC Tumor

Fold

cha

nge

inxC

T m

RN

A ** ****

Vehicl

eSim

va

AZD6244

AZD6244

+ Simva

0

10

20

30

40

50

Apoptotic bodies

Med

ian

scor

e

******

*

***

Vehicl

eSim

va

AZD6244

AZD6244

+ Simva

0

20

40

60

80

100

Caspase-3

Med

ian

scor

e

*** ***

Vehicle Simva AZD6244 AZD6244 + Simva

Vehicle Simva AZD6244 AZD6244 + Simva

A B

C D E

F

G

Figure 5.

A MEK inhibitor (AZD6244) synergizes with statin treatment to induce cell death due to excessive ROS. A, qPCR analysis of xCT expression following 48-hourtreatment with simvastatin, AZD6244, or combination. B, Intracellular ROS as measured by DCFDA assay after 24-hour treatment with simvastatin, AZD6244, or acombination. C, Cell numbers following 96-hour exposure to indicated conditions. Numbers are relative to vehicle (DMSO)-treated control. D, qPCR analysis of xCT(Slc7a11) expression in KPC PDAC tumors. E, Schematic to show AZD6244 action reducing xCT level. F, Caspase-3 IHC and scoring of KPCmice treated with vehiclecontrol, simvastatin, AZD6244, or AZD6244 þ simvastatin. G, Hematoxylin and eosin IHC and scoring of apoptotic bodies in KPC mice treated as in F. Arrows,apoptotic bodies. Scale bar in larger image, 50 mm; smaller image, 20 mm. Data shown as mean� SEM of three biological replicates, with each 6 technical replicates(A), three biological replicates, with each 8 technical replicates (B), three biological replicates, each performed in triplicate (C). Data are shown for n ¼ 4 mice pergroup (D, F, and G). In F and G, quantification is shown as median score � SEM from 20 frames. Statistical significance was tested by ANOVA for A–D or Mann–Whitney for F–G. � , P < 0.05; �� , P < 0.01; �� , P < 0.001; ��, P < 0.0001. See also Supplementary Fig. S5.






CoQ is to act as an electron carrier in the electron transport chain(ETC), to facilitate mitochondrial respiration. Apart from distinctoncogenic mutations and deletions in TCA cycle enzymes (46),mitochondrial metabolism is typically active in tumor cells and animportant source for both energy and building blocks for macro-molecules (47). In fact, multiple recent reports demonstratedheightened glucose oxidation in tumors (48, 49), stressing theimportance of mitochondrial metabolism in cancer.

Statin-mediated CoQ depletion causes severe oxidative stress,which is likely caused by the disruption in mitochondrial metab-olism. A few reports have previously postulated a link betweenstatins, reduced CoQ levels, and increased ROS in other cell types,and this has been suggested as a cause for statin-induced myop-athy (50, 51). However, the published data supporting this wascircumstantial. We now establish this link in unprecedented detailand show it also occurs in cancer cells. Furthermore, we made thenovel observation that statin-mediated CoQ depletion leads to thecompensatory induction of multiple metabolic pathways, with eachhaving a unique antioxidant role. Particularly pronounced in bothin vitro and in vivo settings was the upregulated expression of thexCT transporter. This has previously been shown to occur inresponse to oxidative stress by helping cells to obtain cystine neededfor glutathione production (52). Of note, the statin-mediated effecton ROS through CoQ is distinctly different from recent reports onsqualene, which accumulates in some cancers and has an antiox-idant function (53, 54).

Our study highlights the capability of statins to inhibit CoQsynthesis. However, we recognize that this may not be the solechemotherapeutic effect of statins. Multiple elegant reports havehighlighted the pronounced effect of statins on protein prenylation,a posttranslational modification that occurs on prominent onco-proteins, including members of the RAS family (55, 56). Recentevidence, however, clearly demonstrated that the anticancer effectsof statins is not due to reduced RAS protein prenylation (12).Therefore, other statin-induced alterations, including the pro-nounced ROS production due to CoQ loss, contribute to itschemotherapeutic potential.

