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CLINICAL CANCER RESEARCH | TRANSLATIONAL CANCER MECHANISMS AND THERAPY

Compartmental Analysis of T-cell Clonal Dynamics as aFunction of Pathologic Response to Neoadjuvant PD-1Blockade in Resectable Non–Small Cell Lung Cancer A C

Jiajia Zhang1,2, Zhicheng Ji3, Justina X. Caushi1,2, Margueritta El Asmar1,2, Valsamo Anagnostou1,2,Tricia R. Cottrell1,2,4, Hok Yee Chan1,2, Prerna Suri1,2, Haidan Guo1,2, Taha Merghoub5, Jamie E. Chaft5,Joshua E. Reuss1,2, Ada J. Tam1,2, Richard L. Blosser1,2, Mohsen Abu-Akeel5, John-William Sidhom1,2,Ni Zhao3, Jinny S. Ha2,6, David R. Jones7, Kristen A. Marrone1,2, Jarushka Naidoo1,2, Edward Gabrielson1,2,Janis M. Taube1,2,4, Victor E. Velculescu1,2, Julie R. Brahmer1,2, Franck Housseau1,2, Matthew D. Hellmann5,Patrick M. Forde1,2, Drew M. Pardoll1,2, Hongkai Ji3, and Kellie N. Smith1,2

ABSTRACT◥

Purpose: Neoadjuvant PD-1 blockade is a promising treatmentfor resectable non–small cell lung cancer (NSCLC), yet immuno-logicmechanisms contributing to tumor regression and biomarkersof response are unknown.Using paired tumor/blood samples fromaphase II clinical trial (NCT02259621), we explored whether theperipheral T-cell clonotypic dynamics can serve as a biomarker forresponse to neoadjuvant PD-1 blockade.

Experimental Design: T-cell receptor (TCR) sequencing wasperformed on serial peripheral blood, tumor, and normal lungsamples from resectable NSCLC patients treated with neoadjuvantPD-1 blockade. We explored the temporal dynamics of the T-cellrepertoire in theperipheral and tumoral compartments in response toneoadjuvant PD-1blockadebyusing theTCRas amolecular barcode.

Results: Higher intratumoral TCR clonality was associatedwith reduced percent residual tumor at the time of surgery, and the

TCR repertoire of tumors with major pathologic response (MPR;<10% residual tumor after neoadjuvant therapy) had a higherclonality and greater sharing of tumor-infiltrating clonotypes withthe peripheral blood relative to tumors without MPR. Additionally,the posttreatment tumor bed of patients withMPRwas enrichedwithT-cell clones that had peripherally expanded between weeks 2 and 4after anti–PD-1 initiation and the intratumoral space occupied bythese clonotypes was inversely correlated with percent residualtumor.

Conclusions: Our study suggests that exchange of T-cell clonesbetween tumor and blood represents a key correlate of pathologicresponse to neoadjuvant immunotherapy and shows that the periph-ery may be a previously underappreciated originating compartmentfor effective antitumor immunity.

See related commentary by Henick, p. 1205

IntroductionPD-1/PD-L1 axis blockade enhances antitumor immunity, induces

sustained tumor regression, and extends overall survival in many

advanced cancers (1). More recently, neoadjuvant PD-1/PD-L1 path-way blockade in early stage lung cancer has shown clinical efficacy(2, 3) while inducing peripheral expansion of mutation-associatedneoantigen-specific T-cell clones (3). Neoadjuvant phase III clinicaltrials incorporating PD-1 blockade are now active across multiplesolid tumors (3–6).

T cells are key determinants of immune response to checkpointblockade. Blockade of PD-1 signaling with anti–PD-1/PD-L1 anti-bodies reinvigorates preexisting tumor-specific T-cell clones (7). Inaddition to PD-L1 expression (8), other immune correlates of clinicalresponse to PD-1 blockade include CD8þ T-cell infiltration (9), thepresence of PD-1þCD8þ T cells at the invasive tumor margin (9, 10),high densities of CD45ROþgranzymeþ T cells (11), IFNg-associatedgene expression (12), the proximity of PD1þ to PDL1þ cells (13), andCD8/Ki-67 coexpression (9). Peripheral expansion of intratumoralclonotypes (14) and proliferation of peripheral Ki-67þ PD-1þCD8þTcells (15) have been linked with clinical benefit from PD-1 blockadein advanced NSCLC using pretreatment tumor specimens, butconnecting these changes with the intratumoral immune responseafter treatment has not been done. Herein we report the coordinateddynamics of the peripheral and tumor-infiltrating T-cell repertoirefollowing neoadjuvant anti–PD-1 treatment in resectable NSCLC.We analyzed specimens collected during a clinical trial evaluatingthe safety and feasibility of neoadjuvant PD-1 blockade in resectableNSCLC (NCT02259621). The neoadjuvant setting, whereby PD-1blockade is given before surgical resections, was introduced basedon the hypothesis that the “in-place” tumor at the time of

1The Bloomberg-Kimmel Institute for Cancer Immunotherapy, Johns HopkinsUniversity School of Medicine, Baltimore, Maryland. 2The Sidney KimmelComprehensive Cancer Center, Johns Hopkins University School of Medicine,Baltimore, Maryland. 3Department of Biostatistics, Johns Hopkins BloombergSchool of Public Health, JohnsHopkinsUniversity, Baltimore, Maryland. 4Depart-ment of Pathology, Johns Hopkins University School of Medicine, Baltimore,Maryland. 5Thoracic Oncology Service, Department of Medicine, Memorial SloanKettering Cancer Center andWeill Cornell Medical Center, New York, New York.6Division of Thoracic Surgery, Department of Surgery, Johns Hopkins UniversitySchool of Medicine, Baltimore, Maryland. 7Thoracic Service, Department ofSurgery, Memorial Sloan Kettering Cancer Center and Weill Cornell MedicalCenter, New York, New York.

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

J. Zhang, Z. Ji, J.X. Caushi, and M. El Asmar contributed equally to this article.

H. Ji and K.N. Smith contributed equally to this article.

Corresponding Author: Kellie N. Smith, Johns Hopkins University School ofMedicine, 1650 Orleans Street, Room 4M51, Baltimore, MD 21287. Phone: 410-502-7523; Fax: 410-614-0549; E-mail: [email protected]

Clin Cancer Res 2020;26:1327–37

doi: 10.1158/1078-0432.CCR-19-2931

�2019 American Association for Cancer Research.

