# Extracellular vesicles from triple negative breast cancer promote pro-inflammatory macrophages associated with better clinical outcome

Mercedes Tkach, Jessie Thalmensi, Eleonora Timperi, Paul Gueguen, Nathalie Névo, Eleonora Grisard, Philemon Sirven, Federico Cocozza, Alizée Gouronnec, Lorena Martin-Jaular, et al.

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## ► To cite this version:

Mercedes Tkach, Jessie Thalmensi, Eleonora Timperi, Paul Gueguen, Nathalie Névo, et al. Extra-cellular vesicles from triple negative breast cancer promote pro-inflammatory macrophages associated with better clinical outcome. Proceedings of the National Academy of Sciences of the United States of America, 2022, 119 (17), pp.e2107394119. 10.1073/pnas.2107394119. inserm-04169286

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# Extracellular vesicles from triple negative breast cancer promote pro-inflammatory macrophages associated with better clinical outcome

Mercedes Tkach<sup>a,1</sup>, Jessie Thalmensi<sup>a</sup>, Eleonora Timperi<sup>a</sup>, Paul Gueguen<sup>a</sup>, Nathalie Névo<sup>a</sup>, Eleonora Grisard<sup>a</sup>, Philemon Sirven<sup>a</sup>, Federico Cocozza<sup>a</sup>, Alizée Gouronnec<sup>a</sup>, Lorena Martin-Jaular<sup>a</sup>, Mabel Jouve<sup>b</sup>, Fabien Delisle<sup>a</sup>, Nicolas Manel<sup>a</sup>, Derek C. Rookhuizen<sup>a</sup>, Coralie L. Guerin<sup>c,d</sup>, Vassili Soumelis<sup>e,f</sup>, Emanuela Romano<sup>a</sup>, Elodie Segura<sup>a</sup>, and Clotilde Théry<sup>a,1</sup>

Edited by Myles Brown, Dana-Farber Cancer Institute, Boston, MA; received April 23, 2021; accepted March 14, 2022

Tumor associated macrophages (TAMs), which differentiate from circulating monocytes, are pervasive across human cancers and comprise heterogeneous populations. The contribution of tumor-derived signals to TAM heterogeneity is not well understood. In particular, tumors release both soluble factors and extracellular vesicles (EVs), whose respective impact on TAM precursors may be different. Here, we show that triple negative breast cancer cells (TNBCs) release EVs and soluble molecules promoting monocyte differentiation toward distinct macrophage fates. EVs specifically promoted proinflammatory macrophages bearing an interferon response signature. The combination in TNBC EVs of surface CSF-1 promoting survival and cargoes promoting cGAS/STING or other activation pathways led to differentiation of this particular macrophage subset. Notably, macrophages expressing the EV-induced signature were found among patients' TAMs. Furthermore, higher expression of this signature was associated with T cell infiltration and extended patient survival. Together, this data indicates that TNBC-released CSF-1-bearing EVs promote a tumor immune microenvironment associated with a better prognosis in TNBC patients.

extracellular vesicles | exosomes | macrophages | triple-negative breast cancer | CSF-1

Tumors are infiltrated by different populations of immune cells, macrophages, in particular, being major components of the tumor microenvironment. Tumor-associated macrophages (TAMs) favor tumor progression, promoting cancer cell invasion and metastasis in mouse models (1). Recent single-cell analyses of human cancers revealed the heterogeneity of macrophage populations, thus challenging our understanding of TAM biology (2–4). TAMs derive from circulating monocytes that are recruited into the tumor via the CCL2-CCR2 chemokine signaling pathway (5, 6). The fate of monocytes is not predetermined and largely depend on the microenvironmental cues they encounter (7). Specifically, the identity of tumor-derived factors that contribute to TAM heterogeneity and the mechanisms underlying intratumoral monocyte differentiation remain unclear.

Among the signals that can impact TAM differentiation and activation, cytokines and chemokines are well-characterized factors (8); extracellular vesicles (EVs), however, represent novel candidates. EVs are complex vehicles of intercellular communication and were suggested to have an impact on macrophage activation (9–12). EVs, such as exosomes, ectosomes, microvesicles, and oncosomes, are membrane-enclosed structures that contain proteins and nucleic acids and can be released into the extracellular environment by all cell types, including cancer cells (13, 14). Once released, EVs can interact with recipient cells and modulate their function (15). Particularly, EVs released by cancer cells play an important role in shaping the tumor immune microenvironment. EVs were shown to modulate lymphocytes and myeloid cell functions in cancer by triggering either protumor or anti-tumor immune responses (16, 17), which may depend on numerous factors, such as the cancer type, stage, or EV subtype analyzed (18). Here, we address the specific contribution of tumor-derived EVs, as compared to the tumor-derived soluble factors, in driving TAM heterogeneity. For this, we focus on human breast cancer since these tumors are highly infiltrated with macrophages (1). Our results confirm a striking functional difference of EVs and soluble factors in tuning TAM profile that we attribute to the combination of survival and activation signals carried by EVs. Furthermore, we unravel an unexpected ability of TNBC-EVs to promote an inflammatory tumor microenvironment associated with a better clinical outcome.

## Significance

Our work uncovers mechanisms by which tumor cells impact tumor-associated macrophages in human triple-negative breast cancer. Via extracellular vesicles (EVs), these tumors promote macrophages with proinflammatory features, correlated with better clinical outcome. Our results suggest exploration of these EVs as tools, alone, or in combination with other therapies, to promote a favorable environment for the generation of anti-tumor immune responses.

Author affiliations: <sup>a</sup>INSERM U932, Institut Curie, PSL Research University, 75005, Paris, France; <sup>b</sup>CNRS UMR3215, Institut Curie, PSL Research University, 75005, Paris, France; <sup>c</sup>Cytometry Platform, CurieCoreTech, Institut Curie, Paris, F-75005 France; <sup>d</sup>Innovative Therapies in Haemostasis, INSERM, Université de Paris, Paris, F-75006 France; <sup>e</sup>Université de Paris, Inserm, U976 HPI Unit, F-75006, Paris, France; and <sup>f</sup>Assistance Publique-Hôpitaux de Paris (AP-HP), Laboratoire d'Immunologie et Histocompatibilité, Hôpital Saint-Louis, F-75010, Paris, France

Author contributions: M.T., E.S., and C.T. designed research; M.T., J.T., E.T., N.N., E.G., P.S., F.C., A.G., L.M.-J., M.J., F.D., and C.L.G. performed research; P.G., P.S., N.M., D.C.R., V.S., and E.R. contributed new reagents/analytic tools; M.T., J.T., E.T., P.G., N.N., E.G., P.S., F.C., A.G., L.M.-J., M.J., F.D., N.M., C.L.G., E.S., and C.T. analyzed data; and M.T., E.S., and C.T. wrote the paper.

The authors declare no competing interest.

This article is a PNAS Direct Submission.

Copyright © 2022 the Author(s). Published by PNAS. This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

<sup>1</sup>To whom correspondence may be addressed. Email: mercedes.tkach@gmail.com or clotilde.thery@curie.fr.

This article contains supporting information online at http://www.pnas.org/lookup/suppl/doi:10.1073/pnas.2107394119/-/DCSupplemental.

Published April 19, 2022.
## Results

**Efficient Separation of EVs from Soluble Factors by Size Exclusion Chromatography.** While analyzing EVs from a triple negative breast cancer cell (TNBC) cell line interacting with human immune cells, we have observed a major targeting of these EVs to monocytes (SI Appendix, Fig. 1), suggesting a possible downstream action of EVs on monocyte differentiation. For this experiment, EVs had been obtained by a crude process of differential ultracentrifugation of the cell conditioned medium (CM), known to coisolate other nonvesicular components (19). To minimize the level of soluble proteins coisolated with EVs, and thus be able to evaluate the specific impact of cancer cell derived EVs on monocyte fate, we implemented a sequential purification protocol (20). CM of MDA-MB-231 tumor cells was concentrated by ultrafiltration using 100 kDa MWCO filter, followed by size exclusion chromatography (SEC) (Fig. 1A). This enabled us to efficiently separate the components present in the preconcentrated CM (CCM) (Fig. 1A and B). EVs eluted in fractions 8–10, as evidenced by the high concentration of particles measured by Nanoparticle Tracking Analysis (NTA), whereas protein concentration increased from fraction 12 onwards and peaked after fraction 17 (Fig. 1B and total protein gel in Fig. 1C). To characterize the eluted vesicles, we performed Western blot analysis on all the collected SEC fractions and evaluated the presence of classical EV markers. Most particles eluted before F10 (Fig. 1B), and the EV markers CD63 and CD9 were observed mainly in

F8–F11 and F8–F9 for CD63 and CD9, respectively; however, we note that both were also detected at lower levels up to F17–19 (Fig. 1C). Similarly, the EV-specific marker HSC70 was only eluted in the first fractions (up to F10), whereas Syntenin-1, which is also associated with EVs, was present from F8 up to F17. Another marker recently attributed to non-exosomal small EVs (21), 14-3-3 protein, appeared in the late SEC fractions, thus, not associated with the EV-specific markers (Fig. 1C). Further visualization of the pooled EV SEC fractions using transmission electron microscopy (TEM) with negative staining confirmed that early fractions (F7–F10) contained a mixture of cup-shaped EVs of 80–100 nm, together with smaller round structures of 30–40 nm (Fig. 1C, Lower Part). Conversely, late SEC fractions (F15–F22) lacked EVs as well as these smaller structures and were enriched in electro-dense particles smaller than 25 nm (Fig. 1C). Finally, interleukin (IL)-6 and IL-8, two cytokines known to be secreted by MDA-MB-231, were detected from F13 onward, with higher amounts in F17 and later fractions (Fig. 1D). Collectively, these results demonstrate the suitability of SEC to isolate EV-rich (EV-R: F7–F10) and EV-poor (EV-P: F15–F22) fractions (Fig. 1C).

We next analyzed the MDA-MB-231-EV-R surface signature using a bead-based assay based on the capture of EVs on antibody-coated beads, which are subsequently detected by flow-cytometry using a combination of three antibodies against CD9, CD81, and CD63 tetraspanins (TSPs) (MACSPlex Exosome) (22). Among the 37 surface markers analyzed in this

<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Efficient separation of MDA-MB-231-derived secretome into EVs and soluble factors by ultrafiltration and SEC. (A) Scheme of collection of the EV-enriched and EV-poor fractions. Conditioned medium from MDA-MB-231 cells cultured ON in serum free medium was concentrated by ultrafiltration with 100 KDa cutoff filters. 0.5 mL of the concentrated conditioned medium (CCM) was subjected to size exclusion chromatography, and 0.5 mL individual or pooled fractions were collected and concentrated using 10 KDa cutoff filters. (B) Vesicle count and protein quantification on individual fractions is shown. Representative of two independent experiments. (C) WB of EV-associated proteins done on individual fractions and transmission electron microscopy of the pooled EV-rich (EV-R) and EV-poor (EV-P) fractions. (Scale bar: 100 nm.) Representative of three independent experiments. (D) Quantification of IL-6 and IL-8 present in pooled SEC fractions from MDA-MB-231 cells. Representative of two independent experiments. (E) MACSPlex Exosome on EV-containing fractions (F7-10) developed using a mix of antibodies against TSPs (CD9, CD63, and CD81). Results for individual EV isolations are shown (n = 7).</figcaption></figure>
assay, MDA-MB-231 EVs expressed the TSPs CD9, CD63, and CD81, the sialylated glycolipid SSEA-4, several receptors for signaling molecules: ROR1 (receptor for Wnt5a), CD44 (heparan sulfate proteoglycan that can bind cytokines), and CD142 (F3, tissue factor = initiator of coagulation), and several molecules mediating adhesion to other cells or to extracellular matrix: integrins CD29 (ITGB1) and CD49e (ITGA5), and cell adhesion molecules CD146 (MCAM) and CD326 (EPCAM) (Fig. 1E). This complex array of surface molecules could therefore confer EVs a particular way of interacting with their environment, different from the way soluble proteins interact with their targets via a single receptor.

