Human Papilloma Virus Speciﬁc Immunogenicity and ...Tumor Biology and Immunology Human Papilloma Virus Speciﬁc Immunogenicity and Dysfunction of CD8þ T Cells in Head and Neck

Tumor Biology and Immunology

Human Papilloma Virus Specific Immunogenicityand Dysfunction of CD8þ T Cells in Head andNeck CancerSri Krishna1,2, Peaches Ulrich1,3, Eric Wilson1, Falguni Parikh4, Pooja Narang3,Shanshan Yang5, Amelia K. Read6, Seunghee Kim-Schulze7, Jin G. Park1, Marshall Posner8,Melissa A.Wilson Sayres3,9, Andrew Sikora4, and Karen S. Anderson1,3

Abstract

Human papillomavirus subtype 16 (HPV16) is the pri-mary cause of an increasing number of head and necksquamous cell carcinomas (HNSCC), providing strongrationale for T-cell immune therapies against HPVþHNSCC.Here we assess immunogenicity of HPV16-specific CD8þ Tcells (CTL) and characterize HPV-specific mechanisms ofT-cell dysfunction. We identified 16 strong and 29 moder-ately immunogenic CTL-epitopes from HPV16 E2, E6, andE7 antigens restricted by 12 common HLA class I alleles.E2-specific CTL-reactivity was higher in patients with HPVþ

HNSCC than in healthy controls (>3-fold; P ¼ 0.026).Patient-derived E2, E6, and E7 peripheral CTLs exhibitedheterogeneity in dysfunctional phenotypes. Immunoge-nomic analyses of 119 HNSCC transcriptomes revealed highT-cell infiltration and dysfunction in HPVþ HNSCC andcorrelation of HPV antigen expression with T-cell exhaus-tion gene signatures. Indoleamine 2,3-dioxygenase (IDO-1)was strongly expressed in HPVþ HNSCC versus HPV�

HNSCC (P ¼ 0.001) and correlated with E7 expression

(R2 ¼ 0.84; P ¼ 0.033). Combination treatment with PD-1blockade and IDO-1 inhibition overcame profound CTL-dysfunction, enhancing HPVþ HNSCC sensitivity to CTL-cytotoxicity in vitro (up to 10-fold in E7-CTLs, P ¼ 0.011).Our findings implicate mechanisms of T-cell escape in HPVþ

HNSCC, wherein high tumoral HPV-antigen load results inhigh expression of immune dysfunction genes on tumorcells (e.g., IDO-1), and dysfunction of HPV-specific CTLs(e.g., E7, E2-CTLs). The HPV16 CTL-epitopes identified inthis study, in combination with blockade of HPVþ HNSCC-specific PD-1/IDO-1 checkpoints, may be useful for targetedimmunotherapy.

Significance: This study evaluates the HPV antigen T-cellimmunogenicity role of inhibitory receptors andother exhaus-tion markers in the cytotoxic function of HPV antigen-specificCTLs and identifies combined inhibition of PD-1/IDO-1 asa strategy to enhance CTL targeting of HPVþ HNSCC. CancerRes; 78(21); 6159–70. �2018 AACR.

IntroductionHead and neck squamous cell carcinoma (HNSCC) is the sixth

most common cancer worldwide with close to 600,000 cases

diagnosed annually (1). A subset of HNSCCs in the oropharynxare caused by the humanpapillomavirus (HPV), (HPVþHNSCCs;ref. 2), which are molecularly and clinically distinct from non-HPV-associated HNSCCs (HPV� HNSCCs; ref. 3). In the UnitedStates, 70% to80%ofHPVþHNSCCs are caused by the oncogenicHPV type 16 (HPV16; ref. 4). Incidence of HPVþ HNSCCincreased 225% from 1984 to 2004 and has now surpassed theincidence of cervical cancer (5). AlthoughHPVvaccines effectivelyprevent HPV-related cancers, the impact of vaccination onHNSCC incidence may not occur until 2060, likely due in partto slow vaccine uptake, and the decades between infection andclinical HPVþ HNSCC diagnosis (6). As a result, over 600,000cases are predicted in the interim, providing a strong rationalefor the development of novel therapeutic strategies againstHPVþ HNSCC.

The recent development of clinically effective tumor immu-notherapies, such as checkpoint blockade (CKB) using PD-1/PD-L1 inhibitors (7, 8), has led to FDA approval of nivolumabandpembrolizumab forHNSCC (9, 10). It is now established thatthe clinical response to CKB is correlated with tumor neo-epitopeload. Tumor-specific neo-epitopes have been directly targetedusing therapeutic vaccines and/or adoptive T-cell therapy (ACT),and have been shown to enhance cytotoxic T-cell targetingof multiple solid tumors (11–13). Thus, there is a renewedinterest in defining the HLA-restricted antigenic repertoire of

1Biodesign Center for Personalized Diagnostics, Arizona State University,Tempe, Arizona. 2School of Biological and Health Systems Engineering, ArizonaState University, Tempe, Arizona. 3School of Life Sciences, Arizona StateUniversity, Tempe, Arizona. 4Department of Otolaryngology and Head andNeck Surgery, Baylor College of Medicine, Houston, Texas. 5Biodesign InstituteBioinformatics Core Facility, Arizona State University, Tempe, Arizona.6Department of Otolaryngology, Stanford University, Stanford, California.7Human Immune Monitoring Center, Icahn School of Medicine at Mount SinaiMedical Center, New York, New York. 8Tisch Cancer institute, Icahn School ofMedicine at Mount Sinai Medical Center, New York, New York. 9Center forEvolution and Medicine, Arizona State University, Tempe, Arizona.

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

Current address for S. Krishna: Surgery Branch, National Cancer Institute,Bethesda, Maryland.

Corresponding Author: Karen S. Anderson, Arizona State University, 727 E.Tyler St., Tempe, AZ 85287. Phone: 480-965-6982; Fax: 480-727-7351; E-mail:[email protected]

doi: 10.1158/0008-5472.CAN-18-0163

�2018 American Association for Cancer Research.

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tumor-infiltrating lymphocytes (TIL) to develop targetedtherapeutic vaccines (14), to identify T-cell receptors (TCR) forACT (11), and to monitor clinical responses to complex cancerimmunotherapies (15, 16).

HPV-associated cancers express multiple viral antigens. HPVintegration into host genome in cervical cancer results in dere-pression of the oncogenic drivers E6 and E7 (17). Immunetherapies targeting E6 andE7have thus beendeveloped, includingpeptides, DNA, and ACT therapies (14, 18, 19). However, incomparison to cervical cancer, HPVþ HNSCCs have both lowerrates of genome integration, and less interruption of the viraltranscriptional regulatory gene E2 (2, 20, 21). Thus, subsets ofHPVþ HNSCCs also express E2 in addition to E6 and E7 (2, 22).

