compartmental analysis of t cell clonal dynamics as a ......repertoire in nsclc patients receiving...

Compartmental analysis of T cell clonal dynamics as a function of pathologic response 1

to neoadjuvant PD-1 blockade in resectable non-small cell lung cancer 2

3

Authors: Jiajia Zhang1,2†

, Zhicheng Ji3†

, Justina X. Caushi1,2†

, Margueritta El Asmar1,2†

, Valsamo 4

Anagnostou1,2

, Tricia R. Cottrell1,2,4

, Hok Yee Chan1,2

, Prerna Suri1,2

, Haidan Guo1,2

, Taha Merghoub6, Jamie 5

E. Chaft6, Joshua E. Reuss

1,2, Ada Tam

1,2, Richard Blosser

1,2, Mohsen Abu-Akeel

6, John-William Sidhom

1,2, 6

Ni Zhao3, Jinny S. Ha

2,5, David R. Jones

7, Kristen A. Marrone

1,2, Jarushka Naidoo

1,2, Edward Gabrielson

1,2, 7

Janis M. Taube1,2,4

, Victor E. Velculescu1,2,4

, Julie R. Brahmer1,2

, Franck Housseau1,2

, Matthew D. 8

Hellmann6, Patrick M. Forde

1,2, Drew M. Pardoll

1,2, Hongkai Ji

3#, Kellie N. Smith

1,2#* 9

Affiliations: 10

1 The Bloomberg-Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University School of 11

Medicine, Baltimore, MD, USA. 12

2 The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, 13

Baltimore, MD, USA. 14

3 Department of Biostatistics, Johns Hopkins Bloomberg School of Public Heath, Johns Hopkins University, 15


4 Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA. 17

5 Division of Thoracic Surgery, Department of Surgery, Johns Hopkins University School of Medicine, 18


6 Thoracic Oncology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center and Weill 20

Cornell Medical Center, New York, NY, United States 21

7 Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center and Weill Cornell 22

Medical Center, New York, NY, United States 23

Research. on March 24, 2020. © 2019 American Association for Cancerclincancerres.aacrjournals.org Downloaded from

Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on November 21, 2019; DOI: 10.1158/1078-0432.CCR-19-2931

http://clincancerres.aacrjournals.org/

2

24

†These authors contributed equally 25

#These authors contributed equally 26

27

Running title: T cell dynamics during neoadjuvant anti-PD-1 in NSCLC 28

Key words: Neoadjuvant, PD-1 Blockade, T cell dynamics, TCR repertoire 29

30

31

Financial Support 32

K.N. S. and H.Y.C. were funded by The Lung Cancer Foundation of America and the International 33

Association for the Study of Lung Cancer Foundation. H.J. was funded by the National Human Genome 34

Research Institute of the National Institutes of Health (NIH) under Award Number R01 HG009518. F.H. was 35

funded by NIH R01 CA203891-01A1. K.N. S., H. G., P. F., and J.R.B. were funded by SU2C/AACR 36

(SU2C-AACR-DT1012). K.N.S, J.W. S., J. Z., and D.M. P. were funded by the Mark Foundation for Cancer 37

Research. V. A. was funded by the Eastern Cooperative Oncology Group- American College of Radiology 38

Imaging Network, MacMillan Foundation, and LUNGevity Foundation. V.E.V. was funded by US National 39

Institutes of Health grants CA121113, CA180950, the Dr. Miriam and Sheldon G. Adelson Medical 40

Research Foundation, and the Commonwealth Foundation. J.M. T. was funded by National Cancer Institute 41

R01 CA142779; T.R.C. was funded by NIH T32 CA193145. This research was funded in part through the 42

Bloomberg-Kimmel Institute for Cancer Immunotherapy, Bloomberg Philanthropies, NIH Cancer Center 43

Support Grant P30 CA008747, NIH Cancer Center Support Grant P30 CA008748, NIH/NCI R01 44

CA056821, the Swim Across America, Ludwig Institute for Cancer Research, Parker Institute for Cancer 45

Immunotherapy and Virginia B. Squiers Foundation. 46

47

Corresponding author: To whom correspondence should be addressed: Kellie N. Smith, [email protected]; 48

Tel: (410) 502-7523; Address: The Bunting Blaustein Cancer Research Building, 1650 Orleans Street, 49

Room 4M51, Baltimore, MD 21287 50

51

52



mailto:[email protected]


3

Disclosure of Potential Conflicts of Interest 53

J.M.T. receives research funding from BMS, and is a consultant/advisory board member for Bristol-Myers 54

Squibb (BMS), Merck, and MedImmune/AstraZeneca. J. C. is a consultant for AstraZeneca, BMS, and 55

Genentech and received research funding from AstraZeneca, BMS, Genentech, and Merck. T. M. is a 56

consultant for Leap Therapeutics, Immunos Therapeutics and Pfizer, and co-founder of Imvaq therapeutics; 57

has equity in Imvaq therapeutics; reports grants from BMS, Surface Oncology, Kyn Therapeutics, Infinity 58

Pharmaceuticals, Peregrine Pharmeceuticals, Adaptive Biotechnologies, Leap Therapeutics and Aprea; is 59

inventor on patent applications related to work on oncolytic viral therapy, alphavirus-based vaccines, neo-60

antigen modeling, CD40, GITR, OX40, PD-1 and CTLA-4. J.N. receives research funding from Merck and 61

AstraZeneca, is a consultant/advisory board member for BMS, Roche/Genentech, and AstraZeneca, and has 62

received honoraria from AstraZeneca and BMS. V.A. receives research funding from BMS. M.D.H. has 63

received research funding from BMS; is a paid consultant to Merck, BMS, AstraZeneca, Roche/Genentech, 64

Janssen, Nektar, Syndax, Mirati, and Shattuck Lab; has received travel support/honoraria from AstraZeneca 65

and BMS; and a patent has been filed by MSK related to the use of tumor mutation burden to predict 66

response to immunotherapy (PCT/US2015/062208), which has received licensing fees from PGDx. P.M.F 67

receives research funding from AZ, BMS, Corvus, Kyowa, and Novartis and is a consultant/advisory board 68

member for Abbvie, AstraZeneca, BMS, Boehringer, EMD Serono, Iniviata, Janssen, Lilly, Merck, and 69

