notch-induced myeloid reprogramming in spontaneous … · notch-induced myeloid reprogramming in...

Tumor Biology and Immunology

Notch-Induced Myeloid Reprogramming inSpontaneous Pancreatic Ductal Adenocarcinomaby Dual Genetic TargetingPhyllis F. Cheung1,2, Florian Neff1,2, Christian Neander1,2, Anna Bazarna1,2,Konstantinos Savvatakis1,2, Sven-Thorsten Liffers1,2, Kristina Althoff1,2, Chang-Lung Lee3,Everett J. Moding3, David G Kirsch3, Dieter Saur2,4, Alexandr V. Bazhin5,6,Marija Trajkovic-Arsic1,2, Mathias F. Heikenwalder7, and Jens T. Siveke1,2,4

Abstract

Despite advances in our understanding of the genetics ofpancreatic ductal adenocarcinoma (PDAC), the efficacy oftherapeutic regimens targeting aberrant signaling pathwaysremains highly limited. Therapeutic strategies are greatly ham-pered by the extensive desmoplasia that comprises heteroge-neous cell populations. Notch signaling is a contentiouspathway exerting opposite roles in tumorigenesis dependingon cellular context. Advanced model systems are needed togain more insights into complex signaling in the multilayeredtumor microenvironment. In this study, we employed a dualrecombinase-based in vivo strategy to modulate Notch signal-ing specifically in myeloid cells to dissect the tumorigenic roleof Notch in PDAC stroma. Pancreas-specific KrasG12D acti-vation and loss of Tp53 was induced using a Pdx1-Flp trans-gene, whereas Notch signaling was genetically targeted using amyeloid-targeting Lyz2-Cre strain for either activation of

Notch2-IC or deletion of Rbpj. Myeloid-specific Notch acti-vation significantly decreased tumor infiltration byprotumori-genic M2 macrophages in spontaneous endogenous PDAC,which translated into significant survival benefit. Further char-acterization revealed upregulated antigen presentation andcytotoxic T effector phenotype uponNotch-inducedM2 reduc-tion. This approach is the first proof of concept for genetictargeting and reprogramming of myeloid cells in a complexdiseasemodel of PDAC and provides evidence for a regulatoryrole of Notch signaling in intratumoral immune phenotypes.

Significance: This study provides insight into the role ofmyeloid-dependent NOTCH signaling in PDAC and accent-uates the need to dissect differential roles of signaling path-ways in different cellular componentswithin the tumormicro-environment. Cancer Res; 78(17); 4997–5010. �2018 AACR.

IntroductionPancreatic ductal adenocarcinoma (PDAC) is one of the most

aggressive malignancies with no effective therapeutic options forlong-term tumor control thus far. Therapeutic targeting of PDACfocusing on deregulated molecular signaling pathways in cancercells has been largely disappointing. One of the hallmarks ofPDAC is the presence of extensive desmoplasia, which comprisesheterogeneous cell populations including fibroblasts, immune

cells, and extracellular matrix (1, 2). Recent studies have revealedcrucial role of stromal components in promoting the inductionand progression of tumorigenesis (1, 3–5). Comprehensive stud-ies on differential roles of signaling pathways in regulating tumorcells and stromal components in PDAC will advance our under-standing of the complicated pathogenesis.

Notch signaling is a key developmental pathway that is knownto regulate cell proliferation, apoptosis, as well as tumorigenesisof various solid tumors including pancreatic cancers (6–8). How-ever, the role of Notch signaling in PDAC still remains highlycontentious. Notch receptors and ligands, and their downstreamtargets have been frequently reported to be overexpressed inPDAC, suggesting a role in PDAC development and progression(7, 9). Activation of Notch1-IC led to the progression ofpreneoplastic lesions in a genetic mouse model (10), whileanother study showed that genetic ablation ofNotch1 in a mousemodel of KRAS-induced PDAC resulted in an increase in high-grade pancreatic intraepithelial neoplasia (PanIN) lesions (11).We described an oncogenic role of Notch2 but not Notch1 inregulating PanIN progression and tumor differentiation (12).Notably, phase II clinical trials assessing the use of blockingantibodies against Notch2/3 or the Notch ligand Dll4 in combi-nation with chemotherapy have reported no benefit or evendetrimental outcomes (13, 14), therefore casting doubts ontothe efficacy of Notch as a therapeutic target in PDAC.

Given the importance of stromal components in tumorigene-sis, Notch might exert either oncogenic or tumor-suppressive role

1Division of Solid Tumor Translational Oncology, West German Cancer Center,University Hospital Essen, Essen, Germany. 2German Cancer Consortium (DKTK,partner site Essen) and German Cancer Research Center, DKFZ, Heidelberg,Germany. 3Department of Radiation Oncology, Duke University Medical Center,Durham, North Carolina. 4Medical Department, Klinikum rechts der Isar, Tech-nische Universit€at M€unchen, Munich, Germany. 5Department of General, Visceraland Transplant Surgery, Ludwig-Maximilians University, Munich, Germany.6German Caner Consortium (DKTK), Partner Site Munich, Germany. 7Divisionof Chronic Inflammation and Cancer, DKFZ, Heidelberg, Germany.

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

P.F. Cheung and F. Neff are co-first authors of this article.

Corresponding Author: Jens T. Siveke, West German Cancer Center and DKTKpartner site Essen, University Hospital Essen, Hufeland, Essen 45147, Germany.Phone: 4920-1723-3704; Fax: 4920-1723-6725; E-mail: [email protected]

doi: 10.1158/0008-5472.CAN-18-0052

�2018 American Association for Cancer Research.

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depending on cellular context. Indeed, impairment of Notchsignaling in epidermis and fibroblasts was shown to result inprofound changes in stroma, leading to induction of tumordevelopment (15, 16). Increasing evidence has indicated that theNotch-mediated tumor suppression might be at least partiallymediated by regulating inflammation in the tumor microenvi-ronment (15, 17). Ablation of Notch in mice significantly upre-gulated proinflammatory cytokine expression (18, 19). Intrigu-ingly, deletion or inactivation of Notch signaling induced inflam-matory responses, which suppressed tumorigenesis through theantitumor function of T cells present in the inflammatory milieu(20, 21). Collectively, these studies demonstrated that Notchsignaling in stromal cells could induce tumor-suppressive effectsthrough mediating inflammation in the tumor microenviron-ment. However, precise cellular and molecular mechanismsunderlying these phenomena still need further examination.

Tumor-associated macrophages (TAM) represent the mostabundant immune cell population in the tumor microenviron-ment, and dysregulated polarization facilitates tumor growth andmetastasis of PDAC (22–24). In patients with PDAC, increasedtumor-promoting M2 TAMs are associated with significantlyshorter patient survival (25–28). Recently, Notch signaling wasshown to regulate myeloid cell differentiation (29), potentiallyvia transcriptional repression of M2-associated genes by Notchactivation (30), and upregulation of M2-associated genes viaposttranslational modification of IRAK2 (31). However, the rel-evance of these findings in complex diseasemodels of cancer suchas in PDAC has not been addressed so far. Moreover, the role ofNotch signaling in myeloid cells in tumor formation and pro-gression has not been investigated.

