Mei-Qun Cao1, Zheng-Zhi Wu, Wei-Kang Wu. 1. Shenzhen Institute of Integrated Traditional Chinese and Western Medicine, Shenzhen Second People's Hospital, Shenzhen 518035, Guangdong Province, China.
Abstract
OBJECTIVE: To explore the presence of informative protein biomarkers in the salivary proteome of breast cancer patients with thick white or thick yellow tongue fur. METHODS: Salivia samples were collected from 20 breast cancer patients with thick white or yellow tongue fur and 10 healthy controls. The samples were profiled by using isobaric tags for relative and absolute quantitation (iTRAQ) technology coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS). The analyzed map and data were assessed with Mascott 2.2 and Scaffold software. Ratio of proteins between groups of less than 0.6 or more than 1.5 could confirm that there was difference between groups. RESULTS: A total of 464 proteins were identified and 125 proteins met strict quantitative criteria. There were 9 proteins associated with breast cancer, expression levels of which were up- or down-regulated more than 1.5 folds compared with healthy people. There were 16 proteins associated with tongue coating, of which 10 proteins expressed in breast cancer patients with thick white fur were lower than in patients with thick yellow fur, and the expressions of the other 6 proteins were increased. CONCLUSION: This study demonstrates that iTRAQ combined with LC-MS/MS quantitative proteomics is a powerful tool for biomarker discovery and the identification of proteins associated with breast cancer and tongue coating.
OBJECTIVE: To explore the presence of informative protein biomarkers in the salivary proteome of breast cancerpatients with thick white or thick yellow tongue fur. METHODS: Salivia samples were collected from 20 breast cancerpatients with thick white or yellow tongue fur and 10 healthy controls. The samples were profiled by using isobaric tags for relative and absolute quantitation (iTRAQ) technology coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS). The analyzed map and data were assessed with Mascott 2.2 and Scaffold software. Ratio of proteins between groups of less than 0.6 or more than 1.5 could confirm that there was difference between groups. RESULTS: A total of 464 proteins were identified and 125 proteins met strict quantitative criteria. There were 9 proteins associated with breast cancer, expression levels of which were up- or down-regulated more than 1.5 folds compared with healthy people. There were 16 proteins associated with tongue coating, of which 10 proteins expressed in breast cancerpatients with thick white fur were lower than in patients with thick yellow fur, and the expressions of the other 6 proteins were increased. CONCLUSION: This study demonstrates that iTRAQ combined with LC-MS/MS quantitative proteomics is a powerful tool for biomarker discovery and the identification of proteins associated with breast cancer and tongue coating.