of May 20, 2016.This information is current as

ImmunityBlockade Synergize To Induce Antileukemia Heterologous Vaccination and Checkpoint

Michael A. FarrarKristen E. Pauken, Richard T. Williams, Vaiva Vezys and Luke S. Manlove, Jason M. Schenkel, Kezia R. Manlove,

ol.1600130http://www.jimmunol.org/content/early/2016/04/23/jimmun

published online 25 April 2016J Immunol 

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Print ISSN: 0022-1767 Online ISSN: 1550-6606. Immunologists, Inc. All rights reserved.Copyright © 2016 by The American Association of9650 Rockville Pike, Bethesda, MD 20814-3994.The American Association of Immunologists, Inc.,

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The Journal of Immunology

Heterologous Vaccination and Checkpoint BlockadeSynergize To Induce Antileukemia Immunity

Luke S. Manlove,*,† Jason M. Schenkel,*,‡ Kezia R. Manlove,x Kristen E. Pauken,*,{

Richard T. Williams,‖ Vaiva Vezys,*,‡ and Michael A. Farrar*,†,#

Checkpoint blockade-based immunotherapies are effective in cancers with high numbers of nonsynonymous mutations. In contrast,

current paradigms suggest that such approaches will be ineffective in cancers with few nonsynonymous mutations. To examine this

issue, we made use of a murine model of BCR-ABL+ B-lineage acute lymphoblastic leukemia. Using a principal component

analysis, we found that robust MHC class II expression, coupled with appropriate costimulation, correlated with lower leukemic

burden. We next assessed whether checkpoint blockade or therapeutic vaccination could improve survival in mice with pre-

established leukemia. Consistent with the low mutation load in our leukemia model, we found that checkpoint blockade alone had

only modest effects on survival. In contrast, robust heterologous vaccination with a peptide derived from the BCR-ABL fusion

(BAp), a key driver mutation, generated a small population of mice that survived long-term. Checkpoint blockade strongly

synergized with heterologous vaccination to enhance overall survival in mice with leukemia. Enhanced survival did not correlate

with numbers of BAp:I-Ab–specific T cells, but rather with increased expression of IL-10, IL-17, and granzyme B and decreased

expression of programmed death 1 on these cells. Our findings demonstrate that vaccination to key driver mutations cooperates

with checkpoint blockade and allows for immune control of cancers with low nonsynonymous mutation loads. The Journal of

Immunology, 2016, 196: 000–000.

Patients with B cell acute lymphoblastic leukemia (B-ALL)harboring the BCR-ABL chromosomal translocation havevery poor outcomes (1, 2). Current therapies for BCR-

ABL+ B-ALL include cytotoxic chemotherapeutics, tyrosine kinaseinhibitors, and bone marrow transplantation. These treatments areoften transiently effective, indicating that new treatment optionsare urgently needed. One such option is immunotherapy. Recent

work in cancers with frequent nonsynonymous mutations, such asmelanomas, has demonstrated that immunotherapy involving neu-

tralization of programmed death 1 (PD1) and CTLA4 (checkpoint

blockade) is an effective treatment option (3, 4). It remains unclear

whether immunotherapy involving checkpoint blockade strategies

will also be effective in cancers with few nonsynonymous muta-

tions, such as B-ALL (5).To determine whether immunotherapy is an effective option for

treating B-ALL, we used a syngeneic mouse model of BCR-ABL+

B-ALL to characterize the host immune response to this leukemia

in immune-competent recipient animals (6–8). We previously dem-

onstrated that the host adaptive immune system responds to BCR-

ABL+ B-ALL (9). Although B-ALL cells have been shown to have

low numbers of nonsynonymous mutations (5), the fusion between

BCR and ABL does generate an MHC class II (MHC-II)–restricted

peptide Ag that can be recognized by a small population of en-

dogenous BCR-ABL peptide (BAp):I-Ab–specific T cells in mice

(9). Transfer of BCR-ABL+ leukemic cells into C57BL/6 mice

resulted in proliferation of BAp:I-Ab–specific T cells, although 50%

of these cells differentiated into FOXP3+ regulatory T cells (Tregs)

(10). Thus, T cells do respond to BCR-ABL+ leukemia in this

mouse model, but the response was immunosuppressive in nature

and detrimental to host survival. In this study, we address whether

the immune response to leukemia could be modulated, thus making

BCR-ABL+ B-ALL malleable to checkpoint blockade–based T cell

immunotherapy.

Materials and MethodsMice

C57BL/6 mice and Cdkn2a2/2 (strain 01XF6, B6, 129-Cdkn2atm1Cjs/Nci) (11)mice came from the National Cancer Institute. Foxp3-GFP (stock no. 006772)and Ifng2/2 (stock no. 002287) mice came from The Jackson Laboratory (BarHarbor, ME). OT-I 3 Rag22/2 mice were generated locally as previouslydescribed (12). Mice were housed at the University of Minnesota in specificpathogen-free conditions or biosafety level 2 facilities, and all experimentswere approved by the Institutional Animal Care and Use Committee.

*Center for Immunology, University of Minnesota, Minneapolis, MN 55455;†Department of Laboratory Medicine and Pathology, University of Minnesota, Min-neapolis, MN 55455; ‡Department of Microbiology and Immunology, University ofMinnesota, Minneapolis, MN 55455; xCenter for Infectious Disease Dynamics, Penn-sylvania State University, University Park, PA 16802; {Department of Microbiology,Institute of Immunology, University of Pennsylvania Perelman School of Medicine,Philadelphia, PA 19104; ‖Medical Sciences, Amgen, Inc., Thousand Oaks, CA91320; and #Masonic Cancer Center, University of Minnesota, Minneapolis, MN55455

ORCIDs: 0000-0003-4781-7707 (L.S.M.); 0000-0003-4641-6872 (J.M.S.); 0000-0002-7200-5236 (K.R.M.); 0000-0002-5569-0366 (M.A.F.).

Received for publication January 21, 2016. Accepted for publication March 25, 2016.

This work was supported in part by National Institutes of Health Grant P30CA77598,which supports the University of Minnesota Flow Cytometry Resource. L.S.M. andJ.M.S. are supported by National Institutes of Health Fellowships F31CA183226 andF30DK100159, respectively. K.R.M. is supported by a Pennsylvania State Universityacademic computing fellowship. K.E.P. is supported by the Robertson Foundation/Cancer Research Institute Irvington Fellowship. M.A.F. is supported by NationalInstitutes of Health Grants R01CA151845, R01CA154998, R56AI113138, andR01CA185062, the University of Minnesota Masonic Cancer Center, and a Leukemiaand Lymphoma Society Scholar Award.

