Measurement Proteomics Vs Traditional Proteomics

Multiplexed immunoassays used to identify novel biomarker patterns is a form of proteomics. However, it is often confused with traditional proteomics, which typically use complex separation technologies such as two-dimensional gel electrophoresis and/or mass spectrometry to identify patterns of peaks that are peptides or proteins of unknown origin. This approach provides new targets for future research but lacks the quantitation and certainly the precision necessary for clinical use. In contrast, the approach discussed here measures only those analytes where a specific assay has been developed. It requires specific ligand-binding reagents, generally antibodies, and a physical address to localize that binding reaction. This technique has been described as measurement proteomics, where a restricted set of analytes is measured and data reported in absolute terms (e.g., pg/mL) [3].

One caveat of measurement proteomics that must be addressed is the inherent variability among individuals for expression of different IBs. This variation results from a blend of genetic and environmental factors. Before one can accurately predict the biological response to a disease or its therapy, the natural variance within a population as well as within a person must be determined for the protein analytes in question. This is typically performed by assessing the biomarker patterning data for a control group of people while simultaneously measuring the identical markers in the diseased or drug-treated group. Statistical tools and means are widely available to use either cutoff values for individual analytes or multivariate analysis for multiple biomarkers in order to achieve a valuable test. Experience has shown that the level of a given protein biomarker or biomarker pattern often correlates with a particu lar disease state. In addition, these biomarker levels in serum or plasma have been shown to be stable in a person over time [1,2].

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