**TNBC-Derived EVs and Soluble Factors Induce Monocyte Differentiation Toward Macrophages.** Blood monocytes are plastic cells that can be recruited to tissues during inflammation, giving rise to monocyte-derived (mo-derived) cells, such as TAMs. To evaluate the role of EVs and soluble factors released by tumors in monocyte activation and differentiation, we incubated human blood CD14⁺ monocytes with MDA-MB-231 tumor cell-derived EV-R or EV-P fractions. In both cases, a higher number of mo-derived cells after 5 d of culture were obtained, as compared to untreated monocytes (Fig. 2A). Human monocytes do not proliferate in vitro, thus, our results suggest that SEC fractions promote monocyte survival. Notably, the

increased survival was comparable to that observed when monocytes were cultured with essential myeloid growth factors (23), recombinant macrophage-colony-stimulating factor (M-CSF = CSF-1, gene CSF1) or granulocyte-macrophage CSF (GM-CSF, gene CSF2) (Fig. 2A). Furthermore, phenotypic characterization of these mo-derived cells revealed a typical macrophage morphology for EV-R-, EV-P-, and CSF-1-treated monocytes, while this was slightly less evident for GM-CSF-activated monocytes (Fig. 2B). Classical macrophage surface markers, such as CD68 and MERTK (Fig. 2C), were readily detected in all the mo-derived cells. However, we observed differences in their expression levels between mo-derived macrophages (mo-macs) exposed to EV-R (EV-R-mo-macs) or EV-P (EV-P-mo-macs) fractions (Fig. 2C and SI Appendix, Fig. 2A). Notably, EV-R-mo-macs expressed higher levels of CD163, MERTK, CD88, CD204, and PD-L1 and lower levels of the mannose receptor (MRC1/CD206) compared to EV-P-mo-macs (Fig. 2C).

Because TAMs coexpress high levels of CD206 and CD163, we decided to focus on the number of live mo-derived cells that expressed these two markers upon EV-R or EV-P in vitro stimulation (Fig. 2D). When compared to macrophages differentiated in vitro with recombinant cytokines, we observed that expression of these markers on EV-R-mo-macs resembled that of CSF-1-induced mo-macs, while EV-P-mo-macs were more similar to the mo-derived cells generated by GM-CSF

<figure><img src="image_5.png" /><figcaption>**Fig. 2.** EVs and soluble factors from MDA-MB-231 cells promote the differentiation of monocytes toward macrophages. (A) Equal amount of proteins (4 µg) from pooled EV-R (F7–F10) or EV-poor (F15–F22) fractions were incubated for 5 d with freshly isolated CD14⁺ monocytes from healthy donors in the absence of any other stimuli. As control, CD14⁺ cells were also incubated with 100 ng/mL of rCSF-1 or rGM-CSF. On day 5, live cells were counted on each well by flow cytometry. (B) Mo-derived cells morphology was analyzed by cytospin at the end of the culture (Day 5). (Scale bars: 30 µm.) Representative of two independent experiments. (C) Analysis of macrophage marker expression by flow cytometry. Representative of two (for CD68, CD88, and CD1a expression) and of three to ten independent donors for the other markers (isotype control on CSF-1-treated cells is shown in gray). (D) CD206 vs. CD163 density plot of cells at day 5. Representative of four independent experiments. (E) Quantification of CD206⁺CD163⁺ live macrophages on day 5 of culture of monocytes with increasing doses of each pooled fraction (0.5, 1, and 2 µg of proteins). (F) Quantification of CD206⁺CD163⁺ live macrophages on day 5 of culture of monocytes with EV-R or EV-P fractions from equal numbers of control (CTRL gRNA) or Rab11a-KO (Rab11 gRNA) MDA-MB-231 cells. Each individual donor is shown (n = 9). Comparison between groups was performed by two-tailed, Wilcoxon test. *P* values ≤0.05 were considered significant and are indicated for each comparison. Each individual donor is shown. Results shown represent mean ± SEM.</figcaption></figure>
(Fig. 2D). Finally, the number of CD206<sup>+</sup>CD163<sup>+</sup> mo-macs recovered at the end of the culture was dependent on the amount of EV-R or EV-P (Fig. 2E).

To directly test the role of EVs in macrophage differentiation, we depleted Rab11a by CRISPR/Cas9 as this protein was proposed to be required for the release of EVs (24, 25). Consistent with observations in other cell types, depletion of Rab11 by CRISPR/Cas9 (SI Appendix, Fig. 2B) decreased the release of EVs, as quantified by total number of particles (SI Appendix, Fig. 2C), and signal for all the EV-specific surface markers detected by the bead-based multiplex assay (SI Appendix, Fig. 2D). Incubation of monocytes with the EV-R fraction derived from Rab11-depleted cells led to a lower number of total recovered cells (SI Appendix, Fig. 2E) and of CD206<sup>+</sup>CD163<sup>+</sup> cells when compared to monocytes exposed to the EV-R fraction obtained from equal number of control cells, whereas the EV-P fractions of wild-type and Rab11 knockout cells led to similar number of CD206<sup>+</sup>CD163<sup>+</sup> cells (Fig. 2F). Collectively, these results demonstrate that both MDA-MB-231-derived EVs and the soluble factors fraction, poor in EVs, can trigger the differentiation of

monocytes toward CD206<sup>+</sup>CD163<sup>+</sup> macrophages, although the resulting macrophages display different phenotypes.

**CSF-1 Exposed on TNBC-Derived EVs Is Required for Macrophage Differentiation.** EVs can carry various cytokines as part of their internal cargo or in association with their surface (26). We thus assessed the presence in SEC fractions of cytokines known to be secreted by tumor cells and to potentially affect monocyte fate. Like IL-6 and IL-8 shown in Fig. 1D, G-CSF (CSF3 gene), GM-CSF, and CCL2 were absent in EV-R fractions (Fig. 3A). By contrast, CSF-1 was detected both in EV-R and in EV-P fractions. This observation is consistent with the fact that CSF-1 is synthesized as a transmembrane protein and is subsequently cleaved to release the soluble form (27). To determine whether CSF-1 is physically associated with EVs, we isolated EVs by pull-down using beads coated with antibodies against tetraspanins (TSPs) CD9, CD63, and CD81 (PanEVs) (SI Appendix, Fig. 3A). A total of 30–40% of CSF-1 found in the EV-R is pulled-down together with TSPs-positive EVs (Fig. 3B). To confirm the presence of CSF-1 on the surface of

<figure><img src="image_6.png" /><figcaption>**Fig. 3.** EVs from TNBC MDA-MB-231 and BT-549 cells but not from luminal MCF-7 cells expose CSF-1 which is required for mo-macs induction. (A) Quantification of cytokines present in pooled SEC fractions from MDA-MB-231 cells measured by flow cytometry bead-based assays. Representative of two independent EV isolations. (B) Recovery of CSF-1 on MDA-MB-231 EVs by pull-down with anti-CD9, anti-CD81, and anti-CD63 (Pan-EV). (C) Presence of CSF-1 on lipid dye positive (membright 488) EVs measured by imaging flow cytometry (ImageStream-X). (D) MACSPlexExo analysis of MDA-MB-231 EV-R fractions, developed using a fluorescently coupled antibody against CSF-1. (E) Quantification of CD206<sup>+</sup>CD163<sup>+</sup> live macrophages on day 5 of culture of monocytes with MDA-MB-231 EV-R in the presence of blocking antibodies against CSF-1 Receptor (CD115) or GM-CSF Receptor (CD116) molecules. Each individual donor is shown (n = 6). Results shown represent mean ± SEM (F) mRNA levels of CSF1 measured by RT-qPCR in MDA-MB-231 cells transduced with CRISPR/Cas9 lentivectors coding for control gRNA or two gRNA against CSF1 (n = 3, one representative experiment is shown). (G) CSF-1 levels in CCM or pooled EV-R fractions from MDA-MB-231 deleted for CSF1 as indicated. Quantification done on independent EV isolations is shown. (H) Number of live CD163<sup>+</sup>CD206<sup>+</sup> mo-macs obtained upon 5-d culture of purified CD14<sup>+</sup> monocytes from healthy donors with EV-R fractions from equal number of secreting control or CSF1 deleted MDA-MB-231 cells. Each individual donor is shown (n = 7). (I) CSF-1 levels in CCM or pooled EV-R fractions from MDA-MB-231, BT-549, and MCF-7 cells. Quantification done on independent EV isolations is shown. (J) CD206<sup>+</sup>CD163<sup>+</sup>-positive cells recovered after 5 d or culture of equal amounts of proteins from pooled EV-R fractions from MDA-MB-231, BT-549, or MCF-7 cells with freshly isolated CD14<sup>+</sup> monocytes from healthy donors. (K) CSF-1 levels in CCM or pooled EV-R fractions from MCF-7 wild-type cells or MCF-7 overexpressing the full-length CSF-1 protein. Quantification done on independent EV isolations is shown. (L) EVs from control MCF-7 cells or MCF-7 expressing full-length CSF-1 were incubated with CD14<sup>+</sup> cells for 5 d and the number of CD206<sup>+</sup>CD163<sup>+</sup> cells at the end of the culture is indicated. Comparison between groups was performed by two-tailed, Wilcoxon test. *P* values ≤ 0.05 were considered significant and are indicated for each comparison. Each individual donor is shown. Results shown represent mean ± SEM.</figcaption></figure>
EVs, we analyzed them by imaging flow cytometry (28) (SI Appendix, Fig. 3B) after labeling with Membright-488 (29), a fluorescent probe that efficiently stains EV membranes (30). Using a combination of fluorochrome-conjugated antibodies against CSF-1 and CD81, we observed that ~40% of CD81⁺ EVs were positive for CSF-1 (Fig. 3C and SI Appendix, Fig. 3C), while no events positive for both markers were detected in the absence of EVs (SI Appendix, Fig. 3D). To investigate whether other surface markers may be present on CSF-1-positive EVs, we analyzed the EV-R fraction by the multiplex flow cytometry bead-based assay, replacing the anti-TSPs detection antibodies by an antibody against CSF-1 (Fig. 3D). In addition to CD9- and CD81-EVs, we observed that CD29-containing EVs were positive for CSF-1 and, to a lesser extent, CD44-, CD49e-, CD63-, CD142-, CD146-, and ROR1-containing EVs as well, when compared to the isotype control (Fig. 3D). Therefore, we conclude that MDA-MB-231-derived EVs transport CSF-1 on their surface.

CSF-1 acts through the cell surface receptor (CD115/CSF-1R), promoting the proliferation, differentiation, and survival of macrophages and their bone marrow progenitors. Given the presence of CSF-1 on the surface of MDA-MB-231-derived EVs and the striking similarity in the CD163/CD206 ratios between EV-R-mo-macs- and rCSF-1-treated cells (Fig. 2C), we reasoned that CSF-1 could be, at least in part, mediating EV-induced differentiation of macrophages. To test this hypothesis, we preincubated monocytes with blocking antibodies against CSF-1R (CD115) or GM-CSFR (CD116) before treating them with EV-R fractions. Impairment of CSF-1 signaling dramatically reduced the number of total live cells (SI Appendix, Fig. 3E) and of CD206⁺CD163⁺ cells recovered at the end of the culture when compared to IgG controls, while, as expected, blocking the receptor for GM-CSF did not affect monocyte survival nor differentiation (Fig. 3E). To directly test the role of tumor CSF-1 in EV-mediated monocyte differentiation, we depleted CSF-1 in MDA-MB-231 cells by CRISPR/Cas9 based on two guide RNAs (gRNAs) inducing mild (gRNA#1) or strong (gRNA#2) depletion (Fig. 3F). Consistently, the rate of CSF1-deletion correlated well with the levels of CSF-1 secreted into the supernatant and associated to EVs (Fig. 3G). Furthermore, deletion of CSF1 decreased the EV-R-induced mo-macs differentiation (Fig. 3H) and survival (SI Appendix, Fig. 3F). Combined, our results obtained using blocking antibodies and gene-editing-based deletion demonstrates that CSF-1 signaling is required for monocyte differentiation induced by MDA-MB-231-derived EVs.

