Objective: The early diagnosis of nonfunctioning pituitary adenoma (NFPA) is difficult. The objective of this study was to find specific protein biomarkers to aid in the early detection of NFPA.
Methods: Serum samples from 34 patients with NFPA and 34 age- and sex-matched healthy control subjects were analysed using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technology. The spectra were generated, protein peak clustering was performed and classification analyses were carried out using a decision tree classification algorithm.
Results: Nine differentially expressed serum proteins were identified in the patients with NFPA compared with the control subjects. Both the sensitivity and specificity of the decision tree classification algorithm were 82.4% for NFPA.
Conclusions: Nine new serum protein biomarkers for NFPA were identified. SELDI-TOF-MS coupled with data mining tools might provide a novel approach for the early diagnosis of NFPA and population screening for the disease.