Skip to main content

Thank you for visiting nature.com. 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.

Anti-GD2 synergizes with CD47 blockade to mediate tumor eradication

Nature Medicine volume 28, pages 333–344 (2022)Cite this article

Subjects

Abstract

The disialoganglioside GD2 is overexpressed on several solid tumors, and monoclonal antibodies targeting GD2 have substantially improved outcomes for children with high-risk neuroblastoma. However, approximately 40% of patients with neuroblastoma still relapse, and anti-GD2 has not mediated significant clinical activity in any other GD2+ malignancy. Macrophages are important mediators of anti-tumor immunity, but tumors resist macrophage phagocytosis through expression of the checkpoint molecule CD47, a so-called ‘Don’t eat me’ signal. In this study, we establish potent synergy for the combination of anti-GD2 and anti-CD47 in syngeneic and xenograft mouse models of neuroblastoma, where the combination eradicates tumors, as well as osteosarcoma and small-cell lung cancer, where the combination significantly reduces tumor burden and extends survival. This synergy is driven by two GD2-specific factors that reorient the balance of macrophage activity. Ligation of GD2 on tumor cells (a) causes upregulation of surface calreticulin, a pro-phagocytic ‘Eat me’ signal that primes cells for removal and (b) interrupts the interaction of GD2 with its newly identified ligand, the inhibitory immunoreceptor Siglec-7. This work credentials the combination of anti-GD2 and anti-CD47 for clinical translation and suggests that CD47 blockade will be most efficacious in combination with monoclonal antibodies that alter additional pro- and anti-phagocytic signals within the tumor microenvironment.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Anti-CD47 and anti-GD2 synergize to mediate anti-tumor activity in xenograft models of neuroblastoma.
Fig. 2: CD47 blockade licenses TAMs to enhance the activity of anti-GD2 in a syngeneic model of neuroblastoma.
Fig. 3: Absence of neurotoxicity related to combined anti-GD2 and anti-CD47 treatment.
Fig. 4: Anti-GD2 blocks the interaction of GD2 with its ligand Siglec-7, an inhibitory immune receptor.
Fig. 5: Anti-GD2 antibody primes neuroblastoma cells for removal by the immune system.
Fig. 6: Anti-CD47 and anti-GD2 elicit anti-tumor responses in models of osteosarcoma via TAM activation.

Data availability

All statistics for the main and extended data figures are provided in the Supplementary Information. Source data for Figs. 1–3 and 5 and 6 and Extended Data Figs. 1–2 and 4–9 are supplied. The unprocessed gel blot image for Extended Data Fig. 3 is also provided. Source data are provided with this paper.

References

  1. Schulz, G. et al. Detection of ganglioside GD2 in tumor tissues and sera of neuroblastoma patients. Cancer Res. 44, 5914–5920 (1984).

    CAS  PubMed  Google Scholar 

  2. Long, A. H. et al. Reduction of MDSCs with all-trans retinoic acid improves CAR therapy efficacy for sarcomas. Cancer Immunol. Res. 4, 869–880 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Dobrenkov, K., Ostrovnaya, I., Gu, J., Cheung, I. Y. & Cheung, N. K. Oncotargets GD2 and GD3 are highly expressed in sarcomas of children, adolescents, and young adults. Pediatr. Blood Cancer 63, 1780–1785 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Mount, C. W. et al. Potent antitumor efficacy of anti-GD2 CAR T cells in H3-K27M+ diffuse midline gliomas. Nat. Med. 24, 572–579 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Cheresh, D. A., Rosenberg, J., Mujoo, K., Hirschowitz, L. & Reisfeld, R. A. Biosynthesis and expression of the disialoganglioside GD2, a relevant target antigen on small cell lung carcinoma for monoclonal antibody-mediated cytolysis. Cancer Res. 46, 5112–5118 (1986).

    CAS  PubMed  Google Scholar 

  6. Battula, V. L. et al. Ganglioside GD2 identifies breast cancer stem cells and promotes tumorigenesis. J. Clin. Invest. 122, 2066–2078 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Yu, A. L. et al. Anti-GD2 antibody with GM-CSF, interleukin-2, and isotretinoin for neuroblastoma. N. Engl. J. Med. 363, 1324–1334 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Ladenstein, R. et al. Interleukin 2 with anti-GD2 antibody ch14.18/CHO (dinutuximab beta) in patients with high-risk neuroblastoma (HR-NBL1/SIOPEN): a multicentre, randomised, phase 3 trial. Lancet Oncol. 19, 1617–1629 (2018).

    Article  CAS  PubMed  Google Scholar 

  9. Cheung, N. K. et al. Murine anti-GD2 monoclonal antibody 3F8 combined with granulocyte-macrophage colony-stimulating factor and 13-cis-retinoic acid in high-risk patients with stage 4 neuroblastoma in first remission. J. Clin. Oncol. 30, 3264–3270 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Hobbie, W. L. et al. Late effects in survivors of tandem peripheral blood stem cell transplant for high-risk neuroblastoma. Pediatr. Blood Cancer 51, 679–683 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Suh, E. et al. Late mortality and chronic health conditions in long-term survivors of early-adolescent and young adult cancers: a retrospective cohort analysis from the Childhood Cancer Survivor Study. Lancet Oncol. 21, 421–435 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Moreno, L. et al. Outcome of children with relapsed or refractory neuroblastoma: a meta-analysis of ITCC/SIOPEN European phase II clinical trials. Pediatr. Blood Cancer 64, 25–31 (2017).

