Patient Derived Xenografts for Genome-Driven Therapy of Osteosarcoma
Abstract
:1. Introduction
2. Establishment of OS PDX Models
2.1. Ectopic vs. Orthotopic Models
2.2. Animal Models
2.3. OS PDX Validation
3. OS PDX-Derived Cell Cultures and Cell Lines
4. OS PDX Models of Tumor Progression and Metastasis
4.1. OS PDX and Metastasis
4.2. Genetically-Engineered Models of OS Metastasis
4.3. Large Dog OS and Metastatic Disease
5. OS PDX in International PDX Platforms
6. Innovative Therapies and Genome-Driven Approaches Evaluated in OS PDX
7. Mouse PDX Clinical Trials and Co-Clinical Trials
8. Critical Issues and Perspectives
- OS is a rare, highly malignant tumor with a high level of inter- and intra-tumor heterogeneity. Rarity and complexity severely hampered the development of innovative treatments, and very few targeted agents have achieved clinical endpoints for OS.
- OS lack pharmacologically tractable DNA alterations. Thus, the application of precision medicine requires a deeper understanding of cancer biology. There is a need to explore oncogenic mechanisms beyond the identification of genomic driver aberrations and to incorporate new methodologies, such as transcriptional analysis and the development of suitable experimental models.
- PDX models are an important tool for the expansion of patient-derived biopsies. This is highly relevant for rare tumors that are frequently diagnosed by needle-biopsy, such as OS. However, while they closely resemble the original tumor specimen at the morphological and molecular level, they might be overly expensive and cumbersome for many laboratories. In addition, very few laboratories may have direct access to patient material in real-time. Multicenter collaborative networks are highly recommended to increase the number of OS models and to analyze data following standardized procedures.
- PDXs may be unsuitable for large high-throughput drug testing, whereas PDX-derived cell cultures can be easily established and faithfully represent the original tumor. They are a valuable platform for drug response profiling. PDX-derived cell lines are readily exchangeable among laboratories, which may help the harmonization of data, even for rare tumors.
- Therapeutic failure for patients with OS still involves the development of metastasis to the lungs, despite effective and complete control of the primary tumor. The complexity of the metastatic cascade is difficult to be modeled in vitro. 3D cultures could represent an excellent option to mimic the interactions of tumor cells within the tumor microenvironment. 3D printing is being used to create bone scaffolds that can incorporate a variety of cells, growth factors, and drugs (for a review, see [104]). Even if some technical issues are to be solved and extensive optimization is still needed, these scaffolds have the potential to accelerate the transition from the laboratory to patient care. Thus, their development is highly recommended.
9. Concluding Remarks
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Mirabello, L.; Troisi, R.J.; Savage, S.A. International osteosarcoma incidence patterns in children and adolescents, middle ages and elderly persons. Int. J. Cancer 2009, 125, 229–234. [Google Scholar] [CrossRef] [Green Version]
- Ottaviani, G.; Jaffe, N. The Epidemiology of Osteosarcoma. In Cancer Treatment and Research; Kluwer Academic Publishers: Alphen aan den Rijn, The Netherlands, 2009; Volume 152, pp. 3–13. ISBN 9781441902832. [Google Scholar]
- Picci, P.; Manfrini, M.; Donati, D.M.; Gambarotti, M.; Righi, A.; Vanel, D.; Dei Tos, A.P. (Eds.) Diagnosis of Musculoskeletal Tumors and Tumor-Like Conditions; Springer: Cham, Switzerland, 2020; pp. 185–212. [Google Scholar]
- Marina, N.M.; Smeland, S.; Bielack, S.S.; Bernstein, M.; Jovic, G.; Krailo, M.D.; Hook, J.M.; Arndt, C.; van den Berg, H.; Brennan, B.; et al. Comparison of MAPIE versus MAP in patients with a poor response to preoperative chemotherapy for newly diagnosed high-grade osteosarcoma (EURAMOS-1): An open-label, international, randomised controlled trial. Lancet Oncol. 2016, 17, 1396–1408. [Google Scholar] [CrossRef] [Green Version]
- Stiller, C.; Craft, A.; Corazziari, I. Survival of children with bone sarcoma in Europe since 1978. Eur. J. Cancer 2001, 37, 760–766. [Google Scholar] [CrossRef]
- Kager, L.; Tamamyan, G.; Bielack, S. Novel insights and therapeutic interventions for pediatric osteosarcoma. Futur. Oncol. 2017, 13, 357–368. [Google Scholar] [CrossRef] [PubMed]
