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Cooperative phagocytosis of solid tumours by macrophages triggers durable anti-tumour responses

Nature Biomedical Engineering volume 7, pages 1081–1096 (2023)Cite this article

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Abstract

In solid tumours, the abundance of macrophages is typically associated with a poor prognosis. However, macrophage clusters in tumour-cell nests have been associated with survival in some tumour types. Here, by using tumour organoids comprising macrophages and cancer cells opsonized via a monoclonal antibody, we show that highly ordered clusters of macrophages cooperatively phagocytose cancer cells to suppress tumour growth. In mice with poorly immunogenic tumours, the systemic delivery of macrophages with signal-regulatory protein alpha (SIRPα) genetically knocked out or else with blockade of the CD47–SIRPα macrophage checkpoint was combined with the monoclonal antibody and subsequently triggered the production of endogenous tumour-opsonizing immunoglobulin G, substantially increased the survival of the animals and helped confer durable protection from tumour re-challenge and metastasis. Maximizing phagocytic potency by increasing macrophage numbers, by tumour-cell opsonization and by disrupting the phagocytic checkpoint CD47–SIRPα may lead to durable anti-tumour responses in solid cancers.

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Fig. 1: Macrophages cooperatively phagocytose IgG-opsonized cancer cells in engineered tumouroids.
Fig. 2: Macrophage clusters in tumouroids are consistent with cooperative phagocytosis.
Fig. 3: Macrophages infiltrate, cluster and repress CD47-depleted syngeneic tumours in vivo only in combination with therapeutic IgG opsonization.
Fig. 4: Engineered macrophages phagocytose cancer cells efficiently and clear WT tumours in a dose-dependent fashion.
Fig. 5: Acquired anti-tumour immunity is required for long-term survival and protects against tumour re-challenge, experimental metastases and target antigen loss.
Fig. 6: Convalescent serum IgG drives B16-specific phagocytosis and clustering in tumouroids, and suppresses tumour initiation in vivo.
Fig. 7: Cooperative macrophages eliminate tumour cells to initiate an acquired immune response with phagocytic feedback.

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Data availability

The main data supporting the results in the study are available within the paper and its Supplementary Information. Source data are provided with this paper. Source data for the tumour-growth curves in Figs. 3f and 6c and in Extended Data Figs. 6a and 9a,b are provided with this paper. No large sequencing datasets were generated as part of this study, yet publicly available data from The Cancer Genome Atlas, The Human Protein Atlas and the National Center for Biotechnology Information GEO repository were accessed via the identifiers provided in Methods and in the relevant figure captions.

Code availability

Python code to generate random and structured simulated images is provided in Supplementary Information.

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Acknowledgements

This work was supported by funding from the National Institutes of Health (NIH) and the National Science Foundation (NSF). D.E.D. discloses support for the research described in this study from NIH (U54 CA193417, U01 CA254886 and R01 HL124106), NSF (Materials Research Science and Engineering Center DMR-1720530 and DMR-1420530 and Grant Agreements CMMI 1548571 and 154857) and the Pennsylvania Department of Health (HRFF 4100083101). L.J.D. discloses support for the research described in this study from NIH (F32 CA228285). J.C.A and B.H.H. disclose support from the NSF (DGE-1845298). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH or NSF. We thank C. Van Dang of the Wistar Institute for providing YUMM2.1 cells, S. Singhal for providing TC-1 cells and I. Brodsky of Penn Vet for providing editable CIM lines. We additionally thank J. Lee for aiding in development of the gene editing pipeline and S. Shin of Penn Vet for support on CIM progenitors. We acknowledge the following University of Pennsylvania core facilities: Cell Center, Stem Cell & Xenograft Core, Molecular Pathology & Imaging Core (supported by the Center for Molecular Studies in Digestive and Liver Diseases NIH/NIDDK Grant P30 DK050306), the Penn Vet Comparative Pathology Core, the Cell & Developmental Biology Microscopy Core, the Penn Cytomics & Cell Sorting Shared Research Laboratory (supported by the Abramson Cancer Center NIH/NCI Grant P30 CA016520) and the Penn Genomic Analysis Core.

