Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

ROCK-mediated selective activation of PERK signalling causes fibroblast reprogramming and tumour progression through a CRELD2-dependent mechanism

Nature Cell Biology volume 22, pages 882–895 (2020)Cite this article

Subjects

A Publisher Correction to this article was published on 04 June 2020

This article has been updated

Abstract

It is well accepted that cancers co-opt the microenvironment for their growth. However, the molecular mechanisms that underlie cancer–microenvironment interactions are still poorly defined. Here, we show that Rho-associated kinase (ROCK) in the mammary tumour epithelium selectively actuates protein-kinase-R-like endoplasmic reticulum kinase (PERK), causing the recruitment and persistent education of tumour-promoting cancer-associated fibroblasts (CAFs), which are part of the cancer microenvironment. An analysis of tumours from patients and mice reveals that cysteine-rich with EGF-like domains 2 (CRELD2) is the paracrine factor that underlies PERK-mediated CAF education downstream of ROCK. We find that CRELD2 is regulated by PERK-regulated ATF4, and depleting CRELD2 suppressed tumour progression, demonstrating that the paracrine ROCK–PERK–ATF4–CRELD2 axis promotes the progression of breast cancer, with implications for cancer therapy.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: ROCK activation enhances tumour burden, fibroblast numbers and ECM production.
Fig. 2: ROCK education of mammary fibroblasts yields a tumour-promoting fibroblast phenotype.
Fig. 3: ROCK education of mammary fibroblasts yields a tumour-promoting fibroblast phenotype through paracrine Creld2.
Fig. 4: Perk is selectively activated downstream of ROCK in mammary cancer.
Fig. 5: Perk signalling is required for the ROCK-induced, tumour-promoting education of mammary tumour fibroblasts.
Fig. 6: ROCK activation in mammary cancers induces Atf4-regulated Creld2 transcription downstream of actin stress.
Fig. 7: High CRELD2 expression is associated with progressive human breast cancer.

Similar content being viewed by others

Data availability

MS data have been deposited at ProteomeXchange with the primary accession code PXD018253 (http://www.ebi.ac.uk/pride). Source data for Figs. 1–7 and Extended Data Figs. 1–7 are provided with the paper. All other data supporting the findings of this study are available from the corresponding author on reasonable request.

Change history

References

  1. Boudreau, A., van’t Veer, L. J. & Bissell, M. J. An ‘elite hacker’: breast tumors exploit the normal microenvironment program to instruct their progression and biological diversity. Cell Adh. Migr. 6, 236–248 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  2. Sakakura, T., Suzuki, Y. & Shiurba, R. Mammary stroma in development and carcinogenesis. J. Mammary Gland Biol. Neoplasia 18, 189–197 (2013).

    Article  PubMed  Google Scholar 

  3. Gascard, P. & Tlsty, T. D. Carcinoma-associated fibroblasts: orchestrating the composition of malignancy. Genes Dev. 30, 1002–1019 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Luo, H., Tu, G., Liu, Z. & Liu, M. Cancer-associated fibroblasts: a multifaceted driver of breast cancer progression. Cancer Lett. 361, 155–163 (2015).

    Article  PubMed  CAS  Google Scholar 

  5. Cazet, A. S. et al. Targeting stromal remodeling and cancer stem cell plasticity overcomes chemoresistance in triple negative breast cancer Nat. Commun. 9, 2897 (2018).

  6. Erez, N., Glanz, S., Raz, Y., Avivi, C. & Barshack, I. Cancer associated fibroblasts express pro-inflammatory factors in human breast and ovarian tumors. Biochem. Biophys. Res. Commun. 437, 397–402 (2013).

    Article  CAS  PubMed  Google Scholar 

  7. Levental, K. R. et al. Matrix crosslinking forces tumor progression by enhancing integrin signaling. Cell 139, 891–906 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Kular, J. et al. A negative regulatory mechanism involving 14-3-3ζ limits signaling downstream of ROCK to regulate tissue stiffness in epidermal homeostasis. Dev. Cell 35, 759–774 (2015).

    Article  CAS  PubMed  Google Scholar 

  9. Wei, S. C. et al. Matrix stiffness drives epithelial–mesenchymal transition and tumour metastasis through a TWIST1–G3BP2 mechanotransduction pathway. Nat. Cell Biol. 17, 678–688 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Samuel, M. S. et al. Actomyosin-mediated cellular tension drives increased tissue stiffness and β-catenin activation to induce epidermal hyperplasia and tumor growth. Cancer Cell 19, 776–791 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Vennin, C. et al. CAF hierarchy driven by pancreatic cancer cell p53-status creates a pro-metastatic and chemoresistant environment via perlecan. Nat. Commun. 10, 3637 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Ozdemir, B. C. et al. Depletion of carcinoma-associated fibroblasts and fibrosis induces immunosuppression and accelerates pancreas cancer with reduced survival. Cancer Cell 25, 719–734 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Julian, L. & Olson, M. F. Rho-associated coiled-coil containing kinases (ROCK): structure, regulation, and functions. Small GTPases 5, e29846 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Boyle, S. T. & Samuel, M. S. Mechano-reciprocity is maintained between physiological boundaries by tuning signal flux through the Rho-associated protein kinase. Small GTPases 7, 139–146 (2016).