- Lilienthal, I.; Herold, N. Targeting Molecular Mechanisms Underlying Treatment Efficacy and Resistance in Osteosarcoma: A Review of Current and Future Strategies. Int. J. Mol. Sci. 2020, 21, 6885. [Google Scholar] [CrossRef] [PubMed]
- Cortés-Ciriano, I.; Lee, J.J.K.; Xi, R.; Jain, D.; Jung, Y.L.; Yang, L.; Gordenin, D.; Klimczak, L.J.; Zhang, C.Z.; Pellman, D.S.; et al. Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing. Nat. Genet. 2020, 52, 331–341. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Stephens, P.J.; Greenman, C.D.; Fu, B.; Yang, F.; Bignell, G.R.; Mudie, L.J.; Pleasance, E.D.; Lau, K.W.; Beare, D.; Stebbings, L.A.; et al. Massive genomic rearrangement acquired in a single catastrophic event during cancer development. Cell 2011, 144, 27–40. [Google Scholar] [CrossRef] [PubMed]
- Ly, P.; Cleveland, D.W. Rebuilding Chromosomes After Catastrophe: Emerging Mechanisms of Chromothripsis. Trends Cell Biol. 2017, 27, 917–930. [Google Scholar] [CrossRef]
- Behjati, S.; Tarpey, P.S.; Haase, K.; Ye, H.; Young, M.D.; Alexandrov, L.B.; Farndon, S.J.; Collord, G.; Wedge, D.C.; Martincorena, I.; et al. Recurrent mutation of IGF signalling genes and distinct patterns of genomic rearrangement in osteosarcoma. Nat. Commun. 2017, 8. [Google Scholar] [CrossRef]
- Nanni, P.; Landuzzi, L.; Manara, M.C.; Righi, A.; Nicoletti, G.; Cristalli, C.; Pasello, M.; Parra, A.; Carrabotta, M.; Ferracin, M.; et al. Bone sarcoma patient-derived xenografts are faithful and stable preclinical models for molecular and therapeutic investigations. Sci. Rep. 2019, 9. [Google Scholar] [CrossRef]
- Sayles, L.C.; Breese, M.R.; Koehne, A.L.; Leung, S.G.; Lee, A.G.; Liu, H.Y.; Spillinger, A.; Shah, A.T.; Tanasa, B.; Straessler, K.; et al. Genome-informed targeted therapy for osteosarcoma. Cancer Discov. 2019, 9, 46–63. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Loh, A.H.P.; Stewart, E.; Bradley, C.L.; Chen, X.; Daryani, V.; Stewart, C.F.; Calabrese, C.; Funk, A.; Miller, G.; Karlstrom, A.; et al. Combinatorial screening using orthotopic patient derived xenograft-expanded early phase cultures of osteosarcoma identify novel therapeutic drug combinations. Cancer Lett. 2019, 442, 262–270. [Google Scholar] [CrossRef] [PubMed]
- Izumchenko, E.; Paz, K.; Ciznadija, D.; Sloma, I.; Katz, A.; Vasquez-Dunddel, D.; Ben-Zvi, I.; Stebbing, J.; McGuire, W.; Harris, W.; et al. Patient-derived xenografts effectively capture responses to oncology therapy in a heterogeneous cohort of patients with solid tumors. Ann. Oncol. 2017, 28, 2595–2605. [Google Scholar] [CrossRef]
- Mattar, M.; McCarthy, C.R.; Kulick, A.R.; Qeriqi, B.; Guzman, S.; de Stanchina, E. Establishing and maintaining an extensive library of patient-derived xenograft models. Front. Oncol. 2018, 8. [Google Scholar] [CrossRef]
- Bruheim, S.; Bruland, O.S.; Breistol, K.; Maelandsmo, G.M.; Fodstad, Ø. Human osteosarcoma xenografts and their sensitivity to chemotherapy. Pathol. Oncol. Res. 2004, 10, 133–141. [Google Scholar] [CrossRef]
- Stewart, E.; Federico, S.M.; Chen, X.; Shelat, A.A.; Bradley, C.; Gordon, B.; Karlstrom, A.; Twarog, N.R.; Clay, M.R.; Bahrami, A.; et al. Orthotopic patient-derived xenografts of paediatric solid tumours. Nature 2017, 549, 96–100. [Google Scholar] [CrossRef]
- Wang, Y.; Wang, J.X.; Xue, H.; Lin, D.; Dong, X.; Gout, P.W.; Gao, X.; Pang, J. Subrenal capsule grafting technology in human cancer modeling and translational cancer research. Differentiation 2016, 91, 15–19. [Google Scholar] [CrossRef] [PubMed]
- Surdez, D.; Landuzzi, L.; Scotlandi, K.; Manara, M.C. Ewing Sarcoma PDX Models. In Methods in Molecular Biology; Humana Press Inc.: New York, NY, USA; Springer: Heidelberg, Germany, 2021; Volume 2226, pp. 223–242. [Google Scholar]
- Crnalic, S.; Håkansson, I.; Boquist, L.; Löfvenberg, R.; Broström, L.Å. A novel spontaneous metastasis model of human osteosarcoma developed using orthotopic transplantation of intact tumor tissue into tibia of nude mice. Clin. Exp. Metastasis 1997, 15, 164–172. [Google Scholar] [CrossRef]
- Goldstein, S.D.; Hayashi, M.; Albert, C.M.; Jackson, K.W.; Loeb, D.M. An orthotopic xenograft model with survival hindlimb amputation allows investigation of the effect of tumor microenvironment on sarcoma metastasis. Clin. Exp. Metastasis 2015, 32, 703–715. [Google Scholar] [CrossRef]
