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  • Review Article
  • Published:

Imaging preclinical tumour models: improving translational power

Key Points

  • Small-animal imaging in cancer research is a dynamic research field, with tremendous progress that has resulted from substantial developments in small-animal imaging techniques, specific imaging probes and advances in innovative animal tumour models.

  • Multimodal small-animal imaging techniques provide complementary and therefore more complete information (as one technique can compensate for the weaker characteristics of others).

  • Molecular imaging probes can be applied for many different purposes in cancer research, including visualization of tumour cell and extracellular matrix characteristics, diagnosis, staging, therapy selection, therapy and monitoring of therapy response.

  • Well-defined model systems and study designs are needed to bridge the gap between oncological in vitro studies and clinical application. Two stages in the translation of in vitro results can be distinguished: the first step comprises translation from the laboratory bench to animal models, the second step involves translation from animal models to the clinic. Research questions related to each stage ask for different models and matching imaging techniques to get the most reliable answers.

  • Increased knowledge of cancer type-specific genes has supported the generation of genetically engineered mouse models that capture both the cell-intrinsic and cell-extrinsic factors that drive organ-specific cancer development and the progression towards metastatic disease.

  • 'Close to patient' models, such as patient-derived xenografts and reconstituted 'humanized' xenografts, as well as patient-derived ex vivo organoid three-dimensional cultures and tissue-slice systems, aim to capture the unique patient-specific tumour microenvironment and to sustain tumour heterogeneity.

  • Careful selection of the most appropriate model system and best (multimodal) imaging modalities, as well as an optimal study design, are crucial decision points that determine the translational impact of the study.

  • Close collaboration of different disciplines, specific training of preclinical and basic researchers, harmonization of protocols and stricter publication guidelines are needed and will help to further improve the translation of results from the small-animal imaging research field into the clinic.

Abstract

Recent developments and improvements of multimodal imaging methods for use in animal research have substantially strengthened the options of in vivo visualization of cancer-related processes over time. Moreover, technological developments in probe synthesis and labelling have resulted in imaging probes with the potential for basic research, as well as for translational and clinical applications. In addition, more sophisticated cancer models are available to address cancer-related research questions. This Review gives an overview of developments in these three fields, with a focus on imaging approaches in animal cancer models and how these can help the translation of new therapies into the clinic.

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Figure 1: Model systems and main imaging techniques for translation from in vitro analysis to clinical implementation.
Figure 2: Overview of various types of currently commercially available in vivo molecular multimodal imaging systems and applications.
Figure 3: Schematic representation of molecular imaging targets in tumour cells and the general structure of imaging probes.
Figure 4: Alternative models for molecular imaging.

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References

  1. Cook, N., Jodrell, D. I. & Tuveson, D. A. Predictive in vivo animal models and translation to clinical trials. Drug Discov. Today 17, 253–260 (2012).

    Article  PubMed  Google Scholar 

  2. Heyer, J., Kwong, L. N., Lowe, S. W. & Chin, L. Non-germline genetically engineered mouse models for translational cancer research. Nature Rev. Cancer 10, 470–480 (2010).

    Article  CAS  Google Scholar 

  3. Langdon, S. P. Animal modeling of cancer pathology and studying tumor response to therapy. Curr. Drug Targets 13, 1535–1547 (2012).

    Article  CAS  PubMed  Google Scholar 

  4. Tentler, J. J. et al. Patient-derived tumour xenografts as models for oncology drug development. Nature Rev. Clin. Oncol. 9, 338–350 (2012). This review highlights the opportunities and limitations of PDX models in cancer drug development and describes concepts regarding predictive biomarker development and future applications.

    Article  CAS  Google Scholar 

  5. Konantz, M. et al. Zebrafish xenografts as a tool for in vivo studies on human cancer. Ann. N. Y. Acad. Sci. 1266, 124–137 (2012).

    Article  PubMed  Google Scholar 

  6. Leong, H. S., Chambers, A. F. & Lewis, J. D. Assessing cancer cell migration and metastatic growth in vivo in the chick embryo using fluorescence intravital imaging. Methods Mol. Biol. 872, 1–14 (2012).

    Article  CAS  PubMed  Google Scholar 

  7. Mimeault, M. & Batra, S. K. Emergence of zebrafish models in oncology for validating novel anticancer drug targets and nanomaterials. Drug Discov. Today 18, 128–140 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Vaira, V. et al. Preclinical model of organotypic culture for pharmacodynamic profiling of human tumors. Proc. Natl Acad. Sci. USA 107, 8352–8356 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  9. van der Kuip, H. et al. Short term culture of breast cancer tissues to study the activity of the anticancer drug taxol in an intact tumor environment. BMC Cancer 6, 86 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Graves, E. E., Weissleder, R. & Ntziachristos, V. Fluorescence molecular imaging of small animal tumor models. Curr. Mol. Med. 4, 419–430 (2004).

    Article  CAS  PubMed  Google Scholar 

  11. Massoud, T. F. & Gambhir, S. S. Molecular imaging in living subjects: seeing fundamental biological processes in a new light. Genes Dev. 17, 545–580 (2003).

    Article  CAS  PubMed  Google Scholar 

  12. Weissleder, R. & Mahmood, U. Molecular imaging. Radiology 219, 316–333 (2001).

    Article  CAS  PubMed  Google Scholar 

  13. Timpson, P., McGhee, E. J. & Anderson, K. I. Imaging molecular dynamics in vivo—from cell biology to animal models. J. Cell Sci. 124, 2877–2890 (2011).