  15. Kim, H. J., Kim, J. G., Moon, M. Y., Park, S. H. & Park, J. B. IκB kinase gamma/nuclear factor-κB-essential modulator (IKKγ/NEMO) facilitates RhoA GTPase activation, which, in turn, activates Rho-associated KINASE (ROCK) to phosphorylate IKKβ in response to transforming growth factor (TGF)-β1. J. Biol. Chem. 289, 1429–1440 (2014).

    Article  CAS  PubMed  Google Scholar 

  16. Varga, A. et al. RAF1/BRAF dimerization integrates the signal from RAS to ERK and ROKα. Sci. Signal. 10, eaaai8482 (2017).

  17. Nobis, M. et al. A RhoA-FRET biosensor mouse for intravital imaging in normal tissue homeostasis and disease contexts. Cell Rep. 21, 274–288 (2017).

    Article  CAS  PubMed  Google Scholar 

  18. Boyle, S. T. et al. Acute compressive stress activates RHO/ROCK-mediated cellular processes. Small GTPases https://doi.org/10.1080/21541248.2017.1413496 (2018).

  19. Vennin, C. et al. Transient tissue priming via ROCK inhibition uncouples pancreatic cancer progression, sensitivity to chemotherapy, and metastasis. Sci. Transl. Med. 9, eaai8504 (2017).

  20. Rath, N. et al. ROCK signaling promotes collagen remodeling to facilitate invasive pancreatic ductal adenocarcinoma tumor cell growth. EMBO Mol. Med. 9, 198–218 (2017).

    Article  CAS  PubMed  Google Scholar 

  21. Ibbetson, S. J., Pyne, N. T., Pollard, A. N., Olson, M. F. & Samuel, M. S. Mechanotransduction pathways promoting tumor progression are activated in invasive human squamous cell carcinoma. Am. J. Pathol. 183, 930–937 (2013).

    Article  CAS  PubMed  Google Scholar 

  22. Samuel, M. S. et al. Tissue selective expression of conditionally-regulated ROCK by gene targeting to a defined locus. Genesis 47, 440–446 (2009).

    Article  CAS  PubMed  Google Scholar 

  23. Samuel, M. S. et al. Tissue-selective expression of a conditionally-active ROCK2-estrogen receptor fusion protein. Genesis 54, 636–646 (2016).

    Article  CAS  PubMed  Google Scholar 

  24. Liu, Z. W. et al. Protein kinase RNA-like endoplasmic reticulum kinase (PERK) signaling pathway plays a major role in reactive oxygen species (ROS)-mediated endoplasmic reticulum stress-induced apoptosis in diabetic cardiomyopathy. Cardiovasc. Diabetol. 12, 158 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. Feng, J. et al. Inhibitory phosphorylation site for Rho-associated kinase on smooth muscle myosin phosphatase. J. Biol. Chem. 274, 37385–37390 (1999).

    Article  CAS  PubMed  Google Scholar 

  26. Guy, C. T., Cardiff, R. D. & Muller, W. J. Induction of mammary tumors by expression of polyomavirus middle T oncogene: a transgenic mouse model for metastatic disease. Mol. Cell. Biol. 12, 954–961 (1992).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Lucchini, F. et al. Early and multifocal tumors in breast, salivary, harderian and epididymal tissues developed in MMTY-Neu transgenic mice. Cancer Lett. 64, 203–209 (1992).

    Article  CAS  PubMed  Google Scholar 

  28. Li, Y., Hively, W. P. & Varmus, H. E. Use of MMTV-Wnt-1 transgenic mice for studying the genetic basis of breast cancer. Oncogene 19, 1002–1009 (2000).

    Article  CAS  PubMed  Google Scholar 

  29. Amano, M. et al. Phosphorylation and activation of myosin by Rho-associated kinase (Rho-kinase). J. Biol. Chem. 271, 20246–20249 (1996).

    Article  CAS  PubMed  Google Scholar 

  30. Boyle, S. T., Faulkner, J. W., McColl, S. R. & Kochetkova, M. The chemokine receptor CCR6 facilitates the onset of mammary neoplasia in the MMTV-PyMT mouse model via recruitment of tumor-promoting macrophages. Mol Cancer 14, 115 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  31. Boyle, S. T. et al. The chemokine receptor CCR7 promotes mammary tumorigenesis through amplification of stem-like cells. Oncogene 35, 105–115 (2016).

    Article  CAS  PubMed  Google Scholar 

  32. Nagumo, H. et al. Rho kinase inhibitor HA-1077 prevents Rho-mediated myosin phosphatase inhibition in smooth muscle cells. Am. J. Physiol. Cell Physiol. 278, C57–C65 (2000).

