Direct investigation of the early cellular changes induced by metastatic cells within the surrounding tissue remains a challenge. Here we present a system in which metastatic cancer cells release a cell-penetrating fluorescent protein, which is taken up by neighbouring cells and enables spatial identification of the local metastatic cellular environment. Using this system, tissue cells with low representation in the metastatic niche can be identified and characterized within the bulk tissue. To highlight its potential, we applied this strategy to study the cellular environment of metastatic breast cancer cells in the lung. We report the presence of cancer-associated parenchymal cells, which exhibit stem-cell-like features, expression of lung progenitor markers, multi-lineage differentiation potential and self-renewal activity. In ex vivo assays, lung epithelial cells acquire a cancer-associated parenchymal-cell-like phenotype when co-cultured with cancer cells and support their growth. These results highlight the potential of this method as a platform for new discoveries.
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The RNA-sequencing datasets have been deposited in the Gene Expression Omnibus with accession number GSE117930; the single-cell RNA-sequencing datasets have been deposited with accession number GSE131508. The proteomic datasets have been deposited in the Proteomics Identifications Database with accession number PXD010597.
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We thank E. Sahai, P. Scaffidi (The Francis Crick Institute) and V. Sanz-Moreno (Barts Cancer Institute) for scientific discussions, critical reading of the manuscript and sharing cell lines and mouse strains; M. Izquierdo (CSIC, Madrid) for sharing the CD63–GFP plasmid; E. Nye and the pathologists G. Stamp and E. Herbert from the Experimental Histopathology Unit at the Francis Crick Institute for histological processing and analysis support; J. Bee from the Biological Resources Unit at the Francis Crick Institute for technical support with mice and mouse tissues; R. Goldstone and A. Edwards from the Advanced Sequencing Facility at the Francis Crick Institute for technical support; M. Llorian-Sopena from the Bioinformatics and Biostatistics Unit at the Francis Crick Institute for helping with the RNA sequencing analysis; the Flow Cytometry Unit at the Francis Crick Institute, particularly S. Purewal and J. Cerveira, for invaluable technical help; the Cell Services Unit at the Francis Crick Institute; C. Moore (The Francis Crick Institute) for intra-tracheal injections; and I. Pshenichnaya, P. Humphreys, S. McCallum and Cambridge Stem Cell Institute core facilities for technical assistance. We acknowledge support from the FLI Core Facility Proteomics, which is a member of the Leibniz Association and is financially supported by the Federal Government of Germany and the State of Thuringia. This work was supported by the Francis Crick Institute, which receives its core funding from Cancer Research UK (FC001112), the UK Medical Research Council (FC001112), and the Wellcome Trust (FC001112) and the European Research Council grant (ERC CoG-H2020-725492); and by the Wellcome Trust—MRC Stem Cell Institute, which receives funding from the Sir Henry Dale Fellowship from Wellcome, the Royal Society (107633/Z/15/Z) and the European Research Council Starting Grant (679411).
The authors declare no competing interests.
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Peer review information Nature thanks Marie-Liesse Asselin-Labat, Thomas Tüting and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Extended data figures and tables
a, sLP–mCherry design. b, Fluorescence images of labelling-4T1 cells after thawing. Scale bar, 10 μm. c, Representative FACS plot of labelling-4T1 cells. d, In vitro cultures of the indicated cell types with LCM: culture scheme and representative fluorescence images of HC11 (mouse mammary epithelial cells) and hNLF (human normal lung fibroblasts) with LCM (scale bar, 10 μm). e, FACS plots of 4T1, HC11, RAW264.7 (mouse macrophages), hNLF and mouse breast CAFs cultured with LCM. f, FACS analysis of 293T cells cultured with LCM, at different time points after LCM removal (black dots); white dots show the theoretical decrease considering the cell proliferation rate only (the amount of 293T cells labelled with mCherry after 24 h incubation with LCM was set to 100%). g, Representative fluorescence image of 4T1-CD63–GFP cells cultured with LCM. Scale bars: main panels, 5 μm; enlarged region, 1 μm. h, Representative correlative light and electron microscopy of labelling-4T1 cells showing re-uptake of sLP–mCherry (n = 5 different cells analysed). Top left, bright-field image overlaid with mCherry immunofluorescence (∼700 nm optical section). Bottom left, electron microscopy of the same cell (∼70-nm section thickness). Centre, best approximation of immunofluorescence–bright-field–electron microscopy overlay (scale bar, 5 μm). Right, electron microscopy of the outlined regions (centre, labelled a–c) (black arrows point at vesicular structures containing mCherry; scale bar, 1 μm). i, j, Analysis of in vitro labelling potential of soluble fraction and extracellular vesicles isolated from LCM by FACS. i, Schematic representation of LCM fractionation. j, HC11 cells cultured with either LCM, soluble fraction after depletion of extracellular vesicles (soluble) or purified extracellular vesicles. k, ImageStream analysis of mCherry+ extracellular vesicles in LCM (16% of total extracellular vesicles are mCherry+). Data are representative of three (b), ten (c) or two (d–g, j, k) independent experiments.
