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TCR Repertoire Diversity of Peripheral PD-1+CD8+ T Cells Predicts Clinical Outcomes after Immunotherapy in Patients with Non–Small Cell Lung Cancer

Jiefei Han, Jianchun Duan, Hua Bai, Yuqi Wang, Rui Wan, Xin Wang, Si Chen, Yanhua Tian, Di Wang, Kailun Fei, Zhuoran Yao, Shuhang Wang, Zhimin Lu, Zhijie Wang and Jie Wang
Jiefei Han
1State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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Jianchun Duan
1State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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Hua Bai
1State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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Yuqi Wang
2Geneplus-Beijing Institute, Beijing, China.
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Rui Wan
1State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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Xin Wang
1State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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Si Chen
2Geneplus-Beijing Institute, Beijing, China.
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Yanhua Tian
1State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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Di Wang
1State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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Kailun Fei
1State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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Zhuoran Yao
1State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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Shuhang Wang
3GCP Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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Zhimin Lu
4State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
5Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
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  • For correspondence: zlhuxi@163.com Jie_969@163.com zlumdacc@yahoo.com
Zhijie Wang
1State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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  • For correspondence: zlhuxi@163.com Jie_969@163.com zlumdacc@yahoo.com
Jie Wang
1State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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  • For correspondence: zlhuxi@163.com Jie_969@163.com zlumdacc@yahoo.com
DOI: 10.1158/2326-6066.CIR-19-0398 Published January 2020
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    Figure 1.

    Flowchart describing patient participation in the study. PD, progressive disease; PR, partial response; SD, stable disease.

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    Figure 2.

    Correlations of TCR diversity with the response and PFS associated with PD-1 or PD-L1 inhibitors. A, Comparison of PD-1+ CD8+ TCR diversity between the DC and PD subgroups after PD-1/PD-L1 inhibitor treatment in the discovery set (n = 25). B, An ROC curve was used to distinguish PD cases from DC cases in the discovery set (n = 25). C, PFS stratified by PD-1+ CD8+ TCR diversity in the discovery set (n = 25). D, PFS stratified by PD-1+ CD8+ TCR diversity in the validation set (n = 15). E, OS stratified by PD-1+ CD8+ TCR diversity in the discovery set (n = 25). F, OS stratified by PD-1+ CD8+ TCR diversity in the validation set (n = 15). G, Sensitivity and specificity of TCR diversity for determining the clinical response (DC vs. PD) to PD-1 or PD-L1 inhibitors (n = 40; DC, n = 23, and PD, n = 17).

  • Figure 3.
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    Figure 3.

    Cox regression model assessing the correlation of clinical variables with PFS (A) and OS (B). LUAD, lung adenocarcinoma; LUSC,lung squamous cell carcinoma.

  • Figure 4.
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    Figure 4.

    A, Comparison of TCR diversity in PBMCs between the DC and PD subgroups after PD-1/PD-L1 inhibitor treatment (n = 18). B, PFS stratified by TCR diversity in PBMCs (n = 18).

  • Figure 5.
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    Figure 5.

    Correlations of the dynamic changes in TCR clonality with the response and PFS associated with PD-1 or PD-L1 inhibitors (n = 19). A, Waterfall plot of the best observed response to PD-1/PD-L1 inhibitors and the corresponding change in PD-1+ CD8+ TCR clonality. B, Dynamic changes in PD-1+ CD8+ TCR clonality and the corresponding changes in the MVAF in cfDNA. MVAF indicates the maximum variant allele frequency based on the response to PD-1/PD-L1 inhibitors. C, The response to immunotherapy based on changes in TCR clonality. D, PFS stratified by dynamic changes in PD-1+ CD8+ TCR clonality (increased vs. decreased). PsPD, pseudo PD. E, OS stratified by dynamic changes in PD-1+ CD8+ TCR clonality (increased vs. decreased).

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    Figure 6.

