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A Sleeping Beauty forward genetic screen identifies new genes and pathways driving osteosarcoma development and metastasis

Nature Genetics volume 47, pages 615–624 (2015)Cite this article

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Abstract

Osteosarcomas are sarcomas of the bone, derived from osteoblasts or their precursors, with a high propensity to metastasize. Osteosarcoma is associated with massive genomic instability, making it problematic to identify driver genes using human tumors or prototypical mouse models, many of which involve loss of Trp53 function. To identify the genes driving osteosarcoma development and metastasis, we performed a Sleeping Beauty (SB) transposon-based forward genetic screen in mice with and without somatic loss of Trp53. Common insertion site (CIS) analysis of 119 primary tumors and 134 metastatic nodules identified 232 sites associated with osteosarcoma development and 43 sites associated with metastasis, respectively. Analysis of CIS-associated genes identified numerous known and new osteosarcoma-associated genes enriched in the ErbB, PI3K-AKT-mTOR and MAPK signaling pathways. Lastly, we identified several oncogenes involved in axon guidance, including Sema4d and Sema6d, which we functionally validated as oncogenes in human osteosarcoma.

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Figure 1: SB mutagenesis can accelerate or induce osteosarcoma development in cells with Sp7-cre expression.
Figure 2: CIS analysis identifies osteosarcoma driver genes.
Figure 3: Analysis of CIS-associated genes identifies cooperating mutations, genetic pathways and upstream regulators in osteosarcoma development.
Figure 4: Comparative genomics analysis of CIS-associated genes in osteosarcoma.
Figure 5: Pten loss accelerates osteosarcoma development in mice and PTEN loss enhances the anchorage-independent growth of immortalized human osteoblast cells.
Figure 6: Axon guidance–related genes are implicated in osteosarcoma.
Figure 7: SEMA4D and SEMA6D overexpression increases the levels of phosphorylated AKT and/or ERK.
Figure 8: Osteosarcoma metastases are clonal in nature and identify CIS-associated metastasis genes.

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References

  1. Kansara, M. & Thomas, D.M. Molecular pathogenesis of osteosarcoma. DNA Cell Biol. 26, 1–18 (2007).

    Article  CAS  PubMed  Google Scholar 

  2. Allison, D.C. et al. A meta-analysis of osteosarcoma outcomes in the modern medical era. Sarcoma 2012, 704872 (2012).

    PubMed  PubMed Central  Google Scholar 

  3. Jaffe, N., Puri, A. & Gelderblom, H. Osteosarcoma: evolution of treatment paradigms. Sarcoma 2013, 203531 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Tsuchiya, H. et al. Effect of timing of pulmonary metastases identification on prognosis of patients with osteosarcoma: the Japanese Musculoskeletal Oncology Group study. J. Clin. Oncol. 20, 3470–3477 (2002).

    Article  PubMed  Google Scholar 

  5. Kager, L. et al. Primary metastatic osteosarcoma: presentation and outcome of patients treated on neoadjuvant Cooperative Osteosarcoma Study Group protocols. J. Clin. Oncol. 21, 2011–2018 (2003).

    Article  PubMed  Google Scholar 

  6. Meyers, P.A. et al. Osteogenic sarcoma with clinically detectable metastasis at initial presentation. J. Clin. Oncol. 11, 449–453 (1993).

    Article  CAS  PubMed  Google Scholar 

  7. Dobson, J.M. Breed-predispositions to cancer in pedigree dogs. ISRN Vet. Sci. 2013, 2013:941275 (2013).

    Article  CAS  PubMed  Google Scholar 

  8. Overholtzer, M. et al. The presence of p53 mutations in human osteosarcomas correlates with high levels of genomic instability. Proc. Natl. Acad. Sci. USA 100, 11547–11552 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Kansara, M., Teng, M.W., Smyth, M.J. & Thomas, D.M. Translational biology of osteosarcoma. Nat. Rev. Cancer 14, 722–735 (2014).

    Article  CAS  PubMed  Google Scholar 

  10. Kuijjer, M.L. et al. Identification of osteosarcoma driver genes by integrative analysis of copy number and gene expression data. Genes Chromosom. Cancer 51, 696–706 (2012).

