expression analysis and signiﬁcance of pd-1, lag-3, and ... · precision medicine and imaging...

Precision Medicine and Imaging

Expression Analysis and Significance of PD-1,LAG-3, and TIM-3 in Human Non–Small Cell LungCancer Using Spatially Resolved andMultiparametric Single-Cell AnalysisIla Datar1,2, Miguel F. Sanmamed3,4,5, Jun Wang3, Brian S. Henick1,2, Jungmin Choi6,Ti Badri3,Weilai Dong6, Nikita Mani1, Maria Toki1, Luis D. Mejías4, Maria D. Lozano4,Jose Luis Perez-Gracia4,Vamsidhar Velcheti7, MatthewD. Hellmann8,9,10, Justin F.Gainor11,Kristen McEachern12, David Jenkins12, Konstantinos Syrigos13, Katerina Politi1,2,Scott Gettinger2, David L. Rimm1,2, Roy S. Herbst2, Ignacio Melero4,5, Lieping Chen3, andKurt A. Schalper1,2

Abstract

Purpose: To determine the tumor tissue/cell distribution,functional associations, and clinical significance of PD-1, LAG-3, and TIM-3protein expression in humannon–small cell lungcancer (NSCLC).

Experimental Design: Using multiplexed quantitativeimmunofluorescence, we performed localized measure-ments of CD3, PD-1, LAG-3, and TIM-3 protein in >800clinically annotated NSCLCs from three independentcohorts represented in tissue microarrays. Associationsbetween the marker's expression and major genomic altera-tions were studied in The Cancer Genome Atlas NSCLCdataset. Using mass cytometry (CyTOF) analysis of leuko-cytes collected from 20 resected NSCLCs, we determined thelevels, coexpression, and functional profile of PD-1, LAG-3,and TIM-3 expressing immune cells. Finally, we measuredthe markers in baseline samples from 90 patients withadvanced NSCLC treated with PD-1 axis blockers andknown response to treatment.

Results: PD-1, LAG-3, and TIM-3 were detected in tumor-infiltrating lymphocytes (TIL) from55%, 41.5%, and25.3%ofNSCLC cases, respectively. Thesemarkers showed a prominentassociationwith eachother and limited associationwithmajorclinicopathologic variables and survival in patients not receiv-

ing immunotherapy. Expression of the markers was lower inEGFR-mutated adenocarcinomas and displayed limited asso-ciation with tumor mutational burden. In single-cell CyTOFanalysis, PD-1 and LAG-3 were predominantly localized onT-cell subsets/NKT cells, whereas TIM-3 expression was higherin NK cells and macrophages. Coexpression of PD-1, LAG-3,and TIM-3 was associated with prominent T-cell activation(CD69/CD137), effector function (Granzyme-B), and prolif-eration (Ki-67), but also with elevated levels of proapoptoticmarkers (FAS/BIM). LAG-3 and TIM-3 were present in TILsubsets lacking PD-1 expression and showed a distinct func-tional profile. In baseline samples from 90 patients withadvanced NSCLC treated with PD-1 axis blockers, elevatedLAG-3 was significantly associated with shorter progression-free survival.

Conclusions: PD-1, LAG-3, and TIM-3 have distinct tissue/cell distribution, functional implications, and genomic corre-lates in human NSCLC. Expression of these immune inhibi-tory receptors in TILs is associated with prominent activation,but alsowith a proapoptotic T-cell phenotype. Elevated LAG-3expression is associated with insensitivity to PD-1 axis block-ade, suggesting independence of these immune evasionpathways.

1Department of Pathology, Yale University School of Medicine, New Haven,Connecticut. 2Department of Medical Oncology, Yale University, Yale CancerCenter, New Haven, Connecticut. 3Department of Immunobiology, Yale Univer-sity School of Medicine, New Haven, Connecticut. 4Clinic University of Navarra,Pamplona, Spain. 5CIBERONC, Madrid, Spain. 6Department of Genetics, YaleUniversity School of Medicine, New Haven, Connecticut. 7Department of Tho-racic Oncology, New York University, Langone Medical Center, New York, NewYork. 8Memorial Sloan Kettering Cancer Center, New York, New York. 9WeillCornell Medical College, New York, New York. 10Parker Institute for CancerImmunotherapy, San Francisco, California. 11Massachusetts General Hospital andHarvard Medical School, Boston, Massachusetts. 12Tesaro Inc., Boston,Massachusetts. 13Oncology Unit GPP, Athens School of Medicine, Athens,Greece.

Note: Supplementary data for this article are available at Clinical CancerResearch Online (http://clincancerres.aacrjournals.org/).

I. Datar and M.F. Sanmamed contributed equally in this article.

Corresponding Author: Kurt A. Schalper, Yale School of Medicine, PO Box208023, 310 Cedar Street, New Haven, CT 06520-8023. Phone: 203-988-5773;Fax: 203-737-5089; E-mail: [email protected]

Clin Cancer Res 2019;25:4663–73

doi: 10.1158/1078-0432.CCR-18-4142

�2019 American Association for Cancer Research.

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IntroductionImmunostimulatory therapies blocking the PD-1 axis pathway

have become major antitumor treatment options in diversemalignancies including non–small cell lung cancer (NSCLC;refs. 1–5). To date, single-agent treatment using mAbs targetingPD-1 receptor or its ligand PD-L1 induce lasting clinical responsesin approximately 18% of patients with advanced NSCLC. How-ever, primary resistance occurs in the majority of patients andacquired adaptation of tumors to immune pressure in patientsinitially responding to therapy has also become a clinical chal-lenge (6–9). Therefore, identification of biomarkers for patientselection and characterization of additional nonredundantactionable immunostimulatory targets are needed.