- Khanna, C.; Fan, T.M.; Gorlick, R.; Helman, L.J.; Kleinerman, E.S.; Adamson, P.C.; Houghton, P.J.; Tap, W.D.; Welch, D.R.; Steeg, P.S.; et al. Toward a Drug Development Path That Targets Metastatic Progression in Osteosarcoma. Clin. Cancer Res. 2014, 20, 4200–4209. [Google Scholar] [CrossRef] [Green Version]
- Luu, H.H.; Kang, Q.; Jong, K.P.; Si, W.; Luo, Q.; Jiang, W.; Yin, H.; Montag, A.G.; Simon, M.A.; Peabody, T.D.; et al. An orthotopic model of human osteosarcoma growth and spontaneous pulmonary metastasis. Clin. Exp. Metastasis 2005, 22, 319–329. [Google Scholar] [CrossRef] [PubMed]
- Blattmann, C.; Thiemann, M.; Stenzinger, A.; Roth, E.K.; Dittmar, A.; Witt, H.; Lehner, B.; Renker, E.; Jugold, M.; Eichwald, V.; et al. Establishment of a patient-derived orthotopic osteosarcoma mouse model. J. Transl. Med. 2015, 13. [Google Scholar] [CrossRef] [Green Version]
- Maloney, C.; Edelman, M.C.; Kallis, M.P.; Soffer, S.Z.; Symons, M.; Steinberg, B.M. Intratibial injection causes direct pulmonary seeding of osteosarcoma cells and is not a spontaneous model of metastasis: A mouse osteosarcoma model. Clin. Orthop. Relat. Res. 2018, 476, 1514–1522. [Google Scholar] [CrossRef] [PubMed]
- Shultz, L.D.; Lyons, B.L.; Burzenski, L.M.; Gott, B.; Chen, X.; Chaleff, S.; Kotb, M.; Gillies, S.D.; King, M.; Mangada, J.; et al. Human Lymphoid and Myeloid Cell Development in NOD/LtSz- scid IL2R γ null Mice Engrafted with Mobilized Human Hemopoietic Stem Cells. J. Immunol. 2005, 174, 6477–6489. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Okada, S.; Vaeteewoottacharn, K.; Kariya, R. Application of Highly Immunocompromised Mice for the Establishment of Patient-Derived Xenograft (PDX) Models. Cells 2019, 8, 889. [Google Scholar] [CrossRef] [Green Version]
- Zarzosa, P.; Navarro, N.; Giralt, I.; Molist, C.; Almazán-Moga, A.; Vidal, I.; Soriano, A.; Segura, M.F.; Hladun, R.; Villanueva, A.; et al. Patient-derived xenografts for childhood solid tumors: A valuable tool to test new drugs and personalize treatments. Clin. Transl. Oncol. 2017, 19, 44–50. [Google Scholar] [CrossRef] [PubMed]
- Lu, W.; Chao, T.; Ruiqi, C.; Juan, S.; Zhihong, L. Patient-derived xenograft models in musculoskeletal malignancies. J. Transl. Med. 2018, 16, 107. [Google Scholar] [CrossRef]
- Hidalgo, M.; Amant, F.; Biankin, A.V.; Budinská, E.; Byrne, A.T.; Caldas, C.; Clarke, R.B.; de Jong, S.; Jonkers, J.; Mælandsmo, G.M.; et al. Patient-derived Xenograft models: An emerging platform for translational cancer research. Cancer Discov. 2014, 4, 998–1013. [Google Scholar] [CrossRef] [Green Version]
- Aparicio, S.; Hidalgo, M.; Kung, A.L. Examining the utility of patient-derived xenograft mouse models. Nat. Rev. Cancer 2015, 15, 311–316. [Google Scholar] [CrossRef]
- Byrne, A.T.; Alférez, D.G.; Amant, F.; Annibali, D.; Arribas, J.; Biankin, A.V.; Bruna, A.; Budinská, E.; Caldas, C.; Chang, D.K.; et al. Interrogating open issues in cancer precision medicine with patient-derived xenografts. Nat. Rev. Cancer 2017, 17, 254–268. [Google Scholar] [CrossRef]
- Mosmann, T.R.; Yokota, T.; Kastelein, R.; Zurawski, S.M.; Arai, N.; Takebe, Y. Species-specificity of T cell stimulating activities of IL 2 and BSF-1 (IL 4): Comparison of normal and recombinant, mouse and human IL 2 and BSF-1 (IL 4). J. Immunol. 1987, 138, 1813–1816. [Google Scholar] [PubMed]
- Collins, M.K.L. Species specificity of interleukin 2 binding to individual receptor components. Eur. J. Immunol. 1989, 19, 1517–1520. [Google Scholar] [CrossRef]
- Eisenman, J.; Ahdieh, M.; Beers, C.; Brasel, K.; Kennedy, M.K.; Le, T.; Bonnert, T.P.; Paxton, R.J.; Park, L.S. Interleukin-15 interactions with interleukin-15 receptor complexes: Characterization and species specificity. Cytokine 2002, 20, 121–129. [Google Scholar] [CrossRef]
- Stripecke, R.; Münz, C.; Schuringa, J.J.; Bissig, K.; Soper, B.; Meeham, T.; Yao, L.; Di Santo, J.P.; Brehm, M.; Rodriguez, E.; et al. Innovations, challenges, and minimal information for standardization of humanized mice. EMBO Mol. Med. 2020, 12. [Google Scholar] [CrossRef]
- Rao, S.R.; Somarelli, J.A.; Altunel, E.; Selmic, L.E.; Byrum, M.; Sheth, M.U.; Cheng, S.; Ware, K.E.; Kim, S.Y.; Prinz, J.A.; et al. From the Clinic to the Bench and Back Again in One Dog Year: How a Cross-Species Pipeline to Identify New Treatments for Sarcoma Illuminates the Path Forward in Precision Medicine. Front. Oncol. 2020, 10. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Shao, Y.W.; Wood, G.A.; Lu, J.; Tang, Q.L.; Liu, J.; Molyneux, S.; Chen, Y.; Fang, H.; Adissu, H.; McKee, T.; et al. Cross-species genomics identifies DLG2 as a tumor suppressor in osteosarcoma. Oncogene 2019, 38, 291–298. [Google Scholar] [CrossRef] [Green Version]
