OBJECTIVETo detect the serum proteomic patterns by using SELDI-TOF-MS and CM10 ProteinChip techniques in colorectal cancer (CRC) patients, and to evaluate the significance of the proteomic patterns in colorectal cancer staging.

METHODSA total of 76 serum samples were obtained from CRC patients at different clinical stages, including Dukes A (n = 10), Dukes B (n = 19), Dukes C (n = 16) and Dukes D (n = 31). Different stage models were developed and validated by bioinformatics methods of support vector machines, discriminant analysis and time-sequence analysis.

RESULTSThe model I formed by six proteins of peaks at m/z 2759.6, 2964.7, 2048.0, 4795.9, 4139.8 and 37 761.6 could do the best as potential biomarkers to distinguish local CRC patients (Dukes A and Dukes B) from regional CRC patients (Dukes C ) with an accuracy of 86.7%. The model II formed by 3 proteins of peaks at m/z 6885.3, 2058.3 and 8567.8 could do the best to distinguish locoregional CRC patients (Dukes A, B and C) from systematic CRC patients (Dukes D) with an accuracy of 75.0%. The mode III could distinguish Dukes A from Dukes B with an accuracy of 86.2% (25/29). The model IV could distinguish Dukes A from Dukes C with an accuracy of 84.6% (22/26). The model V could distinguish Dukes B from Dukes C with an accuracy of 85.7% (30/35). The model VI could distinguish Dukes B from Dukes D with an accuracy of 80.0% (40/50). The model VII could distinguish Dukes C from Dukes D with an accuracy of 78.7% (37/47). Different stage groups could be distinguished by the two-dimensional scattered spots figure obviously.

CONCLUSIONOur findings indicate that this method can well be used in preoperative staging of colorectal cancers and the screened tumor markers may serve for guidance of integrating treatment of colorectal cancers.