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Stiff matrix induces exosome secretion to promote tumour growth

Nature Cell Biology volume 25, pages 415–424 (2023)Cite this article

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An Author Correction to this article was published on 12 February 2024

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Abstract

Tissue fibrosis and extracellular matrix (ECM) stiffening promote tumour progression. The mechanisms by which ECM regulates its contacting cells have been extensively studied. However, how stiffness influences intercellular communications in the microenvironment for tumour progression remains unknown. Here we report that stiff ECM stimulates the release of exosomes from cancer cells. We delineate a molecular pathway that links stiff ECM to activation of Akt, which in turn promotes GTP loading to Rab8 that drives exosome secretion. We further show that exosomes generated from cells grown on stiff ECM effectively promote tumour growth. Proteomic analysis revealed that the Notch signalling pathway is activated in cells treated with exosomes derived from tumour cells grown on stiff ECM, consistent with our gene expression analysis of liver tissues from patients. Our study reveals a molecular mechanism that regulates exosome secretion and provides insight into how mechanical properties of the ECM control the tumour microenvironment for tumour growth.

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Fig. 1: Stiff ECM promotes exosome secretion.
Fig. 2: Akt promotes exosome secretion from cells grown on stiff matrix.
Fig. 3: Rab8 regulates stiff ECM-mediated exosome secretion.
Fig. 4: Rabin8 is phosphorylated and activated by Akt in cells grown on stiff ECM.
Fig. 5: Exosomes induced by stiff matrix promote tumour growth.
Fig. 6: Notch signalling is activated in cells grown on stiffness ECM or treated with Exostiff.
Fig. 7: Jagged1 is enriched in Exostiff.

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Data availability

Source data are provided with this paper. For patient cohort expression data, the accession code is in the methods section (GSE14520). The gene expression and clinical data for the LCI dataset including 486 tumours and matched non-tumour liver specimens (non-tumour 239 and tumour 247) are available on Gene Expression Omnibus GSE14520 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=gse14520). All other data supporting the findings of this study are available from the corresponding author on reasonable request.

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Acknowledgements

The work is supported by NIH grants R35 GM141832 to W.G., NCI U01 CA250044 to R.R., V.M.W. and W.G., NCI intramural research programme Z01 BC 010877, Z01 BC 010876, Z01 BC 010313 to H.D. and X.W.W., and Abramson Cancer Center Support Grant (CA016520) to P.A.G.

Author information

Author notes

  1. These authors contributed equally: Bin Wu, Di-Ao Liu, Lei Guan.

Authors and Affiliations

  1. Department of Biology, School of Arts & Sciences, University of Pennsylvania, Philadelphia, PA, USA

    Bin Wu, Di-Ao Liu, Lei Guan, Phyoe Kyawe Myint, Ye Xu, Jinqi Ren, Ziyan Yu, Sophie Jabban & Wei Guo

  2. Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    LiKang Chin & Rebecca G. Wells

  3. Department of Surgery, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA

    Hien Dang

  4. Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Ting Li, Youhai H. Chen, Emma E. Furth & Rebecca G. Wells

  5. Knight Cancer Institute, Oregon Health and Science University, Portland, OR, USA

    Gordon B. Mills

  6. Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA

    Jonathan Nukpezah, Rebecca G. Wells & Ravi Radhakrishnan

  7. Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Emma E. Furth & Phyllis A. Gimotty

  8. Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA

    Phyllis A. Gimotty

  9. Department of Surgery, Center for Bioengineering and Tissue Regeneration, University of California, San Francisco, San Francisco, CA, USA

    Valerie M. Weaver

  10. Laboratory of Human Carcinogenesis and Liver Cancer Program, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA

    Xin Wei Wang

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Contributions

B.W., D.-A.L., L.G. and W.G. conceived the project and designed the experiments. B.W. (Figs. 1a,d, 2a, 3f and 4c,e,f and Extended Data Fig. 1a,c–e), L.G., D.-A.L. (Figs. 1f and 2c,d,k and Extended Data Figs. 1b,f, 2c, 3b,c and 4d), Y.X. and P.K.M. (Figs. 1e,f, 2b, 3e and 6a and Extended Data Fig. 3f) purified and characterized the exosomes. B.W., L.G., D.-A.L., Y.X., L.C. and P.K.M. performed the polyacrylamide gel and cell culture experiments. B.W. (Figs. 3a–d, 4a,b,d, 6b and 7e and Extended Data Figs. 2b and 3a), D.-A.L. (Figs. 1b,c, 2e,h–j, 3g,h and 7a–d and Extended Data Fig. 4a–c), L.G., Z.Y. and Y.X. performed western blot analysis. B.W. and L.G. performed the immunoprecipitation (Fig. 4d–f). B.W. performed the BRET assay, cell proliferation assay, the immunofluorescence (Figs. 2f,g and 3i,j) and electronic microscopy imaging. B.W., L.G., L.C. and T.L. performed the mouse experiments. J.R. performed the GEF assay (Figs. 4g,h). H.D. performed the clinical data analysis. G.B.M. performed the RPPA experiments. J.N. and R.R. performed bioinformatics analyses. B.W., L.G., D.-A.L., Z.Y., H.D., Y.X., E.E.F., X.W.W. and W.G. analysed and interpreted the data. P.A.G. helped with the statistical analysis. B.W. and W.G. wrote the paper. L.G., D.-A.L., Y.X., P.K.M., L.C., S.J., R.G.W., X.W.W., Y.H.C., R.R. and V.M.W. edited the paper. All authors have read and approved the final manuscript.