Various immune and tumor genomic metrics are associatedwith sensitivity to PD-1 axis blockers including tumor PD-L1expression,measurement of tumor-infiltrating lymphocytes (TIL)or inflammation-related mRNA expression profiles, tumor muta-tional burden, and microsatellite instability (3, 4, 10–13). Todate, however, only detection of PD-L1 protein using IHC andmismatch repair deficiency are approved by the FDA as compan-ion biomarkers for PD-1–blocking antibodies.

Additional immune coinhibitory receptors beyond PD-1, suchas LAG-3 and TIM-3, are induced after T-cell receptor (TCR)stimulation andmediate T-cell suppression/dysfunction (14–17).The potential role of these receptors in mediating tumorimmune evasion in human malignancies and their interaction/independence from PD-1 pathway remain poorly understood.

Lymphocyte-activation Gene-3 (LAG-3 or CD223) is a 498amino acid type I transmembrane protein with high structuralhomology with CD4 protein and capacity to bind MHC class IImolecules (18, 19). Alternative ligands have been proposed toexplain some of the suppressive effects of LAG-3 in CD8þ cyto-toxic cells in the absence of MHC class II, such as Galectin-3,LSECtin, and a-synuclein fibers (20–22). Recent work from ourgroup identified FGL-1 as a novel high-affinity and cell-free ligandfor LAG-3 involved in tumor immune evasion (23). Despite beingstudied in diverse anticancer clinical trials (19), the tissue distri-bution and functional role of LAG-3 in human malignancies hasnot been clearly defined.

T-cell immunoglobulin and mucin domain-3 (TIM-3) is a 281amino acid long type I transmembrane protein containing a

variable N-terminal Ig domain and a mucin stalk domain (24).An immunosuppressive effect of TIM-3 signaling on T cells wasreported to be related with the binding of Galectin-9 and CEA-CAM1 (25, 26). Additional candidate ligands have also beenshown to be able to modulate TIM-3 functions including phos-phatidyl serine (PtdSer) and high-mobility group protein B1(HMGB1; ref. 14).Clinical studies assessing the safety and anti-tumor effect of TIM-3blockers alone or in combinationwith othertherapies are currently ongoing: NCT02817633, NCT03099109,NCT03066648. The expression, tissue distribution, and associa-tion of TIM-3 with other immune-inhibitory receptors in humanlung cancer are not well understood.

Here, we used multiplexed tissue imaging of large tumorcollections and single-cell phenotypic analysis of primary cancersto evaluate the distribution and significance of PD-1, LAG-3, andTIM-3 expression in NSCLC. Our results reveal complex func-tional associations and support independent functions of thesereceptors to suppress T-cell function.

Materials and MethodsPatients, cohorts, and tissue microarrays

Formalin-fixed, paraffin-embedded (FFPE) samples from pre-viously reported retrospective collections of NSCLC not treatedwith immune checkpoint blockers and represented in tissuemicroarrays (TMA) were analyzed (27, 28). The first collectionincludes samples from 426 patients with NSCLC seen at YalePathology between 1988 and 2012 (cohort #1). The secondcohort includes samples from 304 patients with NSCLCcollected at Sotiria General Hospital and Patras UniversityGeneral Hospital (Greece) between 1991 and 2001 (cohort#2). All cases in the cohorts were reviewed by a local pathologistusing hematoxylin and eosin–stained preparations and tumorhistology variant was confirmed by morphology analysis. Tumorcores for TMA construction were obtained from case areasselected by a pathologist to represent the disease. Tumor coreselection was not based on specific tumor segments or location.Clinicopathologic information from patients in both cohortswas collected from clinical records and pathology reports.Analysis of mRNA expression and nonsynonymous mutationswas performed using the lung cancer dataset from TCGA (cohort#3, n ¼ 370). Another TMA-based cohort from Yale (cohort #4)including retrospective samples from 108 lung adenocarcinomasclinically tested for EGFR and KRAS mutations was alsostudied. Fresh immune cell/leukocyte extracts from 20 primaryresected NSCLCs were also included for mass cytometry analysis(cohort #5). To assess the value of the markers in patients treatedwith PD-1 axis blockers, we analyzed a combined retrospectivecohort from Yale, Cleveland Clinic, and Navarra Universityincluding 90 baseline/pretreatment cases treated with PD-1–blocking antibodies (nivolumab or pembrolizumab) or a PD-L1 blocking Ab (atezolizumab; cohort #6). A summary descrip-tion of all 6 cohorts/datasets included in the study is provided inSupplementary Table S1. All the studies were conducted inaccordance with recognized ethical guidelines (e.g., Declarationof Helsinki, CIOMS, Belmont Report, U.S. Common Rule) andtissue and clinical information were used after approval from theYale Human Investigation Committee protocols 9505008219,1412015109, 1608018220, and 1603017333 or local institution-al protocols, which approved the patient consent forms or waiverof consent.

Translational Relevance

Our results reveal that PD-1, LAG-3, and TIM-3 showdifferential tissue/cell distribution, functional impact, andclinical significance in NSCLCs. In addition, single-cell studiesshow that simultaneous coexpression of these immune-inhib-itory receptors is associated with prominent tumor-infiltratinglymphocyte activation, but also with acquisition of a proa-poptotic phenotype. Finally, we determine the prognosticvalue of the markers and identify a negative associationbetween elevated baseline LAG-3 and sensitivity to PD-1 axisblockade. Taken together, our results support independence ofthese immune-inhibitory pathways and expand the currentunderstanding of their interplay in cancer. This informationcould be used to guide and interpret results from ongoing andfuture clinical trials.

