Abstract
Breast cancer becomes invasive when carcinoma cells invade through the basement membrane (BM)—a nanoporous layer of matrix that physically separates the primary tumour from the stroma. Single cells can invade through nanoporous three-dimensional matrices due to protease-mediated degradation or force-mediated widening of pores via invadopodial protrusions. However, how multiple cells collectively invade through the physiological BM, as they do during breast cancer progression, remains unclear. Here we developed a three-dimensional in vitro model of collective invasion of the BM during breast cancer. We show that cells utilize both proteases and forces—but not invadopodia—to breach the BM. Forces are generated from a combination of global cell volume expansion, which stretches the BM, and local contractile forces that act in the plane of the BM to breach it, allowing invasion. These results uncover a mechanism by which cells collectively interact to overcome a critical barrier to metastasis.
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Data availability
Raw images are available from the corresponding author upon request due to the large file sizes of images. Source data are provided with this paper.
Code availability
The code for the theoretical model is available via GitHub at https://github.com/edwinnewton/Collective-invasion-of-the-basement-membrane-in-breast-cancer.
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Acknowledgements
We gratefully acknowledge an Advancing Science in America (ARCS) fellowship for J.C., a National Defense Science and Engineering Graduate fellowship for J.C., a National Science Foundation Graduate Research fellowship for J.C., a National Institutes of Health National Cancer Institute Grant (R37 CA214136) to O.C. and a National Institute of General Medicine Grant (R35 GM136226) to L.H. L.H. is an Irma T. Hirschl Career Scientist. The computational work was supported by National Cancer Institute awards U54CA261694 (to Z.S. and V.S.); National Institute of Biomedical Imaging and Bioengineering awards R01EB017753 (to V.S.) and R01EB030876 (to V.S.); NSF Center for Engineering Mechanobiology Grant CMMI-154857 (to Z.S. and V.S.); and NSF Grant DMS-1953572 (to V.S.). The funding from the Office of Research and Development in the Palo Alto VA Medical Center pays the salary for M.P.M. We thank J. Notbohm (The University of Wisconsin-Madison) for providing the MATLAB program to compute the curvature of the BM.
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Contributions
Conceived and designed the experiments: J.C., A.S. and O.C. Performed the experiments: J.C., A.S., S.V., C.S., N.H.K.A., D.I., R.S., K.L. and L.H. Contributed to the analytical guidance: A.S., S.S., L.H. and M.P.M. Designed and implemented the computational model: Z.S. and V.S. Supervised and administered the project: M.C.B., R.B.W. and O.C. Acquired the funding: O.C. Wrote the manuscript: J.C., A.S., Z.S., S.V., V.S. and O.C.
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Extended data
Extended Data Fig. 1 Loss tangent and permanent strain of soft and stiff IPNs, basement membrane in transformed cells and after encapsulation of MCF10A cells into IPNs.
a, Loss tangent of alginate-rBM IPNs (soft and stiff) (N = 3–6 gels). b, Representative creep and recovery test. Example creep and recovery test used to measure plasticity, in which plasticity is quantified as the remaining strain after 10,000 seconds divided by the total deformation during the creep test. c, Permanent strain of alginate-rBM IPNs (soft and stiff) (N = 3–6 gels). d-e, Confocal images of nuclei, collagen-IV, and laminin of MCF10AT (d) and MCF10CA1a acini (e). f, No additional laminin secretion observed in BM after encapsulation of acini into IPNs. Laminin-antibody added to MCF10A acini before IPN encapsulation (green) and laminin-antibody added after IPN encapsulation (yellow) show no new secretion of laminin within 24 hours. Two-sided unpaired t-test was performed for panels (a) and (c). Scale bars, 25 μm (d, e), 20 μm (f).
Extended Data Fig. 2 Analysis of BM volume after the breaching.
a a, Time-lapse of cell invasion (brightfield) and BM (cyan) movement. b, Time-lapse outlines of BM over twenty hours. c, Normalized volumes of BM shells over twenty hours. Scale bars, 20 μm (a).
