M Rathore

Christophe Girard

M Ohanna

M Tichet

R Ben Jouira

E Garcia

F Larbret

M Gesson

S Audebert

J.-P Lacour

• M Ohanna

• M Tichet

R Ben Jouira

• E Garcia

• F Larbret

• M Gesson

• S Audebert

• H Montaudié

V Prod'homme

S Tartare-Deckert

• M Deckert
email: deckert@unice.fr

M Deckert

Cancer cell-derived long pentraxin 3 (PTX3) promotes melanoma migration through a toll-like receptor 4 (TLR4)/NF-κB signaling pathway

    Cancer cell-derived long pentraxin 3 (PTX3) promotes melanoma migration through a toll-like receptor 4 (TLR4)/NF-κB signaling pathway

Introduction

Melanoma is the leading cause of skin cancer-related deaths, whose incidence has increased dramatically in the past 30 years. Melanoma arises from neural-crest-derived melanocytes found in the basal layer of the epidermis and responsible for melanin production and pigmentation. Early metastatic spread, intratumor heterogeneity, and therapeutic resistance are hallmarks of melanoma. During the last years, much has been learned about the genetic and epigenetic driver events of tumor initiation, progression, and response to targeted therapies. Activating mutations of the BRAF proto-oncogene, which are the most prevalent mutations predict clinical efficacy to BRAF inhibitors such as vemurafenib in BRAF-mutated metastatic melanomas; and NRAS mutant tumors are known to exhibit sensitivity to MEK inhibition [START_REF] Flaherty | From genes to drugs: targeted strategies for melanoma[END_REF][START_REF] Holderfield | Targeting RAF kinases for cancer therapy: BRAF-mutated melanoma and beyond[END_REF]. Despite recent breakthroughs in melanoma treatments with the combination of targeted therapies using BRAF and MEK inhibitors and immunotherapies using checkpoint-blocking antibodies, resistance invariably develops and the prognosis remains dismal for most patients. Notably, current targeted therapies have even been shown to promote a mesenchymal-like invasive cell state and metastasis of resistant melanoma cells [START_REF] Kemper | Phenotype switching: tumor cell plasticity as a resistance mechanism and target for therapy[END_REF].

The acquisition of an invasive behavior is one of the key events in the progression to aggressive and deadly melanoma. Thus, identification of tumor cell intrinsic and extrinsic factors and characterization of the molecular mechanisms that drive this behavior are essential to our understanding of how melanoma metastasis develops, and to the development of novel therapeutic strategies. Emerging evidence support that progression to metastasis involves a series of reversible phenotypic changes in tumor cells. Under microenvironmental influences melanoma cells can undergo transcriptional reprogramming and switch between two different dominant states, either proliferative and poorly invasive or invasive and poorly proliferative, both being characterized by distinct gene expression signatures [START_REF] Kemper | Phenotype switching: tumor cell plasticity as a resistance mechanism and target for therapy[END_REF][START_REF] Widmer | Systematic classification of melanoma cells by phenotype-specific gene expression mapping[END_REF][START_REF] Cheli | Hypoxia and MITF control metastatic behaviour in mouse and human melanoma cells[END_REF][START_REF] Verfaillie | Decoding the regulatory landscape of melanoma reveals TEADS as regulators of the invasive cell state[END_REF]. Levels and activity of microphthalmiaassociated transcription factor (MITF), the melanocyte lineage-restricted transcription factor, are key determinants of the melanoma phenotype switch and tumor cell plasticity. The "proliferative" cellular state expresses higher levels of MITF than the "invasive" state. Importantly, the MITF low invasive signature has been associated with intrinsic resistance to new drugs targeting mutant BRAF and MEK [START_REF] Kemper | Phenotype switching: tumor cell plasticity as a resistance mechanism and target for therapy[END_REF][START_REF] Muller | Low MITF/AXL ratio predicts early resistance to multiple targeted drugs in melanoma[END_REF][START_REF] Shaffer | Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance[END_REF]. Finally, acquisition of migratory and invasive traits by melanoma cells also involved modulation of epithelial-mesenchymal transition (EMT)-inducing transcription factors expression, including members of the SNAIL, TWIST, and ZEB families [START_REF] Fenouille | The epithelial-mesenchymal transition (EMT) regulatory factor SLUG (SNAI2) is a downstream target of SPARC and AKT in promoting melanoma cell invasion[END_REF][START_REF] Weiss | TWIST1 is an ERK1/2 effector that promotes invasion and regulates MMP-1 expression in human melanoma cells[END_REF][START_REF] Caramel | A switch in the expression of embryonic EMT-inducers drives the development of malignant melanoma[END_REF].

Tumor cell-secreted factors play a key role in the process of malignant progression via their ability to regulate cell autonomous signaling and paracrine stroma communication. Drivers of melanoma invasion include such autocrine signals propagated by secreted factors that may thus represent potential candidate molecules for diagnosis and specific anti-invasive therapies. By proteomic profiling of metastatic and non-metastatic melanomas we recently identified a spectrum of secreted factors and inflammatory mediators that were enriched in conditioned medium (CM) of metastatic cells compared to non-metastatic cells [START_REF] Tichet | Tumour-derived SPARC drives vascular permeability and extravasation through endothelial VCAM1 signalling to promote metastasis[END_REF]. Of potential interest, the long pentraxin 3 (PTX3) was found abundantly produced by metastatic melanoma cells. PTX3 is an evolutionarily conserved pattern recognition molecule involved in innate immune response, complement activation and inflammation, and have been linked to diseases such as cancer [START_REF] Garlanda | 3. a humoral pattern recognition molecule at the interface between microbe and matrix recognition[END_REF][START_REF] Bottazzi | The pentraxins PTX3 and SAP in innate immunity, regulation of inflammation and tissue remodelling[END_REF]. A complex role of PTX3 in cancer, either as an oncosuppressor or a protumorigenic factor, is emerging [START_REF] Bonavita | PTX3 is an extrinsic oncosuppressor regulating complementdependent inflammation in cancer[END_REF][START_REF] Magrini | The dual complexity of PTX3 in health and disease: a balancing act?[END_REF]. The goal of this study was to analyze the autocrine function of PTX3 in melanoma cell invasive signaling and metastasis and to determine the relevance of these observations to human disease. We show that PTX3 is a key factor secreted by a MITF low invasive subpopulation of melanoma, and contributes to tumor cell migration and invasion in vitro and in vivo. Importantly, tissues and systemic PTX3 levels are elevated in a fraction of metastatic melanoma patients, and in mesenchymal drug-resistant melanoma cells. Mechanistically, we found that PTX3 functions through a TLR4/MYD88/IKK/NF-κB feedforward signaling pathway to mediate the expression of EMT transcription factor TWIST1, and to promote melanoma migration. In summary, our results point to PTX3 as a potentially useful biomarker for advanced melanoma and as an anti-melanoma therapeutic target.

Results

PTX3 expression is associated with an invasive melanoma cell state

Using quantitative mass spectrometry analysis [START_REF] Tichet | Tumour-derived SPARC drives vascular permeability and extravasation through endothelial VCAM1 signalling to promote metastasis[END_REF], the pentraxin-related protein PTX3 was found enriched in CM from metastatic 1205Lu cells compared to the poorly invasive 501Mel cells (Supplementary Table 1). Antibody arrays analysis confirmed that PTX3 is abundantly produced by metastatic melanoma cells in addition to other proteins involved in migration and inflammation (IL-1α, IL-6, IL-8, MCP-1, TNFsR1, CCL2), matrix remodeling and adhesion (TSP1, TIMP1) (Supplementary Fig. 1). Direct dosage by enzyme-linked immunosorbent assay (ELISA) and immunoblot analysis of PTX3 in CM obtained from different malignant melanoma cells showed that PTX3 was preferentially produced by 1205Lu and A375 cell lines (Fig. 1a,b). PTX3 was also secreted by cultures of primary tumor cells from metastatic melanoma patients (Pt1 and Pt2) (Fig. 1a). It is recognized that melanoma cells can switch from a proliferative and poorly invasive MITF high phenotype to an invasive and poorly proliferative MITF low phenotype [START_REF] Widmer | Systematic classification of melanoma cells by phenotype-specific gene expression mapping[END_REF]. Given our observations, we thus searched publicly available gene expression data sets for PTX3 expression in proliferative vs. invasive melanoma cell population within the Mannheim, Philadelphia, and Zurich cohorts (GSE4843, GSE4841, and GSE4840 data sets, respectively) and found an inverse correlation between PTX3 and MITF expression across proliferative and invasive cell states (Fig. 1c,d). GSE61544) (Fig. 1e) and that short-hairpin RNA (shRNA)mediated depletion of MITF in COLO829 melanoma cells upregulated PTX3 mRNA expression (GSE50686) (Fig. 1f). Finally, knockdown of MITF expression in the poorly invasive cell line 501Mel was associated with increased levels and secretion of PTX3 (Fig. 1g). Consistent with our previous report [START_REF] Cheli | Hypoxia and MITF control metastatic behaviour in mouse and human melanoma cells[END_REF], the expression of the mesenchymal marker SPARC and p27 Kip1 was also augmented following MITF depletion in 501Mel cells. Altogether our data identify high levels of PTX3 in MITF low invasive melanoma cells.

PTX3 is upregulated during human metastatic melanoma disease and acquisition of mesenchymal drug resistance

The finding that PTX3 level was associated with a melanoma invasive signature prompted us to examine its expression in metastases and blood samples from melanoma patients. In silico data analysis of PTX3 expression in public databases showed that PTX3 mRNA was increased in metastatic melanoma compared to benign skin lesions (nevi) (Fig. 2a). In addition, the examination of PTX3 in melanoma patients from The Cancer Genome Atlas (TCGA) data sets revealed that PTX3 alterations (PTX3 amplifications and mRNA upregulation) were associated with a trend toward shorter disease-free progression (P = 0.0151) and shorter overall survival (P = 9.872e-3) (Fig. 2b). Interestingly, gene set enrichment analysis (GSEA) showed that high PTX3 levels in melanoma tumors positively correlated with Epithelial-to-Mesenchymal Transition (EMT) and Inflammatory Response gene signatures (Fig. 2c). Immunohistochemical analysis of PTX3 in melanoma tissue microarrays showed that a marked PTX3 cytoplasmic and membranous immunoreactivity in malignant melanoma at stage IV (3 out of 10) compared to four adjacent normal skin tissues. In contrast, malignant melanoma at stage III (6 out of 6) showed low to medium levels of PTX3 (Fig. 2d,e and Supplementary Fig. 2). Consistently, the amount of circulating PTX3 in blood from patients with stage IV metastatic disease (n = 16) was significantly increased in diseased (7.98 ± 5.12 ng/ml) compared to healthy subjects (n = 10) (2.36 ± 1.15 ng/ml) samples (Fig. 2f). These observations indicate that high PTX3 levels correlated with melanoma cells from advanced metastatic disease.

