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Elimination of acquired resistance to PD-1 blockade via the concurrent depletion of tumour cells and immunosuppressive cells

Nature Biomedical Engineering volume 5, pages 1306–1319 (2021)Cite this article

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Abstract

Antigen release resulting from the death of tumour cells induced by chemotherapies and targeted therapies can augment the antitumour responses induced by immune checkpoint blockade (ICB). However, tumours responding to ICB therapies often become resistant to them. Here we show that the specific targeting of tumour cells promotes the growth of tumour-cell variants that are resistant to ICB, and that the acquired resistance can be overcome via the concurrent depletion of tumour cells and of major types of immunosuppressive cell via a monoclonal antibody binding the enzyme CD73, which we identified as highly expressed on tumour cells and on regulatory T cells, myeloid-derived suppressor cells and tumour-associated macrophages, but not on cytolytic T lymphocytes, natural killer cells and dendritic cells. In mice with murine tumours, the systemic administration of anti-PD1 antibodies and anti-CD73 antibodies conjugated to a near-infrared dye prevented near-infrared-irradiated tumours from acquiring resistance to ICB and resulted in the eradication of advanced tumours. The elimination of immunosuppressive cells may overcome acquired resistance to ICB across a range of tumour types and combination therapies.

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Fig. 1: Relapse of resistant tumours is inevitable when merely targeting tumour-expressed antigen.
Fig. 2: Targeting CD73 specifically kills cancer cells and all major types of immunosuppressive cell.
Fig. 3: Targeting CD73+ cells modifies the tumour immune landscape and bolsters CTL responses in vivo.
Fig. 4: Local αCD73-Dye + NIR irradiation favours systemic CTL responses.
Fig. 5: αCD73-Dye + NIR irradiation synergizes with αPD-1 ICB to promote curative responses.
Fig. 6: Targeting all major types of immunosuppressive cell in tumours is indispensable to the curative response.
Fig. 7: αCD73-Dye + NIR irradiation synergizes with αPD-1 to eradicate spontaneous TNBCs.

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Data availability

The main data supporting the results in this study are available within the paper and its Supplementary Information. The raw and analysed datasets generated during the study are too large to be publicly shared, but they are available for research purposes from the corresponding author on reasonable request. Source data are provided with this paper.

References

  1. Reck, M. et al. Pembrolizumab versus chemotherapy for PD-L1-positive non-small-cell lung cancer. N. Engl. J. Med. 375, 1823–1833 (2016).

    Article  CAS  PubMed  Google Scholar 

  2. Hodi, F. S. et al. Improved survival with ipilimumab in patients with metastatic melanoma. N. Engl. J. Med. 363, 711–723 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Adams, S. et al. Phase 2 study of pembrolizumab (pembro) monotherapy for previously treated metastatic triple-negative breast cancer (mTNBC): KEYNOTE-086 cohort A. J. Clin. Oncol. 35, 1008 (2017).

  4. Vonderheide, R. H. et al. Tremelimumab in combination with exemestane in patients with advanced breast cancer and treatment-associated modulation of inducible costimulator expression on patient T cells. Clin. Cancer Res. 16, 3485–3494 (2010).

    Article  CAS  PubMed  Google Scholar 

  5. Patnaik, A. et al. Phase I study of pembrolizumab (MK-3475; anti-PD-1 monoclonal antibody) in patients with advanced solid tumors. Clin. Cancer Res. 21, 4286–4293 (2015).

    Article  CAS  PubMed  Google Scholar 

  6. Brahmer, J. R. et al. Safety and activity of anti–PD-L1 antibody in patients with advanced cancer. N. Engl. J. Med. 366, 2455–2465 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Segal, N. et al. Preliminary data from a multi-arm expansion study of MEDI4736, an anti-PD-L1 antibody. J. Clin. Oncol. 32, 3002 (2014) .

