Establishing a panel of biomarkers for early diagnosis of cancer holds tremendous promise but also faces daunting obstacles. The major challenge stems from the very nature of a biological system, its complexity, dynamics, variability, and versatility all making it difficult to draw clear lines between a state that would be considered normal and one that appears to be slightly different and in danger of becoming abnormal. Then come barriers of logistics, such as a dichotomy between a need to mainly rely on population studies while facing tremendous intra- and interpersonal phenotypic variability, defining adequate controls, availability of specimens, and the danger of their potential adulteration before analysis (i.e., in the course of collection, processing, and storage). Last but not least is the requirement for sensitive technologies capable of measuring target compounds directly from a biological milieu with a level of specificity and selectivity that allows differentiation among discrete cohorts of individuals/patients that is reliable enough to justify the risk of acting on specific clinical modalities. There is a growing recognition that achieving true breakthroughs in the use of biomarkers to improve human conditions, while delivering health care in an economically sustainable way, requires concerted and coordinated efforts of stakeholders across disciplines and across borders. A large consortium of authors has recently published an in-depth analysis of the status of implementation of proteomics biomarkers of disease with a focus on postdiscovery/postvalidation barriers and outlined a need for a roadmap to biomarker implementation. ⁴ In our review, we concentrate on the preimplementation stages of the biomarker pipeline from the perspective of technologies that are currently available for biomarker discovery and validation, with a focus on protein biomarkers for which mass spectrometry (MS) plays a primary role.

The discipline of MS-based proteomics ⁵