Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Model organisms

The mighty mouse: genetically engineered mouse models in cancer drug development

Key Points

  • The high attrition rate of compounds entering clinical testing as potential anticancer drugs indicates a need for better methods to predict efficacy before testing in humans.

  • The poor correlation between therapeutic activity of compounds tested in xenograft mouse models and their efficacy in humans does not necessarily mean that more faithful genetically engineered mouse models (GEMMs) will be of limited use in drug development.

  • Indeed, a major untapped solution could lie in the use of refined GEMMs of human cancer that are capable of facilitating the identification of the right target, the right drug and the right patients.

  • The attributes of a 'well-designed' GEMM include moderate penetrance and short latency of single tumours, engineered alleles that are representative of the human disease, and simplicity in colony management and technical use.

  • There are several important applications for GEMMs in anticancer drug development, including target validation, assessment of tumour response, investigation of pharmacodynamic markers of drug action, modelling resistance and understanding toxicity, which are discussed in this article.

Abstract

Deficiencies in the standard preclinical methods for evaluating potential anticancer drugs,such as xenograft mouse models, have been highlighted as a key obstacle in the translation of the major advances in basic cancer research into meaningful clinical benefits. In this article, we discuss the established uses and limitations of xenograft mouse models for cancer drug development, and then describe the opportunities and challenges in the application of novel genetically engineered mouse models that more faithfully mimic the genetic and biological evolution of human cancers. Greater use of such models in target validation, assessment of tumour response, investigation of pharmacodynamic markers of drug action, modelling resistance and understanding toxicity has the potential to markedly improve the success of cancer drug development.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Attrition rates by stage of clinical testing for all classes of compounds and oncology-specific compounds.
Figure 2: Preclinical uses of murine models for drug discovery.
Figure 3: Xenograft versus GEMM testing.
Figure 4: A different kind of xenograft.
Figure 5: Why do drugs fail?

Similar content being viewed by others

References

  1. Leaf, C. Why we're losing the war on cancer: and how to win it. Fortune 149, 77–92 (2004).

    Google Scholar 

  2. National Cancer Institute. Cancer Trends Progress Report [online] (2005).

  3. Weiss, A. J. et al. Phase II study of 5-azacytidine in solid tumors. Cancer Treat. Rep. 61, 55–58 (1977).

    CAS  PubMed  Google Scholar 

  4. Lomen, P. L., Khilanani, P. & Kessel, D. Phase I study using combination of hydroxyurea and 5-azacytidine (NSC-102816). Neoplasma 27, 101–106 (1980).

    CAS  PubMed  Google Scholar 

  5. Lomen, P. L., Baker, L. H., Neil, G. L. & Samson, M. K. Phase I study of 5-azacytidine (NSC-102816) using 24-hour continuous infusion for 5 days. Cancer Chemother. Rep. 59, 1123–1126 (1975).

    CAS  PubMed  Google Scholar 

  6. Silverman, L. R. et al. Randomized controlled trial of azacitidine in patients with the myelodysplastic syndrome: a study of the cancer and leukemia group B. J. Clin. Oncol. 20, 2429–2440 (2002).

    CAS  PubMed  Google Scholar 

  7. Kola, I. & Landis, J. Can the pharmaceutical industry reduce attrition rates? Nature Rev. Drug Discov. 3, 711–715 (2004).

    CAS  Google Scholar 

  8. Horrobin, D. F. Are large clinical trials in rapidly lethal diseases usually unethical? Lancet 361, 695–697 (2003).

    PubMed  Google Scholar 

  9. Decoster, G., Stein, G. & Holdener, E. E. Responses and toxic deaths in phase I clinical trials. Ann. Oncol. 1, 175–181 (1990).

    CAS  PubMed  Google Scholar 

  10. Roberts, T. G. et al. Trends in the risks and benefits to patients with cancer participating in phase 1 clinical trials. JAMA 292, 2130–2140 (2004). References 9 and 10 illustrate a significant problem with Phase I trials (namely a 4% response rate) carried out using empirically discovered would-be chemotherapeutics. We believe that using better preclinical models would improve this low level of clinical benefit, allowing for more efficient and ethical drug discovery.

    CAS  PubMed  Google Scholar 

  11. Voskoglou-Nomikos, T., Pater, J. L. & Seymour, L. Clinical predictive value of the in vitro cell line, human xenograft, and mouse allograft preclinical cancer models. Clin. Cancer Res. 9, 4227–4239 (2003).

