Oxidative Stress Downstream of Mtorc1 but Not AKT Causes a Proliferative Defect in Cancer Cells Resistant to PI3K Inhibition

OPEN Oncogene (2017) 36, 2762–2774 www.nature.com/onc

ORIGINAL ARTICLE Oxidative stress downstream of mTORC1 but not AKT causes a proliferative defect in cancer cells resistant to PI3K inhibition

M Dermit1, P Casado1, V Rajeeve1, EH Wilkes1, DE Foxler2, H Campbell3, S Critchlow3, TV Sharp2, JG Gribben4, R Unwin5 and PR Cutillas1

Compounds targeting phosphatidylinositol-3-kinase/mammalian target of rapamycin (PI3K/mTOR) signaling are being investigated in multiple clinical settings, but drug resistance may reduce their beneﬁt. Compound rechallenge after drug holidays can overcome such resistance, yet little is known about the impact of drug holidays on cell biochemistry. We found that PI3K inhibitor (PI3Ki)- resistant cells cultured in the absence of PI3Ki developed a proliferative defect, increased oxygen consumption and accumulated reactive oxygen species (ROS), leading to lactate production through hypoxia-inducible factor-1α. This metabolic imbalance was reversed by mammalian target of rapamycin complex 1 (mTORC1) inhibitors. Interestingly, neither AKT nor c-MYC was involved in mediating the metabolic phenotype, despite the latter contributing to resistant cells’ proliferation. These data suggest that an AKT- independent PI3K/mTORC1 axis operates in these cells. The excessive ROS hampered cell division, and the metabolic phenotype made resistant cells more sensitive to hydrogen peroxide and nutrient starvation. Thus, the proliferative defect of PI3Ki-resistant cells during drug holidays is caused by defective metabolic adaptation to chronic PI3K/mTOR pathway inhibition. This metabolic imbalance may open the therapeutic window for challenge with metabolic drugs during drug holidays.

Oncogene (2017) 36, 2762–2774; doi:10.1038/onc.2016.435; published online 19 December 2016

INTRODUCTION such as RAF/MEK/ERK11 and EGFR/PKC (epidermal growth factor 12 Phosphatidylinositol-3-kinase/AKT/mammalian target of rapamy- receptor/protein kinase C) signaling axes. cin (PI3K/AKT/mTOR) signaling has key roles in the regulation of Here, we aimed to understand the adaptations that occur in cell growth, survival, motility and bioenergetic metabolism, and it cells with acquired resistance to PI3K/mTOR inhibitors and the is one of the most frequently mutated pathways in cancer.1 impact of drug holidays on cell biochemistry. We found that Consequently, small-molecule inhibitors targeting the PI3K path- resistant cells adapted their metabolic homeostasis to compen- way are being developed at a rapid pace, and both preclinical and sate for chronic PI3K pathway inhibition and underwent profound early clinical studies are beginning to suggest strategies for their metabolic changes after drug deprivation (that is, in drug holidays effective therapeutic use.2 Experience with other successful conditions). Interestingly, these alterations included an increase of glycolytic activity that in other systems is known to promote cell targeted agents, however, suggests that resistance is likely to 13 reduce the durability of any clinical benefit.3,4 proliferation. The accumulation of reactive oxygen species (ROS), The drug holiday strategy (drug removal followed by rechal- however, not only prevented resistant cells from recovering the lenge) has been successfully used to overcome resistance in division rate of parental cells but was also detrimental to their melanoma, chronic myeloid leukemia and lung cancer cells proliferation. We found that ROS were produced in a mammalian treated with the kinase inhibitors vemurafenib, imatinib and target of rapamycin complex 1 (mTORC1)-dependent, but erlotinib, respectively.5–7 In a heterogeneous tumor environment, AKT-independent, manner and mediated glycolytic activity via resistant cells develop a proliferative disadvantage during hypoxia-inducible factor (HIF), but not c-MYC. Our results suggest drug removal, resulting in their replacement by sensitive cells. that a metabolic imbalance is not only a hallmark of cancer, but it The proliferative disadvantage suffered by resistant cells in the also causes resistant cancer cells on drug holidays to acquire a absence of drug is considered as a key event for the success of this proliferative defect that could be enhanced with additional strategy.6 The molecular mechanisms that give rise to this deficit oxidative challenge. in proliferation are poorly understood, and a better knowledge could be used to develop strategies to improve the response of RESULTS patients treated with signaling inhibitors. The overactivation of the c-Myc oncogene has been identified Cells with chronic inhibition of PI3K develop a proliferative defect as a mechanism of acquired resistance to PI3K inhibition in several and a hypermetabolic phenotype during drug holidays preclinical studies.8–10 Resistance to inhibitors of the PI3K/AKT/ To investigate the biochemical adaptations that occur in cells with mTOR axis may also arise by the activation of parallel pathways, acquired resistance to PI3K inhibition, we used three independent

