Pieter Goossens

Juan Rodriguez-Vita

Anders Etzerodt

Marion Massé

Olivia Rastoin

Victoire Gouirand

Thomas Ulas

Olympia Papantonopoulou

Miranda Van Eck

Nathalie Auphan-Anezin

Marion Masse

Magali Bebien

Christophe Verthuy

Thien Phong

Vu Manh

Martin Turner

Marc Dalod

Joachim L Schultze

Toby Lawrence
email: toby.lawrence@kcl.ac.uk.

Prof Toby Lawrence

Membrane Cholesterol Efflux Drives Tumor-Associated Macrophage Reprogramming and Tumor Progression

Keywords: Tumor-associated macrophages, Ovarian cancer, Cholesterol efflux, Lipid rafts, IL-4 signaling

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

There is now a wealth of clinical and experimental evidence that strongly links tumorassociated macrophages (TAMs) with tumor progression, invasion and metastasis [START_REF] Noy | Tumor-associated macrophages: from mechanisms to therapy[END_REF]. In the vast majority of published studies, increased numbers of TAMs correlate with poor prognosis, but in some cases, specific TAM subsets have been associated with beneficial outcomes (de Vos van [START_REF] De Vos Van Steenwijk | Tumor-infiltrating CD14-positive myeloid cells and CD8-positive T-cells prolong survival in patients with cervical carcinoma[END_REF]. Indeed, macrophages have been shown to posses intrinsic tumoricidal activity and promote the activation of cytotoxic lymphocytes [START_REF] Hagemann | Re-educating" tumor-associated macrophages by targeting NF-kappaB[END_REF], but they rapidly adopt an alternative phenotype within tumors, associated with immune-suppression and trophic functions that support tumor growth [START_REF] Mantovani | Cancer-related inflammation[END_REF]. However, the mechanisms that promote TAM reprogramming in the tumor-microenvironment remain poorly understood.

In mammals, macrophages are found in all tissues after birth and are endowed with trophic functions that contribute to organ development and remodelling [START_REF] Pollard | Trophic macrophages in development and disease[END_REF]. Recent advances in genetic fate-mapping techniques have revealed that the majority of tissue-resident macrophages, at least in steady-state, develop from embryonic precursors and are maintained by local proliferation with little input from hematopoeitc stem cells (HSC) in the bone marrow [START_REF] Schulz | A lineage of myeloid cells independent of Myb and hematopoietic stem cells[END_REF]. Subsequent studies have shown that embryonic macrophages can be gradually replaced by HSC-derived blood monocytes, to varying degrees depending on the specific context [START_REF] Ginhoux | Tissue-Resident Macrophage Ontogeny and Homeostasis[END_REF]. But the functional implications of these distinct developmental origins and certainly their respective contributions to tumor progression remain unclear. In a recent study, both tissue-resident macrophages of embryonic origin and monocyte-derived TAMs were shown to contribute towards tumor growth in a mouse model of pancreatic cancer [START_REF] Zhu | Tissue-Resident Macrophages in Pancreatic Ductal Adenocarcinoma Originate from Embryonic Hematopoiesis and Promote Tumor Progression[END_REF]. The phenotype of tissue-resident macrophages is dictated by the tissue-specific signals in their respective niche [START_REF] Lavin | Tissue-resident macrophage enhancer landscapes are shaped by the local microenvironment[END_REF]. Along these lines, TAMs in various experimental models and human cancers have been shown to express uniques sets of gene patterns including the production of specific chemokines, cytokines and growth factors linked with tumor progression, such as CCL2, TNF, VEGF, basic fibroblast growth factor (bFGF) and matrix metalloproteinases (MMPs) [START_REF] Kratochvill | TNF Counterbalances the Emergence of M2 Tumor Macrophages[END_REF]. Thus, TAMs are reprogrammed towards a functional state that supports tumor growth and immunesuppression and away from inflammatory phenotypes that could be associated with anti-tumor functions. However, the specific mechanisms that drive TAM accumulation and polarization in different tumors remain unclear.

Here we have characterized TAMs in a mouse model of metastatic ovarian cancer. We show that monocyte-derived TAMs gradually replaced resident macrophages in this model and displayed an upregulation of cholesterol metabolism and reverse cholesterol efflux pathways during tumor progression. Further experiments revealed that ovarian cancer cells actively promoted plasma membrane cholesterol efflux from macrophages and the subsequent loss of cholesterol-rich membrane microdomains, or so called "lipid rafts". Increased cholesterol efflux promoted enhanced IL-4 signaling in macrophages while inhibiting IFNγ-induced gene expression. As previously reported, IL-4-induced gene expression in TAMs is associated with tumor-promoting functions, including increased arginine metabolism promoting immunesuppression and trophic functions, supporting invasion and metastasis [START_REF] Denardo | CD4(+) T cells regulate pulmonary metastasis of mammary carcinomas by enhancing protumor properties of macrophages[END_REF].

Whereas, IFNγ induced gene expression in TAMs drives anti-tumor functions. We further demonstrate that IL-4 signaling and cholesterol efflux pathways in TAMs significantly contribute to tumor progression in vivo. Furthermore, genetic deletion of ABC transporters reverts the tumor-promoting functions of TAMs. These studies suggest an important role for membrane-cholesterol efflux in driving IL-4 signaling and tumor-promoting functions of TAMs in ovarian cancer, while rendering them refractory to reprogramming by anti-tumor cytokines.

Therefore, preventing cholesterol efflux in TAMs could represent a novel therapeutic strategy to block their pro-tumor functions and restore anti-tumor immunity.

Results

Origins of TAMs during ID8 tumor development.

High grade serous ovarian cancer (HGSC) is frequently associated with colonisation of the peritoneal cavity by cancer cells [START_REF] George | Ovarian Cancer: The Fallopian Tube as the Site of Origin and Opportunities for Prevention[END_REF]. ID8 cells are spontaneously transformed mouse ovarian surface epithelial cells [START_REF] Urzua | Dysregulation of mitotic machinery genes precedes genome instability during spontaneous pre-malignant transformation of mouse ovarian surface epithelial cells[END_REF], when adoptively transferred by intra-peritoneal (i.p.) injection in syngeneic mice, these cells progressively develop a malignant ascites with tumor nodules throughout the peritoneal cavity [START_REF] Hagemann | Re-educating" tumor-associated macrophages by targeting NF-kappaB[END_REF], which is characteristic of HGSC. The peritoneal cavity is populated by two major subsets of serosal macrophages; large peritoneal macrophages (LPM), which are most abundant, and a minor population of small peritoneal macrophages (SPM) [START_REF] Ghosn | Two physically, functionally, and developmentally distinct peritoneal macrophage subsets[END_REF]. Previous studies have shown that SPM and LPM have distinct developmental origins; SPM develop from blood monocytes which are derived from bone marrow progenitors, whereas LPM are derived from embryonic progenitors and are maintained independently of blood monocytes, retaining proliferative capacity for self-renewal [START_REF] Yona | Fate Mapping Reveals Origins and Dynamics of Monocytes and Tissue Macrophages under Homeostasis[END_REF]. More recent studies have shown that LPM can be progressively replaced by long-lived bone marrow-derived macrophages that maintain self-renewal potential [START_REF] Bain | Long-lived self-renewing bone marrow-derived macrophages displace embryo-derived cells to inhabit adult serous cavities[END_REF]. To monitor the dynamics of peritoneal macrophages (PM) during ID8 tumor growth, we first characterized macrophage subsets by flow cytometry. SPM and LPM can be distinguished by F4/80 and MHCII expression; SPM are MHCII hi F4/80 lo whereas LPM are F4/80 hi MHCII lo (Fig. 1A). LPM represent approximately 80 % of PM in naïve mice, however, after seeding of ID8 cells in the peritoneal cavity, a significant population of F4/80 int MHCII int PM rapidly accumulates (intPM; Fig. 1A). Kinetic analysis of total cell numbers revealed that LPM numbers remain relatively constant throughout tumor progression, while intPM progressively accumulate and eventually become the dominant TAM population (Fig. 1B).

To determine the dynamics of PM subsets during ID8 tumor growth, we performed fatemapping studies with shielded radiation chimera mice. Radiation chimeras can be used to determine the contribution of bone marrow-derived progenitors towards cells in a given tissue.

However, irradiation kills tissue-resident macrophages that then become replaced by monocyte-derived cells, thus to distinguish tissue-resident cells from monocyte-derived macrophages from the bone marrow, it is necessary to protect the tissue from the effects of radiation using lead shielding. To study the origins of PM subsets during ID8 tumor growth, we shielded the abdomen of host C57BL6 CD45.1 congenic mice during irradiation and then adoptively transferred a mixture of bone marrow cells from mice expressing both CD45.1 and CD45.2 (CD45.1/2) and Ccr2 -/-mice, expressing only CD45.2. This allowed the distinction between host (CD45.1) and donor cells (CD45.1/2 or CD45.2), as well as their CCR2dependency, CD45.2 single-positive cells being CCR2-dependent. Due to the low engraftment efficiency of Ccr2 -/-bone marrow cells, Ccr2 -/-donor cells were mixed at a ratio of 4:1 with competitor B6.CD45.1/2 cells. Five weeks after bone marrow engraftment, chimeric mice were injected with ID8 cells to track the contribution of bone marrow-derived cells to PM subsets (Fig. 1C). CD45.1 and CD45.2 expression in TAM subsets was measured by flow cytometry a further 8 weeks after injection of ID8 cells, a total of 13 weeks after adoptive transfer of bone marrow cells, chimerism was normalised to blood monocytes. These experiments revealed that SPM and intPM were derived from CCR2-dependent bone marrow progenitors, with almost 100 % chimerism after 8 weeks of tumor growth (Fig. 1D,E). However, at this time point, LPM only showed approximately 30 % chimerism, implying that LPM are more gradually replaced by bone marrow-derived cells during tumor development. To confirm the CCR2dependency of intPM, we analyzed the accumulation of PM subsets in full CCR2 deficient mice (Ccr2 -/-), as expected, both SPM and intPM were drastically reduced in Ccr2 -/-mice bearing ID8 tumors, whereas CCR2 deficiency had little impact on LPM numbers (Fig. S1).

To confirm the continuous contribution of blood monocytes to SPM and intPM populations throughout tumor growth, we used a fluorescent fate-mapping approach. The chemokine receptor Cx3cr1 is expressed by blood monocytes [START_REF] Geissmann | Blood monocytes consist of two principal subsets with distinct migratory properties[END_REF] and previous studies have demonstrated the fate-mapping of monocyte-derived cells using knock-in mice that express a tamoxifen-inducible Cre-recombinase from the Cx3cr1 locus (Cx3cr1 CreER ), crossed to mice expressing a ubiquitous lox-STOP-lox reporter cassette [START_REF] Yona | Fate Mapping Reveals Origins and Dynamics of Monocytes and Tissue Macrophages under Homeostasis[END_REF].

As expected, we did not detect Cx3cr1 expression in steady-state LPM using the Cx3cr1 egfp/+ reporter mice, however, high levels of Cx3cr1 expression were observed in SPM and intermediated levels in intPM (Fig. S1), reflecting the likely monocyte origins of these cells. We crossed Cx3cr1 CreER mice with Rosa26-lsl-tdRFP reporter mice (Cx3cr1 CreER :R26-tdRFP) and injected these mice with ID8 cells to track monocyte-derived cells during tumor growth. Six weeks after injection of ID8 cells, mice were given a single dose of 4-OHT by oral gavage (p.o.) and RFP expression in TAM subsets was measured by flow cytometry ten days later. These experiments showed strong RFP labelling in SPM and intPM within 10 days of 4-OHT administration, with very little labelling of LPM (Fig. 1F,G). These data clearly demonstrated the contribution of blood monocytes to SPM and intPM during tumor growth, even within this short time frame.

