Identification of serum proteins discriminating colorectal cancer patients and healthy controls using surface-enhanced laser desorption ionisation-time of flight mass spectrometry

AIM： To detect the new serum biomarkers for colorectal cancer （CRC） by serum protein profiling with surfaceenhanced laser desorption ionisation - time of flight mass spectrometry （SELDI-TOF MS）. METHODS： Two independent serum sample sets were analysed separately with the ProteinChip technology （set A： 40 CRC ＋ 49 healthy controls; set B： 37 CRC ＋ 31 healthy controls）, using chips with a weak cation exchange moiety and buffer pH 5. Discriminative power of differentially expressed proteins was assessed with a classification tree algorithm. Sensitivities and specificities of the generated classification trees were obtained by blindly applying data from set A to the generated trees from set B and vice versa. CRC serum protein profiles were also compared with those from breast, ovarian, prostate, and non-small cell lung cancer. RESULTS： Mass-to-charge ratios （m/z） 3.1×10^3, 3.3× 10^3, 4.5×10^3, 6.6×10^3 and 28×10^3 were used as classitiers in the best-performing classification trees. Tree sensitivities and specificities were between 65% and 90%.Host of these discriminative m/z values were also different in the other tumour types investigated. M/z 3.3× 10^3, main classifier in most trees, was a doubly charged form of the 6.6× 10^3-Da protein. The latter was identified as apolipoprotein C-I. M/z 3.1×10^3 was identified as an N-terminal fragment of albumin, and m/z 28× 10^3 as apolipoprotein A-I. CONCLUSION： SELDI-TOF MS followed by classification tree pattern analysis is a suitable technique for finding new serum markers for CRC. Biomarkers can be identified and reproducibly detected in independent sample sets with high sensitivities and specificities. Although not specific for CRC, these biomarkers have a potential role in disease and treatment monitoring.