Many cancers today are diagnosed with the aid of tests to determine the presence of specific genetic mutations or over-expressed receptor proteins associated with the disease. The results of these tests are used to guide selection of drug therapy. While the actual molecular targets of most targeted therapies are elements of a signaling pathway, most biomarker tests only provide indirect and inferential information about the signaling pathway activity itself. These tests typically only measure one static component of a labyrinth of biochemical reactions that involves an enormous number of complex and dynamic signaling pathway interactions. These biochemical reactions are impossible to assess using current established testing and analysis. As a result, measurement of even a panel of biomarkers is incapable of discerning whether a signaling pathway is functioning abnormally.
Thus, a patient’s genomic biomarker status may not represent underlying signaling pathway dysfunction; this can lead to misdiagnosis and selection of the wrong targeted therapy to treat the patient.
To better realize the promise of personalized medicine, where patients receive the drugs best suited to specific biology of their disease, a new approach is required.