Novartis. J.R.B receives research funding (to institution) from BMS, Merck, AstraZeneca, and is on 70

consulting/advisory boards of BMS (uncompensated), Merck and Genentech. D.M.P. reports grant and 71

patent royalties through institution from BMS, grant from Compugen, stock from Trieza Therapeutics and 72

Dracen Pharmaceuticals, and founder equity from Potenza; being consultant for Aduro Biotech, Amgen, 73

Astra Zeneca (Medimmune/Amplimmune), Bayer, DNAtrix, Dynavax Technologies Corporation, Ervaxx, 74

FLX Bio, Rock Springs Capital, Janssen, Merck, Tizona, and Immunomic- Therapeutics; being on the 75

scientific advisory board of Five Prime Therapeutics, Camden Nexus II, WindMil; being on the board of 76

director for Dracen Pharmaceuticals. V.E.V. is a founder of Personal Genome Diagnostics, a member of its 77




4

Scientific Advisory Board and Board of Directors, and owns Personal Genome Diagnostics stock, which are 78

subject to certain restrictions under university policy. V.E.V. is an advisor to Takeda Pharmaceuticals. 79

Within the last five years, V.E.V. has been an advisor to Daiichi Sankyo, Janssen Diagnostics, and Ignyta. 80

K.N.S. has received travel support/honoraria from Neon Therapeutics and Illumina. The terms of these 81

arrangements are managed by Johns Hopkins University in accordance with its conflict of interest policies. 82

Word count: 4,551 83

Total number of figures: 4 84

Total number of tables: 0 85

86

Translational Relevance 87

Neoadjuvant PD-1 blockade has emerged as a promising treatment for resectable NSCLC and is being tested 88

in at least 10 cancer types. It will be critical to investigate mechanisms of action and identify novel 89

biomarkers for robust antitumor immune responses. Here, we used matched tumor, normal lung tissue, and 90

longitudinal peripheral blood samples to examine the quantitative and qualitative changes in the T cell 91

repertoire in NSCLC patients receiving neoadjuvant anti-PD-1. Our results add to the growing body of 92

evidence that PD-1 blockade can boost antitumor immune responses by re-invigorating peripheral T cells to 93

enter the tumor. Our results indicate that the periphery may be a previously underappreciated compartment 94

for anti-tumor T cells that could be exploited in biomarker approaches for monitoring the response to 95

immunotherapy. 96

97

Abstract 98

Purpose: Neoadjuvant PD-1 blockade is a promising treatment for resectable non-small cell lung cancer 99

(NSCLC), yet immunological mechanisms contributing to tumor regression and biomarkers of response are 100

unknown. Using paired tumor/blood samples from a phase 2 clinical trial (NCT02259621), we explored 101

whether the peripheral T cell clonotypic dynamics can serve as a biomarker for response to neoadjuvant PD-102




5

1 blockade. Experimental Design: T cell receptor (TCR) sequencing was performed on serial peripheral 103

blood, tumor and normal lung samples from resectable NSCLC patients treated with neoadjuvant PD-1 104

blockade. We explored the temporal dynamics of the T cell repertoire in the peripheral and tumoral 105

compartments in response to neoadjuvant PD-1 blockade by using the TCR as a molecular barcode. Results: 106

Higher intratumoral TCR clonality was associated with reduced percent residual tumor at the time of 107

surgery, and the TCR repertoire of tumors with major pathologic response (MPR; <10% residual tumor after 108

neoadjuvant therapy) had a higher clonality and greater sharing of tumor infiltrating clonotypes with the 109

peripheral blood relative to tumors without MPR. Additionally, the post-treatment tumor bed of patients with 110

MPR was enriched with T cell clones that had peripherally expanded between weeks 2-4 after anti-PD-1 111

initiation and the intratumoral space occupied by these clonotypes was inversely correlated with percent 112

residual tumor. Conclusions: Our study suggests that exchange of T cell clones between tumor and blood 113

represents a key correlate of pathologic response to neoadjuvant immunotherapy, and shows that the 114

periphery may be a previously underappreciated originating compartment for effective anti-tumor immunity. 115

Introduction 116

PD-1/PD-L1 axis blockade enhances antitumor immunity, induces sustained tumor regression, and 117

extends overall survival in many advanced cancers (1). More recently, neoadjuvant PD-1/PD-L1 pathway 118

blockade in earlier stage lung cancer has shown clinical efficacy (2,3) while inducing peripheral expansion 119

of mutation-associated neoantigen-specific T-cell clones (3). Neoadjuvant phase 3 clinical trials 120

incorporating PD-1 blockade are now active across multiple solid tumors (3-6). 121

T cells are key determinants of immune response to checkpoint blockade. Blockade of PD-1 signaling 122

with anti-PD-1/PD-L1 antibodies reinvigorates pre-existing tumor-specific T cell clones (7). In addition to 123

PD-L1 expression (8), other immune correlates of clinical response to PD-1 blockade include CD8+ T cell 124

infiltration (9), the presence of PD-1+CD8

+ T cells at the invasive tumor margin (9,10), high densities of 125

CD45RO+granzyme

+ T cells (11), IFN-γ associated gene expression (12), the proximity of PD1

+ to PDL1

+ 126

cells (13), and CD8/Ki-67 co-expression (9). Peripheral expansion of intratumoral clonotypes (14) and 127

proliferation of peripheral Ki-67+ PD-1

+ CD8

+ T cells (15) have been linked with clinical benefit from PD-1 128




6

blockade in advanced NSCLC using pre-treatment tumor specimens, but connecting these changes with the 129

intratumoral immune response after treatment has not be done. Herein we report the coordinated dynamics of 130

the peripheral and tumor-infiltrating T cell repertoire following neoadjuvant anti-PD1 treatment in resectable 131

NSCLC. We analyzed specimens collected during a clinical trial evaluating the safety and feasibility of 132

neoadjuvant PD-1 blockade in resectable NSCLC (NCT02259621). The neoadjuvant setting, whereby PD-1 133

blockade is given before surgical resections, was introduced based on the hypothesis that the “in-place” 134

tumor at the time of immunotherapeutic intervention could serve as a large antigen source to drive enhanced 135

systemic anti-tumor immunity (3).The neoadjuvant format also provides a unique opportunity to monitor the 136