Datar et al.

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Multiplexed quantitative immunofluorescenceA 5-color quantitative immunofluorescence (QIF) protocol for

FFPE tissue specimens was developed for simultaneous detectionof DAPI, CD3, PD-1, LAG-3, and TIM-3 using isotype-specificantibodies and different fluorescence conjugates as describedpreviously by our group (28). To reliably measure the markers,we first validated individual assays using control preparationsfrom cell line transfectants and human tissues. As shown inSupplementary Fig. S1, PD-1, LAG-3, and TIM-3 were detectedexclusively in FFPE cell preparations from HEK293 cells trans-fected with each respective target, but not in parental cells lackingendogenous expression. The markers were then integrated into amultiplexed panel together with 40,6-diamidino-2-phenylindole(DAPI) to highlight every cell in the sample and CD3 to mapT cells (Fig. 1). For the multiplexed staining, sections were depar-affinized and subjected to antigen retrieval using EDTA buffer(Sigma-Aldrich) pH 8.0 and boiled for 20minutes at 97�C in apressure-boiling container (PT module; Lab Vision). Slides werethen incubated with dual endogenous peroxidase block (#S2003;Dako) for 10minutes at room temperature and subsequentlywitha blocking solution containing 0.3% BSA in 0.05% Tween solu-tion for 30 minutes. Primary antibodies included CD3 (rabbitpolyclonal; Dako), PD-1 (clone EH33), LAG-3 (clone 17B4), andTIM-3 (clone D5D5R). Secondary antibodies and fluorescentreagents used were anti-rabbit Envision (K4003; Dako) withfluorescein-tyramide (PerkinElmer), antimouse IgG2a antibody(Abcam) with Cy3 plus (PerkinElmer), goat anti-rabbit (Abcam)with biotinylated tyramide/Streptavidine–Alexa Fluor 750 con-jugate (PerkinElmer), anti-mouse Envision (K40001) withCy5-tyramide (PerkinElmer). Residual horseradish peroxidaseactivity between incubations with secondary antibodies was elim-inated by exposing the slides twice for 10 minutes to a solutioncontaining benzoic hydrazide (0.136mg) and hydrogen peroxide(50 mL). To determine the reproducibility of the QIF assay, wemeasured serial sections from an index TMA containing positiveand negative controls (YTMA345) at different time points. Thelinear regression coefficients of scores obtained between indepen-dent runs were high (R > 0.9, P < 0.001; Supplementary Fig. S2),supporting the consistency of the measurements.

Tissue fluorescence measurement and scoringQuantitative measurement of the fluorescent signal was per-

formed using the AQUA method that enables objective andsensitive measurement of targets within user-defined tissue com-partments (28). Briefly, theQIF score of each target in CD3þ T-cellcompartment from the whole TMA spot was calculated by divid-ing the target pixel intensities by the area of CD3 positivity. Scoreswere normalized to the exposure time and bit depth at which theimages were captured, allowing scores collected at different expo-sure times to be comparable. Markers were also measured in thetotal tissue compartment by collecting the signal score in the areadefined by DAPI staining (e.g., all cells in the sample). Forgraphical representation of the retrospective TMA collections, thescores of LAG-3 and TIM-3 were mean-normalized relative toPD-1 scores to display them in a comparable scale.

Cell preparation and cytometry by time-of-flight analysisAs described previously (29), primary resected NSCLC

tissues were finely minced and mechanically dissociated with theGentleMACS Dissociator (Miltenyi Biotec) in the presence ofRPMI1640 with 0.5% BSA and 5 mmol/L EDTA. The resulting

cell suspension was filtered using a 70-mm cell strainer (BDFalcon). Cells were centrifuged at 600 � g for 7 minutes at 4�Cand resuspended in PBS with 0.5% BSA and 0.02% NaN3. A totalof 2–4 � 106 cells from each tumor were incubated with anti-bodies against CD16/32 at 50mg/mL in a total volumeof 50mL for10 minutes at room temperature to block Fc receptors. Surfacemarker metal-conjugated antibodies' cocktail were then added,yielding 100-mL final reaction volume and stained for 30minutesat 4�C. After staining, cells were washed two times with PBS with0.5% BSA and 0.02% NaN3. Then, cells were resuspended withRPMI1640 and 10 mmol/L cisplatin (Fluidigm) in a total volumeof 400 mL for 60 seconds before quenching 1:1 with pure FBS todetermine viability. Cells were centrifuged at 600 � g for 7minutes at 4�C and washed once with PBS with 0.5% BSA and0.02% NaN3. Cells were then fixed using fixation/permeabiliza-tion buffer (eBioscience) for 30 minutes at 4�C. After two washeswith permeabilization buffer (eBioscience), cells were incubatedwith intracellular metal-conjugated antibodies cocktail in 100 mLfor 30minutes at 4�C.A summaryof the antibodies/clones used inthe mass cytometry analyses is presented in the SupplementaryTable S2. Antibodies were either purchased preconjugated fromFluidigm or purchased purified and conjugated in-house usingmass cytometry antibody conjugation kits according to the man-ufacturer's instructions. Cells were washed twice in PBSwith 0.5%BSA and 0.02%NaN3 and then stainedwith 1mL of 1:4,000 191/193Ir DNA Intercalator (Fluidigm) diluted in PBS with 1.6% PFAovernight. Cells were then washed once with PBS with 0.5% BSAand 0.02% NaN3 and then two times with double-deionizedddH2O. Mass cytometry samples were diluted in ddH2O contain-ing bead standards (Fluidigm) to approximately 106 cells/mL andthen analyzed on a CyTOF mass cytometer equilibrated withddH2O. All mass cytometry files were normalized together usingthe mass cytometry data normalization algorithm (30). Foranalysis, FCS files weremanually pregated on Ir193DNAþCD45þ

events, excluding cisplatinþ dead cells, doublets, and DNA- neg-ative debris by Cytobank. The gated CD45þ population was thenclustered on the basis of all labeled phenotypic markers usingspanning-tree progression analysis of density-normalized events(SPADE; ref. 31). Putative cell populations on the resultingSPADE trees were manually annotated on the basis of the expres-sion of key markers as shown in Supplementary Fig. S3.

