ORIGINAL RESEARCH published: 08 August 2019 doi: 10.3389/ﬁmmu.2019.01832 Frontiers in Immunology | www.frontiersin.org 1 August 2019 | Volume 10 | Article 1832Editedby: DeniseDoolan, JamesCookUniversity,Australia Reviewedby: SaidDermime, NationalCenterforCancerCareand Research,Qatar EstrellaMarielLevy, NationalCouncilforScientiﬁcand TechnicalResearch (CONICET),Argentina *Correspondence: MichalBassani-Sternberg michal.bassani@chuv.ch LanaE.Kandalaft lana.kandalaft@chuv.ch †Theseauthorshavecontributed equallytothiswork Specialtysection: Thisarticlewassubmittedto VaccinesandMolecularTherapeutics, asectionofthejournal FrontiersinImmunology Received: 29April2019 Accepted: 19July2019 Published: 08August2019 Citation: Bassani-SternbergM,DigkliaA, HuberF,WagnerD,SempouxC, StevensonBJ,ThierryA-C, MichauxJ,PakH,RacleJ, BoudousquieC,BalintK,CoukosG, GfellerD,MartinLluesmaS,HarariA, DemartinesNandKandalaftLE(2019) APhaseIbStudyoftheCombination ofPersonalizedAutologousDendritic CellVaccine,Aspirin,andStandardof CareAdjuvantChemotherapy FollowedbyNivolumabforResected PancreaticAdenocarcinoma—AProof ofAntigenDiscoveryFeasibilityin ThreePatients. Front.Immunol.10:1832. doi:10.3389/ﬁmmu.2019.01832A Phase Ib Study of the Combination of Personalized Autologous Dendritic Cell Vaccine, Aspirin, and Standard of Care Adjuvant Chemotherapy Followed by Nivolumab for Resected Pancreatic Adenocarcinoma—A Proof of Antigen Discovery Feasibility in Three Patients MichalBassani-Sternberg1,2*†,AntoniaDigklia2†,FlorianHuber1,2,DorotheaWagner2, ChristineSempoux3,BrianJ.Stevenson4,Anne-ChristineThierry2,JustineMichaux1,2, HuiSongPak1,2,JulienRacle1,4,CarolineBoudousquie2,KlaraBalint1,2,GeorgeCoukos1,2, DavidGfeller1,4,SilviaMartinLluesma1,2,AlexandreHarari1,2,NicolasDemartines5and LanaE.Kandalaft1,2* 1LudwigInstituteforCancerResearch,UniversityofLausann e,Lausanne,Switzerland,2DepartmentofOncology,Centre HospitalierUniversitaireVaudois,UniversityofLausann e,Lausanne,Switzerland,3InstituteofPathology,CentreHospitalier UniversitaireVaudois,UniversityofLausanne,Lausanne, Switzerland,4SIBSwissInstituteofBioinformatics,Lausanne, Switzerland,5DepartmentofVisceralSurgery,CentreHospitalierUniver sitaireVaudois,UniversityofLausanne,Lausanne, Switzerland Despite the promising therapeutic effects of immune checkp oint blockade (ICB), most patients with solid tumors treated with anti-PD-1/PD- L1 monotherapy do not achieve objective responses, with most tumor regressions b eing partial rather than complete. It is hypothesized that the absence of pre-existi ng antitumor immunity and/or the presence of additional tumor immune suppressive factors at the tumor microenvironment are responsible for such therapeutic fai lures. It is therefore clear that in order to fully exploit the potential of PD-1 blockade therapy, antitumor immune response should be ampliﬁed, while tumor immune supp ression should be further attenuated. Cancer vaccines may prime patients for treatments with ICB by inducing effective anti-tumor immunity, especially in pat ients lacking tumor-inﬁltrating T-cells. These “non-inﬂamed” non-permissive tumors that a re resistant to ICB could be rendered sensitive and transformed into “inﬂamed” tumor by vaccination. In this article we describe a clinical study where we use pancreatic cancer as a model, and we hypothesize that effective vaccination in pancreati c cancer patients, along with interventions that can reprogram important immunosup pressive factors in the tumor microenvironment, can enhance tumor immune recognit ion, thus enhancing response to PD-1/PD-L1 blockade. We incorporate into the sc hedule of standard of care (SOC) chemotherapy adjuvant setting a vaccine platfor m comprised of autologous dendritic cells loaded with personalized neoantigen pepti des (PEP-DC) identiﬁed through our own proteo-genomics antigen discovery pipelin e. Furthermore, we add nivolumab, an antibody against PD-1, to boost and maintain t he vaccine’s effect. Bassani-Sternberg et al. Personalized Vaccine for Pancreatic Cancer We also demonstrate the feasibility of identifying persona lized neoantigens in three pancreatic ductal adenocarcinoma (PDAC) patients, and we d escribe their optimal incorporation into long peptides for manufacturing into va ccine products. We ﬁnally discuss the advantages as well as the scientiﬁc and logistic challenges of such an exploratory vaccine clinical trial, and we highlight its no velty. Keywords: pancreatic adenocarcinoma, dendritic cell vacci ne, antigen discovery, neoantigen, cancer immunotherapy INTRODUCTION Pancreaticductaladenocarcinoma(PDAC)istheseventhlea ding cause of cancer-related death in the world in 2018 ( 1), with an overall 5-year survival rate of ∼5% (2). Approximately 70% of deaths are due to widespread metastasis and the remaining cases have limited metastasis but extensive primary tumors which eventually lead to mortality ( 3). Surgery is the only potential hope of cure for PDAC, but tumors are resectable only in 20% of patients at the time of diagnosis. Therapeutic research eﬀorts have mainly focused on improvements in radio/chemo treatments and to date, there are only a few chemotherapeutic agents that have shown to be eﬀective agains t advanced pancreatic cancer, including gemcitabine with or without abraxane ( 4). At present, it is diﬃcult to conclude that there is a deﬁnite SOC adjuvant chemotherapy for all patients with PDAC. However, multiagent adjuvant therapy (modiﬁed folforinox) has been demonstrated to be more eﬀective than gemcitabine alone in the adjuvant setting, but its use is lim ited onlytopatientswithexcellentperformancestatus( 5).Recentlyit hassuggestedthatgemcitabinepluscapecitabineisavalidopt ion forthesepatientssinceithasbeenshownthatitismoreeﬃcie nt thangemcitabinealone( 6). Oneofthemostpromisingnewcancertreatmentapproaches is immunotherapy. Recent studies have shown that PDAC is an immunogenic tumor. Antigens expressed on pancreatic tumor cells able to induce speciﬁc B and T cells comprise (7): Wilms’ tumor gene 1 (WT1) (75%) ( 8), mucin 1 (MUC1) (over85%)( 9),humantelomerasereversetranscriptase(hTERT) (88%) (10), mutated K-RAS (nearly 100%), survivin (77%), carcinoembryonic antigen (CEA) (over 90%) ( 11), HER- 2/neu (over 60%) ( 12), p53 (over 65%) ( 13), and α-enolase (ENO1) ( 14). Several studies have reported that dysfunction of the immune system is one of the key contributors for the development of PDAC ( 15,16). Moreover, PDAC is knowntohaveanimmunosuppressivetumormicroenvironment characterized by (i) the absence of intratumoral eﬀector T-c ells (17,18), (ii) the presence of an inﬂammatory tumor micro- environment led by the RAS oncogene ( 19), and (iii) massive inﬁltration of immunosuppressive leukocytes into the tumor microenvironment, which predicts poor survival ( 18,20,21). Additionally,theanalysisofimmuneinﬁltratesinhumantu mors has demonstrated a positive correlation between prognosis an d the presence of humoral response topancreatic antigens (MUC- 1andmesothelin)( 22,23)oroftumor-inﬁltratingTcells( 20,24). Therefore,cancerimmunotherapycanbeapromisingalternati ve treatmentforPDACpatients.Amajormechanismofimmuneresistanceengagedbytumors is the enforcement of immune checkpoint pathways, aiming to shutdown T cells speciﬁc for tumor antigens. An important immune checkpoint is mediated by the programmed cell death protein 1 (PD-1) expressed on the surface of activated T cells during initial activation ( 25,26). The major role of PD-1 is to limit the activity of T cells in peripheral tissues at the time of an inﬂammatory response to infection and to restrict autoimmunity ( 27,28). Cancer immunotherapy