    Article  CAS  PubMed  Google Scholar 

  33. Gehler, S. et al. Filamin A-β1 integrin complex tunes epithelial cell response to matrix tension. Mol. Biol. Cell. 20, 3224–3238 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Schwarzbauer, J. E. & DeSimone, D. W. Fibronectins, their fibrillogenesis, and in vivo functions. Cold Spring Harb. Perspect. Biol. 3, a005041 (2011).

  35. Gritsenko, P. G., Ilina, O. & Friedl, P. Interstitial guidance of cancer invasion. J. Pathol. 226, 185–199 (2012).

    Article  CAS  PubMed  Google Scholar 

  36. Tian, C. et al. Proteomic analyses of ECM during pancreatic ductal adenocarcinoma progression reveal different contributions by tumor and stromal cells. Proc. Natl Acad. Sci. USA 116, 19609–19618 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Poltavets, V., Pitson, S. M., Kochetkova, M. & Samuel, M. S. The role of the extracellular matrix and its molecular and cellular regulators in cancer cell plasticity. Front. Oncol. Mol. Cell. Oncol. 8, 431 (2018).

  38. Henke, A. et al. Reduced contractility and motility of prostatic cancer-associated fibroblasts after inhibition of heat shock protein 90. Cancers 8, 77 (2016).

  39. Ishimoto, T. et al. Activation of transforming growth factor beta 1 signaling in gastric cancer-associated fibroblasts increases their motility, via expression of rhomboid 5 homolog 2, and ability to induce invasiveness of gastric cancer cells. Gastroenterology 153, 191–204 (2017).

    Article  CAS  PubMed  Google Scholar 

  40. Cukierman, E., Pankov, R., Stevens, D. R. & Yamada, K. M. Taking cell-matrix adhesions to the third dimension. Science 294, 1708–1712 (2001).

    Article  CAS  PubMed  Google Scholar 

  41. Blyth, K. et al. SEARCHBreast: a new resource to locate and share surplus archival material from breast cancer animal models to help address the 3Rs. Breast Cancer Res. Treat. 156, 447–452 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Hartley, C. L. et al. Armet/Manf and Creld2 are components of a specialized ER stress response provoked by inappropriate formation of disulphide bonds: implications for genetic skeletal diseases. Hum. Mol. Genet. 22, 5262–5275 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Yoshida, H., Matsui, T., Yamamoto, A., Okada, T. & Mori, K. XBP1 mRNA is induced by ATF6 and spliced by IRE1 in response to ER stress to produce a highly active transcription factor. Cell 107, 881–891 (2001).

    Article  CAS  PubMed  Google Scholar 

  44. Haze, K., Yoshida, H., Yanagi, H., Yura, T. & Mori, K. Mammalian transcription factor ATF6 is synthesized as a transmembrane protein and activated by proteolysis in response to endoplasmic reticulum stress. Mol. Biol. Cell 10, 3787–3799 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Harding, H. P. et al. Regulated translation initiation controls stress-induced gene expression in mammalian cells. Mol. Cell 6, 1099–1108 (2000).

    Article  CAS  PubMed  Google Scholar 

  46. Sidrauski, C., McGeachy, A. M., Ingolia, N. T. & Walter, P. The small molecule ISRIB reverses the effects of eIF2α phosphorylation on translation and stress granule assembly. eLife 4, e05033 (2015).

    Article  PubMed Central  CAS  Google Scholar 

  47. Pakos-Zebrucka, K. et al. The integrated stress response. EMBO Rep. 17, 1374–1395 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Banerjee, A. et al. Unfolded protein response is required in nu/nu mice microvasculature for treating breast tumor with tunicamycin. J. Biol. Chem. 286, 29127–29138 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Fawcett, T. W., Martindale, J. L., Guyton, K. Z., Hai, T. & Holbrook, N. J. Complexes containing activating transcription factor (ATF)/cAMP-responsive-element-binding protein (CREB) interact with the CCAAT/enhancer-binding protein (C/EBP)-ATF composite site to regulate Gadd153 expression during the stress response. Biochem. J. 339, 135–141 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Straight, A. F. et al. Dissecting temporal and spatial control of cytokinesis with a myosin II Inhibitor. Science 299, 1743–1747 (2003).

    Article  CAS  PubMed  Google Scholar 

  51. Croft, D. R. et al. p53-mediated transcriptional regulation and activation of the actin cytoskeleton regulatory RhoC to LIMK2 signaling pathway promotes cell survival. Cell Res. 21, 666–682 (2011).

    Article  CAS  PubMed  Google Scholar 

  52. Orimo, A. et al. Stromal fibroblasts present in invasive human breast carcinomas promote tumor growth and angiogenesis through elevated SDF-1/CXCL12 secretion. Cell 121, 335–348 (2005).

    Article  CAS  PubMed  Google Scholar 

  53. Sappino, A. P., Skalli, O., Jackson, B., Schurch, W. & Gabbiani, G. Smooth-muscle differentiation in stromal cells of malignant and non-malignant breast tissues. Int. J. Cancer 41, 707–712 (1988).