    Article  CAS  PubMed  Google Scholar 

  14. Ntziachristos, V. Going deeper than microscopy: the optical imaging frontier in biology. Nature Methods 7, 603–614 (2010).

    Article  CAS  PubMed  Google Scholar 

  15. Massoud, T. F. & Gambhir, S. S. Integrating noninvasive molecular imaging into molecular medicine: an evolving paradigm. Trends Mol. Med. 13, 183–191 (2007).

    Article  CAS  PubMed  Google Scholar 

  16. Pichler, B. J., Wehrl, H. F. & Judenhofer, M. S. Latest advances in molecular imaging instrumentation. J. Nucl. Med. 49 (Suppl 2), 5S–23S (2008).

    Article  PubMed  Google Scholar 

  17. Condeelis, J. & Weissleder, R. In vivo imaging in cancer. Cold Spring Harb. Perspect. Biol. 2, a003848 (2010). This paper gives an overview of current macroscopic and microscopic imaging technologies aimed at the translation of basic molecular insight at the single cell level to clinical applications.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Cai, W. & Chen, X. Nanoplatforms for targeted molecular imaging in living subjects. Small 3, 1840–1854 (2007).

    Article  CAS  PubMed  Google Scholar 

  19. Goldenberg, D. M., Rossi, E. A., Sharkey, R. M., McBride, W. J. & Chang, C. H. Multifunctional antibodies by the Dock-and-Lock method for improved cancer imaging and therapy by pretargeting. J. Nucl. Med. 49, 158–163 (2008).

    Article  CAS  PubMed  Google Scholar 

  20. Schottelius, M. & Wester, H. J. Molecular imaging targeting peptide receptors. Methods 48, 161–177 (2009).

    Article  CAS  PubMed  Google Scholar 

  21. Zhang, Z. et al. Activatable molecular systems using homologous near-infrared fluorescent probes for monitoring enzyme activities in vitro, in cellulo, and in vivo. Mol. Pharm. 6, 416–427 (2009).

    Article  CAS  PubMed  Google Scholar 

  22. Lofblom, J. et al. Affibody molecules: engineered proteins for therapeutic, diagnostic and biotechnological applications. FEBS Lett. 584, 2670–2680 (2010).

    Article  CAS  PubMed  Google Scholar 

  23. Olafsen, T. & Wu, A. M. Antibody vectors for imaging. Semin. Nucl. Med. 40, 167–181 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Godin, B., Tasciotti, E., Liu, X., Serda, R. E. & Ferrari, M. Multistage nanovectors: from concept to novel imaging contrast agents and therapeutics. Acc. Chem. Res. 44, 979–989 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Jokerst, J. V. & Gambhir, S. S. Molecular imaging with theranostic nanoparticles. Acc. Chem. Res. 44, 1050–1060 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Devoogdt, N. et al. Molecular imaging using nanobodies: a case study. Methods Mol. Biol. 911, 559–567 (2012).

    Article  CAS  PubMed  Google Scholar 

  27. Gulyas, B. & Halldin, C. New PET radiopharmaceuticals beyond FDG for brain tumor imaging. Q. J. Nucl. Med. Mol. Imag. 56, 173–190 (2012).

    CAS  Google Scholar 

  28. Laverman, P., Sosabowski, J. K., Boerman, O. C. & Oyen, W. J. Radiolabelled peptides for oncological diagnosis. Eur. J. Nucl. Med. Mol. Imag. 39 (Suppl. 1), S78–S92 (2012).

    Article  CAS  Google Scholar 

  29. Olafsen, T., Sirk, S. J., Olma, S., Shen, C. K. & Wu, A. M. ImmunoPET using engineered antibody fragments: fluorine-18 labeled diabodies for same-day imaging. Tumour Biol. 33, 669–677 (2012).

    Article  CAS  PubMed  Google Scholar 

  30. Tran Cao, H. S. et al. Tumor-specific fluorescence antibody imaging enables accurate staging laparoscopy in an orthotopic model of pancreatic cancer. Hepatogastroenterology 59, 1994–1999 (2012).

    PubMed  Google Scholar 

  31. Weissleder, R. & Pittet, M. J. Imaging in the era of molecular oncology. Nature 452, 580–589 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Arosio, D., Casagrande, C. & Manzoni, L. Integrin-mediated drug delivery in cancer and cardiovascular diseases with peptide-functionalized nanoparticles. Curr. Med. Chem. 19, 3128–3151 (2012).

    Article  CAS  PubMed  Google Scholar 

  33. Deshpande, N., Needles, A. & Willmann, J. K. Molecular ultrasound imaging: current status and future directions. Clin. Radiol. 65, 567–581 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Lee, J. H. et al. Artificially engineered magnetic nanoparticles for ultra-sensitive molecular imaging. Nature Med. 13, 95–99 (2007).

    Article  CAS  PubMed  Google Scholar 

  35. Kiessling, F., Fokong, S., Koczera, P., Lederle, W. & Lammers, T. Ultrasound microbubbles for molecular diagnosis, therapy, and theranostics. J. Nucl. Med. 53, 345–348 (2012).

    Article  CAS  PubMed  Google Scholar 

  36. Karmakar, A. et al. Raman spectroscopy as a detection and analysis tool for in vitro specific targeting of pancreatic cancer cells by EGF-conjugated, single-walled carbon nanotubes. J. Appl. Toxicol. 32, 365–375 (2012).

    Article  CAS  PubMed  Google Scholar 

  37. Ciarlo, M. et al. Use of the semiconductor nanotechnologies “quantum dots” for in vivo cancer imaging. Recent Pat. Anticancer Drug Discov. 4, 207–215 (2009).