Author information

Author notes

  1. These authors contributed equally: Lawrence J. Dooling, Jason C. Andrechak.

Authors and Affiliations

  1. Molecular and Cell Biophysics Lab, University of Pennsylvania, Philadelphia, PA, USA

    Lawrence J. Dooling, Jason C. Andrechak, Brandon H. Hayes, Siddhant Kadu, William Zhang, Ruby Pan, Manasvita Vashisth, Cory M. Alvey & Dennis E. Discher

  2. Physical Sciences-Oncology Center at Penn, University of Pennsylvania, Philadelphia, PA, USA

    Lawrence J. Dooling, Jason C. Andrechak, Brandon H. Hayes, Siddhant Kadu, William Zhang, Ruby Pan, Manasvita Vashisth, Cory M. Alvey & Dennis E. Discher

  3. Bioengineering Graduate Group, University of Pennsylvania, Philadelphia, PA, USA

    Jason C. Andrechak, Brandon H. Hayes, William Zhang, Leyuan Ma & Dennis E. Discher

  4. Department of Biomedical Sciences, College of Medicine, Florida State University, Tallahassee, FL, USA

    Jerome Irianto

  5. Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Leyuan Ma

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  1. Lawrence J. Dooling
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Contributions

J.C.A., L.J.D. and D.E.D. designed the research. J.C.A., L.J.D., B.H.H., S.K., W.Z., R.P. and J.I. performed experiments. J.C.A., L.J.D., B.H.H., S.K., W.Z., R.P., M.V. and J.I. analysed data. J.C.A., L.J.D., B.H.H., J.I. and C.M.A. developed methodology. L.M. provided materials. D.E.D. supervised the work. J.C.A., L.J.D. and D.E.D. wrote the paper.

Corresponding author

Correspondence to Dennis E. Discher.

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Nature Biomedical Engineering thanks George Georgiou, In-San Kim and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Characterization of B16 tumouroids and subcutaneous tumours.

