Combined Inhibition of PI3Kb and mTOR Inhibits Growth of ... · Small Molecule Therapeutics Combined Inhibition of PI3Kb and mTOR Inhibits Growth of PTEN-null Tumors James T. Lynch1,

Small Molecule Therapeutics

Combined Inhibition of PI3Kb and mTOR InhibitsGrowth of PTEN-null TumorsJames T. Lynch1, Urszula M. Polanska1, Ursula Hancox2, Oona Delpuech1,Juliana Maynard3, Catherine Trigwell1, Catherine Eberlein1, Carol Lenaghan1,Radoslaw Polanski4, Alvaro Avivar-Valderas5, Marie Cumberbatch1, Teresa Klinowska1,Susan E. Critchlow1, Francisco Cruzalegui5, and Simon T. Barry1

Abstract

Loss of the tumor suppressor PTEN confers a tumor celldependency on the PI3Kb isoform. Achieving maximal inhi-bition of tumor growth through PI3K pathway inhibitionrequires sustained inhibition of PI3K signaling; however,efficacy is often limited by suboptimal inhibition or reactiva-tion of the pathway. To select combinations that delivercomprehensive suppression of PI3K signaling in PTEN-nulltumors, the PI3Kb inhibitor AZD8186 was combinedwith inhibitors of kinases implicated in pathway reactivationin an extended cell proliferation assay. Inhibiting PI3Kb andmTOR gave the most effective antiproliferative effects acrossa panel of PTEN-null tumor cell lines. The combinationof AZD8186 and the mTOR inhibitor vistusertib was also

effective in vivo controlling growth of PTEN-null tumormodels of TNBC, prostate, and renal cancers. In vitro, thecombination resulted in increased suppression of pNDRG1,p4EBP1, as well as HMGCS1 with reduced pNDRG1 andp4EBP1 more closely associated with effective suppression ofproliferation. In vivo biomarker analysis revealed that themonotherapy and combination treatment consistentlyreduced similar biomarkers, while combination increasednuclear translocation of the transcription factor FOXO3 andreduction in glucose uptake. These data suggest that combin-ing the PI3Kb inhibitor AZD8186 and vistusertib has potentialto be an effective combination treatment for PTEN-nulltumors. Mol Cancer Ther; 17(11); 2309–19. �2018 AACR.

IntroductionLoss of PTEN protein expression is observed in many tumors

and is associated with poorer prognosis (1–5), and resistance toimmunotherapy (6, 7). Given the incidence of aberrations inPTEN protein loss, there is a need to find effective therapeuticstrategies to treat PTEN-null tumors. The tumor suppressor PTENregulates PI3K signaling (5, 8). Epithelial cells are normallydependent on the PI3Ka isoform, but when PTEN is deleted,signaling through the PI3Kb isoform is important for tumorprogression (2, 9). Although the mechanism that creates thisdependency is unknown, it may be associated with an increase

in cellular PIP3 levels (10, 11) via constitutive basal activity ofPI3Kb. PI3Kb is the only PI3K isoform that can be activated byboth G-protein–coupled receptors (GPCR) and transmembranegrowth factors receptors (GFR; ref. 12). Unlike the PI3Ka isoformwhere activatingmutations are common (5), the PI3Kb isoform israrely mutated (13, 14), hence the activation remains dependenton other proteins.

A number of kinase inhibitors targeting PI3Kb (GSK2636771,SAR260301, and AZD8186; refs. 15–18) have been progressed toclinical trialswith the aimof treating PTEN-null tumors.However,it has become apparent that while PTEN-null cell lines areenriched for a dependency on PI3Kb, multiple mechanisms havebeen associated with either feedback-mediated reactivation ofsignaling, or resistance to PI3Kb inhibition (19, 20). Thesemechanisms include the activation of EGFR, IGFR, IR, and acti-vation of PI3Ka or ERK signaling (21–25). All of these pathwayshave the potential to limit efficacy, therefore identifying combi-nation strategies to enhance or sustain pathway inhibition isimportant for maximal therapeutic effect. In this study, inhibitorsof pathways implicated in feedback reactivation or resistancewerecombined with the PI3Kb inhibitor AZD8186 with the aim ofidentifying an optimal combination for treatment of PI3Kb-dependent PTEN-null tumors.

Materials and MethodsCell line culture

Cell lines used for in vitro and in vivo experiments are listed inSupplementary Table S1. Cell lines were cultured at 37�C, 5%carbon dioxide. All cell lines were authenticated at AstraZenecausing DNA fingerprinting short-tandem repeat (STR) assays. Cellswere usedwithin 15passages, and cultured for less than6months.

1Bioscience, Oncology, IMED Biotech Unit, AstraZeneca, Cambridge, UnitedKingdom. 2Bioscience, Oncology, IMED Biotech Unit, AstraZeneca, AlderleyPark, United Kingdom. 3Alderley Imaging, Alderley Park Ltd, Alderley Park,United Kingdom. 4Discovery Sciences, IMED Biotech Unit, AstraZeneca, Cam-bridge, United Kingdom. 5Translational Sciences, Oncology, IMED Biotech Unit,AstraZeneca, Cambridge, United Kingdom.

Note: Supplementary data for this article are available at Molecular CancerTherapeutics Online (http://mct.aacrjournals.org/).

Current address for C. Trigwell: Division of Cancer Sciences, The University ofManchester, Christie Hospital, Manchester, United Kingdom; current address forC. Eberlein, CRUK Manchester Institute, Manchester, United Kingdom; andcurrent address for F. Cruzalegui, Institut de Recherche Pierre Fabre, Toulouse,France.

Corresponding Author: Simon T. Barry, IMED Biotech Unit, AstraZeneca,Cambridge Science Park, Cambridge CB4 0WG, United Kingdom. Phone:þ44 7789744771; E-mail: [email protected]

doi: 10.1158/1535-7163.MCT-18-0183

�2018 American Association for Cancer Research.

MolecularCancerTherapeutics

www.aacrjournals.org 2309

on October 17, 2020. © 2018 American Association for Cancer Research. mct.aacrjournals.org Downloaded from

Published OnlineFirst August 10, 2018; DOI: 10.1158/1535-7163.MCT-18-0183

http://crossmark.crossref.org/dialog/?doi=10.1158/1535-7163.MCT-18-0183&domain=pdf&date_stamp=2018-10-23

http://mct.aacrjournals.org/

Details of the cancer relevant genetics for the cell lines aredescribed in Supplementary Table S1.

In vitro Western blot analysisCells were lysed in RIPA buffer (Thermo Fisher Scientific)

supplemented with 1� Protease Inhibitor Cocktail (Roche), 1�phosphatase inhibitor (Thermo Fisher Scientific) and 1:5,000benzonase (Sigma-Aldrich) and equal amounts of protein wereloaded and separated by SDS-PAGE. Horseradish peroxidase–linked secondary antibodies (GE Healthcare) and ECL or super-signal (Thermo Fisher Scientific) were used to detect immunecomplexes. Details of primary antibodies can be found in Sup-plementary Table S2.

Cell proliferation assaysFor the combination screen, fresh media/compounds were

replaced every 3–4 days over the course of 14 days. Cells werefixed with 3.7% formaldehyde containing 0.01% Triton X-100(Sigma-Aldrich) for 30minutes at room temperature. Nucleiwere stained with Hoechst (1:5,000, Thermo Fisher Scientific)in PBS for 30minutes at room temperature. Cells were analyzedon a CellInsight (Thermo Fisher Scientific) using a cell countalgorithm. For long-term proliferation assays, fresh media/compounds were replaced every 7 days over the course of 21days. Every 7 days, cells were counted using the methoddescribed for the combination screen proliferation assay.AZD6244 (ARRY-142886), vistusertib, AZD8835, AZD5363,AZD9291, AZD6244, and BMS536924 were all synthesizedat AstraZeneca.