1Cell Signalling & Proteomics, Centre for Haemato-Oncology, Barts Cancer Institute, Queen Mary University of London, London, UK; 2Centre for Molecular Oncology, Barts Cancer Institute, Queen Mary University of London, London, UK; 3AstraZeneca, Oncology iMED, Cheshire, UK; 4Cancer Immunology Group, Centre for Haemato-Oncology, Barts Cancer Institute, Queen Mary University of London, London, UK and 5UCL Centre for Nephrology, Royal Free Campus and Hospital, University College London, London, UK. Correspondence: Dr PR Cutillas, John Vane Science Centre, Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK. E-mail: [email protected] Received 27 June 2016; revised 10 October 2016; accepted 10 October 2016; published online 19 December 2016 Metabolic defects in PI3K inhibitor-resistant cells M Dermit et al 2763 cell lines (named G1, G2 and G3) derived from chronic treatment acidification as a function of treatment with inhibitors of the PI3K of the MCF7 cell line with the PI3K class IA-specific inhibitor cascade15–19 (Figure 2b). PI3Ki-resistant cells were crossresistant to GDC-0941 (PI3Ki, Figure 1a and Supplementary Figure S1a).14 AKT and mTORC1/2 inhibition (Figure 2c, top panels), indicating Resistant cells were able to proliferate—although at slower rate that these cells had developed the ability to survive in the absence than parental cells—in the presence of 1 μM of compound, of PI3K/AKT/mTOR pathway activity. whereas parental cells could not (Figure 1a and Supplementary The mTORC1/2 and mTORC1 inhibitors prevented media Figure S1a). Of note, none of the resistant cells recovered the acidification in all resistant cell lines (Figure 2c, bottom panels). proliferation rate of the parental cells upon drug withdrawal For example, G2 acidified the media to pH 7.2 (normal media pH is (Figure 1a). Interestingly, G1 and G2 grew even slower in the 8.0); the pH of cells treated with PI3Ki, mTORC1/2i or mTORC1i absence rather than in the presence of the drug (Figure 1a). These remained at pH of 7.8, 7.8 and 8.0, respectively (Figure 2c, bottom data suggest that PI3Ki-resistant cells have developed a prolif- panel). Surprisingly, we found that G2 cells treated with two erative defect that is manifested during drug holidays, with G1 different AKT inhibitors acidified the media to the same extent as and G2 even showing a potential addiction to the PI3Ki. untreated cells (pH 7.3 and 7.2). Similar results for pH values were Drug withdrawal caused a substantial acidification of the media observed for the G1 and G3 cell lines (Figure 2c, bottom panels). (that was greater in G2), suggesting a metabolic alteration Inhibition of SGK (serum- and glucocorticoid-inducible kinase) (Figure 1b). This difference in metabolic rate was associated with with GSK-650394 (ref.20) did not prevent the metabolic phenotype an increased redox activity after compound withdrawal (Figure 2c, bottom panels). Thus, SGK, a signaling mediator that (Figure 1c), and was a reversible process, as drug readministration can occasionally substitute AKT,21 did not replace AKT signaling in restored the initial phenotype (Supplementary Figure S1b). our model of drug resistance. To determine the enzymes involved in the metabolic phenotype, To investigate the relevance and extent of AKT-independent we measured the transcriptional expression of metabolic genes. This PI3K/mTOR signaling in our model, we compared the effects of analysis showed a different expression pattern of metabolic enzymes PI3Ki, mTORC1/2i and AKTi2 on the phosphoproteome of G2 cells between parental and resistant cells (Supplementary Figure S1c). (Figure 2d and Supplementary Figures S2b and c). PI3Ki and Mass spectrometry-based proteomics analysis showed that resistant mTORC1/2i inhibited the phosphorylation of 90 and 99 sites, cells increased the expression of lactate dehydrogenase A, fatty respectively, whereas AKTi2 only inhibited the phosphorylation of acid synthetase, isocitrate dehydrogenase 3A and thiorredoxin-like 24 sites (at Po0.05, log2 fold o − 1, n = 4, Figure 2d). Of note, protein that are involved in production of lactic acid, fatty acid PI3K and mTORC1/2 inhibitors, but not the AKTi2, reduced the metabolism, tricarboxylic acid cycle and electron transport chain, phosphorylation of the EIF4E-BP2 (Ser44/Thr45), a downstream respectively. On drug removal, resistant cells expressed proteins mTORC1 target (Figure 2e). In contrast, mTORC1/2, AKT and PI3K involved in the pentose phosphate pathway and gluconeogenesis, inhibitors blocked the phosphorylation of the AKT substrate including glucose-6-phosphate dehydrogenase and phosphoenol- PRAS40 (Thr246), as determined by liquid chromatography–mass pyruvate carboxykinase 2, respectively (Figure 1d). Immunoblotting spectrometry (Figure 2e). Western blot analysis also showed that analysis confirmed the expression changes of fatty acid synthetase PRAS40 (Thr246) phosphorylation was inhibited by AKTi. The and lactate dehydrogenase B (Figure 1d). mTORC1 inhibition with everolimus reduced the phosphorylation To characterize the metabolic alterations in more detail, we of 4E-BP1 (Thr37/46), whereas AKTi did not reduce the phosphor- measured mitochondrial (oxygen consumption rate (OCR)) and ylation at this site (Figure 2f). Together, these data demonstrate glycolytic (extracellular acidification rate (ECAR)) activities as well that an AKT-independent PI3K/mTORC1 signaling axis is functional as lactic acid levels in the media (Figure 1e). We found that drug in our cell model of drug resistance and that this pathway is removal produced an increase in both ECAR and lactic acid in all involved in the mediation of the metabolic phenotype. resistant cells (Figure 1e). OCR was also significantly increased upon drug removal in G1 and G2; however, in G3 this increase did c-MYC, CAMKII and MEK activities have a role in the viability of fi not reach statistical signi cance (Figure 1e). Taken together, these PI3Ki-resistant cells but are not responsible for the hypermetabolic results indicate that placing PI3Ki-resistant cells in drug holiday phenotype conditions induces a hypermetabolic phenotype characterized by To better understand signaling changes in resistant cells, we an increase in both glycolysis and mitochondrial respiration. analyzed the phosphoproteomes of parental and resistant cells in We observed that the development of the metabolic phenotype the presence or absence of PI3Ki (Supplementary Figure S3a). Of the was associated with an increase in cell size (Figure 1f), and with a 5674 phosphopeptides quantified in these experiments, 2166 were slow cell cycle progression from G /G to S phase (Supplementary 0 1 significantly altered (at Po0.05 and log fold o − 1or41) in at Figure S1d) without affecting apoptosis (Supplementary 2 least one condition. Unsupervised clustering (using a k-means Figure S1e). These data indicate that the drug holiday-induced algorithm) grouped phosphopeptides that significantly increased metabolic changes contributed to the production of cell biomass, (clusters 1–2) or decreased (4 and 6) in resistant compared with but instead of being used to proliferate, PI3Ki-resistant cells parental cells (Figure 3a and Supplementary Dataset S2). Substates diverted such biomass to increase size. for MEK and CAMKII were enriched in cluster 1, suggesting that these kinasesweremoreactiveinresistant relative to parental cells PI3Ki-resistant cells in drug holidays reactivate PI3K/mTORC1 (Figure 3a and Supplementary Figure S3b). To determine whether signaling that mediates the hypermetabolic phenotype MEK and/or CAMKII could mediate resistance to PI3K inhibition, we independently of AKT measured proliferation of resistant cells in the presence of trametinib Markers of mTORC2, AKT and mTORC1 activities (namely phosphor- (a MEK inhibitor)22 or KN-93 (a CAMKII inhibitor).23 As predicted, PI3Ki ylations at AKT Ser473, PRAS40 Thr246 and 4E-BP1 Thr37/46, potentiated the effects of trametinib and KN-93 in PI3Ki-resistant cells respectively) remained inhibited in resistant cells growing in the (Figure 3b). However, treatment with trametinib or KN-93 did not presence of PI3Ki (Figure 2a and Supplementary Figure S2a). On drug avoid the appearance of the metabolic phenotype (Supplementary holidays, phosphorylation on these markers dramatically increased Figure S3c). relative to the same cell line growing exposed to the PI3Ki, although Of interest, Figure 3c shows that resistant cells increased the the extent of such reactivation was different across G1, G2 and G3 phosphorylation of c-MYC at sites (Thr58/Ser62) known to promote cell lines (Figure 2a and Supplementary Figure S2a). c-MYC transcriptional activity.24 Gene expression and western blot To determine the components involved in the development of analysis suggested that this increase in phosphorylation may be the metabolic phenotype, we measured cell viability and media because of a higher expression of mRNA and protein levels

Oncogene (2017) 2762 – 2774 Metabolic defects in PI3K inhibitor-resistant cells M Dermit et al 2764

P G1 G1 G2 G3 6 P - PI3Ki P - PI3Ki P - PI3Ki P - PI3Ki P - PI3Ki G1 - PI3Ki G1 - PI3Ki G2 - PI3Ki G3 - PI3Ki 6 6 3 3 3 P + PI3Ki G1 + PI3Ki G1 + PI3Ki G2 + PI3Ki G3 + PI3Ki

4 4 2 2 ** 2 * ** ** *** ** 2 *** 2 1 1 1 ** ** * ** * * **

) ** 6 0 0 0 0 0 Redox activity (Abs 490 nm) 07140714 1235 1235 1235 G2 G3 Time (days) 6 P - PI3Ki P - PI3Ki -PI3Ki +PI3Ki -PI3Ki +PI3Ki G2 - PI3Ki G3 - PI3Ki KDa 6 6 P G1 G2 G3 G1 G2 G3 P G1 G2 G3 G1 G2 G3 Cell number (X10^ G2 + PI3Ki G3 + PI3Ki 250 - FASN

4 4 50 - LDHB

50 - α-tubulin 2 2 * *

* ** lactic acid production 0 0 fatty acid metabolism 07140714 TCA cycle Time (days) ETC PPP pathway gluconeogenesis -PI3Ki +PI3Ki P G1 G2 G3 G1 G2 G3 Significance (p –value) Fold over control (Log2, n=4) *<0.05 -1.5 -1 -0.5 0 0.5 1 1.5 **<0.01 ***<0.01

** *** *** *** * * 8 *** *** * *** ** 40 * 120 * 800 * 7.5 30 600 7 pH 20 60 400 6.5

6 10 200 Lactic acid (mM) ECAR (mpH/min)

P G1G2G3G1G2G3 OCR (pMoles/min) 0 0 0 -PI3Ki +PI3Ki P G1G2 G3 G1G2 G3 P G1G2 G3 G1G2 G3 P G1G2G3G1G2G3 -PI3Ki +PI3Ki -PI3Ki +PI3Ki -PI3Ki +PI3Ki

* 22 * P G1 G2 G3 )

µm 20 -PI3Ki

18 Cell size (

P G1G2G3G1G2G3 +PI3Ki -PI3Ki +PI3Ki Figure 1. PI3Ki-resistant cells in drug holidays develop a proliferative defect and a hypermetabolic phenotype. (a) Cell proliferation measured after 7 and 14 days of growing in the absence or presence of 1 μM GDC-0941 (PI3Ki). G1, G2, G3, PI3Ki-resistant MCF7 cells; P, parental MCF7 cells. (b) Images and pH values of media collected from cells at day 5. (c) Redox activity as determined by the MTS assay. (d) Expression of proteins involved in several metabolic processes. Western blot images of fatty acid synthetase (FASN) and lactate dehydrogenase B (LDHB; right image). (e) ECAR and OCR and media lactic acid measurements. (f) Representative images and diameter size of cells. Data are represented as mean ± s.d. (n ⩾ 3, independent biological replicates). P-values were calculated using an unpaired, two-tailed Student’s t-test comparing as indicated; *Po0.05; **Po0.01; ***Po0.001.