a, Brightfield and confocal microscopy of B16 tumouroids. Left: Brightfield image of a B16 tumouroid three days after 1000 cells were seeded atop an agarose gel. Scale bar: 0.5 mm. Right: Confocal max intensity projections (xy, xz planes) of GFP (green) and Hoechst 33342 (blue) in a B16 tumouroid fixed ~24 h after 100 cells were seeded in a non-adhesive well. Scale bar: 100 µm. b-d, Tumouroid cohesion depends on Ca2+ and the actin cytoskeleton. Transcriptomic analysis (b-i) of cadherin gene expression in cultured B16 cells (GSE162105) (ref. 72) and immunoblotting (b-ii) of B16 membrane, cytoplasmic, and nuclear protein fractions for N-cadherin, lamin-A/C, and tubulin. The uncropped blots are shown in Supplementary Fig. 5. Tumouroid (GFP+) area (c) following addition of 2 mM EDTA or EGTA (n = 16 tumouroids for PBS control or EGTA and n = 14 tumouroids for EDTA). In the box plots, the centreline is the median, the box is the interquartile range (IQR) from the 25th to 75th percentiles, and the whiskers extend over the entire range of the data. Statistical significance was assessed by one-way ANOVA at t = 1 h or 3 h, and adjusted p values were determined by Dunnett’s multiple comparisons test between PBS and EDTA or EGTA (p < 0.001 for all comparisons). Representative images depict GFP fluorescence in tumouroids at t = 3 h after EDTA (top) and PBS (bottom) treatment. Scale bar: 200 µm. Tumouroid area (d) following addition of 1 µM Latrunculin A (LatA) or DMSO vehicle (n = 16 tumouroids per condition, box plot as described in c). Statistical significance was assessed by Welch’s t-test (unpaired, two-tailed) between DMSO control and LatA treatment at t = 1 h or 3 h (p < 0.001 for both comparisons). Representative images depict GFP fluorescence in tumouroids at t = 3 h after treatment with LatA (top) and DMSO (bottom). Scale bar: 200 µm. e, Photographs of subcutaneous (s.c.) B16 tumours in mice dissected on day 4, 8, or 12 after tumour cell injection. Elongation of early-stage tumours was often observed in the direction in which the needle was inserted during s.c. injection (left). Tumour area calculated in ImageJ is reported beneath each photograph. Scale bars: 10 mm (left) and 5 mm (right). f, Trichrome-stained B16 tumour section. Insets depict the cellular (maroon cytoplasm and black nuclei) tumour interior (region 1) and fibrous ECM (blue) and large, round fat droplets (white) at the tumour periphery (region 2). Scale bar: 1 mm. Inset scale bar: 50 µm. g,h, Ex vivo pipette aspiration rheology of B16 tumours. Brightfield images (g-i) depict the extension (L) of tumour into the pipette after 90 s of aspiration at the indicated ΔP for an interior tumour region that exhibited large L and required low ΔP (left) and for a peripheral tumour region (fibrotic capsule and adjacent subcutaneous tissue) that exhibited small L and required higher ΔP for measurable deformation (right). Scale bar: 50 µm. Tissue strain L/RP, where RP is the radius of the pipette, is plotted (g-ii) for the constant pressure creep phase (0–90 s) and after the pressure was released back to ΔP = 0 for a representative interior tumour region. The black line depicts non-linear regression of L(t)/RP to the standard linear solid model, which includes the elastic modulus E as a fitted parameter. Elastic moduli (h) fit from the plateau in the strain vs. time plot for interior and peripheral regions of tumours excised days 4, 8, and 12 after engraftment. In the box plot, the centreline depicts the median, the box depicts the IQR, and the whiskers depict the 5th and 95th percentiles. The number of measurements n is combined from two or three tumours per time point. The solid lines are fits of simple exponential growth for the periphery (E ~ 0.8et/10) and exponential decay for the interior (E ~ 0.5e-t/10 + 0.3), where non-linear regression of the data was constrained so rates and y-intercepts would be shared for the periphery and interior. The shaded box denotes the range of E reported for B16 cells74,75 that is also typical for B16 tumouroids.

Source data

Extended Data Fig. 2 Analysis of CD47 and Tyrp1 expression and engulfment of B16 tumouroids and cell suspensions.

a, Flow cytometry analysis of CD47 and Tyrp1 expression on B16 cell lines. Representative histograms (a-i) show binding of 10 μg/mL anti-CD47 (left) and 20 μg/mL anti-Tyrp1 (right) to CD47 KO (top) and WT (bottom) B16 cell lines. Binding was detected with secondary antibodies conjugated with Alexa Fluor (AF) 647. The populations shown in the histograms were gated on live, single cells using forward/side scatter and DAPI staining. Median fluorescence intensity (MFI) values (a-ii) of CD47 KO and WT B16 incubated with varying concentrations of anti-CD47 or anti-Tyrp1 followed by secondary antibody (n = 3 tests per antibody concentration, mean ± s.d.). The solid line is a fit of MFI to a hyperbolic model of the form y = A*x/(K + x). The shaded regions correspond to blocking and opsonizing antibody concentrations that are required for tumouroid elimination in Fig. 1g. b, Tyrp1 protein expression on B16 melanoma cells. Immunofluorescence image (b-i) of a B16 cell surface-stained (fixed, unpermeabilized) with anti-Tyrp1 and anti-mouse IgG AF647 (green) and counterstained with Hoechst 33342 (blue). Brightfield image (b-ii) of a B16 cell. Inset: Pigmented melanosomes. Scale bars: 25 µm (left) and 10 µm (right). c, Protein expression data from The Human Protein Atlas76 for CD47 (https://www.proteinatlas.org/ENSG00000196776-CD47/tissue) and Tyrp1 (https://www.proteinatlas.org/ENSG00000107165-TYRP1/tissue) across different normal tissues. d, Conventional 2D phagocytosis (d-i) of CD47 KO and WT B16 from single-cell suspensions by primary mouse bone marrow-derived macrophages (BMDMs). Representative fluorescence image (d-ii) of phagocytosis of opsonized CD47 KO (green) by BMDMs (magenta). Yellow arrows denote phagocytic events. Scale bar: 25 µm. The phagocytic index (d-iii) is calculated as the percentage of macrophages engulfing a target cell multiplied by the number of engulfed cells per macrophage (mean ± s.e.m., n = 3 wells per condition). Statistical significance was assessed by two-way ANOVA and Tukey’s multiple comparisons test. e, Putative tumouroid trogocytic engulfment events consisting of GFP signal without co-localizing DNA signal (yellow arrows) and putative necrotic cell death observed as large, swollen B16 cells in tumouroids (orange arrow). Scale bars: 10 µm (left) and 100 µm (right). f, Co-localization of phagocytic macrophages in tumouroids with melanin pigments, which are visualized as a dark shadow in the GFP channel where the signal intensity is below background as illustrated in the colour heat map. Scale bar: 100 µm.