targeting anti- PD-1(e.g.,nivolumab,pembrolizumab),aswellasanti-cytot oxic T-lymphocyte-associated antigen 4 (anti-CTLA-4, ipilimumab ), has changed the treatment landscape of several tumors ( 29). Yet the success of immunotherapy has not been proven eﬀective for the treatment of metastatic pancreatic cancer patients ( 30), who have been shown unresponsive except for the population withmismatch-repairdeﬁciencywhichcomprisesonly0.8%( 31). A broad array of clinical trials in pancreatic cancer have bee n completedorareongoingusingdiﬀerentcombinationswithICB (32,33). However, the most adequate combination for PDAC patientsisnotclearsofar. Dendritic cell (DC)-based vaccines for cancer immunotherapy have been studied and tested for more than a decade and proven clinically safe and eﬃcient to induce tumor-speciﬁc immune responses, however only limited eﬃcacy was observed in patients with advanced recurrent disease afte r DC vaccination ( 34,35). Several groups have attempted to test safety and eﬃcacy of DC-based vaccines against pancreatic cancer in early phase clinical trials, loading DCs with tumor associatedantigens(TAAs) exvivo,andsubsequentlyre-infusing them in patients, yet with low clinical beneﬁt so far ( 36–39). One possible reason for reduced vaccine eﬃcacy could be that mostcancervaccinestestedtodateweretargetedagainstde ﬁned non-mutated self-antigens. Tumors express two major kinds of antigens that can be recognized by T cells: non-mutated self-antigens and mutated neoantigens, generated in tumor cells due to their inherent genetic instability ( 40). Tumor cells usually harbor between 10 and few thousands private somatic mutations, as identiﬁed by deep sequencing analysis, and ev en among tumors of the same histotype, most mutations are diﬀerent ( 41,42). Thus, neoantigens are mostly “private” and patient-speciﬁc ( 43) and trigger a higher more robust T-cell response. Indeed, increasing evidence associates clinical b eneﬁt from immunotherapy with speciﬁc responses to private tumor epitopes ( 44–48), leading to increased interest in neoantigen vaccination( 40). Several clinical trials describing vaccines designed to ha rness neoantigen-speciﬁc immunity have been recently reported Frontiers in Immunology | www.frontiersin.org 2 August 2019 | Volume 10 | Article 1832 Bassani-Sternberg et al. Personalized Vaccine for Pancreatic Cancer mainly in melanoma patients: The ﬁrst study reported the feasibility, safety and eﬃcacy of a DC vaccine pulsed with neoantigen peptides ( 49). Another phase I study has evaluated a peptide vaccine targeting up to 20 predicted personal tumor neoantigens and demonstrated an expansion of the repertoire of neoantigen-speciﬁc T cells which correlated with clinica l beneﬁt (50). A second group performed a phase I study using RNA vaccines that contained up to 10 mutations per patient and demonstrated that these vaccines can mobilize speciﬁc anti-tumor immunity against these cancers ( 51). These studies provide proof-of-principle that a personalized vaccine can be produced and administered to a patient to generate highlyspeciﬁcimmuneresponsesagainstthatindividual’stum or, showing that a personalized neoantigen vaccine broadens the repertoire of neoantigen-speciﬁc T cells substantially beyon d whatisinducedbyexistingimmunotherapeutics. To determine whether targetable mutations and neoantigens exist in PDAC, several studies have been performed using genomic proﬁles of PDAC tumor samples. A whole-genome sequencing and copy number variation (CNV) analysis was performed on 100 pancreatic ductal adenocarcinomas (PDACs) and found in total 11,868 somatic structural variants at an average of 119 per individual (range 15–558) ( 52). Furthermore, the genomic proﬁle of 221 PDAC tumors were analyzed and the ﬁndings revealed that nearly all PDAC samples harbor potentiallytargetableneoantigens( 53).Todeﬁnetheimportance of neoantigens in PDAC, one study compared stage-matched cohorts of treatment-naive, surgically resected, rare lon g-term survivors to short-term survivors with a more typical poor outcome. The authors detected a median of 38 predicted neoantigenspertumor,andshowedthattheassociationofhig her neoantigen quantity and CD8+T-cell inﬁltrate with survival was independent of adjuvant chemotherapy, suggesting that neoantigen quality, and not purely quantity, correlates wit h survival( 54). We hypothesize that eﬀective vaccination in PDAC patients along with interventions that can reprogram important immunosuppressivefactorsinthetumormicroenvironmentcan enhance tumor immune recognition, thus enhancing response to PD-1/PD-L1 blockade. To this end, we designed a phase 1b trial where we incorporated a vaccination schedule of a novel autologous DC pulsed with personalized neoantigen peptides (PEP-DC) identiﬁed through our own proteo-genomics antigen discovery pipeline in the SOC chemotherapy adjuvant setting followed by nivolumab. We hereby set the objectives and desi gn of our study, and we demonstrate the feasibility of identify ing personalized neoantigens in three PDAC patients, and their optimalincorporationintolongpeptidesformanufacturingint o vaccineproducts. MATERIALS AND METHODS Clinical Study Design This is a phase Ib trial (CHUV-DO-0017_PC-PEPDC_2017) to evaluate the feasibility, safety, immunogenicity, and eﬃc acy of subcutaneous DC vaccine loaded with personalized peptides (PEP-DC), in combination with SOC chemotherapy(gemcitabine/capecitabine) and enteric-coated aspirin, fo llowed by the anti-PD-1 antibody nivolumab to boost and maintain the vaccine’s eﬀect in patients with surgically resected PDAC . The components of the vaccine to be investigated in this study includeagentsforwhichsafetyhasbeenpreviouslydemonstra ted to be acceptable. This trial has been approved by Swissmedic and the competent Ethics Committee. Before any study-speciﬁc procedure is performed, a signed and dated informed consent is obtained. In order to be eligible, patients must present: (a) histologically conﬁrmed resected adenocarcinoma of th e pancreas (T1–T4, N 0–1, minimum 2 cm–AJCC 8th ed.) and (b) appropriate amount of tumoral tissue collected from the cytoreductive surgery, allowing the identiﬁcation of top 1 0 personalizedpeptides(PEP)forpreparationofPEP-DCvaccine. Objectives The primary objectives of the trial are to determine: (1) the feasibility of producing and administering PEP-DC vaccine i n the indicated patient population; (2) the safety and tolerabili ty of the study treatment vaccine and aspirin given together with SOC chemotherapy, and followed by nivolumab; (3) the immunogenicity by measuring acquired T cell mediated immune activation events post vaccination. This study has also asecondaryobjective,whichistoevaluaterelapsefreesurv ivalat 6,12,18,24,and36monthsandoverallsurvivalintheindica ted populationofpatients. Statistical Methods We hypothesize that the delivery of the PEP-DC vaccine through the subcutaneous route in combination with aspirin, nivolumab, and adjuvant chemotherapy in advanced pancreatic cancer patients is feasible, safe without additional toxicit y, and immunogenic. Basedonstudyfeasibilityandanticipatedacc rual rate, a total of 12 evaluable patients is expected to enter this Phase Ib study if treatment limiting toxicities (TLTs) are i n the acceptablerange. ThefeasibilityhypothesisforPEP-DCvaccinewillbeassess ed by (a) the number of patients in which vaccine production is successful (at least 6 doses are manufactured and released) , and (b) the number of patients who receive at least one dose of PEP-DCvaccine(sincethemainstayofthetherapeuticapproach here is PEP-DC) and the corresponding