Recent findings indicate that by switching from a proliferative MITF high /AXL low to a mesenchymal invasive MITF low /AXL high state, melanoma cells can acquire resistance to targeted therapies [START_REF] Kemper | Phenotype switching: tumor cell plasticity as a resistance mechanism and target for therapy[END_REF][START_REF] Muller | Low MITF/AXL ratio predicts early resistance to multiple targeted drugs in melanoma[END_REF]. We thus investigated the potential link between PTX3 expression and acquired resistance to BRAF inhibitors. Immunoblot analyses performed on isogenic pairs of sensitive and vemurafenibresistant melanoma cells [START_REF] Nazarian | Melanomas acquire resistance to B-RAF(V600E) inhibition by RTK or N-RAS upregulation[END_REF] revealed that MITF low -resistant cells M229R and M238R expressed and secreted high levels of PTX3 when compared to MITF high drug-sensitive parental cells M229P and M238P (Fig. 3a,b). As expected, the mesenchymal markers Fibronectin and PDGFR-β were also upregulated in the two resistant cell lines (Fig. 3a) [START_REF] Titz | JUN dependency in distinct early and late BRAF inhibition adaptation states of melanoma[END_REF]. Importantly, our observations were clinically supported in public gene expression data sets showing that PTX3 increased in progressing tumors biopsies during therapy with BRAFi (vemurafenib or dabrafenib) or MEKi (trametinib) (Fig. 3c). Our analysis of the CM prepared from melanoma cells derived from a relapsing melanoma patient further showed that PTX3 and Fibronectin production by melanoma cells increased following the acquisition of mesenchymal resistance to vemurafenib (Fig. 3d). Altogether, our findings hence link PTX3 expression to a subpopulation of inflammatory, dedifferentiated and invasive melanoma cells, which could be associated with poor prognosis.

Melanoma-derived PTX3 promotes tumor cell migration

We next investigated the contribution of PTX3 to melanoma cell migration. To this end, the migratory ability of PTX3-depleted cells was tested in Boyden chamber assays. Knockdown of PTX3 in 1205Lu and A375 cells using two different non-overlapping PTX3-targeting small-interfering Fig. 1 PTX3 expression is associated with an invasive MITF low melanoma cell state. a ELISA analyses of PTX3 secretion in CM of different melanoma cell lines and patient short-term cultures. Equal amounts of CM from SBcl2, WM35, WM793, 501Mel, MeWo, SKMel28, 1205Lu, A375, and melanoma patient cells (Pt1, Pt2) were subjected to PTX3 ELISA. Data represent the mean concentration of PTX3 in CM ± s.e.m of duplicate determinations. b Equal amounts of CM from melanoma cell lines were immunoblotted with PTX3 antibody. Ponceau staining was used as a loading control for secreted proteins. c Box and whisker plots (10th to 90th percentile) show MITF and PTX3 expression across proliferative vs. invasive cell states of melanoma cultures within the Mannheim, Philadelphia, and Zurich cohorts (GSE4843, GSE4841, and GSE4840 data sets). P-values were calculated by unpaired two-tailed Mann-Whitney test. d Spearman's correlation analysis of the MITF and PTX3 mRNA expression across the Mannheim melanoma cohort (GSE4843). e PTX3 mRNA expression in melanoma cell lines classified based on high (MITF high) or low (MITF low) levels of MITF expression. Box and whisker plots (10th to 90th percentile) show normalized PTX3 expression values mined from publicly available data sets (GSE62526 and GSE61544). P-values were calculated by unpaired two-tailed Mann-Whitney test. f PTX3 and TYRP1 gene mRNA in melanoma cells depleted (shMITF) or not (shSCR) of MITF. Box plots depict PTX3 expression values extracted from a GEO data set (GSE50686). g 501Mel cells were transfected with siCTRL or siMITF for 3 days. Total cell lysates and CM were analyzed by immunoblotting with antibodies against MITF, p27Kip1, SPARC, PTX3, and ERK2 as a loading control. Ponceau staining was used as a loading control for secreted proteins. ***P < 0.0001; **P < 0.01; *P < 0.05 RNAs (siRNAs; siPTX3#1 and siPTX3#2) inhibited the chemotactic migration of melanoma cells towards serum compared to cells transfected with a non-targeting siRNA (siCTRL) (Fig. 4a). Importantly, PTX3 knockdown, which abrogated PTX3 secretion, had no significant effect on cell viability (Supplementary Fig. 3c). Depleting PTX3 also blocked the migration of invasive M229R and M238R BRAFi-resistant cell lines and of metastatic melanoma cells derived from a patient (Pt1) (Fig. 4a). Conversely, the stable expression of PTX3 in PTX3-negative cells 501Mel and SKMel28 increased cell migration (Fig. 4b) (Supplementary Fig. 4). Addition of exogenous recombinant PTX3 rescued the migratory ability of PTX3-depleted A375 and 1205Lu cells (Fig. 4c and Supplementary Fig. 5), suggesting that PTX3 promotes melanoma cell migration in an autocrine manner following its secretion by the cancer cell. To test this hypothesis, we carried out in vitro scratch assays using the non-invasive PTX3-negative 501Mel cells incubated with CM produced by invasive PTX3-positive 1205Lu cells. As shown in Fig. 4d, the addition of CM produced by 1205Lu cells transfected by non-targeting siRNA enhanced the migration of 501Mel cells in the wound gap, whereas adding CM produced by PTX3-depleted 1205Lu cells had no significant effect on 501Mel cell migration. Using 1205Lu CMs that were immuno-depleted of PTX3, we confirmed that secreted PTX3 is required to induce melanoma cell migration (Fig. 4e). Of note, PTX3-expressing 501Mel cells displayed increased cell motility in scratch assays when compared to control PTX3-negative 501Mel cells (Supplementary Fig. 6). In addition, we found that recombinant PTX3 enhanced the migration of another noninvasive PTX3-negative melanoma cell line, SKMel28 (Fig. 4f), indicating that melanoma-derived PTX3 has a direct effect on tumor cell motility.

PTX3 expression increases melanoma invasiveness and lung extravasation

Our observations led us to investigate whether PTX3 participates to melanoma cell invasion. Matrigel invasion assays revealed that siRNA-mediated depletion of PTX3 reduced the invasive migration of 1205Lu, A375, and M229R (Fig. 5a). Interestingly, exogenous recombinant PTX3 restored the impaired invasiveness of PTX3-depleted 1205Lu cells (Fig. 5b). Conversely, stable expression of PTX3 in PTX3-negative SKMel28 cells increased the capacity of melanoma cells to invade matrigel (Fig. 5c). To investigate further the activity of PTX3 in melanoma invasion, A375 and WM266.4 cell spheroids were implanted into gels of type I collagen and three-dimensional (3D) tumor cell invasion was evaluated by microscopy. Whereas knockdown of PTX3 had no significant effect on spheroid growth rate, the depletion of PTX3 impaired melanoma invasion into collagen of both cell lines (Fig. 5d, Supplementary Fig. 7). Consistently, zymographic analysis of the invasion-related matrix metalloproteinase MMP-9 revealed a decrease of its collagenase activity in PTX3depleted melanoma cells compared to control (Fig. 5d).

Tumor cell extravasation is a required early step during tissue colonization and metastatic spread [START_REF] Obenauf | Surviving at a distance: organ-specific metastasis[END_REF]. To examine how PTX3 participates to this process, we assessed the effect of PTX3 knockdown in transendothelial migration of 1205Lu cells on monolayers of TNFα-activated HUVECs.

Compared to control siRNA-transfected cells, the transmigration of PTX3-silenced melanoma cells was markedly reduced (Fig. 5e). Importantly, the reduced potential of PTX3-depleted cells to transmigrate was rescued by the addition of exogenous PTX3, thereby linking autocrine PTX3 production by melanoma cells to their ability to cross endothelial barriers (Fig. 5e).

Next, we sought to confirm our observations in vivo using a long-term lung colonization assay by bioluminescent melanoma cells [START_REF] Tichet | Tumour-derived SPARC drives vascular permeability and extravasation through endothelial VCAM1 signalling to promote metastasis[END_REF]. To this end, 1205Lu-Luc + melanoma cells were stably infected with lentiviruses harboring a control shRNA lentivirus (shCtrl) and different shRNAs against PTX3. The efficiency of PTX3 knockdown was assessed by immunoblotting CM from the infected cells (Supplementary Fig. 8a). Further analysis of in vitro cell migration in Boyden chamber assays showed that shPTX3 sequence 5 (shPTX3-5) was the most efficient in reducing cell migration compared to shCtrl (Supplementary Fig. 8b). Stable control (shCTRL) and PTX3 (shPTX3-5) knockdown (Fig. 6a) bioluminescent melanoma cells were then injected into the tail vein of nude mice. Bioluminescence imaging (BLI) recorded post injection showed that control and PTX3-depleted cells equally arrested into the lungs after 15 min. However, BLI measurements during the next 15 days revealed a dramatic reduction in lung colonization by PTX3-depleted compared to control cells (Fig. 6b). The quantification of lung colonization by ex vivo BLI at the endpoint of the assay revealed a sixfold reduction in experimental lung metastasis by stable PTX3 knockdown cells compared to control cells (Fig. 6c). Importantly, transient PTX3 knockdown also inhibited melanoma lung extravasation in mice (Supplementary Fig. 9). Finally, using a short-term lung colonization assay [START_REF] Tichet | Tumour-derived SPARC drives vascular permeability and extravasation through endothelial VCAM1 signalling to promote metastasis[END_REF], we observed that expression of PTX3 in non-metastatic 501Mel cells significantly increased their extravasation into lungs (Fig. 6d). Altogether, these data suggest that melanoma PTX3 increased the migratory potential of melanoma cells in vivo.

A TLR4-NF-kB-TWIST1 axis is required for melanoma cell migration mediated by PTX3

We next wished to identify the signaling pathways involved in PTX3-mediated melanoma cell migration and invasion. Whereas PTX3 depletion in 1205Lu and M229R cells had no significant effect on the activity of ERK1/2 and AKT (Supplementary Fig. 10), it drastically decreased NF-kB pathway activity, as shown by the reduced level of phosphorylated IKKα/β, IkBα, and NF-kB p65 observed in PTX3-depleted cells (Fig. 7a). Interestingly, reduced NF-kB activity in PTX3-depleted cells decreased the expression of EMT factors TWIST1 and SNAIL. These results suggest that PTX3 activates the NF-kB pathway in melanoma to promote cell migration and invasion through EMT factors.