    Article  CAS  PubMed  Google Scholar 

  54. Curtis, C. et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature 486, 346–352 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Rath, N. & Olson, M. F. Rho-associated kinases in tumorigenesis: re-considering ROCK inhibition for cancer therapy. EMBO Rep. 13, 900–908 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Mali, R. S. et al. Rho kinase regulates the survival and transformation of cells bearing oncogenic forms of KIT, FLT3, and BCR-ABL. Cancer Cell 20, 357–369 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Scriven, P. et al. Activation and clinical significance of the unfolded protein response in breast cancer. Br. J. Cancer 101, 1692–1698 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Wallington-Beddoe, C. T. et al. Sphingosine kinase 2 inhibition synergises with bortezomib to target myeloma by enhancing endoplasmic reticulum stress. Oncotarget 8, 43602–43616 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  59. Chen, O. I., Bobak, Y. P., Stasyk, O. V. & Kunz-Schughart, L. A. A complex scenario and underestimated challenge: the tumor microenvironment, ER stress, and cancer treatment. Curr. Med. Chem. 25, 2465–2502 (2018).

    Article  CAS  PubMed  Google Scholar 

  60. Oh-hashi, K., Kunieda, R., Hirata, Y. & Kiuchi, K. Biosynthesis and secretion of mouse cysteine-rich with EGF-like domains 2. FEBS Lett. 585, 2481–2487 (2011).

    Article  CAS  PubMed  Google Scholar 

  61. Mass, E. Functional Analyses of the Conserved Cysteine-Rich With Egf-Like Domains (Creld) Protein Family in Mus musculus. PhD thesis, Univ. Bonn (2014).

  62. Rios, A. C., Fu, N. Y., Lindeman, G. J. & Visvader, J. E. In situ identification of bipotent stem cells in the mammary gland. Nature 506, 322–327 (2014).

    Article  CAS  PubMed  Google Scholar 

  63. Boyle, S. T. et al. Interplay between CCR7 and Notch1 axes promotes stemness in MMTV-PyMT mammary cancer cells. Mol. Cancer 16, 19 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  64. Adikusuma, F., Pfitzner, C. & Thomas, P. Q. Versatile single-step-assembly CRISPR/Cas9 vectors for dual gRNA expression. PLoS ONE 12, e0187236 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  65. Benchling software. https://benchling.com (Benchling Inc., 2019).

  66. Samuel, M. S., Lourenco, F. C. & Olson, M. F. K-Ras mediated murine epidermal tumorigenesis is dependent upon and associated with elevated Rac1 activity. PLoS ONE 6, e17143 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Samuel, M. S. et al. Elevated Dnmt3a activity promotes polyposis in ApcMin mice by relaxing extracellular restraints on Wnt signaling. Gastroenterology 137, 902–913 (2009).

    Article  CAS  PubMed  Google Scholar 

  68. Boudaoud, A. et al. FibrilTool, an ImageJ plug-in to quantify fibrillar structures in raw microscopy images. Nat. Protoc. 9, 457–463 (2014).

    Article  CAS  PubMed  Google Scholar 

  69. Cox, J. & Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 26, 1367–1372 (2008).

    CAS  PubMed  Google Scholar 

  70. Cox, J. et al. Andromeda: a peptide search engine integrated into the MaxQuant environment. J. Proteome Res. 10, 1794–1805 (2011).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We thank J. Visvader for mouse mammary cancer tissue; P. Thomas for providing CRISPR vector pDG461; and M. White for assistance in designing CRISPR guides. The PyMT mammary cancer cell line was provided by K. Blyth through SEARCHBreast (https://searchbreast.org/). This research was supported by the NHMRC (to M.S.S., P.T., S.M.P., A.F.L. and M.K.), ARC (to M.S.S. and P.T.), the Cancer Councils of South Australia (M.S.S.) and New South Wales (P.T.), the RAH Research Fund (M.S.S.) and the Fay Fuller Foundation (S.M.P). S.T.B. was supported by a RAH Research Committee Early Career Fellowship. We thank donors to the Health Services Charitable Gifts Board of SA and the Australian Cancer Research Foundation (Cancer Discovery Accelerator) for funding the imaging equipment used.

