Personalized cancer medicine review: predictive biomarkers

In the advanced online issue of Nature Review Clinical Oncology of August 23^rd, Nicholas La Thangue and David Kerr published a detailed analysis of the state and the future of personalized cancer medicine (reference).  In this review, the authors offer a thorough analysis of the history, significance, and evolution of current predictive biomarkers for drug response in cancer (see table 1).

Table 1

First, a note about terminology. The authors use a biomarker nomenclature popular in the oncology field where the term “predictive” biomarker describes two types of disease biomarkers (see previous post for details): 

1. Trait biomarkers: a stable predictor of disease risk or response to treatment (e.g. genotype, liver CYP expression)
2. State biomarkers: evolving predictor of a disease stage (e.g. most medical diagnostics).

Second, beyond their analysis of predictive biomarkers, the authors also point to a potential unintentional negative consequence of personalized cancer medicine.  While novel targeted treatments of cancer offer the prospect of greater efficiency and lower risk to the patients, these new personalized treatment tend to displace older, more affordable “untargeted” drugs, potentially reducing access to treatment for the patients.  Ideally, the use of these older broad spectrum “untargeted” treatments could be optimized through the identification of novel predictive biomarkers of response to treatment.  However, considering the limited incentives associated with such efforts, it is unlikely that the industry will actively pursue this option.

Finally, this review highlights the growing need to revisit some of the initial assumptions associated with the development of predictive biomarkers and established companion diagnostics such as HER2 testing.  As I wrote in a previous post (link), the apparent direct connection between these early biomarkers (i.e. presence of target) and the biological process of interest (i.e. response to treatment) resulted in a development process that put little emphasis on biological qualification.  Now, it has become clear that this apparent connectivity is much more complex than initially assumed, forcing the cancer biomarker community to dedicate substantial efforts to clarify the biological significance of these early cancer biomarkers.

Thierry Sornasse for Integrated Biomarker Strategy