Consistently, IKK targeting in melanoma cells either with IKK inhibitor BMS345541 (Fig. 7b) or with siRNAs directed against IKKα/β (Fig. 7c) reduced EMT factors levels and cell migration. In line with previous reports [START_REF] Weiss | TWIST1 is an ERK1/2 effector that promotes invasion and regulates MMP-1 expression in human melanoma cells[END_REF][START_REF] Caramel | A switch in the expression of embryonic EMT-inducers drives the development of malignant melanoma[END_REF][START_REF] Na | Interleukin-6-induced Twist andx N-cadherin enhance melanoma cell metastasis[END_REF], we confirmed that TWIST1 is an important regulator of melanoma cell migration (Fig. 7d). Conversely, the activation of the NF-kB pathway and TWIST1 expression was significantly increased in 501Mel cells stably expressing PTX3 compared to control cells (Fig. 7e). Using an NF-kB-luciferase reporter construct, we confirmed that overexpression of PTX3 in melanoma cells enhanced NF-kB transcriptional activity in non-stimulated cells and showed additive effects with TNFα stimulation to further increase NF-kB activity (Fig. 7f). Having shown that PTX3 overexpression increased the migration of poorly invasive melanoma cells, we thus examined whether the NF-kB/ TWIST pathway participates to this process. A reduction of PTX3-mediated cell migration was observed in PTX3- expressing 501Mel cells treated with the IKK inhibitor BMS345541 (Fig. 7g) or transfected with TWIST1 siRNA (Fig. 7h). However, the migration of control cells was also reduced upon IKK inhibition or TWIST1 depletion, indicating that the NF-kB/TWIST axis controls additional PTX3-independent invasive pathways. Finally, we sought to identify the mechanism through which melanoma-secreted PTX3 endows tumor cells with enhanced migratory potential. Our rescue experiments with exogenous recombinant PTX3 point to the existence of a PTX3 receptor that is expressed at the cell surface of melanoma cells. Previous studies showing that PTX3 mediates antifungal resistance through TLR4/MD-2-mediated signaling [START_REF] Bozza | PTX3 binds MD-2 and promotes TRIF-dependent immune protection in aspergillosis[END_REF] and that melanoma cells express functional TLRs including TLR4 [START_REF] Ahn | Human melanocytes express functional Toll-like receptor 4[END_REF][START_REF] Eiro | Expression of TLR3, 4, 7 and 9 in cutaneous malignant melanoma: relationship with clinicopathological characteristics and prognosis[END_REF][START_REF] Takazawa | Toll-like receptor 4 signaling promotes the migration of human melanoma cells[END_REF] led us to hypothesize that TLR4 could mediate the effect of PTX3 on melanoma cell migration. The depletion of TLR4 in melanoma cells using two siRNA sequences markedly reduced cell migration (Fig. 8a). Rescue experiments on melanoma cells that were depleted of PTX3 or TLR4 showed that recombinant PTX3 restored the migration of PTX3-silenced cells, whereas recombinant PTX3 was ineffective to restore the migration of TLR4 silenced cells (Fig. 8b). Interestingly, melanoma cells that were depleted of the TLR4 signal transducer MYD88 displayed a reduced motility, decreased NF-kB p65 phosphorylation and TWIST1 expression (Fig. 8c). Consistent with an action of TLR4/MYD88 axis downstream of PTX3, recombinant PTX3 failed to rescue migration of 1205Lu cells that were treated with a MYD88 inhibitory peptide (Supplementary Fig. 11). Finally, we found that the IKK inhibitor BMS345541 impaired the autocrine production of PTX3 by 1205lu cells (Fig. 8d). Together, our results suggest that melanoma-secreted PTX3 could act through a TLR4/MYD88 receptor complex to promote NF-kB activation, TWIST1 and cell migration (Fig. 8e).

Discussion

Upon tumor microenvironment cues, melanoma cells can switch between different cell states characterized by MITF levels and invasive abilities [START_REF] Kemper | Phenotype switching: tumor cell plasticity as a resistance mechanism and target for therapy[END_REF][START_REF] Widmer | Systematic classification of melanoma cells by phenotype-specific gene expression mapping[END_REF][START_REF] Cheli | Hypoxia and MITF control metastatic behaviour in mouse and human melanoma cells[END_REF][START_REF] Verfaillie | Decoding the regulatory landscape of melanoma reveals TEADS as regulators of the invasive cell state[END_REF]. Using a comparative mass spectrometry approach to characterize the melanoma metastatic secretome, we have identified a spectrum of secreted factors and inflammatory mediators that were enriched in conditioned medium of human metastatic cells compared to non-metastatic cells [START_REF] Tichet | Tumour-derived SPARC drives vascular permeability and extravasation through endothelial VCAM1 signalling to promote metastasis[END_REF]. Here, we further show that PTX3 is one such factor secreted by the MITF low invasive subpopulation of melanomas to promote tumor cell migration through a TLR4/NF-κB signaling pathway. Based on our findings, we propose that PTX3 represents a novel autocrine regulator of melanoma migration and invasiveness.

Analysis of publicly available gene expression databases indicated that high PTX3 levels correlated with a minority of human melanomas that are associated with a shorter disease-free survival. In addition, our immunohistochemical analysis showed a marked PTX3 immunoreactivity in a fraction of stage IV melanoma but not stage III melanoma tissues, suggesting that high PTX3 expression is associated with melanoma cells from advanced metastatic disease. Accordingly, elevated PTX3 levels were also found increased in blood samples from patients with stage IV metastatic disease. Interestingly, bioinformatic survey of melanoma transcriptional signatures correlated PTX3 expression to a MITF low invasive subpopulation of melanoma cells. Furthermore, depletion of MITF resulted in increased PTX3 expression in the MITF high proliferative and poorly invasive cell population, suggesting that MITF could negatively regulate PTX3 expression in melanoma. The MITF low invasive signature has been associated with intrinsic resistance to drugs targeting mutant BRAF and MEK [START_REF] Kemper | Phenotype switching: tumor cell plasticity as a resistance mechanism and target for therapy[END_REF][START_REF] Muller | Low MITF/AXL ratio predicts early resistance to multiple targeted drugs in melanoma[END_REF][START_REF] Shaffer | Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance[END_REF]. Consistently, PTX3 expression and secretion was found inversely correlated with MITF expression and positively correlated with mesenchymal markers, such as Fibronectin and PDGFR-β, in cultured melanoma cells that have acquired resistance to the BRAF inhibitor vemurafenib. Importantly, high levels of PTX3 and Fibronectin were also found in a clinical specimen of melanoma that has relapsed from MAPK targeting therapies. Altogether, these observations, which link PTX3 expression to a subpopulation of dedifferentiated and invasive MITF low melanoma cells, underscore the notion that PTX3 may represent a novel potential indicator of advanced metastatic and/or drug-refractory melanoma.

The acquisition of migratory and invasive abilities by melanoma cells involves induction of mesenchymal traits by transcription factors, including those of the SNAIL, TWIST, and ZEB families [START_REF] Verfaillie | Decoding the regulatory landscape of melanoma reveals TEADS as regulators of the invasive cell state[END_REF][START_REF] Fenouille | The epithelial-mesenchymal transition (EMT) regulatory factor SLUG (SNAI2) is a downstream target of SPARC and AKT in promoting melanoma cell invasion[END_REF][START_REF] Weiss | TWIST1 is an ERK1/2 effector that promotes invasion and regulates MMP-1 expression in human melanoma cells[END_REF][START_REF] Caramel | A switch in the expression of embryonic EMT-inducers drives the development of malignant melanoma[END_REF]. Accordingly, autocrine production of PTX3 by invasive melanoma cells was found to induce an IKK/NFκB signaling pathway that activated the pro-invasive matrix metalloproteinase MMP-9 and the expression of the EMT-inducing factor TWIST1, leading to tumor cell migration and invasion. Thus, we identified PTX3 as a novel crucial regulator of melanoma cell invasive behavior. These observations appear to be in striking contrast with a previous study in which PTX3 was described as an intrinsic oncosuppressive protein in certain melanoma cells [START_REF] Ronca | Long pentraxin-3 inhibits epithelial-mesenchymal transition in melanoma cells[END_REF]. However, there are consistent with other studies that have attributed to PTX3 a cancersupportive activity. For example, knocking down PTX3 in Fig. 7 PTX3 functions through IKK/NF-kB and TWIST1 to promote melanoma cell migration. a 1205Lu and M29R cells were transfected with siCTRL or siPTX3. Cell lysates were immunoblotted with the indicated antibodies. HSP60, loading control. b Transwell migration assays were performed on 1205Lu and M229R cells treated with IKK inhibitor BMS345541 (10 µM). Immunoblots with the indicated antibodies are shown. Bar graphs represent mean ± s.e.m (n = 3 independent experiments). c Transwell migration assays and immunoblot of cell lysate were performed following transfection of 1205Lu and M229R cells with siRNA targeting IKKα and IKKβ (siIKKα/β). Immunoblots for the indicated antibodies are shown. Lower panel represents bar graph of cell migration mean ± s.e.m (n = 3 independent experiments). d Transwell migration assays were performed on control (siCTRL) or TWIST1-depleted (siTWIST1) 1205Lu and M229R cells. Immunoblots against TWIST1 and HSP60 are shown. Bar graphs show mean ± s.e.m (n = 3 independent experiments). e Lysates from 501Mel cells stably expressing PTX3 or not were analyzed by immunoblot with the indicated antibodies. f 501Mel cells stably expressing PTX3 were transfected with a NF-κB luciferase reporter and stimulated or not with TNF-α (10 nM). Normalized luciferase activity was measured. Bar graphs show mean ± s.e.m (n = 3 independent experiments in duplicate). g 501Mel cells expressing PTX3 were treated with the IKK inhibitor BMS345541 (10 µM) for 4 h. Transwell migration assays and immunoblot analysis for the indicated antibodies were performed. Bar graphs represent mean ± s.e.m., n = 3 experiments. h PTX3-expressing 501Mel cells were transfected with siCTRL or siTWIST1. Migration assay was performed as above. Bar graphs show mean ± s.e.m (n = 2 independent experiments). ***P < 0.001, **P < 0.01, *P < 0.05 as determined by two-way ANOVA and Bonferroni post-tests cervical cancer cells decreases migratory and invasive abilities in vitro and metastatic potential by inhibiting MMP-2/9 and the urokinase plasminogen activator (uPA) [START_REF] Ying | Knockdown of Pentraxin 3 suppresses tumorigenicity and metastasis of human cervical cancer cells[END_REF]. In head and neck squamous cell carcinoma (HNSCC), autocrine production of EGF-induced PTX3 expression promotes cell migration, invasion, and lung metastasis through the upregulation of Fibronectin, MMP-9 and Vimentin [START_REF] Chang | PTX3 gene activation in EGF-induced head and neck cancer cell metastasis[END_REF][START_REF] Chan | Oleate-induced PTX3 promotes head and neck squamous cell carcinoma metastasis through the up-regulation of vimentin[END_REF]. Remarkably, our results indicate that overexpression of PTX3 autonomously instigated a migratory and invasive phenotype to poorly invasive MITF high melanoma cells. The observation that recombinant or melanoma-derived PTX3 increased the migration of poorly motile melanoma cell lines further suggests that PTX3 acts both as a paracrine and autocrine factor in the heterogeneous melanoma cell population.

