Whole-body imaging of lymphovascular niches identifies pre-metastatic roles of midkine

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Abstract

Cutaneous melanoma is a type of cancer with an inherent potential for lymph node colonization, which is generally preceded by neolymphangiogenesis1,2,3. However, sentinel lymph node removal does not necessarily extend the overall survival of patients with melanoma4,5. Moreover, lymphatic vessels collapse and become dysfunctional as melanomas progress6,7. Therefore, it is unclear whether (and how) lymphangiogenesis contributes to visceral metastasis. Soluble and vesicle-associated proteins secreted by tumours and/or their stroma have been proposed to condition pre-metastatic sites in patients with melanoma8,9,10,11,12,13,14. Still, the identities and prognostic value of lymphangiogenic mediators remain unclear2,14. Moreover, our understanding of lymphangiogenesis (in melanomas and other tumour types) is limited by the paucity of mouse models for live imaging of distal pre-metastatic niches15. Injectable lymphatic tracers have been developed7, but their limited diffusion precludes whole-body imaging at visceral sites16. Vascular endothelial growth factor receptor 3 (VEGFR3) is an attractive ‘lymphoreporter’17 because its expression is strongly downregulated in normal adult lymphatic endothelial cells, but is activated in pathological situations such as inflammation and cancer17,18. Here, we exploit this inducibility of VEGFR3 to engineer mouse melanoma models for whole-body imaging of metastasis generated by human cells, clinical biopsies or endogenously deregulated oncogenic pathways. This strategy revealed early induction of distal pre-metastatic niches uncoupled from lymphangiogenesis at primary lesions. Analyses of the melanoma secretome and validation in clinical specimens showed that the heparin-binding factor midkine is a systemic inducer of neo-lymphangiogenesis that defines patient prognosis. This role of midkine was linked to a paracrine activation of the mTOR pathway in lymphatic endothelial cells. These data support the use of VEGFR3 reporter mice as a ‘MetAlert’ discovery platform for drivers and inhibitors of metastasis.

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Figure 1: Vegfr3Luc reporter mice for whole-body analysis of benign and malignant melanocytic lesions.
Figure 2: Vegfr3Luc mice reveal pre-metastatic niches.
Figure 3: Proteomic analyses identify MDK as new pro-lymphangiogenic and pro-metastatic factor.
Figure 4: MDK activates the mTOR pathway and is an indicator of poor prognosis in melanoma.

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References

  1. 1

    Zheng, W., Aspelund, A. & Alitalo, K. Lymphangiogenic factors, mechanisms, and applications. J. Clin. Invest. 124, 878–887 (2014)

  2. 2

    Stacker, S. A. et al. Lymphangiogenesis and lymphatic vessel remodelling in cancer. Nat. Rev. Cancer 14, 159–172 (2014)

  3. 3

    Karaman, S. & Detmar, M. Mechanisms of lymphatic metastasis. J. Clin. Invest. 124, 922–928 (2014)

  4. 4

    van Akkooi, A. C. J. & Eggermont, A. M. M. Melanoma: MSLT-1-SNB is a biomarker, not a therapeutic intervention. Nat. Rev. Clin. Oncol. 11, 248–249 (2014)

  5. 5

    Morton, D. L. et al. Final trial report of sentinel-node biopsy versus nodal observation in melanoma. N. Engl. J. Med. 370, 599–609 (2014)

  6. 6

    Padera, T. P. et al. Lymphatic metastasis in the absence of functional intratumor lymphatics. Science 296, 1883–1886 (2002)

  7. 7

    Proulx, S. T. et al. Use of a PEG-conjugated bright near-infrared dye for functional imaging of rerouting of tumor lymphatic drainage after sentinel lymph node metastasis. Biomaterials 34, 5128–5137 (2013)

  8. 8

    Kaplan, R. N. et al. VEGFR1-positive haematopoietic bone marrow progenitors initiate the pre-metastatic niche. Nature 438, 820–827 (2005)

