Ovarian cancer and triple-negative breast cancer are among the most lethal diseases affecting women, with few targeted therapies and high rates of metastasis. Cancer cells are capable of evading clearance by macrophages through the overexpression of anti-phagocytic surface proteins called ‘don’t eat me’ signals—including CD471, programmed cell death ligand 1 (PD-L1)2 and the beta-2 microglobulin subunit of the major histocompatibility class I complex (B2M)3. Monoclonal antibodies that antagonize the interaction of ‘don’t eat me’ signals with their macrophage-expressed receptors have demonstrated therapeutic potential in several cancers4,5. However, variability in the magnitude and durability of the response to these agents has suggested the presence of additional, as yet unknown ‘don’t eat me’ signals. Here we show that CD24 can be the dominant innate immune checkpoint in ovarian cancer and breast cancer, and is a promising target for cancer immunotherapy. We demonstrate a role for tumour-expressed CD24 in promoting immune evasion through its interaction with the inhibitory receptor sialic-acid-binding Ig-like lectin 10 (Siglec-10), which is expressed by tumour-associated macrophages. We find that many tumours overexpress CD24 and that tumour-associated macrophages express high levels of Siglec-10. Genetic ablation of either CD24 or Siglec-10, as well as blockade of the CD24–Siglec-10 interaction using monoclonal antibodies, robustly augment the phagocytosis of all CD24-expressing human tumours that we tested. Genetic ablation and therapeutic blockade of CD24 resulted in a macrophage-dependent reduction of tumour growth in vivo and an increase in survival time. These data reveal CD24 as a highly expressed, anti-phagocytic signal in several cancers and demonstrate the therapeutic potential for CD24 blockade in cancer immunotherapy.
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All primary data for all figures and supplementary figures are available from the corresponding authors upon request.
Majeti, R. et al. CD47 is an adverse prognostic factor and therapeutic antibody target on human acute myeloid leukemia stem cells. Cell 138, 286–299 (2009).
Gordon, S. R. et al. PD-1 expression by tumour-associated macrophages inhibits phagocytosis and tumour immunity. Nature 545, 495–499 (2017).
Barkal, A. A. et al. Engagement of MHC class I by the inhibitory receptor LILRB1 suppresses macrophages and is a target of cancer immunotherapy. Nat. Immunol. 19, 76–84 (2018).
Advani, R. et al. CD47 blockade by Hu5F9-G4 and rituximab in non-Hodgkin’s lymphoma. N. Engl. J. Med. 379, 1711–1721 (2018).
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).
Pirruccello, S. J. & LeBien, T. W. The human B cell-associated antigen CD24 is a single chain sialoglycoprotein. J. Immunol. 136, 3779–3784 (1986).
Chen, G. Y., Brown, N. K., Zheng, P. & Liu, Y. Siglec-G/10 in self–nonself discrimination of innate and adaptive immunity. Glycobiology 24, 800–806 (2014).
Chen, W. et al. Induction of Siglec-G by RNA viruses inhibits the innate immune response by promoting RIG-I degradation. Cell 152, 467–478 (2013).
Chen, G. Y. et al. Amelioration of sepsis by inhibiting sialidase-mediated disruption of the CD24–SiglecG interaction. Nat. Biotechnol. 29, 428–435 (2011).
Chen, G. Y., Tang, J., Zheng, P. & Liu, Y. CD24 and Siglec-10 selectively repress tissue damage-induced immune responses. Science 323, 1722–1725 (2009).
Toubai, T. et al. Siglec-G–CD24 axis controls the severity of graft-versus-host disease in mice. Blood 123, 3512–3523 (2014).
Crocker, P. R., Paulson, J. C. & Varki, A. Siglecs and their roles in the immune system. Nat. Rev. Immunol. 7, 255–266 (2007).
Abram, C. L. & Lowell, C. A. Shp1 function in myeloid cells. J. Leukoc. Biol. 102, 657–675 (2017).