Address correspondence and reprint requests to Dr. Michael A. Farrar, University ofMinnesota Center for Immunology, 2-116 Wallin Medical Biosciences Building,2101 6th Street SE, Minneapolis, MN 55455. E-mail address: farra005@umn.edu

Abbreviations used in this article: B-ALL, B cell acute lymphoblastic leukemia;BAp, BCR-ABL peptide; IQR, interquartile range; LCMV, lymphocytic choriomen-ingitis virus; LCMV+BAp, lymphocytic choriomeningitis virus plus BCR-ABL pep-tide; LM+BAp, Listeria monocytogenes expressing BCR-ABL peptide; MHC-II,MHC class II; PC, principal component; PCA, principal component analysis; PD1,programmed death 1; PDL1, programmed death ligand 1; Treg, regulatory T cell;VSV, vesicular stomatitis virus; VSV+BAp, vesicular stomatitis virus plus BCR-ABLpeptide.

Copyright� 2016 by The American Association of Immunologists, Inc. 0022-1767/16/$30.00

www.jimmunol.org/cgi/doi/10.4049/jimmunol.1600130

Published April 25, 2016, doi:10.4049/jimmunol.1600130 at U

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Listeria monocytogenes generation

ActA–L. monocytogenes strain 1942 (from Dr. Sing Sing Way) expressingBAp from a plasmid was constructed as previously described (13–15).

Infections and immunizations

L. monocytogenes expressing BAp (LM+BAp) (107 CFU) was injected i.v.through the tail vein. Mice vaccinated with lymphocytic choriomeningitisvirus (LCMV)–Armstrong received 2 3 105 PFU i.p. at day 0. Vesicularstomatitis virus (VSV)–Indiana was used at 5 3 105 PFU i.v. at day 0. Atdays 3 and 5, mice were injected i.v. with 200 mg BAp. Mice were harvestedat indicated time points.

Leukemia model

Cdkn2a2/2 mouse bone marrow cells were transduced with viral super-natant containing a BCR-ABL (P190)–IRES-GFP retrovirus (16) and cul-tured for adoptive transfer as previously described (7, 9).

Tetramer production

Purified monomer was tetramerized with streptavidin-PE or streptavidin-allophycocyanin and cells were enriched as previously described (9, 17).

In vivo Ab treatment

Unvaccinated mice were treated with 100 mg anti–PD ligand 1 (PDL1) andanti-CTLA i.p. every other day. Vaccinated mice received 200 mg anti-PDL1 and anti-CTLA i.p. twice per week. Mice treated with anti-CD40received 200 mg i.p. every other day.

Abs

Abs for flow cytometry included CD3 PE, CD4 (RM4-5) PerCP-Cy5.5,CD8 (53-6.7) BV650, CD11c (N418) PE, FOXP3 (FJK16S) PE, CD80(16-10A1) allophycocyanin, CD86 (GL1) PE-Cy7, CD19 BV605, B220(RA3-6B2) Horizon V500, IFN-g (XMG1.2) BV650, LAP (TW7-16B4)PE, TNF-a (MP6-XT22) BV421, IL-17A (TC11-18H10) Alexa Fluor 488,and PSGL1 (2PH1) BV421 purchased from BD Biosciences (San Jose,CA); NK1.1 (PK136), CD11b (M1/70), CD11c (N418), B220 (RA3-6B2),and F4/80 in allophycocyanin–eFluor 780, and PD1 (J43) FITC, CD73eFluor 450, FR4 PE-Cy7, PDL1 PerCP–eFluor 710, MHC-II I-Ab eFluor450, IL-10 (JESS-16E3) PE, granzyme B (NGZB) PE-Cy7, GARP(YGIC86) eFluor 450, and all ELISPOT Abs were purchased from eBio-science (San Diego, CA); and IgM F(ab9)2 allophycocyanin was purchasedfrom Jackson ImmunoResearch Laboratories (West Grove, PA). Rat IgG1(HRPN) PerCP-Cy5.5 isotype and rat IgG2a (2A3) violet eFluor 450isotype were purchased from Tonbo Biosciences (San Diego, CA). Cellsfrom enriched fractions were analyzed on LSRII or Fortessa cytometers(BD Biosciences, San Jose, CA) and data were analyzed in FlowJo (TreeStar, Ashland, OR).

Statistics and principal component analysis description

Standard normality tests suggested departures from normality, and thusnonparametric tests (Mann–Whitney U test for two groups, Kruskal–Wallisand Dunn tests for more than two groups) were used unless otherwisestated. Normality assessments, nonparametric tests, and survival analyseswere done in GraphPad Prism (La Jolla, CA). For the Cox–Mantel tests,we report hazard ratios, which describe the multiplicative change in riskwhen moving from the baseline group to the treatment group. Principalcomponent analysis (PCA) was conducted in R (prcomp function) (18).Linear regressions and correlation coefficients were estimated in GraphPadPrism and R.

Detailed descriptions of the PCA and corresponding linear regression areincluded below. We performed a PCA on the following five phenotypemetrics collected on each mouse: PDL1, MHC-II, CD40, CD80, CD86. Weadded one to each metric, and then log transformed the resulting value sothat our data met the PCA assumption of joint normality. Components wereestimated using the prcomp function in the stats package in R.

First, pair plots of the raw manifest variables and log-transformedmanifest variables were created. PCA is a method for reducing the di-mension of a dataset by transforming an initial set of possibly correlatedmanifest variables into a set of new orthogonal variables, which are referredto as PCs. These components describe the multivariate correlation in thedataset. Although the method generates as many components as there aremeasured variables in the dataset, most of the variation can usually becaptured with only a few components. Each component consists of a valuethat describes the proportion of variation in the original dataset explained bythe component, and a set of loadings that describe the extent to which each

manifest variable correlates with that component. Let X be an n3 k matrixcontaining measurements of k different manifest variables for n sampledindividuals. Estimation is obtained through an eigen decomposition of thesquare matrix X9X. Eigenvalues correspond to proportions of variance inthe original dataset captured by each component, and eigenvectors describecorrelations between each manifest variable and each component. Al-though the method constructs as many PCs as there are manifest variablesin the dataset, interpretation is limited to those components that explainthe preponderance of variation. The number of components to interpret isoften determined using a scree plot, showing the proportion of varianceexplained by each component.