Statins, extensively prescribed for cardiovascular disease, havebeen widely evaluated for their effects on tumor development andprogression, yet their clinical effect is variable (57–59). A phase IIclinical trial of simvastatin and gemcitabine in patients with PDACfound no clinical benefit to combining the statin with the onlychemotherapy currently available for patients with pancreatic can-cer (60). Similarly, for prostate cancer, a recent randomized doubleblind trial found no significant difference between atorvastatin andplacebo (61). We explored statins in both pancreatic and prostatecancer cell lines, as well as an in vivo genetically engineered mousemodel of PDAC. Both in vitro and in vivo simvastatin reduced CoQsynthesis significantly and tumors exhibited elevated ROS levels and

xCT transcript levels. This led us to target the compensatory xCTupregulation using the MEK inhibitor AZD6244 and we found thisdual combination with simvastatin-induced apoptosis in the tumor.Our findings are directly relevant to unearthing a potential com-binatorial therapy for these cancers by targeting metabolic com-pensation in response to excessive ROS generation following statintreatment.

We urgently need better treatments to target aggressive can-cers such as PDAC, for which therapeutic options are currentlyvery limited. We have used two FDA-approved drugs anddemonstrated their synergy and potential as a combinatorialcancer therapy.

Disclosure of Potential Conflicts of InterestJ.J. Kamphorst is Director of Cellular Metabolism for Rheos Medicines and has

ownership interest (including stock, patents, etc.) in the same. No potential conflictsof interest were disclosed by the other authors.

Authors’ ContributionsConception and design: G.H. McGregor, A.D. Campbell, O.J. Sansom,J.J. KamphorstDevelopment of methodology: G.H. McGregor, A.D. Campbell, S. Tumanov,J.J. KamphorstAcquisition of data (provided animals, acquired and managed patients, providedfacilities, etc.): G.H. McGregor, A.D. Campbell, S.K. Fey, D. Sumpton, G.R. Blanco,G. Mackay, O.J. SansomAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): G.H. McGregor, A. Vazquez, J.J. KamphorstWriting, review, and/or revision of the manuscript: G.H. McGregor, G. Mackay,O.J. Sansom, J.J. KamphorstAdministrative, technical, or material support (i.e., reporting or organizing data,constructing databases): G.H. McGregor, A.D. Campbell, C. Nixon, O.J. SansomStudy supervision: G.H. McGregor, O.J. Sansom, J.J. Kamphorst

AcknowledgmentsThe authors thankVinay Bulusu for comments on themanuscript, Karen Blyth for

using her animal license (70-8645), and Jennifer Morton for help with the in vivowork. The authors thank AstraZeneca for providing the AZD6624 compound. Thiswork was supported by Cancer Research UK Career Development Fellowship(C50242/A17728 to J.J. Kamphorst and S. Tumanov), Cancer Research UK Grant(A17196 to G.H. McGregor, O.J. Sansom, A.D. Campbell, and S.K. Fey), RosetreesTrust (M480 to G.H. McGregor), Cancer Research UK Beatson Institute (C596/A17196), and Cancer Research UK Glasgow Centre (C596/A18076 to D. Sumpton,G.R. Blanco, C. Nixon, and A. Vazquez).

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 February 22, 2019; revised August 1, 2019; accepted September 24, 2019;published first September 27, 2019.

References1. Zhang FL, Casey PJ. Protein prenylation: molecular mechanisms and functional

consequences.Annu Rev Biochem 1996;65:241–69.2. Brandt U. Proton translocation in the respiratory chain involving ubiquinone–a

hypothetical semiquinone switch mechanism for complex I. Biofactors 1999;9:95–101.