We then addressed whether EVs from other breast cancer cell lines carried CSF-1 and induced mo-macs differentiation as do MDA-MB-231 EVs. We first looked at the expression of CSF-1 in different breast cancer cell lines within the CCLE database that we classified into one of the four breast cancer subtypes (luminal A, luminal B, HER2, and basal/TNBC) according to the literature (31) (SI Appendix, Fig. 3G). Most of the cell lines with high CSF-1 expression were of basal origin, including MDA-MB-231 cells that are among the highest expressors of CSF-1 mRNA (SI Appendix, Fig. 3G and H). We chose another TNBC cell line with high level of CSF-1, BT-549, and a luminal A cell line, MCF-7, with low CSF-1 expression. The three cell lines analyzed released a similar amount of EVs (SI Appendix, Fig. 3I). As observed for MDA-MB-231, BT-549 EVs were also positive for CSF-1, while EVs from MCF-7, which released significantly lower amounts of CSF-1 in accordance with the RNA sequencing (RNA-seq) data, contained no detectable levels of the protein (Fig. 3J). MCF-7 EVs induced significantly lower numbers of mo-macs

when compared to EVs produced by the two TNBC cell lines analyzed (Fig. 3J and SI Appendix, Fig. 3J), similarly to the results obtained upon CSF-1 deletion. By contrast, when we overexpressed CSF-1 on MCF-7 cells, the protein was released in higher amounts in the conditioned medium and was present on EVs (Fig. 3K), which promoted increased mo-macs differentiation (Fig. 3L and SI Appendix, Fig. 3K). Collectively, these results indicate that EVs from cells with high CSF-1 expression, which seems to be a feature of TNBC when compared to luminal cell lines, display CSF-1 molecules on their surface which are necessary for the EV-dependent promotion of mo-macs differentiation.

**EVs Released by TNBC Promote an Interferon Response in Macrophages.** Considering the findings that CSF-1-containing EV-R and EV-P fractions induced mo-macs with different phe-notypes (Fig. 2C and D), we decided to establish the mo-macs transcriptome profiles, to better understand their similarities and differences. We performed RNA-seq on mo-macs differen-tiated by equal quantities of CSF-1 on EV-R fraction or EV-P fraction (0.02 ng/mL) and compared them to the in vitro mo-macs generated with rCSF-1 (100 ng/mL). In addition, we decided to treat monocytes with the same amounts of CSF-1 in the CCM, to obtain macrophages stimulated both with soluble factors and EVs (Fig. 4A). We analyzed the overall transcrip-tomic data by identifying genes displaying a significant differen-tial expression between each pair of conditions (adjusted P value <0.01 and log2 fold change >0.5), and performing a principal component analysis (PCA). Despite some similarities in the level of surface markers among EV-R- and EV-P-mo-macs (SI Appendix, Fig. 2C), they grouped separately in the PCA (Fig. 4B), revealing functionally distinct outcomes on mo-macs differentiation. Using K-means clustering of the dif-ferentially expressed genes, we identified seven sets of genes (Fig. 4C and Dataset S1). Clusters 7, 6, 5, and 4 were specific for CCM-mo-macs, CSF-1-mo-macs, EV-R-mo-macs, and EV-P-mo-macs, respectively. By contrast, clusters 2, 3, and 1 contained genes enriched in cells exposed to two different treat-ments: EV-R and EV-P for cluster 2, rCSF-1 and EV-R for cluster 3, and EV-P and CCM for cluster 1. Gene ontology enrichment analysis (GOEA) revealed that enriched terms in EV-R-mo-macs were associated with cytokine-signaling path-ways, in particular to those induced by type II (IFN-γ) and type I interferon (IFN), lymphocyte activation, and innate immune response. Conversely, EV-P-mo-macs GO-enriched terms related to neutrophil-mediated immunity and metabolic processes (Fig. 4D). Two different activation states are pro-posed in TAMs: proinflammatory M1 macrophages, which are thought to oppose tumor progression, and M2 macrophages that promote tumor growth (32). This polarization model applies to activation states of in vitro generated macrophages; however, its applicability to macrophages found in the tumor microenvironment, where cells were shown to coexpress both M1 and M2 associated genes, remains controversial (2). Numerous immunostimulatory genes associated with M1 macrophages (2) were found in the EV-R-mo-macs cluster 5, such as CXCL9, CXCL10, and CXCL11, FCGR1A, IDO1, KNU, PTPRC (CD45), and LY75 (CD205). However, this cluster also comprised several genes previously associated with M2 macrophages—PDCD1LG2 (PD-L2), CD274 (PD-L1), and CCL20. Therefore, we evaluated the expression of the M1 and M2 signatures within the different groups of mo-macs. Consistent with the observed presence of several genes associated with the M1 signature in the EV-R-mo-macs cluster 5, these
<figure><img src="image_7.png" /><figcaption>**Fig. 4.** Mo-macs induced upon MDA-MB-231 EVs treatment express IFN response genes and are enriched in M1 signature. (A) Number of live CD206⁺/CD163⁺ cells obtained after 5 d of culture of CD14⁺ monocytes with equal amounts of CSF-1 on EV-R, EV-P, or CCM (0.02 ng/mL) or with rCSF-1 (100 ng/mL) (n = 5). (B) Transcriptomic analysis of mo-macrophages differentiated as indicated in (A). Principal component analysis on the 5,000 most variant genes. (C) K-means clustering of differentially expressed genes. (D) Gene Ontology analysis of biological processes enriched in the clusters specific for each type of macrophage (cluster 5 for EV-R-mo-macs, cluster 4 for EV-P-mo-macs, cluster 6 for CSF-1-mo-macs, and cluster 7 for CCM-mo-macs). (E) Scatter plot of normalized mean expression of M1 and M2 signatures per group.</figcaption></figure>

mo-macs had the highest expression of the M1 signature while they were low in the M2 signature (Fig. 4E). Conversely, EV-P-mo-macs were high in the M2 signature (2), but were likewise high in the M1 signature in some replicates (Fig. 4E). CCM-mo-macs were slightly higher in M2 signature, and CSF-1-mo-MACS expressed equal low levels of both M1 and M2 signatures.

These findings support the recent idea that macrophage activation in the tumor microenvironment does not necessarily behave as discrete states, since both M1 and M2 associated genes can be induced by tumor-secreted factors. However, we have observed that depending on the nature of the stimuli, EVs or soluble factors or the combination of both, the balance toward one state of activation or the other can be slightly shifted. In addition to the increased PD-L1 and PD-L2 expression in EV-R-mo-macs, other immune checkpoint genes were specifically expressed in these cells, such as *CTLA4* and *LAG3* (Fig. 4C and Dataset S1). Overall, our results demonstrate that tumor cells secrete both EVs and soluble factors that impact differently on monocytes, promoting the generation of distinct macrophage subtypes characterized by their unique transcriptional signatures.

**EVs from TNBC Activate IFN Response Genes in Monocytes Partly through the cGAS/STING Pathway.** EVs can carry nucleic acids and proteins that can act as danger-associated molecular patterns (DAMPs) in recipient cells, triggering a rapid activation of signaling pathways that promote inflammation (17). A characteristic response to the detection of DAMPs is the secretion of elevated levels of cytokines, especially IFN type I and the induction of IFN stimulated genes (ISGs). Our RNA-seq data indicated the activation of both type I and II IFN pathway in EV-R-mo-macs (Fig. 4D). To study which

genes regulated by IFN were induced upon EV treatment, we queried genes in the cluster 5 (i.e., specific for EV-R-mo-macs) in a database of IFN-regulated genes, Interferome (http://www.interferome.org/) (33), and analyzed their expression across the different RNA-seq samples (Fig. 5A). We observed that the IFN type I response genes coding for the chemokines CXCL9 and CXCL10, and the transcription factor IRF7, were highly expressed in EV-R-mo-macs at the RNA level. Thus, we validated these findings by measuring at the protein level either the secretion of these anti-viral induced ISGs into the supernatant of the mo-macs culture (Fig. 5B) or the intracellular expression of IRF7 by FACS (Fig. 5C). We observed a stronger induction of CXCL9 and CXCL10 secretion by EV-R than by any other treatments (rCSF1, EV-P, and CCM), and a specific induction of IRF7 by EV-R and CCM, whereas neither rCSF1 nor EV-P induced its expression.

To better understand what drives the observed IFN response, we evaluated which pathways within monocytes were necessary for the EV-R-induction of ISGs. Activation of the cGAS/STING cytoplasmic DNA sensing pathway results in robust production of type I IFN (34). STING is activated upon binding of its ligand, the second messenger 2′3′-cyclic GMP-AMP (cGAMP) that is synthesized by the enzyme cyclic-GMP-AMP synthase (cGAS) in response to cytosolic double stranded (ds)DNA (35). Since nucleic acids contained within EVs have been proposed to trigger this pathway in recipient cells (36–38), we evaluated whether STING was required for the EV-R-induced ISG response in mo-macs. To assess this, we preincubated monocytes with a pharmacological inhibitor of STING (H-151) before the 5-d treatment with MDA-MB-231-derived EVs or rCSF-1 and analyzed both macrophage differentiation and cytokine secretion. Although not statistically different, the number of CD206⁺/CD163⁺ cells recovered at
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CTRL gRNA-MDA-MB-231

cGAS gRNA-MDA-MB-231

<caption>**Fig. 5.** Role of STING in recipient monocytes and cGAS in EV-producing tumor cells in IFN response in EV-R-mo-macs. (A) Heat map of ISGs present in cluster 5 from RNA-seq K-means clustering analysis (EV-R-mo-macs specific cluster) identified as IFN-related in the GO biological processes analysis. (B) Quantification of CXCL9 and CXCL10 present at day 5 in the supernatant of monocytes treated with rCSF-1, EV-R, EV-P, or CCM was evaluated by cytometric bead array (CBA). (C) Expression of IRF7 (Left) and percentage of IRF7 positive cells (Right) in monocytes treated for 5 d with rCSF-1, EV-R, EV-P, or CCM, measured by intracellular staining. (D) Quantification of CXCL9 (Left) and CXCL10 (Right) present at day 5 in the supernatant of monocytes treated with EV-R with or without STING inhibitor was evaluated by CBA. (E) Percentage of IRF7 positive CD163⁺CD206⁺ cells at day 5 in culture of monocytes treated with EV-R or rCSF1 with or without STING inhibitor. (F) WB for cGAS and EV-associated proteins done on cell lysates (CL), EV-R, and EV-P fractions of MDA-MB-231-SCR-gRNA (Ctrl) or MDA-MB-231-cGAS-gRNA (cGAS). (G) Measurement of cGAMP levels in EV-R and EV-P SEC fractions of MDA-MB-231 control cells or cGAS-deleted cells. (H) EV-R from an equal amount of MDA-MB-231 control (CTRL gRNA) or cGAS-deleted (cGAS gRNA) cells were incubated with CD14⁺ monocytes for 5 d. At the end of the culture the number of CD163⁺CD206⁺ cells was evaluated by FACS (Left) and secretion of CXCL10 (Middle) and IL-8 (Right) was measured by CBA. (I) Percentage of IRF7 and PDL1 positive cells among CD163⁺CD206⁺ at the end of the culture of monocytes treated as in (H) with EVs from control cells or cGAS-deleted cells. For (D), (E), (H), and (I), comparison between groups was performed by two-tailed, Wilcoxon test. *P* values ≤0.05 were considered significant and are indicated for each comparison. For (A) and (B), Friedman test for comparison among groups was performed.</caption>