To study the context and spectrum of immune–tumor inter-actions, endogenous immunocompetent tumor models arenecessary. Genetically engineered mouse models based onpancreas-specific activation of oncogenic KRAS resemblehuman PDAC in many aspects including formation of anextensive fibro-inflammatory stromal reaction (32). To targetnonpancreatic and nontumoral cell lineages, Schonhuber andcolleagues introduced a dual-recombinase approach using aPdx1-Flp transgene to target KRAs and Tp53 (33), allowingselective Cre-based targeting of the tumor microenvironment.In this study, we investigated the role of Notch signaling inTAM polarization in PDAC development and progression usinga dual-recombinase gene targeting strategy as a genetic proof-of-concept approach.

Materials and MethodsMouse strains and tumor models

Unless otherwise stated, Ptf1awt/Cre;Kraswt/LSL-G12D;p53fl/fl (CKP)was used as tumor model of spontaneous PDAC for phenotypiccharacterization and quantification of immune cells. For the dual-recombinase system, a myeloid-specific Cre-line (Lyz2wt/Cre) wascrossed to R26wt/LSL-N2IC and Rbpjfl/fl mice (34, 35). Lyz2wt/Cre;R26wt/LSL-N2IC (Lyz2;N2IC) and Lyz2wt/Cre;Rbpjfl/fl (Lyz2;Rbpj)lines were crossed to the Pdx1-Flp;Kraswt/FSF-G12D;p53frt/frt (FKP)or Pdx1-Flp;Kraswt/FSF-G12D;p53wt/frt (FKPhet) model. Details oforiginal and interbred mouse strains are listed in SupplementaryTable S1A and S1B. All animal protocols were performed accord-ing with appropriate guidelines and the experimental protocolswere approvedby the local AnimalUse andCareCommittee at theKlinikum Rechts der Isar of the TU M€unchen, Germany.

Isolation of bone marrow–derived cells and macrophagedifferentiation

Bone marrow–derived cells were isolated from femur and tibiaofmice aged between 6 and 12weeks. Bonemarrowwas collectedby flushing with RPMI medium (Life Technologies). Red bloodcells (RBC) were lysed with RBC Lysing Buffer (Sigma-AldrichGmbH) for 5 minutes at room temperature, washed, and thenresuspended in macrophage medium (RPMI, 15% FBS, 5% horseserum, 1% NEAA, 1% sodium pyruvate; Life Technologies) con-taining 50 ng/mL murine M-CSF (PELOBiotech) for 7 days. Theuncoated surface of petri dishes allows attachment of highlyadherent cells as macrophages, while floating cells were removedby rinsing with PBS. Macrophage phenotype and purity wereassessed based on CD11b and F4/80 expression using flowcytometry.

Induction of Cre-dependent LoxP site recombination andpolarization in vitro

Bone marrow–derived macrophages (BMDM) were treatedwith 1 mmol/L recombinant NLS-His-Tat-NLS-CRE protein (36)in serum-free RPMImedium1:1 diluted in PBS overnight. Culturesupernatant was removed the next day and then changed tocomplete macrophage medium. To induce M1 polarization, cellswere treated with 1 mg/mL LPS (Sigma-Aldrich) for 6 or 24 hours,whereas for M2, cells were treated with 10 ng/mL recombinantmurine IL4 (eBioscience) for 72 hours.

Isolation of tumor cells from endogenous PDACTumorswereminced and thendigested in 1mg/mL collagenase

type V (Sigma-Aldrich GmbH) for 45 minutes at 37�C. The cellswere filtered through a 100-mm cell strainer. RBCs were lysed byRBC lysing buffer for 5 minutes at room temperature. Cells werethen washed, filtered through 40-mm cell strainer, and subject tosubsequent experiments.

Flow cytometric analysis and cell sortingMulticolor flow cytometry experiments were performed using

Beckman Coulter Gallios flow cytometer (Beckman Coulter),while cell sorting was performed using BD FACSAria III (BDBiosciences). All samples were incubated with CD16/32 antibody(BD Biosciences) to block unspecific FC receptor–mediated anti-body binding prior to antibody incubation. Dead cells wereexcluded by stainingwith Fixable ViabilityDye 780 (eBioscience),LIVE/DEAD Fixable Yellow stain (Life Technologies), or propi-dium iodide (PI) (Clontech). For intracellular staining, cells werefixedwith 2%PFA/PBS after extracellular staining. Cells were thenpermeabilized with 0.5% Saponin/PBS prior to antibody incu-bation. For FOXP3 staining, the Foxp3/Transcription Factor BufferSet (eBioscience) was applied. After washing, cells were subjectedto flow cytometric analysis. The antibody list is shown inSupplementary Table S2. Raw data were analyzed using FlowJosoftware version 7.5.5 (Tree Star Inc.).

IHCIHC staining was performed using the Dako REAL Alkaline

Phosphatase or Peroxidase Detection System (Dako), followingthe manufacturer's instructions. Antigen retrieval on formalin-fixed paraffin-embedded (FFPE) sections was performed by heat-induced epitope retrieval using citrate buffer (pH6) for CD11b,hCD2, MRC1, NK1.1, collagen, MHCII, CD11c and CD80;Tris/EDTA (pH9) for CD3, CD4, CD8, Eomes, T-bet and Lag3,

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and proteinase K treatment for F4/80. After blocking with serum-free protein blocking solution (Dako), slides were incubated forprimary antibodies for 1 hour at room temperature, secondaryantibody for 30minutes at room temperature, and then subjectedto Fast Red or DAB chromogen development. The antibody list isshown in Supplementary Table S3. Slides were then counter-stained with hematoxylin, dehydrated, and mounted. Stromalcontent and acinar cellsweredeterminedbyMovat's pentachromestaining following themanufacturer's protocol (modified accord-ing to Verhoeff, Morphisto GmbH).

Slides were scanned and digitalized by Zeiss Axio Scanner Z.1(Carl Zeiss AG) with 5� and 10� objective magnification. Thepercentage of positive cells for IHC staining, while the area ofcollagen, stroma (ground substance/mucin stained bluish, colla-gen stained yellowish) and/or acinar cells (deep red) for Movat'spentachrome staining were quantified by Definiens (DefiniensAG) as the average of 5 representative fields (10� objectivemagnification) captured from each tissue section of each mouse.For quantification, total number of cells in each field was deter-mined based on nuclei staining (hematoxylin for IHC; DAPI forimmunofluorescence staining) detected by the software. Theaverage number of positive cells (percentage in total number ofcells in each field) from the 5 representative fields was taken as thepercentage of positive cells for each individual mouse. For quan-tification of Ki67 and cleaved caspase-3, the 5 representative fieldswere captured in the area of tumor cells as we aimed to show theproliferation and apoptosis of tumor cells upon myeloid-specificNotch modulation. Tumor cells could be distinguished based ontheir sizes and histology (infiltrating immune cells are largelyfound in stroma). Besides, area of extensive immune cell infiltra-tion, for example, infiltrating lymph nodes or tertiary lymphoidstructures, was avoided.

Immunofluorescence stainingFFPE sections were deparaffinized and then fixed with form-

aldehyde:methanol (1:10) prior to antigen retrieval by heat-induced epitope retrieval using citrate buffer (pH6) or Tris/EDTA(pH9). Each section was put through several sequential rounds ofstaining; each includes a protein blocking followed by primaryantibody and corresponding secondary horseradish peroxidase–conjugated polymer (Zytomed Systems or PerkinElmer). Eachhorseradish peroxidase–conjugated polymer mediated the cova-lent binding of a different fluorophore using tyramide signalamplification. The sequential multiplexed staining protocol isshown in Supplementary Table S4. Such covalent reaction wasfollowed by additional antigen retrieval in heated citric buffer(pH6) or Tris/EDTA (pH9) for 20 minutes to remove antibodiesbefore the next round of staining. After all sequential stainingreactions, sections were counterstained with DAPI (Vector lab).Slides were scanned and digitalized by Zeiss Axio Scanner Z.1(Carl Zeiss AG) with 10� objective magnification.