    PubMed  Google Scholar 

  12. Johnson, J. I. et al. Relationships between drug activity in NCI preclinical in vitro and in vivo models and early clinical trials. Br. J. Cancer 84, 1424–1431 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Reya, T., Morrison, S. J., Clarke, M. F. & Weissman, I. L. Stem cells, cancer, and cancer stem cells. Nature 414, 105–111 (2001).

    CAS  PubMed  Google Scholar 

  14. Mellinghoff, I. K. et al. Molecular determinants of the response of glioblastomas to EGFR kinase inhibitors. N. Engl. J. Med. 353, 2012–2024 (2005).

    CAS  PubMed  Google Scholar 

  15. Sarraf, P. et al. Differentiation and reversal of malignant changes in colon cancer through PPARγ. Nature Med. 4, 1046–1052 (1998).

    CAS  PubMed  Google Scholar 

  16. Kulke, M. H. et al. A phase II study of troglitazone, an activator of the PPARγ receptor, in patients with chemotherapy-resistant metastatic colorectal cancer. Cancer J. 8, 395–399 (2002).

    PubMed  Google Scholar 

  17. Saez, E. et al. Activators of the nuclear receptor PPARγ enhance colon polyp formation. Nature Med. 4, 1058–1061 (1998).

    CAS  PubMed  Google Scholar 

  18. Boehm, T., Folkman, J., Browder, T. & O'Reilly, M. S. Antiangiogenic therapy of experimental cancer does not induce acquired drug resistance. Nature 390, 404–407 (1997).

    CAS  PubMed  Google Scholar 

  19. O'Reilly, M. S., Holmgren, L., Chen, C. & Folkman, J. Angiostatin induces and sustains dormancy of human primary tumors in mice. Nature Med. 2, 689–692 (1996).

    CAS  PubMed  Google Scholar 

  20. Holmgren, L., O'Reilly, M. S. & Folkman, J. Dormancy of micrometastases: balanced proliferation and apoptosis in the presence of angiogenesis suppression. Nature Med. 1, 149–153 (1995).

    CAS  PubMed  Google Scholar 

  21. Hansma, A. H. et al. Recombinant human endostatin administered as a 28-day continuous intravenous infusion, followed by daily subcutaneous injections: a phase I and pharmacokinetic study in patients with advanced cancer. Ann. Oncol. 16, 1695–1701 (2005).

    CAS  PubMed  Google Scholar 

  22. Twombly, R. First clinical trials of endostatin yield lukewarm results. J. Natl Cancer Inst. 94, 1520–1521 (2002).

    PubMed  Google Scholar 

  23. Soff, G. A. et al. In vivo generation of angiostatin isoforms by administration of a plasminogen activator and a free sulfhydryl donor: a phase I study of an angiostatic cocktail of tissue plasminogen activator and mesna. Clin. Cancer Res. 11, 6218–6225 (2005).

    CAS  PubMed  Google Scholar 

  24. Thomas, J. P. et al. Phase I pharmacokinetic and pharmacodynamic study of recombinant human endostatin in patients with advanced solid tumors. J. Clin. Oncol. 21, 223–231 (2003).

    CAS  PubMed  Google Scholar 

  25. Davis, D. W. et al. Quantitative analysis of biomarkers defines an optimal biological dose for recombinant human endostatin in primary human tumors. Clin. Cancer Res. 10, 33–42 (2004).

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  27. Thompson, J., Stewart, C. F. & Houghton, P. J. Animal models for studying the action of topoisomerase I targeted drugs. Biochim. Biophys. Acta 1400, 301–319 (1998).

    CAS  PubMed  Google Scholar 

  28. Peterson, J. K. & Houghton, P. J. Integrating pharmacology and in vivo cancer models in preclinical and clinical drug development. Eur. J. Cancer 40, 837–844 (2004).

    CAS  PubMed  Google Scholar 

  29. Okami, K. et al. Analysis of PTEN/MMAC1 alterations in aerodigestive tract tumors. Cancer Res. 58, 509–511 (1998).

    CAS  PubMed  Google Scholar 

  30. Meyer, W. H. et al. Development and characterization of pediatric osteosarcoma xenografts. Cancer Res. 50, 2781–2785 (1990).