  9. 9

    Demirsoy, S., Martin, S., Maes, H. & Agostinis, P. Adapt, Recycle, and Move on: Proteostasis and Trafficking Mechanisms in Melanoma. Front. Oncol. 6, 240 (2016)

  10. 10

    Peinado, H. et al. Melanoma exosomes educate bone marrow progenitor cells toward a pro-metastatic phenotype through MET. Nat. Med. 18, 883–891 (2012)

  11. 11

    Hoshino, A. et al. Tumour exosome integrins determine organotropic metastasis. Nature 527, 329–335 (2015)

  12. 12

    Coelho, P., Almeida, J., Prudêncio, C., Fernandes, R. & Soares, R. Effect of adipocyte secretome in melanoma progression and vasculogenic mimicry. J. Cell. Biochem. 117, 1697–1706 (2016)

  13. 13

    Obenauf, A. C. et al. Therapy-induced tumour secretomes promote resistance and tumour progression. Nature 520, 368–372 (2015)

  14. 14

    Liu, Y. & Cao, X. Characteristics and significance of the pre-metastatic niche. Cancer Cell 30, 668–681 (2016)

  15. 15

    Eklund, L., Bry, M. & Alitalo, K. Mouse models for studying angiogenesis and lymphangiogenesis in cancer. Mol. Oncol. 7, 259–282 (2013)

  16. 16

    Sevick-Muraca, E. M., Kwon, S. & Rasmussen, J. C. Emerging lymphatic imaging technologies for mouse and man. J. Clin. Invest. 124, 905–914 (2014)

  17. 17

    Martínez-Corral, I. et al. In vivo imaging of lymphatic vessels in development, wound healing, inflammation, and tumor metastasis. Proc. Natl Acad. Sci. USA 109, 6223–6228 (2012)

  18. 18

    Petrova, T. V. et al. VEGFR-3 expression is restricted to blood and lymphatic vessels in solid tumors. Cancer Cell 13, 554–556 (2008)

  19. 19

    Dankort, D. et al. Braf(V600E) cooperates with Pten loss to induce metastatic melanoma. Nat. Genet. 41, 544–552 (2009)

  20. 20

    Muramatsu, T. & Kadomatsu, K. Midkine: an emerging target of drug development for treatment of multiple diseases. Br. J. Pharmacol. 171, 811–813 (2014)

  21. 21

    Yao, J., Li, W. Y. & Gao, S. G. The advances of Midkine with peripheral invasion in pancreatic cancer. Am. J. Cancer Res. 5, 2912–2917 (2015)

  22. 22

    Jones, D. R. Measuring midkine: the utility of midkine as a biomarker in cancer and other diseases. Br. J. Pharmacol. 171, 2925–2939 (2014)

  23. 23

    Kishida, S. & Kadomatsu, K. Involvement of midkine in neuroblastoma tumourigenesis. Br. J. Pharmacol. 171, 896–904 (2014)

  24. 24

    Kadomatsu, K., Kishida, S. & Tsubota, S. The heparin-binding growth factor midkine: the biological activities and candidate receptors. J. Biochem. 153, 511–521 (2013)

  25. 25

    Jono, H. & Ando, Y. Midkine: a novel prognostic biomarker for cancer. Cancers (Basel) 2, 624–641 (2010)

  26. 26

    Weckbach, L. T. et al. Midkine acts as proangiogenic cytokine in hypoxia-induced angiogenesis. Am. J. Physiol. Heart Circ. Physiol. 303, H429–H438 (2012)

  27. 27

    Choudhuri, R., Zhang, H. T., Donnini, S., Ziche, M. & Bicknell, R. An angiogenic role for the neurokines midkine and pleiotrophin in tumorigenesis. Cancer Res. 57, 1814–1819 (1997)

  28. 28

    Luo, Y. et al. Rapamycin inhibits lymphatic endothelial cell tube formation by downregulating vascular endothelial growth factor receptor 3 protein expression. Neoplasia 14, 228–237 (2012)

