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Translational Science

Restraining Network Response to TargetedCancer Therapies Improves Efficacy and ReducesCellular ResistanceTirtha K. Das, Jessica Esernio, and Ross L. Cagan

Abstract

A key tool of cancer therapy has been targeted inhibitionof oncogene-addicted pathways. However, efficacy has beenlimited by progressive emergence of resistance as trans-formed cells adapt. Here, we use Drosophila to dissectresponse to targeted therapies. Treatment with a range ofkinase inhibitors led to hyperactivation of overall cellularnetworks, resulting in emergent resistance and expression ofstem cell markers, including Sox2. Genetic and drug screensrevealed that inhibitors of histone deacetylases, protea-some, and Hsp90 family of proteins restrained this networkhyperactivation. These "network brake" cocktails, used asadjuncts, prevented emergent resistance and promoted cell

death at subtherapeutic doses. Our results highlight ageneral response of cells, transformed and normal, totargeted therapies that leads to resistance and toxicity.Pairing targeted therapeutics with subtherapeutic doses ofbroad-acting "network brake" drugs may provide a meansof extending therapeutic utility while reducing whole bodytoxicity.

Significance: Thesefindingswith a strong therapeutic poten-tial provide an innovative approach of identifying effectivecombination treatments for cancer. Cancer Res; 78(15); 4344–59.�2018 AACR.

IntroductionDespite important progress, cancer remains a serious health

problem worldwide. Recent efforts at developing drugs thatreduce tumor progression have yielded important successes;however, most tumors eventually develop resistance to drugsincluding targeted therapies. After an initial response, manytumors develop poorly understood strategies to evade therapy.In some patients, this reflects previously undetected mutationsthat confer resistance, suggesting a selection process initiated bydrug response. However, many tumors achieve resistancethrough undefined, nongenetic means (reviewed in ref. 1).Furthermore, tumors commonly develop resistance to the ini-tial therapeutic and, simultaneously, to other targeted thera-pies. This suggests broad changes within tumor cells can occurin response to drug therapy including in the kinome andsecretome (2, 3), although the nature of these changes is poorlydefined.

Here we use a Drosophila cancer/normal cell model andhuman cancer cell lines to explore mechanisms by whichtransformed and normal cells respond to targeted therapies.We demonstrate that a key component of this response is broad

alteration of tissues' overall cellular network: the result isactivation of a large cross-section of signaling pathways andexpression of stem cell markers in a subset of cells. This broadalteration in tumor and normal cells' overall network in turnled to progressive resistance to a broad range of standard-of-care targeted therapies.

Our genetic and drug screens identified specific drug cocktailsthat restricted this broad response to therapeutics. For example,pairing (i) targeted therapies such as sorafenib, erlotinib, andtrametinibwith (ii) low, subtherapeutic doses of bortezomib plusvorinostat led to control of cellular networks, reduced "stemness,"reduced whole-animal toxicity, and sustained drug efficacy. Weobserved similar therapeutic benefits with broadly acting drugs,used as adjunct to targeted therapy, that restrain networks throughother means including the Hsp90 inhibitor AUY922 and theHDAC-PI3K dual pathway inhibitor CUDC-907. Our findingsuncover a broader principle: targeted therapies induce hyperacti-vation of the cellular kinase network, an alteration that can berestrained by subtherapeutic doses of broadly acting inhibitors.The result is a significantly improved and sustained therapeuticresponse.

Materials and MethodsAntibodies

Antibodies used for Drosophila and human cancer line Westernblot analysis were: anti-pRet, anti-pJnk, anti-pAkt, anti-SOX2,anti-KLF4, anti-LIN28, anti-Oct4, anti-Nanog, anti-cMyc, anti-pMOB, anti-cleaved PARP (Cell Signaling Technology), anti-pSrc(Y418) (Invitrogen), anti-pERK, anti-total-ERK (Sigma), plusanti-Actin, anti-E-cadherin, anti-a-catenin, anti-Rho1, anti-Syntaxin, anti-CycD, anti-Argos, anti-b-tubulin (DevelopmentalStudies Hybridoma Bank), anti-actin, anti-GAPDH, and anti-RhoA antibodies were purchased from Santa Cruz Biotechnology.Anti-Rac1 antibody was from BD Biosciences, anti-EGFR from

Department of Cell, Developmental, and Regenerative Biology, Icahn School ofMedicine at Mount Sinai, New York, New York.

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

Corresponding Author: Tirtha K. Das, Department of Cell, Developmental, andRegenerative Biology, Icahn School of Medicine at Mount Sinai, One GustaveLevy Place, New York, NY 10029-1020. Phone: 212-214-0135; Fax: 212-860-9279;E-mail: [email protected]

doi: 10.1158/0008-5472.CAN-17-2001

�2018 American Association for Cancer Research.

CancerResearch

Cancer Res; 78(15) August 1, 20184344

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Published OnlineFirst May 29, 2018; DOI: 10.1158/0008-5472.CAN-17-2001

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Julia Cordero, anti-activated-b-Catenin from Millipore, and his-tone modification antibodies from ActiveMotif.

Cancer cell linesThe various human cancer cell lines were obtained from the

scientists mentioned in the Acknowledgements section, as well assome from our own previously acquired collection. Authentica-tion was performed by testing for their growth rates, morphology,previously published sensitivity to targeted therapies, for exam-ple, Ret-inhibitor sensitivity for MZ and TT cells, EGFR-inhibitorsensitivity for H358, etc. No adverse contamination issues werenoticed and therefore Mycoplasma testing was not performed.Typically, a maximum of eight to nine passages were requiredfrom time of thawing to completion of individual experiments,except for chronic drug treatment studies where cells were pas-saged over few months as indicated in experiments.

Chronic drug treatment assays on human cancer linesHuman non–small cell lung cancer (NSCLC) cancer line H358

ormelanoma line 239 were grown in 75-cm2 culture flasks. H358cells were grown in the following conditions: (i) 0.01% DMSO,(ii) 0.5 mmol/L erlotinib, (iii) 1 mmol/L erlotinib, (iv) bortezomib(6 nmol/L) þ vorinostat (50 nmol/L), (v) erlotinib (1 mmol/L)bortezomib (6 nmol/L) þ vorinostat (50 nmol/L). 239-melano-ma cells were grown in the following conditions: (i) 0.01%DMSO, (ii) 0.5 mol/L vemurafenib, (iii) bortezomib (6 nmol/L)þ vorinostat (50 nmol/L), (iv) vemurafenib (0.5 mmol/L), borte-zomib (6 nmol/L) þ vorinostat (50 nmol/L). Initially, cells wereseeded in culture flasks at 20% confluency and incubated inRPMI1640 media with the above-mentioned conditions. Whencells reached confluency (DMSO controls), they were split andtransferred to new culture flask with identical fresh media con-ditions once a week. Otherwise identical fresh media was pro-vided to each flask once a week. When single drug–treated cells(erlotinib or vemurafenib) started growing similar to DMSOcontrol cells, the drug-resistant cells as well as the triple drug–treated cells were further amplified for three generations in theabsence of any drug treatment. This allowed the resistant cells andtriple drug cocktail–treated cells to yield sufficient cells for thevarious assays, that is, phospho-kinome array, Western blot, andMTT viability assay.