the end of the culture trended lower at the highest dose of STING inhibitor for the EV-R treated cells (SI Appendix, Fig. 4A). This was explained by a reduced expression of CD163 upon inhibitor treatment, while CD206 levels remained unchanged (SI Appendix, Fig. 4B), and the number of live cells at the end of the culture tended to increase in STING-inhibited cells, although not significantly (SI Appendix, Fig. 4C). Contrary to the differences observed on EV-R treated monocytes, CSF-1-induced macrophage differentiation was not affected upon STING inhibition (SI Appendix, Fig. 4A–C). These observations indicate that STING activation is necessary for CD163 induction by EVs. In addition, cells incubated with the STING inhibitor produced lower levels of CXCL9 upon EV treatment, whereas no significant changes were observed for CXCL10, a chemokine also highly sensitive to nuclear factor κB activation, in addition to IFN (39) (Fig. 5D). Up-regulation of IRF7 expression was observed upon EV-R (but not upon CSF-1) treatment, and it was abrogated in STING-inhibited

cells, suggesting that this gene is specifically induced by the STING pathway upon EV-R exposure (Fig. 5E). To further validate these findings, we depleted STING in the monocytic cell line THP-1 by CRISPR/Cas9 (SI Appendix, Fig. 4D). As previously observed for freshly isolated monocytes, chemokine secretion was induced upon treatment of THP-1 cells with MDA-MB-231-EV-R (SI Appendix, Fig. 4E). However, in THP-1, secretion of both CXCL10 and CXCL9 was significantly decreased in STING-depleted cells (SI Appendix, Fig. 4F). Moreover, the IFN-inducible genes SIGLEC1 and IRF7 were highly expressed upon EV treatment of control cells but not of STING-depleted THP-1 cells, which expressed at basal level lower levels of these proteins (SI Appendix, Fig. 4G). In parallel, treatment of THP-1 control cells by rCSF1 did not induce SIGLEC1 or IRF7 expression as did EV-R fractions (SI Appendix, Fig. 4G). Thus, STING in THP1 recipient cells is necessary for EVs to induce the IFN response, and secretion of proinflammatory chemokines together with a fully differentiated
macrophage phenotype, whereas in primary monocytes, STING is required for induction by EVs of some inflammatory genes (e.g., CXCL9 and IRF7), but not all (e.g., CXCL10). Plausible explanations of this STING-dependent response would be that either dsDNA within EVs is transferred to recipient cell cytosol and directly activates cGAS or that cGAMP is being transferred within EVs and is directly activating STING in monocytes. Cytosolic cGAMP was shown to spread to bystander cells through gap junctions (40) or through budding viral particles (41, 42). Tumor cells, including MDA-MB-231 cells (43), produce and secrete high quantities of cGAMP, which was proposed to be transferred to host nontumor cells where it triggers STING, resulting in type I IFN production and induction of anti-tumor responses in mouse models (44–46). Thus, to explore the possible transport of cGAMP through EVs, we measured cGAMP levels in the different SEC fractions of conditioned medium and deleted cGAS in tumor cells by CRISPR/Cas9 (Fig. 5F) to evaluate whether EVs from these cells induced an ISG response in monocytes. We confirmed previous work (43), showing that cGAMP can be released by MDA-MB-231 tumor cells (Fig. 5G). A majority of cGAMP was present in the EV-P fractions, but a detectable portion was found in EV-R fractions with a major decrease upon cGAS deletion in EV-secreting tumor cells (Fig. 5G). cGAS-deleted cells released an equal amount of EVs when compared to wild-type MDA-MB-231 cells (SI Appendix, Fig. 4H), with similar protein marker profile (Fig. 5F) and EV-associated CSF-1 (SI Appendix, Fig. 4I). EV-R from cGAS-deleted MDA-MB-231 cells had similar abilities to promote survival (SI Appendix, Fig. 4J) and to generate CD206⁺/CD163⁺ mo-macs when compared to controls (Fig. 5H, Left Panel). However, these EVs were unable to induce CXCL10 secretion (Fig. 5H, Middle Panel), while the induction of IL-8, an IFN-independent cytokine, remained unaltered (Fig. 5H, Right Panel). In addition, EV-R from cGAS-deleted cells induced slightly lower levels of IRF7 when compared to control EVs, while PDL1 levels remained unaltered (Fig. 5I). Similarly, when stimulating THP-1 cells, EVs from cGAS-deleted cells induced lower levels of IRF7 and Siglec-1 (SI Appendix, Fig. 4K) and of CXCL10 secretion (SI Appendix, Fig. 4L) than wild-type EVs. Altogether, these results demonstrate that cGAS-dependent production of cGAMP and its packaging in EVs contribute to the induction of the ISG response triggered by EVs in myeloid cells. Our results, however, do not exclude that, in addition to cGAMP, other cargoes of EVs, including cGAS-independent ones, may also participate in induction of ISG genes, in both STING-dependent and -independent manners.

**Human TNBC Release CSF-1-Containing EVs and Are Infiltrated with Macrophages Enriched in the EV-R-mo-macs Signature.** To investigate the clinical significance of CSF-1-containing EVs in TNBC and their ability to promote macrophage differentiation, we first evaluated whether EVs containing CSF-1 were released ex vivo by human tumors. EVs were concentrated from conditioned medium obtained upon overnight culture of resected primary breast tumor or juxta-tumor (noninvolved) explants (Fig. 6A). We measured CSF-1 in conditioned medium and observed that similar levels of total secreted CSF-1 were observed for TNBC and luminal tumor samples, while low levels were found for the juxta-tumor tissue (Fig. 6B, Left Panel). Strikingly, EVs from TNBC tumors contained detectable levels of CSF-1 when compared to luminal tumor-derived EVs, whose measurements were always close to the detection limit of the assay (Fig. 6B, Right Panel). To assess whether mo-macs

cells obtained in our in vitro system resembled cells present in the tumor microenvironment, we selected the most-deregulated genes (log2 fold change >2 when compared against all the groups) from the EV-R- or EV-P-mo-macs sets of genes (clusters 5 and 4, respectively, Fig. 4C and Dataset S1) to generate an EV-R (Fig. 6C and Dataset S2) and an EV-P gene signature (Dataset S2), which we used for further comparison with different in vivo RNA expression datasets. First, we analyzed in-house generated single-cell RNA-seq (scRNA-seq) data of tumor-infiltrating HLA-DR⁺/CD11c⁺ sorted cells from early-stage treatment-naive TNBC patients (SI Appendix). The scRNA-seq dataset was analyzed considering only the monocyte and macrophage clusters (Fig. 6D). Strikingly, the EV-R gene signature was expressed in specific clusters from myeloid cells infiltrating TNBCs in the scRNA-seq dataset (Fig. 6D, Middle Panel). Visualization of the EV-R signature on the scRNA-seq uniform manifold approximation and projection (UMAP) revealed that EV-R-mo-macs mainly resembled a cluster identified as early-macrophages responsive to IFN (Early-MAC-cluster 4) (Fig. 6D, Left Panel). These results highlight that the EV-R-induced response is found in an ex vivo dataset, suggesting that TNBC-derived EVs can contribute to shaping the phenotype of cells present in human cancers. Moreover, genes of the EV-P signature were highlighted in the regions of the UMAP representing a cluster of monocytes (cluster 7) and an early macrophage cluster 0 (Fig. 6D, Right Panel). Altogether, these results demonstrate that EV-R-mo-macs or EV-P-mo-macs generated in vitro have similar features to different monocyte-derived macrophages subpopulations present in human tumors. We next investigated whether the EV-R-mo-macs and EV-P-mo-macs signatures were associated with clinical outcome in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort (47). We observed a higher expression of the EV-R-mo-macs signature in TNBC when compared to luminal or HER2 subtypes, while the EV-P-mo-macs signature was slightly higher in luminal subset (Fig. 6E). In addition, only the EV-induced signature was correlated with estimated T and natural killer (NK) cell infiltration (2), both for memory, cytotoxic CD8⁺ T cells and exhausted CD8⁺ T cells (48), and core T regulatory cells (49) (Fig. 6F). The chemokines associated to the EV-R-mo-macs, CXCL9 and CXCL10, together with CXCL11 (Fig. 5A), correlate with the level of tumor-infiltrating lymphocytes in human cancers (50–52), and their secretion by macrophages is required for anti-tumor immune responses following immune checkpoint blockade in breast cancer (53). Thus, we evaluated the ability of macrophage CM to attract T cells in a migration assay. CM from EV-R-mo-macs was able to induce migration of total T cells when compared to medium alone (Fig. 6G), indicating that chemokines released by mo-macs upon tumor EV treatment promote T cell migration. Finally, when considering the clinical outcome among TNBC patients, the EV-R-mo-macs signature was significantly associated with an improved survival (Fig. 6H, Left Panel) while EV-P-mo-macs signature had no impact (Fig. 6H, Middle Panel). The EV-R signature contains only 23 genes of cluster 5 (Fig. 4C), and the vast majority (21 genes) are not canonical IFN response genes (Dataset S2). Notably, TNBC patients expressing high level of the canonical IFN signature were not as strongly associated with improved survival as patients expressing high EV-R-mo-macs signature (Fig. 6H). Collectively, our results show that TNBCs release CSF-1-exposing EVs that induce monocyte differentiation into a population of macrophages that possess a unique signature associated with better prognosis.
<figure><img src="image_20.png" /><figcaption>**Fig. 6.** TNBC human tumors release EVs containing CSF-1 and their infiltration with macs containing an EV-R-mo-macs signature confers them better survival probability. (A) Scheme of tissue-explant culture method for EV isolation from paired tumor tissue and juxta-tumor tissue. EVs were isolated from small volumes of prefiltered CM by ultracentrifugation. (B) Absolute CSF-1 pg present in 400 µL of conditioned medium as described in (A) or in EVs obtained from 400 µL of conditioned medium. (C) Heat map of the genes with the strongest up-regulation (log2 fold change >2) in the EV-R-mo-macs when compared to all the other conditions. These 23 genes constitute the EV-R-signature used to analyze RNA from patients' tumor samples. (D) Expression of EV-R-mo-macs- or EV-P-mo-macs-enriched genes in TNBC tumor-infiltrating HLA-DR$^+$CD11c$^+$ cells as determined by scRNA-seq. UMAP embedding of single cells as per the original study are shown, with color intensity representing normalized signature expression level. (Right Panel) UMAP map of macrophage and monocytes clusters from the HLA-DR$^+$CD11c$^+$cells scRNA-seq analysis from all seven TNBC patients with the identified clusters is shown. Each dot represents a cell, colored by clusters. EV-R and EV-P gene signatures (E) EV-R-mo-macs and EV-P-mo-macs signature expression across breast cancer subsets on the METABRIC cohort (Luminal, *n* = 1,314; Her2, *n* = 243; TNBC, *n* = 330). (F) Correlation of the EV-R-signature and the EV-P-signature with established signatures for CD8 cytotoxic, CD8 memory, CD8 exhausted, and CD4 T regulatory cells and NK cells in the METABRIC cohort. (G) Assay for migration of total T cells using xCELLigence. T cells were seeded in the upper chamber, and supernatant from rCSF-1-mo-macs or EV-R-mo-macs or EV-P-mo-macs or rCXCL10 in the lower chamber of CIM-plates. Migration was evaluated for 24 h. (H) Kaplan-Meier curves showing overall survival of TNBC patients from the METABRIC cohort stratified by high (red) and low (blue) expressions of EV-R-mo-macs (Left), EV-P-mo-macs (Middle), or of a canonical IFN signature (Right). Survival curves were compared with the log-rank test (*n* = 330).</figcaption></figure>

Discussion

In this work, we show that TNBC-released EVs induce mono-
cyte differentiation into a subset of proinflammatory mo-derived
macrophages. Our results demonstrate that EVs convey simulta-
neously multiple messages to target cells, which results in the
activation of signaling pathways not provided by soluble messen-
gers signaling individually. The unique association of the macro-
phage growth factor CSF-1 to EVs in TNBC cooperates with
EV molecules to promote the differentiation of macrophages
in vitro whose unique signature is found in patients. Moreover,
the CSF-1-EV-induced macrophages signature is associated with
a favorable patient's clinical condition in TNBC. Our results
show that CSF-1, which is synthesized as a membrane-bound

precursor (27), is sorted toward EVs and can have different
functional features than the classical cleaved soluble form.