Antitumor experimentsAll animal experiments were performed to the according to the

local regulations Home Office UK. A total of 1 � 106 PC3 cells inIscove's serum-free medium mixed 50:50 with Matrigel (BectonDickinson) or 1 � 106 HCC70 cells in RPMI serum-free mediummixed 50:50 with Matrigel were implanted in the flank of femalenude mice (nu/nu:Alpk; AstraZeneca) between the ages of 8 and12 weeks. 786-0 cells (5 � 106 cells in RPMI serum-free mediummixed 50:50 with Matrigel) were implanted into the flank offemale SCID mice (AstraZeneca) between the ages of 8 and 12weeks. MDA-MB-468 cells (ATCC) were implanted into #3mam-mary fat pad (107/mouse) in 0.05 mL of medium without serumand Matrigel (Becton Dickinson) at a 1:1 ratio. Once tumorsreached approximately 200–500mm3, animals were randomizedinto control and treatment groups. Tumor volume was calculatedtwice weekly from bilateral caliper measurements using the for-mula (length � width � width) � p/6). AZD8186 was generallyformulated once weekly as a suspension in 0.5% HPMC/0.1%Tween 80 and dosed once or twice daily (0 and 6–8 hours).Vistusertib was formulated as a suspension in 0.5% HPMC/0.1%Tween 80. For combination dosing, AZD8186 and vistusertibwere coformulated in 0.5% HPMC/0.1% Tween. Growth inhibi-tion from the start of treatmentwas assessed by comparison of thegeometric mean change in tumor volume for the control andtreated groups. Further details of all tumor growth studies areincluded in Supplementary Methods.

Pharmacodynamic studiesFor pharmacokinetic analysis, total blood was collected by

intracardiac puncture and plasma prepared and immediatelyfrozen at �20�C. For pharmacodynamic protein biomarker or

transcript analysis at each time point, aminimumof 4 or 5 tumorswere snap frozen in liquid nitrogen. Lysates were generated asfollows: lysis buffer (1%Triton X-100, Invitrogen), supplementedwith phosphatase inhibitors 2 and 3 (Sigma-Aldrich) and prote-ase inhibitors (Sigma-Aldrich), were added to each tumor in aFastprep tube (MP Biomedicals). The tumors were homogenizedusing a MP Biomedicals Fast Prep-24 machine. Samples weresonicated, centrifuged, and protein concentration determined.Protein was separated using SDS-PAGE and immune complexeswere detected as described in the In vitro Western blot analysissection. Tumor lysates were added toMeso Scale Discovery platesto measure total and phosphorylated AKT and S6 [pAKT-Ser473(MSD K15100D) and pS6-Ser235/236 (MSD K150DFD)]. MSDplates were used according to the manufacturer's instructionsand developed using SECTOR Imager. The calculated values ofthe tested biomarker were logged (log10 scale), averaged foranimals in the same group, and geomean calculated (10^aver-age). Vehicle controls were used for normalizing biomarker signalfor the treated samples. A two-sided t test was performed onlogged data assuming unequal variance. Pharmacokinetic data(free plasma concentration of each drug) was plotted alongsidebiomarker data.

In vivo FOXO3A immunodetection assaysFor in vivo staining, FFPE tissues were sectioned at 4 mm onto

slides, dewaxed, and rehydrated. Antigen retrieval was performedin a RHS microwave vacuum processor (Milestone) at 110�C inEDTA (pH 8; 2 minutes) for Foxo3a (Cell Signaling Technology2497). Endogenous peroxidise activity was blocked with 0.18%hydrogen for 10 minutes and nonspecific binding sites wereblocked with serum-free protein block (Dako X0909) for 20minutes. Sectionswere incubated for 1hour inprimary antibodies(0.2 mg/mL) diluted in Tris-buffered saline containing 0.05%Tween (TBS-T). Staining was visualized using rabbit EnvisionHRP-linked polymer (Dako K4003) followed by incubation for10 minutes in 3,30-diaminobenzidine (Dako K3466). Counter-staining was conducted using Carazzi hematoxylin. All washeswere performed in TBS-T and all incubations were at roomtemperature. No staining was observed in samples incubatedwith appropriate isotype control antibodies. Digital images ofstained slides were acquired using an Aperio slide scanner (LeicaBiosystems). Slides were annotated manually to exclude areas ofpoor tissue/staining quality. Cytoplasmic and nuclear FOXO3Awas assessed by a pathologist to provide percent tumor cellspositive for each localization and data displayed as mean per-centage change in percent positive cells relative to controls.

RNA profiling and analysisCell pellets were snap frozen and total RNAwas extracted using

a mRNeasy kit (Qiagen), with DNAse treatment, following man-ufacturer's instructions. Targeted gene expression was performedusing the BioMark HDTM –Fluidigm Array platform (96.96dynamic array) and TaqMan primers (human vs. mouse specificwhenpossible) followingmanufacturer's instructions. Fifty nano-grams of total RNA was reverse transcribed and preamplified(Thermo Fisher Scientific: #4374967, #4488593) for 14 cycles,with 96 selected primers selected from previous RNA-sequencingdata (26). The 96.96 Fluidigm Dynamic Arrays were primed andloaded on an IFC Controller and qPCR experiments run on theBiomark System, using the standard 96 default protocol. Datawere collected and analyzed using the Fluidigm Real-Time PCR

Lynch et al.

Mol Cancer Ther; 17(11) November 2018 Molecular Cancer Therapeutics2310




Analysis software, generatingCt values.Ct values were normalizedto the average of selected housekeeping genes (DCt) and com-pared with the time-matched DMSO control (�DDCt). All geneexpression calculations and statistical analysis (pairwise Studentt test) were performed on gene expression data (�DDCt) inJmp12.0.1, and data represented in TIBCOTM Spotfire 6.5.2.Details of primers can be found in Supplementary Table S3.

FDG uptake studiesFor static scanning tumor-bearingmice received approximately

15 MBq 18F-FDG (PETNET Solutions) administered as an intra-venous bolus. Following injection, anesthesia wasmaintained fora 45-minute uptake period followed by a20-minute emission PETscan (Inveon Multimodality PET scanner from Siemens MedicalSolutions; ref. 27). Data were acquired using Inveon AcquisitionWorkplace (IAW) software (Siemens) version 1.5 and analyzedusing Inveon Reconstruction (IRW) Software (Siemens) version2.2.0. Images were reconstructed using the 2D filtered backprojection algorithm. Regions of Interest (ROI) were manuallydrawn using the 3D visualization package in the IRW software.Data were expressed as maximum standardized uptake value(MaxSUV). MaxSUV was calculated as described by Gambhir andcolleagues; where injected dose (ID) is the injected activity (28).For dynamic scanning, tumor-bearing mice received approxi-mately 20 MBq 18F-FDG administered by tail vein intravenousinjection and underwent a 90-minute PET emission scan. Datawere acquired as above but analyzed using PMod software version3.2. After determining the length of the first frame (scan start timeto injection time), the list model data were histogrammed usingtwo sequences represented as F:t where F¼ number of frames and

t¼ time (seconds). Sequence A¼ 1: (scan start to injection time),(20:1, 2:5, 1:10, 3:30, 3:60, 1:300, 7:600); Sequence B ¼ 1: (scanstart to injection time), (6:5, 1:10, 3:30, 3:60, 1:300, 2:600).Images were reconstructed using ordered subset expectationmax-imization (OSEM)/maximum a posteriori (MAP) algorithm(28 SEM iterations, 18 MAP iterations, b ¼ 0.004278 giving aspatial resolutionof 1mm). Spatial resolution is improvedusing alower b value at the expense of a higher image noise. The leftventricle time–activity curve (TAC)was extracted fromSequenceAand a hybrid input function was used to correct for myocardiumuptake. The tumor TAC was extracted from the imaging sequence[two-compartment five parameter (K1, k, k3, k4, and vb) modelwas used to fit the tumor TAC for full kinetic analysis]. In allstudies to assess biodistribution, blood, muscle, lung, liver, heart,bone, and tail were removed following scanning and weighed.Tissue samples were counted in a gamma counter (Perkin Elmer,1480, Wizard 3) and after correction for decay converted tokilobecquerels/gram enabling the%ID/g tissue to be determined.All mice in whom the tail activity exceeded 10% of the ID wereexcluded from analysis.