    Article  CAS  PubMed  Google Scholar 

  13. Hingorani, P. et al. Phase II study of antidisialoganglioside antibody, dinutuximab, in combination with GM-CSF in patients with recurrent osteosarcoma (AOST1421): a report from the Children’s Oncology Group. J. Clin. Oncol. 38, 10508–10508 (2020).

    Article  Google Scholar 

  14. Edelman, M. et al. The anti-disialoganglioside (GD2) antibody dinutuximab (D) for second-line treatment (2LT) of patients (pts) with relapsed/refractory small cell lung cancer (RR SCLC): results from part II of the open-label, randomized, phase II/III distinct study. J. Clin. Oncol. 38, 9017–9017 (2020).

    Article  Google Scholar 

  15. Grant, S. C. et al. Targeting of small-cell lung cancer using the anti-GD2 ganglioside monoclonal antibody 3F8: a pilot trial. Eur. J. Nucl. Med. 23, 145–149 (1996).

    Article  CAS  PubMed  Google Scholar 

  16. Chao, M. P. et al. Calreticulin is the dominant pro-phagocytic signal on multiple human cancers and is counterbalanced by CD47. Sci. Transl. Med. 2, 63ra94 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Jaiswal, S. et al. CD47 is upregulated on circulating hematopoietic stem cells and leukemia cells to avoid phagocytosis. Cell 138, 271–285 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Sikic, B. I. et al. First-in-human, first-in-class phase I trial of the anti-CD47 antibody Hu5F9-G4 in patients with advanced cancers. J. Clin. Oncol. 37, 946–953 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Advani, R. et al. CD47 blockade by Hu5F9-G4 and rituximab in non-Hodgkin’s lymphoma. N. Engl. J. Med. 379, 1711–1721 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Chao, M. P. et al. Anti-CD47 antibody synergizes with rituximab to promote phagocytosis and eradicate non-Hodgkin lymphoma. Cell 142, 699–713 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Desai, A. V. et al. Pharmacokinetics of the chimeric anti-GD2 antibody, ch14.18, in children with high-risk neuroblastoma. Cancer Chemother. Pharmacol. 74, 1047–1055 (2014).

    Article  CAS  PubMed  Google Scholar 

  22. Weiss, W. A., Aldape, K., Mohapatra, G., Feuerstein, B. G. & Bishop, J. M. Targeted expression of MYCN causes neuroblastoma in transgenic mice. EMBO J. 16, 2985–2995 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Sockolosky, J. T. et al. Durable antitumor responses to CD47 blockade require adaptive immune stimulation. Proc. Natl Acad. Sci. USA 113, E2646–E2654 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Willingham, S. B. et al. The CD47-signal regulatory protein alpha (SIRPa) interaction is a therapeutic target for human solid tumors. Proc. Natl Acad. Sci. USA 109, 6662–6667 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Lammie, G., Cheung, N., Gerald, W., Rosenblum, M. & Cordoncardo, C. Ganglioside gd(2) expression in the human nervous-system and in neuroblastomas - an immunohistochemical study. Int. J. Oncol. 3, 909–915 (1993).

    CAS  PubMed  Google Scholar 

  26. Svennerholm, L. et al. Gangliosides and allied glycosphingolipids in human peripheral nerve and spinal cord. Biochim. Biophys. Acta 1214, 115–123 (1994).

    Article  CAS  PubMed  Google Scholar 

  27. Zhang, S. et al. Selection of tumor antigens as targets for immune attack using immunohistochemistry: I. Focus on gangliosides. Int J. Cancer 73, 42–49 (1997).

    Article  CAS  PubMed  Google Scholar 

  28. Ngamukote, S., Yanagisawa, M., Ariga, T., Ando, S. & Yu, R. K. Developmental changes of glycosphingolipids and expression of glycogenes in mouse brains. J. Neurochem. 103, 2327–2341 (2007).

    Article  CAS  PubMed  Google Scholar 

  29. Xiao, W. H., Yu, A. L. & Sorkin, L. S. Electrophysiological characteristics of primary afferent fibers after systemic administration of anti-GD2 ganglioside antibody. Pain 69, 145–151 (1997).

    Article  CAS  PubMed  Google Scholar 

  30. Sorkin, L. S. et al. Anti-GD2 with an FC point mutation reduces complement fixation and decreases antibody-induced allodynia. Pain 149, 135–142 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Hamers, F. P., Lankhorst, A. J., van Laar, T. J., Veldhuis, W. B. & Gispen, W. H. Automated quantitative gait analysis during overground locomotion in the rat: its application to spinal cord contusion and transection injuries. J. Neurotrauma 18, 187–201 (2001).

    Article  CAS  PubMed  Google Scholar 

  32. Loo, D. et al. Development of an Fc-enhanced anti-B7-H3 monoclonal antibody with potent antitumor activity. Clin. Cancer Res. 18, 3834–3845 (2012).

    Article  CAS  PubMed  Google Scholar 

  33. Crocker, P. R., Paulson, J. C. & Varki, A. Siglecs and their roles in the immune system. Nat. Rev. Immunol. 7, 255–266 (2007).

    Article  CAS  PubMed  Google Scholar 

  34. Wei, J. S. et al. Clinically relevant cytotoxic immune cell signatures and clonal expansion of T-cell receptors in high-risk MYCN-not-amplified human neuroblastoma. Clin. Cancer Res. 24, 5673–5684 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Asgharzadeh, S. et al. Clinical significance of tumor-associated inflammatory cells in metastatic neuroblastoma. J. Clin. Oncol. 30, 3525–3532 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Avril, T., Floyd, H., Lopez, F., Vivier, E. & Crocker, P. R. The membrane-proximal immunoreceptor tyrosine-based inhibitory motif is critical for the inhibitory signaling mediated by Siglecs-7 and -9, CD33-related Siglecs expressed on human monocytes and NK cells. J. Immunol. 173, 6841–6849 (2004).

