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Xinqidi Biotech Co.,Ltd,Wuhan,China 2008-2022
R&D 14th year

Perivascular tenascin C triggers sequential activation of macrophages and endothelial cells to gener

Issuing time:2022-04-28 13:13

Abstract

Disseminated cancer cells frequently lodge near vasculature in secondary organs. However, our understanding of the cellular crosstalk invoked at perivascular sites is still rudimentary. Here, we identify intercellular machinery governing formation of a pro-metastatic vascular niche during breast cancer colonization in the lung. We show that specific secreted factors, induced in metastasis-associated endothelial cells (ECs), promote metastasis in mice by enhancing stem cell properties and the viability of cancer cells. Perivascular macrophages, activated via tenascin C (TNC) stimulation of Toll-like receptor 4 (TLR4), were shown to be crucial in niche activation by secreting nitric oxide (NO) and tumor necrosis factor (TNF) to induce EC-mediated production of niche components. Notably, this mechanism was independent of vascular endothelial growth factor (VEGF), a key regulator of EC behavior and angiogenesis. However, targeting both macrophage-mediated vascular niche activation and VEGF-regulated angiogenesis resulted in added potency to curb lung metastasis in mice. Together, our findings provide mechanistic insights into the formation of vascular niches in metastasis.

Main

When cancers progress to metastasis, interactions between disseminated cancer cells and nontransformed cells of the microenvironment play an important role1. Crosstalk between disseminated cancer cells and stromal cells of secondary organs can result in the generation of metastatic niches that promote malignant growth2,3. Endothelial cells are frequently prominent within the stroma of both primary tumors and metastases; they form the inner cell layer of vasculature, such as blood vessels that are crucial for cancer growth by delivering nutrients and other essentials to tumors4. Vascular endothelial growth factor is a central promoter of angiogenesis, the formation of new blood vessels from pre-existing ones, by induction of endothelial cell proliferation, migration and survival5. This can lead to increased vascular permeability and sprouting by activating tip cells of established vessels4. Recent findings indicate that blood vessels can have substantial impact on metastatic progression that extends beyond nutrient delivery6. Studies have shown that disseminated cancer cells associate with vasculature at metastatic sites, and suggest that enhanced adhesion and crosstalk with ECs regulate phenotype and function of cancer cells in metastasis7,8,9.

In this study, we analyzed interactions between breast cancer cells and ECs in the lung during metastatic progression. We identified components of a pro-metastatic vascular niche that are independent of VEGF signaling and support stem cell properties and survival of disseminated cancer cells. Exploring the regulatory mechanisms of vascular niche formation, we found that it was not directly induced by cancer cells but required metastasis-associated macrophages as intermediates. Perivascular macrophages, activated by the extracellular matrix protein TNC via TLR4, promote the formation of a vascular niche by secreting NO and TNF to induce expression of niche components in ECs. The results reveal a critical crosstalk within vascular niches, and underscore the importance of extracellular matrix proteins as regulators of the microenvironment in metastasis.

Results

Molecular reprogramming of ECs in lungs harboring metastases

To investigate the molecular changes in ECs during metastatic colonization, we isolated ECs from lungs of mice that had been intravenously injected with MDA231-LM2 breast cancer cells, a highly metastatic derivative of MDA-MB-231 (MDA231) cells10. ECs were purified from lungs with metastases at different stages for transcriptomic studies (Extended Data Fig. 1a,b). Analysis of the endothelial marker CD31 in metastatic nodules at week 1, 2 or 3 post cancer cell injection revealed that, although early nodules (week 1 or 2) grew in proximity to blood vessels, the presence of vessels within metastatic nodules was primarily observed at a later stage (week 3) (Fig. 1a–c). Numbers of ECs also correlated with numbers of cancer cells in the lung, suggesting active EC proliferation in growing metastases (Fig. 1d).

Fig. 1: Transcriptomic analysis identifies characteristic changes in reactive ECs during metastatic colonization of the lung.
figure 1

a, Immunofluorescence images showing association of lung ECs (CD31) with metastatic breast cancer cells (GFP) in mouse lung at indicated time points post intravenous injection of MDA231-LM2 breast cancer cells. Scale bars, 50 μm. Dashed lines indicate margins of metastatic foci. b, Quantification of metastatic nodules from a with intranodular ECs; n = 72 nodules (week 1), n = 76 nodules (week 2) and n = 83 nodules (week 3) from four mice were analyzed for each time point. Data are presented as means ± s.e.m. c, Size of MDA231-LM2-derived metastatic nodules in lung at weeks 1–3. A minimum of 16 nodules were analyzed for each lung; n = 4 mice per group. d, MDA231-LM2 cancer cells (left) and ECs (right) in lung at indicated time points. Data show means ± s.d; n = 4 mice per time point. P values were determined by one-way ANOVA with Dunnett’s multiple comparison test. e, Experimental setup for EC isolation from mouse lung at different stages of MDA231-LM2-derived metastasis, followed by transcriptomic analysis. f, PC analysis of gene expression profiles from ECs isolated from healthy lung (control) or lung with different stages of metastasis (as in e). g, GSEA of isolated ECs using proliferation- or inflammation-related signatures. Signatures with nominal P < 0.05 and FDR < 0.25 were considered significant. h,i, Violin plots showing z-score analysis of tumor angiogenesis and tip cell signatures11,12 (h) or patient poor-outcome gene clusters13,14 (i), calculated from transcriptomic profiles of ECs isolated from metastatic lungs at indicated time points. P values were determined using averaged z-scores of each signature by unpaired two-tailed t-test; n = 3 biological replicates per group. j, Heatmap showing expression of 58 genes of secreted proteins (GSP58) upregulated in lung ECs at week 3 post cancer cell injection. Cutoff log2(fold change (FC)) > 0.75, P < 0.05, FDRq < 0.25. k, GSEA graph showing enrichment of GSP58 in samples of human lung metastases of breast cancer, ranked according to lung metastasis-free survival. NES, normalized enrichment score. FDR was determined from P values calculated by random permutation test.