Oncogene (2017) 2762 – 2774 Metabolic defects in PI3K inhibitor-resistant cells M Dermit et al 2765

Name Drug Concentration -PI3Ki +PI3Ki KDa PI3Ki GDC-0941 1 µM P G1 G2 G3 G1 G2 G3 64 - p-AKT (Ser473) AKTi1 A-VII 1 µM

50 - p-PRAS40 (Thr246) AKTi2 MK-2206 1 µM mTORC1/2i KU-0063794 1 µM 16 - p-4E-BP1 (Thr37/46) mTORC1i everolimus 20 nM 50 - α-tubulin SGKi GSK 650394 0.5 µM

P G1 G2 G3 3 2 2 2 ) 6 2.5 1.5 1.5 1.5 2 * * *** 1.5 *** 1 1 * 1 *** 1 ** *** *** *** 0.5 0.5 0.5 0.5 *** *** Cell number (X10^ 0 0 0 0 8.5 8.5 8.5 8.5 pH ** *** ** ****** ** ***** *** ** ****** *** media 8 8 8 8

7.5 7.5 7.5 7.5 pH

7 7 7 7

6.5 6.5 6.5 6.5 SGKi PI3Ki SGKi SGKi SGKi PI3Ki PI3Ki PI3Ki AKTi1 AKTi2 AKTi1 AKTi1 AKTi1 AKTi2 AKTi2 AKTi2 Control Control Control Control mTORC1i mTORC1i mTORC1i mTORC1i mTORC1/2i mTORC1/2i mTORC1/2i mTORC1/2i

PI3Ki AKTi2 mTORC1/2i # P-peptides AKT downstream target mTORC1 downstream target (Fold<-1 90 24 99 p-PRAS40 p-EIF4E-BP2

-6.99605 -4.79755 -2.12682 246 44 45 -4.27479 -3.27975 -5 P<0.05) -3.01773 -2.84684 -5 -7.65705 -2.20216 -5 (Thr ) (Ser /Thr ) -3.94255 -2.07405 -4.22884 -7.92296 -1.38268 -8.39112 -4.11336 -1.18945 -5.2231 -3.71518 -0.98215 -3.97276 -5.15924 -0.97331 -7.36557 -4.7228 -0.8074 -6.68716 1.5 1.5 -4.15617 -0.70978 -7.50468 -3.44505 -0.68243 -4.86452 -3.4156 -0.69136 -5.32472

-3.05763 -0.66526 -3.74311 ) -2.74815 -0.62789 -3.7311 -2.59179 -0.22196 -6.4468

-2.51948 -0.49626 -2.96557 2 -2.48977 -0.37324 -1.70309 -1.76341 -0.30616 -3.95914 -2.02072 -0.56161 -3.07281 -1.75043 -0.51991 -2.97032 -2.13191 -0.83445 -2.60377 -1.6705 -0.083 -2.6033 -2.16719 -0.64352 -2.30696 -2.16719 -0.64352 -2.30696 -2.00176 -0.17211 -2.21832 -2.16719 -0.64352 -1.85212 -1.64831 -0.18699 -1.26337 -1.84965 -0.30444 -1.19505 -1.61098 -1.05143 -1.03237 -1.46962 -0.63216 -4.28441 -0.99758 -0.27072 -3.22014 -1.24476 -0.15518 -3.1707 -1.35879 -0.63193 -2.51237 -1.14421 -0.60346 -2.48431 -1.27375 -0.14424 -2.24298 1 1 -1.2665 -0.39761 -2.20963 -0.95397 -0.72664 -1.85441 -0.94159 -0.29233 -1.70032 -0.91149 -0.67425 -1.63818 -1.2086 -0.2313 -1.55848 -1.07886 -0.24089 -1.30991 -1.42409 -0.62578 -1.21779 -0.96796 -0.25136 -1.10934 -1.2258 -0.3891 -1.09283 -0.98504 -0.58473 -0.96972 -6.71341 -0.10352 -2.48909 -5 0.636377 -1.7577 -10.1358 -0.59286 -1.68512 -5 -0.33411 -1.3697 -5 -0.33555 -0.94951 -4.75764 -1.67865 -0.69696 -6.39604 -1.28413 -0.60848 -12.544 -0.1914 -0.56652 -5 0.160544 -0.55188 -5.5243 -0.54706 -0.38382 -5 -1.07368 -0.352 -7.31672 -0.12059 -0.30846 -5 -0.49363 -0.30069 -4.81175 0.035088 -0.02194 *** -5 -0.63592 0.075988 -5 -0.22695 0.089413 0.5 0.5 -6.24659 -1.42919 0.333374 -5 0.233126 0.614073 -5 -0.51063 1.209636 -5 1.361056 5.317881 -3.56198 -0.58884 -1.29134 -3.4446 0.643862 0.384704 -2.60779 -0.88873 -0.7727 -2.2978 -0.41365 -0.26493 -2.13718 -0.83036 -0.52479 -1.70049 -0.22144 -0.41974 *** -1.66155 -0.34919 -1.37407 -1.61527 0.564382 1.630012 -1.59929 -0.54587 -0.28949 -1.35692 -1.1127 -0.21373 -1.30088 -0.6551 -2.29191 -0.96056 -0.25447 -1.43062 *** -0.96932 -0.35212 -1.402

-1.19196 -0.70323 -0.93538 Fold Change (log -1.04241 -0.57094 -0.92816 -1.30129 -0.45649 -0.87569 -1.11279 0.097475 -0.72611 -1.24999 0.087336 -0.71371 -1.15812 -0.74256 -0.56221 *** -1.21363 -0.36175 -0.36425 *** -0.88242 -0.28812 -0.16037 -1.25658 0.10434 0.553193 0 0 -1.17663 0.452527 0.885228 -1.29461 0.529952 1.525996 -0.21172 -5 -5 -1.75716 -2.99899 -3.40633 -1.56692 -1.57922 -2.53215 -0.45418 -1.08566 -1.61013 -0.05896 -1.09227 -1.2273 -0.07368 -1.06731 -1.01033 -0.78027 -1.11828 -0.95398 -0.2945 -1.02405 -0.92251 Control PI3Ki AKTi2 mTORC1/2i Control PI3Ki AKTi2 mTORC1/2i -3.82919 -1.35898 -5 -3.44588 -2.06726 -5.58444 -2.76771 -0.15195 -6.18231 -1.91636 -1.59118 -4.3818 -1.84215 -0.3916 -4.88539 -1.58641 -0.11969 -5.50875 -0.6693 -0.42416 -6.23963 -0.40801 -1.74058 -4.54698 0.773459 -2.16359 -6.58484 2.010912 -1.95366 -5 -1.55677 -0.28978 -1.53588 -1.18398 -0.78794 -2.01845