    Article  CAS  PubMed  Google Scholar 

  38. Kiessling, F. Science to practice: the dawn of molecular US imaging for clinical cancer imaging. Radiology 256, 331–333 (2010).

    Article  PubMed  Google Scholar 

  39. Kluza, E. et al. Dual-targeting of αvβ3 and galectin-1 improves the specificity of paramagnetic/fluorescent liposomes to tumor endothelium in vivo. J. Control Release 158, 207–214 (2012).

    Article  CAS  PubMed  Google Scholar 

  40. Cheng, Z., Al Zaki, A., Hui, J. Z., Muzykantov, V. R. & Tsourkas, A. Multifunctional nanoparticles: cost versus benefit of adding targeting and imaging capabilities. Science 338, 903–910 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Martic-Kehl, M. I., Schibli, R. & Schubiger, P. A. Can animal data predict human outcome? Problems and pitfalls of translational animal research. Eur. J. Nucl. Med. Mol. Imaging 39, 1492–1496 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  42. van der Worp, H. B. et al. Can animal models of disease reliably inform human studies? PLoS Med. 7, e1000245 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Begley, C. G. & Ellis, L. M. Drug development: Raise standards for preclinical cancer research. Nature 483, 531–533 (2012).

    Article  CAS  PubMed  Google Scholar 

  44. Perel, P. et al. Comparison of treatment effects between animal experiments and clinical trials: systematic review. BMJ 334, 197 (2007).

    Article  CAS  PubMed  Google Scholar 

  45. Hackam, D. G. & Redelmeier, D. A. Translation of research evidence from animals to humans. JAMA 296, 1731–1732 (2006).

    CAS  PubMed  Google Scholar 

  46. Koba, W., Jelicks, L. A. & Fine, E. J. MicroPET/SPECT/CT imaging of small animal models of disease. Am. J. Pathol. 182, 319–324 (2013).

    Article  CAS  PubMed  Google Scholar 

  47. de Kemp, R. A., Epstein, F. H., Catana, C., Tsui, B. M. & Ritman, E. L. Small-animal molecular imaging methods. J. Nucl. Med. 5, (Suppl 1), 18S–32S (2010).

    Article  CAS  Google Scholar 

  48. Shcherbakova, D. M. & Verkhusha, V. V. Near-infrared fluorescent proteins for multicolor in vivo imaging. Nature Methods 10, 751–754 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. van Dam, G. M. et al. Intraoperative tumor-specific fluorescence imaging in ovarian cancer by folate receptor-α targeting: first in-human results. Nature Med. 17, 1315–1319 (2011).

    Article  CAS  PubMed  Google Scholar 

  50. Brouwer, O. R. et al. Comparing the hybrid fluorescent-radioactive tracer indocyanine green-99mTc-nanocolloid with 99mTc-nanocolloid for sentinel node identification: a validation study using lymphoscintigraphy and SPECT/CT. J. Nucl. Med. 53, 1034–1040 (2012).

    Article  CAS  PubMed  Google Scholar 

  51. Buckle, T., Brouwer, O. R., Valdes Olmos, R. A., van der Poel, H. G. & van Leeuwen, F. W. Relationship between intraprostatic tracer deposits and sentinel lymph node mapping in prostate cancer patients. J. Nucl. Med. 53, 1026–1033 (2012).

    Article  PubMed  Google Scholar 

  52. Buckle, T., Chin, P. T. & van Leeuwen, F. W. (Non-targeted) radioactive/fluorescent nanoparticles and their potential in combined pre- and intraoperative imaging during sentinel lymph node resection. Nanotechnology 21, 482001 (2010).

    Article  CAS  PubMed  Google Scholar 

  53. Filonov, G. S. et al. Bright and stable near-infrared fluorescent protein for in vivo imaging. Nature Biotech. 29, 757–761 (2011).

    Article  CAS  Google Scholar 

  54. Hoffman, R. M. Cellular and subcellular imaging in live mice using fluorescent proteins. Curr. Pharm. Biotechnol. 13, 537–544 (2012).

    Article  CAS  PubMed  Google Scholar 

  55. Kelkar, M. & De, A. Bioluminescence based in vivo screening technologies. Curr. Opin. Pharmacol. 12, 592–600 (2012).

    Article  CAS  PubMed  Google Scholar 

  56. O'Neill, K., Lyons, S. K., Gallagher, W. M., Curran, K. M. & Byrne, A. T. Bioluminescent imaging: a critical tool in pre-clinical oncology research. J. Pathol. 220, 317–327 (2010).

    CAS  PubMed  Google Scholar 

  57. Kim, J. B. et al. Non-invasive detection of a small number of bioluminescent cancer cells in vivo. PLoS ONE 5, e9364 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Hoffman, R. M. The multiple uses of fluorescent proteins to visualize cancer in vivo. Nature Rev. Cancer 5, 796–806 (2005).

    Article  CAS  Google Scholar 

  59. Timpson, P. et al. Spatial regulation of RhoA activity during pancreatic cancer cell invasion driven by mutant p53. Cancer Res. 71, 747–757 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Kiessling, F. & Pichler, B. Small animal imaging. Basics and practical guide., (Springer, 2012).

    Google Scholar 

  61. Rossin, R. et al. In vivo chemistry for pretargeted tumor imaging in live mice. Angew. Chem. Int. Ed. Engl. 49, 3375–3378 (2010).

    Article  CAS  PubMed  Google Scholar 

  62. Elsabahy, M. & Wooley, K. L. Design of polymeric nanoparticles for biomedical delivery applications. Chem. Soc. Rev. 41, 2545–2561 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Petros, R. A. & DeSimone, J. M. Strategies in the design of nanoparticles for therapeutic applications. Nature Rev. Drug Discov. 9, 615–627 (2010).