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immunotherapeutic intervention could serve as a large antigensource to drive enhanced systemic antitumor immunity (3). Theneoadjuvant format also provides a unique opportunity to monitorthe TCR repertoire across time (in serial peripheral blood draws)and space (across different biological compartments) according topathologic response.

Because the T-cell receptor (TCR) confers unique antigen specific-ity, we use TCRVbCDR3 sequencing (TCR-seq) to track intratumoralclonotypes (ITCs) over time and across biological compartments toshow that treatment-induced peripheral TCR repertoire remodelingcorrelates with increased tumor infiltration of T cells and majorpathologic response (MPR). Specifically, peripheral T-cell clonotypicexpansion between weeks 2 and 4 after neoadjuvant anti–PD-1treatment initiation correlated with greater intratumoral clonotypeaccumulation for patients with MPR. These results indicate that theperipheral blood TCR repertoire is an important compartment forrejuvenating antitumor immunity.

Materials and MethodsStudy design

The biospecimens evaluated in this study were obtained frompatients enrolled to a phase II study evaluating the safety and feasibilityof preoperative administration of nivolumab in patients with high-riskresectable NSCLC, along with a comprehensive exploratory charac-terization of the tumor immune milieu and circulating immune cellsand soluble factors in these patients (NCT02259621). Specifically, 21adults with untreated, surgically resectable (stage I, II, or IIIA) NSCLCwere enrolled. Two preoperative doses of nivolumab (at a dose of 3mgper kilogram of body weight) was administered intravenously every2 weeks, with surgery planned approximately 4 weeks after the firstdose (3). Longitudinal peripheral blood samples (pre-, posttreatment,and follow-ups), pre- and posttreatment tumor samples, posttreat-ment lymph nodes, and normal lung tissues were collected (Fig. 1A;Supplementary Table S2). Normal lung tissues were sampled 10 to15 cm from tumormargin of surgically resected specimens. Pathologicresponse and tumor mutational burden for each patient are shown inSupplementary Table S2. This study was approved by the InstitutionalReview Board (IRB) of the Johns Hopkins University and MemorialSloan Kettering Cancer Center, and conformed to the Declaration ofHelsinki and Good Clinical Practice guidelines. Informed consent wasobtained from all patients.

TCR sequencing and assessment of the TCR repertoireDNA was extracted from posttreatment tumor tissue, normal lung

tissue, lymph nodes, and longitudinal pre- and posttreatment periph-eral blood using aQiagenDNAbloodmini kit, DNAFFPE kit, or DNAblood kit, respectively (Qiagen). TCR V b CDR3 sequencing wasperformed using the survey (tissues) or deep (PBMC) resolutionImmunoSEQ platforms (ref. 16; Adaptive Biotechnologies). TCRrepertoire diversity was assessed by productive clonality, which is ameasure of species diversity (17). To normalize between samples thatcontain different numbers of total CDR3 TCRb sequencing reads,entropy was divided by log2 of the number of unique productivesequences. Nonproductive TCR CDR3 sequences (premature stop orframeshift), sequences with amino acid length less than 5, andsequences not starting with “C” or ending with “F/W” were excludedfrom the final analyses.

Fluorescence-activated cell sorting (FACS) for PD-1–positiveT cells in PBMCs

Treatment-induced dynamics of exhausted T cells were assessed bytracking clones with upregulation of PD-1. PBMCs obtained atbaseline, immediately prior to the first anti–PD-1 infusion, werewashed and incubated with BV786-conjugated anti-CD8 (RPA-T8),BV605-conjugated anti-CD3 (SK7), BV510-conjugated anti-CD4(SK3), and PE-Cy7-conjugated anti–PD-1 (EH12.1) for 30 minutesat 4C. Cells were washed, resuspended in FACS Buffer, and live CD3þ

T cells were sorted into four populations: CD4þ/PD-1�, CD4þ/PD-1þ,CD8þ/PD-1�, and CD8þ/PD-1þ using the FACSAria Fusion SORPcell sorter (BD). gDNA extractions were performed on sorted cells andsamples were subsequently sent for TCR sequencing as describedabove.

Identification of differentially expanded/contracted clones inPBMCs

Bioinformatic and biostatistical analysis of differentially expanded/contracted clones in PBMC after each dosing of anti–PD-1 mono-therapy was performed using Fisher exact test with multiple testingcorrection by Benjamini–Hochberg procedure, which controls falsediscovery rate (FDR < 0.05; ref. 18). Differential clonotypes werefurther analyzed for tissue and longitudinal PBMC representation inMPRs and non-MPRs.

Statistical analysisStatistical analysis was performed using R software. The Mann–

Whitney U test was used for comparison of two-group data. Foranalysis of >2 group data, Kruskal–Wallis H test was used. Spearmanrho was used to measure the correlation between two continuousvariables. Data were expressed as mean � SEM unless otherwiseindicated, and P < 0.05 was considered significant. ns: P > 0.05;�, P � 0.05; ��, P � 0.01; ��, P � 0.001; ��, P � 0.0001.

ResultsIntratumoral TCR repertoire is associated with pathologicresponse to neoadjuvant anti–PD-1

We previously reported the feasibility, efficacy, and safety ofneoadjuvant PD-1 blockade in treatment-na€�ve, surgically resectable(stage I, II, or IIIA) NSCLC (3). Briefly, 21 patients were treated withtwo preoperative doses of anti–PD-1 with minimal toxicity and nodelays to surgery. Among the 20 patients who underwent surgicalresection, 9 had �10% residual viable tumor upon histopathologicexamination of the surgically resected tumor (Supplementary

Translational Relevance

Neoadjuvant PD-1 blockade has emerged as a promising treat-ment for resectable NSCLC and is being tested in at least 10 cancertypes. It will be critical to investigate mechanisms of action andidentify novel biomarkers for robust antitumor immune responses.Here, we usedmatched tumor, normal lung tissue, and longitudinalperipheral blood samples to examine the quantitative and quali-tative changes in the T-cell repertoire in NSCLC patients receivingneoadjuvant anti–PD-1. Our results add to the growing body ofevidence that PD-1 blockade can boost antitumor immuneresponses by reinvigorating peripheral T cells to enter the tumor.Our results indicate that the periphery may be a previouslyunderappreciated compartment for antitumor T cells that couldbe exploited in biomarker approaches for monitoring the responseto immunotherapy.