Author information

Author notes

  1. Alexander Charles Lewis

    Present address: Translational Haematology Program, Peter McCallum Cancer Centre, Melbourne, Victoria, Australia

Authors and Affiliations

  1. Centre for Cancer Biology, SA Pathology and the University of South Australia, Adelaide, South Australia, Australia

    Sarah Theresa Boyle, Valentina Poltavets, Jasreen Kular, Natasha Theresa Pyne, Alexander Charles Lewis, Natasha Kolesnikoff, Paul Andre Bartholomew Moretti, Melinda Nay Tea, Vinay Tergaonkar, Stuart Maxwell Pitson, Angel Francisco Lopez, Marina Kochetkova & Michael Susithiran Samuel

  2. Division of Systems Biology and Personalised Medicine, Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia

    Jarrod John Sandow & Andrew Ian Webb

  3. Department of Medical Biology, University of Melbourne, Parkville, Victoria, Australia

    Jarrod John Sandow & Andrew Ian Webb

  4. The Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Cancer Division, St Vincent’s Clinical School, University of NSW, Sydney, New South Wales, Australia

    Kendelle Joan Murphy & Paul Timpson

  5. Institute of Molecular and Cell Biology, A*STAR and Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore

    Vinay Tergaonkar

  6. Adelaide Medical School, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, South Australia, Australia

    Stuart Maxwell Pitson, Angel Francisco Lopez & Michael Susithiran Samuel

  7. Breast, Endocrine and Surgical Oncology Unit, Royal Adelaide Hospital, Adelaide, South Australia, Australia

    Robert John Whitfield

Authors
  1. Sarah Theresa Boyle
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Valentina Poltavets
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jasreen Kular
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Natasha Theresa Pyne
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jarrod John Sandow
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Alexander Charles Lewis
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Kendelle Joan Murphy
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Natasha Kolesnikoff
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Paul Andre Bartholomew Moretti
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Melinda Nay Tea
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Vinay Tergaonkar
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Paul Timpson
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Stuart Maxwell Pitson
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Andrew Ian Webb
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Robert John Whitfield
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Angel Francisco Lopez
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Marina Kochetkova
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Michael Susithiran Samuel
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

S.T.B. designed and performed much of the experimental work, provided substantial intellectual input and wrote the manuscript. V.P. and J.K. performed biochemical analyses. N.T.P. performed histological analyses. J.J.S. and A.I.W. performed proteomic MS analyses. N.K. generated the Creld2 CRISPR plasmids. A.C.L performed Creld2 promoter ChIP analyses, P.A.B.M. generated the Creld2 promoter luciferase reporter constructs and M.N.T. performed Creld2 promoter luciferase analyses with intellectual input and supervision from S.M.P. K.J.M. performed CDM experiments with intellectual input and supervision from P.T. A.F.L., V.T. and R.J.W. provided intellectual input. M.K. and M.S.S. conceived, supervised and were intellectual drivers of the study, designed and performed experiments, and wrote the manuscript.

Corresponding authors

Correspondence to Marina Kochetkova or Michael Susithiran Samuel.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 ROCK activation enhances tumor burden, fibroblast numbers and ECM production; Related to Fig. 1.

ROCK a, and pMYPT1 b, in normal (n = 12 normal/hyperplastic) and cancerous (n = 108 IDC) human breast. Scales: 50 µm. Each TMA was immunolabeled once with each antibody. c, Rock1/2 mRNA in advanced PyMT cells transfected with non-targeting control (NTC) or Rock1 and Rock 2 siRNA (n = 5/group). Mean+SEM, two-sided unpaired t-test. d, pMlc2 protein following Rock1/2 knockdown in tumor cells. e, pMlc2 (greyscale, green) and pMypt1 (greyscale, magenta) in tumor cells following Rock1/2 knockdown. Counter-labels: Phalloidin (F-actin, red); DAPI (nuclei, blue). Scales: 50 µm. (d,e) Repeated twice with similar results. f, ROCK (mean ± SEM; n = 5 NTC, 3 siRNA; two-sided unpaired t-test) and pMlc2 (mean; n = 5 NTC, 2 siRNA) (greyscale and green) in tumors one week after engraftment of tumor cells with Rock1/2 knockdown. Counter-labels: E-cadherin (red); PyMT (blue). Scales: 50 µm. g, Collagen (SHG: magenta, transmission: grey) and fibronectin, periostin and tenascin C (green, counter-labels E-Cadherin (red); DAPI (blue)) in R-PyMT and K-PyMT tumors. Scales: 100 µm. Experiment repeated at least twice and pooled data analyzed. h, Fsp1/S100a4 (n = 6 veh, 5 fas) and Pdgfrβ (n = 10/group) (both green) in tumors from mice engrafted with tumor cells and treated with fasudil or vehicle. Counter-labels: E-Cadherin (red); DAPI (blue). Scales: 100 µm. Median±IQR, two-sided Mann-Whitney. i, Fsp1/S100a4 (n = 7/group) and Pdgfrβ (n = 10 NTC, 7 siRNA) (both green) in tumors in mice engrafted with Rock1/2-depleted tumor cells. Counter-labels: E-Cadherin (red); DAPI (blue). Scales: 100 µm. Median±IQR, two-sided Mann-Whitney. j, Epithelial cells (CK8/18/14, green), fibroblasts (Pdgfrβ, red), immune cells (CD45, green) and endothelial cells (CD31) in total cell suspensions from mammary tissue digest (top), and cultured fibroblasts (bottom). Counter-label: DAPI. Scales: 100 µm. Pie charts show cell type proportions. k, Ex vivo-cultured mammary epithelial cells and fibroblasts. Scales: 200 µm. j,k, Repeated at least twice with similar results. See also Statistics Source Data for Extended Data Fig. 1 and Unprocessed blots for Extended Data Fig. 1.

