Urine Metabolite Profiling of Human Colorectal Cancer by Capillary Electrophoresis Mass Spectrometry Based on MRB

Abstract

Aim. The study was to investigate the metabolic profile of urine metabolites and to elucidate their clinical significance in patients with colorectal cancer. Methods. Colorectal cancers from early stage and advanced stage were used in this study. Urine samples of colorectal cancer patients and healthy adults were collected and subjected to capillary electrophoresis mass spectrometry based on moving reaction boundary analysis. The metabolic data were analyzed by SPSS 17.0 to find urinary biomarkers for colorectal cancer. Results. The results indicated that the urine metabolic profiling of colorectal cancer patients had significant changes compared with the normal controls, and there were also differences between early stage and advanced colorectal cancer patients. Compared with the control group, the levels of isoleucine, valine, arginine, lactate acid and leucine increased (P < 0.05), but those of histidine, methionine, serine, aspartic acid, citric acid, succinate, and malic acid decreased in urine samples from colorectal cancer (P < 0.05). Furthermore, the levels of isoleucine and valine were lower in urine of patients with advanced colorectal cancer than those in early stage colorectal cancer (P < 0.05). Conclusion. The technique of capillary electrophoresis mass spectrometry based on MRB could reveal the significant metabolic alterations during progression of colorectal cancer, and the method is feasible and may be useful for the early diagnosis of colorectal cancer.

Figure 1

Total ion chromatogram of 18 kinds of amino acid standards.

Figure 2

Total ion chromatogram of the urine of a patient with colorectal cancer.

Figure 3

Principal component analysis model and receiver operating characteristic curve for colorectal cancer. (a) Principal component analysis (PCA) scores plot of colorectal cancer urine specimens from control specimens based on 12 marker metabolites. The PCA scores plot showed that different samples (normal group, colorectal cancer group including early stage group and advanced group) were scattered into different regions; (b) receiver operating characteristic (ROC) analysis was performed using the values determined by the first two principal components. Area under the curve (AUC) = 1.00.

Figure 4

Principal component analysis model and receiver operating characteristic curve for advanced colorectal cancer. (a) Principal component analysis (PCA) scores plot of early stage group and advanced group based on 2 marker metabolites. The PCA scores plot showed that the samples from early stage group and advanced group were scattered into two different regions; (b) receiver operating characteristic (ROC) analysis was performed using the values determined by the first two principal components. Area under the curve (AUC) = 0.906.