Zhang et al.

Clin Cancer Res; 26(6) March 15, 2020 CLINICAL CANCER RESEARCH1328




Table S1). An overview of the trial design and biospecimen collection isshown in Fig. 1A and Supplementary Table S2.

Because T-cell clonality in the tumor has been associated withclinical outcome in metastatic cancers (9), we first assessed whetherclonality of the intratumoral TCR repertoire following neoadjuvantanti–PD-1 may reflect an antitumor immune response. TCR-seq onposttreatment (resection) tumor bed was performed to determine theclonality of the intratumoral repertoire. A clonality value of 0 repre-sents the most diverse repertoire (every T-cell in a sample contains a

unique TCR), whereas a value of 1 represents a monoclonal T-cellpopulation. Tumor mutational burden (TMB) was also evaluated as apotential correlate of immunologic response. The methods and resultsof whole-exome sequencing and TMB have been reported previous-ly (3). TMB positively correlated with intratumoral clonality (Spear-man rank correlation, R ¼ 0.7, P ¼ 0.025; Fig. 1B), suggestingexpansion of a small subset of clonotypes in high TMB tumors. Aninverse associationwas observed between intratumoral TCR repertoireclonality and percent residual tumor at the time of surgery (Spearman

Figure 1.

Clonality of the TCR repertoire and association with the antitumor response. A, Flow chart of the phase II clinical trial and biospecimen collection, along withcorrelative studies performed at each time point. B, Correlation between productive clonality in the tumor bed at the time of resection (after anti–PD-1) with thenumber of nonsynonymous sequence alterations (Spearman rho, 0.70; P ¼ 0.025). Each patient is represented by a black dot (n ¼ 10). The blue line indicates thelinear regression line, and the gray area indicates the upper and lower boundaries of the 95% confidence interval. C, Correlation between productive clonality in theposttreatment tumor bed and the percent residual tumor (n¼ 10, Spearman rho,�0.65; P¼0.041). The blue line indicates the linear regression line, and the gray areaindicates the upper and lower boundaries of the 95% confidence interval. Productive clonality: Clonality as determined by using the productive amino acid (AA)sequence of the CDR3.D, Productive clonality of the TCR repertoire in the posttreatment tumor bed and normal lung for patients with MPRs (blue) and without MPR(non-MPR; red).E,Occupied clonal space (the total frequency amongall intratumoral T cells) of ITCs according to their percent rank (top 1% ranked ITCs vs. top 1%–2%ranked ITCs vs. top 2%–5% ranked ITCs vs. >5% ranked ITCs) in the posttreatment tumor bed of each patient. F, Comparison of the clonal space occupied by ITCssegregated by frequency ranks between MPRs (n ¼ 9) and non-MPRs (n ¼ 5).

T-cell Dynamics during Neoadjuvant Anti–PD-1 in NSCLC

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Figure 2.

Dynamics of ITCs across tissue compartments and in longitudinal peripheral blood. A, Proportion of ITCs shared between pretreatment blood and normallung, comparing non-top 1% ITCs and top 1% ITCs (n ¼ 14). B, Top 1% ITCs shared between pretreatment blood and resected normal lung, comparing MPRs (blue)and non-MPRs (red; n¼ 14). C, Proportion of top 1% ITCs by their shared compartment (pretreatment bloodþ resected normal lung, pretreatment blood, resectednormal lung, and tumor resident only). (Continued on the following page.)

Zhang et al.





rank correlation, R ¼ �0.65, P ¼ 0.041; Fig. 1C). No correlation wasobserved between the total number of reads (i.e., total number ofsequenced cells) used for TCR-seq and percent residual tumor orintratumoral clonality (Supplementary Figs. S1 and S2), indicating thatdifferences in sample yield or T-cell number did not bias our analysis.These observations support the hypothesis that high TMB increasesthe likelihood that one or severalmutations can drive a clonally skewedintratumoral T-cell repertoire leading to tumor pathologic regression.Posttreatment tumor, but not normal lung tissue, from patients withMPR had a significantly higher T-cell clonality relative to patients withnon-MPR (Mann–Whitney U test, P ¼ 0.0085; Fig. 1D). Conversely,patients withMPR had a trend toward lower clonality in the peripheralblood compared with non-MPRs at each longitudinal time point,although this was not statistically significant (Mann–Whitney U test,all P > 0.05; Supplementary Fig. S3). These findings of increasedclonality only inside the tumor suggest that these changes may bedirectly related to tumor recognition, with the caveat that antigen-specific recognition is not assessable by TCR-seq alone.

We then tested if themost abundant ITCs, rather than all ITCs, werespecifically contributing to the difference in T-cell repertoire betweenMPRs and non-MPRs. ITCs were ranked according to their frequencyas the top 1%, top 1% to 2%, 2% to 5%, and >5% most frequentclonotypes in the resected tumor bed. T-cell clonal space wasdefined and calculated as the summed frequency of clones in eachof the four respective groups relative to the total T-cell repertoire.There was no difference for clonotype richness, defined as the totalnumber of unique clonotypes, among the different ranges betweenMPRs and non-MPRs. However, consistent with the clonality calcula-tions described above, the top 1% most abundant ITCs occupied asignificantly greater clonal space in MPRs compared with non-MPRs(Mann–Whitney U test, median: 31.6% vs. 18.8%, P ¼ 0.011; Fig. 1Eand F), suggesting the top frequency-ranked ITCs may drive theantitumor response. Of note, MPR patient MD-01-010 with relativelylow clonal space for top 1% ITCs had 100% PD-L1 positivity onpretreatment tumor IHC staining. Of the 788 top 1% ITCs from 16patients with available tumor TCR data, only 1 clonotype was detectedto be shared across patients (CDR3: CASSLGQAYEQYF, sharedbetween patient NY016-007 and patient NY016-009, both werenon-MPR), suggesting that the antitumor TCR repertoire was uniqueto each patient in our cohort.