Comprehensive statistical analysisFor viability adult/pupal analysis, mean and SEM were calcu-

lated and 4–5 vials/experiments, biological replicates, per dosewere analyzed and repeated at least two times. Each vial hadbetween20 and80developing embryos and total (N) indicated inlegend represents the total number of embryos analyzed. To assessstatistical significance of difference between means, t test withWelch correction was performed using PRISM software. Thecorrection was used to account for samples with unequal var-iances, as each drug or mutant affects overall cellular networksdifferently, and unequal sample sizes. For MTT on cancer cells,each dose was performed in quadruplicates and mean signal andSEM analyzed.

Fly stocks, genetics, and subcloningFly stocks were obtained from Bloomington and VDRC

Drosophila stock centers (C. Pfleger, Department of OncologicalSciences, Icahn School ofMedicine atMount Sinai, NewYork,NY;M. Mlodzik, Department of Cell, Developmental, and Regener-

ative Biology, Icahn School of Medicine at Mount Sinai, NewYork, NY). UAS-RetMEN2B

flies were generated and publishedpreviously (4).Drosophila Erk allele (rolled/CyO-Huþ; Bloomingtonstock number #386) is fully viable stock over a CyO-RFP markedbalancer.

Inhibitor studies in fliesDrugswere obtained fromLC laboratories or SelleckChemicals

and dissolved in DMSO as stock solutions ranging from 1 to 200mmol/L. Drugs were diluted in molten (�50–60�C) enriched flyfood, vortexed,mixed by pipetting, aliquoted into 5-mL vials, andsolidified at room temperature to yield the indicated final drugconcentrations. Thirty to 60 embryos of each genotypewere raisedon drug-containing food (500–1,000 mL) in 5-mL vials until theymatured as third-instar larvae (wing disc western assay) orallowed to proceed to adulthood (viability assay and wing veinquantitation assay). Five vials per experiment were analyzed andrepeated at least three times. At the end of 14–16 days, pupae andeclosed adults were counted. The mean for each condition isrepresented as columns with the SEM depicted by the error bars.

Kinase tree render analysisIllustration model was reproduced courtesy of Cell Signaling

Technology, Inc. (www.cellsignal.com). "Kinome-render" pro-gram from the Najmanovich research group (http://bcb.med.usherbrooke.ca/) was used to generate sorafenib kinase inhibitiontree using in vitro targets identified in Karaman and colleagues'(2008) study as input. Tree depicts in vitro targets only, not relativeinhibition of targets, using the available Kd data. Fifty-six of the79 known targets of sorafenib are represented on the "Kinome-Render" generated tree.

MTT assays using cancer linesAll cancer cell lines were cultured in RPMI1640 media, supple-

mented with 10% BSA and penicillin/streptomycin antibioticsmix. Cells were grown in 75-cm2 sterile polystyrene culture flasksto 80% confluency, trypsinized, and reseeded in equal aliquotsinto 96-well plates. After 2 days and approximately 50% con-fluency, media were removed and replaced with DMSO or drug-containing media. Cells were allowed to grow another 6 days(MZ-CRC-1 and TT) or 4 days (all other fast growing cancer lines),after whichMTT assay was performed as described previously (4).To compute combination index (CI), the IC50's each individualdrug on each cell linewas assessed using PRISMsoftware as shownin main figures. Then, CI was analyzed using the followingformula (5):

3 CIð Þ50% ¼ D1ð Þc= D1ð Þalone þð Þ D2ð Þc= D2ð Þalone þð Þ D3ð Þc=D3ð Þalone

Where; Dð Þalone ¼ IC50 of single drug on cell lineDð Þc ¼ IC50 of drug in combination on cell lineD1 ¼ drug1;D2 ¼ drug2;D3 ¼ drug3

Summary of all the computed CIs are provided in Supplemen-tary Table S1.

Phosphoprotein array analysisFor assessment of kinase activity of human cancer cell lines, we

used the PathScan RTK Signaling Antibody Array Kit (catalog no.

Network Brake Drugs Prevent Cancer Drug Resistance

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Figure 1.

An approach to identifying drug cocktails for cancer treatment. A, ptc>Ret2B flies were screened against a panel of drugs (Supplementary Fig. S1B). Some drugsimproved the number of statistically significant animals that survived to pupal stages (blue columns, asterisk). Only sorafenib yielded statistically significantsurvival to adult stages (red column, asterisk). ptc>Ret2B flies were rescreened against the same panel of clinically relevant drugs in the presence ofsorafenib to identify useful combinations. A subset of combinations, including sorafenib/bortezomib, sorafenib/dasatinib, and sorafenib/wortmann, in improvedadult viability compared with sorafenib as single agent (bracket, double asterisk). Significance (P < 0.05; asterisks) of pupa and adult viability was determinedby two-tailed Student t test performed with Welch correction using PRISM software. A list of all the Drosophila viability assay tests, mean values, P values,and total number of flies screened (N) is provided in Supplementary Table S1; details on comprehensive statistical analysis section is given in Materials andMethods. B, Reducing a genomic copy of erk, mek, or hdac1, or knockdown of SP1-transcription factor, or coexpressing InRDN further improved viability offlies fed sorafenib/bortezomib combination. The 3-drug cocktail, sorafenib/bortezomib/vorinostat, also strongly improved adult viability of ptc>Ret2B fliescompared with flies fed sorafenib/bortezomib (bracket, asterisk). Significance (P values) of adult viability was determined by two-tailed Student t testperformed with Welch correction using PRISM software. (Continued on the following page.)

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7982). Briefly, 100-cm2 tissue culture plates were plated withhuman cancer cells at 50%–60% confluency in RPMI1640 mediawith our without drugs and allowed to incubate for 4–5 days.Cells were washed, lysed, quantified, and exposed to phosphoarrays as recommended by the manufacturer, and developedaccording to manufacturer's protocols. Doublet of each signalwas quantitated using densitometric analysis on Image J program,and normalized to time matched untreated cells to create PRISMsoftware–generated heatmap.

Western blot quantitation analysis of fly wing discsForflyWesternblot experiments,we gathered tissues from three

independent biological replicates (�15–20 different animals,total ¼ �30–40 third-instar discs) pooled into one tube for eachtreatment condition. These were then analyzed as Western blotsusing the indicated antibodies. This was done to have enoughsample to cover the large number of Western blots for eachcondition. Third-instar discs of each genotype were dissolved inlysis buffer (50mmol/L Tris, 150mmol/L NaCl, 1% Triton-X100,1 mmol/L EDTA) supplemented with protease inhibitor cocktail(Sigma) and phosphatase inhibitor cocktail (Sigma). For humancell lines, lysis was performed with RIPA buffer. Western blotanalysis was developed as described previously (6). Total proteinamounts in each lysate was established by performing Bradfordassay (Bio-Rad), and equivalent amounts (1–5mg) of total proteinwas loaded per lane. Membranes were stripped with SIGMARestore stripping buffer and reprobed with other antibodies toassess signal under exactly the same loading conditions. Exposedfilmswere scanned andWestern signal for eachmarker (TIFF files)was quantitated using densitometric analysis on Image J program,and normalized to time matched untreated cells/control cells tocreate PRISM software–generated heatmap.

Western blotting of cancer cell linesHuman cancer cell lines were grown in 100-cm2

–well plates inRPMI1640 media each supplemented with 10% heat-inactivatedFBS and penicillin/streptomycin antibiotics. Cells were treated for4–5 days with inhibitors or vehicle (0.1% DMSO). Western blotanalysis was developed as described previously (6). Total proteinamounts in each lysate were established by performing Bradfordassay (Bio-Rad), and equivalent amounts (5–15 mg) of totalprotein was loaded per lane. Multiple loading controls wereanalyzed per experimental set, including GAPDH, actin, b-tubu-lin, histone-H3, and only some were shown in figures.