ResultsCombining PI3Kb and mTOR inhibition gives long-termsuppression of cell growth

To assess the dominant complementary drivers following sup-pression of PI3Kb signaling, a combination screen was performedin a panel of PTEN-null cell lines from different tumor types.PI3Kbwas inhibited with AZD8186 (18). To inhibit key signalingnodes associated with resistance or feedback, inhibitors targeting

A

B

BT-549

HCC1954

HCC70

MDA-MB-468

NCI-H1703

PC3

Con

trol

PI3

Kβi

mTO

Ri

AK

Ti

PI3

Kαi

EG

FRm

i

ME

Ki

IGF-

1Ri

mTO

Ri

AK

Ti

PI3

Kαi

EG

RFm

i

ME

Ki

IGF-

1Ri

AZD8186 (250 nmol/L)-PI3Kβi

Vistusertib (500 nmol/L)-mTORi

AZD5363 (500 nmol/L)-AKTi

AZD8835 (250 nmol/L)-PI3Kαi

AZD9291 (160 nmol/L)-EGFRmi

AZD6244 (100 nmol/L)-MEKi

BMS-536924 (100 nmol/L)-IGF-1Ri

+ 250 nmol/L PI3Kβi

0 5 10 15 20 250

500

1,000

1,500

PC3

Time (days)

AvC**VvC*

0 5 10 15 20 250

500

1,000

1,500

HCC70

Time (days)

AvC*VvC**

0 5 10 15 20 250

800

1,600

2,400

MDA-MB-468

Time (days)

Rel

ativ

e ce

ll nu

mbe

r

Rel

ativ

e ce

ll nu

mbe

r

Rel

ativ

e ce

ll nu

mbe

r

DMSOAZD8186VistusertibAZD8186/vistusertib

NS

MaxAverageMin

Figure 1.

A combination screen identifies mTOR inhibitors as a combination partner for PI3Kb inhibitors. A, AZD8186 was screened in combination with a number ofkinase inhibitors in 14-day proliferation assays across a panel of cancer cell lines. Heatmap represents cell count relative to a DMSO control. B, HCC70, PC3,and MDA-MB-468 cells were treated with AZD8186 (250 nmol/L), vistusertib (250 nmol/L) or in combination for 21 days (n ¼ 3). Graphs represent mean cellnumber over time. Once a treatment arm reaches confluence, dosing is terminated and nomore measurements are taken. Error bars, SD of the mean. AWelch t testwas performed on the day 21 time point comparing monotherapy treatment versus the combination (� , P < 0.05; �� , P < 0.01). AvC, AZD8186 versuscombination; VvC, vistusertib versus combination; NS, not significant.

Combined PI3Kb mTOR Inhibition in PTEN-null Tumors

www.aacrjournals.org Mol Cancer Ther; 17(11) November 2018 2311




the following kinases were selected: mTOR (vistusertib; ref. 29),PI3Ka/d (AZD8835; ref. 30), AKT (AZD5363; ref. 31), EGFR(AZD9291; ref. 32), MEK (AZD6244; refs. 33, 34), and IGF-1R(BMS536924; ref. 35). Each compound was used at a fixedconcentration sufficient to inhibit the primary target, but belowthat at which other kinases were inhibited. To increase thestringency of the screen, the ability to inhibit growth over 14days was determined. While many of the combinations showedlong-term benefit in individual cell lines the most effective com-bination across the panel was PI3Kb and mTOR inhibition. Thiscombination was effective even in cell lines such as PC3 andBT549, which are more resistant to each monotherapy treatment(Fig. 1A). The effects of combined PI3Kb and mTOR inhibitionwere confirmed in selected cell lines using a 21-day proliferationassay. Growth ofHCC70 and PC3 cell lines was suppressed by the

combination at the concentrations tested (Fig. 1B).MDA-MB-468cells were less sensitive to the combination treatment in the cellline screen, and showed minimal reduction in cell growth in thelong-term proliferation assays (Fig. 1B). Collectively, these datasuggest that combining AZD8186 and vistusertib has broadcombination potential in a number of PTEN-null cell lines.

AZD8186 and vistusertib combination gives increasedsuppression of tumor growth in vivo

To assess whether the in vitro combination effects translatein vivo, a panel of PTEN-null human tumor xenograft modelswere treated with AZD8186 and vistusertib (Fig. 2; Supplemen-tary Fig. S1). Combining AZD8186 (50 mg/kg twice daily) andvistusertib (15 mg/kg once daily) gave increased and durableeffects in HCC70 and PC3models (Fig. 2A and B). The PTEN-null

Figure 2.

Enhanced efficacy of AZD8186 and vistusertib across a number of PTEN-null cancer cell line models. HCC70 (A), PC3 (B), 786-0 (C), and MDA-MB-468 (D)tumors were treated with AZD8186, vistusertib, and in combination at the dose and schedules indicated above. Geometric mean of the relative tumorvolume and SEM are shown.

Lynch et al.





renal tumor xenograft 786-0 is more sensitive to AZD8186,therefore the dose of AZD8186 was reduced to 12.5 mg/kg.Combining AZD8186 with vistusertib resulted in 786-0 tumorregression (Fig. 2C). Increased benefit from the combination wasalso observed in PTEN-null LNCAP C4-2 tumor xenografts (Sup-plementary Fig. S1A), a human PTEN-null prostate PDX modelLuCAP E86 (Supplementary Fig. S1B), a PTEN-null renal PDXmodel CTG-824 (Supplementary Fig. S1C) and a PTEN-nullglioblastoma xenograft U87-MG (Supplementary Fig. S1D). Incontrast, the MDA-MB-468 tumor xenografts failed to showincreased antitumor benefit from the combination treatmentconsistent with the in vitro data (Fig. 1D). Collectively, thissuggests that the combination of AZD8186 and vistusertib havepotential to be effective across PTEN-null tumors.