Extended Data Fig. 3 Cooperative tumouroid phagocytosis and non-cooperative phagocytosis in the conventional 2D assay.

a, CD47 KO and WT tumouroid growth curves with or without anti-Tyrp1 added on day 1 in the absence of macrophages (mean ± s.e.m., n = 6 tumouroids per condition). b, CD47 KO or WT tumouroid growth curves and effective growth rates at varying macrophage:B16 ratios without anti-Tyrp1 (mean ± s.e.m., n = 8 tumouroids in a representative experiment). c-e, Growth curves for WT tumouroids treated with 133 nM anti-CD47 and/or 133 nM anti-Tyrp1 at varying macrophage:WT ratios (c), 3:1 macrophage:WT tumouroids with 133 nM anti-Tyrp1 and varying concentrations of anti-CD47 (d), and 3:1 macrophage:CD47 KO tumouroids with varying concentrations of anti-Tyrp1 (e) (mean ± s.e.m. with exact sample numbers given in the plot legend). The tumouroids in panels (c-e) correspond to those used to determine keff as a function of macrophage:WT ratio, anti-CD47 concentration, or anti-Tyrp1 concentration plotted in Fig. 1f, g. f, Max intensity projection of confocal images of a WT tumouroid one day after addition of macrophages, anti-Tyrp1, and anti-CD47. Scale bar: 100 µm. The expansion depicts a single z slice with a cluster of macrophages that have engulfed B16 (white arrows). Scale bar: 25 µm. g, Phagocytic index for conventional 2D phagocytosis (g-i) with adherent macrophages and single-cell suspensions of CD47 KO or WT B16 opsonized with anti-Tyrp1 and treated with either anti-CD47 or rat IgG2a isotype control antibody (mean ± s.e.m., n = 3 wells per condition). Statistical significance was assessed by two-way ANOVA and Tukey’s multiple comparisons test. The phagocytic index (g-ii) calculated for each field of view (FOV) across all four conditions (2 cell lines x 2 blocking conditions) is plotted against the number of macrophages per FOV (Pearson r = −0.32, p = 0.01, two-tailed). h, Conventional 2D phagocytosis assay with varying macrophage surface densities and a fixed density of CD47 KO B16 opsonized with anti-Tyrp1. Representative FOVs with low and high macrophage density are shown (h-i). Scale bar: 50 µm. The phagocytic index (h-ii) calculated for each FOV is plotted against the number of macrophages per FOV as in g-ii (Pearson r = −0.36, p = 0.02, two-tailed). Alternatively, the data are fit with a segmental linear regression model (h-iii) relating the number of engulfed B16 to the number of macrophages per FOV (see Supplementary Fig. 2f for details). The dashed line approximates the expected number of B16 per FOV based on the density of the cell suspension, which is the theoretical maximum number of B16 that can be engulfed even if macrophage density increases.

