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Melanoma miRNA trafficking controls tumour primary niche formation

Nature Cell Biology volume 18, pages 1006–1017 (2016)Cite this article

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Abstract

Melanoma originates in the epidermis and becomes metastatic after invasion into the dermis. Prior interactions between melanoma cells and dermis are poorly studied. Here, we show that melanoma cells directly affect the formation of the dermal tumour niche by microRNA trafficking before invasion. Melanocytes, cells of melanoma origin, are specialized in releasing pigment vesicles, termed melanosomes. In melanoma in situ, we found melanosome markers in distal fibroblasts before melanoma invasion. The melanosomes carry microRNAs into primary fibroblasts triggering changes, including increased proliferation, migration and pro-inflammatory gene expression, all known features of cancer-associated fibroblasts (CAFs). Specifically, melanosomal microRNA-211 directly targets IGF2R and leads to MAPK signalling activation, which reciprocally encourages melanoma growth. Melanosome release inhibitor prevented CAF formation. Since the first interaction of melanoma cells with blood vessels occurs in the dermis, our data suggest an opportunity to block melanoma invasion by preventing the formation of the dermal tumour niche.

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Figure 1: Fibroblast aggregations at a distance from melanoma regions contain melanoma particles.
Figure 2: Transfer of melanoma melanosomes into fibroblasts leads to reprogramming.
Figure 3: Identification of melanosomal miRNAs.
Figure 4: Melanosomal miRNA trafficking into fibroblasts.
Figure 5: Fibroblast reprogramming into CAFs is melanosomal miR-211 dependent.
Figure 6: Melanosomal miR-211 induces CAF formation via upregulation of MAPK signalling.
Figure 7: Melanosomal miR-211 induces CAF formation via upregulation of MAPK signalling in vivo.

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Acknowledgements

This work was supported in part by the Cooperation Program in Cancer Research of the Deutsches Krebsforschungszentrum (DKFZ) and Israel’s Ministry of Science, Technology and Space (MOST) and by the Israel Science Foundation (ISF). We thank the microarray unit of the DKFZ Genomics and Proteomics Core Facility for performing microarray analyses on the Illumina Human Sentrix-12 BeadChip array and the Agilent Human miRNA Microarray.

Author information

Author notes

  1. Shani Dror and Laureen Sander: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Human Genetics and Biochemistry, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel

    Shani Dror, Danna Sheinboim, Yuval Dishon, Tamar Golan, Hagar Malcov, Alona Zilberberg, Lotan Levin, Pinchas Gonen & Carmit Levy

  2. Functional Genome Analysis, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg 69120, Germany

    Laureen Sander & Jörg D. Hoheisel

  3. Department of Pathology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel

    Hila Schwartz & Neta Erez

  4. Institute of Pathology, Sheba Medical Center, Tel Hashomer 52621, Israel

    Aviv Barzilai, Shoshana Greenberger & Iris Barshack

  5. Department of Immunology, Institut Gustave Roussy, Université Paris, 94805 Villejuif, France

    Sebastien Apcher

  6. Imaging and Cytometry Core Facility, Unit for Electron Microscopy, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg 69120, Germany

    Michelle Nessling

  7. The Bio-Imaging Unit, Hebrew University, Jerusalem 91904, Israel

    Yael Friedmann

  8. Department of Dermatology and MGH Cancer Center, Cutaneous Biology Research Center, Massachusetts General Hospital, Boston, Massachusetts 02114, USA

    Vivien Igras

  9. Coller School of Management, Tel Aviv University, Tel Aviv 69978, Israel

    Ohad Barzilay

  10. Institute of Pathology, E. Wolfson Medical Center, Holon 58100, Israel

    Hananya Vaknine & Ronen Brenner

  11. Department of Chemical Engineering, Technion—Israel Institute of Technology, Haifa 32000, Israel

    Assaf Zinger & Avi Schroeder

  12. INSERM 1186, Gustave Roussy, Université Paris-Saclay, Villejuif 94805, France

    Mehdi Khaled

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  1. Shani Dror
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Contributions

S.D. designed the experimental approach, performed experimental work, analysed data and wrote the manuscript. L.S. conducted experimental work, miRNA and gene expression studies, exosomes analysis, and analysis of the microarray data. H.S. and N.E. conducted in vivo experiments, and FACS sorting, and added discussion on CAFs formation, D.S., Y.D. and H.M. conducted melanosome isolation and RNA detection experiments. A.Zilberberg conducted immunofluorescence staining and tyrosinase activity assays. L.L. helped in establishing the melanosome isolation protocol. S.G., A.B., I.B., R.B., P.G. and H.V. provided human skin and melanoma specimens and edited the manuscript. A.Zinger and A.S. generated the labelled liposomes and performed their analysis. T.G. performed the liposome uptake analysis. O.B. provided critical discussion and aided in writing of the manuscript. Y.F. and M.N. performed the electronic microscopy analysis. V.I. provided normal human melanocytes. J.D.H. coordinated the project, analysed and provided gene expression study data, and participated in writing of the manuscript. C.L. developed the hypothesis, designed the experimental approach, coordinated the project, and wrote the manuscript. S.A. conducted the exosome experiment analysis. M.K. designed and cloned the tyrosinase:mCherry plasmid.