Transcriptional profiling of TAMs

To evaluate the impact of the tumor-microenvironment on PM phenotype, we performed global gene expression analysis using microarrays on bulk PM from naïve mice and at different time points during tumor progression. We isolated naïve F4/80 hi PM and TAMs at 5, 12 and 21 days during ID8 tumor development by flow cytometry (Fig. S2). Total RNA was extracted and samples were analyzed using MoGene 1.0st microarrays. RMA normalised data were filtered and analyzed for variations in gene expression. The heatmap in figure S2B shows the 1000 most variable genes in the dataset. To extract differentially expressed genes (DEGs) between naïve PM and TAMs at the different time points, we used Anova with an adjusted p value and a threshold of 1.5 fold change (FC). We then used Gene Ontology (GO) enrichment analysis to identify pathways affected in TAMs at different time points (Fig. 1H,I). DEGs are represented by edges (green = up; blue = down) and individual GO terms are represented by nodes. GO terms that are similar, as indicated by the intersection of DEGs in a given GO term, are closer to each other. This generates clusters of similar GO terms indicating common biological processes within the cluster. This analysis revealed a major cluster of upregulated genes related to immunity in TAMs after 5 days (Fig. 1H), possibly reflecting a tumoricidal response triggered by resident PM in response to ID8 cells. However, after 21 days, when tumors had become more established, the gene expression profile of TAM more closely resembled the phenotype of naïve PM (Fig. S2). At this later time point, there was an upregulation of distinct gene clusters, including a large cluster of genes related to the innate immune response and tumor necrosis factor (TNF) signaling, in keeping with previous data showing an important role for TNF in this model [START_REF] Charles | The tumor-promoting actions of TNF-alpha involve TNFR1 and IL-17 in ovarian cancer in mice and humans[END_REF], and also a distinctive cluster of genes associated with cholesterol metabolism and efflux (Fig. 1I). To confirm the enrichment of genes related to cholesterol homeostasis, we merged several published genesets [START_REF] Rayner | Antagonism of miR-33 in mice promotes reverse cholesterol transport and regression of atherosclerosis[END_REF] and known hallmarks to generate an extended gene list representing cholesterol homeostasis. This compiled geneset also showed a significant enrichment in TAMs and among the up-regulated genes were known actors in cholesterol metabolism and efflux, including; Abcg1, Ldlr, Pparg, Hmgcs1, Hmgcr, Srebf2 (Fig. S2).

Increased membrane cholesterol efflux in TAMs

Changes in membrane cholesterol content have been shown to dramatically affect macrophage activation in response to pro-inflammatory stimuli, such as bacterial lipopolysaccharide (LPS) [START_REF] Fessler | Intracellular lipid flux and membrane microdomains as organizing principles in inflammatory cell signaling[END_REF]. This is thought, at least in part, to be due to the depletion of cholesterol rich membrane micro-domains, also called lipid rafts, which act as signaling platforms for certain receptors. But membrane cholesterol influences multiple facets of membrane structure and dynamics that can also affect receptor signaling. To confirm the finding that cholesterol efflux pathways were upregulated in TAMs, we sought to measure effects on cholesterol membrane content in TAMs from ID8 tumor bearing mice. Cholesterol rich membrane micro-domains are commonly measured using cholera toxin B (CTB) staining, which binds to ganglioside GM1, the accumulation of which is linked with membrane cholesterol content. We isolated naïve PM and TAMs at 5 and 21 days after injection of ID8 cells, stained the cells with Alexa Fluor 488-conjugated CTB and analyzed them by confocal microscopy. We observed that CTB staining was similar in naïve PM and TAMs isolated at 5 days, but was significantly decreased in TAMs after 21 days of tumor growth (Fig. 2A,B), indicating that the tumor-microenvironment may promote the depletion of cholesterol rich membrane micro-domains in TAMs, in accordance with the upregulation of genes regulating cholesterol efflux in these cells (Fig. 1I). To test if ID8 tumor cells had a direct effect on macrophage cholesterol efflux, we co-cultured ID8 cells with bone marrow-derived macrophages (BMDM) in vitro. After just one hour of co-culture, there was a significant decrease of CTB staining in BMDM (Fig. 2C,D), indicating tumor cells actively promoted the depletion of membrane cholesterol in macrophages. To test if factors secreted by tumor cells were responsible for this effect, we incubated BMDM with conditioned medium obtained from ID8 cell cultures (ID8-CM). This also resulted in a rapid reduction in CTB staining, that was almost equivalent to the effects of methyl-β-cyclodextrin (MCD), which extracts cholesterol from cell membranes [START_REF] Ostrom | Detergent and detergent-free methods to define lipid rafts and caveolae[END_REF] (Fig. 2E,F). Although CTB is commonly used to measure cholesterol rich membrane micro-domains, this is a rather indirect measure of membrane cholesterol. Another method to asses membrane cholesterol content exploits the highly ordered structure of cholesterol-rich membrane microdomains by the use of phasesensitive fluorescent probes such as Laurdan and di-4-ANEPPDHQ [START_REF] Owen | Quantitative imaging of membrane lipid order in cells and organisms[END_REF]. These molecules adapt their emission wavelength based on local membrane order, which is a direct reflection of cholesterol content, independently of membrane-associated proteins. To confirm our findings, we labelled macrophages with di-4-ANEPPDHQ and found a significant decrease of membrane order in the presence of ID8-CM (Fig. 2G,H). These assays confirmed that the reduction in CTB staining observed after ID8-CM treatment, correlated with alterations in membrane order that reflect reduced levels of membrane cholesterol. Furthermore, we measured total cholesterol levels in macrophages cultured in the presence or absence of tumor cell-conditioned medium and observed a significant decrease of total cellular cholesterol (Fig. 2I). Finally, to directly measure cholesterol efflux from macrophages, we loaded BMDM with thymidine ( 3 H)-labelled cholesterol and measured its efflux into the culture media after addition of the apolipoprotein A1 (ApoA1). Membrane cholesterol efflux is mediated by the transfer of cholesterol to lipoproteins through ABC transporters [START_REF] Zhao | Relative roles of various efflux pathways in net cholesterol efflux from macrophage foam cells in atherosclerotic lesions[END_REF], in the case of ApoA1 this occurs through the transporter ABCA1. These assays showed that addition of ID8-CM significantly increased cholesterol efflux from macrophages, which was reversed in BMDM from ABCA1-deficient mice (Abca1 -/-), demonstrating that this was due to an increased efflux of membrane cholesterol (Fig. 2J).

Tumor cell-derived hyaluronic acid (HA) drives cholesterol efflux in macrophages.

The studies described above showed that ID8 cells increased cholesterol efflux from macrophages. This effect could be recapitulated with conditioned medium but not with fixed cells (Fig. 3A), indicating that cholesterol efflux is promoted by a secreted factor. In order to further characterize this factor, we exposed ID8-CM to a series of treatments, including ultracentrifugation, boiling (95 o C for 5 min), repeated freeze/thaw cycles, DNAse and proteinase K, none of which had any impact on the ability of ID8-CM to deplete CTB staining in macrophages (data not shown). However, size fractionation of ID8-CM with cut-offs at 3, 10, 30 or 100 kDa, revealed that this activity was present in a fraction with a molecular weight above 100 kDa (Fig. 3B). Several previous studies have shown that the extracellular matrix (ECM) component hyaluronic acid (HA) can be produced by tumor cells and has been linked with increased tumor progression [START_REF] Chanmee | Hyaluronan: A modulator of the tumor microenvironment[END_REF]. HA also forms high molecular weight oligomers (>100 kDa) with distinct biological activity [START_REF] Gomez-Aristizabal | A Systematic Study of the Effect of Different Molecular Weights of Hyaluronic Acid on Mesenchymal Stromal Cell-Mediated Immunomodulation[END_REF]. Furthermore, receptors for HA are expressed by TAMs, namely CD44 and Lyve-1 [START_REF] Turley | Signaling properties of hyaluronan receptors[END_REF]. To test the hypothesis that HA in ID8-CM contributed to the effects on membrane cholesterol content, we treated ID8-CM with hyaluronidase (HAse) to degrade HA. Indeed, ID8-CM treated with HAse was no longer able to deplete CTB staining in macrophages (Fig. 3C). Conversely, when HA of different molecular weights was added to macrophages in normal culture medium, we observed a reductiion of CTB staining with increasing molecular weight (Fig. 3D). These experiments suggested that high molecular weight HA produced by ID8 cells promotes membrane cholesterol depletion in macrophages. Given that HA is an important component of ECM in many cancers, including EOC [START_REF] Kolapalli | Detection of a specific pattern of hyaluronan oligosaccharides and their binding proteins in human ovarian tumour[END_REF], this suggests HA could affect the phenotype of TAMs through membrane cholesterol depletion.

Cholesterol efflux promotes IL-4 mediated macrophage reprogramming.

Depletion of membrane cholesterol has been shown to profoundly affect macrophage activation in response to pro-inflammatory stimuli [START_REF] Fessler | Intracellular lipid flux and membrane microdomains as organizing principles in inflammatory cell signaling[END_REF], which suggests that cholesterol efflux in TAMs could affect their programming by signals in the tumormicroenvironment. In some instances, TAMs have been shown to exhibit a tumor-promoting phenotype that can be driven by Th2 cytokines such as IL-4 or IL-13, and are skewed away from the pro-inflammatory and immunostimulatory activation state, induced by Th1 cytokines such as IFNγ [START_REF] Denardo | CD4(+) T cells regulate pulmonary metastasis of mammary carcinomas by enhancing protumor properties of macrophages[END_REF]. To test the effects of ID8 cells on macrophage reprogramming, we stimulated BMDM with IL-4 or IFNγ in the presence or absence of ID8-CM and measured IL-4 and IFNγ induced gene expression, respectively. ID8-CM pre-treatment profoundly increased the expression of IL-4 induced genes; Arg1, Retnla, Chi3l3 and Mrc1 (Fig. 4A). In contrast, ID8-CM inhibited the IFNγ induced expression of Nos2 and Il12b (Fig. 4B), as well as other IFNγ-regulated genes including Cxcl9, Cxcl10 and Ciita (Fig. S3), demonstrating that ID8-CM promoted macrophage programming towards an IL-4 induced protumor phenotype. Similar results were obtained after co-culture of ID8 cells with BMDM or with IL-13 treatment, which also signals through the IL4 receptor alpha chain (IL4RA) (Fig. S3).

These effects were restricted to the high molecular weight (>100 kDa) fraction of ID8-CM (Fig. S3) and were not sensitive to freeze/thaw cycles, boiling, ultracentrufugation, DNAse or proteinase K treatment (data not shown).

To evaluate the effects of membrane cholesterol depletion on macrophage reprogramming we used several mechanistically distinct treatments to induce cholesterol efflux, in comparison with ID8-CM; 9-cis-retenoic acid (9cRA) upregulates expression of ABC transporters and thereby induces cholesterol efflux [START_REF] Ricote | Decoding transcriptional programs regulated by PPARs and LXRs in the macrophage: effects on lipid homeostasis, inflammation, and atherosclerosis[END_REF], whereas high-density lipoprotein (HDL) and ApoA1 strip cholesterol directly from the cell membrane [START_REF] Zhao | Relative roles of various efflux pathways in net cholesterol efflux from macrophage foam cells in atherosclerotic lesions[END_REF]. Treatment of BMDM with 9cRA, HDL or ApoA1 resulted in similar levels of reduction in CTB staining as seen upon ID8-CM treatment (Fig. 4C), as well as increased IL-4 induced gene expression, while inhibiting IFNγ induced genes (Fig. 4D). In contrast, the addition of exogenous cholesterol to BMDM, reduced the effects of ID8-CM on IL-4 induced Arg1 and IFNγ induced Nos2 expression (Fig. S3).

These data suggested that membrane cholesterol depletion promotes IL-4 mediated macrophage activation and abrogates IFNγ signalling. To directly test the role of cholesterol efflux in macrophage reprogramming by ID8-CM, we used BMDM from mice with a combined myeloid deficiency in the ABCA1 and ABCG1 reverse cholesterol efflux transporters (Abca1/g1 ∆Lyz2 ). Treatment with ID8-CM or other membrane cholesterol-depleting agents failed to reduce CTB staining in BMDM from Abca1/g1 ∆Lyz2 mice (Fig. 4E), which indeed reversed the increase in IL-4 induced gene expression by ID8-CM and the inhibition of IFNγ induced genes (Fig. 4F), indicating that membrane cholesterol efflux through ABCA1 and/or ABCG1 promoted IL-4 mediated macrophage activation in the presence of ID8-CM.

Tumor-induced macrophage reprogramming is STAT6 and PI3K-dependent.

To further characterize the mechanisms behind increased IL-4 induced gene expression in the presence of ID8-CM and how this may relate to cholesterol efflux, we analyzed IL-4 receptor signaling pathways. First, we observed no increase in the expression levels of the IL-4 receptor (IL4RA) on macrophages treated with ID8-CM (data not shown), but immunofluorescent staining illustrated an increased intracellular clustering of the receptor that suggested endosomal accumulation, which previously has been shown to promote downstream signaling (Kurgonaite et al.) (Fig. S4). We therefore measured activation of signaling pathways downstream of the IL-4 receptor. IL-4 induced gene expression is regulated by JAK-mediated phosphorylation of the STAT6 transcription factor. Treatment of BMDM with ID8-CM increased levels of activated STAT6 (pY-STAT6) in response to IL-4 (Fig. 5A,D; Fig. S4) while reducing the accumulation of phosphorylated STAT1 (pY-STAT1), upon IFNγ activation (Fig. 5B,E; Fig. S4). As expected, IL-4 induced gene expression in the presence of ID8-CM was abolished in BMDM derived from STAT6 deficient mice (Stat6 -/-) (Fig. S4). IL-4 signaling also activates PI3K, which was recently shown to be an important pathway for the tumor-promoting functions of TAM (Kaneda et al., 2016a;[START_REF] Kaneda | PI3Kgamma is a molecular switch that controls immune suppression[END_REF], furthermore, increased PI3K signaling has been shown to promote IL-4 induced gene expression in macrophages [START_REF] Rauh | SHIP represses the generation of alternatively activated macrophages[END_REF].

To assess PI3K activation we measured phosphorylation of the downstream kinase Akt/PKB.

We observed a marked increase in serine 473 phosphorylation of Akt (pS-Akt) in the presence of ID8-CM (Fig. 5C,F; Fig. S4), this correlated with increased accumulation of phosphatidylinositol (3,4,5)-triphosphate (PIP3), the product of PI3K activity, as measured by confocal microscopy (Fig. S4). To determine the contribution of PI3K to IL-4 mediated reprogramming in the presence of ID8-CM, we treated cells with the PI3K inhibitor LY294002.

As expected, LY294002 treatment blocked the increase in pS-Akt by ID8-CM (Fig. 5G) and also abrogated the increase in IL-4 induced Arg1 and Chi3l3 expression (Fig. 5H,I; Fig. S4), indicating that PI3K activity was critical for ID8-CM induced reprogramming. To determine the role of cholesterol efflux in STAT6 and PI3K activation, we again treated macrophages with 9cRA and ApoA1 to deplete membrane cholesterol, both treatments resulted in similar increases in the accumulation of pY-STAT6 and pS-Akt (Fig. 5J,K). Furthermore, macrophages lacking the ABCA1 and ABCG1 cholesterol efflux transporters failed to increase pY-STAT6 and pS-Akt upon treatement with ID8-CM (Fig. 5L,M). In addition, increased pY-STAT6 and pS-Akt accumulation was restricted to the high molecular weight (>100 kDa) fraction of ID8-CM and could be reversed by HAse treatment (Fig. S4), indicating that HA-mediated cholesterol efflux promoted increased STAT6 and Akt activation.

The specific accumulation of pS-Akt in the presence of ID8-CM was intriguing, serine 473 phosphorylation of Akt is mediated by mammalian target for rapamycin complex 2 (mTORC2) [START_REF] Jacinto | SIN1/MIP1 maintains rictor-mTOR complex integrity and regulates Akt phosphorylation and substrate specificity[END_REF], which is activated by PI3K through PIP3 accumulation [START_REF] Liu | PtdIns(3,4,5)P3-Dependent Activation of the mTORC2 Kinase Complex[END_REF].

Interestingly, mTORC2 was also recently shown to promote IL-4 induced macrophage activation in response to metabolic stress [START_REF] Huang | Metabolic Reprogramming Mediated by the mTORC2-IRF4 Signaling Axis Is Essential for Macrophage Alternative Activation[END_REF]. Thus, we hypothesised that ID8-CM induced PIP3 accumulation could activate mTORC2-mediated pS-AKT phosphorylation and increase IL-4 induced gene expression. In the absence of any specific mTORC2 inhibitors, to test the role of the mTORC complex we used rapamycin, which blocks mTORC1, and Torin which blocks both mTORC1 and mTORC2. Rapamycin treatment only partially inhibited ID8-CM induced pS-Akt accumulation in macrophages, however, Torin treatment completely inhibited ID8-CM induced pS-Akt phosphorylation in a dose-dependent manner (Fig. 5N,O), suggesting that mTORC2 activity is required for ID8-CM induced pS-Akt accumulation in macrophages.

In summary, IL-4 induced macrophage activation or reprogramming in response to ID8-CM requires PI3K-mTORC2-Akt activity and is driven by STAT6.

IL-4-induced STAT6 and PI3K signaling in TAMs drives tumor progression in EOC.

To test the relevance of these pathways for TAMs and tumor progression in vivo, we revisited our characterisation of TAMs in ID8 tumors. Our conclusions from the data presented in figure 1, was that monocyte-derived TAMs gradually replaced resident macrophages during tumor progression and that TAMs showed an enrichment for cholesterol efflux pathways (Fig. 1I).

However, these analyzes were performed on bulk TAM populations, including resident PM and monocyte-derived TAMs. To refine our analysis and determine the specific gene expression signature of monocyte-derived cells, we isolated F4/80 lo CCR2 + monocytes (MN), alongside F4/80 hi LPM, which were further divided into Tim4 + and Tim4 -subsets (Fig. S5). Tim4 was previously shown to be a marker for proliferative, self-renewing LPM [START_REF] Rosas | The transcription factor Gata6 links tissue macrophage phenotype and proliferative renewal[END_REF], whereas Tim4 -F4/80 hi cells represent monocyte-derived LPM, which are CCR2-dependent (Fig. 1; Fig. S5). First, we collected these 3 populations from naïve mice and at different time points during tumor progression for microarray analysis. We performed a pairwise comparison between the 3 populations in naïve mice and extracted a specific gene signature for each subset, applying a 1.5 FC threshold and a p-value of 0.05. Using the Minimal method (pairwise[Mean(test)/Mean(ref)]), we identified sets of 553 genes specific for MN, 131 for Tim4 + PM and 84 for Tim4 -PM (Table S1). Given that CCR2 was the highest DEG between Tim4 - and Tim4 + populations, this strongly supported the monocytic origin of Tim4 -cells, in keeping with our previous analysis (Fig. S5). We then used these gene sets to perform enrichment analysis (GSEA) with DEGs from the equivalent 3 subsets in ID8 tumor-bearing mice. This analysis showed a significant down-regulation of the naïve Tim4 + PM gene signature and a strong enrichment of the MN and Tim4 -gene signatures in Tim4 + TAMs (Fig. 6A), supporting our conclusion that the tumor-microenvironment promotes the replacement of resident PM with MN-derived cells that acquire a resident-like phenotype, including expression of Tim4 (Fig. 1; Fig. S5). To determine the specific genes associated with this phenotype, we extracted the leading edges (LEs) for this enrichment, that is the genes most strongly associated with the enrichment of the MN gene signature in Tim4 + TAMs. We identified 173 LEs that were enriched at all time points in Tim4 + TAMs (Fig. 6B; Table S2), which we then used for Ingenuity Pathway Analysis (IPA). The most significant pathway associated with these genes was the IL-4 pathway (Fig. 6B), suggesting that IL-4 in the tumor-microenvironment could be an important upstream regulator for the development of the monocyte-derived TAM phenotype. mice with an IL-4 receptor blocking monoclonal antibody (αIL4ra) and monitored tumor progression. Treatment with αIL4ra significantly reduced ID8 tumor growth in vivo (Fig. 6C), suggesting that IL-4 signaling is an important factor for tumor progression in this model. Furthermore, chimeric mice with hematopoietic deficiency in STAT6 (Stat6 -/-) or PI3K (Pik3cd - /-

), also showed significantly reduced tumor growth (Fig. 6D,E), indicating that both signaling pathways in tumor stromal cells are important factors for tumor progression. To evaluate the impact of these pathways on TAM phenotype in vivo, we sorted bulk TAMs from Pik3cd -/- chimeric mice by flow cytometry and isolated RNA for microarray analysis. Expression of Arg1, Il10, Ccl2 and Stab1, which have previsouly been shown to upregulated in TAMs, were significantly downregulated in macrophages from Pik3cd -/-chimeric mice compared to controls (Fig. S5), suggesting that PI3K activation contributes to the TAM phenotype. To further analyze the impact of PI3K activation on TAMs, we generated a gene set from all DEGs between naïve PM and TAMs from wild-type mice. Subsequent GSEA showed a significant enrichment for genes expressed by naïve PM in Pik3cd -/-cells (Fig. 6F), confirming that PI3K activity contributes to the promotion of the TAM phenotype. In addition, there was no enrichment of genes associated with the IL-4 dependent TAM phenotype (Fig. 6G), described above (Fig. 6B; Table S2). These data Indicated that PI3K is an important regulator of this gene set in TAMs.

Interestingly, using an established gene set for tumoricidal phenotype (GSE26912), which was enriched in naïve PM compared to TAMs, we also observed an enrichment in Pik3cd -/-TAMs compared to wild-type cells, suggesting that these cells retained a more tumoricidal phenotype in the absence of PI3K activation (Fig. S5). Finally, to evaluate the role of cholesterol efflux in TAMs in vivo, we established ID8 tumors in mice with a myeloid-specific deletion of both ABCA1 and ABCG1 (Abca1/g1 ∆Lyz2 ). ID8 tumor progression was significantly impaired in Abca1/g1 ∆Lyz2 mice compared to littermate controls (Fig. 6H). Furthermore, microarray analysis of TAMs sorted from these mice showed a significant downregulation of genes associated with the IL-4 dependent TAM phenotype and a positive enrichment for tumoricidal genes (Fig. 6I; Fig. S5), reflecting the phenotype of PI3K deficient TAMs.