percentages in the ITT population (i.e., all registered patients). Exact binomial conﬁdenceintervalsforthecorrespondingrateswillbeesti mated. The safety and tolerability of the PEP-DC vaccine in combination with other protocol drugs will be evaluated by th e occurrence of TLTs and adverse events (AEs) in both the “TLT evaluation” and the safety population. The severity of toxici ties will be classiﬁed according to the NCI CTCAE Version 4.03 and will be presented in tabular as well as graphical format. For each patient,eachAEwillbepresentedconsideringthehighest(wors t) grade of toxicity observed over the whole treatment period according to CTCAE version 4.03. Although the safety of the vaccinationbackbonehasbeenalreadyestablished,aconti nuous monitoringrulewillbefollowed,toallowforearlyterminati onof the study. Any patient who receives at least one vaccination w ill be included in the toxicity (safety) analysis. A Bayesian ru le will Frontiers in Immunology | www.frontiersin.org 3 August 2019 | Volume 10 | Article 1832 Bassani-Sternberg et al. Personalized Vaccine for Pancreatic Cancer beemployedtomonitorTLTsaftergroupsof4patientshavebeen treatedandcompletetheﬁnalTLTevaluation. As only 5 weeks are allocated for target prioritization, assessment of pre-vaccination immune responses against the predicted neoantigens will not be performed to assist their selection. Therefore, the selection of long peptides is done in silicoby the NeoDisc pipeline. The immunogenicity of PEP- DC vaccine will be assessed (based on ITT population as well as the safety population) by measuring acquired, T cell- mediated immune activating events post vaccination compared to pre-vaccination levels. Descriptive statistics of absolu te and relative diﬀerences will be calculated overall and for subgr oups ofinterest. Regimen The study was designed so that eligible subjects with PDAC whoundertookcytoreductivesurgeryfollowedbychemother apy may plan to enroll in the vaccine study. Should the subject wishes, and upon informed consent, tissue can be harvested at the time of surgery for identiﬁcation of personalized targ ets for vaccination. Screening of patients may be completed after the collection of tumor was performed during the surgery. Upon registration for the trial, all patients would receive 8 cycles of 21 day cycle of gemcitabine/capecitabine. Eligibl e patients will undergo apheresis during the last week of the thi rd cycle of gemcitabine/capecitabine to collect peripheral bloo d mononuclear cells for DC vaccine production. Patients will receive at least six PEP-DC vaccinations starting concomit ant with the 5th cycle of chemotherapy. PEP-DC vaccine of 5–10 × 106autologous DC in 1ml volume/treatment will be delivered subcutaneously every 3 weeks. Patients will receive oral ent eric- coatedaspirindailyforthedurationofthestudystartingfr omthe dayofﬁrstvaccinationuntiltheendofstudy.Nivolumabwill be administered starting 3 weeks after last chemotherapy cycle and will be given during the vaccination period until the last vac cine dose. Afterwards, it will be given as a maintenance therapy until appearance of new lesion(s) or unacceptable toxicity for maximum2years. To verify that the combination of PEP-DC vaccine and enteric-coated aspirin during and following standard adjuv ant chemotherapy, followed by nivolumab, will signiﬁcantly enhance tumor immunogenicity, and allow tumor response, the translational objectives of the study are the following: (a) to deeply characterize the tumor microenvironment of pancreati c adenocarcinoma patients; (b) to assess the overall eﬀects of the combined PEP-DC vaccine during and following standard adjuvant chemotherapy, followed by nivolumab on peripheral bloodandplasma;(c)todeterminetumorantigensagainstwhi ch thetreatmentelicitsaresponse. Identiﬁcation of Personalized Targets for Vaccination With NeoDisc Processing of Patients’ Material for PEP-DC Vaccine Preparation Informed consent of the participants was obtained following requirements of the institutional review board (Ethics Commission, CHUV). The translational researchhas been approved by the CHUV ethics committee (protocols2017-00305). DNA Extraction and Sequencing DNA was extracted for HLA typing and exome sequencing with the commercially available DNeasy Blood & Tissue Kit (Qiagen, Hilden, Germany), following manufacturers’ protocols. Five hundred nanograms of gDNA were used to amplify HLA genes by PCR. High resolution 4-digit HLA typing was performed with the TruSight HLA v2 Sequencing Panel from Illumina on a MiniSeq instrument (Illumina) (SupplementaryTable1 ). Sequencing data were analyzed with the Assign TruSight HLA v2.1 software (Illumina). For exome sequencing, SureSelect Exome V5 library type (Sureselect v5 capture,AgilentTechnologies,SantaClara,CA,USA),andpaire d endreadswerechosen,withatleast100xcoverageforthetum or andPBMCs. LC-MS/MS Analyses of Eluted HLA Peptides For immunoaﬃnity puriﬁcation of HLA peptides from tissues, weappliedapreviouslypublishedprotocol( 55,56).Brieﬂy,anti- HLA-I and anti-HLA-II monoclonal antibodies were puriﬁed from the supernatant of HB95 (ATCCR/circlecopyrtHB-95TM) and HB145 cells (ATCCR/circlecopyrtHB-145TM) using protein-A sepharose 4B beads (Invitrogen,Carlsbad,California),andcross-linkedtoth ebeads. Snap-frozen PDAC tissue samples were homogenized in lysis buﬀer on ice in 3–5 short intervals of 5s each using an Ultra Turrax homogenizer (IKA, T10 standard, Staufen, Germany) at maximum speed, as previously described ( 55,56). Lysates were cleared by centrifugation at 25,000 rpm (Beckman Coulte r, JSS15314, Nyon, Switzerland) at 4◦C for 50min. The Waters Positive Pressure-96 Processor (Waters, Milford, Massachu setts) wasusedwith96-well,3 µmglassﬁberand10 µmpolypropylene membranes micro-plates (Seahorse Bioscience, North Biller ica, Massachusetts). A depletion step of endogenous antibodies w as performed with plates containing Protein-A beads, and then the lysates were passed through a plate containing beads cross - linkedtoanti-HLA-I,andthensequentiallythroughaplatew ith the anti-HLA-II cross-linked beads. After washing with vary ing concentrations of salts, the beads were washed twice 2mL of 20mM Tris-HCl pH 8. HLA complexes and the bound peptides were eluted directly into pre-conditioned Sep-Pak tC18 100mg plates (ref number: 186002321, Waters) with 1% TFA. After washing the C18 wells with 2mL of 0.1% TFA, HLA-I peptides were eluted with 28% ACN in 0.1% TFA, and HLA-II peptides wereelutedfromtheclassIIC18platewith500 µLof32%ACN in 0.1% TFA. HLA-I, and HLA-II peptide samples were dried usingvacuumcentrifugation(ConcentratorplusEppendorf)an d storedat−20◦C. WemeasuredthepeptideswithLC-MS/MSsystemconsisting of an Easy-nLC 1200 (Thermo Fisher Scientiﬁc, Bremen, Germany)andtheQExactiveHF-Xmassspectrometer(Thermo FisherScientiﬁc,Bremen,Germany).Peptideswereseparated on a450mmanalyticalcolumnof75 µminnerdiameterfor120min usingagradientofH2O/FA99.9/0.1%(A)andACN/FA80/0.1% (B).Thegradientwasrunasfollows:0min2%B,thento5%Bat Frontiers in Immunology | www.frontiersin.org 4 August 2019 | Volume 10 | Article 1832 Bassani-Sternberg et al. Personalized Vaccine for Pancreatic Cancer 5min,35%Bat85min,60%Bat100min,and95%Bat105min ataﬂowrateof250nL/min. MS spectra were acquired in the Orbitrap from m/z =300– 1,650witharesolution of60,000(m/z =200),ionaccumulation timeof80ms.TheAGCwassetto3e6ions.MS/MSspectrawere acquired in a data-dependent manner, and 10 most abundant precursorionswereselectedforfragmentation,witharesol ution of 15,000 (m/z =200), ion accumulation time of 120ms and an isolation window of 1.2 m/z. The AGC was set to 