    Article  CAS  PubMed  Google Scholar 

  11. Sadikovic, B. et al. Identification of interactive networks of gene expression associated with osteosarcoma oncogenesis by integrated molecular profiling. Hum. Mol. Genet. 18, 1962–1975 (2009).

    Article  CAS  PubMed  Google Scholar 

  12. Kresse, S.H. et al. Integrative analysis reveals relationships of genetic and epigenetic alterations in osteosarcoma. PLoS ONE 7, e48262 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Copeland, N.G. & Jenkins, N.A. Harnessing transposons for cancer gene discovery. Nat. Rev. Cancer 10, 696–706 (2010).

    Article  CAS  PubMed  Google Scholar 

  14. Chen, X. et al. Recurrent somatic structural variations contribute to tumorigenesis in pediatric osteosarcoma. Cell Rep. 7, 104–112 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Jones, K.B. Osteosarcomagenesis: modeling cancer initiation in the mouse. Sarcoma 2011, 694136 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Rodda, S.J. & McMahon, A.P. Distinct roles for Hedgehog and canonical Wnt signaling in specification, differentiation and maintenance of osteoblast progenitors. Development 133, 3231–3244 (2006).

    Article  CAS  PubMed  Google Scholar 

  17. Olive, K.P. et al. Mutant p53 gain of function in two mouse models of Li-Fraumeni syndrome. Cell 119, 847–860 (2004).

    Article  CAS  PubMed  Google Scholar 

  18. Zhang, G., Li, M., Zhu, X., Bai, Y. & Yang, C. Knockdown of Akt sensitizes osteosarcoma cells to apoptosis induced by cisplatin treatment. Int. J. Mol. Sci. 12, 2994–3005 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Clark, J.C., Dass, C.R. & Choong, P.F. A review of clinical and molecular prognostic factors in osteosarcoma. J. Cancer Res. Clin. Oncol. 134, 281–297 (2008).

    Article  CAS  PubMed  Google Scholar 

  20. Sabile, A.A. et al. Caprin-1, a novel Cyr61-interacting protein, promotes osteosarcoma tumor growth and lung metastasis in mice. Biochim. Biophys. Acta 1832, 1173–1182 (2013).

    Article  CAS  PubMed  Google Scholar 

  21. Guo, W. et al. Expression of bone morphogenetic proteins and receptors in sarcomas. Clin. Orthop. Relat. Res. (365), 175–183 (1999).

    Article  Google Scholar 

  22. Nakajima, G. et al. CDH11 expression is associated with survival in patients with osteosarcoma. Cancer Genomics Proteomics 5, 37–42 (2008).

    CAS  PubMed  Google Scholar 

  23. Chueh, F.S. et al. Bufalin-inhibited migration and invasion in human osteosarcoma U-2 OS cells is carried out by suppression of the matrix metalloproteinase-2, ERK, and JNK signaling pathways. Environ. Toxicol. 29, 21–29 (2014).

    Article  CAS  PubMed  Google Scholar 

  24. Chen, L. et al. miR-16 inhibits cell proliferation by targeting IGF1R and the Raf1-MEK1/2-ERK1/2 pathway in osteosarcoma. FEBS Lett. 587, 1366–1372 (2013).

    Article  CAS  PubMed  Google Scholar 

  25. Osborne, T.S. et al. Evaluation of eIF4E expression in an osteosarcoma-specific tissue microarray. J. Pediatr. Hematol. Oncol. 33, 524–528 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Xu, H., Mei, Q., Xiong, C. & Zhao, J. Tumor-suppressing effects of miR-141 in human osteosarcoma. Cell Biochem. Biophys. 69, 319–325 (2014).

    Article  CAS  PubMed  Google Scholar 

  27. Zhao, R., Ni, D., Tian, Y., Ni, B. & Wang, A. Aberrant ADAM10 expression correlates with osteosarcoma progression. Eur. J. Med. Res. 19, 9 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Toledo, S.R.C. et al. Bone deposition, bone resorption, and osteosarcoma. J. Orthop. Res. 28, 1142–1148 (2010).