    CAS  PubMed  Google Scholar 

  31. Furman, W. L. et al. Direct translation of a protracted irinotecan schedule from a xenograft model to a phase I trial in children. J. Clin. Oncol. 17, 1815–1824 (1999).

    CAS  PubMed  Google Scholar 

  32. Sun, B., Chen, M., Hawks, C. L., Pereira-Smith, O. M. & Hornsby, P. J. The minimal set of genetic alterations required for conversion of primary human fibroblasts to cancer cells in the subrenal capsule assay. Neoplasia 7, 585–593 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Sun, B., Chen, M., Hawks, C., Hornsby, P. J. & Wang, X. Tumorigenic study on hepatocytes coexpressing SV40 with Ras. Mol. Carcinog. 45, 213–219 (2006).

    CAS  PubMed  Google Scholar 

  34. Bachoo, R. M. et al. Epidermal growth factor receptor and Ink4a/Arf. Convergent mechanisms governing terminal differentiation and transformation along the neural stem cell to astrocyte axis. Cancer Cell 1, 269–277 (2002).

    CAS  PubMed  Google Scholar 

  35. Yang, J. et al. Twist, a master regulator of morphogenesis, plays an essential role in tumor metastasis. Cell 117, 927–939 (2004).

    CAS  Google Scholar 

  36. Tassone, P. et al. Combination therapy with interleukin-6 receptor superantagonist Sant7 and dexamethasone induces antitumor effects in a novel SCID-hu in vivo model of human multiple myeloma. Clin. Cancer Res. 11, 4251–4258 (2005).

    CAS  PubMed  Google Scholar 

  37. Mitsiades, C. S. et al. Fluorescence imaging of multiple myeloma cells in a clinically relevant SCID/NOD in vivo model: biologic and clinical implications. Cancer Res. 63, 6689–6696 (2003).

    CAS  PubMed  Google Scholar 

  38. Bardeesy, N. et al. Both p16Ink4a and the p19Arf–p53 pathway constrain progression of pancreatic adenocarcinoma in the mouse. Proc. Natl Acad. Sci. USA 103, 5947–5952 (2006).

    CAS  PubMed  Google Scholar 

  39. Sharpless, N. E., Kannan, K., Xu, J., Bosenberg, M. W. & Chin, L. Both products of the mouse Ink4a/Arf locus suppress melanoma formation in vivo. Oncogene 22, 5055–5059 (2003).

    CAS  PubMed  Google Scholar 

  40. Chin, L. et al. Cooperative effects of INK4a and ras in melanoma susceptibility in vivo. Genes Dev. 11, 2822–2834 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Bardeesy, N. et al. Dual inactivation of RB and p53 pathways in RAS-induced melanomas. Mol. Cell. Biol. 21, 2144–2153 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Castresana, J. S. et al. Lack of allelic deletion and point mutation as mechanisms of p53 activation in human malignant melanoma. Int. J. Cancer 55, 562–565 (1993).

    CAS  PubMed  Google Scholar 

  43. Albino, A. P. et al. Mutation and expression of the p53 gene in human malignant melanoma. Melanoma Res. 4, 35–45 (1994).

    CAS  PubMed  Google Scholar 

  44. Lubbe, J., Reichel, M., Burg, G. & Kleihues, P. Absence of p53 gene mutations in cutaneous melanoma. J. Invest. Dermatol. 102, 819–821 (1994).

    CAS  PubMed  Google Scholar 

  45. Rhim, K. J. et al. Aberrant expression of p53 gene product in malignant melanoma. J. Korean Med. Sci. 9, 376–381 (1994).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Kamb, A. et al. A cell cycle regulator potentially involved in genesis of many tumor types. Science 264, 436–440 (1994).

    CAS  PubMed  Google Scholar 

  47. Hussussian, C. J. et al. Germline p16 mutations in familial melanoma. Nature Genet. 8, 15–21 (1994).

    CAS  PubMed  Google Scholar 

  48. Koh, J., Enders, G. H., Dynlacht, B. D. & Harlow, E. Tumour-derived p16 alleles encoding proteins defective in cell-cycle inhibition. Nature 375, 506–510 (1995).

    CAS  PubMed  Google Scholar 

  49. Flores, J. F. et al. Loss of the p16INK4a and p15INK4b genes, as well as neighboring 9p21 markers, in sporadic melanoma. Cancer Res. 56, 5023–5032 (1996).