Dietrich, J., Cella, M. & Colonna, M. Ig-like transcript 2 (ILT2)/leukocyte Ig-like receptor 1 (LIR1) inhibits TCR signaling and actin cytoskeleton reorganization. J. Immunol. 166, 2514–2521 (2001).
Tarhriz, V. et al. Overview of CD24 as a new molecular marker in ovarian cancer. J. Cell. Physiol. 234, 2134–2142 (2019).
Kristiansen, G. et al. CD24 expression is a new prognostic marker in breast cancer. Clin. Cancer Res. 9, 4906–4913 (2003).
Karaayvaz, M. et al. Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq. Nat. Commun. 9, 3588 (2018).
Mantovani, A., Sozzani, S., Locati, M., Allavena, P. & Sica, A. Macrophage polarization: tumor-associated macrophages as a paradigm for polarized M2 mononuclear phagocytes. Trends Immunol. 23, 549–555 (2002).
Liu, J. et al. Pre-clinical development of a humanized anti-CD47 antibody with anti-cancer therapeutic potential. PLoS ONE 10, e0137345 (2015).
Miksa, M., Komura, H., Wu, R., Shah, K. G. & Wang, P. A novel method to determine the engulfment of apoptotic cells by macrophages using pHrodo succinimidyl ester. J. Immunol. Methods 342, 71–77 (2009).
Okazaki, M., Luo, Y., Han, T., Yoshida, M. & Seon, B. K. Three new monoclonal antibodies that define a unique antigen associated with prolymphocytic leukemia/non-Hodgkin’s lymphoma and are effectively internalized after binding to the cell surface antigen. Blood 81, 84–94 (1993).
Shultz, L. D. et al. Human lymphoid and myeloid cell development in NOD/LtSz-scid IL2R γ null mice engrafted with mobilized human hemopoietic stem cells. J. Immunol. 174, 6477–6489 (2005).
Varga A. et al. Pembrolizumab in patients (pts) with PD-L1–positive (PD-L1+) advanced ovarian cancer: updated analysis of KEYNOTE-028. J. Clin. Oncol. 35, 5513 (2017).
Nanda, R. et al. Pebrolizumab in patients with advanced triple-negative breast cancer: Phase Ib KEYNOTE-012 study. J. Clin. Oncol. 34, 2460–2467 (2016).
Alsaab, H. O. et al. PD-1 and PD-L1 checkpoint signaling inhibition for cancer immunotherapy: mechanism, combinations, and clinical outcome. Front. Pharmacol. 8, 561 (2017).
Ayers M. et al. Molecular profiling of cohorts of tumor samples to guide clinical development of pembrolizumab as monotherapy. Clinical Cancer Res. https://doi.org/10.1158/1078-0432.CCR-18-1316 (2018).
Goldman, M., Craft, B., Brooks, A. N., Zhu, J. & Haussler, D. The USCS Xena Platform for cancer genomics data visualization and interpretation. Preprint at https://doi.org/10.1101/326470v3 (2018).
Martinez, F. O. Analysis of gene expression and gene silencing in human macrophages. Curr. Protoc. Immunol. 96, 14.28.1–14.28.23 (2012)
Brinkman, E. K., Chen, T., Amendola, M. & van Steensel, B. Easy quantitative assessment of genome editing by sequence trace decomposition. Nucleic Acids Res. 42, e168 (2014).
We thank the members of the Weissman laboratory, the Stanford Stem Cell Institute, R. L. Maute and K. S. Kao for advice and discussions; A. McCarty, T. Naik and L. Quinn for technical and logistical support; I. Wapnir for providing samples from patients with breast cancer; G. Wernig for providing human ascites samples; and G. Krampitz for the APL1 cell line. The research reported in this publication was supported by the Virginia D. K. Ludwig Fund for Cancer Research (NIHR01CA086017 and NIHGR01GM100315) and the NIH/NCI Outstanding Investigator Award (R35CA220434 to I.L.W.); the Stanford Medical Scientist Training Program (T32GM007365 to A.A.B); the National Cancer Institute (F30CA232472 to A.A.B); and the Program in Translational and Experimental Hematology T32 from the National Heart, Lung, and Blood Institute (1T32HL120824 to B.W.Z.). The contents of this manuscript are solely the responsibility of the authors.
