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Revisiting biomarker discovery by plasma proteomics.
Geyer, Philipp E; Holdt, Lesca M; Teupser, Daniel; Mann, Matthias.
  • Geyer PE; Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany.
  • Holdt LM; Faculty of Health Sciences, NNF Center for Protein Research, University of Copenhagen, Copenhagen, Denmark.
  • Teupser D; Institute of Laboratory Medicine, University Hospital, LMU Munich, Munich, Germany.
  • Mann M; Institute of Laboratory Medicine, University Hospital, LMU Munich, Munich, Germany.
Mol Syst Biol ; 13(9): 942, 2017 09 26.
Article en En | MEDLINE | ID: mdl-28951502
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.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Proteínas Sanguíneas / Proteoma / Proteómica Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Año: 2017 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Proteínas Sanguíneas / Proteoma / Proteómica Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Año: 2017 Tipo del documento: Article