    Article  CAS  PubMed  Google Scholar 

  37. Yamaji, T., Mitsuki, M., Teranishi, T. & Hashimoto, Y. Characterization of inhibitory signaling motifs of the natural killer cell receptor Siglec-7: attenuated recruitment of phosphatases by the receptor is attributed to two amino acids in the motifs. Glycobiology 15, 667–676 (2005).

    Article  CAS  PubMed  Google Scholar 

  38. Tsao, C. Y. et al. Anti-proliferative and pro-apoptotic activity of GD2 ganglioside-specific monoclonal antibody 3F8 in human melanoma cells. Oncoimmunology 4, e1023975 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Doronin, I. I. et al. Ganglioside GD2 in reception and transduction of cell death signal in tumor cells. BMC Cancer 14, 295 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Gardai, S. J. et al. Cell-surface calreticulin initiates clearance of viable or apoptotic cells through trans-activation of LRP on the phagocyte. Cell 123, 321–334 (2005).

    Article  CAS  PubMed  Google Scholar 

  41. Lo, M. et al. Effector-attenuating substitutions that maintain antibody stability and reduce toxicity in mice. J. Biol. Chem. 292, 3900–3908 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Roth, M. et al. Ganglioside GD2 as a therapeutic target for antibody-mediated therapy in patients with osteosarcoma. Cancer 120, 548–554 (2014).

    Article  CAS  PubMed  Google Scholar 

  43. Gibson, T. M. et al. Temporal patterns in the risk of chronic health conditions in survivors of childhood cancer diagnosed 1970–99: a report from the Childhood Cancer Survivor Study cohort. Lancet Oncol. 19, 1590–1601 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Jaffe, N., Puri, A. & Gelderblom, H. Osteosarcoma: evolution of treatment paradigms. Sarcoma 2013, 203531 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  45. Majzner, R. G. et al. Assessment of programmed death-ligand 1 expression and tumor-associated immune cells in pediatric. Cancer Tissues Cancer 123, 3807–3815 (2017).

    CAS  PubMed  Google Scholar 

  46. Yoshida, S. et al. Ganglioside GD2 in small cell lung cancer cell lines: enhancement of cell proliferation and mediation of apoptosis. Cancer Res. 61, 4244–4252 (2001).

    CAS  PubMed  Google Scholar 

  47. Rudin, C. M. et al. Pembrolizumab or placebo plus etoposide and platinum as first-line therapy for extensive-stage small-cell lung cancer: randomized, double-blind, phase III KEYNOTE-604 study. J. Clin. Oncol. 38, 2369–2379 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Aghighi, M. et al. Magnetic resonance imaging of tumor-associated macrophages: clinical translation. Clin. Cancer Res. 24, 4110–4118 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Wiebel, M. et al. Surface expression of the immunotherapeutic target GD2 in osteosarcoma depends on cell confluency. Cancer Rep. (Hoboken) 4, e1394 (2021).

  50. Slart, R., Yu, A. L., Yaksh, T. L. & Sorkin, L. S. An animal model of pain produced by systemic administration of an immunotherapeutic anti-ganglioside antibody. Pain 69, 119–125 (1997).

    Article  CAS  PubMed  Google Scholar 

  51. Song, L. et al. Vα24-invariant NKT cells mediate antitumor activity via killing of tumor-associated macrophages. J. Clin. Invest. 119, 1524–1536 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Chen, Y., Zhao, B. & Wang, X. Tumor infiltrating immune cells (TIICs) as a biomarker for prognosis benefits in patients with osteosarcoma. BMC Cancer 20, 1022 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Best, S. A. et al. Harnessing natural killer immunity in metastatic SCLC. J. Thorac. Oncol. 15, 1507–1521 (2020).

    Article  CAS  PubMed  Google Scholar 

  54. White, P., Liebhaber, S. A. & Cooke, N. E. 129×1/SvJ mouse strain has a novel defect in inflammatory cell recruitment. J. Immunol. 168, 869–874 (2002).

    Article  CAS  PubMed  Google Scholar 

  55. Shan, D., Ledbetter, J. A. & Press, O. W. Signaling events involved in anti-CD20-induced apoptosis of malignant human B cells. Cancer Immunol. Immunother. 48, 673–683 (2000).

    Article  CAS  PubMed  Google Scholar 

  56. Mohanty, S., Aghighi, M., Yerneni, K., Theruvath, J. L. & Daldrup-Link, H. E. Improving the efficacy of osteosarcoma therapy: combining drugs that turn cancer cell ‘don’t eat me’ signals off and ‘eat me’ signals on. Mol. Oncol. 13, 2049–2061 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Barkal, A. A. et al. CD24 signalling through macrophage Siglec-10 is a target for cancer immunotherapy. Nature 572, 392–396 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Wang, J. et al. Siglec-15 as an immune suppressor and potential target for normalization cancer immunotherapy. Nat. Med. 25, 656–666 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Siglec-15: an attractive immunotherapy target. Cancer Discov. 10, 7–8 (2020).

  60. Fisher, G. A. et al. A phase Ib/II study of the anti-CD47 antibody magrolimab with cetuximab in solid tumor and colorectal cancer patients. J. Clin. Oncol. 38, 114–114 (2020).

    Article  Google Scholar 

  61. Majzner, R. G. et al. Tuning the antigen density requirement for CAR T-cell activity. Cancer Discov. 10, 702–723 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Lynn, R. C. et al. c-Jun overexpression in CAR T cells induces exhaustion resistance. Nature 576, 293–300 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Weiskopf, K. et al. Engineered SIRPα variants as immunotherapeutic adjuvants to anticancer antibodies. Science 341, 88–91 (2013).