  29. 29

    Patel, V. et al. Decreased lymphangiogenesis and lymph node metastasis by mTOR inhibition in head and neck cancer. Cancer Res. 71, 7103–7112 (2011)

  30. 30

    Pucci, F. et al. SCS macrophages suppress melanoma by restricting tumor-derived vesicle-B cell interactions. Science 352, 242–246 (2016)

  31. 31

    Yajima, I. et al. Spatiotemporal gene control by the Cre-ERT2 system in melanocytes. Genesis 44, 34–43 (2006)

  32. 32

    Marino, S. et al. PTEN is essential for cell migration but not for fate determination and tumourigenesis in the cerebellum. Development 129, 3513–3522 (2002)

  33. 33

    Denoyelle, C. et al. Anti-oncogenic role of the endoplasmic reticulum differentially activated by mutations in the MAPK pathway. Nat. Cell Biol. 8, 1053–1063 (2006)

  34. 34

    Soengas, M. S. et al. Inactivation of the apoptosis effector Apaf-1 in malignant melanoma. Nature 409, 207–211 (2001)

  35. 35

    Alonso-Curbelo, D. et al. RAB7 counteracts PI3K-driven macropinocytosis activated at early stages of melanoma development. Oncotarget 6, 11848–11862 (2015)

  36. 36

    Workman, P. et al. Guidelines for the welfare and use of animals in cancer research. Br. J. Cancer 102, 1555–1577 (2010)

  37. 37

    Wiśniewski, J. R., Zougman, A., Nagaraj, N. & Mann, M. Universal sample preparation method for proteome analysis. Nat. Methods 6, 359–362 (2009)

  38. 38

    Trapnell, C. et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat. Protocols 7, 562–578 (2012). 10.1038/nprot.2012.016

  39. 39

    Langmead, B., Trapnell, C., Pop, M. & Salzberg, S. L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25 (2009)

  40. 40

    Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009)

  41. 41

    Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005)

  42. 42

    Das, S. et al. Tumor cell entry into the lymph node is controlled by CCL1 chemokine expressed by lymph node lymphatic sinuses. J. Exp. Med. 210, 1509–1528 (2013)

  43. 43

    Patsialou, A. et al. Intravital multiphoton imaging reveals multicellular streaming as a crucial component of in vivo cell migration in human breast tumors. Intravital 2, e25294 (2013)

  44. 44

    Willard-Mack, C. L. Normal structure, function, and histology of lymph nodes. Toxicol. Pathol. 34, 409–424 (2006)

Download references

Acknowledgements

We thank colleagues at the CNIO Melanoma Group, particularly A. Tenaglia for technical assistance; J. A. Esteban for critical reading of this manuscript; the i+12 Biobank of the Hospital 12 de Octubre for help with histological analyses and for patient biopsies; L. Larue and M. McMahon for Tyr:CreERT2 and inducible BrafCA mouse strains, respectively; and the Animal Facility Unit and the Histopathology Core of CNIO for assistance. M.S.S. is funded by grants from the Spanish Ministry of Economy and Innovation (project SAF2014-56868-R), the Asociación Española Contra el Cáncer (AECC), the Worldwide Cancer Research, an Established Investigator Award from the Melanoma Research Alliance (MRA), and a L’Oréal Paris USA-MRA Team Science Award for Woman in Scientific Research. The CNIO Proteomics Unit belongs to ProteoRed, PRB2-ISCIII, supported by grant PT13/0001. N.I. and J.M. are funded by SAF2013-45504-R (MINECO). J.M. is also supported by Ramon y Cajal Programme (MINECO) RYC-2012-10651. J.L.R.-P and P.O.-R are funded by grants FIS 2014/1737, 11/02568 and FIS 2014/01784, 11/1759, respectively, from the Spanish Ministry of Health. F.M. is funded by the AMIT Project/CDTI/CENIT Programme (MICINN), S.O. by SAF2013-44866-R (MINECO), and J.J.B.-C. by an NCI K22CA196750 grant and the TCI Young Scientist Cancer Research Award JJR Fund (P30 CA196521). J.D.M. is the recipient of a postdoctoral fellowship from the ARC Foundation and E.R.-F. from Fundación Científica de la Asociación Española Contra el Cáncer. D.C.-W. is the recipient of a predoctoral fellowship from Fundación La Caixa, and M.C.-A. and X.C. are recipients of the Immutrain Marie Skłodowska-Curie ITN Grant.

