Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

T lymphocyte membrane-decorated epigenetic nanoinducer of interferons for cancer immunotherapy


Impaired type I interferons (IFNs) may cause immune deficiency in tumours. Current supplementary IFN therapy partially restores anticancer immunity but simultaneously induces immune evasion by upregulating multiple immune checkpoints. Here we create a T lymphocyte membrane-decorated epigenetic nanoinducer that is engineered with programmed cell death protein 1 (PD1), which we call OPEN, for the delivery of the IFN inducer ORY-1001. OPEN increases IFNs and blocks IFN-induced immune checkpoint upregulation. OPEN also targets tumours that express programmed cell death ligand 1 (PDL1) through PDL1/PD1 recognition and subsequently triggers the internalization of OPEN and immune checkpoint proteins. OPEN, which is loaded with ORY-1001, upregulates intratumoural IFNs and downstream major histocompatibility complex I and PDL1. The replenished PDL1 enables further ligation of OPEN, which in turn blocks PDL1. These sequential processes result in an eight- and 29-fold increase of the intratumoural densities of total and active cytotoxic T lymphocytes, respectively, and a strong inhibition of xenograft tumour growth. This T lymphocyte membrane-decorated epigenetic nanoinducer presents a generalizable platform to boost antitumour immunity.

This is a preview of subscription content

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Schematic illustration of the preparation and mechanism of action of OPEN.
Fig. 2: Association between intratumoural IFN signature and survival in TNBC patients and the effects of direct or ORY-1001-induced IFN supplement therapy on the survival and tumour infiltration of immune cells in murine TNBC model mice.
Fig. 3: Preparation and characterization of OPEN and its interaction with 4T1 cells.
Fig. 4: Accumulation of OPEN in the tumours.
Fig. 5: Amplifiable effects of OPEN in inducing intratumoural IFN-α/β and initiating the immune response.
Fig. 6: Effect of OPEN on CTLs and its therapeutic efficacy.

Data availability

Source data are provided with this paper. Gene expression and survival data of TNBC patients in Fig. 2a were acquired from the cBioPortal database ( The raw data used in Fig. 2g and Supplementary Fig. 2 are available at with the dataset identifier number OEX010736. Any additional data that support the findings of this study are available from the corresponding authors upon reasonable request.

Code availability

All custom R scripts associated with this manuscript are deposited in the publicly available repository (


  1. 1.

    Dunn, G. P., Koebel, C. M. & Schreiber, R. D. Interferons, immunity and cancer immunoediting. Nat. Rev. Immunol. 6, 836–848 (2006).

    CAS  Google Scholar 

  2. 2.

    Minn, A. J. & Wherry, E. J. Combination cancer therapies with immune checkpoint blockade: convergence on interferon signaling. Cell 165, 272–275 (2016).

    CAS  Google Scholar 

  3. 3.

    Parker, B. S., Rautela, J. & Hertzog, P. J. Antitumour actions of interferons: implications for cancer therapy. Nat. Rev. Cancer 16, 131–144 (2016).

    Google Scholar 

  4. 4.

    Zitvogel, L., Galluzzi, L., Kepp, O., Smyth, M. J. & Kroemer, G. Type I interferons in anticancer immunity. Nat. Rev. Immunol. 15, 405–414 (2015).

    CAS  Google Scholar 

  5. 5.

    Sceneay, J. et al. Interferon signaling is diminished with age and is associated with immune checkpoint blockade efficacy in triple-negative breast cancer. Cancer Discov. 9, 1208–1227 (2019).

    CAS  Google Scholar 

  6. 6.

    Critchley-Thorne, R. J. et al. Impaired interferon signaling is a common immune defect in human cancer. Proc. Natl Acad. Sci. USA 106, 9010–9015 (2009).

    CAS  Google Scholar 

  7. 7.

    Sisirak, V. et al. Impaired IFN-alpha production by plasmacytoid dendritic cells favors regulatory T-cell expansion that may contribute to breast cancer progression. Cancer Res. 72, 5188–5197 (2012).