    Article  CAS  PubMed  Google Scholar 

  64. Gholamin, S. et al. Disrupting the CD47-SIRPα anti-phagocytic axis by a humanized anti-CD47 antibody is an efficacious treatment for malignant pediatric brain tumors. Sci. Transl. Med. 9, eaaf2968 (2017).

  65. Gray, M. A. et al. Targeted glycan degradation potentiates the anticancer immune response in vivo. Nat. Chem. Biol. 16, 1376–1384 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Wu, H. W. et al. Anti-CD105 antibody eliminates tumor microenvironment cells and enhances anti-GD2 antibody immunotherapy of neuroblastoma with activated natural killer cells. Clin. Cancer Res. 25, 4761–4774 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. George, J. et al. Comprehensive genomic profiles of small cell lung cancer. Nature 524, 47–53 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This work was supported by an Alex’s Lemonade Stand ‘A’ Award (R.G.M.) and National Institutes of Health P01 CA217959 (C.L.M., W.A.W. and R.G.M.). R.G.M. is the Taube Distinguished Scholar for Pediatric Immunotherapy at Stanford University School of Medicine. J.T. is supported by German Cancer Aid (Deutsche Krebshilfe) grant number P-91650709. This work was supported by the National Cancer Institute (R01-CA227942 to C.R.B., F30-CA232541 to B.A.H.S., U01-CA217864 to W.A.W. and U01-CA213273 and R35-CA231997 to J.S.), the American Cancer Society (postdoctoral fellowship to G.L.C.) and the Virginia and D. K. Ludwig Fund for Cancer Research (I.W., and M. Monje). B.A.H.S. is supported by the Stanford School of Medicine Medical Scientist Training Program (T32-GM007365). M.H.L. is supported by a Blavatnik Family Fellowship. P.L.L. is supported by the Stanford Bio-X Bowes Fellowship and the Stanford Medical Scientist Training Program. A.C.G. is supported by the Waxman Family Research Fund. We thank the Stanford Neuropathology Department for their help with immunohistochemistry. We thank K. Stegmaier and N. Mabe for providing the SY5Y-GD2-high cell line as well as expertise and advice. All cartoons were created with BioRender.com.

Author information

Author notes

  1. These authors contributed equally: Marie Menard, Benjamin A. H. Smith, Miles H. Linde.

Authors and Affiliations

  1. Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA

    Johanna Theruvath, Garry L. Coles, Guillermo Nicolas Dalton, Molly Thomas Radosevich, Shaurya Dhingra, Aidan Tousley, John Lattin, Peng Xu, Jing Huang, Andy He, Michelle Monje, Heike E. Daldrup-Link, Julien Sage, Crystal L. Mackall & Robbie G. Majzner

  2. Departments of Neurology, Pediatrics, and Neurological Surgery, Brain Tumor Research Center, University of California, San Francisco, San Francisco, CA, USA

    Marie Menard, Nicole Nasholm & William A. Weiss

  3. ChEM-H Institute, Stanford University, Stanford, CA, USA

    Benjamin A. H. Smith & Carolyn R. Bertozzi

  4. Department of Chemical & Systems Biology, Stanford University, Stanford, CA, USA

    Benjamin A. H. Smith & Carolyn R. Bertozzi

  5. Immunology Graduate Program, Stanford University School of Medicine, Stanford, CA, USA

    Miles H. Linde & John L. Silberstein

  6. Institute for Stem Cell Biology and Regenerative Medicine, Stanford, CA, USA

    Miles H. Linde, Allison Banuelos, Amira Barkal, Rachel E. Brewer, Kristopher D. Marjon, Michelle Monje, Heike E. Daldrup-Link, Irving L. Weissman & Ravindra Majeti

  7. Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA

    Miles H. Linde, Garry L. Coles, Elena Sotillo, Allison Banuelos, Sabine Heitzeneder, Amira Barkal, Rachel E. Brewer, Kristopher D. Marjon, Michelle Monje, Irving L. Weissman, Julien Sage, Ravindra Majeti, Crystal L. Mackall & Robbie G. Majzner

  8. Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA

    Miles H. Linde, Ravindra Majeti & Crystal L. Mackall

  9. Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA

    Wei Wu, Louise Kiru & Heike E. Daldrup-Link

  10. British Columbia Cancer Agency, Vancouver, BC, Canada

    Alberto Delaidelli & Poul H. Sorensen

  11. Department of Bioengineering, Stanford University Schools of Engineering and Medicine, Stanford, CA, USA

    John L. Silberstein & Jennifer R. Cochran

  12. Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA

    Anna C. Geraghty & Michelle Monje

  13. ALX Oncology, Burlingame, CA, USA

    Tracy C. Kuo, Emma R. B. Sangalang & Jaume Pons

  14. Ludwig Center for Cancer Stem Cell Research and Medicine, Stanford University School of Medicine, Stanford, CA, USA

    Amira Barkal, Rachel E. Brewer, Kristopher D. Marjon, Michelle Monje, Irving L. Weissman & Ravindra Majeti