- Paoloni, M.; Davis, S.; Lana, S.; Withrow, S.; Sangiorgi, L.; Picci, P.; Hewitt, S.; Triche, T.; Meltzer, P.; Khanna, C. Canine tumor cross-species genomics uncovers targets linked to osteosarcoma progression. BMC Genom. 2009, 10, 625. [Google Scholar] [CrossRef] [Green Version]
- Roy, J.; Wycislo, K.L.; Pondenis, H.; Fan, T.M.; Das, A. Comparative proteomic investigation of metastatic and non-metastatic osteosarcoma cells of human and canine origin. PLoS ONE 2017, 12, e0183930. [Google Scholar] [CrossRef]
- Al-Khan, A.A.; Gunn, H.J.; Day, M.J.; Tayebi, M.; Ryan, S.D.; Kuntz, C.A.; Saad, E.S.; Richardson, S.J.; Danks, J.A. Immunohistochemical Validation of Spontaneously Arising Canine Osteosarcoma as a Model for Human Osteosarcoma. J. Comp. Pathol. 2017, 157, 256–265. [Google Scholar] [CrossRef] [PubMed]
- Mason, N.J.; Gnanandarajah, J.S.; Engiles, J.B.; Gray, F.; Laughlin, D.; Gaurnier-Hausser, A.; Wallecha, A.; Huebner, M.; Paterson, Y. Immunotherapy with a HER2-Targeting listeria induces HER2-Specific immunity and demonstrates potential therapeutic effects in a phase I trial in canine osteosarcoma. Clin. Cancer Res. 2016, 22, 4380–4390. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Naik, S.; Galyon, G.D.; Jenks, N.J.; Steele, M.B.; Miller, A.C.; Allstadt, S.D.; Suksanpaisan, L.; Peng, K.W.; Federspiel, M.J.; Russell, S.J.; et al. Comparative oncology evaluation of intravenous recombinant oncolytic vesicular stomatitis virus therapy in spontaneous canine cancer. Mol. Cancer Ther. 2018, 17, 316–326. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Simpson, S.; Dunning, M.D.; de Brot, S.; Grau-Roma, L.; Mongan, N.P.; Rutland, C.S. Comparative review of human and canine osteosarcoma: Morphology, epidemiology, prognosis, treatment and genetics. Acta Vet. Scand. 2017, 59, 71. [Google Scholar] [CrossRef] [PubMed]
- Schiffman, J.D.; Breen, M. Comparative oncology: What dogs and other species can teach us about humans with cancer. Philos. Trans. R. Soc. B Biol. Sci. 2015, 370, 20140231. [Google Scholar] [CrossRef]
- Ishii, S.; Yamawaki, S.; Sasaki, T.; Usui, M.; Ubayama, Y.; Minaimi, A.; Yagi, T.; Isu, K.; Kobayashi, M. Analysis of osteoid-forming activity of human osteosarcoma implanted into nude mice. Int. Orthop. 1983, 6, 215–223. [Google Scholar] [CrossRef] [PubMed]
- Bauer, H.C.F.; Brosjö, O.; Broström, L.-Å.; Nilsson, O.S.; Reinholt, F.P.; Tribukait, B. Growth and ploidy of human osteosarcoma xenografts in serial passage in nude mice. Eur. J. Cancer Clin. Oncol. 1986, 22, 821–830. [Google Scholar] [CrossRef]
- Meyer, W.H.; Houghton, J.A.; Houghton, P.J.; Webber, B.L.; Douglass, E.C.; Look, A.T. Development and Characterization of Pediatric Osteosarcoma Xenografts. Cancer Res. 1990, 50, 2781–2785. [Google Scholar]
- Fujisaki, T.; Wada, T.; Takahashi, M.; Yamawaki, S.; Ishii, S. In vitro chemosensitivity assay for human osteosarcoma using tumor xenografts. Clin. Orthop. Relat. Res. 1995, 279–285. [Google Scholar]
- Monsma, D.J.; Monks, N.R.; Cherba, D.M.; Dylewski, D.; Eugster, E.; Jahn, H.; Srikanth, S.; Scott, S.B.; Richardson, P.J.; Everts, R.E.; et al. Genomic characterization of explant tumorgraft models derived from fresh patient tumor tissue. J. Transl. Med. 2012, 10. [Google Scholar] [CrossRef] [Green Version]
- Kresse, S.H.; Rydbeck, H.; Skårn, M.; Namløs, H.M.; Barragan-Polania, A.H.; Cleton-Jansen, A.M.; Serra, M.; Liestøl, K.; Hogendoorn, P.C.W.; Hovig, E.; et al. Integrative Analysis Reveals Relationships of Genetic and Epigenetic Alterations in Osteosarcoma. PLoS ONE 2012, 7, e48262. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Pandya, P.H.; Cheng, L.; Saadatzadeh, M.R.; Bijangi-Vishehsaraei, K.; Tang, S.; Sinn, A.L.; Trowbridge, M.A.; Coy, K.L.; Bailey, B.J.; Young, C.N.; et al. Systems biology approach identifies prognostic signatures of poor overall survival and guides the prioritization of novel bet-chk1 combination therapy for osteosarcoma. Cancers 2020, 12, 2426. [Google Scholar] [CrossRef]
- Conner, J.R.; Hornick, J.L. SATB2 is a novel marker of osteoblastic differentiation in bone and soft tissue tumours. Histopathology 2013, 63, 36–49. [Google Scholar] [CrossRef] [PubMed]