Collectively, these data showed that IL-4 signaling in TAMs plays an important role in tumor progression in this model. Furthermore, the PI3K pathway and increased cholesterol efflux, contribute significantly to the functional polarization of TAMs and tumor progression in vivo.

Discussion

Here we have studied TAMs in a mouse model of EOC, that reflects the peritoneal spread of HGSC. During tumor progression we showed that MN-derived TAMs accumulate and gradually replace resident macrophages in the peritoneal cavity. We then analyzed the global changes in gene expression in TAMs over time using microarrays and used pathway analysis to reveal changes in gene expression linked with different pathways and biological functions. At early time points, TAMs displayed a more pro-inflammatory gene signature, which strongly distinguished them from naïve resident PM. However, in established tumors, TAMs acquired a phenotype more closely resembling resident PM, which suggested a dynamic reprogramming of TAM phenotype during tumor progression.

Among the pathways upregulated in TAMs from established tumors compared to naïve PM was a cluster of genes related to cholesterol metabolism and reverse cholesterol efflux.

Reverse cholesterol efflux in macrophages is regulated by membrane cholesterol efflux transporters, such as ABCA1 and ABCG1. These transporters regulate the levels of cholesterol in the plasma membrane, which has a profound influence on macrophage responses to extracellular stimuli. For example, ABCA1 deficient macrophages accumulate cholesterol in the membrane and are hyperresponsive to pro-inflammatory stimuli, such as bacterial lipopolysaccharide (LPS) [START_REF] Fessler | Intracellular lipid flux and membrane microdomains as organizing principles in inflammatory cell signaling[END_REF]. This is thought to be due to the increase in cholesterol-rich membrane microdomains, also called lipid rafts, which are required to promote TLR4-signaling. However, previous studies have also shown that ABCA1-deficient macrophages are hyporesponsive to other stimuli, including IL-4 and IL-13 [START_REF] Pradel | ATP-binding cassette transporter hallmarks tissue macrophages and modulates cytokine-triggered polarization programs[END_REF]. Interestingly, ABCG1 deficiency in macrophages was shown to increase their proinflammatory phenotype and reduce growth of subcutaneous tumors in mice fed on a high-fat diet [START_REF] Sag | The cholesterol transporter ABCG1 links cholesterol homeostasis and tumour immunity[END_REF], suggesting that cholesterol accumulation in TAMs can abrogate their pro-tumor functions.

Here, we showed that ovarian cancer cells actively promoted membrane cholesterol efflux in macrophages, which was associated with increased IL-4 signaling and inhibition of IFNγinduced gene expression, resulting in transcriptional and functional reprogramming of TAMs.

Depletion of membrane cholesterol in macrophages increased PI3K activity and mTORC2mediated Akt phosphorylation. Both PI3K and mTORC2 have previously been linked with IL-4 mediated macrophage activation in different contexts [START_REF] Huang | Metabolic Reprogramming Mediated by the mTORC2-IRF4 Signaling Axis Is Essential for Macrophage Alternative Activation[END_REF][START_REF] Rauh | SHIP represses the generation of alternatively activated macrophages[END_REF]. Furthermore, PI3K was recently shown to be a critical pathway to maintain the pro-tumor functions of TAMs (Kaneda et al., 2016a;[START_REF] Kaneda | PI3Kgamma is a molecular switch that controls immune suppression[END_REF]. The exact mechanism by which membrane cholesterol regulates PI3K/mTORC2 activation remains to be elucidated.

Perhaps cholesterol-rich membrane microdomains are required to recruit negative regulators of PI3K activity, such as the lipid phosphatase SHIP-1. Previous studies have suggested that SHIP may reside in detergent-resistant membrane fractions [START_REF] Galandrini | SH2containing inositol phosphatase (SHIP-1) transiently translocates to raft domains and modulates CD16-mediated cytotoxicity in human NK cells[END_REF] and SHIP-1 is known to inhibit IL-4 signaling in macrophages [START_REF] Rauh | SHIP represses the generation of alternatively activated macrophages[END_REF].

The distinct metabolic environment of tumors has long been suggested to influence the phenotype of tumor-infiltrating immune cells, rendering them hyporesponsive and contributing to immune-suppression. Cancer cells rely heavily on cholesterol, which they can scavenge from the tumor-microenvironement through upregulation of apolipoproteins and their receptors [START_REF] Guillaumond | Cholesterol uptake disruption, in association with chemotherapy, is a promising combined metabolic therapy for pancreatic adenocarcinoma[END_REF]. This may lead to cholesterol depletion in tumor-stromal cells, and particularly TAM which express high levels of the ABCA1 and ABCG1 efflux transporters. Our in vitro studies suggest HA could be an important factor produced by cancer cells that promotes this process. HA is a major component of the extracellular matrix (ECM) in many human cancers, including ovarian cancer, and in many cases the degree of HA accumulation strongly correlates with poor prognosis [START_REF] Kolapalli | Detection of a specific pattern of hyaluronan oligosaccharides and their binding proteins in human ovarian tumour[END_REF]. Macrophages express at least two distinct receptors for HA; CD44 and Lyve1. Interestingly, CD44 signaling has previously been associated with PI3K activation in TAMs [START_REF] Lenart | Hyaluronan carried by tumor-derived microvesicles induces IL-10 production in classical (CD14(++)CD16(-)) monocytes via PI3K/Akt/mTOR-dependent signalling pathway[END_REF]. Co-incidentally, PI3K also upregulates ABCA1 expression in macrophages [START_REF] Okoro | Akt isoform-dependent regulation of ATP-Binding cassette A1 expression by apolipoprotein E[END_REF], potentially creating a feed-forward loop for enhanced cholesterol efflux and IL-4 mediated reprogramming.

In summary, we describe an important role for membrane cholesterol efflux in the regulation of macrophage activation state in the tumor-microenvironment. Depletion of membrane cholesterol renders macrophages hyperresponsive to pro-tumor signals, such as IL-4, but refractory to activation by the anti-tumor cytokine IFNγ. We propose that cholesterol efflux pathways may represent novel targets to abrogate the pro-tumor functions of TAM while retaining potentially beneficial anti-tumor effects in response to therapy.

Limitations of this study

Despite functional data demonstrating the contribution of IL-4 signaling to tumor progression in this model, IL-4 was not detectable in ascites from tumor-bearing mice, indicating this cytokine is produced at very low levels and consumed rapidly. This illustrates the significance of enhanced sensitivity of TAMs to local concentrations of IL-4, which is increased by several orders of magnitude due to membrane cholesterol depletion. These studies are likely to be relevant to human ovarian cancer, where IL-4 expression has been associated with poor clinical outcome (Candido et al.). The source of IL-4 in this context remains unknown. While other cancer cells, including prostate, breast and bladder, have been shown to express IL-4 [START_REF] Conticello | IL-4 protects tumor cells from anti-CD95 and chemotherapeutic agents via up-regulation of antiapoptotic proteins[END_REF], conditioned medium from ID8 cells alone was not sufficient to activate IL-4 signaling in macrophages. Other potential sources of IL-4 include CD4 + T cells [START_REF] Denardo | CD4(+) T cells regulate pulmonary metastasis of mammary carcinomas by enhancing protumor properties of macrophages[END_REF], eosinophils [START_REF] Kratochvill | TNF Counterbalances the Emergence of M2 Tumor Macrophages[END_REF], innate lymphocytes or macrophages themselves.

The precise mechanism by which the activity of ABC transporters is upregulated in TAMs also remains to be elucidated. Cholesterol efflux was rapidly induced upon exposure to tumor-cell conditioned medium and no increase in Abca1 or Abcg1 mRNA was observed (data not shown), suggesting a post-transcriptional mechanism. However, cholesterol efflux was dependent on PI3K activation, associated with increased Akt serine 473 phosphorylation.

Other studies have shown serine 473 phosphorylation of Akt regulates the translocation of ABC transporters to the plasma membrane [START_REF] Huang | MCP-1 impacts RCT by repressing ABCA1, ABCG1, and SR-BI through PI3K/Akt posttranslational regulation in HepG2 cells[END_REF]. This may offer a mechanistic explanation for increased ABC activity in TAMs. [START_REF] Owen | Quantitative imaging of membrane lipid order in cells and organisms[END_REF]. (I) Total cell cholesterol content was measured in BMDM with and without ID8-CM treatment, using the Amplex Red Cholesterol Assay kit. (J) BMDM from wild-type (WT) or Abca1 -/-mice were loaded with 3 H-labeled cholesterol and subsequently treated or not with ID8-CM in the presence of ApoA1, as an acceptor for cholesterol. 3 H-Cholesterol was measured in the medium as a readout for cholesterol efflux. Graphs are represented as mean ± SEM. and IFNγ induced Nos2 expression in BMDM from Abca1/g1 f/f and Abca1/g1 ∆Lyz2 mice with and without ID8-CM treatment. Graphs are represented as mean ± SEM. See also Figure S3.

Figure 6. IL-4-induced STAT6 and PI3K signaling in TAMs drives tumor progression in vivo.

(A) Generation of specific gene signatures for Tim4 + and Tim4 -F4/80 hi PM and F4/80 lo CCR2 + monocytes (MN) using GeneSign (BubbleGUM), cell-specific signatures were assessed for enrichment using BubbleMap [START_REF] Spinelli | BubbleGUM: automatic extraction of phenotype molecular signatures and comprehensive visualization of multiple Gene Set Enrichment Analyses[END_REF], based on the GSEA algorithm in pairwise comparisons of Tim4 + PM from naïve mice or ID8 tumor-bearing mice at different time points.

STAR Methods

Key Resources

METHOD DETAILS

Cell Culture

Bone marrow derived macrophages (BMDM) were obtained as previously described [START_REF] Hagemann | Re-educating" tumor-associated macrophages by targeting NF-kappaB[END_REF]; briefly, femurs and tibiae from mice aged 8 to 10 weeks were flushed and cells collected by centrifugation at 450 g for 5 min at 4°C. Cells were resuspended in DMEM supplemented with L-glutamine (2 mM), penicillin (100 U/ml)/streptomycin (100 µg/ml) (Gibco), 10 % heat-inactivated FBS and 10 ng/ml recombinant mouse M-CSF (Peprotech) and cultured at a density of 10 6 cells/ml in non-tissue culture treated plastic dishes (BD Pharmingen) at 37°C and 5 % CO2. After 7 days, adherent cells were collected and resuspended in complete DMEM containing 10 ng/ml M-CSF. The ID8-Luc ovarian surface epithelial cell line was kindly provided by Prof. Frances Balkwill (Barts Cancer Institute, London, UK). To obtain ID8 cell-conditioned conditioned medium (ID8-CM); 13.75 x10 6 cells in 25 ml were incubated for 72 hours in a 175 cm 2 flasks in DMEM containing 4% of FCS. Medium was filtered through a .22 µM filter, aliquoted and stored at -80°C.