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To purify ECs from lungs with metastases, we used fluorescence-activated cell sorting (FACS) to exclude cells expressing hematopoietic, epithelial, fibroblastic or cancer cell markers (CD45, CD11b, EpCAM, CD140a/b and green fluorescent protein (GFP)), and to select cells expressing the endothelial marker CD31 (Fig. 1e and Extended Data Fig. 1c). Purity of selected populations was determined by expression of additional endothelial markers or distinct markers of other stromal cells (Extended Data Fig. 1d). Isolated ECs were subjected to transcriptomic analysis using microarrays. Principal component analysis (PCA) revealed a notable pattern of gene expression changes at different time points. Certain changes occurred at weeks 1 and 2, but marked differences were not observed between the two time points; however, the most striking changes occurred at week 3, distinguishing this time point from the others (Fig. 1f). Further analyses, such as gene set enrichment analysis (GSEA), Gene Ontology (GO) term analysis or z-score analysis, revealed pronounced induction of gene signatures associated with cell proliferation or inflammation at week 3 (Fig. 1g, Extended Data Fig. 1e–g and Supplementary Table 1). Consistent with these findings, angiogenic activity11,12 was promoted in ECs at week 3 and vascular changes linked to increased permeability (REACTOME) were also observed (Fig. 1h and Extended Data Fig. 1h). In line with changes in EC proliferation and inflammation, specific targets of transcription factors or pathways involved in these processes were upregulated at week 3 (Extended Data Fig. 1i and Supplementary Table 2). To address the significance of these EC functions in human metastases, we assembled genes involved in proliferation or inflammation that were particularly upregulated in ECs from metastases (Supplementary Tables 3 and 4). We applied these specific metastasis-associated EC signatures to transcriptomic datasets from dissected human metastases and observed that both signatures were associated with poor outcome in breast cancer patients with lung metastases (Extended Data Fig. 1j). Moreover, gene signatures associated with poor clinical outcome13,14 were induced in ECs at week 3, suggesting that endothelial activation is linked to metastatic progression (Fig. 1i). Focusing on mediators of intercellular communications, we analyzed the expression of extracellular proteins (GO:0005576) in metastasis-associated ECs. We found significant changes in 58 genes of secreted proteins (GSP58) that were particularly induced in ECs at week 3 (Fig. 1j and Supplementary Table 5). Notably, GSEA or Kaplan–Meier analysis showed that high expression of GSP58 in metastases was associated with poor lung metastasis-free survival in patients with breast cancer, implying that lung ECs may promote metastasis via some of these secreted factors (Fig. 1k and Extended Data Fig. 1k,l).

GSP58 expression in ECs is largely independent of VEGF signaling

Considering that VEGF is a key regulator of EC biology and angiogenesis, we asked whether the gene expression changes in metastasis-associated ECs were dependent on VEGF. We treated metastases-bearing mice with either anti-VEGF antibody (B20.4.1.1)15 or isotype IgG and isolated lung ECs for transcriptomic analysis (Fig. 2a). Specific VEGF target genes were repressed in lung ECs and vascular growth was significantly reduced in metastatic lungs, indicating a robust inhibition of VEGF signaling (Extended Data Fig. 2a,b). Notably, gene signatures linked to cellular proliferation and angiogenesis16,17 were also repressed in lung ECs from anti-VEGF-treated mice (Fig. 2b–f and Extended Data Fig. 2c–e). However, despite repression of VEGF signaling and EC proliferation, gene clusters linked to poor patient outcome were not affected by anti-VEGF treatment (Fig. 2g). Importantly, inflammatory responses and GSP58 were also generally unaffected by anti-VEGF, indicating a VEGF-independent regulation (Fig. 2h,i). Concordant results were observed when we analyzed lung ECs from mice treated with an antibody targeting VEGF receptor 2 (anti-VEGFR2, DC101) (Extended Data Fig. 2f). Whereas both expression of VEGF target genes and proliferation and angiogenesis signatures were repressed in lung ECs by anti-VEGFR2 treatment, inflammation and poor-outcome gene clusters or GSP58 were not significantly affected (Extended Data Fig. 2g–m). These results indicate that, although anti-VEGF treatment effectively suppresses vascularity within metastatic nodules, it does not repress expression of most of the 58 factors, secreted by the vasculature, that were associated with poor outcome in patients.

Fig. 2: Anti-VEGF treatment inhibits proliferation, but not inflammatory responses or induction of GSP58 signature, in metastasis-associated ECs.
figure 2

a, Experimental outline of anti-VEGF treatment of mice with metastatic lung nodules. MDA231-LM2 cells were injected intravenously into NSG mice followed by repeated treatment with either anti-VEGF antibody B20.4.1.1 (B20) or control IgG for 3 weeks. Lung ECs were isolated at week 3 and transcriptomic analysis was performed. Mice harboring comparable lung metastatic loads, as measured by in vivo bioluminescence imaging, were selected for analysis. b, Overview of cell function signatures (REACTOME) repressed in metastasis-associated ECs by anti-VEGF treatment. Signatures with FDR < 0.05 were included in calculations of percentages. c, GSEA of gene clusters: cell cycle mitosis (REACTOME), DNA replication (REACTOME), sprouting angiogenesis (C5 collection in MSigDB) and tip cell signature12 in lung ECs after B20 treatment compared with control IgG. FDR was determined from P values calculated by random permutation test. d,e, Violin plots showing z-scores of genes from a lung EC proliferation signature associated with metastasis (Supplementary Table 3) (d) and tumor angiogenesis UP cluster16 (e) expressed in purified lung ECs from control (ctrl) or metastasis (met.)-bearing mice with the indicated treatment. f, Downregulated gene signatures in metastasis-associated ECs treated with B20 compared to IgG control, based on GSEA. Signatures with FDR < 0.25 are shown. Blue, proliferation-related signatures; red, signatures of VEGF target genes; gray, others. gi, Violin plot analysis of stroma poor-outcome cluster13 (g, left) and angiogenesis genes associated with poor prognosis14 (g, right); lung EC inflammation signature associated with metastasis (Supplementary Table 4) (h) and GSP58 (i) expressed in ECs from mouse lungs under the indicated conditions. In d,e and gi, P values were determined from averaged z-score of genes within signatures by one-way ANOVA with Dunnett’s multiple comparison test; n = 3 mice per group. NS, not significant.

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ECs express genes of secreted factors that promote metastasis

To identify gene candidates from GSP58 for which ECs serve as a primary cellular source compared with other stromal cells, we investigated those genes most highly induced within the signature. All VEGF-independent genes within GSP58 that were induced 3.5-fold or more were selected for further analysis, and their expression determined in four different stromal cell types isolated from mouse lung harboring metastases (Fig. 3a and Extended Data Fig. 3a). Expression analysis in lung ECs, fibroblasts, hematopoietic cells and epithelial cells showed that four genes—that is, inhibin subunit beta B (Inhbb), laminin subunit alpha 1 (Lama1), secretoglobin family 3A member 1 (Scgb3a1) and TNF receptor superfamily member 11b, also called osteoprotegerin (Opg)—were distinctly expressed in ECs compared with other cell types (Fig. 3a and Extended Data Fig. 3b).