- Ben-David, U.; Ha, G.; Tseng, Y.-Y.; Greenwald, N.F.; Oh, C.; Shih, J.; McFarland, J.M.; Wong, B.; Boehm, J.S.; Beroukhim, R.; et al. Patient-derived xenografts undergo mouse-specific tumor evolution. Nat. Genet. 2017, 49, 1567–1575. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Guilhamon, P.; Butcher, L.M.; Presneau, N.; Wilson, G.A.; Feber, A.; Paul, D.S.; Schütte, M.; Haybaeck, J.; Keilholz, U.; Hoffman, J.; et al. Assessment of patient-derived tumour xenografts (PDXs) as a discovery tool for cancer epigenomics. Genome Med. 2014, 6. [Google Scholar] [CrossRef] [Green Version]
- Vaeteewoottacharn, K.; Pairojkul, C.; Kariya, R.; Muisuk, K.; Imtawil, K.; Chamgramol, Y.; Bhudhisawasdi, V.; Khuntikeo, N.; Pugkhem, A.; Saeseow, O.-T.; et al. Establishment of Highly Transplantable Cholangiocarcinoma Cell Lines from a Patient-Derived Xenograft Mouse Model. Cells 2019, 8, 496. [Google Scholar] [CrossRef] [Green Version]
- Oyama, R.; Takahashi, M.; Yoshida, A.; Sakumoto, M.; Takai, Y.; Kito, F.; Shiozawa, K.; Qiao, Z.; Arai, Y.; Shibata, T.; et al. Generation of novel patient-derived CIC-DUX4 sarcoma xenografts and cell lines. Sci. Rep. 2017, 7. [Google Scholar] [CrossRef] [Green Version]
- Borodovsky, A.; McQuiston, T.J.; Stetson, D.; Ahmed, A.; Whitston, D.; Zhang, J.; Grondine, M.; Lawson, D.; Challberg, S.S.; Zinda, M.; et al. Generation of stable PDX derived cell lines using conditional reprogramming. Mol. Cancer 2017, 16, 177. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Gillet, J.P.; Calcagno, A.M.; Varma, S.; Marino, M.; Green, L.J.; Vora, M.I.; Patel, C.; Orina, J.N.; Eliseeva, T.A.; Singal, V.; et al. Redefining the relevance of established cancer cell lines to the study of mechanisms of clinical anti-cancer drug resistance. Proc. Natl. Acad. Sci. USA 2011, 108, 18708–18713. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hausser, H.J.; Brenner, R.E. Phenotypic instability of Saos-2 cells in long-term culture. Biochem. Biophys. Res. Commun. 2005, 333, 216–222. [Google Scholar] [CrossRef]
- Willyard, C. The mice with human tumours: Growing pains for a popular cancer model. Nature 2018, 560, 156–157. [Google Scholar] [CrossRef]
- VanCleave, A.; Palmer, M.; Fang, F.; Torres, H.; Rodezno, T.; Li, Q.; Fuglsby, K.; Evans, C.; Afeworki, Y.; Ross, A.; et al. Development and characterization of the novel human osteosarcoma cell line COS-33 with sustained activation of the mTOR pathway. Oncotarget 2020, 11, 2597–2610. [Google Scholar] [CrossRef] [PubMed]
- Alemany-Ribes, M.; Semino, C.E. Bioengineering 3D environments for cancer models. Adv. Drug Deliv. Rev. 2014, 79–80, 40–49. [Google Scholar] [CrossRef] [PubMed]
- Kondo, J.; Inoue, M. Application of Cancer Organoid Model for Drug Screening and Personalized Therapy. Cells 2019, 8, 470. [Google Scholar] [CrossRef] [Green Version]
- Drost, J.; Clevers, H. Organoids in cancer research. Nat. Rev. Cancer 2018, 18, 407–418. [Google Scholar] [CrossRef] [PubMed]
- Nozaki, K.; Mochizuki, W.; Matsumoto, Y.; Matsumoto, T.; Fukuda, M.; Mizutani, T.; Watanabe, M.; Nakamura, T. Co-culture with intestinal epithelial organoids allows efficient expansion and motility analysis of intraepithelial lymphocytes. J. Gastroenterol. 2016, 51, 206–213. [Google Scholar] [CrossRef] [Green Version]
- He, A.; Huang, Y.; Cheng, W.; Zhang, D.; He, W.; Bai, Y.; Gu, C.; Ma, Z.; He, Z.; Si, G.; et al. Organoid culture system for patient-derived lung metastatic osteosarcoma. Med. Oncol. 2020, 37. [Google Scholar] [CrossRef]
- Wu, T.; Dai, Y. Tumor microenvironment and therapeutic response. Cancer Lett. 2017, 387, 61–68. [Google Scholar] [CrossRef]
- Corre, I.; Verrecchia, F.; Crenn, V.; Redini, F.; Trichet, V. The Osteosarcoma Microenvironment: A Complex but Targetable Ecosystem. Cells 2020, 9, 976. [Google Scholar] [CrossRef] [Green Version]
- Aanstoos, M.E.; Regan, D.P.; Rose, R.J.; Chubb, L.S.; Ehrhart, N.P. Do Mesenchymal Stromal Cells Influence Microscopic Residual or Metastatic Osteosarcoma in a Murine Model? Clin. Orthop. Relat. Res. 2016, 474, 707–715. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Bishop, M.W.; Janeway, K.A.; Gorlick, R. Future directions in the treatment of osteosarcoma. Curr. Opin. Pediatr. 2016, 28, 26–33. [Google Scholar] [CrossRef] [Green Version]
- Fan, T.M.; Roberts, R.D.; Lizardo, M.M. Understanding and Modeling Metastasis Biology to Improve Therapeutic Strategies for Combating Osteosarcoma Progression. Front. Oncol. 2020, 10. [Google Scholar] [CrossRef] [Green Version]
