title: Proteomics in pathology, research and practice.
abstract: Using more reliable and sophisticated protein biochemical techniques, it is possible to perform large scale, partly high-throughput characterization of the human proteome. Two-dimensional electrophoresis (2-DE) and mass spectrometry largely contribute to the identification of proteins and peptides. 2-DE has been used to study differential expression of peptides and proteins in various disease entities, searching for new diagnostic and therapeutic targets. However, 2-DE usually requires large amounts of starting material, is time-consuming, and reveals only a fraction of the proteins present in a given sample. More recently, the ProteinChip technology coupled with bioinformatics has gained considerable attention. This technique uses surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI TOF/MS) to screen any protein source for putative disease biomarkers in a spectrum from 2 to 20 kDa. Between 15,500 (low resolution SELDI TOF) and > 400,000 peptides and proteins (high-resolution SELDI-TOF) can be resolved from a small sample volume (microl-range). Several studies have provided evidence that ProteinChip technology is capable of detecting early stage cancer by its unique cancer-specific proteomic finger prints, with sensitivities and specificities reaching far beyond well established serum-based tumor markers. In this review, we summarize the recent developments of proteomics in research and pathology, and critically discuss putative limitations and future applications of disease-specific biomarkers. Special emphasis is put on the former Human Protein Index project.
authors.affiliation: Department of Pathology, Otto-von-Guericke-University, Leipziger Strasse 44, D-39120 Magdeburg, Germany. christoph.roecken@medizin.uni-magdeburg.de
authors.forename: Christoph
authors.initials: C
authors.lastname: Röcken
authors.forename: Matthias P A
authors.initials: MP
authors.lastname: Ebert
authors.forename: Albert
authors.initials: A
authors.lastname: Roessner
mesh_terms: D035843:Biomedical Research / Q000639:trends*; D006801:Humans; D013058:Mass Spectrometry; D010336:Pathology / Q000295:instrumentation / Q000379:methods* / Q000639:trends*; D011364:Professional Practice / Q000639:trends*; D040081:Protein Array Analysis / Q000379:methods; D040901:Proteomics