Objective: To establish a serum protein fingerprint model for prediction of liver metastasis from colorectal cancer by SELDI-TOF-MS analysis, and to determine the differentiatial proteins associated with the metastatic liver cancers.
Methods: Data were collected from the Department of General Surgery in Zhongshan Hospital. A group of patients with colorectal cancer (CRC) without liver metastasis (n = 36) and another group with liver metastasis (n = 36) were included in this study. Serum samples were collected from peripheral venous blood before operation. Special serum protein or peptide fingerprint was determined by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). The obtained data were analyzed by Biomarker Wizard software to screen the serum protein markers discriminating colorectal cancer patients with and without liver metastasis. A serum protein fingerprint model was established. This model was blindly verified in of CRC patients with and 44 cases without liver metastasis.
Results: Comparing the characteristic proteins in those two groups of patients, 10 specific protein peaks were identified with statistical significance (P < 0.05). According to m/z growing from small to large, they were: 2398, 2814, 4084, 4289, 4465, 6422, 6619, 11 482, 11 649 and 13 714. The predictive model had a sensitivity of 91.7% and a specificity of 97.2%. The validation showed a sensitivity of 75.0% and a specificity of 81.8%.
Conclusion: A predictive model based on differentiatial serum protein fingerprint with high sensitivity and specificity has been successfully established. It should be a very useful tool in detection and diagnosis of liver metastasis in colorectal cancer patients.