Additionally, we have addressed how PTX3 modulates melanoma cell biological properties. A study showing that PTX3 mediates antifungal resistance through TLR4/MD-2mediated signaling [START_REF] Bozza | PTX3 binds MD-2 and promotes TRIF-dependent immune protection in aspergillosis[END_REF] suggested that PTX3 could exogenously promote melanoma migration through a TLR4 signaling axis. Previous reports showing that melanocytes and melanoma cells express functional TLRs including TLR4 [START_REF] Ahn | Human melanocytes express functional Toll-like receptor 4[END_REF][START_REF] Eiro | Expression of TLR3, 4, 7 and 9 in cutaneous malignant melanoma: relationship with clinicopathological characteristics and prognosis[END_REF][START_REF] Takazawa | Toll-like receptor 4 signaling promotes the migration of human melanoma cells[END_REF], and that TLR4 promotes the migration of melanoma cells independently of its canonical agonist LPS [START_REF] Takazawa | Toll-like receptor 4 signaling promotes the migration of human melanoma cells[END_REF] further reinforced this hypothesis. Consistently, we found that TLR4 and MYD88 knockdown or targeting significantly inhibited PTX3-induced melanoma cell migration and TWIST1 expression. However, whether melanoma-derived PTX3 directly associates with TLR4 on the surface of melanoma cells remains to be shown. In addition, the exact mechanism by which PTX3 regulates NF-kB-dependent expression of the EMT factor TWIST1 has yet to be determined. It is possible that PTX3 triggers NF-kB-mediated transcriptional upregulation of TWIST1, in similar ways to what was described for TNFα-induced TWIST1 expression in breast cancer cells [START_REF] Li | Epithelialmesenchymal transition induced by TNF-alpha requires NF-kappaB-mediated transcriptional upregulation of Twist1[END_REF]. Interestingly, TLR4 expression has been associated with a shorter relapse-free survival in cutaneous malignant melanoma [START_REF] Eiro | Expression of TLR3, 4, 7 and 9 in cutaneous malignant melanoma: relationship with clinicopathological characteristics and prognosis[END_REF], suggesting that a feed-forward PTX3/TLR4/NF-kB signaling pathway favors melanoma invasive phenotype. In support of this notion is the finding that IKKα/β activity was necessary to the autocrine production of PTX3 by invasive melanoma cells.

PTX3 plays a major non-redundant role in the humoral innate immunity during complement activation and pathogen recognition, inflammatory responses, and tissue repair [START_REF] Garlanda | 3. a humoral pattern recognition molecule at the interface between microbe and matrix recognition[END_REF][START_REF] Bottazzi | The pentraxins PTX3 and SAP in innate immunity, regulation of inflammation and tissue remodelling[END_REF]. In contrast, its function in tumor development and metastasis remains largely debated in line with studies reporting either its oncosuppressive [START_REF] Bonavita | PTX3 is an extrinsic oncosuppressor regulating complementdependent inflammation in cancer[END_REF][START_REF] Rubino | Epigenetic regulation of the extrinsic oncosuppressor PTX3 gene in inflammation and cancer[END_REF] or its protumorigenic activity [START_REF] Chang | PTX3 gene activation in EGF-induced head and neck cancer cell metastasis[END_REF][START_REF] Choi | Pentraxin-3 silencing suppresses gastric cancer-related inflammation by inhibiting chemotactic migration of macrophages[END_REF][START_REF] Tung | Inhibition of pentraxin 3 in glioma cells impairs proliferation and invasion in vitro and in vivo[END_REF][START_REF] Thomas | Pentraxin-3 is a PI3K signaling target that promotes stem cell-like traits in basal-like breast cancers[END_REF] (recently reviewed in ref. [START_REF] Giacomini | Long pentraxin 3: a novel multifaceted player in cancer[END_REF]. The emerging model for PTX3 implication in tumorigenesis points to an extrinsic activity as an oncosuppressive factor in cancer-related inflammation. The production of PTX3 by tumor microenvironment-associated macrophages (TAMs) and endothelial cells was shown to impede the tumor-promoting inflammation that is driven by complement activation [START_REF] Bonavita | PTX3 is an extrinsic oncosuppressor regulating complementdependent inflammation in cancer[END_REF]. In addition, PTX3 overexpression or targeting prevented FGF-dependent tumor angiogenesis and growth in a variety of cancer models such as prostate cancers [START_REF] Ronca | Long pentraxin-3 as an epithelial-stromal fibroblast growth factortargeting inhibitor in prostate cancer[END_REF][START_REF] Ronca | Long-pentraxin 3 derivative as a small-molecule fgf trap for cancer therapy[END_REF], steroid hormone-regulated tumors [START_REF] Leali | Long pentraxin-3 inhibits FGF8b-dependent angiogenesis and growth of steroid hormone-regulated tumors[END_REF], and breast cancers [START_REF] Margheri | Systemic sclerosis-endothelial cell antiangiogenic pentraxin 3 and matrix metalloprotease 12 control human breast cancer tumor vascularization and development in mice[END_REF]. Similarly, in melanoma, PTX3 has been shown to hamper FGF-driven cell invasiveness and metastatic potential [START_REF] Ronca | Long pentraxin-3 inhibits epithelial-mesenchymal transition in melanoma cells[END_REF]. On the contrary, our study supports a role of PTX3 as an intrinsic prometastatic protein regulating cell motility in a subpopulation of MITF low invasive melanoma. Our data are consistent with studies supporting the role of PTX3 as an intrinsic oncogenic protein in lung [START_REF] Hu | Knockdown of the inflammatory factor pentraxin-3 suppresses growth and invasion of lung adenocarcinoma through the AKT and NF-kappa B pathways[END_REF], head and neck [START_REF] Chang | PTX3 gene activation in EGF-induced head and neck cancer cell metastasis[END_REF], cervical [START_REF] Ying | Knockdown of Pentraxin 3 suppresses tumorigenicity and metastasis of human cervical cancer cells[END_REF], and gastric [START_REF] Choi | Pentraxin-3 silencing suppresses gastric cancer-related inflammation by inhibiting chemotactic migration of macrophages[END_REF] cancers. Similar to our findings, studies have also correlated high levels of tissues and/or circulating PTX3 in patients with lung [START_REF] Diamandis | Pentraxin-3 is a novel biomarker of lung carcinoma[END_REF], breast [START_REF] Margheri | Systemic sclerosis-endothelial cell antiangiogenic pentraxin 3 and matrix metalloprotease 12 control human breast cancer tumor vascularization and development in mice[END_REF], ovarian [START_REF] Tothill | Novel molecular subtypes of serous and endometrioid ovarian cancer linked to clinical outcome[END_REF], pancreatic [START_REF] Kondo | Clinical impact of pentraxin family expression on prognosis of pancreatic carcinoma[END_REF], liver [START_REF] Carmo | Genetic variation in PTX3 and plasma levels associated with hepatocellular carcinoma in patients with HCV[END_REF], glioma [START_REF] Locatelli | The long pentraxin PTX3 as a correlate of cancer-related inflammation and prognosis of malignancy in gliomas[END_REF], and prostate [START_REF] Ravenna | Up-regulation of the inflammatory-reparative phenotype in human prostate carcinoma[END_REF] tumors. In addition, PTX3 represents an effector of oncogenic PI3K signaling that maintains stem cell-like traits in basal-like breast cancers [START_REF] Thomas | Pentraxin-3 is a PI3K signaling target that promotes stem cell-like traits in basal-like breast cancers[END_REF]. Collectively, these observations suggest that PTX3 represents a pleiotropic cancer biomarker and a cell context-dependent therapeutic target.

Chronic inflammation is implicated in tumorigenesis and metastasis through the recruitment and activation of TAMs that produce inflammatory cytokines, such as TNFα, which in turn activate the NF-kB pathway [START_REF] Coussens | Inflammation and cancer[END_REF][START_REF] Karin | NF-kappaB: linking inflammation and immunity to cancer development and progression[END_REF]. In melanoma, TNFα was shown to promote NF-kB-dependent BRAF inhibitor resistance [START_REF] Shao | NF-kappaB regulation of c-FLIP promotes TNFalpha-mediated RAF inhibitor resistance in melanoma[END_REF] and to suppress MITF expression, thereby initiating an inflammation-induced dedifferentiation program [START_REF] Riesenberg | MITF and c-Jun antagonism interconnects M. Rathore et al. melanoma dedifferentiation with pro-inflammatory cytokine responsiveness and myeloid cell recruitment[END_REF]. Of note, MITF low invasive melanoma cells were also found to secrete high amounts of other inflammatory factors, such as IL-6 (Supplementary Fig. 1 and Supplementary Table 1), which has been involved in TWIST-dependent cell invasiveness [START_REF] Na | Interleukin-6-induced Twist andx N-cadherin enhance melanoma cell metastasis[END_REF], and our in silico analysis associated high PTX3 expression in melanoma with a hallmark inflammatory response gene signature. Our experiments further indicate that targeting PTX3-induced IKK/NF-kB pathway is effective to reduce melanoma cell migration. This adds to the list of signaling pathways that contribute to the regulation of the invasive abilities of melanoma cells. Altogether, our data support a model in which a subpopulation of metastatic melanomas have acquired an autoinflammatory-like phenotype characterized by an autoamplifying PTX3/TLR4/NF-kB invasive signaling pathway.

In summary, our study supports a key role of tumorderived PTX3 for melanoma migration and provides a rationale for targeting PTX3-mediated NF-kB invasive signaling as part of a novel therapeutic approach to treat the metastatic disease.

Materials and methods

Cells, reagents, and plasmids

A375, 1205Lu, MeWo, WM35, WM793, and SKMel28 melanoma cell lines were from ATCC. 1205Lu cells that were engineered to express a luciferase reporter (1205Lu-Luc + cells) were described before [START_REF] Tichet | Tumour-derived SPARC drives vascular permeability and extravasation through endothelial VCAM1 signalling to promote metastasis[END_REF]. Other melanoma cell lines and patient melanoma cells were obtained as described before [START_REF] Didier | Targeting the proteasome-associated deubiquitinating enzyme USP14 impairs melanoma cell survival and overcomes resistance to MAPK-targeting therapies[END_REF]. All cell lines were tested and found to be mycoplasma-negative. Melanoma cells were cultured in Dulbecco's modified Eagle Medium (DMEM) plus 7% Fetal Bovine Serum (FBS) (Thermo Fisher Scientific). Conditioned media (CM) from melanoma cells were prepared as previously described [START_REF] Tichet | Tumour-derived SPARC drives vascular permeability and extravasation through endothelial VCAM1 signalling to promote metastasis[END_REF].

Human umbilical vascular endothelial cells (HUVECs) were cultured in complete EGM2 Bullet Kit medium supplemented with 2% FBS and full supplements (Lonza). All other culture reagents and Cell Tracker dyes were from Thermo Fischer Scientific. The source for other reagents was as follows: recombinant human PTX3 (Bio-Techne), MYD88 Inhibitor peptide (NOVUS Biologicals), IKK inhibitor BMS345541 (Selleckchem), chemicals (Sigma-Aldrich). The PTX3 complementary DNA was amplified by PCR from 1205Lu cells using the primers: Fwd: ACTCG AGCCACCATGCATCTCCTTGCGATTCTG; Rev: TAG GATCCTTATGAAACATACTGAGCTCCT and subcloned in the pIRES2-EGFP vector (Takara) using BamHI/ XhoI restriction sites to generate the pPTX3-IRES-EGFP vector. The PTX3-IRES-EGFP cassette was subsequently subcloned into the pLPCX retroviral vector using XhoI/NotI restriction sites to generate the pLPCX-PTX3-pIRES2-EGFP vector. 501Mel-CTRL and 501Mel-PTX3 cells were obtained following pIRES2-EGFP and pPTX3-IRES-EGFP transfection, respectively and geneticin selection. SKMel28-CTRL and SKMel28-PTX3 were generated by retroviral transduction with pLPCX and pLPCX-PTX3-IRES2-EGFP, respectively, and puromycin selection. The NF-κB luciferase reporter vector was from BPS Bioscience.