    CAS  PubMed  Google Scholar 

  50. Weissleder, R. Scaling down imaging: molecular mapping of cancer in mice. Nature Rev. Cancer 2, 11–18 (2002).

    CAS  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  52. Sotillo, R. et al. Cooperation between Cdk4 and p27kip1 in tumor development: a preclinical model to evaluate cell cycle inhibitors with therapeutic activity. Cancer Res. 65, 3846–3852 (2005).

    CAS  PubMed  Google Scholar 

  53. Stewart, T. A., Pattengale, P. K. & Leder, P. Spontaneous mammary adenocarcinomas in transgenic mice that carry and express MTV/myc fusion genes. Cell 38, 627–637 (1984).

    CAS  PubMed  Google Scholar 

  54. Quaife, C. J., Pinkert, C. A., Ornitz, D. M., Palmiter, R. D. & Brinster, R. L. Pancreatic neoplasia induced by ras expression in acinar cells of transgenic mice. Cell 48, 1023–1034 (1987).

    CAS  PubMed  Google Scholar 

  55. Brinster, R. L. et al. Transgenic mice harboring SV40 T-antigen genes develop characteristic brain tumors. Cell 37, 367–379 (1984).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Hanahan, D. Heritable formation of pancreatic β-cell tumours in transgenic mice expressing recombinant insulin/simian virus 40 oncogenes. Nature 315, 115–122 (1985).

    CAS  PubMed  Google Scholar 

  57. Adams, J. M. & Cory, S. Transgenic models of tumor development. Science 254, 1161–1167 (1991).

    CAS  PubMed  Google Scholar 

  58. Jacks, T. et al. Effects of an Rb mutation in the mouse. Nature 359, 295–300 (1992).

    CAS  PubMed  Google Scholar 

  59. Jacks, T. et al. Tumor spectrum analysis in p53-mutant mice. Curr. Biol. 4, 1–7 (1994).

    CAS  PubMed  Google Scholar 

  60. Donehower, L. A. et al. Mice deficient for p53 are developmentally normal but susceptible to spontaneous tumours. Nature 356, 215–221 (1992).

    CAS  PubMed  Google Scholar 

  61. Van Dyke, T. & Jacks, T. Cancer modeling in the modern era: progress and challenges. Cell 108, 135–144 (2002).

    CAS  PubMed  Google Scholar 

  62. Chin, L. et al. Essential role for oncogenic Ras in tumour maintenance. Nature 400, 468–472 (1999).

    CAS  PubMed  Google Scholar 

  63. Felsher, D. W. & Bishop, J. M. Reversible tumorigenesis by MYC in hematopoietic lineages. Mol. Cell 4, 199–207 (1999). References 62 and 63 are classic papers that articulate and prove the concept of the importance of oncogenes, such as MYC and RAS , in tumour maintenance as opposed to tumour progression. Since this research it has become well recognized that establishing the role of a particular gene in tumour maintenance is a crucial step in target validation.

    CAS  PubMed  Google Scholar 

  64. D'Cruz, C. M. et al. c-MYC induces mammary tumorigenesis by means of a preferred pathway involving spontaneous Kras2 mutations. Nature Med. 7, 235–239 (2001).

    CAS  PubMed  Google Scholar 

  65. Politi, K. et al. Lung adenocarcinomas induced in mice by mutant EGF receptors found in human lung cancers respond to a tyrosine kinase inhibitor or to down-regulation of the receptors. Genes Dev. 20, 1496–1510 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  66. Fisher, G. H. et al. Induction and apoptotic regression of lung adenocarcinomas by regulation of a K-Ras transgene in the presence and absence of tumor suppressor genes. Genes Dev. 15, 3249–3262 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  67. Ji, H. et al. The impact of human EGFR kinase domain mutations on lung tumorigenesis and in vivo sensitivity to EGFR-targeted therapies. Cancer Cell 9, 485–495 (2006).

    CAS  PubMed  Google Scholar 

  68. Boxer, R. B., Jang, J. W., Sintasath, L. & Chodosh, L. A. Lack of sustained regression of c-MYC-induced mammary adenocarcinomas following brief or prolonged MYC inactivation. Cancer Cell 6, 577–586 (2004).