a, b, Distance of labelled cells within metastases. a, Representative fluorescence images (lines measure the maximum distance of labelled cells (mCherry+) from labelling-4T1 cells (mCherry+GFP+); scale bar, 50 μm). b, Quantification of labelling distance in micro-metastases (n = 11) and macro-metastases (n = 4). c, Correlation between the percentage of mCherry-labelled niche cells and the percentage of cancer cells in metastatic lungs analysed by FACS. Left, analysis of lungs with a small number of cancer cells (n = 14 mice). Right, analysis with all cancer cell frequencies (n = 31 mice). Statistical analysis by Pearson correlation. d–f, CD45+ cell frequency on live cells in distal lung, mCherry+ niche and not-injected naive lungs by FACS. d, BALB/c mice injected with labelling-4T1 cells (n = 5 mice per group). e, BALB/c mice injected with labelling-HC11 cells (n = 4 mice). f, RAG1-knockout mice injected with labelling-4T1 cells (n = 10 mice). Statistical analysis by paired two-tailed t-test. Data are represented as mean ± s.e.m.
a, b, CD11b+ (a) and Ly6G+ (b) cell frequencies among live cells in distal lung and mCherry+ niche by FACS (n = 9 mice per group). c, Enriched processes by MetaCore analysis and GSEA based on proteomic data by comparing mCherry+-niche (n = 3) and distal lung (n = 3) neutrophils; dominant mCherry+-niche proteins were obtained by using WebGestalt (http://www.webgestalt.org/option.php). d, PCA of proteins found in unlabelled or mCherry+-niche neutrophils (n = 3, each with 10 mice, small circles; large circles represent the average of the triplicates). e, f, Representative FACS plot (e) and scatter plot (f) of intrinsic ROS in Ly6G+ cells (n = 6 mice). g, GFP signal quantification of 3D co-culture with GFP+ MMTV–PyMT cancer cells and MACS-sorted Ly6G+ cells from either naive or metastatic lungs with or without the ROS inhibitor TEMPO (n = 3, each with 3 technical replicates). Data are normalized to cancer cell growth (statistical analysis on biological replicates). h, Representative cancer cell growth on the scaffold (from 14 independent experiments): integrated density of the GFP signal was measured on the scaffold using ImageJ and the corresponding fluorescent image of GFP+ cancer cell growth (scale bar, 400 μm). Statistical analysis by paired two-tailed t-test (a, b, f), hypergeometric test with Benjamini–Hochberg correction (c, Metacore), weighted Kolmogorov–Smirnov-like statistic with Benjamini–Hochberg correction (c, GSEA) and two-way ANOVA (g). Data are presented as mean ± s.d. (f) and mean ± s.e.m. (g).
a, b, GSEA of upregulated genes in mCherry+-niche cells. a, Percentage of correlating processes related to the indicated activity. b, Specific signalling pathways (indicated by the ∗ in a) at early or late time point. c, MetaCore analysis of genes differentially expressed in RNA-seq data, comparing early (n = 3) or late (n = 3) mCherry+ samples versus the respective mCherry− samples (see Fig. 3a, b). Statistical analysis by hypergeometric test with Benjamini–Hochberg correction.
a, b, Representative immunofluorescence images of lung metastatic tissues (n = 2 mice) stained for GFP (green) to detect labelling-4T1 cells, WISP1 (red) and DAPI (blue), showing distal lung and metastatic areas (a; scale bar, 50 μm), and a representative image showing the enrichment of WISP1+ cells within lung metastasis including niche cells (white arrows) (b; scale bar, 50 μm). c–e, WISP1-blocking antibody treatment in vivo. c, Experimental design (IT, intratracheal injection; IP, intraperitoneal injection). d, Metastatic outcome measured as the percentage of lung area covered by metastases (quantification was performed on two lung levels 100 μm apart). e, Representative H&E staining (n = 5 mice per group; black arrows show metastatic foci). Scale bar, 500 μm. Two experiments with lower overall metastatic frequency are quantified in Fig. 3e. Statistical analysis by two-way ANOVA (d). Data are presented as mean ± s.e.m.
a–c, Histology of sections of human breast tumour lung metastases. a, Representative image of distal lung (scale bar, 100 μm). b, Image from the tumour–lung interface showing expression of the pneumocyte marker thyroid transcription factor 1 (TTF1) (scale bar, 50 μm). c, Representative histology of the metastatic border (scale bar, 100 μm). d–f, Alveolar cell proliferation in human breast tumour lung metastases analysed by immunofluorescence. Representative images from distal lung (d) and metastatic border (e) showing TTF1 (red), Ki67 (green) and DAPI (blue). Scale bars: all 100 μm, except e (far right), 50 μm. f, Quantification of alveolar proliferation. Box edges show 25th and 75th percentiles, the horizontal line shows the median and whiskers show the range of values. Statistical analysis by paired two-tailed t-test. Tissue sections from n = 4 independent patients were analysed.
