Proteiomic patterns for endometrial cancer using SELDI-TOF-MS

• Published in: Journal of Zhejiang University. B. Science 2008-04, Vol.9 (4), p.286-290
• Main Authors: Zhu, Li-rong, Zhang, Wen-ying, Yu, Li, Zheng, Yan-hua, Hu, Jun, LIAO, Qin-ping
• Format: Article
• Language: English
• Subjects: Biomarkers, Tumor - metabolism; Biomedical and Life Sciences; Biomedicine; Cancer; Case-Control Studies; Endometrial cancer; Endometrial Neoplasms - diagnosis; Endometrial Neoplasms - metabolism; Female; Gene Expression Regulation, Neoplastic; Humans; Mass spectrometry; 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; 光谱测定; 吸附作用; 子宫癌; 生物标志物
• ISSN: 1673-1581; 1862-1783
• DOI: 10.1631/jzus.B0710589

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 E C 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.