The pro-resolutive agonist αChemR23 mAb was produced and purified by OSE Immunotherapeutics as previously reported and characterized (19). The hIgG1 control mAb (clone MOTA-hIgG1) was produced in parallel by Evitria (Switzerland).

Human monocytes were freshly isolated by magnetic sorting from PBMC of healthy volunteers following the manufacturer’s protocol (classical monocyte isolation kit, Miltenyi Biotec). The MPM cell line Meso13 was established from the pleural fluid of a MPM patient (21), characterized for its karyotype (GSE 134349) and for their mutational status using targeting sequencing (CDKN2Adel, CDKN2Bdel). Cal51 cell line, derived from metastatic site of a triple negative BC (pleural effusion), and the murine triple-negative BC 4T1-luc2 cell line were purchased from DSZM (Braunschweig, Germany) and ATCC, respectively. These cell lines were cultured in complete RPMI-1640 (Gibco) or DMEM 4.5g/l Glucose media (Gibco) supplemented with 2mM L-glutamine, 100IU/mL penicillin, 0.1mg/mL streptomycin (Gibco) and 10% heat-inactivated fetal calf serum FCS (Gibco) at 37°C and 5% CO2 atmosphere.

All RNAseqv2 samples from the The Cancer Genome Atlas (TCGA)-MESO dataset (n=87 patients) and BRCA dataset (n=1997) are available on the Broad’s Genome Data Analysis Centre (http://gdac.Broad-institute.org/). Gene expressions as RNA-seq by expectation maximization values (RSEM values) were analyzed. Clinical data for these samples were downloaded from FireBrowse (http://firebrowse.org; version 2018_02_26 for MESO and BRCA). The Breast Cancer Gene-Expression Miner v4.8 (http://bcgenex.ico.unicancer.fr/BC-GEM/GEM-Accueil.php?js=1) was used to analyze CMKLR1 expression in BC with macrophage markers.

Monocytes were seeded, in 12-wells plates, at 0.5x10⁶ cells/ml in 2.5ml of complete medium supplemented with GM-CSF at 20ng/ml (Cellgenix, 001412-050) or with M-CSF at 50ng/ml (Isokine, 01-A0220). To obtain TAM-like macrophages, monocytes were differentiated with undiluted supernatant from MPM (Meso13) or BC (Cal51) cell lines as previously described (22). Macrophages were kept in culture for 3 days at 37°C and 5% CO2 atmosphere and analyzed after treatment as described below at days 4-5.

M-CSF differentiated macrophages were starved for 4h in medium then stimulated with hIgG1 or αChemR23 (10µg/ml) for different times. Cells were lysed with 200µl of RIPA (Sigma-Aldrich) buffer 1X supplemented with protease inhibitor cocktail (Fast protease inhibitor, Sigma-Aldrich) and phosphatase inhibitors (Phos STOP, Roche). Cell lysates were centrifuged for 25min at 800g at 4°C to remove debris and the supernatants were stored at -80°C. Proteins were quantified using Bradford assay (Interchim). 7µg of proteins were loaded in 4-20% Mini-PROTEAN^® TGX™ Precast Protein Gel (#4561093, Biorad) and then transferred onto a nitrocellulose membrane. After 2h of saturation in 5% milk/TBS-Tween 0,05%, the membranes were incubated with primary antibodies anti–phospho(Thr202/Tyr204) - ERK1/2 (p44/42 MAPK) (#4370, Cell Signaling) (1:1000), anti- ERK1/2 (p44/42 MAPK) (#9102S, Cell Signaling) or anti–phospho(Ser473) -AKT (#4051S, Cell Signaling) (1:1000), anti-AKT (#4691S, Cell Signaling) or anti-Actin M(AB1501 Millipore) for 1h at room temperature. Proteins were incubated with Goat anti-Rabbit (#111-001-003) or Goat anti-Mouse (115-035-008) secondary antibodies (Jackson ImmunoResearch) for 1h at room temperature and then revealed with the Immobile Western Chemiluminescent HRP Substrate (WBKLS0500, EMD Millipore). The data were analyzed with the Fusion FX device (Vilber).