- Ahmed, G.; Zamzam, M.; Kamel, A.; Ahmed, S.; Salama, A.; Zaki, I.; Kamal, N.; Elshafiey, M. Effect of timing of pulmonary metastasis occurrence on the outcome of metastasectomy in osteosarcoma patients. J. Pediatr. Surg. 2019, 54, 775–779. [Google Scholar] [CrossRef] [PubMed]
- Goldstein, S.D.; Trucco, M.; Guzman, W.B.; Hayashi, M.; Loeb, D.M. A monoclonal antibody against the Wnt signaling inhibitor dickkopf-1 inhibits osteosarcoma metastasis in a preclinical model. Oncotarget 2016, 7, 21114–21123. [Google Scholar] [CrossRef] [Green Version]
- Adams, J.; Cory, S. Transgenic models of tumor development. Science 1991, 254, 1161–1167. [Google Scholar] [CrossRef] [PubMed]
- Guijarro, M.V.; Ghivizzani, S.C.; Gibbs, C.P. Animal Models in Osteosarcoma. Front. Oncol. 2014, 4. [Google Scholar] [CrossRef] [Green Version]
- Moriarity, B.S.; Otto, G.M.; Rahrmann, E.P.; Rathe, S.K.; Wolf, N.K.; Weg, M.T.; Manlove, L.A.; Larue, R.S.; Temiz, N.A.; Molyneux, S.D.; et al. A Sleeping Beauty forward genetic screen identifies new genes and pathways driving osteosarcoma development and metastasis. Nat. Genet. 2015, 47, 615–624. [Google Scholar] [CrossRef]
- Mutsaers, A.J.; Ng, A.J.M.; Baker, E.K.; Russell, M.R.; Chalk, A.M.; Wall, M.; Liddicoat, B.J.J.; Ho, P.W.M.; Slavin, J.L.; Goradia, A.; et al. Modeling distinct osteosarcoma subtypes in vivo using Cre: Lox and lineage-restricted transgenic shRNA. Bone 2013, 55, 166–178. [Google Scholar] [CrossRef] [PubMed]
- Withrow, S.J.; Powers, B.E.; Straw, R.C.; Wilkins, R.M. Comparative aspects of osteosarcoma: Dog versus man. Clin. Orthop. Relat. Res. 1991, 159–168. [Google Scholar] [CrossRef]
- Mueller, F.; Fuchs, B.; Kaser-Hotz, B. Comparative biology of human and canine osteosarcoma. Anticancer Res. 2007, 27, 155–164. [Google Scholar]
- Fenger, J.M.; London, C.A.; Kisseberth, W.C. Canine osteosarcoma: A naturally occurring disease to inform pediatric oncology. ILAR J. 2014, 55, 69–85. [Google Scholar] [CrossRef] [Green Version]
- Canter, R.J.; Grossenbacher, S.K.; Foltz, J.A.; Sturgill, I.R.; Park, J.S.; Luna, J.I.; Kent, M.S.; Culp, W.T.N.; Chen, M.; Modiano, J.F.; et al. Radiotherapy enhances natural killer cell cytotoxicity and localization in pre-clinical canine sarcomas and first-in-dog clinical trial. J. Immunother. Cancer 2017, 5, 98. [Google Scholar] [CrossRef] [Green Version]
- Meehan, T.F.; Conte, N.; Goldstein, T.; Inghirami, G.; Murakami, M.A.; Brabetz, S.; Gu, Z.; Wiser, J.A.; Dunn, P.; Begley, D.A.; et al. PDX-MI: Minimal information for patient-derived tumor xenograft models. Cancer Res. 2017, 77, e62–e66. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Stewart, E.; Federico, S.; Karlstrom, A.; Shelat, A.; Sablauer, A.; Pappo, A.; Dyer, M.A. The Childhood Solid Tumor Network: A new resource for the developmental biology and oncology research communities. Dev. Biol. 2016, 411, 287–293. [Google Scholar] [CrossRef] [Green Version]
- Conte, N.; Mason, J.C.; Halmagyi, C.; Neuhauser, S.; Mosaku, A.; Yordanova, G.; Chatzipli, A.; Begley, D.A.; Krupke, D.M.; Parkinson, H.; et al. PDX Finder: A portal for patient-derived tumor xenograft model discovery. Nucleic Acids Res. 2019, 47, D1073–D1079. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Scotlandi, K.; Hattinger, C.M.; Pellegrini, E.; Gambarotti, M.; Serra, M. Genomics and Therapeutic Vulnerabilities of Primary Bone Tumors. Cells 2020, 9, 968. [Google Scholar] [CrossRef] [Green Version]
- Sampson, V.B.; Gorlick, R.; Kamara, D.; Kolb, E.A. A review of targeted therapies evaluated by the pediatric preclinical testing program for osteosarcoma. Front. Oncol. 2013, 3. [Google Scholar] [CrossRef] [Green Version]
- Manara, M.C.; Valente, S.; Cristalli, C.; Nicoletti, G.; Landuzzi, L.; Zwergel, C.; Mazzone, R.; Stazi, G.; Arimondo, P.B.; Pasello, M.; et al. A quinoline-based DNA methyltransferase inhibitor as a possible adjuvant in osteosarcoma therapy. Mol. Cancer Ther. 2018, 17, 1881–1892. [Google Scholar] [CrossRef] [Green Version]
- McGuire, J.J.; Nerlakanti, N.; Lo, C.H.; Tauro, M.; Utset-Ward, T.J.; Reed, D.R.; Lynch, C.C. Histone deacetylase inhibition prevents the growth of primary and metastatic osteosarcoma. Int. J. Cancer 2020, 147, 2811–2823. [Google Scholar] [CrossRef]
- Kreahling, J.M.; Foroutan, P.; Reed, D.; Martinez, G.; Razabdouski, T.; Bui, M.M.; Raghavan, M.; Letson, D.; Gillies, R.J.; Altiok, S. Wee1 Inhibition by MK-1775 Leads to Tumor Inhibition and Enhances Efficacy of Gemcitabine in Human Sarcomas. PLoS ONE 2013, 8, e57523. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Gao, H.; Korn, J.M.; Ferretti, S.; Monahan, J.E.; Wang, Y.; Singh, M.; Zhang, C.; Schnell, C.; Yang, G.; Zhang, Y.; et al. High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response. Nat. Med. 2015, 21, 1318–1325. [Google Scholar] [CrossRef]
- Suehara, Y.; Alex, D.; Bowman, A.; Middha, S.; Zehir, A.; Chakravarty, D.; Wang, L.; Jour, G.; Nafa, K.; Hayashi, T.; et al. Clinical genomic sequencing of pediatric and adult osteosarcoma reveals distinct molecular subsets with potentially targetable alterations. Clin. Cancer Res. 2019, 25, 6346–6356. [Google Scholar] [CrossRef] [PubMed]
- Gupta, S.; Ito, T.; Alex, D.; Vanderbilt, C.M.; Chang, J.C.; Islamdoust, N.; Zhang, Y.; Nafa, K.; Healey, J.; Ladanyi, M.; et al. RUNX2 (6p21.1) amplification in osteosarcoma. Hum. Pathol. 2019, 94, 23–28. [Google Scholar] [CrossRef]
- Clohessy, J.G.; Pandolfi, P.P. Mouse hospital and co-clinical trial project—from bench to bedside. Nat. Rev. Clin. Oncol. 2015, 12, 491–498. [Google Scholar] [CrossRef]
- Clohessy, J.G.; Pandolfi, P.P. The Mouse Hospital and its integration in ultra-precision approaches to cancer care. Front. Oncol. 2018, 8. [Google Scholar] [CrossRef] [Green Version]
- Zhang, X.; Claerhout, S.; Prat, A.; Dobrolecki, L.E.; Petrovic, I.; Lai, Q.; Landis, M.D.; Wiechmann, L.; Schiff, R.; Giuliano, M.; et al. A renewable tissue resource of phenotypically stable, biologically and ethnically diverse, patient-derived human breast cancer xenograft models. Cancer Res. 2013, 73, 4885–4897. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Stewart, E.L.; Mascaux, C.; Pham, N.A.; Sakashita, S.; Sykes, J.; Kim, L.; Yanagawa, N.; Allo, G.; Ishizawa, K.; Wang, D.; et al. Clinical utility of patient-derived xenografts to determine biomarkers of prognosis and map resistance pathways in EGFR-mutant lung adenocarcinoma. J. Clin. Oncol. 2015, 33, 2472–2480. [Google Scholar] [CrossRef] [PubMed]
- Vargas, R.; Gopal, P.; Kuzmishin, G.B.; DeBernardo, R.; Koyfman, S.A.; Jha, B.K.; Mian, O.Y.; Scott, J.; Adams, D.J.; Peacock, C.D.; et al. Case study: Patient-derived clear cell adenocarcinoma xenograft model longitudinally predicts treatment response. NPJ Precis. Oncol. 2018, 2. [Google Scholar] [CrossRef]
- Guo, S.; Jiang, X.; Mao, B.; Li, Q.X. The design, analysis and application of mouse clinical trials in oncology drug development. BMC Cancer 2019, 19, 718. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Park, H.J.; Bae, J.S.; Kim, K.M.; Moon, Y.J.; Park, S.H.; Ha, S.H.; Hussein, U.K.; Zhang, Z.; Park, H.S.; Park, B.H.; et al. The PARP inhibitor olaparib potentiates the effect of the DNA damaging agent doxorubicin in osteosarcoma. J. Exp. Clin. Cancer Res. 2018, 37. [Google Scholar] [CrossRef]
- Goncalves, T.; Zoumpoulidou, G.; Alvarez-Mendoza, C.; Mancusi, C.; Collopy, L.C.; Strauss, S.J.; Mittnacht, S.; Tomita, K. Selective Elimination of Osteosarcoma Cell Lines with Short Telomeres by Ataxia Telangiectasia and Rad3-Related Inhibitors. ACS Pharmacol. Transl. Sci. 2020, 3, 1253–1264. [Google Scholar] [CrossRef] [PubMed]
- Li, A.; Bergan, R.C. Clinical trial design: Past, present, and future in the context of big data and precision medicine. Cancer 2020, 126, 4838–4846. [Google Scholar] [CrossRef]
- Bose, S.; Vahabzadeh, S.; Bandyopadhyay, A. Bone tissue engineering using 3D printing. Mater. Today 2013, 16, 496–504. [Google Scholar] [CrossRef]
- Rodon, J.; Soria, J.C.; Berger, R.; Miller, W.H.; Rubin, E.; Kugel, A.; Tsimberidou, A.; Saintigny, P.; Ackerstein, A.; Braña, I.; et al. Genomic and transcriptomic profiling expands precision cancer medicine: The WINTHER trial. Nat. Med. 2019, 25, 751–758. [Google Scholar] [CrossRef] [PubMed]
- Mitri, Z.I.; Parmar, S.; Johnson, B.; Kolodzie, A.; Keck, J.M.; Morris, M.; Guimaraes, A.R.; Beckett, B.R.; Borate, U.; Lopez, C.D.; et al. Implementing a comprehensive translational oncology platform: From molecular testing to actionability. J. Transl. Med. 2018, 16. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Studies | Immunodeficient Mouse Model | First Tumor Engraftment Site | Rate of Engraftment (PDX/Implanted Tumors) | PDX Validation and Molecular Annotations | OS PDX-Derived Cell Cultures |
---|---|---|---|---|---|
Ishii 1983 [47] | BALB/c Nude | Sc | 80% (24/30) | Histology | No |
Bauer 1986 [48] | BALB/c Nude | Sc | 6 OS PDX | Histology, ploidy, Ki67 | No |
Meyer 1990 [49] | CBA/CaJ (Thymectomy and irradiation) | Sc | 24% (8/33) | Histology, ploidy, LDH | No |