RNAi studies

Negative control and PTX3 siRNA duplexes were designed by Thermo Fisher Scientific. MITF (sc-35934), MYD88 (sc-35986), and TWIST1 (sc-38604) siRNAs were from Santa Cruz Biotechnology. IKKα, IKKβ, and TLR4 siRNAs were from Dharmacon (CO, USA). Transfection of siRNA was carried out using Lipofectamine RNAiMAX (Thermo Fisher Scientific) at a final concentration of 25 or 50 nM. Unless stated otherwise, cells were assayed 3 days post transfection. Lentiviral vectors for stable knockdown of PTX3 (NM_002852) in melanoma cells were TRC1.5-pLKO.1-puro vectors (shPTX3-1 to 5) (Genomic center, University of Minnesota, USA). Lentiviral, packaging (psPAX2) and enveloppe (pMD2.0 G) vectors were transfected into HEK293T cells and viruscontaining supernatant fractions were harvested after 72 h. The supernatant fractions were filtered and used to infect bioluminescent 1205Lu cells (1205Lu-Luc + ) that were described before [START_REF] Tichet | Tumour-derived SPARC drives vascular permeability and extravasation through endothelial VCAM1 signalling to promote metastasis[END_REF]. Transduced cells were selected with 2 µg/ml puromycin for 3 weeks. The efficiency of PTX3 knockdown was assessed by immunoblotting and analysis of in vitro cell migration using modified Boyden chambers. The PTX3 knockdown cells that were selected for in vivo studies were transduced by lentivirus harboring the shPTX3-5 sequence (TRCN0000149744, 5ʹ-CCGGGAGG AGCTCAGTATGTTTCATCTCGAGATGAAACATACT-GAGCTCCTCTTTTTTG-3ʹ).

Immunohistochemistry and immunoblot analysis

Immunohistochemistry and immunoblot analysis were performed as described before [START_REF] Tichet | Tumour-derived SPARC drives vascular permeability and extravasation through endothelial VCAM1 signalling to promote metastasis[END_REF]. IHC analysis was performed on melanoma tissue microarrays (US Biomax) using PTX3 antibody (HPA069320, Sigma-Aldrich; 1:50). For immunoblotting, the following antibodies were used at 1:1000: SPARC (Bio-Techne), PTX3 (Enzo Life Sciences, Switzerland), HSP90, HSP60, TLR4, Fibronectin, ERK2 (Santa Cruz Biotechnology), MITF (Thermo Fisher Scientific), TWIST1 (Abcam, UK), SNAIL, phospho-IKKα/β (Ser176/180), NF-kB p65, phospho-NF-kB p65 (Ser536), IκBα (L35A5), phosphor-IκBα (Ser32/36), IKKα, IKKβ, MYD88, phospho-AKT (Ser473), phospho-ERK1/2 (Thr202/Tyr204), phospho-PRAS40 (Thr246), phospho-c-Jun (Ser63) (Cell Signaling Technology).

Migration, invasion, and in vitro scratch assays

Serum-stimulated chemotaxis, invasion, and transendothelial migration were monitored using modified Boyden chambers (8 µm pores, Sigma) as described before [START_REF] Tichet | Tumour-derived SPARC drives vascular permeability and extravasation through endothelial VCAM1 signalling to promote metastasis[END_REF]. For invasion assays, the upper side of the filter was coated with 0.5 mg/ml matrigel (Corning, NY, USA). Migrated cells were stained with crystal violet and counted (four fields randomly per well). For transendothelial migration, 10 5 HUVECs were grown in the upper chamber of gelatincoated Transwell inserts and treated with human TNFα (10 ng/ml) for 16 h. Melanoma cells were allowed to migrate for 6 h and migrated cells were visualized and quantified as before [START_REF] Tichet | Tumour-derived SPARC drives vascular permeability and extravasation through endothelial VCAM1 signalling to promote metastasis[END_REF]. Pictures of five random fields were captured for quantification using NIH ImageJ analysis software. For scratch assays, melanoma cells were grown ~80% confluence in 6-well plates. Wounds were generated using a sterile 200 μl pipette tip across each well. Following treatment with rhPTX3 or CM, pictures of four random fields were captured using an imaging station and the number of migrated cells in wounded area was counted with NIH ImageJ analysis software.

Spheroid invasion assay and zymography

Melanoma three-dimensional (3D) spheroids were generated as described [START_REF] Bailet | Spleen tyrosine kinase functions as a tumor suppressor in melanoma cells by inducing senescence-like growth arrest[END_REF]. Pictures of migrating cells were taken at day 0 and day 3. Relative invasion was determined using the ImageJ software as the ratio between migration area at day 3 and migration area at day 0. CM from melanoma cells were analyzed by collagen zymography as previously described [START_REF] Robert | SPARC represses E-cadherin and induces mesenchymal transition during melanoma development[END_REF].

Promoter reporter assay

Melanoma cells were transfected with NF-κB-luciferase and β-Galactosidase reporter plasmids. Forty-eight hours after transfection, cells were lysed and luciferase and β-galactosidase activities were measured as described before [START_REF] Fenouille | Thep53/p21(Cip1/ Waf1) pathway mediates the effects of SPARC on melanoma cell cycle progression[END_REF]. Relative NF-κB promoter activity was calculated following normalization against β-galactosidase activity.

In vivo experiments and immunostaining

All mouse experiments were carried out in accordance with the Institutional Animal Care and local ethics committees. For experimental lung metastasis studies, 5-week-old female nude mice (Harlan) were intravenously injected with 1205Lu-Luc+ cells (1 × 10 6 ) that were transduced with a non-targeting shRNA lentivirus (shCTRL) or a PTX3targeting shRNA lentivirus (shPTX3-5). Images were acquired using a Photon Imager (Biospace Lab) on mice injected i.p. with 50 mg/kg D-luciferin (PerkinElmer). Lung metastasis was monitored and quantified using BLI [START_REF] Tichet | Tumour-derived SPARC drives vascular permeability and extravasation through endothelial VCAM1 signalling to promote metastasis[END_REF]. In a second set of experiments, short-term lung colonization assays were performed with Cell Tracker Orange-stained 501Mel cells stably expressing PTX3 or not. Cells were intravenously injected in 5-week-old female nude mice that were sacrificed either 30 min or 24 h later. Lungs were perfused with PBS, fixed in 4% paraformaldehyde, OCTembedded, cryosectioned, immunostained and imaged using a confocal microscope as described [START_REF] Tichet | Tumour-derived SPARC drives vascular permeability and extravasation through endothelial VCAM1 signalling to promote metastasis[END_REF].

ELISA assay

The levels of PTX3 in CM of melanoma cell lines or in human serum samples were measured using the human PTX3 Quantikine ELISA kit (Bio-Techne) as per the manufacturer's protocol. Serum samples were obtained from consenting metastatic melanoma patients through the Dermatology Department of Nice University Hospital (Nice, France) or from healthy volunteers as controls. Results are from two independent experiments performed in triplicate.

Analysis of gene expression from human databases

Publicly available gene expression data sets of human melanoma samples were used to analyze PTX3 levels in melanoma progression (GSE3189). From GEO database, we also examined the Mannheim (GSE4843), Philadelphia (GSE4841), and Zurich (GSE4840) cohorts. Proliferative and invasive melanoma subgroups were defined according to literature mined gene signatures [START_REF] Widmer | Systematic classification of melanoma cells by phenotype-specific gene expression mapping[END_REF]. Gene expression of PTX3 was also examined in data sets derived from patient tumor biopsies before and after development of drug resistance to Vemurafenib (GEO accession number GSE50535) [START_REF] Sun | Reversible and adaptive resistance to BRAF(V600E) inhibition in melanoma[END_REF]. Normalized data were analyzed using GraphPad Prism (GraphPad software, CA, USA). Survival data from the skin melanoma TCGA database were retrieved using cBioPortal (cbioportal.org). Gene set enrichment analysis (GSEA) was performed as described before [START_REF] Ohanna | Pivotal role of NAMPT in the switch of melanoma cells toward an invasive and drug-resistant phenotype[END_REF].

Statistical analysis

  Furthermore, values extracted from additional GEO databases revealed that PTX3 expression increased in MITF low cells compared to MITF high cells (GSE62526 and c

Fig. 2

 2 Fig. 2 Expression of PTX3 in malignant melanoma. a Box and Whisker plots (10th to 90th percentile) show PTX3 mRNA expression in metastatic vs. benign skin lesions (nevi) (GSE3189). P-values were calculated by unpaired two-tailed Mann-Whitney test. b Kaplan-Meier overall survival and disease-free survival curves for melanoma patients with or without PTX3 alterations (PTX3 amplifications and mRNA upregulation). Data were retrieved from the skin melanoma TCGA database using cBioPortal (cbioportal.org). Data were restricted to AMP EXP ≥ 2 to exclude patients with PTX3 deletion. Median months survival: 28 vs. 94.9 (P = 9.872e-3, logrank test). Median months Disease-free: 25.5 vs. 51.4 (P = 0.0151, logrank test). c Gene set enrichment analysis (GSEA) of genes that positively (red) or negatively (blue) correlate with PTX3 expression in skin melanoma TCGA database. Data represent plots for the top two gene sets most significantly enriched. d Immunohistochemical analysis of PTX3

Fig. 3

 3 Fig. 3 Increased PTX3 expression in BRAF inhibitor mesenchymal resistant melanoma. a Immunoblot analyses of PTX3 expression in isogenic pairs of sensitive (M229S, M238S) and vemurafenib-resistant melanoma cells (M229R, M238R). Total cell lysates were immunoblotted with antibodies against PTX3, MITF, PDGFR-β, Fibronectin, and HSP90 as a loading control. b ELISA analyses of PTX3 secretion in CM derived from the above sensitive and resistant melanoma cells. PTX3 levels in CM were normalized against the amount of cellular proteins in each condition. Data represent the mean concentration of PTX3 in CM ± s.e.m of duplicate determinations. **P < 0.01; ***P < 0.001 as determined by two-way ANOVA and Bonferroni post-tests. c PTX3 gene expression levels in data sets (GSE5053) derived from three-paired tumor biopsies of melanoma patients before (Pre) and after (Post) development of resistance to BRAF inhibitors. d CM was prepared from melanoma cell cultures derived from one patient before (Pre) and after (Post) development of drug resistance and immunoblotted with PTX3 and Fibronectin antibodies. Ponceau staining was used as a loading control for secreted proteins

Fig. 4

 4 Fig. 4 Melanoma-derived PTX3 promotes tumor cell migration. a A375, 1205Lu, M229R, M238R, and patient-derived (Pt1) melanoma cells were transfected with siCTRL or two different siPTX3. After 3 days, serum-stimulated migration assays were performed for 4 h using Transwell inserts. Bar graphs show mean number of migrated cells ± s.e.m (n = 3 independent experiments). Lower panel: CMs from transfected cells were immunoblotted with anti-PTX3. b Transwell migration assays for melanoma cells (501Mel, SKMel28) stably expressing PTX3 were performed for 16 h. Bar graphs show mean ± s. e.m (n = 3 independent experiments). PTX3 immunoblots are shown in lower panel. c A375 and 1205Lu cells were transfected with siCTRL or siPTX3. After 3 days, Transwell migration assays were performed in the presence or not of rhPTX3 (100 ng/ml). Bar graphs represent mean ± s.e.m (n = 3 independent experiments). d Confluent