Whole-mount imaging of fly and wingsFor adult wing vein analysis, wings were dissected and kept in

100% ethanol overnight, mounted on slides in 80% glycerol inPBS solution, and imaged by regular light microscopy using LeicaDM5500 Q microscope.

Xenograft analysisA total of 5–10�106 TT cells were injected subcutaneously into

one flank ofmale nu/numice. Fivemice each showing establishedgrowing tumors were separated into vehicle or drug treatmentgroups. A similar range of tumor sizes was selected for eachexperiment and treatment started when each tumor reached asize of 100 mm3. Vehicle, sorafenib (40 or 60 mg/kg)þbortezo-mib (0.05 or 0.3 mg/kg), or sorafenib (40 mg/kg)þbortezomib(0.05 mg/kg)þvorinostat (10 mg/kg) were administered by oralgavage (orally) once daily, five times a week. Tumor and bodyweight measurements were performed three times a week. Thedifference between initial and final tumor size at each measuringpoint was used to calculate percentage change in tumor size.Statistical analyses andwaterfall plots ofmean tumor size changeswere performed using unpaired Student t test with Welch correc-tion using PRISM software. Mouse experiments were carried outby Antitumor Assessment Facility at Memorial Sloan KetteringCancer Center following Public Health Services guidelines, setforth by the Office for Laboratory and Animal Welfare (OLAW)division of the NIH. The work was covered under an approvedInstitutional Animal Care and Use Committee protocol at theMemorial Sloan Kettering Cancer Center facility (#04-03-009,principal investigator: de Stanchina,Head, Antitumor AssessmentCore, Memorial Sloan Kettering Cancer Center, New York, NY).

ResultsMultiple endocrine neoplasia type 2B (MEN2B) is an often

aggressive disease characterized by a series of morbidities includ-ing medullary thyroid carcinoma (MTC), pheochromocytoma,and mucosal neuromas. Most cases are associated with activated,oncogenic RetM918T; previous studies, including our own, haveshown that multiple downstream signaling pathways are activat-ed to promote transformation (7–9). RetM918T is modeled byDrosophila RetM955T; we refer to this oncogenic isoform as Ret2B.Genetic modifier studies (7) as well as Western blot analysisconfirmed that our Drosophila model (Supplementary Fig. S1A)recapitulated important signaling cascades also observed in ver-tebrate systems (7, 8). Using this model, we developed a Dro-sophila whole-animal viability assay to identify potent multi-targeted inhibitors of the Ret signaling cascade (SupplementaryFig. S1B; ref. 4). Using the patched-GAL4 driver to express UAS-Ret2B in multiple developing tissues (ptc>Ret2B) led to approxi-mately 50% of embryos reaching pupal stages but none devel-oping to adults (Fig. 1A). This assay provided a quantitativemeasure of Ret2B activity including transformation activity (4).

Sorafenib altered cellular networks in aDrosophila Ret2B modelMixing drugs into the flies' media, we screened a panel of

clinically relevant anticancer drugs for improved ptc>Ret2B viabil-ity (Supplementary Fig. S1B and S1C). The panel included clin-ically approved Ret inhibitors, for example, vandetanib andcabozantinib, as well as drugs that targeted various pathways,

(Continued.)C,Western blot analysis ofwholewing discs of indicated genotype/treatments represented as a heatmap (left).Western blot data for antibodies testedare in Supplementary Fig. S2B. Heatmap is represented as the ratio of signal, analyzed in Image J, of treated tissue:control wild-type tissue. Comparison of 765>Ret2B

versus 765>Ret2B; erk�/þ tissues (brackets, asterisk) treatedwith sorafenib showed that drug efficacy (Fig. 1B; Supplementary Figs. S2A and S2B and S3A) correlatedwith overall lower levels of the network of proteins tested. At lower sorafenib doses in 765-GAL4 control flies, pERK levels elevated, indicating increase in Raspathway activity; in addition, overall activity increasewasobserved inmost proteins tested (bracket, asterisk). Right,Westernblot analysis of control (765-GAL4) and765>Ret2B larvae exposed to sorafenib/bortezomib or sorafenib/bortezomib/vorinostat drug combinations. As in Fig. 1C, Western blot data are representedas a heatmap normalized to wild-type tissue treated with DMSO alone. Both tissues exposed to the 3-drug cocktail showed reduced activation of themarkers sampled compared with sorafenib/bortezomib combination, including EGFR, pAkt, pErk, Rac1 specifically in control tissues (brackets, asterisks). Thisindicated the 3-drug cocktail was most potent in restraining pathway hyperactivation in normal as well as Ret-expressing cells.






like PI3K, MAPK, SRC/Abl, (Supplementary Fig. S1A) that we andothers have shown to be important for Ret signaling (4, 10–12).Also included in the panel were inhibitors targeting the protea-some, histone deacetylases, Hsp90, whose effects are more sys-temic and have shown promise as therapies in different cancerparadigms, including thyroid cancer (13–15). A couple of thesebroad-acting inhibitors are clinically approved: bortezomib (mul-tiple myeloma) and vorinostat (T-cell lymphoma). Sorafenibexhibited the strongest rescue: a small fraction of embryos wasrescued to adult stages (Fig. 1A and B). Sorafenib is a kinaseinhibitor with multiple targets including Ret and its down-stream effector Raf that is effective against Ret-dependenthuman thyroid cancer cells and Ret2B-dependent oncogenicsignaling in Drosophila tissues (4, 10, 16).

Previous work demonstrated that, at low doses, Raf inhibitorscan activate Ras pathway signaling by promoting formation ofactive complexes (17). Indeed, low-dose sorafenib activated theRas/MAPKpathway in vivo as assessed by increasedwing venation,a phenotype linked to elevated Ras pathway activity (Supplemen-tary Figs. S2A–S2C and S3A–S3C; ref. 18); few animals survived topupariation (Fig. 1A). Interestingly, reducing gene dosage of theRas/Raf downstream pathway effector erk (ptc>Ret2B,erkþ/�) by50% (Supplementary Fig. S2C) significantly improved sorafenibefficacy even at low doses, resulting in improved wing venationand reduced toxicity as assessed by pupariation rates (Fig. 1B;Supplementary Figs. S2A and S2B and S3A). The ability of sor-afenib to demonstrate efficacy at low doses in the proper geneticbackground suggests that sorafenib toxicity is at least, in part, dueto mechanisms beyond directly promoting active complexes.

Expressing oncogenic Ret throughout the larval wing discepithelium (765>Ret2B), followed by Western blot analysis indi-cated that feeding lower doses of sorafenib (50 mmol/L, 100mmol/L) led to activation ofmultiple signal transduction proteinsincluding activated, phosphorylated forms of Ret, Erk, Akt, andSrc, while this hyperactivation was somewhat restrained at higherdoses (Fig. 1C; Supplementary Fig. S3B–S3E). This indicated thatlower doses of Raf inhibitors such as sorafenib evoked activationof cellular pathways beyond MAPK signaling. This contributed tosorafenib's toxicity aswell as increasedwing venation as describedpreviously. In the presence of higher doses of sorafenib, similarto its effects on viability, reducing erk gene dosage (765>Ret2B,erkþ/�) improved wing phenotypes and significantly reducedoverall phosphorylation levels of most assayed proteins (Fig.1C, right; Supplementary Fig. S3A–S3E).

