Ren XJ, Tan XL, Yang CH, Li XQ, Feng F, Hu QY, Ding YH, Dai TY, Wang KZ. Detection of differentially expressed low molecular weight serum proteins for diagnosis and staging of esophageal cancer.
Shijie Huaren Xiaohua Zazhi 2010;
18:2472-2477. [DOI:
10.11569/wcjd.v18.i23.2472]
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Abstract
AIM: To find biomarkers for early diagnosis of esophageal cancer (EC) by detecting differentially expressed low molecular weight serum proteins using mass spectrometry.
METHODS: The serum proteomic patterns of EC patients and healthy controls were detected using the surface-enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDI-TOF-MS). Differential protein peaks between EC patients and controls were analyzed using the Biomarker Pattern Software, and a model for early diagnosis of EC was developed and validated using an artificial neural network (ANN). Differential protein peaks between early and advanced EC patients were analyzed to establish a model for staging of EC.
RESULTS: Five differential serum proteins were identified between EC patients and controls, and three differential serum proteins were found between early and advanced EC. The diagnostic model established based on the five differential serum proteins between EC patients and controls had a sensitivity of 87.88%, a specificity of 91.43%, and an accuracy of 89.71%. The blind test generated a sensitivity of 95.83%, a specificity of 89.13%, and an accuracy of 91.43%. The staging model established based on the three differential serum proteins between early and advanced EC had a sensitivity of 75.76%, a specificity of 79.17%, and an accuracy of 77.19%.
CONCLUSION: SELDI-TOF-MS in combination with ANN is simple and feasible for the diagnosis and staging of EC.
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