Real-time quantitative RT-PCRqPCR was performed by Roche LightCycler 480 using Light-

Cycler 480 SYBR Green I Master Kit (Roche GmbH). Primers forqRT-PCRs were designed using the NCBI Primer Blast and pur-chased from Eurofins MWG Operon GmbH. The primer list isshown in Supplementary Table S5. The PCR products weredesigned with a size of approximately 100 bp. All real-time qPCRexperiments were run under 58�C annealing condition andamplification was run for 45 cycles. A melting curve was imple-

mented in each experiment to prove single product amplification.Data were analyzed using DCt calculations where RPLP0 orcyclophilin A served as housekeeper control for normalization.The amplification efficiency was experimentally determinedor assumed as 2 (doubling each cycle). Relative mRNAexpression levels compared with housekeeper gene expression(efficiency-DCt) were used for visualization.

NanoString nCounter RNA expression analysisThe PanCancer Immune Profiling Panel (NanoString Technol-

ogies Inc.), which includes 730 immune-related genes and 40housekeeping genes, was used in the study. Expression data werenormalized and analyzed with the nSolver Advanced AnalysisSoftware 1.1.4 using the PanCancer Immune Profiling AdvancedAnalysis Module (NanoString Technologies). For backgroundcorrection, the mean count of negative controls plus two timesthe SDwas subtracted from the counts for each gene. The geNormalgorithm was used to identify the most stable housekeepinggenes. The geometric mean of the selected housekeeping geneswas used to calculate a normalization factor for each sample. Thecell-type–specific scores were calculated as mean log2 value ofcharacteristic genes for corresponding immune cell types. When-ever stated, relative score was presented as the relative abundanceof certain immune subset with regard to either total tumor-infiltrating leukocytes (TIL) or total T cells. The pathway scoreswere analyzed by the first principal component (PC). For a givenpathway, PCanalysis scored each sample using aweighted averageof its gene expression values.

Statistical analysisAll statistics were calculated using GraphPad Prism 6.0 (Graph-

Pad Software). Two-tailed nonparametric Mann–Whitney testwas applied for all analysis, except for survival data by log-rank(Mantel–Cox) test, and correlation analysis by Spearman rankcorrelation coefficient.

ResultsM2-phenotype TAM is the predominant immune subset inPDAC microenvironment

We first studied the dynamics of tumor–stroma interactions atdifferent time points during tumor progression in Ptf1awt/Cre;Kraswt/LSL-G12D;p53fl/flmice (namedCKP hereafter; for details, referto Supplementary Table S1), which show a highly aggressiveclinical course and display prominent desmoplasia (37). Pancre-atic tissue was harvested at different stages: preneoplasia(<4 weeks of age), early (4–6 weeks), and advanced PDAC(10weeks). IHC staining showed that the number of proliferativeKi67þ tumor cells significantly increased from preneoplasia toearly PDAC, and then decreased slightly at advanced stage(Supplementary Fig. S1A). A similar trend was observed forapoptotic marker cleaved caspase-3, although the frequency wasrelatively low (Supplementary Fig. S1A). Tumor histology asrevealed by Movat's pentachrome stain demonstrated that acinarcells significantly decreased, whereas desmoplasia increased frompreneoplasia to advanced stage PDAC (Fig. 1A).

Tumor-infiltrating immune cells are a major component ofdesmoplasia. We profiled the dynamics of immune subsets alongPDAC progression. A significant percentage of CD45þ leukocytes(�20%) was detected in preneoplasia, and increased in earlyPDAC (�40%), but then dropped to approximately 30% at

Myeloid-Specific Notch Modulation in Pancreatic Cancer

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Figure 1.

M2 macrophages predominated tumor-infiltrating leukocytes in CKP tumors. A, Representative Movat, CD45, CD19, CD3, CD11b, F4/80, and MRC1 staining ofdifferent tumor stages: preneoplasia (<4weeks), early (4–6weeks), and advanced (>8weeks) PDAC inCKPmice (n� 5/group). Magnification,�25;�200. Scale bar,100 mm. Right, percentage of positive cells or area (for Movat's pentachrome staining only) as the average of 5 fields from eachmouse (objectivemagnification,�10).Mean þ SD is shown. B, Flow cytometric analysis on the immune phenotype of spleens from wild-type or end-stage CKP mice. Percentage of viable CD45þ cellswas pregated for T cells (CD3þ), B cells (CD19þ), and myeloid cells (CD11bþ) quantification. Percentage of CD4þ and CD8þ cells in total CD3þ T cells. Na€�ve,CD44loCD62L

hi; EM (effector memory), CD44hiCD62Llo; CM (central memory), CD44hiCD62Lhi in total CD4þ and CD8þ T cells were quantified.WT, n¼ 6; CKP, n¼ 6.C, PDAC tumors of end-stage CKP mice were digested into desegregated cells and analyzed by flow cytometry. Live CD45þ cells were gated as viableleukocytes for subsequent immune subpopulation characterization: T cells (CD3þ), B cells (CD19þ), and myeloid cells (CD11bþ); CD4þ T (CD3þCD4þCD8�), CD8þ T(CD3þCD4�CD8þ), Treg (CD3þCD4þFoxp3þCD25þ), gdT (CD3þgdTCRþ), B1 (CD19þCD43þ) and B2 (CD19þCD43�), NK (NK1,1þ), M-MDSCs (CD11bþF4/80�/loGR1

�/loLy6Chi), G-MDSCs (CD11bþF4/80�GR1hi), and TAM (CD11bþF4/80þGR1�/lo). TAMs were further dissected into M1 (iNOSþ) and M2 (MRC1þ, ARG1þ).

n ¼ 12, except for Treg and NK (n ¼ 5), gdT (n ¼ 3), M-MDSC (n ¼ 7). Mean þ SD are shown. � , P < 0.05; �� , P < 0.005.

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advanced stage (Fig. 1A). CD3þ T cells demonstrated a similartrend as CD45þ cells, whereas CD19þ B cells were almost unde-tectable in preneoplastic lesions, but then continuously increasedalong PDAC progression (Fig. 1A). However, frequencies of bothCD3þ T and CD19þ B cells were relatively low (less than 5% and1.5%, respectively). On the contrary, a substantial number ofCD11bþ myeloid cells was found in preneoplasia (�15%), andincreased to approximately 20% in early and advanced PDAC,respectively (Fig. 1A). Further characterization showed thatF4/80þ macrophages comprised the major subpopulation ofCD11bþ myeloid cells (Fig. 1A). Among F4/80þ macrophages,MRC1þ M2 macrophages represented the dominant subpopula-tion (Fig. 1A), whereas iNOSþ M1 macrophages were rarelyobserved in all stages (<1.5%, Supplementary Fig. S1A). In normalpancreas, the abovemarkers are all almost absent (SupplementaryFig. S1B).