A scree plot for the components identified for the log-transformed im-munogenicity phenotype metrics is shown in Fig. 1D. Based on the screeplot, we interpreted the first two components. Loading of each manifestvariable on each component is shown in Table I.

We extracted PC scores for PC1 and PC2 for each mouse in our dataset.We used a linear regression model to relate these PC scores to percentageleukemic burden measured on these same mice. The regression modelconsisted of four terms: an intercept (b0), main effects for each PC (b1 andb2), and an interaction term between the two PCs (b3). Let yi be the per-centage leukemic burden in the ith studied mouse, let X1,i be the ith mouse’sPC1 score, and let X2,i be the ith mouse’s PC2 score. Then the regressionmodel we fit can be written as: yi = b0 + b1(X1,i) + b(X2,i) + b( X1,i)( X2,i) + εi.The model was fit using the lm function in R (1). An overall F test clearlysuggested that at least some of the coefficients in the model differed signifi-cantly from 0 (F statistic = 23.76 on 3 and 26 df; p, 0.0001). Specifically, themodel detected strong relationships between the first two PCs and leukemicburden, as well as a marginally significant interaction effect in our dataset.

In general, the intercept term corresponds to expected leukemic burdenfor mice with average scores on both PC1 and PC2. Specifically, under thismodel we expect that mice with average PC1 and PC2 scores have anaverage leukemic burden of 62.64%. Formicewith an average score of PC2,but who are 1 unit above average on PC1, we expect an average leukemicburden of 52.64% (62.64 2 10.00%). For mice with an average score onPC1, but who are 1 unit about average on PC2, we expect an averageleukemic burden of 43.34% (62.64 2 19.30%). For mice that are 1 unitabove average on both PC1 and PC2, we expect an average leukemicburden of 27.38% (62.640210.00219.3025.96%).

ResultsAdaptive immunity plays a role in the anti–BCR-ABL1 B-ALLresponse

We previously showed that there was a higher fraction of liveleukemic cells in the bone marrow and secondary lymphoid organsof OT-I 3 Rag22/2 mice than in C57BL/6 mice. Furthermore, therange of leukemic burdens was quite broad in the C57BL/6 hosts(interquartile range [IQR] = 11–69%) but less so in the OT-I 3Rag22/2 hosts (IQR = 90–98%) (9). To understand why there wassuch a range in leukemic burden, we looked for characteristicdifferences in the leukemic cells from mice with low versus highleukemic burden. Because B cells can function as APCs, we ex-amined the expression of MHC-II to stratify the leukemic burdenbased on expression of surface markers. MHC-II expression in-versely correlated with leukemic burden (mice that had a lowpercentage of leukemic cells in the bone marrow had high MHC-IIexpression on the leukemic cells; Fig. 1A). We also examined theexpression of the costimulatory molecules CD40, CD80, CD86,and PDL1. None of these costimulatory molecules individually cor-related with leukemic burden. Therefore, we used PCA to identifywhether there was an ensemble of costimulatory molecules that cor-related with leukemic burden (Fig. 1B). The first component describeda positive correlation between MHC-II, CD80, CD86, and PDL1. Thesecond component was driven by a negative correlation betweenCD40 and PDL1 (Fig. 1B). These first two components described77% of the variation in leukemic burden that we observed in mice(Fig. 1C, Table I). Mice that had low leukemic burden tended to havehigh scores for both PC1 and PC2 (Fig. 1D). Therefore, we usedlinear regression to examine relationships between the first two PCscores and leukemic burden (Fig. 1E). Both high PC1 and high PC2scores were associated with significantly decreased leukemic burden

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(p, 0.001, Fig. 1E). A low PC1 score (score of22) was predictive ofhigh leukemic burden (Fig. 1E, left panel) regardless of PC2 score. Incontrast, leukemias with higher PC1 scores (score of 0–2) showeddependence on PC2 in predicting leukemic burden (Fig. 1E). Takentogether, this analysis supports the conclusion that robust Ag presen-tation combined with CD80/86 costimulation (PC1), as well as a highratio of CD40/PDL1 (PC2), correlates with improved disease outcome.

Modulation of individual costimulatory molecules modestlyimproves survival of leukemic mice

Our PCA suggested that an ensemble of costimulatory molecules(CD80, CD86, PDL1, CD40) functioned as a cohesive unit to modulate

antileukemia immunity. Nonetheless, it was possible that in-dividual targeting of Ag presentation and costimulatory mole-cules might change the disease course. We tested whether Abtargeting of PDL1, CTLA4, or CD40 would be sufficient tochange leukemia progression. Ab blockade of PDL1 and CTLA4(either individually or in combination) led to a modest butsignificant increase in survival of leukemic mice (Fig. 2A–C).Additionally, treatment of leukemic mice with an anti-CD40 Abthat is characterized as an agonist also led to a modest yetsignificant increase in survival (19) (Fig. 2D). Thus, the com-ponents defined by our PCA do not individually identify veryeffective therapeutic targets in this model. These results support

FIGURE 1. Adaptive immunity plays a role in the anti-BCR-ABL+ B-ALL response. (A) Representative dot plots and histograms from five mice with

varying leukemic burden (gated as live, singlet, CD19+, B220low cells). Black curves are MHC-II, gray curves are isotype. Listed are the percentages of live

singlet events that fall into the CD19+, B220low gate. (B) Correlations of measured variables with first two PCs. PDL1, MHC-II, CD80, and CD86 correlate

positively with PC1; CD40 and (to a lesser extent) CD86 correlate positively, whereas PDL1 correlates negatively, with PC2. (C) Scree plots of PCs. The

y-axis shows proportion of variance accounted for by each PC. (D) Distribution of individual mouse scores on PCs 1 and 2. Mouse leukemic burden is

indicated by dot size and dot shade; larger white dots indicate mice with higher leukemic burden, and smaller black dots indicate mice with lower leukemic

burden. (E) Predicted leukemic burden as a function of PC2 scores at three separate levels of PC1 (low, average, and high). Gray regions denote 95%

confidence bounds. PCs were derived from 27 separate mice in three experiments.

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the concept that the molecules identified by our PCA are bestaddressed as an ensemble.