Fujisaki 1995 [50] | Nude | Sc | 62% (21/34) | NA | PDX-derived short-term cell cultures for in vitro evaluation of drug sensitivity |
Bruheim 2004 [17] | BALB/c Nude | Sc | 20% (11/55) | Histology | No |
Monsma 2012 [51] | Nude | Sc | 100% (3/3) | Histology, Genomic, gene expression | No |
Kresse 2012 [52] | BALB/c Nude | Sc | 9 OS PDX | Genomic | No |
Stewart 2017 [18] | NSG | Orthotopic (intrafemural) in matrigel | 49% (15/31) | Histology, SATB2, Genomic | PDX-derived short-term cell cultures for in vitro evaluation of drug sensitivity |
Sayles 2019 [13] | NSG | Subrenal capsule in matrigel | 50% (15/30) | Histology, Genomic | PDX-derived cell cultures (WGS validated) for in vitro evaluation of drug sensitivity |
Nanni 2019 [12] | NSG, BALB Rag2−/−,Il2rg−/− | Sc (interscapular fat pad) | 36% (22/61) | Histology, SATB2, gene expression | Several Patient and PDX-derived cell cultures |
Loh 2019 [14] | Nude CD1NSG | Sc and then orthotopic (intrafemural) in matrigel | 8 OS PDX | Genomic | PDX-derived short-term cell cultures for in vitro evaluation of drug sensitivity |
Pandya 2020 [53] | NSG | Sc | 1 OS PDX | STR analysis, Genomic | PDX-derived cell culture (WGS validated) for in vitro evaluation of drug sensitivity |
PDX Platforms | Available PDXs | Internet Link |
---|---|---|
Pediatric Preclinical Testing Consortium (PPTC), National Cancer Institute (NCI), USA [29] | PDXs of pediatric tumors | http://www.ncipptc.org * |
PDXNet, National Cancer Institute (NCI), USA | 207 PDX models of 17 different tumor types, including sarcomas | https://www.pdxnetwork.org/ * |
Childhood Solid Tumor Network (CSTN), St. Jude Children’s Research Hospital, USA [85] | 169 PDX models, including 35 OS PDXs | https://www.stjude.org/research/resources-data/childhood-solid-tumor-network.html * |
EurOPDX consortium, many European Universities | 1500 PDXs including sarcomas | https://www.europdx.eu/ * |
ITCC-P4, many European Institutions and companies | 400 PDXs of pediatric solid tumors including OS PDX | https://www.itccp4.eu/ * |
CrownBio | 2500 PDXs including 15 OS PDXs | https://www.crownbio.com/ * |
Champions Oncology | 1000 PDXs, including 150 models of adult and pediatric sarcomas | https://championsoncology.com/ * |
The Jackson Laboratory’s PDX Resource | more than 400 PDX models, including six OS PDXs | https://www.jax.org/ * |
DNA Link | 300 PDX models | http://www.pdx.dnalink.com/index * |
PDXfinder, The Jackson Laboratory and the European Bioinformatics Institute of the European Molecular Biological Laboratory (EMBL-EBI) [86] | 4372 different models, with 84 OS PDXs | http://www.pdxfinder.org * |
Targetable Pathway | Rate of Alteration in OS Patient Cohorts | Targeted Drugs | OS PDX with the Alteration | Responses in Genome-Matched OS PDX (Range of % Tumor Growth Inhibition) |
---|---|---|---|---|
MYC (8q24.21 gain) | CDK inhibitor AT7519 | Two OS PDXs with >12 CN (OS152 and OS186) | 86–97% [13] * | |
8–39% [13,93] | BRD4 inhibitor JQ1 | Two OS PDXs with >12 CN (OS152 and OS186) | No effect on tumor growth in both models [13] * | |
Combination of BETi/OTX-015 and CHK1i/SRA737 | One OS PDX with four CN (TT2-77 PDX) | Around 90% [53] # | ||
CDK4 (12q14.1 gain) | 11–14% [13,93] | Palbociclib (CDK4/6 inhibitor) | Three OS PDXs (OS156, OS128, and OS107) | 61–111% [13] * |
AURKB (17p13.1 gain) | 6–13% [13,93] | AZD1152 | One OS PDX (OS107) | 57% [13] * |
VEGFA (6p12–21 gain) | 22–24% [13,93,94] | Sorafenib | One OS PDX (OS106) | 79% [13] * |
Cyclin E (CCNE1) (19q12 gain) | 8–33% [13,93] | Dinaciclib (SCH 727965) (inhibitor of CDK1,2,5,9) | Three OS PDXs (OS457, OS106, and OS452) | 54–94% [13] * |
PTEN (10q23.21 loss) | 4–56% [13,93] | MK2206 | One OS PDX (OS052, PTEN loss) One OS PDX (OS525, AKT gain) | 61–67% [13] * |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Landuzzi, L.; Manara, M.C.; Lollini, P.-L.; Scotlandi, K. Patient Derived Xenografts for Genome-Driven Therapy of Osteosarcoma. Cells 2021, 10, 416. https://doi.org/10.3390/cells10020416
Landuzzi L, Manara MC, Lollini P-L, Scotlandi K. Patient Derived Xenografts for Genome-Driven Therapy of Osteosarcoma. Cells. 2021; 10(2):416. https://doi.org/10.3390/cells10020416
Chicago/Turabian StyleLanduzzi, Lorena, Maria Cristina Manara, Pier-Luigi Lollini, and Katia Scotlandi. 2021. "Patient Derived Xenografts for Genome-Driven Therapy of Osteosarcoma" Cells 10, no. 2: 416. https://doi.org/10.3390/cells10020416