Biomarker development in the context of urologic cancers

The Food and Drug Administration (FDA) has called for the use of analytically validated biomarkers that have strong evidence of being fit for purpose to identify patients likely to respond and to evaluate the patient response to a therapy, potential toxicity, and drug resistance. This article discusses development and application of these biomarkers in the context of urologic cancers-specifically in cancers of the prostate and urinary bladder.

The FDA has defined four specific categories for contexts of biomarker use: prognostic, predictive, response-indicator, and efficacy-response (surrogate endpoints). Prognostic and predictive biomarkers include pretreatment characteristics of the patient and the tumor. Response-indicator and efficacy response biomarkers occur after treatment and show the effects of treatment on biomarkers. Efficacy response biomarkers show changes associated with clinical benefit and can be surrogates for clinical endpoints leading to drug approvals.

Well-structured development plans are required to satisfy rigorous criteria that must be met to qualify biomarkers for specific contexts of use in drug development and patient management. A description of the extensive effort applied to the validation and qualification of circulating tumor cells in castration resistant prostate cancer is described as an example of the potential utility of biomarkers in urological cancers.

Many potential biomarkers have been identified in prostate and urinary bladder cancers, but few have sufficient demonstration of analytical and clinical validity to meet FDA standards for use in clinical settings. Circulating tumor cell (CTC) assays are particularly promising candidates for informative new biomarkers to measure disease before and after treatment. New technologies are providing opportunities for high definition, more informative analysis. Statistical and computational methodologies to describe assay results are also rapidly evolving. These advances will lead to better diagnosis, earlier indications of treatment response and failure, and better definition of patient cohorts that will respond to a specific treatment.