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Melanoma-derived small extracellular vesicles induce lymphangiogenesis and metastasis through an NGFR-dependent mechanism

Nature Cancer volume 2, pages 1387–1405 (2021)Cite this article

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Abstract

Secreted extracellular vesicles (EVs) influence the tumor microenvironment and promote distal metastasis. Here we analyzed the involvement of melanoma-secreted EVs in lymph node pre-metastatic niche formation in murine models. We found that small EVs (sEVs) derived from metastatic melanoma cell lines were enriched in nerve growth factor (NGF) receptor (NGFR, p75NTR), spread through the lymphatic system and were taken up by lymphatic endothelial cells, reinforcing lymph node metastasis. Remarkably, sEVs enhanced lymphangiogenesis and tumor cell adhesion by inducing ERK kinase, nuclear factor (NF)-κB activation and intracellular adhesion molecule (ICAM)-1 expression in lymphatic endothelial cells. Importantly, ablation or inhibition of NGFR in sEVs reversed the lymphangiogenic phenotype, decreased lymph node metastasis and extended survival in pre-clinical models. Furthermore, NGFR expression was augmented in human lymph node metastases relative to that in matched primary tumors, and the frequency of NGFR+ metastatic melanoma cells in lymph nodes correlated with patient survival. In summary, we found that NGFR is secreted in melanoma-derived sEVs, reinforcing lymph node pre-metastatic niche formation and metastasis.

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Fig. 1: Melanoma-secreted sEVs are retained through the lymphatic system.
Fig. 2: sEVs are incorporated by LN stromal and immune cells.
Fig. 3: Melanoma-derived sEVs influence the transcriptional profile of LECs and promote adhesion.
Fig. 4: Melanoma-derived sEVs promote LN lymphangiogenesis.
Fig. 5: Metastatic melanoma-derived sEVs contain NGFR and transfer it to LECs.
Fig. 6: Melanoma-derived sEVs activate NGFR, MAPK and NF-κB signaling pathways in LECs.
Fig. 7: sEVs induced ICAM-1 expression and lymphangiogenesis through the NGFR pathway.
Fig. 8: EV-shed NGFR favors LN metastasis and influences survival.

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Data availability

RNA-seq data generated have been deposited in the Gene Expression Omnibus under the accession number GSE135187. The public proteomic dataset on human melanoma cell line-derived sEVs was obtained from the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD0009505. Proteomic data for the comparison between mouse B16 cell lines were uploaded to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD024108. Proteomic data for the comparison between human shC and shNGFR SK-MEL-147-derived sEVs were uploaded to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD024852. Information on procedures and analysis of the described sEVs have been included in the EV-TRACK database (EV-TRACK ID EV210127). Source data are provided with this paper. All other data supporting the findings of this study are available from the corresponding author on reasonable request.

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Acknowledgements

We apologize to those authors whose work could not be cited due to size restrictions. We thank M. S. Soengas and the members of her laboratory for melanoma cells, primary melanocyte preparations and helpful discussions. We thank M. Detmar and S. Proulx for the mouse B16-F1R2 cell line. We are grateful to M. Yañez-Mo and M. Valés for antibodies against sEV markers. We thank D. Grela and A. Escobar from IESMAT for their support with the Zetasizer analysis. We thank G. Roncador, L. Maestre and J. L. Martinez Torrecuadrada for their help with the development and characterization of anti-NGFR antibodies and C. Villarroya Beltri for her help in flow cytometry analysis. This work was funded by the Starr Cancer Consortium (B.J.M., D.L. and H.P.), the US NIH (R01-CA169416), the Nancy C. and Daniel P. Paduano Foundation, the Children’s Cancer and Blood Foundation (H.P. and D.L.), the Melanoma Research Alliance, the Feldstein Foundation, RETOS SAF2017-82924-R (AEI/10.13039/501100011033/FEDER-UE), the Fundación Ramón Areces, the Fundación Bancaria ‘la Caixa’ (HR18-00256), ATRES-MEDIA AXA Foundation (CONSTANTES Y VITALES, una iniciativa de laSexta y Fundación AXA) and the Fundación Científica AECC (LABAE19027PEIN, GCB15152978SOEN-HP) (H.P.), the Malcolm Hewitt Wiener Foundation, the AHEPA Fifth District Cancer Research Foundation, the Hartwell Foundation and the Manning Foundation (D.L.). We are also grateful for the support of the Translational Network for the Clinical Application of Extracellular Vesicles (TeNTaCLES), RED2018-102411-T (AEI/10.13039/501100011033), the Ramón y Cajal Programme, the FERO Foundation, Comunidad of Madrid 2017-T2/BMD6026 (L.N.) and La Caixa Foundation (ID100010434, fellowship LCF/BQ/ES17/11600007) (A.H.-B.). The CNIO, certified as a Severo Ochoa Excellence Centre, is supported by the Spanish government through the ISCIII.