    CAS  PubMed  Google Scholar 

  69. Shachaf, C. M. et al. MYC inactivation uncovers pluripotent differentiation and tumour dormancy in hepatocellular cancer. Nature 431, 1112–1117 (2004).

    CAS  PubMed  Google Scholar 

  70. Berthet, C., Aleem, E., Coppola, V., Tessarollo, L. & Kaldis, P. Cdk2 knockout mice are viable. Curr. Biol. 13, 1775–1785 (2003).

    CAS  PubMed  Google Scholar 

  71. Ortega, S. et al. Cyclin-dependent kinase 2 is essential for meiosis but not for mitotic cell division in mice. Nature Genet. 35, 25–31 (2003).

    CAS  PubMed  Google Scholar 

  72. Martin, A. et al. Cdk2 is dispensable for cell cycle inhibition and tumor suppression mediated by p27Kip1 and p21Cip1. Cancer Cell 7, 591–598 (2005).

    CAS  PubMed  Google Scholar 

  73. Aleem, E., Kiyokawa, H. & Kaldis, P. Cdc2–cyclin E complexes regulate the G1/S phase transition. Nature Cell Biol. 7, 831–836 (2005).

    CAS  PubMed  Google Scholar 

  74. Yu, Q. et al. Requirement for CDK4 kinase function in breast cancer. Cancer Cell 9, 23–32 (2006).

    CAS  PubMed  Google Scholar 

  75. Landis, M. W., Pawlyk, B. S., Li, T., Sicinski, P. & Hinds, P. W. Cyclin D1-dependent kinase activity in murine development and mammary tumorigenesis. Cancer Cell 9, 13–22 (2006).

    CAS  PubMed  Google Scholar 

  76. Toogood, P. L. et al. Discovery of a potent and selective inhibitor of cyclin-dependent kinase 4/6. J. Med. Chem. 48, 2388–2406 (2005).

    CAS  PubMed  Google Scholar 

  77. Lowe, S. W., Ruley, H. E., Jacks, T. & Housman, D. E. p53-dependent apoptosis modulates the cytotoxicity of anticancer agents. Cell 74, 957–967 (1993). One of the first GEMM studies to have major implications for the development of human chemotherapeutics. This work showed that the response to cytotoxics in certain malignant cells requires p53 function, establishing a key mechanism of chemotherapy resistance.

    CAS  PubMed  Google Scholar 

  78. Omer, C. A. et al. Mouse mammary tumor virus-Ki-rasB transgenic mice develop mammary carcinomas that can be growth-inhibited by a farnesyl:protein transferase inhibitor. Cancer Res. 60, 2680–2688 (2000). An important early GEMM study showing that FTI efficacy does not correlate with k-Ras mutation. The importance of this work was not fully appreciated until after a large number of human clinical trials were completed in which FTIs failed to demonstrate activity in tumours harbouring mutant k-RAS.

    CAS  PubMed  Google Scholar 

  79. Bergers, G., Song, S., Meyer-Morse, N., Bergsland, E. & Hanahan, D. Benefits of targeting both pericytes and endothelial cells in the tumor vasculature with kinase inhibitors. J. Clin. Invest. 111, 1287–1295 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  80. Pietras, K. & Hanahan, D. A multitargeted, metronomic, and maximum-tolerated dose 'chemo-switch' regimen is antiangiogenic, producing objective responses and survival benefit in a mouse model of cancer. J. Clin. Oncol. 23, 939–952 (2005).

    CAS  PubMed  Google Scholar 

  81. Yilmaz, O. H. et al. Pten dependence distinguishes haematopoietic stem cells from leukaemia-initiating cells. Nature 441, 475–482 (2006).

    CAS  PubMed  Google Scholar 

  82. Wendel, H. G. et al. Survival signalling by Akt and eIF4E in oncogenesis and cancer therapy. Nature 428, 332–337 (2004).

    CAS  PubMed  Google Scholar 

  83. Bergers, G., Javaherian, K., Lo, K. M., Folkman, J. & Hanahan, D. Effects of angiogenesis inhibitors on multistage carcinogenesis in mice. Science 284, 808–812 (1999).