Flow cytometric analysis was performed to quantify variousimmune subpopulations in advanced CKP mice. First, systemicimmunoregulatory effects during PDAC progression wereassessed by measuring CD3þ T cells, CD19þ B cells, and CD11bþ

myeloid cells in the spleens of wild-type andCKPmice. Spleens ofCKP mice showed a significant increase of myeloid cells with areduction of B cells compared with those of wild-type mice(Fig. 1B). However, the number of total and different subsetsof T cells was not affected by the presence of pancreaticneoplasms (Fig. 1B).

Next, we characterized the immune landscape in advancedCKPtumors. Approximately 60% of CD45þ leukocytes were positivefor themyeloid lineagemarker CD11b, whereas CD3þ T cells andCD19þ B cells accounted for 15% and 20% of leukocytes, respec-tively (Fig. 1C). Further analysis was performed to comprehen-sively delineate the composition of tumor-infiltrating immunecells (detailed gating strategies as shown in SupplementaryFig. S1C–S1G). CD4þ and CD8þ T cells contributed to CD3þ

population equally (�7% of total TILs). Regulatory T cells (Treg),gd T cells, and natural killer (NK) cells accounted for only 1%each (Fig. 1C). Conventional CD43� B2 cells represented15% of leukocytes, but no CD19þCD5þCD1dhi Bregs werefound in tumors or spleens. TAMs, characterized by aCD45þCD11bþGR1�/loF4/80

þ phenotype, were the largestmyeloid subpopulation (Fig. 1C). Myeloid-derived suppressorcells (MDSC) accounted for 10% of all CD45þ cells, withdominance of granulocytic (G-MDSC) over monocytic MDSCs(M-MDSC). Further characterization on TAMs revealed a clearenrichment of MRC1þ and ARG1þ M2 phenotypes (Fig. 1C).

Intratumoral T cells do not express markers for effectorfunctions

Although tumor antigens can elicit T cell–mediated antitumorresponse, T cells are frequently prevented from eradicating tumorcells by various immunosuppressive programs (24, 38). IHCstaining showed that CD4þ and CD8þ cells were rarely observedin preneoplastic lesions. Although they increased as tumor pro-gressed, the frequency remained low (less than 1% and 2%,respectively; Supplementary Fig. S1A). Given the M2 predomi-nated PDAC microenvironment, we hypothesized that the anti-tumor activity of infiltrating T cells might be suppressed. We thusassessed the expression of two critical transcription factors foreffector functions of T cells, T-bet, and Eomes, as well as the T-cellactivation marker lymphocyte activation gene-3 (LAG3). T-bet isinduced upon na€�ve T-cell priming and is required for the pro-

duction of effector cytokines such as IFN-suppressed. Eomesregulates cytolytic gene program in CTLs, and T-bethiEomeshi cellsrepresent fully differentiated CTL populations (39). IHC stainingshowed that both transcription factors and LAG3 were foundat low expression levels in the tumor-infiltrating T cells (Supple-mentary Fig. S1A), and absent in normal pancreas (Supplemen-tary Fig. S1B).

Because T-bet and Eomes are also implicated in the cytotoxicfunctions of NK cells, we assessed NK infiltration in PDACdevelopment. IHC analysis showed that NK cells were absent inpreneoplastic lesions. However, NK cells were detected in earlyand late PDAC, albeit at low frequency (<1%; SupplementaryFig. S1A). On the basis of the expression patterns of T-bet, Eomes,and NK1.1 in consecutive tissue sections, NK cells might alsocontribute to the expression of T-bet and Eomes in early and latePDAC (Supplementary Fig. S1A). However, because NK-cellfrequency was relatively low when compared with CD3þ T cells(Fig. 1A), the increased T-bet and Eomes expression should belargely contributed by T cells.

Notch activation counteracts IL4-induced M2 polarization invitro

Predominant M2 TAMs might be associated with defectiveT-cell responses in PDAC. Therefore, we investigated regulatorymechanisms for M2 polarization. The Notch signaling pathwayhas been reported to regulate macrophage polarization, inwhich Notch activation led to M2-associated gene repression(30, 31).

First, we studied the effects ofmanipulating theNotch pathwayusing BMDMs. Bone marrow–derived cells were treated withM-CSF for 8 days, and then confirmed formacrophage phenotypeby expression of both CD11b and F4/80 (Supplementary Fig. S2).To test the ability of BMDMs to undergo CRE-mediated recom-bination, BMDMs from R26LSL-tdTomato reporter mice were treatedwith recombinant NLS-TAT-CRE (40). Approximately, 95% ofcells successfully underwent genetic loxP-site recombination asdetermined by tdTomato fluorescence detected by flow cytometryand fluorescence microscopy (Fig. 2A).

To study the effect of Notch activation in M2 polarization,BMDMs from R26LSL-N2IC mice (34) were pretreated with orwithout recombinant CRE protein, and subsequently stimulatedwith IL4 to induce M2 polarization. In this model, CRE recombi-nase excises a transcriptional STOP-cassette, resulting in consti-tutive expression of transcriptionally active Notch2-IC andhuman CD2, a coexpressed reporter molecule (Fig. 2B). CRE-dependent activation of Notch signaling was confirmed by hCD2,as detected by flow cytometry (Fig. 2C). IL4 strongly induced theexpression of M2-associated genesMrc1, Mgl1, and Arg1, whereasno significant change was observed for M1-associated genes (Fig.2D). The IL4-induced upregulation of Mrc1, Mgl1, and Arg1expression was significantly abrogated by concomitant Notchactivation (Fig. 2D). In addition, effect of Notch activation onMRC1 protein level was validated by flow cytometry (Fig. 2E),supporting the observation that Notch activation counteracts IL4-induced M2 polarization.

To explore the effect of Notch activation in M1 polarization,BMDMs were stimulated with LPS following treatment withrecombinant CRE protein. LPS alone induced an upregulationof iNos, IL1b, IL6, IL12a, and IL12b genes. However, combinationof LPS and CRE did not exert additional effect on M1 geneupregulation or M2 gene reduction (Fig. 2F). The result was






Figure 2.

Notch modulation regulates macrophage polarization in vitro. A, BMDMs isolated from R26LSL-tdTomato reporter mice treated with 1 mmol/L recombinantNLS-TAT-CRE overnight and analyzed for tdTomato fluorescence on day 4 by flow cytometry or observed under microscope. Scale bar, 100 mm. B, Simplifieddescription of geneticR26LSL-N2IC construct.C, In vitro LoxP recombination assessed by detecting hCD2onN2ICBMDMs.D andE,BMDMs fromR26LSL-N2IC stimulatedwith 10 ng/mL IL4 for 72 hours with or without previous CRE treatment. D, Relative expression levels of M1 and M2 marker genes determined by qRT-PCR (n ¼ 6).Mean þ SD is shown. E, Representative flow cytometric analysis showing MRC1 level on CD11bþF4/80þ cells upon CRE and IL4 treatment. F and G, BMDMsfrom R26LSL-N2IC stimulated with 1 mg/mL LPS for 6 hours (F) or overnight (G) with or without previous CRE treatment. F, Relative mRNA expression levels of M1 andM2marker genes determined by qRT-PCR. n¼ 6, except forþCRE-LPS: n¼ 3. G, Flow cytometry analysis showing percentage of iNOSþ and MRC1þ cells in F4/80þ

BMDMs. n¼ 4.Meanþ SD is shown.H, Simplified description of conditionalRbpjfl/fl construct. I–K,BMDMs fromRbpjfl/flmice stimulatedwith 1mg/mL LPS for 6 hours(I) or overnight (J), or with IL4 for 72 hours (K) with or without previous CRE treatment. I, Relative mRNA expression levels of M1 and M2 marker genesdeterminedbyqRT-PCR (n¼6).MeanþSD is shown. J,Flowcytometry analysis showingpercentage of iNOSþ andMRC1þ cells in F4/80þBMDMs (n¼4).MeanþSDis shown. K, Representative histogram showing relative fluorescence intensity of MRC1 on CD11bþF4/80þ cells upon CRE and IL4. � , P < 0.05; �� , P < 0.005.