2e5 ions, dynamic exclusion to 20s, and a normalized collision energy (NCE)of27wasusedforfragmentation. NeoDisc Pipeline Alignment Exome sequence reads were aligned to the Genome Reference Consortium Human Build 37 assembly (GRCh37) with BWA-MEM version 0.7.17 ( 57). The resulting SAM format was sorted by chromosomal coordinate and converted into a BAM ﬁle, then PCR duplicates were ﬂagged, using the Picard AddOrReplaceReadGroups and MarkDuplicates utilities, respectively (from http://broadinstitute.gith ub.io/ picard). Various quality metrics were assessed with the Pica rd MarkDuplicates, CollectAlignmentSummaryMetrics, and CalculateHsMetrics utilities. Following GATK best practice s, GATK BaseRecalibrator (within GATK v3.7-0) was used to recalibrate base quality scores (BSQR) prior to variant calli ng (58,59). BQSR corrects base quality scores based on an estimation of empirical error frequencies in the alignments . The recalibrated tumor and germline BAM ﬁles were then used as input for each of three variant callers: GATK HaplotypeCaller; MuTectv1;andVarScan2. Caller1:GATKHaplotypeCaller The GATK HaplotypeCaller algorithm improves variant calling by incorporating de-novoassembly of haplotypes in variable regions, thus reducing the overall false-positive variant c all rate (58,59).HaplotypeCallerwasruninGVCFmodeoneachtumor and germline recalibrated BAM ﬁle to detect SNV and Indel variants. The resultant gVCF ﬁles were combined using GATK GenotypeGVCF to produce raw variant calls for tumor and germlinewithininasingleVCF.Subsequentvariantqualitys core recalibration, following GATK best practices, was performed separately for SNVs and Indels (insertions/deletions) usin g the GATKvariantRecalibratortooltoidentifyhigh-conﬁdencec alls. Variant quality was assessed by the GATK VariantEval tool. Patient-speciﬁc SNPs were deﬁned as variants present in both tumor and germline, while variants present only in tumor were deﬁnedassomaticmutations. Caller2:MuTectv1 TheMuTectvariantcallingalgorithmpredictssomaticmutati ons basedonlogoddsscoresoftwoBayesianclassiﬁers(fromhtt ps:// github.com/broadinstitute/mutect). The ﬁrst classiﬁer i dentiﬁes non-reference variants in the tumor sample while the second detects whether those variants are tumor speciﬁc. Candidate somatic mutations are then ﬁltered based on read support, for example by ensuring that supporting reads map to both DNAstrands, in order to reduce next-generation sequencing art ifacts. IdentiﬁedsomaticmutationsareexportedinVCFformat. Caller3:VarScan2 The VarScan2 algorithm, unlike GATK and MuTect, relies on hard ﬁltering of calls rather than Bayesian statistics ( 60). This has the advantage of being less sensitive to bias such as extre me readcoverageandsamplecontamination.VarScan2ﬁltersread s based on parameters such as read quality, strand bias, minimu m coverage, and variant frequency. The multisample pileup ﬁle required for VarScan 2 input was generated with SAMtools ( 61, 62). VarScan 2 was run using default parameters and generated a VCF containing SNVs and Indels for both somatic mutations andSNPs. Non-redundantcallset Variant calls from GATK, MuTect v1, and VarScan 2 were combined into a single VCF that contains the union of the variantsofallthreecallers.Ambiguouscalls(i.e.,diﬀere ntcallsat thesamegenomiccoordinate)wereresolvedbyasimplemajori ty rule. If there was no majority, the call was rejected. GATK ReadBackedPhasingwasusedtoretrievethephasinginformati on of all variants in the combined VCF ( 58,59). The functional eﬀect of the variants was annotated by SnpEﬀ which predicts the eﬀects of variants on genes based on reference databases. To maximize variant annotation we used annotations from the hg19 (Refseq) and GRCH37.75 (Ensembl) databases ( 63–65). This non-redundant, annotated VCF ﬁle was used for further genomicsandproteogenomicsanalyses. Prediction and Prioritization of Neoantigens For the identiﬁcation of neoantigens, only “high conﬁdence” calls were selected, deﬁned as the set of variants containin g all somatic mutations plus linked SNPs (i.e., those SNPs present o n the same allele as the somatic mutation) detected by MuTect v1 alone or by a combination of at least two of the three variant callers describedabove. The novel amino acidgenerated by e ach single nucleotide somatic mutation was placed at the center of a 31mer peptide that also included any amino acid changes resulting from non-synonymous linked SNPs. In the case of a somatic indel mutation, the entire polypeptide encoded by the new open-reading frame plus the upstream 24 amino acids could be subjected to HLA ligand prediction. However, for the describedthreePDACsamplesthisoptionwasdisabled. HLA-I and HLA-II ligands were predicted by the MixMHCpred.v2.0.2 and MixMHC2pred.v1 algorithms, respectively ( 66–68). Both algorithms have been trained on naturally presented peptides and compute the likelihood of a peptide to bind to one of a given set of HLA alleles. Mutant peptides of sizes ranging from 9 to 12 and 12 to 19 amino acids, derived from the 31mer were supplied as input for HLA-I and HLA-II predictions, respectively, using patient-speciﬁc alloty pes asdeterminedbyHLAtyping( SupplementaryTable1 ). Tissue-speciﬁc gene expression data was downloaded from The Genotype-Tissue Expression (GTEx) project, a public resource that contains data from 53 non-diseased tissues ac ross nearly 1,000 individuals ( 69). We used a custom R script to Frontiers in Immunology | www.frontiersin.org 5 August 2019 | Volume 10 | Article 1832 Bassani-Sternberg et al. Personalized Vaccine for Pancreatic Cancer retrieve gene expression values, based on GTEx v7 publicly available data. The 90th percentile expression of the wild type gene in the tissue-derived tumor was reported from GTEx data, and mutations in genes not expressed (TPM <1) in pancreas wereexcluded. Due to the intrinsic content and properties of protein sequences,HLAligandsarenotdistributedequallyalongpro teins and tend to cluster in hotspots. We captured this information across dozens of cell types in our ipMSDB database ( 70). The overlapofthewild-type-formofamutantpeptidewithahotspot in ipMSDB was calculated, as well as the level of presentation of the source protein. Any mutant peptide matching any wild-type sequence in SwissProt ( 71) or found in the reference GRCh37 (64)proteomewasﬁlteredout. Finally,weusedacustompythonscripttodesignthebestlong peptide(s)foreverymutation,encompassingthehighestpossib le number of HLA-I and HLA-II binding peptides (MixMHCpred and MixMHC2pred %Rank <5% or found in ipMSDB). Long peptides were ranked by the minimum p-value of the predicted HLA-Ineoantigens,andthetop10longpeptideswereselected. Proteogenomics For every sample, we created a reference fasta ﬁle where residu e mutation information was added to the header of the aﬀected translated transcripts, in a format compatible with MaxQuant v1.5.9.4i as previously reported ( 72). We used the GENCODE v24(73)(GRCh37humanreferenceassembly,downloadedfrom https://www.gencodegenes.org/human/release_24lift37.h tml) as the standard reference dataset (89,543 entries). We parsed t he GENCODEcomprehensivegeneannotationﬁle,inGFF3format, to extract genomic coordinate information for every exon. These coordinates were compared with sample-speciﬁc variant coordinates to derive non-synonymous amino acid changes withineachprotein. For every patient, we searched the immunopeptidomics MS data against the patient-speciﬁc customized reference datab ase, including a list of 247 frequently observed contaminants. T he enzyme speciﬁcity was set as unspeciﬁc, and peptides with a length between 8 and 25 