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A lysosome-targeted DNA nanodevice selectively targets macrophages to attenuate tumours

Abstract

Activating CD8+ T cells by antigen cross-presentation is remarkably effective at eliminating tumours. Although this function is traditionally attributed to dendritic cells, tumour-associated macrophages (TAMs) can also cross-present antigens. TAMs are the most abundant tumour-infiltrating leukocyte. Yet, TAMs have not been leveraged to activate CD8+ T cells because mechanisms that modulate their ability to cross-present antigens are incompletely understood. Here we show that TAMs harbour hyperactive cysteine protease activity in their lysosomes, which impedes antigen cross-presentation, thereby preventing CD8+ T cell activation. We developed a DNA nanodevice (E64-DNA) that targets the lysosomes of TAMs in mice. E64-DNA inhibits the population of cysteine proteases that is present specifically inside the lysosomes of TAMs, improves their ability to cross-present antigens and attenuates tumour growth via CD8+ T cells. When combined with cyclophosphamide, E64-DNA showed sustained tumour regression in a triple-negative-breast-cancer model. Our studies demonstrate that DNA nanodevices can be targeted with organelle-level precision to reprogram macrophages and achieve immunomodulation in vivo.

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Fig. 1: M2 macrophages have elevated lysosomal enzyme levels and activity.
Fig. 2: Deleting Tfeb in myeloid cells attenuates tumour growth through CD8+ T cell activation.
Fig. 3: Lysosomal cysteine proteases are elevated in M2 macrophages.
Fig. 4: A lysosome-targeted DNA nanodevice (E64-DNA) promotes antigen cross-presentation by TAMs.
Fig. 5: The E64-DNA nanodevice preferentially localizes in lysosomes of M2-like TAMs and lowers tumour growth.
Fig. 6: Intravenously delivered E64-DNA targets TAMs to activate CD8+ T cells and attenuate tumour growth.

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Data availability

Source data are provided with this paper. All data generated or analysed during this study are included in this published article and its Supplementary information files. Proteomics data are available via ProteomeXchange with identifier PXD028037.

References

  1. Cassetta, L. & Pollard, J. W. Targeting macrophages: therapeutic approaches in cancer. Nat. Rev. Drug Discov. 17, 887–904 (2018).

    Article  CAS  Google Scholar 

  2. Noy, R. & Pollard, J. W. Tumor-associated macrophages: from mechanisms to therapy. Immunity 41, 49–61 (2014).

    Article  CAS  Google Scholar 

  3. Mantovani, A., Marchesi, F., Malesci, A., Laghi, L. & Allavena, P. Tumour-associated macrophages as treatment targets in oncology. Nat. Rev. Clin. Oncol. 14, 399–416 (2017).

    Article  CAS  Google Scholar 

  4. Poh, A. R. & Ernst, M. Targeting macrophages in cancer: from bench to bedside. Front. Oncol. 8, 49 (2018).

    Article  Google Scholar 

  5. Cotechini, T., Medler, T. R. & Coussens, L. M. Myeloid cells as targets for therapy in solid tumors. Cancer J. 21, 343–350 (2015).

    Article  CAS  Google Scholar 

  6. Gentles, A. J. et al. The prognostic landscape of genes and infiltrating immune cells across human cancers. Nat. Med. 21, 938–945 (2015).

    Article  CAS  Google Scholar 

  7. Takeya, M. & Komohara, Y. Role of tumor-associated macrophages in human malignancies: friend or foe? Pathol. Int. 66, 491–505 (2016).

    Article  Google Scholar 

  8. Vitale, I., Manic, G., Coussens, L. M., Kroemer, G. & Galluzzi, L. Macrophages and metabolism in the tumor microenvironment. Cell Metab. 30, 36–50 (2019).

    Article  CAS  Google Scholar 

  9. DeNardo, D. G. & Ruffell, B. Macrophages as regulators of tumour immunity and immunotherapy. Nat. Rev. Immunol. 19, 369–382 (2019).