Macrophages were detached using phosphate-buffered saline (PBS)-EDTA at 4°C for 30min and labeled with live/dead marker FVS510 (BD, 564406) for 30min at 4°C in PBS. After washing, the cells were labeled with anti-CD14 APC-Vio770 (clone REA599, Miltenyi Biotec), anti-HLA-DR FITC (clone L243, BD), anti-CD16 BV421 (clone 3G8, Biolegend), anti-CD163 AF647 (clone GHI/61, BD) and anti-ChemR23 PE (clone 84939, R&D system) antibodies for 30 min at 4°C in PBS-0,01% bovine serum albumin (BSA) (Sigma Aldrich). IgG1k-AF647 (clone MOPC-21, BD), REA control-APCvio770 (clone REA293, Miltenyi Biotec), IgG3-PE (clone 133316, R&D system), IgG1,k-FITC (MOPC-21, BD) and IgG1,k-BV421 (clone MOPC-21, Biolegend) isotypes were used as controls. Analysis was performed by flow cytometry using FlowJo v10 software. The results are expressed as the ratio of the median fluorescence obtained with the specific antibody to the median fluorescence obtained with the corresponding isotype (RFMI=Ratio of Median fluorescent intensity).

For tSNE data projection, M-CSF differentiated macrophages were incubated with 10µg/ml αChemR23 or hIgG1 antibodies for 24h and processed for flow cytometry staining as mentioned above with the following antibodies: anti-CD14 APC (clone MSE2, Biolegend), anti-CD163 (clone GHI/61.1, Miltenyi), anti-CD192 BV605 (clone K036C2, Biolegend), anti-CD206 BB515 (clone 19.2, BD), anti-CD274 PE (clone MIH1, BD), anti CD45 APC R700 (clone HI30, BD), anti-CD209 BV421 (clone DCN46, BD), anti-CD80 BUV395 (clone L307.4, BD), anti-CD16 BUV737 (clone 3G8, BD), anti HLA-DR BV711 (clone L243, Biolegend).

Analysis of the data was performed using FlowJo v10 software.

After 3 days in culture for differentiation, macrophages were incubated with 10µg/ml αChemR23 or hIgG1 antibodies for 24h. Then, cells were stimulated with 200ng/ml lipopolysaccharide (LPS) (Sigma-Aldrich) and the supernatant were collected after 24h for TNF-α, IL-1β, IL-1RA, IL-6, IL-10, IL-12p70, IL-12p40, CCL17, IL-23 and IP-10 quantification using the LEGENDplex Human M1/M2 macrophages panel (BioLegend) according to the manufacturer’s recommendations.

After 3 days in culture, macrophages were incubated with 10µg/ml of αChemR23 or hIgG1 antibodies for 24h. Then, cells were stimulated with 200ng/ml lipopolysaccharide (LPS) (Sigma-Aldrich) for 6h and cells were lysed using the RLT buffer (Qiagen) supplemented by 1% β-mercaptoethanol (Sigma-Aldrich). Total RNA was isolated using the RNeasy Mini Kit according to the manufacturer’s protocol (Qiagen).

For RT-qPCR experiments, 0.5µg of total RNA was reverse transcribed using MMLV reverse transcriptase (Invitrogen). PCR reactions were performed using QuantiTect Primer Assays (Qiagen) and RT² Real-time SYBR-Green/ROX PCR mastermix (Qiagen) and carried out using QuantStudio™ Real-Time PCR system 3 (ThermoFisher). RPLP0, ACTB and GAPDH gene expression were used as internal standards.

For Nanostring analysis, gene expression was quantified with the NanoString nCounter platform using 50ng of total RNA in the nCounter Human (594 genes) or Mouse (561 genes) Immunology Panel (NanoString Technologies). The code set was hybridized with the RNA overnight at 65°C. RNA transcripts were immobilized and counted using the NanoString nCounter Sprint. Normalized expression data were analyzed with the nSolver software. Standardized not log2-transformed counts were used for differential gene expression analysis with the R package DESeq2 (23). Genes were ranked in order of differential expression and P value score. Gene set enrichment analysis was performed with the GSEA software with 1000 permutations. Score signatures of transcriptomic analysis (single sample GSEA score) were obtained calculating a gene set enrichment score per sample as the normalized difference in empirical cumulative distribution functions of gene expression ranks inside and outside the gene set with the R package GSVA.