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validated for protein level of iNOS and MRC1 by flow cytometry(Fig. 2G).

It is noteworthy that IL1b was upregulated by CRE alonetreatment (Fig. 2D and F). However, the induced IL1b level byCRE alone is significantly lower when compared with thatof CRE plus LPS treatment (Fig. 2F). Besides, the expressionof other M1-associated genes (e.g., IL6, IL12, iNos) induced byCRE alone is generally subtle. Although we cannot exclude thepossibility that NLS-TAT-CRE exposure indeed might inducechanges in M1- and/or M2-associated genes, the magnitudes ofdifferences induced upon LPS and IL4 treatment are at leastseveral folds greater than CRE alone. Because the inductionof M1 and M2-associated genes is clearly different betweenN2IC- and Rbpj-targeted cells, it is deduced that Notchmodulation is the dominant factor counteracting IL4-inducedM2 polarization.

Rbpj knockout blocks LPS-induced M1 polarization in vitroNext, we investigated the role of endogenous Notch signaling

for M1 or M2 macrophage polarization. Rbpjfl/fl construct allowsCRE-dependent ablation of canonical Notch signaling (Fig. 2H).BMDMs from Rbpjfl/flmice were treated analogously to those fromR26LSL-N2IC mice. LPS-induced M1 gene expression was signifi-cantly reduced in Rbpj KO macrophages (Fig. 2I). Moreover,LPS-dependent downregulation of Jmjd3, a critical gene for M2polarization, was retained in Rbpj KO BMDMs (Fig. 2I). Flowcytometric analysis revealed that LPS-induced iNOS expressionwas also downregulated in Rbpj KOmacrophages at protein level(Fig. 2J). However, IL4-induced M2 polarization in terms ofMRC1 protein expression was not affected by Rbpj ablation(Fig. 2K). These findings suggest that canonical Notch signalingis required for robust M1 polarization.

Genetic Notch modulation in myeloid cells using in vivo dualrecombinase system

To validate the regulatory role of Notch in M2 polarization invivo, a myeloid-targeting Cre strain (Lyz2wt/Cre) was crossed toR26wt/LSL-N2IC and Rbpjfl/fl mice. Lyz2wt/Cre;R26wt/LSL-N2IC (Lyz2;N2IC) and Lyz2wt/Cre; Rbpjfl/fl (Lyz2;Rbpj) lines were then interbredwith Pdx1-Flp;Kraswt/FSF-G12D;p53frt/frt (FKP) mice (Fig. 3A and B).FKP mice develop and succumb to PDAC highly similar to theCKP model as reported previously (33). Phenotypic characteri-zation of FKP tumors was performed showing comparable his-tology and biology of tumor cells, as well as immune profile asthose of CKP tumors (Supplementary Fig. S3A). Lyz2-Cre expres-sion was traced with the R26LSL-tdTomato reporter strain to quantifyrecombination efficiency inmyeloid subsets. Approximately 80%of CD11bþ myeloid cells were recombined by Lyz2-Cre in bonemarrow and spleen (Fig. 3C). Among CD11b� cells, there is lessthan 10% positivity for tdTomato expression. This populationmight thus reflect CD11b�CD11cþ dendritic cells that are derivedfrom myeloid cell precursors (41). To confirm myeloid-specificNotch downstream activation in Lyz2;N2IC, bone marrow ofwild-type, Lyz2;N2IC, and Lyz2;Rbpjmice was isolated and sortedaccording to CD11b and hCD2 expression for RNA extraction(Fig. 3D). Real-time qPCR revealed a strong transcriptional upre-gulation of the Notch target gene Hes1 in Lyz2;N2IC bonemarrow, indicating that Notch was Lyz2-Cre dependently activat-ed, whereas wild-type and Lyz2;Rbpjmice both showed low levelsof Hes1 expression in CD11bþ bone marrow cells (Fig. 3E). IHCstaining for hCD2 and CD11b, as well as immunofluorescence

staining for their coexpression pattern in FKP;Lyz2;N2IC tumors,further confirmed the selective Notch activation in CD11bþ

myeloid cells (Fig. 3F).We next addressed the expression of the different Notch recep-

tors. AlthoughNotch2 is the target inR26LSL-N2ICmice, ablation ofRbpj potentially affects other Notch family members. We thusanalyzed the constitutive expression of Notch 1–4 in FKP tumors.IHC analysis revealed the expression of Notch 1 and 2, but notNotch 3 and 4 in FKP tumors (Supplementary Fig. S3B). Subse-quent coexpression analysis by immunofluorescence stainingshowed that Notch1 expression was largely found in tumor cells,but not in CD11bþ myeloid cells (Supplementary Fig. S3C).Besides, Notch1 expression was similar in either FKP, FKP;Lyz2;Rbpjor FKP;Lyz2;N2IC tumors (Supplementary Fig. S3B and S3C),suggesting that Notch1 is not expressed in myeloid cellsand therefore not subject to myeloid-specific modulation inour system.

Notably, Notch2 was found to be highly coexpressed withCD11b, that is, inmyeloid cells. As shown in Fig. 3G,modulationof Notch2 is a target of the genetic intervention, as an increase inNotch2 was mainly found in CD11bþ cells in FKP;Lyz2;N2ICmice, whereas it was largely reduced in FKP;Lyz2;Rbpj. In fact, ourfinding is supported by previous publication that Notch2 isfundamental for myeloid cell differentiation (42, 43).

Importantly, we observed a significant survival benefit in Lyz2;N2ICmice when compared with Lyz2;Rbpjmice in both FKP andFKPhet models with deletion of both or only one Tp53 allele,respectively (Fig. 3H and I), although statistical significance wasnot reached when compared with FKP controls.

Notch activation reprograms M2 TAMs in vivoNext, we investigated the effect of Notch modulation on the

immune systems in vivo. First, mice were examined for systemiceffect of the Lyz2-Cre–mediated Notch manipulation onimmune landscapes in bone marrow, blood, and spleen. Nosignificant change was observed among Notch activation(Lyz2;N2IC), blockage (Lyz2;Rbpj), and wild-type mice inall myeloid and lymphoid subpopulations (SupplementaryFig. S4A–S4C).

We next performed a detailed characterization of tumors fromFKP;Lyz2;N2IC, FKP;Lyz2;Rbpj, and FKP control mice andobserved that Ki67 expression significantly decreased, whereascleaved caspase-3 increased in FKP;Lyz2;N2IC tumors (Fig. 4A),suggesting reduced proliferation and increased apoptosis intumor cells upon myeloid-targeted Notch activation. Movat'spentachrome staining showed that stromal content was alsoreduced in FKP;Lyz2;N2IC group (Fig. 4A). The opposite trendis observed for the above findings in FKP;Lyz2;Rbpj tumors. It isnoteworthy that collagen (yellowish stain), which was rarelyobserved in FKP control tumor (Supplementary Fig. S3A), wasincreased in FKP;Lyz2;Rbpj tumor, indicating rearrangement ofstromal content. IHC staining was performed to confirm thecollagen levels in the tumors, and consistently, there were signif-icantly higher levels of collagen in FKP;Lyz2;Rbpj tumor whencompared with FKP control and FKP;Lyz2;N2IC group (Supple-mentary Fig. S4D).

