2. Discovery of Predictive Biomarkers for Anticancer Drugs

  1. Karen Lackey4 and
  2. Bruce D. Roth5
  1. Richard M. Neve1,
  2. Lisa D. Belmont2,
  3. Richard Bourgon3,
  4. Marie Evangelista2,
  5. Xiaodong Huang2,
  6. Maike Schmidt2,
  7. Robert L. Yauch2 and
  8. Jeffrey Settleman1

Published Online: 13 DEC 2013

DOI: 10.1002/9783527677252.ch02

Medicinal Chemistry Approaches to Personalized Medicine

Medicinal Chemistry Approaches to Personalized Medicine

How to Cite

Neve, R. M., Belmont, L. D., Bourgon, R., Evangelista, M., Huang, X., Schmidt, M., Yauch, R. L. and Settleman, J. (2013) Discovery of Predictive Biomarkers for Anticancer Drugs, in Medicinal Chemistry Approaches to Personalized Medicine (eds K. Lackey and B. D. Roth), Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, Germany. doi: 10.1002/9783527677252.ch02

Editor Information

  1. 4

    JanAush LLC, Charleston, SC 29425, USA

  2. 5

    Genentech Inc., 1 DNA Way, South San Francisco, CA 94080, USA

Author Information

  1. 1

    Genentech Inc., Discovery Oncology, MS 411A, 1 DNA Way, South San Francisco, CA, 94080, USA

  2. 2

    Genentech Inc., Oncology Diagnostics, MS 411A, 1 DNA Way, South San Francisco, CA, 94080, USA

  3. 3

    Genentech Inc., Oncology Bioinformatics, MS 411A, 1 DNA Way, South San Francisco, CA, 94080, USA

Publication History

  1. Published Online: 13 DEC 2013
  2. Published Print: 18 DEC 2013

ISBN Information

Print ISBN: 9783527333943

Online ISBN: 9783527677252

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Keywords:

  • antiangiogenesis;
  • cell lines;
  • drug resistance;
  • oncogene addiction;
  • predictive biomarkers;
  • tumor

Summary

Recently developed pathway-targeted drug therapies have had an enormous impact on the clinical management of several types of advanced cancer. For example, inhibitors of kinases, including EGFR, HER2, BCR-ABL, BRAF, and ALK, as well as nonkinase targets such as the hedgehog pathway component Smoothened, have demonstrated impressive clinical activity in treated patients – even in the metastatic setting in many cases. Importantly, the efficacy of such agents is largely limited to subsets of patients whose tumors are defined by specific genotypes associated with pathway activation and a state of “oncogene addiction.” This relatively new paradigm, in which patients most likely to benefit from a particular therapeutic can be prospectively identified to guide treatment decisions, has been described as “personalized cancer medicine,” and it has highlighted the critical role of predictive biomarkers for the optimal development of new cancer drug therapies. The discovery of such biomarkers can be challenging, although recent advances in genomic technologies and improvements in preclinical models, including large cancer cell line panels, have substantially aided these efforts. The discovery of a variety of mechanisms of acquired drug resistance, which inevitably limit the efficacy of new pathway-targeted drug treatments, has also provided insights into predictive biomarkers. However, significant challenges remain, for example, with the increasing need to identify predictive biomarkers in the context of drug combination treatments, and for treatments that target the tumor vasculature, demanding more sophisticated preclinical models and methods of data analysis to discover such biomarkers.