Top 1% most abundant ITCs have the highest compartmentaldynamics during PD-1 blockade

Using the TCR Vb CDR3 as a biological barcode, we next assessedthe cross-compartment (normal lung and pretreatment blood) andtemporal (before-treatment, on-treatment, and posttreatment blood)dynamics of ITCs, identified as T-cell clonotypes that were detected inthe resected tumor bed, and its association with pathologic response.

The top 1% most frequent ITCs had a significantly higher proportionshared between the pretreatment peripheral blood and resected nor-mal lung as compared with less highly represented ITCs—i.e., non-top1% frequency-ranked clonotypes (Mann–Whitney U test, median:61.6% vs. 28.8%, P ¼ 1.1e�5; 81.4% vs. 24.5%, P ¼ 1.4e�5,respectively, Fig. 2A). Notably, MPRs had a higher proportion of top1% most frequent ITCs detected in pretreatment blood (Mann–Whitney U test, median: 85.7% vs. 55.6%, P ¼ 0.045, Fig. 2B) andnormal lung (Mann–Whitney U test, median, 94.3% vs. 70.6%, P ¼0.023, Fig. 2B) as compared with non-MPRs. No significant differ-ences were found between MPRs and non-MPRs for non-top 1%frequency-ranked ITCs (all P > 0.1; Supplementary Fig. S3). The highproportion of ITCs mobilizing across blood and normal lung, and inparticular for top 1% frequency-ranked ITCs among MPR patients,suggests an active trafficking of antitumor T cells between the tumorand other biological compartments.

Top 1% ITCs were then categorized into four mutually exclusivesubsets: ITCs shared in the pretreatment blood and the resectednormal lung; ITCs found only in the pretreatment blood; ITCs foundonly in the resected normal lung; and tumor-resident ITCs (not foundin the resected normal lung or the pretreatment blood). Although thetotal number of top 1% ITCs was comparable inMPRs and non-MPRs(Supplementary Fig. S5), MPRs had a greater proportion of top 1%ITCs shared with both pretreatment blood and the resected normallung compartment (Mann–Whitney U test, median, 81.0% vs. 50.7%,P ¼ 0.053, Fig. 2C; Supplementary Fig. S6). In contrast, a greaterproportion of the top 1% tumor-resident ITCs was observed in non-MPRs as comparedwithMPRs (Mann–WhitneyU test,median, 21.4%vs. 3.6%, P ¼ 0.013, Fig. 2C; Supplementary Fig. S7), suggesting thatmore migratory T-cell clones correlated with the antitumor response.Supporting this notion, total ITCs shared with both the pretreatmentblood and the resected normal lung occupied a higher clonal space inMPRs as compared with non-MPRs (P ¼ 0.011), whereas non-MPRshad a greater clonal space occupied by tumor-resident ITCs (P ¼0.048, Fig. 2D). It is conceivable that the normal lung TCR repertoirecould be a reflection of the increased vascularization in healthy lungrather than true tissue-resident T cells; however, the normal lung hadsignificantly fewer shared clones with the peripheral blood comparedwith the level of sharing between blood samples obtained fromdifferent time points (median 18% vs. 53%, Wilcoxon: P ¼ 1.5e�07),thereby demonstrating the presence of aT-cell repertoire specific to thenormal lung. No difference was found in the clonal space of ITCsshared with only the pretreatment blood or the resected normal lungbetweenMPRs andnon-MPRs (allP> 0.1). These observations suggestthat the difference of the top clonal space occupied by the top 1% ITCsbetween MPRs and non-MPRs could be driven by ITCs traffickingthrough the blood and normal lung, which could mark a consort of Tcells associated with pathologic response.

(Continued.) D, Clonal space of top 1% ITCs by shared compartment between MPRs and non-MPRs (n¼ 14). The proportion of top 1% ITCs that are shared with thepretreatment peripheral blood and resected normal lung is higher in MPRs vs. non-MPRs. However, an inverse correlation was observed for top 1% frequency-rankedITCs that were only found in the tumor bed. E, Temporal dynamics of the ITCs in the longitudinal blood (n¼ 14). The percent change of top 1% ITCs shared with theperipheral repertoire over timewas calculated as comparedwith pretreatment blood. Data show themean� standard error for all patients (left) andbyMPRsvs. non-MPRs (right) for top 1% ITCs (red) andnon-top 1% ITCs (blue).F,Thepattern anddegree of peripheral remodeling atweeks 2 and4 following treatment initiation for allpatients. The fold change of each clonotypewas calculated, and themeans of the fold changewere plotted on a logarithmic scale (log10), stratified by the abundanceranks in the posttreatment tumor bed (n¼ 14). The left and right plots show the dynamic magnitude in clones that underwent peripheral expansion and contraction,respectively. � , P � 0.05; �� , P � 0.01; �� , P � 0.001; �� , P � 0.0001. G, The dynamic peripheral reshaping of individual TCR Vb clonotypes for a representativepatient (MD043-003, 5% residual tumor) during treatment and in long-term follow-up is shown. Each point on the scatter plots represents a single clonotype withnormalized log10 clone frequency graphed at pairwise time points. The size of the dot represents the frequency in the tumor bed and clones are designated as top 1%ITCs (red), non-top 1% ITCs (blue), or PBMC only (gray). Clones that underwent contraction are found below the x¼ y diagonal, whereas those expanded are foundabove the diagonal. To account for clones that were only present in one sample, the frequency was recalculated by adding a pseudocount of 20 to all clonotypecounts.






Peripheral “TCR repertoire remodeling” (i.e., fluctuations in thefrequency and composition of T-cell clonotypes within the repertoire)has been demonstrated in metastatic melanoma patients treated withanti-CTLA4 (19). In our study here, we characterized the repertoireremodeling in response to PD-1 blockade by evaluating the temporaldynamics of TCR repertoire in blood before, during, and after neoad-juvant treatment and linking these alterations with their tumor-infiltrating status. Between treatment initiation and surgery, theproportion of top 1% ITCs shared with the peripheral TCR repertoiresignificantly increased at weeks 2 and 4 relative to baseline anddeclined after tumor resection (one sample t test, both P <0.0005; Fig. 2E). Both MPRs and non-MPRs had an increasedpercentage of top 1% ITCs in the peripheral blood during anti–PD-1 treatment. However, non-MPRs showed an earlier decline of top 1%ITCs compared withMPRs (Fig. 2E). No significant increase in sharedTCRs between non-top 1% ITCs and peripheral blood were observedinMPRs or non-MPRs at each time point (all P > 0.05). These findingsindicate that top-ranked ITCs are readily detected in peripheral bloodbefore treatment, increase in the periphery subsequent to PD-1blockade regardless of MPR status, and decrease in the peripheralblood after tumor resection/removal of tumor antigen, consistent withT-cell repertoire turnover in response to treatment. Yet this patternwas not present among non-top 1% ITCs, bolstering the notion thattop 1% ITCs were key migratory T cells.

We further systematically evaluated peripheral dynamics of ITCs inall patients at pairwise time points during PD-1 blockade. Clonotypeswith a significant increase in abundance compared with the previoustime point were defined as expanded clones, whereas those with asignificant decrease in abundance were defined as contracted clones.We quantified the degree of TCR repertoire remodeling by clonotypicfold change between pairwise time points. Peripheral clones weregrouped based on their representation in the tumor bed as PBMC-onlyclonotypes, non-top 1% frequency-ranked ITCs, and top 1% frequen-cy-ranked ITCs. Both non-top 1% ITCs and the top 1% ITCs showedgreater fold changes of expansion and contraction as compared withPBMC-only clonotypes during anti–PD-1 treatment (Fig. 2G). Par-ticularly, the top 1% ITCs consistently showed the highest degree ofreshaping, regardless of MPR status. To consolidate our hypothesisthat perturbations of the peripheral T-cell repertoire were specific toanti–PD-1 treatment and not the result of random fluctuations in theTCR repertoire, we evaluated changes in frequency between two long-term follow-up time points taken 6 months apart, during which asignificant amount of peripheral repertoire turnover would beexpected relative to time points taken 2 weeks apart, in a patient whodid not receive adjuvant chemotherapy and had serial blood samplesfor >1 year after surgery. Top 1% ITCs detected in the peripheral bloodunderwent appreciable peripheral expansions and contractions duringthe 4 weeks of anti–PD-1 treatment (Fig. 2F, time window: pretreat-ment to week 2; weeks 2 to 4). Strikingly, limited remodeling of theperipheral TCR repertoire was observed during the 6-month follow-upinterval relative to on-treatment time points (Fig. 2F, right), suggest-ing the systematic remodeling in the peripheral repertoire is a direct,early effect of PD-1 pathway blockade.

Clonal expansion of ITCs in peripheral blood correlates withpathologic response

We next sought to identify the kinetic pattern and time window ofTCR remodeling that correlates with tumor regression upon PD-1blockade. We recently detected peripheral expansion of neoantigen-specific peripheral T-cell clonotypes that were also observed in highabundance in the posttreatment tumor in a single patient with

MPR (3). We therefore hypothesized that peripherally expandedclones may home to the tumor (primary and potentially undetectedmicrometastatic deposits) to produce the antitumor response. Clono-types undergoing contraction or expansion were identified in pairwisetime points (pretreatment vs. week 2; week 2 vs. week 4) duringneoadjuvant PD-1 blockade using methods previously described andcontrolling for an FDR of 0.05 (18). A total of 689 dynamic clonotypeswere found among 17 patients with available serial blood samples(Supplementary Fig. S7). Compared with nondynamic clones, dynam-ic clones are more likely to be intratumoral clones, regardless of MPRstatus (Fig. 3A) and clones that contracted in the periphery betweenpretreatment and week 2 were more likely to be in the tumor bed ascompared with those contracted at between weeks 2 and 4; in contrast,clones expanded between weeks 2 and 4 were more likely to infiltratethe tumor bed (Fig. 3B). Nodifferencewas observed for the proportionof nondynamic clones in the tumor bed. Furthermore, the intratu-moral clonal space of clones expanded between weeks 2 and 4 wasinversely correlated with residual tumor (Spearman rank correlation,R ¼ �0.62, P ¼ 0.041; Fig. 3C).

Because peripherally dynamic clones are thought to be trafficking tothe tumor, we tested if intratumoral clonal occupancy of clones withdifferential peripheral patterns differentiates MPRs from non-MPRs.ITCs were stratified as peripherally contracted, expanded, nondy-namic, or tumor-resident only based on their different dynamicpatterns during treatment. There were no differences in the intratu-moral clonal space of peripherally contracted, expanded, or nondy-namic clones between pretreatment to week 2 (Mann–WhitneyU test,all P > 0.05, Supplementary Fig. S8). However, ITCs that specificallyexpanded between 2 and 4 weeks from anti–PD-1 treatment initiationdemonstrated a significantly greater clonal space in MPRs comparedwith non-MPRs (P¼ 0.018, Mann–WhitneyU test; Fig. 3D), suggest-ing an enhanced antitumor response with the influx or efflux ofperipherally expanded clones. Moreover, no difference was observedin the intratumoral clonal space of tumor-resident–only clonesbetween MPRs and non-MPRs (Fig. 3D), consistent with a previousstudy suggesting low and variable tumor reactivity of the intrinsictumor-resident TCR repertoire (20).

To further interrogate the tumor-specific localization of expandedclones, we repeated the analysis on clonotypes found in normal lungand observed no statistically significant difference in representation ofdifferential clonotypes between MPR and non-MPR (Fig. 3E), sug-gesting an enrichment of peripherally expanded clones that arespecifically concentrated within the tumor. In addition, we found thetop 1% ITCs of MPRs were preferentially constituted of peripheralclones expanded at weeks 2 to 4 (Fig. 3F) as comparedwith non-MPRs(median, 17.7% vs. 0.3%, Mann–Whitney U test, P ¼ 0.012). Nodifferences in clonotype composition among top 1% ITCs wereobserved for contracted, nondynamic, or tumor-resident only clonesbetween MPRs and non-MPRs (all P > 0.1). Based on the aboveobservations, we proposed the model that T-cell clones traffickingbetween the tumor and peripheral blood, particularly those differen-tially expanded at 2 to 4 weeks after PD-1 blockademay be responsiblefor tumor regression (Fig. 3G).