Human tumor specimens were collected from 7 treatment-naive patients with invasive BC after surgical resection at the Institut de Cancérologie de l’Ouest, Nantes/Angers France, and from 3 patients with MPM. Informed consent was obtained from enrolled patients and protocol was approved by Ministère de la Recherche (agreement n°: DC-2012-1598) and by local ethic committee (agreement n°: CB 2012/06) or through the biological resource center (CHU Nantes, Hôtel Dieu, Tumorothèque, Nantes, France BRIF: BB-0033-00040, transfer number 122C366) for patients with BC tumors or MPM, respectively. Three-micrometers-thick tissue sections of formalin-fixed, paraffin-embedded (FFPE) breast cancers were treated with protease for 4min (Protease 1, Ventana, 760-2018) to achieve epitope retrieval. Samples were then incubated during 32min at 37°C with the anti-ChemR23 antibody at a dilution of 1:200 (clone 1A7, mouse monoclonal, Origene) and with the anti-Iba1 antibody at a dilution of 1:1000 (clone EPR16588, rabbit monoclonal, Abcam). Protein expression was detected with an OptiView DAB IHC Detection Kit (Roche Diagnostics, 760-700), optimized for automated immunohistochemistry (Benchmark GX stainer, Ventana Medical Systems, Roche Diagnostics). ChemR23 and Iba1-immunolabelled macrophages were quantified on 10 High Power Fields (HPFs, Fields of 1590 μm² at 400X magnification) in tumor and peritumor (comprising a thickness of 200µm around the periphery of the tumor) areas.

For induction of tumor cell apoptosis, the BC cell line Cal51 was treated with 70nM paclitaxel (Sigma-Aldrich) plus 100nM of the BCLxL antagonist A1331852 (SelleckChem) for 24h, as previously described in (24). Meso13 cells were treated with 1.6 µg/ml cisplatin (Merck) and 80 µM pemetrexed (Sigma-Aldrich) for 72h, as previously described in (16). Apoptotic and control untreated cells were then harvested, washed and labelled with 1µg/ml of the pH sensitive dye pHrodo^® (Incucyte pHrodo Red cell labelling Kit for phagocytosis, Sartorius, 4649) following the manufacturer’s protocol. In parallel, differentiated macrophages were seeded at 10⁴ cells in 96-well plates in 200µl of complete medium and treated with 10µg/ml αChemR23 or hIgG1 antibodies for 24h at 37°C. Then, labelled apoptotic or untreated cancer cells were added to macrophages at a ratio of 1:5 for 24h and phagocytosis was measured by live cell imaging using Incucyte^® technology (Sartorius). Phagocytosis was quantified using fluorescence intensity (“Total integrated intensity”) in integrated software.

Differentiated macrophages treated with 10 µg/ml αChemR23 or hIgG1 antibodies for 24h were stimulated with 200 ng/ml LPS for additional 24h, supernatants (conditioned media) were collected and centrifuged to remove cell debris, aliquoted and stored at -80°C.

Human T lymphocytes were freshly isolated by negative magnetic sorting (EasySep Human T cell isolation kit, Stemcell technologies) from PBMC of healthy volunteers following the manufacturer’s protocol. Isolated T lymphocytes were labelled with 0.5 µM of cell proliferation dye (CPD) following the manufacturer’s protocol (eBioscience™ Cell proliferation dye efluor 670, ThermoFischer). 0.1x10⁶ labelled T lymphocytes were activated with CD3/CD28 beads at a ratio 1:40 or 1:100 for 5 days (Dynabeads Human T-Activator CD3/CD28, ThermoFischer) in 96-well U-bottom plates and treated with conditioned media from macrophages, IL-2 at 75 U/ml or IL-10 at 50 ng/ml (R&D system). After 5 days in culture, T lymphocytes were washed twice with PBS and labeled with live/dead dye APC-H7, anti-CD3 FITC (clone REA163), anti-CD4 PE (clone RPA-T4) and anti-CD8 BV421 (clone RPA-T8) antibodies. Analysis was performed by flow cytometry using DIVA software.