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Author notes

  1. These authors contributed equally: Susana García-Silva, Alberto Benito-Martín.

Authors and Affiliations

  1. Microenvironment and Metastasis Laboratory, Molecular Oncology Programme, Spanish National Cancer Research Center (CNIO), Madrid, Spain

    Susana García-Silva, Laura Nogués, Alberto Hernández-Barranco, Marina S. Mazariegos, Vanesa Santos, Marta Hergueta-Redondo, Ana Amor Lopez, Cristina Merino, Sara Sánchez-Redondo & Héctor Peinado

  2. Children’s Cancer and Blood Foundation Laboratories, Departments of Pediatrics and Cell and Developmental Biology, Weill Cornell Medical College, New York, NY, USA

    Alberto Benito-Martín, Irina Matei & David Lyden

  3. Proteomics Unit, ProteoRed-ISCIII, Spanish National Cancer Research Centre (CNIO), Madrid, Spain

    Pilar Ximénez-Embún & Javier Muñoz

  4. Department of Surgery, Plastic and Reconstructive Surgery Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Raghu P. Kataru & Babak J. Mehrara

  5. Bioinformatics Unit, Structural Biology Programme, Spanish National Cancer Research Centre (CNIO), Madrid, Spain

    Osvaldo Graña-Castro

  6. Area of Developmental and Cell Biology, Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain

    José Ángel Nicolás-Avila & Andrés Hidalgo

  7. Molecular Cytogenetics Unit, Human Cancer Genetics Programme, Spanish National Cancer Research Center (CNIO), Madrid, Spain

    Raúl Torres-Ruiz & Sandra Rodríguez-Perales

  8. Flow Cytometry Unit, Biotechnology Programme, Spanish National Cancer Research Center (CNIO), Madrid, Spain

    Lola Martínez

  9. Cofocal Microscopy Unit, Biotechnology Programme, Spanish National Cancer Research Center (CNIO), Madrid, Spain

    Manuel Pérez-Martínez, Gadea Mata & Diego Megías

  10. Department of Pathology and Laboratory Medicine, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland

    Anna Szumera-Ciećkiewicz

  11. Diagnostic Hematology Department, Institute of Hematology and Transfusion Medicine, Warsaw, Poland

    Anna Szumera-Ciećkiewicz

  12. Department of Soft Tissue/Bone Sarcoma and Melanoma, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland

    Iwona Kalinowska & Piotr Rutkowski

  13. Department of Dermatology, University of Zurich, University of Zurich Hospital, Zurich, Switzerland

    Annalisa Saltari, Julia M. Martínez-Gómez, Sabrina A. Hogan & Mitchell P. Levesque

  14. Lady Davis Institute, Jewish General Hospital, Montreal, Quebec, Canada

    H. Uri Saragovi

  15. Department of Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada

    H. Uri Saragovi

  16. Transgenic Mice Unit, Biotechnology Programme, Spanish National Cancer Research Center (CNIO), Madrid, Spain

    Sagrario Ortega

  17. Electron Microscopy Unit, Spanish National Cancer Research Center (CNIO), Madrid, Spain

    Carmen Garcia-Martin & Jasminka Boskovic

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  1. Susana García-Silva
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  2. Alberto Benito-Martín
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Contributions

