[Establish predictive model of colorectal cancer by using surface enhanced laser desorption/ionization-time of flight-mass spectrometry].

OBJECTIVE

To establish serum proteome fingerprinting predictive models and search for proteins associated with colorectal cancer.

METHODS

Thirty-six randomly selected colorectal cancer patients and 36 cases with hernia or gall bladder diseases scheduled for elective operation were enrolled as cancer group and control group respectively. Peripheral venous blood samples were collected before the operations. Special serum protein or peptide fingerprint was investigated by using surface enhanced laser desorption/ ionization-time of flight-mass spectrometry (SELDI-TOF-MS) measurement after blood sample had been treated with weak cation exchange protein chip (CM10) for each case. The obtained data were analyzed by Biomarker Wizard software to screen serum proteome tumor markers and set up diagnosis predictive model for colorectal cancer. Blind validation of the model with 44 healthy controls and 88 colorectal cancer patients were carried out by using Biomarker Patterns Software.

RESULTS

In comparing colorectal cancer group with control group, 5 specific protein peaks (P < 0.05) were found. The predictive model had a sensitivity of 100% and a specificity of 97.2%. A sensitivity of 71.6% and a specificity of 72.7% was got with the blind validation. The specific protein peaks with a mass-to-charge ratio (m/z) of 8908 and 13,707 showed in all the results and it showed their strong relationship with colorectal cancer.

CONCLUSIONS

The predictive models built by the differences of serum proteome fingerprint could be a very useful diagnostic tool in colorectal cancer. Proteins with m/z of 8908 and 13,707 would possibly be the tumor markers of colorectal cancer.