a, GFP+ MMTV–PyMT cancer cell proliferation in 2D co-culture with MACS-sorted EPCAM+ and Ly6G+ cells stained with EdU and analysed by FACS (n = 3 independent experiments). Data are normalized to cancer cell proliferation. b–d, Three dimensional co-culture of GFP+ MMTV-PyMT cancer cells with MACS-sorted EPCAM+ and Ly6G+ cells. b, Co-culture scheme. c, Representative images from four independent experiments (day 4; scale bar, 400 μm). d, Quantification of GFP signal. Data are normalized to cancer cell growth (n = 4 independent experiments (dots), each with 3–4 technical replicates). Statistical analysis of biological replicates by one-sample two-tailed t-test (a) and two-way ANOVA (d). Data are represented as mean ± s.e.m.
a, t-SNE plots of CD45− cells isolated from distal lung (n = 1,996) or mCherry+ niche (n = 1,473) after scRNA-seq analysis. Stromal cells are coloured on the basis of expression levels of the indicated genes. b, t-SNE niche plots from data in a; each plot shows (in red) the cells expressing the indicated stromal marker. c, MetaCore pathway enrichment analysis using the list of genes detected in at least 50% of the indicated marker-defined cells (n = 66 THY1+ cells, n = 175 PDGFRB1+ cells, n = 322 PDGFRA+ cells, n = 330 ACTA2+ cells, n = 25 LGR6+ cells). Statistical analysis by hypergeometric test with Benjamini–Hochberg correction.
a, Representative FACS plots showing Lin− (CD45−CD31−Ter119−) cells in distal lung and mCherry+ niche from labelling-4T1-injected mice (quantification in Fig. 4i). b, c, Scatter plots showing FACS quantification of EPCAM+SCA1+ cell frequency on Lin− (CD45−CD31−Ter119−) cells in distal lung and mCherry+ niche with injection of labelling-RENCA (b; n = 5 mice) and labelling-CT26 (c; n = 4 mice). d–f, Scatter plot of CD49f+CD104+ cell frequency among Lin− (CD45−CD31−Ter119−) cells in distal lung and mCherry+ niche detected by FACS (d; n = 5 mice), representative FACS plots (e) and representative immunofluorescence image of FACS-sorted mCherry+-niche CD49f+CD104+ cells stained for E-cadherin (green) and with DAPI (blue) (f; scale bar, 20 μm). g–i, Three-dimensional co-culture of GFP+ MMTV–PyMT cancer cells with MACS-sorted EPCAM+ cells. g, Quantification of integrin β4 (CD104) expression on EPCAM+ cells. h, Number of CD104+ cells proximal to cancer cells (n = 4 from three independent sorts). i, Representative immunofluorescence image from the co-culture stained for CD104 (red), GFP+ cancer cells (green) and with DAPI (blue). Scale bar, 20 μm. Statistical analysis of biological replicates by paired two-tailed t-test (b–d, g). Data are presented as mean ± s.e.m.
a, Representative immunofluorescence images of lung metastatic sections (n = 3 mice) co-stained for an airway marker (SCGB1A1 (top; white) or SOX2 (bottom; white)) and mCherry (red), and with DAPI (blue). Scale bar, 100 μm. b, c, Lung organoids from EPCAM+ FACS-sorted cells in co-culture with either lung stromal CD31+ cells or MLg fibroblasts, alone or in the presence of non-labelling 4T1-GFP cells from metastatic lungs in the lower chamber; quantification (b) and representative bright-field images (c; scale bar, 150 μm) of organoids. d, e, Lung organoids with Scgb1a1-CreERT2 lineage cells with or without 4T1-GFP: quantification (d) and representative bright-field images (e; scale bar, 150 μm). f, Representative staining of lineage cells in metastatic lungs from Scgb1a1-CreERT2 mice injected with MMTV–PyMT cancer cells. Scale bars: top left, 200 μm; other panels, 50 μm; top middle inset, 25 μm. Data are generated with sorted EPCAM+ (b) or club-lineage cells (d) and represented as cumulative percentage presented as mean ± s.d. of three co-cultures per sorting. Statistical analysis by two-tailed t-test on original non-cumulative values (b, d). Images are representative of three organoid cultures (c, e).
FACS gating strategy examples, a list of antibodies used for FACS and immune-staining, a list of primers used for the qRT–PCRs (Fig. 4h) and information about the human pulmonary breast cancer metastases from four patients. In addition, supplementary data shows the sLP-mCherry nucleotide sequence (design shown in Ext.Data Fig.1a) that was cloned in a pRRL lentiviral backbone.
The entire list of differentially detected proteins (AVG log2 ratio) in mCherry-niche versus unlabelled Ly6G+ neutrophils. Differences were considered when changes were >0.58 and <−0.58.
Upregulated genes (>2 fold) in non-immune-mCherry-niche compared to unlabelled lung tissue at both 5 and 10 days post cancer cells seeding.
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Ombrato, L., Nolan, E., Kurelac, I. et al. Metastatic-niche labelling reveals parenchymal cells with stem features. Nature 572, 603–608 (2019). https://doi.org/10.1038/s41586-019-1487-6
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