Cell culture and transfectionsFor assay validation experiments, HEK293 parental cells

were transiently transfected with 1 mg of full-length cDNAcoding each target using Lipofectamine 3000 (Thermo FisherScientific) for 24 hours. Cells were used fresh for proteinextraction and immunoblotting; or fixed in 10% neutral buff-ered formalin for 8 to 12 hours and embedded in paraffin forquantification by QIF. Cell lines used in this study werepurchased from the ATCC and authentication was performedevery 3 to 6 months using the GenePrint 10 System in the YaleUniversity DNA Analysis Facility.

TCGA data analysis for mRNA expression and genomicalterations

We analyzed the NSCLC samples from The Cancer GenomeAtlas (TCGA, http://cancergenome.nih.gov/). Briefly, we down-loaded the RNA-sequencing (RNA-seq) and DNA whole-exomesequencing data from 370 NSCLC cases including 250 adenocar-cinomas and 120 squamous cell carcinomas. Using data

PD-1, LAG-3, and TIM-3 in Lung Cancer

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Figure 1.

Distribution and frequency of T-cell PD-1, TIM-3, andLAG-3 expression in NSCLC.A, Representativefluorescence microphotographs showing thesimultaneous detection of PD-1 (red), LAG-3 (white),TIM-3 (green), and CD3 (yellow) positive cells inNSCLC. B, Level of the markers measured using QIF in2 retrospective NSCLC cohorts—cohort #1 (n¼ 426)(A) and #2 (n¼ 304) (B). The markers were measuredin CD3þ T cells and showed a continuous distributionand strong association with CD3 (insets). Thefrequency of expression of each marker is indicatedwith white-colored text within the charts. R, Spearmancorrelation coefficient.

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processed through the cBioPortal interface (http://www.cbioportal.org/), DNA segments and RNA transcripts werealigned and DNA variant calling was performed using defaultTCGA pipelines. We conducted single scatterplot analysisbetween the mRNA scores of PDCD1 (PD-1), LAG-3, andHAVCR2 (TIM-3) genes. The total number of nonsynonymousmutations detected in the whole-exome sequencing data relativeto germline DNA was used as the tumor mutational burden.

Statistical analysisQIF signals between compartments were analyzed using linear

regression, correlation functions, and expressed as regression/correlation coefficients. For experiments including numerousfields of view (FOV) per case slide, we analyzed the top 10%marker scores in each preparation. Patient characteristics werecompared using the Student t test for continuous variables and x2

test for categorical variables. Survival functions were comparedusing Kaplan–Meier estimates and statistical significance wasdetermined using the log-rank test. Correlation studies wereperformed calculating linear regression coefficients and/or Spear-man rho-rank functions. Associations between the markers and

statistical significance were determined using JMP Pro. v11 andGraphPad Prism v7.0a software.

ResultsTumor tissue distribution of PD-1, LAG-3, and TIM-3 in humanNSCLCs

We standardized a QIF panel for simultaneous measurement ofthe markers DAPI, CD3, PD-1, LAG-3, and TIM-3 and studied 730retrospectively collected NSCLC samples from two independentpopulations represented in TMA format [cohort #1 fromYale (N¼426) and cohort #2 from Greece (N ¼ 304)]. All the markersshowed a predominant membranous staining pattern and weredetected in CD3þ TILs (Fig. 1A). However, PD-1 and LAG-3 werepredominantly localized in CD3þ T cells while TIM-3 was recog-nized frequently in CD3� populations. Using the visual detectionthreshold,wedetectedT-cell PD-1, LAG-3, andTIM-3 expression in65%, 33%, and 24% of NSCLCs in the first cohort; and in 45%,49%, and 26%of cases in the second collection (Fig. 1B and C). Inboth cohorts, the levels of T-cell PD-1, LAG-3, and TIM-3 proteinwere significantly correlated with each other (Spearman R ¼

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Figure 2.

Association between PD-1, LAG-3, and TIM-3 in NSCLC bymultiplex QIF and RNA-seq. A and B, Histograms showing the association between the proteinexpression levels of PD-1, LAG-3, and TIM-3 in the NCSLS cohort #1 (A) and #2 (B). C,Association between the transcript levels of HAVCR2 (TIM-3), PDCD1(PD-1), and LAG-3 genes in NSCLC cases from the TCGA database (cohort #3, n¼ 406). R, Spearman correlation coefficient.





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0.3–0.745, P < 0.001; Fig. 2A and B). The lowest correlationcoefficients were between PD-1 and TIM-3. Comparable resultswere obtained when measuring the expression in the total tissuecompartment (e.g., outside T cells) and between the levels ofPD-1 (PDCD1), LAG-3, and TIM-3 (HAVCR2) mRNA transcriptsin406 cases fromtheNSCLCdatasetsof TCGA(cohort #3, Fig. 2C).