Corresponding author

Correspondence to Carmit Levy.

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Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Fibroblasts aggregation at a distance from melanoma regions contain melanoma particles.

(a–d) Immunofluorescence analysis of sections from four melanoma patients. DAPI-stained nuclei appear in blue. (e) Left: Immunohistochemistry staining (20X magnification) of MITF and MelanA in in situ melanoma sample. Right: Immunofluorescence analysis (63X magnification) of DCT (green) and HMB-45 (red) or FSP-1 (green) and HMB-45 (red). (f) Left: H&E staining (20X magnification) of in situ melanoma. Right: Immunofluorescence analysis (63X magnification) of HMB-45 (red) and DCT (green) or FSP-1 (green). Yellow signal indicates co-localization. (g) Left: H&E staining, immunohistochemistry for MITF and MelanA for in situ melanoma (20X magnification). Right: Immunofluorescence analysis of GPNMB (red) and FSP-1 (green). Yellow signal indicates co-localization of FSP-1 and GPNMB (63X magnification), in dashed square higher magnification image (100x magnification). (h) From left to right in in situ melanoma: H&E staining, immunohistochemistry (20X magnification) for MelanA, immunofluorescence analysis of HMB-45 (red) and DCT (green), HMB-45 (red) and FSP-1 (green), GPNMB (red) and FSP-1 (green). Yellow signal indicates co-localization (63X magnification).

Supplementary Figure 2 Fibroblasts aggregation at a distance from melanoma regions contain melanoma particles.

(a) Normal skin stained for HMB-45 (red) and DCT (green). DAPI-stained nuclei appear in blue (63X magnification). (b) Immunohistochemistry for MITF and MelanA for invasive melanoma (20X magnification) shown in Figure 1. (c) Immunofluorescence analysis of FSP-1 (green) and GPNMB (red) for invasive melanoma (20X magnification). Higher magnification image in the lower panel (100X magnification). (d) Left: H&E staining and immunohistochemistry for MelanA (20X magnification) for invasive melanoma. Right: Immunofluorescence analysis of DCT (green) and HMB-45 (red) for invasive melanoma (63X magnification). (e) Melanosome quantification method. Immunofluorescence analysis of dermal fibroblasts in superficial melanoma patient samples reveals staining for GPNMB (red) indicative of melanosomes. Left: Red fluorescence regions within fibroblast cytoplasm at the size of 300-600 nm are marked and were analyzed for fluorescence intensity (n = 80 melanosomes). Right: Whole cell fibroblasts were marked and analyzed for fluorescence intensity (n = 100 cells). (f) A single representative sample is shown stained for FSP-1 (green) and macrophage marker CD68 (red). White arrow indicates non-specific staining, and yellow signal indicates co-localization of FSP-1 and CD68. DAPI-stained nuclei appear in blue.

Supplementary Figure 3 Transfer of melanoma melanosomes into fibroblasts leads to reprogramming.

(a) Tyrosinase activity of MNT-1 whole cell extracts or isolated mature and pre-mature melanosomes. Values are normalized to total protein concentration. Error bars represent ± SEM, ∗ indicates p < 0.05 (n = 5 independent experiments). (b) Tyrosinase protein levels in indicated fractions. Rab27a was analyzed as a loading control. (c) Electron microscopy analysis of exosomes. (d) Expression of CD63 and CD81 in exosomes purified from MNT-1 cells by FACS analysis. Upper panel shows the analysis of expression of CD63 (blue) compared to unstained exosomes (red). Middle panel shows the analysis of expression of CD81 (blue) compared to unstained exosomes (red). Lower panel shows the analysis of expression of exosome markers CD63 and CD81 (blue) compared to unstained exosomes (red). (e) Protein levels in melanosomes isolated from MNT-1 cell homogenates and exosomes isolated from MNT-1 conditioned medium. Hsc70 was used as a loading control. (f) ND-1 levels in indicated fractions, normalized to GAPDH (n = 1 independent experiment). (g) Immunofluorescence staining of HaCat cells upon melanosome treatment. Melanosomal markers: tyrosinase, Tyrp1, and HMB-45 appear in yellow, red, and green, respectively. DAPI-stained nuclei appear blue. (h) Standard curves of melanosome number based on melanin and protein concentrations. (i) Fibroblasts migration upon osteopontin (400 nM) treatment. Unprocessed scans of Western Blots are shown in Supplementary Fig. 8.