Our study uncovers a molecular mechanism of TNBC-EVs
effect on macrophages. On the one hand, CSF-1 exposed on
the surface of the EVs promotes monocyte survival and differen-
tiation into macrophages. On the other hand, EVs carry other
signaling molecules, including (but not only) cGAMP, which
activate the STING and other maturation pathways in mono-
cytes, inducing the expression of IFN response genes. The
finding that EVs can activate STING in recipient monocytes
resulting in the expression of IFN response genes agrees with
the mounting evidence that STING activation in cancer leads
to IFN production and ISG expression. Several mechanisms of
activation have been proposed. On the one hand, tumor DNA
was suggested to be transferred to host immune cells where it
could be sensed by cGAS, leading to the activation of STING
(54–56). On the other hand, cGAMP can be directly transferred
to host immune cells where it triggers STING independently of
host cGAS, inducing the secretion of cytokines that enhance NK
cell cytotoxicity (46). Upon viral infection, cGAMP transfer had
been suggested to occur either via gap junctions (40, 46), through
viral particles (41, 42) and transfer via membrane fusion (57). Our
work thus highlights EVs as an active component of this cGAMP
transfer in vivo but suggests also that other EV components con-
tribute to monocyte activation, in both STING-dependent and
STING-independent manners.

The impact of EVs on monocytes resulted in the generation
of mo-macs transcriptionally different from those generated
upon treatment with tumor-secreted soluble factors poor on
EVs or recombinant CSF-1, thus allowing us to determine a
unique signature for each macrophage subtype. Macrophages
enriched in the EV-R-mo-macs signature were found in a
TNBC patients scRNA-seq dataset performed on HLA-DR+
CD11c+ cells, indicating that macrophages with a similar phe-
notype as those generated in vitro are present in human
tumors. Analysis of the METABRIC cohort indicated that the
signature associated with EV-R-mo-macs was enriched in
TNBC when compared to luminal and HER2 and impor-
tantly, was associated with T lymphocytes and NK cells infiltra-
tion and a better prognosis in TNBC. These results support
previous studies on BC showing that highly infiltrated tumors
are associated with good outcomes and responses to chemother-
apy (58). For TNBC, our results go in line with the finding of
different stratification of immune infiltration in TNBC
patients, and the existence of a population of fully inflamed
tumors associated with better outcomes characterized by a type
I IFN signature, infiltration of effector CD8+ T cells and of
proinflammatory macrophages (59, 60). Another recent work
described a similar immune-active TNBC subtype defined also
by a type I IFN activation, a higher NK and T cell infiltration
and also associated with favorable prognosis (60). Importantly,
despite the better prognosis, these TNBC tumors have the
highest expression of several immune checkpoints such as
PD-L1 (59, 60) and the immune modulator IDO-1, and are
associated with the highest T regulatory cells infiltration (59).
Here, we propose a mechanism consisting of tumor-derived
EVs inducing macrophages with high expression of immune
checkpoint molecules that secrete high levels of T cell chemoat-
tractant. These TAMs thus display a mixture of the M1- and
M2-associated features that were identified by in vitro experi-
mental systems of monocyte differentiation (61, 62), thus con-
firming recent proposals based on scRNA-seq studies of ex vivo
TAMs (2–4), that this simple dichotomy does not apply to the
complex context of tissue in general, and tumor in particular,
environment.

Whether the EV-induced macrophages found in tumors in vivo
are immuno-stimulatory per se will require further experiments.
However, our results suggest that these TAMs contribute to a par-
ticular local immune landscape, associated with T and NK cell
infiltration, which may respond well to immunotherapeutic and
chemotherapeutic approaches (63, 64). This observation has
important therapeutic implications for TNBC. These tumors are
the most aggressive tumors among all the BC subtypes, they have
poor clinical outcome when compared to non-TNBC, lack specific
therapies, and have higher risk of early relapse. Thus, identifying
the subset of patients that do respond to therapy is an unmet chal-
lenge. The EV-R-mo-macs signature identified in this work may
provide important information to classify patients that will respond

well to standard-of-care chemotherapy. In addition to chemother-
apy, immunotherapies have arisen as therapeutic options in TNBC
(65), since these tumors are highly immunogenic (66), which is
reflected by the dense infiltration of immune cells and the intratu-
moral inflammatory response (67, 68). It would now be interesting
to explore whether the EV-R-mo-macs gene expression signature
identified in our study could identify patients likely to respond the
most efficiently to such immunotherapies.

**Materials and Methods**

**Cell Culture and Transfections.** MDA-MB-231 and MCF-7 cells were cultured in Dulbecco's modified Eagle's medium (DMEM-Glutamax, Gibco), with 10% fetal calf serum (FCS, Gibco), 100 U/mL penicillin, and 100 µg/mL streptomycin (Gibco). BT-549 and THP-1 cells were cultured in RPMI-1640-Glutamax medium (Gibco) with penicillin-streptomycin and 10% of FCS. CRISPR/Cas9 modified MDA-MB-231 and MCF-7 cells overexpressing CSF-1 (see *SI Appendix*) were kept in culture in complete medium under antibiotic selection (2 µg/mL puromycin, Thermofisher).

**CRISPR/Cas9 Edited Cells.** STING KO THP1 cells were established by Cas9/gRNA RNP electroporation using predesigned Alt-R CRISPR-Cas9 crRNAs (IDT technologies, see *SI Appendix*). cGAS KO, CSF-1 KO, or Rab11 KO MDA-MB-231 cells were established by lentiviral-mediated CRISPR/Cas9 method (see *SI Appendix*). The knockout efficiency was evaluated by quantitative reverse transcription PCR (RT-qPCR), Western blotting, and/or LEGENDPlex/ELISA (see *SI Appendix*).

**Human Specimens and Processing.** Analysis of tumors was performed following relevant national law on protection of people taking part in biomedical research (https://www.sciencedirect.com/topics/medicine-and-dentistry/biomedical-research). Female patients were included in this study and only samples from patients that provided verbal informed consent for tissue donation were processed. Human experimental procedures were approved by the Institutional Review Board and Ethics committee of the Institut Curie Hospital group (approval February 12, 2014) and CNIL (Commission Nationale de l'informatique et des Libertés) (N° approval: 1674356).

Fresh tumor and juxta-tumor tissue were harvested from patients with BC undergoing resection at Institut Curie (69). Surgical residues available after pathological analysis and not required for diagnosis were used. For tumor secretome analysis, once resected, the tissue was placed in CO₂-independent medium (Gibco) within minutes of collection and submitted for downstream processing and analysis. Tissues were cut into 15-20 mg pieces and cultured in one well of a 48-well plate in 250 µL of RPMI GlutaMAX (Gibco) supplemented with 10% FBS (HyClone), 100 U/mL penicillin/streptomycin (Gibco), 1% MEM non-essential amino acids (Gibco), and 1% Pyruvate (Gibco) at 37 °C with 5% CO₂. After 24 h, conditioned media were diluted 1/2 with complete RPMI medium, then filtered with a 0.22 mm filter before storage at -80 °C.

**EV Isolation.** Cell lines were cultured for 24 h without serum before EVs isolation. The following day concentrated conditioned medium (CCM) was harvested by pelleting cells at 400 × g for 10 min at 4 °C. Supernatant was centrifuged at 2,000 × g for 20 min at 4 °C to discard 2K pellet and then concentrated on a sterilized Sartorius Centrifugal Filter (MWCO = 100 kDa; VS2061) or Centricon Plus-70 Centrifugal Filter (MWCO = 100 kDa; Millipore). Medium was concentrated to 500 µL and overlaid on 70 nm qEV size-exclusion columns (Izon, SP1) for separation. Twenty-two 500-µL fractions were recovered and analyzed separately or pooled, 7-10 as EV-Rich (EV-R) fraction and 15-22 as EV-Poor (EV-P) fraction. Pooled fractions were then concentrated using 10 kDa cutoff filters (Amicon Ultra-15, Millipore). Protein concentration in EV-R, EV-P, or CCM was measured using Micro-BCA (Thermo Scientific) in the presence of 0.2% SDS.

A total of 200-400 µL of thawed human patients' tumor supernatants were ultracentrifuged at 100,000 × g for 30 min in a TLA-45 rotor (Beckman Coulter). Pellets were resuspended in 25 µL of PBS.

**EV Characterization.**

**Western blot.** Cell lysates (CL) from 2.10⁵ (Fig. 1C) or 5.10⁴ (Fig. 5F) cells, 20 µL of the 500 µL unconcentrated SEC fractions from 400 × 10⁶ cells (Fig.
1C) or pooled EV-R and EV-P fractions obtained from $20 \times 10^6$ cells (Fig. 5F) were analyzed by Western blot in nonreducing conditions (see SI Appendix). Membranes were blotted with the following antibodies: mouse anti-human CD63 (clone H5C6, BD Bioscience), mouse anti-human CD9 (clone MM2/57, Millipore), rabbit anti-human 14-3-3 (EPR6380, GeneTex), rat monoclonal anti-human HSC70 (clone 1B5, Enzo Life Sciences), or GP96 (clone 9G10, Enzo Life Sciences). Monoclonal rabbit anti-human syntenin was a gift from P. Zimmermann. Secondary antibodies were purchased from Jackson Immuno-Research.

**Bead-based multiplex flow cytometry assay.** EV-R fractions were subjected to bead-based multiplex analysis by flow cytometry according to manufacturer instructions using either anti-CD9/CD63/CD81-APC (MACSPlex Exosome Kit, human, Miltenyi) or anti-CSF1-APC (clone 26786, R&D systems, 1/50) for detection (see SI Appendix).

**Immunoisolation.** EV-R fraction from $100 \times 10^6$ cells was enriched for tetraspanin (CD9, CD63, and CD81)-expressing EVs using Pan Exosome Isolation Kits (Miltenyi Biotech) following manufacturers' instructions. EVs in the flow-through (FT) were recovered by ultracentrifugation at 100,000 × g in a TLA-45 rotor for 20 min (Beckman). Pulled-down material (PD) and FT from $10 \times 10^6$ cells were analyzed by WB for presence of CD9 and CD63. PD from 40–80 × $10^6$ cells and FT from 4–8 × $10^6$ were used to measure CSF-1 by ELISA.

**Imaging flow cytometry.** A total of $10^8$ EVs were analyzed at the single EV level by imaging flow cytometry (ImageStream X MKII, Amnis/Luminex) following guidelines and principles described in Görgens et al. (28) (see SI Appendix), with the following labels: lipid dye MemGlow 488 (Cytoskeleton, Inc), anti-CD81-APC (dilution 1/25) (Clone 5A6, Biolegend), and anti-CSF-1-PE (dilution 1/25) (Clone 26786, R&D Systems). Adequate PBS, unstained, Membrigh488, CD81, CSF-1 monocolors, and fluorescence minus one (FMOs) EVs controls were performed in parallel.

**Monocyte Isolation and Culture.** Blood $CD14^+$ monocytes from healthy donors' peripheral blood mononuclear cells (see SI Appendix) ($2 \times 10^5$ cells) were cultured for 5 d in complete RPMI medium with 2–4 µg of proteins or equivalent CSF-1 amounts (0.02 ng/mL) from EV-R or EV-P fractions or CCM, or 100 ng/mL of rGM-CSF or 100 ng/mL of rCSF-1 or left untreated. On day 5, supernatants and cells were recovered for analysis. In some experiments, monocytes were pretreated with increasing amounts of STING-specific inhibitor H-151 (Invivogen) or with antibodies against CSF-1R (Bio Techne, MAB3291-SP) or GM-CSFR (Bio Techne, MAB706-SP) for 1 h before the addition of the EV-R fraction.

CTRL or STING KO THP1 cells ($5 \times 10^5$ cells in 100 µL of complete RPMI) were plated with 0.02 ng/mL of CSF-1 or EV-R fractions overnight at 37 °C or left untreated. Cells and supernatants were recovered at 18 h for analysis.