    Article  CAS  Google Scholar 

  64. Brader, P., Serganova, I. & Blasberg, R. G. Noninvasive molecular imaging using reporter genes. J. Nucl. Med. 54, 167–172 (2013).

    Article  CAS  PubMed  Google Scholar 

  65. Ray, P. & De, A. Reporter gene imaging in therapy and diagnosis. Theranostics 2, 333–334 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  66. Pool, S. E., ten Hagen, T. L., Koelewijn, S., de Jong, M. & Koning, G. A. Multimodality imaging of somatostatin receptor-positive tumors with nuclear and bioluminescence imaging. Mol. Imag. 11, 27–32 (2012).

    Article  CAS  Google Scholar 

  67. Schroeder, R. P., van Weerden, W. M., Bangma, C., Krenning, E. P. & de Jong, M. Peptide receptor imaging of prostate cancer with radiolabelled bombesin analogues. Methods 48, 200–204 (2009).

    Article  CAS  PubMed  Google Scholar 

  68. Stelter, L. et al. An orthotopic model of pancreatic somatostatin receptor (SSTR)-positive tumors allows bimodal imaging studies using 3T MRI and animal PET-based molecular imaging of SSTR expression. Neuroendocrinology 87, 233–242 (2008).

    Article  CAS  PubMed  Google Scholar 

  69. Kang, J. H. & Chung, J. K. Molecular-genetic imaging based on reporter gene expression. J. Nucl. Med. 49, (Suppl 2) 164S–179S (2008).

    Article  CAS  PubMed  Google Scholar 

  70. Chua, S., Gnanasegaran, G. & Cook, G. J. Miscellaneous cancers (lung, thyroid, renal cancer, myeloma, and neuroendocrine tumors): role of SPECT and PET in imaging bone metastases. Semin. Nucl. Med. 39, 416–430 (2009).

    Article  PubMed  Google Scholar 

  71. Vandsburger, M. H., Radoul, M., Cohen, B. & Neeman, M. MRI reporter genes: applications for imaging of cell survival, proliferation, migration and differentiation. NMR Biomed. 24, 872–884 (2012).

    Google Scholar 

  72. Cohen, B. et al. MRI detection of transcriptional regulation of gene expression in transgenic mice. Nature Med. 13, 498–503 (2007).

    Article  CAS  PubMed  Google Scholar 

  73. Gilad, A. A. et al. MRI reporter genes. J. Nucl. Med. 49, 1905–1908 (2008).

    Article  CAS  PubMed  Google Scholar 

  74. Avni, R., Cohen, B. & Neeman, M. Hypoxic stress and cancer: imaging the axis of evil in tumor metastasis. NMR Biomed. 24, 569–581 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  75. Cai, W., Niu, G. & Chen, X. Imaging of integrins as biomarkers for tumor angiogenesis. Curr. Pharm. Des. 14, 2943–2973 (2008).

    Article  CAS  PubMed  Google Scholar 

  76. Roivainen, A., Jalkanen, S. & Nanni, C. Gallium-labelled peptides for imaging of inflammation. Eur. J. Nucl. Med. Mol. Imag. 39 (Suppl. 1), S68–S77 (2012).

    Article  CAS  Google Scholar 

  77. de Jong, M., Breeman, W. A., Kwekkeboom, D. J., Valkema, R. & Krenning, E. P. Tumor imaging and therapy using radiolabeled somatostatin analogues. Acc. Chem. Res. 42, 873–880 (2009). This study is an example of the theranostic concept using radiopeptides.

    Article  CAS  PubMed  Google Scholar 

  78. Ambrosini, V., Fani, M., Fanti, S., Forrer, F. & Maecke, H. R. Radiopeptide imaging and therapy in Europe. J. Nucl. Med. 52, (Suppl 2), 42S–55S (2011).

    Article  CAS  PubMed  Google Scholar 

  79. Kwekkeboom, D. J. et al. Treatment with the radiolabeled somatostatin analog [177 Lu-DOTA 0,Tyr3]octreotate: toxicity, efficacy, and survival. J. Clin. Oncol. 26, 2124–2130 (2008).

    Article  CAS  PubMed  Google Scholar 

  80. Louie, A. Multimodality imaging probes: design and challenges. Chem. Rev. 110, 3146–3195 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Zhang, L. et al. Nanoparticles in medicine: therapeutic applications and developments. Clin. Pharmacol. Ther. 83, 761–769 (2008).

    Article  CAS  PubMed  Google Scholar 

  82. Bednar, B. & Ntziachristos, V. Opto-acoustic imaging of drug discovery biomarkers. Curr. Pharm. Biotechnol. 13, 2117–2127 (2012).

    Article  PubMed  Google Scholar 

  83. Kenny, G. D. et al. Multifunctional receptor-targeted nanocomplexes for magnetic resonance imaging and transfection of tumours. Biomaterials 33, 7241–7250 (2012).

    Article  CAS  PubMed  Google Scholar 

  84. Xu, C. & Zhao, W. Nanoparticle-based monitoring of stem cell therapy. Theranostics 3, 616–617 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  85. Agasti, S. S. et al. Dual imaging and photoactivated nanoprobe for controlled cell tracking. Small 9, 222–227 (2013).

    Article  CAS  PubMed  Google Scholar 

  86. Kircher, M. F., Gambhir, S. S. & Grimm, J. Noninvasive cell-tracking methods. Nature Rev. Clin. Oncol. 8, 677–688 (2011). This paper provides an overview of the basic principles of cell-tracking methods.