    CAS  Google Scholar 

  8. 8.

    Domschke, C. et al. Intratumoral cytokines and tumor cell biology determine spontaneous breast cancer-specific immune responses and their correlation to prognosis. Cancer Res. 69, 8420–8428 (2009).

    CAS  Google Scholar 

  9. 9.

    Bidwell, B. N. et al. Silencing of Irf7 pathways in breast cancer cells promotes bone metastasis through immune escape. Nat. Med. 18, 1224–1231 (2012).

    CAS  Google Scholar 

  10. 10.

    Salvagno, C. et al. Therapeutic targeting of macrophages enhances chemotherapy efficacy by unleashing type I interferon response. Nat. Cell Biol. 21, 511–521 (2019).

    CAS  Google Scholar 

  11. 11.

    Sistigu, A. et al. Cancer cell-autonomous contribution of type I interferon signaling to the efficacy of chemotherapy. Nat. Med. 20, 1301–1309 (2014).

    CAS  Google Scholar 

  12. 12.

    Benci, J. L. et al. Tumor interferon signaling regulates a multigenic resistance program to immune checkpoint blockade. Cell 167, 1540–1554 (2016).

    CAS  Google Scholar 

  13. 13.

    Demaria, O. et al. Harnessing innate immunity in cancer therapy. Nature 574, 45–56 (2019).

    CAS  Google Scholar 

  14. 14.

    Cauwels, A. et al. Delivering type I interferon to dendritic cells empowers tumor eradication and immune combination treatments. Cancer Res. 78, 463–474 (2018).

    CAS  Google Scholar 

  15. 15.

    De Palma, M. et al. Tumor-targeted interferon-alpha delivery by Tie2-expressing monocytes inhibits tumor growth and metastasis. Cancer Cell 14, 299–311 (2008).

    Google Scholar 

  16. 16.

    Escobar, G. et al. Genetic engineering of hematopoiesis for targeted IFN-α delivery inhibits breast cancer progression. Sci. Transl. Med. 6, 217ra213 (2014).

    Google Scholar 

  17. 17.

    Topper, M. J., Vaz, M., Marrone, K. A., Brahmer, J. R. & Baylin, S. B. The emerging role of epigenetic therapeutics in immuno-oncology. Nat. Rev. Clin. Oncol. 17, 75–90 (2020).

    Google Scholar 

  18. 18.

    Sheng, W. Q. et al. LSD1 ablation stimulates anti-tumor immunity and enables checkpoint blockade. Cell 174, 549–563 (2018).

    CAS  Google Scholar 

  19. 19.

    Maes, T. et al. ORY-1001, a potent and selective covalent KDM1A inhibitor, for the treatment of acute leukemia. Cancer Cell 33, 495–511 (2018).

    CAS  Google Scholar 

  20. 20.

    Poggio, M. et al. Suppression of exosomal PD-L1 induces systemic anti-tumor immunity and memory. Cell 177, 414–427 (2019).

    CAS  Google Scholar 

  21. 21.

    Hu, C. M. J. et al. Erythrocyte membrane-camouflaged polymeric nanoparticles as a biomimetic delivery platform. Proc. Natl Acad. Sci. USA 108, 10980–10985 (2011).

    CAS  Google Scholar 

  22. 22.

    Hu, C. M. J., Fang, R. H., Luk, B. T. & Zhang, L. F. Nanoparticle-detained toxins for safe and effective vaccination. Nat. Nanotechnol. 8, 933–938 (2013).

    CAS  Google Scholar 

  23. 23.

    Hu, C. M. J. et al. Nanoparticle biointerfacing by platelet membrane cloaking. Nature 526, 118–121 (2015).

    CAS  Google Scholar 

  24. 24.

    Wang, C. et al. In situ activation of platelets with checkpoint inhibitors for post-surgical cancer immunotherapy. Nat. Biomed. Eng. 1, 0011 (2017).

    CAS  Google Scholar 

  25. 25.

