Serum amino acid profiles and their alterations in colorectal cancer

Abstract

Mass spectrometry-based serum metabolic profiling is a promising tool to analyse complex cancer associated metabolic alterations, which may broaden our pathophysiological understanding of the disease and may function as a source of new cancer-associated biomarkers. Highly standardized serum samples of patients suffering from colon cancer (n = 59) and controls (n = 58) were collected at the University Hospital Leipzig. We based our investigations on amino acid screening profiles using electrospray tandem-mass spectrometry. Metabolic profiles were evaluated using the Analyst 1.4.2 software. General, comparative and equivalence statistics were performed by R 2.12.2. 11 out of 26 serum amino acid concentrations were significantly different between colorectal cancer patients and healthy controls. We found a model including CEA, glycine, and tyrosine as best discriminating and superior to CEA alone with an AUROC of 0.878 (95% CI 0.815-0.941). Our serum metabolic profiling in colon cancer revealed multiple significant disease-associated alterations in the amino acid profile with promising diagnostic power. Further large-scale studies are necessary to elucidate the potential of our model also to discriminate between cancer and potential differential diagnoses. In conclusion, serum glycine and tyrosine in combination with CEA are superior to CEA for the discrimination between colorectal cancer patients and controls.

Fig. 1

Correlation matrix plot of the amino acid concentrations [Kendall’s τ_b, circle denotes low correlation and oval denotes high correlation, positive, negative, and neutral correlations are displayed blue, red, and white, respectively (see Murdoch and Chow (1996) for details)] to display the mutual collinearities between amino acid concentrations. The top line (shaded) shows point biserial correlations r _pb and significance levels for the correlation of the respective amino acid with the health state (*P < 0.05; **P < 0.01; ***P < 0.001)

Fig. 2

ROC curves, 95% confidence bands (B = 999) and AUROCs for CEA (red), the model consisting of CEA and principal component 1 (PC1 orange), and the model consisting of CEA, glycine, and tyrosine (green). Sensitivity and specificity and their 95% confidence intervals (B = 999) are given for the best thresholds and denoted by (☩). P-values between AUCs are computed according to DeLong et al. (1988) as described in the Sect. 2