TCR repertoire across time (in serial peripheral blood draws) and space (across different biological 137

compartments) according to pathologic response. 138

Because the T cell receptor (TCR) confers unique antigen specificity, we use TCR Vβ CDR3 139

sequencing (TCRseq) to track intra-tumoral clonotypes (ITCs) over time and across biological compartments 140

to show that treatment-induced peripheral TCR repertoire remodeling correlates with increased tumor 141

infiltration of T cells and major pathologic response (MPR). Specifically, peripheral T cell clonotypic 142

expansion between weeks 2-4 after neoadjuvant anti-PD1 treatment initiation correlated with greater 143

intratumoral clonotype accumulation for patients with MPR. These results indicate that the peripheral blood 144

TCR repertoire is an important compartment for rejuvenating anti-tumor immunity. 145

Materials and Methods 146

Study design 147

The biospecimens evaluated in this study were obtained from patients enrolled to a phase 2 study 148

evaluating the safety and feasibility of preoperative administration of nivolumab in patients with high-risk 149

resectable NSCLC, along with a comprehensive exploratory characterization of the tumor immune milieu 150

and circulating immune cells and soluble factors in these patients (NCT02259621). Specifically, 21 adults 151

with untreated, surgically resectable (stage I, II, or IIIA) NSCLC were enrolled. Two preoperative doses of 152

Nivolumab (at a dose of 3 mg per kilogram of body weight) was administered intravenously every 2 weeks, 153



http://clinicaltrials.gov/show/NCT02259621


7

with surgery planned approximately 4 weeks after the first dose (3). Longitudinal peripheral blood samples 154

(pre-, post-treatment and follow-ups), pre- and post-treatment tumor samples, post-treatment lymph nodes 155

and normal lung tissues were collected (Fig. 1A and Table S2). Normal lung tissues were sampled 10-15 cm 156

from tumor margin of surgically-resected specimens. Pathologic response and tumor mutational burden for 157

each patient are shown in Supplementary Table 2. This study was approved by the Institutional Review 158

Board (IRB) of the Johns Hopkins University and Memorial Sloan Kettering Cancer Center, and conformed 159

to the Declaration of Helsinki and Good Clinical Practice guidelines. Informed consent was obtained from all 160

patients. 161

162

T cell receptor (TCR) sequencing and assessment of the TCR repertoire 163

DNA was extracted from post-treatment tumor tissue, normal lung tissue, lymph nodes, and 164

longitudinal pre- and post-treatment peripheral blood using a Qiagen DNA blood mini kit, DNA FFPE kit, or 165

DNA blood kit, respectively (Qiagen). TCR V β CDR3 sequencing was performed using the survey (tissues) 166

or deep (PBMC) resolution ImmunoSEQ platforms (16) (Adaptive Biotechnologies, Seattle, WA). TCR 167

repertoire diversity was assessed by productive clonality, which is a measure of species diversity (17). To 168

normalize between samples that contain different numbers of total CDR3 TCRβ sequencing reads, entropy 169

was divided by log2 of the number of unique productive sequences. Nonproductive TCR CDR3 sequences 170

(premature stop or frame-shift), sequences with amino acid length less than 5, and sequences not starting 171

with “C” or ending with “F/W” were excluded from the final analyses. 172

173

Fluorescence-activated cell sorting (FACS) for PD-1 positive T cells in PBMC 174

Treatment-induced dynamics of exhausted T cells were assessed by tracking clones with upregulation 175

of PD-1. PBMC obtained at baseline, immediately prior to the first anti-PD-1 infusion, were washed and 176

incubated with BV786-conjugated anti-CD8 (RPA-T8), BV605-conjugated anti-CD3 (SK7), BV510-177




8

conjugated anti-CD4 (SK3), and PE-Cy7-conjugated anti-PD-1 (EH12.1) for 30 minutes at 4C. Cells were 178

washed, resuspended in FACS Buffer, and live CD3+ T cells were sorted into four populations: CD4

+/PD-1

-, 179

CD4+/PD-1

+, CD8

+/PD-1

-, and CD8

+/PD-1

+ using the FACSAria Fusion SORP cell sorter (BD, San Jose, 180

CA). gDNA extractions were performed on sorted cells and samples were subsequently sent for TCR 181

sequencing as described above. 182

183

Identification of differentially expanded/contracted clones in PBMC 184

Bioinformatic and biostatistical analysis of differentially expanded/contracted clones in PBMC after 185

each dosing of anti-PD-1 monotherapy was performed using Fisher’s exact test with multiple testing 186

correction by Benjamini-Hochberg procedure which controls false discovery rate (FDR <0.05) (18). 187

Differential clonotypes were further analyzed for tissue and longitudinal PBMC representation in MPRs and 188

non-MPRs. 189

190

Statistical analysis 191

Statistical analysis was performed using R software. The Mann Whitney U test was used for 192

comparison of 2-group data. For analysis of >2 group data, Kruskal–Wallis H test was used. Spearman’s rho 193

was used to measure the correlation between two continuous variables. Data were expressed as mean ± SEM 194

unless otherwise indicated and P < 0.05 was considered significant. ns: p > 0.05, *: p <= 0.05, **: p <= 0.01, 195

***: p <= 0.001, ****: p <= 0.0001. 196

197

Results 198

Intratumoral TCR repertoire is associated with pathologic response to neoadjuvant anti-PD-1 199




9

We previously reported the feasibility, efficacy, and safety of neoadjuvant PD-1 blockade in 200

treatment naïve, surgically resectable (stage I, II, or IIIA) NSCLC (3). Briefly, 21 patients were treated with 201

two preoperative doses of anti-PD-1 with minimal toxicity and no delays to surgery. Among the 20 patients 202

who underwent surgical resection, 9 had 10% residual viable tumor upon histopathological examination of 203

the surgically resected tumor (Table S1). An overview of the trial design and biospecimen collection is 204

shown in Fig. 1A and Table S2. 205

Because T cell clonality in the tumor has been associated with clinical outcome in metastatic cancers 206

(9), we first assessed whether clonality of the intra-tumoral TCR repertoire following neoadjuvant anti-PD1 207

may reflect an anti-tumor immune response. TCRseq on post-treatment (resection) tumor bed was performed 208

to determine the clonality of the intratumoral repertoire. A clonality value of 0 represents the most diverse 209

repertoire (every T-cell in a sample contains a unique TCR) whereas a value of 1 represents a monoclonal T-210

cell population. Tumor mutational burden (TMB) was also evaluated as a potential correlate of 211

immunological response. The methods and results of whole exome sequencing and tumor mutational burden 212

have been reported previously (3). TMB positively correlated with intratumoral clonality (Spearman's rank 213

correlation, R=0.7, P=0.025; Fig. 1B), suggesting expansion of a small subset of clonotypes in high TMB 214

tumors. An inverse association was observed between intratumoral TCR repertoire clonality and percent 215

residual tumor at the time of surgery (Spearman's rank correlation, R=-0.65, P=0.041, Fig. 1C). No 216

correlation was observed between the total number of reads (ie. total number of sequenced cells) used for 217