Extended Data Fig. 3 Measurement of BM plasticity through hypotonic loading.
a, Schematic of an acini in normal media (left), hypotonic media (middle), and triton-EDTA solution following treatment in hypotonic media (right) seeded on rBM. b, Overlay of confocal images of BM (cyan) and the corresponding phase image of acini in normal media (left), hypotonic media (middle), and triton-EDTA solution (right). c, Radii of acini in reference, hypotonic-loading, and unloading conditions of control and hypotonic-treated acini (N = > 3 acini). d, Normalized radii of acini in reference, hypotonic-loading, and unloading conditions of control and hypotonic-treated acini (N = > 3 acini). e, Radial strain in reference, hypotonic-loading, and unloading conditions of control and hypotonic-treated acini (N = > 3 acini). f, Mechanical plasticity (or residual radial strain) of acini in soft IPN with control and hypotonic media (N = > 3 acini). Two-sided Welch’s t-test was performed for panel (a). Scale bar, 25 μm (a).
Extended Data Fig. 4 Role of proliferation in invasion, and measure of cell and nuclei volumes.
a, Confocal images of nuclei, F-actin, pFAK and merged images of acini in stiff IPN with control. b, Confocal images of nuclei, F-actin, pFAK and merged images of acini in stiff IPN with PI3K inhibitor. c, Percentage of invasive acini in stiff IPNs with and without inhibition of proliferation by mitomycin C (N = 3 gels). d, Cell volume in invasive front and acini of invasive acini. No differences in average cell volume between cells in invasive front and cells within the acini of invasive acini in stiff IPNs (N => 30 acini in 3 gels). e, Measurement of nuclei volume in stiff, soft, and stiff + GSK205 conditions. No differences in nuclei volume between soft, stiff, and GSK205 treated stiff IPNs (N => 30 acini in 3 gels). Two-sided Unpaired t-test was performed for panels (c) and (d). One-way ANOVA was performed for panel (e). Scale bar, 50 μm (a), 25 μm (b).
Extended Data Fig. 5 E-cadherin blocking, gap junction inhibition and Cx43 KO.
a, b, Confocal images of nuclei, F-actin, and α-catenin, and corresponding merges under control, and DECMA-treated conditions encapsulated in stiff IPNs on Day 1. c, d, Confocal images of nuclei, F-actin, and β-catenin, and the corresponding merge under control, and DECMA-treated conditions encapsulated in stiff IPNs on Day 1. e, Average cell volume was decreased when treated with gap junction inhibitor compared to control (N = > 30 acini in 3 gels). f, Percentage of invasion was significantly higher in control compared to Cx43 KO cells (N = 3 gels). g, Acini area were similar in control and Cx43 KO conditions. Acini of Cx43 KO cells were more circular compared to the control condition. BM area to average acini area were similar in control and Cx43 KO conditions (N = > 6 acini in 3 gels). Two-sided Welch’s t-tests were performed for panels (e), (f), and (g). Scale bar, 25 μm (a-d).
Extended Data Fig. 6 Laser ablation of cell-cell and cell-BM interfaces in acini.
a, c, Confocal images of F-actin at −1, 0, and 1 min where 0 min correspond to right after laser ablation of cell-cell (a; left; highlighted by the dotted line) and cell-BM edge (c; left; highlighted by the dotted line). Deformation vectors from laser ablation were overlaid on the confocal images of the F-actin in middle and right panels. b, d, Deformation magnitude in the plane of laser ablation right after the ablation of cell-cell (b) and cell-BM edges (d). Scale bar, 25 μm.