BAp-specific T cells can be primed by acute infection plusexogenous peptide

None of the immune checkpoint modulations we tested sub-stantially improved survival of leukemic mice. However, we havepreviously shown that Ly6C+ BAp:I-Ab–specific T cells corre-late with antileukemia immunity upon Treg depletion (9). Weattempted to recreate an inflammatory environment to generatemany Ly6C+ BAp:I-Ab–specific T cells. To do this, we infectedmice with LM+BAp, which caused a 65-fold increase in BAp:I-Ab–specific T cell numbers. In parallel, we infected mice witheither LCMV-Armstrong or VSV-Indiana and then delivered 200mg BAp i.v. at 3 and 5 d postinfection. This allowed us to use theinflammation caused by acute viral infection to induce a strongBAp:I-Ab–specific CD4+ T cell response (termed LCMV+BApor VSV+BAp). At peak infection LCMV+BAp caused a 74-foldproliferation of BAp:I-Ab–specific T cells, whereas VSV+BApcaused a 114-fold proliferation of BAp:I-Ab–specific T cells(Fig. 3A). These results show that BAp:I-Ab–specific T cellproliferation can be initiated by immunization. Additionally, wefound that LCMV+BAp induced a high frequency of Ly6C+

memory BAp:I-Ab–specific T cells following leukemia rechal-lenge, whereas LM+BAp induced substantially fewer Ly6C+

memory BAp:I-Ab–specific T cells following leukemia rechal-lenge (Fig. 3B). Because our previous work showed that Ly6Cwas expressed on most BAp:I-Ab–specific T cells upon Tregdepletion (which also resulted in significantly less leukemicburden and significantly longer survival of leukemic mice), we

reasoned that acute viral infections that result in increased Ly6Cexpression might induce protective BAp-specific immunity.

BAp-specific adaptive immunity confers long-term survival forleukemic mice

Our PCA suggested that MHC-II expression, and thus Ag pre-sentation, was important in describing the immune response toleukemia. We have identified one peptide from BCR-ABL (BAp)that is processed and presented on MHC-II in vivo (9). Thus,we hypothesized that immunization with BAp plus strongadjuvants might mediate protection from BCR-ABL+ B-ALLin mice. To test this, we infected mice with either LCMV-Armstrong (with and without BAp) or VSV-Indiana (with andwithout BAp) and rechallenged mice with BCR-ABL+ leukemia.40 d later, a memory time point when no acute inflammationremained (Fig. 3C). Mice that were infected with an acute viralpathogen plus BAp survived long-term. In contrast, mice thatwere infected with an acute viral pathogen in the absence ofBAp succumbed to leukemia rapidly. The hazard ratio com-paring all “+BAp” vaccinations to all “2BAp” vaccinations inFig. 3C was 0.24 with a 95% CI from 0.12 to 0.46 (p , 0.0001).Thus, BAp-specific adaptive immunity confers long-term sur-vival in this model. Because BAp only binds to MHC-II and notMHC class I (data not shown), our results support the conclu-sion that BAp:I-Ab–specific T cells are critical for protectingagainst BCR-ABL+ leukemia in our prophylactic vaccinationstudies.

IFN-g potentiates antileukemia immunity during prophylacticvaccination

In CD4+ T cells, IFN-g is normally produced by Th1 cells, whichcan have a role in antitumor immunity (20). We have previouslyshown that in unvaccinated mice most BAp:I-Ab–specific T cellsresponding to BCR-ABL+ leukemia are Tregs and thus are likelynot making IFN-g. Consistent with this idea, we found that the abilityof host T cells to make IFN-g in unvaccinated mice did not affectsurvival following leukemia inoculation, because Ifng2/2 hosts suc-cumbed to leukemia similarly to C57BL/6 hosts (Fig. 3D). How-ever, we hypothesized that IFN-g might play a role in the adaptiveimmune response to leukemia following prophylactic vaccination. To

Table I. SD, proportion of variance, and cumulative proportionaccounted for by each PC for the data plotted in Fig. 1

PC1 PC2 PC3 PC4 PC5

SD 1.67 1.05 0.73 0.73 0.26Proportion of variance 0.55 0.22 0.11 0.11 0.014Cumulative proportion 0.55 0.77 0.88 0.99 1.00

PC1 and PC2 together described 77% of the variation in leukemic burden.

FIGURE 2. Modulation of indi-

vidual Ag presentation and costim-

ulation molecules improves survival

of leukemic mice. (A) C57BL/6

mice were inoculated with 2500

leukemic cells and treated every

other day with 100 mg anti-PDL1

until moribund. (B) Mice were

treated as in (A), except with 100 mg

anti-CTLA4. (C) Mice were treated

as in (A), except with 100 mg anti-

PDL1 plus 100 mg anti-CTLA4. (D)

Mice were treated as in (A), except

with 200 mg anti-CD40. Two or

more independent experiments with

four or more replicates are shown in

each group; the log-rank (Mantel–

Cox) test was used to establish

significance in all panels.

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test this, we vaccinated Ifng2/2 mice with LCMV-Armstrong+BApand rechallenged with leukemia at .40 d postvaccination. Vaccina-

tion of IFN-g–deficient mice did not increase survival following

challenge with leukemia, when compared with unvaccinated control

mice. In contrast, vaccination of Ifng-replete mice resulted in signif-

icant long-term survival when compared with unvaccinated controls

(Fig. 3E). Thus, IFN-g production was one mechanism required for

effective antileukemia immunity following prophylactic vaccination.