3. Goldstein JL, Brown MS. Regulation of the mevalonate pathway. Nature 1990;343:425–30.

4. Nelson RH. Hyperlipidemia as a risk factor for cardiovascular disease. PrimCare2013;40:195–211.

5. DavidsonMH. Safety profiles for the HMG-CoA reductase inhibitors: treatmentand trust. Drugs 2001;61:197–206.

6. Clendening JW, Pandyra A, Boutros PC, El Ghamrasni S, Khosravi F, TrentinGA, et al. Dysregulation of the mevalonate pathway promotes transformation.Proc Natl Acad Sci U S A 2010;107:15051–6.

7. Larson RA, Yachnin S. Mevalonic acid induces DNA synthesis in chroniclymphocytic leukemia cells. Blood 1984;64:257–62.

8. Guillaumond F, Bidaut G, Ouaissi M, Servais S, Gouirand V, Olivares O, et al.Cholesterol uptake disruption, in association with chemotherapy, is a promising

McGregor et al.





combinedmetabolic therapy for pancreatic adenocarcinoma. Proc Natl Acad SciU S A 2015;112:2473–8.

9. Moon S-H, Huang C-H, Houlihan SL, Regunath K, Freed-PastorWA,Morris JP,et al. p53 represses the mevalonate pathway to mediate tumor suppression. Cell2019;176:564–580

10. Harshman LC, Wang X, Nakabayashi M, Xie W, Valenca L, Werner L, et al.Statin use at the time of initiation of androgen deprivation therapy and time toprogression in patients with hormone-sensitive prostate cancer. JAMA Oncol2015;1:495.

11. Chae YK, Valsecchi ME, Kim J, Bianchi AL, Khemasuwan D, Desai A, et al.Reduced risk of breast cancer recurrence in patients using ACE Inhibitors, ARBs,and/or Statins. Cancer Invest 2011;29:585–93.

12. Yu R, Longo J, van Leeuwen JE, Mullen PJ, Ba-Alawi W, Haibe-Kains B, et al.Statin-induced cancer cell death can be mechanistically uncoupled from pre-nylation of RAS Family Proteins. Cancer Res 2018;78:1347–57.

13. Hingorani SR,Wang L,Multani AS, Combs C, Deramaudt TB, Hruban RH, et al.Trp53R172H andKrasG12D cooperate to promote chromosomal instability andwidelymetastatic pancreatic ductal adenocarcinoma inmice. Cancer Cell 2005;7:469–83.

14. Lewis CA, Parker SJ, Fiske BP, McCloskey D, Gui DY, Green CR, et al. Tracingcompartmentalized NADPH metabolism in the cytosol and mitochondria ofmammalian cells. Mol Cell 2014;55:253–63.

15. McCabe BJ, Bederman IR, Croniger C, Millward C, Norment C, Previs SF.Reproducibility of gas chromatography–mass spectrometry measurements of2H labeling of water: application for measuring body composition in mice.Anal Biochem 2006;350:171–6.

16. Yang D, Diraison F, Beylot M, Brunengraber DZ, Samols MA, Anderson VE,et al. Assay of low deuterium enrichment of water by isotopic exchange with [U-13C3]acetone and gas chromatography-mass spectrometry. Anal Biochem 1998;258:315–21.

17. Tumanov S, Bulusu V, Kamphorst JJ. Analysis of fatty acid metabolismusing stable isotope tracers and mass spectrometry. Methods Enzymol 2015;561:197–217.

18. MackayGM,Zheng L, van denBroekNJF, Gottlieb E.Analysis of cellmetabolismusing LC-MS and isotope tracers. Methods Enzymol 2015;171–96.

19. Melamud E, Vastag L, Rabinowitz JD. Metabolomic analysis and visualizationengine for LC�MS Data. Anal Chem 2010;82:9818–26.

20. Lee W-NP, Bassilian S, Lim S, Boros LG. Loss of regulation of lipogenesis in theZucker diabetic (ZDF) rat. Am J Physiol Metab 2000;279:E425–32.