The Drosophila system also allowed us to readily isolate largenumbers of drug-treated tissues from normal nontumor-contain-ing flies to analyze their cellular protein networks. Higher doses ofsorafenib that showed improved viability (ptc>Ret2B) as well assuppression of wing venation (765>Ret2B) also had lowermediannetwork activity levels in normal cells (Fig. 1C, left). This sug-gested that sorafenib has broad effects on cellular protein net-works, leading to cellular toxicity and poor efficacy. Restrainingthese networks genetically can lead to significant improvement ofsorafenib's therapeutic profile.We therefore searched for clinicallyrelevant combination therapeutics that led to a similar networkrestraint.

Drug combinations restrained hyperactivation of cellularprotein networks in both normal and transformed cells

We rescreened the same clinically relevant drug library in thepresence of sorafenib to identify combinations that could

further improve ptc>Ret2B viability. Three drugs combined withsorafenib to increase the viability of these flies (Fig. 1A; Sup-plementary Fig. S1C). We focused on sorafenib/bortezomiband sorafenib/dasatinib as the most clinically relevant combi-nations (Fig. 1B; (19, 20). Western blot analyses indicated thateach combination kept the median network activity level intransformed cells below the level observed with sorafenib alone(Supplementary Fig. S4A and S4B, brackets, asterisk). This onceagain suggested that treatment efficacy is linked to the overallactivity of the cellular protein networks, and that better treat-ments would lead to similar restraining of the protein networkin the normal cells as well.

Indeed, we found that one combination, sorafenib/bortezo-mib, which also kept the median protein network in normal cellscloser to baseline state compared with sorafenib/dasatinib (Fig.1C; Supplementary Fig. S4A–S4D). Bortezomib is a proteasomeinhibitor approved for multiple myeloma and mantle cell lym-phoma. In contrast, another combination, vandetanib/rapamy-cin, showed the opposite effect: increased toxicity in bothptc>Ret2B flies and control flies (Supplementary Fig. S5A–S5D)as well as higher median level of the protein network in normalcells (Supplementary Fig. S5B). Thus, this further supported theidea that restraining cellular protein networks leads to improvedefficacy of anticancer treatments in our fly models.

To further improve sorafenib/bortezomib–mediated rescue weused a dominant genetic modifier screen, focusing on a subset ofgenes that targeted different kinase pathways as well as othercellular networks, for example, epigenetic and transcriptionalregulators. Clinically relevant inhibitors were available for thesepathways. Reducing dosage of genes encoding ERK (rolledþ/�),MEK (dsor1þ/�), orHDAC1 (rpd3þ/�) orthologs, SP1 (SP1-RNAi),or expressing a dominant-negative insulin receptor (InRDN) bytransgene, improved the viability of ptc>Ret2B flies fed sorafenib/bortezomib (Fig. 1B). The combination sorafenib/dasatinib alsobenefited from reducing erk gene dosage, again lowering themedian protein network level (Fig. 1B; Supplementary Fig. S4Aand S4B). This suggested the efficacy of sorafenib/bortezomibcombination could be further improved by targeting other cel-lular networks, for example, MAPK, PI3K, HDACs, and SP1-transcriptional axes.

The requirement for the histone deacetylase Rpd3 was inter-esting given the broad control of cellular networks by epigeneticcomplexes. Vorinostat is approved for the treatment of T-celllymphoma and for multiple myeloma and is one of severalpan-HDAC inhibitors in clinical trials for other cancer types (e.g., refs. 21, 22). Addition of low-dose vorinostat enhanced theviability of both ptc>Ret2B flies and, notably, control flies treatedwith sorafenib/bortezomib (Fig. 1B; Supplementary Fig. S6A).Onthe basis of Western blot analysis, the three-drug combinationsorafenib/bortezomib/vorinostat further reduced cells' overallnetwork activation in both controls and Ret2B- expressing tissues(Fig. 1C, right). Other pan-HDAC inhibitors similarly enhancedviability of control flies when combined with sorafenib/bortezo-mib (Supplementary Fig. S6A). Vorinostat regulates transcriptionof a large number of target genes (23), suggesting it restrainedcellular response to drugs by controlling changes in transcription.Consistent with this view mithramycin, a chemical inhibitorof SP1-class transcription factors (24), similarly improved efficacyof the sorafenib/bortezomib combination (SupplementaryFig. S6B); previous studies had shown that bortezomib treatmentreduced the levels of SP1, a potent transcriptional activator of

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various HDACs (25). Moreover, knockdown of SP1 had alsoimproved sorafenib/bortezomib combination efficacy in our flyviability assays (Fig. 1B). We concluded that inhibition of HDACfunction or other components regulating transcription like SP1,

genetically or through drugs, suppressed oncogenic Ret2B signal-ing in our fly models.

To establish potential translational relevance of our findings,we surveyed previous studies of molecular mechanisms of

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Network brake drug cocktails restrained human thyroid cancer networks. A, MTT viability assay curves indicate that bortezomib/vorinostat reduced viability ofMZ-CRC-1 cells at moderate as well as high doses of sorafenib, including significant reduction of IC50. IC50 are in parentheses; doses of bortezomib (6 nmol/L) andvorinostat (6 nmol/L and 50 nmol/L) are indicated. For each dose–response curve, in this figure as well as subsequent ones, the CI is indicated below andqualitative synergy as per previous studies (5) represented. CI < 0.1 (þþþþþ, very strong synergism), CI¼ 0.1–0.3 (þþþþ, strong synergism), CI¼ 0.3–0.7 (þþþ,synergism), CI¼0.7–0.85 (þþ,moderate synergism), CI¼0.85–0.9 (þ, slight synergism), CI¼0.9–1.10 (�, nearly additive).B,AD80, a leadpolypharmacologic drug,efficacy also improved in the presence of bortezomib/vorinostat. Dosing, IC50s, CI, and synergism are indicated. C, Phosphoprotein array results of MZ-CRC-1 cellswere treated with indicated drugs in the presence or absence of bortezomib (B, 6 nmol/L), vorinostat (V, 6 nmol/L), and sorafenib (S, 1 mmol/L). Sorafenibtreatment alone led to hyperactivation of almost all phosphoprotein markers on the panel; sorafenib/bortezomib/vorinostat was most effective in suppressingoverall network hyperactivation (bracket, asterisk). Quantitation of phospho-array analysis represented as PRISM software–generated heatmap. These data arerepresented as PRISM scatter plot in Fig. 5C. D, Additional broad-acting inhibitors act as network brakes at low subtherapeutic doses (see Fig. 6F for dose ranges).AUY922/vorinostat and bortezomib/CUDC-907 increased efficacy of different targeted therapies, sorafenib, and AD80. IC50s, CI, and synergism are indicated.






sorafenib resistance in human tumors. We found that indeed theInsR/IGF (26, 27), EGFR (28, 29), Akt (30, 31), Src kinases (32),and multiple RTK's (29) were all pathways contributing to sor-afenib resistance in human cancer cells. In our Drosophila studiesrestraining these pathways innormal and transformed cells, eithergenetically or pharmacologically, correlated with increased sor-afenib efficacy (Fig. 1B and C; Supplementary Fig. S3B–S4D).

Broadening our work, we examined other Ret pathway kinaseinhibitors including trametinib (MEK inhibitor; approved for usein patients with melanoma) and the experimental polypharma-cologic drugs AD57 and AD80 (4, 33). Viability of both control(ptc-GAL4) and ptc>Ret2B flies improved in the presence of eachtargeted therapywhen combinedwith bortezomib and vorinostat(Supplementary Fig. S6A and S6C). We also tested whether otherdrugs inhibiting broad protein networks cooperated at subther-apeutic doses; substituting bortezomib with Hsp90 inhibitorAUY922 and vorinostat with the pan HDAC inhibitor CUDC-907. In Drosophila, AUY922/vorinostat paired with sorafenib,trametinib, AD57, and AD80 to improve viability of both controland ptc>Ret2B flies (Supplementary Fig. S6D) in a manner similarto bortezomib/vorinostat.