    CAS  PubMed  Google Scholar 

  84. Casanovas, O., Hicklin, D. J., Bergers, G. & Hanahan, D. Drug resistance by evasion of antiangiogenic targeting of VEGF signaling in late-stage pancreatic islet tumors. Cancer Cell 8, 299–309 (2005). A clever study showing how GEMMs can be used to tackle a difficult problem in drug discovery: how to combine and sequence novel anticancer agents.

    CAS  PubMed  Google Scholar 

  85. Zhang, Z. et al. Farnesyltransferase inhibitors are potent lung cancer chemopreventive agents in A/J mice with a dominant-negative p53 and/or heterozygous deletion of Ink4a/Arf. Oncogene 22, 6257–6265 (2003).

    CAS  PubMed  Google Scholar 

  86. Boolbol, S. K. et al. Cyclooxygenase-2 overexpression and tumor formation are blocked by sulindac in a murine model of familial adenomatous polyposis. Cancer Res. 56, 2556–2560 (1996).

    CAS  PubMed  Google Scholar 

  87. Opitz, O. G. et al. A mouse model of human oral-esophageal cancer. J. Clin. Invest. 110, 761–769 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  88. Jacoby, R. F., Seibert, K., Cole, C. E., Kelloff, G. & Lubet, R. A. The cyclooxygenase-2 inhibitor celecoxib is a potent preventive and therapeutic agent in the min mouse model of adenomatous polyposis. Cancer Res. 60, 5040–5044 (2000).

    CAS  PubMed  Google Scholar 

  89. Laird, P. W. et al. Suppression of intestinal neoplasia by DNA hypomethylation. Cell 81, 197–205 (1995).

    CAS  PubMed  Google Scholar 

  90. McCabe, M. T. et al. Inhibition of DNA methyltransferase activity prevents tumorigenesis in a mouse model of prostate cancer. Cancer Res. 66, 385–392 (2006).

    CAS  PubMed  Google Scholar 

  91. Pao, W. et al. Acquired resistance of lung adenocarcinomas to gefitinib or erlotinib is associated with a second mutation in the EGFR kinase domain. PLoS Med. 2, e73 (2005).

    PubMed  PubMed Central  Google Scholar 

  92. Shah, N. P. et al. Multiple BCR-ABL kinase domain mutations confer polyclonal resistance to the tyrosine kinase inhibitor imatinib (STI571) in chronic phase and blast crisis chronic myeloid leukemia. Cancer Cell 2, 117–125 (2002).

    CAS  PubMed  Google Scholar 

  93. Roumiantsev, S. et al. Clinical resistance to the kinase inhibitor STI-571 in chronic myeloid leukemia by mutation of Tyr-253 in the Abl kinase domain P-loop. Proc. Natl Acad. Sci. USA 99, 10700–10705 (2002).

    CAS  PubMed  Google Scholar 

  94. Gorre, M. E. et al. Clinical resistance to STI-571 cancer therapy caused by BCR-ABL gene mutation or amplification. Science 293, 876–880 (2001).

    CAS  PubMed  Google Scholar 

  95. Maggi, A. & Ciana, P. Reporter mice and drug discovery and development. Nature Rev. Drug Discov. 4, 249–255 (2005).

    CAS  Google Scholar 

  96. Crone, S. A. et al. ErbB2 is essential in the prevention of dilated cardiomyopathy. Nature Med. 8, 459–465 (2002). An excellent example of how a modern, tissue-specific GEMM can be used to understand unexpected toxicity of a novel agent (in this case, a HER2/ neu antibody).

    CAS  PubMed  Google Scholar 

  97. Artandi, S. E. et al. Telomere dysfunction promotes non-reciprocal translocations and epithelial cancers in mice. Nature 406, 641–645 (2000).

    CAS  PubMed  Google Scholar 

  98. Blaug, S., Chien, C. & Shuster, M. J. Managing innovation: university–industry partnerships and the licensing of the Harvard mouse. Nature Biotechnol. 22, 761–764 (2004).

    CAS  Google Scholar 

  99. Marshall, E. Intellectual property. DuPont ups ante on use of Harvard's OncoMouse. Science 296, 1212 (2002).

    CAS  PubMed  Google Scholar 

  100. Maebius, S. B. & Wegner, H. C. Merck V. Integra: the impact of a broader 'safe harbor' exemption on nanobiotechnology. Nanotechnol. Law Business 2, 1–6 (2005).

    Google Scholar 

  101. Nickerson, C. Canada court blocks Harvard bid to patent research mouse. Boston Globe (Boston) A20 6 December (2002).