Fig. 3: Secreted factors produced by reactive ECs promote lung metastasis.
figure 3

a, Analysis of endothelial niche candidate genes in different stromal cells isolated from metastatic lungs. Heatmap summarizes expression of genes with log2FC > 3.5. Z-scores were calculated from qPCR analysis of different stromal cells isolated from three or four mice per group. Genes highly expressed in ECs are marked in red. BMDC, bone marrow-derived cell; fibro., fibroblasts; epi., epithelial cells. b, Expression of four endothelial niche candidate genes in lung ECs isolated from indicated mouse strains with metastasis of different breast cancer cell lines. Heatmap was generated from qPCR analyses and P values calculated by unpaired one-tailed t-test. *P < 0.05, **P < 0.01, ***P < 0.001; n = 3–4 mice per group. c, Correlation analysis of expression of the four candidate genes and CDH5 in metastatic lesions of patients with breast cancer (GSE14020). Linear regression with Pearson correlation (r) and two-tailed P value is shown; n = 65. d, Immunohistochemical analysis of CD31, SCGB3A1 and LAMA1 expression in lung metastasis samples from patients with breast cancer; shown are two representative examples of metastases from analysis of 11 patients. Arrows indicate positively stained endothelial cells. Scale bars, 100 μm (patient 1) and 60 μm (patient 2). e, Proportion of lung metastasis samples expressing SCGB3A1 or LAMA1. fh, Metastatic colonization of lungs (f) by SUM159 breast cancer cells (g) and MDA231 cells (h) overexpressing endothelial niche factors or a control vector. g,h, Bioluminescence images (left) and normalized photon flux (right) 42 days post intravenous injection by SUM159 (g) and MDA231 (h) breast cancer cells. S3A1, SCGB3A1. Boxes depict median with upper and lower quartiles. Data points show values of biological replicates and whiskers indicate minimum and maximum. g, P values were calculated by one-tailed Mann–Whitney test. *P < 0.05, **P < 0.01, ***P < 0.001,P = 0.069. Control, n = 20; INHBB, n = 6; LAMA1, n = 8; SCGB3A1, n = 5; OPG, n = 5. h, Control, n = 19; INHBB, n = 10; LAMA1, n = 4; SCGB3A1, n = 10; OPG; n = 9; and four genes, n = 5. i, Histological examples of metastases marked by expression of human vimentin in lungs of mice from h. Shown are representatives from at least four independent samples. Scale bar, 200 μm. j, Kaplan–Meier analyses on compiled datasets of ER breast cancers (KM plotter) examining association of the four endothelial niche factors with relapse-free survival (n = 347 patients) and overall survival (n = 79 patients). P values were determined by log-rank test. HR, hazard ratio.

Source data

INHBB is a protein subunit of activins and inhibins, members of the TGF-β family, of which activins have been shown to regulate wound healing, fibrosis and cancer18. LAMA1 encodes the α-chain of laminin trimers LN111 and LN121, which are broadly expressed during embryonic development but more restricted in adult tissues19. Notably, LN111 is a component of certain basement membranes. SCGB3A1 is a member of the secretoglobin family of small secreted molecules and is expressed in normal lung, but its function is poorly understood20. OPG, a member of the TNF receptor superfamily, is generally recognized to have a pleiotropic function but its best characterized role is acting as decoy receptor of TRAIL or RANKL21.

We observed consistent induction of Inhbb, Lama1, Scgb3a1 and Opg in lung ECs from two xenograft models (MDA231-LM2/SUM159-LM1) and two syngeneic mouse models of lung metastasis (4T1/E0771), and confirmed that expression in ECs was unaffected by anti-VEGF treatment (Fig. 3b and Extended Data Fig. 3c,d). These four candidates were not markedly expressed in 4T1 or E0771 cancer cells compared with lung ECs from mice with lung metastasis (Extended Data Fig. 3e). To study these genes in the context of a complete metastatic process, we analyzed ECs from lungs of mice with spontaneous metastasis from mammary glands and observed upregulation of all four candidates (Extended Data Fig. 3f,g). This upregulation was associated with growth of metastases and was not detectable at early time points, even though pronounced primary tumor growth was evident. Notably, induction of the factors in metastasis-associated ECs was not affected by primary tumor removal (Extended Data Fig. 3f,g). To examine protein levels of the niche candidates, we performed enzyme-linked immunosorbent assay (ELISA) or enzyme immunoassay (EIA) on sorted ECs from metastatic lungs and revealed a significant upregulation of all four proteins (Extended Data Fig. 4a,b). To determine the relevance of these niche candidates to human metastases, we analyzed samples of lung metastasis from patients with breast cancer. In these samples, expression of the four candidate genes correlated significantly with the endothelial maker CDH5 (VE-cadherin) (Fig. 3c). We also analyzed the expression of SCGB3A1 and LAMA1 using immunohistochemistry on tissue sections from 11 human metastasis samples, and observed EC expression of SCGB3A1 in 8/11 samples (73%) and of LAMA1 in 11/11 samples (100%) (Fig. 3d,e and Supplementary Table 6). This encouraged us to study the function of the four candidate genes in metastasis, and thus we ectopically expressed INHBB, LAMA1, SCGB3A1 and OPG individually in human breast cancer cells and injected these intravenously into NSG mice. We expressed the genes in SUM159 and MDA231 cancer cells, the parental lines of SUM159-LM1 and MDA231-LM2, respectively, and observed that all four candidate genes individually promoted metastatic colonization of the lung (Fig. 3f–i and Extended Data Fig. 4c–e). Moreover, combined expression of the four genes in MDA231 cancer cells showed additive induction of metastatic growth in lungs (Fig. 3h,i). This suggested that, as individual genes, INHBB, LAMA1, SCGB3A1 and OPG can indeed promote metastatic colonization, and that coexpression of the four genes may provide a further advantage to cancer cells. The results indicate that proteins encoded by the four genes are functional components of a pro-metastatic vascular niche.

Patients with breast cancer who are diagnosed with metastatic relapse frequently present with multiple metastases that can seed each other, and such interorgan seeding has been observed between lung and liver22. This spiked our interest to analyze potential liver metastasis in mice with late-stage lung metastasis. Bioluminescence analysis of mice with lung metastasis revealed colonization of the liver (Extended Data Fig. 4f). We isolated ECs from liver areas with high bioluminescence and observed that Inhbb, Lama1, Scgb3a1 and Opg were highly expressed in ECs associated with liver metastasis compared with controls (Extended Data Fig. 4g). Importantly, ectopic expression of the vascular niche factors promoted metastasis of the liver (Extended Data Fig. 4h). This suggests a functional role of the four niche components that extends beyond lung metastasis and to other metastatic sites such as the liver.

Finally, to address the potential association of vascular niches with clinical outcome, we performed Kaplan–Meier analyses using expression of the four vascular niche components in estrogen receptor (ER)-negative breast cancer samples and investigated a potential link to survival. In these samples, expression of the vascular niche factors was significantly associated with poor relapse-free and overall survival, indicating a potential role in breast cancer (Fig. 3j).

