Proteiomic patterns for endometrial cancer using SELDI-TOF-MS.
- Author:
Li-rong ZHU
1
;
Wen-ying ZHANG
;
Li YU
;
Yan-hua ZHENG
;
Jun HU
;
Qin-ping LIAO
Author Information
- Publication Type:Journal Article
- MeSH: Biomarkers, Tumor; metabolism; Case-Control Studies; Endometrial Neoplasms; diagnosis; metabolism; Female; Gene Expression Regulation, Neoplastic; Humans; Medical Oncology; methods; Models, Biological; Neoplasm Proteins; Neoplasm Staging; Protein Array Analysis; Proteomics; methods; Sensitivity and Specificity; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; methods
- From: Journal of Zhejiang University. Science. B 2008;9(4):286-290
- CountryChina
- Language:English
- Abstract: Serum samples from endometrial cancer (EC) patients and healthy females were analyzed using surface-enhanced laser desorption-ionization time-of-flight mass spectrometry (SELDI-TOF-MS) to discover the potential diagnostic biomarker for detection of EC. A preliminary training set of spectra derived from 40 EC patients and 30 healthy women were used to develop a proteomic model that effectively discriminated cancer patients from healthy women. The training set had a specificity of 100% and sensitivity of 92.5% in the EC detection. A blind test set, including 20 new cancer cases and 10 healthy women, was used to validate the sensitivity and specificity of this multivariate model, which had a corresponding results of 60% in specificity and 75% in sensitivity, respectively. The combination of SELDI-TOF-MS with bioinformatics tools could help find new biomarkers and establish the detection of EC with high sensitivity and specificity.
