OBJECTIVE: To study the specific metabonomic profiling of serum from colorectal cancer patients to find out the low molecule metabolites associated intimately with colorectal cancer,and to establish specific metabolic model for the diagnosis of colorectal cancer. METHODS: The metabonomic profiles of the serum samples from colorectal cancer(CRC) patients(n =31) and healthy adults(n =8) were investigated by gas chromatography-mass spectrometry (GC-MS) technique combined with a commercial mass spectral library for the peak clustering based on metabolites. RESULTS: Thirty-four endogenous metabolites including some amino acids, carbohydrates, fatty acids and other intermediate metabolites were identified. By t test statistics with P<0.05, P<0.01 respectively, L-valine, L-threonine, 1-deoxyglucose, glycine and ribitol levels were decreased significantly, but 3-hydroxybutyric acid level was increased significantly in the CRC patient group as compared with healthy adult group. PLS-DA based on these metabolites discriminated two groups for each other. Hierarchical clustering based on above 6 significant differential metabolites revealed that the prediction accuracy of colorectal cancer group was 93.5%. CONCLUSION: GC-MS technique is an alternative tool for the metabonomic study and would be certainly beneficial to the pathological research, early diagnosis and therapy evaluation of CRC.
OBJECTIVE: To study the specific metabonomic profiling of serum from colorectal cancerpatients to find out the low molecule metabolites associated intimately with colorectal cancer,and to establish specific metabolic model for the diagnosis of colorectal cancer. METHODS: The metabonomic profiles of the serum samples from colorectal cancer(CRC) patients(n =31) and healthy adults(n =8) were investigated by gas chromatography-mass spectrometry (GC-MS) technique combined with a commercial mass spectral library for the peak clustering based on metabolites. RESULTS: Thirty-four endogenous metabolites including some amino acids, carbohydrates, fatty acids and other intermediate metabolites were identified. By t test statistics with P<0.05, P<0.01 respectively, L-valine, L-threonine, 1-deoxyglucose, glycine and ribitol levels were decreased significantly, but 3-hydroxybutyric acid level was increased significantly in the CRC patient group as compared with healthy adult group. PLS-DA based on these metabolites discriminated two groups for each other. Hierarchical clustering based on above 6 significant differential metabolites revealed that the prediction accuracy of colorectal cancer group was 93.5%. CONCLUSION: GC-MS technique is an alternative tool for the metabonomic study and would be certainly beneficial to the pathological research, early diagnosis and therapy evaluation of CRC.
Authors: Alexander Benedikt Leichtle; Jean-Marc Nuoffer; Uta Ceglarek; Julia Kase; Tim Conrad; Helmut Witzigmann; Joachim Thiery; Georg Martin Fiedler Journal: Metabolomics Date: 2011-09-16 Impact factor: 4.290