Phosphopeptides -0.90647 -0.37118 -1.70809 -0.85073 -0.4884 -1.69767 -0.8414 -0.33498 -1.64289 -0.78857 -0.45466 -2.19945 -0.76628 -0.15147 -1.98992 -0.60507 -0.4293 -2.05606 -0.53997 -0.68934 -2.3309 -0.53089 -0.47349 -2.17641 -0.47018 -0.4293 -2.05606 -0.47018 -0.44517 -2.05606 -0.40252 -1.11578 -1.73871 0.375293 -0.06487 -1.87221 -0.20717 -0.21457 -1.53492 -1.44587 -0.459 -1.08035 AKTi2 -0.9637 -0.57062 -1.18433 Control Control mTORC1i -0.96277 -0.41071 -1.10163 -0.78438 -0.81288 -1.04722 -0.77887 -0.32062 -1.09436 -0.76652 -0.43702 -1.01856 -0.75071 -0.27214 -0.83861 -0.74673 -0.16015 -1.1531 -0.65629 -0.04971 -0.96739 -0.65451 -0.81753 -1.06865 KDa -0.64174 -0.31845 -1.07093 -0.62979 -0.22299 -1.10726 -0.58647 -0.39278 -1.06802 P G1 G2 G3 G1 G2 G3 P G1 G2 G3 G1 G2 G3 -0.57732 -0.70758 -1.20274 -0.54238 -0.22825 -1.05867 -0.5328 -0.68001 -1.0646 -0.53194 -0.26081 -1.23472 -0.46097 -0.58803 -1.18318 -0.24838 -0.07637 -1.2325 -0.24454 -0.28257 -1.12656 0.335403 -0.57108 -0.99626 -2.37226 -5 -3.60907 -3.00077 -5.8594 -0.58736 -0.21599 -2.69854 0.144705 37/46 -0.43748 -2.26757 -1.14613 -0.20116 -1.20738 -1.97222 -0.00692 -1.10106 -1.83334 p-4E-BP1 (Thr ) -0.34048 -1.00599 -1.38535 16 - -0.31052 -0.99843 -0.92503

Fold over control (log n=4) 246 2, 50 - p-PRAS40 (Thr ) -5 -4 -3 -2 -1 0 1 2 3 4 5 -5 -4 -3 -2 -1 0 1 2 3 4 5 50 - α-tubulin Figure 2. Drug withdrawal from PI3Ki-resistant cells causes an AKT-independent reactivation of mTORC1 that regulates a hypermetabolic phenotype. (a) Phosphorylation of PI3K/AKT/mTORC1 axis activity markers in cells. (b) Inhibitors used in experiments shown in (c). (c) Cell numbers and media pH values in cells as a function of treatment with the named inhibitors for 5 days. Data are represented as mean ± s.d. (n = 3, three independent biological replicates). (d) Phosphopeptides signiﬁcantly modulated in G2 cells treated for 1 h with the named inhibitors. (e) Detailed quantiﬁcation of PRAS40 and EIF4E-BP2 phosphopeptides. (f) Immunoblot images of the named phosphorylation sites as a function of treatment. P-values calculated using an unpaired, two-tailed Student’s t-test between treatment and control; *Po0.05; **Po0.01; ***Po0.001.

(Figure 3c and Supplementary Figure S1d). In addition, pathway c-MYC activity contributes to acquired resistance to PI3K inhibitors enrichment analysis against the NCI pathway database revealed in other models.8–10 We inhibited c-MYC using two different that proteins listed within the process ‘validated targets of c-MYC competitive inhibitors of the c-MYC/MAX interaction (10058-F4; transcriptional activation’ were increased in resistant relative to c-MYC inhibitor 1 (ref.25) and 10074-G5; c-MYC inhibitor 2 (ref.26)). parental cells (Figure 3d and Supplementary Dataset S1). We found that although in isolation PI3K and c-MYC inhibitors had

Oncogene (2017) 2762 – 2774 Metabolic defects in PI3K inhibitor-resistant cells M Dermit et al 2766 a modest effect on reducing cell proliferation of resistant cells, (Figure 3e). Surprisingly, inhibition of c-MYC did not prevent the concomitant inhibition of PI3K and c-MYC activity reduced cell ability of resistant cells to acidify the media (Figure 3f and number by approximately threefold relative to untreated cells Supplementary Figure S3c). Overall, our results indicate that

0.6 G1 0.6 G2 0.6 G3 P Kinase substrate enrichment - PI3Ki +PI3Ki (Cluster 1) 0.2 0.2 0.2 1 3 -0.2 -0.2 -0.2 * * CAMKII MEK -0.6 -0.6 * -0.6

2 ) substrates *** * substrates 10 ** *

(P) -1 *** -1 -1

10 2 p=0.01 *** -1.4 -1.4 * -1.4 -log 0 1 5 0 1 5 0 1 5 10 15 20 15 20 10 15 20 10 0.5 0.5 3 0.5 p=0.05 [MEKi] μM 1 0.6 G1 0.6 G2 0.6 G3 P

Phosphopeptides 1.0 2.0 3.0 4.0 - PI3Ki + PI3Ki 4 log2 fold enrichment 0.2 0.2 0.2

Relative cell number (log -0.2 -0.2 -0.2 Fold over control (log2, n=4) * * 5 -5 -4 -3 -2 -1 0 1 2 3 4 5 -0.6 -0.6 -0.6 6 * * -1 * -1 * -1 ** ** ** ** p-c-MYC (Thr58/Ser62) -1.4 ** -1.4 ** -1.4 0 5 0 5 0 5 10 50 50 50 10 6 10 100 150 200 100 150 200 *** 100 150 200 *** * *** [CAMKIIi] μM 4 1.5 P 1.5 G1 1.5 G2 1.5 G3 ** 2

Fold change ** * * * *** * *** * *** ** 1 1 1 ** 1 0 KDa 0.5 0.5 0.5 0.5 64 - c-MYC 50 - α-tubulin Relative cell number 0 0 0 0 P G1 G2 G3 G1 G2 G3 PI3Ki ---+++ ---+++ ---+++ ---+++ -PI3Ki +PI3Ki c-MYCi1 -+- -+- -+- -+- -+- -+- -+- -+- c-MYCi2 --+--+ --+--+ --+--+ --+--+

Pathway analysis P G1 G2 G3 (Cluster 2) 1 * ** *** *** ** ** *** ** 3 Targets of c-MYC 8 *** 8 8 8 2 transcriptional activation 2.5 HIF-1α transcription

(P) factor network 10 7 7 7 7 pH

3 -log 2 p=0.01 Proteins 1.5 6 6 6 6 1.0 1.5 2.0 PI3Ki --++ --++ --++ --++ 4 log2 fold enrichment c-MYCi -+-+ -+-+ -+-+ -+-+

Fold over control (log2, n=4) 5 -5 -4 -3 -2 -1 0 1 2 3 4 5 6

Figure 3. c-MYC, CAMKII and MEK contribute to the viability of PI3Ki-resistant cells but these proteins do not control the hypermetabolic phenotype. (a) K-means clustering of phosphopeptides signiﬁcantly modulated by chronic PI3Ki treatment. Right panel shows kinase substrate enrichment analysis (KSEA) of phosphopeptides increased in resistant cells (cluster 1). (b) Relative cell numbers as a function of trametinib or KN-93 treatment in the presence or in the absence of PI3Ki (n=3). (c) Phosphorylation of p-c-MYC (Thr58/Ser62) and protein levels of c-MYC. Phosphorylation data are represented as mean ± s.d. (d) K-means clustering of fold changes (log2) for proteins signiﬁcantly modulated by chronic PI3Ki treatment. Right panel shows pathway analysis of entries enriched in PI3Ki-resistant cells relative to parental (Cluster 2). (e) Relative cell numbers as a function of treatment with 1 μM PI3Ki with either 25 μM 10058-F4 (c-MYCi1) or 20 μM 10074-G5 (c-MYCi2) for 5 days. (f) Media pH from cells cultured for 5 days with DMSO control, PI3Ki c-MYCi or the combination. Unless indicated, data are represented as mean ± s.d. (n = 3). P-values calculated using an unpaired, two-tailed Student’s t-test comparing drug-resistant cells growing in the presence or absence of PI3Ki for (b), and as indicated for (c), (e) and (f); *Po0.05; **Po0.01; ***Po0.001.