    Google Scholar 

  102. Check, E. Canada stops Harvard's oncomouse in its tracks. Nature 420, 593 (2002).

    CAS  PubMed  Google Scholar 

  103. Jaffe, S. Ongoing battle over transgenic mice. The Scientist 18, 46 (2004).

    Google Scholar 

  104. Threadgill, D. W. et al. Targeted disruption of mouse EGF receptor: effect of genetic background on mutant phenotype. Science 269, 230–234 (1995).

    CAS  PubMed  Google Scholar 

  105. Tsutsui, T. et al. Targeted disruption of CDK4 delays cell cycle entry with enhanced p27Kip1 activity. Mol. Cell. Biol. 19, 7011–7019 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  106. Rane, S. G. et al. Loss of Cdk4 expression causes insulin-deficient diabetes and Cdk4 activation results in β-islet cell hyperplasia. Nature Genet. 22, 44–52 (1999).

    CAS  PubMed  Google Scholar 

  107. Little, C. C. & Cloudman, A. M. The occurrence of a dominant spotting mutation in the house mouse. Proc. Natl Acad. Sci. USA 23, 535–537 (1937).

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We thank P. Nisen, K.-K. Wong, K. Anderson, D. Hanahan, D. Frost, G. Gordon, A. Shoemaker and S. Mellis for stimulating discussions and critical reading of the manuscript. R. A. D. is an ACS Research Professor and an Ellison Medical Foundation Senior Scholar. This work was supported by grants from the Sidney Kimmel Foundation for Cancer Research (N.E.S.), the Ellison Medical Foundation (N.E.S. and R.A.D.) and the National Institutes of Health. R.A.D. is supported by the LeBow Fund to Cure Myeloma and the Robert A. and Renee E. Belfer Foundation Institute for Innovative Cancer Science.

Author information

Authors and Affiliations

Authors

Ethics declarations

Competing interests

R.A.D. is a director, co-founder and scientific advisor of AVEO Pharmaceuticals, Inc., which develops and uses mouse models of human cancer, including GEMMs and xenotransplants; R.A.D. also serves on the cancer scientific advisory council of Abbott Pharmaceuticals. The views expressed by R.A.D. are his own and do not reflect those of the management of AVEO or Abbott Pharmaceuticals.

Related links

Related links

FURTHER INFORMATION

Mouse Models of Human Cancers Consortium

Jackson laboratory

R. DePinho's laboratory

N. Sharpless' laboratory

Glossary

Xenograft model

Xenograft mouse models of cancer are created by injecting homogeneous human tumour cell lines into immunodeficient (for example, severe combined immunodeficiency) mice.

RECIST Criteria

Response Evaluation Criteria in Solid Tumors are standardized, radiographic criteria for determining tumour response or progression in human clinical trials of cancer therapeutics.

CRE recombinase

A phage enzyme that is used in murine genetic engineering. Expression of the enzyme causes selective excision of all genetic material between two LoxP sites. Murine strains can be engineered with LoxP sites flanking a gene of interest, stop codon and so on, and expression of CRE in these strains allows for tissue-specific and inducible changes in gene function.

Tet-regulation

The ability to regulate gene expression by feeding engineered murine strains tetracycline analogues (for example, doxycycline). Mice are engineered to contain a transgene of interest that is either induced (tet-ON) or repressed (tet-OFF) in the presence of doxycycline. These strains allow for the study of tissue-specific and inducible changes in gene expression. An advantage of tet-regulation is that the gene of interest can be serially induced and repressed by withdrawing and adding doxycycline to the animal's drinking water.

Oncogene addiction

The notion that cancer cells strictly require the activity of certain mutant oncogenes (for example, BCR–ABL in chronic myelogenous leukaemia), and therefore these oncogenes are required for tumour maintenance and are desirable therapeutic targets.

Metronomic therapy

Continuous or frequent treatment with low doses of cancer therapeutics, often given in a schedule-dependent manner with other methods of therapy. The goal is to inhibit an important cancer-relevant process (for example, angiogenesis) with minimal toxicity.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Sharpless, N., DePinho, R. The mighty mouse: genetically engineered mouse models in cancer drug development. Nat Rev Drug Discov 5, 741–754 (2006). https://doi.org/10.1038/nrd2110

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrd2110

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing