Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UNIPROT:P05109 (S100A8)
 1,212 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Human saliva contains a large number of proteins that can be used for diagnosis and are of great potential in clinical and epidemiological research. The aim of this work was to map the proteins in saliva by two-dimensional gel electrophoresis (2-DE), and to identify abundant proteins by peptide mass fingerprinting using trypsin cleavage and matrix-assisted laser desorption/ionization-time of flight-mass spectrometry analysis. One hundred proteins were identified representing 20 different identities according to accession numbers. Abundant proteins expressed in different forms were: alpha-amylase, immunoglobulin A, prolactin-inducible protein, zinc-alpha(2)-glycoprotein and cystatins (S, SA, D and SN). Other proteins found were interleukin-1 receptor antagonist, von Ebner's gland protein (lipocalin-1) and calgranulin A and B (S100A8 and A9). Furthermore, apolipoprotein A-I, beta(2)-microglobulin, glutathione S-transferase P and fatty acid-binding protein were also identified. Our results show that human saliva contains a large number of proteins that are involved in inflammatory and immune responses. The 2-DE protein map constructed opens the possibility to investigate protein changes associated with disease processes.
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PMID:Mapping of proteins in human saliva using two-dimensional gel electrophoresis and peptide mass fingerprinting. 1283 25

The proteins found in tears have an important role in the maintenance of the ocular surface and changes in the quality and quantity of tear components reflect changes in the health of the ocular surface. In this study, we have used quantitative proteomics, iTRAQ technology coupled with 2D-nanoLC-nano-ESI-MS/MS and with a statistical model to uncover proteins that are significantly and reliably changed in the tears of dry eye patients in an effort to reveal potential biomarker candidates. Fifty-six patients with dry eye and 40 healthy subjects were recruited for this study. In total, 93 tear proteins were identified with a ProtScore >or=2 (>or=99% confidence). Associated with dry eye were 6 up-regulated proteins, alpha-enolase, alpha-1-acid glycoprotein 1, S100 A8 (calgranulin A), S100 A9 (calgranulin B), S100 A4 and S100 A11 (calgizzarin) and 4 down-regulated proteins, prolactin-inducible protein (PIP), lipocalin-1, lactoferrin and lysozyme. Receiver operating curves (ROC) were evaluated for individual biomarker candidates and a biomarker panel. With the use of a 4-protein biomarker panel, the diagnostic accuracy for dry eye was 96% (sensitivity, 91.0%; specificity, 90.0%). Two biomarker candidates (alpha-enolase and S100 A4) generated from iTRAQ experiments were successfully verified using an ELISA assay. The levels of these 10 tear proteins reflect aqueous secretion deficiency by lacrimal gland, inflammatory status of the ocular surface. The clinical classification of the severity of the dry eye condition was successfully correlated to the proteomics by using three proteins that are associated with inflammation, alpha1-acid glycoprotein 1, S100 A8 and S100 A9. The nine tear protein biomarker candidates (except alpha1-acid glycoprotein 1) were also verified using an independent age-matched patient sample set. This study demonstrated that iTRAQ technology combined with 2D-nanoLC-nanoESI-MS/MS quantitative proteomics is a powerful tool for biomarker discovery.
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PMID:Identification of tear fluid biomarkers in dry eye syndrome using iTRAQ quantitative proteomics. 1970 75