Oncogene (2017) 2762 – 2774 Metabolic defects in PI3K inhibitor-resistant cells M Dermit et al 2767

** 50 ** -PI3Ki +PI3Ki *** KDa P G1 G2 G3 G1 G2 G3 40

110 - HIF-1α 30

20 50 - α-tubulin activity 10

Normalized luciferase 0 P G1 G2 G3 G1 G2 G3 -PI3Ki +PI3Ki

P G1 G2 G3 1.5 1.5 1.5 1.5 *** * 1 1 1 1

0.5 0.5 0.5 0.5

Relative cell number 0 0 0 0 *** *** *** ** *** *** *** *** 8 *** 8 *** 8 *** 8 ***

7 7 7 7 pH

6 6 6 6 PI3Ki --++ --++ --++ --++ HIFi -+-+ -+-+ -+-+ -+-+

P G1 G2 G3 1.5 1.5 1.5 1.5 * ** *** ** *** *** *** 1 1 1 1

0.5 0.5

Relative [LA] 0.5 0.5

0 0 0 0 PI3Ki --++ --++ --++ --++ HIFi -+-+ -+-+ -+-+ -+-+ Figure 4. HIF activity is responsible for lactic acid production in PI3Ki-resistant cells during drug holidays. (a) HIF-1α protein expression. (b) HIF1 transcriptional activity. Data are represented as mean ± s.d. (n = 3, three independent replicates). (c) Relative cell numbers and pH values from cell media cultured for 5 days with chetomin (HIFi), PI3Ki or the combination. (d) Media lactic acid concentration as a function of treatment for 5 days. For (c) and (d), data are represented as mean ± s.d. (n = 3, three independent biological replicates). P-values calculated using an unpaired, two-tailed Student’s t-test compared as indicated; *Po0.05; **Po0.01; ***Po0.001. although the activities of CAMKII, MEK and c-MYC help resistant resistant cells (Figure 3d). We therefore investigated HIF-1α cells to survive in a background of chronic PI3K/mTOR inhibition, protein expression and found that resistant cells growing in the these proteins do not regulate the metabolic phenotype in these absence of drug had greater HIF-1α protein than parental cells; models.27 this expression decreased dramatically in cells treated with PI3Ki (Figure 4a and Supplementary Figure S4a). Consistent with the immunoblot data (Figure 4a), HIF transcriptional activities were HIF activity regulates the glycolytic phenotype in PI3Ki-resistant between 3.3- and 13.6-fold greater in resistant cells grown in the cells absence of the PI3Ki than in its presence (Figure 4b). In addition to c-MYC, bioenergetic metabolic pathways are To assess the role of HIF in the development29 of the regulated by the transcription factor HIF.28 We found that the hypermetabolic phenotype, we inhibited their activities using process ‘HIF-1α transcription factor network’ was also enriched in chetomin, a disruptor of the HIF/p300 interaction.30 Chetomin

Oncogene (2017) 2762 – 2774 Metabolic defects in PI3K inhibitor-resistant cells M Dermit et al 2768 reduced media acidification to similar levels as when cells were require AKT, SGK, CAMK, MEK or c-MYC to generate ROS that treated with PI3Ki (Figure 4c and Supplementary Figure S4b), and controls HIF-1α to regulate the glycolytic phenotype. also reduced cell division rates of parental cells; however, G1 and fi G2 proliferation rates were not signi cantly affected by inhibition The high metabolic activity of resistant cells may be exploited to of HIF isoforms (Figure 4c). We observed that HIF inhibition caused potentiate the proliferative defect induced during drug holidays a significant decrease in lactic acid content in the media of We hypothesized that PI3Ki-resistant cells in drug holidays would parental and resistant cells (Figure 4d). Thus, an increase in HIF be more sensitive to an additional oxidative challenge.39,40 Thus, activities (involving at least HIF-1α), known to act downstream of 31 we used H2O2 to increase the oxidative stress in sensitive and different oncogenes, regulates the phenotype of our models of 41 resistant cells. Interestingly, H2O2 significantly reduced the PI3Ki-resistant cells. numbers of G1 and G2 cells in growing without PI3Ki to a greater extent than the same cells growing with PI3Ki (Figure 6a). ROS overproduction on drug removal activates HIF and causes a We then examined whether the elevated metabolic rate was defect on the proliferation of resistant cells that can be recovered functionally associated with higher nutrient demand. For this by antioxidants purpose, we measured the viability of cells cultured in glucose- A gene ontology analysis of our phosphoproteomics data showed and glutamine-free media, as these nutrients serve as primary that antioxidant activity (GO: 0016209) was significantly enriched sources of carbon for adenosine triphosphate production.42 The in resistant cells during drug holidays (Figure 5a). Antioxidant absence of PI3Ki made resistant cells more sensitive to glucose activity may be increased in these cells to counteract by-products and glutamine withdrawal than those cultured with PI3Ki, and the of metabolism such as ROS that are expected to increase as a extent of the sensitivity was proportional to the intensity of the result of high metabolic activity.32 To further investigate the glycolytic phenotype (Figures 6b and c). Resistant cells were also involvement of mitochondria in our model, we measured ROS, a more sensitive to glucose deprivation than parental cells natural end product of mitochondrial activity. Untreated G2 and (Figure 6b). Thereby, the hypermetabolic phenotype shown by G1 cells produced approximately twofold more ROS than the PI3Ki-resistant cells during drug holidays leads to an increased same cells treated with PI3Ki and parental cells (Figure 5b and dependency on nutrients and the higher ROS levels made cells Supplementary Figure S5a). PI3Ki-resistant cells increased ROS more susceptible to pro-oxidant treatment (Figure 6). production during drug holidays but, as noted above (Figure 1), these differed in their extent of metabolic dysregulation. The extent of metabolic imbalance determines the capacity of Because a high intracellular ROS concentration can be toxic,32,33 PI3Ki-resistant cells to proliferate we hypothesized that increased ROS levels contributed to the To elucidate whether bioenergetic remodeling occurs in other defective proliferation of resistant cells. We tested whether 34–36 models of acquired resistance to PI3K/mTOR inhibition, we reducing ROS with the antioxidant N-acetylcysteine (NAC) analyzed an additional panel of cells, including seven sensitive would increase the proliferation of resistant cells. After and resistant cell line pairs derived from breast (MCF7-K1, MCF7- fi con rming that NAC was a free radical quencher in our model K2 and MCF7-K3), esophagus (KYSE70 and KYSE180) and head and (Supplementary Figure S5b), we found that reduction of ROS by neck (LB771-HNC and CAL33) (Figure 7). These cells were resistant NAC restored the proliferation of cells with elevated metabolism to PI3K/mTOR inhibition and reactivated this signaling pathway and high ROS levels (G1 and G2 cell lines growing in the absence following drug removal.12,14 Six out of seven of these resistant cell of PI3Ki;Figure 5c and Supplementary Figure S5b). Conversely, lines did not recover the growth rate of parental cells after drug proliferation of cells with lower metabolism and ROS was impaired withdrawal (Figure 7a). Two of these resistant cell lines (K2 and by NAC (Figure 5c). KYSE70) also proliferated less efficiently when growing without 37 Similarly, the lipophilic ROS scavenger α-tocopherol increased inhibitor in the media than when the compound was present the proliferation of G2 cells growing without PI3Ki, but decreased (Figure 7a). Drug holidays resulted in an increase in respiratory cell numbers when cultured with PI3Ki (Supplementary activity in five out of seven of the cell lines tested (Figure 7b), and Figure S5c). This antioxidant also decreased proliferation of ROS (Figure 7c) and glycolytic activity (Figure 7d) also increased in parental cells (Supplementary Figure S5c). Thus, the loss of ROS four of them. homeostasis that occurred in G1 and G2 cells after drug removal In the panel of 10 resistant cell lines, drug withdrawal led to a (probably because of an increase of the OCR; Figure 1f) was reduced proliferation in four of them (G1, G2, K2 and KYSE70) and responsible for their proliferative defect. In contrast, ROS levels increase in proliferation in two of them (K1 and K3) (Figure 7e, were lower in G3 cells (probably because they did not suffer a upper panel). Notably, we found a positive correlation (R = 0.94, significant increase of OCR; Figure 1f) and, consequently, these P = 5.3 × 10−05) between cell proliferation and the ratio of cells did not experience a proliferative defect. ROS can stabilize glycolytic activity to ROS concentration (Figure 7e, lower panel), HIF.38 ROS scavenging with NAC decreased HIF-1α protein suggesting that the toxic effect of ROS accumulation was expression in the resistant cell lines grown without PI3Ki to that counteracted by the pro-proliferative contribution of high of expression in parental cells (Figure 5d) and significantly glycolysis. In summary, Figure 7 indicates that drug removal reduced the levels of lactic acid in all PI3Ki-resistant cells; this causes the loss of ROS homeostasis and the increase of the effect being greater in G1 and G2 grown without PI3Ki (Figure 5e). glycolytic pathway in different models of PI3K/mTOR axis To delineate in more detail the pathway that leads to ROS independence. The extent of glycolysis and ROS dysregulation production in PI3Ki-resistant cells, we measured cellular ROS after and their balance determine the capacity of PI3K/mTOR-resistant the inhibition of several PI3K pathway members. Treatment of cells to proliferate during drug holidays (Figure 7f). resistant cells that present high oxidative stress (G1 and G2) with PI3Ki, mTORC1/2i and mTORC1i reduced ROS levels, whereas inhibitors of AKT, SGK, CAMKII or MEK were unable to prevent the DISCUSSION increase of ROS (Figure 5f and Supplementary Figure S5d). In this study we investigated the biochemical adaptations that Similarly, neither c-MYC nor HIF inhibition reduced ROS accumula- allow cancer cells to compensate for chronic PI3K inhibition and tion (Figure 5f and Supplementary Figure S5d). how these change during drug holidays. The results obtained from Together, the data in Figure 5 reinforce the notion that PI3Ki- the study of three independent cell lines derived from MCF7 resistant cells develop an oxidative phenotype during drug breast cancer cells14 were then confirmed in an independent holidays that is dependent on PI3K and mTORC1, but does not panel of sensitive/resistant models.12,14 In the presence of PI3K

