TY - JOUR

T1 - Revisiting biomarker discovery by plasma proteomics

AU - Geyer, Philipp E

AU - Holdt, Lesca M

AU - Teupser, Daniel

AU - Mann, Matthias

N1 - © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

PY - 2017/9/26

Y1 - 2017/9/26

N2 - Clinical analysis of blood is the most widespread diagnostic procedure in medicine, and blood biomarkers are used to categorize patients and to support treatment decisions. However, existing biomarkers are far from comprehensive and often lack specificity and new ones are being developed at a very slow rate. As described in this review, mass spectrometry (MS)-based proteomics has become a powerful technology in biological research and it is now poised to allow the characterization of the plasma proteome in great depth. Previous "triangular strategies" aimed at discovering single biomarker candidates in small cohorts, followed by classical immunoassays in much larger validation cohorts. We propose a "rectangular" plasma proteome profiling strategy, in which the proteome patterns of large cohorts are correlated with their phenotypes in health and disease. Translating such concepts into clinical practice will require restructuring several aspects of diagnostic decision-making, and we discuss some first steps in this direction.

AB - Clinical analysis of blood is the most widespread diagnostic procedure in medicine, and blood biomarkers are used to categorize patients and to support treatment decisions. However, existing biomarkers are far from comprehensive and often lack specificity and new ones are being developed at a very slow rate. As described in this review, mass spectrometry (MS)-based proteomics has become a powerful technology in biological research and it is now poised to allow the characterization of the plasma proteome in great depth. Previous "triangular strategies" aimed at discovering single biomarker candidates in small cohorts, followed by classical immunoassays in much larger validation cohorts. We propose a "rectangular" plasma proteome profiling strategy, in which the proteome patterns of large cohorts are correlated with their phenotypes in health and disease. Translating such concepts into clinical practice will require restructuring several aspects of diagnostic decision-making, and we discuss some first steps in this direction.

KW - Journal Article

KW - Review

U2 - 10.15252/msb.20156297

DO - 10.15252/msb.20156297

M3 - Review

C2 - 28951502

VL - 13

JO - Molecular Systems Biology

JF - Molecular Systems Biology

SN - 1744-4292

IS - 9

M1 - 942

ER -