Zhonghua nei ke za zhi · 2005
[The application of surface-enhanced laser desorption/ionization-time of flight-mass spectrometry in diagnosing dysplasia and chronic atrophic gastric-carditis in population with high risk of gastric-cardia adenocarcinoma].
Аннотация на английскомСтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Wang Dao-cun, Wang Li-dong, Zheng Shu, Fan Zong-min, Li Ji-lin, Feng Chang-wei, Zhang Yan-rui, Liu Bin, Gao Shan-shan, He Xin
Аннотация
OBJECTIVES: To evaluate the serum biomarkers for diagnosis of gastric cardia dysplasia (DYS) and chronic atrophic gastric-carditis (CAG) and to provide a novel screening method for high risk population of gastric-cardia adenocarcinoma (GCA).
METHODS: Proteomic spectra were generated by surface-enhanced laser desorption/ionization-time of flight-mass spectra (SELDI-TOF-MS) and weak cation exchange protein chip system. A set of spectra derived from analysis of serum from 143 symptom-free subjects at high-risk area for GCA, including 63 cases with histologically normal gastric cardia epithelia, 57 of CAG and 23 of DYS, were analyzed by bioinformatics like decision tree classification algorithm. The sensitivity and the specificity for test group were performed by using 10-fold cross validation classification with the decision tree classification model.
RESULTS: One protein spot with a ratio of mass to charge (M/Z) of M3894. 0 was selected to build a decision tree classification model to identify the case with DYS or normal. With this classification model, the sensitive rate for DYS identification was 87% (20/23). Two proteins with M/Z of M2942. 15 and M33316. 6 were used to build a decision tree classification model. With this model, the sensitivity for discriminating CAG from normal was 93% (53/57) and the specificity was 92 (58/63).
CONCLUSIONS: The gastric cardia lesions of DYS and CAG could be identified by SELDI-TOF-MS technique specifically in symptom-free subjects at high incidence area for GCA. The present findings provide a new screening way for high-risk subjects with CGA.
METHODS: Proteomic spectra were generated by surface-enhanced laser desorption/ionization-time of flight-mass spectra (SELDI-TOF-MS) and weak cation exchange protein chip system. A set of spectra derived from analysis of serum from 143 symptom-free subjects at high-risk area for GCA, including 63 cases with histologically normal gastric cardia epithelia, 57 of CAG and 23 of DYS, were analyzed by bioinformatics like decision tree classification algorithm. The sensitivity and the specificity for test group were performed by using 10-fold cross validation classification with the decision tree classification model.
RESULTS: One protein spot with a ratio of mass to charge (M/Z) of M3894. 0 was selected to build a decision tree classification model to identify the case with DYS or normal. With this classification model, the sensitive rate for DYS identification was 87% (20/23). Two proteins with M/Z of M2942. 15 and M33316. 6 were used to build a decision tree classification model. With this model, the sensitivity for discriminating CAG from normal was 93% (53/57) and the specificity was 92 (58/63).
CONCLUSIONS: The gastric cardia lesions of DYS and CAG could be identified by SELDI-TOF-MS technique specifically in symptom-free subjects at high incidence area for GCA. The present findings provide a new screening way for high-risk subjects with CGA.