**Flow Cytometry.** Cells were stained (see SI Appendix) with different combinations of the following primary antibodies: HLA-DR/DQ/DP FITC (Clone REA33, Miltenyi), CD163 PE (clone GHI/61, Biolegend), MerTK PeCy7 (clone 590H11G1E3, Biolegend), CD206 Alexa647 (clone 15–2, Biolegend), PDL1 BV421 (clone 29E.2A3, Biolegend), CD16 PE-Cy7 (clone 3G8, Biolegend), CD14 APC-Cy7 (clone 63D3, Biolegend), CD1a PE-Cy5 (clone HI149, BD), anti-CD88 PE (clone S5/1, Biolegend), CD204 APC (clone 7C9C20, Biolegend), CD68 Pe-Vio770 (clone REA835, Miltenyi), SIGLEC1 APC (REA197, Miltenyi), and IRF7 AF488 (12G9A36, Biolegend) or isotype-matched control antibodies. For IRF7 staining, cells were permeabilized with Transcription Factor Staining Buffer (Thermo). Cells were analyzed on a FACSVerse (BD Biosciences) or MACSQuant (Miltenyi) instrument. Data were analyzed with FlowJo (FlowJo LLC)

**Morphological Analysis.** Cells were subjected to cytospin and colored with May-Grunwald/Giemsa staining (Sigma). Pictures were taken with a CFW-1308C color digital camera (Scion Corporation) on a Leica DM 4000 B microscope.

**Cytokines Quantification.** CSF-1 and GM-CSF levels in supernatant were measured with LEGENDplex multiplex assay according to manufacturer's instructions. Samples were acquired on a BD FACSverse and analyzed using LEGENDplex software (Biolegend). In some experiments, CSF-1 was measured by ELISA (RAB0098 Sigma-Aldrich) following manufacturer instructions.

Cytometric Bead Array (BD CBA Flex Sets) was used for measuring IL-8, IL-6, G-CSF, CCL2 (MCP1), CXCL10 (IP10), and CXCL9 (MIG) in supernatants according

to manufacturer's instructions. Samples were acquired on a BD FACSverse and analyzed with the FCAP Array software.

**cGAMP Quantification.** 2'3'-cGAMP ELISA Kit (Cayman Chemical) was used for the quantification of cGAMP in EV-R and EV-P fractions according to the manufacturer's instructions, and as described in Jneid et al. (70). After performing the assay, the plate was read at a wavelength of 450 nm. Data were fitted to a 4-parameter sigmoidal curve.

**RNA-Seq Library Preparation and Analysis.** RNA from $5 \times 10^5-10^6$ cells mo-macs cells was used for sequencing performed using NovaSeq (Illumina) (100-nt-length reads, paired end) (see SI Appendix). Data are accessible through Gene Expression Omnibus series accession number GSE173771. Differential gene expression analysis was performed using DESeq2 (v1.22.2) (71). Differentially expressed genes between each pair of conditions displaying an adjusted *P* value <0.01 and log2 fold change >0.5 were kept. The union of these genes was used as input for *k*-means clustering of gene expression. The gene ontology analysis was performed using Enrich (https://maayanlab.cloud/Enrichr/) (72). Enrichments were considered statistically significant if they had *q*-values (i.e., *P*-values adjusted for multiple testing) <0.05. EV-R-genes involved in cytokine mediated signaling pathway (the most significant GO term) were queried in a database of IFN-regulated genes, Interferome (http://www.interferome.org/) (33). Gene signatures for the EV-R-mo-macs and the EV-P-mo-macs groups (Dataset S2) were generated considering the differentially expressed genes displaying an adjusted *P* value <0.01 and log2 fold change >2 when compared among all the other RNA-seq groups. A canonical IFN-gene signature was generated by curation of the literature (kindly provided by L. Niborski, INSERM U932).

**scRNA-Seq Analysis.** Our in-house study of single-cell RNA-seq on HLA-DR$^+$ CD11c$^+$ infiltrating tumors from TNBC patients was used (see SI Appendix) for experimental details; data deposited in Zenodo repository under accession number 5939839). The R package Seurat v3 was used to integrate samples and analyze the datasets. Gene signatures were computed for each cell using Add-ModuleScore function from Seurat. Briefly, this function calculates for each individual cell the average expression of each gene signature, subtracted by the aggregated expression of control gene sets. The calculations were done on the integrated matrix, setting a parameter of 20 control genes.

**Survival Analysis and Correlation Plots in Public Datasets of BC Patients.** Bulk analyses were performed using METABRIC cohort (47). Statistical tests were performed using unpaired *t* tests.

Survival plots were generated using XenaBrowser (https://xenab browser.net/) using METABRIC cohort. High and low cohorts were split in 2 by the median. Correlation plots were computed using the same METABRIC TNBC cohort, using Spearman correlation between gene sum from the signatures, and plotted using heatmap R package (v1.0.12).

**Migration Assay.** Migration assays were performed with the xCELLigence RTCA instrument using CIM-16 Transwell plates according to the manufacturer's recommendations (see SI Appendix). A total of $40 \times 10^5$ CD3 T cells in 100 µL of medium with FBS were added in the upper chamber, CM from EV-R-mo-macs, EV-P-mo-macs or CSF-1-mo-macs, or DMEM 10% FBS without or with 100 ng/mL of CXCL10 (negative and positive controls, respectively) were added in the lower chamber. Plates were loaded into the xCELLigence RTCA DP instrument inside a 37 °C incubator for 24 h with readings every 15 min. Data were collected and analyzed by RTCA software.

**Data Availability.** Bulk RNA sequencing data are openly available in the Gene Expression Omnibus at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE173771, reference number GSE173771.

scRNA sequencing data are openly available in the Zenodo repository at https://zenodo.org/record/5939839, reference number 5939839.

**ACKNOWLEDGMENTS.** We wish to thank Dr. Sebastian Amigorena and Dr. Leticia Niborski (INSERM, U932) for providing tools and helpful discussions, Dr. Jennifer Jones and Dr. Joshua Welsh (NIH/NCI) for helpful discussions, and the Institut Curie NSG and Flow Cytometry facilities for their assistance. This work was supported by Institut Curie (including NCI.NIH-PIC3i-2018 and PIC-TME programs), INSERM, CNRS, the French National Cancer Institute (11548), the French National Research Agency (ANR) (ANR-18-CE13-0017-03, ANR-18-CE15-0008-01,
and ANR-18-CE16-0022-02), Fondation ARC (PGA1 RF20180206962 to C.T. and AAP SIGN'IT2019 to E.R.), H2020-Marie Sklodowska-Curie Innovative Training Network (722148, TRAIN-EV), the National Institute on Drug Abuse (DA040385), French IdEx and LabEx DCBIOL (ANR-10-INSB-04, ANR-10-IDEX-0001-02 PSL, ANR-10-LABX-0038, ANR-11-LABX-0043, and ANR-18-IDEX-0001 Université de

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Extracellular vesicles from triple negative breast cancer promote pro-inflammatory
macrophages associated with better clinical outcome

Mercedes Tkach¹*, Jessie Thalmensi¹, Eleonora Timperi¹, Paul Gueguen¹, Nathalie Névo¹, Eleonora Grisard¹, Philemon Sirven¹, Federico Cocozza¹, Alizée Gouronnec¹, Lorena Martin-Jaular¹, Mabel Jouve², Fabien Delisle¹, Nicolas Manel¹, Derek C Rookhuizen¹, Coralie L Guerin³, Vassili Soumelis⁴,⁵, Emanuela Romano¹, Elodie Segura¹, Clotilde Théry¹#*

**Supplementary Information**

**Supplementary Materials and Methods**

Cell culture and transfections

MDA-MB-231 stably expressing CD9-tdTomato (Supplementary Figure 1) were generated by transfection with the Amaxa kit V (Lonza), following manufacturer's instructions. tdTomato-CD9-10 was a gift from Michael Davidson (Addgene plasmid # 58076; http://n2t.net/addgene:58076; RRID: Addgene_58076). The antibiotic for selection (Geneticin, 2 mg/mL, Gibco) was added the day after transfection. Cells expressing the fluorescent molecules were sorted on a BD FACSARIA III (BD Biosciences) instrument and kept in culture under antibiotic selection.

MCF-7 cells overexpressing CSF-1 were generated by transduction with recombinant
retroviruses. Briefly, the retroviral vector MSCV-(pbabe puro mcs)-human CSF-1 full length
(CSF4)-IRES-GFP (a gift from Martine Roussel & Charles Sherr (Roussel and Sherr 1989);
Addgene plasmid # 86796 ; http://n2t.net/addgene:86796 ; RRID: Addgene_86796), the
packaging construct pCL-10A1 (Novus Biologicals) and the envelope pCMV-VSV-G were co-
transfected into HEK 293 LTV cells using the TransIT®-293 Transfection Reagent (Mirus Bio)
according to the manufacturer's instructions, and culture fluid was harvested 48-72 h post-
transfection and concentrated by ultracentrifugation. Resuspended retroviruses were used to
transduce MCF-7 cells. Transduced cells were selected with 2 µg/ml puromycin
(ThermoFischer Scientific) that was added the day after transduction. Cells expressing GFP were sorted on a BD FACSARIA III (BD Biosciences) instrument and kept in culture under antibiotic selection.

## CRISPR/Cas9 edited cells

STING KO THP1 cells were established by Cas9/gRNA RNP electroporation. Predesigned Alt-R CRISPR-Cas9 crRNAs, Hs. Cas9.TMEM173.1. AA, was ordered from IDT technologies. crRNA (100uM) was mixed with tracrRNA (100uM) and annealed 5 min at 95°C. To form the RNP complex, the tracrRNA-crRNA duplex was incubated with 10ug of Cas9 Nuclease V3 protein (IDT technologies). After 10 min at room temperature, the RNP complex was electroporated in 2x10⁶ THP-1 cells using Lonza Electroporation Kit (SG Cell Line 4D-NucleofectorTM X Kit S, V4XC-3032) following manufacturer's instructions. After 24h at 37°C cells were expanded. The knockout efficiency was evaluated by western blotting.

cGAS KO, CSF-1 KO or Rab11 KO MDA-MB-231 cells were established by lentiviral-mediated CRISPR/Cas9 method. Briefly, lentiviruses were produced with the co-transfection in HEK 293-LTV cells using the TransIT® 293 Transfection Reagent (Mirus Bio) of the envelope pCMV VSV G, the packaging psPAX2 with plasmids pLentiCRISPRv2 for CSF-1KO (guide RNA sequences 1 and 2 respectively CACCGGCGAGCAGGAGTATCACCG and CACCGGTGTCCACTCCCAATCATG) and Rab11KO (guide RNA sequence CATATGAAAATGTAGAGCGA), or pLCRISPR-CMV for cGAS (pLCRISPR-CMV-cGAS3 described in ¹, guide RNA sequence GGGGATCCCGACTTCCTGGC). Supernatants were recovered after 48h, concentrated by ultracentrifugation at 120,000xg during 1h 30 min in a SW32 Ti rotor. Resuspended pellets containing the lentiviruses were added to MDA-MB-231 cells. Following transduction, cells were selected with puromycin (2 µg/ml). The knockout efficiency was evaluated by RT-qPCR, western blotting and/or LegendPLEX/ELISA.