S.G.-S., A.B.-M., L.N., A.H.-B., M.S.M., V.S., M.H.-R., P.X.-E., R.P.K., A.A.L., C.M., S.S.-R., I.M., J.A.N.-A., R.T.-R., L.M., M.P.-M. and H.P. performed experiments. O.G.-C. performed bioinformatic analysis. P.X.-E. and J.M. performed proteomic analysis. D.M., R.P.K., G.M., S.G.-S., L.N. and A.H.-B. performed imaging analysis. A.S.-C., I.K., A.S., J.M.M.-G., S.A.H., S.G.-S., M.P.L. and P.R. provided patient samples and/or performed human sample analysis. L.M., D.M., S.R.-P. and J.M. contributed to analysis of results. S.O. provided Vegfr3-Luc mice. H.U.S. advised on THX-B use and provided pharmacological studies. A.H. provided CD169DTR mice. C.G.-M. and J.B. performed electron microscopy studies. B.J.M., D.L. and H.P. conceived the original hypothesis. S.G.-S., A.B.-M. and H.P. planned experiments. S.G.-S. and H.P. wrote the manuscript. H.P. directed and supervised the work. H.P. is the lead contact. All authors contributed to and approved the final version of the manuscript.

Corresponding authors

Correspondence to Babak J. Mehrara, David Lyden or Héctor Peinado.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Cancer thanks Wei Guo and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Biophysical properties and cargo of melanoma-derived sEVs.

a, Analysis of sEV (ALIX, CD81 and CD9) and non-sEV markers (GM130 and CALNEXIN) in sEVs from the indicated mouse melanoma cell lines purified by ultracentrifugation. Two independent experiments were performed (n = 2 samples per group). b, Electron microscopy images of the indicated sEVs after iodixanol density gradient. Two independent experiments were performed (n = 2 samples per group). Scale bar, 200 μm. c, Analysis of sEV markers in iodixanol density gradient fractions obtained for B16F10 and B16-F1R2 sEVs. EEA-1 was included as non-sEV marker. Two independent experiments were performed (n = 2 samples per group). d,e, Measurement of the average and mode diameter size and protein content of sEVs purified by ultracentrifugation from the indicated cell lines. Two independent experiments were performed (n = 6 samples per group) f, Z-potential measurements of B16-F1, B16-F10 and B16-F1R2-derived sEVs. N = 2 samples per group. g, Venn diagram for significant upregulated proteins in B16-F10 and B16-F1R2-secreted sEVs compared to B16-F1-derived sEVs. Statistically significant changes were defined using a Student’s t test (FDR < 0.05, p value < 0.05). Fold change was set at 1.32 (log2). h, Significantly enriched pathways associated with the upregulated proteins found in B16-F10 and B16-F1R2-secreted sEVs compared to B16-F1-derived sEVs. The enrichment analysis was performed using ClueGO pluggin and used a two-sided test for p value calculation followed by Bonferroni step down correction for p adjusted value. Padj, p adjusted value. i, Quantification of integrins detected by mass spectrometry in the indicated sEVs (n = 2 samples per group). j-l, Schemes showing the experimental planning for LN education experiments. j, Doses of 5 μg of melanoma-derived sEVs were injected intra-footpad every 2 days for the indicated days. At indicated time points, 50,000 B16-F1-mCherry or B16-F1-GFP cells were injected intra-footpad (j, k) or in the flank (l). Data represent mean ± s.e.m. and p values were calculated by two-sided Kruskal-Wallis test in d and by one-way ANOVA in e and f.