PI3Kb and mTOR inhibition delivers comprehensive pathwaymodulation in vitro and in vivo

Inhibiting PI3Kb signaling in PTEN-null cell lines reduces PI3Kpathway biomarkers such as pAKT and pS6, downregulatesenzymes in the cholesterol biosynthesis pathway, and reducesnucleotide synthesis (36). To gain greater insight into the conse-quence of targeting both mTOR and PI3Kb, HCC70, PC3, andMDA-MB-468 cells were treated with AZD8186, vistusertib, andthe combination (Fig. 3). Twenty-four hours following vistusertibtreatment, inhibition of pS6 and p4EBP1 was evident, but pAKT,pNDRG1, and pPRAS40 levels returned to basal levels. Twenty-four hours following AZD8186 treatment, inhibition of pAKT,pNDRG1, and pPRAS40 was observed. However AZD8186 wasless effective at inhibiting pS6 and p4EBP1 relative to vistusertib.Combination treatment effectively inhibited both PI3K andmTOR signaling nodes in HCC70 and PC3 cell lines. Consistentwith the effects in the long-term proliferation assays, the combi-

nation did not effectively inhibit pathway signaling in theMDA-MB-468 cell line. Combination treatment resulted in asmall induction of cleaved caspase-3 in HCC70 cells, but not inthe PC3 or MDA-MB-468 cell lines. In addition to assessingmodulation of protein biomarkers, HCC70 and PC3 cells wereprofiled for changes in expression of specific transcripts associatedwith cell metabolism and cell stress. AZD8186 and vistusertibmodulated similar transcript profiles; however, the combinationresulted in enhancedmodulation of a number of genes associatedwith metabolism and cellular stress (Supplementary Fig. S2).Collectively, these data demonstrate that in cells where the com-bination of AZD8186 and vistusertib gave long-term growthsuppression, there is greater suppression of both PI3K andmTORsignaling nodes beyond which either AZD8186 or vistusertibachieved when used as a monotherapy.

To assess pathway modulation in vivo, HCC70 and PC3 tumorxenografts were treated with AZD8186 and vistusertib and ana-lyzed for changes in the same biomarkers. In both models,biomarker modulation was similar but not identical (Fig. 4;Supplementary Fig. S3). Consistent reduction in pAKT, pS6,pNDRG1 and p4EBP1, and HMGCS1 occurred following bothmonotherapy and combination treatment. At the doses andschedules assessed, the combination of AZD8186 and vistusertibsuppressed similar pathway biomarkers with some evidence ofincreased suppression of pNDRG1. In both HCC70 and PC3tumor xenografts, AZD8186 monotherapy treatment was lesseffective at inhibiting pS6 and p4EBP1 than vistusertib mono-therapy or the combination. In contrast, in PC3 tumor xenografts,vistusertib was less effective at reducing pAKT than AZD8186monotherapy and the combination. AZD8186 has a variablepharmacokinetic profile. While exposure appears higher inthe combination treatment groups at these time points, the

3CP07CCH MDA-MB-468

Survivin

Vinculin

pAKT (S473)

pPRAS40 (T246)

pS6 RP (S235/236)

p4EBP1 (S65)

c-MYC

pAKT (T308)

pNDRG1 (T346)

HMGCS1

Cleaved caspase 3

Time (hrs): .5 6 24 .5 6 24 .5 6 24 .5 6 24DMSO AZD8186 Vistusertib AZD8186/

vistusertib

.5 6 24 .5 6 24 .5 6 24 .5 6 24 .5 6 24 .5 6 24 .5 6 24 .5 6 24DMSO AZD8186 Vistusertib AZD8186/

vistusertibDMSO AZD8186 Vistusertib AZD8186

/vistusertib

Figure 3.

The combination of AZD8186 and vistusertib modulate feedback reactivation of pathway signaling in PTEN-null cancer cell lines. Western blot analysis wasperformed to determine modulation of the indicated proteins and phosphorylated proteins following pathway inhibition (n ¼ 2).






difference reflects the intrinsic variability in exposure seen across anumber ofmonotherapy and combination experiments analyzed,Evidence of increased biomarker modulation following combi-nation treatment was modest; however, there was an indicationthat more consistent suppression of pNDRG1 was achieved at6 hours in the HCC70 and PC3 models. In contrast to the in vitro

experiments, it is important to recognize that deconvoluting thecontribution of pathway reactivation in vivo and drug pharmaco-kinetics to pathway recovery is challenging. This is due to theintrinsic variability in biomarker modulation between tumorsamples and the pharmacokinetic profile of the compoundschanging over time both influence the biomarker signal.

A

B

pAKT (S473)

Bio

mar

ker s

igna

l (%

con

trol

)

PK: free plasm

a concentration (mmol/L)

PK: free plasm


PK: free plasm


PK: free plasm


PK: free plasm


PK: free plasm


PK: free plasm


PK: free plasm


PK: free plasm


PK: free plasm


PK: free plasm


PK: free plasm


6 h2 h6 h2 h6 h2 h6 h2 h0

50

100

150

0.001

0.01

0.1

1

AZD8186/VistusertibAZD8186ctrlvistusertib

*** ******

***

**

pPRAS40 (T246)

Bio

mar

ker s

igna

l (%

cont

rol)

2 h 6 h 2 h 6 h 2 h 6 h 2 h 6 h0

50

100

150

200

250

0.001

0.01

0.1

1

*

*


pNDRG1 (T346)

Bio

mar

ker s

igna

l (%

cont

rol)

6 h2 h6 h2 h6 h2 h6 h2 h0

50

100

150

0.001

0.01

0.1

1

****** ***

**

*P = 0 .0 5 3

AZD 8186/VistusertibAZD 8186ctrlVistusertib

pS6RP (S235/236)

Bio

mar

ker s

igna

l (%

con

trol

)B

iom

arke

r sig

nal (

% c

ontr

ol)

Bio

mar

ker s

igna

l (%

con

trol

)

Bio

mar

ker s

igna

l (%

con

trol

)

Bio

mar

ker s

igna

l (%

con

trol

)

Bio

mar

ker s

igna

l (%

con

trol

)

Bio

mar

ker s

igna

l (%

con

trol

)

Bio

mar

ker s

igna

l (%

con

trol

)

Bio

mar

ker s

igna

l (%

con

trol

)

6 h2 h6 h2 h6 h2 h6 h2 h0

50

100

150

200

250

0.001

0.01

0.1

1

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


p4EBP1 (T37/46)

2 h 6 h 2 h 6 h 2 h 6 h 2 h 6 h0

50

100

150

200

250

0.001

0.01

0.1

1

***** **

VistusertibAZD8186ctrl AZD8186/vistusertib

HMGCS1

6 h2 h6 h2 h6 h2 h6 h2 h0

50

100

150

0.001

0.01

0.1

1

***

*

**

VistusertibAZD8186ctrl AZD8186/vistusertib

pAKT (S473)

6 h2 h6 h2 h6 h2 h6 h2 h0

50

100

150

200

0.001

0.01

0.1

1

AZD8186/VistusertibAZD8186vistusertib

ctrl

***** ***

*

pPRAS40 (T246)

6 h2 h6 h2 h6 h2 h6 h2 h0

50

100

150

200

0.001

0.01

0.1

1

*** *** ***

VistusertibAZD8186 AZD8186/vistusertib

ctrl

pNDRG1 (T346)

6 h2 h6 h2 h6 h2 h6 h2 h0

5 0

1 0 0

1 5 0

0.001

0.01

0.1

1

*** ***

**

***

**

***

**

***

**


ctrl

pS6RP (S235/236)

6 h2 h6 h2 h6 h2 h6 h2 h0

50

100

150

200

0.001

0.01

0.1

1

*** ***

*


ctrl

p4EBP1 (T37/46)

6 h2 h6 h2 h6 h2 h6 h2 h0

50

100

150

0.001

0.01

0.1

1

*****

***


ctrl

HMGCS1

6 h2 h6 h2 h6 h2 h6 h2 h0

50

100

150

200

0.001

0.01

0.1

1

** ***


ctrl

Figure 4.