Animal housing and surgical procedures were conducted according to the guidelines of the French Agriculture Ministry (APAFIS 8629-2017011915305978) and were approved by the local animal ethics committee (CEEA-PdL n°6 (pour Comité d’éthique en expérimentation animale_Pays de la loire n°6)). BALB/c mice were purchased from Janvier Laboratories and kept in the UTE Nantes SFR Bonamy animal facility. 4T1-luc2 cells were harvested and resuspended in PBS for animal inoculation. Metastasis spreading was monitored using bioluminescence (Biospace Imager) by injecting 100µl of D-luciferin (Interchim) at 33.33mg/ml through intraperitoneal route. 4T1-luc2 cells (0.25x10⁶/mouse in PBS) were injected into the fat pad of mammary gland of 8-week-old BALB/c female mice (day 0). Mice were treated with αChemR23 or hIgG1 mAbs intraperitoneally at 1mg/kg 3 times a week for 3 weeks from day 7 to day 28. At day 13, primary tumors were surgically removed from mammary glands. Tumor spreading was analyzed by overall survival and by in vivo bioluminescence on lungs every week using a bioimager. Mice were euthanized when critical endpoints were reached according to criteria defined by ethical committees and lungs were harvested for further experiments including transcriptomic analysis (Nanostring technology and RT-qPCR) and flow cytometry, as previously described.

The two data groups were compared with the nonparametric test Mann-Whitney. To assess the significance of the effect of αChemR23 compared with hIgG on macrophages, the Wilcoxon paired t-test was used. The log-rank test was used to compare survival times between the two groups. Errors bars represent standard errors of mean (SEM). The symbols correspond to a P-value inferior to *0.05, **0.01, ***0.001, ****0.0001. All statistical analyses were performed using GraphPad Prism software (version 8.0).

We first evaluated the expression of ChemR23 in M-CSF or GM-CSF differentiated human macrophages. M-CSF is a cytokine usually secreted by tumor cells and found in malignant tissues (25). M-CSF macrophages present phenotypic and functional characteristics different from M2a-c macrophages (26–28), but close to those of TAM as described in ovarian cancer (28) thus representing an interesting model of macrophages with immunomodulatory properties in the context of a malignancy. In contrast, using GM-CSF usually found elevated in the context of inflammation or immune response (29) leads to macrophages with proinflammatory properties however different from macrophages obtained using IFN-γ -/+ LPS corresponding to a particular context of host defense (30). As previously observed, M-CSF macrophages expressed a significantly higher level of CD14 and CD163 (27), and a significantly lower level of CD80 and HLA-DR than GM-CSF macrophages ( Figure S1 ) (28). GM-CSF expressed a higher level of CD206 and CD192 than M-CSF macrophages whereas the latter expressed a significantly higher level of CD16 than GM-CSF macrophages ( Figure S1 ). No evident differences in CD209, CD45 and CD274 expression were observed on both model of macrophages ( Figure S1 ). As expected, GM-CSF macrophages secreted significant higher level of IL-12p70 and TNFα, and significant lower level of IL-10, IL-1RA and IP-10 than M-CSF macrophages ( Figure S2A ) (30, 31). No differences in the secretion of IL-6 and IL-1β was observed between M-CSF and GM-CSF macrophages ( Figure S2A ). M-CSF macrophages expressed significantly more ChemR23 than GM-CSF macrophages ( Figure 1A ). To evaluate the biological activity of ChemR23 agonist antibody, previously reported to activate the pro-resolutive signaling of ChemR23 (19), on macrophages, we measured cytokine secretion. Treatment with αChemR23 mAb significantly decreased IL-10, IP-10 and IL-6 secretion, and significantly increased TNFα and IL-1RA secretion while not changing IL-12p70 and IL-1β secretion of M-CSF macrophages ( Figures 1B , S3A ). On GM-CSF macrophages, αChemR23 treatment led to a significant decrease of IP-10 secretion only ( Figure S3B ). These results suggest that αChemR23 mAb mainly impact M-CSF macrophages functions thus, we focused our study on this macrophage subtype.

To confirm that αChemR23 triggered ChemR23 activation in M-CSF macrophages, we studied intracellular signaling pathways. Treatment by αChemR23 mAb induced phosphorylation of ERK1/2 within 30min or 1h ( Figure 1C ) without triggering AKT pathway ( Figure 1D ). These results demonstrate the capacity of the agonist mAb to induce an intracellular signaling pathway in M-CSF macrophages.