Oncogene (2017) 2762 – 2774 Metabolic defects in PI3K inhibitor-resistant cells M Dermit et al 2769

Associated function (cluster 2) Rank Gene Ontology and Function 6 1 GO:0016209; F:antioxidant activity 1 5 GO:0016209 2 GO:0005507; F:copper ion binding F:antioxidant activity

(P) 4 3 GO:0005504; F:fatty acid binding 10 4 2 3 5 3 4 GO:0034185; F:apolipoprotein binding

-log 6 2 p=0.01 5 GO:0030170; F:pyridoxal phosphate binding p=0.05 1 6 GO:0003785; F:actin monomer binding 1.5 2.5 3.5

log2 fold enrichment

P G1 G2 G3 ** ** * ** 15

-PI3Ki 10

5 ROS (a.u.)

0 +PI3Ki P G1 G2 G3 G1 G2 G3 -PI3Ki +PI3Ki

P G1 G2 G3 6 Control 3 Control 3 Control 3 Control NAC NAC NAC NAC 4 2 * 2 2 * *** *** * 2 1 1 1 ) 6 *** 0 *** 0 0 0 0714071407140714

6 PI3Ki 3 PI3Ki 3 PI3Ki 3 PI3Ki PI3Ki+NAC PI3Ki+NAC PI3Ki+NAC PI3Ki+NAC

Cell number (X10^ 4 2 2 2 ** 2 1 1 ** 1 *** *** ** ** 0 0 0 0 0714071407140714 Time (days)

P G1 G2 G3 160 160 160 160 Control NAC KDa P G1 G2 G3 G1 G2 G3 120 120 120 120 110 - HIF-1α 80 80 80 80 50 - α-tubulin * 40 40 * 40 40 *

[Lactic acid] /Mcell (mM) 0 0 0 0 PI3Ki --++ --++ --++ --++ NAC -+-+ -+-+ -+-+ -+-+

P G1 G2 G3 15 15 15 15

10 10 10 10

*** *** ***** 5 ** 5 *** 5 *** 5 *** ROS (a.u.) *** *** *** *** ****** *** 0 0 0 0 i i i i1 ol ol 1 Ki K r r Ti1 t t trol C I3Ki I3 HIFi HIFi HIFi HIFi Y RC1 SGKi SGKi SGKi SGKi P PI3 P PI3Ki on on AK AKTi1 AKTi1 AKTi1 AKTi2 AKTi2 AKTi2 AKTi2 C Control Con C TO TORC c-MYCi1 c-MYCi1 c-M c-MYCi1 m mTORC1i mTORC1i m mTORC1/2i mTORC1/2i mTORC1/2i mTORC1/2i Figure 5. ROS produced during drug holidays in resistant cells activate HIF and cause a proliferative defect that can be recovered by free radical scavengers. (a) Gene Ontology analysis of proteins increased in PI3Ki-resistant cells relative to parental (cluster 2 in Figure 3a). (b) Representative images and quantiﬁcation of ROS in cells cultured for 7 days. (c) Proliferation of cells as a function of treatment with the named compounds. Media were replaced daily. (d) HIF-1α protein expression in cells treated with 200 μM NAC for 5 days. (e) Lactic acid produced by cells cultured for 5 days in the absence or presence of vehicle, PI3Ki, NAC or both. Lactic acid form the media were normalized to cell number. (f) ROS levels in cells cultured for 7 days with vehicle or inhibitors of the named proteins. Data are mean ± s.d. of seven ﬁelds per condition. For (b), (c) and (e), data are mean ± s.d. of three independent biological replicates. P-values calculated using an unpaired, two-tailed Student’s t- test comparing as indicated for (b), and presence or absence of NAC for (c) and (e). For (f), presence or absence of the indicated inhibitor was compared. *Po0.05; **Po0.01; ***Po0.001.

Oncogene (2017) 2762 – 2774 Metabolic defects in PI3K inhibitor-resistant cells M Dermit et al 2770

Glucose free-media 1.5 2 G1 G2 G3 O

2 1.5 1.5 1.5 ) ** * 6 * 1 1 1 1

0.5 0.5 0.5 0.5 **

Cell number(X10^ ** * 0 ** 0 0 012 012 012

Relative cell number after H 0 Time (days) P G1G2G3G1G2G3 -PI3Ki +PI3Ki Glutamine free-media G1 G2 G3 1.5 1.5 1.5 ) 6

1 1 1 * 0.5 0.5 0.5 * **

Cell number (X10^ 0 0 0 012 012 012 Time (days)

P - PI3Ki P - PI3Ki P - PI3Ki G1 - PI3Ki G2 - PI3Ki G3 - PI3Ki G1 + PI3Ki G2 + PI3Ki G3 + PI3Ki Figure 6. Metabolism as a therapeutic target for PI3Ki-resistant cells during drug holidays. (a) Relative cell numbers after 5-day treatment with 130 μM H2O2 either in the presence or absence of PI3Ki. (b) Cell numbers as a function of culture in glucose-free media for 1 and 2 days. (c) Cell numbers as a function of culture in glutamine-free media for 1 and 2 days. Data are mean ± s.d. of three independent biological replicates. P- values calculated using an unpaired, two-tailed Student’s t-test comparing for (a) and (b) as indicated, and for (c) presence or absence of PI3Ki at days 1 and 2; *Po0.05; **Po0.01; ***Po0.001.