TCRseq and percent residual tumor or intratumoral clonality (Fig. S1-S2), indicating that differences in 218

sample yield or T cell number did not bias our analysis. These observations support the hypothesis that high 219

TMB increases the likelihood that one or several mutations can drive a clonally skewed intratumoral T cell 220

repertoire leading to tumor pathologic regression. Post-treatment tumor, but not normal lung tissue, from 221

patients with MPR had a significantly higher T cell clonality relative to patients with non-MPR (Mann–222

Whitney U test, P=0.0085, Fig. 1D). Conversely, patients with MPR had a trend toward lower clonality in 223

the peripheral blood compared to non-MPRs at each longitudinal timepoint, although this was not 224



https://www.nature.com/articles/s41467-017-02540-x#Fig1

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4246418/figure/F3/




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statistically significant (Mann–Whitney U test, all p>0.05, Fig. S3). These findings of increased clonality 225

only inside the tumor suggest that these changes may be directly related to tumor recognition, with the caveat 226

that antigen-specific recognition is not assessable by TCRseq alone. 227

We then tested if the most abundant intratumoral clonotypes (ITCs), rather than all ITCs, were 228

specifically contributing to the difference in T cell repertoire between MPRs and non-MPRs. ITCs were 229

ranked according to their frequency as the top 1%, top 1-2%, 2-5% and >5% most frequent clonotypes in the 230

resected tumor bed. T cell clonal space was defined and calculated as the summed frequency of clones in 231

each of the four respective groups relative to the total T cell repertoire. There was no difference for 232

clonotype richness, defined as total number of unique clonotypes, among the different ranges between MPRs 233

and non-MPRs. However, consistent with the clonality calculations described above, the top 1% most 234

abundant ITCs occupied a significantly greater clonal space in MPRs compared to non-MPRs (Mann–235

Whitney U test, median: 31.6% vs 18.8%, P=0.011, Fig. 1E-F), suggesting the top frequency-ranked ITCs 236

may drive the anti-tumor response. Of note, MPR patient MD-01-010 with relatively low clonal space for top 237

1% ITCs had 100% PD-L1 positivity on pre-treatment tumor immunohistochemistry staining. Of the 788 top 238

1% ITCs from 16 patients with available tumor TCR data, only 1 clonotype was detected to be shared across 239

patients (CDR3: CASSLGQAYEQYF, shared between patient NY016-007 and patient NY016-009, both 240

were non-MPR), suggesting that the anti-tumor TCR repertoire was unique to each patient in our cohort. 241

242

Top 1% most abundant ITCs have the highest compartmental dynamics during PD-1 blockade 243

Using the TCR Vβ CDR3 as a biological barcode, we next assessed the cross-compartment (normal 244

lung and pre-treatment blood) and temporal (before-treatment, on-treatment, and post-treatment blood) 245

dynamics of ITCs, identified as T cell clonotypes that were detected in the resected tumor bed, and its 246

association with pathologic response. The top 1% most frequent ITCs had a significantly higher proportion 247

shared between the pre-treatment peripheral blood and resected normal lung as compared with less highly 248




11

represented ITCs– ie. non-top 1% frequency-ranked clonotypes (Mann–Whitney U test, median: 61.6% vs 249

28.8%, P=1.1e-5; 81.4% vs 24.5%, P=1.4e-5, respectively, Fig. 2A). Notably, MPRs had a higher proportion 250

of top 1% most frequent ITCs detected in pre-treatment blood (Mann–Whitney U test, median: 85.7% vs 251

55.6%, P=0.045, Fig. 2B) and normal lung (Mann–Whitney U test, median, 94.3% vs 70.6%, P=0.023, Fig. 252

2B) as compared to non-MPRs. No significant differences were found between MPRs and non MPRs for 253

non-top 1% frequency-ranked ITCs (all p>0.1, Fig. S3). The high proportion of ITCs mobilizing across 254

blood and normal lung, and in particular for top 1% frequency-ranked ITCs among MPR patients, suggests 255

an active trafficking of anti-tumor T cells between the tumor and other biological compartments. 256

Top 1% ITCs were then categorized into 4 mutually-exclusive subsets: ITCs shared in the pre-257

treatment blood and the resected normal lung; ITCs found only in the pre-treatment blood; ITCs found only 258

in the resected normal lung; and tumor-resident ITCs (not found in the resected normal lung or the pre-259

treatment blood). Although the total number of top 1% ITCs was comparable in MPRs and non-MPRs (Fig. 260

5S), MPRs had a greater proportion of top 1% ITCs shared with both pre-treatment blood and the resected 261

normal lung compartment (Mann–Whitney U test, median, 81.0% vs 50.7%, P=0.053, Fig. 2C, Fig. S6). In 262

contrast, a greater proportion of the top 1% tumor-resident ITCs was observed in non-MPRs as compared to 263

MPRs (Mann–Whitney U test, median, 21.4% vs 3.6%, P=0.013, Fig. 2C, Fig. S7), suggesting that more 264

migratory T cell clones correlated with the anti-tumor response. Supporting this notion, total ITCs shared 265

with both the pre-treatment blood and the resected normal lung occupied a higher clonal space in MPRs as 266

compared to non-MPRs (P=0.011); whereas non-MPRs had a greater clonal space occupied by tumor-267

resident ITCs (P=0.048, Fig. 2D). It is conceivable that the normal lung TCR repertoire could be a reflection 268

of the increased vascularization in healthy lung rather than true tissue-resident T cells, however the normal 269

lung had significantly fewer shared clones with the peripheral blood compared to the level of sharing 270

between blood samples obtained from different timepoints (median 18 % vs 53%, Wilcoxon: p=1.5e-07), 271

thereby demonstrating the presence of a T cell repertoire specific to the normal lung. No difference was 272

found in the clonal space of ITCs shared with only the pre-treatment blood or the resected normal lung 273