Source data

Extended Data Fig. 2 ROCK-education of mammary fibroblasts yields a tumor-promoting fibroblast phenotype; Related to Fig. 2.

a, Schematic of the inverse invasion assay assessing fibroblast motility ex vivo. b, Confocal z-stack images (7 µm intervals) through a Matrigel plug following migration by fibroblasts from ROCK-activated R-PyMT and K-PyMT mammary tumors. Repeated more than 3 times with similar results. c, Schematic of ex vivo cell-derived matrix (CDM) establishment to study cancer cell anisotropy. d, Images of picrosirius red-stained CDM formed by fibroblasts from ROCK-activated R-PyMT and K-PyMT mammary tumors. Scales: 100 µm. e, Streaming images of PyMT tumor cells seeded onto CDM generated from ROCK- or KD-educated fibroblasts. Arrows demonstrate streaming direction (insets of boxes shown below). d,e, Repeated 3 times. f, Schematic of co-engraftment strategy to examine educated fibroblast function in vivo. g, ECM proteins fibronectin, periostin and tenascin C (green) in tumors arising in mice that were co-engrafted with PyMT tumor cells and either ROCK- or KD-educated fibroblasts. Counter-label: DAPI (blue). Scales: 100 µm. Dot plots show the area coverage of respective ECM component IF signals. Median±IQR, n = 5 tumors/group, two-sided Mann-Whitney tests. h, Left: Western analysis of pMlc2 in ex vivo-cultured K-PyMT and R-PyMT tumor cells following 4−hydroxy tamoxifen (4HT) treatment. Graphical representations of starved and 4HT-treated densitometries are shown below. Right: pMlc2 (green) in ex vivo-cultured K-PyMT and R-PyMT tumor cells treated with 4HT. Counter-labels: Phalloidin (F-actin, red) and DAPI (blue). Scales: 100 µm. Repeated at least twice with similar results. i, Schematic of co-engraftment strategy to examine the effect of paracrine signaling between ROCK-activated tumor cells and fibroblasts on tumor promotion in vivo. See also Statistics Source Data for Extended Data Fig. 2 and Unprocessed blots for Extended Data Fig. 2.

Source data

Extended Data Fig. 3 ROCK-education of mammary fibroblasts yields a tumor-promoting fibroblast phenotype via paracrine Creld2; Related to Fig. 3.

a, Creld2 protein in 4HT-treated K-PyMT and R-PyMT ex vivo-cultured tumor cells. Experiment repeated twice with similar results. b, Creld2 (greyscale and green) in tumors one week following engraftment of tumor cells transfected with non-targeting control (NTC) or Rock1/2 siRNA. Counter-labels: E-cadherin (red); PyMT (blue). Scales: 50 µm. Mean±SEM (n = 5 NTC, 3 siRNA), two-sided unpaired t-test. c, Creld2 (green) in advanced tumor cells treated with fasudil and Y-27632. Counter-labels: Phalloidin (F-actin, red) and DAPI (blue). Scales: 50 µm. Mean±SEM (n = 10/group), one-way ANOVA. FOV = Field of view. d, Creld2 mRNA in R-PyMT cells following Creld2 knockdown (n = 3/group). Mean+SEM, one-way ANOVA. e, Creld2 (greyscale and green) in immortalized PyMT cell line following Creld2-CRISPR, clone E4. Counter-labels: Phalloidin (red); DAPI (blue). Scales: 50 µm. Mean±SEM (n = 13 Parental, 10 E4), two-sided unpaired t-test. f, Mean distance migrated by fibroblasts exposed to CM from PyMT cells with Creld2-CRISPR (n = 3/group) in inverse invasion assay. Mean±SEM, two-sided unpaired t-test. g, Co-engraftment strategies to examine effect of Creld2 on fibroblast function in vivo. h, Fibronectin (n = 5 KD + NTC,6 ROCK + NTC,6 ROCK + siRNA) and periostin (n = 6 KD + NTC,6 ROCK + NTC,5 ROCK + siRNA) (green) in tumors following co-engraftment of tumor cells and fibroblasts exposed to tumor cell CM following Creld2 knockdown. Counter-labels: E-Cadherin (red); DAPI (blue). Scales: 100 µm. Mean±SEM, one-way ANOVA. i, Progressive tumor volume following co-engraftment of tumor cells with fibroblasts exposed to CM from K-PyMT cells following Creld2 knockdown (n = 8 tumors/group). Mean&SEM, 2-way ANOVA. j, Final weights of tumors from i, two-sided Mann-Whitney test. Box plot: midline=median; box=25-75th percentile; whisker=minima to maxima. k, Fibronectin and periostin (green) in tumors following co-engraftment of tumor cells and fibroblasts treated with recombinant Creld2. Counter-labels: E-Cadherin (red); DAPI (blue). Scales: 100 µm. Median±IQR (n = 8 tumors untreated, 9 Creld2), two-sided Mann-Whitney. See also Statistics Source Data for Extended Data Fig. 3 and Unprocessed blots for Extended Data Fig. 3.