We and others have previously shown that high titers of serumantibodies against HPV16-E2, E6, and E7 are detectable in mostpatients with HPVþ HNSCC, indicating immunogenicity andpersistence of these antigens (23, 24). We thus hypothesized thatpatients with HPVþHNSCCwould have preexisting HPV-specificCD8þT cells (CTL), and thatHPV-antigen expression levelswouldinfluence CTL-dysregulation in tumor microenvironment. Weidentified the T-cell antigenic landscape of globally frequentHLA class I alleles from HPV16 E2, E6, and E7. By phenotypingHPV-specific CTLs from patients with HPVþ HNSCC, and ana-lyzing the immune transcriptomes of 119 HNSCCs, we demon-strate intratumoral and peripheral CTL-dysfunction in HPVþ

HNSCC.We show that this CTL-dysfunction can be reversed usingtargeted HPV-specific T-cell expansion, and synergistic inhibitionof IDO-1 and PD-1. These results have implications for thedevelopment of effective T-cell therapies for HPVþ HNSCC.

Materials and MethodsHPV16 candidate CTL-epitope prediction

HPV16-candidate CTL epitopes were predicted using previous-ly described prediction strategies developed by us (25, 26), exceptfor the incorporation of immunogenicity scores. For the 15 HLA-class I alleles, 9-mer and 10-mer candidate epitopes derived fromthe HPV16 proteins E2, E6, and E7 were predicted from fiveindependent prediction algorithms and normalized. Top four tofive candidate peptides/HLA-allele were used for in vitro experi-ments. Further details are provided in Supplementary Materialsand Methods. Predicted candidate HPV16-peptides, individualnormalized, and total binding percentile scores are listed inSupplementary Table S1. For full list of candidate peptides, seeSupplementary Table S2.

Epitope mapping from HPVþ HNSCC peripheral bloodmononuclear cells

Peripheral blood mononuclear cells (PBMC) were obtainedfrom stage III or stage IV patients with HPVþ HNSCC (MSSMcohort). Informed consent was obtained from all patients; thestudies were conducted in accordance to the U.S. common ruleand was approved by MSSM and ASU institutional review board.Patient characteristics are described in ref. 27. All HPV16-peptides(>80% purity) were synthesized by Proimmune, UK. HPVþ

HNSCC PBMCs were thawed, rested with 1 mg/mL of CKB anti-bodies anti-PD1 (eBioscience), anti-CTLA4 (eBioscience) for 1hour at 37�C.HPV16-peptides in pool or individually were addedsubsequently in biological triplicates, along with recombinanthuman IL2 (20 U/mL), human IL7 (5 ng/mL). On day 5, half themediawas removed and replacedwith fresh IL2 and peptide pool.

On day 8, half the media was removed and fresh media, IL2, andpeptide was added to the cells and replated into a 96-wellmultiscreen elispot plate for Elispot detection. Elispot detectionis described in Supplementary Materials and Methods.

HPV-CTL stimulation for phenotypingHPV-specific T cells were generated by stimulating autologous

HPVþ HNSCC patient B-cell antigen-presenting cells (APC;SupplementaryMaterials andMethods). APCswere either peptidepulsed with HPV16-epitopes, or transfected with whole HPV-antigen encoded in mammalian expression plasmid pCDNA3.2(Invitrogen). APCs were washed and incubated with thawedwhole HPVþ HNSCC PBMCs at a ratio of 1:2 (200,000 APCs:400,000 PBMCs) supplemented with 20 U/mL recombinanthuman IL2 (R&D Systems), 5 ng/mL IL7 (R&D Systems). NoCKB antibodies were added for phenotyping experiments.Onday5, partial media exchange was performed. On day 10, expandedHPV-CTLs were restimulated with peptide-pulsed or transfectedAPCs like day 1. CTLs were used for cytolytic assays or immuno-phenotyped after day 14 or 20.

Tetramer staining, HPV-CTL, and HPVþ cell line phenotypingHPV16-tetramers were obtained from NIH Tetramer Core

Facility at Emory University. Positive control Flu-M1 and BMLF1pentamers were obtained from Proimmune, UK. For multimerstaining, cells were resuspended in 100 mL staining buffer with 5%human serumand1mmol/Ldasatanib (ThermoFisher Scientific),and each multimer was added at concentration of 1:100 for 30minutes at room temperature. Cells were washed twice andrestained with anti-CD8-PC5, anti-CD4-FITC, anti-CD14-FITC,and anti-CD19-FITC for exclusion gates, and either a combinationof anti-PD1-BV605 and anti-CD39-BV-421 or anti-PD1-BV-605and anti-TIM3-BV-421 for 30 minutes on ice. For memory mar-kers, CCR7-BV421, anti-CD45RO- BV605, and anti-CD45RA-FITC were stained for 30 minutes on ice after multimer staining.HPVþ cell line PD-L1 staining was done for 30 minutes on ice.Samples were then washed twice in 1� PBS, and analyzedby Attune flow cytometer (ThermoFisher Scientific). Multimerand antibody details are provided in Supplementary Materialsand Methods.

HPV-CTL cytotoxicity assaysCervical cancer cell lines SiHa and Caski were obtained from

ATCC. HPVþ HNSCC cell lines were obtained from the follow-ing sources: UPCI:SCC90 (SCC90) was obtained from ATCC,UM-SCC-47 (SCC47) and UM-SCC-104 (SCC104) from MerckMillipore. 93-VU-147T (147T) cell line was a kind gift fromDr. Josephine Dorsman, VU Medical Center, the Netherlands.Cell lines were periodically tested for Mycoplasma by PCRand confirmed to be Mycoplasma free. HLA-A�02:01þ HPVþ

HNSCCþ SCC-104 cells were prelabeled with 0.5 mmol/L Cell-Tracker Green CMFDA (ThermoFisher Scientific) for 1 hour andwashed. HPV-specific CTLs were pooled by HPV-antigen, washedand resuspended inmedia supplemented with 20 U/mL IL2, with1 mg/mL isotype IgG or anti-PD1 antibody, DMSO, and 1 mmol/LIDO-1 inhibitor epacadostat (Selleck Chemicals) in various com-binations as described. HPV-CTLs were added at ratio of 5:1 toSCC-104 cells and incubated for 48 hours at 37�C, 5% CO2. Co-cultured cells were harvested, neutralized withmedia supernatantfrom each well containing dead cells and centrifuged for 850� g,10 minutes. Cell pellets were washed twice with sterile 1� PBS,

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resuspended with 1 mL 1� PBS, and 2 mL propidium iodide(ThermoFisher Scientific) and cell death was assessed by flowcytometry.