    Article  CAS  Google Scholar 

  10. Singhal, S. et al. Human tumor-associated monocytes/macrophages and their regulation of T cell responses in early-stage lung cancer. Sci. Transl. Med. 11, eaat1500 (2019).

    Article  CAS  Google Scholar 

  11. Fehres, C. M., Unger, W. W. J., Garcia-Vallejo, J. J. & van Kooyk, Y. Understanding the biology of antigen cross-presentation for the design of vaccines against cancer. Front. Immunol. 5, 149 (2014).

    Article  Google Scholar 

  12. Kurts, C., Robinson, B. W. S. & Knolle, P. A. Cross-priming in health and disease. Nat. Rev. Immunol. 10, 403–414 (2010).

    Article  CAS  Google Scholar 

  13. Joffre, O. P., Segura, E., Savina, A. & Amigorena, S. Cross-presentation by dendritic cells. Nat. Rev. Immunol. 12, 557–569 (2012).

    Article  CAS  Google Scholar 

  14. Cruz-Leal, Y. et al. The vacuolar pathway in macrophages plays a major role in antigen cross-presentation induced by the pore-forming protein sticholysin II encapsulated into liposomes. Front. Immunol. 9, 2473 (2018).

    Article  Google Scholar 

  15. Embgenbroich, M. & Burgdorf, S. Current concepts of antigen cross-presentation. Front. Immunol. 9, 1643 (2018).

    Article  Google Scholar 

  16. Shen, L., Sigal, L. J., Boes, M. & Rock, K. L. Important role of cathepsin S in generating peptides for TAP-independent MHC class I crosspresentation in vivo. Immunity 21, 155–165 (2004).

    Article  CAS  Google Scholar 

  17. Surana, S., Bhat, J. M., Koushika, S. P. & Krishnan, Y. An autonomous DNA nanomachine maps spatiotemporal pH changes in a multicellular living organism. Nat. Commun. 2, 340 (2011).

    Article  Google Scholar 

  18. Chakraborty, K., Leung, K. & Krishnan, Y. High lumenal chloride in the lysosome is critical for lysosome function. Elife 6, e28862 (2017).

    Article  Google Scholar 

  19. Narayanaswamy, N. et al. A pH-correctable, DNA-based fluorescent reporter for organellar calcium. Nat. Methods 16, 95–102 (2019).

    Article  CAS  Google Scholar 

  20. Leung, K., Chakraborty, K., Saminathan, A. & Krishnan, Y. A DNA nanomachine chemically resolves lysosomes in live cells. Nat. Nanotechnol. 14, 176–183 (2019).

    Article  CAS  Google Scholar 

  21. Dan, K., Veetil, A. T., Chakraborty, K. & Krishnan, Y. DNA nanodevices map enzymatic activity in organelles. Nat. Nanotechnol. 14, 252–259 (2019).

    Article  CAS  Google Scholar 

  22. Veetil, A. T. et al. DNA-based fluorescent probes of NOS2 activity in live brains. Proc. Natl Acad. Sci. USA 117, 14694–14702 (2020).

    Article  CAS  Google Scholar 

  23. Becker, L. et al. Unique proteomic signatures distinguish macrophages and dendritic cells. PLoS One 7, e33297 (2012).

    Article  CAS  Google Scholar 

  24. Odegaard, J. I. & Chawla, A. Alternative macrophage activation and metabolism. Annu. Rev. Pathol. 6, 275–297 (2011).

    Article  CAS  Google Scholar 

  25. Rodríguez-Prados, J.-C. et al. Substrate fate in activated macrophages: a comparison between innate, classic, and alternative activation. J. Immunol. 185, 605–614 (2010).

    Article  Google Scholar 

  26. Geissmann, F., Gordon, S., Hume, D. A., Mowat, A. M. & Randolph, G. J. Unravelling mononuclear phagocyte heterogeneity. Nat. Rev. Immunol. 10, 453–460 (2010).

    Article  CAS  Google Scholar 

  27. Xiong, H. et al. Anti-PD-L1 treatment results in functional remodeling of the macrophage compartment. Cancer Res. 79, 1493–1506 (2019).