Together, these data support amodel inwhich kinase inhibitorssuch as sorafenib, trametinib, as well as polypharmacologicalinhibitors like AD80, etc., promote strong hyperactivation of theoverall cellular network in both transformed and normal tissues,limiting efficacy and promoting toxicity. Drug efficacy is stronglyimproved by restraining broad network hyperactivation throughthe selective use of genetics or through drugs that broadly controlthe cellular network including bortezomib and vorinostat. Thesedrugs act as adjunct treatments to provide a "network brake" to theliabilities of sorafenib at doses well below those required forsignificant efficacy.

Our Western blot data showing that targeted therapeuticsinduced hyperactivation of kinase networks matches findingsfrom previous studies. For example, multiplexed kinase inhibitorbeads and mass spectrometry (MIB/MS) analysis showed thattreatment of tumor cells led to upregulation of the majority ofRTKs, tyrosine kinases, and MAPKs analyzed within 24 hours(34). We hypothesized that our findings may provide a potentialtherapeutic solution to this problem. We therefore next assessedwhether vertebrate cancer cells would respond similarly to "net-work brake" cocktails.

"Network brake" cocktails restrained human thyroid cancernetworks to oppose tumor progression

The MTC cancer cell line MZ-CRC-1 (35) harbors an activatingmutation in Ret analogous to the Drosophila Ret2B mutation.Sorafenib has been previously demonstrated to inhibit MTCcell line growth (36); this efficacy required high-dose treatment(Fig. 2A) or lower doses of polypharmacologic compound AD80(Fig. 2B). MZ-CRC-1 cells treated with sorafenib for 4 hoursshowed inhibition of several intracellular pathway effectorsincluding ERK as assessed by phosphoprotein array (Fig. 2C);overall, a low hyperactivation of the signaling network wasobserved. But four days of chronic sorafenib treatment led to astriking shift: nearly all assayed phosphoproteins were stronglyupregulated (Fig. 2C). Hyperactivation of RTKs such as EGFR,HER2/3, MET, FGFR1 were especially intriguing as these areknown to promote drug resistance in different cancers (37, 38).

Low-dose bortezomib/vorinostat enhanced the growth-inhib-itory effects of sorafenib: low-dose bortezomib plus vorinostat

(6 nmol/L each) reduced sorafenib's IC50 20-fold to achievesimilar efficacy (Fig. 2A), while the IC50 of AD80 was reduced10-fold (Fig. 2B). Bortezomib/vorinostat cotreatment alsorestrained network hyperactivation: EGFR, HER2, MET, FGFR1,and other kinases were at lower levels compared with sorafenibtreatment alone (Fig. 2C). That is, the growth-inhibitory effects ofbortezomib/vorinostat/sorafenib correlated with the drug cock-tail's ability to restrain broad network hyperactivation. Similarly,AUY922/vorinostat as well as bortezomib/CUDC-907, used asadjuncts, also strongly reduced the IC50s of sorafenib as well asAD80 (Fig. 2D; MZ-CRC-1, MTC cell line). Combination Index(CI) computes whether drug combinations work together in asynergistic, additive, or antagonistic manner (5). We found thatthese drug combinations were working synergistically onMZ cells(CI<0.9; Fig. 2A, B, and D; Supplementary Table S2).

Presence of cancer stem cells are associated with resistance inmany cancers (39–41). Stem cell associated transcription factors(STF) like Sox2 are at the apex of multiple pathways of tumor-igenesis, many of them regulating kinase networks like the IGF,EGF, and VEGF pathway (42) and cell-cycle progression compo-nents (43). Another STF, Oct4, binds the PTEN promoter toregulate Akt signaling in cancer cells (43). Oct4/Sox2 can alsoregulate cell-cycle progression indirectly through regulation ofmiRNAs (44). Finally, focal adhesion kinase (FAK) componentPEAK1 increases Oct4, Nanog, and cMyc levels to promote 3Dtumor sphere growth in pancreatic cancer, indicating a morecomplex relationship between kinase signaling networks andSTFs. Thus, currently there is a significant effort to identify ther-apies that can regulate stemness in cancer (45) and we nextexplored the effects of the therapies we identified on STFs.

MZ-CRC-1 cells treated chronically with sorafenib upregulatedlevels of Sox2 (Fig. 3A), a stem cell fate marker previouslydemonstrated to promote a broad program of tumorigenesis(42, 46). Importantly, expression of Sox2was strongly suppressedby addition of bortezomib alone or a bortezomib/vorinostat drugcombination (Fig. 3A). Similar results were observedwith TT cells,MTC-derived cells that harbor the oncogenic Ret isoformRetC634W: chronic sorafenib treatment had a moderate inhibitoryeffect on cell growth and signaling while promoting stem cellmarkers Sox2 (strongly) and c-Myc (moderately; Fig. 3B–D,Supplementary Fig. S7A–S7C, quantitation). Sox2 levels weresuppressed by bortezomib and, to a lesser extent, by bortezo-mib/vorinostat (Fig. 3B and D; Supplementary Fig. S7C, quanti-tation). Importantly, bortezomib/vorinostat prevented accumu-lation of nuclear Sox2 (Fig. 3D) in TT cells, indicating that despitemodest effects on overall protein levels, the treatment preventsenrichment in the nucleus, where Sox2 is required. Finally,cotreatment led to strong progressive upregulation of cleavedPARP in both MZ-CRC-1 and TT cells (Fig. 3B and C), indicatinga significant increase in apoptotic cell death. Finally, in TT cells,the effect on broad kinase networks was similar, as sorafenibcotreatment with bortezomib alone or bortezomib/vorinostatfurther decreased overall levels of phosphoprotein network (Sup-plementary Fig. S7A and S7B).

In whole-animal experiments, growth of established TT cellmouse xenografts were potently inhibited with sorafenib/borte-zomib/vorinostat compared with vehicle or sorafenib/bortezomibtreatments. Treating with all three drugs together inhibited tumorgrowth and, in some animals, induced tumor regression (Fig. 3Eand F; Supplementary Fig. S7D). Of note, sorafenib workedpotently at 40mg/kg in combination with bortezomib/vorinostat,

Das et al.