    Representative evolutionary patterns of peripheral PD-1+ CD8+ TCR V-β gene families based on the best observed response to PD-1 or PD-L1 inhibitors. A, The dominant TRBV clones in patient no. 10 with PD from pre-ICB to post-ICB. B, The dominant TRBV clones in patient no. 32 with SD from pre-ICB to post-ICB. C, The dominant TRBV clones in patient no. 12 with PR from pre-ICB to post-ICB. D, The dominant TRBV clones in patient no. 3 with pseudo-PD from pre-ICB to post-ICB.

Tables

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  • Table 1.

    Patient sets and baseline characteristics.

    Number/total number (%)
    VariableTotal (N = 40)Discovery set (n = 25)Validation set (n = 15)P value
    Age, y
     ≥6520 (50.0)12 (48.0)8 (53.3)0.744
     <6520 (50.0)13 (52.0)7 (46.7)
    Gender
     Male32 (80.0)21 (84.0)11 (73.3)0.683
     Female8 (20.0)4 (16.0)4 (26.7)
    Smoking history
     Current/former30 (75.0)19 (76.0)11 (73.3)1.000
     Never/light10 (25.0)6 (24.0)4 (26.7)
    Histology
     Adenocarcinoma24 (60.0)16 (64.0)8 (53.3)0.138
     Squamous16 (40.0)9 (36)7 (46.7)
    ECOG score
     <236 (90.0)22 (88.0)14 (93.3)1.000
     ≥24 (10.0)3 (12.0)1 (6.7)
    Kind of immunotherapy
     Anti–PD-132 (80.0)18 (72.0)14 (93.3)0.221
     Anti–PD-L18 (20.0)7 (28.0)1 (6.7)
    Stage of disease
     IIIB4 (10.0)3 (12.0)1 (6.7)1.000
     IV36 (90.0)22 (88.0)14 (93.3)
    Number of prior lines of treatment
     123 (57.5)13 (52.0)10 (66.7)0.364
     ≥217 (42.5)12 (48.0)5 (33.3)
    • Abbreviation: ECOG, Eastern Cooperative Oncology Group.

Additional Files

  • Figures
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  • Supplementary Data

    • Legend for the Supplementary Figures and Tables - Legend for the Supplementary Figures and Tables
    • Supplementary Fig. S1-S5 - Supplementary Figures 1-5
    • Supplementary Table S1 - Details on the genes included in the 1021 gene panel in next-generation sequencing (NGS).
    • Supplementary Table S2 - Univariable and multivariable analysis of progression-free survival (PFS).
    • Supplementary Table S3 - Baseline characteristics of patients in the exploratory group (discovery set and validation set) and the control group.
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Cancer Immunology Research: 8 (1)
January 2020
Volume 8, Issue 1
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TCR Repertoire Diversity of Peripheral PD-1+CD8+ T Cells Predicts Clinical Outcomes after Immunotherapy in Patients with Non–Small Cell Lung Cancer
Jiefei Han, Jianchun Duan, Hua Bai, Yuqi Wang, Rui Wan, Xin Wang, Si Chen, Yanhua Tian, Di Wang, Kailun Fei, Zhuoran Yao, Shuhang Wang, Zhimin Lu, Zhijie Wang and Jie Wang
Cancer Immunol Res January 1 2020 (8) (1) 146-154; DOI: 10.1158/2326-6066.CIR-19-0398

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TCR Repertoire Diversity of Peripheral PD-1+CD8+ T Cells Predicts Clinical Outcomes after Immunotherapy in Patients with Non–Small Cell Lung Cancer
Jiefei Han, Jianchun Duan, Hua Bai, Yuqi Wang, Rui Wan, Xin Wang, Si Chen, Yanhua Tian, Di Wang, Kailun Fei, Zhuoran Yao, Shuhang Wang, Zhimin Lu, Zhijie Wang and Jie Wang
Cancer Immunol Res January 1 2020 (8) (1) 146-154; DOI: 10.1158/2326-6066.CIR-19-0398
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