Immunofluorescence and lipid raft staining

BMDM were grown in Lab-Tek chambered slides (ThermoFisher Scientific) and fixed with 4 % PFA, permeabilized (0.1 % Triton-X100) and blocked in 5 % BSA with 10 mM glycine. The following primary antibodies were used for incubation during 90 minutes at 4°C; anti-pSTAT1, anti-pSTAT6, anti-pSer473-Akt, anti-pThr308-Akt, anti-PIP3 (Cell Signaling) or anti-IL4Rα (Novus biologicals). After washing, anti-rabbit-Alexa488 (Invitrogen) and TO-PRO-3 (ThermoFisher Scientific) were added for 60 minutes. Lipid rafts were stained using the Vybrant Alexa Fluor 488 Lipid Raft Labelling Kit (ThermoFisher Scientific), following manufacturer's instructions. Briefly, BMDM were grown and stimulated in Lab-Tek chambered slides. After washing with serum-free DMEM, they were incubated for 10 minutes with Alexa488-conjugated cholera toxin subunit B (CTB) at 4°C, followed by cross-linking with an anti-CTB antibody for 15 minutes at 4°C. Subsequently, the cells were fixed with 4 % Antigenfix (DiaPath) for 10 minutes on ice and nuclei were stained with TO-PRO-3. The di-4-ANEPPDHQ lipid raft staining protocol was adapted from the one described by Owen et al. [START_REF] Owen | Quantitative imaging of membrane lipid order in cells and organisms[END_REF]. Briefly, culture medium was replaced with fresh, serum-free DMEM containing 2 µl of di-4-ANEPPDHQ (5 µM). Dishes were shaken to ensure good mixing. After 30 min incubation at 37 °C in a humidified 5 % CO2 atmosphere, cells were fixed with 4 % PFA. Fluorescence was measured by confocal microscopy (Zeiss LSM780 or Leica SP5X) and blindly analyzed with FIJI software. The corrected total cell fluorescence (CTCF) was measured for each cell in at least 6 different fields of view per well.

Cholesterol measurement

Total cell cholesterol content was measured in BMDM using the Amplex Red Cholesterol Assay kit (ThermoFisher Scientific), according to the manufacturer's instructions.

Immunoblotting

BMDM were lysed on ice in lysis buffer supplemented with proteinase inhibitor cocktail, PNPP, β-glycerophosphate and DTT. Separation by SDS-PAGE was followed by blotting on PVDF membrane. Blots were blocked with 5 % skimmed milk in TBS-0.05 %Tween20. The following primary antibodies were used; anti-Nos2, anti-Arg1 (Santa Cruz), anti-β-Actin (Sigma), anti-Akt, anti-pSer473-Akt, anti-pTyr701-STAT1, anti-STAT1, anti-pTyr641-STAT6 (Cell Signaling) and anti-STAT6 (Santa Cruz). Primary antibodies were incubated overnight at 4°C and appropriate HRP-conjugated secondary antibodies (DAKO) for 1 hour at room temperature.

Chemoluminescence was detected by Pierce ECL Western Blotting Substrate (Thermo Scientific).

Gene expression analysis

Total cellular RNA was extracted from BMDM using TRIzol and cDNA was synthesised with cDNA Synthesis Kit (Thermo Fisher Sientific) according to the manufacturer's protocol. Gene expression was quantified using sequence specific primers in the presence of SYBR Green PCR Master Mix using an ABI 7900HT thermocycler (Applied Biosystems). Reactions were performed in duplicate or triplicate and Ct-values were normalised to the mean Ct-values of cyclophillin. Relative quantification of gene expression was calculated as 2ΔΔCt to controls.

Primers used for RT-qPCRs are shown as part of the Supplementary data.

Ovarian cancer model

One million ID8 cells were injected intraperitoneally in the different mouse strains using a 27G syringe. Mice were euthanized at the indicated times and peritoneal lavages were collected for cytometric analysis, ex vivo bioluminescence measurement and/or lipid raft staining. Briefly, 9 ml of ice-cold PBS was injected intraperitoneally and after a careful massage to detach all the cells in the cavity, peritoneal fluid was collected through a 23G syringe. Tubes were weighed to determine the recovered lavage volume and the cell density was assessed using a Casy cell counter (Innovatis). Cells were centrifugated and resuspended in 1 ml cold PBS. One million cells from each peritoneal lavage were stained for flow cytometry. 50 µl of the 1 ml cell suspension obtained from peritoneal lavage was used for luciferase activity measurements.

Cells were plated in a white 96-well plate and 50 µl luciferin was added to each well, Luminescence [photons/s] was measured for each well using the Mithras Microplate Reader (Berthold Technologies).

Flow Cytometry

Peritoneal lavage cells underwent a short NH4Cl red blood cell lysis and were incubated at 4°C

for 10 min with the 2.4.G2 antibody to block Fc receptors. The cells were stained with the indicated antibodies for 30 min at 4°C. Dead cells were gated out using SYTOX Blue dead cell stain (Life Technologies). After cell-surface staining, cells were fixed. Analysis was performed using an LSR-II flow cytometer or sorted using an Aria III cell sorter (both BD Biosciences

Figure 1 .

 1 Figure 1. Ontogeny and phenotype of TAMs during ID8 tumor development.(A) Analysis of PM by flow cytometry after intra-peritoneal (i.p.) injection of 10 6 ID8-Luc cells. PM were gated as; live, single cells (FSC-H versus FSC-W), CD45.2 + , Lin -(NK1.1 Ly6G CD5 CD19), CD11b + , CD64 + . LPM were subsequently gated as F4/80 hi MHCII -(blue), intPM as F4/80 int MHCII int (orange) and SPM as F4/80 -MHCII hi (green). (B) Total numbers of LPM, intPM and SPM during tumor growth. (C) Shielded chimeras reconstituted with mixed bone marrow to analyze ontogeny of PM after engraftment with ID8-Luc cells. Host mice (CD45.1) were placed in protective lead shield with only the hind legs exposed, before irradiation with 9 Gy. The following day, mice were reconstituted with a mixture of bone marrow cells from Ccr2 -/- (CD45.2) and CD45.1/2 congenic mice, at a ratio of 4:1. 5 weeks after reconstitution, mice were injected with ID8-Luc cells. A further 8 weeks after tumor inoculation, PM were collected for analysis. (D) Analysis of PM from chimeric mice by flow cytometry; CD45.1 and CD45.2 expression was analyzed on LPM (blue), intPM (orange) and SPM (green), as described above. (E) Proportion of chimerism was calculated relative to blood monocytes. (F,G) Fate mapping of Cx3cr1-expressing monocytes in ID8 tumor-bearing mice; Cx3cr1 CreER :R26-tdRFP mice were inoculated with ID8-Luc cells, after 8 weeks 1 mg tamoxifen was administered by oral gavage and RFP expression was analyzed in PM subsets 10 days later. RFP expression within LPM, intPM and SPM is shown. (H,I) PM were collected from naïve mice and at 5 or 21 days after tumor inoculation by flow cytometry. Total cellular mRNA was extracted and global gene expression profiles analyzed using microarrays. Gene ontology enrichment was perfomed on the differentially expressed genes (DEGs) between naïve PM and TAMs at (H) 5 and (I) 21 days, respectively. Graphs are represented as mean ± SEM. See also Figures S1 and S2.

Figure 2 .

 2 Figure 2. Increased membrane cholesterol efflux in TAMs. (A,B) PM were isolated from naïve mice (Ctrl) or at 5 and 21 days after inoculation with ID8 cells. Cells were seeded in chambered plastic slides and stained with Cholera Toxin B (CTB; green) and TO-PRO-3 (blue). (A) Representative images for all three groups are shown, (B) quantification of corrected total cell fluorescence (CTCF). (C,D) BMDM were co-cultured with ID8 cells for the indicated time points prior to CTB staining, (C) representative images for BMDM alone (Ctrl) and 3 hours after ID8 co-culture and (D) quantification of CTCF. (E-H) BMDM were incubated with ID8-CM overnight, or Methyl-β-cyclodextrin for 30 min, prior to CTB staining or di-4-ANEPPDHQ staining; (E) representative images for CTB staining in each condition and (F) quantification of CTCF. (G) Representative images of di-4-ANEPPDHQ staining and (H) quantification of relative changes in GP values[START_REF] Owen | Quantitative imaging of membrane lipid order in cells and organisms[END_REF]. (I) Total

Figure 3 .

 3 Figure 3. Tumor cell-derived hyaluronic acid (HA) oligomers deplete lipid rafts in macrophages. (A) BMDM were co-cultured with live or paraformaldehyde-treated (fixed) ID8 cells, prior to CTB staining, quantification of CTCF is shown. (B) High and low molecular weight fractions of ID8-CM were prepared using Centricon filters with 100 kDa pores, each fraction was compared with unfractionated ID8-CM for effects on CTB staining. (C) BMDM were treated with ID8-CM with and without hyaluronidase (HAse) treatement prior to CTB staining and quantification. (D) BMDM were incubated with HA oligomers of increasing molecular weights before CTB staining and quantification, ID8-CM was used as a positive control. Graphs are represented as mean ± SEM.

Figure 4 .

 4 Figure 4. Cholesterol efflux promotes IL-4 mediated macrophage reprogramming. (A,B) BMDM were treated with or without ID8-CM before stimulation with increasing concentrations of IL-4 or IFNγ for 8 hours. (A) Quantitative PCR (qPCR) analysis of IL-4 induced gene expression; Arg1, Chi3l3, Mrc1, Retnla and (B) IFNγ-induced expression of Nos2 and Il12b. (C) BMDM were treated with different cholesterol depleting agents; 9-cis-retenoic acid (9cRA), high-density lipoprotein (HDL) or apolipoprotein A1 (ApoA1), as well as ID8-CM; lipid raft density was subsequently measured by CTB staining, quantification of CTCF is shown. (D) IL-4 (20 ng/ml) induced Arg1 and IFNγ (20 ng/ml) induced Nos2 expression in

Figure 5 .

 5 Figure 5. Tumor-induced reprogramming is STAT6-and PI3K-dependent. (A-F) BMDM were treated with or without ID8-CM overnight before stimulation with either IL-4 or IFNγ for 20 min. Cells were then fixed and stained for p-STAT6, p-STAT1 or p-Akt and analyzed by confocal microscopy; representative micrographs for (A) p-STAT6, (B) p-STAT1 and (C) p-Akt staining are shown (green), nuclei are counterstained with TO-PRO-3 (blue). (D-F) Quantification of CTCF for (D) p-STAT6, (E) p-STAT1 and (F) p-Akt (NS -non stimulated). (G-I) BMDM were incubated with or without ID8-CM in the presence or absence of the PI3K inhibitor LY294002 (1.25 µM); (G) Quantification of p-Akt staining by confocal microscopy and (H-I) qPCR analysis of IL-4-induced Arg1 and Chi3l3 expression. (J-K) BMDM were incubated overnight with ID8-CM, 9cRA, HDL or ApoA1 before stimulation with IL-4 for 20 min; quantification of (J) p-STAT6 and (K) p-Akt by confocal microscopy. (L-M) BMDM from Abca1/g1 f/f and Abca1/g1 ∆Lyz2 mice were treated with ID8-CM before stimulation with IL-4 and quantification of (L) p-STAT6 and (M) p-Akt by confocal micrscopy. (N-O) BMDM treated with ID8-CM in the presence or absence of Rapamycin (Rapa) or Torin at the indicated concentrations; (N) quantification of p-Akt by confocal micrscopy and (O) western blot analysis of Ser473 and Thr308 Akt phosphorylation (pAkt(Ser) and pAkt(Thr), respectively) in Rapamycin (R) and Torin (T) treated BMDM with and without ID8-CM treatment. Graphs are represented as mean ± SEM. See also Figure S4.

