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Predictive biomarkers: a paradigm shift towards personalized cancer medicine

Nature Reviews Clinical Oncology volume 8, pages 587–596 (2011)Cite this article

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Abstract

Advances in our understanding of the intricate molecular mechanisms for transformation of a normal cell to a cancer cell, and the aberrant control of complementary pathways, have presented a much more complex set of challenges for the diagnostic and therapeutic disciplines than originally appreciated. The oncology field has entered an era of personalized medicine where treatment selection for each cancer patient is becoming individualized or customized. This advance reflects the molecular and genetic composition of the tumors and progress in biomarker technology, which allow us to align the most appropriate treatment according to the patient's disease. There is a worldwide acceptance that advances in our ability to identify predictive biomarkers and provide them as companion diagnostics for stratifying and subgrouping patients represents the next leap forward in improving the quality of clinical care in oncology. As such, we are progressing from a population-based empirical 'one drug fits all' treatment model, to a focused personalized approach where rational companion diagnostic tests support the drug's clinical utility by identifying the most responsive patient subgroup.

Key Points

  • Cancer is a diverse collection of diseases that have different causative factors, molecular composition, and natural histories

  • Many recently developed cancer drugs target discrete molecular aberrations or pathways in tumor cells and consequently are active on a subset of the patient population

  • Companion diagnostics that measure biomarkers that allow responsive patients to be identified and subgrouped are being increasingly integrated with the drug-development process and clinical trials

  • Most response-specific biomarkers that have reached clinical validation were identified through retrospective analysis of clinical data

  • Molecular techniques are available that allow biomarkers to be identified in a systematic prospectively driven fashion

  • The long sought after goal where therapeutic choice is guided by an informative biomarker 'code' is now upon us

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Figure 1: Action of drugs targeting EGFR and HER2.
Figure 2: Design of biomarker testing clinical trials.
Figure 3: Response-specific biomarkers in cancer clinical trials.
Figure 4: A theoretical approach to personalized cancer therapy.

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  1. Department of Clinical Pharmacology, Laboratory of Cancer Biology, University of Oxford, Old Road Campus Research Building, Old Road Campus, OX3 7DQ, Oxford, UK

    Nicholas B. La Thangue

  2. Nuffield Department of Clinical and Laboratory Sciences, University of Oxford, Old Road Campus Research Building, Old Road Campus, OX3 7DQ, Oxford, UK

    David J. Kerr

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Both authors researched data for inclusion in the article. N. B. La Thangue contributed to the writing, editing and reviewing the manuscript before submission and during the reviewing process.

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N. B. La Thangue is a consultant, stock holder and patent holder for Celleron Therapeutics. D. J. Kerr is a consultant for Celleron Therapeutics.

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La Thangue, N., Kerr, D. Predictive biomarkers: a paradigm shift towards personalized cancer medicine. Nat Rev Clin Oncol 8, 587–596 (2011). https://doi.org/10.1038/nrclinonc.2011.121

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