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Network brake drug cocktails restrained induction of stem cell markers.A,MTT viability assay curves indicate that bortezomib/vorinostat reduced viability of TT cellsat moderate aswell as high doses of sorafenib, including significant reduction of IC50. IC50s are in parentheses; doses of bortezomib (0.75 nmol/L and 2 nmol/L) andvorinostat (0.75 nmol/L and 2 nmol/L) are indicated. IC50s, CI, and synergism are indicated. B, Western blot analysis of MZ-CRC-1 cells demonstrating thatbortezomib/vorinostat restrained sorafenib-induced hyperactivation of the cancer stem cell marker Sox2. Levels of other stem cell markers Oct4, Nanog, and cMycwere reduced by the triple combination compared with untreated cells. Drug combinations promoted strong upregulation of the cell death marker cPARP.Data are quantitated in Supplementary Fig. S7C. C,Western blot analysis of TT cells demonstrating that sorafenib induced elevation of stem cell marker cMyc, andbortezomib/vorinostat restrained this activation. The triple-drug combination also reduced levels of Oct4 and Nanog compared with untreated cells. Sorafenib alsoinduced Sox2 levels, which were suppressed moderately by bortezomib and, to a lesser extent, by bortezomib/vorinostat. The triple-drug combination stronglypotentiated sorafenib-induced upregulation of cPARP. Data are quantitated in Supplementary Fig. S7C, with pixel densitometric analysis values of Sox2 indicated.D,Immunofluorescence staining showing that sorafenib-treated TT cells upregulated levels of nuclear Sox2. This upregulation was blocked in cells treated withsorafenib (0.5mmol/L) plus bortezomib (2 nmol/L) plus vorinostat (2 nmol/L). Higher doses of bortezomib/vorinostat (4 nmol/L each and6nmol/L each) completelysuppressed sorafenib-induced upregulation of Sox2 (Supplementary Fig. S9A). E, Subcutaneous mouse xenograft assays using human TT cells showing medianrelative tumor growth of: (i) vehicle-treated controls, (ii) sorafenib (S; 40 mg/kg) þ bortezomib (B; 0.05 mg/kg)-treated, and (iii) sorafenib (40 mg/kg) þbortezomib (0.05 mg/kg) þ vorinostat (V; 10 mg/kg)-treated animals. Eight animals for vehicle treatment and five each for drug treatments were used to analyzerelative tumor growth, defined as the difference betweenmedian size of tumors at initiation of drug dosing to indicated timepoints. F, Relative growth of each tumorfor each treatment class at the end of the experiment in E represented as a column graph plot. The mean relative growth of each class was compared for statisticallysignificant differences using Student t test (Welch correction). Asterisks indicate two animals in SþBþV group showing tumor regression.






a concentration lower than many previous xenograft studies (47,48). Higher doses of sorafenib treatment alone, at 60 mg/kg, alsoinduced tumor regression, which was further enhanced in thepresence of bortezomib/vorinostat (Supplementary Fig. S7Eand S7F). This indicated the usefulness of using bortezomib/vorinostat across a range of sorafenib doses in mouse whole-animal models. Together, these data indicate that, similar toour whole-animal Drosophila data, broadly acting cocktails thatinclude combinations such as bortezomib/vorinostat can act as"network brakes" in at least two thyroid cancer paradigms.

Bortezomib/vorinostat was effective against multiple cancercell types

To assess the broader applicability of our results, we assembleda panel of cancer cell lines with defined genetic mutations thatrespond to different targeted kinase inhibitors. The NSCLC cellline H358 exhibits high EGFR activity and is sensitive to erlotinib,an EGFR inhibitor approved for NSCLC (49, 50). Chronic erlo-tinib treatment led to progressive hyperactivation of the kinasenetwork as assessed by phospho-kinase array analysis; this effectwas suppressed and the IC50 of erlotinib reduced significantly in

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Figure 4.

Network brake drug cocktails restrained lung cancer cell networks. A, H358 cells were treated with indicated drugs in the presence or absence of bortezomib(B; 6 nmol/L), vorinostat (V; 50 nmol/L), and erlotinib (E; 1 mmol/L). Erlotinib induced hyperactivation of various phosphoproteins, which was restrained in thepresence of bortezomib/vorinostat (bracket, asterisk). Quantitation of phospho-array analysis represented as PRISM software–generated heatmap. The data arerepresented as PRISM scatter plot in Fig. 5C. IC50s, CI, and synergism are indicated. B, H1299-NSCLC cells treated with targeted therapy, trametinib, or trametinib incombination with low-dose network brake drugs bortezomib (B, 0.25 nmol/L)/vorinostat (V, 0.25 nmol/L). Heatmap generated as in A. Trametinib inducedhyperactivation of many phosphoproteins, which was restrained in the presence of bortezomib/vorinostat (bracket, asterisk). A rare signal showed higher levels inthe presence of three drugs (pAKT-308). The data are represented as PRISM scatter plot in Fig. 5C. C, An MTT viability assay demonstrated that bortezomib/vorinostat significantly lowered the IC50 (in parentheses) of erlotinib on H358 cells and trametinib on H1299 cells. The 3-drug combination doses were the sameas the ones used in A and B above. D, Western blot analysis of H358 cells shows that the bortezomib/vorinostat combination restrained erlotinib-inducedupregulation of Sox2. Erlotinib also upregulated cMyc,whichwasmoderately reduced by bortezomib/vorinostat. Other stem cellmarkerswere kept belowuntreatedlevels, including EMTmarker vimentin. The cell death marker cPARP was significantly upregulated in the presence of bortezomib and maintained at similar levels toerlotinib treatment alone by bortezomib/vorinostat combination.

Das et al.





the presence of bortezomib/vorinostat. A similar pattern wasobserved with the NSCLC cell line H1299, which contains anoncogenic isoform of K-RAS: the approved standard-of-care drugtrametinib led to network hyperactivation that was restrained bybortezomib/vorinostat (Fig. 4A–C). In each case, this restraintcoincided with an increase in efficacy.

Regarding stem cell markers, erlotinib-treated H358 NSCLCcells showed upregulation of Sox2 and c-Myc. Cotreatment with

bortezomib/vorinostat restrained Sox2 activation quite effectivelyas well as c-Myc levels weakly. In addition, stem cell marker,LIN28, as well as epithelial-to-mesenchymal marker vimentinwere both kept below untreated levels with bortezomib/vorino-stat cotreatment (Fig. 4D). In H1299 cells, levels of stem cellmarkers c-Myc, KLF4, and EMTmarker vimentin were reduced bytreating with trametinib/bortezomib/vorinostat (SupplementaryFig. S8A and S8B) while in the HCC cell line HepG2 stem cell

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Figure 5.

Network brake drug cocktails restrained multiple cancer cell networks. A,MTT viability assays of indicated cell lines with indicated drugs and doses. Trametinib (T);BEZ235 (BEZ); bortezomib (B); vorinostat (V). Bortezomib and vorinostat doses are in nmol/L. IC50s are in parentheses, and CI and synergism are indicated.B, IC50s of various kinase inhibitor drugs on different cancer lines were lowered significantly in the presence of indicated dose of bortezomib/vorinostat (fromFigs. 2A, 4C, and 5A). S, sorafenib; E, erlotinib; T, trametinib; BEZ, BEZ235; V, vemurafenib. C, Scatter plot (PRISM) summary of phosphoprotein array data onindicated cancer lines treated with sorafenib (S), erlotinib (E), trametinib (T) alone or in combination with bortezomib/vorinostat. Each phosphoprotein signal wascompared between treatments, and median level of entire network is indicated with blue line; interquartile range is indicated. Bortezomib/vorinostattreatment consistently reducedmedian phosphoprotein level of each cancer network. Paired t tests (PRISM) between single- and triple-treated samples for each cellline indicated P values <0.05 (asterisks).