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Extended Data Fig. 2 Analysis of sEV distribution in LNs.

a, Representative images of colocalization of labeled B16-F1R2-secreted sEVs with LYVE-1+ LECs and CD169+ macrophages in popliteal LNs. Nodules were analyzed 16 h after intra-footpad injection of DiD-labeled sEVs. Two experiments were performed (n = 4 mice per group). Scale bar, 20 μm. b, Gating strategy for the analysis of sEV uptake by LN populations. c, sEV-associated fluorescence in the indicated CD45− cell populations in popliteal and inguinal LNs 16 h after intra-footpad injection of DiD-labeled B16-F10-secreted sEVs determined by flow cytometry. Three experiments were performed (n = 3 samples per group). BECs, blood endothelial cells; FRCs, fibroblastic reticular cells. d, Representative plots showing sEV-associated fluorescence in the indicated LN macrophage populations treated in the same conditions as in (c). Three experiments were performed (n = 3 samples per group). e, Percentage of LECs and CD169+F4/80+ macrophages exhibiting sEV-associated fluorescence at the indicated times after intra-footpad injection of B16-F1R2 sEVs as determined by flow cytometry. Three experiments were performed (n = 3 samples per group). Data represent mean ± s.e.m and p values were calculated by two-way ANOVA.

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Extended Data Fig. 3 Characterization of SK-MEL-147-derived sEVs.

a, Representative profile of nanoparticle size distribution analyzed by nanotracking analysis (NTA) of SK-MEL-147-derived sEVs. Three experiments were performed (n = 3 samples per group). b, Electron microscopy images of SK-MEL-147-secreted sEVs after iodixanol density gradient. Two experiments were performed (n = 2 samples per group). Scale bar, 200 nm. c, Analysis of sEV markers (ALIX, CD63 and CD81) and non-sEV markers (GM130 and CALNEXIN) in SK-MEL-147-derived sEVs purified by ultracentrifugation compared to whole SK-MEL-147 cell extracts. Two experiments were performed (n = 2 samples per group).d, Analysis of sEV markers in the sequential fractions obtained after iodixanol density gradient of a representative SK-MEL-147-derived sEV preparation. EEA-1 was included as non-sEV marker. Two experiments were performed (n = 2 samples per group).

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Extended Data Fig. 4 Human LECs incorporate melanoma-secreted sEVs.

a, Representative bright field image of HLECs growing in monolayer, images were obtained from three independent experiments (n = 3 samples). Scale bar, 100 μm. b, Co-staining of lymphatic markers PROX-1 and CD31 in HLECs cultures (n = 3 samples). Scale bar 150 μm. c, Representative immunofluorescence (left panel) and bright field (right panel) images of cultured HLECs exposed to CSFE-labeled SK-MEL-147 sEVs for 16 h. Data were collected from two independent experiments (n = 4 samples per group). Scale bar, 100 μm. d, Representative flow cytometry plots showing apoptotic cell levels in HLECs treated with SK-MEL-147 sEVs for 48 h. Numbers on the gates show the percentage of live cells in each condition (n = 2 samples per group). e, Representative immunofluorescence and bright field images of cultures of HLECs 8 h after exposure to CSFE-labeled SK-MEL-147- or human primary melanocytes (Melano)-derived sEVs. Two experiments were performed (n = 3 samples per group). Scale bar, 100 μm. f, Representative flow cytometry plots for in vitro sEV uptake. Human LECs were treated with PKH67-labeled SK-MEL-147 or melanocyte sEVs and fluorescence was measured at the indicated time points (n = 2 samples per group). g, Median fluorescence intensity (MFI) signal obtained by flow cytometry analysis from measurements performed in (e), (n = 2 samples per group). h,i, Modal distribution and quantification of mean fluorescence intensity (MFI) of sEV-associated fluorescence in HLECs upon exposure to DiD-labeled SK-MEL-147 sEVs in combination with 10 µg ml-1 GRGDSP or 0.1 µg ml-1 anti-integrin αv antibody for 16 h obtained by flow cytometry. Control condition (CTRL) represented HLECs treated with the DiD dye alone. Data were collected from two independent experiments (CTRL, sEVs and sEVs+anti-αv groups, n = 4 samples, sEVs+GRGDSP group, n = 3 samples). Data represent mean ± s.e.m and p values were calculated by one-way ANOVA.