INHBB and SCGB3A1 induce stem cell properties in breast cancer cells

Vascular niches have been recognized to produce secreted factors that support stem cell properties of certain malignancies such as brain tumors23. To address this in the context of metastatic breast cancer, we studied the potential of conditioned medium (CM) from ECs to stimulate cancer cells to form spheres on ultra-low adhesive plates, a method that promotes stem cell attributes24,25. EC-CM significantly enhanced sphere formation by breast cancer cells (Fig. 4a). Therefore, we wanted to address the potential of each of the four vascular niche components to promote sphere formation. SUM159-LM1 breast cancer cells were treated with CM from HEK293T cells, containing individual niche factor, and oncosphere formation was determined. The sphere-forming ability of breast cancer cells was markedly increased when treated with CM containing INHBB or SCGB3A1, but not with OPG or LAMA1 (Fig. 4b). Considering these results, we stimulated SUM159-LM1 breast cancer cells with either recombinant activin B, a homodimer of INHBB, or recombinant SCGB3A1, and this also induced sphere formation by cancer cells (Fig. 4c). Moreover, CM obtained from lung ECs transduced with short hairpin RNA against INHBB showed reduced potential to stimulate oncospheres compared with control CM (Extended Data Fig. 4i,j). The results suggest a putative role for INHBB and SCGB3A1 in the promotion of stem cell properties in breast cancer cells. To explore this connection further, we performed transcriptomic analysis on SUM159 breast cancer cells treated with activin B or SCGB3A1 and revealed their respective response signatures (Fig. 4d,e and Supplementary Tables 7 and 8). Notably, within the activin B signature, three members of the family of inhibitors of DNA binding and cell differentiation (ID) proteins (ID1, ID2 and ID3) were among the top induced genes (Fig. 4d). These proteins are recognized to promote stem cell self-renewal and multipotency, and were previously shown to facilitate metastatic colonization by breast cancer cells26,27.

Fig. 4: The INHBB homodimer, activin B, and SCGB3A1 promote stem cell properties of breast cancer cells.
figure 4

a, Oncosphere formation of SUM159-LM1 breast cancer cells cultured with CM from ST1.6R human lung ECs. CM, n = 9; CM+, n = 9 technical replicates from 3 independent experiments. Scale bar, 250 μm. b, Analysis of oncosphere formation in SUM159-LM1 breast cancer cells stimulated with HEK293-derived CM containing indicated factors of the vascular niche. Control, n = 24; INHBB, n = 12; LAMA1, n = 12; SCGB3A1, n = 12; OPG, n = 12 technical replicates from 4 independent experiments. c, Oncosphere formation in SUM159-LM1 stimulated with either recombinant activin B (ActB, 50 ng ml–1) or SCGB3A1 (S3A1, 1 μg ml–1). ActB, n = 8; ActB+, n = 8; S3A1, n = 9; S3A1+, n = 9 technical replicates from 4 (ActB) or 3 (S3A1) independent experiments. ac, Pvalues were determined by ratio-paired, two-tailed t-test from biologically independent experiments. Boxes depict median with upper and lower quartiles and whiskers indicate minimum and maximum values. d,e, Heatmaps of top upregulated genes in response to ActB (d) or S3A1 (e). f, Schematic diagram of GSEA setup to analyze datasets from patients with breast cancer stratified according to expression of ActB or S3A1 signatures (ActB-S or S3A1-S). g,h, Stem cell-associated gene sets enriched in patients with high ActB-S or S3A1-S in breast cancer samples from Metabric (g) or, GSE14018 (h) datasets. Stem cell signatures are indicated as follows: A, Lim_Mammary stem cell up; B, Lee_Neural crest stem cell up; C, Oswald_Hematopoietic stem cell in collagen gel up; D, Yamashita_Liver cancer stem cell up; E, Ivanova_Hematopoiesis stem cell (all from C2 collection in MSigDB). Dataset from triple-negative breast cancer samples in METABRIC discovery (upper and lower quantile, n = 66) and lung metastases of breast cancer in GSE14018 (upper and lower quantile, n = 8) were analyzed. FDR was determined from P values calculated by random permutation test. *FDR < 0.25, **FDR < 0.05. i, Kaplan–Meier analysis of relapse-free survival of ER patients with breast cancer stratified according to expression of ActB-S or S3A1-S; n = 347 patients. P values were determined by log-rank test. j, Diagram summarizing the findings on roles of INHBB and SCGB3A1 in breast cancer metastasis.

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To investigate the potential stem cell phenotype associated with activin B or SCGB3A1 signatures in clinical samples, we stratified gene expression datasets from breast cancer patients (METABRIC or lung metastasis samples) based on expression of activin B or SCGB3A1 signatures (Fig. 4f and Supplementary Tables 7 and 8). GSEA revealed that patients with high activin B- or SCGB3A1-mediated gene responses exhibited enrichment in several stem cell signatures (Fig. 4g,h). Importantly, Kaplan–Meier analysis showed that activin B and SCGB3A1 signatures were both associated with poor clinical outcome in patients with breast cancer (Fig. 4i). Together, these results suggest that INHBB and SCGBA1 promote stem cell properties and aggression in breast cancer cells (Fig. 4j).

OPG and LAMA1 support viability of metastatic breast cancer cells

Prompted by OPG potential to function as a decoy receptor for TRAIL21, we analyzed its function in the context of lung metastasis. TRAIL is highly expressed in the lung microenvironment (Fig. 5a) and is an important regulator of apoptosis in the lung during metastasis28. We analyzed TRAIL-induced apoptosis in MDA231-LM2 breast cancer cells by cleaved caspase 3 expression in the presence of incremental levels of OPG, and observed OPG-mediated protection from TRAIL (Fig. 5b). This suggested that OPG, induced in metastasis-associated ECs, may protect invading cancer cells from TRAIL-induced apoptosis. Indeed, we observed reduced apoptosis in metastases overexpressing OPG compared to control metastases in mice (Fig. 5c). TRAIL-induced apoptosis is mediated by death receptors 4 and 5 (DR4/5)29,30. To address the significance of these receptors for metastatic colonization of the lung, we induced shRNA-mediated knockdown of DR4/5 in MDA231 breast cancer cells (Extended Data Fig. 4k) and injected these intravenously into NSG mice. DR4/5 knockdown enhanced metastatic colonization of the lung (Fig. 5d) and less apoptosis was observed in lung nodules (Fig. 5e), suggesting that this mechanism plays a role in protection of the lung against metastatic colonization.