  15. Stanford Medical Scientist Training Program, Stanford University, Stanford, CA, USA

    Amira Barkal & Payton L. Marshall

  16. Department of Comparative Medicine, Stanford University School of Medicine, Stanford, CA, USA

    Jose G. Vilches-Moure

  17. Chinese Academy of Medical Sciences (CAMS) Oxford Institute (COI), University of Oxford, Oxford, UK

    Ricardo Fernandes

  18. Nuffield Department of Medicine, University of Oxford, Oxford, UK

    Ricardo Fernandes

  19. Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA

    Michelle Monje & Irving L. Weissman

Authors
  1. Johanna Theruvath
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Marie Menard
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Benjamin A. H. Smith
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Miles H. Linde
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Garry L. Coles
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Guillermo Nicolas Dalton
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Wei Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Louise Kiru
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Alberto Delaidelli
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Elena Sotillo
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. John L. Silberstein
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Anna C. Geraghty
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Allison Banuelos
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Molly Thomas Radosevich
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Shaurya Dhingra
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Sabine Heitzeneder
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Aidan Tousley
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. John Lattin
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Peng Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Jing Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Nicole Nasholm
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Andy He
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. Tracy C. Kuo
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Emma R. B. Sangalang
    View author publications

    You can also search for this author in PubMed Google Scholar

  25. Jaume Pons
    View author publications

    You can also search for this author in PubMed Google Scholar

  26. Amira Barkal
    View author publications

    You can also search for this author in PubMed Google Scholar

  27. Rachel E. Brewer
    View author publications

    You can also search for this author in PubMed Google Scholar

  28. Kristopher D. Marjon
    View author publications

    You can also search for this author in PubMed Google Scholar

  29. Jose G. Vilches-Moure
    View author publications

    You can also search for this author in PubMed Google Scholar

  30. Payton L. Marshall
    View author publications

    You can also search for this author in PubMed Google Scholar

  31. Ricardo Fernandes
    View author publications

    You can also search for this author in PubMed Google Scholar

  32. Michelle Monje
    View author publications

    You can also search for this author in PubMed Google Scholar

  33. Jennifer R. Cochran
    View author publications

    You can also search for this author in PubMed Google Scholar

  34. Poul H. Sorensen
    View author publications

    You can also search for this author in PubMed Google Scholar

  35. Heike E. Daldrup-Link
    View author publications

    You can also search for this author in PubMed Google Scholar

  36. Irving L. Weissman
    View author publications

    You can also search for this author in PubMed Google Scholar

  37. Julien Sage
    View author publications

    You can also search for this author in PubMed Google Scholar

  38. Ravindra Majeti
    View author publications

    You can also search for this author in PubMed Google Scholar

  39. Carolyn R. Bertozzi
    View author publications

    You can also search for this author in PubMed Google Scholar

  40. William A. Weiss
    View author publications

    You can also search for this author in PubMed Google Scholar

  41. Crystal L. Mackall
    View author publications

    You can also search for this author in PubMed Google Scholar

  42. Robbie G. Majzner
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

J.T., M. Menard, B.A.H.S., M.H.L., G.L.C., G.N.D., W.W., L.K., A.D., E.S., J.L.S., A.C.G., A.B., M.T.R., S.D., S.H., A.T., J.L., P.X., J.H., N.N., A.H., A.B., R.B., K.D.M., J.G.V.-M., P.L.M., R.F. and R.G.M. designed experiments, performed experiments and/or performed data analysis. M. Monje, J.R.C., P.H.S., H.E.D.-L., I.L.W., J.S., R.M., C.R.B., W.A.W., C.L.M. and R.G.M. designed experiments and/or oversaw the research. T.C.K., E.R.B.S. and J.P. generated and provided ALX301. J.T., E.S. and R.G.M. wrote the manuscript. All authors reviewed the manuscript.

Corresponding author

Correspondence to Robbie G. Majzner.

Ethics declarations

Competing interests

R.G.M. and C.L.M. are founders of, hold equity in and receive consulting fees from Syncopation Life Sciences. C.L.M. is a founder of, holds equity in and receives consulting fees from Lyell Immunopharma. R.G.M. and E.S. are consultants for Lyell Immunopharma. R.G.M. is a consultant for NKarta, Illumina Radiopharmaceuticals, GammaDelta Therapeutics, Aptorum Group and Zai Labs. J.T. is a consultant for Dorian Therapeutics. C.L.M. has also received consulting fees from NeoImmune Tech, Nektar Therapeutics and Apricity Health and royalties from Juno Therapeutics for CD22-CAR. W.A.W. is a founder of, holds equity in and receives consulting fees from StemSynergy Therapeutics. R.M. is on the Board of Directors of BeyondSpring and the Scientific Advisory Boards of Coherus BioSciences, Kodikaz Therapeutic Solutions and Zenshine Pharmaceuticals. R.M. and I.W. are inventors on several patents related to CD47 cancer immunotherapy that are licensed to Gilead Sciences. J.P. is an employee and shareholder of ALX Oncology, and T.C.K. and E.R.B.S. are shareholders of ALX Oncology. J.S. receives research funding from Stemcentrx/Abbvie and Pfizer and licensed a patent to Forty Seven/Gilead on the use of CD47 blocking strategies in SCLC (with I.W.). C.R.B. is a co-founder of Redwood Biosciences (a subsidiary of Catalent), Enable Biosciences, Palleon Pharmaceuticals, InterVenn Bio, Lycia Therapeutics and OliLux Biosciences and is a member of the Board of Directors of Eli Lilly. J.R.C. is a co-founder and equity holder of xCella Biosciences, Combangio and Trapeze Therapeutics. All other authors declare no competing interests.