    Article  CAS  Google Scholar 

  28. Lawrence, T. & Natoli, G. Transcriptional regulation of macrophage polarization: enabling diversity with identity. Nat. Rev. Immunol. 11, 750–761 (2011).

    Article  CAS  Google Scholar 

  29. Martinez, F. O. & Gordon, S. The M1 and M2 paradigm of macrophage activation: time for reassessment. F1000Prime Rep. 6, 13 (2014).

    Article  Google Scholar 

  30. Schroder, K. et al. Conservation and divergence in Toll-like receptor 4-regulated gene expression in primary human versus mouse macrophages. Proc. Natl Acad. Sci. USA 109, E944–E953 (2012).

    Article  CAS  Google Scholar 

  31. Thomas, A. C. & Mattila, J. T. “Of mice and men”: arginine metabolism in macrophages. Front. Immunol. 5, 479 (2014).

    Article  Google Scholar 

  32. Settembre, C. et al. TFEB links autophagy to lysosomal biogenesis. Science 332, 1429–1433 (2011).

    Article  CAS  Google Scholar 

  33. Sardiello, M. et al. A gene network regulating lysosomal biogenesis and function. Science 325, 473–477 (2009).

    Article  CAS  Google Scholar 

  34. Napolitano, G. & Ballabio, A. TFEB at a glance. J. Cell Sci. 129, 2475–2481 (2016).

    CAS  Google Scholar 

  35. Delamarre, L., Pack, M., Chang, H., Mellman, I. & Trombetta, E. S. Differential lysosomal proteolysis in antigen-presenting cells determines antigen fate. Science 307, 1630–1634 (2005).

    Article  CAS  Google Scholar 

  36. Trombetta, E. S. & Mellman, I. Cell biology of antigen processing in vitro and in vivo. Annu. Rev. Immunol. 23, 975–1028 (2005).

    Article  CAS  Google Scholar 

  37. Lund, A. W. et al. VEGF-C promotes immune tolerance in B16 melanomas and cross-presentation of tumor antigen by lymph node lymphatics. Cell Rep. 1, 191–199 (2012).

    Article  CAS  Google Scholar 

  38. Satpathy, A. T. et al. Zbtb46 expression distinguishes classical dendritic cells and their committed progenitors from other immune lineages. J. Exp. Med. 209, 1135–1152 (2012).

    Article  CAS  Google Scholar 

  39. Diment, S. Different roles for thiol and aspartyl proteases in antigen presentation of ovalbumin. J. Immunol. 145, 417–422 (1990).

    Article  CAS  Google Scholar 

  40. Rodriguez, G. M. & Diment, S. Destructive proteolysis by cysteine proteases in antigen presentation of ovalbumin. Eur. J. Immunol. 25, 1823–1827 (1995).

    Article  CAS  Google Scholar 

  41. Matsumoto, K. et al. Structural basis of inhibition of cysteine proteases by E-64 and its derivatives. Biopolymers 51, 99–107 (1999).

    Article  CAS  Google Scholar 

  42. Powers, J. C., Asgian, J. L., Ekici, Ö. D. & James, K. E. Irreversible inhibitors of serine, cysteine, and threonine proteases. Chem. Rev. 102, 4639–4750 (2002).

    Article  CAS  Google Scholar 

  43. Chakraborty, K. et al. Tissue specific targeting of DNA nanodevices in a multicellular living organism. Elife 10, e67830 (2021).

    Article  Google Scholar 

  44. Burdette, D. L. & Vance, R. E. STING and the innate immune response to nucleic acids in the cytosol. Nat. Immunol. 14, 19–26 (2013).

    Article  CAS  Google Scholar 

  45. Canton, J., Neculai, D. & Grinstein, S. Scavenger receptors in homeostasis and immunity. Nat. Rev. Immunol. 13, 621–634 (2013).

    Article  CAS  Google Scholar 

  46. Olson, O. C. & Joyce, J. A. Cysteine cathepsin proteases: regulators of cancer progression and therapeutic response. Nat. Rev. Cancer 15, 712–729 (2015).