Corresponding author

Correspondence to Wei Guo.

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Nature Cell Biology thanks Jacky G. Goetz, Adam Engler, Marino Zerial 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 Characterization of exosomes derived from different cells.

a, Representative TEM image of exosomes purified from the conditioned media of Huh7 cells. Scale bar: 100 nm. b, Purified exosome proteins were quantitated by Bradford assay and the mean was normalized to 1 for exosomal proteins from soft (0.5 kPa) matrix. Exosomes were collected from equal numbers of cells. Values are presented as Mean ± S.D. n = 3. c, The mean diameters of exosomes purified from the conditioned media of Huh7 cells on soft or stiff matrix. Values are presented as mean ± S.D. 3 independent experiments were performed. At least 106 of purified exosomes were measured by NTA for each experiment. d, Exosomes (10 µg) derived from Huh7 cells on soft or stiff matrix were diluted with 1 ml PBS. The particle concentration was determined by NTA. Values are presented as Mean ± S.D. n = 3. e, Exosomes released from the same number of primary hepatocytes grown on matrix with different stiffness were quantified, and the concentration of exosomes released from cells were normalized to the 0.5 kPa group. Values are presented as Mean ± S.D. n = 3. F, Exosomes released from the same number of MCF10A, MCF10AT, and MCF10CA cells grown on matrix with different stiffness were quantified. The amounts of exosomes released from the cells were normalized to the 0.5 kPa for each cell line. Mean ± S.D. n = 3. Source numerical data and unprocessed blots are available in source data. n represents the number of independent experiments.

Source data

Extended Data Fig. 2 Exosome secretion from Huh7 cells treated with Akt and FAK inhibitors.

a, Volcano plot of RPPA data displaying the pattern of protein expression for Huh7 cells cultured on stiff (10 kPa) matrix relative to soft (0.5 kPa) matrix. Significantly up- and down-regulated proteins are indicated by red and blue dots, respectively (cut-off p < 0.05). All the data points were normalized for protein loading and transformed to Log2 values (labeled “NormLog2” on X-axis). b, Western blots showing the up-regulation of p-Akt but not p-ERK in Huh7 cells grown on stiff ECM. Molecular weights (in kDa) are shown to the right. c, Huh7 cells on soft or stiff matrix were treated with DMSO or Akt inhibitor GDC-0068. The conditioned media were collected and proceeded for NTA. Exosome concentration from the cells treated with DMSO on soft matrix was normalized to 1. Values are presented as Mean ± S.D., n = 3. d-f, Huh7 cells were treated with DMSO or various concentrations of Akt inhibitors MK-2206, GDC-0068 or FAK inhibitor PND-1168. Cell viability was examined by CCK-8 assay and normalized to the value of DMSO treated group. Values are presented as Mean ± S.D. n = 3. Source numerical data and unprocessed blots are available in source data. n represents the number of independent experiments.

Source data

Extended Data Fig. 3 Characterization of Rab8 and Rabin8 in cells grown on different matrix.

a, Huh7 cells were transfected with GFP or GFP-Rab8 and grown on soft matrix. Exosomes in the conditioned media were purified by ultracentrifugation, and exosomes from the same number of cells were loaded for western blotting with antibodies against exosome markers HRS and CD63. b, Conditioned media from cells expressing GFP or GFP-Rab8 and treated with DMSO or MK-2206 were collected and proceeded for NTA. Exosome concentration was normalized to those from GFP expressing cells treated with DMSO. Values are presented as Mean ± S.D. n = 3. c, Conditioned media from cells with control or Rab8 shRNA treated with DMSO or MK-2206 were collected and proceeded for NTA. Exosome concentration was normalized to those from cells with control shRNA and DMSO. Values are presented as Mean ± S.D. n = 3. d, Sequence alignment of Rabin8 from different species. The phosphorylation site Serine 149 was shown in red. e, Schematic diagram showing the use of BRET in analyzing Rabin8 conformation. NanoLuc (BRET donor) and HaloTag (BRET acceptor) were fused to the N and C terminus of Rabin8, respectively. When Rabin8 is adopted in a “closed” conformation and autoinhibited, BRET will occur owing to the close proximity between the donor and acceptor. If Rabin8 switches to an “open” conformation induced by Akt phosphorylation on S149, the BRET signal will decrease. f, Huh7 cells were transfected with different Rabin8 variants (WT, S149A, and S149D). Conditioned media were collected and proceeded for NTA. Exosome concentration was normalized to those from cells expressing wild type Rabin8 on soft matrix (n = 3). Values are presented as Mean ± S.D. Source numerical data and unprocessed blots are available in source data. n represents the number of independent experiments.