Combining AZD8186 with vistusertib, results in increased depth and/or time of PI3K pathway suppression, and impact on cholesterol synthesis in vivo.Pharmacokinetic/pharmacodynamic relationship examples for pathway biomarkers and HMGCS1 expression in HCC70 xenografts (A) after 5 days oftreatment with 50 mg/kg AZD8186 dosed twice daily, 15 mg/kg vistusertib dosed once daily, and their combination; PC3 xenografts after 21 days of treatmentwith 50 mg/kg AZD8186 dosed twice daily, 15 mg/kg vistusertib dosed once daily and their combination (B). Bar charts represent geomean � SEMbiomarker signal (left y-axis) and drugs plasma–free pharmacokinetics (red circles for AZD8186 and blue triangles for vistusertib, right y-axis; � , P < 0.05;�� , P < 0.01; �� , P < 0.001). n ¼ 3–6 animals/time point. QD, once daily; BID ¼ twice a day; ctrl, control.

Lynch et al.





AZD8186 and vistusertib combination sustains nuclearFOXO3A translocation

Inhibition of PI3K signaling in PTEN-null tumors results inthe translocation of FOXO3A to the nucleus. Conversely, reac-tivation of the pathway through feedback or as a result of loss ofcompound-mediated pathway suppression reduces the levels ofFOXO3A in the nucleus and increases the cytoplasmic levels(37). Therefore sustained FOXO3A nuclear translocation mayserve as a more discriminating measure of sustained pathwaysuppression in vivo. In HCC70 tumors, nuclear translocationwas observed following treatment with AZD8186 and to alesser extent vistusertib (Fig. 5). Six hours after compounddosing, the levels of nuclear FOXO3A were significantly sus-tained in mice treated with the combination compared withboth monotherapy treatments (Fig. 5B). This supports theconclusion that the combination achieves increased effectivepathway suppression at 6 hours.

Combination of AZD8186 and vistusertib reduces glucoseuptake

Inhibition of PI3K-AKT signaling reduces cellular glucoseuptake. In PTEN-null tumors, AZD8186 treatment reduced glu-cose uptake (38, 39) and hence increased reduction of glucoseuptake would also serve as an in vivo biomarker of increasedpathway suppression. The PTEN-null renal tumor xenograft 786-0is also 18F-FDG avid, with uptake modulated by AZD8186 (39).Animals bearing 786-0 tumorwere imaged to determine the effectof the combination on 18F-FDG uptake. Pathway biomarkerchanges were similar to those observed in the HCC70 and PC3tumors (Fig. 2). 18F-FDG uptake was reduced by AZD8186 andvistusertib, and further reduced in combination. AZD8186 gavea 25.6% reduction in 18F-FDG uptake, (P < 0.05), vistusertib a23.1% reduction (P < 0.05), and the combination resulted a37.5% decrease (P < 0.001) in MaxSUV uptake at 2 hours(Fig. 6A). The 18F-FDG biodistribution in both blood and tumor

2 h 6 h 2 h 6 h 2 h 6 h 2 h 6 h0

20

40

60

80

100

1 +

2 +

3 +

0

Control AZD8186 Vistusertib AZD8186/vistusertib

% F

OXO

3A N

ucle

ar p

ositi

ve

% F

OXO

3A N

ucle

ar p

ositi

ve

Control

AZD8186

Vistuse

rtib

AZD8186

/vistu

serti

b0

20

40

60

80

1002 h

6 h

**

**

A

B C

Control 2 h AZD8186 2 h Vistuser�b 2 h AZD8186/vistuser�b 2 h

Control 6 h AZD8186 6 h Vistuser�b 6 h AZD8186/vistuser�b 6 h

Figure 5.

Enhanced FOXO3A nuclear translocation following AZD8186/vistusertib combination treatment. AZD8186 was administered as a single dose(100 mg/kg) to nude mice bearing established HCC70 tumors. FFPE tumor tissues were prepared 2 and 6 hours following treatment with vehicle(control), AZD8186, vistusertib or the combination. A, Representative images show cytoplasmic to nuclear translocation of FOXO3A. B andC, Graphs for FOXO3A represent mean % change in nuclear FOXO3A positivity evaluated by a pathologist. Graphical results are displayed asmean � SEM (� , P < 0.05, Mann–Whitney U test).






showed no significant change in systemic glucose levels with anytreatment; however, AZD8186 gave a 26.3% reduction in 18F-FDGuptake (P < 0.05), vistusertib a 25.5% reduction (P < 0.05), andthe combination a 42.8% decrease (P < 0.001) inMaxSUV uptakeat 2 hours (Fig. 6B). Dynamic compartment analysis confirmedthe changes in intracellular 18F-FDG. 18F-FDG uptake into theinterstitial space across the time course of the 90-minute PET scandid not change, but by the end of the PET scanning procedure,there was significantly less 18F-FDG trapped in the intracellularspace in the combination treated group compared with vehicle(Fig. 6C). Similar effects on 18F-FDG uptake were observed inHCC70 tumors. A single dose of AZD8186 showed a 29.2%decrease (P¼ 0.0004) inMaxSUV uptake 2 hours after treatment,

while combination treatment gave a 42.7%decrease (P<0.00001;Supplementary Fig. S4A). Biodistribution analysis revealed a36.4% decrease in 18F-FDG uptake (%ID/g) with AZD8186 anda 43.5% decrease in the combination. (Supplementary Fig. S4B).There were no significant changes seen in the blood. In U87-MGtumor xenografts, the combination also gave a 40.1% decrease(P < 0.001) in MaxSUV (Supplementary Fig. S5A). In parallelanalyses (previously published in ref. 39), administration ofAZD8186 alone resulted in a 26% reduction in 18F-FDG in thismodel (39). Biodistribution data also showed a 50.9% decreasein 18F-FDG uptake (%ID/g) with the combination treatment(Supplementary Fig. S5B). Interestingly, the combination gavesignificant changes in the vascular delivery of 18F-FDG uptake in

Figure 6.

AZD8186 shows a significant and additive reduction in 18F-FDG uptake when dosed in combination with vistusertib. The overall reduction in 18F-FDG uptakeis as a result of changes in the phosphorylation capability of 18F-FDGas evidenced in the dynamic compartment analysis.A, Tumor 18F-FDGuptake in the 786-0modelfollowing AZD8186 alone, vistusertib alone, and AZD8186 and vistusertib in combination (mean � SEM). B, Biodistribution Tumor and blood 18F-FDG uptakefollowing AZD8186 alone, vistusertib alone, and AZD8186 and vistusertib in combination (mean � SEM). C, Delivery of 18F-FDG into the interstitial spaceand 18F-FDG trapped in the intracellular space following AZD8186 þ vistusertib dosing (mean � SEM) in the 786-0 model.

Lynch et al.





tumors at early time points; however, there was no significantchange in the interstitial space at later time points suggesting anearly vascular effect of the combination. Combination treatmentresulted in a significant decrease in the 18F-FDG that was trappedin the intracellular space (Supplementary Fig. S5C). Collectively,these data confirm that the combination of AZD8186and AZD2014 can give increased suppression of PI3K pathwayfunction in PTEN-null tumor cells.

DiscussionDurable inhibition of PTEN-null tumor cell proliferation

in vitrowas achievedby combined inhibition of PI3Kb andmTOR.Pathway biomarker analysis revealed that in sensitive cell lines thecombination maintained the suppression of both PI3K andmTOR signaling and prevented recovery of active pS6 and AKTeven after long-term exposure. The combination was equallyeffective in a range of in vivo tumor xenograft models. While itis challenging to show clear differential impact on pathwaybiomarkers in vivo, analysis ofmore proximal biomarkers revealedevidence of increased pathway suppression evidenced byincreased nuclear translocation of FOXO3A in HCC70 tumorxenografts and suppression of glucose uptake in 786-0 andU87MG. Collectively, the in vitro and in vivo data are consistentwith combined inhibition of PI3Kb and mTOR giving greaterpathway suppression. In vitro pathway recovery was observed thatwas absent in the combination; however, in vivo it is not possibleto discriminate whether the increased biomarker modulation issimply additive increased pathway inhibition or prevention ofreactivation. Independent of the mechanism, the combinationwas consistently more effective in multiple in vivo models.

The concept that failure to achieve sufficient inhibition of PI3Ksignaling or reactivation of signaling may limit efficacy of PI3Kinhibitors is well established. This can occur through acute feed-back reactivation or through acquired resistance. Inhibition ofPI3Ka in PI3Ka-mutant tumors results in reactivation of PI3Kb(20, 40), while inhibition of PI3Kb with AZD8186 results inpathway reactivation through activation of PI3Ka (19). Thisfeedback resulting in reactivation of AKT and phosphorylationof S6 kinase occurs through downregulation of PTEN expressionor function following PI3Ka inhibition, or through receptortyrosine kinase activation in PTEN-null tumors. In addition,long-term exposure of PI3Ka-mutant tumors to PI3Ka inhibitorscan result in loss of PTEN and activation of PI3Kb (39).Combining AZD8186 with an EGFR inhibitor in the HCC70,MDA-MB-468, and HCC1954 resulted in increased growth sup-pression consistent with feedback through RTK activation. More-over, the inhibition of MEK and IGFR gave a modest increase ingrowth suppression in the HCC70 cells. Across the cell panel,there was a range of intrinsic sensitivity to each monotherapy;however, the combination of vistusertib and AZD8186 wasextremely effective even in the more resistant lines such as PC3and BT549, suggesting this combination had greater potential forbroad activity. Combining PI3K isoform inhibitors to achievemaximal pathway inhibition is therefore an attractive strategy tomaximize the clinical benefit in tumors with activated PI3Ksignaling. While it is possible to monitor pathway dynamics invitro, it is more challenging to demonstrate whether acute feed-back is occurringwhen tumors are treated in vivo. This is because inthese experiments, both AZD8186 and AZD2014 compoundlevels in the blood vary over time as they are cleared from the

system. Therefore, biomarker recovery will be influenced by boththe exposure of the compound and any pathway reactivation thatis occurring. Independent of the mechanism of pathway reacti-vation, the combination treatment does appear more effective atsuppressing signaling.

The combined inhibition of PI3Kb and mTOR was effectiveacross a broad range of tumor xenograft and explant modelsconfirming the value of targeting these points in the PI3K path-way. The degree of antitumor activity did, however, vary across themodels reflecting that PTEN-null tumors vary in sensitivity toinhibition of the PI3K pathway. Modeling of the biomarkerchanges and pharmacokinetics suggest that this dosing strategymay not achieve full pathway inhibition over a 24-hour dosingperiod. When tumors are treated with vistusertib, inhibition ofpS6 and p4EBP1 is achieved over a 24-hour period, whereas it hasonly transient effects on the activation of AKT and downstreambiomarkers. The combination with AZD8186 in these tumorsdelivers the suppression of theAKT signaling axis. AZD8186 is lesseffective at suppressing pS6 activation. Hence, both compoundstarget complementary nodes in this pivotal signaling axis. Therewas variability in the response of the tumors tested to the com-bination therapy ranging from growth inhibition through totumor stasis and regression. It will be important to explore thisin more detail to gain insight into the degree of differentialdependency of tumors on mTORC1 and PI3K arms of the path-way, whether this is the sole driver of tumor growth inhibition, orwhether other pathways limit efficacy.

Signaling through the broader PI3K pathway is complex withmultiple points of regulation, and integration with other net-works. There are different downstream effects associated withPI3K inhibition. Recently, PI3K has been shown to control theglycolytic phenotype of tumor cells through the regulation ofAldolase (41). Inhibition of PI3K reduces nucleotide levels reg-ulate nucleotide levels in cells (26, 42). Finally PI3K and AKTinhibition can reduce lipid and cholesterol pathway activity (26,43, 44), whilemTORC2 signaling promoted development of livercancer through regulation of lipid synthesis (45). Through coor-dinated targeting of FOXO, GSK3, and TSC2/mTORC1 function,there are significant impacts on pathway critical for tumor cellfunction (46). A tolerated combination that achieves optimalpathway inhibition over a threshold of inhibition is therefore anattractive approach. Targeting mTOR and PI3Kb is well-toleratedpreclinically andwould not be predicted to introduce overlappingtoxicities, in contrast to combinations that may target PI3Ksignaling. This combination is not only active in PTEN-nulltumors. Interestingly the combination of vistusertib andAZD8186 also delivers positive benefit in a kras p53-mutantgenetic model of pancreatic cancer (KPC model; ref. 47). Thissuggests that the combination concept may be important beyondPTEN-null tumors.

Activation of both translation-dependent effects and anabolicmetabolism as well as cell survival and proliferation pathways isimportant for all cells. In the PTEN-null cells, inhibition of PI3Kbreduces cholesterol biosynthesis enzymes, nucleotide levels, andinduces cell stress (26). However, the balance of pathway depen-dencymay vary between genotypes, and even between individualcells of a similar genotype. Targeting mTORC1, mTORC2, andPI3Kb tackles this diversity. We hypothesize that the combinationtreatment results in more comprehensive pathway modulationachieving a threshold of pathway suppression which the cell isunable to resist. Specific biomarker changes observed support






this. The combination of AZD8186 and vistusertib markedlyreduced 4EBP1, and pNDRG1 in addition to the classicalbiomarkers of PI3K–AKT signaling. Moreover, in vivo, there isevidence of sustained FOXO3A nuclear translocation and alsoreduced glucose uptake. Interestingly, combined inhibition ofrapamycin and BKM120 also resulted in increased antitumorbenefit in a PTEN-null Her-2–positive brain metastasis model,and was superior to combined PI3K MEK inhibition (48), and iscurrently being tested clinically (NCT01470209).

In conclusion, AZD8186 and vistusertib can be combined todeliver comprehensive suppression of the PI3K/AKT/mTORpathway resulting in activity across a broad range PTEN-nulltumor cell models. The combination is current being exploredin clinical trials.

Disclosure of Potential Conflicts of InterestAll authors are current or former AstraZeneca employees and shareholders.

No other potential conflicts of interest were disclosed.

Authors' ContributionsConception and design: J.T. Lynch, U.M. Polanska, U. Hancox, O. Delpuech,J. Maynard, C. Lenaghan, S.E. Critchlow, F. Cruzalegui, S.T. BarryDevelopment of methodology: J.T. Lynch, U.M. Polanska, O. Delpuech,J. Maynard, C.B. Trigwell, C. Eberlein, C. Lenaghan, A. Avivar-Valderas,M. Cumberbatch

Acquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): J.T. Lynch, U.M. Polanska, O. Delpuech, J. Maynard,C. Eberlein, R. Polanski, M. CumberbatchAnalysis and interpretation of data (e.g., statistical analysis, biostatis-tics, computational analysis): J.T. Lynch, U.M. Polanska, U. Hancox,O. Delpuech, J. Maynard, C.B. Trigwell, C. Eberlein, A. Avivar-Valderas,F. CruzaleguiWriting, review, and/or revision of themanuscript: J.T. Lynch, U.M. Polanska,U. Hancox, O. Delpuech, J. Maynard, R. Polanski, T. Klinowska, S.T. BarryAdministrative, technical, or material support (i.e., reporting or organizingdata, constructing databases): J.T. Lynch, U.M. Polanska, U. HancoxStudy supervision: J.T. Lynch, U. Hancox, S.T. BarryOther (extensively discussed data with corresponding author as member ofproject team): F. Cruzalegui

AcknowledgmentsWewould like to thank the Alderley Park and the IMEDOncology Bioscience

In Vivo group and the Laboratory Animal Science team for support.