Peer review information

Nature Medicine thanks Leonid Metelitsa, John Anderson and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Editor recognition statement Saheli Sadanand was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

Additional information

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

Extended data

Extended Data Fig. 1 anti-GD2 and anti-CD47 synergize to promote tumor cell phagocytosis.

a-b, Representative Images of Incucyte based live cell phagocytosis assay. a, pHrodo red labeled KCNR (top) or CHLA255 (bottom) neuroblastoma cells were co-cultured with human blood derived macrophages in the presence of anti-GD2 mAb, anti-CD47 mAb or dual treatment. Red indicative of tumor cell phagocytosis. Images were obtained after 24 hours of co-culture. b, Magnified image of cells shown in a. c-d, Quantification of phagocytosis normalized to the phagocytosis in the untreated control for each cell line, c, KCNR (Untreated vs. GD2+CD47 p = 2.9E-14, GD2 vs. GD2+CD47 p = 5.4681E-10, CD47 vs. GD2+CD47 p = 1.13E-12) d, CHLA255 (Untreated vs. GD2+CD47 p = 3.3E-14, GD2 vs. GD2+CD47 p = 2.128E-12, CD47 vs. GD2+CD47 p = 3.3E-14). Data are mean values +/− s.e.m. of five experimental replicates. Experiment was performed one time. e, Flow-based phagocytosis assay of KCNR neuroblastoma cells co-cultured with human blood derived macrophages in the presence of different concentrations of anti-GD2 mAb, anti-CD47 mAb or dual treatment. % phagocytosing macrophages are reported. Data are mean values +/− s.d. of three experimental replicates. Experiment was performed one time. Statistical comparisons performed with one-way ANOVA with multiple comparisons correction, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, ns P>0.05.

Source data

Extended Data Fig. 2 Anti-CD47 and anti-GD2 synergize to mediate significant anti-tumor activity in orthotopic models of neuroblastoma.

One million KCNR neuroblastoma cells expressing GFP-luciferase were implanted into the renal capsule and treated four days later with IgG control, anti-G2 mAb, anti-CD47 (magrolimab, Hu5F9-G4) mAb or dual anti-GD2/anti-CD47 (Hu5F9-G4) every other day for three doses as in Fig. 1c. a, Quantification of tumor progression for each individual mouse as measured by flux values acquired via bioluminescence (BLI) photometry. b, BLI images of representative mice from each treatment group at different time points. Experiment was performed one time. N = 4 mice for IgG, and N = 5 for anti-GD2 per group and those groups are the same as in Fig. 1c–f. N=3 for anti-CD47 and anti-CD47 + anti-GD2 c, One million CHLA255 neuroblastoma cells expressing GFP-luciferase cells were implanted into the renal capsule in NSG mice. Four days later, mice were injected with IgG control, anti-GD2 mAb, anti-CD47 mAb or dual anti-GD2/anti-CD47 treatment every other day for three doses. d, Quantification of tumor progression for each individual mouse as measured by flux values acquired via BLI photometry. e, BLI images of representative mice from each treatment group shown in d at different time points. Red cross indicates deceased mouse. f, Survival curves for mice bearing tumors shown in d. d-f, Representative data from three independent experiments with N = 5 mice per group. All survival curves were compared using the Log-rank test (two-tailed).

Source data

Extended Data Fig. 3 Expression and affinity of ALX301, an engineered molecule capable of blocking murine CD47.

a, Schematic of ALX301: Murine IgG1 containing a N297A mutation was fused to a mutated SIRPα capable of binding murine CD47 with enhanced affinity. b, Purified ALX301 was detected on 4-20% Tris-glycine gel in non-reducing (NR) and reducing (R) buffer. ALX301 runs slightly larger than the expected 76.16 kDa (NR) and 38.038 kDa (R). c, ALX301 was immobilized on GLC sensor chip (Bio-rad). Recombinant mouse CD47 protein was injected as analyte over the chip at 5 concentrations, 3-fold dilution (100nM, 33.3nM, 11.1nM, 3.7nM, 1.2nM). Using Langmuir binding model for curve fitting, the binding of ALX301 to mouse SIRPα was determined to be 3.41nM. Association rate (ka), dissociation rate (kd), affinity (KD). b-c were performed one time.

Extended Data Fig. 4 Absence of toxicity of anti-GD2 and anti-CD47 treated mice in a model of metastatic neuroblastoma.

a, One million CHLA255 neuroblastoma cell were injected in the tail vein of the mice. After 4 days mice were treated intraperitoneally with PBS (control), anti-GD2, anti-CD47 or the combination of anti-GD2 and anti-CD47 3x/week for a total of 7 doses. b, Weight was serially recorded. c-e, CatWalk gait analysis was performed at indicated time points and c, swing speed, d, stride length and e, regularity index are reported from mice treated as in a. Data shown are mean values +/− s.e.m. n = 5 mice per group. Experiment was performed one time. f, Hematoxylin and eosin (H&E) stained sections of all organs examined were within normal limits as assessed by brightfield microscopy. Shown are sections of cerebrum, cerebellum, peripheral nerve, heart, liver, kidney, spleen, and lung of animals from mice treated as in a. Magnification: 40x, Scale bars: 20𝝁m.