In order to better characterize the impact of ChemR23 activation on M-CSF macrophages, we performed a transcriptomic analysis using NanoString Technology with the Human immunology panel. Unsupervised hierarchical clustering representation shows that ChemR23 triggering by the agonist antibody induced strong gene expression modifications compared to hIgG1 control ( Figure 1E ). Volcano plot representation ( Figure 1F ) indicates in red points significant (padj < 0.05) gene expression modifications with 53 induced and 137 repressed genes on a total of 594 analyzed genes, and genes with an absolute log2 fold change ≥ 2 are highlighted by their gene code name (8 induced and 19 repressed). Using discriminating genes between M1-like and M2-like signatures (32), we evidenced a decrease of both M2-associated markers CCL18, IL10, CD14, CD163, IL6 expression as well as M1-associated ones CD80, HLA-DRA and CXCL10, encoding IP-10, and a slight increase of TNFalpha and TGFB1 (M1 associated) ( Figure 1G ). In contrast MRC1 and IL1B were not affected. Interestingly, we found that IDO1 expression, coding for Indoleamine 2,3-dioxygenase-1 a potent T-cell immunosuppressive enzyme, was also reduced by anti-ChemR23 treatment on M-CSF macrophages ( Figure S4A ). These results argue for the induction of an intermediate phenotype different from the GM-CSF or M-CSF-induced macrophages polarization following ChemR23 activation.

In order to study the impact of αChemR23 mAb on macrophage phenotype, we measured the expression of 10 cell surface markers, CD14, CD163, CD192, CD206, CD274, CD45, CD209, CD80, CD16, HLA-DR, using flow cytometry. According to our transcriptomic study, the expression of CD14, CD16, CD163 and HLA-DR was decreased whereas CD206 was not modified ( Figure S5 ). tSNE representation ( Figure 2A ) shows that the decrease of marker expression was not homogenous and led to a redistribution of macrophage subpopulations. Indeed, as examples, we observed an increase of CD14 high, CD163 med, CD16 low and HLA-DR low cells (16.8% to 57.3%) ( Figure 2B , pop 3), CD14 high, CD163 -, CD16 -, and HLA-DR low cells (2.06% to 14.1%) ( Figure 2B , pop 5) and CD14 low, CD163 -, CD16 -, and HLA-DR low cells (0.95% to 3.82%) ( Figure 2B , pop 4), and a decrease of CD14 high, CD163 high, CD16 high and HLA-DR med (62.7% to 11.6%) ( Figure 2B , pop 1) macrophage subpopulations. CD14 high, CD163 med, CD16 med and HLA-DR med macrophage subpopulation was weakly impacted by αChemR23 mAb (16.3% to 12.6%) ( Figure 2B , pop 2).

Since M-CSF macrophages were deeply impacted in response to ChemR23 activation, we further extended our study on two macrophage main functions, phagocytosis and T-cell proliferation modulation. Phagocytic activity of macrophages during inflammation is fundamental for its resolution, we thus evaluated macrophage phagocytosis capacity, i.e. their ability to phagocyte apoptotic tumor cells, here BC and MPM apoptotic cells, following ChemR23 activation. We found that phagocytosis capacity was, as expected, higher in M-CSF (3.5 fold) compared to GM-CSF macrophages and only occurred towards apoptotic cancer cells ( Figures S6A, B ). Treatment of M-CSF macrophages with αChemR23 induced a significant reduction of their capacity to internalize apoptotic cancer cells ( Figures 3A, B ). No effect of the agonist mAb was observed on GM-CSF macrophages phagocytosis activity ( Figures S6C, D ). These results illustrate that ChemR23 activation by the antibody deeply affects human M-CSF macrophages including modification of their capacity to phagocyte apoptotic tumor cells.

Furthermore, macrophages can also exert their immunomodulatory function through regulation of T-cell proliferation, hence we incubated T lymphocytes from PBMC from 3 healthy donors with macrophages supernatants previously incubated with ChemR23 agonist antibody or with the isotype control antibody. T-cell activation was induced by stimulation with CD3-CD28 beads for 5 days, then cell-proliferation dye dilution was measured by flow cytometry in total CD3+ T cells ( Figure 3C ) or CD3+ CD8+ T lymphocytes ( Figure 3D ) and CD3+ CD4+ T lymphocytes ( Figure S7 ). As positive control, IL-2 potently increased T cell proliferation while IL-10 decreased T-cell proliferation at the concentration used in this assay. Of interest, we found that the supernatants from M-CSF macrophages also reduced the proliferation of human T-cell but this immunosuppressive effect was reversed when macrophages were priorly incubated with the agonist anti-ChemR23 mAb ( Figures 3C, D ). Of note, this effect was not significant on CD4 T-cells ( Figure S7 ).

