DocumentCode :
560588
Title :
Establishment of a non-invasive salivary diagnostic model for TCM syndrome differentiation in breast cancer based on SELDI and bioinformatics techniques
Author :
Meiqun, Cao ; Zhengzhi, Wu ; Kehuan, Sun ; Xiaoli, Zhang ; Yinghong, Li ; Anming, Wu ; Yu, Jin
Author_Institution :
Shenzhen Inst. of Geriatric Med., Shenzhen People´´s Hosp., Shenzhen, China
Volume :
1
fYear :
2011
fDate :
9-11 Dec. 2011
Firstpage :
464
Lastpage :
468
Abstract :
Objective The salivary proteins of breast cancer patients of liver-qi stagnation syndrome and of liver-kidney yin deficiency syndrome were examined using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS), and specific protein markers were screened out to establish a salivary protein fingerprint model for distinguishing breast cancer liver-qi stagnation and liver-kidney yin deficiency. Methods The protein patterns of 47 salivary specimens (26 cases of liver-qi stagnation of breast cancer, 21 cases of liver-kidney yin deficiency of breast cancer) were examined with SELDI-TOF-MS to establish a TCM syndrome diagnosis model for breast cancer. Results 243 protein peaks were detected in the specimens, 33 of which showed significant difference between the two groups. The liver-qi stagnation syndrome and the liver-kidney yin deficiency syndrome of breast cancer could be correctly distinguished by the diagnostic model comprised of two proteins with M/Z of 8087.575 and 3378.142 Da, respectively; 25 out of the 26 cases of liver-qi stagnation syndrome was correctly diagnosed, and all the 21 cases of liver-kidney yin deficiency were correctly excluded; the sensitivity reached 96.15% (25/26) and the specificity was 80.95%(17/21). Conclusion The salivary protein fingerprint model for TCM syndrome differentiation established with SELDI-TOF-MS provided a highly specific, sensitive new method that is worth further study and application.
Keywords :
bioinformatics; cancer; fingerprint identification; kidney; liver; patient diagnosis; proteins; time of flight mass spectrometers; SELDI-TOF-MS; TCM syndrome diagnosis model; TCM syndrome differentiation; bioinformatics technique; breast cancer liver-qi stagnation; liver-kidney yin deficiency syndrome; liver-qi stagnation syndrome; noninvasive salivary diagnostic model; protein marker; protein pattern; salivary protein fingerprint model; salivary specimen; surface-enhanced laser desorption-ionization time-of-flight mass spectrometry; Analytical models; Biological system modeling; Breast cancer; Diseases; Medical diagnostic imaging; Proteins; Sensitivity; Breast cancer; SELDI-TOF-MS; diagnosis model; proteomics; saliva; syndrome;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
IT in Medicine and Education (ITME), 2011 International Symposium on
Conference_Location :
Cuangzhou
Print_ISBN :
978-1-61284-701-6
Type :
conf
DOI :
10.1109/ITiME.2011.6130877
Filename :
6130877
Link To Document :
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