Fig. 5

 5 Fig. 5 PTX3 increases melanoma invasiveness in vitro. a Transwell invasion assays were performed on siCTRL and siPTX3 transfected cells (1205Lu, A375, M229R) obtained from transfections performed for migration assays (Fig. 4a). Cells were left to migrate for 6 h and counted. Bar graphs show mean number of invaded cells ± s.e.m (n = 3 independent experiments). b 1205Lu cells were transfected with siCTRL or siPTX3 as described above. After 3 days, serum-stimulated Transwell invasion assays were performed in the presence or not of rhPTX3 (100 ng/ml). Images of one representative insert out of three are shown (left). Bar graphs represent mean ± s.e.m (n = 2 independent experiments) (right). c Transwell invasion assay was performed as above on SKMel28 cells stably expressing PTX3 or not from Fig. 4b. Cells were left to migrate for 6 h and counted. Bar graphs show mean number ± s.e.m (n = 3 independent experiments). d Three-dimensional tumor spheroid invasion assay was performed on A375 cells

Fig. 6

 6 Fig. 6 PTX3 promotes melanoma invasiveness in experimental lung extravasation assay. a Immunoblot analysis of PTX3 expression on 1205Lu-Luc + control (shCTRL) and stable PTX3 knockdown (shPTX3-5) cells (see Supplementary Fig. 7 for details). HSP60 was used as a loading control. b shCTRL and shPTX3-5 1205Lu-Luc + were injected by tail vein into nude mice (n = 5 mice per group) and lung metastasic progression was monitored and quantified using a photon imager. Representative images of photon fluxes produced by bioluminescent melanoma cells from day 0 to day 15 are shown (left panels, n = 2) and normalized photon flux (BLI, right graph, n = 5) of lungs from control and PTX3-depleted cells. c Quantification of lung

Fig. 8

 8 Fig. 8 TLR4/MYD88 expression is required for PTX3induced melanoma cell migration. a Transwell migration assays were performed on 1205Lu cells transfected with siCTRL or two different siTLR4. Immunoblot analysis shows TLR4 depletion. HSP60, loading control. Bar graphs represent mean of migrated cells ± s.e.m (n = 3 independent experiments). b 1205Lu cells were transfected with siPTX3 or siTLR4. After 3 days, cells were stimulated or not with rhPTX3 for 4 h and Transwell migration assays were performed. Bar graphs show migration mean ± s.e.m (n = 2 independent experiments). c Transwell migration assays on control and MYD88-depleted 1205Lu cells. Bar graphs show migration mean ± s.e.m (n = 2 independent experiments). MYD88 and TWIST1 levels were controlled by immunoblot. d 1205Lu cells were treated with the IKK inhibitor BMS345541 and PTX3 expression was assessed by immunoblot. e Schematic model of PTX3 autocrine action on melanoma cell migration. ***P < 0.001, **P < 0.01 as determined by two-way ANOVA and Bonferroni post-tests

  Unless otherwise stated, all the experiments were repeated at least three times and representative data/images are shown. Statistical data analysis was performed using GraphPad Prism software. Unpaired two-tailed Mann-Whitney tests or two-way ANOVA tests with Bonferroni post-tests were used for statistical comparisons. Error bars are mean ± s.e.m.

Acknowledgements We thank RS Lo and R Ballotti for melanoma cells. We acknowledge the C3M animal and imaging (Microscopy and Imaging platform Côte d'Azur, MICA) facilities. This work was supported by Ligue Contre le Cancer, Fondation ARC, Fondation de France and the French Government (National Research Agency, ANR) through the "Investments for the Future" LABEX SIGNALIFE: program reference # ANR-11-LABX-0028-01. We also thank financial supports by Conseil Général des Alpes-Maritimes, Canceropôle PACA and Région PACA. MR was a recipient of a post-doctoral fellowship from Fondation ARC. The Marseille Proteomic facility (MaP; http:// map.univmed.fr/) is supported by IBiSA (Infrastructures Biologie Santé et Agronomie), Canceropôle PACA, Région PACA, and Institut Paoli-Calmettes.

Author contributions MD, STD, and MR designed the study. MD and STD wrote the manuscript. MR, CG, MT and RBJ performed the experiments and analyzed the data with the help of EG, FL, and VP. MG provided technical expertize in microscopy. SA performed mass spectrometry analyses. J-PL and HM contributed clinical samples and expertize.

Compliance with ethical standards

Conflict of interest The authors declare that they have no conflict of interest.

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Wilfried Thuiller
email: wilfriedthuiller@univ-grenoble-alpes.fr

Dominique Gravel

Francesco Gentile

Sébastien Ficetola

Tamara Lavergne

Laura Münkemüller

Niklaus Pollock

Florent Zimmermann

Mazel

Gentile Francesco Ficetola

Sébastien Lavergne

Tamara Münkemüller

Laura J Pollock

Niklaus E Zimmermann

Florent Mazel

Productivity begets less phylogenetic diversity but higher uniqueness than expected

Keywords:

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

INTRODUCTION

The increase in species richness with increasing primary productivity is one of the most consistent patterns in ecology, and one of few ecological patterns that holds across scales and vertebrate taxa [START_REF] Evans | Species-energy relationships at the macroecological scale: a review of the mechanisms[END_REF], as well as through geologic time [START_REF] Fritz | Twenty-million-year relationship between mammalian diversity and primary productivity[END_REF]. The processes behind this richness-productivity relationship have long been debated on the grounds of several ecological and evolutionary hypotheses on why there are more species in productive areas.

From an ecological perspective, productivity could directly impact the number of species through supporting higher densities, greater ecological heterogeneity, higher specialisation and larger total niche space [START_REF] Wright | Energy supply and patterns of species richness on local and regional scales. Species diversity in ecological communities: Historical and geographical perspectives[END_REF][START_REF] Currie | Predictions and tests of climate-based hypotheses of broad-scale variation in taxonomic richness[END_REF][START_REF] Evans | Species-energy relationships at the macroecological scale: a review of the mechanisms[END_REF][START_REF] Wright | Energy and spatial order in niche and community[END_REF][START_REF] Brown | Why are there so many species in the tropics?[END_REF][START_REF] Storch | The more-individuals hypothesis revisited: the role of community abundance in species richness regulation and the productivitydiversity relationship[END_REF]. However, from an evolutionary perspective, productivity could also influence diversification by either decreasing species' extinction rates or by enabling higher in situ speciation rates due to higher population densities and thus faster rates of molecular evolution [START_REF] Rosenzweig | Species Diversity in Space and Time[END_REF][START_REF] Allen | Assessing latitudinal gradients in speciation rates and biodiversity at the global scale[END_REF], stronger biotic interactions or higher ecological opportunities [START_REF] Schemske | Is There a Latitudinal Gradient in the Importance of Biotic Interactions?[END_REF][START_REF] Schluter | Speciation gradients and the distribution of biodiversity[END_REF][START_REF] Rabosky | An inverse latitudinal gradient in speciation rate for marine fishes[END_REF]. In all cases, evolutionary trajectories were substantially altered by periods of historical environmental stability and by glaciation cycles in some regions, which are relevant to understanding the productivitydiversity relationship. For instance, the latitudinal gradient hypothesis posits that climatic variation (e.g. glaciation cycles) in temperate regions may have led to large-scale extinction events and potentially enhanced speciation [START_REF] Weir | The latitudinal gradient in recent speciation and extinction rates of birds and mammals[END_REF]. This would imply that regions of low productivity and major glaciations could harbor species assemblages that have originated largely from speciation during these cycles. The different ecological and evolutionary explanations cannot be disentangled when focussing simply on species (or genus) richness because they all expect more species in highly productive areas. Only when combining species diversity with additional biodiversity metrics can further our understanding of the relevant processes. Here, we re-examine the productivity-diversity relationship in the light of the evolutionary history of vertebrate species and the resulting phylogenetic diversity patterns. We provide a novel understanding of why increasing primary productivity leads to higher diversity in some regions but not in others.

The above mentioned ecological and evolutionary processes are expected to result in a broad range of geographic and phylogenetic patterns of biodiversity that we can observe today. This includes both the diversity of species assemblages in local areas (so we can ask: are the species in an assemblage phylogenetically closely or rather distantly related?) and characteristics of individual species (so we can ask: does a species belong to a rapidly diversifying group with many closely related species or does it belong to a phylogenetically distinct, species poor lineage?). For example, if net primary productivity (NPP) promotes diversification through increased in situ speciation, we then would expect to see increasing densities of closely related species belonging to rapidly radiating clades in local species assemblages. However, if NPP promotes diversification through reduced extinction rates, we would also expect to observe species that are phylogenetically more distinct, as "old" lineages could have survived. In contrast and from an ecological perspective, if high NPP regions increase the available niche space and allow for narrower niche partitioning and species' niches are phylogenetically conserved [START_REF] Lavergne | Biodiversity and climate change: Integrating evolutionary and ecological responses of species and communities[END_REF], we would expect significantly higher phylogenetic diversity (when correcting for species richness) and higher numbers of phylogenetically distinct species in high compared to low NPP regions (see Table 1 for a summary of the expectations).

Studying the multiple imprints of ecological and evolutionary processes on species' assemblages can cast novel insights into our understanding why species richness often scales positively with productivity. Here, we propose to complement the widely reported positive species richness-productivity relationship by documenting how productivity correlates with phylogenetic diversity, the richness of top evolutionary distinct species and the richness of top species-level lineage diversification rates. As these three complementary measures are inherently influenced by species richness, they need to be corrected by species richness to be useful for further interpretation.

Thus, we here analyse how the worldwide spatial distribution of richness corrected phylogenetic diversity (i.e. relative phylogenetic diversity, rPD hereafter), the relative richness of the top 25% most evolutionarily distinct (ED) species and of species with the fastest species-level lineage diversification rates (DR) in terrestrial amphibians, birds and mammals relates to the distribution of net primary productivity (NPP). We considered NPP since it is a suitable measurement of primary energy production metric for investigating consumer species-energy relationships and consistency in productivity-richness studies [START_REF] Evans | Climate change: implications for insect pests. Climate change: impacts on UK forests[END_REF]. We also tested whether patterns observed at the global scale hold within zoogeographical regions [regions harbouring relatively homogenous species assemblages from a taxonomic and phylogenetic viewpoint [START_REF] Holt | An Update of Wallace's Zoogeographic Regions of the World[END_REF]]. We thus conducted this analysis at both the global scale and within the different zoogeographic regions of the world [START_REF] Holt | An Update of Wallace's Zoogeographic Regions of the World[END_REF] but also by varying the spatial extent of the species pool considered when calculating rPD [START_REF] Kissling | Quaternary and pre-Quaternary historical legacies in the global distribution of a major tropical plant lineage[END_REF]. Finally, we tested whether those trends are driven by the response of specific lineages within the three main vertebrate taxa considered.

We addressed these objectives by using geographic range maps of amphibians, birds and mammals of the world from the IUCN Red List Assessment and from BirdLife (at 200km resolution), combined with comprehensive sets of species-level phylogenies for the three groups.

METHODS

Distribution data -We used the distribution maps provided by the Amphibian and Mammal Red List Assessment (http://www.iucnredlist.org/) for 5547 and 4616 species, respectively. For birds, breeding ranges distribution maps were extracted from BirdLife (http://www.birdlife.org/) for 9993 species. Since the best resolution to use these maps is still under discussion in the literature, we used a 200x200km resolution (equal-area projection), which is the most commonly used at the global scale [START_REF] Hurlbert | Species richness, hotspots, and the scale dependence of range maps in ecology and conservation[END_REF][START_REF] Ficetola | An evaluation of the robustness of global amphibian range maps[END_REF][START_REF] Pollock | Large conservation gains possible for global biodiversity facets[END_REF]. The total number of grid cells was 3646. Domestic and fully aquatic species were excluded from the analysis.

Net primary productivity -NPP was extracted from the Socioeconomic Data and Applications

Center -A data center in NASA's Earth Observing System Data and Information System. NPP is measured in units of elemental carbon (grams of carbon per year per pixel) and represents the primary energy source for secondary productivity. This data set is distributed by the Columbia University Center for International Earth Science Information Network (CIESIN, [START_REF] Imhoff | Global patterns in human consumption of net primary production[END_REF][START_REF] Imhoff | Exploring global patterns of net primary production carbon supply and demand using satellite observations and statistical data[END_REF]).

Zoogeographic regions [START_REF] Holt | An Update of Wallace's Zoogeographic Regions of the World[END_REF] defined zoogeographic regions as regions of evolutionarily unique assemblages, with distinct regionalization for the three classes. The classification of vertebrate assemblages into zoogeographic units was done to get between 6 (amphibians and birds) and 8 regions (mammals) to be consistent between the three groups (see Fig. S2 for the distribution and naming of the zoogeographic regions). Regions were then converted to a raster with a 200 km resolution.

Phylogenetic trees -We used a random set of 100 time-calibrated, ultrametric phylogenetic trees from [START_REF] Bininda-Emonds | The delayed rise of present-day mammals[END_REF][START_REF] Fritz | Geographical variation in predictors of mammalian extinction risk: big is bad, but only in the tropics[END_REF] and from [START_REF] Jetz | Global Gradients in Vertebrate Diversity Predicted by Historical Area-Productivity Dynamics and Contemporary Environment[END_REF], respectively for both mammals and birds. We updated the mammal phylogenetic trees by replacing the Carnivora clade with a highly resolved supertree published more recently [START_REF] Nyakatura | Updating the evolutionary history of Carnivora (Mammalia): a new species-level supertree complete with divergence time estimates[END_REF]. For amphibians, we used the single supertree available for all amphibians of the world [START_REF] Isaac | Phylogenetically-Informed Priorities for Amphibian Conservation[END_REF].

Phylogenetic metrics -Phylogenetic diversity (PD) was calculated for each single pixel as "the branch length sum of all branches that are members of the corresponding minimum spanning path", in which 'branch' is a segment of a tree, and the minimum spanning path is the minimum patristic distance between nodes including the roots [START_REF] Faith | Conservation evaluation and phylogenetic diversity[END_REF][START_REF] Faith | Quantifying biodiversity: a phylogenetic perspective[END_REF]. PD was estimated using each of the the richness-controlled version of PD (called relative PD hereafter, rPD), we used the PhyloMeasures package in R [START_REF] Tsirogiannis | PhyloMeasures: a package for computing phylogenetic biodiversity measures and their statistical moments[END_REF]. For each single assemblage (pixel in this study), the observed PD value is compared to an expected distribution of possible PD values derived from a particular null model. In our case, we used a null model where the species richness of the assemblage, the species pool phylogenetic tree topology and branch lengths are held constant but tip labels are shuffled (see below for various definition of the species pool). The rPD value is obtained by subtracting the mean expected PD and then dividing it by the expected PD standard deviation. Note that these rPD values are also sometimes approximated using a randomization procedure (e.g. randomly shuffling the tree tip labels 1000 time to compute the expected PD distribution). However, the exact rPD values provided by the PhyloMeasures R package is preferred here because of reduced computational time.

We measured species evolutionary distinctiveness (ED) as the sum of the branch length from the species tip to the root of the tree divided by the number of species subtended to each branch (function evol.distinct in R package picante, measure 'equal-split' [START_REF] Redding | Measuring Evolutionary Isolation for Conservation[END_REF]. We measured species-level lineage diversification rates (DR) as the inverse of the species' distinctiveness measure (see Jetz et al., 2012) for a complete description of the measure and its relationships with traditional clade level diversification rates).

Richness of the top most evolutionarily distinct species (top ED) and of the highest species-level lineage diversification rates (top DR) was computed as the number of species that belong to the top 25% of each of the two classes. Since these measures correlate positively with total species richness by pure sampling effects, we ran a null model in which the distinctiveness and diversification measures were randomised among species. The richness of the top 25% species was then recalculated. The null model was repeated 999 times and the standardised effect size in richness of the top 25% evolutionary distinctiveness (SES of top ED) and top 25% species-level lineage diversification rates (SES of top DR) was calculated by subtracting the mean richness and dividing it by the standard deviation of this measure. Note that while ED and DR are mathematically linked by calculation, this is not the case when focusing on the richness of the standardised effect size of the top 25% species from each group and there are no a priori expectations on their relationships.

Spatial extents for the sampling pools

The three metrics (rPD, SES of top ED and SES of top DR) were initially calculated using a global species pool. In other words, the analytical solution for rPD and the null models for SES of top ED and top DR considered that under random expectation, every species could occur everywhere, independent of dispersal constraints and historical contingencies. Since a global species pool might seem too liberal, we also calculated the three metrics for two other species pools following [START_REF] Kissling | Quaternary and pre-Quaternary historical legacies in the global distribution of a major tropical plant lineage[END_REF]. In the first case, we considered a hemispheric species pool ('New World' and 'Old World') and, in the second case, we considered the zoogeographic regions themselves. Practically, rPD, SES of top ED and top DR were thus also calculated against random expectation coming from the appropriate species pool. For instance, for pixels occurring in Europe, the species pool for the hemispheric case was 'Old World', and North Hemisphere for the zoogeographic species pool.

Varying the extent of the species pool allows for testing whether, within a continent or a zoogeographic region, the relationship between our three metrics and NPP widely differ or not, with consequences for the interpretation of the observed patterns [START_REF] Kissling | Quaternary and pre-Quaternary historical legacies in the global distribution of a major tropical plant lineage[END_REF].

Statistical analyses

Standard ordinary least square regressions were run between rPD, SES of top ED, SES of top DR, and NPP at the global scale, and for each of the zoogeographic regions. We then extracted the adjusted R 2 values of the regressions. For mammals and birds, regression analyses were carried out for the 100 available trees. We thus reported mean R 2 and the associated standard errors. In the main text, we represented the relationship between NPP and our three metrics per zoogeographical regions with a global species pool for Fig. 1, 3 and 4, and while varying the spatial extent of the species pool in Fig. 2. rPD strongly varied in space and between the different groups (Fig. 1). A striking common result among the three taxa was that rPD took generally negative values across the globe (i.e. lower than the expected PD given the species richness of the assemblage). For both birds and mammals, less than 1% of the cells were actually positive, against ~20% for amphibians. This was expected given the spatial structuring of phylogenetic groups at global scales [START_REF] Holt | An Update of Wallace's Zoogeographic Regions of the World[END_REF], which implies that local assemblages harbour less PD than randomly expected (e.g. [START_REF] Mazel | Mammalian phylogenetic diversity area relationships at a continental scale[END_REF]. Some regions consistently host much lower PD than expected, like Indonesia and South America (notably around the Andes). Those regions either harbour relatively closely related species that belong to a single group in the phylogeny or several distinct groups distributed across the phylogeny.

Group specific results showed that rPD of mammals and amphibians was negatively related to NPP (Fig. 1, Fig. S3 for the general trends with R 2 =0.54 and 0.29 for amphibians and mammals, respectively, Table S1A, B), with the lowest peaks in Madagascar, south-east Brazil and Indonesia for amphibians and in western US, western South-America and Indonesia for mammals. Thus, the most phylogenetically diverse assemblages (with respect to species richness) were consistently found in areas with low NPP. This result was consistent across the 100 phylogenetic trees analysed for mammals (data limitations prevented this test for amphibians). In contrast, rPD of birds was the lowest in the Andes, Himalaya and northern America, and was weakly negatively related to NPP (R 2 =0.03), irrespective of phylogenetic uncertainty (Fig. 1, Fig. S3, Table S1B).

Focusing on each zoogeographical region reveals diverging distribution patterns in birds compared to the other groups. While for birds there was by tendency a negative relationship between rPD and NPP in five regions (R 2 =0.41 for Africa, Table S1B), a single large region ('North America') displayed a weak but positive relationship between rPD and NPP (Fig. 1, Table S1B). This relatively large outlier region explains the globally weak relationship between rPD and NPP for birds. Interestingly, a similar observation occurred for mammals for the 'US' region. However, as this region is relatively small, it did not change the entire relationship much. In summary, the relationship between rPD and NPP was consistently negative both at the global and at the zoogeographic region scales, except for a zoogeographic region around North America for both birds and mammals (Table S1).

The observed relationship between NPP and evolutionary history was not constant across major lineages (Fig. S4 A-C). For amphibians, the three orders (Anura, Gymnophiona and Caudata) showed a coherent distribution of evolutionary history across the different zoogeographical regions (Fig. S4 A). However, for both birds and mammals, our analyses show that some particular orders diverge from the average relationship (Fig S4 B -C). For birds, the rPD of Passeriformes and Psittaciformes was strongly negatively correlated with NPP (Fig. S4 B), while for mammals the relationship between rPD and NPP was even positive for one group (Cetartiodactyla). Striking differences appeared between orders within zoogeographic regions. The positive relationship between rPD and NPP in 'US' and 'North Hemisphere' was indeed driven by the Apodiformes, Charadriiformes, and Galliformes for birds, which are non-passeriformes (Fig. S4 B), and by the Rodentia and Soricomorpha for mammals (Fig. S4 C).

Interestingly, varying the spatial extent of the species pool to estimate relative phylogenetic diversity did not clearly change the overall patterns (Fig. 2). There were strong consistencies between the results obtained with the global and hemispheric species pools. Despite few notable exceptions (South America for both birds and mammals), the relationships between rPD and NPP was similarly negative or positive (i.e. US for mammals and North America for birds). For South America, there was a drastic shift from a strong negative to a strong positive relationship between rPD and NPP for both birds and mammals. For amphibians, the results did not differ much across the three spatial extent of the species pool. Only for the zoogeographic species pool, the overall estimated relationships between rPD and NPP were rather weak in most cases, while still generally consistent with the overall pattern calculated with the global species pool (Fig. 2). Therefore, we will only present results from the global species pool for all further analyses.

The analysis of the relationship between NPP and the standardized effect sizes of the top 25% species regarding evolutionary distinctiveness (SES of top ED) and of the top 25% fastest specieslevel lineage diversification rates (SES of top DR) (both measured on the global phylogenies of the three clades) allows to evaluate whether regions of high NPP also hold more evolutionarily distinct species and more species with higher diversification rates than expected (cf. table 1). Both measures reveal strong relationships with NPP for birds and mammals but not for amphibians (Fig. 3 &4, Fig. S5 & S6 for the general trends). For the former two groups, and consistently across zoogeographical regions, areas of high NPP harbour fewer species than expected among the top DR (Fig. 3, Fig. S5). Interestingly, for the three groups, areas with more species than expected from the top DR are only found in the Northern Hemisphere (with few exceptions in extreme western South Americas) (Fig. 3). Reciprocally, more species than expected from the top ED are found with increasing NPP (Fig. 4, Fig. S6). In general, striking differences exist in the distribution of SES of top ED and SES of top DR for both birds and mammals (Fig. 3 & 4, Fig. S5 & S6), while this relationship is not as clear when considering the absolute richness of top ED and DR (Fig. S7). For instance for birds, central Africa and Madagascar, Indonesia and Australia were hotspots of evolutionary distinctiveness (with respect to species richness) but also coldspots of species-level lineage diversification rates (see Fig. S7 for the absolute richness). A similar pattern emerged for mammals, where South America (i.e. the Amazonian forest), Australia and Southern Africa (and Madagascar) were hotspots of evolutionary distinctiveness (with respect to species richness) but coldspots of species-level lineage diversification rates (see Fig. S7 for the absolute richness).

However, despite slight differences in the relative numbers, the distribution of the two metrics was relatively similar between the two groups. For amphibians, the relationships were more homogenous except for the North Hemisphere, where North America hosts a high proportion of top DR but a low proportion of top ED. The opposite pattern emerges for Northern Europe and Russia (Fig. 3 &4).

In this paper, we proposed to test if the commonly-observed positive species richnessproductivity relationship also holds for phylogenetic diversity, the richness of the top most evolutionarily distinct species and the richness of the top highest species-level lineage diversification rates. After controlling for species richness, we found that regions with higher productivity harbour relatively lower phylogenetic diversity, have an unexpectedly high number of evolutionarily distinct species and an unexpectedly low number of species belonging to rapidly diversifying clades.

These seemingly contradictory results provide new insights into the processes that drive the relationship between vertebrate diversity distribution and ecosystems' primary productivity. The observation that highly productive sites harbour much lower rPD scores than expected suggests that elevated NPP (i) promotes radiations in certain parts of the tree of life, and/or (ii) promotes the coexistence of closely related species [START_REF] Evans | Species-energy relationships at the macroecological scale: a review of the mechanisms[END_REF]. However, the relatively low number of species belonging to rapidly diversifying clades in sites of high NPP suggests that rapid diversification might not necessarily be a mechanism that drives the relationship between rPD and NPP (see also [START_REF] Schluter | Speciation, Ecological Opportunity, and Latitude[END_REF]. Rather, more local ecological processes that we cannot capture at our coarse resolution (filtering or niche partitioning) could be key in structuring assemblages, at least in high NPP regions. Interestingly, those regions also harbour a higher than expected richness in evolutionarily most distinct species, suggesting that extinction might be reduced under these conditions. This finding is consistent with the hypothesis that the greater combined age and expansion of highly productive regions (usually tropical forest) have facilitated greater species accumulations without necessarily facilitating greater rates of speciation, yet by simply packing more species per unit of space and by a reduced extinction rate (Jetz et al., 2012;[START_REF] Belmaker | Relative roles of ecological and energetic constraints, diversification rates and region history on global species richness gradients[END_REF].

Low NPP regions harbour relatively high rPD, while having an unexpectedly low number of evolutionarily distinct species and a high number of species belonging to clades with high diversification rates. This means that these areas harbour phylogenetically relatively distant species (e.g. sister species are unlikely to occur in the same pixel), but that these species belong to different disproportionately rapidly diversifying clades. Areas of high diversification rates are found throughout the northern hemisphere and the southwest of the South America zoogeographical regions (Fig. 3, see also Jetz et al., 2012). Those areas are known to host several of the rapidly diversifying clades (e.g. warblers, gulls, some rodent groups), have all been characterized by strong climatic fluctuations from the Pliocene to the present, have generally lower NPP than tropical areas, and were mostly glaciated and experienced the fastest climate change during the last 40,000 years.

In other words, the composition of these regions is the result of a recent assembly, rather than insitu evolution. Interestingly, most species in these low NPP regions have very broad ranges. We could hypothesize that low NPP regions were recolonized by certain distantly related but rapidly diversifying clades from more productive areas that have evolved broad niches and are better adapted to cold / less productive environments [START_REF] Wiens | Evolutionary and ecological causes of the latitudinal diversity gradient in hylid frogs: Treefrog trees unearth the roots of high tropical diversity[END_REF]. None of these mechanisms are mutually exclusive and their relative importance may likely vary with temporal and spatial scales.

In the era of Big Data, it becomes clear that long standing hypotheses and descriptive analyses need to be revisited in light of the increasing availability of data on species distribution and their phylogenetic relationships. Here, we build on the most up-to-date macroecological data for three vertebrate groups and analysed the relationships between their evolutionary history and net primary productivity of ecosystems. Our analysis should eventually be complemented with a more detailed modeling of diversification rates [START_REF] Schluter | Speciation gradients and the distribution of biodiversity[END_REF][START_REF] Rabosky | An inverse latitudinal gradient in speciation rate for marine fishes[END_REF]. Of course, a part of the non-explained variance in the regression analyses is likely due to the effects of other environmental variables (e.g. temperature) and could lead to more in-depth analyses to tease-apart their effects (but see [START_REF] Belmaker | Relative roles of ecological and energetic constraints, diversification rates and region history on global species richness gradients[END_REF]. We acknowledge that our analyses may suffer to some degree from the coarse resolution of both distribution and phylogenetic data. In order to obtain more robust results, the same type of analyses should be repeated at much higher resolution (perhaps using a combination of IUCN and GBIF data) to more rigorously test for niche packing which is rather difficult at a 200km resolution and with more reliable phylogenetic trees. The amphibian phylogeny is for instance based on an incomplete set of species and lack strong support in several places. However, we are confident that our analyses could pave the way for more in-depth analyses in the coming years given the rise of available data, to more formally test the effects of scale [START_REF] Chase | Stochastic Community Assembly Causes Higher Biodiversity in More Productive Environments[END_REF], community assembly processes and energy constraints [START_REF] Barnes | Consequences of tropical land use for multitrophic biodiversity and ecosystem functioning[END_REF].

5-BIOSKETCH

Wilfried Thuiller is broadly interested in merging concepts and theories from biogeography, community ecology and spatial network ecology through the use of state-of-the-art statistical and mathematical approaches.

Author contributions: WT and DG conceived the ideas with the help of FM, TM and LJP. WT compiled all data and ran the analyses, prepared the figures, wrote the initial draft and lead the revisions of the paper. All authors contributed to interpreting the results and to writing the manuscript.

6-ACKNOWLEDGEMENTS

W.T., T.M., L.J.P, and N.E.Z. received funding from the ERA-Net BiodivERsA -Belmont Forum, with the national funder Agence Nationale pour la Recherche (ANR-18-EBI4-0009) and Swiss National Foundation (20BD21_184131/1), part of the 2018 Joint call BiodivERsA-Belmont Forum call (project 'FutureWeb').

Metrics

. Maps of relative phylogenetic diversity (rPD) and the relationships with net primary productivity (NPP). Plots represent the global relationship estimated for the available trees (100 for mammals and birds, 1 for amphibians) represented as grey dots, while different colours represent the relationships for the different zoogeographic regions. The R 2 displayed on the play represent the explained variance of the global relationship between rPD and NPP (see Fig. S3). The width of the lines is proportional to the (mean) R square of the relationship between rPD and NPP calculated for each zoogeographic region (narrow: R 2 £0.1, medium: 0.1<R 2 <0.3, large: R 2 ³0.3). The distributions of the zoogeographic regions are presented in Fig. S2. Plots represent the global relationship estimated for the available trees (100 for mammals and birds, 1 for amphibians) represented as grey dots, while different colours represent the relationships for the different zoogeographic regions. The width of the lines is proportional to the (mean) R square of the relationship (narrow: R 2 £0.1, medium: 0.1<R 2 <0.3, large: R 2 ³0.3). The distributions of the zoogeographic regions are presented in Fig. S2.

Figure 1

Figure 2 A) rPD -global species pool B) rPD -hemispheric species pool C) rPD -regional species pool 0e+00 3e+11 6e+11 9e+11 0e+00 3e+11 6e+11 9e+11 0e+00 3e+11 6e+11 9e+11

Figure 2 .

 2 Figure 2. Effect of the sampling pool extent on the global relationship between relative PD and net primary productivity. Plots represent the global relationship estimated for the available trees (100 for mammals and birds, 1 for amphibians) represented as grey dots, while different colours represent the relationships for the different zoogeographic regions. The distributions of the zoogeographic regions are presented in Fig. S2.

Figure 3 .

 3 Figure3. Maps of the standardized effect size of richness of the top 25% highest species-level lineage diversification rates (SES of top DR) and the relationships with net primary productivity (NPP). Plots represent the global relationship estimated for the available trees (100 for mammals and birds, 1 for amphibians) represented as grey dots, while different colours represent the relationships for the different zoogeographic regions. The width of the lines is proportional to the (mean) R square of the relationship (narrow: R 2 £0.1, medium: 0.1<R 2 <0.3, large: R 2 ³0.3). The distributions of the zoogeographic regions are presented in Fig.S2.

Figure 4 .

 4 Figure 4. Maps of standardized effect size of richness of the top 25% evolutionarily most distinct species (SES of top ED) and the relationships with net primary productivity (NPP).Plots represent the global relationship estimated for the available trees (100 for mammals and birds, 1 for amphibians) represented as grey dots, while different colours represent the relationships for the different zoogeographic regions. The width of the lines is proportional to the (mean) R square of the relationship (narrow: R 2 £0.1, medium: 0.1<R 2 <0.3, large: R 2 ³0.3). The distributions of the zoogeographic regions are presented in Fig.S2.

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  Figure 3

Table 1 -Phylogenetic diversity metrics and associated interpretations of the correlation with NPP.

 1 Relative phylogenetic diversity (rPD) relates to relative phylogenetic diversity, SES of top ED to standardized effect size of richness of the top 25% evolutionarily most distinctive species, and SES of top DR to standardized effect size of richness of top 25% species-level lineage diversification rates.

			Meaning	Metric Correlation with NPP
		Low	High	Negative	Positive
		(negative)	(positive)
		values	values
	Relative PD	Closely related species co-occur	Distantly related species co-occur	High NPP enables tight niche packing or promotes diversification	High NPP enables loose niche packing or slowdowns diversification
	SES of top ED	Evolutionary distinct species are rare in the assemblage	Evolutionary distinct species are frequent in the assemblage	High NPP decreases the survival of distinct species	High NPP promotes the survival of distinct species
				High NPP	High NPP
	SES of top DR	Species belonging to clades with high diversification rates are rare in the assemblage	Species belonging to clades with high diversification rates are frequent in the assemblage	decreases diversification in-situ or decrease the survival of species belonging to fast diversifying	promotes diversification in situ or promotes the survival of species belonging to fast diversifying
				clades	clades