Extended Data Fig. 4 Informational entropy calculation of macrophage order based on image compression.

a, Simulated 1024 × 1024 pixel (px) images containing 10,000 dark px on a white background that are arranged in random squares varying in size from 10,000 1 × 1 px squares to one 100 × 100 px square. The images were compressed in the lossless portable network graphics (PNG) file format. The PNG file size (in bytes) below each image is the average of 50 randomly generated images with the same specifications. b, To compare images with different numbers of dark pixels (N), a normalization procedure involved subtracting the PNG file size of an equal dimension white image and dividing this value by the PNG file size of an equal dimension random image with N dark pixels (minus a white image). c,d, Macrophages disperse spontaneously following phagocytosis of tumouroids. Representative images (c) of a 3:1 macrophage:CD47 KO tumouroid with anti-Tyrp1 on days 1–4. Scale bar: 100 µm. Macrophage entropy (d) during and after elimination of CD47 KO cells from tumouroids. The centreline depicts the median, the box depicts the IQR, and the whiskers depict the range of the data (n = 18 tumouroids). Statistical significance was assessed by one-way repeated measures ANOVA followed by Tukey’s multiple comparisons test.

Extended Data Fig. 5 Effects of cytokine priming or myosin-II inhibition on tumouroid growth suppression and macrophage clustering.

a, Tumouroid growth curves (a-i) following addition of macrophages primed for 48 h with 20 ng ml−1 IFNγ or 20 ng ml−1 IL-4 (mean ± s.e.m, n = 8 tumouroids). Statistical significance was assessed by one-way ANOVA and Dunnett’s multiple comparisons test between the mean area of tumouroids with unprimed macrophages and tumouroids with cytokine-primed macrophages at each time point. Growth curves for CD47 KO tumouroids (a-ii) in the presence of 20 µM p-amino-blebbistatin (NH2-blebb) to inhibit myosin-II or DMSO vehicle control (mean ± s.e.m., n = 4 tumouroids). b, Transcriptomic microarray analyses of BMDMs treated with IFNγ (GSE60290) (ref. 70) or IL-4 (GSE69607) (ref. 71) versus untreated BMDMs. The p values for differentially expressed genes were adjusted for multiple comparisons by the method of Benjamini and Hochberg to control the false discovery rate. The heat map depicts log2(fold change) for selected genes. Proteins encoded by differentially expressed genes are depicted in the schematic detailing a putative cytoskeleton and nuclear mechanosensing pathway and membrane receptors involved in phagocytosis and macrophage adhesion. c-e, Measurements of protein expression of selected differentially expressed genes in BMDMs treated with IFNγ or IL-4 for 48 h. Flow cytometry histograms (c) for surface staining of MHCII and CD206 in IFNγ- or IL-4-treated or untreated BMDMs. Similar staining was performed with antibodies against FcR’s, CD47, and SIRPα. The ratio of lamin-A to lamin-B and the projected nuclear area were quantified (d) by immunofluorescence microscopy (individual values for n > 140 cells per condition across 8 fields of view with a line denoting the median). Statistical significance was assessed by one-way ANOVA followed by Tukey’s multiple comparisons test. Scatterplot (e) of the fold change (cytokine-primed vs. untreated) of indicated proteins from flow cytometry (panel c) (mean ± s.d., replicates were BMDMs from n = 3 mice for MHCII staining and 4 mice for all other proteins) and lamin-A immunofluorescence staining (panel d) versus the fold change in gene expression from microarrays (panel b). f,g, Representative fluorescence images and entropy analysis for cytokine-primed (f) and blebbistatin-treated (g) macrophage monocultures on non-adhesive surfaces (mean ± s.e.m, n = 8 wells per condition). Cytokines and drugs were added after 6 h and images were acquired 20 h later. Scale bars: 100 µm. Statistical significance in panels f,g was assessed by one-way ANOVA followed by Tukey’s multiple comparisons test.