    Article  PubMed  Google Scholar 

  29. Liu, Y. et al. Rapamycin increases pCREB, Bcl-2, and VEGF-A through ERK under normoxia. Acta Biochim. Biophys. Sin. (Shanghai) 45, 259–267 (2013).

    Article  CAS  Google Scholar 

  30. Zhang, P., Yang, Y., Zweidler-McKay, P.A. & Hughes, D.P. Critical role of Notch signaling in osteosarcoma invasion and metastasis. Clin. Cancer Res. 14, 2962–2969 (2008); retracted 15 September 2013.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Patiño-García, A., Zalacaín, M., Marrodán, L., San-Julián, M. & Sierrasesúmaga, L. Methotrexate in pediatric osteosarcoma: response and toxicity in relation to genetic polymorphisms and dihydrofolate reductase and reduced folate carrier 1 expression. J. Pediatr. 154, 688–693 (2009).

    Article  CAS  PubMed  Google Scholar 

  32. Kim, K.O. et al. Proteomic identification of 14-3-3ɛ as a linker protein between pERK1/2 inhibition and BIM upregulation in human osteosarcoma cells. J. Orthop. Res. 32, 848–854 (2014).

    Article  CAS  PubMed  Google Scholar 

  33. de Nigris, F. et al. YY1 overexpression is associated with poor prognosis and metastasis-free survival in patients suffering osteosarcoma. BMC Cancer 11, 472 (2011).

    Article  PubMed  Google Scholar 

  34. Lu, X.Y. et al. Cell cycle regulator gene CDC5L, a potential target for 6p12-p21 amplicon in osteosarcoma. Mol. Cancer Res. 6, 937–946 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Yuan, D. et al. Overexpression of fibroblast activation protein and its clinical implications in patients with osteosarcoma. J. Surg. Oncol. 108, 157–162 (2013).

    Article  CAS  PubMed  Google Scholar 

  36. Sato, H. et al. Repression of p53-dependent sequence-specific transactivation by MEF2c. Biochem. Biophys. Res. Commun. 214, 468–474 (1995).

    Article  CAS  PubMed  Google Scholar 

  37. Zhu, Y., Zhou, J., Ji, Y. & Yu, B. Elevated expression of AKT2 correlates with disease severity and poor prognosis in human osteosarcoma. Mol. Med. Rep. 10, 737–742 (2014).

    Article  CAS  PubMed  Google Scholar 

  38. Han, K. et al. microRNA-194 suppresses osteosarcoma cell proliferation and metastasis in vitro and in vivo by targeting CDH2 and IGF1R. Int. J. Oncol. 45, 1437–1449 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Wang, K. & Zhang, X. Inhibition of SENP5 suppresses cell growth and promotes apoptosis in osteosarcoma cells. Exp. Ther. Med. 7, 1691–1695 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Jones, K.B. et al. miRNA signatures associate with pathogenesis and progression of osteosarcoma. Cancer Res. 72, 1865–1877 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Gao, Y., Luo, L., Li, S. & Yang, C. miR-17 inhibitor suppressed osteosarcoma tumor growth and metastasis via increasing PTEN expression. Biochem. Biophys. Res. Commun. 444, 230–234 (2014).

    Article  CAS  PubMed  Google Scholar 

  42. Song, Q.C. et al. Downregulation of microRNA-26a is associated with metastatic potential and the poor prognosis of osteosarcoma patients. Oncol. Rep. 31, 1263–1270 (2014).

    Article  CAS  PubMed  Google Scholar 

  43. Tesser-Gamba, F. et al. MAPK7 and MAP2K4 as prognostic markers in osteosarcoma. Hum. Pathol. 43, 994–1002 (2012).

    Article  CAS  PubMed  Google Scholar 

  44. Srivastava, A. et al. High WT1 expression is associated with very poor survival of patients with osteogenic sarcoma metastasis. Clin. Cancer Res. 12, 4237–4243 (2006).

    Article  CAS  PubMed  Google Scholar 

  45. Scott, M.C. et al. Molecular subtypes of osteosarcoma identified by reducing tumor heterogeneity through an interspecies comparative approach. Bone 49, 356–367 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Freeman, S.S. et al. Copy number gains in EGFR and copy number losses in PTEN are common events in osteosarcoma tumors. Cancer 113, 1453–1461 (2008).