Acomplete pathologic responder is characterizedby significantexpansion of PD-1þ ITCs in the periphery

Our data suggest that PD-1 blockade rejuvenates preexistingperipheral T cells that expand upon treatment and accumulate intumor tissues. As prior studies have demonstrated PD-1 expression tobe reflective of a subset of PD-1-blockade–responsive, tumor-specificT cells, we examined the PD-1 expression status of these expanded

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ITCs using TCR-seq of sorted PD-1þ and PD-1� peripheral bloodT cells. This analysis focused on twopatients with extreme but oppositeresponses to neoadjuvant PD-1 blockade: a complete pathologicresponder, patient MD01-005, with 0% residual primary tumor withminimal tumor involvement of an adjacent lymph node, and non-responding patient MD01-024, with 100% residual tumor. In the

pathologic responder (MD01-005), among the 5 top 1% ITCs thatdifferentially expanded between 2 and 4 weeks after treatment initi-ation, all were found to be PD-1þ in the pretreatment peripheral blood(4 PD-1þCD8þ clones; 1 PD-1þCD4þ clone, Fig. 4A). These clono-types were additionally found to be top 1% clonotypes in a tumor-involved lymph node and a tumor-draining lymph node obtained at

Figure 3.

Differentially dynamic clones and their association with tumor infiltration and tumor accumulation. A, The proportion of dynamic clones vs. nondynamic clones thatinfiltrated tumor bed upon PD-1 blockade in MPR and non-MPR (n ¼ 12). B, The total proportion of clones in the tumor is shown for significantly contracted clones,significantly expanded clones, and nondynamic clones at week 2 (dark gray) andweek 4 (light gray) after treatment initiation (n¼ 12). C,Association of intratumoralclonal space of peripherally expanded clones and percent residual tumor by time window (pretreatment–W2, Spearman rho ¼ �0.35, W2–W4 Spearman rho ¼�0.62). Each patient is represented by a black dot. The blue line indicates the robust linear regression line (fitted using R function “rlm” from “MASS” package basedon M estimator), and the gray area indicates the upper and lower boundaries of the 95% confidence interval (n ¼ 12). D, The clonal space occupied by ITCswith different peripheral dynamic patterns (expanded, contracted, nondynamic or tumor-resident only) at 2–4 weeks after immunotherapy initiation is shown forMPRs and non-MPRs (n¼ 12). E, The clonal space occupied by normal lung T cells with differential patterns in the periphery is shown for MPRs and non-MPRs at 2 to4weeks after treatment initiation (n¼ 12).F,Theproportion of top 1% ITCs and their peripheral dynamic pattern at 2 to 4weeks after treatment initiation forMPRs andnon-MPRs (n¼ 12).G,Proposed schema of peripheral activation of the antitumor repertoire homing back to the tumor bed. ns, not significant. � ,P�0.05; �� ,P�0.01;�� , P � 0.001.






Zhang et al.





the time of surgical resection (Fig. 4A). PD-1 intraclonal positivity,defined as the percent of PD-1þ T cells within a particular clonotype,was markedly high for all 5 clonotypes in MD01-005 (Fig. 4B;median, 99%; range, 98%–100%). By contrast, for the nonresponder(MD01-024), the 7 top 1% ITCs that expanded at 2 to 4 weeksdemonstrated low PD-1 intraclonal positivity (median, 0.6%; range,0.2%–20.6%, Fig. 4C and D). Moreover, these expanded clones in thetumor bed of the nonresponder had a significantly lower proportionin the tumor relative to normal lung (paired Wilcoxon test, P ¼0.022, Fig. 4E). These results suggest that peripheral expansion isindicative of activation and migration of PD1þ T cells into the tumormicroenvironment, which could subsequently facilitate pathologicresponse in the tumor bed.

DiscussionWe recently identified neoantigen-specific T-cell clones in blood

obtained prior to anti–PD-1, at the preoperative visit, and after surgeryin a patient with MPR, with a transient expansion of these clones inperipheral blood after treatment initiation (3, 18). Based on thisobservation, we hypothesized that trafficking of relevant T-cell clonesbetween the periphery, normal tissues, and tumor would be importantfor effecting pathologic response. We therefore performed a compre-hensive assessment of T-cell repertoire and dynamics in the neoadju-vant setting and further sought to determine if specific variables ofclonal dynamics may be an early biological correlate of antitumorimmunity. As such, we used pathologic response to PD-1 blockade asan outcome. Although longer follow-up will be necessary to determinehow pathologic response correlates with clinical outcome in lungcancer, reports in melanoma indicate that early pathologic responsesto anti–PD-1 indeed correlate with improved survival (21, 22).

In this study, we use theTCRas a barcode to track clonal sharing anddynamics and observed a positive association between intratumoral T-cell repertoire clonality and pathologic tumor regression at surgery.Although we did not observe significant global changes in clonality ofthe peripheral TCR repertoire throughout the 4 weeks of treatment, wedetermined that the most significant parameter that differentiatesMPRs from non-MPRs is the clonal space occupied by the mostfrequent, i.e., top 1% frequency-ranked, ITCs, which demonstratedsystematic perturbations in frequency in the periphery upon PD-1blockade. More interestingly, our results showed that the top 1% ITCswere observed to be highly shared in both peripheral blood and normallung tissue from the same patient. Furthermore, the level of clonalsharing of ITCs with blood and normal lung was significantly higher inMPR patients relative to non-MPR patients, whereas non-MPRs hadmore tumor-resident–only ITCs, consistent with the notion thatintrinsic tumor-resident T-cell repertoire may likely to be exhaustedwith low tumor reactivity and that the T-cell response to checkpointblockade may derive from reinvigorated T cells that recently enteredthe tumor (23). Whereas the observation that non-MPRs have more

clones that are restricted in the tumor bed implicates potentialdeficiency in replenishment by the peripheral T-cell repertoire.

We additionally systematically characterized the dynamic pattern ofITCs in longitudinal blood. We found that significant dynamicchanges in the frequency of shared peripheral clones, regardless oftheir dynamic nature (contraction or expansion), associated withincreased tumor infiltration, suggesting an active compartmentalexchange of ITCs induced by neoadjuvant PD-1 blockade. Notably,peripherally expanded ITCs at weeks 2 to 4 from the initiation of anti–PD-1 preferentially occupy a greater clonal space in the tumor bed ofMPRs relative to non-MPRs. This observation highlights the impor-tance of effective peripheral activation in promoting pathologicresponse. On the contrary, we observed that non-MPR tumors donot successfully traffic top 1% ITCs to the tumor bed, possibly due to anintrinsically more exhausted, less migratory T-cell repertoire. Theseclones, when trapped in the tumor, could experience inhibited rein-vigoration upon PD-1 blockade owing to an immunosuppressivetumor microenvironment. Therefore, detection of tumor-infiltratingclones' expansion in the peripheral blood may be an early biologicalcorrelate of antitumor T-cell recognition and the peripheral bloodmaybe a valuable compartment for monitoring early T-cell responses toPD-1 blockade.

Supporting the notion that dynamics of shared clones are relevant tooutcomes of PD-1 blockade, we demonstrated that expanded clono-types in a patient with a complete pathologic response exhibitedextremely high intraclonal PD-1 positivity, in contrast to a patientwith no pathologic response, whose expanded clonotypes exhibitedvery low frequencies of PD-1 positivity. Although anti–PD-1 has beenreported to reinvigorate peripheral T-cell clones that are also present inthe tumor (24), our study further suggests that anti–PD-1 may inducean exchange of reinvigorated effector PD1þ T cells between theperiphery and tumor, where they may contribute to tumor regression.We recently showed that in stage 4 NSCLC treated with anti–PD-1,general expansion in the blood of all clones found in pretreatmenttumors correlated with radiographic response and clearance of circu-lating tumor DNA (14). Here we show in the neoadjuvant setting thatperipheral expansion of the most frequent ITCs (top 1% frequency)correlates much more closely with the pathologic response at the timeof resection.

Although a limited number of patients have been included in ouranalysis, we performed an in-depth integration of the intratumoralantitumor repertoire and peripheral T-cell repertoire. Larger cohortsare warranted to evaluate these features as predictive markers forresponse to neoadjuvant PD-1 blockade and relapse-free survival.However, we acknowledge that the median duration of recurrence-free survival has not been reached in this cohort, and we are thereforeunable to assess the association of TCR dynamics with survival.Additionally, although our approach utilizing TCRb chain sequencingis a common approach owing to (i) greater diversity of the b chainrelative to the a chain, (ii) stricter allelic exclusion of the b locus, and

Figure 4.PD1 sorting revealed differential patterns of intraclonal PD1þ positivity between complete pathologic responder and nonresponder. A, TCR-seq was performed onsorted PD-1–positive and –negative CD4þ and CD8þ peripheral blood T cells obtained from patient MD01-005 (0% residual tumor) prior to treatment (left). Thefrequency of clonotypes detected in the PD-1þ population is shown in serial peripheral blood (center) and biopsied and resected tissues (right) is shown. All 5differentially expanded ITCs identified in this patient were detected in the PD1þ-sorted population. B, Pie charts showing the intraclonal PD-1 positivity (theproportion of total reads of each clone that was detected in the PD-1þ vs. PD-1� sorted population) for the 5 peripherally expanded, top 1% ITCs is shown. C, TCR-seqwas performed on sorted PD-1–positive and –negative CD4þ and CD8þ peripheral blood T cells obtained from patient MD01-024 (100% residual tumor) prior totreatment (left). The frequency of clonotypes detected in the PD-1þ population is shown in serial peripheral blood (center) and resected tissues (right). D, Pie chartsshowing the intraclonal PD-1 positivity for peripherally expanded, top 1% ITCs. E, The read proportion of top 1% ITCs in the normal lung and tumor bed is shown forpatient MD01-005 and patient MD01-024. Comparisons between normal lung and tumor bed were evaluated using the Wilcoxon signed-rank test.






(iii) technical ease of performing TCR-seq on theb chain, we recognizethat single-cell paired ab sequencing approaches should be used infuture studies aimed at determining the antigen specificity or functionof these T cells. Similarly, a limitation of our study is that we did notdifferentiate between CD4þ and CD8þ T-cell clones. Although, tra-ditionally, CD8þ T-cell infiltration has been associated with improvedprognosis in untreated/pretreatment tumor specimens, it is importantto note that our specimens were obtained after neoadjuvant PD-1blockade and the association of CD4þ versus CD8þ T-cell infiltrationwith pathologic response or clinical outcome has not been systemat-ically evaluated in this setting. To that end, ascertaining theCD4 versusCD8 identity of these T cells would also be useful in determiningfunction in future studies. Correlation with ‘Immune-Related Path-ologic Response Criteria’ (irPRC; ref. 25), a newly proposed pathologicassessment of residual tumor in immunotherapy, should also beexplored if validated as a surrogate for recurrence-free and overallsurvival. Efforts to extrapolate the current findings to patients withmetastatic disease should be met with caution, as we are specificallyevaluating tumor-infiltrating T cells after PD-1 blockade in patientswith resectable disease. However, our results have important implica-tions for the establishment of predictive biomarkers through liquidbiopsy approaches. In conclusion, our study shows that TCR profilingholds promise for monitoring antitumor responses in the peripheryand will spur future development of biomarkers to predict response toimmunotherapy and to guide what additional therapies may bewarranted after surgical resection.

Disclosure of Potential Conflicts of InterestV. Anagnostou reports receiving commercial research grants from Bristol-Myers

Squibb. J.E. Chaft is a paid consultant for Bristol-Myers Squibb, AstraZeneca, Merck,and Genentech. D.R. Jones is an employee of Diffusion Pharmaceuticals and a paidconsultant forMerck andAstraZeneca. J. Naidoo is a paid consultant for AstraZeneca,Roche/Genentech, and Bristol-Myers Squibb, and reports receiving commercialresearch grants from Merck and AstraZeneca. J.M. Taube is a paid consultant forBristol-Myers Squibb, AstraZeneca, Merck, and Akoya Biosciences, and reportsreceiving commercial research grants from Bristol-Myers Squibb and Akoya Bio-sciences. V.E. Velculescu is an employee of PersonalGenomeDiagnostics and is a paidconsultant for Takeda, and holds ownership interest (including patents) in PersonalGenome Diagnostics. J.R. Brahmer is a paid consultant for Bristol-Myers Squibb,Merck, AstraZeneca, and Genentech, and reports receiving commercial researchgrants from Bristol-Myers Squibb. M.D. Hellmann is a paid consultant for Merck,AstraZeneca, Genentech, Bristol-Myers Squibb, Blueprint Medicines, Nektar, Syn-dax, Mirati, Shattuck Labs, and Immunai; reports receiving commercial researchgrants from Bristol-Myers Squibb; holds ownership interests in Shattuck Labs andImmunai; and is listed as a coinventor on a patent that has been filed byMSK related tothe use of tumor mutation burned to predict response to immunotherapy which hasreceived licensing fees from PGDx. P.M. Forde reports receiving commercial researchgrants from AstraZeneca, Bristol-Myers Squibb, Corvus, Kyowa, and Novartis, and isan unpaid consultant/advisory boardmember forAstraZeneca, Bristol-Myers Squibb,Janssen, Merck, Novartis, Lilly, and Boehringer. D.M. Pardoll holds ownershipinterest (including patents) in Bristol-Myers Squibb. K.N. Smith reports receivingspeakers bureau honoraria from Illumina, Inc. and Neon Therapeutics. No potentialconflicts of interest were disclosed by the other authors.

Authors’ ContributionsConception and design: J. Zhang, J.X. Caushi, T.R. Cottrell, P.M. Forde,D.M. Pardoll, H. Ji, K.N. SmithDevelopment of methodology: J. Zhang, Z. Ji, J.X. Caushi, D.M. Pardoll, H. Ji,K.N. SmithAcquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): M. El Asmar, T.R. Cottrell, H.Y. Chan, P. Suri,T. Merghoub, J.E. Chaft, J.E. Reuss, A.J. Tam, D.R. Jones, K.A. Marrone,J. Naidoo, E. Gabrielson, J.M. Taube, J.R. Brahmer, M.D. Hellmann,P.M. Forde, K.N. SmithAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): J. Zhang, Z. Ji, J.X. Caushi, M. El Asmar,V. Anagnostou, T. Merghoub, J.-W. Sidhom, N. Zhao, D.R. Jones, J. Naidoo,J.M. Taube, V.E. Velculescu, M.D. Hellmann, P.M. Forde, D.M. Pardoll, H. Ji,K.N. SmithWriting, review, and/or revision of themanuscript: J. Zhang, Z. Ji, J.X. Caushi,M. ElAsmar, V. Anagnostou, T.R. Cottrell, J.E. Chaft, J.E. Reuss, J.S. Ha, D.R. Jones,K.A. Marrone, J. Naidoo, J.M. Taube, V.E. Velculescu, J.R. Brahmer, F. Housseau,M.D. Hellmann, P.M. Forde, D.M. Pardoll, H. Ji, K.N. SmithAdministrative, technical, or material support (i.e., reporting or organizing data,constructing databases): H. Guo, M. Abu-Akeel, J. NaidooStudy supervision: H. Guo, J.E. Chaft, D.R. Jones, J. Naidoo, V.E. Velculescu,P.M. Forde, D.M. Pardoll, H. Ji, K.N. SmithOther (processed samples for TCR sequencing): P. SuriOther (flow cytometry analysis and cell sorting): R.L BlosserOther (data discussion): F. Housseau

AcknowledgmentsWe would like to thank the patients and their families for participation in

this study, as well as Chanice Barkley, Iiasha Beadles, and members of ourrespective research and administrative teams who contributed to this study.K.N. Smith and H.Y. Chan were funded by The Lung Cancer Foundation of Americaand the International Association for the Study of Lung Cancer Foundation. H. Ji wasfunded by the National Human Genome Research Institute of the NIH underAward Number R01 HG009518. F. Housseau was funded by NIH R01 CA203891-01A1. K.N. Smith, H. Guo, P.M. Forde, and J.R. Brahmer were funded bySU2C/AACR (SU2C-AACR-DT1012). K.N. Smith, J.-W. Sidhom, J. Zhang, andD.M. Pardoll were funded by the Mark Foundation for Cancer Research. V.Anagnostou was funded by the Eastern Cooperative Oncology Group- AmericanCollege of Radiology Imaging Network, the V Foundation, the LUNGevity Foun-dation and by NIH grant CA121113. V.E. Velculescu was funded by NIH grantsCA121113, CA180950, the Dr. Miriam and Sheldon G. Adelson Medical ResearchFoundation, and theCommonwealth Foundation. J.M. Taubewas funded byNCIR01CA142779; T.R. Cottrell was funded by NIH T32 CA193145. This research wasfunded in part through the Bloomberg-Kimmel Institute for Cancer Immunotherapy,Bloomberg Philanthropies, NIH Cancer Center Support Grant P30 CA008747, NIHCancer Center Support Grant P30 CA008748, NIH/NCI R01 CA056821, the SwimAcross America, Ludwig Institute for Cancer Research, Parker Institute for CancerImmunotherapy, and Virginia B. Squiers Foundation.

The costs of publication of this article were defrayed in part by the payment of pagecharges. This article must therefore be hereby marked advertisement in accordancewith 18 U.S.C. Section 1734 solely to indicate this fact.

Received September 6, 2019; revised October 21, 2019; accepted November 18,2019; published first November 21, 2019.

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2020;26:1327-1337. Published OnlineFirst November 21, 2019.Clin Cancer Res Jiajia Zhang, Zhicheng Ji, Justina X. Caushi, et al.

Small Cell Lung Cancer−Non esectablePathologic Response to Neoadjuvant PD-1 Blockade in R

Compartmental Analysis of T-cell Clonal Dynamics as a Function of

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