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Network brake drug cocktails delayed emergence of resistance. A, H358 cells treated chronically with 1 mmol/L erlotinib for 65 days developed resistance to erlotinib(IC50 ¼ 4 mmol/L). Cells treated with erlotinib þ bortezomib (6 nmol/L) þ vorinostat (50 nmol/L) retained erlotinib sensitivity similar to the parental line. IC50s inparentheses. For these experiments, when single-drug–treated cells (erlotinib or vemurafenib) started growing similar to DMSO control cells, the drug-resistant cells aswellas the triple-drug–treated cells were further amplified for three generations in the absence of any treatment. This allowed the drug-resistant cells and triple-drug cocktail–treated cells to grow to sufficient numbers for the various assays, that is, phospho-kinome array, Western blot analysis, and MTT viability assay. B, Phase contrastimages provide examples from A. Only erlotinib/bortezomib/vorinostat treatment strongly reduced cell number. See Materials and Methods for how triple-drug–treatedcells were amplified and tested. C, Parental, erlotinib resistant, and erlotinib/bortezomib/vorinostat (EþBþV) treated cell lysates analyzed on phosphoprotein arrays.Outlined in red are phosphoproteinswhose levels showmuch higher signals in the resistant line comparedwith the other two cell treatment conditions. Identities are listedbeneath boxes; for example c-Met is a protein known to promote resistance to erlotinib treatment in NSCLC (37).D,Western blot analysis of lysates fromerlotinib-resistantH358 NSCLC cells. Resistant lines (res.) upregulated Sox2, RhoA, and active-b-catenin; erlotinib/bortezomib/vorinostat treatment kept these below parental H358 cells,while increasing activity of the tumor suppressor MOB. Active histone marks H3K9-Ac, H3K4-Me3, and H4K5-Ac were upregulated in erlotinib-resistant cells.Erlotinib/bortezomib/vorinostat blocked this upregulation while elevating the repressive mark H3K27Me3. E, Phase contrast images of 239-melanoma cells lines treatedwith the indicated conditions for 120 days. Cells treatedwith 0.5 mmol/L vemurafenib developed resistance to the drug and grew confluently similar to the parental line. The239 cells treated continuouslywith combined vemurafenib/bortezomib/vorinostat (0.5 mmol/L, 6 nmol/L, and 50 nmol/L, respectively) displayedminimal growth over 120daysof culturing. The combinationofbortezomib/vorinostat (6nmol/L, 50nmol/L)without targeted therapyvemurafenibgrewsimilar to untreatedparental lines.F,Drug–responsecurve foreachnetworkbrakedrugas single agents—vorinostat, bortezomib, CUDC-907,AUY922—onvariousdifferent cancer cell lines tested inour study. Shadedgray-boxed area indicates low nanomolar doses used for each of these drugs in these studies. At these doses, individual network brake drugs have very little effecton cancer cell line viability. Relevant viability assay results for network brake drug combinations by themselves on cancer lines provided in Supplementary Fig. S9B.

Das et al.





markers Oct4, Nanog, c-Myc, and EMT marker vimentin werereduced by trametinib/bortezomib/vorinostat (SupplementaryFig. S8C and S8D). In each cell line, high levels of cleaved PARPwere observed with bortezomib/vorinostat cotreatment indicat-ing increase in apoptotic death.

Broadening our survey, we tested whether bortezomib/vorino-stat cotreatment improved the efficacy of kinase inhibitors thattargeted deregulated pathways in other cancer cells. Synergy wasobserved with A549 cells (NSCLC), HepG2, and PLC5 (hepato-cellular carcinoma), T47D (ERþ breast cancer), and A375(melanoma; Fig. 5A and B). The IC50s of each standard-of-caretargeted therapy was lowered significantly in the presence ofbortezomib/vorinostat, ranging from modest reduction (5-foldin BEZ235-treated T47D cells) to more potent reduction (83-foldin trametinib-treated H1299 cells; Fig. 5B). We found the medianlevel of the phospho-kinase network in the MTC and the NSCLCcells demonstrated a similar trend: presence of bortezomib/vor-inostat as adjuncts restrained hyperactivation of the kinase net-work in each cell type (Fig. 5C), tracking with the increase inefficacy of the triple drug combinations. We conclude that inDrosophila and in human cancer cells, restraining the overallactivity of the kinase network led to better drug efficacy.

Together, these results indicate that, across a large number ofhuman cancer cell types, bortezomib/vorinostat cotreatmentenhanced efficacy of established therapies by restraining net-work hyperactivation and reducing levels of protumorigenicmarkers.

Bortezomib/vorinostat restrained emergence ofdrug resistance

Cancer cells lose sensitivity to targeted kinase inhibitor thera-pies by upregulating multiple cellular kinases and RTKs, leadingto drug resistance (51). As bortezomib/vorinostat cotreatmentrestrained hyperactivation of kinase networks, we hypothesizedthat it would also delay or prevent drug resistance over extendedtreatment periods.

Cellular resistance to erlotinib in the clinic and in NSCLChuman cancer cells such as H358 have been well documented(52, 53). H358 cells became insensitive to erlotinib by approx-imately 35 days of chronic treatment: parental cells had an IC50 of0.5 mmol/L, while resistant lines displayed an 8-fold increase to4 mmol/L (Fig. 6A and B). Chronic cotreatment with erlotinib/bortezomib/vorinostat prevented resistance: H358 cells retainedsensitivity to erlotinib similar to parental cells (Fig. 6A and B; IC50

of 0.7 mmol/L).We used phospho-kinase array analysis to explore the

mechanisms by which bortezomib/vorinostat blocked drugresistance. Erlotinib-resistant H358 NSCLC cells showed upre-gulation of a large network of kinases when compared with theparental cell line (Fig. 6C). This included ERBB3, Met, c-Kit, Src,and Stat3, pathway effectors associated with drug resistance(37, 38, 54, 55), suggesting that broad network upregulationcontributes to cellular resistance. Consistent with this view,erlotinib-resistant cells that upregulated Met were almost 3-foldmore responsive to the Met inhibitor crizotinib (Supplemen-tary Fig. S8E). Erlotinib-resistant cells also showed increasedlevels of Sox2 and activation of protumorigenic proteins suchas b-Catenin and RhoA. The combination erlotinib/bortezo-mib/vorinostat prevented these increases (Fig. 6D). Interest-ingly, the three-drug combination elevated levels of phosphor-ylated Mob, a key effector of the Hippo signaling pathway that

suppresses growth (Fig. 6D; Supplementary Fig. S8F and S8G;ref. 56). Similar effects were observed with Mel-239, a mela-noma cell line harboring oncogenic BRAFV600E: 90 days oftreatment led to resistance to the standard-of-care drug vemur-afenib, while bortezomib/vorinostat–treated cells retained sen-sitivity (Fig. 6E), but we did not explore the molecular mech-anism underlying resistance in these cells.

HDAC inhibitors such as vorinostat alter histone modifica-tions to exert broad effects on transcription (57) and canrestrain stem cell markers in different cancers (58, 59) as wellas oppose tumorigenic states by restoring epithelial markers(60). We examined whether alterations in histone modifica-tions could contribute to the broad network changes provokedby targeted therapies. Erlotinib-resistant lines showed strongupregulation of the active histone mark H3K9-Ac and moderateactivation of the active marks H4K5-Ac and H3K4-Me3(Fig. 6D). Treatment with erlotinib/bortezomib/vorinostatexhibited strongly reduced levels of these active marks andelevated levels of the inactive histone mark H3K27-Me3(Fig. 6D). An important finding of these studies is that lowdoses of "network brake" drugs as single agents (Fig. 6F) or incombination with other "network brake" drugs (Supplemen-tary Fig. S9A and S9B) did not significantly affect cancer cellviability. In summary, addition of bortezomib plus vorinostatin our long-term experiments directed the histone code towardlowered transcription, prevented upregulation of overall cellu-lar network activity, and achieved a balance of low protumori-genic and high tumor suppressor signals.