Target expression in individual immune cell populations andfunctional impact

To determine the expression of the targets and functionalassociations in specific immune cell subpopulations, we usedmass cytometry by time-of-flight (CyTOF) to analyze freshlyisolated leukocytes obtained from a collection of 20 primary

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Single-cell multiparametric analysis of PD-1, TIM-3, and LAG-3 expression in immune cell subsets from NSCLC. CyTOF analysis of TILs from primary NSCLCsurgical specimens (cohort #5, n¼ 20). A, Bar plots depict median PD-1 (left), LAG-3 (middle), and TIM-3 (right) expression levels for each immune cellpopulation defined as indicated in Supplementary Fig. S3. The marker levels in each population were compared with CD8þ T-cell levels. MMI, Median massintensity. B, Frequency of the specific CD3þ subpopulations defined by the combination of PD1 and LAG3 (left), PD1 and TIM3 (middle), and TIM3 andLAG3 (right) expression as indicated. C, Heatmap showing relative normalized expression of activated markers in TILs PD-1�/LAG-3�/TIM-3� (black square)or TILs PD-1þ/LAG-3þ/TIM-3þ (red square) across 20 lung cancer primary tumors. D, Bar plots of indicated activation marker expression levels forTILs PD-1�/LAG-3�/TIM-3� (black) or TILs PD-1þ/LAG-3þ/TIM-3þ (red). �, P < 0.05; �� , P < 0.01; �� , P < 0.005; �� , P < 0.001.

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resected NSCLCs (cohort #4). A panel of 35 phenotypical andfunctional markers was costained (Supplementary Table S2) andSPADE was used to identify distinct immune cell populations(Supplementary Fig. S3). PD-1 was predominantly expressed oncytotoxic CD8þ T cells, CD4þ/CD25�/Foxp3� helper cells, regu-latory CD4þ/CD25þ/Foxp3þ T cells (Tregs), and CD3þ/CD56þ

NKT cells (Fig. 3A, left). Virtually, no PD-1 signalwas detected in Blymphocytes, NK cells, and myeloid cell subsets. LAG-3 expres-sion was seen in all studied T-cell groups with the highest levels inCD8þ T cells. LAG-3 was also present on NK cells, NKT cells, andgranulocytes, but it was low or absent in antigen-presenting cells(APC) and B lymphocytes (Fig. 3A, middle). TIM-3 was broadlyexpressed in adaptive and innate immune cells, with detectablelevels in all T-lymphocyte subsets, NK cells, NKT cells, anddendritic cells. Notably, the highest TIM-3 levels were seen inmacrophages/NK/NKT cells, whereas low/absent expression wasfound in granulocytes (Fig. 3A, right).

Overall, simultaneous coexpression of PD-1, LAG-3, and TIM-3was seen in 5.4%ofCD3þ TILs. PD-1 and LAG-3were coexpressedin 9.1% of cells, PD-1 and TIM-3 in 21% of cells, and LAG-3 andTIM-3 in 10.5% of TILs (Fig. 3B, green chart area). The proportionof TILs lacking all 3markers was 29.4%. Notably, 8.6%of LAG-3þ

and 16.8% of TIM-3þ TILs showed absence of PD-1 expression;and 15.8% showed LAG-3 positivity in the absence of TIM-3(Fig. 3B, red chart area).

To evaluate the impact of the markers, we analyzed the expres-sion of functional indicators in individual T-cell populations.Coexpression of PD-1, LAG-3, and TIM-3 was prominently asso-ciated with high levels of markers of T-cell activation (CD69, 4-1BB), cytotoxic/effector function [Granzyme-B (GZB)] and pro-liferation (Ki-67), but also with higher levels of the apoptotic

signal receptors (FAS or CD95) and proapoptotic proteins(BIM; Fig. 3C and D). TILs with high LAG-3, but low PD-1 andTIM-3 expression (e.g., PD-1�LAG-3þTIM3�) showed highercytotoxic potential (GZB, CD69, and CD137) than T cells withelevated TIM-3 alone (e.g., PD1�LAG3�TIM-3þ) or those expres-sing only PD-1 (e.g., PD-1þLAG3�TIM-3�; Supplementary Fig.S4A and S4B). Notably, coexpression of two or more of theimmune-inhibitory receptors was associated with higher levelsof all functional markers (Supplementary Fig. S4C).

Clinical significance and molecular associations of PD-1,LAG-3, and TIM-3 expression in NSCLC

To explore the clinical role of the markers, we studied theirassociationwithmajor clinicopathologic variables and survival inthe retrospective cohorts #1 and #2. There was a significantassociation between the levels of the markers and TILabundance; and all the markers showed a positive associationwith each other (Supplementary Tables S3 and S4). There were noconsistent associations between expression of PD-1, LAG-3, orTIM-3 andmajor clinicopathologic features including age, gender,smoking status, clinical stage, and tumor histology variant.

As shown in Fig. 4A, the level of PD-1 and TIM-3 were signif-icantly lower in tumor harboring KRAS mutations than in caseswith wild-type EGFR and KRAS. EGFR-mutated lung adenocarci-nomas showed significantly lower TIM-3 than tumors lackingmutations in both oncogenes. In the TCGA lung cancer datasets,there was a positive correlation between tumor mutational bur-den and LAG-3, but this association was not evident for the othermarkers (Fig. 4B).