## Transfer of CD9-tdTomato EVs to PBMCs
EVs from CD9-tdTomato-MDA-MB-231 cells (Supplementary Figure 1) were isolated by differential ultracentrifugation. Briefly, cells were incubated for 24 hours in DMEM-Glutamax (Gibco) without serum before collection of CM for EV isolation. CM was centrifuged 350xg for 10 min, at 4°C to pellet cells. Supernatant was centrifuged at 2,000xg for 20 min at 4°C, transferred to new tubes and centrifuged directly for 120 min at 200,000xg in a 45Ti rotor (Beckman). The pellet was washed in 40-50 ml of PBS and re-centrifuged at the same speed before being re-suspended in sterile PBS (1 µl per million of secreting MDA-MB-231 cells). For the transfer assay, EVs from 10 million secreting cells were incubated for 18 h with fresh PBMCs (5 million cells) in a round bottom 96 well plate. Cells were incubated with human Fc block reagent (Miltenyi) and LIVE/DEAD Fixable Aqua Dead Cell Stain Kit (ThermoFischer) before the staining with the following anti-human antibodies: CD3 FITC (Clone UCHT1, BD), CD4 BV785 (clone OKT4, Biolegend), CD8 BUV395 (Clone RPA-T8, BD), CD14 BV605 (Clone M5E2, Biolegend), CD56 BV711 (Clone NCAM16.2, BD), CD11c PE-Cy7 (Clone Bu15, Biolegend), HLA-DR PE-Cy5 (Clone G46-6, BD), CD19 Alexa Fluor 700 (Clone HIB19, BD) and BDCA-2 BV421 (Clone 201A, Biolegend). Cell populations within PBMCs were identified as follows: Monocytes (CD14⁺ CD19⁻ CD3⁻), CD4 T cells (CD3⁺ CD4⁺), CD8 T cells (CD3⁺ CD8⁺), NK cells (CD56⁺ CD3⁻), B cells (CD19⁺ CD3⁻), DCs (CD3⁻ CD56⁻ CD19⁻ CD11c⁺ HLA-DR⁺), pDC (CD3⁻ CD56⁻ CD19⁻ CD11c⁻ HLA-DR⁺ CD123⁺).

## CSF-1 gene expression quantification

Knockout efficiency of CSF-1 using CRISPR/Cas9 was evaluated by RT-qPCR. Briefly, RNA was extracted from one million MDA-MB-231 control cells or cells transduced with CSF-1 plentiCRISPRCas9 (or pLentiCRISPRv2-CSF-1) lentiviruses using RNeasy Mini Kit (Qiagen). cDNA was synthesized with random hexamer from 1 µg total RNA using SuperScript II Reverse Transcriptase (ThermoFischer Scientific). Real-time qPCR was performed using QuantiFast SYBR Green (Qiagen). Expression level of mRNA was evaluated by the cycle of quantitation thresholds (Cq) normalized to Cq of GAPDH and the expression level was
calculated as compared with the control cells value. The primers for hGAPDH and hCSF-1 are
from Qiagen (QuantiTect Primer Assay).

Western blot

Cell lysates (CL) for western blot were obtained by incubating 1.10⁶ cells in 25 µL of lysis buffer (50 mM Tris, pH 7.5, 0.3 M NaCl, 1% Triton X-100, 0.1% sodium azide) with 2% complete protease inhibitor (Roche) for 20 min on ice, followed by a 13,000 rpm centrifugation for 15 min at 4°C to recover the supernatant. 20 µL of the 500 µL unconcentrated SEC fractions from 400.10⁶ cells or pooled EV-R and EV-P fractions obtained from 20.10⁶ cells and CL from 2.10⁵ cells were mixed with Laemmli sample buffer without reducing agent (BioRad). After boiling 5 min at 95°C, samples were loaded on a 4-15% Mini-protean TGX-stain free gels (BioRad). Transfer was performed on Immuno-Blot PVDF membranes (BioRad), with the Trans-blot turbo transfer system (BioRad) during 7min. Blocking was performed during 30 min with Roche blotting solution in TBS 0,1% Tween. Primary antibodies were incubated overnight at 4°C and secondary antibodies (HRP-conjugated goat anti-rabbit IgG (H+L), HRP conjugated goat anti-mouse IgG (H+L) and HRP-conjugated goat anti-rat IgG (H+L), Jackson Immuno-Research) during 1h at room temperature (RT). Development was performed using Clarity western ECL substrate (BioRad) and the Chemidoc Touch imager (BioRad).

Bead-Based Multiplex Flow Cytometry Assay

EV-R fractions were subjected to bead-based multiplex analysis by flow cytometry (MACSPlex Exosome Kit, human, Miltenyi). Samples were processed according to manufacturer instructions. EV-R fraction corresponding to EVs secreted by 40 million cells were diluted with MACSPlex buffer to a final volume of 120 µL and 15 µL of MACSPlex Exosome Capture Beads were added. Samples were incubated on an orbital shaker overnight at room temperature protected from light. After washing, detection antibodies (APC-conjugated anti-CD9/anti-CD63/ anti-CD81 mix at dilution recommended by provider, or anti-CSF1-APC (clone 26786, R&D systems, 1/50) were incubated for 1 h at RT. Flow cytometric analysis was performed
with a MACSQuant Analyzer 10 with the corresponding software (Miltenyi Biotec) following the
acquisition recommendations for the MACSPlex Exosome kit (Miltenyi Biotec). FlowJo
software (v10, FlowJo LLC) was used to analyze flow cytometric data. The 39 single bead
populations were gated to allow the determination of the APC signal intensity on the respective
bead population. Median fluorescence intensity (MFI) for each capture bead was background
corrected by dividing respective MFI values from matched non-EV controls that were treated
exactly like EV-containing samples. Values were log10 transformed. Only normalized log10
values higher than 0 were considered as positive.

Imaging Flow Cytometry

10⁸ EVs were stained with lipid dye Membright 488 (Idylle, now MemGlow 488, Cytoskeleton, Inc) to reach a final concentration of 200 nM in filtered PBS (0.22 µm filters). After 30 min of incubation at room temperature in the dark, EVs were washed with 1 ml of filtered PBS and ultracentrifugation at 100,000 xg for 30 min in a TLA-45 rotor (Beckman Coulter). EVs were then stained with anti-CD81-APC (dilution 1/25) (Clone 5A6, Biolegend) and anti-CSF-1-PE (dilution 1/25) (Clone 26786, R&D Systems). Washing step was repeated before resuspending the EV pellet in 40 µl of filtered PBS (2.5x10⁶ EVs/µl). Adequate PBS, unstained, Membright488, CD81, CSF-1 monocolors and Fluorescence Minus One (FMOs) EVs controls were performed in parallel. EVs were analyzed with a four lasers Image Stream X MKII (Amnis/Luminex) equipped with two cameras. The instrument was set to remove beads during acquisition and to collect Brightfields (channels 1 and 9), Side Scatter (channel 6 laser 785 nm 25 mW), Membright 488 (channel 2 laser 488 nm 100 mW), anti-CSF-1-PE (channel 3 laser 561 nm 110 mW) and anti-CD81-APC (channel 11 laser 642 nm 150 mW) with the 60x magnification. Data were analyzed with IDEAS software.

Monocyte isolation and culture
Peripheral Blood Mononuclear Cells (PBMC) were prepared by centrifugation on a Ficoll gradient (Lymphoprep, Greiner Bio-One). Blood CD14+ monocytes were isolated from healthy donors' PBMC by positive selection using magnetic beads (Miltenyi). Monocytes (2x10⁵ cells) were cultured for 5 days in complete medium (RPMI-1640-GlutamaxTM supplemented with 10% FCS, 10mM Hepes (Gibco), 0.1 mM nonessential amino acids (Gibco), 1 mM Sodium Pyruvate (Gibco), 100 U/mL penicillin, 100µg/mL streptomycin) with treatments or left untreated. On day 5, supernatants and cells were recovered for analysis.

### Flow cytometry

Cells were stained in PBS containing 0.5% BSA and 2mM EDTA with different combinations of the primary antibodies or isotype-matched control antibodies. Prior to the staining with the primary antibodies, cells were incubated with human FC Blocking reagent (Miltenyi) and LIVE/DEAD Fixable Aqua Dead Cell Stain Kit (ThermoFischer). For CD68 staining, cells were permeabilized with BD Cytofix/Cytoperm™ Fixation/Permeablization Kit (BD Biosciences). For IRF7 staining, cells were permeabilized with Transcription Factor Staining Buffer (Thermo). Cells were analyzed on a FACSVerse (BD Biosciences) or MACSQuant (Miltenyi) instrument. Data was analyzed with FlowJo (FlowJo LLC)

### RNA-seq library preparation and analysis

RNA from mo-macs cells (5.10⁵-10⁶ cells) was extracted by RNeasy Mini Kit (QIAGEN), including on-column DNase digestion as described by the manufacturer's protocol. The integrity of the RNA was confirmed in BioAnalyzer using RNA 6000 Pico kit (Agilent Technologies). Libraries were prepared according to Illumina's instructions accompanying the TruSeq Stranded mRNA library Prep Kit (Illumina). 500 ng of RNA was used for each sample. Library length profiles were controlled with the LabChip GXTouchHT system (Perkin Elmer). Sequencing was performed using NovaSeq (Illumina) (100-nt-length reads, paired end).
Genome assembly was based on the Genome Reference Consortium (hg38). Quality of RNA-seq data was assessed using *FastQC* (v0.11.5)². Reads were aligned to the transcriptome using *STAR* (v2.5.3a)³. Differential gene expression analysis was performed using *DESeq2* (v1.22.2)⁴. Genes with low number of counts (<10 across all samples) were filtered out. Differentially expressed genes between each pair of conditions were calculated with the design 'donor + condition'. Only genes displaying an adjusted p-value <0.01 and log2FoldChange > 0.5 were kept. The union of these genes was used as input for k-means clustering of gene expression. The normalized count matrix was scaled and centered, and k-means clustering was performed using *stats* (v3.5.0) with k=7.

The gene ontology analysis was performed using Enrichr (https://maayanlab.cloud/Enrichr/)⁵. We evaluated results from Enrichr for Gene Ontology (GO) annotated sets of genes based on the biological processes in which they participate. For these analyses, enrichments were considered statistically significant if they had *q*-values (i.e., *p*-values adjusted for multiple testing) <.05. EV-R-genes involved in cytokine mediated signaling pathway (the most significant GO term) were queried in a database of IFN-regulated genes, Interferome (http://www.interferome.org/)⁶.

Gene signatures for the EV-R-mo-macs (Figure 6C, Supplementary Dataset 2) and the EV-P-mo-macs groups (Supplementary Dataset S2) were generated considering the differentially expressed genes displaying an adjusted p-value<0.01 and log2FoldChange>2 when compared among all the other RNAseq groups. A canonical IFN-gene signature was generated by curation of the literature (Supplementary Dataset S2, kindly provided by L. Niborski, INSERM U932).

### scRNASeq analysis of myeloid cells of TNBC patients

### Breast cancer patient cohorts and tissue specimens

Tumor (TUM) and adjacent-juxta (JT) tissue samples were obtained from early-stage, treatment-naïve triple-negative breast cancer (TNBC) (N=4). For single-cell RNAseq studies,
fresh TUM specimens from treatment-naïve TNBC (N=4) pts were obtained, of which 3 were
paired with JT samples.

Tissue dissociation

Samples from prophylactic mastectomies, TUM and JT were gently dissociated and enzymatically digested by an incubation of 30-40 minutes, at 37°C in agitation, in CO2-independent medium (Gibco) supplemented by Collagenase I (2mg/mL), (Sigma) Hyaluronidase (2mg/mL) (Sigma), and DNase (25ug/mL) (Roche). Afterwards, single cell suspensions were obtained by disrupting the fragments with a syringe plunger over a 40uM cell strainer (Fisher Scientific), washing with PBS (Gibco) supplemented by 2mM EDTA (Gibco) and 1% of human serum (BioWest). Cell suspension was obtained after 10' of centrifugation. After isolation of total tissue-infiltrating cells, cells were counted in CO2-independent medium plus 5% of FBS. Peripheral blood mononuclear cells (PBMCs) were isolated using Lymphoprep solution (StemCell).