    Article  CAS  Google Scholar 

  87. Srinivas, M. et al. Imaging of cellular therapies. Adv. Drug Deliv. Rev. 62, 1080–1093 (2010).

    Article  CAS  PubMed  Google Scholar 

  88. Rygaard, J. & Povlsen, C. O. Heterotransplantation of a human malignant tumour to “Nude” mice. Acta Pathol. Microbiol. Scand. 77, 758–760 (1969).

    Article  CAS  PubMed  Google Scholar 

  89. Sausville, E. A. & Burger, A. M. Contributions of human tumor xenografts to anticancer drug development. Cancer Res. 66, 3351–3354, (discussion 3354) (2006).

    Article  CAS  PubMed  Google Scholar 

  90. Moro, M. et al. Patient-derived xenografts of non small cell lung cancer: resurgence of an old model for investigation of modern concepts of tailored therapy and cancer stem cells. J. Biomed. Biotechnol. http://dx.doi.org/10.1155/2012/568567 (2012).

  91. Ito, R., Takahashi, T., Katano, I. & Ito, M. Current advances in humanized mouse models. Cell. Mol. Immunol. 9, 208–214 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Zhao, H., Nolley, R., Chen, Z. & Peehl, D. M. Tissue slice grafts: an in vivo model of human prostate androgen signaling. Am. J. Pathol. 177, 229–239 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  93. Fidler, I. J. Host and tumour factors in cancer metastasis. Eur. J. Clin. Invest. 20, 481–486 (1990).

    Article  CAS  PubMed  Google Scholar 

  94. Pettaway, C. A. et al. Selection of highly metastatic variants of different human prostatic carcinomas using orthotopic implantation in nude mice. Clin. Cancer Res. 2, 1627–1636 (1996).

    CAS  PubMed  Google Scholar 

  95. Hoffman, R. M. Orthotopic metastatic mouse models for anticancer drug discovery and evaluation: a bridge to the clinic. Invest. New Drugs 17, 343–359 (1999).

    Article  CAS  PubMed  Google Scholar 

  96. Fidler, I. J. Biological heterogeneity of cancer: implication to therapy. Hum. Vaccin Immunother. 8, 1141–1142 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Langley, R. R. & Fidler, I. J. The seed and soil hypothesis revisited—the role of tumor-stroma interactions in metastasis to different organs. Int. J. Cancer 128, 2527–2535 (2011). This review describes the favourable tumour–stroma interactions that underlie the organ-preference pattern of metastasis that is observed in cancer.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Scheer, N. & Roland Wolf, C. Xenobiotic receptor humanized mice and their utility. Drug Metab. Rev. 45, 110–121 (2012).

    Article  CAS  PubMed  Google Scholar 

  99. Friedl, P. & Alexander, S. Cancer invasion and the microenvironment: plasticity and reciprocity. Cell 147, 992–1009 (2011).

    Article  CAS  PubMed  Google Scholar 

  100. Friedl, P., Locker, J., Sahai, E. & Segall, J. E. Classifying collective cancer cell invasion. Nature Cell Biol. 14, 777–783 (2012). This is a proposed framework for studying collective invasion.

    Article  CAS  PubMed  Google Scholar 

  101. Neeman, M., Gilad, A. A., Dafni, H. & Cohen, B. Molecular imaging of angiogenesis. J. Magn. Reson. Imag. 25, 1–12 (2007).

    Article  Google Scholar 

  102. Vandoorne, K., Addadi, Y. & Neeman, M. Visualizing vascular permeability and lymphatic drainage using labeled serum albumin. Angiogenesis 13, 75–85 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Nemati, F. et al. Establishment and characterization of a panel of human uveal melanoma xenografts derived from primary and/or metastatic tumors. Clin. Cancer Res. 16, 2352–2362 (2010).

    Article  CAS  PubMed  Google Scholar 

  104. Press, J. Z. et al. Xenografts of primary human gynecological tumors grown under the renal capsule of NOD/SCID mice show genetic stability during serial transplantation and respond to cytotoxic chemotherapy. Gynecol. Oncol. 110, 256–264 (2008).

    Article  CAS  PubMed  Google Scholar 

  105. van Weerden, W. M. & van Steenbrugge, G. J. Human prostate tumor xenografts as representative models for clinical prostate cancer. Urol. Oncol. 2, 122–125 (1996).

    Article  CAS  PubMed  Google Scholar 

  106. Jin, K. et al. Patient-derived human tumour tissue xenografts in immunodeficient mice: a systematic review. Clin. Transl. Oncol. 12, 473–480 (2010).

    Article  PubMed  Google Scholar 

  107. Fu, X., Guadagni, F. & Hoffman, R. M. A metastatic nude-mouse model of human pancreatic cancer constructed orthotopically with histologically intact patient specimens. Proc. Natl Acad. Sci. USA 89, 5645–5649 (1992).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Fu, X. Y., Besterman, J. M., Monosov, A. & Hoffman, R. M. Models of human metastatic colon cancer in nude mice orthotopically constructed by using histologically intact patient specimens. Proc. Natl Acad. Sci. USA 88, 9345–9349 (1991).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Metildi, C. A. et al. Fluorescently labeled chimeric anti-CEA antibody improves detection and resection of human colon cancer in a patient-derived orthotopic xenograft (PDOX) nude mouse model. J. Surg. Oncol. 109, 451–458 (2014).