Fig. 5: OPG and LAMA1 regulate breast cancer cell survival.
figure 5

a, TRAIL messenger RNA levels in different organ tissues isolated from NSG mice; n =3 mice per group. Expression was determined by qPCR. Data are means with s.e.m. b, Left, immunoblot analysis of cleaved caspase 3 expression in MDA231-LM2 cells treated with TRAIL (50 ng ml–1) and with indicated concentrations of OPG. Right, quantification based on the ratio between cleaved and uncleaved caspase 3. Means with s.e.m. from three independent experiments are shown. Statistical analysis was performed with one-way ANOVA and Dunnett’s multiple comparison test. c, Immunofluorescence analysis of cleaved caspase 3 expression in lung metastasis from mice injected with OPG-expressing MDA231 cancer cells. Top, representative examples; cell nuclei stained with DAPI. Scale bar, 100 μm. Bottom, quantification; n = 5 (control) and n = 3 (OPG). Values are means with s.e.m. P value was determined by one-tailed Mann–Whitney test. d, Lung colonization of MDA231 cancer cells transduced with shRNA control (shControl) or shRNA against death receptors 4 and 5 (shDR4/5, two independent hairpins). Representative bioluminescence images (top) and normalized photon flux (bottom) 21 days after intravenous injection are shown; n = 5 mice per group. Boxes show median with upper and lower quartiles, and whiskers indicate maximum and minimum. P values were calculated by one-tailed Mann–Whitney test. e, Cleaved caspase 3 analysis of lung metastasis as in d. Top, representative examples; nuclei stained by DAPI. Scale bar, 100 μm. Bottom, quantification; n = 5 mice (control and shDR4/5 no. 1) and n = 3 mice (shDR4.5 no. 2). Data are means with s.e.m. P values were determined by one-tailed Mann–Whitney test. f, Immunofluorescence analysis of paxillin expression in breast cancer cells plated on LN111 or LN121. DAPI was used to stain nuclei. Arrows indicate dense paxillin at focal adhesions; n = 3. Scale bar, 20 μm. g, Analysis of spreading of breast cancer cells plated onto LN111 or LN121. Shown are relative cell areas of all cells examined over three independent experiments, with means and s.d. h, Expression of cleaved caspase 3 in breast cancer cells plated on LN111 or LN121 matrix. Data are means with s.e.m. from three independent experiments. Scale bar, 100 μm. i,j, Integrin β1 function in laminin-induced cell spreading and survival. Relative cell area (i) and cleaved caspase 3 expression (j) were analyzed in cells plated on LN111 or LN121 matrix with or without neutralizing antibody against integrin β1 (anti-int. β1). Shown are means ± s.d. with relative cell area of all examined cells (i) or means with s.e.m. (j) from three independent experiments. P values were determined by one-way ANOVA with Dunnett’s (g,h) or Tukey’s (i,j) multiple comparison test from three independent experiments. **P< 0.01, ***P< 0.001. k, Schematic summarizing OPG and LAMA1 functions in breast cancer metastasis.

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To analyze the functional role of LAMA1, we plated breast cancer cells onto surfaces coated with LN111 or LN121, the only laminin trimers containing the α-chain transcribed by LAMA1. This resulted in enhanced focal adhesion, based on increased expression and punctuated localization of paxillin with increased cellular spreading (Fig. 5f,g). Moreover, analysis of cleaved caspase 3 expression in breast cancer cells under serum starvation revealed that LN111 and LN121 can inhibit apoptosis (Fig. 5h). Notably, LN111- and LN121-induced spreading and resistance to apoptosis were dependent on the adhesion receptor integrin β1 expressed by breast cancer cells (Fig. 5i,j). Taken together, the results on OPG and LAMA1 function suggest that they respectively promote protection from TRAIL-induced apoptosis and adhesion-mediated survival of breast cancer cells (Fig. 5k).

The vascular niche is regulated by macrophages in metastatic lung

To address whether breast cancer cells directly induce the vascular niche components, we treated lung ECs with CM from MDA231-LM2 cancer cells and analyzed the expression of niche genes. However, CM from cancer cells did not induce the niche factors in ECs (Extended Data Fig. 5a), indicating that another cell type is probably required for the induction. In light of this, we used GSEA to analyze the properties of lung metastasis samples stratified according to GSP58 (Fig. 6a) and observed that samples expressing high GSP58 showed enrichment of gene signatures of innate immune cells (Fig. 6b). Thus, we examined whether these cells might be inducers of the vascular niche and selected neutrophils and macrophages for further analysis. CM from an activated macrophage cell line (RAW264.7), but not a neutrophil cell line (HL60), promoted expression of niche components in lung ECs (Fig. 6c and Extended Data Fig. 5b). This suggested that macrophages could be intermediates for metastasis-induced changes in ECs. We performed immunofluorescence analysis of the F4/80 macrophage marker in metastatic nodules in lung, and observed substantial numbers of infiltrating macrophages frequently localized to blood vessels (Fig. 6d,e and Extended Data Fig. 5c). To analyze the identity of this macrophage population we used flow cytometry and determined the expression of CD170 and CD11b, which can distinguish between local alveolar macrophages (CD170+ CD11b) and bone marrow-derived interstitial macrophages (CD170 CD11b+). We analyzed macrophages sorted from healthy mouse lungs or from lungs harboring metastases by MDA231-LM2 (in NSG mice) or 4T1 (in BALB/c mice). These experiments showed that interstitial macrophages, but not alveolar macrophages, were increased during metastatic progression (Fig. 6f,g and Extended Data Fig. 5d,e). VEGFR1 expression, combined with F4/80, has also been demonstrated to mark interstitial macrophages31, and immunofluorescence analysis of VEGFR1, F4/80 and CD31 in metastatic nodules showed that VEGFR1 and F4/80 double-positive macrophages were found in proximity to CD31+ ECs (Extended Data Fig. 5f). This suggested that interstitial macrophages are probable inducers of the perivascular niche.

Fig. 6: The endothelial niche is regulated by perivascular macrophages in lung metastasis.
figure 6

a, Schematic overview of GSEA setup used to analyze datasets from human metastasis samples ranked according to GSP58. All patients with lung metastasis (16 patients) were selected from GSE14018. b, Cellular functions enriched in GSP58-expressing human lung metastases. Cellular functions are ranked based on NES. FDR was determined from P values calculated by random permutation tests. c, Expression of niche factors in ECs treated with CM from naïve or activated macrophage cell line RAW264.7. Means with s.e.m. from either four (SCGB3A1) or five (INHBB, LAMA1 and OPG) independent experiments are shown. Statistical analysis was performed with ratio-paired, two-tailed t-tests. d, Immunofluorescence analysis of endothelial cells (CD31, white), macrophages (F4/80, red) and MDA231-LM2 (GFP, green) in metastatic nodules from mouse lung. Shown are representative images from four independent samples. Arrowheads indicate perivascular localization of macrophages. Scale bar, 50 μm. e, Quantification (percentages) of nodules with infiltrated macrophages (mac.) or macrophages associated with vessels. f,g, Macrophage subpopulations within lungs of healthy mice or mice harboring lung metastases, analyzed by flow cytometry. Interstitial and alveolar macrophages were quantified in MDA231-LM2- (f) and 4T1-mediated (g) lung metastases in NSG or BALB/c mice, respectively; n = 3 (control), n = 5 (metastasis, f) and n = 4 (metastasis, g). Means with s.e.m. are shown. h, Experimental setup of clodronate (clod.)-mediated macrophage depletion in mice with lung metastasis, followed by transcriptional analysis of lung ECs. i, Volcano plot showing differential expression of genes in lung ECs after macrophage depletion (GSP58 highlighted in red). j, Violin plot showing expression of GSP58 in ECs from lungs of metastasis-bearing mice following macrophage depletion. Pvalues were determined by one-way ANOVA with Dunnett’s multiple comparison test; n = 3 for each group. k, Expression of endothelial niche factors in purified lung ECs as in hj. mRNA levels were determined by qPCR; n = 3 mice. Shown are means with s.e.m., and P values were calculated by one-way ANOVA with Holm–Sidak’s multiple comparison test. *P < 0.05, **P < 0.01, ***P < 0.001, P = 0.086. l, Lung colonization of MDA231-LM2 cells in mice after clodronate-liposome treatment. Representative bioluminescence (left) and normalized photon flux at day 14 (right); n = 5 mice (vehicle (veh.) and PBS-liposome) and n = 3 mice (clodronate-liposome). Boxes show medians with upper and lower quartiles, and whiskers represent minimum and maximum values. Pvalues were calculated by one-tailed Mann–Whitney test.

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To investigate the functional role of macrophages in endothelial activation and metastatic colonization, we depleted macrophages from mice harboring growing metastases using clodronate-liposome (Fig. 6h and Extended Data Fig. 5g,h). We isolated lung ECs from the mice, performed transcriptomic analysis and observed that macrophage depletion repressed the expression of numerous genes within GSP58 in ECs, including Inhbb, Lama1, Scgb3a1 and Opg (Fig. 6i–k). Interestingly, whereas expression of EC proliferation genes was unaffected by macrophage depletion, EC inflammatory responses were markedly repressed (Extended Data Fig. 5i–m). These results suggest that metastasis-associated macrophages induce inflammatory responses in lung ECs. In line with the findings from xenograft mouse models, elimination of macrophages in the fully immunocompetent 4T1 mouse mammary tumor model also repressed expression of the four niche genes, indicating that macrophages are a crucial regulator of vascular niche factors in the context of an intact immune system (Extended Data Fig. 6a–c). Furthermore, consistent with the in vitro results, no change in niche factor expression was observed following elimination of neutrophils in the 4T1 model (Extended Data Fig. 6d–f). Finally, depletion of macrophages significantly repressed metastatic colonization of the lung by MDA231-LM2 cancer cells (Fig. 6l). Together, these results indicate that perivascular macrophages function as regulators of the vascular niche during lung metastasis.

TNC–TLR4-activated macrophages induce the endothelial niche

The extracellular matrix is increasingly recognized as an important regulator of cancer progression and metastasis32,33,34. TNC is a matrix glycoprotein expressed by breast cancer cells as a crucial niche component and promoter of lung metastasis35. In breast cancer cells, TNC expression is linked to both the basal subtype and a mesenchymal phenotype (Extended Data Fig. 6g,h and Supplementary Table 9). We used immunofluorescence analysis to explore the localization of TNC with respect to metastasis-associated macrophages and ECs, and observed that TNC colocalizes with both cell types in metastatic nodules (Fig. 7a). Moreover, in metastases from patients with breast cancer, TNC expression—or expression of a gene signature from activated macrophages36—overlapped GSP58 expression and with each other in patient samples and the expression levels correlated (Fig. 7b,c and Extended Data Fig. 6i). This suggested a link between TNC, metastasis-associated macrophages and activation of vascular niches in human metastases. Interestingly, previous studies have shown that TNC can bind and activate TLR4 in different cell types, leading to inflammatory signaling in mouse models of arthritis37. In line with these findings, we observed that macrophages treated with recombinant TNC induced expression of Tnf, Il1b, Il6 and Nos2 as activation markers, and this was reversed by TLR4 inhibitor (TLR4i) (Fig. 7d). However, although recombinant TNC can affect the adhesive properties of ECs, it did not directly induce expression of vascular niche components (Extended Data Fig. 6j,k). Furthermore, TNC expression in breast cancer cells was unaffected by treatment with EC-CM or recombinant vascular niche factors (Extended Data Fig. 6l). Considering these results in the context of vascular niche-regulation by macrophages, we hypothesized that perivascular TNC might be involved in the activation of macrophages to induce vascular niche components in metastasis. To address this in vivo, we injected control or TNC knockdown MDA231-LM2 cancer cells intravenously into NSG mice (Fig. 7e, top and Extended Data Fig. 6m). Consistent with previous studies35,38, TNC deficiency repressed metastatic colonization by breast cancer cells (Fig. 7f). We isolated ECs from mice harboring control or TNC knockdown metastases using FACS and determined the expression of GSP58 by microarrays (Extended Data Fig. 6n). The majority of GSP58 genes was repressed in TNC knockdown metastases (Extended Data Fig. 6o,p). Furthermore, quantitative PCR (qPCR) analysis of ECs isolated from mice confirmed that expression of the four niche factors was induced in metastases in a TNC-dependent manner (Fig. 7g). To further investigate direct TNC effects on macrophages and subsequent activation of endothelial niches, we cocultured ECs with TNC-treated RAW264.7 macrophages and analyzed expression of the four niche components. TNC-treated macrophages induced the niche factors in cocultured ECs (Extended Data Fig. 7a). In light of this, we aimed to uncover which factors from TNC-activated macrophages were responsible for induction of the vascular niche. We stimulated macrophages with TNC, alone or in combination with TLR4i, and performed transcriptomic analysis. PCA revealed major TNC-induced changes that were reversed by TLR4i cotreatment (Extended Data Fig. 7b). GSEA showed that a Toll-like receptor signature (KEGG) was enriched in TNC-stimulated macrophages and was under-represented when TLR4i was included (Extended Data Fig. 7c). Moreover, violin plot analysis showed induction of a metastasis-associated macrophage signature39 by TNC in a TLR4-dependent manner (Extended Data Fig. 7d). Further investigation of gene signatures associated with macrophage phenotypes40,41 showed that TNC can induce changes linked to different phenotypes such as the classical inflammatory macrophage phenotype (M1), alternatively activated macrophages (M2) and a wound-healing phenotype (Extended Data Fig. 7e–g). To address potential paracrine effects of TNC-stimulated macrophages, we analyzed genes of secreted proteins and observed induction of 75 by TNC, of which 54 were dependent on TLR4 (Extended Data Fig. 7h,i and Supplementary Table 10). To address whether TNC-induced factors from macrophages could promote niche components in ECs, we investigated a set of 20 of these cytokines and, since Nos2 was induced by TNC in a TLR4-dependend manner (Fig. 7d), we also included a NO-inducing NONOate as a stimulant. Of these factors, only NONOate upregulated INHBB and SCGB3A1 whereas both NONOate and TNF-α induced LAMA1 and OPG (Extended Data Fig. 7j). Importantly, ECs from metastatic nodules in mice showed indications of high responses to both TNF and NO (Extended Data Fig. 7k,l). These results suggest that NO and TNF produced by macrophages can activate the vascular niche.

Fig. 7: TNC–TLR4 axis promotes activation of perivascular macrophages and subsequent formation of a pro-metastatic endothelial niche in lung.
figure 7