The costs of publication of this article were defrayed in part by thepayment of page charges. This article must therefore be hereby markedadvertisement in accordance with 18 U.S.C. Section 1734 solely to indicatethis fact.

Received February 14, 2018; revised June 12, 2018; accepted August 2, 2018;published first August 10, 2018.

References1. Marty B, Maire V, Gravier E, Rigaill G, Vincent-Salomon A, Kappler M, et al.

Frequent PTEN genomic alterations and activated phosphatidylinositol3-kinase pathway in basal-like breast cancer cells. Breast Cancer Res2008;10:R101.

2. Ni J, Liu Q, Xie S, Carlson C, Von T, Vogel K, et al. Functional character-ization of an isoform-selective inhibitor of PI3K-p110b as a potentialanticancer agent. Cancer Discov 2012;2:425–33.

3. Reid AHM, Attard G, Ambroisine L, Fisher G, Kovacs G, Brewer D, et al.Molecular characterisation of ERG, ETV1 and PTEN gene loci identifiespatients at low and high risk of death from prostate cancer. Br J Cancer2010;102:678–84.

4. Taylor BS, Schultz N, Hieronymus H, Gopalan A, Xiao Y, Carver BS, et al.Integrative genomic profiling of human prostate cancer. Cancer Cell2010;18:11–22.

5. Vanhaesebroeck B, Stephens L, Hawkins P. PI3K signalling: the pathto discovery and understanding. Nat Rev Mol Cell Biol 2012;13:195–203.

6. George S, Miao D, Demetri GD, Adeegbe D, Rodig SJ, Shukla S, et al.Loss of PTEN is associated with resistance to anti-PD-1 checkpointblockade therapy in metastatic uterine leiomyosarcoma. Immunity2017;46:197–204.

7. Peng W, Chen JQ, Liu C, Malu S, Creasy C, Tetzlaff MT, et al. Loss of PTENpromotes resistance to T cell-mediated immunotherapy. Cancer Discov2016;6:202–16.

8. Cully M, You H, Levine AJ, Mak TW. Beyond PTEN mutations: the PI3Kpathway as an integrator of multiple inputs during tumorigenesis. Nat RevCancer 2006;6:184–92.

9. Wee S, Wiederschain D, Maira S-M, Loo A, Miller C, deBeaumont R, et al.PTEN-deficient cancers depend on PIK3CB. Proc Natl Acad Sci U S A2008;105:13057–62.

10. HollanderMC,BlumenthalGM,Dennis PA. PTEN loss in the continuumofcommon cancers, rare syndromes and mouse models. Nat Rev Cancer2011;11:289–301.

11. Malek M, Kielkowska A, Chessa T, Anderson KE, Barneda D, Pir P, et al.PTEN regulates PI(3,4)P2 signaling downstream of class I PI3K. Mol Cell2017;68:566–80.

12. Fritsch R, de Krijger I, Fritsch K, George R, Reason B, Kumar MS, et al.RAS and RHO families of GTPases directly regulate distinct phosphoinosi-tide 3-kinase isoforms. Cell 2013;153:1050–63.

13. Nakanishi Y,Walter K, Spoerke JM,O'BrienC,HuwLY,HamptonGM, et al.Activating mutations in PIK3CB confer resistance to PI3K inhibition anddefine a novel oncogenic role for p110b. Cancer Res 2016;76:1193–203.

14. Pazarentzos E, Giannikopoulos P, Hrustanovic G, St John J, Olivas VR,Gubens MA, et al. Oncogenic activation of the PI3-kinase p110[beta]isoform via the tumor-derived PIK3C[beta]D1067V kinase domain muta-tion. Oncogene 2016;35:1198–205.

15. Barlaam B, Cosulich S, Degorce S, Fitzek M, Green S, Hancox U, et al.Discovery of (R)-8-(1-(3,5-Difluorophenylamino)ethyl)-N,N-dimethyl-2-morpholino-4-oxo-4H-chromene-6-carboxamide (AZD8186): a potentand selective inhibitor of PI3Kb and PI3Kd for the treatment of PTEN-deficient cancers. J Med Chem 2015;58:943–62.

16. Bonnevaux H, Lemaitre O, Vincent L, Levit MN, Windenberger F, Halley F,et al. Concomitant inhibition of PI3Kbeta and BRAF or MEK in PTEN-deficient/BRAF-mutant melanoma treatment: preclinical assessment ofSAR260301 oral PI3Kbeta-selective inhibitor. Mol Cancer Ther 2016;15:1460–71.

17. Certal V, Carry J-C, Halley F, Virone-Oddos A, Thompson F, Filoche-Romm�e B, et al. Discovery and optimization of pyrimidone indolineamide PI3Kb inhibitors for the treatment of phosphatase and tensinhomologue (PTEN)-deficient cancers. J Med Chem 2014;57:903–20.

18. Hancox U, Cosulich S, Hanson L, Trigwell C, Lenaghan C, Ellston R, et al.Inhibition of PI3Kb signaling with AZD8186 inhibits growth of PTEN-deficient breast and prostate tumors alone and in combination withdocetaxel. Mol Cancer Ther 2015;14:48–58.

19. Schwartz S,Wongvipat J, Trigwell Cath B,HancoxU, Carver Brett S, Rodrik-Outmezguine V, et al. Feedback suppression of PI3Ka signaling in PTEN-mutated tumors is relieved by selective inhibition of PI3Kb. Cancer Cell2015;27:109–22.

20. Costa C, Ebi H, Martini M, Beausoleil SA, Faber AC, Jakubik CT, et al.Measurement of PIP3 levels reveals an unexpected role for p110b in earlyadaptive responses to p110a-specific inhibitors in luminal breast cancer.Cancer Cell 2015;27:97–108.

21. Serra V, Scaltriti M, Prudkin L, Eichhorn PJ, Ibrahim YH, Chandarlapaty S,et al. PI3K inhibition results in enhanced HER signaling and acquired ERKdependency in HER2-overexpressing breast cancer. Oncogene 2011;30:2547–57.

22. Chandarlapaty S, Sawai A, Scaltriti M, Rodrik-Outmezguine V, Grbovic-Huezo O, Serra V, et al. AKT inhibition relieves feedback suppression of

Lynch et al.





receptor tyrosine kinase expression and activity. Cancer Cell 2011;19:58–71.

23. Muranen T, Selfors LM,Worster DT, Iwanicki MP, Song L,Morales FC, et al.Inhibition of PI3K/mTOR leads to adaptive resistance in matrix-attachedcancer cells. Cancer Cell 2012;21:227–39.

24. Garrett JT, Sutton CR, Kurupi R, Bialucha CU, Ettenberg SA, Collins SD,et al. Combination of antibody that inhibits ligand-independent HER3dimerization and a p110alpha inhibitor potently blocks PI3K signalingand growth of HER2þ breast cancers. Cancer Res 2013;73:6013–23.

25. She QB, Solit DB, Ye Q, O'Reilly KE, Lobo J, Rosen N. The BAD proteinintegrates survival signaling byEGFR/MAPKandPI3K/Akt kinase pathwaysin PTEN-deficient tumor cells. Cancer Cell 2005;8:287–97.

26. Lynch JT, Polanska UM, Delpuech O, Hancox U, Trinidad AG, Michopou-los F, et al. Inhibiting PI3Kbeta with AZD8186 regulates key metabolicpathways in PTEN-null tumors. Clin Cancer Res 2017;23:7584–95.