To explore the survival effect of dominant expression of eachmarker, we assessed the 5-year overall survival in cases with scores

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Association of LAG-3, PD-1, TIM-3, and CD3 with major driver mutations and tumor mutational burden in NSCLC. A, Levels of PD-1, LAG-3, and TIM-3 in lungadenocarcinoma cohort #3 comprising cases wild type for EGFR and KRAS driver mutations and with oncogenic KRAS or EGFR variants. B,Association betweenthe marker mRNA levels (FPKMs) and tumor mutational burden (e.g., number of nonsynonymousmutations) in the TCGA NSCLC cohort (cohort 3,N¼ 406). � , P< 0.01; �� , P < 0.01; �� , P < 0.001; R, Spearman correlation coefficient.






above or below the top 15th percentile of the cohort. As shownin Fig. 5A–F, prominent T-cell PD-1, LAG-3, and TIM-3 weresignificantly associated with longer 5-year overall survival in thefirst cohort, but this was not evident in the second population.Similar associations with survival were seen when stratifying themarkers by quartiles (Supplementary Fig. S5).

PD-1, LAG-3, TIM-3, and sensitivity/resistance to PD-1 axisblockers in NSCLC

We then studied the association between the baseline level ofthemarkers and survival after treatmentwith PD-1 axis blockers in90 patients. Cases with prominent T-cell LAG-3 expression (top15th percentile of the cohort) showed a significantly shorterprogression-free survival (log-rank P ¼ 0.03; Fig. 6A–C). Incontrast, elevated levels of T-cell PD-1 or TIM-3 were not signif-icantly associated with survival in the cohort. Notably, cases withhigh LAG-3 and low tumor PD-L1 expression [<50% tumorproportion score (TPS)] showed a markedly lower progression-free survival than cases with low LAG-3 and high (�50% TPS)tumor PD-L1 expression (Fig. 6D).

DiscussionUsing QIF and mass cytometry, we determined the expression,

functional associations, and clinical significance of PD-1, LAG-3,and TIM-3 in human NSCLC. Specifically, we found that all threereceptors display variable expression in NSCLC, distinct immunecell distribution, and association with T-cell activation and proa-

poptotic markers. Notably, TILs with elevated LAG-3 showed themost prominent activated and proapoptotic phenotype and ele-vated T-cell LAG-3 (but not PD-1 or TIM-3) was significantlyassociated with shorter survival after PD-1 axis blockade. Takentogether, our findings support a distinct and independent role ofthese immune-inhibitory receptors in lung cancer and show thattumorswith dominant LAG-3 expression are less sensitive to PD-1axis blockers.

Detectable expression of PD-1, LAG-3, and TIM-3 was seen in55%, 41.5%, and 25.3 % of NSCLCs, respectively; and wasassociated with T-cell–inflamed tumors, but not consistentlyassociated with other clinicopathologic variables. A recentstudy detecting PD-1 and LAG-3 using single-marker IHC in139 surgically resected lung carcinomas reported PD-1 expressionin43.4%andLAG-3 in26.9%of cases (32).Here, LAG-3detectionwas associated with higher PD-1, nonsquamous tumor histology,and worse survival. Although our study showed no consistentassociation between elevated LAG-3 and specific tumor histologyor with survival in cases not receiving immunotherapy, we foundsimilar frequencies andpatterns of tumor LAG-3andPD-1proteinexpression. Theprimary source explaining thedifferences betweenthis study andourfindings is uncertain, and diversemethodologicconsiderationsmay account for this, including the cases analyzed,modality of marker testing, cut-points used for stratification, andassay-specific variables. In our study, we evaluated four differentLAG-3 antibodies using control FFPE samples including clones17B4,D2G40, EPR4392, and 11E3; and selected clone 17B4 for itshigh specificity and broader dynamic range.

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Association of PD-1, LAG-3, and TIM-3 with survival in retrospective cohorts. A–F, Association of markers with 5-year overall survival in 379 NSCLC cases fromcohort # 1 (A–C) and 252 cases from the cohort # 2 (D–F). Elevated expression of the markers was defined as signal above the 85th percentile of the cohort.

Datar et al.





The single-cell studies revealed distinct expression and func-tional impact of PD-1, LAG-3, and TIM-3 in immune cell sub-populations. Although PD-1 and LAG-3 were predominantlylocalized in NKT and CD8þ T cells, TIM-3 was commonly seeninmacrophages andNKcells. The elevated expressionof PD-1 andLAG-3 in cytotoxic T CD8þ and NKT cells is consistent with theirexpected immune regulatory function in effector cells. Notably,both targets were also highly expressed in Tregs, suggesting thatPD-1 and LAG-3 pathways can have additional and cell-specificsuppressive functions constituting complex internal systemsmediating immune tolerance. Prominent expression of TIM-3 ininnate immune cells such as monocytes, dendritic cells, and NKcells has been previously reported in nontumor tissues such asperipheral blood (33–35), but this is the first time to our knowl-edge it is reported in lung cancer.

KRAS and EGFR are the most commonly mutated driver onco-genes in lung adenocarcinoma. EGFR-mutant tumors displaycommonly lower TILs, PD-L1 expression, and tumor mutationalburden than EGFR-wild-type tumors (36–38). Consistent withthis, patients with EGFR-mutated carcinomas derive less clinicalbenefit from PD-1 axis blockade (39, 40). In our study, we foundlower levels of PD-1, LAG-3, and TIM-3 in KRAS- and EGFR-mutant tumors than in cases lackingmutations in both genes. Thissupports lower overall immune activation and regulation medi-ated by PD-1, LAG-3, and TIM-3 in these malignancies andsuggests limited therapeutic potential of targeting these receptors.However, a fraction of NSCLCs with KRAS driver mutations mayalso harbor other genomic variants which could alter the tumor–immune microenvironment (41).