  The bubble area is proportional to the absolute value of the normalised enrichment score (NES). The color intensity indicates the false-discovery rate (FDR), modified for multiple testing. The size and intensity of color increases with the enrichment of the gene signature from the matching cell population; the Tim4 + gene signature is enriched in naïve cells (red), whereas the Tim4 -and MN gene signatures are enriched in TAMs (blue). (B) Leading edges (LEs) of the MN gene signature enrichment at different time points (highlighted by colored boxes) were extracted and plotted in a Venn diagram. Ingenuity Pathway Analysis (IPA) was performed on the 173 common LEs, showing IL4 as the top upstream regulator. (C) ID8-Luc cells were injected i.p. and mice treated with either IL4Rα blocking antibody (anti-IL4Rα) or an isotype control antbody (Iso-ctrl) after 2 weeks; tumor growth was assessed at 4 weeks by ex vivo luciferase assay on peritoneal cells. (D-E) Cohorts of chimeric mice receiving either wildtype (WT), (D) Stat6 -/-or (E) Pik3cd -/-bone marrow cells were injected with ID8-Luc cells and tumor growth assessed after 6 weeks. (F,G) TAMs were isolated from Pik3cd -/-chimeric mice and WT controls after 6 weeks of tumor growth by flow cytometry. Microarray analysis was performed to assess geneset enrichment using GSEA. (F) Positive enrichment of the naïve PM gene signature in Pik3cd -/-TAMs compared to WT cells and (G) negative enrichment of the IL-4 pathway signature of TAMs (from B) in Pik3cd -/-cells. ES plots are shown on the left and the 25 most enriched genes on the right. NES, normalised enrichment score; FDR, false discovery rate. (H) Abca1/g1 f/f and Abca1/g1 ∆Lyz2 mice were injected with ID8-Luc cells and tumor growth assessed after 6 weeks. (I) GSEA with TAMs isolated from Abca1/g1 f/f and Abca1/g1 ∆Lyz2 mice showing negative enrichment of the TAM-associated IL4 pathway in Abca1/g1 ∆Lyz2 mice. Graphs are represented as mean ± SEM. See also Figure S5.

  ) and data analysis was conducted with the FlowJo cytometric analytical software (Tree Star). Anti-CD11b (M1/70), anti-CD44 (IM7), anti-CD45.1 (A20), anti-CD45.2 (104), NK1.1, Ly6G, anti-CD5 (53-7.3), anti-CD19 (1D3), anti-CD64, anti-Ly6C (AL-21), anti-F4/80 and anti-MHCII (M5/114) were purchased from BD Biosciences, eBioscience, BioLegend,

Table

  leukocytes was assessed by flow cytometry. All mice were housed under specific pathogen-free conditions at a temperature of 21 o C with water and food ad libitum, and animal experimentation was conducted in strict accordance with good animal practice as defined by the French animal welfare bodies relative to European Convention (EEC Directive 86/609) and approved by the Direction Départmentale des Services Vétérinaires des Bouches du Rhônes. All the mice used were female, did not have impaired immunity and were aged between 8 and 12 weeks and showed no noticeable signs of sickness or discomfort at the onset of the experiments.

	anti-CD45.1 (A20)	BD Biosciences	553775
	REAGENT or RESOURCE Antibodies anti-Nos2 (M-19) anti-Arg1 (N-20) HRP-conjugated anti-Rabbit immunoglobulins HRP-conjugated anti-Mouse immunoglobulins anti-NK1.1 (PK136) anti-Ly6G (1A8) anti-CD5 (53-7.3) anti-CD19 (1D3) anti-CD64 (X54-5/7.1 anti-Ly6C (AL-21) anti-MHCII (M5/114) anti-F4/80 (BM8) anti-Lyve-1 (ALY7) anti-rabbit-Alexa488 Chemicals, Peptides, and Recombinant Proteins LY294002 Rapamycin Hyaluronic acid Hyaluronidase Torin Methyl-β-cyclodextrin High-density lipoprotein 9-cis-retenoic acid Cholesterol-methyl-β-cyclodextrin Proteinase inhibitor cocktail Xylazine PNPP β-glycerophosphate DTT Apolipoprotein A1 Recombinant mouse IL4 Recombinant mouse IFNγ Recombinant mouse M-CSF Recombinant mouse IL13 Vybrant Alexa Fluor 488 Lipid Raft Labelling Kit TRIzol di-4-ANEPPDHQ TO-PRO-3 SYBR Green PCR Master Mix IL4Rα neutralizing antibody Critical Commercial Assays Superscript IV Reverse Transcriptase Amplex Red Cholesterol Assay kit Mice C57Bl/6 mice were obtained from Charles River. All transgenic mouse strains were SOURCE IDENTIFIER Santa Cruz sc-650 Santa Cruz sc-18351 DAKO P044801-2 DAKO P026002-2 BioLegend 108724 BD Biosciences 560600 BD Biosciences 563194 BD Biosciences 565076 BioLegend 139311 BD Biosciences 553104 eBioscience 56-5321-82 BioLegend 123141 eBioscience 53-0443-82 Invitrogen A-10040 R&D Systems 1130 Merck 553211 Lifecore Biomedical HA15M-1 Sigma H3506 Sigma 475991 Sigma C4555 Sigma L8039 Sigma R4643 Sigma C4951 Sigma P8340 Sigma 23076-35-9 Sigma 333338-18-4 Sigma G9422 Sigma 43819 Sigma A0722 Peprotech 214-14 Peprotech 315-05 Peprotech 315-02 Peprotech 210-13 ThermoFisher Scientific V34403 ThermoFisher Scientific 15596018 ThermoFisher Scientific D36802 ThermoFisher Scientific T3605 ThermoFisher Scientific 4312704 BD Biosciences 552508 ThermoFisher Scientific 18090050 ThermoFisher Scientific backcrossed to a C57Bl/6 background. Abca1 tm1Jp Abcg1 tm1Tall (Abca1/g1 f/f ) and Lyz2 tm1(cre)Ifo (Lyz2 Cre ) mice were obtained from Jackson Laboratories. Stat6 -/-mice were kindly donated by Dr. Bernard Malissen (CIML, Marseille, FR), Abca1 -/-mice by Prof. Miranda van Eck (Leiden University, NL) and Pik3cd -/-mice by Prof. Martin Turner (Babraham Institute, Cambridge, UK). Generation of shielded chimeras was performed as previously described (Scott et al., 2016); briefly, CD45.1 congenic mice were anaesthetized with Ketamine (150 mg/kg) and Xylazine (10 mg/kg) and placed in 6 mm thick lead cylinders, exposing only the hind legs. With the peritoneal cavity protected, mice were irradiated with 9 Gy and reconstituted with 10 7 bone marrow cells from Ccr2 -/-(CD45.2) and CD45.1/2 mice, at a ratio of 4:1. After 5 weeks, A12216 EXPERIMENTAL MODEL DETAILS chimerism of blood
	anti-β-Actin (AC-74)	Sigma	A5316
	anti-Akt (40D4)	Cell Signaling	2920
	anti-pSer473-Akt (D9E)	Cell Signaling	4060
	anti-pThr308-Akt (D25E6)	Cell Signaling	13038
	anti-STAT1	Cell Signaling	9172
	anti-pTyr701-STAT1	Cell Signaling	9171
	anti-STAT6 (M-20)	Santa Cruz	sc-981
	anti-pTyr641-STAT6	Cell Signaling	9361
	anti-PIP3	Invitrogen	A-21328
	Anti-CD124	Novus Biologicals	NBP1-00884
	anti-CD11b (M1/70)	BD Biosciences,	563553

Acknowledgements

We thank Bernard Malissen (CIML, FR) for Stat6 -/-mice. These studies were supported by grants to TL from: L'Agence Nationale de la Recherche (ANR); ANR-09-MIEN-029-01, ANR-10-BLAN-1302-01 and European Research Council; FP7/2007-2013 Grant agreement number 260753, and institutional funding from INSERM, CNRS and Aix-Marseille-Université. JRV was funded by Marie Curie actions IEF (No.234823). PG was funded by the French Ligue Nationale contre le Cancer (LNCC). AE was funded by the Novo Nordisk Foundation (NNF14OC0008781). Microscopy facilities are supported by ANR-10-INBS-04-01 France Bio Imaging. JLS is a member of the Excellence Cluster ImmunoSensation. The research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme FP7/2077-2013 under REA grant agreement no. 317445 to JLS.

Deposited Data GSE126079 This paper https://www.ncbi. nlm.nih.gov/geo/q uery/acc.cgi?acc =GSE126079 GSE126080 This paper https://www.ncbi. nlm.nih.gov/geo/q uery/acc.cgi?acc =GSE126080 GSE126098 This paper https://www.ncbi. nlm.nih.gov/geo/q uery/acc.cgi?acc =GSE126098

DATA AND SOFTWARE AVAILABILITY

The accession numbers for the microarray data reported in this paper are: GSE126079, GSE126080, GSE126098 and GSE126378.

Author contributions

PG, JRV, AE and TL designed the experiments. PG, JRV, AE performed the experiments with help from OR, VG, CV, MB, NAA. Bioinformatics analysis was performed by MM, TPVM, MD, OP, TU and JLS. MVE performed cholesterol efflux assays. MT provided Pik3cd -/-mice. PG, JRV, AE and TL wrote the manuscript.

Declaration of Interests

The authors declare no competing interests.

CONTACT FOR REAGENT AND RESOURCE SHARING

Further information and requests for resources and reagents should be directed to and will be fulfilled by Toby Lawrence (toby.lawrence@kcl.ac.uk).

Microarray Analysis

RNA samples were hybridized on Affymetrix Mouse 430 2.0 or MoGene 1.0 st chips. Samples were processed as follows: The biotinylated cRNAs were prepared according to a double amplification protocol using MessageAmp™ II aRNA Amplification Kit (Ambion). The images of the chips were generated with Affymetrix software AGCC version 3.2. The expression data was then extracted with the Affymetrix Expression Console version 1.1 software using the RMA (log2 scale) and MAS5 (linear scale) algorithms. Gene Set Enrichment Analysis (GSEA, Broad Institute) [START_REF] Subramanian | Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles[END_REF] was used to examine differentially expressed genes (DEGs). The output of GSEA is an enrichment plot (ES), a normalized enrichment score (NES)

which accounts for the size of the gene set being tested, a p-value, and an estimated False Discovery rate (FDR). We computed P values using 1,000 permutations for each gene set and corrected them with the false-discovery rate (FDR) method. When several probe sets were present for a gene, the mean of the probe set was used. Cell-specific gene sets were generated by performing pairwise comparisons between DEGs from different populations, applying a 1.5 FC threshold and a p value of 0.05, using the Minimal (pairwise[Mean(test)/Mean(ref)]) method. Sample correlation analysis was performed based on Pearson's correlation coefficients using BioLayout Express3D [START_REF] Theocharidis | Network visualization and analysis of gene expression data using BioLayout Express(3D)[END_REF].

