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:

Profiling drugs for rheumatoid arthritis that inhibit synovial fibroblast activation

Nature Chemical Biology volume 13, pages 38–45 (2017)Cite this article

Subjects

Abstract

Activation of synovial fibroblasts (SFs) contributes to rheumatoid arthritis (RA) by damaging synovial membranes and generating inflammatory cytokines that recruit immune cells to the joint. In this paper we profile cytokine secretion by primary human SFs from healthy tissues and from donors with RA and show that SF activation by TNF, IL-1α, and polyinosinic-polycytidylic acid (Poly(I:C)) cause secretion of multiple cytokines found at high levels in RA synovial fluids. We used interaction multiple linear regression to quantify therapeutic and countertherapeutic drug effects across activators and donors and found that the ability of drugs to block SF activation was strongly dependent on the identity of the activating cytokine. (5z)-7-oxozeaenol (5ZO), a preclinical drug that targets transforming growth factor-β–activated kinase 1 (TAK1), was more effective at blocking SF activation across all contexts than the approved drug tofacitinib, which supports the development of molecules similar to 5ZO for use as RA therapeutics.

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

Figure 1: Experimental strategy exploring SF activation and composition of RA synovial fluids.
Figure 2: Multivariate analysis of the effect of small-molecule kinase inhibitors on induced cytokine secretion.
Figure 3: iMLR to analyze context dependencies in perturbation-response data.
Figure 4: Dependence of SF activation on the identity of the activating ligand.
Figure 5: 5ZO normalizes SF activation across multiple contexts.
Figure 6: Inferring the likely targets of 5ZO on the basis of experiments in SFs and current understanding of the drug.

Similar content being viewed by others

References

  1. Scott, D.L., Wolfe, F. & Huizinga, T.W. Rheumatoid arthritis. Lancet 376, 1094–1108 (2010).

    Article  Google Scholar 

  2. McInnes, I.B. & Schett, G. The pathogenesis of rheumatoid arthritis. N. Engl. J. Med. 365, 2205–2219 (2011).

    Article  CAS  Google Scholar 

  3. Taylor, P.C. & Feldmann, M. Anti-TNF biologic agents: still the therapy of choice for rheumatoid arthritis. Nat. Rev. Rheumatol. 5, 578–582 (2009).

    Article  CAS  Google Scholar 

  4. Emery, P. et al. IL-6 receptor inhibition with tocilizumab improves treatment outcomes in patients with rheumatoid arthritis refractory to anti-tumour necrosis factor biologicals: results from a 24-week multicentre randomised placebo-controlled trial. Ann. Rheum. Dis. 67, 1516–1523 (2008).

    Article  CAS  Google Scholar 

  5. Stanczyk, J., Ospelt, C. & Gay, S. Is there a future for small molecule drugs in the treatment of rheumatic diseases? Curr. Opin. Rheumatol. 20, 257–262 (2008).

    Article  CAS  Google Scholar 

  6. Lindstrom, T.M. & Robinson, W.H. A multitude of kinases—which are the best targets in treating rheumatoid arthritis? Rheum. Dis. Clin. North Am. 36, 367–383 (2010).

    Article  Google Scholar 

  7. Arthur, J.S.C. & Ley, S.C. Mitogen-activated protein kinases in innate immunity. Nat. Rev. Immunol. 13, 679–692 (2013).

    Article  CAS  Google Scholar 

  8. Neumann, E., Lefèvre, S., Zimmermann, B., Gay, S. & Müller-Ladner, U. Rheumatoid arthritis progression mediated by activated synovial fibroblasts. Trends Mol. Med. 16, 458–468 (2010).

    Article  CAS  Google Scholar 

  9. Bottini, N. & Firestein, G.S. Duality of fibroblast-like synoviocytes in RA: passive responders and imprinted aggressors. Nat. Rev. Rheumatol. 9, 24–33 (2013).

    Article  CAS  Google Scholar 

  10. Noss, E.H. & Brenner, M.B. The role and therapeutic implications of fibroblast-like synoviocytes in inflammation and cartilage erosion in rheumatoid arthritis. Immunol. Rev. 223, 252–270 (2008).

    Article  CAS  Google Scholar 

  11. Lefèvre, S. et al. Synovial fibroblasts spread rheumatoid arthritis to unaffected joints. Nat. Med. 15, 1414–1420 (2009).

