Renyong Guo1, Chunqin Pan, Jianmin Shen, Chibo Liu. 1. Department of Clinical Laboratory, The First Affiliated Hospital of Medical College, Zhejiang University, Hangzhou, China.
Abstract
PURPOSE: To screen for the potential protein biomarkers in serum for the diagnosis of esophageal carcinoma (EC) using proteomic fingerprint technology. METHODS: Proteomic fingerprint technology combining magnetic beads with MALDI-TOF-MS was used to profile and compare the serum proteins from 78 patients with EC and 95 healthy blood donors. Proteomic patterns associated with EC were identified by Biomarker Patterns Software. Model of biomarkers was constructed and evaluated using the Biomarker Patterns Software. RESULTS: A total of 60 discriminating m/z peaks were identified that were related to EC (P < 0.01). The model of biomarkers constructed by the Biomarker Patterns Software based on the four biomarkers (2049.6, 3936.5, 5339.9, and 13748.8 Da) generated excellent separation between the EC and control groups. The sensitivity was 92.5% and the specificity was 88%. Blind test data indicated a sensitivity of 89.5% and a specificity of 84.4%. CONCLUSIONS: Biomarkers for EC can be discovered in serum by MALDI-TOF-MS combining the use of magnetic beads. The pattern of combined markers provides a powerful and reliable diagnostic method for EC with a high sensitivity and specificity.
PURPOSE: To screen for the potential protein biomarkers in serum for the diagnosis of esophageal carcinoma (EC) using proteomic fingerprint technology. METHODS: Proteomic fingerprint technology combining magnetic beads with MALDI-TOF-MS was used to profile and compare the serum proteins from 78 patients with EC and 95 healthy blood donors. Proteomic patterns associated with EC were identified by Biomarker Patterns Software. Model of biomarkers was constructed and evaluated using the Biomarker Patterns Software. RESULTS: A total of 60 discriminating m/z peaks were identified that were related to EC (P < 0.01). The model of biomarkers constructed by the Biomarker Patterns Software based on the four biomarkers (2049.6, 3936.5, 5339.9, and 13748.8 Da) generated excellent separation between the EC and control groups. The sensitivity was 92.5% and the specificity was 88%. Blind test data indicated a sensitivity of 89.5% and a specificity of 84.4%. CONCLUSIONS: Biomarkers for EC can be discovered in serum by MALDI-TOF-MS combining the use of magnetic beads. The pattern of combined markers provides a powerful and reliable diagnostic method for EC with a high sensitivity and specificity.
Authors: T P Conrads; V A Fusaro; S Ross; D Johann; V Rajapakse; B A Hitt; S M Steinberg; E C Kohn; D A Fishman; G Whitely; J C Barrett; L A Liotta; E F Petricoin; T D Veenstra Journal: Endocr Relat Cancer Date: 2004-06 Impact factor: 5.678
Authors: Thomas Linke; Sundari Doraiswamy; Earl H Harrison Journal: J Chromatogr B Analyt Technol Biomed Life Sci Date: 2006-12-22 Impact factor: 3.205
Authors: Gunjan Malik; Michael D Ward; Saurabh K Gupta; Michael W Trosset; William E Grizzle; Bao-Ling Adam; Jose I Diaz; O John Semmes Journal: Clin Cancer Res Date: 2005-02-01 Impact factor: 12.531
Authors: Katherine R Kozak; Malaika W Amneus; Suzanne M Pusey; Feng Su; Mui N Luong; Sam A Luong; Srinivasa T Reddy; Robin Farias-Eisner Journal: Proc Natl Acad Sci U S A Date: 2003-10-01 Impact factor: 11.205
Authors: Jia Fan; Yi Huang; Inez Finoulst; Hung-Jen Wu; Zaian Deng; Rong Xu; Xiaojun Xia; Mauro Ferrari; Haifa Shen; Ye Hu Journal: Cancer Lett Date: 2012-11-27 Impact factor: 8.679
Authors: Roland Matthews; Andres Azuero; Senait Asmellash; Earl Brewster; Edward E Partridge; Chandrika J Piyathilake Journal: Int J Womens Health Date: 2011-07-12