    Article  CAS  PubMed  Google Scholar 

  110. Berger, D. P., Winterhalter, B. R. & Fiebig, H. H. in Immunodeficient mice in oncology, Vol. 42 (eds Fiebig, H. H. & Berger, D. P.) 23–46 (Karger, 1992).

    Book  Google Scholar 

  111. Vlietstra, R. J., van Alewijk, D. C., Hermans, K. G., van Steenbrugge, G. J. & Trapman, J. Frequent inactivation of PTEN in prostate cancer cell lines and xenografts. Cancer Res. 58, 2720–2723 (1998).

    CAS  PubMed  Google Scholar 

  112. Kerbel, R. S. Human tumor xenografts as predictive preclinical models for anticancer drug activity in humans: better than commonly perceived-but they can be improved. Cancer Biol. Ther. 2, S134–S139 (2003).

    CAS  PubMed  Google Scholar 

  113. Fichtner, I. et al. Establishment of patient-derived non-small cell lung cancer xenografts as models for the identification of predictive biomarkers. Clin. Cancer Res. 14, 6456–6468 (2008).

    Article  CAS  PubMed  Google Scholar 

  114. Hermans, K. G. et al. TMPRSS2:ERG fusion by translocation or interstitial deletion is highly relevant in androgen-dependent prostate cancer, but is bypassed in late-stage androgen receptor-negative prostate cancer. Cancer Res. 66, 10658–10663 (2006).

    Article  CAS  PubMed  Google Scholar 

  115. DeRose, Y. S. et al. Tumor grafts derived from women with breast cancer authentically reflect tumor pathology, growth, metastasis and disease outcomes. Nature Med. 17, 1514–1520 (2011).

    Article  CAS  PubMed  Google Scholar 

  116. Bankert, R. B. et al. Humanized mouse model of ovarian cancer recapitulates patient solid tumor progression, ascites formation, and metastasis. PLoS ONE 6, e24420 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Garcia, S. & Freitas, A. A. Humanized mice: current states and perspectives. Immunol. Lett. 146, 1–7 (2012). In this review, an update is provided on the newest versions of humanized mice bearing a human immune system. It describes the limitations of these mice and the current approaches to overcome these limitations.

    Article  CAS  PubMed  Google Scholar 

  118. Shultz, L. D., Brehm, M. A., Bavari, S. & Greiner, D. L. Humanized mice as a preclinical tool for infectious disease and biomedical research. Ann. NY Acad. Sci. 1245, 50–54 (2011).

    Article  PubMed  Google Scholar 

  119. Shultz, L. D., Ishikawa, F. & Greiner, D. L. Humanized mice in translational biomedical research. Nature Rev. Immunol. 7, 118–130 (2007).

    Article  CAS  Google Scholar 

  120. Montecinos, V. P., Godoy, A., Hinklin, J., Vethanayagam, R. R. & Smith, G. J. Primary xenografts of human prostate tissue as a model to study angiogenesis induced by reactive stroma. PLoS ONE 7, e29623 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  121. Wang, Y. et al. Development and characterization of efficient xenograft models for benign and malignant human prostate tissue. Prostate 64, 149–159 (2005).

    Article  CAS  PubMed  Google Scholar 

  122. Simpson-Abelson, M. R. et al. Long-term engraftment and expansion of tumor-derived memory T cells following the implantation of non-disrupted pieces of human lung tumor into NOD-scid IL2Rγ(null) mice. J. Immunol. 180, 7009–7018 (2008).

    Article  CAS  PubMed  Google Scholar 

  123. Ito, R. et al. Antigen-specific antibody production of human B cells in NOG mice reconstituted with the human immune system. Curr. Top. Microbiol. Immunol. 324, 95–107 (2008).

    CAS  PubMed  Google Scholar 

  124. Ji, M., Jin, X., Phillips, P. & Yi, S. A humanized mouse model to study human immune response in xenotransplantation. Hepatobiliary Pancreat. Dis. Int. 11, 494–498 (2012).

    Article  CAS  PubMed  Google Scholar 

  125. van Miltenburg, M. H. & Jonkers, J. Using genetically engineered mouse models to validate candidate cancer genes and test new therapeutic approaches. Curr. Opin. Genet. Dev. 22, 21–27 (2012). This review highlights the recent technological advances in modelling cancer in GEMMs, their usefulness and the challenges encountered.

    Article  CAS  PubMed  Google Scholar 

  126. Walrath, J. C., Hawes, J. J., Van Dyke, T. & Reilly, K. M. Genetically engineered mouse models in cancer research. Adv. Cancer Res. 106, 113–164 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. Eklund, L., Bry, M. & Alitalo, K. Mouse models for studying angiogenesis and lymphangiogenesis in cancer. Mol. Oncol. 7, 259–282 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  128. Firestone, B. The challenge of selecting the 'right' in vivo oncology pharmacology model. Curr. Opin. Pharmacol. 10, 391–396 (2010).

    Article  CAS  PubMed  Google Scholar 

  129. Schaffer, B. S. et al. Immune competency of a hairless mouse strain for improved preclinical studies in genetically engineered mice. Mol. Cancer Ther. 9, 2354–2364 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  130. Naumov, G. N. et al. Cellular expression of green fluorescent protein, coupled with high-resolution in vivo videomicroscopy, to monitor steps in tumor metastasis. J. Cell Sci. 112, 1835–1842 (1999).

    CAS  PubMed  Google Scholar 

  131. Yang, M. et al. Direct external imaging of nascent cancer, tumor progression, angiogenesis, and metastasis on internal organs in the fluorescent orthotopic model. Proc. Natl Acad. Sci. USA 99, 3824–3829 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  132. Yang, M., Jiang, P. & Hoffman, R. M. Whole-body subcellular multicolor imaging of tumor-host interaction and drug response in real time. Cancer Res. 67, 5195–5200 (2007).

    Article  CAS  PubMed  Google Scholar 

  133. Hoffman, R. M. Imaging cancer dynamics in vivo at the tumor and cellular level with fluorescent proteins. Clin. Exp. Metastasis 26, 345–355 (2009).

    Article  CAS  PubMed  Google Scholar 

  134. Yamamoto, N., Tsuchiya, H. & Hoffman, R. M. Tumor imaging with multicolor fluorescent protein expression. Int. J. Clin. Oncol. 16, 84–91 (2011).

    Article  CAS  PubMed  Google Scholar 

  135. Nothdurft, R., Sarder, P., Bloch, S., Culver, J. & Achilefu, S. Fluorescence lifetime imaging microscopy using near-infrared contrast agents. J. Microsc. 247, 202–207 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  136. Lin, M. Z. et al. Autofluorescent proteins with excitation in the optical window for intravital imaging in mammals. Chem. Biol. 16, 1169–1179 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  137. Morozova, K. S. et al. Far-red fluorescent protein excitable with red lasers for flow cytometry and superresolution STED nanoscopy. Biophys. J. 99, L13–15 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  138. Shcherbo, D. et al. Far-red fluorescent tags for protein imaging in living tissues. Biochem. J. 418, 567–574 (2009).

    Article  CAS  PubMed  Google Scholar 

  139. Shcherbo, D. et al. Near-infrared fluorescent proteins. Nature Methods 7, 827–829 (2010). This paper describes the development of NIRF proteins with red-shifted emission maxima and high photostability for in vivo imaging.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  140. Strack, R. L. et al. A rapidly maturing far-red derivative of DsRed-Express2 for whole-cell labeling. Biochemistry 48, 8279–8281 (2009).

    Article  PubMed  Google Scholar 

  141. Beerling, E., Ritsma, L., Vrisekoop, N., Derksen, P. W. & van Rheenen, J. Intravital microscopy: new insights into metastasis of tumors. J. Cell Sci. 124, 299–310 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  142. Ritsma, L. et al. Intravital microscopy through an abdominal imaging window reveals a pre-micrometastasis stage during liver metastasis. Sci. Transl. Med. 4, 158ra145 (2012).

    Article  CAS  PubMed  Google Scholar 

  143. Souris, J. S., Hickson, J. A., Msezane, L., Rinker-Schaeffer, C. W. & Chen, C. T. Flexible peritoneal windows for quantitative fluorescence and bioluminescence preclinical imaging. Mol. Imag. 12, 28–38 (2013).

    CAS  Google Scholar 

  144. Tanaka, K. et al. Intravital dual-colored visualization of colorectal liver metastasis in living mice using two photon laser scanning microscopy. Microsc. Res. Tech. 75, 307–315 (2012).

    Article  PubMed  Google Scholar 

  145. Amoh, Y., Katsuoka, K. & Hoffman, R. M. Color-coded fluorescent protein imaging of angiogenesis: the AngioMouse models. Curr. Pharm. Des. 14, 3810–3819 (2008).

    Article  CAS  PubMed  Google Scholar 

  146. van der Horst, G. et al. Real-time cancer cell tracking by bioluminescence in a preclinical model of human bladder cancer growth and metastasis. Eur. Urol. 60, 337–343 (2011).

    Article  PubMed  Google Scholar 

  147. Durupt, F. et al. The chicken chorioallantoic membrane tumor assay as model for qualitative testing of oncolytic adenoviruses. Cancer Gene Ther. 19, 58–68 (2012).

    Article  CAS  PubMed  Google Scholar 

  148. Harma, V. et al. A comprehensive panel of three-dimensional models for studies of prostate cancer growth, invasion and drug responses. PLoS ONE 5, e10431 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  149. Sato, T. & Clevers, H. Growing self-organizing mini-guts from a single intestinal stem cell: mechanism and applications. Science 340, 1190–1194 (2013).

    Article  CAS  PubMed  Google Scholar 

  150. Sachs, N. & Clevers, H. Organoid cultures for the analysis of cancer phenotypes. Curr. Opin. Genet. Dev. 24C, 68–73 (2014).

    Article  CAS  Google Scholar 

  151. Fiebig, H. H. et al. Gene signatures developed from patient tumor explants grown in nude mice to predict tumor response to 11 cytotoxic drugs. Cancer Genomics Proteomics 4, 197–209 (2007).

    CAS  PubMed  Google Scholar 

  152. Parrish, A. R., Gandolfi, A. J. & Brendel, K. Precision-cut tissue slices: applications in pharmacology and toxicology. Life Sci. 57, 1887–1901 (1995).

    Article  CAS  PubMed  Google Scholar 

  153. Pickl, M. & Ries, C. H. Comparison of 3D and 2D tumor models reveals enhanced HER2 activation in 3D associated with an increased response to trastuzumab. Oncogene 28, 461–468 (2009).

    Article  CAS  PubMed  Google Scholar 

  154. Willoughby, H. W., Maughan, G. B., Tremblay, P. C. & Wood, N. Determination of individual human tumour sensitivity to antitumour agents by tissue-slice incubation. Can. J. Surg. 14, 406–409 (1971).