Despite being traditionally considered as exhaustion T-cellmarkers (42, 43), PD-1, LAG-3, and TIM-3 are expressed pref-erentially in activated TILs. This is consistent with a modelwhere coinhibitory receptors are upregulated upon T-cell stim-

ulation in order to limit exaggerated responses and potentialtissue damage. In this regard, it has been reported that theexpression of these three markers is associated and could beused to identify antigen-experienced T cells in patients withcancer (44). However, previous studies have also shown thatprominent T-cell activation is associated with a dysfunctionalphenotype characterized by engagement of apoptotic pro-grams (45). Consistent with this notion, expression of PD-1,LAG-3, and TIM-3 was associated with elevated levels of keyproapoptotic targets in lung carcinomas. Additional studies areongoing to refine the phenotype of cells expressing eachimmune-inhibitory receptor combination and determine howto use this information therapeutically. Studies simultaneouslymeasuring key ligand(s) for PD-1, LAG-3, and TIM-3 are alsowarranted because functional consequences probably requirecoexpression of the ligands and receptors in close proximitywithin the tumor microenvironment.

An intriguing finding of our study is the negative associationbetween LAG-3 overexpression and survival benefit in patientswith NSCLC treated with PD-1 axis blockers. These suggest thattumors in which immune evasion is mediated predominantly byLAG-3 are less sensitive to PD-1 axis blockade and opens thepossibility of eventually using LAG-3 for selection of patients forimmunotherapy. Early results from LAG-3 inhibitors in theCA224-020 clinical trial (NCT01968109) show promising resultsin patients with advanced melanoma with resistance to PD-1blockers. Here, LAG-3 positivity by IHC in pretreatment tumorsamples is associated with higher response rate supporting apredictive role of LAG-3 expression. In recent work, we also foundLAG-3 upregulation by protein andmRNAmeasurements in TILsfrom 5 of 8 patients with NSCLC with acquired resistance toimmune checkpoint blockers, suggesting a possible role of LAG-3in this setting (38).

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Association of PD-1, LAG-3, andTIM-3 expression with survival inpatients with NSCLC treated withPD-1 axis blockers.A–C, Chartsshowing the Kaplan–Meier survivalestimates of patients treated withPD-1 axis blockers (cohort #6,n¼ 90). The scores of T-cell PD-1(A), LAG-3 (B), and TIM-3 (C) weremeasured using multiplex QIF inpretreatment samples and stratifiedusing top 15th percentile as cut-point. The differences betweengroups were compared using thelog-rank test. D, Kaplan–Meiersurvival estimates of patientstreated with PD-1 axis blockersstratified by LAG-3 expression(high, above top 15th; low, below orequal to top 15th) and PD-L1expression (high, above 50% tumorproportion score; low, below orequal to 50% tumor proportionscore).






Our study has limitations. The evaluation of three retrospectivecohorts (cohorts #1, #2, and #4) was performed using TMAs thatanalyze relatively small sample fragments andmayover- or under-represent the marker measurements. Although not the standardmethod to measure proteins in tumor tissues clinically, diversereports from our group and others using TMAs have shownconsistent results and significant association with clinical, path-ologic variables and outcome (46). In addition, (i) each case wasrepresented two or three times in the TMA to account for possiblemarker variations across different tumor areas; (ii) the dataobtained in the TMA cohorts were consistent with results in theTCGA collection (cohort #3) that was conducted using wholetissue sections andmRNAanalysis; and (iii) themarker scores anddistribution obtained using TMAs were similar to those in wholetissue sections used for the cohort #6 analysis. Finally, the col-lection of patients treated with PD-1 axis blockers (cohort #6)included cases treated with different PD-1 axis blockers andsamples collected at different time points before treatment initi-ation and withmultiple previous lines of treatment. These factorsare common limitations of retrospective cohort studies and theirpossible impact in the results are uncertain.

Overall, we have characterized the expression and significanceof PD-1, LAG-3, and TIM-3 in a sizable number of NSCLC casesfrom six independent tumor collections. Our results demonstratedissimilar and nonredundant expression of these targets in TILsfrom primary lung tumors and provide valuable insights aboutT-cell activation and dysfunction in this setting.

Disclosure of Potential Conflicts of InterestB.S. Henick holds ownership interest (including patents) in AbbVie and is a

consultant/advisory board member for Boehringer Ingelheim. V. Velcheti is aconsultant/advisory boardmember for Bristol-Myers Squibb, Genentech, Astra-Zeneca, Nektar Therapeutics, Reddy Labs, Celgene, Merck, and FoundationMedicine. M.D. Hellmann reports receiving other commercial research supportfrom Bristol-Myers Squibb; holds ownership interest (including patents) inShattuck Labs; is listed as an inventor on a patent that has been filed byMSK related to the use of tumor mutation burden to predict response toimmunotherapy, which has received licensing fees from PGDx; is a consul-tant/advisory board member for Merck, AstraZeneca, Bristol-Myers Squibb,Genentech/Roche, Janssen, Nektar, Syndax, Mirati, and Shattuck Labs; andreports receiving other remuneration from Bristol-Myers Squibb and AstraZe-neca. J.F. Gainor reports receiving other commercial research support fromNovartis, Genentech/Roche, and Ariad/Takeda, and is a consultant/advisoryboard member for Merck, Bristol-Myers Squibb, Genentech/Roche, Incyte,Loxo, Pfizer, Takeda, Amgen, Agios, Regeneron, Jounce, and Oncorus. K. Politireports receiving commercial research grants from AstraZeneca, Roche, Sym-phogen, and Kolltan; holds ownership interest (including patents) in Molecu-larMD/MSDKCC; and is a consultant/advisory board member for AstraZeneca,Tocagen, Maverick Therapeutics, Dynamo Therapeutics, and NCCN. S. Gettin-ger is a consultant/advisory boardmember for Bristol-Myers Squibb andNektar.D.L. Rimm reports receiving commercial research grants from AstraZeneca,Cepheid, NextCure, Lilly, Ultivue, Perkin Elmer, Nanostring, and Navigate/Novartis, and is a consultant/advisory board member for AstraZeneca, Amgen,Daiichi Sankyo, GSK, Bristol-Myers Squibb, Konica Minolta, Biocept, CellSignaling Technology, Nanostring, Cepheid, and Ventana. R.S. Herbst is anemployee of Junshi Pharmaceuticals; reports receiving commercial researchgrants fromAstraZeneca, Eli Lilly andCompany, andMerck; and is a consultant/advisory board member for AbbVie, Pharmaceuticals, ARMO Biosciences,AstraZeneca, Biodesix, Bristol-Myers Squibb, Eli Lilly and Company, EMDSerrano, Genentech/Roche, Genmab, Heat Biologics, Halozyme, Loxo Oncol-