Specific pathogens mediate effective prophylactic vaccinationfor BCR-ABL+ B-ALL

Immune memory is a critical component of prophylactic vacci-nation. To determine whether effective BAp:I-Ab–specific memoryT cells were formed by vaccination, we infected mice with LM+BApor LCMV+BAp and waited 40 d to enumerate BAp:I-Ab–specificmemory T cells. We recovered significantly more memory BAp:I-Ab–specific T cells from LCMV+BAp–infected mice than from

FIGURE 3. Prophylactic vaccination with

BAp allows long-term survival in leukemic

mice. (A) Naive mice (N) were immunized

with CFA+BAp, LM+BAp, LCMV+BAp, or

VSV+BAp. Secondary lymphoid organs were

harvested at peak infection or 2 wk post-

immunization (CFA+BAp) and BAp:I-Ab–spe-

cific T cells were enumerated. More than two

independent experiments are shown for each

infection. Kruskal–Wallis and Dunn tests were

used to establish significance. (B) Percentage

Ly6C+ BAp:I-Ab–specific T cells from mice

vaccinated with either LM+BAp or LCMV+BAp

at day 0 and then rechallenged with leukemia at

day 30. Two or more independent experiments

with four or more replicates conducted for each

infection were used. A Mann–Whitney U test

was used to establish significance. (C) Mice were

vaccinated with LCMV-Armstrong with/without

BAp or VSV-Indiana with/without BAp. More

than 40 d later, mice were rechallenged with

2500 leukemic cells and survival assessed by a

log-rank (Mantel–Cox) test. Shown are three or

more independent experiments with eight or

more replicates used for each group. (D) Two

thousand five hundred BCR-ABL+ leukemic

cells were adoptively transferred into control

C57BL/6 mice or Ifng2/2 mice. Survival was

analyzed using the log-rank (Mantel–Cox) test.

(E) Control C57BL/6 mice or Ifng2/2 mice were

vaccinated with LCMV-Armstrong+BAp and

challenged with 2500 leukemic cells as in (B). A

log-rank (Mantel–Cox) test was used to establish

significance. Shown are two or more indepen-

dent experiments with seven or more replicates

used in each group.

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LM+BAp–infected mice (Fig. 4A). We then vaccinated mice witheither LCMV+BAp or LM+BAp and rechallenged them by trans-ferring 2500 leukemic cells into the mice 30 d later. Vaccinationwith LCMV+BAp, but not LM+BAp, led to a significant increasein the number of BAp:I-Ab–specific T cells following leukemiachallenge and decreased leukemic burden (4-fold, Fig. 4B, 4C).Thus, the increase in BAp:I-Ab memory T cell numbers followingLCMV+BAp but not LM+BAp vaccination correlated with diseaseoutcome.The quality and quantity of BAp:I-Ab-specific memory T cells

was different comparing LM+BAp vaccination to LCMV+BApvaccination. We observed that the IQR of leukemic burdens in themice vaccinated with LCMV+BAp was broad (IQR = 1.4 3 106,Fig. 4C), showing that protection mediated by LCMV+BAp vacci-nation was more effective in some mice than in others. We previ-ously observed that Ly6C expression was increased on BAp:I-Ab–specific T cells when Tregs were depleted (9). Therefore, we examinedwhether Ly6C expression on BAp:I-Ab–specific T cells correlated withleukemic burden. Mice with high leukemic burden despite prophy-lactic vaccination (and thus considered “failed vaccinated mice”) hada significantly lower percentage of Ly6C+ BAp:I-Ab–specific T cellsthan did the “successfully vaccinated mice” (Fig. 4D). Additionally,significantly more BAp:I-Ab–specific T cells expressed Ly6Cafter LCMV+BAp vaccination (which lowered leukemic burden)

than did LM+BAp (which had no effect on leukemic burden)(Fig. 3B). Importantly, the number of Ly6C+ BAp:I-Ab–specific T cells was inversely correlated with leukemic burden inLCMV+BAp–vaccinated mice (Fig. 4E). In contrast, leukemicburden did not correlate with total CD4+Ly6C+ cells in these mice(Fig. 4F). We also observed that Tregs made up a smaller portionof the BAp:I-Ab–specific T cell population in mice that wereprophylactically vaccinated with LCMV+BAp than in unvacci-nated mice (Fig. 4G). These results support a functional role forLy6C+FOXP32 BAp:I-Ab–specific T cells during the immuneresponse to leukemia following prophylactic vaccination.

Ag presentation and costimulation on leukemic cells aremodulated by prophylactic vaccination

Our PCA suggests that high ratios of CD40/PDL1 and MHC-II/PDL1 may be predictive of low leukemic burden. We examinedthe leukemic cells from LCMV+BAp–vaccinated mice and LM+BAp–vaccinated mice. First, we found that leukemias in mice that weresuccessfully vaccinated with LCMV+BAp had higher expres-sion of CD40 and MHC-II than did their “failed vaccination”counterparts (Fig. 5A, 5B). Second, we found that CD40/PDL1and MHC-II/PDL1 increased on LCMV+BAp–vaccinated mice(which was an effective vaccination regimen, Fig. 5C, 5D) butnot significantly on LM1BAp–vaccinated mice (an ineffective

FIGURE 4. Prophylactic vaccination induces protective immune responses against BCR-ABL+ leukemia. (A) Mice were infected as in Fig. 3A and rested

30 d, when BAp:I-Ab–specific T cells counts were compared with those in naive mice. Shown are BAp:I-Ab–specific log(y + 1) T cell counts of BAp:I-Ab–

specific memory cells following vaccinations, gated on CD11ahighCD44high cells. (B) Mice were unvaccinated or vaccinated with LCMV+BAp or LM+BAp,

and 2500 BCR-ABL+ cells were transferred 30 d postinfection. Shown are BAp:I-Ab–specific log(y + 1) T cell counts; two or more independent experiments

are shown for each infection. (C) Mice were treated as in (B), and leukemic burden was analyzed. Lines are median values; numbers represent fold

changes in median. (D) Percentage Ly6C+ on BAp:I-Ab–specific T cells harvested from LCMV+BAp–vaccinated mice. (E) Ly6C+ BAp:I-Ab–specific T cell

count negatively correlates with leukemic burden from secondary lymphoid organs. Spearman correlation r = 20.8201, p , 0.05. (F) Ly6C+CD4+ T cell

count does not correlate with leukemic burden from secondary lymphoid organs. Spearman correlation r = 0.3515, p . 0.05. (G) Percentage BAp:I-Ab–

specific Tregs recovered from leukemic Foxp3-GFP mice unvaccinated or vaccinated with LCMV+BAp. All comparisons were done by Kruskal–Wallis and

Dunn tests (more than two groups) or a Mann–Whitney U test (two groups). Two or more independent experiments with four or more replicates are shown for

each group.

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vaccination regimen, Fig. 5E, 5F). Thus, prophylactic vaccinationwith acute viral pathogens plus BAp results in protection fromleukemia and correlates with expression of the biomarkers that wepreviously demonstrated were linked to strong antileukemia im-mune responses (Fig. 1).