Source data

Extended Data Fig. 4 Hepa1-6 cells secreted more exosomes when grown on stiff Matrix.

a, Hepa1-6 cells were cultured on soft (0.5 kPa) or stiff (10 kPa) matrix. Exosomes in the conditioned media were purified. Quantification of the exosomal proteins by Bradford assay. The amounts of exosomal proteins were normalized to those from soft matrix. Values are presented as Mean ± S.D. n = 3. b, Exosomes from the same number of cells were analyzed by immunoblotting using antibodies against indicated exosome markers. c, Quantification of the levels of HRS, Syntenin-1, CD63, Alix and Tsg101 is presented. Mean ± S.D. n = 3. d, Exosomes released from the same number of Hepa1-6 cells grown on matrix with different stiffness were quantified, and the concentration of exosomes released from cells grown on 0.5 kPa matrix were normalized as 1. Values are presented as Mean ± S.D. n = 3. n represents the number of independent experiments. e, Growth curves of Hepa1-6 tumors in C57L/J mice injected with PBS or the same amounts of exosomes derived from Hepa1-6 cells treated with DMSO or MK-2206 (n = 5 mice). Values are presented as Mean ± S.D. Source numerical data and unprocessed blots are available in source data.

Source data

Extended Data Fig. 5 Expression of the Notch pathway proteins in Huh7 cells grown on soft or stiff matrix.

Heatmap of RPPA data showing the levels of the Notch pathway proteins in Huh7 cells grown on soft (0.5 kPa) or stiff (10 kPa) matrix. Source numerical data is available in source data.

Source data

Extended Data Fig. 6 Gene expression analysis of liver tissues from patients.

Box and whisker plot (bars represent 10-90 percentile, dots represent outliers) of albumin levels in the serum of 226 HCC patients with high (n = 113 patients) or low (n = 113 patients) Notch gene expression (p value is from Mann-Whitney test (two-tailed). b, Box and whisker plot (bars represent 10-90 percentile, dots represent outliers) of alanine transaminase (ALT) levels in the serum of 226 HCC patients with high (n = 113 patients) or low (n = 113 patients) Notch gene expression (p value is from Mann-Whitney test (two-tailed). c, Analysis of Notch-high and Notch-low patients with HSC or without (nHSC) the HSC gene signature (Fishers Exact test). d, Notch-high (n = 113 patients) and Notch-low (n = 113 patients) patients with or without cirrhosis (Fishers Exact test). The proportion of patients with high Notch genes expression in each group were analyzed (Fishers Exact test). e, Survival risk prediction analysis based on the expression data of four Notch associated genes, HEY1, HEY2, HES1, and SOX9 in non-tumor tissues derived from 226 HCC patients (Kaplan-Meier Cox Log Rank test between two groups and leave one out permutation analyses (1000X)). f, Top enriched signaling pathways associated with Notch activation. Ingenuity Pathway Analysis was performed on 1,872 differentially expressed genes (p < 0.001) between high-Notch) and low-Notch patient non-tumor samples (see Methods for detail). -log(p-value) were calculated using Fisher’s Exact test with Bonferroni correction. g, Box and whisker plot (bars represent 10-90 percentile, dots represent outliers) analysis of Jagged1 expression in 226 HCC patients with Notch-high (n = 113 patients) and Notch-low (n = 113 patients) expression.

Source data

Extended Data Fig. 7 RPPA of the exosomal proteins collected from Huh7 cells grown on soft or stiff matrix.

Volcano plot of RPPA data displaying the pattern of protein expression in exosomes derived from Huh7 cells cultured on stiff relative to soft matrix. Significantly up- and down-regulated proteins are indicated by red and blue dots, respectively (cut-off p < 0.05). All the data points were normalized for protein loading and transformed to Log2 values on X axis. Source numerical data is available in source data.

Source data

Supplementary information

Supplementary Information

Supplementary Table 1. Antibody list.

Reporting Summary

Source data

Source Data Fig. 1

Unprocessed western blots and/or gels.

Source Data Fig. 2

Unprocessed western blots and/or gels.

Source Data Fig. 3

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Wu, B., Liu, DA., Guan, L. et al. Stiff matrix induces exosome secretion to promote tumour growth. Nat Cell Biol 25, 415–424 (2023). https://doi.org/10.1038/s41556-023-01092-1

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