Author information

M.S.S. and D.O. conceived and designed all expression studies, mechanistic analyses and prognostic evaluations. S.O. conceived, designed and developed the Vegfr3Luc (Flt4tm1.1Sgo) and Vegfr3Luc nu/nu mouse models (Strain 1), contributed to experimental design, discussed data and revised the manuscript. I.M.-C. generated the Vegfr3Luc immunocomptetent allele and the Vegfr3Luc nu/nu Strain 1, and contributed to their initial characterization. D.O. performed all spatio-temporal studies of neolymphangiogenesis, as well as loss- and gain-of-function studies of MDK in vivo. D.C.-W. contributed to mechanistic and histological analyses of lymphangiogenesis, helped with in vivo experiments and revised the manuscript. E.R.-F., P.O.-R. and J.L.R.-P. performed the analysis of patient prognosis (with bioinformatic aid from D.L. and S.P.). P.C.P., M.C.-A., and X.C. contributed to functional analyses of lymphangiogenesis. N.I. and J.M. performed LC–MS/MS. F.M. helped with whole-body image analyses, D.M. with time-lapse confocal microscopy and M.Ca. with histological evaluations. O.G. and M.Ci. performed RNA-seq. T.G.C. was in charge of animal breeding and genotyping. J.J.B.-C., C.M. and J.D.M. performed intravital microscopy. J.S., L.O., J.L.M.-T., E.C., T.G.C. and D.A.-C. provided technical assistance. The manuscript was written by M.S.S. and D.O., revised by S.O. and D.A.-C., and approved by all authors. M.S.S. supervised the project.

Correspondence to María S. Soengas.

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Extended data figures and tables

Extended Data Figure 1 Non-invasive imaging of neolymphangiogenesis in Vegfr3Luc reporter mice.

a, qRT–PCR analysis of VEGFC mRNA levels in the indicated melanoma cell lines. Graphs show mean ± s.d. of three biological replicates. Data were normalized to mRNA levels in the poorly metastatic WM164 cell line. b, Immunostaining for VEGFC (pink) in xenografts of the indicated melanoma cell lines. c, Histological staining of Lyve1 (brown) in lymph nodes with low or high V3-Luc emission. d, Costaining of VEGFR3 (green) and Lyve1 LEC (brown) in the spleens of mice identified as low and high V3-Luc emitters in vivo. e, Lung metastases in mice as in Fig. 1c imaged by immunofluorescence for the detection of VEGFR3 (green) and melanoma cells (red). Source data

Extended Data Figure 2 Assessment of metastatic potential of melanoma cell lines in Vegfr3Luc mice.

a, b, Tumour-associated bioluminiscence driven by subcutaneous implantation of the indicated cell lines (labelled with mCherry) in Vegfr3Luc nu/nu mice, with images centred on the tumour (a) or showing the lateral flank of the mice to visualize sentinel-inguinal and brachial lymph nodes, as well as signal from spleen, liver and lung (b). Four main patterns (I–IV) of V3-Luc emission are shown. Red lines mark the tumour area as detected by mCherry emission (data not shown). Detection of the lymphatic marker Lyve1 in histological sections of sentinel lymph nodes from mice with xenografts generated as in a and killed when primary tumours reached 1,500 mm3. d, Tumour-positive lymph nodes (sentinel, brachial and axillar) in mice bearing xenografts of the indicated cell lines. e, Relative V3-Luc signal in subcutaneous xenografts generated by the indicated cell lines. f, Average signal in sentinel and brachial lymph nodes. Data are mean ± s.e. (minimum 6 mice per condition, 24 lymph nodes per cell line). Cell lines labelled in green in af express detectable VEGFC mRNA as summarized in Fig. 1a. Source data

Extended Data Figure 3 Whole-body analysis of neolymphangiogenesis induced in immunodeficient and immunocompetent GEMM.

a, Imaging of luciferase induction by a PDX isolated from a skin melanoma metastasis and implanted in Vegfr3Luc nu/nu mice. Mice were imaged at different time points to show V3-Luc induced at distal lymph nodes before detection of V3-Luc at the subcutaneous lesion. Dashed red lines mark tumour area. b, Quantification of the luciferase signal in tumour, lymph node (sentinel and brachial), spleen, liver and lung, at the defined average tumour sizes indicated in the x-axis (visualized with a dotted red line for simplicity). Specific tumour volumes are indicated in the right y-axis. Bioluminescence data correspond to mean ± s.d. (4 mice per condition, 16 lymph nodes per PDX). Statistical analysis: t-test. c, Comparative imaging of V3-Luc emission induced by benign nevi and cutaneous melanomas generated in Tyr::CreERT2-inducible BrafV600E and BrafV600E; Ptenlox/lox mice, respectively (black coat background), imaged 4 weeks after topical administration of 4-OH-tamoxifen. Arrows mark systemic activation of luciferase. Bottom, quantification of luciferase signal in tumour, sentinel and brachial lymph nodes, spleen, liver and lung. Units: p s−1 cm−2 per sr × 106. Data correspond to mean ± s.d. (4 mice for nevi and 10 mice for melanoma). Statistical analysis: one-way ANOVA with Dunnett’s test for multiple comparisons. d, Luciferase emission induced by cutaneous melanomas generated in immunocompetent Vegfr3Luc; BrafV600E; Ptenlox/lox (albino) mice, visualized at the indicated times after topical administration of 4-OH-tamoxifen. e, Quantification of the luciferase signal in the indicated organs, as defined in Methods. The average tumour size at each point is indicated by a red dotted line and in the x-axis. Data correspond to mean ± s.d. (four mice per condition). Statistical analysis: t-test. Source data

Extended Data Figure 4 Analysis of metastatic potential in Vegfr3Luc mice.

a, Pearson correlation analyses of the luciferase signal versus cell burden, corresponding to data presented in Fig. 2a. Shown are lymph nodes or lungs with luciferase signal over the background. b, V3-Luc emission in immunocompetent BrafV600E;Ptenlox/lox (albino) mice at the indicated times before and after surgical removal of primary cutaneous melanoma. Note the reduction in tumour-driven V3-Luc signal, particularly at visceral sites, and the reactivation at later time points (black arrows), marking metastatic relapse. Fur was removed to facilitate imaging. Source data

Extended Data Figure 5 MDK loss of function impairs melanoma–induced lymphangiogenesis and metastasis.

a, Detection of MDK protein expression by immunohistochemistry in xenografts of the indicated cell lines. b, Secreted MDK in the indicated cell lines. Upper, immunoblots of conditioned medium containing (+) or depleted of exosomes (−). Lower, ELISA-based quantification of MDK in conditioned medium of the indicated cell lines containing or depleted of exosomes (black and grey bars, respectively). MDK levels in the purified exosome fraction (white bars) are indicted as a reference. Data were normalized to levels in the complete soluble fraction (black), and correspond to mean ± s.d. of three biological replicates. c, Depletion of MDK mRNA detected by qPCR of SK-Mel-147 cells infected with lentiviruses coding for control or MDK shRNA (1) or (5). Data correspond to mean ± s.d. of three biological replicates. d, Effect of the indicated shRNAs on MDK secretion, analysed by ELISA. e, qRT–PCR analysis of VEGFC (left) and VEGFD (right) mRNA expression in SK-Mel-147 cells expressing control or MDK shRNA (1) or (5). Data correspond to mean ± s.d. of three biological replicates. f, Lack of significant effect of MDK shRNA (shown for shRNA (1) and (5)) on the growth of SK-Mel-147 cells as subcutaneous xenografts in Vegfr3Luc nu/nu mice. Data correspond to mean ± s.d. for six mice per condition. g, Blood vessel density (BLV) defined by immunohistochemical staining for CD31 in xenografts of SK-Mel-147 cells expressing control or MDK shRNA (1) or (5). h, i, Peri-tumoural or intratumoural lymphatic vessel density (LVD) determined by histological staining for Lyve1 in lesions as in f. Data correspond to mean ± s.d. for three tumours per experimental condition. Source data

Extended Data Figure 6 MDK accumulates at sites of neolymphangiogenesis.

a, Relative expression of secreted MDK in WM164 cells infected with control lentiviruses (empty) or lentiviruses expressing MDK cDNA (right), analysed in parallel with respect to basal levels in primary melanocytes and the indicated cell lines (left). Data correspond to biological triplicates measured by ELISA, using purified recombinant protein as a reference for quantification. b, Representative images of lung metastases identified by mCherry fluorescence. c, qRT–PCR analysis of VEGFC (left) and VEGFD (right) mRNA showing minimal changes in control compared with MDK-overexpressing WM164 cells. d, Assessment of peri-tumoural lymphatic vessel density (Lyve1 staining) in consecutive histological sections of xenografts generated by WM164 cells expressing MDK (and their parental controls). e, Increased VEGFR3 mRNA in MDK-expressing HLEC, determined by qRT–PCR. Data in ae correspond to mean ± s.d. of three biological replicates. f, Proliferative capacity of HLEC incubated with conditioned medium from control- or MDK-overexpressing WM164 cells (left, red). Statistical analysis: t-test. g, Depletion of MDK in SK-Mel-147 cells (blue). Data are represented as the relative mean ± s.d. of three biological replicates. Statistical analysis: one-way ANOVA. h, Dual immunofluorescence analysis to visualize MDK (green) and lymphatic vessels (Lyve1, red) in V3-Luc-positive lymph nodes of mice implanted with WM164 cells expressing MDK. i, The equivalent analysis in lungs. Source data

Extended Data Figure 7 MDK enhances the ability of melanoma cells to interact with and migrate through HLEC.

a, Attachment and spreading of mCherry-labelled WM164 or SK-MEL-147 melanoma cell lines on a confluent monolayer of HLEC preincubated for 16 h with 500 μg ml−1 recombinant MDK. Statistical analysis: t-test. See Supplementary Videos 1 and 2 for live imaging of the spreading capacity of WM164 and SK-Mel-147 melanoma cells, respectively, in control versus MDK-treated HLEC. b, Migration of SK-Mel-147 cells through a confluent layer of HLEC in the absence or presence of recombinant MDK (500 μg ml−1). Pictures show representative images of cells retained (up, pseudocoloured in red) or transmigrating (down, green) through the HLEC layer defined by confocal videomicroscopy as described in Methods. c, Percentage of migrating WM-164 or SK-MEL-147 cells in conditions as in b. Statistical analysis: t-test. d, Histological sections of xenografts generated by SK-Mel-147 cells expressing control or MDK shRNA and stained for Lyve-1 (brown) to visualize tumour cell intravasation. e, Quantification of lymphatic vessels colonized by melanoma cells in d per 25-mm2 field analysed. Data correspond to mean ± s.d. for three biological replicates (with a minimum of six fields analysed per tumour). Source data

Extended Data Figure 8 Intravital multiphoton imaging of lymph node metastases from melanoma cells expressing or lacking MDK.

