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Preamble |
1 University of Florida, Gainesville, FL
2 Broad Institute of MIT and Harvard, Cambridge, MA
3 Plasma Proteome Institute, Washington, DC
aAddress correspondence to this author at:, Department of Pathology, Immunology, and, Laboratory Medicine, University of Florida College, of Medicine, PO Box 100275, Gainesville, FL 32610-0275, Fax +352-265-0447; e-mail ghortin@pathology.ufl.edu
| The first 300 words of the full text of this article appear below. |
"The determination of the structure of insulin clearly opens up the way to similar studies on other proteins ... One may also hope that studies on proteins may reveal changes that take place in disease and that our efforts may be of more practical use to humanity."
—Frederick S. Sanger, Nobel Lecture December 11, 1958 (1)
This special issue of Clinical Chemistry is devoted to recent developments in the diagnostic application of protein analysis. Proteins have been used as diagnostic markers for disease for more than 150 years—from the development of tests for urinary albumin as an indicator of kidney disease by Bright in 1827 and the first tumor marker, immunoglobulin light chains in urine associated with multiple myeloma, by Bence Jones in 1845. Over the succeeding years, the number of proteins analyzed for diagnostic purposes (2) has gradually increased until, at present, we analyze more than 200 different proteins in serum or plasma, as summarized by Anderson in the present issue (3), and many additional proteins as cellular markers for flow cytometry, red cell antigens, or tissue antigens. The rate of addition of new protein biomarkers has been quite slow, however. Only a few have been added per year, and proteins analyzed for diagnostic purposes represent a small subset of proteins in plasma or the human body. Technological advances allowing simultaneous analysis of hundreds of proteins at a time created hope for identifying a wealth of new protein biomarkers, but progress has been slower than anticipated. Application of multianalyte technologies has identified many candidate biomarkers for disease, but the efforts have been hindered by statistical problems of false discovery; sample stability; dominance of high-abundance components; lack of reproducibility, standardization, and calibration of methods; and lack of sufficient throughput and well-characterized
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