GO enrichment analysis was applied using the Cytoscape plug-in BiNGO (v2.44) [START_REF] Maere | BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks[END_REF] with FDR q-value threshold of 0.05 as default. The Cytoscape plugins Enrichment Map (v1.1) [START_REF] Merico | Enrichment map: a network-based method for gene-set enrichment visualization and interpretation[END_REF] and Word Cloud [START_REF] Oesper | WordCloud: a Cytoscape plugin to create a visual semantic summary of networks[END_REF] were used to visualize the GO networks. Accession numbers for datasets are; GSE126079, GSE126080, GSE126098.

QUANTIFICATION AND STATISTICAL ANALYSIS

Graphs were made and statistical analysis was performed using Prism software (Graphpad).

All quantitative data are presented as mean ± SEM. The statistical parameters (n, mean, SEM) can be found within the figure legends. The t-test was used to define differences between 2 datasets. To define differences between 3 or 4 datasets, One-way Analysis of Variance (ANOVA) was used with a Bonferroni multiple comparison post-test. The criterion for significance was set at P<0.05. No statistical method was used to determine whether the data met assumptions of the statistical approach.

Iso-ctrl anti-IL4Rα


Pablo Carpio

Lech Pawlowski

Bernard Pateyron

Lech Pawłowski

Numerical investigation of influence of precursors on transport properties of the jets used in solution precursor plasma spraying

Keywords: Transport properties, solution precursors, plasma spraying

niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

ABSTRACT

The solution precursor plasma spraying is a modification of the conventional plasma spraying technique where the feedstock is a liquid precursor instead of a powder. The phenomena which occurs in both techniques are different since the feedstock is liquid and consequently, the jet fragmentation, the solvent evaporation and the chemical reaction or pyrolysis must occurs before the solid melting and impact onto the substrate.

The evaporation of the precursor changes the chemical composition of the plasma plume, hence it implies an important modification in the thermodynamic properties. In the present study, the influence of the solution precursor ion these properties, concretely the thermal conductivity and dynamic viscosity of the plasma plume, has been addressed. Then, the ability of heating factor of the plasma plume was estimated and different effects of the precursor on the mentioned transport properties were evaluated.

The effect of the type of precursor, the feedstock flow rate and the solution concentration has been evaluated in the present work. Concretely, transport properties of the plasma plume, as thermal conductivity, dynamic viscosity or the ability of heating factor has been estimated. It is concluded that all of these variables affects slightly the viscosity but considerably in the thermal conductivity and the ability of heating factor.

1.

Introduction

The solution precursor plasma spraying (SPPS) is an emerging technique enabling manufacturing of nanostructured coatings. It is a modification of the conventional atmospheric plasma spraying (APS) where the feedstock is injected inside a plasma plume and the material is melted and accelerated up to the impacting onto the substrate.

Studies have been performed employing SPPS for producing materials intended for desired application such as thermal barrier coatings [START_REF] Gell | Thermal barrier coatings made by the solution precursor plasma spray process[END_REF][START_REF] Joulia | Comparing the deposition mechanisms in suspension plasma spray (SPS) and solution precursor plasma spray (SPPS) deposition of yttria-stabilised zirconia (YSZ)[END_REF], gas sensors [START_REF] Zhang | Microstructure and gas sensing properties of solution precursor plasma-sprayed zinc oxide coatings[END_REF][START_REF] Chien | Rapid and continuous deposition of porous nanocrystalline SnO2coating with interpenetrating pores for gas sensor applications[END_REF], biomaterials [START_REF] Candidato | Development of high purity hydroxyapatite coatings by solution precursor plasma spray process[END_REF][START_REF] Xiao | Bioactive glass-ceramic coatings synthesized by the liquid precursor plasma spraying process[END_REF], etc. SPPS coatings display improved properties with respect to their APS counterparts because of the fine microstructure characteristic in this kind of coatings.

The differences between APS and SPPS technique is based on the feedstock is a solution precursor instead of a powder; therefore, the process changes considerably. On one hand, the liquid nature of the feedstocks implies the injection process is changed and a liquid jet is injected which must be fragmented and the solvent must be evaporated before the solid melting. On the other hand, the feedstock consists in of a precursor, which whose composition is transformed inside the plasma plume. It means a chemical reaction or pyrolysis occurs and depending on the kinetics and the heating transfer, the phenomenon changes and it affect in the final coating [START_REF] Pawłowski | Application of solution precursor spray techniques to obtain ceramic films and coatings[END_REF][START_REF] Jordan | The Solution Precursor Plasma Spray (SPPS) Process: A Review with Energy Considerations[END_REF][START_REF] Killinger | Review of new developments in suspension and solution precursor thermal spray processes[END_REF].

The microstructure and properties of the coating depends on the starting feedstocks as well as the process deposition process [START_REF] Chen | The solution precursor plasma spray coatings: Influence of solvent type[END_REF][START_REF] Muoto | Identification of desirable precursor properties for solution precursor plasma spray[END_REF][START_REF] Ramachandran | Multiobjective optimization of atmospheric plasma spray process parameters to deposit yttria-stabilized zirconia coatings using response surface methodology[END_REF]. One of the keys in the process is the heat transfer between the material and the plasma plume, it means that both material and plasma plume properties are affected in this step. Concretely, the plasma plume characteristics which are related with the heating and momentum transfer, called transport properties, are the thermal conductivity and the dynamic viscosity [START_REF] Marchand | Liquid precursor plasma spraying: Modeling the interactions between the transient plasma jet and the droplets[END_REF][START_REF] Chen | Heat and Momentum Transfer between Thermal Plasma and Suspended Particles for different Knudsen Numbers[END_REF][START_REF] Xiong | Threedimensional simulation of plasma spray: Effects of carrier gas flow and particle injection on plasma jet and entrained particle behavior[END_REF].

They depends basically on the chemical composition of the plasma plume but the environment also affects. For example, vapors generated during the process varyies the chemical composition of the plume; therefore, the transport properties are modified. This is the case of the SPPS process where the solvent and the sub-products of the precursor decomposition become part of the plume.

In spite of fact the that the SPPS technique is being studied since 2001, more studies to know the technique are necessary. Several works have dealt with the development and evaluation of SPPS coatings but the examination on of the thermo-physical changes inside the plasma plume has been limited. Experimental examination of these phenomena is difficult because of the high temperature of the plasma jet and rapidity of the reaction. In this way, some numerical modeling works on the transformation of droplets in SPPS haves been reported [START_REF] Hu | Modeling of Solution Droplet Evolution and Particle Morphologies in Solution Plasma Spraying[END_REF][START_REF] Saha | Surface & Coatings Technology Thermo-physical processes in cerium nitrate precursor droplets injected into high temperature plasma[END_REF]. However, the analysis of thermodynamic properties must be also be considered. Previous researches have addressed the change in the transport properties experimented in the plasma plume when the feedstock is a suspension instead of a powder in the case of suspension plasma spraying [START_REF] Pateyron | Modeling of phenomena occurring in plasma jet during suspension spraying of hydroxyapatite coatings[END_REF][START_REF] Pateyron | Surface & Coatings Technology In fl uence of water and ethanol on transport properties of the jets used in suspension plasma spraying[END_REF].

Hence, the aim of the present study is the evaluation of the transport properties injecting a solution precursor. Besides, the influence of the type of precursor and its concentration, as well as the effect of the feedstock flow rate, is also analyzed. This study was focused ion precursors commonly used to develop zirconia coatings since this material is important owing to its applications as thermal barrier or solid oxide fuel cell's electrolyte [START_REF] Gell | Thermal barrier coatings made by the solution precursor plasma spray process[END_REF][START_REF] Joulia | Comparing the deposition mechanisms in suspension plasma spray (SPS) and solution precursor plasma spray (SPPS) deposition of yttria-stabilised zirconia (YSZ)[END_REF][START_REF] Wang | Solution precursor plasma spray of nickel-yittia stabilized zirconia anodes for solid oxide fuel cell application[END_REF]. Nevertheless, the obtained conclusions can be translated to any kind of coating developed by SPPS.

Methodology

Feedstocks and spray parameters

The feedstocks considered in the present work consisted of ZrO2 precursors. Concretely, three of the most used precursors (one organic and two inorganics ones) were selected to be evaluated for the evaluation. Moreover, the effect of the solution molarity as well as the feedstock flow rate was examined. The wWater was taken as diluting agent although ethanol or other agents can be considered. It is important because it affects considerably the thermal transport properties, as it was demonstrated in a previous the work [START_REF] Pateyron | Surface & Coatings Technology In fl uence of water and ethanol on transport properties of the jets used in suspension plasma spraying[END_REF]. Table 1 displays the kind of precursors as well as the molarity and flow rate values contemplated in the thermal transport estimations. These value range The range of these values and the precursors were taken from previous experimental works about SPPS coatings [START_REF] Joulia | Comparing the deposition mechanisms in suspension plasma spray (SPS) and solution precursor plasma spray (SPPS) deposition of yttria-stabilised zirconia (YSZ)[END_REF][START_REF] Candidato | Development of high purity hydroxyapatite coatings by solution precursor plasma spray process[END_REF][START_REF] Wang | Optimization of solution precursor plasma spray process by statistical design of experiment[END_REF][START_REF] Joshi | Hybrid plasma-sprayed thermal barrier coatings using powder and solution precursor feedstock[END_REF].

The plasma spray parameters remained constant because their optimization was not the objective of this study. Argon and hydrogen wereas selected as primary and secondary plasmaogen gases and their flow rates wereas 45 and 5 slpm respectively. A monocathode nozzle with a diameter of 9 mm was considered and the electrical power was 40 kW. All of these parameters, like feedstock conditions, were taken from our previous works [START_REF] Candidato | Development of high purity hydroxyapatite coatings by solution precursor plasma spray process[END_REF]. The molar fraction of precursors and working gas wereas calculated in order to estimate the plasma plume properties.

Estimation of transport properties

The transport properties described the fluxes such as mass, electric charges and thermal energy which enable to prevent predict the gas system. The transport properties related to momentum and heat transfer are the dynamic viscosity and the thermal conductivity respectively. Dynamic viscosity ( ), [Pa⋅s] or [kg/(m⋅s)], is a coefficient of proportionality between the friction force ( ) and its consequent gradient of gas velocity ( , ):

= , (1)
Likewise, thermal conductivity ( ), [W•m -1 •K -1 ], is the coefficient of proportionality between the heat flux ( ) and the gradient in temperature ( ):

= (2)
The transport properties can be guessed from the Boltzmann equation in the Chapman-Enskog approach described elsewhere [START_REF] Mason | Transport coefficients of ionized gases[END_REF]. The plasma plume characteristics are strongly related to the chemical composition. The different chemical species, both neutral (as Ar, H2…) and ionic (as Ar + , H + , e -…), inside the plasma plume depends on temperature which results from the balance between the electrical energy dissipated and the heat losses that occur in the plasma plume.

The guesses of chemical composition and transport properties at different temperatures were carried out with the use of T&TWinner software which is feed by a huge database of chemical species. This software established the equilibrium onto minimization of Gibbs's free energy of Gibbs and Chapman-Enskog approach [24].

is established onto minimization of Gibbs's free energy of Gibbs [START_REF] White | Chemical equilibrium in complex mixtures[END_REF] and Chapman-Enskog approach [24] with the use of the database.