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Extended Data Fig. 5 Melanoma sEVs promote transcriptional changes in LECs.

a, Single sample GSEA analysis showing KEGG significantly downregulated signatures obtained by RNAseq analysis in human LECs upon exposure to SK-MEL-147-derived sEVs during 48 h (n = 3 samples per group). b, GSEA plots of neural-related gene signatures exhibiting significant enrichment in sEV-treated LECs versus non treated cells according to RNAseq data. Nominal p value <0.0001. c, mRNA levels analyzed by qPCR of some of the most up-regulated genes obtained by RNAseq in hLECs. Cells were incubated with SK-MEL-147-derived sEVs (sEVs) or PBS for 24 h and 48 h or with sEV-depleted conditioned medium (CM) from SK-MEL-147 cells for 24 h. Data were collected from two independent experiments (n = 5 independent cell cultures per group). d, GSEAs showing positive enrichment of adhesion-related signatures in sEV-treated LECs versus non treated cells. Nominal p value <0.01. e,f, ICAM-1 expression in HLECs treated SK-MEL-147 sEVs during 48 h. Two experiments were performed (n = 4 samples per group). Scale bar, 25 μm. g,h Quantification and representative images of tumor adhesion on HLECs monolayer. HLECs were pre-treated with SK-MEL-147. sEVs during 48 and subsequently incubated with 5,263 tumor cells cm-2 for 3 h before fixation. Two independent experiments were performed (n = 9 samples per group). Scale bar, 50 μm. Data represent mean ± s.e.m and p values were calculated by one-way ANOVA in c and by two-tailed Student t-test in f and g.

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Extended Data Fig. 6 Melanoma-derived sEVs promote lymphangiogenesis.

a, GSEA plots for lymphangiogenesis and angiogenesis-related gene sets positively enriched in HLECs treated with SK-MEL-147-derived sEVs for 48 h compared to control LECs (n = 3 samples per group). Nominal p value <0.01. b, Number and length of branches/tubes in endothelial cell tube assays in HLECs incubated for 48 h with SK-MEL-147 sEVs and subsequently plated on matrigel for 16 h. Data were collected from two independent experiments (n = 7 samples per group). c,d, Representative images and quantification of endothelial cell tube assays performed in HMVECs treated in the same conditions as described in (b). Data were collected from two independent experiments (n = 5 samples per group) Scale bar, 100 µm. e,f, Representative images and quantification of tubular structures in co-cultures of HMVECs (CD31+ cells) and HLF fibroblasts treated for 48 h with SK-MEL-147 sEVs and untreated (PBS) control. Two independent experiments were performed (CTRL group, n = 6 samples, SK-MEL-147 sEVs group, n = 8 samples). Scale bar, 50 μm. g, Quantitative PCR analysis of Lyve-1 and Prox-1 genes in sorted cell populations from popliteal LNs of Prox-1-tdTomato mice 24 h after injection of DiD-labeled B16-F10 sEVs or control dye (n = 4 samples per group). h,i, Representative histological images of popliteal LNs stained with LYVE-1 (magenta) and Ki67 (brown) and corresponding quantification of Ki67+LYVE-1+ cells. Animals were injected intra-footpad 3 times with B16-F1R2 sEVs for 1 week (n = 5 mice per group, CTRL, n = 8 LN sections and B16-F1R2 sEVs 10 LN sections). Scale bar, 150 µm. Boxes and whiskers in the box plots in b and d are defined as in Fig. 1. Data represent mean ± s.e.m and p values were calculated by two-tailed Student t-test in b, d and g or by two-tailed Student t test with Welch’s correction in f and i.

