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Functional screening of FGFR4-driven tumorigenesis identifies PI3K/mTOR inhibition as a therapeutic strategy in rhabdomyosarcoma

Abstract

Rhabdomyosarcoma (RMS) is the most common pediatric soft tissue sarcoma and outcomes have stagnated, highlighting a need for novel therapies. Genomic analysis of RMS has revealed that alterations in the receptor tyrosine kinase (RTK)/RAS/PI3K axis are common and that FGFR4 is frequently mutated or overexpressed. Although FGFR4 is a potentially druggable receptor tyrosine kinase, its functions in RMS are undefined. This study tested FGFR4-activating mutations and overexpression for the ability to generate RMS in mice. Murine tumor models were subsequently used to discover potential therapeutic targets and to test a dual PI3K/mTOR inhibitor in a preclinical setting. Specifically, we provide the first mechanistic evidence of differential potency in the most common human RMS mutations, V550E or N535K, compared to FGFR4wt overexpression as murine myoblasts expressing FGFR4V550E undergo higher rates of cellular transformation, engraftment into mice, and rapidly form sarcomas that highly resemble human RMS. Murine tumor cells overexpressing FGFR4V550E were tested in an in vitro dose–response drug screen along with human RMS cell lines. Compounds were grouped by target class, and potency was determined using average percentage of area under the dose–response curve (AUC). RMS cells were highly sensitive to PI3K/mTOR inhibitors, in particular, GSK2126458 (omipalisib) was a potent inhibitor of FGFR4V550E tumor-derived cell and human RMS cell viability. FGFR4V550E-overexpressing myoblasts and tumor cells had low nanomolar GSK2126458 EC50 values. Mass cytometry using mouse and human RMS cell lines validated GSK2126458 specificity at single-cell resolution, decreasing the abundance of phosphorylated Akt as well as decreasing phosphorylation of the downstream mTOR effectors 4ebp1, Eif4e, and S6. Moreover, PI3K/mTOR inhibition also robustly decreased the growth of RMS tumors in vivo. Thus, by developing a preclinical platform for testing novel therapies, we identified PI3K/mTOR inhibition as a promising new therapy for this devastating pediatric cancer.

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References

  1. Tenente IM, Hayes MN, Ignatius MS, McCarthy K, Yohe M, Sindiri S, et al. Myogenic regulatory transcription factors regulate growth in rhabdomyosarcoma. Elife. 2017;6:e19214.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Kikuchi K, Rubin BP, Keller C. Developmental origins of fusion-negative rhabdomyosarcomas. Curr Top Dev Biol. 2011;96:33–56.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Barr FG. The role of chimeric paired box transcription factors in the pathogenesis of pediatric rhabdomysarcoma. Cancer Res. 1999;59:1711s–15.

    CAS  PubMed  Google Scholar 

  4. Galili N, Davis RJ, Fredericks WJ, Mukhopadhyay S, Rauscher FJ 3rd, Emanuel BS, et al. Fusion of a fork head domain gene to PAX3 in the solid tumour alveolar rhabdomyosarcoma. Nat Genet. 1993;5:230–5.

    Article  CAS  PubMed  Google Scholar 

  5. Linardic CM. PAX3-FOXO1 fusion gene in rhabdomyosarcoma. Cancer Lett. 2008;270:10–18.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Williamson D, Missiaglia E, de Reynies A, Pierron G, Thuille B, Palenzuela G, et al. Fusion gene-negative alveolar rhabdomyosarcoma is clinically and molecularly indistinguishable from embryonal rhabdomyosarcoma. J Clin Oncol. 2010;28:2151–8.

    Article  PubMed  Google Scholar 

  7. Shern JF, Chen L, Chmielecki J, Wei JS, Patidar R, Rosenberg M, et al. Comprehensive genomic analysis of rhabdomyosarcoma reveals a landscape of alterations affecting a common genetic axis in fusion-positive and fusion-negative tumors. Cancer Discov. 2014;4:216–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Abraham J, Nunez-Alvarez Y, Hettmer S, Carrio E, Chen HI, Nishijo K, et al. Lineage of origin in rhabdomyosarcoma informs pharmacological response. Genes Dev. 2014;28:1578–91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Chmielecki J, Bailey M, He J, Elvin J, Vergilio JA, Ramkissoon S, et al. Genomic profiling of a large set of diverse pediatric cancers identifies known and novel mutations across tumor spectra. Cancer Res. 2017;77:509–19.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Vogelstein B, Papadopoulos N, Velculescu VE, Zhou S, Diaz LA Jr, Kinzler KW. Cancer genome landscapes. Science. 2013;339:1546–58.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Ognjanovic S, Linabery AM, Charbonneau B, Ross JA. Trends in childhood rhabdomyosarcoma incidence and survival in the United States, 1975-2005. Cancer. 2009;115:4218–26.

    Article  PubMed  Google Scholar 

  12. Weigel BJ, Lyden E, Anderson JR, Meyer WH, Parham DM, Rodeberg DA, et al. Intensive multiagent therapy, including dose-compressed cycles of ifosfamide/etoposide and vincristine/doxorubicin/cyclophosphamide, irinotecan, and radiation, in patients with high-risk rhabdomyosarcoma: a report from the Children’s Oncology Group. J Clin Oncol. 2016;34:117–22.

    Article  CAS  PubMed  Google Scholar 

  13. Khan J, Wei JS, Ringner M, Saal LH, Ladanyi M, Westermann F, et al. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Nat Med. 2001;7:673–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Gryder BE, Yohe ME, Chou HC, Zhang X, Marques J, Wachtel M, et al. PAX3-FOXO1 establishes myogenic super enhancers and confers BET bromodomain vulnerability. Cancer Discov. 2017;7:884–99.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Seki M, Nishimura R, Yoshida K, Shimamura T, Shiraishi Y, Sato Y, et al. Integrated genetic and epigenetic analysis defines novel molecular subgroups in rhabdomyosarcoma. Nat Commun. 2015;6:7557.

    Article  PubMed  Google Scholar 

  16. Taylor JGT, Cheuk AT, Tsang PS, Chung JY, Song YK, Desai K, et al. Identification of FGFR4-activating mutations in human rhabdomyosarcomas that promote metastasis in xenotransplanted models. J Clin Invest. 2009;119:3395–407.

    CAS  PubMed  Google Scholar 

  17. Li SQ, Cheuk AT, Shern JF, Song YK, Hurd L, Liao H, et al. Targeting wild-type and mutationally activated FGFR4 in rhabdomyosarcoma with the inhibitor ponatinib (AP24534). PLoS ONE. 2013;8:e76551.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. McKinnon T, Venier R, Dickson BC, Kabaroff L, Alkema M, Chen L, et al. Kras activation in p53-deficient myoblasts results in high-grade sarcoma formation with impaired myogenic differentiation. Oncotarget. 2015;6:14220–32.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Knight SD, Adams ND, Burgess JL, Chaudhari AM, Darcy MG, Donatelli CA, et al. Discovery of GSK2126458, a highly potent inhibitor of PI3K and the mammalian target of rapamycin. ACS Med Chem Lett. 2010;1:39–43.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Fletcher CDM, Bridge, JA, Hogendoorn, P, Mertens, F. WHO classification of tumours, vol. 5. International Agency for Research on Cancer (IARC): Lyon, France, 2013.

  21. Mathews Griner LA, Guha R, Shinn P, Young RM, Keller JM, Liu D, et al. High-throughput combinatorial screening identifies drugs that cooperate with ibrutinib to kill activated B-cell-like diffuse large B-cell lymphoma cells. Proc Natl Acad Sci USA. 2014;111:2349–54.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Bendall SC, Simonds EF, Qiu P, Amir el AD, Krutzik PO, Finck R, et al. Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science. 2011;332:687–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Perova T, Grandal I, Nutter LM, Papp E, Matei IR, Beyene J, et al. Therapeutic potential of spleen tyrosine kinase inhibition for treating high-risk precursor B cell acute lymphoblastic leukemia. Sci Transl Med. 2014;6:236ra262.

    Article  CAS  Google Scholar 

  24. Dowling RJ, Topisirovic I, Alain T, Bidinosti M, Fonseca BD, Petroulakis E, et al. mTORC1-mediated cell proliferation, but not cell growth, controlled by the 4E-BPs. Science. 2010;328:1172–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Fruman DA, Rommel C. PI3K and cancer: lessons, challenges and opportunities. Nat Rev Drug Discov. 2014;13:140–56.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Chen L, Shern JF, Wei JS, Yohe ME, Song YK, Hurd L, et al. Clonality and evolutionary history of rhabdomyosarcoma. PLoS Genet. 2015;11:e1005075.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Crose LE, Etheridge KT, Chen C, Belyea B, Talbot LJ, Bentley RC, et al. FGFR4 blockade exerts distinct antitumorigenic effects in human embryonal versus alveolar rhabdomyosarcoma. Clin Cancer Res. 2012;18:3780–90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Cao L, Yu Y, Bilke S, Walker RL, Mayeenuddin LH, Azorsa DO, et al. Genome-wide identification of PAX3-FKHR binding sites in rhabdomyosarcoma reveals candidate target genes important for development and cancer. Cancer Res. 2010;70:6497–508.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Paulson V, Chandler G, Rakheja D, Galindo RL, Wilson K, Amatruda JF, et al. High-resolution array CGH identifies common mechanisms that drive embryonal rhabdomyosarcoma pathogenesis. Genes Chromosomes Cancer. 2011;50:397–408.

    Article  CAS  PubMed  Google Scholar 

  30. Marics I, Padilla F, Guillemot JF, Scaal M, Marcelle C. FGFR4 signaling is a necessary step in limb muscle differentiation. Development. 2002;129:4559–69.

    CAS  PubMed  Google Scholar 

  31. Zhao P, Caretti G, Mitchell S, McKeehan WL, Boskey AL, Pachman LM, et al. Fgfr4 is required for effective muscle regeneration in vivo. Delineation of a MyoD-Tead2-Fgfr4 transcriptional pathway. J Biol Chem. 2006;281:429–38.

    Article  CAS  PubMed  Google Scholar 

  32. Zhao P, Hoffman EP. Embryonic myogenesis pathways in muscle regeneration. Dev Dyn. 2004;229:380–92.

    Article  CAS  PubMed  Google Scholar 

  33. Lewin J, Siu LL. Development of fibroblast growth factor receptor inhibitors: kissing frogs to find a prince? J Clin Oncol. 2015;33:3372–4.

    Article  CAS  PubMed  Google Scholar 

  34. Kashi VP, Hatley ME, Galindo RL. Probing for a deeper understanding of rhabdomyosarcoma: insights from complementary model systems. Nat Rev Cancer. 2015;15:426–39.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Campeau E, Ruhl VE, Rodier F, Smith CL, Rahmberg BL, Fuss JO, et al. A versatile viral system for expression and depletion of proteins in mammalian cells. PLoS ONE. 2009;4:e6529.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Rando TA, Blau HM. Primary mouse myoblast purification, characterization, and transplantation for cell-mediated gene therapy. J Cell Biol. 1994;125:1275–87.

    Article  CAS  PubMed  Google Scholar 

  37. Johnson RA, Wright KD, Poppleton H, Mohankumar KM, Finkelstein D, Pounds SB, et al. Cross-species genomics matches driver mutations and cell compartments to model ependymoma. Nature. 2010;466:632–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Poschl J, Stark S, Neumann P, Grobner S, Kawauchi D, Jones DT, et al. Genomic and transcriptomic analyses match medulloblastoma mouse models to their human counterparts. Acta Neuropathol. 2014;128:123–36.

    Article  CAS  PubMed  Google Scholar 

  39. Ceribelli M, Kelly PN, Shaffer AL, Wright GW, Xiao W, Yang Y, et al. Blockade of oncogenic IkappaB kinase activity in diffuse large B-cell lymphoma by bromodomain and extraterminal domain protein inhibitors. Proc Natl Acad Sci USA. 2014;111:11365–70.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We acknowledge Dr. M. Bhaskhurov (LTRI) for high content image analysis, S. Burtenshaw for statistical analysis and manuscript preparation, Dr. D. Holmyard (Mount Sinai Hospital) for electron microscopy, Dr. E. Stewart (St. Jude’s) for preclinical study design and Dr. J. Fletcher (Brigham and Women’s Hospital) for use of RMS559.

Funding

CJG was supported by funding from the Canadian Cancer Society Research Institute and the Cancer Stem Cells Program of the Ontario Institute for Cancer Research; RAG was supported by a Clinical Investigator Award from Ontario Institute for Cancer Research.

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Correspondence to Rebecca A. Gladdy.

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McKinnon, T., Venier, R., Yohe, M. et al. Functional screening of FGFR4-driven tumorigenesis identifies PI3K/mTOR inhibition as a therapeutic strategy in rhabdomyosarcoma. Oncogene 37, 2630–2644 (2018). https://doi.org/10.1038/s41388-017-0122-y

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