Understanding of the functional states and clonal dynamics of T cells after immune checkpoint blockade (ICB) is valuable for improving these therapeutic strategies. Here we performed Smart-seq2 single-cell RNA sequencing (scRNA-seq) analysis on 3,110 peripheral T cells of non-small cell lung cancer (NSCLC) patients before and after the initiation of programmed cell death protein 1 (PD-1) blockade. We identified individual peripheral T cell clones based on the full-length T cell receptor (TCR) sequences and monitored their dynamics during immunotherapy. We found a higher cytotoxic activity in the tumor-related CD4+ T cell clones than in the CD8+ T cell clones. Based on a large tumor-related CD4+ T cell clone, we observed a dramatically decreased abundance after progression, as well as a reduction in the percentage of PD-1+ T cells. We also detected 25 genes, such as CXCR4, DUSP2 and ZFP36, that were noticeably upregulated or downregulated following progression. In addition, the pseudotime trajectory of CD8+ T cell clones corresponded to the treatment time points, showing a decreased activity in the “cytokine and cytokine receptor interaction” pathway. These analyses provided an insight into the dynamics of peripheral T cell clones during PD-1 blockade in NSCLC.
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Sequencing raw data is available at GSA (Genome Sequence Archive in BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences). The accession number is HRA000104. Gene expression profiling of individual T cell clones at different time points can be explored on https://22.214.171.124:3838/lcpd.
Differentially expressed gene
Immune checkpoint blockade
Non-small cell lung cancer
Programmed cell death protein 1
Programmed death-ligand 1
Single-cell RNA sequencing
T cell receptor
Ribas A, Wolchok JD (2018) Cancer immunotherapy using checkpoint blockade. Science 359:1350–1355. https://doi.org/10.1126/science.aar4060
Tumeh PC, Harview CL, Yearley JH et al (2014) PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature 515:568–571. https://doi.org/10.1038/nature13954
Chen P-L, Roh W, Reuben A et al (2016) Analysis of immune signatures in longitudinal tumor samples yields insight into biomarkers of response and mechanisms of resistance to immune checkpoint blockade. Cancer Discov 6:827–837. https://doi.org/10.1158/2159-8290.CD-15-1545
Ayers M, Lunceford J, Nebozhyn M et al (2017) IFN-γ–related mRNA profile predicts clinical response to PD-1 blockade. J Clin Invest 127:2930–2940. https://doi.org/10.1172/JCI91190
Prat A, Navarro A, Paré L et al (2017) Immune-related gene expression profiling after pd-1 blockade in non-small cell lung carcinoma, head and neck squamous cell carcinoma, and melanoma. Cancer Res 77:3540–3550. https://doi.org/10.1158/0008-5472.CAN-16-3556
Riaz N, Havel JJ, Makarov V et al (2017) Tumor and microenvironment evolution during immunotherapy with nivolumab. Cell 171:934–949. https://doi.org/10.1016/j.cell.2017.09.028
Daud AI, Wolchok JD, Robert C et al (2016) Programmed death-ligand 1 expression and response to the anti-programmed death 1 antibody pembrolizumab in melanoma. J Clin Oncol 34:4102–4109. https://doi.org/10.1200/JCO.2016.67.2477
Huang AC, Postow MA, Orlowski RJ et al (2017) T-cell invigoration to tumour burden ratio associated with anti-PD-1 response. Nature 545:60–65. https://doi.org/10.1038/nature22079
Jerby-Arnon L, Shah P, Cuoco MS et al (2018) A cancer cell program promotes T cell exclusion and resistance to checkpoint blockade. Cell 175:984–997.e24. https://doi.org/10.1016/j.cell.2018.09.006
Paulson KG, Voillet V, McAfee MS et al (2018) Acquired cancer resistance to combination immunotherapy from transcriptional loss of class I HLA. Nat Commun 9:3868. https://doi.org/10.1038/s41467-018-06300-3
Skoulidis F, Goldberg ME, Greenawalt DM et al (2018) STK11/LKB1 mutations and PD-1 inhibitor resistance in KRAS-Mutant lung adenocarcinoma. Cancer Discov 8:822–835. https://doi.org/10.1158/2159-8290.CD-18-0099
Zaretsky JM, Garcia-Diaz A, Shin DS et al (2016) Mutations associated with acquired resistance to PD-1 blockade in melanoma. N Engl J Med 375:819–829. https://doi.org/10.1056/NEJMoa1604958
Finotello F, Trajanoski Z (2018) Quantifying tumor-infiltrating immune cells from transcriptomics data. Cancer Immunol Immunother 67:1031–1040. https://doi.org/10.1007/s00262-018-2150-z
Guo X, Zhang Y, Zheng L et al (2018) Global characterization of T cells in non-small-cell lung cancer by single-cell sequencing. Nat Med 24:978–985. https://doi.org/10.1038/s41591-018-0045-3
Zhang L, Yu X, Zheng L et al (2018) Lineage tracking reveals dynamic relationships of T cells in colorectal cancer. Nature 564:268–272. https://doi.org/10.1038/s41586-018-0694-x
Zheng C, Zheng L, Yoo J-K et al (2017) Landscape of Infiltrating T cells in liver cancer revealed by single-cell sequencing. Cell 169:1342–1356.e16. https://doi.org/10.1016/j.cell.2017.05.035
Sharma P, Hu-Lieskovan S, Wargo JA, Ribas A (2017) Primary, adaptive, and acquired resistance to cancer immunotherapy. Cell 168:707–723. https://doi.org/10.1016/j.cell.2017.01.017
Anagnostou V, Forde PM, White JR et al (2019) Dynamics of tumor and immune responses during immune checkpoint blockade in non-small cell lung cancer. Cancer Res 79:1214–1225. https://doi.org/10.1158/0008-5472.CAN-18-1127
Osa A, Uenami T, Koyama S et al (2018) Clinical implications of monitoring nivolumab immunokinetics in non-small cell lung cancer patients. JCI Insight 3:e59125
Wang Z, Duan J, Cai S et al (2019) Assessment of blood tumor mutational burden as a potential biomarker for immunotherapy in patients with non-small cell lung cancer with use of a next-generation sequencing cancer gene panel. JAMA Oncol 5:696–702. https://doi.org/10.1001/jamaoncol.2018.7098
Szolek A, Schubert B, Mohr C et al (2014) OptiType: precision HLA typing from next-generation sequencing data. Bioinformatics 30:3310–3316. https://doi.org/10.1093/bioinformatics/btu548
Jurtz V, Paul S, Andreatta M et al (2017) NetMHCpan-4.0: Improved peptide–MHC class I interaction predictions integrating eluted ligand and peptide binding affinity data. J Immunol 199:3360–3368. https://doi.org/10.4049/jimmunol.1700893
Picelli S, Faridani OR, Björklund ÅK et al (2014) Full-length RNA-seq from single cells using smart-seq2. Nat Protoc 9:171–181. https://doi.org/10.1038/nprot.2014.006
Bray NL, Pimentel H, Melsted P, Pachter L (2016) Near-optimal probabilistic RNA-seq quantification. Nat Biotechnol 34:525–527. https://doi.org/10.1038/nbt.3519
Kiselev VY, Kirschner K, Schaub MT et al (2017) SC3: consensus clustering of single-cell RNA-seq data. Nat Methods 14:483–486. https://doi.org/10.1038/nmeth.4236
Stubbington MJT, Lönnberg T, Proserpio V et al (2016) T cell fate and clonality inference from single-cell transcriptomes. Nat Methods 13:329–332. https://doi.org/10.1038/nmeth.3800
Qiu X, Hill A, Packer J et al (2017) Single-cell mRNA quantification and differential analysis with Census. Nat Methods 14:309–315. https://doi.org/10.1038/nmeth.4150
Hunter KA, Socinski MA, Villaruz LC (2018) PD-L1 testing in guiding patient selection for PD-1/PD-L1 inhibitor therapy in lung cancer. Mol Diagn Ther 22:1–10. https://doi.org/10.1007/s40291-017-0308-6
Rizvi NA, Hellmann MD, Snyder A et al (2015) Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer. Science 348:124–128. https://doi.org/10.1126/science.aaa1348
Hidalgo LG, Einecke G, Allanach K, Halloran PF (2008) The Transcriptome of human cytotoxic T cells: similarities and disparities among allostimulated CD4+ CTL, CD8+ CTL and NK cells. Am J Transplant 8:627–636. https://doi.org/10.1111/j.1600-6143.2007.02128.x
Thommen DS, Koelzer VH, Herzig P et al (2018) A transcriptionally and functionally distinct PD-1 + CD8 + T cell pool with predictive potential in non-small-cell lung cancer treated with PD-1 blockade. Nat Med 24:994–1004. https://doi.org/10.1038/s41591-018-0057-z
Osa A, Uenami T, Koyama S et al (2018) Clinical implications of monitoring nivolumab immunokinetics in non–small cell lung cancer patients. JCI 3:12. https://doi.org/10.1172/jci.insight.59125
Gros A, Parkhurst MR, Tran E et al (2016) Prospective identification of neoantigen-specific lymphocytes in the peripheral blood of melanoma patients. Nat Med 22:433–438. https://doi.org/10.1038/nm.4051
Wu TD, Madireddi S, de Almeida PE et al (2020) Peripheral T cell expansion predicts tumour infiltration and clinical response. Nature 579:274–278. https://doi.org/10.1038/s41586-020-2056-8
Fairfax BP, Taylor CA, Watson RA et al (2020) Peripheral CD8 + T cell characteristics associated with durable responses to immune checkpoint blockade in patients with metastatic melanoma. Nat Med 26:193–199. https://doi.org/10.1038/s41591-019-0734-6
Burger JA, Kipps TJ (2006) CXCR4: a key receptor in the crosstalk between tumor cells and their microenvironment. Blood 107:1761–1767. https://doi.org/10.1182/blood-2005-08-3182
Peng L, Zhuang Y, Shi Y et al (2012) Increased tumor-infiltrating CD8+Foxp3+ T lymphocytes are associated with tumor progression in human gastric cancer. Cancer Immunol Immunother 61:2183–2192. https://doi.org/10.1007/s00262-012-1277-6
Righi E, Kashiwagi S, Yuan J et al (2011) CXCL12/CXCR4 blockade induces multimodal anti-tumor effects that prolong survival in an immunocompetent mouse model of ovarian cancer. Cancer Res 71:5522–5534. https://doi.org/10.1158/0008-5472.CAN-10-3143
Scala S (2015) Molecular pathways: targeting the CXCR4–CXCL12 axis—untapped potential in the tumor microenvironment. Clin Cancer Res 21:4278–4285. https://doi.org/10.1158/1078-0432.CCR-14-0914
Rohan PJ, Davis P, Moskaluk CA et al (1993) PAC-1: a mitogen-induced nuclear protein tyrosine phosphatase. Science 259:1763–1766. https://doi.org/10.1126/science.7681221
Schietinger A, Delrow JJ, Basom RS et al (2012) Rescued tolerant cd8 t cells are preprogrammed to reestablish the Tolerant State. Science 335:723–727. https://doi.org/10.1126/science.1214277
Carballo E, Lai WS, Blackshear PJ (1998) Feedback inhibition of macrophage tumor necrosis factor-α production by Tristetraprolin. Science 281:1001–1005. https://doi.org/10.1126/science.281.5379.1001
Raghavan A, Robison RL, McNabb J et al (2001) HuA and tristetraprolin are induced following T cell activation and display distinct but overlapping rna binding specificities. J Biol Chem 276:47958–47965. https://doi.org/10.1074/jbc.M109511200
Moore MJ, Blachere NE, Fak JJ et al (2018) ZFP36 RNA-binding proteins restrain T cell activation and anti-viral immunity. ELife 7:3–57
Wang X, He Y, Zhang Q et al (2019) Direct comparative analysis of 10x genomics chromium and smart-seq2. BioRxiv 61:5–13
We thank Xuefang Zhang and Fei Wang for assistance with flow cytometry. We thank the Computing Platform of the CLS (Peking University).
This project was supported by Beijing Advanced Innovation Center for Genomics at Peking University, National Natural Science Foundation of China (31530036, 91742203, 91942307, 81988101, 81630071), National Key Research and Development Project (2019YFC1315700) and CAMS Innovation Fund for Medical Sciences (CIFMS 2016-I2M-3-008).
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The authors report no financial interests or potential conflicts of interests.
This study was approved by the Research and Ethical Committee of Cancer Hospital, Chinese Academy of Medical Sciences, China and complied with relevant ethical regulations.
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Zhang, F., Bai, H., Gao, R. et al. Dynamics of peripheral T cell clones during PD-1 blockade in non-small cell lung cancer. Cancer Immunol Immunother (2020). https://doi.org/10.1007/s00262-020-02642-4
- Cancer immunotherapy
- Single cell sequencing
- Non-small cell lung cancer