21. LeeWN, Bassilian S, Ajie HO, Schoeller DA, Edmond J, Bergner EA, et al. In vivomeasurement of fatty acids and cholesterol synthesis using D2O and massisotopomer analysis. Am J Physiol Metab 1994;266:E699–708.

22. Chou T-C, Talalay P. Quantitative analysis of dose-effect relationships: thecombined effects of multiple drugs or enzyme inhibitors. Adv Enzyme Regul1984;22:27–55.

23. Faust JR, Goldstein JL, Brown MS. Synthesis of ubiquinone and cholesterol inhuman fibroblasts: regulation of a branched pathway. Arch Biochem Biophys1979;192:86–99.

24. Ashida S, Kawada C, Inoue K. Stromal regulation of prostate cancer cell growthby mevalonate pathway enzymes HMGCS1 and HMGCR. Oncol Lett 2017;14:6533–42.

25. Chojnacki T, Dallner G. The biological role of dolichol. Biochem J 1988;251:1–9.26. Crane FL. Biochemical Functions of Coenzyme Q 10. J Am Coll Nutr 2001;20:

591–8.27. Tretter L, Patocs A, Chinopoulos C. Succinate, an intermediate in metabolism,

signal transduction, ROS, hypoxia, and tumorigenesis. Biochim Biophys Acta2016;1857:1086–101.

28. Sabharwal SS, Schumacker PT. Mitochondrial ROS in cancer: initiators, ampli-fiers or an Achilles’ heel? Nat Rev Cancer 2014;14:709–21.

29. Ernster L, Forsmark-Andr�ee P. Ubiquinol: an endogenous antioxidant in aerobicorganisms. Clin Investig 1993;71:S60–5.

30. Starkov AA. The role ofmitochondria in reactive oxygen species metabolism andsignaling. Ann N Y Acad Sci 2008;1147:37–52.

31. Jiang L, Shestov AA, Swain P, Yang C, Parker SJ, Wang QA, et al. Reductivecarboxylation supports redox homeostasis during anchorage-independentgrowth. Nature 2016;532:255–8.

32. Meister A, Anderson ME. Glutathione. Annu Rev Biochem 1983;52:711–60.33. Alia, Mohanty P,Matysik J. Effect of proline on the production of singlet oxygen.

Amino Acids 2001;21:195–200.34. Hollinshead KER,MunfordH, Eales KL, Bardella C, Li C, Escribano-Gonzalez C,

et al. Oncogenic IDH1 mutations promote enhanced proline synthesis through

PYCR1 to support the maintenance of mitochondrial redox homeostasis.Cell Rep 2018;22:3107–14.

35. Smirnoff N, Cumbes QJ. Hydroxyl radical scavenging activity of compatiblesolutes. Phytochemistry 1989;28:1057–60.

36. Patton GM, Lowenstein JM. Measurements of fatty acid synthesis by incorpo-ration of deuterium from deuterated water. Biochemistry 1979;18:3186–8.

37. Diraison F, Pachiaudi C, Beylot M. In vivo measurement of plasma cholesteroland fatty acid synthesis with deuterated water: determination of the averagenumber of deuterium atoms incorporated. Metabolism 1996;45:817–21.

38. Choudhury RP, Carrelli AL, Stern JD, Chereshnev I, Soccio R, Elmalem VI,et al. Effects of simvastatin on plasma lipoproteins and response to arterialinjury in wild-type and apolipoprotein-E-deficient mice. J Vasc Res 2004;41:75–83.

39. Sparrow CP, Burton CA, Hernandez M, Mundt S, Hassing H, Patel S, et al.Simvastatin has anti-inflammatory and antiatherosclerotic activities indepen-dent of plasma cholesterol lowering. Arterioscler Thromb Vasc Biol 2001;21:115–21.

40. Ghirlanda G, Oradei A, Manto A, Lippa S, Uccioli L, Caputo S, et al. Evidence ofplasma CoQ10-lowering effect by HMG-CoA reductase inhibitors: a double-blind, placebo-controlled study. J Clin Pharmacol 1993;33:226–9.

41. Young O, Crotty T, O’Connell R, O’Sullivan J, Curran AJ. Levels of oxidativedamage and lipid peroxidation in thyroid neoplasia. Head Neck 2010;32:750–6.

42. DeNicola GM, Karreth FA, Humpton TJ, Gopinathan A, Wei C, Frese K, et al.Oncogene-induced Nrf2 transcription promotes ROS detoxification and tumor-igenesis. Nature 2011;475:106–9.

43. Habib E, Linher-Melville K, Lin H-X, Singh G. Expression of xCT and activity ofsystem xc� are regulated by NRF2 in human breast cancer cells in response tooxidative stress. Redox Biol 2015;5:33–42.

44. Cheung KL, Lee JH, Shu L, Kim J-H, Sacks DB, Kong A-NT. The Ras GTPase-activating-like protein IQGAP1 mediates Nrf2 protein activation via the mito-gen-activated protein kinase/extracellular signal-regulated kinase (ERK) kinase(MEK)-ERK pathway. J Biol Chem 2013;288:22378–86.

45. Warita K, Warita T, Beckwitt CH, Schurdak ME, Vazquez A, Wells A, et al.Statin-induced mevalonate pathway inhibition attenuates the growth of mes-enchymal-like cancer cells that lack functional E-cadherin mediated cell cohe-sion. Sci Rep 2014;4:7593.

46. Cardaci S, Zheng L, MacKay G, van den Broek NJF, MacKenzie ED, Nixon C,et al. Pyruvate carboxylation enables growth of SDH-deficient cells by supportingaspartate biosynthesis. Nat Cell Biol 2015;17:1317–26.

47. Fan J, Kamphorst JJ, Rabinowitz JD, Shlomi T. Fatty acid labeling fromglutaminein hypoxia can be explained by isotope exchange without net reductive isocitratedehydrogenase (IDH) Flux. Mol Syst Biol.2013;9:712.

48. Davidson SM, Papagiannakopoulos T, Olenchock BA, Heyman JE, Keibler MA,Luengo A, et al. Environment impacts the metabolic dependencies of ras-drivennon-small cell lung cancer. Cell Metab 2016;23:517–28.

49. Marin-Valencia I, Yang C, Mashimo T, Cho S, Baek H, Yang X-L, et al. Analysisof tumor metabolism reveals mitochondrial glucose oxidation in geneticallydiverse human glioblastomas in the mouse brain in vivo. Cell Metab 2012;15:827–37.

50. Kettawan A, Takahashi T, Kongkachuichai R, Charoenkiatkul S, Kishi T,Okamoto1 T. Protective effects of coenzyme Q10 on decreased oxidative stressresistance induced by simvastatin. J Clin Biochem Nutr 2007;40:194–202.

51. Beltowski J. Statins and modulation of oxidative stress. Toxicol Mech Methods2005;15:61–92.

52. Conrad M, Sato H. The oxidative stress-inducible cystine/glutamate antiporter,system x c �: cystine supplier and beyond. Amino Acids 2012;42:231–46.

53. Mahoney CE, Pirman D, Chubukov V, Sleger T, Hayes S, Fan ZP, et al. Achemical biology screen identifies a vulnerability of neuroendocrine cancer cellsto SQLE inhibition. Nat Commun 2019;10:96.

54. Ge H, Zhao Y, Shi X, Tan Z, Chi X, HeM, et al. Squalene epoxidase promotes theproliferation and metastasis of lung squamous cell carcinoma cells thoughextracellular signal-regulated kinase signaling. Thorac Cancer 2019;10:428–436

55. Liao J, Chung YT, Yang AL, ZhangM, Li H, ZhangW, et al. Atorvastatin inhibitspancreatic carcinogenesis and increases survival in LSL-KrasG12D-LSL-Trp53R172H-Pdx1-Cre mice. Mol Carcinog 2013;52:739–50.