Source data

Extended Data Fig. 4 Perk is selectively activated downstream of ROCK in mammary cancer; Related to Fig. 4.

a, Western analysis of Atf4 in K-PyMT and R-PyMT ex vivo-cultured mammary tumor cells following serum-starvation and 4HT-stimulation. Experiment repeated twice with similar results. b, Atf4 (greyscale and green) in 4HT-treated K-PyMT and R-PyMT tumor cells. Counter-labels: Phalloidin (red); DAPI (blue). Scales: 100 µm. Higher magnification images from an independent experiment shown in Fig. 4d. Experiment repeated 3 times with similar results. c, Phosphorylated Perk (green) in R-PyMT and K-PyMT tumor cells cultured ex vivo. Counter-labels: Phalloidin (red); DAPI (blue). Scales: 50 µm. Mean+SEM (n = 5 K-PyMT, 6 R-PyMT), two-sided unpaired t-tests. d, Phosphorylated Mlc2 and Perk (both green) in advanced PyMT tumor cells cultured ex vivo, serum-starved and serum-treated following starvation, in the presence of ROCK pharmacological inhibitors fasudil and Y27632. Counter-labels: Phalloidin (red); DAPI (blue). Scales: 50 µm. Mean+SEM (n = 8 untreated, 10 Y27632, 10 fasudil) relative to untreated, one-way ANOVA. See also Statistics Source Data for Extended Data Fig. 4 and Unprocessed blots for Extended Data Fig. 4.

Source data

Extended Data Fig. 5 Perk signaling is required for ROCK-induced production of Creld2; Related to Fig. 5.

a, mRNA expression of indicated genes in R-PyMT tumor cells following transfection with non-targeting control (NTC) or siRNAs against Atf6 (Atf6 UPR pathway), Ern1 (Ire1α UPR pathway), Eif2ak2 (Pkr ISR pathway), Eif2ak4 (Gcn2 ISR pathway) and Eif2ak3 (Perk pathway) (n = 2/group). Mean values shown. ND = not detected. Representative data from more than 3 independent experiments. b, Bip (Atf6 pathway), Xbp1−spliced (Ire1 pathway) and Atf4 (Perk pathway) (green) in R-PyMT and K-PyMT tumor cells, transfected with either NTC or siRNAs to separately knockdown UPR pathways as indicated. Counter-labels: Phalloidin (F-Actin, red); DAPI (blue). Scales: 50 µm. Repeated twice with similar results. c, Mean distance migrated by PyMT fibroblasts exposed to CM from 4HT-treated K-PyMT tumor cells transfected with NTC or siRNAs against Ern1, Atf6 and Eif2ak3 (n = 6 KD + NTC, 4 KD + Ern1, 4 KD + Atf6, 5 KD + Eif2ak3) in inverse invasion assay. Mean±SEM, one-way ANOVA. d, Atf4 in K-PyMT and R-PyMT tumor cells transfected with NTC or siRNA targeting Perk (Eif2ak3). Mean±SEM (n = 8 KD + NTC, 11 ROCK + NTC, 9 ROCK + siRNA) relative to KD, one-way ANOVA. Representative images shown in e. e, Atf4 (green) in R-PyMT and K-PyMT tumor cells, transfected with NTC or siRNAs to knockdown the ISR mediators, Eif2ak2 (Pkr), Eif2ak4 (Gcn2) and Eif2ak3 (Perk). Counter-labels: Phalloidin (red) and DAPI (blue). Scales: 50 µm. f, Creld2 (green) in R-PyMT tumor cells treated with ISR inhibitors against Pkr and Gcn2. Counter-labels: Phalloidin (red); DAPI (blue). Scales: 50 µm. Mean±SEM (n = 4/group) relative to untreated, one-way ANOVA. See also Statistics Source Data for Extended Data Fig. 5.

Source data

Extended Data Fig. 6 ROCK activation in mammary cancers induces Atf4-regulated Creld2 transcription downstream of actin stress; Related to Fig. 6.

a, Atf4, Bip and Xbp1-spliced (green), indicating induction of Perk, Atf6 and Ire1 UPR pathways respectively in PyMT tumor cells treated with tunicamycin (10 µg/ml) to induce ER stress. Counter-labels: Phalloidin (F-actin, red); DAPI (blue). Scales: 50 µm. Experiment repeated 3 times with similar results. b, mRNA levels of Creld2 in PyMT tumor cells treated with tunicamycin (10 µg/ml), mean ± SEM (n = 3/group) relative to untreated, two-sided unpaired t-test. c, Creld2 (green) in PyMT tumor cells treated with tunicamycin. Counter-labels: Phalloidin (red); DAPI (blue). Scales: 50 µm. Mean±SEM (n = 25 untreated, 26 tunicamycin), two-sided unpaired t-test. d-f, Immunofluorescence analysis of pPerk (n = 6 KD, 5 ROCK, 5 ROCK + BMS5) d, Atf4 (n = 11/group) e, and Creld2 (n = 17 KD, 16 ROCK, 16 ROCK + BMS5) f, (all green) in K-PyMT and R-PyMT tumor cells treated with BMS5. Counter-labels: Phalloidin (red); DAPI (blue). Scales: 50 µm. Mean±SEM relative to KD, one-way ANOVA tests. See also Statistics Source Data for Extended Data Fig. 6.

