Biomarker Discovery Efforts

The perceived need to identify objective markers to supplement, or conceivably supplant, the more subjective established histologic parameters has been a major driving force behind biomarker discovery efforts. It is crucial to recognize and account for the potential variability that can exist even with the new molecular parameters. Sources of variability include differences in molecular technique methodologies, tissue fixation and processing, interobserver and intraobserver variability (in immunohistochemistry-based biomarkers), and differences in cutoff points. Furthermore, illustration of statistical significance for a particular biomarker does... 

It is important to think about the question that you are asking in several ways because the formation of the right question is the key to a successful biomarker discovery experiment. A good question has several qualities that help to direct the biomarker discovery work and focus the research efforts in a clear and organized manner. Is the question reasonable with respect to what is known about the disease and the disease state For example, a poor question is I want to find a diagnostic for cancer. This is a poor question for several reasons ... 

It is important to make sure that the methods used for sample preparation are reproducible and robust. It is not important at this stage to develop a method that will be used during validation and any subsequent clinical method. The goal of discovery work is to see as much of the sample diversity as possible. Remember that biomarker discovery is a statistical game where the more choices that you have the better the chance that you will find a marker that can be validated, so it is important to see as much of the diversity in the chosen class of molecule as possible. One should try and find a method that will eliminate classes of biomolecules that are not of interest, will interfere with the analysis of molecules that are of interest, complicate the separation/detection of the species of interest, and could cause confusion during data analysis. Time and effort spent in the process of sample preparation will make life much easier in subsequent experimental processes. 

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