To investigate any alteration in immune landscape uponmyeloid-specific Notch modulation, tumors of end-stage FKP;Lyz2;N2IC and FKP;Lyz2;Rbpj mice were characterized for infil-trating leukocyte subsets. Flow cytometric analysis showeda slightincrease in CD3þ T cells and CD19þ B cells in FKP;Lyz2;N2IC






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mice, although statistical significance was not reached (Fig. 4B).CD11bþ myeloid cells remained the predominant population ininfiltrating leukocytes in bothmodels.We observed no significantchanges in overall MDSC and TAM proportions, and TAMscomprised the majority of CD11bþ cells (Fig. 4B). However, wefound a significant reduction of M2 TAMs (iNOS�MRC1þ) inFKP;Lyz2;N2IC tumors when compared with FKP;Lyz2;Rbpj(Fig. 4B). Multiplexed immunofluorescent staining for MDSCssupported the FACS results by showing a slight, but not signif-icant, decrease in G-MDSCs in FKP;Lyz2;N2IC mice, while thelevels ofM-MDSCs remained low and therewas no change amongthe three groups (Supplementary Fig. S4E). Besides, IHC stainingechoed the findings by demonstrating prominent reduction inMRC1 expression in FKP;Lyz2;N2IC tumors (Fig. 4C). Subsequentmultiplexed staining for hCD2, CD11b, and MRC1 was per-formed in FKP;Lyz2;N2IC tumors to assess the M2 phenotype ofthe CD11bþhCD2þ cells. As shown in Supplementary Fig. S4F,MRC1 expression did not show similar pattern to that of hCD2,suggesting that hCD2þ cells were largely MRC1 negative. The M1TAM marker iNOS was significantly upregulated in FKP;Lyz2;N2IC tumors, although the level was relatively low (Fig. 4C).

Association of myeloid-specific Notch modulation withimmune profiles in tumor microenvironment

Next, we characterized and compared the immune landscapesof FKP;Lyz2;N2IC (n¼ 7) and FKP;Lyz2;Rbpj (n¼ 9) tumors usingthe NanoString PanCancer Immune Panel. The 35 genes mostregulated upon Notch modulation are listed in SupplementaryTable S6 and plotted in the heatmap (Fig. 5A). NanoStringadvanced analysis revealed an increase in infiltrating T cells inFKP;Lyz2;N2IC tumors. Specifically, CD4þ T cells and exhaustedCD8þ cells significantly increased in FKP;Lyz2;N2IC tumors(Fig. 5B). Note that the cell scores indicate the relative abundanceof immune subsets out of total TILs or total T cells. Consistently,flow cytometric analysis also revealed increased CD3þ (Fig. 4E),CD4þ, and CD8þ T cells (Fig. 5C) in FKP;Lyz2;N2IC, althoughstatistical significance was not reached, likely due to small samplesize (n ¼ 3; Fig. 5C).

Besides, immune pathway analysis by NanoString showedhigher scores for antigen processing, MHC, IFN, senescence,chemokines and receptors, inflammation, and apoptosis path-ways in FKP;Lyz2;N2IC tumors (Fig. 5D). This analysis revealedthat MHC class II–related genes, for example, Lag3, Ciita,H2-DMb1, and H2-Eb1, comprised the majority of genes that

were significantly altered upon Notch modulation in antigenprocessing and MHC pathways. Indeed, these MHC classII–related genes were all upregulated for approximately 2- to3-fold (log2 scale) in FKP;Lyz2;N2IC tumors (SupplementaryTable S6). For chemokines and receptors pathway,Ccl24, a strongchemotactic factor for resting T cells (44), was significantly upre-gulatedwith the greatest fold increase (5-fold in log2 scale) in FKP;Lyz2;N2IC. We next validated findings from NanoString analysisat protein levels by IHC. Consistent with NanoString analysis, weobserved significantly higher levels of CD3þ, CD4þ, and CD8þ

cells in FKP;Lyz2;N2IC tumors (Fig. 5E). In addition, Eomes andLag3, markers for both activation and exhaustion of T cells(45, 46), were among the most significantly altered genes inFKP;Lyz2;N2IC as revealed by NanoString analysis (Supplemen-tary Table S6). Their protein levels were also shown to besignificantly higher in FKP;Lyz2;N2IC (Fig. 5E). To verify whetherNK cells also contributed the increase in Eomes expression, wemeasured infiltrating NK cells in the tumors and found that NKcells were significantly reduced in FKP;Lyz2;N2ICwhen comparedwith FKP;Lyz2;Rbpj (Supplementary Fig. S5A). Therefore, theincrease in Eomes in FKP;Lyz2;N2IC tumors should be largelyT cell dependent.

Next, we validated the markers for antigen presentation asrevealed byNanoString analysis. IHC staining for CD11c,MHCII,and CD80 in FKP;Lyz2;Rbpj, FKP;Lyz2;N2IC and FKP controltumors were performed as their genes, CD11c (itgax), CD80,MHCII (e.g., ciita, H2-DMb1, H2-Eb1), were among the mostsignificantly upregulated genes upon Notch modulation(Fig. 5A; Supplementary Table S6). Consistent with NanoStringanalysis, IHC staining showed increase in CD11cþ, MHCIIþ, andCD80þ cells in N2IC-targeted mice, whereas a reduction in FKP;Lyz2;Rbpj group was observed (Supplementary Fig. S5A). Multi-plexed immunofluorescent staining of CD11c with the humanCD2 reporter protein in FKP;Lyz2;N2IC showed that CD11cþ cellsare mostly, if not all, hCD2 negative (Supplementary Fig. S5B).Subsequent costaining of CD11b, CD11c, MHCII, and CD80 inFKP;Lyz2;N2IC showed that upregulation of MHCII and CD80 islargely expressed by CD11cþ cells (Supplementary Fig. S5C). Thepresence of hCD2þCD11cþ cells might be due to the fact thatsome CD11cþ cells are derived from myeloid cell precursors, asreported by Clausen and colleagues (41). Regarding the cytokineprofile, we observed an increase in the M1-associated cytokinesIFNg , IL12p70, and TNFa, whereas the M2-associated cytokinesCXCL1 and TGFb were decreased in FKP;Lyz2;N2IC mice

Figure 3.Lyz2-Cre directs geneticNotch activation tomyeloid cells.A,Mouse crossing strategy.Pdx1-Flp;Kraswt/FSF-G12D;p53frt/frt (FKP)mice crossed to Lyz2;Rbpjor Lyz2;N2ICstrains to generate FKP;Lyz2;Rbpj and FKP;Lyz2;N2IC mice, respectively. B, Oncogenic KrasG12D-driven pancreatic tumorigenesis (FKP) and myeloid-specificmanipulation of Notch signaling were concomitantly genetically induced. C, The R26LSL-tdTomato reporter mouse line was used to visualize Lyz2-Cre expressionand recombination activity in vivo. tdTomatoþ fractions in CD11bþ and CD11c� cells isolated from bone marrow (BM) and spleen (SP) were quantified byflow cytometry (n ¼ 3). Mean þ SD is shown. D, Bone marrow–derived cells of wild-type, Lyz2;N2IC, and Lyz2;Rbpj mice were sorted based on hCD2 andCD11b expression, and mRNA was extracted from the sorted populations (red gates). Lower gate, CD11bþhCD2�; upper gate, CD11bþhCD2þ. E, Specific Hes1expression in sorted CD11bþhCD2� and CD11bþhCD2þ cells was assessed by qRT-PCR. F, Left, IHC staining for CD11b, hCD2, and isotype control on the tumor of FKP;Lyz2;N2IC tumor. Magnification, �100; �200. Scale bar, 50 mm. Right, immunofluorescence staining for coexpression of CD11b (green) and hCD2 (red) on thetumor of FKP;Lyz2;N2IC tumor. DAPI (blue), nuclei. Magnification,�25;�200. Scale bar, 100 mm.G, Immunofluorescence staining for coexpression of CD11b (green)and Notch2 (red) on the tumor of FKP, FKP;Lyz2;Rbpj, and FKP;Lyz2;N2IC tumors. DAPI (blue), nuclei. Magnification,�25;�200. Scale bar, 100 mm.H and I, Kaplan–Meier plot showing the survival of FKP;Lyz2;Rbpj, FKP;Lyz2;N2IC, and FKP control mice in FKP (H) and FKPhet (I) models. H, Median survival: FKP;Lyz2;Rbpj, 67 days(n¼ 24); FKP;Lyz2;N2IC, 78 days (n¼ 11); FKP, 70 days (n¼ 19). Log-rank test: FKP;Lyz2;Rbpj versus FKP;Lyz2;N2IC, P¼0.014; FKP;Lyz2;Rbpj versus FKP, P¼0.482;FKP;Lyz2;N2IC versus FKP, P¼0.095. I,Median survival: FKPhet;Lyz2;Rbpj, 147 days (n¼ 17); FKPhet;Lyz2;N2IC, 186.5 days (n¼ 8); FKPhet, 172 days (n¼ 24). Log-ranktest: FKP;Lyz2;Rbpj versus FKP;Lyz2;N2IC, P¼0.013; FKP;Lyz2;Rbpj versus FKP, P¼0.184; FKP;Lyz2;N2IC versus FKP, P¼0.317. �,P<0.05when comparingbetweengroups denoted by horizontal bars.






Figure 4.

Notch signaling antagonizesM2 polarization in PDACTAMs.A,Movat's pentachrome staining, IHC staining of Ki67, and cleaved caspase-3 in FKP, FKP;Lyz2;Rbpj, andFKP;Lyz2;N2IC tumors (n � 5/group). Magnification, �25; �200. Scale bar, 100 mm. Bottom, percentage of positive cells or area (for Movat's pentachromestaining only) as the average of 5 fields from each mouse (objective magnification, 10�). Mean þ SD is shown. B, Tumors of end-stage FKP;Lyz2;Rbpj andFKP;Lyz2;N2IC mice were digested into desegregated cells and analyzed by flow cytometry. Live CD45þ cells were gated as viable leukocytes for subsequentimmune subpopulation characterization: T cells (CD3þ), B cells (CD19þ), and myeloid cells (CD11bþ); M-MDSCs (CD11bþF4/80�/loGR1

�/loLy6Chi), G-MDSCs

(CD11bþF4/80�GR1hi), and TAM (CD11bþF4/80þGR1�/lo). TAMs were further dissected into subpopulations based on iNOS and MRC1 expression. Mean þ SD isshown. C, IHC staining for CD11b, F4/80, MRC1, and iNOS in FKP;Lyz2;Rbpj and FKP;Lyz2;N2IC tumors (n � 5/group). Magnification,�25;�200. Scale bar, 100 mm.Bottom, percentage of positive cells as the average of 5 fields (n � 5/group; objective magnification, 10�). Mean þ SD is shown. � , P < 0.05; �� , P < 0.01.

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Figure 5.

Association of myeloid-specific Notch modulation with immune landscapes in tumor microenvironment. A, B, and D, Profile of immune-related expressionsignatures in FKP;Lyz2;Rbpj (n ¼ 9) and FKP;Lyz2;N2IC (n ¼ 7) tumors determined by the NanoString PanCancer Immune Profiling Panel. A, Heatmap withhierarchical clustering for genes with at least 2-fold change up or downwith P < 0.05 as cutoff. Significant upregulation is shown in red and downregulation in green.B, The cell-type–specific scores of T cells and exhausted CD8þ T cells (relative to total tumor-infiltrating cells), and CD4þ T cells (relative to total CD3þ T cells)were calculated by PanCancer Immune Profiling Advanced Analysis as described in Materials and Methods. C, Flow cytometric analysis showing the percentage ofCD4þ T cells (CD3þCD4þCD8�) and CD8þ T cells (CD3þCD4�CD8þ) of total leukocytes (CD45þ) in FKP;Lyz2;Rbpj and FKP; Lyz2;N2IC tumors (n ¼ 3/group). D,Pathway scores of antigen processing, MHC, IFN, senescence, chemokines and receptors, inflammation, and apoptosis were calculated by PanCancer ImmuneProfilingAdvancedAnalysis as described inMaterials andMethods.E, IHC stainingofCD3, CD4, CD8, Eomes, andLAG3 inFKP;Lyz2;Rbpj andFKP;Lyz2;N2IC tumors (n� 5/group). Magnification,�25;�200. Scale bar, 100 mm. Right, percentage of positive cells as the average of 5 fields (n� 5/group; objective magnification, 10�).Mean þ SD is shown. � , P < 0.05; �� , P < 0.005; �� , P < 0.001.






(Supplementary Fig. S5D). It is noteworthy that serum TGFblevels were also decreased in the FKP;Lyz2;N2IC group, suggestinga systemic change in this cytokine. However, no statistical signif-icancewas reached in the above cytokineprofiling due to the smallsample size.

In addition to the above-mentioned cell types and pathways,no significant change was observed for the infiltration of immunecell types including B cells, mast cells, neutrophils (Supplemen-tary Fig. S5E), and pathways, for example, TNF, NK function, andinnate immunity (Supplementary Fig. S5F).

DiscussionOne of the distinctive features of PDAC is that the malignant

epithelial cells often account for only a minority of tumor mass,whereas the desmoplastic stroma and other nontumor cellsconstitute up to 80% (47). Currently, most targetingapproaches focus on aberrant signaling of tumor cells, whilethe effect on other cellular compartments remains elusive giventhe lack of comprehensive model systems. As such, targeting ofNotch signaling has been disappointing clinically in PDACdespite supportive preclinical evidence. However, in morecomplex disease models, the role of Notch signaling has beencontroversial in PDAC, exerting both pro- and antitumorigeniceffects (48).

In this study, we used a genetic approach to modulate Notchsignaling specifically in myeloid cells and characterized theconsequent effects on the immune landscape in spontaneousendogenous PDAC in immunocompetent mice. In line withprevious findings, tumor-promoting M2 TAMs were shown topredominate the TILs (49, 50). A significant amount of M2 TAMswas observed in preneoplastic lesions, and the level increasedalong tumorprogression, suggesting thatM2TAMsparticipate notonly in PDAC progression, but also in tumor formation (51–53).Here, we demonstrated a tumor-suppressive role of Notchsignaling in myeloid cells in PDAC. Upon Notch activation inmyeloid cells, M2 TAMs were significantly reduced, while antigenpresentation and cytotoxic T-cell activity were restored, andimportantly, survival of mice with spontaneous PDAC wassignificantly improved. Our findings therefore may help explainthe limited efficacy of targeting Notch signaling in PDAC aspreviously reported (13, 14).

