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What's wrong with our cancer models?

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Abstract

Oncology, as a therapeutic area, is characterized by a desperate medical need for new drugs; the use of drugs that kill cells and which are consequently often toxic; and rates of failure in expensive Phase III trials that eclipse many other disease areas. The poor performance of most investigational cancer drugs implies that the standard preclinical disease models are faulty or, at least, improperly used. Some studies, however, support the view that cancer models can be highly effective, but only when selected and interpreted with care.

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Figure 1: Requirements for an effective and safe cancer drug.

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References

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

    Article  CAS  Google Scholar 

  2. Gorre, M. E. & Sawyers, C. L. Molecular mechanisms of resistance to STI571 in chronic myeloid leukemia. Curr. Opin. Hematol. 9, 303–307 (2002).

    Article  Google Scholar 

  3. Kamb, A. Consequences of nonadaptive alterations in cancer. Mol. Biol. Cell. 14, 2201–2205 (2003).

    Article  CAS  Google Scholar 

  4. Roberts Jr., 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).

    Article  CAS  Google Scholar 

  5. Ishii, N., Robert, M., Nakayama, Y., Kanai, A. & Tomita, M. Toward large-scale modeling of the microbial cell for computer simulation. J. Biotechnol. 113, 281–294 (2004).

    Article  CAS  Google Scholar 

  6. Oskoglou-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).

    Google Scholar 

  7. Yingling, J. M., Blanchard, K. L. & Sawyer, J. S. Development of TGF-β signaling inhibitors for cancer therapy. Nature Rev. Drug Discov. 3, 1011–1022.

  8. 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).

    Article  CAS  Google Scholar 

  9. Druker, B. J. Imatinib as a paradigm of targeted therapies. Adv. Cancer Res. 91, 1–30 (2004).

    Article  CAS  Google Scholar 

  10. Dancey, J. E. Predictive factors for epidermal growth factor receptor inhibitors — the bull's-eye hits the arrow. Cancer Cell 5, 411–415 (2004).

    Article  CAS  Google Scholar 

  11. Tuveson, D. A. et al. STI571 inactivation of the gastrointestinal stromal tumor c-KIT oncoprotein: biological and clinical implications. Oncogene 20, 5054–5058 (2001).

    Article  CAS  Google Scholar 

  12. Griffin, J. D. FLT3 tyrosine kinase as a target in acute leukemias. Hematol. J. 5, S188–190 (2004).

    Article  CAS  Google Scholar 

  13. Slamon, D. & Pegram, M. Rationale for trastuzumab (Herceptin) in adjuvant breast cancer trials. Semin. Oncol. 28, 13–19 (2001).

    Article  CAS  Google Scholar 

  14. Weisberg, E. & Griffin, J. D. Resistance to imatinib (Glivec): update on clinical mechanisms. Drug Resist. Updat. 6, 231–238 (2003).

    Article  CAS  Google Scholar 

  15. Scherf, U. et al. A gene expression database for the molecular pharmacology of cancer. Nature Genet. 24, 236–244 (2000).

    Article  CAS  Google Scholar 

  16. Jonkers, J. & Berns, A. Conditional mouse models of sporadic cancer. Nature Rev. Cancer 2, 251–265.

  17. 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)

    Article  CAS  Google Scholar 

  18. Wong, S. L. et al. Proc. Natl Acad. Sci. USA 101, 15682–15687 (2004).

    Article  CAS  Google Scholar 

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DATABASES

Entrez Gene

ABL

BCR

EGFR

FLT3

HER2/neu

KIT

National Cancer Institute Cancer Topics

Acute myelogenous leukaemia

chronic myelogenous leukaemia

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Kamb, A. What's wrong with our cancer models?. Nat Rev Drug Discov 4, 161–165 (2005). https://doi.org/10.1038/nrd1635

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