    Article  CAS  PubMed  Google Scholar 

  47. Xiao, A. et al. Somatic induction of Pten loss in a preclinical astrocytoma model reveals major roles in disease progression and avenues for target discovery and validation. Cancer Res. 65, 5172 (2005).

    Article  CAS  PubMed  Google Scholar 

  48. Neale, G. et al. Molecular characterization of the pediatric preclinical testing panel. Clin. Cancer Res. 14, 4572–4583 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Swiercz, J.M., Worzfeld, T. & Offermanns, S. ErbB-2 and Met reciprocally regulate cellular signaling via plexin-B1. J. Biol. Chem. 283, 1893–1901 (2008).

    Article  CAS  PubMed  Google Scholar 

  50. Jiang, L. et al. CLDN3 inhibits cancer aggressiveness via Wnt-EMT signaling and is a potential prognostic biomarker for hepatocellular carcinoma. Oncotarget. 5, 7663–7676 (2014).

    PubMed  PubMed Central  Google Scholar 

  51. Wang, S. et al. Prostate-specific deletion of the murine Pten tumor suppressor gene leads to metastatic prostate cancer. Cancer Cell 4, 209–221 (2003).

    Article  CAS  PubMed  Google Scholar 

  52. Williams, K.C. & Coppolino, M.G. SNARE-dependent interaction of Src, EGFR and β1 integrin regulates invadopodia formation and tumor cell invasion. J. Cell Sci. 127, 1712–1725 (2014).

    Article  CAS  PubMed  Google Scholar 

  53. Zhao, B. et al. MicroRNA let-7c inhibits migration and invasion of human non–small cell lung cancer by targeting ITGB3 and MAP4K3. Cancer Lett. 342, 43–51 (2014).

    Article  CAS  PubMed  Google Scholar 

  54. Kusama, T. et al. Inactivation of Rho GTPases by p190 RhoGAP reduces human pancreatic cancer cell invasion and metastasis. Cancer Sci. 97, 848–853 (2006).

    Article  CAS  PubMed  Google Scholar 

  55. Song, C. et al. Expression of p114RhoGEF predicts lymph node metastasis and poor survival of squamous-cell lung carcinoma patients. Tumour Biol. 34, 1925–1933 (2013).

    Article  CAS  PubMed  Google Scholar 

  56. Zhou, C.X. & Gao, Y. Frequent genetic alterations and reduced expression of the Axin1 gene in oral squamous cell carcinoma: involvement in tumor progression and metastasis. Oncol. Rep. 17, 73–79 (2007).

    CAS  PubMed  Google Scholar 

  57. Li, X. et al. PHLPP is a negative regulator of RAF1, which reduces colorectal cancer cell motility and prevents tumor progression in mice. Gastroenterology 146, 1301–1312 (2014).

    Article  CAS  PubMed  Google Scholar 

  58. Li, D. & Huang, Y. Knockdown of ubiquitin associated protein 2–like inhibits the growth and migration of prostate cancer cells. Oncol. Rep. 32, 1578–1584 (2014).

    Article  CAS  PubMed  Google Scholar 

  59. Keng, V.W. et al. A conditional transposon-based insertional mutagenesis screen for genes associated with mouse hepatocellular carcinoma. Nat. Biotechnol. 27, 264–274 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Wu, X. et al. Clonal selection drives genetic divergence of metastatic medulloblastoma. Nature 482, 529–533 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Klein, C.A. Parallel progression of primary tumours and metastases. Nat. Rev. Cancer 9, 302–312 (2009).

    Article  CAS  PubMed  Google Scholar 

  62. Loh, A.H. et al. Dissecting the PI3K signaling axis in pediatric solid tumors: novel targets for clinical integration. Front. Oncol. 3, 93 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  63. Yue, B., Ren, Q., Su, T., Wang, L. & Zhang, L. ERK5 silencing inhibits invasion of human osteosarcoma cell via modulating the Slug/MMP-9 pathway. J. Clin. Exp. Pathol. 4, 2640–2647 (2014).

    Google Scholar 

  64. Geryk-Hall, M. & Hughes, D.P.M. Critical signaling pathways in bone sarcoma: candidates for therapeutic interventions. Curr. Oncol. Rep. 11, 446–453 (2009).

    Article  CAS  PubMed  Google Scholar 

  65. Rahrmann, E.P. Forward genetic screen for malignant peripheral nerve sheath tumor formation identifies novel genes and genetic pathways driving tumorigenesis. Nat. Genet. 45, 756–766 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Starr, T.K. et al. A transposon-based genetic screen in mice identifies genes altered in colorectal cancer. Science 323, 1747–1750 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Dupuy, A.J. et al. A modified Sleeping Beauty transposon system that can be used to model a wide variety of human cancers in mice. Cancer Res. 69, 8150 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Cinamon, U., Avinoach, I. & Harell, M. Neurofibromatosis type 1, hyperparathyroidism, and osteosarcoma: interplay? Eur. Arch. Otorhinolaryngol. 259, 540–542 (2002).

    PubMed  Google Scholar 

  69. Ferrari, A., Bisogno, G. & Carli, M. Management of childhood malignant peripheral nerve sheath tumor. Paediatr. Drugs 9, 239–248 (2007).

    Article  PubMed  Google Scholar 

  70. Chowdhry, M. et al. Bone sarcomas arising in patients with neurofibromatosis type 1. J. Bone Joint Surg. Br. 91, 1223 (2009).

    Article  CAS  PubMed  Google Scholar 

  71. McClatchey, A.I. et al. Mice heterozygous for a mutation at the Nf2 tumor suppressor locus develop a range of highly metastatic tumors. Genes Dev. 12, 1121–1133 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Stemmer-Rachamimov, A.O. et al. The NF2 gene and merlin protein in human osteosarcomas. Neurogenetics 2, 73–74 (1998).

    Article  CAS  PubMed  Google Scholar 

  73. Rudolph, K.L. et al. Longevity, stress response, and cancer in aging telomerase-deficient mice. Cell 96, 701–712 (1999).

    Article  CAS  PubMed  Google Scholar 

  74. Law, J.W.S. & Lee, A.Y.W. The role of semaphorins and their receptors in gliomas. J. Signal Transduct. 2012, 902854 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Catalano, A., Lazzarini, R., Di Nuzzo, S., Orciari, S. & Procopio, A. The plexin-A1 receptor activates vascular endothelial growth factor–receptor 2 and nuclear factor–κB to mediate survival and anchorage-independent growth of malignant mesothelioma cells. Cancer Res. 69, 1485–1493 (2009).

    Article  CAS  PubMed  Google Scholar 

  76. Negishi-Koga, T. et al. Suppression of bone formation by osteoclastic expression of semaphorin 4D. Nat. Med. 17, 1473–1480 (2011).

    Article  CAS  PubMed  Google Scholar 

  77. Patanè, S. et al. MET overexpression turns human primary osteoblasts into osteosarcomas. Cancer Res. 66, 4750–4757 (2006).

    Article  PubMed  Google Scholar 

  78. Akatsuka, T. et al. ErbB2 expression is correlated with increased survival of patients with osteosarcoma. Cancer 94, 1397–1404 (2002).

    Article  CAS  PubMed  Google Scholar 

  79. Zhou, H., Binmadi, N.O., Yang, Y., Proia, P. & Basile, J.R. Semaphorin 4D cooperates with VEGF to promote angiogenesis and tumor progression. Angiogenesis 15, 391–407 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Nguyen, D.X., Bos, P.D. & Massagué, J. Metastasis: from dissemination to organ-specific colonization. Nat. Rev. Cancer 9, 274–284 (2009).

    Article  CAS  PubMed  Google Scholar 

  81. Ognjanovic, S., Olivier, M., Bergemann, T.L. & Hainaut, P. Sarcomas in TP53 germline mutation carriers. Cancer 118, 1387–1396 (2012).

    Article  CAS  PubMed  Google Scholar 

  82. Sarver, A.L., Erdman, J., Starr, T., Largaespada, D.A. & Silverstein, K.A. TAPDANCE: an automated tool to identify and annotate transposon insertion CISs and associations between CISs from next generation sequence data. BMC Bioinformatics 13, 154 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  83. Brett, B.T. et al. Novel molecular and computational methods improve the accuracy of insertion site analysis in Sleeping Beauty–induced tumors. PLoS ONE 6, e24668 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Moriarity, B. & Largaespada, D.A. A comprehensive guide to Sleeping Beauty–based somatic transposon mutagenesis in the mouse. Curr. Protoc. Mouse Biol. 347–368 (2011).

  85. Collier, L.S., Carlson, C.M., Ravimohan, S., Dupuy, A.J. & Largaespada, D.A. Cancer gene discovery in solid tumours using transposon-based somatic mutagenesis in the mouse. Nature 436, 272–276 (2005).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

B.S.M. was funded by US National Institutes of Health/National Institute of Arthritis and Musculoskeletal and Skin Diseases Musculoskeletal Training Grant AR050938. This research was funded by the Sobiech Osteosarcoma Fund Award, the Children's Cancer Research Fund, an American Cancer Center Research Professor Grant (123939) and National Cancer Institute grant R01 CA113636 (to D.A.L.). We extend our thanks to the University of Minnesota resources involved in our project. The University of Minnesota Genomics Center provided services for RNA sequencing, oligonucleotide preparation and Sanger sequencing. The Minnesota Supercomputing Institute maintains the Galaxy software platform, as well as provides data management services and training. The cytogenetic analyses were performed in the Cytogenomics Shared Resource at the University of Minnesota with support from the comprehensive Masonic Cancer Center (US National Institutes of Health grant P30 CA077598).

Author information

Authors and Affiliations

  1. Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota, USA

    Branden S Moriarity, George M Otto, Eric P Rahrmann & David A Largaespada

  2. Center for Genome Engineering, University of Minnesota, Minneapolis, Minnesota, USA

    Branden S Moriarity, George M Otto, Eric P Rahrmann & David A Largaespada

  3. Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota, USA

    Branden S Moriarity, George M Otto, Eric P Rahrmann, Susan K Rathe, Natalie K Wolf, Madison T Weg, Rebecca S LaRue, Nuri A Temiz, Aaron L Sarver, Milcah C Scott, Jaime F Modiano & David A Largaespada

  4. Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, Minnesota, USA

    George M Otto, Eric P Rahrmann, Natalie K Wolf, Madison T Weg, Luke A Manlove, Kevin J Holly & David A Largaespada

  5. Department of Medicine, University of Minnesota, Minneapolis, Minnesota, USA

    Rebecca S LaRue

  6. Ontario Cancer Institute, Toronto, Ontario, Canada

    Sam D Molyneux & Rama Khokha

  7. Division of Experimental Hematology and Cancer Biology, Cincinnati Children's Hospital Research Foundation, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA

    Kwangmin Choi

  8. Department of Veterinary Clinical Sciences, University of Minnesota, St. Paul, Minnesota, USA

    Milcah C Scott & Jaime F Modiano

  9. BioNet, Academic Health Center, University of Minnesota, Minneapolis, Minnesota, USA

    Colleen L Forster

  10. Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota, USA

    Jaime F Modiano

  11. Tumor and Metastasis Biology Section, Pediatric Oncology Branch, National Cancer Institute, Bethesda, Maryland, USA

    Chand Khanna

  12. Tissue Array Research Program (TARP), Laboratory of Pathology, National Cancer Institute, Bethesda, Maryland, USA

    Stephen M Hewitt

  13. Department of Orthopedic Surgery, Musculoskeletal Tumor Center, People's Hospital, Peking University, Beijing, China

    Yi Yang

  14. Department of Pediatrics, Albert Einstein College of Medicine and Children's Hospital at Montefiore, Bronx, New York, USA

    Richard Gorlick

  15. Department of Molecular Pharmacology, Albert Einstein College of Medicine and Children's Hospital at Montefiore, Bronx, New York, USA

    Richard Gorlick

  16. Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA

    Michael A Dyer

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  1. Branden S Moriarity
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  23. David A Largaespada
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Contributions

