Identification of colorectal cancer using proteomic patterns in serum
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Abstract
Objective
At present there are no serological indicators with high sensitivity and specificity to diagnose colorectal cancer (CRC). This study was designed to establish a serum protein fingerprinting technique coupled with a pattern -matching algorithm to distinguish patients of colorectal cancer from that of benign colorectal diseases (BCD) and healthy people (HP).
Methods
Proteomic patterns were procured by surface enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDI-TOF-MS). Sera randomly selected from 73 CRC patients, 31 HP and 16 BCD patients were analyzed to develop a classification tree, which is a standard configuration to distinguish the sera of CRC patients and noncancer cohorts. The classifiction tree proved to be valid by using 120 double-blind sera samples in the test group, including 73 CRC, 31 HP and 16 BCD.
Results
At the protein masses of 4,467 Da; 8,131 Da; 8,939 Da; 9,192 Da; 9,134 Da; 8,221 Da; 5,928 Da; 8,324 Da; and 11,732 Da, protein levels from the CRC, HP and BCD patients in the preliminary group were significantly different based on software analysis. Correct ratio, sensitivity and specificity of the method were up to 98.33%, 97.26% (71/73) and 100% (47/47), respectively. Results of double-blind detection for the test group indicated that the correct ratio, sensitivity and specificity of the method were 96.77% (116/20), 95.89% (70/73) and 97.87% (46/47), respectively.
Conclusion
Via comparative proteomics analysis of the serum from CRC, HP and BCD patients using the SELDI-TOF-MS method, CRC can be diagnosed rapidly and correctly with high sensitivity and specificity.
Keywords
surface enhanced laser desorpfion/ionization-time of flight-mass spectrometry colorectal cancer serum biomarkers proteomicsPreview
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