RNA-seq data alignmentRNA-seq reads for each sample were quality checked using

FastQC(version0.10.1; BabrahamBioinformatics) and aligned tothe human genome build 38 (GRCh38) primary assembly andHPV16 genome (GCF_000863945.1) simultaneously using STAR(version 2.5.2B). After alignment, variants were discovered fol-lowing GATK Best Practices workflow for RNA-seq. Raw RNA-seqreads were preprocessed by adding read groups, indexing, mark-ing duplicates and sorting, Split'N'Trim, reassigning mappingquality and base recalibration.

ssGSEA analysis of HPV and immune gene signaturesLog-transformed transcripts per million (Log2 TPMþ1) from

each HNSCC sample, after subtraction of low expression geneswas used for ssGSEA as previously described inSenbabao�glu andcolleagues (28). Predefined immune signatures (SupplementaryTable S3) have been extensively validated in Senbabao�glu andcolleagues (28) and Mandal and colleagues (29). ssGSEA scoreswere computed for each tumor sample using the R package GSVA,and Z-transformed across the cohort prior to analysis. To assessimpact of HPV-gene expression on immune signatures, a corre-lation matrix was built using the R-library Corrplot with theZ-transformed ssGSEA scores and were displayed by hierarchicalclustering of correlations. Individual gene expression analysis wasperformed by unsupervised hierarchical clustering methods andwere used for heatmap analysis.

Statistical analysisCategorical variables, such as Elispot data, and flow cytometric

data were summarized as SFUs, and percentages. Continuousvariables (RNA-seq data) were presented with mean with SEM.UnpairedT testwithWelch's correctionwasused for all categoricalvariable analyses, and for continuous variable analyses nonpara-metric Wilcoxon rank-sum (Mann–Whitney) test was used. Forheatmaps of T-cell frequencies and ssGSEA RNA-seq analyses,Z-transformation was performed to normalize the data across thecohorts. R statistical software V3.4.0 and Prism software (Graph-Pad Software) were used for data managements and statisticalanalyses. Significance levels were set at 0.05 (�), and P-values of0.01 (��) or 0.001 (��) for all tests are indicated.

ResultsFrequency and specificity ofHPV16E2, E6, and E7-specific CTLsin HPVþ HNSCC

We performed a systematic analysis of potential CTL-epitopesfrom HPV16 E2, E6, and E7 antigens restricted by 15 globallyfrequent HLA class I alleles representative of major HLA super-types (Fig. 1A; Supplementary Fig. S1; ref. 30). We used a com-prehensive CTL-epitope prediction strategy we previously devel-oped by incorporating stringent selection criteria (Materials andMethods) to control for inter-algorithmic variations (25, 26).Fifty-nine candidate peptides (24 from E2, 20 from E6, and 15fromE7) were selected covering 13 of the 15 commonHLA class-Ialleles as candidate HPV-CTL peptides based on predictedHLA-affinity and antigen-processing percentile scores (Fig. 1A;Supplementary Fig. S1). Several previously described HLA-

A�02:01-restricted HPV16 E6 and E7 epitopes were predictedwith high scores (e.g., E6-KLP epitope, total percentile 94.6;Supplementary Table S1) confirming our prediction strategy.Within the 59 candidate HPV16-peptides, E2 had the lowestnumber of previously definedCTL-epitopes (3/24, 12%),whereasE6 and E7 had higher number of previously describedCTL-epitopes (35% and 46%, respectively). The number of pre-dicted HPV16-peptides ranged from 15 peptides (A�02:01), to 0peptides (B�40:01, B�44:02) among the selected HLA-alleles (Fig.1A). To determine if lack ofHLA-bindingmotifs in the threeHPV-antigens can poise specific HLA-alleles as risk-factors for HPVþ

HNSCCs, we calculated the odds-ratio of HLA-allele frequenciesin HPVþHNSCCs (N¼ 77), compared withHPV�HNSCCs (N¼64; Supplementary Materials andMethods). HLA B�40:01, whichhad no predictedHPV16-peptides for E2, E6, and E7 had an odds-ratio of 7.48 compared with HPV� HNSCCs (Fig. 1A and B; P ¼0.059), and had poor-binding peptides for all HPV16-antigens(bottom 20th percentile compared with other HLAs; Supplemen-tary Fig. S2; Supplementary Table S2). HLA-alleles A�24:02,B�07:02, and B�51:01 were also overrepresented (OR � 2) inHPVþHNSCCs, although theywere not statistically significant.Ofnote,HLA-B�07:02 (OR¼2; Fig. 1B) has been previously reportedto be associated with poor clinical outcome in cervical cancer andescape HPV-specific T-cell (HPV-CTL) recognition (31). Theseresults point to the importance of CTL-mediated control ofHPV16 malignancies.

Because HPV-CTLs in PBMCs are not abundant (32, 33), weused PBMCs stimulated for 10 days with candidate peptides andCKB antibodies aCTLA4 and aPD-1 to enhance HPV-CTL reac-tivity (Supplementary Fig. S3). We compared HPV-CTL frequencyin PBMCs between patients with HPVþ HNSCC (N ¼ 18) andhealthy controls (N¼ 14) by IFNg Elispots using antigen-specificpeptide pools (Fig. 1C and D; Supplementary Table S1; ref. 27).The HLA-frequency distribution of this cohort largely mirroredmedian HLA-frequency distribution in the United States (Sup-plementary Fig. S1B). IFNg responses against HPV16-E2 weresubstantially more common (>3-fold higher) in HPVþ HNSCCPBMCs compared with healthy control PBMCs (Wilcoxon rank-sum test, P¼ 0.0261; Fig. 1C).Moderate-to-high E6-reactivity wasobserved in patients withHPVþHNSCC (1.5-fold higher inHPVþ

HNSCCs), whereas E7-reactivity was generally low (Fig. 1C andD). To determine if PBMC T-cell reactivity correlates with B-cellimmunity,wemeasured IgG serologic responses to theE2, E6, andE7 antigens in all 18 patient samples in which we tested CTLreactivity. E2- and E7-specific serum IgG titers were higher relativeto E6 (>2-fold, P < 0.05) in the patients (Fig. 1E). The majority ofpatients who had IgG to E2, E6, and E7 also had ameasurable CTLresponse (E2¼ 72%, E6¼ 60%, E7¼ 70%, respectively; Fig. 1F).There was strong concordance between seroreactivity and T-cellreactivity within same antigens (Chi-squared independence test,P¼ 0.03). Finally, we observed amodest trend towards decreasedHPV CTL-response with advanced age and tumor stage of thepatient but these were not statistically significant (SupplementaryFig. S4). Thus, our results indicate that E2 and E6 antigens aremore CTL-reactive than E7 in patients with HPVþ HNSCC, andHPV-CTL response can be enhanced by CKB antibodies.

Mapping immunodominant epitopes of HPV16 E2, E6, and E7in HPVþ HNSCCs

To identify novel CTL epitopes from E2, E6, and E7, weperformed a second IFNg Elispot analysis using individual

Immunogenic and Dysfunctional CD8þ T Cells in HPVþ HNSCC

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predicted HPV16-peptides against patient-specific HLA-alleles(Fig. 2A). Fifty-one of 59 predicted peptides elicited a T-cellresponse in at least one patient, indicating a high degree of success(86%) of our prediction-validation strategy (Fig. 2A; Supplemen-tary Table S1). Consistent with pooled-antigen Elispot results(Fig. 1C and D), we observed sub-dominant E7-specific CTL-reactivity relative to E2, E6 epitope-specific CTL-responses (Fig.2A). Sixteen epitopes had an average response frequency of�100mean spot forming units (SFU)/106 PBMCs and were classified asstrongly immunogenic (representative e.g., Fig. 2B–E; Supple-mentary Table S1). Twenty-nine CTL-epitopes had an averageresponse frequency between 10 and 100 SFU/106 PBMCs (mod-erately immunogenic), whereas six epitopes had an averageresponse frequency <10 SFU/106 PBMCs (low immunogenic).Themajority ofmoderate to highly immunogenic epitopes (77%)were novel, or had not been described with the observed HLArestriction (Fig. 2B–E; Supplementary Table S1).We also observed16 unique epitopes that elicited a cross-reactive response to otheralleles within the same supertype supporting the strategy forHLA-supertype based epitope prediction (Supplementary Table

S1). Figure 2E shows a representative example, where an HLA-A�11:01 restricted E2-peptide had strong predicted binding affin-ity and elicited strong CTL-reactivity to HLA-A�68:01 (A3 super-type). Within the E2 antigen, most CTL-epitopes (52%) wereclustered within the trans-activating DNA-binding domain, 23%in the hinge region, and 24% in the DNA-binding domain(Supplementary Fig. S5A). Within E6, the immunodominantregions (70% of epitopes) encompassed amino acids 37–109with 40% of epitopes arising in the first zinc finger domain(Supplementary Fig. S5B). Interestingly, the zinc finger domainof E7 also had 42% of the CTL-epitopes (SupplementaryFig. S5C). Thus, we have enhanced the landscape of E2, E6, andE7 CTL-epitopes, and mapped the immunodominant regionsof E2, E6, and E7 for future studies.

HPV-specific CTLs exhibit dysfunctional phenotype in patientswith HPVþ HNSCC

We first interrogated whether responding ex vivo stimulatedHPV-specific peripheral CTLs in patients with HPVþ HNSCCwere in naive or memory T-cell compartments. After one round

Figure 1.

HPV16 E2, E6, and E7 epitope distribution and immunogenicity in HPVþ HNSCCs. A, Distribution of 59 predicted HPV16-peptides by each HLA-alleleranked from highest to lowest. B, OR of HLA-allele frequency from A in patients with HPVþ HNSCC (N ¼ 77) compared with patients with HPV� HNSCC (N ¼ 64).� , P ¼ 0.059. C, Summary of CTL-reactivity. Predicted HPV16-peptides were pooled according to antigen (Supplementary Table S1) and tested forCTL-reactivity by IFNg Elispot. P values from Wilcoxon rank sum test are shown. CEF, positive CTL-epitopes pool from CMV, EBV, Flu. D, Representativeexample of CTL-reactivity from one HPVþ HNSCC patient PBMC with SFUs after background subtraction (left) and images from each pool in triplicate (right).E, Seroreactivity of HPV16-E2, E6, and E7 antigens in HPVþ HNSCC MSSM patients screened for CTL-responses by Rapid-ELISA (Supplementary Materialsand Methods). F, Seroreactivity and CTL-reactivity concordance for each HPV-antigen in responding patients with HPVþ HNSCC. Circles are proportionalto the number of responding patients with HPVþ HNSCC for each antigen. Percentages represent patient responses. N.S., nonsignificant.

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of ex vivo stimulation by autologous APC presenting cognateHPV16-antigen, themajority (>79%)ofHPV-specific CTLs detect-able by antigen-specific multimers in HLA-A�02:01þ patientsexhibited memory phenotype distributed between effector mem-ory (TEM, CD45ROhiCCR7lo) and central memory (TCM,CD45ROhiCCR7hi) compartments (representative examples inSupplementary Fig. S6A and S6B).

E2-CTLs had a slightly higher frequency in the TEM compart-ment, compared with E6, E7 CTLs. Although CTL dysfunction inchronic viral infections and cancers has been extensively described(34), few studies have focused on the extent of T-cell exhaust-ion in patients with HPVþ HNSCC because of the difficulties instudying low-frequency HPV-CTLs (33). Although themajority ofHPV-CTLs were in the memory compartment, we then evaluatedthe prevalence of dysfunctional HPV-CTLs from patients withHPVþHNSCC after stimulation in the absence of CKB antibodies.We reasoned that ex vivo activated HPV-specific PD1þ CTLs thatare poised towards the exhaustion spectrum will become furtherdysfunctional after APC-stimulation and acquire additionalinhibitory markers characteristic of profound dysfunction,

defined by antigen-specific CTLs exhibiting the CD39þPD-1þ orTIM-3þPD-1þ phenotype (DPEx-phenotype; refs. 35–38).

First, chronic EBV-BMLF1 antigen-specific HLA-A�02:01-restrictedCTLs comparedwith acute Flu-M1 antigen specificCTLs,displayed a substantially higher DPEx-phenotype (CD39þPD-1þ

7.5-fold, TIM-3þPD-1þ 67-fold), indicating the validity of thisapproach (Supplementary Fig. S6C).

In four HLA-A�02:01þ patients with HPV-specific CTLsdetectable by antigen-specific tetramers (Fig. 3A–C), and oneHLA-A�68:01þ patient where CD137-positivity defined HPV-CTLs, we phenotyped total and E2, E6, and E7-specific DPEx CTLsindicating substantial exhaustion. As shown in the representativeexample Pt.7002, E2-CTLs were higher in frequency than E6 andE7-CTLs (Fig. 3A and B). Within the HPV16-antigens in Pt.7002,CTLs stimulated with E7-transfected APCs exhibited the highestlevels of CD8þDPEx fold-change relative to mock-antigen trans-fected (2- to 4-fold; Fig. 3B) followed by E2 (1- to 3-fold; Fig. 3B)and E6, respectively. In three of five patients with HPVþ HNSCC,total CD8þDPEx andHPV-specific CD8þDPEx cells were higher inCTLs stimulated with E7-antigen (between 2- and 10-fold)

Figure 2.

Landscape of CTL-epitopes from HPV16 E2, E6, and E7 in HPVþ HNSCCs. HPVþ HNSCC PBMCs from the initial pooled antigen screen (Fig. 1C) were testedagainst individual HPV16-predicted peptides corresponding to the patient HLA-type (Supplementary Materials and Methods). A, Summary of Elispot epitopedeconvolution screen showing all responding patients with HPVþ HNSCC (each column) against tested HPV16-peptides (each row) in log scale. Within eachantigen, peptides are ranked from most number of CTL responses (top) to the least (bottom). B–D, Examples of individual responding patients after backgroundsubtraction. HLA-A�02:01þ patient (B); HLA-A�02:01/B�07:02þ patient (C); HLA-A�24:02/B�35:01þ patient (D). E, HPV16-peptides predicted for theHLA-A3-supertype can stimulate a CTL response to representative allele (A�68:01). Inset shows binding affinities for predicted peptides for A�68:01; peptide labelsshow the HLA-allele fromwhich the peptidewas originally predicted. Positive responders are shown in bold. � , P < 0.05; �� , P <0.01, unpaired two-tailedWelch t test.






relative to E2/E6 antigen-stimulated CTLs (Pts. 7002, 7007,7012; Fig. 3B and C, unpairedWelch t test, P < 0.05), independentof HLA-status (e.g., HLA-A�68:01þ Pt. 7007; Fig. 3C). In the othertwo patients, E2-CD8þDPEx was higher than E7-CD8þDPEx (2- to3-fold, Pts. 7035, 7050; Fig. 3C, unpaired Welch t test, P < 0.05),indicating heterogeneity in HPV-specific CTL-dysfunction inHPVþ HNSCC. Interestingly, compared with E2 and E7-CTLs,E6-CD8þDPEx remained relatively low in most patients, andthere was an inverse relationship within patients betweenE7-CD8þDPEx and E2/E6-CD8þDPEx (Fig. 3C). Unsupervisedhierarchical clustering of DPEx-frequencies of total CD8þ andHPV-specific CD8þ T cells revealed this trend where highE2-CD8þDPEx and E6-CD8þDPEx co-occurred in patients whohad relatively lower E7-CD8þDPEx and vice versa (Tukey's mul-tiple comparisons test, E2 vs. E7, P ¼ 0.014, E6 vs. E7, P¼ 0.084,E2 vs. E6, P ¼ NS; Fig. 3D). These results suggest that in patientswithHPVþHNSCC, E7/E2CTL relative dysfunction levelsmay be

higher compared with E6-CTLs, although larger cohort experi-ments are necessary to validate these observations.

HPV16-antigen load correlates with T-cell exhaustionTo provide a broader analysis of immune dysfunction from the

tumor side in HPVþ HNSCCs, we performed an immune signa-ture analysis of two large publicly available HNSCC transcrip-tomes (TCGA, UM-cohorts,N¼ 119, 51 HPVþ, 68 HPV�; refs. 3,22). We used previously validated immune signatures represent-ing tumor-infiltrating immune cell subsets and performed single-sample gene set enrichment analysis (ssGSEA; SupplementaryMaterials and Methods; Supplementary Table S3 lists the genesignatures) to score the HPVþ and HPV� subsets (28, 29, 39).Patients with HPVþ HNSCC in general had higher immuneinfiltration scores compared with HPV� HNSCCs (Supplemen-tary Fig. S7), with 36/51 (70%) of HPVþ HNSCC samples repre-sented in the T-cell-high gene cluster, and few HPVþ HNSCC

Figure 3.

HPV16-specific T cells acquire dysfunctional phenotype upon ex vivo stimulation. A, Representative flow cytometry plots from an HLA-A�02:01 HPVþ HNSCCpatient CTLs stimulated with autologous APCs transfected with cognate antigen. Left, HPV16-MultimerþCD8þ T cells are one example for each HPV16-antigen;labels correspond to HPV16-epitope; percentages indicate multimerþ events within CD8þ gate. Right, CD8þPD1þCD39þ (black) or CD8þTetramerþPD1þCD39þ

(DPEx-phenotype, back gated in red). % back gated CD8þTetramerþDPEx. B, Pt.7002 HPV-CTL dysfunction. Top, CD8þ Tetramerþ events from the threeHPV16-antigens (left), each point is an HPV16-epitope-tetramer. Fold change in total CD8þDPEx percentage after CTL-stimulation with HPV16-antigen–transfectedAPCs, compared with mock-transfected APCs (right). Bottom, % Total CD8þDPEx (left), % CD8þTetramerþDPEx (right). C, Summary of dysfunction experiments infour other patients with HPVþ HNSCC. Top, % Total CD8þDPEx; bottom, % CD8þTetramerþDPEx for all except Pt. 7007 (% CD8þCD137þDPEx). D, Unsupervisedhierarchical clustering of %DPEx from E2, E6, and E7 total CTLs (left) and HPV-specific CTLs (HPV-Tetramerþ, CD137þ, right) from patients analyzed in A–C.Each row is an epitope-specific DPEx response per patient. � , P < 0.05; �� , P < 0.005; ��, P < 0.001, unpaired two-tailed Welch t test.

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samples (17%) with very low immune cell infiltration scores,confirming and expanding the findings in previous studies (29).To assess the impact of HPV gene expression on immune cellinfiltration, we calculated the Spearman correlation coefficientsamong ssGSEA scores for the entire gene sets across all patients,including HPV16 genes and performed an unsupervised cluster-ing on the correlation matrix (Fig. 4A). We observed that HPV16-gene signatures formed a distinct module, correlating best withcytotoxic T-cell infiltration (CYT, cytotoxic), B-cells, regulatoryT-cell signatures (TIL.Treg), and dysfunctional T-cell signatures(Exhaustion, TIGIT signatures; Fig. 4A; Supplementary Table S3).Interestingly, HPV-gene signatures also negatively correlated withneutrophils and other myeloid gene signatures, indicating thatlymphocytes dominate the immune landscape of HPVþHNSCCs(Fig. 4A; Supplementary Fig. S7). We also observed a previously

described exhaustion gene set correlating with HPV-gene sets inthis module (Spearman r ¼ 0.33; Fig. 4A). Unsupervised hierar-chical clustering on expression levels of constituent genes withinthe exhaustion gene set revealed three main groups with low (L),moderate (M), and high (H) expression of immune regulatorygene expression within patients with HPV16þ HNSCC (Fig. 4B).We then analyzed individual HPV16-gene expression in theHPV16þ HNSCC tumors (N ¼ 40) stratified into Exhaustion-high (EX-H) and Exhaustion moderate/low tumors (EX-ML;Fig. 4C). EX-H HPV16þ HNSCC tumors had higher gene expres-sion of E1, E2, E4, E6, and L2 genes compared with the EX-MLsubset (Fig. 4C, unpaired Welch t test; E1, E2, P < 0.01; E4, E6, L2,P < 0.1). E7-expression was comparably high in both the subsets,whereas E5 known to downregulate MHC-class I expression (40),remained low in the EX-H subset (Fig. 4C). These computational

Figure 4.

T-cell exhaustion signatures correlate with HPV16-antigen expression. A total of 119 HNSCC transcriptomes (68 HPV� HNSCCs and 51 HPVþ HNSCCs) wereanalyzed for immune cell infiltration by ssGSEA (Supplementary Materials and Methods). A, Clustered correlation matrix of immune signatures with HPV-genesets (HPV, all eight HPV genes; HPV.Early, E1, E2, E4, E5; HPV.Onco, E6, E7). All gene sets are listed in Supplementary Table S3. Gene set correlations wereclustered by hierarchical clustering creating distinct modules. B, Unsupervised hierarchical clustering of 49 genes in the exhaustion gene set (39) in HPVþ HNSCC.Patient clusters: low exhaustion (L), moderate (M), and high exhaustion (H). C, HPV gene levels (Log2-TPMþ1) in 40 HPV16þHNSCCs from B classified intoexhaustion high (EX-H in main text, N ¼ 15) and exhaustion lowþmoderate subsets (EX-ML in main text, N ¼ 25). � , P < 0.1; �� , P < 0.01, unpaired two-tailedWelch t test.






analyses along with previous HPV-CTL-dysfunction experiments(Fig. 3) suggest that HPV-specific CTLs have T-cell exhaustion attumor sites, driven by intratumoral HPV-antigen expression.

IDO-1 represents a novel HPVþHNSCC-specific immune targetWeanalyzed differential expression of constituent geneswithin

the exhaustion gene set between HPVþ HNSCCs and HPV�

HNSCCs (Fig. 5A; Supplementary Fig. S8). We observed severalwell-known T-cell regulatory genes such as LAG-3, GAL-9,CEACAM-1, and CTLA-4 overexpressed in HPVþ HNSCCs com-paredwithHPV�HNSCCs, consistent with high T-cell infiltrationand dysfunction as observed in our results (Figs. 3 and 4; Sup-plementary Fig. S7), and other studies (29). Interestingly, we alsoobserved exhaustion genes NRP1 and CD73 that were selectivelyupregulated in HPV� HNSCCs compared with HPVþ HNSCCs(Supplementary Fig. S8), indicating distinct types of T-cell

dysfunction between the two HNSCC subtypes. Indoleamine2,3-dioxygenase (IDO-1), an L-tryptophan catabolizing enzymewas one of the highest differentially expressed gene (based onranked P-value) from the exhaustion set HPVþ HNSCCs com-pared with HPV� HNSCCs (Fig. 5A; Mann–Whitney test, P ¼0.0012). A cross-cancer (N¼ 30 types, 45,708 total tumors) geneexpression analysis from cBioPortal (41), revealed that IDO-1 isalso highly expressed in the HPV-malignancy cervical cancer(Supplementary Fig. S9A). Within the HPVþ HNSCCs, IDO-1mRNA levels correlated with HPV16-E7 expression (Fig. 5B;Pearson r¼ 0.447, P¼ 0.001), and with tumor PD-L1 expression(Fig. 5B; Pearson r ¼ 0.71, P < 0.0001). IDO-1 expression furthercorrelated with M1-Macrophage signature (Pearson r ¼ 0.517,P < 0.0001), and as expected with cytotoxic signature (Pearson r¼0.61, P < 0.0001), but only modestly with M2-Macrophagesignature (Pearson r ¼ 0.24, Supplementary Fig. S9B). To

Figure 5.

IDO-1 is an HPV-specific immune target and can enhance HPV-T-cell cytotoxicity. A, IDO-1 expression in HPVþ, HPV� HNSCC transcriptomes. Each datapoint represents one patient. B, IDO-1 transcript levels correlated with HPV-E7 (top) and PD-L1 (bottom) expression. Data derived from HPVþ HNSCC samplesanalyzed in Fig. 4. Pearson correlation coefficients and best fit line (red) are shown. C, Correlation of IDO-1 protein levels to HPV16-E7 antigen expressionin six HPV16 cell lines (two cervical cancer, four HPV16þ HNSCC). Top, immunoblot; bottom, correlation of IDO-1 and E7 protein levels normalized toGAPDH (R2 ¼ 0.84; P ¼ 0.033). D and E, Celltracker labeled SCC-104 cells were co-incubated with polyclonal E2, E6, and E7-specific T cells at an effector/targetratio of 5:1 for 48hours and assessed for cell death (TRACKþPIþ events) underaPD-1, IDO-1 single or dual-inhibition conditions.D,Representativeflowcytometry plotfrom E7-specific T-cell–mediated cytotoxicity on SCC-104 cells. Percentage indicates CellTracker-labeled dead SCC-104 cells. E, Summary of SCC-104 cytotoxicity(three biological replicates) by E2, E6, and E7-CTLs under treatments indicated. � , P < 0.1; �� , P < 0.01, unpaired two-tailed Welch t test.

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experimentally validate these in silico immune signature analysesindicating that HPV-antigen expression can impact immuneregulatory gene expression such as IDO-1 (Fig. 4), we performedimmunoblotting for IDO-1 expression in a panel of HPV16þ

cancer cell lines (2 cervical, 4 HPVþ HNSCC). These showedvariability in HPV16-E7 protein expression (Fig. 5C). IDO-1expression followed a striking correlation with E7-protein expres-sion in the same cell lines (R2 ¼ 0.84, P ¼ 0.033; Fig. 5C).Transfection of the 3-HPV16-antigens into a non-HPV cell line(HEK-293-T) did not alter IDO-1 protein expression (Supple-mentary Fig. S9C).Of note, PD-L1 protein expression on the samecell lines did not correlate with E7-antigen expression (Spearmanr ¼ 0.17; P ¼ NS; Supplementary Fig. S9D).

IDO-1 inhibition enhances T-cell targeting of HPVþ HNSCCsIDO-1 inhibitors are being evaluated in preclinical and clinical

settings to enhance tumor immunity (42, 43). We thereforeexplored the possibility of validating our immunogenomic anal-yses by exploiting IDO-1 inhibition to overcome HPV-CTLexhaustion, especially using the more dysfunctional E7-CTLs(Fig. 3). We fluorescently labeled the HLA-A�02:01þ HPVþ

HNSCC cell line UM-SCC-104 (SCC-104), which has highIDO-1, E7 and PD-L1 expression (Fig. 5C; SupplementaryFig. S9D). SCC-104 cells were previously reported to have adistinct hierarchy of HPV16-antigen expression where E7 > E6> E2 (44). We assessed HPV-CTL–mediated cytotoxicity onSCC-104 cells, after co-incubation with ex vivo expandedHPV-CTLs from an HLA-A�02:01þ HPVþ HNSCC patient in thepresence of either anti-PD-1 antibody (aPD-1þDMSO) or IDO-1inhibitor epacadostat (IgþIDO-1i), or both (aPD-1þIDO-1i;Fig. 5D and E). Within E7-CTLs, single-agent treatment witheither aPD-1 or IDO-1i individually resulted in a three- tofive-fold increase in sensitivity of SCC-104 to E7-CTL–mediated cytotoxicity compared with mock (IgþDMSO) treat-ment (Fig. 5D andE,aPD-1 vs.mock, P¼ 0.024; IDO-1i vs.mock,P ¼ 0.064). In contrast, synergistic combination blockade withboth aPD-1þIDO-1i resulted in a 10-fold increase in tumorcytotoxicity compared with mock treatment (Fig. 5C and D,P¼ 0.011), and a two- to three-fold increase in tumor cytotoxicitycompared with the single-agent treatments (Fig. 5D and E,P ¼ 0.04 compared with IDO-1i, P ¼ 0.013 compared withaPD-1). Similar results were obtained with aPD-1þIDO-1i com-bination therapy on E2 and E6 CTL cytotoxicity although to alesser extent (three-fold increase for E2, and five-fold increase forE6 compared with mock treatment, P < 0.01), likely reflecting thelower expression of these antigens in SCC-104 cell line (44). Theseresults demonstrate that IDO-1 is a novel HPVþ HNSCC-specificcheckpoint correlating with HPV-antigen expression, andcombination inhibition of PD-1 and IDO-1 can sensitize HPVþ

HNSCCs to HPV-CTL–mediated cytotoxicity.

DiscussionHPV-driven malignancies remain an ideal model system for

cancer immunotherapy, due to (i) a long lead time from infectionto malignancy, (ii) emerging immune and viral biomarkers forearly detection, (iii) the persistent tissue expression of viraloncogenes, and (iv) epidemiologic evidence of the central roleof T-cell control of viral persistence. However, the dynamics ofviral persistence within immunocompetent individuals and themechanisms of tumor immune escape remain largely unknown,

in particular for HPVþ HNSCC. The emerging epidemic ofHPVþHNSCCand lack of screeningmodalities represents amajorclinical challenge and opportunity for targeted T-cellimmunotherapy.

In this study,wehave expanded the spectrumofHPVþHNSCC-specific immune therapeutic targets at the CTL-epitope level andat the target tumor cell-modulatory level.We choseE2, E6, andE7-antigens, as they induce strong B-cell immunity, have beendetected in preinvasive and/or invasive cervical cancer, and weconfirmed viral antigen expression in HPV16þ HNSCCtranscriptomes. Most studies that have attempted to defineCTL-immunogenicity from HPV16 have primarily focused on alimited number of HLA-alleles (e.g., A�02:01) and peptides fromE6 and E7 (Supplementary Table S1), with limited data onimmunogenic targets in in HPVþ HNSCC (32, 45, 46). The 15HLA alleles chosen for this study are predicted to include 10/12 ofHLA supertypes and over 95% of the global population (30, 32).Of the 15 HLA alleles, we failed to identify peptides for HLA-B�40:01 and HLA-B�4402. HLA B�40:01 is significantly overrep-resented in the HPVþ HNSCC cohort compared with HPV�

HNSCC (Fig. 1B), but these data remain to be confirmed in largerdatasets and association studies. Viral immune escape by alteringHLA-binding CTL epitopes has been documented in HIV-1 andHCV infections (47, 48), but not as well for DNA viruses such asHPV, where the mutation rates are markedly lower.

We identified several immunogenic CTL-epitopes from thethree HPV16-antigens (Fig. 2; Supplementary Table S1). In ourexperiments, addition of PD-1 and CTLA-4 CKB antibodies aidedour ability amplify and detect low-frequency HPV-CTL-responsein both healthy and HPVþ PBMCs ex vivo (Fig. 1C and D;Supplementary Fig. S3). A potential caveat of this approach isthat we did not specifically assess tumor-infiltrating HPV-TILs inthese patients; however, the presence of HPV-antigen-specificCTLs in the memory compartments, along with the expressionof tumor-specific dysfunction markers such as PD-1, CD39, andTIM3 lends support to their tumor specificity (37, 38). Our resultsindicate that HPV16-E2 and E6 induce more CTL responses thanHPV16-E7 (Figs. 1 and 2). HPV16-E6 and E7 have been thedominant targets for T-cell–based immune therapies against HPVthus far (14, 18). In contrast, E2-specific CTL-reactivity has beenunexplored as an immunotherapeutic target in HPVþ HNSCCsdue to the assumption that E2-locus is interrupted by viralintegration, similar to that observed in cervical cancer (17).However, several recent whole genome studies in HNSCCs haveindicated that viral breakpoints in HPVþHNSCCs are distributedthroughout the genome, with preferential integration in the E1region (2, 21). E2 is also a larger antigenmore than three times thesize of E6, E7, possibly explaining the bigger spectrum ofCTL-epitopes from the protein. These results, taken along withthe high proportion of episomal full-length HPVDNA inHNSCClesions (49), and our data demonstrating strong E2-specific T-celland B-cell reactivity (Figs. 1 and 2) warrant further investigationof E2 as a T-cell therapeutic target in addition to E6 and E7 inHPVþ HNSCCs.

We detected low levels of E7-CTLs compared with E2 and E6-CTLs in this study. This can be due to (i) inaccurate prediction ofCTL-epitopes, (ii) inherently low immunogenicity of E7-antigen,(iii) low antigen load in patients, or (iv) higher levels of dysfunc-tional E7-specific CTLs. Our ability to accurately predict previ-ously described epitopes fromE7 and the successful identificationof novel CTL-epitopes from E2 and E6 across various HLA-alleles






(Fig. 2A), argues against a suboptimal prediction strategy. Thepresence of high levels of serum titers against E7 in patients withHPVþ HNSCC indicates that the antigen is presented and isimmunogenic at least in context of B-cell immunity (Fig. 1E andF). Gene expression analysis of HPVþHNSCC tissue and cell linesshowed that E7-antigen load is high in patient tumors, consistentwith several other studies (22, 49). In our exploratory experi-ments, E7-CTLs tended to exhibit higher levels of PD1þCD39þ orPD1þTIM3þ DPEx-phenotypes compared with E2 and E6-CTLsafter ex vivo stimulation in three/five independent patients withHPVþ HNSCC (Fig. 3). In particular, E7-CTL relative dysfunctionlevels occurred distinct from E2/E6 CTL dysfunction within thesame patient (Fig. 3B–D). Because antigen persistence and thesubsequent magnitude of CTL-response are major factors inchronic viral T-cell exhaustion (50), we speculate that in each ofthese patients, the variably dysfunctional CTLs might reflecttemporal tumor HPV-load or tumor heterogeneity. Although theeffect of low sample size in these experiments is not precluded,future studies with larger cohorts that compare and correlatetumor antigen load in vivo with the dynamics of E2, E6, andE7-CTL phenotypes in peripheral blood and tumorwill be neededto verify our findings.

Although other studies have shown high levels of immuneinfiltration in HPVþ HNSCCs (22, 29), we show here thatHPV-antigen load likely drives high CTL-infiltration and CTL-dysfunction (Fig. 4A), arguing for better response to immuneCKB therapies. Indeed, preliminary data from ongoing HNSCCclinical trials targeting the PD-1/PD-L1 axis indicate more benefitfor HPVþ HNSCCs compared with HPV� HNSCCs (9, 10). Ourdata thus provide mechanistic insights into this clinical response,wherein, high HPV-antigen load likely drives T-cell infiltrationinto HPVþ HNSCCs causing immune selection pressure forHPV-CTL dysfunction (in particular E7-CTLs), and that immuneCKB can at least partially reverse this effect in HPVþ HNSCCs(�32% ORR in ref. 10).

In addition to the well-described PD-1 checkpoint, we dem-onstrate by computational analysis and subsequent experimentalin vitro validation that IDO-1 is highly expressed inHPVþHNSCCand other HPV-driven malignancies (Fig. 5A; SupplementaryS9A). In preclinical murine melanoma models, TILs increasetumor IDO-1 expression (51) and IDO-1 inhibitors are showingpromise in clinical trials in particular with PD-1/PD-L1 blockade(52). HPVþ HNSCCs expressing IDO-1 might similarly be drivenby HPV-specific-CTL infiltration in response to high tumoralHPV antigen load (Figs. 4 and 5). In vitro, this resistance toCTL-targeting by HPVþ HNSCCs is apparent in the absence ofPD-1/IDO-1 inhibition, where only �5% of SCC-104 cells weresensitive to CTL-cytotoxicity regardless of the antigen-specificityof the HPV-CTLs (Fig. 5E). In contrast, inhibition of IDO-1 aloneor in combination with PD-1 blockade significantly enhancestumor cell cytotoxicity of E7-CTL (and, to a lesser extent, E2 and

E6-CTL) derived from patients with HPVþ HNSCCs (Fig. 5E).These data suggest that IDO-1/PD-1 blockade may have asignificant effect to activate preexisting HPV-specific CTLs inHPVþ HNSCCs.

Sixty years after the discovery of HPV and 10 years after FDAapproval of the first HPV vaccine, HPV-associated malignanciesremain a major public threat, with an estimated 14 million newHPV-infections occurring every year (53). The presence of highly-expressed viral antigens makes HPVþ HNSCCs a promising set-ting for targeted immunotherapies. We propose that vaccinationor ACT to HPV16-specific CTL epitopes from E2, E6, and E7, andtargeted immune modulation with a combination of PD-1 andIDO-1 inhibition warrant further evaluation in HPVþ HNSCCand other HPV-associated malignancies.

Disclosure of Potential Conflicts of InterestA. Sikora reports receiving a commercial research grant from Tessa Thera-

peutics. No potential conflicts of interest were disclosed by the other authors.

Authors' ContributionsConception and design: S. Krishna, A.K. Read, K.S. AndersonDevelopment ofmethodology: S. Krishna, P. Ulrich, A.K. Read, S. Kim-Schulze,M.A. Wilson Sayres, K.S. AndersonAcquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): S. Krishna, P. Ulrich, E. Wilson, F. Parikh, A.K. Read,S. Kim-Schulze, M. Posner, A. Sikora, K.S. AndersonAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): S. Krishna, E. Wilson, P. Narang, S. Yang,S. Kim-Schulze, J.G. Park, M. Posner, M.A. Wilson Sayres, A. Sikora,K.S. AndersonWriting, review, and/or revision of the manuscript: S. Krishna, P. Ulrich,S. Kim-Schulze, J.G. Park, M. Posner, M.A. Wilson Sayres, A. Sikora,K.S. AndersonAdministrative, technical, or material support (i.e., reporting or organizingdata, constructing databases): S. Krishna, A.K. Read, K.S. AndersonStudy supervision: K.S. Anderson

AcknowledgmentsWe thankMarika Hopper, Padhmavathy Yuvaraj from Anderson lab for help

with cell culture and R-ELISA analysis, and Samantha Cotsmire (BiodesignCIVV, ASU) for helpful advice. We thank Yasin Senbabao�glu (Genentech) forinput on ssGSEA analysis. S. Krishna acknowledges funding support from ASUSchool of Graduate EducationDissertationCompletion Fellowship, and Schoolof Biological and Health Systems Engineering, ASU. We also thank the HumanImmune Monitoring Center, Ichan School of Medicine for patient sampleprocessing and management. This work was supported by institutional fundsfrom Arizona State University.

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

Received February 4, 2018; revised June 26, 2018; accepted August 20, 2018;published first August 28, 2018.

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Krishna et al.




2018;78:6159-6170. Published OnlineFirst August 28, 2018.Cancer Res Sri Krishna, Peaches Ulrich, Eric Wilson, et al.

T Cells in Head and Neck Cancer+of CD8Human Papilloma Virus Specific Immunogenicity and Dysfunction

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