12

between MPRs and non-MPRs (all P>0.1). These observations suggest that the difference of the top clonal 274

space occupied by the top 1% ITCs between MPRs and non-MPRs could be driven by ITCs trafficking 275

through the blood and normal lung, which could mark a consort of T cells associated with pathologic 276

response. 277

Peripheral “TCR repertoire remodeling” (i.e. fluctuations in the frequency and composition of T cell 278

clonotypes within the repertoire) has been demonstrated in metastatic melanoma patients treated with anti-279

CTLA4 (19). In our study here, we characterized the repertoire remodeling in response to PD-1 blockade by 280

evaluating the temporal dynamics of TCR repertoire in blood before, during, and after neoadjuvant treatment 281

and linking these alterations with their tumor-infiltrating status. Between treatment initiation and surgery, the 282

proportion of top 1% ITCs shared with the peripheral TCR repertoire significantly increased at week 2 and 283

week 4 relative to baseline and declined after tumor resection (one sample t test, both P<0.0005, Fig. 2E). 284

Both MPRs and non-MPRs had an increased percent of top 1% ITCs in the peripheral blood during anti-PD-285

1 treatment. However, non-MPRs showed an earlier decline of top 1% ITCs compared to MPRs (Fig. 2E). 286

No significant increase in shared TCRs between non-top 1% ITCs and peripheral blood were observed in 287

MPRs or non-MPRs at each timepoint (all p>0.05). These findings indicate that top-ranked ITCs are readily 288

detected in peripheral blood before treatment, increase in the periphery subsequent to PD-1 blockade 289

regardless of MPR status, and decrease in the peripheral blood after tumor resection/removal of tumor 290

antigen, consistent with T cell repertoire turnover in response to treatment. Yet this pattern was not present 291

among non-top 1% ITCs, bolstering the notion that top 1% ITCs were key migratory T cells. 292

We further systematically evaluated peripheral dynamics of ITCs in all patients at pairwise 293

timepoints during PD-1 blockade. Clonotypes with a significant increase in abundance compared to the 294

previous timepoint were defined as expanded clones, whereas those with a significant decrease in abundance 295

were defined as contracted clones. We quantified the degree of TCR repertoire remodeling by clonotypic 296

fold change between pairwise timepoints. Peripheral clones were grouped based on their representation in the 297

tumor bed as PBMC-only clonotypes, non-top 1% frequency-ranked ITCs, and top 1% frequency-ranked 298




13

ITCs. Both non-top 1% ITCs and the top 1% ITCs showed greater fold changes of expansion and contraction 299

as compared to PBMC-only clonotypes during anti-PD-1 treatment (Fig. 2G). Particularly, the top 1% ITCs 300

consistently showed the highest degree of reshaping, regardless of MPR status. To consolidate our 301

hypothesis that perturbations of the peripheral T cell repertoire were specific to anti-PD-1 treatment and not 302

the result of random fluctuations in the TCR repertoire, we evaluated changes in frequency between two 303

long-term follow-up timepoints taken 6 months apart, during which a significant amount of peripheral 304

repertoire turnover would be expected relative to timepoints taken 2 weeks apart, in a patient who did not 305

receive adjuvant chemotherapy and had serial blood samples for >1 year after surgery. Top 1% ITCs 306

detected in the peripheral blood underwent appreciable peripheral expansions and contractions during the 4 307

weeks of anti-PD-1 treatment (Fig. 2F, time window: pre-treatment to week 2; week 2 to week 4). Strikingly, 308

limited remodeling of the peripheral TCR repertoire was observed during the 6-month follow-up interval 309

relative to on-treatment timepoints (Fig. 2F, right panel), suggesting the systematic remodeling in the 310

peripheral repertoire is a direct, early effect of PD-1 pathway blockade. 311

Clonal expansion of ITCs in peripheral blood correlates with pathologic response 312

We next sought to identify the kinetic pattern and time window of TCR remodeling that correlates 313

with tumor regression upon PD-1 blockade. We recently detected peripheral expansion of neoantigen-314

specific peripheral T cell clonotypes that were also observed in high abundance in the post-treatment tumor 315

in a single patient with MPR (3). We therefore hypothesized that peripherally-expanded clones may home to 316

the tumor (primary and potentially undetected micrometastatic deposits) to produce the anti-tumor response. 317

Clonotypes undergoing contraction or expansion were identified in pairwise timepoints (pre-treatment vs 318

week 2; week 2 vs week 4) during neoadjuvant PD-1 blockade using methods previously described and 319

controlling for an FDR of 0.05 (18). A total of 689 dynamic clonotypes were found among 17 patients with 320

available serial blood samples (Fig. S7). Compared with non-dynamic clones, dynamic clones are more 321

likely to be intratumoral clones, regardless of MPR status (Fig. 3A) and clones that contracted in the 322

periphery between pre-treatment and week 2 were more likely to be in the tumor bed as compared to those 323




14

contracted at between weeks 2 to 4; in contrast, clones expanded between weeks 2 to 4 were more likely to 324

infiltrate the tumor bed (Fig. 3B). No difference was observed for the proportion of non-dynamic clones in 325

the tumor bed. Furthermore, the intratumoral clonal space of clones expanded between weeks 2 to 4 was 326

inversely correlated with residual tumor (Spearman's rank correlation, R=-0.62, P=0.041, Fig. 3C). 327

Because peripherally-dynamic clones are thought to be trafficking to the tumor, we tested if 328

intratumoral clonal occupancy of clones with differential peripheral patterns differentiates MPRs from non-329

MPRs. ITCs were stratified as peripherally contracted, expanded, non-dynamic, or tumor-resident only based 330

on their different dynamic patterns during treatment. There were no differences in the intratumoral clonal 331

space of peripherally contracted, expanded, or non-dynamic clones between pre-treatment to week 2 (Mann–332

Whitney U test, all p >0.05, Fig. S8). However, ITCs that specifically expanded between 2 to 4 weeks from 333

anti-PD-1 treatment initiation demonstrated a significantly greater clonal space in MPRs compared to non-334

MPRs (P = 0.018, Mann–Whitney U test, Fig. 3D), suggesting an enhanced anti-tumor response with the 335

influx or efflux of peripherally expanded clones. Moreover, no difference was observed in the intratumoral 336

clonal space of tumor-resident only clones between MPRs and non-MPRs (Fig. 3D), consistent with a 337

previous study suggesting low and variable tumor reactivity of the intrinsic tumor-resident TCR repertoire 338