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Extended Data Fig. 7 sEVs induce macrophage-independent changes in LECs.

a, Expression of pro-lymph-angiogenic genes in sorted CD169+F4/80+ macrophages. LNs were harvested 48 h after intra-footpad injection of B16-F1R2 sEVs. Data were collected from two independent experiments (n = 4 mice per group). b, Percentage of LECs with DiD-sEV associated fluorescence analyzed by flow cytometry. WT or CD169DTR mice were treated with diphtheria toxin and 48 h later, B16-F1R2 sEVs were injected intra-footpad. Animals were sacrificed 24 h later. (n = 5 mice per group). c, Measurement of proliferating PROX-1+ LECs in popliteal LNs from WT and CD169DTR mice. Animals were treated with diphtheria toxin and 24 h later, B16-F1R2 sEVs were injected intra-footpad. Mice were sacrificed 48 h later (n = 5 mice per group). d, Comparison of NGFR mRNA levels (z-score) in cell lines from different tumor types obtained from the CCLE database (melanoma, n = 58; endometrium cancer, n = 25; breast cancer, n = 56; ovary cancer, n = 44; pancreatic cancer n = 42; lung cancer, n = 166; central nervous system (CNS) cancer, n = 47; and stomach cancer, n = 34). e, NGFR mRNA levels in a panel of primary melanocytes (Melano1 and Melano2) and human melanoma cell lines. Data were acquired from two independent experiments (n = 4 samples per group). f, Ngfr mRNA levels in mouse melanoma B16 cell lines. Data were collected from two independent experiments (all groups, n = 4 independent cell cultures per group. g, NGFR fluorescence distribution analyzed by flow cytometry in mouse melanoma sEVs. Plot shows a representative analysis of two independent experiments (n = 2 samples per group). h, NGFR protein levels in human melanoma cell lines compared to primary melanocytes analyzed from a published mass spectrometry data set. (Melano and SK-MEL-147 groups, n = 4 samples, WM-164 and SK-MEL-28 groups, n = 3). Data represent mean ± s.e.m and p values were calculated by two-tailed Student t-test in a and by one-way ANOVA in b-f and h.

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Extended Data Fig. 8 NGFR knock-down in metastatic melanoma cell lines.

a, Representative Western blot showing NGFR protein levels in control (shC) or NGFR shRNA (shNGFR) SK-MEL-147 whole cell lysates and secreted sEVs. Two independent experiments were performed (n = 2 samples per group). b, NGFR protein levels in whole cell lysates and sEVs from control (CTRL) and Ngfr KO B16-F1R2 cells. Two independent experiments were performed (n = 2 samples per group). c, Measurement by nanoparticle tracking analysis (NTA) of the number of particles (right plot) and protein content (left plot) after paired purification of sEVs from the indicated B16-F1R2 cell lines. Data were collected from six independent experiments (n = 6 samples per group). d, Percentage of LN cell types incorporating DiD-labeled sEVs 16 h after footpad injection of control (CTRL) and Ngfr KO B16-F1R2-derived sEVs (n = 3 mice per group). e, Overrepresented pathways associated with the significantly downregulated proteins found in shNGFR SK-MEL-147-derived sEVs compared to shC SK-MEL-147-derived sEVs (n = 3 samples per group). Pathways were obtained using PANTHER software overrepresentation tool applying Fisher’s exact test and FDR for multiple comparison correction. Padj, adjusted p value. f, Representative immunoblotting displaying ERK1/2 phosphorylation levels in HLECs treated with 5 μg ml−1 of SK-MEL-147-derived sEVs for the indicated times in the presence or absence of 1 μM MEK inhibitor PD0325901. Total ERK-1/2 levels are shown as loading control. Two independent experiments were performed (n = 2 cell samples per group). g, Quantification of phospho-AKT and phospho-mTOR staining in HLECs in basal conditions or after the addition of SK-MEL-147 sEVs for 30 min. Fluorescent signal was measured using Opera high content screening system. (Phosho-AKT fluorescence, CTRL cells n = 3598, sEV n = 3457. Phospho mTOR fluorescence, CTRL n = 517, sEV n = 1509). Data represent mean ± s.e.m and p values were calculated by two-tailed paired Student t-test in c, by one-way ANOVA in d and by two-tailed unpaired Student t-test in g.