Myeloid cell sorting, Single-cell RNAseq and library preparation

HLA-DR⁺CD11c⁺ myeloid cells from TUM and JT-infiltrating cells were FACS sorted (ARIA-BD Bioscience). DAPI solution (BD-Bioscience) was used for dead cells exclusion. CD11c (PE), HLA-DR (PE-Cy7), CD45 (APC-Cy7), CD3-CD56-CD19 (Alexa Flour 700) were included for the staining. Single-cell suspension was loaded into a Chromium Single Cell Chip (10X Genomics) according to the manufacturer's instructions. Target capture rate correspond to 5000 -10.000 individual cells/sample. Single-cell RNA-seq libraries were prepared using Chromium Single Cell 3' v3 Reagent Kit (10X Genomics) according to manufacturer's protocol. Indexed libraries were equimolarly pooled and sequenced on an Illumina NovaSeq 6000 system using paired-end 28x91bp as sequencing mode. A coverage corresponding to 50,000 reads/cell was obtained.
Single cell-RNA-sequencing data processing

Data have been deposited in the zenodo repository: https://zenodo.org/record/5939839.

Single-cell expression was analyzed using the Cell Ranger single-cell Software Suite (v3.0.1 -
10X Genomics) to perform quality control, sample de-multiplexing, barcode processing and
single-cell 3' gene counting. Sequencing reads were aligned to the GRCh38 human reference
genome. Further analysis was performed in R (v3.5.1) using the Seurat package (v3.1.1)
(https://pubmed.ncbi.nlm.nih.gov/31178118/). Cells were then filtered out when expressing
less than 500 genes, or when expressing more than 10% mitochondrial genes. From the 7
samples, 11340 cells (10005 cells for TUM and 1335 for JT) were kept for statistical analysis.

For each sample, the gene-cell-barcode matrix of the samples was then normalized to a total
of 1e4 molecules. The top 5000 variable features were identified using the "vst" method from
Seurat where both lowly and highly expressed genes are transformed onto a common scale.

For the 7 samples altogether, we computed the integration anchors using the Seurat v3
integration method. This method is leveraging closely-related cells (termed anchors) between
datasets to compute a batch-corrected matrix. Top 30 CCA components were used to find
transfer anchors between datasets and used to generated the integrated matrix for the 7
samples. Top 30 Principal Components were computed and Uniform Manifold Approximation
and Projection (UMAP) was performed using the top 30 PCs of the integrated matrix. Clusters
were identified using the *FindNeighbors* and *FindClusters* function in Seurat with a resolution
parameter of 0.6 and using the first 30 principal components. Unique cluster-specific genes
were identified by running the *Seurat FindAllMarkers* function using Wilcoxon test on the
uncorrected matrix. Then clusters containing contaminating cells were removed from the
analysis. CD3, CD4, CD8 expression was used to remove T cell clusters. CD19, MS4A1
expression was used to remove B cell clusters, CD56 expression was used to remove NK cell
clusters. CD1c, LAMP3, AXL and CLEC9A were used to remove DCs. Signature scores were computed using the Seurat function *AddModuleScore* using the gene signature of interest and the integrated matrix. Briefly this function calculates for each individual cell the average expression of each gene signature, subtracted by the aggregated expression of control gene sets.

## Migration assay

Migration assays were performed with the xCELLigence RTCA instrument according to Manufacturer's recommendations. Briefly in the lower chamber of the CIM-16 plate, CM from EV-R-mo-macs, EV-P-mo-macs and CSF-1-mo-macs was added. DMEM 10% FBS, 1%P/S without or with 100 ng/ml of CXCL10 was added as negative and positive control respectively. Once the upper chamber was placed on top of the lower chamber, 50 µl of medium with FBS were added to each well of the upper chamber to cover the membrane surface. Plates were left during 1h inside the 37°C incubator to reach equilibrium. After this incubation, background measurement was performed. 40000 CD3 T cells in 100 µl of medium with FBS were added to each well of the upper chamber. Plates were left at room temperature for 30 minutes to allow the cells to settle evenly. Plates were then loaded into the xCELLigence RTCA DP instrument inside a 37°C incubator. A run of 24 hours with readings every 15 minutes was programmed. Data was collected and analyzed by RTCA software.

## References:

1. Gentili, M. et al. Transmission of innate immune signaling by packaging of cGAMP in viral particles. *Science* **349**, 1232-1236 (2015).

2. Andrews, S. FastQC: a quality control tool for high throughput sequence data. *Available online at*: http://www.bioinformatics.babraham.ac.uk/projects/fastqc (2010).

3. Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. *Bioinformatics* **29**, 15-21 (2013).

4. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. *Genome Biol.* **15**, 550 (2014).

5. Kuleshov, M. v et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. *Nucleic Acids Res.* **44**, W90-7 (2016).

6. Rusinova, I. et al. Interferome v2.0: an updated database of annotated interferon-regulated genes. *Nucleic Acids Res.* **41**, D1040-6 (2013).
**Supplementary Dataset S1:** List of genes present in the K-means clusters.

**Supplementary Dataset S2:** List of gene signatures calculated as the differentially expressed genes with an adjusted p-value <0.01 and log2FC > 2 when compared to all the other RNAseq groups, and of canonical IFN-genes curated from the literature.

<figure><img src="image_21.png" /><figcaption>**Supplementary Figure 1**</figcaption></figure>

**Supplementary Figure 1. PBMC uptake of tumor derived EVs**

(A) EVs from MDA-MB-231-CD9-tdTomato cells were cultured ON with total PBMCs from healthy donors. Cells were stained with different markers in order to identify all cell populations present in peripheral blood mononucleated cells. We gated on the positive tdTomato cells and then calculated the percentage from the tdTomato+ cells that corresponded to each immune cell type. The mean + SD of five individual PBMC donors is shown.
<figure><img src="image_22.png" /><figcaption>Supplementary Figure 2</figcaption></figure>

Supplementary Figure 2 (related to figure 2). Quantification of surface markers on d5 monocyte cultures, Rab11a-depleted MDA-MB-231 cells and EV characterization and effect on monocyte cultures.

(A) Expression of different markers in monocytes exposed to EV-R, EV-P, rGM-CSF and rCSF-1, calculated as Gmean of whole live cells. Each dot represents an individual biological replicate.

(B) Expression of Rab11a and actin in MDA-MB-231 transduced with a control gRNA or gRNA against Rab11a (n = 3, one representative experiment is shown).

(C) Quantification by NTA of EVs released by control or Rab11a-deleted MDA-MB-231 cells.

(D) MACSPlex Exosome analysis on EVs from equal numbers of CTRL or Rab11a-deleted MDA-MB-231 cells developed using a mix of antibodies against tetraspanins (CD9, CD63 and CD81).

(E) Total number of live cells recovered after monocyte exposure to EVs from CTRL or Rab11 gRNA MDA-MB-231. Comparison between groups was performed by two-tailed, Wilcoxon test. P values ≤0.05 were considered significant and are indicated for each comparison. Each individual donor is shown. Results shown represent mean ± SEM.
<figure><img src="image_23.png" /><figcaption>Supplementary Figure 3</figcaption></figure>

Supplementary Figure 3 (related to figure 3). CSF-1 expression on EVs and in breast cancer cell lines and role in monocyte survival

(A) EVs were subjected to immuno-isolation with beads coupled to antibodies against TSPs (CD9, CD63 and CD81) (Pan Exosome Isolation Kit Miltenyi). Bead-associated (Pull-down: PD) EVs and those left behind (flow-through: FT) were analyzed by western blot with specific antibodies for CD63 and CD9. Representative of three independent experiments.

(B) Gating strategy for the imaging flow cytometry analysis of single EVs. MDA-MB-231 EVs were stained with the lipid dye Membright488 with or without the addition of fluorochrome-coupled anti-CD81 antibody (CD81-APC). Washed samples were acquired with the ImageStream-X. Dot plots gated on low SSC membright488+ events were analyzed for CD81. Membright+ CD81+ events were gated for further analysis of CSF-1 on samples stained simultaneously for CD81 and CSF-1. Representative of two independent experiments.
(C) Example images for Membright(+) CD81-APC(+) CSF-1-PE(+) triple positive events. Representative of two independent experiments.

(D) Dot plots following the same gating strategy performed on non-EV containing samples labeled with the same combination of Membright488, CSF-1 and CD81 antibodies.

(E) Quantification of total live macrophages on day 5 of culture of monocytes with MDA-MB-231 EV-R in the presence of blocking antibodies against CSF-1 Receptor (CD115) or GM-CSF Receptor (CD116) molecules. Each individual donor is shown (n = 6). Results shown represent mean ± SEM.

(F) Total number of live cells recovered after monocyte exposure to EVs from CTRL or CSF1 gRNA MDA-MB-231.

(E G) CSF-1 expression in breast cancer cell lines according to the Broad Institute Cancer Cell Line Encyclopedia (CCLE). Cells lines were categorized according to the subtype they have been described to belong to.

(F-H) CSF-1 expression values from CCLE breast cancer cell lines grouped according to cancer subtype.

(G-I) Number of particles released per 10⁶ cells by MDA-MB-231, BT-549 and MCF-7.

(J) Total number of live cells recovered after monocyte exposure to EVs from MDA-MB-231, BT549 or MCF-7 cells.

(K) Total number of live cells recovered after monocyte exposure to EVs from MCF-7 control or overexpressing CSF-1.

Comparison to control group was performed by two-tailed, Wilcoxon test. P values ≤0.05 were considered significant and are indicated for each comparison. Each individual donor is shown. Results shown represent mean ± SEM.
<figure><img src="image_24.png" /><figcaption>Supplementary Figure 4</figcaption></figure>

Supplementary Figure 4 (related to Figure 5). Characterization of Sting-inhibited EV-R-monocytes and STING-ko THP-1 response to EV-R, of EVs from cGAS ko tumor cells and response of THP1.

(A) CD14+ monocytes were incubated with the indicated concentrations of the Sting inhibitor (H-151) or DMSO prior to the treatment with MDA-MB-231 EV-R or rCSF-1. The number of CD163+CD206+ cells was evaluated by FACS on day 5 of macrophage differentiation.

(B) Expression of CD163 (left) and CD206 (right) on macrophages differentiated upon EV-R or rCSF-1 treatment in the presence or not of a Sting inhibitor (H-151).

(C) Number of live cells at day 5 of monocyte culture with EV-R or rCSF-1 in the presence of STING inhibitor.

(D) Expression of STING and gp96 on THP-1 wild-type cells (scr-gRNA) or STING-deleted (STING-gRNA) by CRISPR/Cas9 (n=1).

(E) CXCL9 and CXCL10 secretion was measured by CBA on THP-1 wild-type cells treated for 18 hours with increasing amounts of EV-R from MDA-MB-231 cells (0.25-2 µg of proteins).

(F) THP-1 wild-type control cells or CRISPR/Cas9-STING-deleted THP-1 cells were stimulated for 18 hours with EV-R from MDA-MB-231 cells and secretion of CXCL9 and CXCL10 into the supernatant was evaluated.

(G) Expression of Siglec1 (left) and IRF7 (right) in THP-1 wild-type control cells or CRISPR/Cas9-STING-deleted THP-1 cells stimulated for 18 hours with EV-R from MDA-MB-231 cells or rCSF-1.

(H) Particle count in EV-R from MDA-MB-231-SCR-gRNA and MDA-MB-231-cGAS-gRNA.

(I) CSF-1 levels in CCM or pooled EV-R fractions from MDA-MB-231 deleted for cGAS as indicated. Quantification done on independent EV isolations is shown.

(J) Number of live cells at day 5 of monocyte culture with EV-R from MDA-MB-231-SCR-gRNA and MDA-MB-231-cGAS-gRNA.
(K) THP-1 wild-type cells were stimulated for 18 hours with EV-R from MDA-MB-231-SCR-gRNA or MDA-MB-231-cGAS-gRNA and IRF7 (left) and siglec1 (right) expression was evaluated by flow cytometry.

(L) Secretion of CXCL10 into the supernatant was evaluated on THP-1 treated as described in K.

For (F), (G), (K) and (L), comparison between groups was performed by two-tailed, Wilcoxon test. P values ≤ 0.05 were considered significant and are indicated for each comparison. Each individual donor is shown. Results shown represent mean ± SEM.