Ability of heating factor

The heat transfer from plasma plume to a particle is governed by the convention heating of the plasma around the particle and the conduction heating inside the particle, supposing that the radiation heating by the plasma and radiation cooling of particles can be neglected [START_REF] Pawlowski | The Science and Engineering of Thermal Spray Coating[END_REF]. In this case, the heat transfer equation has a form:

ℎ - = (3)
where

dp -particle diameter [m], h -heat transport coefficient [W.m -2 K -1 ],
Tg and Tptemperature of plasma and particle respectively [K], Cp -specific heat of particle, [J•kg - 1 •K -1 ] and t -time [s] [START_REF] Pawlowski | The Science and Engineering of Thermal Spray Coating[END_REF].

Assuming that the energy-transfer mechanism is purely conductive, the length of the trajectory of all particles is constant and equal to L, the plasma gas velocity is constant and the relative movement of particles correspond to Stokes regime, the integration of the eq. ( 3) leads to the following expression: One approach assumed in the integration of the eq. ( 3) is that the transport properties of the gas in at the interface solid particle-plasma plume are averaged between the temperature of the gas (Tg) and the temperature of the particle surface (Tp). Therefore, the averaged thermal conductivity and average viscosity, can be calculated form from the following expression:

!" = # $ % 〈' 〉 % 〈) 〉 = + , % -% . = /0 (4) in which L is length of high temperature zone of plasma jet [m], 〈 〉 -average thermal conductivity [W.kg -1 •K -1 ], 〈 〉 -dynamic viscosity [kg.m -1 •s -1 ], 1 -particle velocity [m.s -1 ], " 2 -
〈 〉 = $ 4 5 6d (5)
〈 〉 = 1 - 8 5 6d
The AHF results an interesting factor to estimate the possibility of obtaining dense coatings [START_REF] Pateyron | Surface & Coatings Technology In fl uence of water and ethanol on transport properties of the jets used in suspension plasma spraying[END_REF][START_REF] Pawlowski | The Science and Engineering of Thermal Spray Coating[END_REF]. Thus, its has been considered in the present study but the final calculations were modified to only take the transport coefficients and is expressed as:

!" 29-= $ : ;+<• # = 〈' 〉 〈) 〉 % (6)

Results and discussion

Study of plasma plume composition

Prior to studingy the transport properties, the composition of the plasma plume at different temperatures is analyzed in order to explain later the motives of the properties changes. In the calculation, it was assumed a flow rate of plasma working gases Ar + H2 equal to 45 + 5 slpm, a solution feed rate of 50 mL/min and a solution concentration of 2 mol/L, values token from previous experimental works [START_REF] Joshi | Hybrid plasma-sprayed thermal barrier coatings using powder and solution precursor feedstock[END_REF][START_REF] Kozerski | Preliminary study on suspension plasma sprayed ZrO 2 + 8 wt .% Y 2 O 3 coatings[END_REF].

Fig. 1 shows the plasma plume composition at different temperatures using an inorganic precursor (zirconyl chloride) and an organic precursor (zirconium acetate). The precursor decomposition to zirconia and the secondary compound, hydrogen chloride (HCl) or methane (CH4), occurs at low temperatures. Nevertheless, the molar ration of these compounds is poorly significant compared to the initial working gases or the steam. It is important to note that the water concentration depends on the molarity but also on the precursor compound since solutions of big molecules with high mole number (as zirconium acetate with M=327.2 g/mol) needs less amount of water to obtain the same solution molarity.

The water decomposition in atomic hydrogen and oxygen begins at about 3000K, as it is shown in eq. 7:

" > → " @ + >" $ → 2" + >

These atomic species, concretely atomic hydrogen, really are excited (its kinetic energy is really high) therefore, increase the mobility, i.e. the thermal conductivity, inside the plasma plume [START_REF] Rat | Treatment of non-equilibrium phenomena in thermal plasma flows[END_REF]. High hydrogen ratio on the plasma working gases or high amount of water into the solution feedstock increase the plasma thermal conductivity.

In the case of organic precursors, an oxidation occurs at high temperatures (around 6000 K), as it is described in eq. 8 [START_REF] Pateyron | Chemical and transport properties of carbonoxygen-hydrogen plasmas in isochoric conditions[END_REF]:

" C + 1 2 D > → > + 2 " → + > + 4" (8)
Thus, the decomposition of organic compounds creates also diatomic molecules and, after highly excited atoms, but it the latter phenomenon occurs at higher temperatures, and its level of excitation is lower than this of hydrogen atoms and it is less significant since amount of methane in the gas mixture is considerable lower than the amount of water and hydrogen.

Effect of the composition on transport properties

The transport properties, such as viscosity and thermal conductivity, of the plasma plume are compared considering the different solution precursors displayed in Table 1.

The considered working mixture, feedstock flow rate and molarities are equal to the those in section 3.1. The results of dynamic viscosity calculus are collected in Fig. 2.

This property is hardly modified by the composition variation, being the mixture with a higher molecular weight (zirconium acetate) the composition which displays a lower viscosity. Besides, a small negative peak of viscosity was observed at 3600 K which is attributed to the presence of the OH -radicals due to the decomposition of water steam [START_REF] Pateyron | Surface & Coatings Technology In fl uence of water and ethanol on transport properties of the jets used in suspension plasma spraying[END_REF][START_REF] Pateyron | Chemical and transport properties of carbonoxygen-hydrogen plasmas in isochoric conditions[END_REF]. This peak is less marked in mixtures with lower amount of water (zirconium acetate) or it is imperceptible in the case of gas pure working gases.

In On the other hand, the composition exhibited a strongly effect in the case of on thermal conductivity, as it is shown in Fig. 3. A noteworthy peak appears near 3000K owing to the generation of atomic hydrogen. Thus, feedstocks mixtures with higher amount of water (higher dilutions or smaller molecules as chloride) considerably increase the thermal conductivity [START_REF] Rat | Treatment of non-equilibrium phenomena in thermal plasma flows[END_REF]. Another secondary peak around 6000 K is appreciated just using an organic precursor as feedstock. This singularity is due to the final decomposition of organic compounds in C, H and O atoms. However, this secondary peak is less marked than the first mentioned. The appreciation of this secondary peak agrees with previous studies which concluded that a similar peak is observed using ethanol as solvent instead of water [START_REF] Pateyron | Chemical and transport properties of carbonoxygen-hydrogen plasmas in isochoric conditions[END_REF]. It is important to highlight the thermal conductivity is an important property to take into account in the SPPS technique, rather than in the conventional APS technique, since the spraying distances are relatively shorts ( 40-60 mm instead of 80-120 mm used at for coarse powder spraying) [START_REF] Pawłowski | Application of solution precursor spray techniques to obtain ceramic films and coatings[END_REF][START_REF] Killinger | Review of new developments in suspension and solution precursor thermal spray processes[END_REF].

Besides the transport properties, the modified ability of heating factor is also calculated, as it can be observed in Fig. 4, with the aim of evaluating the heat flux between the plasma and the feedstock. The AHFmod is 3 times, or more, greater for the working gases including the precursors than for pure Ar+H2 plasma. This factor increases near 3000 K because of the hydrogen dissociation and it reaches its maximum near 4000 K. Then, AHFmod is slightly reduced at higher temperatures and the decomposition of organic compounds into elements is hardly reflected in this factor. In conclusion, the compositions which provide a higher amount of hydrogen atoms exhibit a greater AHF.

Effect of the concentration and flow rate on transport properties

The zirconium acetate is taken as feedstock for this part of the study. The effect of the concentration and flow rate on transport properties was studied considering other precursors and the results were similar. The considered solution concentrations and the feedstock flow rates are shown in Table 1. These parameters hardly affect viscosity but their effect is visible in thermal conductivity and in the ability of heating factor displayed in Fig. 5 and Fig. 6 respectively. The main peak in thermal conductivity is more marked at higher flow rates or lower concentrations, it means when the amount of water inside the precursor is higher. However, the secondary peak is greater at higher flow rates, as occurs in the mainly peak, but the concentration plays an opposite effect, being favorable a higher concentration. The reason is based that the secondary peak is caused by the decomposition of the organic part and it increases at higher flow rate or concentrations. Regarding the AHF, a pronounced increment between 3000 and 4000 K is observed. Besides, the secondary peak is hardly appreciated (the gradient is just 1 % in the case of 4 mol/L solutions). AHF is a 35 % greater increasing twice the flow rate and reducing the concentration. It means a higher heat flux between the plasma and the feedstocks, an important consideration in SPPS technique, and it modifies the phenomena which occurs inside the plasma plume. Nevertheless, energetic considerations should be taken into account since compositions with a higher amount of solvent need a more energetic plasma to evaporate it [START_REF] Jordan | The Solution Precursor Plasma Spray (SPPS) Process: A Review with Energy Considerations[END_REF].

The effect of the concentration and flow rate on transport properties was studied considering other precursors and the results were similar.

Conclusions

Transport properties allow to estimate the heat and momentum transfer between the plasma plume and the feedstock. These properties depends on the chemical composition of the plasma plume and it is they are strongly modified when a liquid feedstock is injected fed.

• A marked increment of the thermal conductivity, therefore of the ability of heating factor, is produced in the SPPS technique when a solution is injected inside the plasma plume. The reason is based on the decomposition of molecular H2O into highly energetic radicals at 3000 K. Thus the increase is more notable when the feedstock hasve a greater amount of water. It does not just imply a higher feedstock flow rate or a lower solution concentration, but precursors with a smaller molecule size.

• The decomposition of organic compounds also contributed to the increment of thermal conductivity but it hardly affects the ability of heating factor.

• Plasma plume viscosity is less sensible to precursor variation than thermal conductivity.

Definitively, the estimation to transport properties, linked to the energetic requirements, can explain the phenomena which occurs inside the plasma plume in a plasma deposition technique. • Zirconyl chloride [ZrOCl24]

• 2 mol/L

• 4 mol/L

• 30 mL/min

• 50 mL/min

  total enthalpy of fusion [J.kg-1], -particle diameter [m], 3particle density [kg.m -3 ] [26]. The variables of the integration are separated into two parameters: ion the left hand, are set up the variables related to the plasma plume are collected in a parameter called ability of heating factor (AHF) while ion the right hand are set the solid properties are collected and they defined another parameter named Difficulty of Melting Factor (DFM). The whole fusion of the solid occurs when AHF is equal or greater to DFM.

Figure captions Figure 1 .

 captions1 Figure captions

Figure 2 .

 2 Figure 2. Dynamic viscosity of the plasma plume injecting different precursors.

Figure 3 .

 3 Figure 3. Thermal conductivity of the plasma plume injecting different precursors.

Figure 4 .

 4 Figure 4. Modified ability of heating factor of the plasma plume injecting different

Figure 5 .

 5 Figure 5. Thermal conductivity of the plasma plume at different feedstock flow rates

Figure 6 .

 6 Figure 6. Modified ability of heating factor of the plasma plume at different feedstock

Figure 4 Figure 5

 45 Figure 4

Figure 6

 6 Figure 6

TableTable 1 .

 1 Type of precursor, the molarity and flow rate values contemplated in the thermal transport estimations.

	Kind of precursor	Molarity	Solution flow rate
	(2 mol/L and 50 mL/min)	(zirconium acetate)
	• Zirconium acetate [Zr(CH3COO)4]
	• Zirconyl nitrate [ZrO(NO3)24]

Acknowledgment P. Carpio acknowledges the Valencia Government (APOSTD/2016/040) and the Spanish Ministry of Science, Innovation and Universities for his current post-doc contract (FJCI-2016-27822 ) for his post-doc contract.