Extended Data Fig. 7 Analysis of collective invasion, BM curvature, and collective motion of cells.
a, Histogram of differences between the angle between cell invasion and laminin indentation (N = 10 acini in 3–6 gels). b, Representative image of direction of cell movement within the acini compared to BM curvature. Arrow in points to area of BM deformation. c, Acini actin with cell velocity vectors shown in cyan. d, Schematic of region analyzed for cell velocity measurements. e-f, Tangential cell velocities and radial cell velocities, normalized by the total velocity, in acini with intact BM and breached BM (N = > 30 acini in 3 gels). Two-sided unpaired t-test was performed for panels (e) and (f). Scale bar, 25 μm (c).
Extended Data Fig. 8 Heterogeneous K14 staining for cells in invasive clusters.
Cytokeratin-14 (red), actin (green) and DAPI (blue) staining in acini of soft and stiff IPNs. Scale bar, 25 μm.
Extended Data Fig. 9 Optimized FRET biosensor for RhoA GTPase.
a, Schematic representation of the optimized, single-chain, genetically-encoded FRET biosensor for RhoA GTPase, based on the previously published design36. Fluorescent proteins are replaced with monomeric versions containing the A206K mutations, and the dipole coupling angle is optimized by using a circular permutation of the donor at position 173. b, Representative, normalized fluorescence emission spectra are shown, from the constitutively activated Q63L (‘Active Biosensor’) and the dominant negative T19N (‘Inactive Biosensor’) mutant versions of the biosensors overexpressed in live cell suspensions of HEK293T cells, excited at 433 nm and the emission scanned from 450 nm to 600 nm. Spectra are normalized to the emission maxima of the donor fluorophore at 427 nm. c, Changes in FRET/donor ratio responses comparing active versus inactive mutant versions of the RhoA biosensor during optimization of the fluorescent protein FRET pair. ‘dd’ indicates original RhoA biosensor36 containing the dimerizing A206 residue in both the donor and the acceptor fluorescent proteins, ‘mm’ indicates A206K monomeric mutations are introduced into the original ECFP and the Citrine YFP, and ‘mmcp173’ indicates A206K monomeric mutations in both the donor and acceptor fluorescent proteins in addition to circular permutation of the donor at amino acid position 173 (N = 7 experiments for dd and mm, and N = 10 for mmcp173), shown with SEM. d, Fluorometric FRET/donor emission ratio of the optimized RhoA biosensor overexpressed in HEK293T cells. WT biosensor expression and the Q63L, G14V, and F30L constitutively activated mutant biosensors showed high emission ratios. The dominant negative T19N mutant biosensor, constitutively activated (Q63L) biosensor with non-specific binding domain (PBD) showed low emission ratios. 2-fold excess expression of the guanine nucleotide dissociation inhibitor-1 (GDI) showed reduced ratio for those that are targeted by GDI, whereas the Q63L mutant that does not bind GDI produced elevated ratio (N = 10 experiments for WT, Q63L and T19N, N = 9 for G14V, N = 8 for F30L, and all +GDI conditions, N = 6 for Q63L+PBD); all shown with SEM. e, Ratiometric microscopy measurements of the transiently expressed RhoA biosensor mutants in MCF10A cells under 60x magnification, and the quantification of the whole-cell average ratio values. White bars = 10 µm. Linear pseudocolor corresponds to the indicated scaling limits (N = 3 experiments); shown with 95% confidence intervals of the aggregate data points from the pooled datapoints. f, Competitive pull-downs of the optimized RhoA biosensor. Lane designations are also shown. The Q63L constitutively activated RhoA biosensor is pulled down by excess exogenous GST-RBD, only when the built-in RBD domain of the biosensor is exchanged for a non-Rho-specific PBD. Two-sided Student’s t-test was performed for panels (c), (d) and (e).
Extended Data Fig. 10 Biosensor expression analysis in MCF10A cells.
a, Inducible expression of the optimized RhoA biosensor in MCF10A cells, stably incorporating the biosensor under the tetracycline-OFF regulation. MCF10A cells stably transduced with the tet-OFF inducible biosensor expression system were FACS sorted to enrich for the biosensor-positive cell population and analyzed following the same biosensor induction protocol used in the current biological assays. b, Quantification of induced RhoA biosensor band intensities compared to the endogenous RhoA, indicating 37.8% +/−17.2% of the endogenous RhoA levels, shown with SEM, N = 3 experiments. c, Quantification of (a); induced expression of the RhoA biosensor does not affect the relative expression levels of endogenous RhoA (N = 3 experiments). d, Western blot detection of endogenous Cdc42, with or without RhoA biosensor induction. e, Quantification of (d); induced expression of the RhoA biosensor does not affect the relative expression levels of endogenous Cdc42 (N = 3 experiments). f, Western blot detection of endogenous Rac1, with or without RhoA biosensor induction. g, Quantification of (f); induced expression of the RhoA biosensor does not affect the relative expression levels of endogenous Rac1 (N = 3 experiments). h, β-Actin loading control for the Western blots in (a), (d), and (f). Two-sided Student’s t-test, paired-analysis was used for panels (c), (e) and (g).
Supplementary information
Supplementary Information
Supplementary Notes 1–5, Videos 1–19 and Tables 1 and 2.
Supplementary Video 1
Three-dimensional rendering of the confocal images of F-actin of MCF10A acini.
Supplementary Video 2
Three-dimensional rendering of the confocal images of laminin-332 of MCF10A acini.
Supplementary Video 3
Three-dimensional rendering of the confocal images of F-actin of invasive MCF10A acini encapsulated in stiff IPN.
Supplementary Video 4
Three-dimensional rendering of the confocal images of laminin-332 of invasive MCF10A acini encapsulated in stiff IPN.
Supplementary Video 5
Time-lapse images of F-actin (red) and laminin-332 (cyan) encapsulated in stiff IPN.
Supplementary Video 6
Time-lapse images of bright field and laminin-332 of MCF10A acini after breaching its BM.
Supplementary Video 7
Time-lapse images of F-actin of MCF10A acini encapsulated in stiff IPN.
Supplementary Video 8
Time-lapse images of laminin-332 of MCF10A acini encapsulated in stiff IPN.
Supplementary Video 9
Time-lapse images of F-actin of MCF10A acini post breaching its BM.
Supplementary Video 10
Time-lapse images of laminin-332 of a breached BM.
Supplementary Video 11
Three-dimensional rendering of the time-lapse images of laminin-332 of an MCF10A acini.
Supplementary Video 12
Laser ablation of the cell–cell interface in an MCF10A acini.
Supplementary Video 13
Laser ablation of the cell–BM interface in an MCF10A acini.
Supplementary Video 14
Time-lapse images of the confocal imaging of laminin-332 during BM breaching.
Supplementary Video 15
Time-lapse images of F-actin and laminin-332 of MCF10A acini when subjected to a hypotonic medium. Here 0 min corresponds to hypotonic treatment.
Supplementary Video 16
Time-lapse images of laminin-332 of MCF10A acini in control. Here 0 min corresponds to the respective treatment time.
Supplementary Video 17
Time-lapse images of laminin-332 of MCF10A acini in the hypotonic condition. Here 0 min corresponds to the respective treatment time.
Supplementary Video 18
Time-lapse images of laminin-332 of MCF10A acini in the hypotonic + ROCK condition. Here 0 min corresponds to the respective treatment time.
Supplementary Video 19
Time-lapse images of laminin-332 of MCF10A acini in the hypotonic + blebbistatin condition. Here 0 min corresponds to the respective treatment time.
Source data
Source Data Fig. 1
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Source Data Extended Data Fig./Table 1
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Source Data Extended Data Fig./Table 5
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Source Data Extended Data Fig./Table 9
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Source Data Extended Data Fig./Table 10
Source data for all the quantitative plots in this figure.
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Chang, J., Saraswathibhatla, A., Song, Z. et al. Cell volume expansion and local contractility drive collective invasion of the basement membrane in breast cancer. Nat. Mater. 23, 711–722 (2024). https://doi.org/10.1038/s41563-023-01716-9
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DOI: https://doi.org/10.1038/s41563-023-01716-9