pathway inhibitors, resistant cells proliferated at a lower rate than During drug holidays PI3Ki-resistant cells reactivated the PI3K/ the parental cells from which they originated. This proliferative mTORC1 pathway, which is a positive regulator of mitochondrial defect could not be reversed by reactivation of the PI3K/mTOR respiration,44–46 leading to a dysregulation of ROS homeostasis pathway (Figures 1 and 2). Indeed, some of the resistant cells that in turn hampered resistant cell proliferation (Figure 7f). proliferated less efﬁciently with an active PI3K pathway (during Resistant cells growing in the presence of drug adapted their ROS drug holidays) than in the context of an inactive PI3K pathway levels to those of parental cells (Figure 5), suggesting that a (that is, when the PI3Ki was present in the media; Figures 1 and 7). minimum concentration of ROS is required for their proliferation. Drug holidays reduced melanoma cells resistant to the BRAF Free radical accumulation is toxic, whereas at lower concentra- inhibitor vemurafenib but the underlying biochemical causes have tions these molecules promote cell proliferation.47,48 However, remained elusive.43 In our models of PI3Ki resistance, drug ROS also act as second messengers to regulate the stabilization of withdrawal caused a proliferative defect that, interestingly, was the transcription factor HIF-1α38 that induces the expression of associated with the appearance of a metabolic phenotype metabolic enzymes, leading to an increase in glycolytic activity. characterized by increased respiratory and glycolytic activities Thus, our data imply that altered cellular metabolism is not just a (Figure 1). hallmark of oncogenesis, but also occurs during the acquisition of Untargeted proteomics and phosphoproteomics analyses resistance to targeted drug therapy in order to maintain ROS showed that c-MYC, CAMKII and MEK activities were increased homeostasis. in resistant cells. Cell proliferation was inhibited by interfering with We observed this high metabolic phenotype in two of the initial c-MYC, CAMKII or MEK activities, suggesting that these proteins set of PI3Ki-resistant cell lines analyzed. To address the question of contributed to the PI3Ki resistance phenotype. The oncogene how frequently this phenotype occurs in cells resistant to PI3K/ c-Myc and the MAPK pathway have been previously implicated in mTOR inhibition, we investigated whether this mechanism also the ability of cells to survive without PI3K.9–11 However, c-MYC, applied to three breast cancer cell lines resistant to Ku-0063794 CAMKII or MEK were not involved in the metabolic phenotype of and to four models of resistance to BYL719 (two of which were our models. In contrast, this hypermetabolism could be reversed derived from esophagus and two from head and neck cancers). by inhibiting mTORC1/2 or PI3K but not by AKT or SGK inhibitors, After drug removal, 9/10 of these models did not recover the implying that, contrary to the canonical understanding of PI3K proliferative capacity of parental cells despite reactivating signaling, these cells possess a PI3K/mTORC1 axis that is mTORC1. Respiration, ROS production and glycolytic activity were independent of AKT. This notion was also supported by increased in seven, six and seven of these models, respectively. phosphoproteomics data showing that PI3K and mTORC1/2 Despite the variability in the extent of the metabolic dysregula- blockade reduced the phosphorylation of a large number of sites tion, a common feature across all the resistant models analyzed that were insensitive to AKT inactivation (Figure 2). was that these showed a remarkable association between cell

Oncogene (2017) 2762 – 2774 Metabolic defects in PI3K inhibitor-resistant cells M Dermit et al 2771 BreastEsophagus Head and Neck

MCF7-K1 MCF7-K2 MCF7-K3 KYSE70 KYSE180 LB771-HNC CAL33 ) 6 *** *** *** * * 3.0 *** *** 3.0 *** *** 3.0 *** * 5.0 * ** 3.0 * 6.0 ** 3.0 *

1.5 1.5 1.5 2.5 1.5 3.0 1.5

0.0 0.0 0.0 0.0 0.0 0.0 0.0 PR-R+ PR-R+ PR-R+ PR-R+ PR-R+ PR-R+ PR-R+

*** *** *** *** *** * * * * *** *** *** *** *** *** *** *** 800 800 800 800 800 800 800

400 400 400 400 400 400 400

OCR (pMoles/min)0 Cell number (X10^ 0 0 0 0 0 0 PR-R+ PR-R+ PR-R+ PR-R+ PR-R+ PR-R+ PR-R+

P P P P P P P

R- R- R- R- R- R- R-

R+ R+ R+ R+ R+ R+ R+

7.0 ** 20 ** *** 5 ** *** 20 * 20 * 10 ** 5 ** *** *** .)

3.5 10 2.5 2.5 10 10 5 ROS (a.u 0.0 0 0 0 0 0 0 PR-R+ PR-R+ PR-R+ PR-R+ PR-R+ PR-R+ PR-R+

** *** * ** * 60 ** ** 90 * * 30 *** 90 * 90 ****90 *** 60 * /min)

30 45 15 45 45 45 30 R(mpH

ECA 0 0 0 0 0 0 0 PR-R+ PR-R+ PR-R+ PR-R+ PR-R+ PR-R+ PR-R+

Effect of drug removal Ratio fold ECAR: fold ROS Resistant cells 3 * Fold change in proliferation *** - DRUG 2 ld * ** Fo mTOR (10/10) 1 * ** **** * ** * 0 OXPHOS (7/10) Resistant cells DRUG +DRUG REMOVAL ROS (6/10) Adjust ROS levels to 3 parental cells HIF Proliferation (mTORC1) ion