A.A.B. and I.L.W. are co-inventors on a patent application (62/684,407) related to this work. I.L.W. is a founder, director, stockholder and consultant of Forty Seven, a cancer immunotherapy company.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Peer review information Nature thanks Gregory Beatty, Heinz Läubli and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Extended data figures and tables
a, Heat map of expression (log2(normalized counts + 1)) of CD24 from bulk TCGA and TARGET studies, as compared to known innate immune checkpoint molecules CD47, PD-L1 and B2M (tumour study abbreviations and n values are defined in Supplementary Table 1). b, Expression levels of CD24 in ovarian cancer (OV, red box plot, n = 419) in comparison with ovarian tissue from healthy individuals (grey box plot, n = 89), boxes show the median and whiskers indicate the 95th and 5th percentiles, ****P < 0.0001, unpaired, two-tailed Student’s t-test. c, Expression levels of CD24 in TNBC (red box plot, n = 124) in comparison with ER+PR+ breast cancer (purple box plot, n = 508) and healthy breast cells (grey box plot, n = 293). Each symbol represents an individual patient sample, boxes show the median and whiskers indicate the 95th and 5th percentiles, ****P < 0.0001, one-way ANOVA with multiple comparisons correction, F(2,922) = 95.80. d, Heat map of marker gene expression (y axis) across TNBC single cells (x axis) and cell clusters identified (top). e, UMAP dimension 1 and 2 plots displaying all TNBC cells analysed from six patients (n = 1,001 single cells); cell clusters are coloured by cell patient (for key, see right). f, CD24 compared with PD-L1 expression in the ‘Tumour epithelial cell’ cluster for individual TNBC patients. Number of single cells analysed: PT039, n = 151 cells; PT058, n = 11 cells; PT081, n = 196 cells; PT084, n = 84 cells; PT089, n = 117 cells; PT126, n = 60 cells. **P < 0.01, ****P < 0.0001. Data are violin plots showing median expression (log2(normalized counts +1) and quartiles (paired, two-tailed t-test).
Extended Data Fig. 2 Flow-cytometry analysis of CD24 and Siglec-10 expression in human tumours and primary immune cells.
a, Gating strategy for CD24+ cancer cells and Siglec-10+ TAMs in primary human tumours; after debris and doublet removal, cancer cells were assessed as DAPI−CD14−EpCAM+ and TAMs were assessed as DAPI−EpCAM−CD14+CD11b+. Plots are representative of six experimental replicates. b, Left, representative flow-cytometry histogram measuring the expression of Siglec-10 (blue shaded curves) versus isotype control (black lines) by non-cancerous peritoneal macrophages; numbers above bracketed line indicate the percentage of macrophages positive for expression of Siglec-10. Right, frequency of peritoneal macrophages positive for Siglec-10 among all peritoneal macrophages as defined by isotype controls (n = 9 donors). c, Gating strategy for CD24+ cells and Siglec-10+ cells among PBMC cell types; after debris and doublet removal, monocytes were assessed as DAPI−CD3−CD14+; T cells were assessed as DAPI−CD14−CD3+; natural killer (NK) cells were assessed as DAPI−CD14−CD3−CD56+; B cells were assessed as DAPI−CD56−CD14−CD3−CD19+. Plots are representative of two