a, Immunofluorescence analysis of TNC (purple), macrophages (F4/80, green) and ECs (CD31, blue) in MDA231-LM2 metastasis from mouse lung. Arrowheads indicate colocalization of TNC and macrophages at perivasculature. Dashed line indicates margins of metastasis. Shown are representative images from four independent samples. Scale bars, 50 μm. b, Hierarchical clustering of 65 human metastases of breast cancer (GSE14020) according to expression of GSP58. TNC- or classically activated macrophage-signature (CAM-S)-positive metastases are indicated by red bars. c, Correlation analysis of indicated parameters in 65 metastasis samples from patients with breast cancer. Linear regression with Pearson’s r and two-tailed P values are shown. d, Expression of indicated markers in macrophages treated with recombinant TNC or a combination of TNC and TLR4i (TAK-242) for 6 h; n = 3 (Nos2) or n = 4 (Tnf, Il1b and Il6) independent experiments. Shown are means with s.e.m. e, Experimental outlines showing MDA231-LM2 cancer cells, transduced with shRNA control (shControl) or shRNA against TNC (shTNC), injected intravenously (i.v.) into mice (top) or MDA231-LM2 cells injected i.v. into mice followed by treatment with TLR4i (bottom). f, Lung metastasis based on bioluminescence in mice injected with shControl or shTNC (two independent hairpins) transduced breast cancer cells; n = 6 mice for each group. P values calculated by one-tailed Mann–Whitney test. g, Expression of perivascular niche factors in ECs isolated from metastatic lung as in f; n = 4 mice. Data are means with s.e.m., and P values were determined by one-way ANOVA with Holm–Sidak’s multiple comparison test. *P < 0.05, **P < 0.01, ***P < 0.001. h, Bioluminescence analysis of mouse lungs harboring metastases and treated with TLR4i. For MDA231-LM2 and control, n = 10 mice; TLR4i, n = 8 mice; 4T1 and control, n = 8 mice; TLR4i, n = 9 mice. P values were calculated by one-tailed Mann–Whitney test. i, Expression of indicated genes in ECs isolated from lungs harboring MDA231-LM2 metastases as in h; n = 4 mice (control and metastasis with vehicle treatment) and n = 3 mice (metastasis with TLR4i treatment). Data are means with s.e.m., and P values were determined by one-way ANOVA with Holm–Sidak’s multiple comparison test. *P < 0.05, **P < 0.01, ***P < 0.001. j, Experimental outline of spontaneous lung metastasis in an orthotopic model. MDA231-LM2 cancer cells were implanted to the fourth mammary fat pad and their growth followed for 24 days, then tumors were removed surgically. Mice were treated with TLR4i from day 25 onwards. k, Metastasis in lungs of mice from j. Left, ex vivo bioluminescence; right, quantification of metastasis; n = 6 (vehicle) and n = 3 (TLR4i). P value was determined by one-tailed Mann–Whitney test. l, Expression of four niche factors in EC lungs isolated from mice harboring metastasis and treated with vehicle or TLR4i as in j,k. Data are means with s.e.m. obtained from n = 6 mice (vehicle) and n = 3 mice (TLR4i). P value was determined by one-tailed Mann–Whitney test. *P < 0.05. d,g,i,l, Expression was determined by qPCR. m,n, Rescue experiments where niche factors were ectopically expressed in metastatic breast cancer cells in the context of TNC knockdown (m) or TLR4i treatment (n) during lung colonization; n = 6 mice for each group. P values were determined by one-tailed Mann–Whitney test. f,h,k,m,n, Boxes show median with upper and lower quartiles, and whiskers indicate maximum and minimum values.

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To address the functional role of TLR4 as a regulator of vascular niches, we treated metastasis-bearing mice with TLR4i and isolated ECs for analysis (Fig. 7e, bottom). Whereas treatment with TLR4i did not affect recruitment of macrophages, it significantly reduced activation (Extended Data Fig. 8a,b). Importantly, inhibition of TLR4 caused downregulation of the vascular niche components and impeded metastatic colonization of the lungs (Fig. 7h, left and 7i). Considering the crosstalk between innate and adaptive immunity, we addressed the functional role of TLR4 in the immunocompetent 4T1 mammary tumor model. In line with results from xenograft models, TLR4i treatment inhibited metastatic colonization in the 4T1 model (Fig. 7h, right), and these results were crucially reproduced in an orthotopic mouse model of spontaneous metastasis to the lung (Extended Data Fig. 8c). Whereas mammary tumor growth was not significantly affected by TLR4 inhibition, both the size and number of metastatic nodules were reduced by TLR4i (Extended Data Fig. 8d,e). Notably, analysis of livers in the orthotopic mouse model showed significantly reduced liver metastasis following TLR4i treatment (Extended Data Fig. 8f). To provide evidence from a model that would mimic clinical settings, we analyzed metastatic progression and expression of the four niche components in ECs from mice where primary tumors had been surgically removed before analysis of metastasis. The experiments were done in the context of either TNC knockdown or TLR4i-treated metastases, after primary tumor removal (Fig. 7j and Extended Data Fig. 8g). Both TNC knockdown and TLR4i treatment reduced metastatic burden in the lung and repressed expression of the four niche components in lung ECs (Fig. 7k,l and Extended Data Fig. 8h,i). Finally, we investigated whether overexpression of the four niche factors could circumvent macrophage activation and restore diminished metastases in the absence of TNC or TLR4 function. Indeed, ectopic expression of the four niche components rescued both TNC knockdown and TLR4 inhibition in metastasis-bearing mice (Fig. 7m,n). Together, these results suggest a stromal interaction in metastasis where cancer cells produce TNC that activates macrophages which consequently promote the formation of a pro-metastatic vascular niche.

Combined inhibition of TLR4 and VEGF impedes lung metastasis

Our findings indicated a distinction between EC genes regulated by VEGF and those regulated by activated macrophages. To address this further, we analyzed transcriptomic changes in ECs isolated from metastatic lungs where mice had been depleted of macrophages, and compared these to expression changes in ECs from mice treated with anti-VEGF antibody. The results from GSEA show that macrophage-depended EC gene induction is particularly linked to inflammatory responses and GSP58, whereas VEGF-dependent induction leads to stimulation of proliferation (Fig. 8a). In light of this, we examined whether a combination of anti-TLR4 and anti-VEGF therapy could provide increased efficacy in suppression of metastasis. We treated xenograft and syngeneic metastasis-bearing mice with TLR4i and anti-VEGF antibody, either individually or together (Fig. 8b). The results showed that combined inhibition of TLR4 and VEGF provides improved efficacy in repression of metastasis compared to single treatments (Fig. 8c,d). Considering a potential effect of the combination treatment on tumor-induced immune responses, we analyzed T cell exhaustion markers and the presence of regulatory T cells (Tregs), natural killer cells (NK cells), macrophages and neutrophils—in a syngeneic mouse model of metastasis (the 4T1 model) where mice were treated with TLR4i and anti-VEGF antibody. Although we observed induction of all these markers in metastases, the combination treatment did not affect the responses (Extended Data Fig. 9a–e). However, we observed increased apoptosis and reduced proliferation in cancer cells of metastases following combination treatment (Fig. 8e and Extended Data Fig. 10a). We treated mice with TLR4i and anti-VEGF antibody in an orthotopic setting, where mammary fat pad tumors were surgically removed on day 22 post implantation and treatment was initiated on day 23 (Extended Data Fig. 10b). Combined TLR4i and anti-VEGF treatment significantly repressed lung metastasis (Extended Data Fig. 10c). Notably, analysis of the discovery dataset from the METABRIC study revealed that expression of VEGF and TLR4 signatures42,43 in patient samples is associated with poor overall survival (Extended Data Fig. 10d). Together, our results describe distinct endothelial activation properties where macrophage-mediated inflammation induces the production of vascular niche proteins and VEGF signaling promotes EC proliferation (Fig. 8f). These results provide a rationale to explore the combination of TLR4i with anti-VEGF therapy in suppression of vascular functions in metastases.