These results demonstrate that ChemR23 triggering by an agonist mAb strongly modifies human M-CSF macrophages polarization as illustrated by the profound transcriptomic, phenotypic, cytokines secretion and immune functions modifications.

Regarding the involvement of M2-like macrophages in cancers (33), we extended our study to two malignancies in which the presence of these cells was described as associated with the severity of the disease, breast cancer (34) and malignant pleural mesothelioma (35). We first studied the expression of CMKLR1 in BC and MPM, using the dataset of The Cancer Genome Atlas (TCGA), where these pathologies appear to express high level of CMKLR1 among 37 cancers analyzed ( Figure S8A ). We observed that CMKLR1 was expressed in all subtypes of BC or MPM with a significant lower expression in luminal breast tumors ( Figure S8B ) and epithelioid mesothelioma tumors ( Figure S8C ). Importantly correlation analyses showed significant co-expression between CMKLR1 and genes specific of tumor associated macrophages (TAM) such as CD14, CD163, MRC1 and HLA-DRA in BC ( Figure 4A ) and MPM ( Figure 4B ). Of note, IHC analysis performed in breast and mesothelioma tumors from patients indicated that ChemR23 expression could be detected in a part of macrophages evidenced by Iba1 staining in tumor or in peritumoral areas ( Figures 4C, D ). Using a public database of single cell RNA sequencing performed on 8 breast tumors ((36), http://panmyeloid.cancer-pku.cn/), we observed that CMKLR1 is mainly expressed in a macrophage subpopulation with a high expression of CD14, CD163 and HLA-DRA, and with a low expression of CD80 and CD86. Additionally, expression of CMKLR1 was not observed in macrophage subpopulations expressing high levels of HLA-DRA, CD80 and CD86 ( Figure S9A ). The high expression of CMKLR1 in macrophages expressing high level of CD14 and CD163 was confirmed using two additional public databases ( Figures S9B, C ) (37, 38). Based on these observations, we evaluated the expression of ChemR23 on macrophages obtained by incubation of monocytes from healthy donors with BC or MPM cancer cell culture supernatants, as model of TAM (TAM-like), and compared to the one of M-CSF and GM-CSF macrophages. Figure S2B shows TAM-like exhibited a phenotype close to the M-CSF one with high expression of CD14 and CD163, low/med expression of HLA-DR, high/med secretion of IL-10 and IP-10, and low secretion of TNFα and IL12p70 ( Figure S2A ). Importantly, TAM-like macrophages expressed significantly higher levels of ChemR23 compared to GM-CSF macrophages and similar levels of ChemR23 compared to M-CSF macrophages ( Figure S2B ).

Altogether, these data illustrate that ChemR23 is expressed by TAM in human tumors. Moreover, our in vitro models of TAM seem to reproduce, at least partially, pathological situation.

In order to appreciate the potential of ChemR23 triggering on human macrophages, we used our models of BC and MPM TAM-like macrophages. As observed for M-CSF macrophages, ChemR23 activation by the agonist antibody significantly reduced IL-10, IP-10 and IL-6 secretion, and significantly induced TNFα and IL-1RA secretion while not affecting IL-12p70 in both BC ( Figures 5A , S10A ) and MPM TAM-like ( Figure 5B , S10B ). Using RT-PCR, we also observed a significant decrease of CD163 and CXCL10 genes, a tendency for IL-10 expression to decrease, and a significant increase of CCL22 and a tendency for TGFB1 genes to increase in both BC ( Figure 5C ) and MPM ( Figure 5D ) TAM-like macrophages. As in M-CSF macrophages, we observed that IDO1 expression tended to be reduced by anti-ChemR23 treatment on MPM TAM-like macrophages, but not significantly due to the limited number of donors (decreased expression of IDO1 in 4 out of 5 donors, p=0.0625), ( Figure S4B ). This tendency was not obtained in BC TAM-like where IDO1 expression was poorly detectable compared to MPM ( Figure S4C ). These data indicate that ChemR23 receptor strongly controls macrophage phenotype and that its activation promotes a different macrophage polarization with a phenotype potentially less inflammatory and less immunosuppressive. Moreover, the tumor microenvironment could drive angiogenesis by modulating macrophage activity, thus to address the possibility of the αChemR23 antibody modulation on this function in macrophages, we studied the expression of two well-known genes involved in angiogenesis and vessel remodeling, VEGFA and MMP9 ( Figure S11A, B ). First, we observed a difference of expression of VEGFA and MMP9 by TAM-like depending on the cell culture supernatant was from BC or MPM. Indeed, BC TAM-like highly expressed VEGFA compared to MPM TAM-like ( Figure S11A right panel) and MPM TAM-like expressed more MMP9 than BC TAM-like ( Figure S11B right panel). ChemR23 activation with the agonistic antibody decreased the VEGFA expression by BC TAM-like ( Figure S11A ), the MMP9 expression by MPM TAM-like and tended to decrease MMP9 expression by BC TAM-like ( Figure S11B ).

We further assessed the effect of αChemR23 mAb on TAM-like phagocytosis activity. BC and MPM TAM-like macrophages displayed a phagocytosis activity similar to the one of M-CSF macrophages ( Figures S7A, B ). As previously observed for M-CSF macrophages, a reduction of phagocytosis activity in BC and MPM TAM-like by 4 and 3 folds, respectively, was observed following treatment with αChemR23 ( Figures 6A, B ).

αChemR23 antibody being able to activate human as well as mouse ChemR23 receptor ( Figure S12 ), we further investigate the interest to target ChemR23 in cancers, we evaluated agonist anti-ChemR23 mAb treatment in vivo on BC progression using the orthotopic syngeneic triple-negative 4T1-luc2 model. Mice treated with ChemR23 agonist antibody in monotherapy initiated 7-8 days after tumor implantation, displayed no significant tumor growth modification compared to hIgG1 control at the dose tested ( Figure S13 ). To closer mimic clinic situation for most patients with BC, tumor resection 13 days after tumor cell injection was performed in mice treated with anti-ChemR23 mAb 7-8 days after tumor implantation and 5-6 days before tumor resection (corresponding to the peak of metastatic risk), in order to reprogram ChemR23 expressing cells before the tumor resection and to evaluate the subsequent effect on long term metastatic development. Our results indicate that mice survival was significantly increased in the treated group resulting in 7/15 mice still alive (complete response) 100 days after tumor injection while only 2/14 in the control group survive at long-term ( Figure 7A ). In addition, 4 mice in the treated group had a partial response that improved their survival. Importantly, this observation correlated with significant decreased lung metastasis detection in treated mice using in vivo bioluminescence ( Figure 7B ) compared to the control group. No lung metastasis 30 days after tumor cell injection could be detected in 55% of treated mice compared to 18% in the control group. Transcriptomic analysis of lung metastasis (using the murine immunology panel from Nanostring technology) indicated that αChemR23 treatment induced significant gene expression modifications compared to hIgG1 control as shown in unsupervised hierarchical clustering representation in Figure 7C and showed, in particular, an increase of the resolution score in αChemR23 mAb treated group, although macrophages or M1/M2 scores were not modified ( Figure 7D ). Importantly, based on the metastasis associated gene expression SPP1, coding for Osteopontin, as a marker of the 4T1-luc2 metastatic cells, we defined 2 mice groups corresponding to responders, low SPP1 expression, and non-responders, high SPP1 expression ( Figure 7E ). Using Nanostring data, we observed that M1 score signature was strongly increased in the responding mice compared to the non-responding ones ( Figure 7F ). This was confirmed by the increase of CCR7 positive macrophages detected in metastasis microenvironment by flow cytometry ( Figure S14A ). Moreover, neutrophil chemotaxis score significantly decreased in responders ( Figure 7G , S14B ), as previously observed in inflammatory disease model (19). Finally, using the IFNγ score that predicts the response to T-cell immunotherapy (39) and is correlated to the NK and T cell activity, we found a significant increase of the IFNγ score in responder animals compared to non-responders even at this very early stage of metastasis development ( Figure 7H ).

Altogether, these results illustrate that an anti-ChemR23 agonist mAb can modify in vivo ChemR23 positive cells and limits distant metastasis development in monotherapy.