experimental replicates. d, Frequency of PBMC cell types positive for Siglec-10 (blue shaded bars) or CD24 (red shaded bars) out of total cell type (n = 3 donors). e, Left, flow-cytometry-based measurement of the surface expression of Siglec-10 on primary human donor-derived macrophages either unstimulated (top) or after stimulation with M2-polarizing cytokines TGFβ1 and IL-10 (bottom), numbers above bracketed line indicate the per cent of CD11b+ macrophages positive for expression of Siglec-10. Right, frequency of primary human donor-derived macrophages positive for Siglec-10 either without stimulation (unstimulated, M0) or following stimulation with TGFβ1 and IL-10 (stimulated, M2-like) (n = 30 unstimulated donors, 33 stimulated donors; unpaired, two-tailed Student’s t-test, ****P < 0.0001, data are mean ± s.e.m.). f, Flow-cytometry-based measurement of phagocytosis of MCF-7 cells by unstimulated donor-derived macrophages (white data points) versus TGFβ1 and IL-10-stimulated donor-derived macrophages (n = 3 donors, unpaired, one-tailed t-test, *P = 0.0168). g, Left, flow-cytometry-based measurement of the surface expression of Siglec-10 on matched, primary donor-derived macrophages either unstimulated (grey shaded curve), or after stimulation with TGFβ1 and IL-10 (blue line), or IL-4 (green line). Right, frequency of matched, human donor-derived macrophages positive for Siglec-10 either without stimulation (unstimulated, M0), or after stimulation with TGFβ1 and IL-10 (blue dots), or stimulated with IL-4 (n = 4 donors). Data are mean ± s.e.m.
a, Flow cytometry histogram measuring the binding of Siglec-10 to wild-type MCF-7 cells (blue shaded curve) versus MCF-7(ΔCD24) cells (red shaded curve). Data are representative of two experimental replicates. b, Merged flow cytometry histogram measuring the binding of Siglec-10–Fc to wild-type MCF-7 cells treated with heat-inactivated neuraminidase (WT-HI NA, blue line), wild-type MCF-7 cells treated with neuraminidase (WT-NA, green line), MCF-7(ΔCD24) cells treated with heat-inactivated neuraminidase (red line, ΔCD24-HI NA), and MCF-7(ΔCD24) cells treated with neuraminidase (purple line, ΔCD24-NA) as compared to isotype control (black line). Data are representative of two experimental replicates. c, Flow-cytometry-based measurement of phagocytosis of CD24+ parental MCF-7 cells (WT) and CD24– (ΔCD24) MCF-7 cells by co-cultured human macrophages in the presence of neuraminidase (+NA) or heat-inactivated neuraminidase (+HI-NA) (n = 4 donors; two-way ANOVA with multiple comparison’s correction, cell line F(1,12) = 180.5, treatment F(1,12) = 71.12, ****P < 0.0001, data are mean ± s.e.m.). d, f, Representative flow cytometry histogram measuring the binding of Siglec-5 (d) or Siglec-9 (f) to wild-type MCF-7 cells treated with either vehicle (blue shaded curve) or neuraminidase (green shaded curve). Data are representative of two experimental replicates. e, g, Frequency of macrophages positive for Siglec-5 (e) or Siglec-9 (g) among unstimulated M0 macrophages or stimulated M2-like macrophages (n = 4 donors). Data are mean ± s.e.m.
Extended Data Fig. 4 Anti-CD24 monoclonal antibodies promote phagocytic clearance of cancer cells over time.