    Article  CAS  Google Scholar 

  47. Gocheva, V. et al. IL-4 induces cathepsin protease activity in tumor-associated macrophages to promote cancer growth and invasion. Genes Dev. 24, 241–255 (2010).

    Article  CAS  Google Scholar 

  48. Gopinathan, A. et al. Cathepsin B promotes the progression of pancreatic ductal adenocarcinoma in mice. Gut 61, 877–884 (2012).

    Article  CAS  Google Scholar 

  49. Kerbel, R. S. & Kamen, B. A. The anti-angiogenic basis of metronomic chemotherapy. Nat. Rev. Cancer 4, 423–436 (2004).

    Article  CAS  Google Scholar 

  50. Sistigu, A. et al. Immunomodulatory effects of cyclophosphamide and implementations for vaccine design. Semin. Immunopathol. 33, 369–383 (2011).

    Article  CAS  Google Scholar 

  51. Murray, P. J. Macrophage polarization. Annu. Rev. Physiol. 79, 541–566 (2017).

    Article  CAS  Google Scholar 

  52. Pastor, F., Kolonias, D., McNamara, J. O. & Gilboa, E. Targeting 4-1BB costimulation to disseminated tumor lesions with bi-specific oligonucleotide aptamers. Mol. Ther. 19, 1878–1886 (2011).

    Article  CAS  Google Scholar 

  53. Siegers, G. M. et al. Anti-leukemia activity of in vitro-expanded human gamma delta T cells in a xenogeneic Ph+ leukemia model. PLoS ONE 6, e16700 (2011).

    Article  CAS  Google Scholar 

  54. Cho, Y., Lee, J. B. & Hong, J. Controlled release of an anti-cancer drug from DNA structured nano-films. Sci. Rep. 4, 4078 (2014).

    Article  Google Scholar 

  55. Lee, H. et al. Molecularly self-assembled nucleic acid nanoparticles for targeted in vivo siRNA delivery. Nat. Nanotechnol. 7, 389–393 (2012).

    Article  CAS  Google Scholar 

  56. Li, S. et al. A DNA nanorobot functions as a cancer therapeutic in response to a molecular trigger in vivo. Nat. Biotechnol. 36, 258–264 (2018).

    Article  CAS  Google Scholar 

  57. Li, Z., He, X., Luo, X., Wang, L. & Ma, N. DNA-programmed quantum dot polymerization for ultrasensitive molecular imaging of cancer cells. Anal. Chem. 88, 9355–9358 (2016).

    Article  CAS  Google Scholar 

  58. Zhang, P. et al. Near infrared-guided smart nanocarriers for microRNA-controlled release of doxorubicin/siRNA with intracellular ATP as fuel. ACS Nano 10, 3637–3647 (2016).

    Article  CAS  Google Scholar 

  59. Gustafson, H. H., Holt-Casper, D., Grainger, D. W. & Ghandehari, H. Nanoparticle uptake: the phagocyte problem. Nano Today 10, 487–510 (2015).

    Article  CAS  Google Scholar 

  60. Kelly, C., Jefferies, C. & Cryan, S.-A. Targeted liposomal drug delivery to monocytes and macrophages. J. Drug Deliv. 2011, 727241 (2011).

    Article  Google Scholar 

  61. Kratz, M. et al. Metabolic dysfunction drives a mechanistically distinct proinflammatory phenotype in adipose tissue macrophages. Cell Metab. 20, 614–625 (2014).

    Article  CAS  Google Scholar 

  62. Cassetta, L. et al. Human tumor-associated macrophage and monocyte transcriptional landscapes reveal cancer-specific reprogramming, biomarkers, and therapeutic targets. Cancer Cell 35, 588–602 (2019).

    Article  CAS  Google Scholar 

  63. Reardon, C. A. et al. Obesity and insulin resistance promote atherosclerosis through an IFNγ-regulated macrophage protein network. Cell Rep. 23, 3021–3030 (2018).

    Article  CAS  Google Scholar 

  64. Eng, J. K. et al. A deeper look into Comet—implementation and features. J. Am. Soc. Mass. Spectrom. 26, 1865–1874 (2015).