Source data

Extended Data Fig. 5 Lack of synergy of anti-B7-H3 with anti-CD47 in xenograft models of neuroblastoma or osteosarcoma.

a, Graphs show flow cytometry-based quantification of phagocytosis of neuroblastoma cell lines co-cultured with human blood derived macrophages in the presence of anti-CD47 mAb, anti-B7-H3 mAb, or dual treatment, compared with untreated control; results normalized to the phagocytosis in the untreated control for each cell line and blood donor. Shown are mean values +/− s.d. of three experimental replicates. Statistical comparisons performed with one-way ANOVA with multiple comparisons correction (KCNR: control vs. anti-B7-H3 p = 0.9643, anti-CD47 vs. anti-B7-H3 and anti-CD47 p = 0.9976; CHLA255: control vs. anti-B7-H3 p>0.9999, anti-CD47 vs. anti-B7-H3 and anti-CD47 p = 0.8519). Representative data from at least three experiments with three different blood donors. Inset: B7-H3 expression as assessed by flow cytometry on respective cell lines. b, One million CHLA255 neuroblastoma cells were engrafted into NSG mice by tail-vein injection. On D+4, mice were treated with IgG control, anti-CD47 mAb, anti-B7-H3 mAb, or anti-B7-H3+anti-CD47 every other day for three doses. Quantification of tumor progression for each individual mouse as measured by flux values acquired via BLI photometry. c, BLI images of representative mice from each treatment group shown in b at one time point. d, Survival curves for mice bearing tumors shown in b. N = 5 mice per group, performed one time. Survival curves were compared using the Log-rank test (two-tailed). e, Graph shows flow cytometry-based quantification of phagocytosis of osteosarcoma cell lines co-cultured with human blood derived macrophages; results normalized to the phagocytosis in the untreated control for each cell line and blood donor. Shown are mean values +/− s.d. of three experimental replicates. Statistical comparisons performed as in a. Representative data from at least three experiments with three different blood donors. Inset: B7-H3 expression as assessed by flow cytometry on respective cell lines. f, Survival curves for mice that received hind leg injection of 1e6 MG63.3 cells and treated on D+7 with indicated antibodies 3x/week for four weeks. N = 5 mice per group, performed one time. Survival curves were compared using the Log-rank test (two-tailed). *P < 0.05, ns P>0.05.

Source data

Extended Data Fig. 6 Upregulation of ‘Eat me’ signal calreticulin and induction of cell death by ligation with anti-GD2 mAb on neuroblastoma cell lines.

a, Flow cytometric analysis of the levels of expression of GD2 on the surface of neuroblastoma cell lines CHLA255 and KCNR and their GD2-KO (B4GALNT1 KO) versions. b, Flow-based quantification of cell viability. Neuroblastoma cell lines and their GD2-KO versions were incubated with anti-GD2 mAb for the indicated times at 37 degrees and stained with DAPI. Percent of DAPI- populations were normalized to the untreated control for each cell line. Shown are mean values +/− s.d. of 6 experimental replicates. (CHLA255: 3hr p = 4.17E-08, 6hr p = 6.5044E-09, 12hr p = 1.2983E-11, 24hr p = 1.9094E-07, 48hr p = 7E-15, 72hr p = 1.2397E-08; CHLA255 GD2 KO: 3hr p = 0.3013, 6hr p = 0.506, 12hr p = 0.4125, 24hr p = 0.983, 48hr p = 0.4263, 72hr p = 0.8453; KCNR: 3hr p = 3.75E-10, 6hr p = 7.0881E-07, 12hr p = 1.1406E-07, 24hr p = 4.2986E-08, 48hr p = 2.6777E-06, 72hr p = 2.9544E-06; KCNR GD2 KO: 3hr p = 0.0059, 6hr p = 0.0083, 12hr p = 0.3223, 24hr p = 0.8197, 48hr p = 0.1443, 72hr p = 0.1002). c, Graph shows flow cytometric quantification of the expression of calreticulin (∆MFI) on the surface of live neuroblastoma cell lines treated as in b. Shown are mean values +/− s.d. of 3 experimental replicates. CHLA255: 3hr p = 6.57E-05, 6hr p = 0.0004, 12hr p = 0.0002, 24hr p = 9.2150E-06, 48hr p = 0.0167, 72hr p = 0.027; CHLA255 GD2 KO: 3hr p = 0.4701, 6hr p = 0.9563, 12hr p = 0.9024, 24hr p = 0.7235, 48hr p = 0.6415, 72hr p = 0.4069; KCNR: 3hr p = 7.41E-07, 6hr p = 7.4552E-07, 12hr p = 0.0038, 24hr p = 0.0024, 48hr p = 0.0019, 72hr p = 0.0005; KCNR GD2 KO: 3hr p = 0.671, 6hr p = 0.9445, 12hr p = 0.023, 24hr p = 0.2359, 48hr p = 0.0426, 72hr p = 0.8656. ∆MFI was calculated as the difference between the MFI in the PE channel of the calreticulin stained sample and the MFI in the PE channel of an isotype stained sample from the same experimental condition. The full time-course experiment was performed twice and the twelve-hour timepoint shown is identical to Fig. 4h. b-c, Statistical comparisons performed with the unpaired t-test, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, ns P>0.05.

Source data

Extended Data Fig. 7 Anti-CD47 and anti-GD2 synergize to mediate significant anti-tumor activity in xenograft model of small cell lung cancer (SCLC).

a, NCI-H69 SCLC were engrafted on both flanks of NSG mice. Quantification of tumor growth for each individual tumor was assessed by caliper measurement. b, Survival curves for mice bearing tumors shown in a. Survival curves were compared using the Log-rank test (two-tailed). Representative of two independent experiments with n = 5 mice per group.