B.S.M., G.M.O., E.P.R., S.K.R., N.K.W., M.T.W., L.A.M. and K.J.H. performed laboratory experiments and/or analyzed the data. N.A.T. and K.C. performed bioinformatic data analysis of RNA sequencing, methylome and copy number analysis data. M.A.D. provided RNA sequencing and methylation data for human osteosarcoma samples. C.L.F. performed immunohistochemistry staining on osteosarcoma tumor microarrays. M.C.S. and J.F.M. provided data on canine osteosarcoma gene expression and outcome. A.L.S. analyzed the deep sequencing data for CIS analysis. R.K. and S.D.M. acquired and analyzed data from COSMIC and CGC. R.S.L. performed comparative analysis of CIS genes among SB screens. S.M.H. and C.K. assessed the histology of mouse tumors. R.G. and Y.Y. generated the immortalized osteoblast cells. D.A.L. supervised laboratory experiments and assisted in writing the manuscript. B.S.M. wrote the manuscript.

Corresponding author

Correspondence to David A Largaespada.

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Competing interests

D.A.L. is a founder of Discovery Genomics, Inc., and holds stock. D.A.L. is a founder of NeoClone Biotechnology, Inc., and holds stock. Some research in the Largaespada laboratory, not related to this work, is funded by Genentech, Inc.

Integrated supplementary information

Supplementary Figure 1 Breeding scheme, transgenes, histological analysis and site distribution of SB-mutagenized osteosarcoma.

(a) Breeding scheme. R26-LSL-SB11 homozygous mice were bred to Trp53LSL-R270H/+ mice to generate doubly transgenic mice. Concurrently, Osx-cre mice were bred to T2/Onc mice. These doubly transgenic mice were then intercrossed to obtain experimental and control animals. (b) Transgene architecture of the Rosa26-LSL-SB11, T2/Onc, Osx-cre and Trp53LSL-R270H/+ alleles used in this study. T2/Onc is engineered with splice acceptors (SA) and polyadenylation (pA) signals in both orientations for gene inactivation and the strong murine stem cell virus (MSCV) 5′ LTR promoter followed by a splice donor (SD) sequence for overexpressing genes. (c–k) Hematoxylin and eosin (H&E)-stained sections showing the representative tumor morphology of SB-mutagenized osteosarcoma with areas of high cellularity (d,e), invasive growth into surrounding tissue (f,g) and large areas of osteoid deposits (h–k). Scale bars, 200 µm for c,e,g,i and 50 µm for d,f,h,k. (n) Graphs displaying the percentage of tumors that developed at each site in Trp53-C (n = 30), Trp53-SBmut (n = 96) and SBmut (n = 23) animals.

Supplementary Figure 2 Validation of SB mutagenesis, local hopping and Myc/Cdkn2a.

(a) Representative photomicrographs of positive IHC staining for SB protein and an appropriate control with no primary antibody, performed on SB-mutagenized osteosarcomas. (b,c) PCR-based transposon excision assay demonstrating that transposition is occurring in all SB-mutagenized osteosarcoma tumors (225-bp amplicon) and absent in background tumors (2.4-kb amplicon). Appropriate positive and negative excision controls are shown. (d) Diagram depicting the CISs identified on all chromosomes from animals with T2/Onc concatemers on chromosomes 4 (red symbols) and 15 (blue symbols). The height of each symbol indicates the frequency of the CIS, with symbols stacked for chromosomes 4 (0–40) and 15 (40–80). (e) Diagram depicting T2/Onc insertion sites driving overexpression of Myc and causing loss of function of Cdkn2a. Black and red arrows represent T2/Onc insertions identified in tumors from Trp53-SBmut and SBmut animals, respectively. The direction of the arrows is representative of the direction of the mouse stem cell virus (MSCV) LTR and splice donor (SD) sequence of T2/Onc. (f) Relative levels of mRNA for Myc and Cdkn2a isolated from tumors with or without T2/Onc insertions in the respective genes analyzed by quantitative PCR. Error bars, s.d.

Supplementary Figure 3 The CIS-associated genes identified from the Trp53-SBmut and SBmut tumor cohorts are mutated below significance in both cohorts.