56. Alizadeh J,ZekiAA,MirzaeiN,Tewary S, RezaeiMoghadamA,GlogowskaA, et al.Mevalonate cascade inhibition by simvastatin induces the intrinsic apoptosispathway via depletion of isoprenoids in tumor cells. Sci Rep 2017;7:44841.

57. Kawata S, Yamasaki E, Nagase T, Inui Y, Ito N, Matsuda Y, et al. Effect ofpravastatin on survival in patients with advanced hepatocellular carcinoma. Arandomized controlled trial. Br J Cancer 2001;84:886–91.






58. Kwan ML, Habel LA, Flick ED, Quesenberry CP, Caan B. Post-diagnosis statinuse and breast cancer recurrence in a prospective cohort study of early stagebreast cancer survivors. Breast Cancer Res Treat 2008;109:573–9.

59. Krens LL, Simkens LHJ, Baas JM, Koomen ER, Gelderblom H, Punt CJA, et al.Statin use is not associated with improved progression free survival in cetuximabtreated KRAS mutant metastatic colorectal cancer patients. PLoS One 2014;9:e112201.

60. Hong JY, Nam EM, Lee J, Park JO, Lee S-C, Song S-Y, et al. Randomized double-blinded, placebo-controlledphase II trial of simvastatinandgemcitabine inadvancedpancreatic cancer patients. Cancer Chemother Pharmacol 2014;73:125–30.

61. Murtola TJ, Syv€al€a H, Tolonen T, Helminen M, Riikonen J, Koskim€aki J, et al.Atorvastatin versus placebo for prostate cancer before radical prostatectomy—arandomized, double-blind, placebo-controlled clinical trial. Eur Urol 2018;74:697–701.


McGregor et al.




2020;80:175-188. Published OnlineFirst September 27, 2019.Cancer Res Grace H. McGregor, Andrew D. Campbell, Sigrid K. Fey, et al. Stress Produces a Synergistic Antitumor ResponseTargeting the Metabolic Response to Statin-Mediated Oxidative

Updated version

10.1158/0008-5472.CAN-19-0644doi:

Access the most recent version of this article at:

Material

Supplementary

http://cancerres.aacrjournals.org/content/suppl/2019/09/27/0008-5472.CAN-19-0644.DC1

Access the most recent supplemental material at:

Cited articles

http://cancerres.aacrjournals.org/content/80/2/175.full#ref-list-1

This article cites 59 articles, 8 of which you can access for free at:

Citing articles

http://cancerres.aacrjournals.org/content/80/2/175.full#related-urls

This article has been cited by 4 HighWire-hosted articles. Access the articles at:

E-mail alerts related to this article or journal.Sign up to receive free email-alerts

Subscriptions

Reprints and

[email protected]

To order reprints of this article or to subscribe to the journal, contact the AACR Publications Department at

Permissions

Rightslink site. Click on "Request Permissions" which will take you to the Copyright Clearance Center's (CCC)

.http://cancerres.aacrjournals.org/content/80/2/175To request permission to re-use all or part of this article, use this link



http://cancerres.aacrjournals.org/lookup/doi/10.1158/0008-5472.CAN-19-0644

http://cancerres.aacrjournals.org/content/suppl/2019/09/27/0008-5472.CAN-19-0644.DC1

http://cancerres.aacrjournals.org/content/80/2/175.full#ref-list-1

http://cancerres.aacrjournals.org/content/80/2/175.full#related-urls

http://cancerres.aacrjournals.org/cgi/alerts

mailto:[email protected]

http://cancerres.aacrjournals.org/content/80/2/175


Documents

Targeting the Metabolic Response to Statin-Mediated ... · Giovanny Rodriguez Blanco1, Gillian Mackay1, Colin Nixon1, Alexei Vazquez1,2, Owen J. Sansom1,2, and Jurre J. Kamphorst1,2,3