a, Schematic of the inhibition of phagocytosis by CD24–Siglec-10. The inhibitory receptor Siglec-10 engages its ligand CD24 on cancer cells, leading to phosphorylation of the two immunoreceptor tyrosine-based inhibition motifs in the cytoplasmic domain of Siglec-10 and subsequent anti-inflammatory, anti-phagocytic signalling cascades mediated by SHP-1 and SHP-2 phosphatases; upon the addition of a CD24 blocking antibody, macrophages are disinhibited and are thus capable of phagocytosis-mediated tumour clearance. b, Quantification of phagocytosis events of MCF-7 cells treated with anti-CD24 mAb (red curve) versus IgG control (blue curve) as measured by live-cell microscopy over time, normalized to maximum measured phagocytosis events per donor (n = two donors; P value computed by two-way ANOVA of biological replicates, F(1,24) = 65.02). Line is the mean of two biological replicates with individual replicates shown. c, Representative fluorescence microscopy images of in vitro phagocytosis of MCF-7 cells (mCherry+, red) by macrophages (Calcein, AM; green) in the presence of IgG control (left), anti-CD24 mAb (middle), or anti-CD24 mAb and anti-CD47 mAb (right), after 6 h of co-culture. Experiment was repeated with three donors. Scale bar, 100 μm. d, Representative Z-stack images collected from high-resolution confocal fluorescence microscopy of macrophage phagocytosis demonstrating engulfment of whole MCF-7 cells (mCherry+, red) by macrophages (Calcein, AM; green). Experiment was repeated with three donors. Scale bar, 50 μm.
Extended Data Fig. 5 CD24 antibody blockade of CD24–Siglec-10 signalling promotes dose-responsive enhancement of phagocytosis.
a, Gating strategy for in vitro phagocytosis assay. Following debris and doublet removal, phagocytosis was assessed as the frequency of DAPI−CD11b+FITC+ events out of all DAPI−CD11b+ events. Numbers indicate frequency of events out of previous gate. Plots are representative of at least 10 experimental replicates. b, Dose–response relationship of anti-CD24 mAb on phagocytosis of MCF-7 cells, concentrations listed on the x axis as compared to IgG control (n = 3 donors). Connecting line is mean. c, Flow-cytometry-based measurement of phagocytosis of NCI-H82 cells by donor-derived macrophages (n = 3 donors) in the presence of anti-CD24 mAb as compared to IgG control; each symbol represents an individual donor (paired, two-tailed Student’s t-test, ***P = 0.0001). Data are mean ± s.e.m. d, Flow-cytometry-based measurement of phagocytosis of CD24+ parental MCF-7 cells (WT) and CD47– (ΔCD47) MCF-7 cells by co-cultured human macrophages, in the presence or absence of anti-CD24 mAb (horizontal axis), (n = 4 donors; two-way ANOVA with multiple comparisons correction, cell line F(1,8) = 6.490; treatment F(1,8) = 98.73, **P = 0.0054). Data are mean ± s.e.m. e, Flow-cytometry-based measurement of phagocytosis of Panc1 pancreatic adenocarcinoma cells in the presence of anti-CD24 mAb, cetuximab (anti-EGFR), or both anti-CD24 mAb and cetuximab, as compared to IgG control (n = 6 donors) (one-way ANOVA with multiple comparisons correction, F(3,20) = 66.10, *P = 0.0373, **P = 0.0057, data are mean ± s.e.m.).
Extended Data Fig. 6 The opsonization effect of anti-CD24 mAb is minor and CD24 blockade promotes phagocytosis of primary TNBC.