Earlier studies reporting the repolarization of macrophages inexperimental PDAC demonstrated beneficial outcome when M2polarization was antagonized either genetically or by low-doseirradiation (54, 55). These studies, however, were conductedeither by tumor transplantation or transgenic mouse models,which do not recapitulate seminal features of human PDAC asfaithfully as spontaneous KrasG12D-driven PDAC mouse modelsdo. We thus employed a novel dual-recombinase system togenetically induce both KrasG12D-driven pancreatic tumorigenesisandmyeloid-specificmodulation of Notch signaling. In our Lyz2-CREmodel, Notch signaling was genetically targeted in amyeloidcell–specific manner. It is noteworthy that although TAMsrepresent the majority (�50%–60%) of intratumoral myeloidcells in our PDAC model, MDSCs also account for a significantproportion (�20%–30%). Indeed, recent studies have shown thatNotch signaling can regulate MDSC differentiation. Blockageof Notch signaling promoted the differentiation and expansionof G-MDSCs both in vitro and in vivo (29, 56). Our finding of areduction in G-MDSCs upon Notch activation, although not

statistically significant, would be consistent with this effect(Fig. 4B; Supplementary Fig. S4E). Thus, we cannot rule outthe possibility that Notch-induced MDSC differentiationalso contributed to the observed alterations in the tumormicroenvironment. Further investigation will be requiredto further dissect the roles of MDSCs and TAMs in modulatingimmunosuppression.

Analysis of immune landscape of FKP;Lyz2;N2IC and FKP;Lyz2;Rbpj tumors by NanoString showed that Notch-induced M2reduction was significantly associated with gene expressionsignatures of increased antigen processing and presentation,infiltrating T cells, and IFN pathway. Intriguingly, a strong expres-sion of exhausted T-cell signature was observed in FKP;Lyz2;N2ICmice, in which Eomes, Lag3, and PD-1 were expressed at highlevels. Although described as exhaustion markers for T cells, theyare in many ways considered as T-cell activation markers (45, 46,57). Upregulation of these markers may suggest that these cellshave undergone priming and were consequently activated. Onekey feature of T-cell exhaustion is the continuous exposure toantigen rather than acutely terminated or intermittent exposure(58). Here, we observed that upon M2 reduction, antigen proces-sing and presentation was significantly enhanced, which might atleast partially explain the restored T-cell activation andpotentiallythe survival benefit of FKP;Lyz2;N2IC mice. This is supportedby the strong correlation between the mRNA levels of Eomes,Lag3, and PD-1, with antigen processing/presentation–relatedgenes that are highly upregulated upon Notch activation inmyeloid cells.

In addition to T-cell infiltration and activation, another inter-esting impact of myeloid-specific Notch modulation is antigenpresentation. NanoString analysis and subsequent IHC stainingdemonstrated augmented antigen presentation in FKP;Lyz2;N2ICtumors. Upregulated MHCII and CD80 were predominantlyexpressed by CD11cþ dendritic cells, which are mostly hCD2negative. One possible explanation for increased CD11cþ

dendritic cells may be an altered cytokine and chemokine profilein the tumor microenvironment. Although not statisticallysignificant, cytokine profiling revealed increased cytotoxiccytokines IFNg , IL12p70, and TNFa, and decreased tumor-promoting cytokines CXCL1 and TGFb in FKP;Lyz2;N2IC tumors(Supplementary Fig. S5D). Besides, a systemic change in TGFbwas observed in FKP;Lyz2;N2IC mice, as illustrated by decreasedserum TGFb level. It is notable that TGFb is crucial for inducingM2 phenotype and inhibiting dendritic cell maturation andactivation (59). A reduction in TGFb might at least partiallyexplain the increased CD11cþ dendritic cells with higher MHCIIand CD80 expression levels in FKP;Lyz2;N2IC cohort. In thisregard, it can be speculated that the application of Notch inhibi-tors in clinical settings might lead to suppressed antigen presen-tation, which potentially compromises the efficacy of otherimmunotherapies. However, further investigation is needed tocomprehensively characterize the impact of the Notch-inducedmyeloid polarization on the complex antigen presentationmachinery.

The current study may serve as proof of concept for genetictargeting of myeloid subsets in complex models of immunocom-petent endogenous PDAC. The dual recombinase-based approachoffers a platform to assess their contribution in PDACprogressionand immune-based approaches. Our findings on the antitumori-genic role of Notch signaling specifically in myeloid cells call forattention on the need to dissect the differential roles of signaling

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pathways in different cellular components within the tumormicroenvironment. The dual-recombinase system is a usefulmodel system for dissecting the complex network amongtumor and stromal components to validate nontumor-targetingstrategies in PDAC, a disease in high need for better treatmentapproaches.

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

Authors' ContributionsConception and design: P.F. Cheung, F. Neff, J.T. SivekeDevelopment of methodology: P.F. Cheung, F. Neff, C. Neander, A. Bazarna,K. Savvatakis, S.-T. Liffers, D. Saur, J.T. SivekeAcquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): P.F. Cheung, F. Neff, K. Savvatakis, S.-T. Liffers,K. Althoff, C.-L. Lee, E.J. Moding, D.G. Kirsch, D. Saur, M. Trajkovic-Arsic,M.F. HeikenwalderAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): P.F. Cheung, F. Neff, C. Neander, A. Bazarna,S.-T. Liffers, A.V. Bazhin, M.F. Heikenwalder, J.T. SivekeWriting, review, and/or revision of the manuscript: P.F. Cheung, F. Neff,E.J. Moding, D.G. Kirsch, A.V. Bazhin, M.F. Heikenwalder, J.T. Siveke

Administrative, technical, or material support (i.e., reporting or organizingdata, constructing databases): P.F. Cheung, C. Neander, A. Bazarna,K. Savvatakis, S.-T. LiffersStudy supervision: P.F. Cheung, J.T. Siveke

AcknowledgmentsThe authors would like to thankM. Schmid-Supprian for helpful discussions

and providing recombinant CRE protein; U. Zimber-Strobel for providingR26LSL-N2IC mice; H. Nakhai for floxed Rbpj and Ptf1aCre mice; T. Jacks andD.A. Tuveson for KrasLSL-G12Dmice; and A. Berns for floxed p53mice. We thankN. Bielefeld, R.Hillermann, and S. Sch€afers for excellent technical assistance andthe International Max Planck Research School for Molecular Life Sciences(IMPRS) for providing educational and financial support to F. Neff. J.T. Sivekehad been awarded for European Union's Seventh Framework Programme forresearch, technological development and demonstration (FP7/CAM-PaC)under grant agreement no. 602783, the German Cancer Consortium (DKTK),and the Deutsche Forschungsgemeinschaft (DFG, SI1549/1-1).

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 January 7, 2018; revised April 20, 2018; accepted May 22, 2018;published first May 29, 2018.

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Cheung et al.




2018;78:4997-5010. Published OnlineFirst May 29, 2018.Cancer Res Phyllis F. Cheung, Florian Neff, Christian Neander, et al. Ductal Adenocarcinoma by Dual Genetic TargetingNotch-Induced Myeloid Reprogramming in Spontaneous Pancreatic

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