a, Maximum projection, top views or side views of lymph nodes from representative mice three weeks after implantation of SK-Mel-147 cells labelled with GFP and transduced with control shRNA (shC, top) or MKD shRNA (shMDK, bottom). Tumour cells are visualized by green fluorescence, and collagen fibres by second harmonic generation (blue). Vessels at the subcapsular sinus (SCS) are stained with 155-kD dextran (magenta). Note the horizontal and vertical growth of shC cells (metastasis expressing MDK), and the disorganization of the surrounding SCS. By contrast, shMDK cells were identified as single cells or rare micrometastases. Scale bar, 50 μm. b, Still images showing the differential intralesional motility of the indicated SK-Mel-147 cell populations from lesions in a. The yellow dotted lines are shown to visualize the border of a dextran-labelled vessel in the context of a highly motile shC-melanoma cell (solid white outline). Vertical dotted white lines are included as reference to track cell movements. Scale bar, 10 μm. c, Z-slices at different time points from the time images in b. Bottom panels correspond to orthogonal zy views at the indicated time points to show the 3D location of the cell (circled in b and marked with an arrow in c) with respect to the lymphatic vasculature. Scale bar, 10 μm.

Extended Data Figure 9 Modulation of lymphangiogenic features by MDK via the mTOR pathway.

a, Sprouting ability of collagen-embedded LEC (stained with CellTracker green for fluorescence imaging). Data correspond to the length of sprouts generated when LEC colonies were incubated with conditioned medium (CM) from WM164 or WM164-MDK cells. b, Length of sprouts of collagen-embedded LEC colonies in the absence or presence of mTOR inhibitors. Statistical analysis: t-test; n = 10. c, Micrographs to visualize LEC-sprouting assays in a, b. Yellow dots mark the ends of sprouts. d, Immunofluorescence micrographs showing the expression of MDK (pink), lymphatic vessels (LYVE1, green) and p-RPS6 (red) in lymph nodes in an MDK gain-of-function setting, where Vegfr3Luc mice were implanted subcutaneously with WM164 cells and their isogenic derivatives WM164-MDK. Images were collected 2 weeks after implantation. White boxes mark magnified areas shown to the right. Source data

Extended Data Figure 10 MDK expression in human melanoma specimens.

a, MDK expression shown by immunostaining (brown) in paraffin-embedded sections of representative examples of human benign nevus, stage I–II melanoma specimens and skin and lymph node metasases. b, MDK levels in the indicated melanocytic lesions scored as negative, low and high (see Methods). Statistical analysis, χ2 t-test; n = 20 per category. c, Micrographs of low- and high-MDK expressing sentinel lymph nodes, focusing on subcapsular sinus (top) and medullary areas (bottom). d, Kaplan–Meier survival curves of melanoma patients as in Fig. 4h, considering only stage I–II (sentinel lymph node-negative) patients classified on the basis of low and high MDK expression in the corresponding sentinel lymph nodes. The number of patients at risk is shown for each time point. e, Multivariate analysis of the prognostic value of MDK expression on DFS, showing that it is independent of age, gender and Breslow depth. f, Proposed mode of action of MDK in the induction of lymphovascular niches and metastasis in melanoma.

Supplementary information

Supplementary Information

This file contains the uncropped gels and Supplementary Tables 1-4. (PDF 654 kb)

Impact of MDK on the ability of WM164 melanoma cells to adhere to and spread onto HLEC

Time lapse video microscopy of mCherry-labeled WM164 melanoma cells (red) plated on top of a monolayer of HLEC preincubated for 24h with vehicle (left) or 500ug/ml recombinant MDK (right). at 3.33 min intervals for a total of 965.7 minutes to visualize adhesion and spreading of melanoma cells as a function of changes in the size and area of mCherry-emitting cells. (MP4 6275 kb)

Impact of MDK on the ability of SK-Mel-147 melanoma cells to adhere to and spread onto HLEC

Time lapse video-microscopy of the metastatic SK-Mel-M17 cells labeled in red with mCherry to assay for increases in cell spreading and adhesion to HLEC preincubated for 24h with vehicle (left) or 500ug/ml recombinant MDK (right). Images were captured at 2.33 min intervals for a total of 200 minutes. (MP4 1936 kb)

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Olmeda, D., Cerezo-Wallis, D., Riveiro-Falkenbach, E. et al. Whole-body imaging of lymphovascular niches identifies pre-metastatic roles of midkine. Nature 546, 676–680 (2017) doi:10.1038/nature22977

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