Source data

Extended Data Fig. 8 Anti-GD2 and anti-CD47 treatment leads to an increase in macrophage infiltration and reduction of M2 macrophages.

a, Flow cytometric analysis of M2 macrophages (defined as CD163+ and CD206+, gated on CD45+, CD11b+, F4/80 + macrophages) in osteosarcoma tumors treated as described in Fig. 6, pooled results from two independent experiments. Shown are mean values +/− s.em. of 10 experimental replicates. Control vs. GD2+CD47 p = 0.0007, CD47 vs. GD2+CD47 p = 0.0738, GD2 vs. GD2+CD47 p = 0.8869. b-f, CHLA255 neuroblastoma tumor cells were engrafted in the flank and allowed to grow for 19 days before initiation of treatment with IgG control, anti-GD2 mAb, anti-CD47 mAb or dual anti-GD2/anti-CD47. After one week of treatment, tumors were harvested for immunohistochemistry (IHC) and flow cytometric analysis. b, Representative IHC images showing detection of macrophages via staining with anti-F4/80 on tumors harvested from mice treated with indicated mAbs. c, Quantification of percent of positive F4/80 staining obtained from IHC analysis. Shown are mean values +/− s.e.m. of 4-5 biologic replicates. Control vs. GD2+CD47 p = 0.0281, CD47 vs. GD2+CD47 p = 0.0415, GD2 vs. GD2+CD47 p = 0.2804. d, Quantification of percent of positive iNOS staining obtained from IHC analysis. Shown are mean values +/− s.e.m. of 4-5 biologic replicates. Control vs. GD2+CD47 p = 0.2401, CD47 vs. GD2+CD47 p = 0.413, GD2 vs. GD2+CD47 p = 0.7487. e-f, Flow cytometric analysis of M2 macrophages (defined as CD163+ and CD206+, gated on CD45+, CD11b+, F4/80 + macrophages) in CHLA255 tumors. e, Representative flow plots and f, quantification of M2 macrophages. Shown are mean values +/− s.e.m. of 4-5 biologic replicates. Control vs. GD2+CD47 p = 0.0218, CD47 vs. GD2+CD47 p = 0.9999, GD2 vs. GD2+CD47 p = 0.7102. b-f, Experiment was performed one time. All statistical comparisons were made between groups with the one-way ANOVA with correction for multiple comparisons correction, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, ns P>0.05.

Source data

Extended Data Fig. 9 GD2 antigen density may determine response to anti-GD2/anti-CD47.

a, Expression levels of CD47 mRNA in samples from three different datasets of primary tumors from high-risk, stage 4 neuroblastoma stratified by MYCN status (amplified vs non-amplified), age at diagnosis, and ploidy (where available). b, Expression levels of CD163, CD86, and SIGLEC7, together with CD47 and MYCN in samples from the same databases as in a grouped based on MYCN amplification status. c-d, Expression levels of CD47 and MYC family genes in samples from osteosarcoma c or SCLC d primary tumors. Samples are stratified based on high or low expression of any of the three MYC family genes: MYC, MYCL or MYCN. Dot plots represent log2 (a-c) or TPM (d) expression values. Error bars represent median ± s.d. Differences in gene expression levels between groups were calculated using the Mann-Whitney U test (unpaired, two-sided). e, Flow cytometric analysis of the expression of GD2 (top) and CD47 (bottom) on tumor cell lines used in in vivo models. f, Flow cytometric analysis of the expression of GD2 (top) and CD47 (bottom) on isogenic SH-SY5Y neuroblastoma GD2-low and GD2-high cell lines. g, Graphs show flow cytometry-based quantification of phagocytosis of SY5Y-GD2-low and SY5Y-GD2-high neuroblastoma cell lines co-cultured with human blood derived macrophages in the presence of anti-GD2 mAb, anti-CD47 mAb or dual treatment, compared with untreated control; results normalized to the phagocytosis in the untreated (UT) control for each cell line and blood donor. Shown are mean values +/− s.d. of three experimental replicates. SY5Y-GD2-high-UT vs. SY5Y-GD2-low-UT p>0.9999, SY5Y-GD2-high-GD2-treated vs. SY5Y-GD2-low-GD2-treated p = 5.1941E-07, SY5Y-GD2-high-CD47-treated vs. SY5Y-GD2-low-CD47-treated p = 0.5091, SY5Y-GD2-high-GD2+CD47-treated vs. SY5Y-GD2-low-GD2+CD47-treated p = 9.8567E-07. Representative data from two experiments performed with two different blood donors. Statistical comparisons performed with one-way ANOVA with multiple comparisons correction, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, ns P>0.05.

Source data

Supplementary information

41591_2021_1625_MOESM1_ESM.pdf

Supplementary Information Representative gating strategies for flow cytometry. a, Representative gating strategy for macrophage phagocytosis assay. b, Representative gating strategy for Ly6G depletion experiments. c, Representative gating strategy for M2 macrophage phenotyping experiments.

Reporting Summary

Supplementary Data

Statistical data for main and extended data figures

Supplementary Data

Supplementary Table 1

Source data

Source Data Fig. 1

Fig. 1_Source Data

Source Data Fig. 2

Fig. 2_Source Data

Source Data Fig. 3

Fig. 3_Source Data

Source Data Fig. 5

Fig. 5_Source Data

Source Data Fig. 6

Fig. 6_Source Data

Source Data Extended Data Fig. 1

ED Fig. 1 Source Data

Source Data Extended Data Fig. 2

ED Fig. 2 Source Data

Source Data Extended Data Fig. 4

ED Fig. 4 Source Data

Source Data Extended Data Fig. 5

ED Fig. 5 Source Data

Source Data Extended Data Fig. 6

ED Fig. 6 Source Data

Source Data Extended Data Fig. 7

ED Figure 7 Source Data

Source Data Extended Data Fig. 8

ED Figure 8 Source Data

Source Data Extended Data Fig. 9

ED Figure 9 Source Data

Source Data for ED Figure3

Source Data for ED Figure3_Uncropped Gel

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Theruvath, J., Menard, M., Smith, B.A.H. et al. Anti-GD2 synergizes with CD47 blockade to mediate tumor eradication. Nat Med 28, 333–344 (2022). https://doi.org/10.1038/s41591-021-01625-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41591-021-01625-x

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer