Serum Profiling Of Esophageal Squamous Cell Carcinoma By SELDI Technology

Objective: Most patients of esophageal squamous cell carcinoma(ESCC) have developed to advanced stages at the time of diagnosis and more than a half have either unresectable tumors or radiographically visible metastases. The 5-year survival rate was less than 10% for all patients of ESCC. But a 5-year survival rate of 84.1% and a 10-year survival rate of 73% would be achieved if the patients were diagnosed in early stage. However, early detection of cancer truly depends on the discovery of specific and sensitive molecular biomarkers. Promising diagnostic patterns have recently been reported using surface enhanced laser desorption/ionization-time of flight-mass spectrometry technology (SELDI-TOF-MS ) . SELDI is an affinity-based MS method in which proteins are selectively adsorbed to a chemically modified surface and impurities are removed by washing with buffer. By combining different ProteinChipR array surfaces and wash conditions, SELDI allows on-chip protein capture and micropurification, thereby permitting high-throughput protein expression analysis of a large number of clinical samples. So the aim of this study is to screen biomarkers and identify proteomic pattern through analyzing 305 serum profiling of both ESCC healthy donors by SELDI-TOF-MS technology.Materials and methods: One hundred and ninety-nine serum samples from patients with different stage and grade ESCC and 106 ones from age- and sex-matched healthy individuals were analyzed by WCX2 ProteinChip under defined binding and washing conditions. All samples were divided into two groups, Fifty-nine ESCC and 61 control samples were used to train a diagnostic model, and the others for blind test. Biomarker Pattern Software was used to detect the protein peaks significantlydifferent between ESCC and controls, and set up the primary diagnosis model of ESCC. Staging for 187 cases of ESCC was done according to TNM staging system. SPSS software was performed for statistical analysis between different staging subgroups.Results: Ninety-two protein peaks were detected at the molecular range of 0 to 20 OOODa in the training set (59 ESCC and 61 control), among which 34 ones were significantly different between ESCC and controls (P <0.05). A diagnostic pattern consisting of 12 protein peaks was established with a sensitivity of 91.5% (54/59) and a specificity of 86.9% (53/61). The discriminatory pattern could recognize 119 from 140 cases of esophageal cancer and 38 from 45 cases of control, achieving a sensitivity of 85% and specificity of 84.4% in the blind test for validation. There was no significant difference between the capabilities of the discriminatory pattern for different TNM staging. Eight of the 92 peaks expressed significantly different between different TNM staging. Expression of 3 peaks were found to be significantly different between stage I and II, two peaks between stage II and HI, 4 peaks between stage I and III. The expression of M3160 existed significant difference between stage I and stage II or III, however, the difference between stage II and III was not significant.Conclusion: Using SELDI-TOF technology, we have discovered a candidate ESCC pattern consisting of 12 peaks that can effectively distinguish serum samples from healthy controls and ESCC patients, which might be useful for detection and monitor of this cancer. Combined use of bioinformatics tools and proteomic profiling provides an effective approach for screening potential serum tumor markers.