AA were allowed. The second peptideidentiﬁcationoptioninAndromedawasenabled.Afalse discovery rate (FDR) of 5% was required for peptides and no protein FDR was set. The initial allowed mass deviation of the precursor ion was set to 6 ppm and the maximum fragment mass deviation was set to 20 ppm. Methionine oxidation and N-terminalacetylationweresetasvariablemodiﬁcations. PEP-DC Manufacturing The PEP-DC vaccine is composed of autologous monocyte- derivedDCpulsedwithpersonalizedpeptides(PEP).Monocytes are enriched from a fresh leukapheresis using CD14+cells selection on the CliniMACS Prodigy (Miltenyi). This process is GMP compliant and allows for a fast and reliable monocyte selectioninaclosedsystem.Puriﬁedmonocytesarediﬀerent iated into immature monocyte-derived DC (iDC) by a 5 days culture in the presence of IL-4 and GM-CSF. On day 6, iDC are then loadedovernightwith10longpeptidesandmatured/activated for 6–8husingamaturationcocktailcomposedofMPLAandIFN γ.Cellsareﬁnallyharvestedandcryopreservedasvaccinedoses (5– 10×106cells per dose). For each injection of PEP-DC vaccine, one dose is thawed, washed and resuspended in NaCl 0.9% supplemented with 1% human albumin before being transferred intosyringesandstoredat2–8◦Cuntiladministration. Immunogenicity Assessment of PEP-DC Candidates Pre-immunization The immunogenicity the long peptides was evaluated in cryopreservedperipheralbloodmononuclearcells(PBMC)from the three subjects as described ( 74). PBMC were thawed, rested overnight in RPMI 10% FBS with Penicillin/Streptomycin. For thein vitrostimulation (IVS), cells were plated in 24- to 96- well plates at 2 ×106cells per well in RPMI, 8% human serum supplemented with Penicillin/Streptomycin, 50 µM beta- mercaptoethanol and recombinant human IL-2 at a ﬁnal concentration of 100 UI/ml. The cells were stimulated with peptide pools containing 1 µg/ml of each candidate peptide. At day 12, intracellular cytokine stainings (ICS) were performe d. Each individual well was splitted in two identical fractions and one fraction only was re-challenged with 1 µg/ml of the corresponding peptide for 16–18h at 37◦C and 5% CO2 in presence of 1 µg of brefeldin A (Golgiplug, BD). As a positive control, cells stimulated with staphylococcal enterotoxin B (SEB) at a concentration of 0.25ng/ml. After 16–18h of re- stimulation with individual long peptides, cells were harvest ed and stained with anti-CD3, anti-CD8, anti-CD4, anti-IL-2, anti- TNF-α, anti-IFN- γ(BD biosciences), and with viability dye (Life technologies). Flow cytometry was performed using a four-lasers Fortessa (BD biosciences) and analyzed with Flo wJo v10(TreeStar). RESULTS We here present a novel study were a vaccination schedule is incorporated in the SOC chemotherapy adjuvant setting in patients with non-metastatic resectable pancreatic adenocarcinoma followed by nivolumab (an antibody against PD-1), to boost and maintain the vaccine’s eﬀect ( Figure1). The studywasoptimallydesignedtooﬀerinnovativecancervaccine s for a PDAC patient population that on one hand would ﬁt the courseofstandardofcare,andontheotherhandwillbefeasi ble intermsofthetimerequiredfortheprocessofantigendiscov ery andthemanufacturingofthevaccine. It has been correctly pointed out that putting a mutanome- based individualized treatment concept into practice require s both highly interdisciplinary research and an innovative dr ug development process ( 75). To ﬁt the tight schedule of the clinical trial, a period of 5 weeks was dedicated for antigen discovery. Upon reception of a pair of tumor tissue sample and matchedPBMCs,DNAextractionisperformedforwholeexome sequencing and HLA typing, and the tumor tissue sample is processed for puriﬁcation of HLA-I and HLA-II peptides for MS analyses. Within the 2 weeks required for sequencing the DNA samples, HLA typing and MS analyses are completed. The following 2 weeks are dedicated for executing the NeoDisc Frontiers in Immunology | www.frontiersin.org 6 August 2019 | Volume 10 | Article 1832 Bassani-Sternberg et al. Personalized Vaccine for Pancreatic Cancer FIGURE 1 | Clinical trial study design. pipeline, for data mining and for manual inspection of the data andresults,leadingtotheselectionof10longoptimallydesi gned neoantigens. Finally, the production needs to be “on demand, ” cost-eﬀective, rapid, and compliant with Good Manufacturing Practice(GMP). NeoDisc Pipeline for Neoantigen Discovery in PDAC We here tested the feasibility of prioritizing neoantigens i n PDAC as targets for our PEP-DC vaccine in three PDAC patients,14JQ,154H,and16AY.TheNeoDiscpipelineintegrates multiple types of data input from next generation sequencing data, MS immunopeptidomics datasets, and publicly available resources ( Figure2). First, the NeoDisc pipeline requires a list of non-synonymous somatic mutations that aﬀect protein- coding regions as identiﬁed by three diﬀerent mutation-call ing algorithms: MuTect, VarScan2, and GATK. A combined VCF ﬁle is generated and annotated with amino acid changes and transcript information. To increase accuracy, only “hig h conﬁdence” calls were selected, deﬁned as the set of somatic mutations detected by MuTect alone or by a combination of at leasttwoofthethreevariantcallersdescribedabove.Asex pected, themutationalloadinthethreePDACpatientswaslow,with60 , 39, and 23, non-synonymous somatic mutations in 14JQ, 154H, and 16AY, respectively, which is within the range previously reported ( 53). Among them, we detected mutations in predicted drivergenes,theMLLT4(Ser1708Ala)andPTPN12(Gly532Glu) (76–78).Wethenattemptedtoidentifypersonalizedneoantigens using two diﬀerent approaches; direct identiﬁcation with mass spectrometry and by prediction of HLA ligands encompassing anyofthesemutations.We ﬁrst performed MS immunopeptidomics analyses on exactly the same tumor tissue used for the genomics analysis from the three PDAC patients, and applied a proteogenomics pipeline as previously described ( 72) in order to identify neoantigens naturally presented in the PDAC tissues. We have identiﬁed 11,437, 4,437, and 6,158 HLA-I and 1,569, 448, and 3,319 HLA-II peptides, from the 14JQ, 154H, and 16AY tumor tissues, respectively ( SupplementaryTable2 ). However, no neoantigens could be identiﬁed by MS. Either many of the potential neoantigens remain undetected in the MS-based analyses because of the lack of sensitivity, or they might not be naturally presented. The likelihood of detectingneoantigensbydiscoveryMSincreaseswiththeove rall depth of ligandomic data available and with the mutational load. Here, both aspects were not suﬃcient to successfully detectneoantigens. Additional tumor-associated antigen (TAAs) derived HLA ligands are frequently identiﬁed by MS, such as “normal” (wild-type) proteins overexpressed or restricted to tumors (e .g., MelanA, Tyrosinase, PMEL in melanoma; NY-ESO in multiple cancer types). Such targets have been exploited in innovative personalized vaccines and T cell based therapies ( 79,80). We have identiﬁed multiple TAAs in the immunopeptidome for each of the three PDAC patients, including the testis- speciﬁc protein bromodomain testis-speciﬁc protein (BRDT), L-lactate dehydrogenase C chain (LDHC), outer dense ﬁber protein 2 (ODF2), coiled-coil domain-containing protein 110 (CCDC110), tumor associated antigens mesothelin (MSLN), mucin-1 (MUC1), prolyl endopeptidase FAP (FAP), and the cellular tumor antigen p53 (TP53) ( SupplementaryTable2 ). Nevertheless,afterthoroughdatamining,weestimatedtha tthese Frontiers in Immunology | www.frontiersin.org 7 August 2019 | Volume 10 | Article 1832 Bassani-Sternberg et al. Personalized Vaccine for Pancreatic Cancer