    CAS  PubMed  Google Scholar 

  155. Zschenker, O., Streichert, T., Hehlgans, S. & Cordes, N. Genome-wide gene expression analysis in cancer cells reveals 3D growth to affect ECM and processes associated with cell adhesion but not DNA repair. PLoS ONE 7, e34279 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  156. Keyaerts, M. et al. Inhibition of firefly luciferase by general anesthetics: effect on in vitro and in vivo bioluminescence imaging. PLoS ONE 7, e30061 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  157. Fueger, B. J. et al. Impact of animal handling on the results of 18F-FDG PET studies in mice. J. Nucl. Med. 47, 999–1006 (2006).

    CAS  PubMed  Google Scholar 

  158. Emonds, K. M. et al. Do androgens control the uptake of 18F-FDG, 11C-choline and 11C-acetate in human prostate cancer cell lines? Eur. J. Nucl. Med. Mol. Imaging 38, 1842–1853 (2011).

    Article  CAS  PubMed  Google Scholar 

  159. Gros, S. J. et al. Complementary use of fluorescence and magnetic resonance imaging of metastatic esophageal cancer in a novel orthotopic mouse model. Int. J. Cancer 126, 2671–2681 (2010).

    CAS  PubMed  Google Scholar 

  160. Kosaka, N., Bernardo, M., Mitsunaga, M., Choyke, P. L. & Kobayashi, H. MR and optical imaging of early micrometastases in lymph nodes: triple labeling with nano-sized agents yielding distinct signals. Contrast Media Mol. Imag. 7, 247–253 (2012).

    CAS  Google Scholar 

  161. Krupnick, A. S. et al. Quantitative monitoring of mouse lung tumors by magnetic resonance imaging. Nature Protoc. 7, 128–142 (2012).

    Article  CAS  Google Scholar 

  162. Wolf, G. & Abolmaali, N. Preclinical molecular imaging using PET and MRI. Recent Results Cancer Res. 187, 257–310 (2013).

    Article  CAS  PubMed  Google Scholar 

  163. Pittet, M. J. & Weissleder, R. Intravital imaging. Cell 147, 983–991 (2011). This is an overview of state-of-the-art intravital imaging techniques and emerging technologies in this field.

    Article  CAS  PubMed  Google Scholar 

  164. Workman, P. et al. Guidelines for the welfare and use of animals in cancer research. Br. J. Cancer 102, 1555–1577 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  165. Festing, M. F. Improving the design and analysis of animal experiments: a personal odyssey. Altern. Lab. Anim. 37 (Suppl. 2), 75–81 (2009).

    Article  CAS  PubMed  Google Scholar 

  166. Festing, M. F. Inbred strains should replace outbred stocks in toxicology, safety testing, and drug development. Toxicol. Pathol. 38, 681–690 (2010).

    Article  CAS  PubMed  Google Scholar 

  167. Klaunberg, B. A. & Davis, J. A. Considerations for laboratory animal imaging center design and setup. ILAR J. 49, 4–16 (2008).

    Article  CAS  PubMed  Google Scholar 

  168. Maina, T. et al. Species differences of bombesin analog interactions with GRP-R define the choice of animal models in the development of GRP-R-targeting drugs. J. Nucl. Med. 46, 823–830 (2005).

    CAS  PubMed  Google Scholar 

  169. Wagner, P. D. & Srivastava, S. New paradigms in translational science research in cancer biomarkers. Transl. Res. 159, 343–353 (2012). This is a perspective on cancer biomarker translation.

    Article  PubMed  PubMed Central  Google Scholar 

  170. Roberts, S. F., Fischhoff, M. A., Sakowski, S. A. & Feldman, E. L. Perspective: Transforming science into medicine: how clinician-scientists can build bridges across research's valley of death. Acad. Med. 87, 266–270 (2012).

    Article  PubMed  Google Scholar 

  171. Caponigro, G. & Sellers, W. R. Advances in the preclinical testing of cancer therapeutic hypotheses. Nature Rev. Drug Discov. 10, 179–187 (2011).

    Article  CAS  Google Scholar 

  172. Feitsma, H. & Cuppen, E. Zebrafish as a cancer model. Mol. Cancer Res. 6, 685–694 (2008).

    Article  CAS  PubMed  Google Scholar 

  173. Ale, A. et al. FMT-XCT: in vivo animal studies with hybrid fluorescence molecular tomography-X-ray computed tomography. Nature Methods 9, 615–620 (2012).

    Article  CAS  PubMed  Google Scholar 

  174. Afaq, A. & Akin, O. Imaging assessment of tumor response: past, present and future. Future Oncol. 7, 669–677 (2011).

    Article  PubMed  Google Scholar 

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Acknowledgements

The authors thank the members of their laboratories for their critical comments and helpful discussions. The authors thank the biotechnicians in the groups for many years of dedicated work 'behind the scenes' to propagate precious PDX models valuable to many research projects, as well as for the many imaging studies performed; the authors thank the SPECTRIM group at Erasmus MC, The Netherlands, for providing Figures 2a and 2b. The authors apologize to those whose work is not cited owing to space limitations. Part of the authors' research is funded by Erasmus MC grants, grants from the SUWO (Stichting Urologisch Wetenschappelijk Onderzoek), from the Innovative Medicines Initiative (IMI) Joint Undertaking ('PREDECT', grant agreement number 115188) by EU FP7 and EFPIA companies, a grant from the 'Lijf en Leven' foundation ('DIVERS'), equipment grants (91111012 and 91105015) from the Dutch Organization of Scientific Research (NWO), a grant from the Dutch Cancer Society (KWF; EMCR 2008-4037) and a grant from EU FP7 ITN PITN-GA-2012-317019.

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de Jong, M., Essers, J. & van Weerden, W. Imaging preclinical tumour models: improving translational power. Nat Rev Cancer 14, 481–493 (2014). https://doi.org/10.1038/nrc3751

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