    Article  CAS  Google Scholar 

  65. Becker, L. et al. A macrophage sterol-responsive network linked to atherogenesis. Cell Metab. 11, 125–135 (2010).

    Article  CAS  Google Scholar 

  66. Heinecke, N. L., Pratt, B. S., Vaisar, T. & Becker, L. PepC: proteomics software for identifying differentially expressed proteins based on spectral counting. Bioinformatics 26, 1574–1575 (2010).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank N. Hansen, K. Bethke and S. Khan, as well as B. LaBomascus at Northwestern University for assistance with obtaining tumours from ER+ breast cancer patients. Tfebfl/fl mice were a gift from A. Ballabio, Telethon Institute of Genetics and Medicine. pMel and TRP1 mice were a gift from M. Swartz, University of Chicago. E0771 cells were a gift from M. Rosner, University of Chicago. B16F10 cells were a gift from T. Gajewski, University of Chicago. B16.OVA cells were a gift from J. Hubbell, University of Chicago. This work was supported by the Women’s Board Faculty Research Startup Funds and Ben May Department Startup Funds (L.B.), the University of Chicago Women’s Board (Y.K.) and the Ono Pharma Breakthrough Science Award (Y.K.). C.C. was supported by a Bernice Goldblatt Scholarship. K.C. was supported by a Schmidt Science Fellowship, in partnership with the Rhodes Trust. B.M. was supported by the National Cancer Institute (R25CA221767).

Author information

Authors and Affiliations

Authors

Contributions

C.C., K.C., Y.K. and L.B. conceived and designed the experiments. C.C., K.C., X.A.T., K.Q.S., A.H., A. Blank, B.M., C.A.R. and T.V. performed the experiments: A. Ballabio provided material support. N.P. and S.A.K. provided the patient tumours. All authors critically reviewed the manuscript. C.C., Y.K. and L.B. wrote the manuscript.

Corresponding authors

Correspondence to Yamuna Krishnan or Lev Becker.

Ethics declarations

Competing interests

L.B., Y.K., C.C. and K.C. are inventors on a provisional patent (related to DNA-based therapeutics delivery) filed by the University of Chicago. L.B. and Y.K. are co-founders of MacroLogic, a startup biotechnology company focused on developing DNA-conjugated therapeutics. A. Ballabio is a co-founder of CASMA Therapeutics and is an Advisory Board member of Next Generation Diagnostics and of Avilar Therapeutics. X.A.T., K.Q.S., A.H., A. Blank, B.M., N.P., C.A.R., S.A.K. and T.V. declare no competing interests.

Additional information

Peer review information Nature Nanotechnology thanks Chunhai Fan, Lisa Sevenich 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.

Extended data

Extended Data Fig. 1 TFEB is responsible for elevated lysosomal enzymes in M2-like macrophages.

a, Validation of lysosomal proteins elevated in M2 BMDMs by immunoblotting, related to Fig. 1d. Representative of 2 independent experiments. b, mRNA levels of lysosomal genes in M1 and M2 BMDMs. n = 3/group. c, Tfeb mRNA levels in M1 and M2 BMDMs. n = 3/group. d, Immunoblot of TFEB protein levels in M1 and M2 BMDMs. Representative of 3 independent experiments. e, Immunoblot of cytosolic and nuclear TFEB levels in M1 and M2 BMDMs. Representative of 2 independent experiments. f, Validation of mTfeb-/-. mRNA levels (top) n = 3/group and protein levels (bottom). Representative of 3 independent experiments. g, A comparison of lysosomal gene expression in M1 and M2 BMDMs from fl/fl mice versus M2 BMDMs from mTfeb-/- mice, n = 3/group; and a comparison of lysosomal gene expression in TAMs from fl/fl and mTfeb-/- E0771 tumors, n = 4/group. h, DQ-OVA degradation assays of fl/fl and mTfeb-/- M2 BMDMs. n = 3/group. Statistical significance was calculated via two-tailed Student’s t-test (P < 0.05 values are provided); error bars indicate the mean of independent experiments ± s.e.m. All measurements (n) are biological replicates.