FIGURE 2 | Schematic overview of NeoDisc pipeline for prioritization of neoantigens in PDAC for the design of optimally long pepti des for vaccination. ligands were unlikely to be immunogenic and therefore have decidednottoincludetheminthevaccine. Prioritization of Neoantigens and Design of Long Peptides Consequently,inthethreePDACpatients,theselectionofta rgets was based exclusively on prediction of neoantigens. To incre ase accuracy, the “high conﬁdence” calls were selected, and a li st of 31 mer peptides with mutation in the middle position was then generatedandsubjectedtobindingpredictionsofHLAclassI (9– 12mers)andclassII(12–19mers)withtheMixMHCpred.v2.0.2 andMixMHC2pred.v1algorithms,respectively( 66,68,81).Both algorithms have been trained on naturally presented peptides and compute the likelihood of a peptide to bind to one of the given set of the patient HLA alleles. We have previously showed that large scale immunopeptidomics dataset may help in prioritizing predicted neoantigens ( 70,82). Therefore, we mapped the list of predicted neoantigens on our ipMSDB ligandomic database that contains a million of HLA-I and HLA - II ligands. The overlap between the predicted neoantigen and the wild-type (WT) form present in ipMSDB was determined, as well as the level of presentation of the source genes. These values were considered for prioritization; neoantigens mat ching exactly WT counterparts in ipMSDB were prioritized ( Table1). Mutated source genes that were underrepresented in ipMSDB were excluded. In addition, we excluded predicted neoantige ns thatareidenticaltootherWTsequencesinthehumanproteome (GRCh37 Genome assembly and UniProt database) and all predictedneoantigensderivedfromhighlymutatedgenes,wh ich are likely to be false positives. Finally, we excluded genes t hat are known not to be expressed in pancreas (TPM <1 in GTEx). For each mutation, we designed a few long peptides covering as many predicted HLA-I and HLA-II neoantigens as possible. Weranked the mutations in the format of long peptides according to the best predicted binding aﬃnity to HLA-I alleles (%Rank ≤5% MixMHCpred.v2.0.2), the number of HLA-I and HLA-II predicted neoantigens harboring the mutation, and the numbe r ofrepresentedHLAalleles.Finally,foreachmutationwesel ected theshortestlongpeptidecoveringasmanypredictedHLA-Iand HLA-IIneoantigens( Figure3)andcompletedthelistoftenlong peptides(PEP). DC Vaccine Production The DC-vaccine used in this study is a frozen suspension of patient-speciﬁc, ex vivocultured autologous monocyte derived DCs loaded with synthetic neoantigen (personalized) peptides . The proprietary name for the biological product comprising this substance is PEP-DC, which refers to Personalized Pepti des loadedontoautologousDCs.ManufacturingofPEP-DCconsists of ﬁve main steps described in Figure4, starting with peptides identiﬁcation and manufacturing. We have tested and valida ted this production process with healthy donor leukapheresis and peptides mixes of up to 9 peptides. Indeed, because of the peptide length, some synthesis failure should be expected even after sequence optimization and careful peptide selection. Ba sed on three experimental batches, we can evaluate that PEP-DC process leads to the production of 2.8 ±2.1×108PEP-DC cells, corresponding to 56 ±41 PEP-DC cryopreserved vaccine doses (based on 5.0 ×106cells per dose) per manufacturing run. Speciﬁcations of the ﬁnal product ensure safety (sterili ty, mycoplasma, endotoxin), viability (Trypan blue exclusion), identity (phenotype), and functionality (IL12p70 secretion u pon maturation) of the PEP-DC vaccine ( Table2). For each vaccine injection, a PEP-DC dose is thawed, washed and reconstituted NaCl-Albumin before injection. Viability is checked on eac h reconstituted dose with a target of ≥60.0% viable cells. All Frontiers in Immunology | www.frontiersin.org 8 August 2019 | Volume 10 | Article 1832 Bassani-Sternberg et al. Personalized Vaccine for Pancreatic CancerTABLE 1 | Basic clinical information and detailed information about the 10 optimally designed long peptides for each patient. Rank Chromosome positionGene Expression in pancreas, GTEx [TPM]Mutation Gene driver and mutation statusLong peptide sequence ipMSDB HLA-I ipMSDB HLA-IILowest HLA-I binding pvalLowest HLA-II binding pval# predicted peptides# HLA-I alleles# HLA-II alleles 14JQ, PDAC, 60 NON-SYNONYMOUS SOMATIC MUTATIONS 1 16_8994451 USP7 11.509 p.Tyr749Asp LYEEVKPNLTERIQD DDVSLDKALDE EXACT 0.002 0.01209 31 4 3 2 7_27169740 HOXA4 1.06 p.Ala205Thr VVYPWMKKIHVS TVNPSYNGGEPKRSRT EXACT EXACT 0.004 0.0005 58 3 7 3 9_33797978 PRSS3 13983 p.Val175Ile TLDNDILLIKLSSPA IINSRVSAISLPT EXACT INCLUDED 0.02 0.00096 39 4 7 4 14_105415346 AHNAK2 1.162 p.Thr2148Ala AHLQGDLTLANKDLT AKDSRFKM EXACT PARTIAL 0.002 0.00914 31 3 2 5 1_17083776 MST1L 34.35 p.Arg674Leu ARSRWPAVFT LVSVFVDWIHKVMRLG 0.0001 0.00578 54 3 6 6 6_168366581 MLLT4 11.744 p.Ser1708Ala Driver LPRDYEPPSP APAPGAPPPPPQRNAS 0.0001 0.00054 80 3 3 7 8_52732961 PCMTD1 16.471 p.Pro342Thr EPPQNLLREKIMKL TLPESLKAYLT PARTIAL PARTIAL 0.0008 0.00098 66 4 3 8 6_150001239 LATS1 3.182 p.Asp789Asn KDNLYFVMDYIPGG NMMSLLIRMGIFPE PARTIAL 0.0009 0.00126 58 3 7 9 3_123419461 MYLK 3.273 p.Asp952Asn Passenger RKVHSPQQV NFRSVLAKKGTSKT 0.001 0.01599 24 4 3 10 1_155697428 DAP3 12.728 p.Leu168Phe IPDAHLWVKNCRD FLQSSYNKQRFD 0.002 0.00521 45 4 2 154H, PDAC, 39 NON-SYNONYMOUS SOMATIC MUTATIONS 1 2_85576579 RETSAT 17.724 p.Arg309Trp IAFHTIPVIQ WAGGAVLTKATVQSVL EXACT EXACT 0.0004 0.00026 65 5 4 2 12_51453191 LETMD1 14.494 p.Asn367Asp AELSLLLHNVVLLST DYLGTRR EXACT EXACT 0.006 0.00298 50 4 4 3 20_34457413 PHF20 2.4 p.Arg288Gly NSQTLQPITLELRR GKISKGCEVPL EXACT 0.02 0.03246 19 4 2 4 3_57908703 SLMAP 3.553 p.Lys783Gln KQSITDEL QQCKNNLKLLREK 0.0007 0.00357 40 3 2 5 2_241700220 KIF1A 11.548 p.Ser769Phe KKVQFQFVLLTDTLY FPLPPDLLPPEAA 0.0008 0.00201 72 5 5 6 2_238253286 COL6A3 16.075 p.Arg2459Trp VAVVTYNNEVTTEI WFADSKRKSVLLDK 0.0009 0.00133 61 5 5 7 13_96592287 UGGT2 3.986 p.Val579Gly KKDQNILTVDNVKS GLQNTF 0.002 0.01697 24 6 3 8 7_77256591 PTPN12 12.375 p.Gly532Glu Driver DRLPLDEK EHVTWSFHGPENAIPI PARTIAL PARTIAL 0.003 0.0391 12 6 1 9 18_55352319 ATP8B1 10.673 p.Asn486Lys DHRDASQH KHNKIEQVDFSWNTYA 0.003 0.0339 14 5 2 10 8_9627645 TNKS 3.91 p.Gly1257Glu HRQMLFCRVTL EKSFLQFSTMKMAHA PARTIAL PARTIAL 0.003 0.00039 39 6 5 16AY, PDAC, 23 NON-SYNONYMOUS SOMATIC MUTATIONS 1 17_15134320 PMP22 11.978 p.Gly133Ser HPEWHLNSDYSY SFAYILAWVAFPLALL EXACT 0.0004 0.00018 86 4 8 2 X_54014354 PHF8 5.113 p.Ser621Tyr LLMSNGSTKRVKSL YKSRRTKIAKKVDK 0.0001 0.0075 48 5 2 3 9_33794809 PRSS3 13983 p.Ser5Asn MRET NVFTLKKGRSAPLVF 0.0004 0.00558 10 4 3 4 12_9085452 PHC1 9.639 p.Gln467Lys TQQVPPSQSQQ KAQTLVVQPMLQSSPL PARTIAL 0.0004 0.0044 42 5 6 5 19_1037681 CNN2 20.083 p.Asp259Asn APGTRRHIYDTKLGT NKCDNSSMSLQMG 0.0008 0.01696 27 5 5 6 20_50704942 ZFP64 1.539 p.Arg187Leu YASRNSSQLTVHL LSHTGDTPFQ 0.002 0.00077 40 3 4 7 12_31254897 DDX11 5.459 p.Arg728His LRQVHAHWEKGGLLG HLAARKKIFQE 0.003 0.00764 37 3 2 8 11_32954416 QSER1 3.78 p.Asn409Asp SSNQQEVLSSVTNE DYPAQTRDLSSVSQ PARTIAL 0.003 0.00478 39 3 4 9 1_27177681 ZDHHC18 4.114 p.His299Tyr FFSIWSILGLSGF YTYLVASNLTTNEDI PARTIAL 0.005 0.00012 106 4 8 10 20_60892518 LAMA5 23.906 p.Arg2465Gln AKEELERLAASLDGA QTPLLQRMQT PARTIAL PARTIAL 0.008 0.00763 41 5 6 The position of the mutation in the long peptide is indicated in red. ipMSDB HLA -I and ipMSDB HLA-II columns show the matching of the WT counterpart of the pre dicted neoantigen in the ipMSDB. Prediction of driver genes and mutationstatusannotationsarederivedfromIntOGendatabase. Frontiers in Immunology | www.frontiersin.org 9 August 2019 | Volume 