    Article  Google Scholar 

  8. Royal, R. E. et al. Phase 2 trial of single agent ipilimumab (anti-CTLA-4) for locally advanced or metastatic pancreatic adenocarcinoma. J. Immunother. 33, 828–833 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Sharma, P., Hu-Lieskovan, S., Wargo, J. A. & Ribas, A. Primary, adaptive, and acquired resistance to cancer immunotherapy. Cell 168, 707–723 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Granier, C. et al. Mechanisms of action and rationale for the use of checkpoint inhibitors in cancer. ESMO Open 2, e000213 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Bjoern, J. et al. Immunological correlates of treatment and response in stage IV malignant melanoma patients treated with Ipilimumab. Oncoimmunology 5, e1100788 (2016).

    Article  PubMed  Google Scholar 

  12. Holmgaard, R. B., Zamarin, D., Lesokhin, A., Merghoub, T. & Wolchok, J. D. Targeting myeloid-derived suppressor cells with colony stimulating factor-1 receptor blockade can reverse immune resistance to immunotherapy in indoleamine 2,3-dioxygenase-expressing tumors. EBioMedicine 6, 50–58 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Meyer, C. et al. Frequencies of circulating MDSC correlate with clinical outcome of melanoma patients treated with ipilimumab. Cancer Immunol. Immunother. 63, 247–257 (2014).

    Article  CAS  PubMed  Google Scholar 

  14. Highfill, S. L. et al. Disruption of CXCR2-mediated MDSC tumor trafficking enhances anti-PD1 efficacy. Sci. Transl. Med. 6, 237ra67 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Gebhardt, C. et al. Myeloid cells and related chronic inflammatory factors as novel predictive markers in melanoma treatment with ipilimumab. Clin. Cancer Res. 21, 5453–5459 (2015).

    Article  CAS  PubMed  Google Scholar 

  16. Diaz-Montero, C. M., Finke, J. & Montero, A. J. Myeloid-derived suppressor cells in cancer: therapeutic, predictive, and prognostic implications. Semin. Oncol. 41, 174–184 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Kumar, V., Patel, S., Tcyganov, E. & Gabrilovich, D. I. The nature of myeloid-derived suppressor cells in the tumor microenvironment. Trends Immunol. 37, 208–220 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Talmadge, J. E. & Gabrilovich, D. I. History of myeloid-derived suppressor cells. Nat. Rev. Cancer 13, 739–752 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Colombo, M. P. & Piconese, S. Regulatory T-cell inhibition versus depletion: the right choice in cancer immunotherapy. Nat. Rev. Cancer 7, 880–887 (2007).

    Article  CAS  PubMed  Google Scholar 

  20. Nishikawa, H. & Sakaguchi, S. Regulatory T cells in cancer immunotherapy. Curr. Opin. Immunol. 27, 1–7 (2014).

    Article  CAS  PubMed  Google Scholar 

  21. Buckner, J. H. Mechanisms of impaired regulation by CD4+CD25+FOXP3+ regulatory T cells in human autoimmune diseases. Nat. Rev. Immunol. 10, 849–859 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Sato, K., Nagaya, T., Mitsunaga, M., Choyke, P. L. & Kobayashi, H. Near infrared photoimmunotherapy for lung metastases. Cancer Lett. 365, 112–121 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Mitsunaga, M. et al. Cancer cell-selective in vivo near infrared photoimmunotherapy targeting specific membrane molecules. Nat. Med. 17, 1685–1691 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Sato, K. et al. Spatially selective depletion of tumor-associated regulatory T cells with near-infrared photoimmunotherapy. Sci. Transl. Med. 8, 352ra110 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Mellman, I., Coukos, G. & Dranoff, G. Cancer immunotherapy comes of age. Nature https://doi.org/10.1038/nature10673 (2011).

  26. Li, P. et al. BATF-JUN is critical for IRF4-mediated transcription in T cells. Nature https://doi.org/10.1038/nature11530 (2012).

  27. Elpek, K. G. et al. The tumor microenvironment shapes lineage, transcriptional, and functional diversity of infiltrating myeloid cells. Cancer Immunol. Res. https://doi.org/10.1158/2326-6066.CIR-13-0209 (2014).