(a–c) Heat maps depicting the percentage of tumors in the Trp53-SBmut and SBmut cohorts that harbor T2/Onc insertions for the CIS-associated genes identified in only Trp53-SBmut (a) or SBmut (b) tumors or in both Trp53-SBmut and SBmut tumors (c).

Supplementary Figure 4 A subset of CIS-associated genes are predictive of outcome in canine osteosarcoma.

(a) Unsupervised hierarchical clustering of all CIS genes with appreciable expression variation (n = 48 genes) resulting in the clustering of afflicted dogs into two groups with significantly different survival times. Gene color denotes SB prediction as an oncogene (red) or TSG (blue). (b) Kaplan-Meier survival curve of canine osteosarcoma using the 48 CIS-associated genes with appreciable expression variation. Kaplan-Meier survival curve of dogs for CIS-associated genes whose expression significantly correlates with outcome. (c) CIS-associated genes were evaluated against survival in a set of 27 canine osteosarcoma cell lines established from patients with known outcome (overall survival time). Gene color denotes SB prediction as an oncogene (red) or TSG (blue). Impact on survival was analyzed by median-centered (high, low) expression. Log-rank Mantel-Cox P values of <0.05 were considered significant.

Supplementary Figure 5 NF1 loss transforms iOB cells.

(a) Diagram of the experimental procedure used to knock out NF1 with transcription activator-like effector nucleases (TALENs) in immortalized osteoblast (iOB) cells. (b) Results of a surveyor assay performed on DNA extracted from iOB cells 5 d after transfection with TALENs targeting NF1 or HPRT. (c) Average number of colonies formed in soft agar by iOB cells treated with NF1 or HPRT TALENs. Data are the means ± SE of five independent experiments; ***P < 0.0001, Student’s t test. Error bars, s.d.

Supplementary Figure 6 Axon guidance genes are misexpressed in human osteosarcoma.

Relative mRNA levels of CIS genes involved in axon guidance in normal human osteoblast (OB) samples and human osteosarcoma tumors analyzed by RNA sequencing (n = 12 human osteosarcoma and 3 normal osteoblast samples). *P < 0.05, **P < 0.001, ***P < 0.0001, Student’s t test. Error bars, s.d.

Supplementary Figure 7 Immunoblot analysis of proteins involved in the SEMA4D and SEMA6D signaling pathways in human osteosarcoma cell lines and shRNA knockdown validation.

(a) Immunoblot analysis for the indicated proteins in lysates from HOS, MG63, U2OS and SaOS2 cells overexpressing luciferase control, SEMA4D or SEMA6D cDNA. (b) RT-PCR analysis of SEMA4D and SEMA6D transcripts in shRNA-expressing HOS cells normalized to Actb levels. Error bars, s.d.

Supplementary Figure 8 Hierarchical clustering analysis of T2/Onc insertion in animals that developed metastatic osteosarcoma.

(a) Group 1 animals in which primary tumors represent the most ancestral state in the phylogenic tree owing to the metastases sharing few insertions with the primary tumor. (b) Group 2 animals in which the primary tumor had the greatest separation from the ancestral state and therefore shared many insertions with the metastases. (c) Group 3 animals in which the primary tumor did not correspond to the most recent common ancestor and did not share as many insertion sites with the metastases as seen in group 2. (d) Animals containing multiple tumors that developed independent sets of metastases that were categorized into more than one of the three groups.

Supplementary Figure 9 Parsimony analysis of T2/Onc insertions in animals that developed metastatic osteosarcoma.

(a) Group 1 animals in which primary tumors corresponded to the most ancestral state in the phylogenic tree owing to the metastases sharing few insertions with the primary tumor. (b) Group 2 animals in which the primary tumor had the greatest separation from the ancestral state and therefore shared many insertions with the metastases. (c) Group 3 animals in which the primary tumor did not correspond to the most recent common ancestor and did not share as many insertion sites with the metastases as seen in group 2. (d) Animals containing multiple tumors that developed independent sets of metastases that were categorized into more than one of the three groups.

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Moriarity, B., Otto, G., Rahrmann, E. et al. A Sleeping Beauty forward genetic screen identifies new genes and pathways driving osteosarcoma development and metastasis. Nat Genet 47, 615–624 (2015). https://doi.org/10.1038/ng.3293

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