10 | Article 1832 Bassani-Sternberg et al. Personalized Vaccine for Pancreatic Cancer FIGURE 3 | Example for the design of the minimally long peptide coverin g the mutation Arg288Gly in PFH20 gene identiﬁed in 154H PDAC p atient. FIGURE 4 | Schematic overview of PEP-DC manufacturing process and tim elines. PEP-DC batches prepared in this pilot study met speciﬁcation for product release as described in Table2. This conﬁrms that our GMP-compliant manufacturing process is suitable for the productionPEP-DC. Pre-immunization Immunogenicity of PEP Candidates Even though immune responses against neoantigens prior to vaccination are typically rare, we decided to test if any of th e 10 PEPlongpeptidesmayberecognizedbyautologousTcellsfrom peripheral blood. Pre-immunization immunogenicity was test edforthethreePDACpatients.Althoughsomeofthelongpeptides failedthesynthesisqualitycontrolandcouldnotbetested,C D4+ T-cell responses against PEP candidates were detected again st at least one long peptide in all three donors, while no CD8 +T cell responsescouldbedetected( Figure5). DISCUSSION AND INNOVATION Over the last 10 years immunotherapy has changed the treatment landscape of several tumor types in metastatic sett ing. Management of patients with non-metastatic cancer relies Frontiers in Immunology | www.frontiersin.org 10 August 2019 | Volume 10 | Article 1832 Bassani-Sternberg et al. Personalized Vaccine for Pancreatic Cancer on multimodality treatment that includes surgical resecti on depending on tumor type and peri-operative chemotherapy. In PDAC, despite these aggressive measures, the high propensity of relapse has a detrimental eﬀect on survival. The high metastatic potential is due to the presence of micrometastasi s at systemic sites in patients with early-stage pancreatic can cer (83). In this proof of concept trial, our aim is to demonstrate that in such very aggressive diseases, there is a need to act without any delay, and early immunomodulation may be the keyresponse. TABLE 2 | Speciﬁcation for release for the ﬁnal product of PEP-DC doses. Test Analytical procedure Speciﬁcation PEP-DC at day 6 (ﬁnal product)Sterility BacTEC (aerobic and anaerobic)No growth Mycoplasma MycoSeq Negative Endotoxin Endosafe ≤10.0 EU/mL Cell count Manual cell count by Trypan blue exclusion≥45.0×106viable cells Viability ≥60.0% viability Cell purity/identityFlow cytometry ≥60.0% live HLA-DR+CD86+ cells ≤20.0% CD14+cells Culture supernatant at day 6 after maturationFunctionality IL-12p70ELISA ≥50.0 pg/mLAlthough pancreatic cancer patients present high frequencies of functional tumor-reactive T cells in the bone-marrow and blood(84),andshowanaveragemutationburdensimilartoother solid tumors ( 85), parsing tumor immune microenvironment (TME) of pancreatic cancer seems to be a challenge. In PDAC, tumor-speciﬁcCTLsbecome“trapped”intheperitumoraltissue and in the tumor stroma, not reaching pancreatic tumor cells in suﬃcient amounts ( 86,87). Additionally, exhaustion of eﬀector CD8+T-cells by the TME as well as hampered recruitment of cDC1s by downregulating CCL4 signaling upon constitutively active β-cateninsignalingmayexplaintheineﬀectiveantitumoral response,whichunderscorestheimportanceofendogenousDCs forinitiatinganti-tumorimmunity. Rationale for Combination Immunotherapy in PDAC Currently,clinicalbeneﬁtusingdiﬀerentagentsinmonother apy is very limited in PDAC. Therefore, combination strategies are required, in order to obtain a synergistic eﬀect on potential eﬃcacy, yet keeping expected adverse events under manageable conditions. Therefore, it is important to establish both the scientiﬁc rationale of the proposed combination, as well as the besttimingforintroducingeachcomponent. Treatment of metastatic cancer essentially relies on cytoto xic drugs that kill tumor cells or hinder their proliferation. Although a primary goal of anti-cancer chemotherapy is the tumor mass reduction, it is now clear that oﬀ-target eﬀects, especially directed to the host immune system, may reduce the FIGURE 5 | T-cell responses in donors 14JQ, 16AY, and 154H against long peptides. The percentage of IFN- γ-producing T cells are shown. Black (unstim) and white (SEB) bars represents negative and positive controls, resp ectively. Positive peptides are identiﬁed in red. Frontiers in Immunology | www.frontiersin.org 11 August 2019 | Volume 10 | Article 1832 Bassani-Sternberg et al. Personalized Vaccine for Pancreatic Cancer immunosuppressive activity of malignant cells and cooperate for successful tumor eradication ( 88). Gemcitabine (GEM) is a chemotherapeutic agent acting as a nucleoside analog that also targets ribonucleotide reductase by inactivating the enzyme irreversibly. It is used in various carcinomas such as non-s mall cell lung cancer, pancreatic cancer, bladder cancer, and bre ast cancer, and it represents the primary systemic agent for the treatment of pancreatic cancer. On standard dose schedules in patients with pancreatic cancer, the drug is associated wit h manageable toxicity, and its administration has led to a sur vival beneﬁt both in the primary and adjuvant settings ( 89,90). In advanced pancreatic cancer patients, GEM therapy may decrease memory T-cells, promote naive T-cell activation ( 91), and induce the proliferation of CD14+monocytes and CD11c+ DC (92). GEM is also able to induce apoptotic destruction of tumor cells and potentially load the immune system with large amounts of tumor antigen, but this is not enough to initiate a protective antitumor response and adjuvant immunotherapy is required( 93). A peptide cocktail vaccine OCV-C01 containing epitope peptides [coding for vascular epithelial growth factor recepto r (VEGFR1 ad VEGFR2)] was investigated in combination with GEM in the adjuvant treatment for resected pancreatic cancer patients ( n=30) in a single arm multicenter Phase II study. OCV-C01combinedwithGEMwastolerablewithamedianDFS of15.8months(andaDFSrateat18monthsof34.6%),whichwas favorable compared with previous data for resected pancreatic cancer(94).InanotherphaseIpilotstudy,aWilmstumorgene- 1 peptide-pulsed DC vaccination was evaluated in combination withGEMasaﬁrst-lineoftreatmentin10patientswithadvanc ed pancreaticcancer.WT1peptide-pulsedDCGEMisfeasible,well- tolerated, and eﬀective for inducing anti-tumor T-cell respo nses (95). Kimura et al. evaluated a DC-based vaccine alone or in combinationwithlymphokine-activatedkiller(LAK)cells, along with gemcitabine and/or S-1 in 49 patients with inoperable pancreatic cancer ( 96). Of these patients, two manifested a complete remission, ﬁve a partial remission, and 10 had stable disease. The median survival of these individuals was 360 day s, which appeared to be longer than what could be achieved with gemcitabine and/or S-1. Thus, the combination of DC- based immunotherapy and chemotherapy seems well-tolerated by advanced PDAC patients but warrants further investigatio n through combination with ICB or other immunotherapies. In our study, we build on the gemcitabine/capecitabine backbon e for not ﬁt pancreatic cancer population (ECOG PS 1 or 2) and exploretheadditivebeneﬁtsofDC-vaccinationfromthe5thc ycle ofchemotherapy,followedbynivolumabtreatment. Inpancreaticcancer,apossibleexplanationforthetherapeuti c failure of PD-1/PD-L1 blockade therapy is the lack of natural inﬁltration of eﬀector immune cells in most cases (17,18,20). Vaccine-based immunotherapy is a potential strategy to activate eﬀector T cell traﬃcking into the TME. Additionally, it has been shown that the repertoire of clonal ly expanded tumor antigen-reactive cells within TILs expresses PD-1 (97), either in spontaneous responses