X Hu1, P Zhang, A Shang, Q Li, Y Xia, G Jia, W Liu, X Xiao, D He. 1. Medical Research Institute, Key Laboratory of Cell Proliferation and Regulation Biology Ministry of Education, Beijing Normal University, and Department of Endocrinology, General Hospital of the Second Artillery Force, The People's Liberation Army, Beijing, China.
Abstract
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.
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.
Authors: Thomas J van Ee; Heleen H Van Acker; Tom G van Oorschot; Viggo F Van Tendeloo; Evelien L Smits; Ghaith Bakdash; Gerty Schreibelt; I Jolanda M de Vries Journal: Vaccines (Basel) Date: 2018-09-19