Fig. 8: TLR4 inhibition and anti-VEGF therapy target different vascular functions, with combination treatment further impeding lung metastasis.
figure 8

a, GSEA of GSP58, inflammation- or proliferation-related signatures expressed in ECs from mice with either macrophage-depleted lung metastases (clodronate-liposome) or metastases treated with anti-VEGF therapy (B20). bd, Inhibition of TLR4 and VEGF in mice harboring lung metastasis. b, Experimental outline where mice were intravenously injected with indicated breast cancer cells and treated with TLR4i or B20 as single treatments, or together as a combination treatment. c,d, Bioluminescence analysis of metastatic colonization of lungs in mice injected with MDA231-LM2 (c) or 4T1 (d) cancer cells and treated as described in b. Left, representative bioluminescence images; right, quantification of metastatic lung colonization based on bioluminescence signal. MDA231-LM2, n = 11 mice; 4T1, n = 5 mice (single TLR4i or B20 treatments) and n = 4 mice (control or double treatment). P values were calculated by one-tailed Mann–Whitney test. e, Immunofluorescence analysis of apoptosis by expression of cleaved caspase 3 in metastatic nodules treated with TLR4i, B20 or a combination of the two; n = 5 mice for each group. Scale bar, 50 μm. P values were determined by one-tailed Mann–Whitney test. ce, Boxes show median with upper and lower quartiles, and whiskers indicate maximum and minimum values. f, Model depicting two regulatory arms of vascular activation, where VEGF promotes proliferation of ECs and macrophages, stimulated by TNC–TLR4 signaling, promote inflammatory reaction in ECs and secretion of pro-metastatic factors of the vascular niche that are utilized by cancer cells. Shown are interactions between breast cancer cells and macrophages via the TNC–TLR4 axis, which lead to macrophage activation and subsequent induction of the perivascular niche by NO and TNF to produce pro-metastatic factors including INHBB, OPG, LAMA1 and SCGB3A1. INHBB and SCGB3A1 induce stem cell properties in breast cancer cells while OPG and LAMA1 promote survival of cancer cells at the metastatic site.

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Discussion

In this study we describe characteristic changes in lung ECs induced during metastatic colonization. We demonstrate a crucial role of specific molecular crosstalk at perivascular sites among colonizing breast cancer cells, macrophages and vascular endothelium during lung metastasis. The study provides insights into vascular regulation during metastasis, revealing a distinction between VEGF-induced proliferation and macrophage-induced inflammatory responses. Global transcriptomic analysis showed that VEGF-regulated gene expression patterns linked to cell proliferation and angiogenesis are induced in metastasis-associated lung ECs. However, the results also revealed an inflammatory reaction of ECs leading to production of numerous secreted proteins (GSP58) that are largely independent of VEGF, among which we identified INHBB, LAMA1, SCGB3A1 and OPG as crucial secreted components of the vascular niche in metastasis.

Growing evidence indicates that ECs play an important role in intercellular communication during development, tissue homeostasis and disease6. Transmembrane or secreted endothelial factors involved in cellular crosstalk have been termed angiocrine factors and can influence cancer progression44. For example, E-selectin produced by ECs in bone can promote epithelial-to-mesenchymal transition and stem cell properties in cancer cells to further metastatic colonization45. ECs can also produce specific extracellular matrix proteins that regulate states of dormancy and activation in disseminated breast cancer cells, and may enhance resistance to therapeutic intervention9,46. Antiangiogenic therapy targeting VEGF has been applied as part of a regimen to treat patients with advanced breast cancer. However, the clinical benefits from VEGF neutralization in patients with breast cancer have been limited47,48. Our results suggest that, although anti-VEGF therapy represses EC proliferation, it may not be able to block specific angiocrine functions of ECs during lung metastasis. However, the results also indicate that combined inhibition of VEGF-mediated proliferation and macrophage-induced vascular niche formation may be a promising approach to suppress broad endothelial functions in metastasis.

Our findings suggest that a crosstalk among disseminated breast cancer cells, activated macrophages and ECs is crucial to the formation of pro-metastatic vascular niches in the lung. Macrophages are activated by cancer cell-derived TNC and subsequently stimulate lung ECs by secreting NO and TNF to invoke vascular niche formation. TNC is recognized as a promoter of cancer progression in numerous malignancies and is expressed in highly aggressive cancer cells49,50. In metastatic breast cancer cells, TNC expression has been shown to be induced by JNK signaling and can be curbed by the metastasis-suppressing microRNA, miR335 (refs. 38,51). In addition to exerting changes in tumor stroma, TNC expressed by breast cancer cells functions in an autocrine manner, modulating Notch and Wnt signaling components to promote metastatic fitness of the cells35. Here, we reveal how TNC produced by cancer cells initiates activation of macrophages via TLR4 leading to induction of vascular niches. Notably, TNC-induced TLR4 activation has been shown to occur in the context of arthritis37. TNC is composed of multiple domains, among which the C-terminal fibrinogen globe was demonstrated to bind and activate TLR4 (refs. 37,52). In growing metastases, cancer cells are not the only source of TNC as activated fibroblasts can produce high TNC levels50. However, studies show that expression of TNC by reactive fibroblasts occurs at late time points and thus, in early metastasis, cancer cells are the primary source of TNC35. Although TNC from fibroblasts may contribute to vascular niches, our results indicate that TNC produced by cancer cells is crucial for the activation process.

Growing primary tumors can invoke specific changes in secondary organs, before colonization, leading to the generation of a premetastatic niche that facilitates colonization of these organs53. Some of these changes may affect blood vessels, as recently shown for leucine-rich alpha-2-glycoprotein 1 (ref. 54). However, our findings indicate that the four vascular niche genes are not induced by secreted factors from primary tumors. We conclude that TNC, produced by cancer cells invading the lungs, jump-starts the cascade that results in the formation of a pro-metastatic vascular niche.

Macrophages are recognized to express heterogeneous phenotypes depending on origin and function. Our results suggest that pro-metastatic macrophages that play a regulatory role for vascular niches in the lung are interstitial—that is, recruited from blood circulation—rather than local alveolar macrophages. This is in line with previous findings suggesting that alveolar macrophages are dispensable for metastatic progression whereas those recruited from the blood circulation are required for metastasis31. We explored the macrophage phenotype induced by TNC and observed induction of the classical inflammatory phenotype (M1), as well as features of alternatively activated macrophages (M2) and wound-healing properties. It is important to note the growing evidence which suggests that polarization of macrophages may be more complex and plastic than previously understood55. For example, single-cell analysis within the breast tumor microenvironment has shown that tumor-associated macrophages can exhibit both M1 and M2 features simultaneously56.

In conclusion, our findings delineate a multifaceted cellular crosstalk within growing metastases in the lung. The results show a crucial role for the vascular niche during metastatic progression, and emphasize the role of the extracellular matrix in its regulation. These interactions in metastatic nodules may serve as useful targets when developing future therapies against metastatic disease.

Article classification: Biological abstract
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