or vaccine- mediated.Furthermore,vaccinationinducesintratumoral PD-L1 expression( 98),suggestingaroleforPD-1blockadeinenhancingvaccine eﬃcacy ( 98,99). Consistently, in a preclinical model for pancreatic cancer, GVAX administration (a cancer vaccin e composed of allogeneic pancreatic tumor cell line engineered to secrete GM-CSF) induced upregulation of PD-L1 expression when compared to untreated human and mouse pancreatic tumors. Combination therapy with GVAX and PD-1/PD-L1 blockade improved survival, and correlated with increased CD8+Tinﬁltrationintopancreatictumors( 100). Currently very few clinical trials combining cancer vaccin es and PD-1/PD-L1 blockade have been reported in the setting of pancreatic cancer. Combination strategies using DC vaccin es withICBshouldgenerateanadditiveeﬀect( 98,99,101),withlow additional toxicity due to DC vaccination ( 102,103). Nesselhut et al. demonstrated that the eﬃcacy of DC based therapy can be improved by blockade of PD-L1, enhancing the T-cell speciﬁc response ( 104). Dose and schedule for anti-PD-1 therapy and vaccines have been minimally studied; however, both PD-1 on activated T cells and PD-L1 on tumors appear rapidly following exposure to interferon ( 105), suggesting that early application of PD-1 blockade may be important. For this reason, we have decided to start nivolumab treatment 3 weeks after the end of SOC treatment, aiming also to avoid potential toxicities due to combinedchemo-ICB. Because Treg may persist despite checkpoint blockade, Treg depletion in conjunction with checkpoint blockade and vaccinationmayenhanceclinicalanti-tumoreﬃcacy.Systema tic reviews of the results of aspirin in cardiovascular studies h ave suggested that low-dose aspirin reduces overall cancer inci dence andmortalityincludinginpancreaticcancer( 106,107).Interms ofitsmechanism( 108),ithasbeenshownthatnon-steroidalanti- inﬂammatory drugs may limit carcinogenesis and enhance the immune response by (a) preventing prostaglandin E 2(PGE2)- mediated inhibition of DCs and reducing the transition of monocytes to immunosuppressive MDSCs ( 109); (b) reducing the inhibitory potential of Tregs induced by PGE2 ( 110); and (c) abrogating the PGE2 induced suppression of eﬀector T-cell proliferation by regulatory T cells ( 111), therefore contributing toenhancedimmunesurveillance.Furthermore,PGE2inhibi tors like aspirin can counteract the FasL mediated elimination of activated lymphocytes by the tumor endothelial cells, as well as reduce the immunosuppressive conditions, thus enhancing the immune response against the tumor. We therefore consider that blockade of PGE2 in cancers using aspirin can reverse the endothelial barrier and synergize with vaccination allowi ng T cell inﬁltration. Consequently, we will use aspirin all along our study, which we expect to synergize with T cell activation by PD-1/PD-L1blockade. Neoantigen Prediction and Selection for PEP-DC Identiﬁcation and selection of targets for neoantigen base d vaccinesischallenging.Massspectrometryhasbeeninstrum ental for the identiﬁcation of cancer-associated antigens among the endogenously presented peptides. In recent years, dedicated computational pipelines for proteogenomic applications facilitated the direct identiﬁcation of neoantigens by MS in Frontiers in Immunology | www.frontiersin.org 12 August 2019 | Volume 10 | Article 1832 Bassani-Sternberg et al. Personalized Vaccine for Pancreatic Cancer murine and human cancer cell line models ( 49,112–115), B cell lymphomas ( 116), and melanoma tissues ( 72) as well as other cryptic peptides resulting from unconventional coding sequences in the genome ( 117,118). However, only a handful of neoantigens have been identiﬁed by MS in a given sample, and typically in high mutational load tumors such as melanoma (72). Indeed, we could not identify with discovery MS-based immunopeptidomics neoantigens in the three investigated PDAC samples. While several tumor-associated antigens were identiﬁed, after literature mining we concluded that these antigens might be poorly immunogenic, and in these three case s wedecidedtoexcludenon-mutatedtargets. The prioritization and selection of neoantigens for personalized vaccines in low mutational load tumors like PDAC is largely performed with HLA ligand interaction prediction algorithms. The performance of such tools has improved signiﬁcantly with the incorporation of MS HLA ligand elution data in the training of the algorithms, both for HLA-I ( 81,119–121), and more recently for HLA-II ( 68). Furthermore, interrogation of properties of the thousands of diﬀerent source-proteins has revealed biological determinan ts that correlate with presentation, such as level of translati on and expression, turnover rate, proteasomal cleavage speciﬁcitie s, hotspots,andbiologicalfunctions.Integratingsuchvaria blesinto a single predictor further improves prediction of neoantigens (70,72,120,122).Becausepredictorsofimmunogenicityarestill immature ( 123) false positives are inevitably included among the predicted neoantigens, which may eventually be included in avaccine. A main innovative aspect of our study is the identiﬁcation of PDACmutatedneoantigens.WehavedesignedNeoDisc,anovel proteogenomics antigen discovery pipeline for identiﬁcation and selection of neoantigens, and we apply it for the ﬁrst time in PDAC. NeoDisc integrates multiple state of the art prediction tools, large-scale ligandomic database, and a unique personalized and optimized design of long peptides that maximizes the likelihood that the selected mutations w ill eventually be presented by the HLA-I and HLA-II complexes on the loaded DCs. While in this PEP-DC study the existence of pre-existing immune responses against the long peptides is not a prerequisite for inclusion in the vaccine, such analysis is performed as part of a large translational program that aims to provide extensive immunogenicity training data that will allow future development to improve the performance ofNeoDisc. This proof of concept study aimed to assess speciﬁcally the feasibility of prioritizing immunogenic neoantigens wi th NeoDisc. Indeed, we were able to conﬁrm for the three patientspre-existingimmuneresponsesagainstintotalfourl ong neoantigen peptides with autologous peripheral CD4 +T cells. No CD8+T cell responses could be detected. This might be related to the low frequency of neoantigen speciﬁc CD8 +T cells. Alternative strategies could have been more sensiti ve to detect CD8 +T-cell responses, such as peptide-MHC multimers screening. However, unfortunately, there were no PBMC left to test this hypothesis. The clinical trial has not started yet, and therefore the investigation of immune responses post-vaccin ecouldnotbeperformed.Thistrialwillgiveustheopportunityt o (1)betterunderstandPDACTMEsincewewillbeabletoevaluat e the mutational rate in PDAC and predict the presentation of neoantigens; (2) assess the frequency of speciﬁc T cells to suc h mutant epitopes in PDAC patients, before and after treatment with ICB; (3) validate the immunogenicity of neoantigens an d theirtherapeuticeﬀect. In conclusion, PDAC in early-stage remains a deadly disease with limited treatment options and the development of novel strategiestailoredtoindividualpatientsisthekey.Ourappr oach isfocusedparticularlyonpatientswithaborderlineperforma nce statusoracomorbidityproﬁlethatprecludesmultiagentadjuv ant therapy(typefolforinox).Inthiscontext,wegivetheopportun ity even in patients with the worst prognosis to have access to innovativetherapies. DATA AVAILABILITY The raw data supporting the conclusions of this manuscript will be made available by the authors.