Extended Data Fig. 6 Isotype control, vehicle injections, and FcR-primed, SIRPα-blocked marrow cell injections; Biophysical crosslinking mechanism for SIRPα blockade by the anti-mouse SIRPα mAb clone P84.

a, Growth curves of tumours in mice injected with 2 × 105 CD47 KO cells and treated i.v. on days 4, 5, 7, 9, 11, 13, and 15 with 250 µg mouse IgG2a isotype control, with PBS vehicle, or left untreated (mean ± s.e.m., n = 6 mice per group). b, WT tumouroid growth curves and effective growth rates at varying macrophage:B16 ratios with anti-Tyrp1 and/or anti-SIRPα (mean ± s.e.m., n = 6–8 tumouroids in a representative experiment with exact n for anti-SIRPα + anti-Tyrp1 tumouroids reported in the plot legend). Statistical significance was assessed at each macrophage:B16 ratio by one-way ANOVA and Tukey’s multiple comparisons test. The p values reported in the plot correspond to differences in mean area between tumouroids treated with anti-SIRPα + anti-Tyrp1 and with anti-Tyrp1 only. c, Survival curves of mice bearing WT B16 tumours (parental line) treated with 2 × 107 A’PB (n = 22 mice), A’ (FcR-primed only, no SIRPα block; n = 14), or B (no FcR priming, only SIRPα block; n = 5) marrow cells i.v. on day 4 after tumour engraftment or left untreated (n = 21 mice). A’PB and A’ conditions included additional 250 µg anti-Tyrp1 i.v. on days 5, 7, 9, 11, 13, and 15. Statistical significance was determined by the log-rank (Mantel-Cox) test. d-g, Anti-mouse SIRPα antibody clone P84 binds to mouse macrophages and immobilizes SIRPα. Representative fluorescence images (d) and quantification (e) of fluorescence recovery after photobleaching (FRAP) for SIRPα-GFP ± anti-mSIRPα clone P84. Bleached regions (yellow arrow) are shown prior to bleaching and at early and late time points of recovery (n = 3). Scale bar: 10 µm. Experimental schematic and representative images (f) of J774A.1 mouse macrophages ± anti-mSIRPα clone P84 incubated with IgG-opsonized mouse RBCs for 30 min prior to immunostaining for SIRPα and phospho-tyrosine (p-Tyr). Quantification (g) of SIRPα and p-Tyr immunofluorescence at the phagocytic synapse between the macrophage and target RBC. Scale bar: 10 µm. Fluorescence intensity in the phagocytic synapse was normalized to fluorescence from macrophages that were not undergoing phagocytosis (mean ± s.e.m., n = 7). Statistical significance of each imaging bin along the phagocytic synapse was assessed by Welch’s t-test (two-tailed, unpaired with Holm-Šídák correction for multiple comparisons). h, Summary of macrophage number versus therapeutic outcome for tumouroids in vitro and tumours in vivo. Growth rate is controlled by tumour cell proliferation and macrophage phagocytosis. CD47 signalling dominates pro-phagocytic signalling at low and high macrophage numbers, but CD47 depletion, IgG opsonization, and macrophage infiltration can eliminate tumours.