(20). 339

To further interrogate the tumor-specific localization of expanded clones, we repeated the analysis on 340

clonotypes found in normal lung and observed no statistically significant difference in representation of 341

differential clonotypes between MPR and non-MPR (Fig. 3E), suggesting an enrichment of peripherally-342

expanded clones that are specifically concentrated within the tumor. In addition, we found the top 1% ITCs 343

of MPRs were preferentially constituted of peripheral clones expanded at week 2-4 (Fig. 3F) as compared to 344

non-MPRs (median, 17.7% vs 0.3%, Mann–Whitney U test, P=0.012). No differences in clonotype 345

composition among top 1% ITCs were observed for contracted, non-dynamic, or tumor-resident only clones 346

between MPRs vs non-MPRs (all P>0.1). Based on the above observations, we proposed the model that T 347




15

cell clones trafficking between the tumor and peripheral blood, particularly those differentially expanded at 348

2-4 weeks after PD-1 blockade may be responsible for tumor regression (Fig. 3G). 349

350

A complete pathologic responder is characterized by significant expansion of PD-1+ ITCs in the periphery 351

Our data suggest that PD-1 blockade rejuvenates pre-existing peripheral T cells that expand upon 352

treatment and accumulate in tumor tissues. As prior studies have demonstrated PD-1 expression to be 353

reflective of a subset of PD-1-blockade responsive, tumor-specific T cells, we examined the PD-1 expression 354

status of these expanded ITCs using TCRseq of sorted PD-1+ and PD-1

- peripheral blood T cells. This 355

analysis focused on two patients with extreme but opposite responses to neoadjuvant PD-1 blockade: a 356

complete pathologic responder, patient MD01-005, with 0% residual primary tumor with minimal tumor 357

involvement of an adjacent lymph node, and non-responding patient MD01-024, with 100% residual tumor. 358

In the pathologic responder (MD01-005), among the 5 top 1% ITCs that differentially expanded between 2-4 359

weeks after treatment initiation, all were found to be PD-1+ in the pre-treatment peripheral blood (4 PD-360

1+CD8

+ clones; 1 PD-1

+CD4

+ clone, Fig. 4A). These clonotypes were additionally found to be top 1% 361

clonotypes in a tumor-involved lymph node and a tumor draining lymph node obtained at the time of surgical 362

resection (Fig. 4A). PD-1 intraclonal positivity, defined as the percent of a unique clonotype that was found 363

within the PD-1+ population, was markedly high for all 5 clonotypes in MD01-005 (Fig. 4b, median: 99%, 364

range: 98%-100%). By contrast, for the non-responder (MD01-024), the 7 top 1% ITCs that expanded at 2-4 365

weeks demonstrated low PD-1 intraclonal positivity (median: 0.6%, range: 0.2%-20.6%, Fig.4C-D). 366

Moreover, these expanded clones in the tumor bed of the non-responder had a significantly lower proportion 367

in the tumor relative to normal lung (Paired Wilcoxon test, P=0.022, Fig. 4E). These results suggest that 368

peripheral expansion is indicative of activation and migration of PD1+ T cells into the tumor 369

microenvironment, which could subsequently facilitate pathologic response in the tumor bed. 370

371




16

Discussion 372

We recently identified neoantigen-specific T-cell clones in blood obtained prior to anti-PD-1, at the 373

pre-operative visit, and after surgery in a patient with MPR, with a transient expansion of these clones in 374

peripheral blood after treatment initiation (3,18). Based on this observation, we hypothesized that trafficking 375

of relevant T cell clones between the periphery, normal tissues, and tumor would be important for effecting 376

pathologic response. We therefore performed a comprehensive assessment of T cell repertoire and dynamics 377

in the neoadjuvant setting and further sought to determine if specific variables of clonal dynamics may be an 378

early biologic correlate of anti-tumor immunity. As such, we used pathologic response to PD-1 blockade as 379

an outcome. While longer follow-up will be necessary to determine how pathologic response correlates with 380

clinical outcome in lung cancer, reports in melanoma indicate that early pathologic responses to anti-PD-1 381

indeed correlate with improved survival (21,22). 382

In this study, we use the TCR as a barcode to track clonal sharing and dynamics and observed a 383

positive association between intra-tumoral T cell repertoire clonality and pathologic tumor regression at 384

surgery. Although we did not observe significant global changes in clonality of the peripheral TCR repertoire 385

throughout the 4 weeks of treatment, we determined that the most significant parameter that differentiates 386

MPRs from non-MPRs is the clonal space occupied by the most frequent, i.e. top 1% frequency-ranked, 387

ITCs, which demonstrated systematic perturbations in frequency in the periphery upon PD-1 blockade. More 388

interestingly, our results showed that the top 1% ITCs were observed to be highly shared in both peripheral 389

blood and normal lung tissue from the same patient. Furthermore, the level of clonal sharing of ITCs with 390

blood and normal lung was significantly higher in MPR patients relative to non-MPR patients, whereas non-391

MPRs had more tumor-resident only ITCs, consistent with the notion that intrinsic tumor-resident T cell 392

repertoire may likely to be exhausted with low tumor reactivity and that the T cell response to checkpoint 393

blockade may derive from re-invigorated T cells that recently entered the tumor (23). Whereas the 394

observation that non-MPRs have more clones that are restricted in the tumor bed implicates potential 395

deficiency in replenishment by the peripheral T cell repertoire. 396




17

We additionally systematically characterized the dynamic pattern of ITCs in longitudinal blood. We 397

found that significant dynamic changes in frequency of shared peripheral clones, regardless of their dynamic 398

nature (contraction or expansion), associated with increased tumor infiltration, suggesting an active 399

compartmental exchange of ITCs induced by neoadjuvant PD-1 blockade. Notably, peripherally expanded 400

ITCs at week 2-4 from initiation of anti-PD-1 preferentially occupy a greater clonal space in the tumor bed 401

of MPRs relative to non-MPRs. This observation highlights the importance of effective peripheral activation 402

in promoting pathologic response. On the contrary, we observed that non-MPR tumors do not successfully 403

traffic top 1% ITCs to the tumor bed, possibly due to an intrinsically more exhausted, less migratory T cell 404

repertoire. These clones, when trapped in the tumor, could experience inhibited reinvigoration upon PD-1 405

blockade owing to an immunosuppressive tumor microenvironment. Therefore, detection of tumor 406

infiltrating clones’ expansion in the peripheral blood may be an early biological correlate of anti-tumor T cell 407

recognition and the peripheral blood may be a valuable compartment for monitoring early T cell responses to 408