Source data

Extended Data Fig. 7 High CRELD2 expression is associated with human breast cancer; Related to Fig. 7.

a, Representative images of immunohistochemical analyses of FSP1 in human normal/hyperplastic mammary specimens and invasive ductal carcinoma. Scales: 100 µm. Graph shows positive pixel analysis of FSP1 on a human breast cancer TMA of 14 normal (N)/hyperplasia (HP)/ductal carcinomas in situ (DCIS) and 50 invasive ductal carcinoma (IDC) specimens, analyzed by two-sided Mann-Whitney test. Box plot: midline=median; box=25−75th percentile; whisker=minima to maxima. b, CRELD2 expression in human patient samples based on breast cancer grade 1 (n = 170), 2 (n = 775) and 3 (n = 957), analyzed using the publicly available METABRIC dataset consisting of 2,000 primary breast cancers (see Methods). Median±IQR, Kruskal-Wallis test. c, Representative images of immunohistochemical analyses of CRELD2 in human normal/hyperplastic mammary specimens and invasive ductal carcinoma. Insets of boxes shown in Fig. 7f. Scales: 200 µm. d, Top: IF images of pMlc2 and Creld2 in normal mouse mammary tissue, ROCK-activated R−PyMT mouse mammary tumor tissue, and various mouse models of breast cancer (MMTV-PyMT, MMTV-Neu, MMTV-Wnt-1 and p53-null) as indicated. Merged images shown in Fig. 7h. Scales: 50 µm. Bottom: Histograms show area coverage analysis of pMlc2 and Creld2 signal, relative to signal in normal gland. Mean+SEM, two-sided unpaired t-tests. pMlc2: n = 5 normal, 5 R−PyMT+TAM, 4 MMTV-PyMT, 5 MMTV-Neu, 6 MMTV-Wnt-1, 6 p53-Null. Creld2: n = 10 normal, 9 R-PyMT+TAM, 8 MMTV-PyMT, 9 MMTV-Neu, 9 MMTV-Wnt-1, 10 p53-Null. See also Statistics Source Data for Extended Data Fig. 7.

Source data

Supplementary information

Reporting Summary

Supplementary Tables

Supplementary Table 1: patient details. Supplementary Table 2: experimental conditions for immunofluorescence, immunohistochemistry and western analyses.

Source data

Source Data Fig. 1

Statistical source data for Fig. 1.

Source Data Fig. 1

Unprocessed western blot for Fig. 1l.

Source Data Fig. 2

Statistical source data for Fig. 2.

Source Data Fig. 3

Statistical source data for Fig. 3.

Source Data Fig. 3

Unprocessed western blot for Fig. 3b.

Source Data Fig. 4

Statistical source data for Fig. 4.

Source Data Fig. 4

Unprocessed western blot for Fig. 4f.

Source Data Fig. 5

Statistical source data for Fig. 5.

Source Data Fig. 6

Statistical source data for Fig. 6.

Source Data Fig. 7

Statistical source data for Fig. 7.

Source Data Extended Data Fig. 1

Statistical source data for Extended Data Fig. 1.

Source Data Extended Data Fig. 1

Unprocessed western blot for Extended Data Fig. 1d.

Source Data Extended Data Fig. 2

Statistical source data for Extended Data Fig. 2.

Source Data Extended Data Fig. 2

Unprocessed western blot for Extended Data Fig. 2i.

Source Data Extended Data Fig. 3

Statistical source data for Extended Data Fig. 3.

Source Data Extended Data Fig. 3

Unprocessed western blot for Extended Data Fig. 3a.

Source Data Extended Data Fig. 4

Statistical source data for Extended Data Fig. 4.

Source Data Extended Data Fig. 4

Unprocessed western blot for Extended Data Fig. 4a.

Source Data Extended Data Fig. 5

Statistical source data for Extended Data Fig. 5.

Source Data Extended Data Fig. 6

Statistical source data for Extended Data Fig. 6.

Source Data Extended Data Fig. 7

Statistical source data for Extended Data Fig. 7.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Boyle, S.T., Poltavets, V., Kular, J. et al. ROCK-mediated selective activation of PERK signalling causes fibroblast reprogramming and tumour progression through a CRELD2-dependent mechanism. Nat Cell Biol 22, 882–895 (2020). https://doi.org/10.1038/s41556-020-0523-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41556-020-0523-y

Search

Advanced search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer