title: Qualification and Verification of Protein Biomarker Candidates.
abstract: The importance of biomarkers has long been recognized by the public, scientific community, and industry. Yet despite extensive efforts and funding investments in biomarker discovery, only 109 protein biomarkers in plasma or serum were approved by the US Food and Drug Administration throughout 2008 (Anderson NL. Clin Chem 56:177-185, 2010), and even fewer protein biomarkers are currently used routinely in the clinic. In recent years, the introduction of new protein biomarkers approved by the US Food and Drug Administration has fallen to an average of 1.5 per year (a median of only 1 per year) (Anderson NL. Clin Chem 56:177-185, 2010). The low efficiency of biomarker development is due to several reasons, including the poor quality of clinical samples, the gap between subjective clinical definition of a disease and objective protein measurements, and high false discovery rate of differentially expressed proteins identified in the initial discovery phase (Rifai N, Gillette MA, Carr SA. Nat Biotechnol 24:971-983, 2006). It has become clear that the vast majority of differentially expressed proteins identified in the discovery phase will ultimately fail as useful clinical biomarkers, and only few true positive candidates can move through the biomarker development pipeline. Isolation of true biomarkers from the large pool of differentially expressed proteins identified in the discovery phase becomes the greatest challenge and the bottleneck in most biomarker pipelines. To succeed, after the initial discovery study (see Chap. 20 ), the authenticity of biomarker candidates need to be tested in a pilot study with high throughput, high accuracy and reasonable cost. This essential process is addressed by qualification and verification phase of the biomarker development pipeline.
authors.affiliation: The University of Texas Medical Branch, 301 University Blvd, 77555, Galveston, TX, USA. yizhao@utmb.edu.
authors.forename: Yingxin
authors.initials: Y
authors.lastname: Zhao
authors.affiliation: The University of Texas Medical Branch, 301 University Blvd, 77555, Galveston, TX, USA.
authors.forename: Allan R
authors.initials: AR
authors.lastname: Brasier
mesh_terms: D000465:Algorithms; D015415:Biomarkers / Q000032:analysis; D019295:Computational Biology / Q000379:methods*; D057225:Data Mining / Q000379:methods*; D030562:Databases, Protein; D057166:High-Throughput Screening Assays; D006801:Humans; D013058:Mass Spectrometry / Q000379:methods*; D011237:Predictive Value of Tests; D011506:Proteins / Q000032:analysis*; D020543:Proteome; D040901:Proteomics / Q000379:methods*; D015203:Reproducibility of Results; D012984:Software
chemical_list: D015415:Biomarkers; D011506:Proteins; D020543:Proteome
keywords: Accurate inclusion mass screening (AIMS); Biomarker verification; Cohort selection; Data-independent MS/MS acquisition (DIA-MS/MS); ELISA-based verification; Parallel reaction monitoring (PRM); Selected Reaction Monitoring (SRM)