PD-1 blockade. 409

Supporting the notion that dynamics of shared clones are relevant to outcomes of PD-1 blockade, we 410

demonstrated that expanded clonotypes in a patient with a complete pathologic response exhibited extremely 411

high intraclonal PD-1 positivity, in contrast to a patient with no pathologic response, whose expanded 412

clonotypes exhibited very low frequencies of PD-1 positivity. While anti-PD-1 has been reported to 413

reinvigorate peripheral T cell clones that are also present in the tumor (24), our study further suggests that 414

anti-PD-1 may induce an exchange of reinvigorated effector PD1+ T cells between the periphery and tumor, 415

where they contribute to tumor regression. We recently showed that in Stage 4 NSCLC treated with anti-PD-416

1, general expansion in the blood of all clones found in pre-treatment tumors correlated with radiographic 417

response and clearance of circulating tumor DNA (14). Here we show in the neoadjuvant setting that 418

peripheral expansion of the most frequent ITCs (top 1% frequency) correlates much more closely with the 419

pathologic response at the time of resection. 420




18

Although a limited number of patients has been included in our analysis, we performed an in-depth 421

integration of the intra-tumoral anti-tumor repertoire and peripheral T cell repertoire. Larger cohorts are 422

warranted to evaluate these features as predictive markers for response to neoadjuvant PD-1 blockade and 423

relapse-free survival. However, we acknowledge that the median duration of recurrence-free survival has not 424

been reached in this cohort and we are therefore unable to assess the association of TCR dynamics with 425

survival. Additionally, while our approach utilizing TCR β chain sequencing is a common approach owing to 426

1) greater diversity of the β chain relative to the α chain, 2) stricter allelic exclusion of the β locus, and 3) 427

technical ease of performing TCRseq on the β chain, we recognize that single cell paired αβ sequencing 428

approaches should be employed in future studies aimed at determining the antigen specificity or function of 429

these T cells. Similarly, a limitation of our study is that we did not differentiate between CD4+ and CD8

+ T 430

cell clones. While traditionally, CD8+ T cell infiltration has been associated with improved prognosis in 431

untreated/pre-treatment tumor specimens, it is important to note that our specimens were obtained after 432

neoadjuvant PD-1 blockade and the association of CD4+ vs. CD8

+ T cell infiltration with pathologic response 433

or clinical outcome has not been systematically evaluated in this setting. To that end, ascertaining the CD4 434

vs. CD8 identity of these T cells would also be useful in determining function in future studies. Correlation 435

with ‘Immune-Related Pathologic Response Criteria’ (irPRC) (25), a newly proposed pathologic assessment 436

of residual tumor in immunotherapy, should also be explored if validated as a surrogate for recurrence-free 437

and overall survival. Efforts to extrapolate the current findings to patients with metastatic disease should be 438

met with caution, as we are specifically evaluating tumor-infiltrating T cells after PD-1 blockade in patients 439

with resectable disease. However, our results have important implications for establishment of predictive 440

biomarkers through liquid biopsy approaches. In conclusion, our study shows that TCR profiling holds 441

promise for monitoring anti-tumor responses in the periphery and will spur future development of 442

biomarkers to predict response to immunotherapy and to guide what additional therapies may be warranted 443

after surgical resection. 444

445




19

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25. Cottrell TR, Thompson ED, Forde PM, Stein JE, Duffield AS, Anagnostou V, et al. Pathologic 514

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2018;29:1853-60 517

518

Acknowledgments: We would like to thank the patients and their families for participation in this study, 519

as well as Chanice Barkley, Iiasha Beadles, and members of our respective research and administrative 520

teams who contributed to this study. 521

Author contributions: J.Z., Z.J., H.J. and K.N.S. designed the correlative study and developed 522

hypotheses; J.Z., and Z.J. led data analysis. H.J. mentored the data analysis. J.Z., Z.J., J.X.C., M.A., 523

J.W.S., N.Z., and K.N.S interpreted the data. J.X.C. M.A., H.Y.C., P.S., and H.G. processed the samples 524

for TCR sequencing. V.A and V.E.V. performed whole exome sequencing and variant calling. A.T. and 525

R.B. designed and performed flow cytometric sorting experiments. T.R.C., E.G., and J.T. reviewed the 526

pathologic response for all patients. J.E.C., J.R., K.A.M., J.N., M.D.H., P.M.F. and J.R.B. assisted with 527

enrollment, clinical treatment, evaluation, and clinical annotation of the patients described herein. T.M., 528

K.N.S., and V.A. led sample acquisition. J.Z., Z.J., J.X.C., M.A., and K.N.S. wrote the manuscript. F.H., 529




21

M.D.H., P.M.F., D.M.P., H.J, and K.N.S provided critical revisions on the manuscript. All authors 530

reviewed and approved the final version of the manuscript. 531

532

Figure legends 533

534

Figure 1. Clonality of the TCR repertoire and association with the anti-tumor response. A. Flow chart 535

of the phase 2 clinical trial and biospecimen collection, along with correlative studies performed at each 536

timepoint. B. Correlation between productive clonality in the tumor bed at the time of resection (after anti-537

PD-1) with the number of non-synonymous sequence alterations (Spearman’s rho, 0.70; P=0.025). Each 538

patient is represented by a black dot (n=10). The blue line indicates the linear regression line, and the gray 539

area indicates the upper and lower boundaries of the 95% confidence interval. C. Correlation between 540

productive clonality in the post-treatment tumor bed and the percent residual tumor (n=10, Spearman’s rho, -541

0.65; P=0.041).The blue line indicates the linear regression line, and the gray area indicate the upper and 542

lower boundaries of the 95% confidence interval. Productive clonality: Clonality as determined by using the 543

productive amino acid (AA) sequence of the CDR3. D. Productive clonality of the TCR repertoire in the 544

post-treatment tumor bed and normal lung for patients with major pathologic response (MPRs; blue) and 545

without MPR (non-MPR; red). E, Occupied clonal space (the total frequency among all intratumoral T cells) 546

of ITCs according to their percent rank (top 1% ranked ITCs vs top 1-2% ranked ITCs vs top 2-5% ranked 547