Therapeutic heterologous vaccination drives long-termsurvival

We hypothesized that a proinflammatory environment mightcounter leukemia-derived immune suppression while also in-ducing BAp-specific adaptive immunity, and thus inhibit leukemiaprogression. To test this hypothesis, we therapeutically vaccinatedmice, which had established leukemia, using either homologousvaccinations with LCMV-Armstrong+BAp or heterologous vac-cinations with LCMV-Armstrong+BAp, LM+BAp, and VSV-Indiana+BAp (Fig. 6A). Homologous vaccination with LCMV+BApsignificantly prolonged survival, although all mice ultimately suc-cumbed to leukemia. Heterologous vaccination should create amore robust proinflammatory response, because Abs created duringthe primary infection will not neutralize the secondary and tertiaryinfections. Indeed, heterologous vaccination was significantly moreeffective and led to long-term survival (more than twice the medianuntreated survival) in ∼10% of mice. Thus, repeated vaccinationwith heterologous agents was an effective treatment strategy in micewith BCR-ABL+ B-ALL.The immune response to acute viral and bacterial infection is ca-

nonically proinflammatory. However, because mice with active leu-kemia have high doses of leukemia Ags during this proinflammatory

state, this may cause chronic Ag stimulation, a situation where PDL1signaling is highly expressed (21). Additionally, our initial findingsshowing that CD44 was not highly expressed on all BAp:I-Ab–specificT cells responding to leukemia suggest that BAp-specific T cellpriming is not optimal (9). CTLA4 blocks interaction of CD28 withB7-1 and B7-2 molecules, thereby reducing T cell functionality (22–24). Thus, we hypothesized that therapeutically vaccinated mice thatwere treated with dual PDL1/CTLA4 checkpoint blockade mightshow improved survival. This treatment strategy led to a significantincrease in survival beyond that seen for either PDL1+CTLA4blockade (Fig. 2C) or therapeutic vaccination (Fig. 6A), with 31%of mice surviving long-term. Because this long-term survival is farpast the time point when inflammation would remain from the ther-apeutic vaccination, it suggests that an adaptive immune response ismediating long-term survival.To understand some of the mechanisms allowing effective ther-

apeutic vaccination, we compared homologous, heterologous, andheterologous plus checkpoint blockade treatments and assessedBAp:I-Ab–specific T cell expansion and effector function. To dothis, we inoculated mice with BCR-ABL+ leukemia and startedtherapeutic vaccination at the same time point. We then harvestedthe mice 21 d later and enumerated BAp:I-Ab–specific T cells. Wefound that all regimens induced robust proliferation (∼1250-foldover naive precursor numbers); however, there was no differencein the number of BAp:I-Ab–specific T cells recovered between anyof the three treatment groups (Fig. 6B). Because total numbers ofBAp:I-Ab–specific T cells did not help give insight into themechanisms that allowed effective therapeutic vaccination, we

FIGURE 5. Prophylactic vaccination induces Ag presentation and costimulation on leukemic cells. (A) Mice were vaccinated with LCMV+BAp and

inoculated with leukemia 30 d later. CD40 mean fluorescence intensity from leukemic cells harvested from successfully vaccinated mice or failed vac-

cinated mice derived from Fig. 4C. A Mann–Whitney U test was used to establish significance. (B) MHC-II mean fluorescence intensity from leukemic cells

harvested from successfully vaccinated mice or failed Vaccinated mice. A Mann–Whitney U test was used to establish significance. (C) Ratio of mean

fluorescence intensity of CD40/PDL1 on leukemic cells was calculated from mice vaccinated with LCMV+BAp, and a correlation was calculated between

this ratio (x-axis) and the log leukemic cell count (y-axis). (D) Ratio of mean fluorescence intensity of MHC-II/PDL1 on leukemic cells was calculated from

mice vaccinated with LCMV+BAp, and a correlation was calculated between this ratio (x-axis) and the log leukemic cell count (y-axis). (E) Ratio of mean

fluorescence intensity of CD40/PDL1 on leukemic cells was calculated from mice vaccinated with LM+BAp, and a correlation was calculated between this

ratio (x-axis) and the log leukemic cell count (y-axis). (F) Ratio of mean fluorescence intensity of MHC-II/PDL1 on leukemic cells was calculated from

mice vaccinated with LM+BAp, and a correlation was calculated between this ratio (x-axis) and the log leukemic cell count (y-axis). The values on graphs

are from the Spearman correlation test. Two or more independent experiments with four or more replicates are shown for each group.

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examined the phenotype of the BAp:I-Ab–specific T cells. Wereasoned that BAp:I-Ab–specific T cells should take on a moreTh1-like phenotype in response to therapeutic vaccination, andthat this phenotype should correlate with improved disease out-come. However, we found no significant increase in IFN-g orTNF-a (two canonical Th1 cytokines) when comparing all threetreatment groups. Interestingly, in mice that received heterologousvaccination plus checkpoint blockade, we found that a largerfraction of BAp:I-Ab–specific T cells produced more IL-10,granzyme B, and both IL-17 and granzyme B together (Fig. 7A,7C–F), all of which have previously been associated with proin-flammatory tumor clearance (25–28). Additionally, we found thatPD1 expression on BAp:I-Ab–specific T cells positively correlated

with leukemic burden in all therapeutically vaccinated mice(Fig. 7B), and that PD1 expression was lowest on these cells inheterologous vaccination plus checkpoint blockade–treated mice(Fig. 7A). Taken together, these results demonstrate that poly-functional CD4+ leukemia-specific T cells produce a combinationof IL-10, IL-17, and granzyme B, and this correlated with effec-tive antileukemia adaptive immunity.

DiscussionBCR-ABL+ B-ALL is only transiently responsive to currenttherapies (29), with a 5-y survival of ∼35% (30, 31). Given thislow survival rate, additional therapies are needed. One approachthat has not been well explored in this disease is checkpoint

FIGURE 6. Therapeutic vaccination synergizes with checkpoint blockade to improve outcome. (A) Mice were inoculated with 2500 BCR-ABL+ leu-

kemic cells at day 0 and then rechallenged with one of four different treatments: 1) no treatment (black); 2) homologous vaccination with LCMV-

Armstrong at days 7, 14, and 21, with 200 mg exogenous BAp delivered i.v. at 3 and 5 d postinfection (days 10, 12, 17, 19, 24, and 26) (brown); 3)

heterologous vaccination with LCMV-Armstrong at day 7, LM1BAp at day 14, and VSV-Indiana at day 21, with with 200 mg exogenous BAp delivered i.v.

at 3 and 5 d postinfection (days 10, 12, 17, 19, 24, and 26) (blue); and 4) as in no. 3, except with 200 mg anti-PDL1 and 200 mg anti-CTLA4 twice per week

from day 7 to day 80 (green). Surviving mice were euthanized at day 80 after leukemia inoculation. Shown are survival curves; a log-rank (Mantel–Cox)

test was used to analyze statistics. (B) Mice were treated as in (A), but treatment was started on the same day as leukemia challenge. Mice were euthanized

at day 21 and BAp:I-Ab–specific T cells were harvested and enumerated. Shown are BAp:I-Ab–specific log(y + 1) T cell counts; two or more independent

experiments are shown for each infection. Groups were compared with Kruskal–Wallis and Dunn tests; no significant differences were found. Two or more

independent experiments with $10 replicates are shown for each group.

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blockade–based immunotherapy. Checkpoint blockade works wellin malignancies with many nonsynonymous mutations and canlead to improved long-term survival in patients with such cancers(4, 32–36). Presumably, this is because the increased number ofnonsynonymous mutations allows for a concurrent increase in thenumber of neoantigen-specific T cells. Comparatively, in cancerswith low numbers of nonsynonymous mutations, such as B-ALL(36), checkpoint blockade–based immunotherapy targeting theendogenous immune response is relatively unstudied. In fact,current paradigms suggest that cancers with low numbers ofnonsynonymous mutations may not be effectively treated usinganti-CTLA4 and anti-PD1 checkpoint blockade (35). In the pre-sent study, we show that an endogenous T cell response can beeffective in controlling BCR-ABL+ B-ALL, but this requires bothcheckpoint blockade and an intensive heterologous vaccinationstrategy.In this study, we found that a strong immune response correlated

with decreased leukemic burden. MHC-II expression on leukemiccells correlated with disease outcome, which hinted that CD4+

T cells were important for antileukemia immunity. We have pre-viously shown that the leukemia Ag BAp is presented on MHC-II(9). In contrast, BAp does not bind to MHC class I in C57BL/6mice (data not shown). These findings, in combination with ourstudies showing that the presence of BAp during prophylacticvaccination is required for protection from leukemia (Fig. 3C),provide evidence supporting a role for MHC-II–mediated pre-sentation of BAp in antileukemia immunity. Moreover, an effec-tive antileukemia immune response requires IFN-g and correlateswith increased induction of Ly6C on the BAp:I-Ab–specific T cells(Fig. 3D, 3E).Our PCA strongly suggested a role for targeting the immune

checkpoint molecules PDL1 and CTLA4 as part of a therapeuticstrategy for BCR-ABL+ B-ALL. Costimulatory and coinhibitorymolecules play a role in cancer progression (4, 37–42). In ourmodel we observed statistically significant increases in survivalupon monotherapy with either anti-PDL1 or anti-CTLA4, or dualcheckpoint blockade therapy with both anti-PDL1 and anti-CTLA4. However, despite achieving statistical significance, theeffects of checkpoint blockade alone were modest (increasedsurvival of 2–4 d), and thus possibly of limited biological impact.The limited impact of checkpoint blockade treatment alone inBCR-ABL+ leukemia fits prevailing concepts regarding check-point blockade. Current models suggest that cancers with lownumbers of nonsynonymous mutations will not be susceptible tocheckpoint blockade (35, 36). Our leukemia model likely hasfew nonsynonymous mutations, and checkpoint blockade is notvery effective in this leukemia model. Thus, our observations areconsistent with the idea that small numbers of nonsynonymousmutations result in poor anticancer responses following check-point blockade therapy.Immune checkpoint blockade therapy alone was only mini-

mally effective in treating leukemic mice in our model. Thus, weexplored therapeutic vaccination immunotherapy. Two lines of evi-dence precipitated this strategy. First, previous reports show thattherapeutic heterologous vaccination can be effective in other cancers,albeit those with higher mutation rates (43). Second, it was clear thatMHC-II–mediated Ag presentation was important for leukemia out-come, and the pathogens used in our therapeutic vaccination schemeall induce MHC-II expression on APCs (44–46). When micewere therapeutically vaccinated with these MHC-II–inducing proin-flammatory pathogens, we saw increased survival (Fig. 6). We usedheterologous vaccination because this approach has previously beenshown to be effective at inducing a robust T cell response (47–49). Inthis approach, we used multiple infectious adjuvants to generate a

proinflammatory environment that should promote robust adaptiveimmune activation. Similar approaches have been used prophylacti-cally (47) and therapeutically for cancer (43, 49). However, our studyexamines therapeutic heterologous vaccination in combination withcheckpoint blockade specifically to target CD4+ T cells in cancer, anunderexplored field.We found that therapeutic vaccination synergized with anti-

PDL1 and anti-CTLA4 therapies to improve long-term survivalin mice with BCR-ABL+ leukemia. Thirty-one percent of the micethat received therapeutic heterologous vaccination in combinationwith anti-PDL1 and anti-CTLA4 checkpoint blockade exhibitedlong-term survival. In contrast, only 10% of mice treated withtherapeutic heterologous vaccination alone survived long-term.Furthermore, no leukemia-bearing mice treated therapeuticallywith checkpoint blockade alone exhibited long-term survival.These results suggest that even malignancies with few non-synonymous mutations (such as B-ALL) can be responsive toimmunotherapies that classically work well only in malignancieswith high levels of nonsynonymous mutations (35). Importantly,such results are contingent upon intensive therapeutic vaccinationapproaches. One possible explanation for the synergistic effect ofvaccination plus checkpoint blockade is that leukemia-derived Agis available for the entire duration of the therapeutic vaccinationregimen. This chronic Ag stimulation may lead to continual highexpression of PDL1 and CD80/86 on leukemic cells, which mayexplain the synergy between therapeutic vaccination (which issusceptible to inhibition by PDL1/PD1 and CD80/86/CTLA4pathways) and dual checkpoint blockade (which inhibits thosepathways). Finally and importantly, note that oncolytic viruses(which include VSV, used in our scheme) have been used foranticancer immunotherapy in the past (50) and are currently beingused in clinical trials as a treatment option for cancer (51, 52).Thus, the approach taken to treat leukemia in our murine model isfeasible to consider for human patients with BCR-ABL+ leukemia.Our data provide initial mechanistic insights into how thera-