27. Bao Q, Newport D, Chen M, Stout DB, Chatziioannou AF. Performanceevaluationof the inveondedicated PETpreclinical tomographbased on theNEMA NU-4 standards. J Nucl Med 2009;50:401–8.

28. Gambhir A, Hangyas-Mihalyne G, Zaitseva I, Cafiso DS,Wang J, Murray D,et al. Electrostatic sequestration of PIP2 on phospholipid membranes bybasic/aromatic regions of proteins. Biophys J 2004;86:2188–207.

29. Guichard SM, Curwen J, Bihani T, D'Cruz CM, Yates JW, GrondineM, et al.AZD2014, an inhibitor of mTORC1 and mTORC2, is highly effective inERþ breast cancer when administered using intermittent or continuousschedules. Mol Cancer Ther 2015;14:2508–18.

30. Hudson K, Hancox U, Trigwell C, McEwen R, Polanska U, Nikolaou M,et al. Intermittent high dose scheduling of AZD8835, a novel selectiveinhibitor of PI3Ka and PI3Kd, demonstrates treatment strategies forPIK3CA-dependent breast cancers. Mol Cancer Ther 2016;15:877–89.

31. Davies BR, Greenwood H, Dudley P, Crafter C, Yu D-H, Zhang J, et al.Preclinical pharmacology of AZD5363, an inhibitor of AKT: pharmaco-dynamics, antitumor activity, and correlationofmonotherapy activitywithgenetic background. Mol Cancer Ther 2012;11:873–87.

32. CrossDA, Ashton SE,Ghiorghiu S, EberleinC,NebhanCA, Spitzler PJ, et al.AZD9291, an irreversible EGFR TKI, overcomes T790M-mediated resis-tance to EGFR inhibitors in lung cancer. Cancer Discov 2014;4:1046–61.

33. Davies BR, Logie A, McKay JS, Martin P, Steele S, Jenkins R, et al. AZD6244(ARRY-142886), a potent inhibitor of mitogen-activated protein kinase/extracellular signal-regulated kinase kinase 1/2 kinases: mechanism ofaction in vivo, pharmacokinetic/pharmacodynamic relationship, andpotential for combination in preclinical models. Mol Cancer Ther 2007;6:2209–19.

34. Yeh TC, Marsh V, Bernat BA, Ballard J, Colwell H, Evans RJ, et al. Biologicalcharacterization of ARRY-142886 (AZD6244), a potent, highly selectivemitogen-activated protein kinase kinase 1/2 inhibitor. Clin Cancer Res2007;13:1576–83.

35. Wittman M, Carboni J, Attar R, Balasubramanian B, Balimane P, Brassil P,et al. Discovery of a (1H-benzoimidazol-2-yl)-1H-pyridin-2-one (BMS-536924) inhibitor of insulin-like growth factor I receptor kinase with invivo antitumor activity. J Med Chem 2005;48:5639–43.

36. Lynch JT, McEwen R, Crafter C, McDermott U, Garnett MJ, Barry ST, et al.Identification of differential PI3K pathway target dependencies in T-cellacute lymphoblastic leukemia through a large cancer cell panel screen.Oncotarget 2016;7:22128–39.

37. Stitt TN, Drujan D, Clarke BA, Panaro F, Timofeyva Y, Kline WO, et al. TheIGF-1/PI3K/Akt pathway prevents expression of muscle atrophy-inducedubiquitin ligases by inhibiting FOXO transcription factors. Mol Cell2004;14:395–403.

38. Altomare DA, Testa JR. Perturbations of the AKT signaling pathway inhuman cancer. Oncogene 2005;24:7455–64.

39. Maynard J, Emmas S-A, Bl�e F-X, Barjat H, Lawrie E, HancoxU, et al. The useof 18F-fluorodeoxyglucose positron emission tomography (18F-FDGPET)as a pathway-specific biomarker with AZD8186, a PI3Kb/d inhibitor.EJNMMI Res 2016;6:62.

40. Juric D, Castel P, GriffithM,GriffithOL,WonHH, Ellis H, et al. Convergentloss of PTEN leads to clinical resistance to a PI(3)Kalpha inhibitor. Nature2015;518:240–4.

41. HuH, Juvekar A, Lyssiotis Costas A, Lien EvanC, Albeck JohnG,OhD, et al.Phosphoinositide 3-kinase regulates glycolysis through mobilization ofaldolase from the actin cytoskeleton. Cell 2016;164:433–46.

42. Juvekar A, Hu H, Yadegarynia S, Lyssiotis CA, Ullas S, Lien EC, et al.Phosphoinositide 3-kinase inhibitors induce DNA damage through nucle-oside depletion. Proc Natl Acad Sci U S A 2016;113:E4338–47.

43. King MA, Ganley IG, Flemington V. Inhibition of cholesterol metabolismunderlies synergy between mTOR pathway inhibition and chloroquine inbladder cancer cells. Oncogene 2016;35:4518–28.

44. Yue S, Li J, Lee S-Y, Lee Hyeon J, Shao T, Song B, et al. Cholesterylester accumulation induced by PTEN loss and PI3K/AKT activationunderlies human prostate cancer aggressiveness. Cell Metab 2014;19:393–406.

45. Guri Y, Colombi M, Dazert E, Hindupur SK, Roszik J, Moes S, et al.mTORC2promotes tumorigenesis via lipid synthesis. Cancer Cell 2017;32:807–23.

46. Manning BD, Toker A. AKT/PKB signaling: navigating the network. Cell2017;169:381–405.

47. Driscoll DR, Karim SA, Sano M, Gay DM, Jacob W, Yu J, et al. mTORC2signaling drives the development and progression of pancreatic cancer.Cancer Res 2016;76:6911–23.

48. Ni J, Ramkissoon SH, Xie S, Goel S, Stover DG, Guo H, et al. Combinationinhibition of PI3K andmTORC1 yields durable remissions inmice bearingorthotopic patient-derived xenografts of HER2-positive breast cancer brainmetastases. Nat Med 2016;22:723–6.






2018;17:2309-2319. Published OnlineFirst August 10, 2018.Mol Cancer Ther James T. Lynch, Urszula M. Polanska, Ursula Hancox, et al. PTEN-null Tumors

and mTOR Inhibits Growth ofβCombined Inhibition of PI3K

Updated version

10.1158/1535-7163.MCT-18-0183doi:

Access the most recent version of this article at:

Material

Supplementary

http://mct.aacrjournals.org/content/suppl/2018/08/10/1535-7163.MCT-18-0183.DC1

Access the most recent supplemental material at:

Cited articles

http://mct.aacrjournals.org/content/17/11/2309.full#ref-list-1

This article cites 48 articles, 17 of which you can access for free at:

Citing articles

http://mct.aacrjournals.org/content/17/11/2309.full#related-urls

This article has been cited by 1 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://mct.aacrjournals.org/content/17/11/2309To request permission to re-use all or part of this article, use this link



http://mct.aacrjournals.org/lookup/doi/10.1158/1535-7163.MCT-18-0183

http://mct.aacrjournals.org/content/suppl/2018/08/10/1535-7163.MCT-18-0183.DC1

http://mct.aacrjournals.org/content/17/11/2309.full#ref-list-1

http://mct.aacrjournals.org/content/17/11/2309.full#related-urls

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

mailto:[email protected]

http://mct.aacrjournals.org/content/17/11/2309


Documents

Combined Inhibition of PI3Kb and mTOR Inhibits Growth of ... · Small Molecule Therapeutics Combined Inhibition of PI3Kb and mTOR Inhibits Growth of PTEN-null Tumors James T. Lynch1,