ein 2 at Glycolysis (7/10) R=0.94 lifer 1 P=5.3e-05 Chang pro

0 Proliferative deficit 0123 when glycolysis/ROS Change in glycolysis/ROS Figure 7. For caption see page 2772.

Oncogene (2017) 2762 – 2774 Metabolic defects in PI3K inhibitor-resistant cells M Dermit et al 2772 proliferation and the ratio of glycolytic activity to ROS levels obtained and the area under the curve was measured using Excalibur (Figure 7e). This observation supports the notion that the software (version 2, Thermo Fisher Scientific). metabolic status of PI3Ki-resistant cells determines their ability to proliferate. ROS measurement The hypermetabolic phenotype suggests new therapeutic ROS were assayed by addition of 10 μM dichloro-dihydro-fluorescein diacetate opportunities as adjuvant to the drug holiday strategy. Increased (DCFH-DA, Sigma-Aldrich, St Louis, MO, USA) for 30 min, and they were further glycolysis during drug holidays rendered resistant cells more washed with cold phosphate-buffered saline and observed under a Nikon sensitive to nutrient starvation, and high levels of free radicals eclipse CiS/Ci-L microscope and process with Nis elements D imaging software increased their sensitivity to further oxidative stress (Figure 6). (Nikon Instruments, Amsterdam, The Netherlands). Quantification of ROS was Drugs that cause an intracellular accumulation of lactic acid levels, done with Image J 1.48V (National Institutes of Health, Bethesda, Maryland, such as inhibitors of the monocarboxylate transporters49 or USA). The mean intensity of pixel was calculated for each image. Data for each biological replicate are the mean of seven fields per condition. compounds that inhibit free radical scavengers,32,50 could increase the therapeutic window of these compounds, enhancing the ability of the drug holiday strategy to delay the occurrence of HIF transcriptional activity resistance to PI3Ki. Cells at 70% confluence were transfected with of a plasmid (30 ng per well). At 2 days after transfection, cells were lysed for 20 min using 1 × passive lysis buffer (Promega). Reporter activation was determined using MATERIALS AND METHODS the Nano-Glo Dual-Luciferase Reporter Assay System (Promega). Luciferase activity was measured using a Dynex Revelation 4.06 luminometer (Dynex Details of reagents used in this study, including compounds, media, Technologies, Chantilly, VA, USA). antibodies and nutrients are given in Supplementary Tables S1–S4. fl Cell lines Micro uid expression of metabolic genes Expression of 96 metabolic genes was quantified on the multiplex Fluidigm MCF7 breast cancer cell line was obtained from ATCC (HTB-22; Manassas, platform following the manufactures’ instructions. VA, USA). Three cell lines resistant to GDC-0941 (G1-G3) or to Ku-0063794 (K1-K3) were obtained by exposing MCF7 cells to increasing concentrations of the respective compound during 6 months.14 Cell pairs sensitive or Mass spectrometry-based proteomics and phosphoprotemics resistant to BYL719, namely CAL-33, LB771-HNC, KYSE180 and KYSE70, Cells from four independent biological replicates were lysed using urea were a kind gift from Dr Baselga (Human Oncology and Pathogenesis lysis buffer containing phosphatase inhibitors (1 mM Na3VO4,1mM NaF, 12 Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA). 1mM β-glycerol-phosphate and 2.5 mM Na P O ). Extracted proteins were fi 4 2 7 Cells were maintained in humidi ed incubator with 5% CO2 using culture digested with trypsin and peptides analyzed in two technical replicates on media Dulbecco’s modified Eagle’s medium supplemented with 10% fetal an LTQ-Orbitrap mass spectrometer (Thermo Fisher Scientific). For μ bovine serum, 100 U/ml penicillin and 1 M of the respective compound, phosphoproteomics experiments, TiO2 enrichment method was used in except when indicated (see Supplementary Tables S1 for details of media two independent biological replicates and run in two technical replicates and compounds used for cell culture). in an LTQ Orbitrap or in a Q Exactive Plus mass spectrometer (Thermo Fisher Scientific). Mascot was used to identify peptides from tandem mass fi 14 Cell proliferation assay spectrometry data. Pescal was used for label-free quanti cation. Normalized peak areas of peptides or phosphopeptides were averaged The number of viable cells was assayed using a Vi-CELL cell counter between replicates and fold change between conditions was calculated. (Beckman Coulter, Inc., Brea, CA, USA). A total of 2000 cells on 96-well Kinase activity was estimated from phosphoproteomics data using the plates were analyzed by addition and 30 min of incubation of the Guava kinase substrate enrichment analysis approach as previously described4 Nexin reagent (EMD Millipore, Billerica, MA, USA) or the Guava Cell Cycle (see Supplementary Materials and methods). Data are available via reagent (EMD Millipore). Then, 2000 events (apoptosis assays) or 5000 ProteomeXchange with identifier PXD003594. events (cell cycle distribution) were acquired per sample and FSC files were analyzed using CytoSoft software (Guava Technologies, Billerica, MA, USA). Statistical analysis Metabolic assays All data represent the mean ± s.d. of a minimum of three independent experiment. The resulting data were considered significant when the Oxidative capacity was measured via the MTS assay after 2 h of incubation P-value was o0.05. Significance of enrichment of kinase substrates, (Promega, Madison, WI, USA). To measure basal OCR and ECAR, 80 000 cells ontologies and pathways in each cluster was determined by the per well were incubated for 24 h at 37 °C in 5% CO2 with XF assay media hypergeometric test. For cell viability assays, bioenergetic assays, micro- (Agilent technologies, Santa Clara, CA, USA). To establish OCR and ECAR scopic fluorescence data and proteomics data, paired Student’s t-tests values, four readings were acquired per experiment (Seahorse Bioscience, were performed following the assumption of normal distribution and Santa Clara, CA, USA). Culture media pH was measured using a pH meter equal variance of the data. (Hanna Instrument). For lactate measurements, lactate was extracted from the media after 5 days of culture and subsequently analyzed by TSQ Vantage mass spectrometer (Thermo Fisher Scientific, Waltham, MA, USA). Western blot The parental ion mass followed on a negative mode was 89.0244 Da. For After washing with phosphate-buffered saline containing 1 mM Na3VO4 quantification extracted ions chromatograms for the parental ion were and 1 mM NaF, cells were lysed with a Triton base buffer supplemented

Figure 7. The balance between glycolytic and oxidative metabolic activities determines the proliferation of drug-resistant cells. (a) Cell numbers of seven cell lines resistant to different PI3K/mTORC1/2 inhibitors. Cells were cultured in the presence (R+) or absence (R − ) of the selection drug. P, parental cells. Data are mean ± s.d. of three independent biological replicates. P-values were calculated using an unpaired, two-tailed Student’s t-test comparing conditions as indicated; *Po0.05; **Po0.01; ***Po0.001. (b) OCR measured in the same cells as in (a). (c) ROS measured in the same cells as in (a), and (d) ECAR measured in the same cells as in (a). (e) The glycolysis to ROS ratio associates with the proliferation capacity of cells during drug holidays. Change in proliferation was calculated by dividing the number of viable cells remaining after culture in drug holidays by those in cells treated with the speciﬁc inhibitor. Ratio of changes in ECAR and ROS was calculated by dividing these values in cells in drug holiday conditions by those of cells growing in the presence of the inhibitors. Values above 1 denote that drug removal had a positive effect on proliferation or glycolysis/ROS ratio (upper panel). The association was statistically signiﬁcant (bottom panel). R, Pearson’s correlation value. P, P-value for Pearson’s correlation value. (f) Proposed mechanism to explain the proliferative and metabolic alterations that occur in cells with acquired resistance to PI3K/mTOR inhibition during drug holidays.

Oncogene (2017) 2762 – 2774 Metabolic defects in PI3K inhibitor-resistant cells M Dermit et al 2773 with protease inhibitors (Complete Mini EDTA-free; Roche, Basel, Switzer- 16 Hirai H, Sootome H, Nakatsuru Y, Miyama K, Taguchi S, Tsujioka K et al. fi land) and phosphatase inhibitors (1 mM Na3VO4,1mM NaF, 1 mM β- MK-2206, an allosteric Akt inhibitor, enhances antitumor ef cacy by standard glycerol-phosphate, 2.5 mM Na4P2O7 and 1 μM okadaic acid). Cell extracts chemotherapeutic agents or molecular targeted drugs in vitro and in vivo. Mol were maintained during 30 min on ice. Proteins were quantified by BCA Cancer Ther 2010; 9: 1956–1967. (Thermo Fisher Scientific) and separated by gradient gels. Primary 17 Rehan M, Beg MA, Parveen S, Damanhouri GA, Zaher GF. Computational insights antibodies (see Supplementary Table S3 for details) were incubated into the inhibitory mechanism of human AKT1 by an orally active inhibitor, 9 overnight at 4 °C and secondary antibodies were incubated for 1 h. MK-2206. PLoS One 2014; : e109705. Detection was by enhanced chemiluminescence (Thermo Fisher Scientific). 18 Lindsley CW, Zhao Z, Leister WH, Robinson RG, Barnett SF, Defeo-Jones D et al. Allosteric Akt (PKB) inhibitors: discovery and SAR of isozyme selective inhibitors. Bioorg Med Chem Lett 2005; 15:761–764. CONFLICT OF INTEREST 19 Piguet AC, Majumder S, Maheshwari U, Manjunathan R, Saran U, Chatterjee S et al. Everolimus is a potent inhibitor of activated hepatic stellate cell functions in vitro fl The authors declare no con ict of interest. and in vivo, while demonstrating anti-angiogenic activities. Clin Sci 2014; 126: 775–784. 20 Anacker C, Cattaneo A, Musaelyan K, Zunszain PA, Horowitz M, Molteni R et al. ACKNOWLEDGEMENTS Role for the kinase SGK1 in stress, depression, and glucocorticoid We thank Gemma Bridge for advice with Seahorse experiments and Dr Soong effects on hippocampal neurogenesis. Proc Natl Acad Sci USA 2013; 110: and Dr Baselga for kindly providing LB771-HNC, CAL33, KYSE70 and KYSE180 8708–8713. parental/resistant pairs of cells. This work was supported by St Peters Trust and 21 Sommer EM, Dry H, Cross D, Guichard S, Davies BR, Alessi DR. Elevated SGK1 452 Barts and The London Charity (BLT 297/2249). PRC was supported by BBSRC Grant predicts resistance of breast cancer cells to Akt inhibitors. Biochem J 2013; : – BB/M006174/1. 499 508. 22 Gilmartin AG, Bleam MR, Groy A, Moss KG, Minthorn EA, Kulkarni SG et al. GSK1120212 (JTP-74057) is an inhibitor of MEK activity and activation with AUTHOR CONTRIBUTIONS favorable pharmacokinetic properties for sustained in vivo pathway inhibition. Clin Cancer Res 2011; 17: 989–1000. 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