Objective: To investigate the differentially expressed proteins among chronic sinusitis, nasal polyps and normal nasal mucosa by means of proteomic technology, and select the candidate biomarkers of chronic sinusitis and nasal polyps.
Methods: Proteins extracted from chronic sinusitis, nasal polyps and normal nasal mucosa were separated and the differentially expressed proteins were identified by series of proteomic tools, including immobilized pH4-7 gradient two-dimensional sodium dodecyl sulfate polyacrylamide gel electrophoresis, modified coomassie brilliant blue staining, images scanning by the Image Scanner apparatus, PDQuest analysis software, peptide mass fingerprinting based on matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS) by in-gel digestion extract, and Mascot searching in NCBInr and SWISS-PROT databases.
Results: The 2-DE patterns with high resolution and reproducibility were obtained. The protein spots separated and visualized in chronic sinusitis, nasal polyps and normal nasal mucosa gel were 1020 +/- 40, 1112 +/- 10 and 1008 +/- 25, respectively. And the match rates were (93 +/- 2)%, (95 +/- 1)% [see text] (90 +/- 3)% respectively. Thirteen differentially expressed spots were found from chronic sinusitis, nasal polyps and normal nasal mucosa gel. We selected and recommend Keratin 8 and APOA1 proteins as candidate biomarkers of nasal polyps, and PLUNC protein, PACAP protein, NKEF-B and SOD as candidate biomarkers of chronic sinusitis.
Conclusions: The differentially expressed proteins among chronic sinusitis, nasal polyps and normal nasal mucosa can be efficiently and relatively reliably identified via the techniques of proteomics. These techniques will play a very important role in the researches for new objective indicators possibly employed in the future classifying, staging and prognosis.