ITCs vs >5% ranked ITCs) in the post-treatment tumor bed of each patient. F. Comparison of the clonal 548

space occupied by ITCs segregated by frequency-ranks between MPRs (n=9) and non-MPRs (n=5). 549

550

Figure 2. Dynamics of ITCs across tissue compartments and in longitudinal peripheral blood. A. 551

Proportion of ITCs shared between pre-treatment blood and normal lung, comparing non-top 1% ITCs (blue) 552

and top 1% ITCs (red) (n=14). B. Top 1% ITCs shared between pre-treatment blood and resected normal 553

lung, comparing MPRs (blue) and non-MPRs (red) (n=14). C. Proportion of top 1% ITCs by their shared 554

compartment (pre-treatment blood+resected normal lung, pretreatment blood, resected normal lung, and 555

tumor resident only). D. Clonal space of top 1% ITCs by shared compartment between MPRs and non-MPRs 556

(n=14). The proportion of top 1% ITCs that are shared with the pre-treatment peripheral blood and resected 557

normal lung is higher in MPRs vs. non-MPRs. However, an inverse correlation was observed for top 1% 558

frequency-ranked ITCs that were only found in the tumor bed. E. Temporal dynamics of the ITCs in the 559

longitudinal blood (n=14). The percent change of top 1% ITCs shared with the peripheral repertoire over 560

time was calculated as compared to pre-treatment blood. Data show the mean +/- standard error for all 561

patients (left panel) and by MPRs vs. non-MPRs (right panel) for top 1% ITCs (red) and non-top 1% ITCs 562

(blue). F. The pattern and degree of peripheral remodeling at week 2 and week 4 following treatment 563

initiation for all patients. The fold change of each clonotype was calculated, and the means of the fold 564

change were plotted on a logarithmic scale (log10), stratified by the abundance ranks in the post-treatment 565

tumor bed (n=14). The left and right panels show the dynamic magnitude in clones that underwent peripheral 566

expansion and contraction, respectively. *: p <= 0.05, **: p <= 0.01, ***: p <= 0.001, ****: p <= 0.0001. G. 567

The dynamic peripheral reshaping of individual TCR Vβ clonotypes for a representative patient (MD043-568

003, 5% residual tumor) during treatment and in long term follow up is shown. Each point on the scatter 569

plots represents a single clonotype with normalized log10 clone frequency graphed at pairwise timepoints. 570

The size of the dot represents the frequency in the tumor bed and clones are designated as top 1% ITCs(red), 571

non-top 1% ITCs (blue), or PBMC only (gray). Clones that underwent contraction are found below the x=y 572

diagonal, whereas those expanded are found above the diagonal. To account for clones that were only 573

present in one sample, the frequency was recalculated by adding a pseudo count of 20 to all clonotype 574

counts. 575

576




22

Fig. 3. Differentially dynamic clones and their association with tumor infiltration and tumor 577

accumulation. A. The proportion of dynamic clones vs non-dynamic clones that infiltrated tumor bed upon 578

PD-1 blockade in MPR and non-MPR (n=12). B. The total proportion of clones in the tumor is shown for 579

significantly contracted clones, significantly expanded clones, and non-dynamic clones at week 2 (dark grey) 580

and week 4 (light grey) after treatment initiation (n=12). C. Association of intratumoral clonal space of 581

peripherally expanded clones and percent residual tumor by time window (pre-treatment~W2, Spearman’s 582

rho=-0.35, W2~W4 Spearman’s rho=-0.62). Each patient is represented by a black dot. The blue line 583

indicates the robust linear regression line (fitted using R function ‘rlm’ from ‘MASS’ package based on M 584

estimator), and the gray area indicates the upper and lower boundaries of the 95% confidence interval 585

(n=12). D. The clonal space occupied by ITCs with different peripheral dynamic patterns (expanded, 586

contracted, non-dynamic or tumor resident-only) at 2-4 weeks after immunotherapy initiation is shown for 587

MPRs and non-MPRs (n=12). E. The clonal space occupied by normal lung T cells with differential patterns 588

in the periphery is shown for MPRs and non-MPRs at 2-4 weeks after treatment initiation (n=12). F. The 589

proportion of top 1% ITCs and their peripheral dynamic pattern at 2-4 weeks after treatment initiation for 590

MPRs and non-MPRs (n=12). G. Proposed schema of peripheral activation of the anti-tumor repertoire 591

homing back to the tumor bed. ns, not significant . *: p <= 0.05, **: p <= 0.01, ***: p <= 0.001. 592

593

Figure 4. PD1 sorting revealed differential patterns of intra-clonal PD1+ positivity between complete 594

pathologic responder and non-responder. A. TCRseq was performed on sorted PD-1 positive and negative 595

CD4+ and CD8

+ peripheral blood T cells obtained from patient MD01-005 (0% residual tumor) prior to 596

treatment (left panel). The frequency of clonotypes detected in the PD-1+ population is shown in serial 597

peripheral blood (center) and biopsied and resected tissues (right) is shown. All 5 differentially expanded 598

ITCs identified in this patient were detected in the PD1+

sorted population. B. Pie charts showing the intra-599

clonal PD-1 positivity (the proportion of total reads of each clone that was detected in the PD-1+ vs. PD-1

- 600

sorted population) for the 5 peripherally expanded, top 1% ITCs is shown. C. TCRseq was performed on 601

sorted PD-1 positive and negative CD4+ and CD8+ peripheral blood T cells obtained from patient MD01-602

024 (100% residual tumor) prior to treatment (left panel). The frequency of clonotypes detected in the PD-1+ 603

population is shown in serial peripheral blood (center) and resected tissues (right). D. Pie charts showing the 604

intraclonal PD-1 positivity for peripherally expanded, top 1 % ITCs. E. The read proportion of top 1% ITCs 605

in the normal lung and tumor bed is shown for patient MD01-005 and patient MD01-024. Comparisons 606

between normal lung and tumor bed were evaluated using the Wilcoxon signed-rank test. 607

608

609

610




Published OnlineFirst November 21, 2019.Clin Cancer Res Jiajia Zhang, Zhicheng Ji, Justina X Caushi, et al. resectable non-small cell lung cancerof pathologic response to neoadjuvant PD-1 blockade in Compartmental analysis of T cell clonal dynamics as a function

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