a, Left, representative flow cytometry histogram measuring the expression of EpCAM (green shaded curve) by parental MCF-7 cells; number above bracketed line indicates the percentage of MCF-7 cells positive for expression of EpCAM. Right, flow cytometry–based measurement of phagocytosis of parental MCF-7 cells by co-cultured human macrophages, in the presence of either IgG control, anti-EpCAM mAb or anti-CD24 mAb (n = 4 donors; repeated measures ANOVA with multiple comparisons correction, F(2,9) = 340.9, *P = 0.0287, **P = 0.0015, ****P < 0.0001). Data are mean ± s.e.m. b, Fold change in phagocytosis by M0 (unstimulated) or M2-like (TGFβ1, IL-10-stimulated) macrophages upon the addition of anti-EpCAM mAb as compared to IgG control (n = 9 donors, paired, two-tailed t-test). Data are mean ± s.e.m. c, Flow-cytometry-based measurement of anti-CD24 mAb-induced phagocytosis of MCF-7 cells by untreated macrophages (white bar) versus macrophages treated with anti-CD16/32 mAb (+FcR blockade, blue bar) (n = 3 macrophage donors. Paired, two-tailed t-test. Each point represents an individual donor. *P = 0.0358). Data are mean ± s.e.m. d, Response to anti-CD24 mAb by M2-like macrophages compared with M0 macrophages; each symbol represents an individual donor (n = 4, M0 donors; n = 6, M2-like donors; unpaired, two-tailed Student’s t-test, *P = 0.0160). e, Pearson correlation between stimulated (M2-like) donor-derived macrophage Siglec-10 expression and response to anti-CD24 mAb as computed by the phagocytosis fold change between anti-CD24 mAb treatment and IgG control (n = 7 donors); exponential growth curve is shown. f, Spearman correlation between cancer cell CD24 expression and baseline, un-normalized phagocytosis levels (IgG control) averaged across all donors per cell line. Exponential growth equation is shown (n values are the same as in Fig. 3b and Extended Data Fig. 5c, *P = 0.0417). Data are mean ± s.e.m. g, Flow-cytometry-based measurement of phagocytosis of a sample of primary TNBC cells from a patient, in the presence of anti-CD24 mAb, anti-CD47 mAb, or both anti-CD24 mAb and anti-CD47 mAb, as compared to IgG control (n = 3 macrophage donors challenged with n = 1 primary TNBC donor; repeated-measures one-way ANOVA with multiple comparisons correction, F(1.217,2.434) = 26.17). Each point represents an individual donor. *P = 0.0434, **P = 0.0028. Data are mean ± s.e.m.
Gating strategy for in vivo TAM phagocytosis of MCF-7 cells; after debris and doublet removal, TAM phagocytosis is assessed as the frequency of DAPI−CD11b+F4/80+GFP+ events out of total DAPI−CD11b+F4/80+ events; M1-like TAMs assessed as DAPI−CD11b+F4/80+CD80+, numbers indicate frequency of events out of the previous gate. Plots are representative of three experimental replicates.
Extended Data Fig. 8 Characterization of MCF-7 wild-type and MCF-7(ΔCD24) cells in vitro and in vivo.
a, Representative flow cytometry plots demonstrating TAM phagocytosis in GFP-luciferase+CD24+ (WT) MCF-7 tumours (left) versus CD24– (ΔCD24) MCF-7 tumours (middle), numbers indicate frequency of phagocytosis events out of all TAMs. Right, frequency of phagocytosis events out of all TAMs in wild-type tumours versus ΔCD24 tumours 28 days after engraftment (WT, n = 10; ΔCD24, n = 9; unpaired, two-tailed Student’s t-test, ****P < 0.0001). b, Frequency of TAMs positive for CD80 (M1-like) as per gating in a, among all TAMs macrophages as defined by fluorescence minus one controls (WT, n = 10; ΔCD24, n = 9; unpaired, two-tailed Student’s t-test, *P < 0.0203). Data are mean ± s.e.m. c, In vitro proliferation rates of MCF-7 wild-type and MCF-7(ΔCD24) as assessed by a plot of confluence percentage over time (n = 6 technical replicates, one experimental replicate). Individual technical replicates are shown, the connecting line indicates the mean. d, Flow-cytometry-based measurement of the surface expression of CD24 on MCF-7 cells (blue shaded curve) versus CD24 knockout cells (ΔCD24) (red shaded curve) before tumour engraftment as compared to isotype control (black line), numbers above the bracketed line indicate the percentage of MCF-7 wild-type cells positive for expression of CD24. The plot is representative of ten experimental replicates. e, Left, representative flow-cytometry histogram of the surface expression of CD24 on day-35 wild-type MCF-7 tumours (blue shaded curve) versus day-35 CD24 knockout tumours (ΔCD24) (red shaded curve) as compared to isotype control (black line). Right, flow-cytometry-based measurement of the frequency of CD24+ cells among all cancer cells in day-35 wild-type tumours versus day 35 ΔCD24 tumours (WT, n = 4; ΔCD24, n = 4). Data are mean ± s.e.m. f, Representative flow cytometry plots of tissue-resident macrophages out of total live cells in vehicle-treated mice (left) compared with anti-CSF1R-treated mice (middle); numbers indicate frequency of CD11b+F4/80+ macrophage events out of total live events. Right, frequency of TAMs (CD11b+F4/80+) out of total live cells in vehicle-treated mice (n = 5, blue shaded box plot) versus anti-CSF1R-treated mice (n = 4, red shaded box plot) as measured by flow cytometry. **P < 0.01. Box plots depict mean and range.
a, In vivo phagocytosis of wild-type or ΔCd24a cancer cells by mouse TAMs. Flow cytometry–based measurement of in vivo phagocytosis of CD24+GFP+ ID8 cells (WT) versus CD24–GFP+ ID8 cells (ΔCd24a) by mouse peritoneal macrophages (n = 5 mice; unpaired, two-tailed Student’s t-test with multiple comparisons correction, *P = 0.0196). b, Representative bioluminescence image of tumour burden in C57Bl/6 mice with ID8 wild-type versus ID8(ΔCd24a) tumours (image taken 49 days after engraftment and representative of one experimental replicate). c, Burden of ID8 wild-type tumours (blue) versus ID8(ΔCd24a) tumours (red) as measured by bioluminescence imaging (WT, n = 5; ΔCd24a, n = 5; two-way ANOVA with multiple comparisons correction, tumour genotype F(1,48) = 10.70, ***P = 0.0001). Data are representative of one experimental replicate. d, Extended measurement (as in Fig. 4e) of burden of MCF-7 wild-type tumours treated with IgG control (blue) versus anti-CD24 mAb (red) as measured by bioluminescence (IgG control, n = 5; anti-CD24 mAb, n = 5; days on which treatment was administered are indicated by arrows below the x axis; data are of one experimental cohort; two-way ANOVA with multiple comparisons correction, tumour treatment F(1,81) = 16.75). ****P < 0.0001. Data are mean ± s.e.m.
Extended Data Fig. 10 Anti-CD24 mAb induces B cell clearance but does not bind human red blood cells, and CD47 and CD24 demonstrate inversely correlated expression in human diffuse large B-cell lymphoma.
a, Flow-cytometry-based measurement of phagocytosis of B cells (n = 4 donors, pooled) by donor-derived macrophages (n = 4 donors) in the presence of anti-CD24 mAb as compared to IgG control; each symbol represents an individual donor (paired, two-tailed Student’s t-test, ***P = 0.0008). b, Left, representative flow cytometry histogram measuring the expression of CD24 (red line) and CD47 (blue line) by human red blood cells (RBCs); right, flow-cytometry-based measurement of the frequency of CD24+ compared with CD47+ RBCs out of total RBCs (n = 3 donors). Data are mean ± s.e.m. c, Left, expression levels in log2(normalized counts + 1) of CD24 and CD47 in diffuse large B cell lymphomas from TCGA (n = 48); data are divided into quadrants by median expression of each gene as indicated by dotted lines. The number and percentage of total patients in each quadrant are indicated on the plot. Each dot indicates a single patient. Right, two-dimensional contour plot of expression levels of CD24 and CD47 in the large B cell lymphoma samples featured in the left plot.
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Barkal, A.A., Brewer, R.E., Markovic, M. et al. CD24 signalling through macrophage Siglec-10 is a target for cancer immunotherapy. Nature 572, 392–396 (2019). https://doi.org/10.1038/s41586-019-1456-0
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