Supplementary Figure 4 Melanoma melanosomes transfer into fibroblasts leads to reprogramming.

(a) Dynamic light scattering image of liposomes from a NanoSight analysis. Middle: Snapshot image of liposomes movie (Supplementary video 1). (b) Fibroblast migration upon indicated treatments. (c) Growth rate of fibroblasts upon indicated treatments (n = 2 independent experiments). (d,e) The pro-inflammatory gene signature of CAFs upon indicated treatments. Data were normalized to GAPDH (n = 3 independent experiments). (f) Left: Representative images of fibroblasts treated with 500 rhodamine-labeled liposomes or melanosomes (immunostained with GPNMB) per cell. Right: Average number of vesicles per cell (n = 6 cells for each group, 2 independent experiments). (g) Standard curve of liposome number. (h) Left: Number of liposomes per cell, calculated based on the standard curve (n = 3 measurements each of 9∗ 103 cells). Right: Representative image of fibroblasts treated with 500 rhodamine-labeled liposomes per cell. (i) Left: Electron microscopy analysis of secreted vesicles. Right: Higher magnification of the same sample. Red arrows indicate exosomes. Graphs: Percentages of indicated vesicles (n = 3 individual experiments). (j) Electron microscopy analysis of secreted melanosomes. (k) FACS analysis of CD63 and CD81 expression in indicated vesicles. Unstained MNT-1 cells appear in pale purple, stained MNT-1 cells in purple, unstained MNT-1 exosomes in pale red, stained MNT-1 exosomes in red, unstained MNT-1 melanosomes in pale blue, and stained MNT-1 melanosomes in blue. (l) NanoSight analysis of the secreted vesicle population upon P38 inhibitor treatment (n = 3 independent experiments). (m) Left: Melanin levels in melanoma medium upon SB202190 treatment. Data were normalized to RNU6B (n = 4 independent experiments). Right: Melanin levels in fibroblasts treated with medium from melanoma cells incubated with or without SB202190. Fibroblast medium was used as a control. Values were normalized to total protein amount (n = 8 samples, 3 independent experiments). (n) Immunostaining of fibroblasts treated with medium from melanoma cells that were pre-treated with SB202190. Tyrosinase is stained green; DAPI-stained nuclei appear in blue. (o) Bright field pictures of melanoma cells upon SB202190 treatment. (p) Growth rates of melanoma cells upon SB202190 treatment. (n = 3 independent experiments). (q,r) Migration and pro-inflammatory gene signature of fibroblasts treated with SB202190. Data were normalized to GAPDH (n = 2 independent experiments). In all relevant panels error bars represent ± SEM; ∗ indicates p < 0.05.

Supplementary Figure 5 Identification of melanosomal miRNAs and their trafficking into fibroblasts.

(a) Venn diagram showing the overlap between the 100 most highly expressed miRNAs in melanosomes, exosomes and melanoma-related miRNAs (literature based 41,42). (b) Yield of mature miRNAs in preparations from whole cells, mature melanosomes, and early melanosomes. Data were normalized to levels of RNU6B. Error bars represent ± SEM (n = 3 independent experiments). (c) Levels of indicated mature miRNAs were evaluated in fibroblasts treated with melanosomes or PBS (control) using RT-PCR. Data were normalized to RNU6B levels. Error bars represent ± SEM, ∗ indicates p < 0.05 (n = 4 independent experiments). (d) Table of the five microRNAs that are most up-regulated in mature melanosomes compared to their levels in whole cells. (e) Expression level of mature mmu-miR-211 in human fibroblasts after treatment with B16F10 melanosomes was determined using qRT-PCR. Data were normalized to RNU6B (n = 2 independent experiments). (f) Human primary fibroblasts were transfected with human or mouse miR-211 mimic (hsa and mmu, respectively). qRT- PCR analysis of both miRNAs. Data were normalized to RNU6B (n = 2 independent experiments). (g) Mature miRNAs levels in normal and melanoma melanosomes (n = 2 independent experiments). (h) Levels of mature miRNAs in indicated fractions (n = 2 independent experiments). (i) Levels of mature miRNAs in secreted melanosomes treated with the inhibitor (SB202190), normalized to RNU6B (n = 2 independent experiments).

Supplementary Figure 6 Fibroblast reprogramming into CAFs is melanosomal miR-211 dependent.