  28. Tuit, S. et al. Transcriptional signature derived from murine tumor-associated macrophages correlates with poor outcome in breast cancer patients. Cell Rep. https://doi.org/10.1016/j.celrep.2019.09.067 (2019).

  29. Azambuja, J. H. et al. Blockade of CD73 delays glioblastoma growth by modulating the immune environment. Cancer Immunol. Immunother. https://doi.org/10.1007/s00262-020-02569-w (2020).

  30. Goswami, S. et al. Immune profiling of human tumors identifies CD73 as a combinatorial target in glioblastoma. Nat. Med. https://doi.org/10.1038/s41591-019-0694-x (2020).

  31. Beavis, P. A., Stagg, J., Darcy, P. K. & Smyth, M. J. CD73: A potent suppressor of antitumor immune responses. Trends Immunol. 33, 231–237 (2012).

    Article  CAS  PubMed  Google Scholar 

  32. Buisseret, L. et al. Clinical significance of CD73 in triple-negative breast cancer: multiplex analysis of a phase III clinical trial. Ann. Oncol. https://doi.org/10.1093/annonc/mdx730 (2018).

  33. Azad, A. et al. PD‐L1 blockade enhances response of pancreatic ductal adenocarcinoma to radiotherapy. EMBO Mol. Med. 9, 167–180 (2017).

    Article  CAS  PubMed  Google Scholar 

  34. Corbett, T. H. et al. Induction and chemotherapeutic response of two transplantable ductal adenocarcinomas of the pancreas in C57BL/6 mice. Cancer Res. 44, 717–726 (1984).

    CAS  PubMed  Google Scholar 

  35. Allard, B., Pommey, S., Smyth, M. J. & Stagg, J. Targeting CD73 enhances the antitumor activity of anti-PD-1 and anti-CTLA-4 mAbs. Clin. Cancer Res. https://doi.org/10.1158/1078-0432.CCR-13-0545 (2013).

  36. Stagg, J. et al. Anti-CD73 antibody therapy inhibits breast tumor growth and metastasis. Proc. Natl Acad. Sci. USA https://doi.org/10.1073/pnas.0908801107 (2010).

  37. de Mingo Pulido, Á. et al. TIM-3 regulates CD103+ dendritic cell function and response to chemotherapy in breast cancer. Cancer Cell https://doi.org/10.1016/j.ccell.2017.11.019 (2018).

  38. Lin, E. Y. et al. Progression to malignancy in the polyoma middle T oncoprotein mouse breast cancer model provides a reliable model for human diseases. Am. J. Pathol. 163, 2113–2126 (2003).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Guy, C. T., Cardiff, R. D. & Muller, W. J. Induction of mammary tumors by expression of polyomavirus middle T oncogene: a transgenic mouse model for metastatic disease. Mol. Cell Biol. 12, 954–961 (1992).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Uhlen, M. et al. Tissue-based map of the human proteome. Science 347, 1260419 (2015).

    Article  PubMed  Google Scholar 

  41. Bedard, P. L., Hansen, A. R., Ratain, M. J. & Siu, L. L. Tumour heterogeneity in the clinic. Nature 501, 355–364 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Agarwal, R. & Kaye, S. B. Ovarian cancer: strategies for overcoming resistance to chemotherapy. Nat. Rev. Cancer 3, 502–516 (2003).

    Article  CAS  PubMed  Google Scholar 

  43. Lackner, M. R., Wilson, T. R. & Settleman, J. Mechanisms of acquired resistance to targeted cancer therapies. Future Oncol. 8, 999–1014 (2012).

    Article  CAS  PubMed  Google Scholar 

  44. Neel, D. S. & Bivona, T. G. Resistance is futile: overcoming resistance to targeted therapies in lung adenocarcinoma. NPJ Precis. Oncol. 1, 3 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  45. Vijayan, D., Young, A., Teng, M. W. L. & Smyth, M. J. Targeting immunosuppressive adenosine in cancer. Nat. Rev. Cancer 17, 709–724 (2017).

    Article  CAS  PubMed  Google Scholar 

  46. Chen, S. et al. CD73 expression on effector T cells sustained by TGF-β facilitates tumor resistance to anti-4-1BB/CD137 therapy. Nat. Commun. https://doi.org/10.1038/s41467-018-08123-8 (2019).

  47. de Leve, S., Wirsdörfer, F. & Jendrossek, V. Targeting the immunomodulatory CD73/adenosine system to improve the therapeutic gain of radiotherapy. Front. Immunol. https://doi.org/10.3389/fimmu.2019.00698 (2019).

  48. Zhang, B. CD73: a novel target for cancer immunotherapy. Cancer Res. https://doi.org/10.1158/0008-5472.CAN-10-1544 (2010).

  49. Leone, R. D. & Emens, L. A. Targeting adenosine for cancer immunotherapy. J. Immunother. Cancer https://doi.org/10.1186/s40425-018-0360-8 (2018).

  50. Mixed reviews for A2AR inhibitor in NSCLC. Cancer Discov. 9, OF2 (2019).

  51. Narravula, S., Lennon, P. F., Mueller, B. U. & Colgan, S. P. Regulation of endothelial CD73 by adenosine: paracrine pathway for enhanced endothelial barrier function. J. Immunol. https://doi.org/10.4049/jimmunol.165.9.5262 (2000).

  52. Yu, M. et al. CD73 on cancer-associated fibroblasts enhanced by the A2B-mediated feedforward circuit enforces an immune checkpoint. Nat. Commun. https://doi.org/10.1038/s41467-019-14060-x (2020).

  53. Seaman, S. et al. Eradication of tumors through simultaneous ablation of CD276/B7-H3-positive tumor cells and tumor vasculature. Cancer Cell 31, 501–515.e8 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Keen, J. C. & Moore, H. M. The genotype-tissue expression (GTEx) project: linking clinical data with molecular analysis to advance personalized medicine. J. Pers. Med. 5, 22–29 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  55. Yu, N. Y. L. et al. Complementing tissue characterization by integrating transcriptome profiling from the human protein atlas and from the FANTOM5 consortium. Nucleic Acids Res. 43, 6787–6798 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Sciarra, A. et al. CD73 expression in normal and pathological human hepatobiliopancreatic tissues. Cancer Immunol. Immunother. https://doi.org/10.1007/s00262-018-2290-1 (2019).

  57. Bown, S. G. et al. Photodynamic therapy for cancer of the pancreas. Gut 50, 549–557 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Xue, G., Jin, G., Fang, J. & Lu, Y. IL-4 together with IL-1β induces antitumor Th9 cell differentiation in the absence of TGF-β signaling. Nat. Commun. 10, 1376 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  59. Brinke, A. T. et al. Monitoring T-cell responses in translational studies: optimization of dye-based proliferation assay for evaluation of antigen-specific responses. Front. Immunol. https://doi.org/10.3389/fimmu.2017.01870 (2017).

  60. Mao, C., Li, F., Zhao, Y., Debinski, W. & Ming, X. P-glycoprotein-targeted photodynamic therapy boosts cancer nanomedicine by priming tumor microenvironment. Theranostics https://doi.org/10.7150/thno.29580 (2018).

  61. Jenkins, R. W. et al. Ex vivo profiling of PD-1 blockade using organotypic tumor spheroids. Cancer Discov. 8, 196–215 (2018).

    Article  CAS  PubMed  Google Scholar 

  62. Ootani, A. et al. Sustained in vitro intestinal epithelial culture within a Wnt-dependent stem cell niche. Nat. Med. https://doi.org/10.1038/nm.1951 (2009).

  63. Lu, Y. et al. Th9 cells promote antitumor immune responses in vivo. J. Clin. Invest. 122, 4160–4171 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Lu, Y. et al. Th9 cells represent a unique subset of CD4+ T cells endowed with the ability to eradicate advanced tumors. Cancer Cell 33, 1048–1060.e7 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This work was supported by grants from the National Cancer Institute (NCI, 4R00CA190910-03; 1R37CA251318-01; 1R01CA248111-01A1; R01 CA258477-01; 1R01CA264102-01), NCI P30 Administrative Supplement for Cell-Based Therapy (3P30CA012197-44S5), Daryl and Marguerite Errett Discovery Award 2020, ACS Research Scholar Grant (RSG-19-149-01-LIB), Wake Forest Baptist Comprehensive Cancer Center (WFBCCC) Push Pilot projects and CPRIT Scholar (RR210067). Research reported in this publication was also supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under award number UL1TR001420 (CTSI Pilot Grant Award 2018, CTSI Pilot Grant Award 2019 and CTSI Ignition Fund Pilot award). We thank I. M. Newman from the Wake Forest CTSI for manuscript editing assistance. This study was also supported by the NCI’s Cancer Center Support Grant award number P30CA012197 issued to the Wake Forest Baptist Comprehensive Cancer Center. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NCI.

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Authors and Affiliations

  1. Comprehensive Cancer Center, Wake Forest Baptist Health, Winston-Salem, NC, USA

    Gang Xue, Ziyu Wang, Ningbo Zheng, Jing Fang, Chengqiong Mao, Guangxu Jin, Xin Ming & Yong Lu

  2. Department of Microbiology and Immunology, Wake Forest School of Medicine, Winston-Salem, NC, USA

    Gang Xue, Ziyu Wang, Ningbo Zheng, Jing Fang & Yong Lu

  3. Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC, USA

    Chengqiong Mao, Guangxu Jin & Xin Ming

  4. Department of Mathematics and Statistics, St. Cloud State University, Saint Cloud, MN, USA

    Xiaoyin Li

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Contributions

G.X. and Y.L. designed the experiments, analysed the data and wrote the paper. G.X. performed most of the experiments. G.J. helped with CyTOF data analysis. X.L. performed statistical analysis. J.F., Z.W. and N.Z. helped with animal studies. C.M. and X.M. provided technical support.

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Correspondence to Yong Lu.

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Extended data

Extended Data Fig. 1 αCD73-Dye + NIR treatment shrinks advanced tumors in vivo.

(a) Treatment procedures of αCD73-Dye-mediated NIR irradiation against 4T1.2 and Pan02 tumors in vivo. NIR was given on tumors only, while other parts of the mice were shielded from light. Tumor growth curves of 4T1.2 (b) and Pan02 (c) tumors treated with IgG, IgG-Dye + NIR, αCD73-Dye, or αCD73-Dye + NIR (n=5 mice/group). The red arrow represents near-infrared (NIR) irradiation. Representative results from one of two repeated experiments are shown.

Extended Data Fig. 2 Changes in ratios of different immune cells in tumors after αCD73-Dye + NIR treatment.

CD8 + T cells to Treg cells ratio (a), CD8 + T cells to TAM.M2 cells ratio (b), CD8 + T cells to PMN.MDSC cells ratio (c), CD8 + T cells to Mo.MDSC cells ratio (d), NK cells to Treg cells ratio (e), NK cells to TAM.M2 cells ratio (f), NK cells to PMN.MDSC cells ratio (g), NK cells to Mo.MDSC cells ratio (h), and Foxp3.neg CD4 + T cells to Treg cells ratio (i) in 4T1.2 tumors after indicated treatments (as described in Extended Data Fig. 1) were tested by CyTOF (n = 3 biological replicates). The t-SNE plot of tumour-infiltrating CD45 + compartment overlaid with the expression of GzmB (j) and IFN-γ (k) from the 4T1.2 tumour after treatment. Data are mean ± SD. ****P < 0.0001, αCD73-Dye + NIR group compared with IgG, IgG-Dye + NIR, or αCD73-Dye group, one-way ANOVA with Tukey’s correction (a, b, c, d, and h). # means **P = 0.005834, αCD73-Dye + NIR group compared with IgG group, ## means **P = 0.006561, αCD73-Dye + NIR group compared with IgG-Dye + NIR group, ### means *P = 0.010734, αCD73-Dye + NIR group compared with αCD73-Dye group, one-way ANOVA with Tukey’s correction (f). # means **P = 0.002767, αCD73-Dye + NIR group compared with IgG group, ## means **P = 0.005519, αCD73-Dye + NIR group compared with IgG-Dye + NIR group, ### means *P = 0.028222, αCD73-Dye + NIR group compared with αCD73-Dye group, one-way ANOVA with Tukey’s correction (g). # means **P = 0.007576, αCD73-Dye + NIR group compared with IgG group, ## means **P = 0.004057, αCD73-Dye + NIR group compared with IgG-Dye + NIR group, ### means *P = 0.015673, αCD73-Dye + NIR group compared with αCD73-Dye group, one-way ANOVA with Tukey’s correction (i).