peutic vaccination therapy plus checkpoint blockade can lead toleukemia rejection by the C57BL/6 host. First, we saw a trendtoward decreased PD1 expression on BAp:I-Ab–specific T cellsthat correlated significantly with decreased leukemic burden(Fig. 7A, 7B). Checkpoint blockade could interfere with this po-tential mechanism of tolerance induction. Second, during thetherapeutic vaccination response, we saw that many BAp:I-Ab–specific T cells were polyfunctional (producing granzyme B andmultiple cytokines such as IFN-g, TNF-a, IL-10, and IL-17).Importantly, in the most effective vaccination regimen (thera-peutic heterologous vaccination plus checkpoint blockade), wesaw a significantly increased fraction of BAp:I-Ab–specific T cellsthat produced granzyme B, IL-10, and a combination of granzymeB plus IL-17. This observation demonstrates that effective thera-peutic vaccination induces formation of polyfunctional leukemia-specific CD4+ T cells. Future studies are needed to delineate theimportance of these cytokines and granzyme B expression. How-ever, it is intriguing that although IL-10 is more typically associatedwith immunosuppression, previous literature supports a role forT cell–derived IL-10 in antitumor immunotherapy (25, 53, 54).Additionally, IL-17 and granzyme B have both been implicated inT cell responses to cancer (26, 28, 55). Thus, we envision twopossibilities for how and when BAp:I-Ab–specific T cells mightelicit antileukemia immunity after therapeutic vaccination. First,because the most effective therapeutic vaccination regimen weused (heterologous vaccination plus checkpoint blockade) yieldedthe greatest fraction of granzyme B–producing BAp:I-Ab–specificT cells, it is possible that these cells directly kill MHC-II+ BCR-ABL+ leukemic cells. Second, it is possible these polyfunctional

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BAp:I-Ab–specific T cells induce BAp:I-Ab–specific memoryT cells, which may be required for long-term leukemia control. Insupport of this idea, Th17 cells responding to tumors in other

models have a long lifespan, which may be associated withmemory formation (28, 56). Therefore, our observations supportthe idea that polyfunctional BAp:I-Ab–specific T cells are induced

FIGURE 7. BAp:I-Ab–specific T cell–derived cytokines change in response to therapeutic vaccination. (A) BAp:I-Ab–specific T cells were harvested

from mice as in Fig. 6B and restimulated ex vivo with PMA and ionomycin to analyze potential cytokine production. Shown are concatenated data from 10

individual mice in two or more independent experiments. Numbers in histograms represent median fluorescence intensities. (B) PD1 expression on

BAp:I-Ab–specific T cells was analyzed and linear regression was used to compare with leukemic burden in the same mouse. Data from Spearman

correlation are shown. (C) Based on concatenated histograms from (A), gates were drawn to delineate “positive” versus “negative” fractions of cells and

applied to individual mice. Percentage positive is shown on the y-axis for IL-10. (D) Data were acquired as in (C) and granzyme B was analyzed. (E)

Percentage of BAp:I-Ab–specific T cells that are double-positive for IL-17 and granzyme B is shown and analyzed as in (C) and (D). Results in (C)–(E)

were analyzed by Kruskal–Wallis and Dunn tests. (F) BAp:I-Ab–specific T cells were harvested as in (A), and concatenated events from 10 mice were

gated to show IL-17+, granzyme B+ percentages of BAp:I-Ab–specific T cells. Numbers on the graph are percentage of double-positive events in the

gates as shown. Two or more independent experiments with $10 replicates are shown for each group.

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by intensive therapeutic vaccination, and that these cells contrib-ute to effective leukemia control.The current paradigm suggests that neoantigen-specific T cells

respond better to tumors because the repertoires of these cellshave not been pruned by thymic central tolerance (36). This ideaimplies that cross-reactive T cells will respond poorly to tumorsbecause the repertoires of these cells have been limited by thymiccentral tolerance. We have previously shown that BAp:I-Ab–specific T cells are cross-reactive with self-Ag and that the BAp:I-Ab–specific T cell repertoire is limited by thymic central toler-ance (9). Nonetheless, we observed in this study that BAp-specificadaptive immunity is crucial for antileukemia immunity followingprophylactic vaccination. Thus, our observations provide a coun-terpoint to the idea that neoantigen-specific T cells are a prereq-uisite for effective endogenous anticancer T cell responses (36).Taken broadly, our observations suggest that fusion proteins cre-ated by chromosomal translocations may be viable immunother-apy targets even when the fusions do not create neoantigens. Thisis particularly relevant because chromosomal translocations oftenresult in “driver” mutations, thus leaving minimal opportunity forcancer immunoediting to occur.Checkpoint blockade is thought to work best in tumors with high

numbers of nonsynonymous mutations (35). Our results supportthis concept, as checkpoint blockade was only minimally effectivein B-ALL, a leukemia that generally has lower numbers of non-synonymous mutations (5). However, we also demonstrate thatintensive heterologous vaccination synergizes with checkpointblockade to unmask a strong immune response that is capable ofcontrolling this highly aggressive and uniformly fatal form ofleukemia in mice. In conclusion, our work establishes that im-munotherapy approaches can induce long-term survival withB-ALL, even though mice with B-ALL are refractory to check-point blockade–based immunotherapy (36).

AcknowledgmentsWe thank Gregory Hubbard, Alyssa Kne, Christopher Reis, Amy Mack,

and Emilea Sykes for assistance with mouse husbandry, Justin Taylor for

experimental design, Markus Muschen for BCR-ABL–IRES-GFP retro-

virus, Christine Henzler for statistical advice, and Lynn Heltemes-Harris,

Casey Katerndahl, and Dan Kaplan for commentary on the manuscript.

David Masopust and Marc Jenkins contributed ideas and reagents, partic-

ularly in support of the vaccination regimens.

DisclosuresR.T.W. is currently an employee at Amgen, Inc. Thework in this manuscript

was completed prior to his accepting a position there. His previous em-

ployer, Puma Biotechnology, has no interests in leukemia, and thus we

do not think there is an inherent conflict of interest. The interaction with

R.T.W. dates back to the time when he was an Asst. Prof. at St. Jude Chil-

dren’s Research Hospital (Memphis, TN). The other authors have no

financial conflicts of interest.

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