Serum proteomic analysis in patients with lung cancer
- VernacularTitle:肺癌患者血清蛋白质组的特征研究
- Author:
Chunfang GAO
;
Guang ZHAO
;
Xiuli WANG
;
Donghui LI
- Publication Type:Journal Article
- Keywords:
lung neoplasms;
spectrometry,mass,surface-enhanced laser desorption/ionization time-of-flight;
proteomics;
biological markers
- From:
Medical Journal of Chinese People's Liberation Army
1981;0(04):-
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore and determine the biologic markers for the diagnosis of lung cancer by comparison of proteomics among patients with lung cancer,those with benign lung tumor and healthy people.Methods The serum proteomics patterns of 89 cases of lung cancer,64 cases of benign lung tumor and 68 healthy subjects were read by surface enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDI-TOF-MS) to screen significant differential proteins,and to develop a classification tree model for the diagnosis of lung cancer.Thirty cases of lung cancer,30 cases of benign lung tumor and 30 healthy subjects were randomly selected at the same period and assigned as test groups for double-blind verification of the model.Results Thirty-nine differential proteins were identified from the three groups,and the classification tree model formed by 17 proteins (M/Z:4485,5252,5807,5908,5969,6113,6625,8946,8998,9137,9183,9298,9498,13878,15128,15867 and 16081) could be used to identify lung cancer,benign lung tumor and healthy subjects with an accuracy of 98.2% (217/221),sensitivity of 98.9% (88/89) and specificity of 97.7% (129/132),respectively.The double-blind test challenged the model with a sensitivity of 90.0% (27/30) and specificity of 93.3% (56/60).Conclusion The classification tree model constructed by SELDI-TOF-MS possesses high sensitivity and specificity,and it may be used for rapid diagnosis of lung cancer.