DiscussionPreclinical and clinical cancer studies show that resistance

eventually emerges even with kinase inhibitors with high targetselectivity (61). Cancer cells respond to inhibition of oncogene-addicted pathways by finding alternative mechanisms to pro-vide high signaling through these addicted pathways, or byshifting their dependence to other pathways (62). For example,at least six different mechanisms by which cancer cells developresistance to drugs targeting BRAFV600E have been identified(61, 63). This highlights the adaptability and high degree ofconnectivity within the kinase signaling network: inhibitingsignaling in one part of the network provokes responses inother parts (Fig. 7, model).

Our current findings suggest one path toward addressingthese major challenges in cancer therapeutics. Using "networkbrake" drugs as part of a cocktail would allow standard-of-carekinase inhibitors to be used at lower doses over longer periods.This would reduce the toxicity that may result from both strongon-target inhibition as well as off-target effects. In our analysis,the IC50s of at least five different kinase inhibitors were reducedconsiderably in the presence of low-dose bortezomib plusvorinostat. Furthermore, sorafenib/bortezomib/vorinostatinhibited tumor growth in xenografted mice at low doses,indicating that sorafenib, and perhaps other targeted therapies,can work potently in vertebrate models if paired with at leastone "network brake" cocktail.

Restraining network hyperactivation prevented upregulation ofstem cell markers, most prominently Sox2, a factor that controlsstem cell fate during development and in cancer progressionincluding EMT (42, 46, 64). In some cancer cells, restraining thenetwork reduced other stem cell markers like Oct4, Nanog, and c-






Myc below untreated levels, suggesting these combinationsreduce overall "stemness." A recent study found that therapy-induced upregulation of cellular components such as integrinscontribute to "stemness" and drug resistance, a condition thatwasrestrained by cotreatment with bortezomib (65). By allowingtargeted therapies to function at lower doses, by restraininghyperactivation of the signaling network, by preventing the upre-gulation of stem cell markers, and by promoting increased deathof cancer cells, "network brake" drugs hold the potential forimproving the therapeutic index and longevity of a broad palateof targeted therapies (Fig. 7, model). One practical use of ourfindings could be for monitoring effectiveness of cancer therapy.Using phospho-kinome arrays or simpler assays such as serial

Western blots or single-cell Western blots (66), would provide awindow into how cancers cells' signaling network respond totreatment. Treatment-induced broad cellular network hyperacti-vationwould indicate limited therapeutic benefits in the long run.

Our findings indicate that low doses of "network brake" drugsas single agents or in combination with other "network brake"drugs do not significantly affect cancer cell viability. The thera-peutic potential of "network brake" drugs at these doses becameapparent only when they were paired with optimal doses of thetargeted therapies. For example, previous studies have shown thatthe combination of bortezomib plus vorinostat is effective againstmultiple myeloma and other cancers, although at significantlyhigher doses (25, 67, 68). Our studies indicate a potential

EFFECT OUTCOMESTRATEGY

Targetedtherapy

(e.g., sorafenib)

• Low efficacy• Toxicity in

normal cells• Drug resistance

in tumors

• Increased efficacy• Reduced toxicity• Suppression of

resistance

Activationof kinasenetwork

Restrainsactivation

= Low-dose of broad-actinginhibitors

= Targeted inhibition

Targeted therapy+

Networkbrakes (NB)

MODEL

NB drug A

NB drug B

Figure 7.

Model: an approach to increase efficacy of targeted cancer therapeutics. Targeted therapeutics, for example, sorafenib, inhibit a number of kinases (red circles;strategy), but over the course of treatment, cancer cells respond by hyperactivation of large number of kinases (effect). This provides cancer cells avenuesfor resistance to therapy, but is also the source of toxicity in normal cells (outcome). Inclusion of low doses of broad-acting "network brake" drugs (gray),as an adjunct to targeted therapy could directly or indirectly restrain the hyperactivation of different cellular kinase subgroups. The effect is bettertreatment with high efficacy, low toxicity, and potentially less drug resistance. Generation of rendered kinome tree with target inhibition pattern explainedin Materials and Methods.

Das et al.





mechanism as to how these drugs potentiate the effects of targetedtherapies at lowdoses. Cancer cells rely on a subset of the availablecellular signaling pathways, a phenomenon termed "oncogeneaddiction." The mechanism by which cancer cells undergo apo-ptotic deathwhen addictedpathways are inhibited is unclear.Onetheory is that cancer cells are reliant on fewer signaling pathwaysand therefore inhibition of the addicted pathways sends cancercells into crisis thereby hastening death (69, 70). We and othershave shown that targeted therapies can hyperactivate the overallcellular network; this may allow cancer cells to shift dependenceto other pathways, providing a route for resistance (71). Ourstudies suggest that long-term treatment with "network brake"drug combination directed the histone code towards loweredtranscription, which could be one possible way to prevent upre-gulation of overall cellular network activity. By restraining hyper-activation of the network in response to targeted therapies, the"network brake" drugs may block this alternative path. Broadly-acting drugs such as bortezomib and vorinostat can act onmultiple targets; the most relevant target (s) can be difficult toidentify. Furthermore, the "network brake" drugs may not alwaysact solely through their intended targets, but our study shows thatthepresence of thesedrugs consistently restrains thebroad cellulareffects elicited by a broad palette of targeted therapies.

This study has identified multiple "network brake" drugs thatcan improve efficacy of targeted therapies: bortezomib (protea-some), vorinostat, and CUDC-907 (histone deacetylases),mithramycin (Sp1 transcriptome), and AUY922 (Hsp90 inhibi-tor). Other classes of broadly acting drugs—targeting cell cycle,metabolism, cytoskeleton, proteases, topoisomerases, mitochon-dria, etc.—may also prove useful. Currently, there are approxi-mately 15,000 cancer clinical trials involving combinations oftargeted therapies. One challenge will be to match specific "net-work brake" cocktails to particular tumors based on the details of

the tumor network. Using a whole-animal approach will permitus to address the effects of these powerful drugs on transformedcells and, importantly, on normal untransformed tissue.

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

Authors' ContributionsConception and design: T.K. Das, R. CaganDevelopment of methodology: T.K. Das, J. EsernioAcquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): T.K. Das, J. EsernioAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): T.K. Das, J. Esernio, R. CaganWriting, review, and/or revision of the manuscript: T.K. Das, R. CaganAdministrative, technical, or material support (i.e., reporting or organizingdata, constructing databases): T.K. Das, J. EsernioStudy supervision: T.K. Das, R. Cagan

AcknowledgmentsWe thank members of the Cagan laboratory for technical assistance and for

helpful discussions. We thank the Bloomington Drosophila Stock Center forDrosophila reagents.Microscopywas performed in part at theMicroscopy SharedResource Facility at the Icahn School of Medicine at Mount Sinai. The authorsalso thank Ran Brosh, Emily Bernstein, Stuart Aaronson, and Barry Nelkin forhuman cancer cells. This research was supported by NIH grants R01-CA170495and R01-CA109730, Department of Defense grant W81XWH-15-1-0111,and American Cancer Society grants 120616-RSGM-11-018-01-CDD (to R.L.Cagan) and 120886-PFM-11-137-01-DDC (to T.K. Das).

The costs of publication of this articlewere defrayed inpart by the payment ofpage charges. This article must therefore be hereby marked advertisement inaccordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received July 10, 2017; revised October 4, 2017; accepted May 21, 2018;published first May 29, 2018.

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2018;78:4344-4359. Published OnlineFirst May 29, 2018.Cancer Res Tirtha K. Das, Jessica Esernio and Ross L. Cagan Improves Efficacy and Reduces Cellular ResistanceRestraining Network Response to Targeted Cancer Therapies

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