    Article  Google Scholar 

  12. Müller-Ladner, U. et al. Synovial fibroblasts of patients with rheumatoid arthritis attach to and invade normal human cartilage when engrafted into SCID mice. Am. J. Pathol. 149, 1607–1615 (1996).

    PubMed  PubMed Central  Google Scholar 

  13. Bartok, B. & Firestein, G.S. Fibroblast-like synoviocytes: key effector cells in rheumatoid arthritis. Immunol. Rev. 233, 233–255 (2010).

    Article  CAS  Google Scholar 

  14. Janes, K.A. et al. A systems model of signaling identifies a molecular basis set for cytokine-induced apoptosis. Science 310, 1646–1653 (2005).

    Article  CAS  Google Scholar 

  15. Scheller, J., Chalaris, A., Schmidt-Arras, D. & Rose-John, S. The pro- and anti-inflammatory properties of the cytokine interleukin-6. Biochim. Biophys. Acta 1813, 878–888 (2011).

    Article  CAS  Google Scholar 

  16. Baggiolini, M. & Clark-Lewis, I. Interleukin-8, a chemotactic and inflammatory cytokine. FEBS Lett. 307, 97–101 (1992).

    Article  CAS  Google Scholar 

  17. Moser, B., Clark-Lewis, I., Zwahlen, R. & Baggiolini, M. Neutrophil-activating properties of the melanoma growth-stimulatory activity. J. Exp. Med. 171, 1797–1802 (1990).

    Article  CAS  Google Scholar 

  18. Schumacher, C., Clark-Lewis, I., Baggiolini, M. & Moser, B. High- and low-affinity binding of GRO alpha and neutrophil-activating peptide 2 to interleukin 8 receptors on human neutrophils. Proc. Natl. Acad. Sci. USA 89, 10542–10546 (1992).

    Article  CAS  Google Scholar 

  19. Carr, M.W., Roth, S.J., Luther, E., Rose, S.S. & Springer, T.A. Monocyte chemoattractant protein 1 acts as a T-lymphocyte chemoattractant. Proc. Natl. Acad. Sci. USA 91, 3652–3656 (1994).

    Article  CAS  Google Scholar 

  20. Xu, L.L., Warren, M.K., Rose, W.L., Gong, W. & Wang, J.M. Human recombinant monocyte chemotactic protein and other C-C chemokines bind and induce directional migration of dendritic cells in vitro. J. Leukoc. Biol. 60, 365–371 (1996).

    Article  CAS  Google Scholar 

  21. Maghazachi, A.A., Al-Aoukaty, A. & Schall, T.J. CC chemokines induce the generation of killer cells from CD56+ cells. Eur. J. Immunol. 26, 315–319 (1996).

    Article  CAS  Google Scholar 

  22. Conti, P. & DiGioacchino, M. MCP-1 and RANTES are mediators of acute and chronic inflammation. Allergy Asthma Proc. 22, 133–137 (2001).

    Article  CAS  Google Scholar 

  23. Taub, D.D. et al. Recombinant human interferon-inducible protein 10 is a chemoattractant for human monocytes and T lymphocytes and promotes T cell adhesion to endothelial cells. J. Exp. Med. 177, 1809–1814 (1993).

    Article  CAS  Google Scholar 

  24. de Jager, W., Prakken, B.J., Bijlsma, J.W.J., Kuis, W. & Rijkers, G.T. Improved multiplex immunoassay performance in human plasma and synovial fluid following removal of interfering heterophilic antibodies. J. Immunol. Methods 300, 124–135 (2005).

    Article  CAS  Google Scholar 

  25. Ellingsen, T., Buus, A. & Stengaard-Pedersen, K. Plasma monocyte chemoattractant protein 1 is a marker for joint inflammation in rheumatoid arthritis. J. Rheumatol. 28, 41–46 (2001).

    CAS  PubMed  Google Scholar 

  26. Boiardi, L. et al. Relationship between serum RANTES levels and radiological progression in rheumatoid arthritis patients treated with methotrexate. Clin. Exp. Rheumatol. 17, 419–425 (1999).

    CAS  PubMed  Google Scholar 

  27. Opdenakker, G., Froyen, G., Fiten, P., Proost, P. & Van Damme, J. Human monocyte chemotactic protein-3 (MCP-3): molecular cloning of the cDNA and comparison with other chemokines. Biochem. Biophys. Res. Commun. 191, 535–542 (1993).

    Article  CAS  Google Scholar 

  28. Souza, L.M. et al. Recombinant human granulocyte colony-stimulating factor: effects on normal and leukemic myeloid cells. Science 232, 61–65 (1986).

    Article  CAS  Google Scholar 

  29. Bacher, M. et al. An essential regulatory role for macrophage migration inhibitory factor in T-cell activation. Proc. Natl. Acad. Sci. USA 93, 7849–7854 (1996).

    Article  CAS  Google Scholar 

  30. Calandra, T., Bernhagen, J., Mitchell, R.A. & Bucala, R. The macrophage is an important and previously unrecognized source of macrophage migration inhibitory factor. J. Exp. Med. 179, 1895–1902 (1994).

    Article  CAS  Google Scholar 

  31. Malemud, C.J. Growth hormone, VEGF and FGF: involvement in rheumatoid arthritis. Clin. Chim. Acta 375, 10–19 (2007).

    Article  CAS  Google Scholar 

  32. Davis, M.I. et al. Comprehensive analysis of kinase inhibitor selectivity. Nat. Biotechnol. 29, 1046–1051 (2011).

    Article  CAS  Google Scholar 

  33. Zhang, T. et al. Discovery of potent and selective covalent inhibitors of JNK. Chem. Biol. 19, 140–154 (2012).

    Article  CAS  Google Scholar 

  34. Ninomiya-Tsuji, J. et al. The kinase TAK1 can activate the NIK-IκB as well as the MAP kinase cascade in the IL-1 signalling pathway. Nature 398, 252–256 (1999).

    Article  CAS  Google Scholar 

  35. Sakurai, H. Targeting of TAK1 in inflammatory disorders and cancer. Trends Pharmacol. Sci. 33, 522–530 (2012).

    Article  CAS  Google Scholar 

  36. Ajibade, A.A ., Wang, H. Y., Wang, R.F. Cell type-specific function of TAK1 in innate immune signaling. Trends Immunol. 34, 307–316 (2013).

    Article  CAS  Google Scholar 

  37. Cohen, J. Multiple regression as a general data-analytic system. Psychol. Bull. 70, 426–443 (1968).

    Article  Google Scholar 

  38. Jaccard, J., Wan, C.K. & Turrisi, R. The detection and interpretation of interaction effects between continuous variables in multiple regression. Multivariate Behav. Res. 25, 467–478 (1990).

    Article  CAS  Google Scholar 

  39. Jaccard, J. & Turrisi, R. Interaction Effects in Multiple Regression (SAGE Publications, 2003).

  40. Takeda, K. & Akira, S. TLR signaling pathways. Semin. Immunol. 16, 3–9 (2004).

    Article  CAS  Google Scholar 

  41. Li, X. & Qin, J. Modulation of Toll-interleukin 1 receptor mediated signaling. J. Mol. Med. 83, 258–266 (2005).

    Article  CAS  Google Scholar 

  42. Tan, L. et al. Discovery of type II inhibitors of TGFβ-activated kinase 1 (TAK1) and mitogen-activated protein kinase kinase kinase kinase 2 (MAP4K2). J. Med. Chem. 58, 183–196 (2015).

    Article  CAS  Google Scholar 

  43. Filer, A. The fibroblast as a therapeutic target in rheumatoid arthritis. Curr. Opin. Pharmacol. 13, 413–419 (2013).

    Article  CAS  Google Scholar 

  44. Knight, Z.A., Lin, H. & Shokat, K.M. Targeting the cancer kinome through polypharmacology. Nat. Rev. Cancer 10, 130–137 (2010).

    Article  CAS  Google Scholar 

  45. Shaw, S.Y. et al. Perturbational profiling of nanomaterial biologic activity. Proc. Natl. Acad. Sci. USA 105, 7387–7392 (2008).

    Article  CAS  Google Scholar 

  46. Kahle, P. et al. Determination of cytokines in synovial fluids: correlation with diagnosis and histomorphological characteristics of synovial tissue. Ann. Rheum. Dis. 51, 731–734 (1992).

    Article  CAS  Google Scholar 

  47. Rosengren, S., Boyle, D.L. & Firestein, G.S. Acquisition, culture, and phenotyping of synovial fibroblasts. Methods Mol. Med. 135, 365–375 (2007).

    Article  Google Scholar 

  48. Millard, B.L., Niepel, M., Menden, M.P., Muhlich, J.L. & Sorger, P.K. Adaptive informatics for multifactorial and high-content biological data. Nat. Methods 8, 487–493 (2011).

    Article  CAS  Google Scholar 

  49. Niepel, M. et al. Profiles of basal and stimulated receptor signaling networks predict drug response in breast cancer lines. Sci. Signal. 6, ra84 (2013).

    Article  Google Scholar 

  50. Todd, D.J. et al. Erroneous augmentation of multiplex assay measurements in patients with rheumatoid arthritis due to heterophilic binding by serum rheumatoid factor. Arthritis Rheum. 63, 894–903 (2011).

    Article  CAS  Google Scholar 

  51. Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Series B Stat. Methodol. 57, 289–300 (1995).

    Google Scholar 

  52. Burnham, K.P. & Anderson, D.R. Model Selection and Multimodel Inference (Springer Science & Business Media, 2007).

Download references

Acknowledgements

We thank S. Rudnicki and the HMS ICCB for automation assistance; B. Joughin, D. Clarke, M. Morris, J. Copeland, G. Nabozny, D. Klatte, and S. Pullen for helpful discussions; and N. Gray and T. Zhang at DFCI (Boston, Massachusetts, USA) for providing JNK-IN-8. This work was supported by the NIH (LINCS grant U54HL127365 to P.K.S., grant P50 GM107618 to P.K.S., and NRSA Fellowship 5F32AR062931 to D.S.J.) and by a sponsored research agreement dated 1 August 2009 from Boehringer Ingelheim Inc. to P.K.S. and D.A.L.

Author information

Author notes

  1. Jennifer L Swantek & John M Burke

    Present address: Present addresses: AbbVie, Worcester, Massachusetts, USA (J.L.S.) and Applied BioMath LLC, Lincoln, Massachusetts, USA (J.M.B.).,

Authors and Affiliations

  1. HMS LINCS Center, Laboratory of Systems Pharmacology, Harvard Medical School, Boston, Massachusetts, USA

    Douglas S Jones, Anne P Jenney & Peter K Sorger

  2. Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Douglas S Jones & Douglas A Lauffenburger

  3. Immunology and Inflammation, Boehringer Ingelheim, Ridgefield, Connecticut, USA

    Jennifer L Swantek & John M Burke

  4. Systems Biology, Boehringer Ingelheim, Ridgefield, Connecticut, USA

    John M Burke

Authors
  1. Douglas S Jones
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anne P Jenney
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jennifer L Swantek
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. John M Burke
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Douglas A Lauffenburger
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Peter K Sorger
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

D.S.J. performed experiments and computational analyses, analyzed the results, and wrote and edited the paper; A.P.J. performed experiments; D.A.L. and P.K.S. analyzed the results and wrote and edited the paper; J.M.B. and J.L.S. made key intellectual contributions.

Corresponding author

Correspondence to Peter K Sorger.

Ethics declarations

Competing interests

J.M.B. and J.L.S. were employees at Boehringer Ingelheim Pharmaceuticals Inc. during the course of the studies; D.A.L. and P.K.S. were consultants to Boehringer Ingelheim Pharmaceuticals Inc.

Supplementary information

Supplementary Text and Figures

Supplementary Results, Supplementary Tables 1–7 and Supplementary Figures 1–18. (PDF 12484 kb)

Supplementary Data 1

SF donor sample N2586. (XLS 602 kb)

Supplementary Data 2

SF donor sample N2645. (XLS 602 kb)

Supplementary Data 3

SF donor sample N2759. (XLS 602 kb)

Supplementary Data 4

SF donor sample RA1869. (XLS 602 kb)

Supplementary Data 5

SF donor sample RA1931. (XLS 602 kb)

Supplementary Data 6

SF donor sample RA2159. (XLS 602 kb)

Supplementary Data 7

SF donor sample RA2708. (XLS 602 kb)

Supplementary Data 8

SF donor sample N2586. (XLS 175 kb)

Supplementary Data 9

SF donor sample N2645. (XLS 175 kb)

Supplementary Data 10

SF donor sample N2759. (XLS 175 kb)

Supplementary Data 11

SF donor sample RA1869. (XLS 175 kb)

Supplementary Data 12

SF donor sample RA1931. (XLS 175 kb)

Supplementary Data 13

SF donor sample RA2159. (XLS 175 kb)

Supplementary Data 14

SF donor sample RA2708. (XLS 175 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jones, D., Jenney, A., Swantek, J. et al. Profiling drugs for rheumatoid arthritis that inhibit synovial fibroblast activation. Nat Chem Biol 13, 38–45 (2017). https://doi.org/10.1038/nchembio.2211

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nchembio.2211

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing