RANKL inhibition reduces lesional cellularity and Gαs variant expression and enables osteogenic maturation in fibrous dysplasia

Luis F. de Castro1, Jarred M. Whitlock2, Zachary Michel1, Kristen Pan3,4, Jocelyn Taylor3, Vivian Szymczuk3, Brendan Boyce5, Daniel Martin6, Vardit Kram3, Rebeca Galisteo1, Kamran Melikov2, Leonid V. Chernomordik2, Michael T. Collins1, Alison M. Boyce3

Bone Research ›› 2024, Vol. 12 ›› Issue (0) : 9. DOI: 10.1038/s41413-023-00311-7

RANKL inhibition reduces lesional cellularity and Gαs variant expression and enables osteogenic maturation in fibrous dysplasia

  • Luis F. de Castro1, Jarred M. Whitlock2, Zachary Michel1, Kristen Pan3,4, Jocelyn Taylor3, Vivian Szymczuk3, Brendan Boyce5, Daniel Martin6, Vardit Kram3, Rebeca Galisteo1, Kamran Melikov2, Leonid V. Chernomordik2, Michael T. Collins1, Alison M. Boyce3
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Abstract

Fibrous dysplasia (FD) is a rare, disabling skeletal disease for which there are no established treatments. Growing evidence supports inhibiting the osteoclastogenic factor receptor activator of nuclear kappa-B ligand (RANKL) as a potential treatment strategy. In this study, we investigated the mechanisms underlying RANKL inhibition in FD tissue and its likely indirect effects on osteoprogenitors by evaluating human FD tissue pre- and post-treatment in a phase 2 clinical trial of denosumab (NCT03571191) and in murine in vivo and ex vivo preclinical models. Histological analysis of human and mouse tissue demonstrated increased osteogenic maturation, reduced cellularity, and reduced expression of the pathogenic Gαs variant in FD lesions after RANKL inhibition. RNA sequencing of human and mouse tissue supported these findings. The interaction between osteoclasts and mutant osteoprogenitors was further assessed in an ex vivo lesion model, which indicated that the proliferation of abnormal FD osteoprogenitors was dependent on osteoclasts. The results from this study demonstrated that, in addition to its expected antiosteoclastic effect, denosumab reduces FD lesion activity by decreasing FD cell proliferation and increasing osteogenic maturation, leading to increased bone formation within lesions. These findings highlight the unappreciated role of cellular crosstalk between osteoclasts and preosteoblasts/osteoblasts as a driver of FD pathology and demonstrate a novel mechanism of action of denosumab in the treatment of bone disease.

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Luis F. de Castro, Jarred M. Whitlock, Zachary Michel, Kristen Pan, Jocelyn Taylor, Vivian Szymczuk, Brendan Boyce, Daniel Martin, Vardit Kram, Rebeca Galisteo, Kamran Melikov, Leonid V. Chernomordik, Michael T. Collins, Alison M. Boyce. RANKL inhibition reduces lesional cellularity and Gαs variant expression and enables osteogenic maturation in fibrous dysplasia. Bone Research, 2024, 12(0): 9 https://doi.org/10.1038/s41413-023-00311-7

References

1. Riminucci, M.et al.The histopathology of fibrous dysplasia of bone in patients with activating mutations of the Gs alpha gene: site-specific patterns and recurrent histological hallmarks. J. Pathol. 187, 249-258 (1999).
2. Szymczuk, V., Taylor, J.& Boyce, A. M. Craniofacial fibrous dysplasia: clinical and therapeutic implications. Curr. Osteoporos. Rep. 21, 147-153 (2023).
3. Boyce A. M.& Collins, M. T. Fibrous dysplasia/McCune-Albright Syndrome: a rare, mosaic disease of gαs activation. Endocr. Rev. 41, 345-370 (2020).
4. de Castro, L. F.et al. Safety and efficacy of Denosumab for fibrous dysplasia of bone. N. Engl. J. Med. 388, 766-768 (2023).
5. Kodama J.& Kaito, T. Osteoclast multinucleation: review of current literature. Int. J. Mol. Sci. 21, 5685(2020).
6. Liu, Z.et al.RANKL inhibition halts lesion progression and promotes bone remineralization in mice with fibrous dysplasia. Bone 156, 116301 (2022).
7. Palmisano, B.et al.RANKL inhibition in fibrous Dysplasia of bone: a preclinical study in a mouse model of the human disease. J. Bone Min. Res. 34, 2171-2182 (2019).
8. Zhao, X.et al. Expression of an active Gα(s) mutant in skeletal stem cells is sufficient and necessary for fibrous dysplasia initiation and maintenance. Proc. Natl. Acad. Sci. USA 115, E428-e437 (2018).
9. Yousef, E. M.et al.MCM2: an alternative to Ki-67 for measuring breast cancer cell proliferation. Mod. Pathol. 30, 682-697 (2017).
10. Venet, D., Dumont, J. E.& Detours, V. Most random gene expression signatures are significantly associated with breast cancer outcome. PLoS Comput. Biol. 7, e1002240(2011).
11. Whitlock J. M., de Castro, L. F., Collins, M. T., Chernomordik, L. V. & Boyce, A. M. An inducible explant model of osteoclast-osteoprogenitor coordination in exacerbated osteoclastogenesis. iScience 26, 106470 (2023).
12. Li, D.et al.Osteoclast-derived exosomal miR-214-3p inhibits osteoblastic bone formation. Nat. Commun. 7, 10872(2016).
13. Sun, W.et al.Osteoclast-derived microRNA-containing exosomes selectively inhibit osteoblast activity. Cell Discov. 2, 16015(2016).
14. Huynh, N.et al.Characterization of regulatory extracellular vesicles from osteoclasts. J. Dent. Res. 95, 673-679 (2016).
15. de Castro, L. F.et al. Activation of RANK/RANKL/OPG pathway is involved in the pathophysiology of fibrous dysplasia and associated with disease burden. J. Bone Min. Res. 34, 290-294 (2019).
16. Boyce, A. M.et al.Surgical management of polyostotic craniofacial fibrous dysplasia: long-term outcomes and predictors for postoperative regrowth. Plast. Reconstr. Surg. 137, 1833-1839 (2016).
17. Hart, E. S.et al.Onset, progression, and plateau of skeletal lesions in fibrous dysplasia and the relationship to functional outcome. J. Bone Min. Res. 22, 1468-1474 (2007).
18. Florenzano, P.et al.Age-related changes and effects of bisphosphonates on bone turnover and disease progression in fibrous dysplasia of bone. J. Bone Min. Res. 34, 653-660 (2019).
19. Yeni, Y. N., Brown, C. U. & Norman, T. L. Influence of bone composition and apparent density on fracture toughness of the human femur and tibia. Bone 22, 79-84 (1998).
20. Wasserman H.& Gordon, C. M. Bone mineralization and fracture risk assessment in the pediatric population. J. Clin. Densitom. 20, 389-396 (2017).
21. Isobe, Y.et al.Direct evidence for the age-dependent demise of GNAS-mutated cells in oral fibrous dysplasia. Arch. Oral. Biol. 93, 133-140 (2018).
22. Kuznetsov, S. A.et al.Age-dependent demise of GNAS-mutated skeletal stem cells and “normalization” of fibrous dysplasia of bone. J. Bone Min. Res. 23, 1731-1740 (2008).
23. Majoor B. C.J. et al. Denosumab in patients with fibrous dysplasia previously treated with bisphosphonates. J. Clin. Endocrinol. Metab. 104, 6069-6078 (2019).
24. Ikebuchi, Y.et al. Coupling of bone resorption and formation by RANKL reverse signalling. Nature 561, 195-200 (2018).
25. Boyce, A. M.et al.A randomized, double blind, placebo-controlled trial of alendronate treatment for fibrous dysplasia of bone. J. Clin. Endocrinol. Metab. 99, 4133-4140 (2014).
26. Plotkin, H.et al.Effect of pamidronate treatment in children with polyostotic fibrous dysplasia of bone. J. Clin. Endocrinol. Metab. 88, 4569-4575 (2003).
27. Anastasilakis A. D., Papapoulos S. E., Polyzos S. A., Appelman-Dijkstra, N. M. & Makras, P. Zoledronate for the prevention of bone loss in women discontinuing Denosumab treatment. a prospective 2-year clinical trial. J. Bone Min. Res. 34, 2220-2228 (2019).
28. Collins, M. T.et al.An instrument to measure skeletal burden and predict functional outcome in fibrous dysplasia of bone. J. Bone Min. Res. 20, 219-226 (2005).
29. Hopkins, C.et al.Fibrous dysplasia animal models: A systematic review. Bone 155, 116270 (2022).
30. Xgeva (denosumab) [package insert]. Thousand Oaks,Xgeva (denosumab) [package insert]. Thousand Oaks, CA: Amgen Inc; 2020.
31. Hwang P. W.& Horton, J. A. Variable osteogenic performance of MC3T3-E1 subclones impacts their utility as models of osteoblast biology. Sci. Rep. 9, 8299(2019).
32. Andrews S.FastQC a quality control tool for high throughput sequence data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc/.
33. Dobin, A.et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15-21 (2013).
34. in R Foundation for Statistical Computing Ch. R: A language and environment for statistical computing, (2008).
35. Love, M. I., Huber, W.& Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550(2014).
36. Hänzelmann, S., Castelo, R.& Guinney, J. GSVA: gene set variation analysis for microarray and RNA-seq data. BMC Bioinforma. 14, 7(2013).
37. Dyment, N. A.et al. High-throughput, multi-image cryohistology of mineralized tissues. J. Vis. Exp. https://doi.org/10.3791/54468 (2016).
38. Verma, S. K.et al.Cell-surface phosphatidylserine regulates osteoclast precursor fusion. J. Biol. Chem. 293, 254-270 (2018).
39. Bankhead, P.et al.QuPath: open source software for digital pathology image analysis. Sci. Rep. 7, 16878(2017).
40. Verma, S. K., Chernomordik, L. V.& Melikov, K. An improved metrics for osteoclast multinucleation. Sci. Rep. 8, 1768(2018).
Funding
Alison M. Boyce (alison.boyce@nih.gov)

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