Source data

Extended Data Fig. 7 Conditionally immortalized macrophage progenitor engineering and opsonization of various B16 lines with convalescent serum.

a,b, Flow cytometry analysis of surface markers on conditionally immortalized macrophage (CIM) progenitors. Staining for myeloid markers (a) on CIM progenitors and freshly harvested bone marrow cells for comparison. Flow histograms of SIRPα staining (b) on SIRPα KO CIM progenitors and unedited wild-type CIM progenitors. Anti-SIRPα binding was detected with AF546 anti-rat IgG. c–f, Convalescent serum IgG from CD47 KO tumour complete responders opsonizes CD47 KO, DKO, and WT B16. (c) Representative fluorescence image of serum-opsonized CD47 KO B16 engulfed by BMDMs (yellow arrows). Scale bar: 50 μm. (d) Quantification of the phagocytic index for macrophages engulfing CD47 KO B16 opsonized with convalescent sera, naïve serum, or mAb controls. Convalescent sera were collected from second challenge survivors 70 days after tumour challenge (mean ± s.e.m., n = 3 wells for antibody conditions, n = 3 wells per serum sample for one naïve serum and three convalescent sera). (e) Percent phagocytic macrophages engulfing DKO B16 (lacking CD47 and Tyrp1) opsonized with convalescent sera collected from first challenge survivors 99 days after tumour challenge, naïve sera, or mAb controls (mean ± s.e.m., n = 3 wells for antibody conditions, n = 3 wells per serum sample for four naïve or convalescent sera). (f) Percent phagocytic macrophages engulfing WT B16 opsonized with convalescent serum from a third challenge survivor, naïve serum, or anti-Tyrp1 (mean ± s.e.m., n = 3 wells per condition). In panels (d-f), statistical significance was assessed by one-way ANOVA and Šídák’s multiple comparisons test between selected groups.

Extended Data Fig. 8 Convalescent sera from CD47 KO tumour complete responders contain multiple subclasses of IgG that bind CD47 KO and DKO B16, but not syngeneic YUMM2.1 melanoma cells.

a, Kinetics of de novo IgG generation revealed by flow cytometry of CD47 KO (filled symbols) and DKO B16 cells (open symbols) stained with serum followed by a polyclonal anti-mouse IgG [H+L] secondary antibody (row 1) or secondary antibodies specific for mouse IgG1 and IgG3 (rows 2 and 3). The corresponding data for IgG2a/c and IgG2b are shown in Fig. 6b. The median fluorescence intensity was corrected by subtracting the background fluorescence equal to the signal of cells incubated with secondary antibodies only. Symbols and error bars depict the mean ± s.e.m. of each group. The range of staining observed with 10 µg ml−1 anti-Tyrp1 is denoted by the pink boxes or lines. The gating strategy and representative histograms are shown in Supplementary Fig. 4. b, Median fluorescence intensity of B16 WT or Yumm2.1 cells incubated with 5% (v/v) serum collected from a mouse that survived the third challenge, with naïve serum, or with anti-Tyrp1 followed by staining with monoclonal secondary antibodies as in Fig. 6b and panel (a) of this figure. c, Growth curves for CD47 KO tumouroids treated with convalescent serum, naïve serum, anti-Tyrp1, or mIgG2a isotype control Ab without macrophages. Solid lines are non-linear regression of the data to a simple exponential of the form A(t) = A1ek(t-1) (mean ± s.e.m., n = 3 or 4 tumouroids each for anti-Tyrp1, mIgG2a, 9 convalescent sera, and 9 naïve sera).

Extended Data Fig. 9 Generalization of CD47 disruption and macrophage phagocytosis in prostate, lung, and glioblastoma tumour models.

a, Targeting RM-9 prostate tumours for phagocytosis. Immunostaining of RM-9 (a-i) with anti-GD2 and mIgG2a isotype control Ab. Bound primary antibodies were detected with a secondary antibody conjugated with AF647. Clusters of anti-GD2 are consistent with ‘cap formation’ as should occur due to GD2 association with rafts77 or due to the polyclonal secondary antibody. Scale bar: 100 µm. Flow cytometry histograms (a-ii) of anti-GD2 (left) and anti-CD47 (right) and their isotype (iso.) controls binding to RM-9. Bound primary antibodies were detected with secondary antibodies conjugated with PE and AF647, respectively. Phagocytosis of RM-9 cells (a-iii) by BMDMs with anti-GD2 opsonization and/or CD47 antibody blockade. Statistical significance was assessed by one-way ANOVA with Tukey’s multiple comparisons test (mean ± s.e.m., n = 3 wells per condition). WT RM-9 tumour growth curves (a-iv). Mice were treated with 4 × 106 SIRPα KO CIM progenitors i.v. on day 4 and 250 µg anti-GD2 i.v. on days 4, 5, 7, 9, 11, 13, and 15 (n = 10) or left untreated (n = 5). Each symbol represents a separate tumour, and complete responses (‘survivor’, 1) in which a tumour was never palpable are depicted with the half-filled squares. b, Targeting TC-1 lung tumours for phagocytosis. (b-i) Phagocytosis of CD47 KO TC-1 by BMDMs with anti-mouse RBC IgG opsonization (mean ± s.e.m., n = 3 per condition). Statistical significance was assessed by Welch’s t-test (two-tailed, unpaired). (b-ii) Tumour growth curves at early timepoints following injection of TC-1 cells pre-opsonized with anti-mouse RBC and anti-CD47 or unopsonized controls (mean ± s.e.m., n = 10 mice per group). Statistical significance at each timepoint between control (squares) and pre-opsonized (circles) was assessed by Student’s t-test (two-tailed, unpaired). The dashed lines are linear fits, which were compared by the extra sum-of-squares F test (p = 0.002, two-tailed). c, Binding and functional analysis of convalescent serum IgG from vaccine-enhanced CAR-T therapy against CT-2A glioma54. Median fluorescence intensity (c-i) (corrected by subtracting the background signal measured on unstained cells) of CT-2A stained with 5% (v/v) convalescent or naïve serum followed by the same secondary Ab panel used for Fig. 6b and Extended Data Fig. 8a, b (median with all data points, n = 5 convalescent and 3 naïve sera). (c-ii) Lack of phagocytosis of CT-2A cells treated with convalescent sera even when CD47 was blocked. As a positive control, CT-2A were opsonized with 5% (v/v) anti-mRBC polyclonal antiserum (mean ± s.d., n = 3 wells per condition).

Source data

Extended Data Fig. 10 Potential for combination immunotherapy in human melanoma and rationale for CD47 combination therapy versus monotherapy in syngeneic mouse models.

a, TCGA analysis of TYRP1 and CD47 in human melanoma. Survival analysis of metastatic melanoma patients in The Cancer Genome Atlas (TCGA SKCM) based on expression of TYRP1 (left) and CD47 (right) above or below the median. Significance was determined by the log-rank (Mantel-Cox) test. Expression levels of TYRP1 (left, one-way ANOVA, p = 0.68) and CD47 (right, p = 0.36) across different treatment modalities reported in TCGA. In the box plots, the centreline depicts the median, the boxes span the IQR, and the whiskers span 1.5 × IQR with outlier points included. b, Meta-analysis of tumour growth from data reported by Mosely et al.78 and Lechner et al.79 across different syngeneic mouse tumour models plotted against an immunogenicity score defined as the summation of log2(expression) of MHC class I-related genes reported by Mosely et al. (Pearson correlation coefficients r and two-tailed p values are reported in the plot legend). Graphical growth data were digitized using WebPlotDigitizer version 4.2, and growth curves were fit to the exponential growth equation V(t) = V0ekt to determine the tumour growth rate k (± standard error). Tumour types are: melanoma (B16), lung (LLC), kidney (RENCA), breast (4T1), and colon (CT26 and MC38). Note that B16 doubling rates in our studies are consistent with the data here, even with CD47 knockout.

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Dooling, L.J., Andrechak, J.C., Hayes, B.H. et al. Cooperative phagocytosis of solid tumours by macrophages triggers durable anti-tumour responses. Nat. Biomed. Eng 7, 1081–1096 (2023). https://doi.org/10.1038/s41551-023-01031-3

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