ogy, Infinity Pharmaceuticals,Merck andCompany,Nektar, Neon Therapeutics,NextCure, Novartis, Sanofi, Seattle Genetics, Shire PLC, Spectrum Pharmaceu-ticals, Symphogen, Tocagen, and Tesaro. I. Melero reports receiving commercialresearch grants from Bristol-Myers Squibb, Roche, Alligator, and Biocotech;reports receiving speakers bureau honoraria from MSD; holds ownershipinterest (including patents) in Tusk; and is a consultant/advisory boardmemberfor Bristol-Myers Squibb, Roche, Bayer, Molecular Partners, F-STAR, MerckSerono, MSD, Alligator, Genmab, and Biocotech. L. Chen is an employee ofJunshi Bioscience; reports receiving commercial research grants from NextCureand Tayu Biotech; holds ownership interest (including patents) in NextCure;and is a consultant/advisory boardmember forNextCure, Zai Lab,GenomiCare,and Vcanbio. K.A. Schalper reports receiving commercial research grants fromNavigate Biopharma, Vasculox, Tesaro, Moderna, Takeda, Surface Oncology,Pierre Fabre,Merck, andBristol-Myser Squibb; reports receiving speakers bureauhonoraria from Merck, Takeda, and Fluidigm; and is a consultant/advisoryboard member for Celgene, Moderna, Shattuck Labs, AstraZeneca, Pierre Fabre,and AbbVie.

Authors' ContributionsConception and design: I. Datar, M.F. Sanmamed, M.D. Lozano, J.L. Perez-Gracia, K. McEachern, D. Jenkins, K. Syrigos, R.S. Herbst, L. Chen, K.A. SchalperDevelopment of methodology: I. Datar, M.F. Sanmamed, J. Wang, B.S. Henick,N. Mani, M.D. Lozano, J.L. Perez-Gracia, V. Velcheti, R.S. Herbst, K.A. SchalperAcquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): M.F. Sanmamed, T. Badri, M. Toki, J.L. Perez-Gracia, V. Velcheti, M.D. Hellmann, J.F. Gainor, K. Syrigos, K. Politi,D.L. Rimm, R.S. HerbstAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): I. Datar, M.F. Sanmamed, B.S. Henick, J. Choi,W. Dong, M.D. Lozano, V. Velcheti, J.F. Gainor, K. McEachern, S. Gettinger,R.S. Herbst, I. Melero, L. Chen, K.A. SchalperWriting, review, and/or revision of the manuscript: I. Datar, M.F. Sanmamed,B.S. Henick, M. Toki, M.D. Lozano, J.L. Perez-Gracia, V. Velcheti,M.D. Hellmann, J.F. Gainor, K. McEachern, D. Jenkins, K. Syrigos,S. Gettinger, D.L. Rimm, R.S. Herbst, I. Melero, L. Chen, K.A. SchalperAdministrative, technical, or material support (i.e., reporting or organizingdata, constructing databases):M.F. Sanmamed, B.S. Henick, T. Badri, N. Mani,M. Toki, K.A. SchalperStudy supervision: M.F. Sanmamed, K. Syrigos, R.S. Herbst, L. Chen,K.A. SchalperOther (pathology analysis): L.D. Mejías

AcknowledgmentsThe authors thank Dr. Paula Kavathas (Yale University) for providing access

to key resources and Lori Charette from Yale Pathology Tissue Services forexcellent support in histology and TMA sample preparation. The authorsacknowledge Lung Cancer Research Foundation (LCRF), Yale SPORE in LungCancer (P50CA196530), Department of Defense-Lung Cancer Research Pro-gram Career Development Award (W81XWH-16-1-0160), sponsored researchgrant by Tesaro Inc., Yale Cancer Center Support Grant (P30CA016359), a giftby the Grunley Family Fund, and a Stand Up To Cancer – American CancerSociety Lung Cancer Dream Team Translational Research Grant (SU2C-AACR-DT1715 and SU2C-AACR-DT22-17). Stand Up To Cancer is a program of theEntertainment Industry Foundation. Research grants are administered by theAmerican Association for Cancer Research, the scientific partner of SU2C. M.F.Sanmamed was supported by a Miguel Servet contract from Instituto de SaludCarlos III, Fondo de Investigaci�on Sanitaria (Spain).

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

Received December 18, 2018; revised March 12, 2019; accepted April 29,2019; published first May 3, 2019.

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2019;25:4663-4673. Published OnlineFirst May 3, 2019.Clin Cancer Res Ila Datar, Miguel F. Sanmamed, Jun Wang, et al. Multiparametric Single-Cell Analysis

Small Cell Lung Cancer Using Spatially Resolved and−Human NonExpression Analysis and Significance of PD-1, LAG-3, and TIM-3 in

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