    Hu, Q. Y. et al. Anticancer platelet-mimicking nanovehicles. Adv. Mater. 27, 7043–7050 (2015).

    CAS  Google Scholar 

  26. 26.

    Ciriello, G. et al. Comprehensive molecular portraits of invasive lobular breast cancer. Cell 163, 506–519 (2015).

    CAS  Google Scholar 

  27. 27.

    Rueda, O. M. et al. Dynamics of breast-cancer relapse reveal late-recurring ER-positive genomic subgroups. Nature 567, 399–404 (2019).

    CAS  Google Scholar 

  28. 28.

    Tokuyama, M. et al. ERVmap analysis reveals genome-wide transcription of human endogenous retroviruses. Proc. Natl Acad. Sci. USA 115, 12565–12572 (2018).

    CAS  Google Scholar 

  29. 29.

    Kinter, A. L. et al. The common gamma-chain cytokines IL-2, IL-7, IL-15, and IL-21 induce the expression of programmed death-1 and its ligands. J. Immunol. 181, 6738–6746 (2008).

    CAS  Google Scholar 

  30. 30.

    Parry, R. V. et al. CTLA-4 and PD-1 receptors inhibit T-cell activation by distinct mechanisms. Mol. Cell. Biol. 25, 9543–9553 (2005).

    CAS  Google Scholar 

  31. 31.

    Jiang, W., Kim, B. Y. S., Rutka, J. T. & Chan, W. C. W. Nanoparticle-mediated cellular response is size-dependent. Nat. Nanotechnol. 3, 145–150 (2008).

    CAS  Google Scholar 

  32. 32.

    Gillis, S. & Smith, K. A. Long term culture of tumour-specific cytotoxic T cells. Nature 268, 154–156 (1977).

    CAS  Google Scholar 

  33. 33.

    Li, C. W. et al. Eradication of triple-negative breast cancer cells by targeting glycosylated PD-L1. Cancer Cell 33, 187–201 (2018).

    CAS  Google Scholar 

  34. 34.

    Kalbasi, A. et al. Uncoupling interferon signaling and antigen presentation to overcome immunotherapy resistance due to JAK1 loss in melanoma. Sci. Transl. Med. 12, eabb0152 (2020).

    CAS  Google Scholar 

  35. 35.

    Seliger, B., Wollscheid, U., Momburg, F., Blankenstein, T. & Huber, C. Characterization of the major histocompatibility complex class I deficiencies in B16 melanoma cells. Cancer Res. 61, 1095–1099 (2001).

    CAS  Google Scholar 

  36. 36.

    Tang, L. et al. Enhancing T cell therapy through TCR-signaling-responsive nanoparticle drug delivery. Nat. Biotechnol. 36, 707–716 (2018).

    CAS  Google Scholar 

  37. 37.

    Schmidt-Arras, D. & Rose-John, S. IL-6 pathway in the liver: from physiopathology to therapy. J. Hepatol. 64, 1403–1415 (2016).

    CAS  Google Scholar 

  38. 38.

    Garrido-Castro, A. C., Lin, N. U. & Polyak, K. Insights into molecular classifications of triple-negative breast cancer: improving patient selection for treatment. Cancer Discov. 9, 176–198 (2019).

    CAS  Google Scholar 

  39. 39.

    Bareche, Y. et al. Unraveling triple-negative breast cancer tumor microenvironment heterogeneity: towards an optimized treatment approach. J. Natl Cancer Inst. 112, 708–719 (2020).

    Google Scholar 

  40. 40.

    Savas, P. et al. Clinical relevance of host immunity in breast cancer: from TILs to the clinic. Nat. Rev. Clin. Oncol. 13, 228–241 (2016).

    CAS  Google Scholar 

  41. 41.

    Gruosso, T. et al. Spatially distinct tumor immune microenvironments stratify triple-negative breast cancers. J. Clin. Invest. 129, 1785–1800 (2019).

    Google Scholar 

  42. 42.

    Zhang, X. et al. PD-1 blockade cellular vesicles for cancer immunotherapy. Adv. Mater. 30, 1707112 (2018).

    Google Scholar 

  43. 43.

    Zhang, X. et al. Engineering PD-1-presenting platelets for cancer immunotherapy. Nano Lett. 18, 5716–5725 (2018).

    CAS  Google Scholar 

  44. 44.

    Ferguson, S. S. Evolving concepts in G protein-coupled receptor endocytosis: the role in receptor desensitization and signaling. Pharmacol. Rev. 53, 1–24 (2001).

    CAS  Google Scholar 

  45. 45.

    Sagiv-Barfi, I. et al. Therapeutic antitumor immunity by checkpoint blockade is enhanced by ibrutinib, an inhibitor of both BTK and ITK. Proc. Natl Acad. Sci. USA 112, E966–E972 (2015).

    CAS  Google Scholar 

  46. 46.

    de Graauw, M. et al. Annexin A1 regulates TGF-beta signaling and promotes metastasis formation of basal-like breast cancer cells. Proc. Natl Acad. Sci. USA 107, 6340–6345 (2010).

    Google Scholar 

  47. 47.

    Spranger, S., Bao, R. Y. & Gajewski, T. F. Melanoma-intrinsic β-catenin signalling prevents anti-tumour immunity. Nature 523, 231–235 (2015).

    CAS  Google Scholar 

  48. 48.

    Bald, T. et al. Immune cell-poor melanomas benefit from PD-1 blockade after targeted type I IFN activation. Cancer Discov. 4, 674–687 (2014).

    CAS  Google Scholar 

  49. 49.

    Rafiq, S., Hackett, C. S. & Brentjens, R. J. Engineering strategies to overcome the current roadblocks in CAR T cell therapy. Nat. Rev. Clin. Oncol. 17, 147–167 (2020).

    Google Scholar 

Download references


Y.L. thanks the National Natural Science Foundation of China (81690265) for financial support. P.Z. thanks the National Natural Science Foundation of China (31870995 and 81671808), the Youth Innovation Promotion Association of CAS (2017335) and the SA-SIBS Scholarship Program for financial support. Y.L. thanks the Shandong Provincial Natural Science Foundation (ZR2019ZD25) for financial support. We are grateful to the National Centre for Protein Science Shanghai (electron microscopy system) for instrument support and technical assistance during data collection. We also thank L. Deng at the Shanghai Institute of Immunology for the kind gift of OT I mice and we thank J. Wang at Shanghai Institute of Materia Medica for the help with linker synthesis.

Author information




P.Z. and Y.Z. conceived and designed the project; Y.Z. synthesized and characterized the nanovesicles; Y.Z., J.W., T.L., Y.K., R.R., Y.C., W.R., F.X., C.Z., Y.W. and Y.Y. performed the cell and animal experiments; J.W., H.H.Z. and P.Z. performed bioinformatic analysis; P.Z., Y.Z. and Y.L. interpreted the data and wrote the manuscript with input from all of the authors. P.Z. and Y.L. supervised the study.

Corresponding authors

Correspondence to Pengcheng Zhang or Yaping Li.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Nanotechnology thanks Riccardo Dolcetti, Liangfang Zhang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–40 and ref. 1.

Reporting Summary

Supplementary Data1

Statistical source data for the supplementary figures.

Source data

Source Data Fig. 2

Statistical source data and unprocessed western blots.

Source Data Fig. 3

Statistical source data and unprocessed gel and western blot.

Source Data Fig. 4

Statistical source data.

Source Data Fig. 5

Statistical source data.

Source Data Fig. 6

Statistical source data.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Zhai, Y., Wang, J., Lang, T. et al. T lymphocyte membrane-decorated epigenetic nanoinducer of interferons for cancer immunotherapy. Nat. Nanotechnol. 16, 1271–1280 (2021).

Download citation


Quick links

Find nanotechnology articles, nanomaterial data and patents all in one place. Visit Nano by Nature Research