Fibroblasts treated with miR-320c were analyzed in comparison to control fibroblasts treated with scrambled miRs. The fibroblasts were subjected to the following analyses: (a) growth rate (error bars represent ± SEM, n = 4 independent experiments); (b) migration tested by scratch assay; (c) fibroblast collagen remodeling capacity examined by three-dimensional collagen contraction assay (error bars represent ± SEM, n = 5 independent experiments); and (d) pro-inflammatory gene expression levels tested by qRT-PCR normalized to GAPDH levels (error bars represent ± SEM,∗ indicates p < 0.05, n = 3 independent experiments). (e) In situ hybridization analysis (green, 20x magnification) of miR-211 expression levels in healthy skin sample (left) and sections from the skin of a melanoma patient (right). Immunofluorescence staining of HMB-45 of the same magnification and location (red). DAPI-stained nuclei appear blue. (f) Mature mouse miR-211 levels (mmu-miR-211) were measured in human fibroblasts that were treated with medium of Ret melanoma cell line or with control medium. Data were normalized to RNU6B levels. Error bars represent ± SEM, ∗ indicates p < 0.05 (n = 3 independent experiments). (g) PDGFRα-positive fibroblasts from local tumor stroma and melanoma cells from tumor were assessed for the expression of fibroblast markers (α-SMA, collagen), macrophage markers (CD45, F40/80), and melanoma markers (trpm1, tyrosinase). Results were compared to the expression in normal fibroblasts sorted from mouse ears and normalized to GAPDH. Error bars represent ± SEM, ∗ indicates p < 0.05 (n = 20 mice for treatment and 12 for control in 3 independent experiments). (h) Sorted fibroblasts from normal and stromal tissue stained for tyrosinase (green). DAPI-stained nuclei appear blue. Left panel: 40x magnification, right panel: 100x magnification.

Supplementary Figure 7 Melanosomal miR-211 induces CAF formation via up-regulation of MAPK signaling.

(a) Hierarchical clustering analysis of mRNA expression profiles of fibroblasts upon indicated treatments. Each row represents the mean of signal log ratios using a color-code scale. (b) Canonical pathway for IGF1R signaling in fibroblasts upon indicated treatments, generated with IPA. Gene expression levels are relative to control fibroblasts. Up- and down-regulated genes are labeled red or green, respectively; predicted activation is shown in orange, inhibition in blue. Lines represent known interactions. Orange arrows: activation; blue arrows: inhibition; yellow arrows: inconsistency between observation and prediction; grey arrows: lack of supporting data. (c,d) Immunostaining of HMB-45 and IGF2R in human specimens. Dashed lines separate tumor (T) and stroma (S); epidermis (E) and dermis (D) are indicated. DAPI-stained nuclei appear blue.. (e) Left: Immunostaining of HMB-45 and IGF2R in human specimens. Right: In situ hybridization of miR-211. Dashed lines separate tumor (T) and stroma (S); epidermis (E) and dermis (D) are indicated. DAPI-stained nuclei appear blue (63X magnification). (f) Top: Immunostaining of HMB-45 and IGF2R in human specimens. Bottom: In situ hybridization of miR-211. Dashed lines separate tumor (T) and stroma (S); epidermis (E) and dermis (D) are indicated. DAPI-stained nuclei appear blue (63X magnification). (g) MNT-1 and WM3314 melanoma cells invasion abilities, measured with a Matrigel invasion assay. Graph plots percent of invading cells. Representative images of invading and seeded cells are shown; DAPI-stained nuclei appear in blue. Error bars represent ± SEM, ∗ indicates p < 0.05 (n = 3 independent experiments). (h) MITF expression levels in MNT-1 and WM3314 melanoma cells normalized to GAPDH. Error bars represent ± SEM (n = 3 independent experiments). (i) Venn diagram showing the overlap between the 100 most highly expressed miRNAs in MNT-1 and WM3314 mature melanosomes and melanoma-related miRNAs (literature based43,44). (j) Pearson’s correlation for the expression level of each miRNA relative to MITF in 11 melanoma cell lines. miR-211, Let7a, miR-17 and miR-125b are highlighted (correlations of p < 0.05). (k) A summary model - The formation of the melanoma primary niche by miRNA trafficking. Graphical model describing our findings which demonstrate that melanoma cells directly affect the formation of the dermal tumor niche by miRNA trafficking prior to invading the dermis.

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Dror, S., Sander, L., Schwartz, H. et al. Melanoma miRNA trafficking controls tumour primary niche formation. Nat Cell Biol 18, 1006–1017 (2016). https://doi.org/10.1038/ncb3399

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