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Extended Data Fig. 9 NGFR promotes tumor adhesion and lymphangiogenesis in LECs.

a,b, Images and quantification of SK-MEL-147-GFP tumor cells attached to a monolayer of human LECs after 3 h incubation. hLECs were pre-treated for 48 h with control shRNA (shC) or NGFR shRNA (shNGFR) SK-MEL-147 sEVs. Treatment with primary melanocytes-derived sEVs (Melano sEVs) was included as additional control. Two independent experiments were performed (n = 14 samples per group). Scale bar, 50 μm. c, NGFR protein levels in hLECs treated with control (shC) or NGFR shRNA (shNGFR) SK-MEL-147 sEVs for 24 h and 48 h. When indicated, cells were treated with THX-B 2 h before harvesting. Two independent experiments were performed (n = 2 samples per group). d,e, Images and quantification of NGFR staining in HLECs incubated with shControl or shNGFR SK-MEL-147 sEVs in the presence or absence of THX-B. Data were acquired from two independent experiments (n = 14 images per group). Scale bar, 25 μm. f, Expression of NGFR and pro-lymphangiogenic genes in HLECs treated with shControl or shNGFR SK-MEL-147 sEVs for 48 h in the presence or absence of JSH-23. Two independent experiments were performed (n = 6 samples per group). g, Quantification of tube structures in endothelial cell tube assays performed in HLECs incubated for 48 h with SK-MEL-147 sEVs alone or in combination with Pro-NGF (n = 5 samples per group). h, Quantification of LYVE-1+ cells in histological sections of matrigel plugs 15 days after implantation. SK-MEL-147-derived sEVs were embedded alone or in combination with BDNF or Pro-NGF in matrigel immediately prior to implantation (n = 3 plugs per group). i, Expression levels of neurotrophin receptors and NGFR ligands in popliteal LN exposed to B16-R2 sEVs for 48 h (n = 3 mice per group). Boxes and whiskers in the box plots in g are defined as in Fig. 1. All other data represent mean ± s.e.m and p values were calculated by one-way ANOVA in b-h and by two-way ANOVA in i.

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Extended Data Fig. 10 NGFR influences LN metastasis.

a, Growth curves of flank tumors in mice injected with 200,000 control or Ngfr KO B16-F1R2 cells (n = 6 mice per group). b, HMB-45 histological staining in inguinal LN sections in mice from experiment described in (a) (n = 6 mice per group). Scale bar 150 µm. c, Metastatic foci quantification in inguinal LN sections of animals from experiment described in (a) (n = 6 mice per group). d, Metastatic lesions in LN of mice 15 days after intra-footpad injection of 50,000 control or NGFR KO B16-F1R2 cells (n = 6 mice per group). e, NGFR mRNA levels in primary tumors (PT) and metastatic tumors (Met) according to TCGA melanoma data set (PT group, n = 103 patients and Met group, n = 367 patients). f, NGFR mRNA levels in primary tumors (PT LN+) and metastatic tumors (Met LN+) with LN involvement. (PT LN+ group, n = 42 patients and Met LN+ group, n = 171 patients). Data represent mean ± s.e.m and p values were calculated by two-way ANOVA in a, by two-tailed Student t-test in c and d and by two-sided Mann-Whitney test in e and f.

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García-Silva, S., Benito-Martín, A., Nogués, L. et al. Melanoma-derived small extracellular vesicles induce lymphangiogenesis and metastasis through an NGFR-dependent mechanism. Nat Cancer 2, 1387–1405 (2021). https://doi.org/10.1038/s43018-021-00272-y

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