Source data

Extended Data Fig. 2 TAMs exhibit increased lysosomal enzyme levels and activity.

a, Isolation of mammary ATMs from tumor-free mice and TAMs from E0771 mammary tumor-bearing mice. Purity of ATMs and TAMs was validated by flow cytometry. b, Immunoblots of lysosomal protein levels in ATMs and TAMs. Experiment was performed once with n = 3/group. c, DQ-OVA degradation assays of ATMs and TAMs. n = 3/group. d, mRNA expression of lysosomal genes in TAMs isolated from E0771 tumors and thioglycolate-elicited peritoneal macrophages from tumor-free mice. n = 3/group. Statistical significance was calculated via two-tailed Student’s t-test (P < 0.05 values are provided); error bars indicate the mean of independent experiments ± s.e.m. All measurements (n) are biological replicates.

Source data

Extended Data Fig. 3 TAMs from mTfeb-/- mice exhibit improved antigen cross-presentation with minimal phenotypic changes.

a-c, TAMs were isolated from E0771 tumors. a, Quantification of lysosomes in fl/fl and mTfeb-/- TAMs based on LAMP1 immunostaining. Schematic for quantification (left). Quantification of average LAMP1 signal/cell area (n = 10/group) with an average of >40 cells/field (middle). Representative images (right). LAMP1 (red) and DAPI (blue). b, Quantification of lysosomal pH in fl/fl and mTfeb-/- TAMs based on lysotracker staining. Representative flow cytometry image (left). Quantification of relative MFI of lysotracker signal (right). n = 3/group. c, Autophagy gene expression in fl/fl and mTfeb-/- TAMs (left, n = 5). LC3B and p62 protein levels in fl/fl and mTfeb-/- TAMs following treatment with vehicle (Veh) or chloroquine (CQ, 50μM) for 24 h (right). Veh = H2O. Experiment was performed once with n = 3/group. d, M1- and M2-associated gene expression in TAMs from fl/fl and mTfeb-/- E0771 tumors (left, n = 5/group), LLC1 tumors (middle, n = 5/group) and B16F10 tumors (right, n = 4 group). e-f, Quantification of pMel-CD8+ T cell activation (e) and proliferation (f) following co-culture with TAMs isolated from fl/fl and mTfeb-/- B16.OVA tumors. n = 6/group Statistical significance was calculated via two-tailed Student’s t-test (P < 0.05 values are provided); error bars indicate the mean of independent experiments ± s.e.m. ns; not significant. All measurements (n) are biological replicates.

Source data

Extended Data Fig. 4 Deleting Tfeb in myeloid cells attenuates tumor growth via CD8+ T cells (B16F10 & LLC1 models).

a, B16F10 tumor growth rates in fl/fl (n = 14) and mTfeb-/- (n = 10) mice (left). LLC1 tumor growth rates in fl/fl (n = 10) and mTfeb-/- (n = 8) mice (right). b, Tumor immune cell composition in B16F10 tumor bearing fl/fl (n = 8) and mTfeb-/- (n = 6) mice; Tumor immune cell composition in LLC1 tumor bearing fl/fl (n = 9) and mTfeb-/- (n = 8) mice. CD8+ Teff = effector CD8+ T cells. c, Blood CD8+ T cell levels in mice treated with α-CD8 or IgG antibodies. Representative flow cytometry data (left). Quantification of CD8+ and CD4+ T cells (right). n = 4/group. d, Final tumor volume in B16F10 (n = 5/group) and LLC1 (fl/fl: n = 6, mTfeb-/-: n = 7 (IgG), n = 6 (α-CD8)) tumor bearing fl/fl and mTfeb-/- mice treated with IgG or α-CD8 antibodies. Statistical significance was calculated via two-tailed Student’s t-test (P < 0.05 values are provided); error bars indicate the mean of independent experiments ± s.e.m. ns; not significant. All measurements (n) are biological replicates.

Extended Data Fig. 5 DNA nanodevice uptake and stability.

a, Schematic of various fluorescently labeled nucleic acid structures used for uptake studies in BMDMs. Each nucleic acid scaffold is either a single stranded or double stranded 38 mer DNA or RNA sequence. Each scaffold is labelled with an Alexa Fluor® 647 fluorophore on the 5′ end of one of the strands. b, Uptake of various types of nucleic acids by M2 BMDMs. n = 3/group. c, Native polyacrylamide gel of dsDNA incubated in 100% mouse serum for various time points. Intact dsDNA was quantified by densitometry. Representative of 2 independent experiments. d, Schematic of an E64 − DNA uptake competition assay in M1 and M2 BMDMs. e, Hoechst dye levels in individually cultured M1 and M2 BMDMs. f, E64 − DNA uptake by co-cultured M1 and M2 BMDMs. Representative flow cytometry data (left) and quantification (right) are shown. n = 3/group. Statistical significance was calculated via two-tailed Student’s t-test (P < 0.05 values are provided); error bars indicate the mean of independent experiments ± s.e.m. ns; not significant. All measurements (n) are biological replicates.

Source data

Extended Data Fig. 6 Effects of E64-DNA on the functional properties of TAMs.

a, Catalytic activity assays for lysosomal cysteine proteases (CTSB, CTSL; 5 nM) or aspartic proteases (CTSD, CTSE; 5 nM) in the presence of vehicle (Veh; PBS) or E64-DNA (25 nM). Results are plotted as fluorescence intensity at time t, relative to time 0 (I/Io). n = 3/group. b-d, TAMs isolated from E0771 tumors were treated with vehicle (Veh; PBS), DNA, E64, or E64-DNA (100 nM). b, Cell viability (Calcein-AM) following a 72 h exposure. n = 4/group. c, CTSB and CTSL protein levels following a 24 h exposure. Experiment was performed once with n = 3/group. d, Relative mRNA levels of autophagy genes following a 24 h exposure. n = 3/group. e, LC3B and p62 protein levels in DNA or E64-DNA (10uM) treated TAMs following a 24 h treatment with vehicle (Veh; H2O) or chloroquine (CQ, 50μM). Representative of 2 independent experiments. f, Effect of E64-DNA (2 h) on TBK and IRF3 phosphorylation. TAMs treated with 3’3′-cGAMP (10μg/mL, 6 h) were used as a positive control for STING activation Representative of 2 independent experiments. g, Effect of E64-DNA (24 h) on M1- and M2-associated gene expression. n = 3/group. Statistical significance was calculated via two-tailed Student’s t-test (P < 0.05 values are provided); error bars indicate the mean of independent experiments ± s.e.m. ns; not significant. All measurements (n) are biological replicates.

Source data

Extended Data Fig. 7 E64-DNA does not activate T cells through allostimulation or direct stimulation.

a-b, Control for allostimulation. CD8+ T cell activation (a) and proliferation (b) after 72 h of co-culture with E64-DNA-treated (100 nM) TAMs that had not been exposed to antigen. CD3/CD28 antibodies were included as a positive control for T cell activation. n = 3/group. c-d, Control for direct effects of E64-DNA on T cells. CD8+ T cell activation (c) and proliferation (d) after 72 h of culturing in complete growth media (Media) in the presence/absence of E64-DNA (100 nM). CD3/CD28 antibodies were included as a positive control for T cell activation. n = 3/group. Statistical significance was calculated via two-tailed Student’s t-test (P < 0.05 values are provided); error bars indicate the mean of independent experiments ± s.e.m. All measurements (n) are biological replicates.

Extended Data Fig. 8 Inhibiting aspartic protease activity in the lysosome has minimal effect on antigen cross-presentation by macrophages.

a, PepA-DNA design: one strand is conjugated with PepA on its 5’ end and the other with Alexa Fluor 647 to monitor uptake. b, Catalytic activity assays for lysosomal cysteine proteases (CTSB, CTSL; 5 nM) or aspartic proteases (CTSD, CTSE; 5 nM) in the presence of vehicle (Veh; PBS) or PepA-DNA (25 nM). Results are plotted as fluorescence intensity at time t, relative to time 0 (I/Io). n = 3/group. c–f, Peritoneal macrophages were isolated and treated with vehicle (Veh; PBS), DNA, PepA, or PepA-DNA (100 nM) for the indicated times and various functional endpoints were measured. c, Effect of PepA-DNA (2 h) on DQ-OVA degradation. n = 3/group. d, Quantification of MHCI-bound OVA257-264 on peritoneal macrophages 3 h post treatment with OVA protein or OVA257-264 peptide. n = 3/group. e–f, pMel-CD8+ T cell activation (e) and proliferation (f) after 72 h of co-culture with peritoneal macrophages pre-stimulated with irradiated B16F10 cells (irrB16). n = 3/group. Statistical significance was calculated via two-tailed Student’s t-test (P < 0.05 values are provided); error bars indicate the mean of independent experiments ± s.e.m. ns; not significant. All measurements (n) are biological replicates.

Extended Data Fig. 9 E64-DNA does not improve MHCII-restricted antigen presentation.

Effect of E64-DNA on MHCII-restricted antigen presentation by TAMs (isolated from E0771 tumors) pre-treated with E64-DNA, DNA, or E64 (100 nM) for 2 h. a–d, TAMs were incubated with OVA protein or OVA332-339 peptide for 3 h. OT-2 CD4+ T-cell activation (a–b) and proliferation (c–d) after 72 h of co-culture with TAMs. n = 3/group. e-f, TAMs were incubated with irradiated B16F10 cells (irrB16) or TRP1113-126 peptide for 3 h. TRP1 CD4+ T-cell activation (e) and proliferation (f) after 72 h of co-culture with TAMs. n = 3/group. Statistical significance was calculated via two-tailed Student’s t-test (P < 0.05 values are provided); error bars indicate the mean of independent experiments ± s.e.m. All measurements (n) are biological replicates.

Extended Data Fig. 10 E64-DNA attenuates tumor growth and improves antigen cross-presentation by TAMs in the B16.OVA model.

a, Experimental design (left). Effect of E64-DNA (25μg, i.v.) on B16.OVA tumor growth (right). n = 8/group. b, OT-1-CD8+ T cell activation (left) and proliferation (right) after 72 h of co-culture with TAM isolated from DNA or E64-DNA (i.v.) treated B16.OVA tumors. n = 6/group. c, pMel-CD8+ T cell activation (left) and proliferation (right) after 72 h of co-culture with TAMs isolated from DNA or E64-DNA (i.v.) treated B16.OVA tumors. n = 6/group. d-e. Effects of E64-DNA on CD8+ T cell activation and proliferation status 5 days after a single injection. Representative flow images (d) and quantification (e). n = 9/group. Statistical significance was calculated via two-tailed Student’s t-test (P < 0.05 values are provided); error bars indicate the mean of independent experiments ± s.e.m. All measurements (n) are biological replicates.

Supplementary information

Supplementary Information

Supplementary Figs. 1–4.

Reporting Summary

Supplementary Table 1

Shotgun proteomics analysis of M1 and M2 BMDMs.

Supplementary Table 2

Shotgun proteomics analysis of M1-like and M2-like TAMs from E0771 tumours.

Supplementary Table 3

Primers for PCR analysis.

Supplementary Table 4

DNA nanodevice sequences.

Source data

Source Data Fig. 3

Unprocessed western blots.

Source Data Fig. 4

Unprocessed gels.

Source Data Extended Data Fig. 1

Unprocessed western blots.

Source Data Extended Data Fig. 2

Unprocessed western blots.

Source Data Extended Data Fig. 3

Unprocessed western blots.

Source Data Extended Data Fig. 5

Unprocessed gels.

Source Data Extended Data Fig. 6

Unprocessed western blots.

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Cui, C., Chakraborty, K., Tang, X.A. et al. A lysosome-targeted DNA nanodevice selectively targets macrophages to attenuate tumours. Nat. Nanotechnol. 16, 1394–1402 (2021). https://doi.org/10.1038/s41565-021-00988-z

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