Extended Data Fig. 3 αCD73-Dye + NIR irradiation synergizes with αPD-1, promoting curative responses in the 4T1.2 tumour model.

(a) Diagram of the treatments. BALB/c mice bearing both orthotopic 4T1.2 tumor (5 × 105 4T1.2 tumor cells injection in the mammary gland) and lung metastasis tumors (1 × 105 tumor cells injection via tail vein) were treated on day 7 with control IgG, αPD-1, αCD73-Dye + αPD-1, αCD73-Dye + NIR, or αCD73-Dye + NIR + αPD-1 (Combo). NIR irradiation was given on the orthotopic tumor only (other parts of the mice were shielded from light). (b) Tumor growth curves (n = 5 mice/group) of the orthotopic 4T1.2 tumors after indicated treatments. (c) Some mice were euthanized on day 28 and representative lung pictures are shown. (d) Summarized lung weight of mice receiving indicated treatments (n = 5 biological replicates). (e) Surviving curves of 4T1.2 tumor-bearing mice. Representative results from one of two repeated experiments are shown (n = 10 mice/group). Data are mean ± SD. ****P < 0.0001, Combo group compared with IgG, αPD-1, αCD73-Dye + αPD-1, or αCD73-Dye + NIR group, one-way ANOVA with Tukey’s correction (d). ***P < 0.001, αCD73-Dye + NIR group compared with IgG, αPD-1, or αCD73-Dye + αPD-1 group; ****P < 0.0001, Combo group compared with IgG, αPD-1, αCD73-Dye + αPD-1, or αCD73-Dye + NIR group, survival analysis was conducted by log-rank test with holm test for multiple comparisons (e).

Extended Data Fig. 4 αCD73-Dye + NIR + αPD-1 combination treatment induced curative responses in the Pan02 tumor model.

(a) Diagram of the treatments. Pan02 tumor cells were s.c. injected on the left (2 × 106 Pan02 cells) and right (5 × 105 Pan02 cells) flanks of B6 mice, and treated on day 7 with control IgG, αPD-1, αCD73-Dye + αPD-1, αCD73-Dye + NIR, or αCD73-Dye + NIR + αPD-1 (Combo). NIR was performed on the left-side tumor only (right-side tumors were shielded from light). (b) Tumor growth curves of NIR-treated left tumors are shown (n = 5 mice/group). (c) Tumor growth curves of non-NIR-treated right tumors are shown (n = 5 mice/group). (d) Surviving curves of Pan02 tumor-bearing mice (n = 10 mice/group). (e) Tumor growth curves and (f) survival curves of Pan02 tumor-bearing mice treated with αCD73-Dye + NIR + αPD-1 combo therapy together with the depletion of NK cells, CD4 + T cells or CD8 + T cells. Representative results from one of two repeated experiments are shown. Data are mean ± SD. # means ****P < 0.0001, αCD73-Dye + NIR group compared with IgG, αPD-1, or αCD73-Dye + αPD-1 group; # means **P = 0.00592, Combo group compared with αCD73-Dye + NIR group, ## means **** P < 0.0001, Combo group compared with IgG, αPD-1, or αCD73-Dye + αPD-1 group, two-way ANOVA with Holm–Sidak test for multiple comparisons (c). ***P < 0.001, αCD73-Dye + NIR group compared with IgG, αPD-1, or αCD73-Dye + αPD-1 group, ****P < 0.0001, Combo group compared with IgG, αPD-1, αCD73-Dye + αPD-1, or αCD73-Dye + NIR group, survival analysis was conducted by log-rank test with holm test for multiple comparisons (d). ***P < 0.001, Combo + αCD8 group compared with Combo + IgG, Combo + αNK1.1, or Combo + αCD4 group, two-way ANOVA with Holm–Sidak test for multiple comparisons (e). ***P < 0.001, Combo + αCD8 group compared with Combo + IgG, Combo + αNK1.1, or Combo + αCD4 group, survival analysis was conducted by log-rank test with holm test for multiple comparisons (f).

Extended Data Fig. 5 Effects of αCD73-Dye + NIR + αPD-1 combination treatment in the EMT6CD73 KO tumor model.

(a) FACS analysis for surface expression of CD73 in EMT6 CD73 knockout (EMT6CD73 KO) cells. (b) EMT6CD73 KO cells were treated as indicated in vitro. The percentage of dead cells was determined by FACS after PI staining (n = 3 biological replicates). (c) BALB/c mice bearing both orthotopic EMT6CD73 KO tumor (5 × 105 EMT6CD73 KO tumor cells injection in the mammary gland) and lung metastasis tumors (1 × 105 EMT6CD73 KO tumor cells injection via tail vein) were treated on day 5 with control IgG, αPD-1, αCD73-Dye + αPD-1, αCD73-Dye + NIR, or αCD73-Dye + NIR + αPD-1 (Combo). NIR irradiation was given on the orthotopic tumor only (other parts of the mice were shielded from light). Mice survival curves (n = 9/αPD-1 group, n = 11/αCD73-Dye + NIR group, n = 12/ Combo group, n = 10/other groups) are shown. Representative results from one of two repeated experiments are shown. Data are mean ± SD. # mean **P = 0.00114439, Combo group compared with αCD73-Dye + NIR group; ## means ***P < 0.001, Combo group compared with IgG, αPD-1, or αCD73-Dye + αPD-1 group, survival analysis was conducted by log-rank test with holm test for multiple comparisons (c).

Extended Data Fig. 6 Effects of αCD73-Dye + NIR + αPD-1 combination therapy in human pancreatic cancer.

(a) CD73 protein levels in the HPA dataset. Most cancer tissues displayed strong to moderate membranous and cytoplasmic CD73 positivity. Lymphomas and testicular cancers showed weak positivity or were negative. (b) Cell number per 100 mg tumor tissue of indicated immune cell subsets were determined by FACS (n = 3). (c) FACS analysis for surface expression of CD73 or B7H3 on cells isolated from pancreatic tumor specimens. Representative data are shown. (d) Diagram of organotypic tumor spheroids (OTS), modified from a published study62. (e) Human PDAC OTS were treated as indicated ex vivo. Cell death was tested by Nexcelom ViaStain AO/PI staining Solution. Green represents live cells; red represents dead cells. Orange bar: 50 μM. Representative data and summarized results are shown, n = 8/group (2-3 OTS from each patient for each indicated treatment; and OTS from 3 patients were used). Data are mean ± SD. ***P < 0.001, αCD73-Dye + NIR + αPD-1 group compared with any other groups, one-way ANOVA with Tukey’s correction (e).

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Xue, G., Wang, Z., Zheng, N. et al. Elimination of acquired resistance to PD-1 blockade via the concurrent depletion of tumour cells and immunosuppressive cells. Nat Biomed Eng 5, 1306–1319 (2021). https://doi.org/10.1038/s41551-021-00799-6

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